Desirable Dietary Pattern for Bangladesh

Home , Annona reticulata, Carambola, Dioscorea pentaphylla

The study conducted by:

Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM)

Principal Investigator: Quamrun Nahar, PhD Senior Research Officer, Dept of Biochemistry & Cell Biology BIRDEM

Co-Investigators: Subhagata Choudhury, MBBS, FCPS, MPhil Director and Professor, Laboratory Services, BIRDEM

Md Omar Faruque, PhD, Senior Research Officer, Dept of Biochemistry & Cell Biology, BIRDEM

Sayeda Saleha Saliheen Sultana, MSc. Assoc. Prof., College of Home Economics, Dhaka

Muhammad Ali Siddiquee, PhD Head, Grain Quality and Nutrition, BRRI

This study was carried out with the support of the

National Food Policy Capacity Strengthening Programme

June 2013 [Type a quote from the docu ment

This study was financed under the Research Grants Scheme (RGS) of the National Food Policy Capacity Strengthening Programme (NFPCSP) Phase II. The purpose of the RGS is to support studies that directly address the policy research needs identified by the Food Planning and Monitoring Unit of the Ministry of Food. The NFPCSP is being implemented by the Food and Agriculture Organization of the United Nations (FAO) and the Food Planning and Monitoring Unit (FPMU), Ministry of Food with the financial support of EU and USAID.

The designation and presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of FAO nor of the NFPCSP, Government of Bangladesh, EU or USAID and reflects the sole opinions and views of the authors who are fully responsible for the contents, findings and recommendations of this report.

Acknowledgements It is with great pleasure that we acknowledge the Food and Agriculture Organization (FAO) of the UN, Bangladesh for providing technical support to BIRDEM for conducting the study ―Desirable Dietary Pattern for Bangladesh.‖ This study is a fundamental step towards improving the health and nutritional status of the population of Bangladesh. We are also grateful to the authority of BIRDEM for the permission and support given to us to carry out this work. We are expressing our indebtedness and gratitude to Dr. Lalita Bhattacharjee, Nutritionist and Dr. Mohammad Abdul Mannan, National Food Utilization and Nutrition Advisor, NFPCSP, FAO of the United Nations for their technical guidance and support given throughout the study period thus leading to its fruitful completion. We are also grateful to Dr. Ciro Fiorillo, CTA, NFPCSP, FAO of the United Nations for his kind suggestions and overall supervision. Our special thanks go to Dr. Nur Ahamed Khondaker, Research Grants Administrator of NFPCSP, FAO of the United Nations for his assistance and cooperation on issues related to the research management and logistics. Special thanks are also due to Mr. Touhidul Islam, Deputy Project Director of Bangladesh Bureau of Statistics (BBS) for his help from time to time on the HIES data management and to Mr. SM Manzoor Ahmed Hanifi and Dr. Nurul Alam of ICDDRB for support on the statistical tools. We are also grateful to Ms. Jillian Waid of HKI for her help regarding Dietary Diversity Score (DDS) calculation and for review of that section in the study. We thank Kbd SM Emdadul Hoque, Deputy Director (Fruit and Vegetables), Food Crop Wing, DAE, Khamarbari and Mr. SM Quamruzzaman, Project Director, Integrated Quality Horticulture Development Project, DAE, Khamarbari, Dhaka for their support in adapting the crop calendar and related materials. We are also thankful to Prof. Ekhlasur Rahman, Director IPHN and Line Director NNS; Prof. SM Keramat Ali of Daffodil University, Prof. Shaheen Ahmed, Former Principal, Home Economics College, Prof. Khursheed Jahan, Prof. Moududur Rahman, Prof. SK Nazrul Islam, Prof. Nazrul Islam Khan, Prof. Nazma Shaheen and Prof. ATA Rahim of INFS for their valuable suggestions. We would like to express our heartfelt thanks to all the household members who have spent important time to give us information on the 24 hr dietary recall for the DDS calculation. The working group that was set up for this research work also deserves special thanks for their keen interest and contribution towards the study.

Quamrun Nahar Senior Research Officer, BIRDEM Principal Investigator, DDP

Table of Contents

Contents Page No Acronyms viii Executive Summary xi 1. Introduction 1 1.1.Objectives and key research questions 1 2. Literature review 3 2.1 Dietary pattern 3 2.2 Nutrition situation 4 2.2.1. Energy deficiency 5 2.2.2. Obesity and chronic diseases 6 2.2.3. Micronutrient deficiency 6 2.2.3.1.Iron deficiency 6 2.2.3.2.Vitamin A deficiency 8 2.2.3.3.Iodine deficiency 8 2.2.3.4.Zinc deficiency 9 2.3 Energy requirements and reference body weight 9 2.4 Basal metabolic rate 11 2.5 Physical Activity Level (PAL) 11 2.6 Nutrient requirements 12 2.7 Health and food crop diversity 16 2.8 Dietary Diversity Score 16

3. Methodology 20 3.1. Energy requirements 20 3.2. Nutrient requirements 21 3.3. Food intake patterns in Bangladesh 21 3.4. Household dietary diversity score 21 3.5. Key food identification 22 3.6. Crop calendar 22 3.7. Compilation of Bangladeshi foods 22 3.8. Optimizing nutrition return 22 3.9. Menu planning 22 3.10. Serving size calculation 23 3.11. Food exchange lists 23 3.12. Key stakeholders 23 3.13. Dietary guidelines for Bangladesh 23 3.14. Analysis of datasets 23

4. Results and discussion 24 4.1.Energy requirements for Bangladeshi population 24 4.2.Requirements of macro and micronutrients for Bangladesh 31 4.3.Diet and nutrient consumption patterns in Bangladeshi population 35

4.4.Dietary diversity score 45 4.4.1 DDS of Khagrachari, Rangamati and Dhaka city populations 47 4.5. Desirable intake for Bangladeshi population 47 4.6. Energy and nutrient gap calculation for Bangladeshi population 48 4.7. Identification of key foods 50 4.8. Exchange lists of foods based on energy values 58 4.9. Optimizing nutrition return 63 4.10. Dietary guidelines for Bangladeshi population 63 4.11. Menu planning 63 4.12. Conclusion 64 4.13. Recommendations 64

5. Bibliography 65

Appendices

A1: Physical Activity Level (PAL) calculations in different occupations in 73 Bangladeshi population A2: List of occupations in different PAL group 82 A3: PAL values for different type works 83 A4: Physical Activity Level (PAL) value of different work for females 85 A5: BMR in male and females according to age and body weight (FAO, 2004) 86 A6: Rich source of Energy, Carbohydrate, Protein and Fat 87 A7: Rich sources of Thiamine, β-carotene and Vitamin-C 89 A8: Rich sources of Calcium, Iron and Fiber 91 A9: Nutrient Return per 100 taka Spent 94 A10: Vegetable calendar for Bangladesh from January to June 103 A11: Vegetable calendar for Bangladesh from July to December 104 A12: Seasonal fruit calendar from January to June 105 A13: Seasonal fruit calendar from July to December 106 A14: Menu plan 107 A15: Scientific name of all the available Bangladeshi foods 131 A16: Selected photographs of DDP activity 139

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List of Tables Page No

Table 2.1: Per capita/day intake of major food items (g) in Bangladeshi population 3 Table 2.2: Prevalence of anaemia among pregnant and non-pregnant rural women 7 Table 2.3 Nutrition situation of Bangladesh 10 Table 2.4 Ranges of population intake goals 13 Table 2.5 Summary of the different terms of reference intake 16 Table 2.6 Measures of DDS at a glance 19 Table 4.1: Energy Requirements of Boys and Girls (up to 17 yrs of age) 25 Table 4.2: Energy Requirements of male and females of urban and rural areas 26 for 18-29.9yrs of age Table 4.3: Energy Requirements of male and females of urban and rural areas for 27 30-59.9yrs of age Table 4.4: Energy Requirements (kcal/day) of male and females of urban and rural 28 areas for >60yrs of age Table 4.5: Energy Requirements of male and females for hilly region (PAL, 2.41) 29 Table 4.6: Energy requirements for pregnant women and lactating mothers 30 Table 4.7: RDA for Macronutrients in different age groups for both male and females 31 Table 4.8: RNI of Vitamins for Bangladeshi population 32 Table 4.9: RNI (Recommended nutrient intake) of Calcium, Phosphorus, Iron, 33 Magnesium and RI (recommended intake) of Sodium and Potassium Table 4.10: RNI of iodine and zinc for Bangladeshi population 34 Table 4.11: Food intake (g/p/d) of the Bangladeshi population 35

Table 4.12: Mean per capita energy, protein, carbohydrate, fat and fiber intake of Bangladeshi population (weighted value) 36 Table 4.13: Distribution ranges of population- nutrient intake goals 36 Table 4.14: Adult male equivalent (AME) consumption for household members in different age groups according to HIES 2010 data 37 Table 4.15: Cereal intake of Bangladeshi population 41 Table 4.16: Comparison of energy, cereal and rice intake, HIES 2005 and 2010 41 Table 4.17: Diversity of pulse intake in Bangladeshi population 41 Table 4.18: Diversity of fish intake of Bangladeshi population 42 Table 4.19: Diversity of poultry and meat intake of Bangladeshi population 42

Table 4.20: Diversity of vegetables intake for Bangladeshi population 43 Table 4.21: Diversity of fruit intake among the Bangladeshi population 43 Table 4.22: Diversity of Oil and visible Fat intake of Bangladeshi population 44 Table 4.23: Diversity of milk and dairy product intake of Bangladeshi population 44 Table 4.24: Diversity of spices intake of the Bangladeshi population 44 Table 4.25: List of food groups for DDS Calculation 45 Table 4.26: Desirable intake for Bangladeshi population 48 Table 4.27: Current Intake and RNI of different Vitamins for adult Bangladeshi Population 49 Table 4.28: Intake and RDA of Zinc and Iron for adult Bangladeshi Population 50 Table 4.29: List of key foods with nutrient contributions according to HIES 2010 55 Table 4.29.1: Nutrient values of key foods 56 Table 4.30: Exchange list of fish according to energy contents 58 Table 4.31: Exchange list of lentils according to energy content 59 Table 4.32: Exchange list of leafy vegetables according to energy content 60 Table 4.33: Exchange list of nonleafy vegetables according to energy content 61 Table 4.34: Exchange list of fruits according to energy content 62

List of figures Page No Figure 2.1: Trends of anaemia among infants and preschool children in Bangladesh 7 Figure 4.1: Contribution of energy from carbohydrate, protein and fat 38 Figure 4.2: Distribution of carbohydrate intake of Bangladeshi population 39 Figure 4.3: Distribution of protein intake of Bangladeshi population 39 Figure 4.4: Distribution of fat intake of Bangladeshi population 40 Figure 4.5: DDS among Bangladeshi households of 14 different days 46 Figure 4.6: Distribution of DDS among Bangladeshi households 46 Figure 4.6.1: HDDS (Dhaka city, Khagrachari and Rangamati) 47 and IDDS (Students and slum peoples) Figure 4.7: Key foods for fibre 50 Figure 4.8: Key foods for protein 50 Figure 4.9: Key foods for fat 51 Figure 4.10: Key foods for carbohydrate 51 Figure 4.11: Key foods for calcium 51 Figure 4.12: Key foods for iron 51 Figure 4.13: Key foods for 52 Figure 4.14: Key foods for 52 Figure 4.15: Key foods for vitamin C 52 Figure 4.16: Key foods for Vitamin A 52 Figure 4.17: Key foods for folic acid 53 Figure 4.18: Key foods for zinc 53 Figure 4.19: Key foods for magnesium 53 Figure 4.20: Key foods for sodium 53 Figure 4.21: Key foods for potassium 54 Figure 4.22: Key foods for phosphorus 54

Acronyms AED Academy for Educational Development AI Adequate Intake AME Adult Male Equivalent ANR Average Nutrient Requirement ATP III Adult Treatment Panel III BARC Bangladesh Agriculture Research Council BARI Bangladesh Agriculture Research Institute BBS Bangladesh Bureau of Statistics BDHS Bangladesh Demographic Health Survey BDT Bangladesh Taka BIRDEM Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders BIRTAN Bangladesh Institute of Research and Training on Applied Nutrition BMI Body Mass Index BMMS Bangladesh Maternal Mortality Survey BMR Basal Metabolic Rate BRRI Bangladesh Rice Research Institute CBN Cost Basic Need CED Chronic Energy Deficiency DAM Department of Agriculture and Marketing DCI Direct Calorie Intake DDS Dietary Diversity Score DDP Desirable Dietary Pattern DEI Dietary Energy Intake DRI Dietary Reference Intake DRV Dietary Reference Value DHS Demographic and Health survey EAR Estimated Average Requirement FANTA Food and Nutrition Technical Assistance FAO Food and Agriculture Organization FCS Food Consumption Score FCT Food Composition Table

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FPMU Food Planning and Monitoring Unit GOB Government of Bangladesh HIES Household Income and Expenditure Survey HKI Helen Keller International HDDS Households Dietary Diversity Score HH Household HNPSP Health Nutrition and Population Sector Programme ICDDR'B International Centre for Diarrheal Diseases Research; Bangladesh ICMR Indian Council on Medical Research ID Iron Deficiency IDA Iron Deficiency Anemia IDD Iodine Deficiency Disorder IDF International Diabetes Foundation IDDS Individual Dietary Diversity score IOM Institute of Medicine INFS Institute of Nutrition and Food science IPHN Institute of Public Health and Nutrition LBW Low birth Weight LRNI Lower Reference Nutrient Intake MDG Millennium Development Goals NIN National Institute of Nutrition NIV Nutrient Intake Value NPNL Non pregnant non lactating PAL Physical Activity Level PopER Population Energy Requirement PSU Primary Sampling Unit RDA Recommended Daily Allowance RDI Reference daily Intake RNI Recommended Nutrient Intake SPSS Statistical Package for Social Science TDEE Total Daily Energy Expenditure TEE Total Energy Expenditure UNICEF United Nations Children‘s Fund UL Upper Limit

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UNL Upper Nutrient Level UNU United Nation University VAD Vitamin A Deficiency WDDS Women Dietary Diversity Score WHO World Health Organization WFP World Food Programme

Executive Summary Nutrition is a basic human need and prerequisite to a healthy life. A proper diet is essential from the very early stages of life for proper growth, development and to remain active. Food consumption, which to a large extent depends on production, access, distribution and affordability, impacts on the health and nutritional status of the population. Although Bangladesh has made considerable progress in increasing national level food availability, the intake of energy and other essential nutrients is still below the requirements and recommended dietary allowances. Diets are largely imbalanced with the staple food cereals contributing around 70% of total energy intake (HIES, 2010). A desirable dietary pattern therefore needs to be developed based on the current knowledge of nutritional requirements of different age, sex and occupational groups, the country‘s food and dietary habits and normative guidelines for a healthy diet. Such recommendations for the desirable dietary pattern are used for formulating dietary guidelines for individuals and groups and for planning national food and agricultural strategies. National guidelines for translating the required energy and nutrients play an important role in supporting long-term planning for balanced food intake, but these are not yet available for Bangladesh. The present study is an attempt to develop a desirable dietary pattern and diet plans for Bangladesh that will help to meet the both macro- and micro-nutrient requirements at affordable costs. Energy requirements for the Bangladeshi population were calculated using the FAO/WHO recommendations. For this purpose, the physical activity levels (PAL) of all the occupations were estimated. PAL values for specific work were adapted from the FAO classification (FAO, 1985; FAO, 2004). After estimating the PAL values, all the occupations were categorized according to physical activity (sedentary, moderate and heavy work) PAL values that varied between 1.4 and 1.69 were considered for the sedentary group, 1.70-1.99 were considered for the moderate activity group and >2.0 were considered for the heavy worker group (FAO, 2004). PAL values for all the occupations were analyzed to calculate the mean PAL values of sedentary, moderate and heavy worker group which are estimated as : sedentary 1.5, moderate 1.88 and heavy 2.46. Moderate and heavy worker groups in the hilly region were considered together because the population doing moderate work are engaged in tasks that involve both up hill and downhill movement. They need to expend more energy, and as such are engaged heavy work with an estimated PAL value for hilly region people at 2.41. The basal metabolic rate (BMR) for different age groups with different body weight have been adapted from the FAO assessment of energy requirements based on energy expenditure estimates expressed as multiples of basal metabolic rates (FAO, 2004). The FAO methodology was used for calculating population energy requirements. Accordingly, the energy (kcal) requirements were for sedentary: urban: male, 2430, female, 1980; rural: male, 2430, female 1980; moderate: Urban: male, 2997, female, 2442; rural: male, 3045, female, 2480; and heavy worker groups: urban: male, 3758, female, 3062; rural: male, 3985, female 3280. This study also documented the comparison of energy requirements and current energy intakes. To estimate the current energy intakes, secondary data from HIES 2010 was analyzed. Weighted per capita/day mean energy consumption according to

HIES 2010 was 2190 kcal (urban 2094, rural 2223kcal). It appears that the current energy consumption is about 240kcal deficient compared to the requirements of the average adult Bangladeshi population. But in terms of intra-household energy distribution according to adult male consumption equivalents, adult males are consuming adequate energy whereas females are still energy deficient. About 40% of the population take more than 75% of total calorie from carbohydrate which may have a linked with obesity and related diseases. Forty percent of the population take less than 10% of total calorie from protein sources and 53% of the population take less than 15% of total calorie from fat which reflects the scenario of stunting wasting and underweight in the country. Dietary diversity score (DDS) which is a proxy for nutrient adequacy of the diet of individuals, was calculated using the HIES 2010 food consumption data. Fifty percent of the households a dietary diversity score of less than 6 indicating those households at risk for micronutrient deficiency. Weighted per capita/day mean (±SD) carbohydrate (g), protein (g) and fat (g) intake for Bangladeshi population were 413±106, 57.2±15.6and 29.3±14.0 respectively. When protein intake of Bangladeshi population has been analyzed it is found that 66.5% of the population take more than 50g of protein but which are largely from plant sources. Weighted mean intake of vitamin A (µg/day), calcium (mg/day), iron (mg/day) and thiamine (mg/day) for Bangladeshi population according to the HIES 2010 data were 388±291, 439±227, 10.96±3.82 and 1.0±0.6. More than 70% of the population are consuming less than the requirements of vitamin a, calcium and iron. Although it appears that the mean intake of vitamin C (85.4±67.1mg/day) is sufficient, more than 25% of the population are noted to be consuming less than the requirement. Mean pulse intake was 14.68g/person/day and it was mostly from lentil (masur), but interestingly different kinds of pulses were also present in the diet. Mean fish and meat intake were 50.3 and 19 g/person/day respectively. On the other hand mean vegetable (167g) and fruit (45g) intake amounts to about half of the recommended dietary allowances. Mean oil intake was 20.4g/person/day in the Bangladeshi population. This study adapted the RDA of macro- and micro-nutrients (carbohydrate, protein fat, fibre, vitamin A, thiamine, riboflavin, niacin, folic acid, vitamin B12, vitamin C, calcium, magnesium, sodium, potassium, iron, zinc, phosphorus, iodine) from the FAO /WHO recommendations for all the age groups of the Bangladeshi population categorized by gender and physiological status. The present study proposes a total of 400g of cereals as against the current average current intake which is higher and from largely only rice. The present study recommends a combination of cereals (wheat and maize) rather than focus only on rice. For the fulfilment of macro- and micronutrient requirements, 50g of pulses, 130g of animal products (fish, meat, eggs), 100 g leafy vegetables, 200 g non leafy vegetables, 100g seasonal fruits and 130ml of milk or milk products have been proposed. Thirty key foods were identified and various menu options have been proposed to meet required nutrients. This study will be helpful to individuals to plan healthy diets and meals for their household and for stakeholders and policy makers for food and agriculture planning as well as for health and nutrition programmes.

1. Introduction Over the last decades, Bangladesh has made considerable progress in increasing national level food availability and also individual level energy intake. Nevertheless, the intake of energy and other essential nutrients is still far below the nutrient requirements and recommended dietary allowances. Diets are largely imbalanced with the staple food cereals contributing around 70% of total energy intake (HIES 2010). While a declining trend in the consumption of cereals has been noted, the pace of decline needs to be accelerated. A desirable dietary pattern (DDP) should be aimed at, with a proportion of no more than 60% dietary energy intakes (DEI) from cereals. The desirable dietary pattern of nutrients for a country‘s population is recommended based on the current knowledge of nutritional requirements of different age and sex groups and the country‘s food and dietary habits. Such recommendations for the desirable dietary pattern are used as the basis for dietary guidelines for individuals and groups and for planning national food and agricultural strategies. The Joint FAO/WHO/UNU Expert Consultation on Human Energy Requirements in 2001 led to review and update for energy, nutrient requirements and dietary intakes towards informing and guiding nutrition policy and planning (FAO, 2004). Further the recommended dietary allowances for protein and amino acids in human nutrition were also revised (WHO/FAO/UNU Expert Consultation, 2007). The Expert Consultation also proposed that countries could develop their own guidelines adapting from the FAO/WHO/UNU recommendations. The National Institute of Nutrition (NIN) updated its nutrient requirements and recommended dietary allowances based on the 2004 FAO/WHO/UNU Expert Consultation.

Diet plans that identify the quantities of different foods to be consumed to provide the human body with the required energy and nutrients play an important role in supporting long-term planning for balanced food intake, but these are not yet available in Bangladesh.

The present study is an attempt to develop a desirable dietary pattern and diet plans for Bangladesh that will help to meet the macro and micronutrient requirements at affordable costs. Such diets will have adequate dietary diversity; will be sustainable with an emphasis on the consumption of a variety of traditional and seasonal foods for ensuring diet improvement on a long term basis. This is in line with one of the key areas of interventions, namely long term planning for balanced food as outlined in National Food Policy Plan of Action 2008-2015.

1.1 Objectives and key research questions

Objectives

A. Compute energy requirements using PAL values for different physical activity categories segregated by age and gender in rural and urban areas of Bangladesh B. Compile nutrient requirements disaggregated by gender, age and physiological status (pregnancy, lactation) and physical activity levels

C. Develop diet plans that identify the types and quantities of foods required to provide energy and essential nutrients for a balanced diet of population disaggregated by gender, age, physiological status and physical activity levels in urban and rural areas with due attention to local food habits, food availability and biodiversity.

Research questions 1. What is the current dietary intake and pattern in Bangladesh? What are the gaps in meeting the nutrient requirements? How to fill up the gaps given the factors of (a) seasonality; (b) cost; (c) local availability; and (d) biodiversity 2. What is the energy and nutrient requirements for different age (0-65yrs) categories disaggregated by gender, physiological status and physical activity levels (sedentary, moderate and heavy workers) in both rural and urban areas of Bangladesh? 3. What are the types and quantities of foods to be identified for a desirable dietary pattern? 4. What is extent of biodiversity that exists for the Bangladesh diet? 5. What time frame should be used to assess the dietary intake? 6. What are the different food baskets that can be proposed? 7. What is the optimum nutrient return per 100 taka spent? 8. Who are the key stakeholders for building consensus on the desirable dietary pattern?

2. Literature Review

Diet, nutrition and health are closely interrelated. Mere availability of foods does not ensure the intake of a well balanced diet; it depends on proper nutritional knowledge, purchasing capacity and also on local food habits. Dietary intake patterns especially related to energy, protein and micronutrient rich foods and the diversity of diets are discussed in this section.

2.1 Dietary pattern Cereals, largely rice, form the main components of the diet in Bangladesh. The typical diet in Bangladesh is not balanced and remains dominated by a high intake of cereals (Jahan et al 1998; BBS, 2005; BBS, 2010). Household food consumption studies over the last 15 Table 2.1: Per capita/d intake of major food items (g) in Bangladeshi population, HIES Survey years 2010 Food items, g 1995-96 2000 2005 Poor Non-poor Total Total 913.8 893.06 947.75 816.22 1084.53 999.99 Rice 464.3 458.54 439.64 406.19 420.52 416.01 Wheat 33.7 17.24 12.08 20.36 28.73 26.09 Potato 49.5 55.45 63.30 63.44 73.78 70.52 Pulses 13.9 15.77 14.19 10.15 16.22 14.30 Vegetables 152.5 140.47 157.02 141.8 177.25 166.08 Edible oil 9.8 12.82 16.45 14.20 23.41 20.51 Onion 11.6 15.41 18.37 15.69 24.74 21.89 Beef 6.6 8.30 7.78 1.55 9.27 6.84 Mutton 1.0 0.49 0.59 0.11 0.83 0.60 Chicken/Duck 4.0 4.50 6.85 4.11 15.09 11.22 Eggs 3.2 5.27 5.15 3.40 9.02 7.25 Fish 43.8 38.45 42.14 31.16 57.81 49.41 Milk & milk 32.6 29.71 32.40 12.18 43.63 33.72 products Fruits 27.6 28.35 32.54 20.46 56.0 44.80 Sugar/Gur 9.2 6.85 8.08 3.32 10.88 8.50 Food taken - - 24.76 17.70 35.41 29.83 outside Miscellaneous 50.9 55.44 48.38 50.28 81.81 72.41 years have shown the consumption of cereal intake decreases but it still makes up the largest share (70 percent) of the diet, followed by non-leafy vegetables, roots and tubers, which together comprise more than four-fifths of the rural people‘s total diet (BBS, 2010). Protein and

3 micronutrient-rich foods like fish, meat, eggs, milk, milk products, fats and oils account for less than 10 percent of the rural person‘s diet, and the consumption of vegetables and fruits are slowly improving over the years. Rural consumption of leafy and non-leafy vegetables has remained more or less the same over the past two decades after increasing over the preceding 30 years. With an average national per capita consumption of 31g of leafy vegetables, 136g of non- leafy vegetables and 45g of fruit, the average Bangladeshi eats a total of 212g of fruit and vegetables daily (HIES 2010). This is far below the amount of 400 g of vegetables and fruit recommended by FAO/WHO in 2003.It is encouraging that the HIES 2010 points towards an increase in vitamin A and iron consumption as compared to HIES 2005 and Bermudez et al, 2012) but it still needs improvements to fulfill the requirements. In addition, cultural norms dictate a better diet for males over females with the male head of the household getting the best meal portions. Persistent poverty, inadequate nutrition information and gender inequity cause pervasive malnutrition among women, especially pregnant women and lactating mothers

2.2. Nutrition situation

The nutritional well-being of large part of the population is still being neglected because of insufficient access to sufficient, safe and nutritious food. As a result, children and women in Bangladesh continue to suffer high levels of malnutrition and micronutrient deficiencies, including low birth weight (LBW), under nutrition (underweight, stunting and wasting), vitamin A deficiency, iodine deficiency disorders and iron deficiency anaemia. At the same time, over nutrition, obesity and related health problems are emerging as multiple public health problems. Chronic energy deficiency (CED) is expressed as BMI less than 18.5 kg/m2 and used as a measure of malnutrition and health status in adults. A recent report (WHO, 2011) on non- communicable disease risk factor survey Bangladesh 2010 have been documented that about one fourth of the population are underweight (BMI<18.5 kg/m2). Among rural adult non-pregnant mothers, 30 percent have a Body Mass Index (BMI) of less than 18.5, which is indicative of ‗critical‘ food insecurity (BDHS 2007). The proportion of women suffering from CED has been decreasing in Bangladesh during the last decade, from 52% in 1996 to 32% in 2005 and to 25% in 2010 (FPMU 2012). Poor maternal nutrition affects the high incidence of low birth weight (LBW) in Bangladesh, estimated at 36 percent (BDHS 2007). Recently WHO reported that the percentage of LBW in Bangladesh is 22 (WHO, 2012).Among the children, the latest report of BDHS documented that 41% of children under five are stunted, 16% of children are wasted and 36% are underweight (low weight for age) (BDHS 2011). Dietary intakes of both children and adults are severely deficient in multiple micronutrients, particularly vitamin A, iron, iodine and zinc. Bangladesh has made significant progress in reducing vitamin-A deficiency among preschool children over the past 15 years. In National Micronutrient status survey 2011/12, the prevalence of vitamin A deficiency was reported as 20.5%, 20.9% and 5.4% respectively in preschool age children, school age children and the non-pregnant non-lactating women. However, the consumption of vitamin A rich foods is still low, suggesting that the underlying

4 causes of Vitamin A deficiency require further attention and support. Iron deficiency anemia affects one-third of adolescent girls and non-pregnant women and is even higher in pregnant women (51 percent; HKI/IPHN 2002). The latest National Micronutrient survey 2011/12 has shown a significant improvement where the prevalence of anaemia in the non-pregnant non- lactating women was 26% and in the preschool age children (under-5) was 33%. The immediate cause of malnutrition inadequate dietary diversity, as well as high infectious disease burden, household food insecurity and inappropriate household practices in feeding especially adolescent girls, pregnant women, mothers and young children.

2.2.1Energy deficiency Energy deficiency is defined as negative energy balance and includes chronic energy deficiency which is characterized by decreased body mass index i.e., BMI less than 18.5kg/m2. This is also termed as adult under nutrition. Present undernutrition among both sexes in the country is about 25% (WHO, 2011). Maternal undernutrition (body mass index <18.5 kg/m2) in non-pregnant rural women in Bangladesh declined from 54% in 1996/97 to 38% in 2003, 34% in 2004 and 30% in 2007 (BDHS), which is still very high. Undernutrition both before and during pregnancy causes intrauterine growth retardation and is one of the major factors responsible for the high prevalence of LBW (22%) in the country. Anaemia during pregnancy which is an outcome of maternal undernutrition in pregnancy is linked with the high prevalence of low birth weight (LBW) in the country. While updated estimates on LBW are not available, it is likely that between a fourth to a third of children are born of low birth weight. With regard to undernutrition among children under 5 years, between 1990 and 2011, underweight fell from 67% to 36%, and stunting fell from 66 to 41% (BDHS, 1990; BDHS 2011). Intrauterine and/or early childhood undernutrition is also linked with adult obesity or abdominal obesity and related adult diseases such as hypertension and diabetes (Godfrey and Barker, 2000; Popkin, 2001). Undernutrition at critical periods in intrauterine development causes permanent changes in the structure and/or function of the developing systems of the fetus (Lucas, 1991; Barker, 1998; Yajnik, 2004). This increases the susceptibility to disease in later life. Of the many possible insults during the intrauterine life, Hales and Barker have highlighted undernutrition as the most likely cause, though many factors could operate in a similar manner. The original hypothesis overlooked the classic association among maternal diabetes, fetal macrosomia and increased risk of diabetes for the offspring but new hypothesis allows for this (Hales and Barker 2001). However, the relationships among maternal nutrition, fetal nutrition, neonatal size and later diabetes appear to be more complicated than originally proposed (Harding, 2001)). This may have important implications for preventive strategies.

2.2.2. Obesity and chronic diseases Along with the problem of under nutrition among children and chronic energy deficiency in adults in many parts of Asia including Bangladesh, the burden of overweight and obesity is becoming increasingly widespread (WHO, 2007). In some countries, this situation exists amidst food shortage and nutrient inadequacies. Over the last decade, there has also been a progressive increase in over nutrition. Reduced physical activity is identified as a major attributable factor. In affluent urban segments, increased energy intake from fats, refined cereals and sugar, combined with simultaneous reductions in physical activity, have contributed to steep increases in over nutrition in all age groups. Recent evidence (WHO, 2011) from the non-communicable disease risk factor survey Bangladesh 2010 has shown that 17.6% of the Bangladeshi population are overweight and obesity and noticed that urban population (25.1%) are more prone than rural population (10.2%). In that report it is also documented that 3.9% of the population are diabetic on the basis of self reporting system, blood sugar was not measured to diagnose diabetes. Thus it may not the real picture because it is generally accepted worldwide that half of the diabetic population are undiagnosed. A study in a rural Bangladeshi population over a 10 year period have shown that the prevalence of diabetes increased from 2.3% in 1999 to 7.9% in 2009 (Bhowmik et al, 2012& 2013). In that study under nutrition, overweight and obesity in 2009 were 14%, 17% and 26% respectively, and the presence of metabolic syndrome (cluster of metabolic risk factors, i.e., insulin resistance, diabetes, obesity indicators, hypertension, hyperlipidemia) according to WHO, IDF (International Diabetes Federation) and ATP (Adult Treatment Panel III) criteria were 9.9%, 23.7% and 29.6%respectively with the prevalence of overweight and obesity, diabetes and other non-communicable diseases also on the rise in Asian regions.

2.2.3. Micronutrient deficiencies Micronutrient-related malnutrition is often termed ‗hidden hunger‘ as the consequences are not always visible. There are four micronutrients that are particularly relevant to public health: vitamin A, iron, iodine, and zinc. The following sections briefly describe the situation of micronutrient deficiencies in Bangladesh.

2.2.3.1. Iron deficiency Anaemia is the most commonly-used indicator to define iron deficiency in population-based studies or in clinical settings. It has been estimated about two billion people in the world are anaemic, mostly in the low income countries of Africa and Asia. In Bangladesh anaemia is common among all age groups and both sexes are affected, especially children and women-both pregnant and non-pregnant. Anaemia in under-5 children, pregnant and non-pregnant women studied by different organizations in different time periods like 1975/76 (Ahmed et al, 1977), 1981/82 (Hasan and Ahmed, 1983), 1995/1996 (Jahan and Hasan 1998), 1999 (HKI, 2000), 2001 (HKI, 2002), 2003 (Salam et al, 2006), 2004 (HKI, 2006), 2010 (Eneroth, 2010) and in 2011/12 (National Micronutrient Status Survey, 2013) are summarized in figure 2.1 and table 2.2.

Although the prevalence of anaemia decreased in 2001, after that the condition again deteriorated as reported 2003 and 2004 which may be due to gaps and challenges in the implementation of strategies. The recent national micronutrient survey (2013) reported that the prevalence of anaemia in preschool children and non-pregnant non-lactating women has been declining.

Fig 2.1: Trends of anaemia among infants and preschool children in Bangladesh

Table 2.2: Prevalence of anaemia among pregnant and non-pregnant rural women

Year Prevalence of anaemia (%)

Pregnant women Non-pregnant women 1975/1976 50 70 1981/1982 47 74 1995/1996 60 81 1997/1998 49.2 45 2003 41 34 2004 38.8 46 2011/12 26

Although the 2012 National Micronutrient Survey indicated significant improvements in the anemia situation of both preschool children and non-pregnant women, it continues to remain a public-health problem in Bangladesh. The cause of anaemia among young children and women is multi-factorial, including the low intake of bioavailable iron in the diet and high rates of infection. The intake of iron from complementary foods is critical for the infant from six months as breast milk alone cannot provide for the infant‘s increased need for iron for accelerated growth during that period. A WHO/UNICEF review of complementary foods in developing countries concluded that requirements of iron might be difficult to meet from non-fortified complimentary foods, especially if animal foods are not widely consumed.

2.2.3.2. Vitamin A deficiency In Bangladesh, vitamin A deficiency (VAD) had been identified previously as a major public- health(HKI, 1985). Study of Helen Keller International has been found a dramatic reduction in the prevalence of night blindness among preschool children from the 1980s to 2004, which is attributed to the successful programme of vitamin A supplementation launched in 1973 (HKI, 2005). Keratomalacia, the most severe form of VAD, is now seen occasionally among children hospitalized for SAM. However, a study in rural Bangladesh, sub-clinical VAD (serum retinol <0.7 µg/dL) was found in 18.5% of 200 pregnant women (Lee et al, 2008). The vitamin A intake by nearly half of pregnant women was less than the recommended dietary allowance. The recent national micronutrient survey 2011/12 have shown that vitamin A deficiency were 20.5%, 20.9% and 5.4% respectively in preschool age children, school age children and the non- pregnant non-lactating women. The current estimates indicated vitamin A deficiency still exists at a magnitude of public health significance in preschool age children and the school age children. The problem was aggravates in the slum stratum, where the prevalence was 38.0% and 27.0% respectively in the preschool age children and the school age children.

2.2.3.3. Iodine deficiency Iodine deficiency is one of the most important causes of preventable brain damage in children. Results of surveys conducted since the 1960s have indicated that Bangladesh is one of the country are most affected by iodine deficiency disorders (IDD) in the world. Due to universal salt iodization programme, the goitre prevalence decreased from 47% in 1993 to 18% in 1999 and biochemical iodine deficiency among population decreased from 69% in 1993 to 43% in 1999 as the coverage of households consuming iodized salt increased from 14% in 1995 to 70% in 2003. Despite this encouraging result, IDD remain a significant public health problem in the country. The latest Iodine Deficiency Disorder (IDD) Survey showed that the prevalence of goitre among 6-12 years old children was 6.2%, and it was 11.7% among women aged 15-44 years (Yusuf et al, 2007). However, more than one-third of children and women were suffering from sub-clinical iodine deficiency which also remains steady in the recent national

8 micronutrient survey 2011/12where it is stated that 40% of the school children and 42% of the non-pregnant non-lactating women are iodine deficient.

2.2.3.4. Zinc deficiency At the population level, the risk of zinc deficiency can be assessed based on two indirect indicators: (a) the prevalence of stunting and (b) the adequacy of absorbable zinc in food supply at the country level (Black et al, 2008). A stunting rate of more than 20% in under-five children is indicative of high risk for zinc deficiency at the country level (Black et al, 2008). With a 41% prevalence of stunting among under-five children, zinc deficiency is a major nutritional disorder in Bangladesh. The recent study has shown that national prevalence of zinc deficiency was 44.0% in the preschool age children and 57.0% in the NPNL women (National Micronutrients Status Survey 2011/12).

The nutritional status of the Bangladeshi population was studied by different national and international organizations in different time periods and is summarized in the table 2.3.

2.3. Energy Requirements and Reference Body Weight Dietary energy requirements of a healthy, well-nourished population should allow for maintaining an adequate BMI at the population‘s usual level of energy expenditure. At the individual level, a normal range of 18.5 to 24.9 kg/m2 BMI is generally accepted (WHO 1995, 2000). At a population level, a median BMI of 21.0 was suggested by the joint WHO/FAO Expert Consultation on Diet, Nutrition and the Prevention of Chronic Diseases (WHO/FAO, 2003). Age, gender, height, weight and BMI are interlinked to the energy and nutrient requirements of individuals. Anthropometric standards for population groups differ from country to country. Each country has to set up its own reference standards since height and weight of the population are not equal with other country. The purpose of recommending nutrient requirements help in planning norms for attaining anthropometric reference standards. International Organizations WHO, FAO have proposed reference standards applicable for developing countries. The 95th centile values of weights and heights for given age/gender can be taken to be representative of well- nourished normal population and considered as standard reference values for India. For children below age 17, the reference body weight is fixed at the median of the range of weight-for-height given by the BMI reference tables (WHO, 2006 and 2007). For adults and children of age 10 and above, the reference body weight is estimated on the basis of the fifth percentile of the distribution of the BMI (WHO, 1995; 2007).

Table 2.3:Nutrition situation of Bangladesh

1996- 1993- 2011 2007 2005 2004 2002 1999-2000 1990 1970 1997 1994 LBW% 36 36 Stunting (height-for-age) 66(HKI/IP 41 43 51 (%) HN,BDHS) Child Wasting (weight-for- nutritional 16 17 15 height) (%) status Underweight (weight- 39.7(Under 67(HKI/PH 36 41 43 for-age) (%) 5yrs) N,BDHS) Neonatal mortality 32 37 41 42 48 52 Post-neonatal mortality 10 15 24 24 34 35 Child 52 mortality/1 Infant mortality 43 52 65 (2002- 66 82 87 153 000 2006) Child mortality 11 14 24 30 37 50 Under-five mortality 53 65 88 94 116 133 3.51 2.90 3.20 -4.0 Maternal mortality Rate /1000 (BBS) (BBS) (BMMS) BMI (Woman) (<18.5) (%) 30 34 BMI (Woman) (>30) (%) 1.7 49(BBS/ 51(HKI Preschool child UNICEF) /IPHN) 47(BBS/ Pregnant woman UNICEF) Anemia % 33(BBS/

Non pregnant woman UNICEF) 29(BBS/ Adolescent UNICEF) 47 18 (1999 Goiter% (1993) HNPSP) HNPSP 43 (1999 69 (1993 Biochemical iodine deficiency% HNPSP) HNPSP)

2.4. Basal Metabolic Rate (BMR) BMR constitutes about 45 to 70 percent of total energy expenditure (TEE) in adults, and is determined principally by gender, body size, body composition and age. It can be measured accurately with small intra-individual variation by direct or indirect calorimetry under standard conditions, which include being awake in the supine position, ten to 12 hours after a meal, following eight hours of physical rest and no strenuous exercise in the preceding day, and being in a state of mental relaxation and an ambient environmental temperature that does not evoke shivering or sweating. BMR can be measured only under laboratory conditions and in small groups of representative individuals. There is a need to estimate BMR at the population level when using the factorial approach to estimate TEE from the average BMR and PAL value attributable to that population. Hence, the alternative has been to estimate a group‘s mean BMR using predictive equations based on measurements that are easier to obtain, such as body weight and/or height (FAO/WHO/UNU 2004).

The report from the 1985 FAO/WHO/UNU expert consultation used a set of equations derived mostly from studies in Western Europe and North America (Schofield, 1985). Almost half of the data used to generate the equations for adults were from studies carried out in the late 1930s and early 1940s on Italian men with relatively high BMR values, and questions have been raised about the universal applicability of those equations (Soares and Shetty, 1988; de Boer et al., 1988; Henry and Rees, 1991; Arciero et al., 1993; Piers and Shetty, 1993; Soares, Francis and Shetty, 1993; Hayter and Henry, 1993 and 1994; Valencia et al., 1994; Cruz, da Silva and dos Anjos, 1999; Henry, 2001; Ismail et al., 1998). The use of closed-circuit indirect calorimetry in most studies has also been questioned, as this technique might overestimate oxygen consumption and energy expenditure. FAO (2004) has reviewed extensively the predictive equations derived from a database with broader geographical and ethnic representation and recommended retaining the equations proposed in 1985 by Schofield to pursue a more thorough analysis of existing information, or to promote a prospective study with broad global geographic and ethnic representation.

2.5. Physical Activity Level (PAL) The 1981 FAO/WHO/UNU Expert Consultation estimated the energy requirements of adults as multiples of BMR (WHO 1985). This was later called ―physical activity level‖ (PAL) as per FAO software used for the calculation of human energy requirements. The average PAL of healthy, well-nourished adults is a major determinant of their total energy requirement. As growth does not contribute to energy needs in adulthood, PAL can be measured or estimated from the average 24-hour TEE and BMR. Multiplying the PAL by the BMR gives the actual energy requirements. Therefore, a person's Physical activity level (PAL) is a numeric method of expressing one's daily energy expenditure. PAL takes into account total daily energy expenditure (TDEE) and basal metabolic rate (BMR). The equation can be written as:

Classification of physical activity levels: Energy requirements are highly dependent on habitual physical activity. This consultation classified the intensity of a population‘s habitual physical activity into three categories, as was done by the 1981 FAO/WHO/UNU expert consultation (WHO 1985). However, in contrast with the 1981 consultation, a range of PAL values, rather than a mean PAL value, was established for each category. Furthermore, the same PAL values were used to assign men and women to a PAL category.

Classification of lifestyles in relation to physical activity, or PAL (FAO 2004) Category PAL value

Sedentary or light activity lifestyle 1.40-1.69

Active or moderately active lifestyle 1.70-1.99

Vigorous or vigorously active lifestyle 2.00-2.40*

* PAL values <1.40 extremely inactive cerebral palsy patient * PAL values > 2.40 are difficult to maintain over a long period of time.

2.6 Nutrient Requirements Humans need a wide range of nutrients to lead a healthy and active life. Establishing nutrient requirements is a vast and never-ending task, given the large number of essential human nutrients. The nutrients include protein, energy, carbohydrates, fats and lipids, a range of vitamins, and a host of minerals and trace elements. The required nutrients for different physiological groups can only be derived from a well balanced diet. Components of the diet must be chosen judiciously to provide all the nutrients to meet the human requirements in proper proportions for the different physiological activities. The establishment of human nutrient requirements is the common foundation for all countries to develop food- based dietary guidelines for their population. WHO and FAO provide technical support worldwide to establish and disseminate information on nutrient requirements which are adopted as part of the national dietary allowances. Others use it as a base for their standards. The concept of population nutrient intake goals is based on the first priority to ensure national food security and equity of distribution of available food in accordance with individual needs. Recommended nutrient intake (RNI) is the daily intake, which meets the nutrient requirements of almost all (97.5 percent) apparently healthy individuals in an age and sex specific population group. The FAO/WHO Expert Consultation‘s nutrient recommendations are population intake goals, not individual dietary guidelines. Most nutritional guidelines address the estimated needs of individuals and identify the minimum intake to meet the nutritional needs of individuals. However, in recognition of the detrimental effects the excessively high intakes of essential nutrients may have, the concept of a safe range of intakes has evolved. Population nutrient intake goals follow this concept and focus on the maintenance of low population risk rather than low individual risk. The joint WHO/FAO

Expert Consultation stressed that because population nutrient intake goals refer to substantially greater than intended if they are to be applied to the individuals. The population nutrient intake goals for consideration by national and regional bodies establishing dietary recommendations for the prevention of diet related chronic diseases as recommended by FAO/WHO are expressed in numerical terms below.

Table 2.4 Range of population nutrient intake goals (WHO/FAO 2003)

Goal (% of total energy, unless and otherwise Dietary factor specified elsewhere ) Total Fat 15-30%

Saturated fatty acids <10%

Polyunsaturated fatty acids 6-10%

n-6 PUFA 5-8%

n-3 PUFA 1-2%

Trans fatty acids <1%

Total Carbohydrate 55-75%

Free sugar <10%

Protein 10-15%

Cholesterol <300mg/day

Sodium chloride (sodium) <5g/day (<2g/day)

Fruits and vegetables >400g/day

Total dietary fiber From foods ( > 25g/day)

NSP (Non starch polysaccharides) From foods ( > 20 g/day)

In 2004, FAO/WHO Expert Consultations updated the requirements of all the essential vitamins and minerals for humans. Indian Council on Medical Research (ICMR) of National Institute of Nutrition (NIN) has also updated the requirements of micronutrients for Indians (NIN 2010). No such studies were conducted for Bangladeshi population though sporadic reports exist (Faruque et al., 1995; Ahmed et al., 1997, 1998) on micronutrient intakes (Vitamin A, folic acid, iron, iodine, Zn), and have shown that most of the authors reported that intake were not up to the desired level as recommended by FAO/WHO expert committee.

Reference nutrient intake values: The World Health Organization/Food and Agriculture Organization (WHO/FAO) together with the United Nations University (UNU), has published a number of recommendations (reference values) for different groups of nutrients over time. The most recent report on vitamin and mineral standard intake (FAO, 2004) uses the term RNI (recommended nutrient intake). The RNI is the daily intake that meets the nutrient requirements of almost all (97.5%) apparently healthy individuals in an age- and sex- specific population group. In 2004, FAO has published RNIs for 6 minerals and 11vitamins. Dietary Reference Intake (DRI): DRI (dietary reference intake) was proposed by the Joint Committee of the United States of America and Canada in 1995, in order to solve such problems. This term was charged with establishing reference values for planning and assessing diets of healthy population as well as serving as a basis for nutrition policies. The DRIs refer to the complete set of reference intakes, including the RDA (recommended dietary allowance), AI (adequate intake), UL (tolerable upper intake level), and EAR (estimated average requirement) (Institute of Medicine National Academy Press 1997, 1998, 2002, 2004). DRIs are expressed as intakes per day but are meant to represent average intakes of individuals over time. It is thought that the nutrient intake can vary substantially from day to day without ill effects (Murphy and Vorster 2007; Institute of Medicine National Academy Press 1997). Each DRI expression (RDA, AI, UL, and EAR) has specific uses for planning and assessing diets or for applications to nutrition policy and education. ―Dietary Reference Intakes for Japanese, 2005 (DRI-J)‖ was published in April, 2005. The DRIs-J were prepared for health individuals and groups and designed to present a reference for intake values of energy and 34 nutrients to maintain and promote health and to prevent lifestyle-related diseases and illness due to excessive consumption of either energy or nutrients. The DRI-J also includes a special chapter for basic knowledge of DRIs. Recommended Dietary Allowances (RDA): The RDA is the original term introduced by the US Food and Nutrition Board of the National Research Council in the 1940s (National Academy Press, 1989). It was defined as the level of intake of an essential nutrient that, on the basis of scientific knowledge, is judged by the Food and Nutrition Board to be adequate to meet the known nutrient needs of practically all healthy people. The RDA continues to be used as one of the nutrient intake values included in the US/Canadian dietary reference intake (DRIs). The DRIs refer to the complete set of reference intakes, including the RDA, AI adequate intake), UL (tolerable upper intake level) and EAR (estimated average intake). The RDA is set at a level of intake that meets the needs of 97% to 98% of healthy individuals in a particular age-and sex-specific group. It is the value that can be obtained from estimated average requirements (EARs) and an adequate margin of safety. They are calculated by the formula of RDAs=EARs+2SD (standard deviation). In Japan, the Recommended Dietary Allowances (RDA) was first established in 1970, after which a revision was made every five years. In June 1999, the sixth Revision of RDA was announced by the Ministry of Health and Welfare, and already started to use since 2000 effective to the year 2004. In the past years, RDAs had been established and used as the group target values to prevent nutritional deficiency. RDAs had been also used a guideline applicable for an individual only in case where such factors as sex, age, physical activity, physical generally correspond to those of a specific group on the other hand.

Dietary Reference Value (DRV): Dietary reference values (DRVs) are nutrient-based dietary standards recommended by the United Kingdom in 1991 (Department of Health 1991, Department of Health 1998). The DRVs apply to groups of healthy people and are not appropriate for those with disease or metabolic abnormalities. As for US/Canadian DRIs, the DRVs for a nutrient assume that requirements for energy and all other nutrients are met when deriving a specific reference value. The British DRVs provide three values for most nutrients: the lower reference nutrient intake (LRNI), the estimated average requirement (EAR), and the reference nutrient intake (RNI). For some nutrients, a ―safe intake‖ is given, and for carbohydrate and fat, individual minimum, maximum, and population averages are specified (Department of Health 1991). Recommended Nutrient Intake (RNI) : FAO and WHO with the United Nations University (UNU) has published a number of recommendations for different groups of nutrients. The most recent report on vitamin and mineral standards, published in 2004, uses the term RNI (recommended nutrient intake). The RNI is the daily intake that meets the nutrient requirements of almost all (97.5%) apparently healthy individuals in an age- and sex-specific population group. The most recent RNIs (for 6 minerals and 11vitamins) are based on nutrient-specific criteria. This term is set at 2 SD of the requirement above the EAR and will meet the needs of 97% to 98% of the population; it is similar to the US/Canadian RDA. The RNI is the daily intake that meets the nutrient requirements of almost all (97.5%) apparently healthy individuals in an age-and sex-specific population group. The most recent RNIs (for 6 minerals and 11 vitamins) are based on nutrient-specific criteria. A statistical distribution of requirements is derived from primary data, and the RNI equals the mean requirement plus 2 SD. It is equivalent, therefore, to the US/Canadian RDA, the British RNI, and the European PRI. Insufficient data were available to establish an RNI for vitamins E and A. An acceptable intake that supports the known function of vitamin E was determined and used as the best estimate of requirements. A recommended safe intake level was specified for vitamin A as the level of intake that prevents clinical signs of deficiency and allows normal growth, but it does not protect vitamin A status during prolonged periods of infection or other stresses. Nutrient intake value (NIV): FAO/WHO/UNU concurred (King and Garza, 2007) to use the term NIV (Nutrient Intake Value) to encompass the set of recommendations based on primary data that are analogous to those developed by various regional groups, e.g., dietary reference values (DRVs) by the United Kingdom, nutrient reference values (NRVs) by Australia and New Zealand, reference values for nutrient supply by Germany/Austria/Switzerland, and dietary reference intakes (DRIs) by the United States and Canada. The recommended terminology suggests that the set of values be called nutrient intake values (NIVs) and that the set be composed of three different values. . The group agreed to recommend only two NIVs, the average nutrient requirement (ANR) and the upper nutrient level (UNL). It recognized that groups charged with the development of such recommendations have derived other values, but that these other values usually are derived from estimates of nutrient-specific ANRs or UNLs. ANR reflects the median requirement for a nutrient in a specific population.

The above discussion about different terms of reference intake with initiating countries or organizations and introducing year are summarizes in the table 2.5. Expert Committee has suggested to use the uniform term NIV in 2007 for the nutrient recommendations but still the guideline with the value for NIV has not yet published so in this study the latest recommendations of FAO, RNIs are used for 6 mineral and 11 minerals.

Table 2.5. Summary of the different terms of reference intake

Name Abbreviation Country/Organization Year RDA Recommended dietary US Food and Nutrition Board of the 1940 allowances National Research Council RDI Reference daily intake USA/Canada 1968 DRV Dietary reference value United Kingdom 1991

DRI Dietary reference intake Joint of US Canadian Committee 1995

World Health Organization/ Food and RNI Recommended nutrient Agriculture Organization and United 2004 intake Nations University NIV Nutrient intake value FAO/WHO Expert Group 2007

2.7. Health and food crop diversity There is a crucial link between the maintenance of food crop diversity and effective strategies that ensure optimum nutritional status. Unfortunately, food production strategies to date have resulted in increasing dependence on cereals and other starchy staples, especially in poor communities (Tontisirin et al 2002). This has been linked to poorer nutrition. In this regard, the narrowing of the food base, a global phenomenon, is seen as an important factor affecting dietary diversity. Micronutrient malnutrition remains a problem of public health concern in most developing countries including Bangladesh. Food-based strategies have been recommended as the first priority to meet micronutrient needs (Allen, 2008) and an essential element of food-based approaches involves dietary diversification.

2.8. Dietary Diversity Score (DDS) Dietary diversity score is defined as the number of individual food items or food groups consumed over a given period of time (Ruel, 2003). It can be measured at the household or individual level through use of a questionnaire. Most often it is measured by counting the number of food groups rather than food items consumed. At the household level, dietary diversity is usually considered as a measure of access to food, (e.g. of households‘ capacity to access costly food groups), while at individual level it reflects dietary quality, mainly

16 micronutrient adequacy of the diet. The reference period can vary, but is most often the previous day or week (FAO & FANTA, 2011; WFP, 2009). Food and Agriculture Organization (FAO) in 2011 has published operational guidelines for measuring dietary diversity in a standardized way in both individual and household levels, based on a tool originally developed by FANTA (FAO, 2011; Swindale and Bilinsky, 2006). FAO suggested a reference period of the previous 24 hours. Using once 24 hour recall period does not provide an indication of an individual‘s habitual diet, but it does provide an assessment of the diet at the population level and can be useful to monitor progress or target interventions. There are various other valid time frames for recall, such as the previous 3 or 7 days, and in the case of some foods, the previous month. FAO has been suggested to use 24 hours because it is less subjects to recall error, less cumbersome for the respondents and moreover, DDS based on a 24 hour recall period is easier than with longer recall periods; For the DDS of household levels FAO has been suggested 16 different food groups and intake of foods from each group counts for one score. According to the suggestion of FAO, households who consumed <3 food groups are lowest DDS, households who consumed 4 to 5 food groups are medium DDS and households who consumed >6 food groups are high DDS.

Different type of DDS: The household dietary diversity score (HDDS) and individual dietary diversity score (IDDS) are calculated differently because the scores are used for different purposes. The HDDS is meant to provide an indication of household economic access to food, thus items that require household resources to obtain, such as condiments, sugar and sugary foods, and beverages are included in the score. The Individual Dietary Diversity Score (IDDS) reflects the nutrient adequacy of the diet and the food groups considered in this score place more emphasis on micronutrient intake rather than economic access to food. For this reason, the IDDS excludes the last two food groups from the 16 food groups which are recommended for HDDS and these two groups are: sweets, and spices, condiments and beverages. These groups may be used for additional analysis and considerations of bioavailability of micronutrients, but do not count as part of the IDDS. So, it is referred as IDDS14. The food groups considered in the score for the women dietary diversity score (WDDS) put more emphasis on micronutrient intake by FAO (2011) than on economic access to foods and a score based on nine food groups has been suggests for WDDS.

Amount of foods in HDDS: The amount of foods to be taken from each food group is an important factor to be considers while ensuring the micronutrient adequacy of diets. To avoid giving credit for consumption of a food group when the amounts reported were small (Kant et al 1993), excluded foods consumed in less than a minimum amount. For the meat, fruit and vegetable groups, the minimum reported amount for inclusion in the diversity score was 30g for all solid foods with a single ingredient and 60g for all liquids and mixed dishes, for the dairy and grain groups, this minimum amount was 15g for all solids and 30g for all liquids and mixed dishes. In the guidelines for measuring household and individual dietary diversity (FAO, 2011) it is recommended not need to set minimum quantities below which foods are not considered, so even small amounts of foods (for example, a very small portion of meat

17 included in mixed dish) needs to be counted. This is because the score is designed to reflect economic access to foods, and therefore even small quantities of food item reflect some ability to purchase that item. For women aged 15-49yrs, DDS were more strongly correlated with micronutrient adequacy of the diet when food quantities of approximately one tablespoon or less (<15g) were not included in the score (Arimond et al, 2010). In 2008, WFP standardized the food consumption score (FCS) to define dietary diversification on the basis of 7 days food frequency. In that method they divided the foods as nine groups and the consumption frequency of each food group per week was multiplied by the assigned weight of each food group. A specific weight was assigned for each food group. For example the assigned weight for rice is 2. If a person takes rice 7days/week then she will get 14 points from this food. In this method, if a person scores between 0-21, it is considered as poor diversification, 21-35 as borderline and >35 as acceptable. Spices and condiments have no score.

Correlation of HDDS with micronutrient density: DDS has been found to be positively correlated with adequate micronutrient density of complementary foods for infants and young children (FANTA 2006), and macronutrient and micronutrient adequacy of the diet for non breast-fed children (Hatloy et al, 1998; Ruel et al, 2004; Steyn et al, 2006; Kennedy et al, 2007), adolescents (Mirmiran et al, 2004) and adults (Foote et al, 2004; Arimond et al, 2010). A number of studies have looked at the association between some measure of dietary diversity and child nutrition outcomes. The Demographic and Health Survey (DHS) from Ethiopia has shown a strong and statistically significant association between food-group diversity measures based either on a 24-hour or seven-day recall and children‘s height-for- age Z-scores (HAZ) (Arimond and Ruel 2002). In that study a positive, and generally linear, trend in mean HAZ has been observed as food group diversity in the previous 7 days increases. A difference as large as 1.6 Z-scores has been observed between children who consumed one food group in the previous seven days compared to those who consumed eight food groups with adjusted other potentially confounding factors (Arimond and Ruel 2002). Over the past decade, three large multi-country validation studies (Hoddinott and Yohannes, 2002; Working Group on Infant and Young Child Feeding Indicators, 2006; Arimond et al, 2010) and many smaller studies have looked at the association between dietary diversity and food security and/or micronutrient adequacy of the diet. Hoddinott and Yohannes (2002) studied the association between household dietary diversity scores and dietary energy availability in ten countries. Increasing household dietary diversity significantly improved energy availability. The results suggest that dietary diversity scores have potential for monitoring changes in dietary energy availability, particularly when resources are lacking for quantitative measurements. A second multi-country study of diets of children 6-23 months from ten sites was undertaken to test the association between dietary diversity and mean micronutrient density adequacy of complementary foods. Significant positive correlations were observed in all age groups and in most of the countries (FANTA/AED, 2006). Recently the association between dietary diversity and micronutrient adequacy of diets of women of

18 reproductive age was assessed in five countries. Dietary diversity was significantly associated with micronutrient adequacy in all sites (Arimond et al, 2010). Studies carried out in individual countries and across diverse age groups showed correlations of 0.36 to 0.66 between dietary diversity scores and micronutrient adequacy ratios (Kennedy et al., 2007; Mirmiran et al., 2004; Mirmiran, Azadbakht and Azizi, 2006; Steyn et al., 2006; Hatloy, Torheim and Oshaug, 1998). Therefore, dietary diversity scores have been shown to be valid proxy indicators for dietary energy availability at household level and micronutrient adequacy of diets of young children and women of reproductive age. In a summary of seven studies reviewed by Ruel (2002), five found a positive association between dietary diversity score and nutrient adequacy. Of the studies focusing on young children, a positive correlation was found between DDS and nutrient adequacy in Mali, Kenya and Niger, while inconsistence results or no correlation were found in Guatemala, Ghana and Malawi. Greater dietary diversity has been associated with improved nutrient adequacy in children 4-8yrs of age in Kenya. Analysis of children aged 6-13.9 months from four developing countries concluded that there has been promising evidence for the utility of dietary diversity as an indicator of inadequate nutrient intake (Dewey et al 2005). In Table 2.6measures of DDS (FANTA/FAO) are presented where food groups used at household, individual, women, children and the food consumption score (WFP) are included.

Table 2.6 Measures of dietary diversity

Dietary Number diversity at Food groups Amount (g) of foods household level Cereals, white tubers and roots, vegetables, fruits, 30g for all solid HDDS (FAO & meat, eggs, fish and other seafood, legumes, nuts foods, 60g for all 12 FANTA 2011) & seeds, milk & milk products, oils & fats, liquids and mixed Sweets, spices, condiments and beverages. dishes Cereals, vitamin A rich vegetables, roots and 30g for all solid Dietary diversity white tubers, dark green leafy vegetables, other foods, 60g for all at individual 14 vegetables, vitamin A rich fruits, other fruits, liquids and mixed levels (IDDS) organ meat, flesh meat, eggs, fish, legumes, nuts dishes (FANTA 2006) & seeds, milk and milk products, oils and fats Starchy staples, dark green leafy vegetables, other At least 15g Women‘s dietary vitamin A rich fruits and vegetables, other fruits diversity 9 & vegetables, organ meat, meat and fish, eggs, (WDDS) legumes, nuts and seeds. Cereals and tubers, vitamin A rich fruits & Children (3yrs) vegetables,other fruits, other vegetables, legumes Dietary Diversity 10 and nuts, oils and fats, meat/poultry/fish, dairy, (Steyn et al, eggs, others (sweets,chips,soda,condiments,solid 2006) foods and liquid foods). Cereals and tubers; pulses; vegetables; fruits; WFP (2008) 8 meat, fish, eggs; Milk and milk products; sugar; oil 19

3. Methodology Although the country is producing more food and improving nutritional status but still a large part of the population are facing both under- and over-nutrition related morbidity and mortality which is delaying the national economic cycle. A national desirable dietary guideline is essential for each county following the criteria of International Experts considering habit, PAL, seasonality and availability of foods for healthy life. Most of the developed and developing countries already have developed the dietary guideline but still there is a little information regarding the guidelines for desirable dietary pattern for the Bangladeshi population. The present study focused on the calculation of energy requirements, adaptation of micronutrient requirements using the FAO/WHO recommendations, analysis of the current food and nutrient intake patterns and menu development for the Bangladeshi people, for future healthy generation with the consensus of the key stakeholders of the country.

3.1. Energy requirement: For the calculation of energy requirements of adults we have considered reference body weight, BMR and PAL value according to the suggestions of Expert Consultations (FAO/WHO/UNU, 2004). Reference body weight and BMR for all ages have been adapted from FAO Guidelines 2004 considering gender and physiological condition. In this work energy requirement for 0-17 yrs age have directly adapted from the software named population energy requirement (PopER) which is developed by FAO for both developed and developing countries. In this software physical activity levels of the population in this age group are considered as a common group because they are doing almost similar type of work. Therefore, for a specific age, it is assumed that all the children have similar energy demands. Average PAL values for different occupations of the Bangladeshi population have been calculated using the PAL values established by FAO/WHO/UNU (2004).In this study we have calculated PAL values of 139 occupations considering 8 hours as occupational work,18 hours for sleeping, and the rest 8 hours for house hold work and personal hygiene and recreation. Out of 139 occupations 17 were urban, 17 were rural and 105 occupations were in both urban and rural areas. These occupations have classified as sedentary, moderate and heavy activities, using the FAO/WHO/UNU classification (sedentary PAL 1.40-1.69, moderate PAL 1.70-1.99 and vigorous PAL 2.00-2.40). Energy requirements for adults were calculated from the factorial estimates of PAL by multiplying with BMR and body weight. The following example to calculate the average energy requirement of a female population aged between 18 – 29.9 yrs with a moderately active lifestyle and a mean body weight of 55kg is illustrated in the calculation:

Energy requirement = BMR x PAL x Body weight = 24kcal/kg/d x 1.85 x 55kg = 2442 kcal/day

1As established by International Labour Organization 20

After the estimation of energy requirements for individual age groups of males and females with different physical activity levels for both the urban and rural areas we have calculated the average energy requirements for Bangladeshi adults considering the body weight of males as 60kg and females as 55kg. The proportion of sedentary, moderate and heavy work groups were considered from a previous study (Murshid et al, 2008). 3.2. Nutrient requirement: Reference nutrient requirements have been revised by different organizations as well as different countries over time based on newer scientific knowledge and applications for estimating nutrient requirements and food needs of the population worldwide. The present study has adapted the latest FAO/WHO recommendations for requirements of macro and micro nutrients considering gender and physiological conditions. The recommended dietary allowances (RDA) of carbohydrate and protein were adapted from the recommendations of FAO, 2007 and fat from FAO, 2008. Ranges of population nutrient intake goals were included from the WHO/FAO Expert Consultation 2003. Carbohydrate, protein and fat requirements as a percentage of total energy requirements were recommended as 55 to 75% of total energy from carbohydrate, 10 to 15% energy from protein and 15 to 30 % energy from fat. Micronutrients and fiber requirements were adapted from other sources (Nutrient reference values for Australia & New Zealand, 2005). Recommended nutrient intake (RNI) of Vitamin A, vitamin B like thiamine, riboflavin, niacin, B12, folic acid, and vitamin C were adapted from FAO (Human vitamin and mineral requirements, 2004). Calcium, phosphorus, Iron, magnesium, iodine and zinc were also adapted from FAO (Human vitamin and mineral requirements, 2004). Sodium and potassium requirements were adapted from NIN 2010 that has been based on the FAO/WHO recommendations. 3.3. Food intake pattern in Bangladesh: Current patterns of food and nutrient intake were calculated using secondary data from HIES 2010 considering all the studied households (12240) using the food composition table (FCT) of INFS (Shaheen et al, 2013) for the nutritive value of energy, fat protein, carbohydrate and all the micronutrients (vitamin A, thiamine, riboflavin, vitamin C, calcium, iron, fiber, magnesium, sodium, potassium, phosphorus, iodine, zinc and niacin). 3.4. Household Dietary Diversity Score (HDDS): HDDS of Bangladeshi population were calculated according to the HIES 2010 data using FANTA and FAO, 2011 Guidelines. In this method 24hr dietary recall for 14 different days of 12240 households were analyzed, total foods items have been divided into 12 food groups as in FANTA/FAO guidelines. For consumption of each group food with amounts of at least 30g for solid and 60g for liquid form have been considered for one score. Mean HDDS of 14 different days and as a whole mean HDDS have been calculated. According to the suggestion of FAO, households who consumed <3 food groups are lowest DDS, households who consumed 4 to 5 food groups are medium DDS and households who consumed >6 food groups are high DDS. As a cross check for the DDS value of HIES 2010, the present study also collected 24hr household food consumption data of 511 households and 300 individual women from Dhaka city (386 households from Zurain, Mohammadpur, Lalmatia and Mirpur areas, 200 students of graduation level, 100 adults from slum area), Khagrachari (75 households) and Rangamati

(50 households) districts. HDDS was calculated as above and IDDS for individual students and women from slums were calculated using 9 food groups. 3.5. Key Food Identification: In the identification of key foods for Bangladesh, we have used HIES 2010 food consumption data and applied the methodology established by Haytowitz et al (2002). HIES 2010 data have shown that about 139 types food item were consumed by Bangladeshi population. For the identification of key foods, we have considered amount of food consumption, nutrient content of consumed food and frequency of house hold consumed the food. At first we have calculated per capita average consumption of each food item consumed by the survey respondent. After that we have calculated total consumption of each food item by multiplying average amount of food and the total survey respondents. After that we have calculated total grams consumed for each nutrient from all foods (total quantity of nutrient like carbohydrate, protein, fat, calcium, sodium, potassium, phosphorus, magnesium, zinc, iron, folic acid, vitamin A, thiamine, riboflavin, niacin vitamin C). Finally we have calculated nutrient contribution percent for each individual food by dividing total amount of nutrient consumed from all foods. A cumulative percent up to 75% was considered ‗as key food‘ for individual nutrients. In this way we have selected 5 to 8 food items for each nutrient. About 110 foods have primarily identified as key foods for 17 nutrients. Among the 110 foods we have identified 30 key foods from maximum amount and number of nutrient contributions. The 30 key food lists have arranged on the basis of number of nutrient contribution (Table 4.41). 3.6. Crop Calendar: Staple foods like rice and wheat are available throughout the year, therefore, Bangladeshi fruits and vegetables were documented in the calendar with the help of experts from Bangladesh Agriculture Research Council (BARC) and Agriculture Information Services, Khamar Bari. In this calendar we have included all the available leafy vegetables, non-leafy vegetable and fruits which are grown in Bangladesh. In this study we have included the name of food when it is available in market. Crop calendar is placed in appendix A10 – A13. 3.7. Compilation of Bangladeshi Foods: List of all available foods of Bangladesh with local English and scientific names were compiled from reference books and web address and summarized in appendix A14. 3.8. Optimizing Nutrition Return: Money should be spent logically to get the required nutrients. Nutrient return for each hundred taka spent were calculated in this study using updated food composition table and average market prices. Average market prices were determined using the food price from the period of January 2010 to December 2010 of DAM (Department of Agricultural Marketing), Ministry of Agriculture, Bangladesh. 3.9. Menu planning: Different combination of menus with serving size and food exchange lists considering energy content of the menus and diet plans were documented. Desirable dietary plans for average adults with 60kg weight for male and 55kg weight for female were proposed to meet the energy and essential nutrients for different economic (poor and non-poor) categories giving due attention to local food habits, food availability and

22 biodiversity. Photo documentation of different menus, food lists corresponding to calorie requirements have also developed. 3.10. Serving size calculation: Serving size is known as the measuring unit of foods. We have calculated the serving size of Bangladeshi foods especially leafy vegetables, non-leafy vegetables and fruits. Detailed serving size has been discussed in the dietary guidelines. 3.11. Food Exchange list: All available fruits in Bangladesh have been classified into 9 groups according to similarity of calorie contents so as to have an equal exchange of foods/fruits from any group according to need and choice. An exchange list for cereals, leafy vegetables, non-leafy vegetables and fish has been developed.

3.12. Key Stakeholders for building consensus: Faculty members of INFS, Dhaka University; and Food and Nutrition Departments of public and private affiliated colleges of Dhaka University, scientist and researchers in the field of Nutrition from ICDDR'B, BRRI, BARI, IPHN, BIRTAN and BARC, Nutritionists working in different hospitals in Dhaka city, policy makers from the Ministries of Agriculture, Food, Disaster Management, and Health and Family Welfare, Representatives from FAO, WHO, UNICEF, WFP (Country Office). A dietary guidelines booklet and a technical report for a desirable dietary pattern for Bangladesh with all necessary information have been developed for use.

3.13. Dietary guidelines for Bangladesh: A desirable dietary guideline for Bangladesh has been developed based on food and nutrient intake analysis of HIES 2010 data along with current nutrient situation of Bangladesh and also consider the suggestions of National and International stakeholders in the field of nutrition.

3.14. Analysis of datasets: Data were analyzed using Statistical Package for Social Sciences (SPSS) for Windows version 17 and database. Mean ±SD intake of foods, energy and micronutrients were calculated using SPSS. Graphs (bar diagram, pie charts) were prepared using Microsoft Excel 2010. Dietary diversity score for the households were calculated using the same database.

4. Results and Discussion

4.1. Energy requirements for Bangladeshi population Human energy requirements are estimated from measures of energy expenditure plus the additional energy needs for growth, pregnancy and lactation. Recommendations for dietary energy intake from food must satisfy these requirements for the attainment and maintenance of optimal health, physiological function and well-being. Energy requirements for Bangladeshi population were calculated using the FAO recommendations and methodology (FAO/WHO, 2004). Occupation has a very significant impact on daily energy expenditure, and thus, on per capita energy requirement. This is because individuals engaged in a particular occupation have to remain engaged in a specific activity for one third of the total daily available time, and the type of occupation determines the mean physical activity level (PAL) of a person. Therefore, all the available occupations in the country were tabulated and physical activity level (PAL) of all the occupations were estimated. PAL values for specific works were noted from FAO literatures (FAO 1985, FAO, 2004). For the calculation of energy requirement, the present study considered PAL, BMR, and desired bodyweight following FAO/WHO/UNU (2004) recommendations. PAL values for different occupations in the country were estimated using PAL values of different activities suggested by the Expert Committee (Appendix A1). Bangladeshi occupations were classified into 3 groups: Sedentary having a PAL value between 1.4 and 1.69; Moderate having a PAL value between 1.70-1.99 and heavy worker category with a PAL value >2.0 (FAO 2004). The mean PAL values within the categories were calculated and in the rural occupations, the mean PAL values for sedentary, moderate and heavy workers were calculated as1.5, 1.88 and 2.46 and the values for urban occupations were 1.5, 1.85 and 2.32. Moderate and heavy worker groups in the hilly region were considered together because the moderate need to expend more energy for climbing up hill and downhill activities, the moderate and heavy category of workers are classified into one group. Accordingly estimated PAL values for hilly region people were 2.41. Occupations in sedentary, moderate and heavy work are summarized in Appendix A2 and PAL values of different activities in male and females are tabulated in appendix A3 and A4. The previous study estimated the PAL values for sedentary, moderate and vigorous work groups as 1.46, 1.81 and 2.55 respectively (Murshid et al, 2008) where only 20 occupations were recruited. Basal metabolic rate (BMR) in different age groups with different body weight from FAO literature (FAO/WHO/UNU, 2004) was used to calculate the energy requirements (Appendix A5).

Energy requirements (ER) for children -up to 17 yrs of both boys and girls were adapted from PopER software developed by FAO for the developing countries (table 4.1). For this calculation energy requirement for growth considered with total energy expenditure. In this method PAL values of all the boys for a specific age are considered similar since their activities are mostly similar. Accordingly, PAL values of all the girls for a specific age are similarly considered. For example, energy requirement for 17 year old boys have been

24 calculated as 3108kcal/day and for girls as 2377kcal/day. A proportion of urban children are engaged in video games rather than out-door playing, in this situation parents should think about their energy needs and may consults with the proper dieticians otherwise they are going to be overweight and obese. WHO reported in World Health Statistics that about 1.1% of the Bangladeshi children (<5yrs) are overweight (WHO, 2012). The percentage is much higher in school-aged urban children (Mohsin et al, 2012).

Table 4.1: Energy Requirements of Boys and Girls (up to 17 yrs of age)

Boys Girls Age, yrs Body wt kcal/kg/d kcal/d Body wt kcal/kg/d kcal/d <1 7.47 83 620 7 83 574 1.00 11.43 82 937 11 80 863 2.00 13.51 84 1135 13 81 1053 3.00 15.67 80 1254 15 77 1160 4.00 17.69 77 1362 17 74 1244 5.00 16.71 78 1303 16 75 1202 6.00 18.46 76 1403 18 73 1300 7.00 20.37 74 1507 20 71 1403 8.00 22.55 72 1624 22 68 1502 9.00 25.00 70 1750 25 66 1638 10.00 27.80 68 1890 28 63 1777 11.00 30.88 66 2038 32 60 1942 12.00 34.38 64 2200 37 56 2070 13.00 38.63 62 2395 41 54 2198 14.00 43.96 60 2638 43 52 2247 15.00 49.87 57 2843 45 51 2294 16.00 55.21 55 3037 47 50 2333 17.00 58.64 53 3108 49 49 2377

Energy requirements (ER) for the adult Bangladeshi population from 18-65 yrs were developed for a certain range of body weights considering BMR and calculated PAL values. There are differences of BMR between male and females, and also differences of PAL values (moderate and heavy workers) between rural and urban workers. Therefore, ER of male and female for both urban and rural areas were calculated and are given in following tables. The energy requirements estimated here are for the persons with normal BMI (18.5-23kg/m2). In the same age group BMR also varies with differences of bodyweight, for instance, a man between 18-30 age groups BMR for 45kg and 75kg body weight are29kcal/kg/day and 24kcal/kg/day respectively which consequences in the variation of energy requirements. Table 4.2 shows the energy requirements of male and females with 18 to 29 years of age disaggregated by physical activity levels in both urban and rural areas. A male person with 60kg body weight of urban area have shown 2430, 2997 and 3758 kcal of energy requirements per day for sedentary, moderate and heavy work groups respectively and for the person with same body weight in rural areas the values are 2430, 3046 and 3985 kcal respectively. 25

Table 4.2 Energy Requirements of male and females of urban and rural areas, 18-29.9yrs

BW, BMR, Urban Rural kg kcal/kg/d Sedentary, Moderate, Heavy, Sedentary, Moderate, Heavy, PAL 1.5 PAL 1.85 PAL 2.32 PAL 1.5 PAL 1.88 PAL 2.46 45 29 1958 2414 3048 1958 2453 3210 50 29 2175 2683 3364 2175 2726 3567 Male 55 28 2310 2849 3573 2310 2895 3788 60 27 2430 2997 3758 2430 3046 3985 65 26 2535 3127 3921 2535 3177 4157 70 25 2625 3238 4060 2625 3290 4305 75 24 2700 3330 4176 2700 3384 4428 40 26 1560 1924 2413 1560 1955 2558 45 26 1755 2165 2714 1755 2200 2878 Female 50 25 1875 2313 2900 1875 2350 3075 55 24 1980 2442 3062 1980 2482 3247 60 23 2070 2553 3202 2070 2594 3395 65 22 2145 2646 3318 2145 2688 3518 70 22 2310 2849 3573 2310 2895 3788 75 21 2363 2914 3654 2363 2961 3875 BW, Body weight; BMR, Basal metabolic rate

Table 4.3 shows the energy requirements of male and females with 30 to 60 years of age disaggregated by physical activity levels in both urban and rural areas. A male person with 60kg body weight requires 2340, 2886 and 3619 kcal energy for sedentary, moderate and heavy work groups respectively in urban areas whereas 2340, 2933 and 3838 kcal respectively requires for rural areas. Similarly a female person with 55kg body weight requires 1980, 2442 and 3062 kcal energy respectively, in urban areas whereas the energy requirements of rural females with 55kg body weight are 1980, 2482 and 3247 kcal, respectively.

Table 4.3: Energy Requirements of male and females of urban and rural areas, 30-59.9yrs

Sex BW, BMR, Urban Rural kg kcal/kg/ d Sedentary, Moderate, Heavy, Sedentary, Moderate, Heavy, PAL 1.5 PAL 1.85 PAL 2.32 PAL 1.5 PAL 1.88 PAL 2.46 45 23 1553 1915 2401 1553 1946 2546

50 23 1725 2128 2668 1725 2162 2829 Male 55 22 181 2239 2807 181 2275 2977 60 22 1980 2442 3062 1980 2482 3247 65 21 2048 2525 3167 2048 2566 3358 70 20 2100 2590 3248 2100 2632 3444 75 20 2250 2775 3480 2250 2820 3690 40 24 1440 1776 2227 1440 1805 2362

45 24 1620 1998 2506 1620 2030 2657 Female 50 22 1650 2035 2552 1650 2068 2706 55 21 1733 2137 2680 1733 2171 2841 60 20 1800 2220 2784 1800 2256 2952 65 19 1853 2285 2865 1853 2322 3038 70 18 1890 2331 2923 1890 2369 3100 75 18 2025 2498 3132 2025 2538 3321 BW, Body weight; BMR, Basal metabolic rate

Table 4.4 shows the energy requirement for people more than 60 years of age disaggregated by sex and physical activity levels in urban and rural areas. In this age group, male persons with 60kg body weight of sedentary, moderate and heavy work groups in urban areas require 1980, 2442 and 3062 kcal of energy respectively whereas for the rural persons with same body weight requires 180, 2482 and 3247 kcal of energy respectively. Similarly females with 55kg body weight of urban areas require 1733, 2137 and 2680 kcal energy for sedentary, moderate and heavy work group population whereas the same females in rural areas require 1733, 2171 and 2841 kcal of energy, respectively.

Table 4.4: Energy Requirements (kcal/day) of male and females of urban and rural areas, >60yrs

Sex BW, BMR, Urban Rural kg kcal/kg/d Sedentary, Moderate, Heavy, Sedentary, Moderate, Heavy, PAL 1.5 PAL 1.85 PAL 2.32 PAL 1.5 PAL 1.88 PAL 2.46 45 29 1958 2414 3028 1958 2453 3210

50 29 2175 2683 3364 2175 2726 3567 Male 55 27 2228 2747 3445 2228 2792 3653 60 26 2340 2886 3619 2340 2933 3838 65 25 2438 3006 3770 2438 3055 3998 70 24 2520 3108 3898 2520 3158 4133 75 23 2588 3191 4002 2588 3243 4244 40 27 1620 1998 2506 1620 2030 2657

45 27 1823 2248 2829 1823 2284 2989 Female 50 25 1875 2313 2900 1875 2350 3075 55 24 1980 2442 3062 1980 2482 3247 60 22 1980 2442 3062 1980 2482 3247 65 21 2048 2525 3167 2048 2566 3358 70 20 2100 2590 3248 2100 2632 3444 75 19 2138 2636 3306 2138 2679 3506 BW, Body weight; BMR, Basal metabolic rate

The following table (table 4.5) shows energy requirements of the population of hilly region for all the adult age groups in both male and females.

Table 4.5: Energy Requirements of male and females for hilly region (PAL, 2.41)

18-29.9 yrs 30-59.9 yrs >60 yrs Sex BW, BMR, kcal/d BMR, kcal/d BMR, kcal/d kg kcal/kg/d kcal/kg/d kcal/kg/d 45 29 3145 29 3145 23 2494

50 29 3495 29 3495 23 2772 Male 55 28 3711 27 3711 22 2916 60 27 3904 26 3904 22 3181 65 26 4073 25 4073 21 3290 70 25 4218 24 4218 20 3374 75 24 4338 23 4338 20 3615 40 26 2506 27 2603 24 2314

45 26 2820 27 2928 24 2603 Female 50 25 3013 25 3013 22 2651 55 24 3181 24 3181 21 2784 60 23 3326 22 3181 20 2892 65 22 3446 21 3290 19 2976 70 22 3711 20 3374 18 3037 75 21 3796 19 3434 18 3253 BW, Body weight; BMR, Basal metabolic rate

Average energy requirements for Bangladeshi adults Average energy requirements for adult Bangladeshi population were calculated considering the PAL values of males and females in both urban and rural areas and a desired body weight of 60kg for male and 55kg for females. The percentage of population engaged in different physical activity levels (sedentary, moderate, heavy) are considered according to the work done in a previous study (Murshid et al, 2008). After considering these factors the average daily energy requirement for adult Bangladeshi population was estimated as 2430kcal. It may be noted that the mean dietary energy requirement for the population reported by Murshid et al (2008) was 2187kcal which is 243 kcal lower than this study. This discrepancy may be explained by the lower desired body weight (male 56kg, female 47kg) used by Murshid et al. We have adapted the desired body weight from the latest report of NIN (2010) which is comparable to the body size and structure in Bangladesh given the similarities in body size and composition.

Energy requirements in pregnancy Pregnancy is a special physiological condition where 12kg weight gain throughout the gestational period is considered as standard to ensure the full-term delivery of a healthy baby. This weight gain is the total growth of foetus, placenta and associated maternal tissues. For these growths extra energy needed from the beginning of conception and the requirement is increasing with the increase of gestational period. A Joint FAO/WHO/UNU Expert

Consultation on Human Energy Requirements estimated the total energy cost of pregnancy at around 77000kcal based on data from longitudinal studies and factorial calculations of the extra energy required during this period (FAO/WHO/UNU, 2004). The additional energy recommended during pregnancy is: 85kcal, 285kcal and 475kcal per day for first, second and third trimester, respectively. These recommendations are proposed as additional energy needs during pregnancy for Bangladeshi females. Accordingly, the total energy requirements for sedentary, moderate and heavy worker females in both urban and rural areas are summarized in table 4.6. In this calculation the body weight for females was considered as 55kg.

Energy requirements during lactation Like pregnancy, lactating mothers also require an additional energy which corresponds to the energy cost of milk production and secretion, its energy content and the efficiency with which the dietary energy is converted to milk energy. Considering the amount of milk production in first six months and second six months, FAO/WHO/UNU, 2004 have suggested an additional 675kcal/day for the first six months of exclusive breastfeeding and 460kcal/day for the second six months (Table 4.6) . This is recommended as additional energy requirements for lactating mothers in urban and rural areas having different physical activity levels and considering a body weight as 55kg. It has also been recommended that well- nourished women with adequate gestational weight gain may increase their food intake by 505kcal/day for the first six months of lactation. Energy requirements for milk production in the second months are dependent on rates of milk production, which are highly variable among women in the population.

Table 4.6: Energy requirements for pregnant women and lactating mothers

Physiological Period of Urban Rural condition pregnancy/ lactation Sedentary Moderate Heavy Sedentary Moderate Heavy

1st 2065 2527 3147 2065 2567 3332 Trimester (1980+85) (2442+85) (3062+85) (1980+85) (2482+85) (3247+85)

2nd 2265 2727 3347 2265 2767 3532 Pregnancy Trimester (1980+285) (2442+285) (3062+285) (1980+285) (2482+285) (3247+285)

3rd 2455 2917 3537 2455 2957 3722 Trimester (1980+475) (2442+475) (3062+475) (1980+475) (2482+475) (3247+475)

0-6 Month 2655 3117 3737 2655 3157 3922 (1980+675) (2442+675) (3062+675) (1980+675) (2482+675) (3247+675) Lactation 7-12 2440 2902 3522 2440 2942 3707 Months (1980+460) (2442+460) (3062+460) (1980+460) (2482+460) (3247+460)

4.2. Requirements of macro and micronutrients for Bangladeshi population The human body requires a certain amounts of macro and micronutrients for minimizing risk of nutrient deficit or excess for optimum health and function. The requirements vary with individual age group, physical activity levels, physiological conditions and gender. In advancement of scientific knowledge the requirement of both the macro and micronutrients has been revised and the Expert Committee of FAO/WHO/UNU has contributed significantly to the establishment and harmonization of the nutrient requirements. In the present study, the FAO/WHO recommendations for macro and micronutrients established in 2004 and 2007 have been adapted. Previously the requirements of macro and micronutrients for Bangladeshi population documented from the 1985 FAO/WHO recommendations in a booklet named ―Deshio Khaddodrobber Pushtiman‖ by INFS, Dhaka University in 1992. These have served as reference throughout the country. In 2007 WHO/FAO/UNU recommended a protein requirement of 33 to 66 g (0.83g/kg/day) depending on the body weight. This requirement is being proposed for the Bangladesh population asp resented in table 4.7.

Table 4.7: RDA for Macronutrients in different age groups for both male and females

Total Fat Age( Protein (FAO-2008) Body wt(kg) Fiber g/d yrs) (FAO 2007) g/day (%E) Numeric Amount) Femal Male Female Male Female Male Female Male Male Female e No AI No AI has <1 7.47 6.91 10.2 9.4 40-60 40-60 ND ND has been been set set 1 11.43 10.79 11.6 10.8 35 35 19 19 14 14 2 13.51 13 11.9 11.4 35 35 19 19 14 14 3 15.67 15.06 13.1 12.7 25-35 25-35 19 19 14 14 4 17.69 16.81 17.1 16.2 25-35 25-35 25 25 18 18 5 16.71 16.02 17.1 16.2 25-35 25-35 25 25 18 18 6 18.46 17.81 17.1 16.2 25-35 25-35 25 25 18 18 7 20.37 19.76 25.9 26.2 25-35 25-35 25 25 18 18 8 22.55 22.09 25.9 26.2 25-35 25-35 25 25 18 18 9 25 24.82 25.9 26.2 25-35 25-35 31 26 24 20 10 27.8 28.21 25.9 26.2 25-35 25-35 31 26 24 20 11 30.88 32.36 40.5 41 25-35 25-35 31 26 24 20 12 34.88 36.96 40.5 41 25-35 25-35 31 26 24 20 13 38.63 40.71 40.5 41 25-35 25-35 31 26 24 20 14 43.96 43.22 40.5 41 25-35 25-35 38 26 28 22 15 49.87 44.99 57.9 47.4 25-35 25-35 38 26 28 22 16 55.21 46.66 57.9 47.4 25-35 25-35 38 26 28 22 17 58.64 48.51 57.9 47.4 25-35 25-35 38 26 28 22 18 45-75 40-75 57.9 47.4 20-35 20-35 38 26 28 22 19-50 45-75 40-75 33-66 33-66 20-35 20-35 38 25 30 25 51- 45-75 40-75 33-66 33-66 20-35 20-35 30 21 30 25 65+ Pregnancy +14 28 25-28 Lactation (0-6 Month) +19 29 27-30 Lactation (7-12 Month) +13 29 27-30 Nutrient Reference Values for fiber has been adopted from nutrient recommendations for Australia and New Zealand 2005

Requirements of all the micronutrients were adapted according to the suggestions of FAO/WHO in 2004 and are summarized in tables 4.8, 4.9 and 4.10. In the booklet of INFS, daily requirements of calcium and folic acid for adult male and females were suggested as 450mg and 200µg, in the present study the requirement of these two nutrients has been suggested as 1000mg and 400µg for the wellbeing of the physical fitness.

Table 4.8: RNI of Vitamins for Bangladeshi population Vit-A Thiamine Riboflavin Niacin Vit-B12 Folic acid Vit-C Body wt(kg) (FAO-2004) (FAO-2004) (FAO-2004) (FAO-2004) (FAO-2004) (FAO-2004) (FAO-2004)

retinol, µg/d mg/day mg/day Mg NE/day µg/day µg/day RNI mg/day

Age (yrs) Male Male Male Male Male Male Male Male Female Female Female Female Female Female Female Female

<1 7.47 6.9 375- 375- 0.2-0.3 0.2-0.3 0.3-0.4 0.3-0.4 2a-4 2a-4 0.4-0.7 0.4-0.7 80 80 25- 25-30b 400 400 30b 1 11.4 11 400 400 0.5 0.5 0.5 0.5 6 6 0.9 0.9 150 150 30b 30b 2 13.5 13 400 400 0.5 0.5 0.5 0.5 6 6 0.9 0.9 150 150 30b 30b 3 15.7 15 400 400 0.5 0.5 0.5 0.5 6 6 0.9 0.9 150 150 30b 30b 4 17.7 17 450 450 0.6 0.6 0.6 0.6 8 8 1.2 1.2 200 200 30b 30b 5 16.7 16 450 450 0.6 0.6 0.6 0.6 8 8 1.2 1.2 200 200 30b 30b 6 18.5 18 450 450 0.6 0.6 0.6 0.6 8 8 1.2 1.2 200 200 30b 30b 7 20.4 20 500 500 0.9 0.9 0.9 0.9 12 12 1.8 1.8 300 300 35b 35b 8 22.6 22 500 500 0.9 0.9 0.9 0.9 12 12 1.8 1.8 300 300 35b 35b 9 25 25 500 500 0.9 0.9 0.9 0.9 12 12 1.8 1.8 300 300 35b 35b 10 27.8 28 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 11 30.9 32 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 12 34.9 37 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 13 38.6 41 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 14 44 43 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 15 49.9 45 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 16 55.2 47 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 17 58.6 49 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 18 45-75 40-75 600 600 1.2 1.1 1.3 1 16 16 2.4 2.4 400 400 40 40 19- 45-75 40-75 600 600 1.2 1.1 1.3 1 16 14 2.4 2.4 400 400 40 40 65+ Pregnancy 800 1.4 1.4 18 2.6 600 55 Lactation (0-6mont) 850 1.5 1.6 17 2.8 500 70 Lactation (7-12mont 1.5 1.6 2.8 barbitrary values, Niacin-NE, niacin equivalents.

Table 4.9 : RNI (Recommended nutrient intake) of Calcium, Phosphorus, Iron, Magnesium and RI (recommended intake) of Sodium and Potassium

Iron(FAO-2004) Phosphorus Recommended nutrient intake (mg/day) Na mg/day K mg/day Mg Body wt(kg) Ca (FAO-2004)mg/day (FAO- (NIN 2010) (NIN 2010) (FAO-2004) for a dietary iron bioavailability 2002)mg/day (RI) (RI) mg/day Age(yrs) 15% 12% 10% 5% 15% 12% 10% 5% Male Female Male Female Male Female Male Female Male Female Male Female Male Female < 7.47 6.91 300d-400g 300d-400g 90-275 90-275 6.21 7.71 9.31 18.61 6.21 7.71 9.31 18.61 407 407 628 628 26-54 26-54 1 1 11.43 10.79 500 500 460 460 3.9 4.8 5.8 11.6 3.9 4.8 5.8 11.6 589 589 1100 1100 60 60 2 13.51 13 500 500 460 460 3.9 4.8 5.8 11.6 3.9 4.8 5.8 11.6 589 589 1100 1100 60 60 3 15.67 15.06 500 500 460 460 3.9 4.8 5.8 11.6 3.9 4.8 5.8 11.6 589 589 1100 1100 60 60 4 17.69 16.81 600 600 500 500 4.2 5.3 6.3 12.6 4.2 5.3 6.3 12.6 1005 1005 1550 1550 76 76 5 16.71 16.02 600 600 500 500 4.2 5.3 6.3 12.6 4.2 5.3 6.3 12.6 1005 1005 1550 1550 76 76 6 18.46 17.81 600 600 500 500 4.2 5.3 6.3 12.6 4.2 5.3 6.3 12.6 1005 1005 1550 1550 76 76 7 20.37 19.76 700 700 500 500 5.9 7.4 8.9 17.8 5.9 7.4 8.9 17.8 100 100 8 22.55 22.09 700 700 500 500 5.9 7.4 8.9 17.8 5.9 7.4 8.9 17.8 100 100 9 25 24.82 700 700 500 500 5.9 7.4 8.9 17.8 5.9 7.4 8.9 17.8 100 100 10 27.8 28.21 1300 1300 1250 1250 5.9 7.4 8.9 17.8 5.9 7.4 8.9 17.8 230 220 11yrs 9.3 11.7 14.0 28.0 -

12yrs e 9.3 11.7 14.0 28.0 13yrs Pre 9.3 11.7 14.0 28.0 14yrs menarch 9.3 11.7 14.0 28.0 11 30.88 32.36 1300 1300 1250 1250 9.7 12.2 14.6 29.2 21.8 27.7 32.7 65.4 230 220 12 34.88 36.96 1300 1300 1250 1250 9.7 12.2 14.6 29.2 21.8 27.7 32.7 65.4 230 220 13 38.63 40.71 1300 1300 1250 1250 9.7 12.2 14.6 29.2 21.8 27.7 32.7 65.4 230 220 14 43.96 43.22 1300 1300 1250 1250 9.7 12.2 14.6 29.2 21.8 27.7 32.7 65.4 230 220 15 49.87 44.99 1300 1300 1250 1250 12.5 15.7 18.8 37.6 20.7 25.8 31.0 62.0 230 220 16 55.21 46.66 1300 1300 1250 1250 12.5 15.7 18.8 37.6 20.7 25.8 31.0 62.0 230 220 17 58.64 48.51 1300 1300 1250 1250 12.5 15.7 18.8 37.6 20.7 25.8 31.0 62.0 230 220 18 45-75 40-75 1300 1300 1250 1250 9.1 11.4 13.7 27.4 19.6 24.5 29.4 58.8 230 220 19 - 45-75 40-75 1000 1000 700 700 9.1 11.4 13.7 27.4 19.6 24.5 29.4 58.8 2092 1902 3750 3225 260 220 50 51 - 45-75 40-75 1000 1300 700 700 9.1 11.4 13.7 27.4 19.6 24.5 29.4 58.8 2092 1902 3750 3225 260 220 65 + Post menopausal 7.5 9.4 11.3 22.6 Pregnancy 1200 700 700 220 Lactation (0-6mont) 1000 700 700 10.0 12.5 15.0 30.0 270 Lactation (7-12mont) 1000 270 33

Table 4.10: RNI of iodine and zinc for Bangladeshi population

Zinc mg/day (FAO-2004) Iodine, µg/day High Moderate Low High Moderate Low Body wt (kg) Age (FAO-2004) bioavail bioavailabi bioavaila bioavaila bioavaila bioavaila (yrs) ability lity bility bility bility bility Male Female Male Female Male Female

1.1d- <1 7.47 6.9 90 90 2.8-4.1 6.6-8.4 1.1d-2.5j 2.8-4.1 6.6-8.4 2.5j

1-3 11.4-15.7 11-15 90 90 2.4 4.1 8.3 2.4 4.1 8.3

4-6 17.7-18.5 17-18 90 90 2.9 4.8 9.6 2.9 4.8 9.6

7-9 20.4-25 20-25 120 120 3.3 5.6 11.2 3.3 5.6 11.2

10-12 27.8-34.9 28-37 120 120 5.1 8.6 17.1 4.3 7.2 14.4

13-18 38.6-75 41-75 150 150 5.1 8.6 17.1 4.3 7.2 14.4

19-65+ 45-75 40-75 150 150 4.2 7 14 3 4.9 9.8

Pregnancy (1st trimester) 200 3.4 5.5 11

Pregnancy (2nd trimester) 200 4.2 7.0 14

Pregnancy (3rd trimester) 200 6.0 10 20

Lactation(0-6mont) 200 5.8-5.3 9.5-8.8 19-17.5

Lactation (7-12mont) 200 4.3 7.2 14.4

d Breastfed, j Not applicable to infants exclusively breastfed.

4.3. Diet and nutrient consumption patterns in the Bangladeshi population For the evaluation of current dietary and nutrient consumption patterns the HIES 2010 data were analyzed. The nutrient intake was calculated using the food composition table of INFS (Shaheen et al, 2013). The foregoing describes the energy and nutrient intake patterns.

HIES Data Analysis: In the HIES 2010, 12240 households were selected from the different regions of the country considering both urban and rural areas and including both poor and non- poor families. The data sets of the HIES were analyzed for food consumption and nutrient intake.

It was found that total food grain intake was 464g/person/day where the intakes of rice and wheat were 424g and 40g respectively. The intakes of fish, poultry, meat, pulses, oils and fruits and vegetables (g/person/day) were 50.3, 11.5, 7.3, 14.7, 20.4 and 212g, respectively. The following figure below depicts the proportionate amounts of food from different food groups among the Bangladeshi population.

Table 4.11: Mean food intake (g/p/d) of the Bangladeshi population

Food items Intake (g/p/d) Cereals 464 Pulses 14.7 Fishes 50.3 Poultry 11.5 Meat 7.3 Egg 5.72 Potatoes 70 Leafy vegetables 36 Non-leafy vegetables 131 Fruits 45 Oils 20.4 Milk 32 Spices 40 Salt 15 Sugar/molasses 9

Energy and protein intake of the Bangladeshi population: The per capita mean energy and protein intake of Bangladeshi population was 2190 kcal/day and 57.2g/day respectively. The distribution of energy intake in the urban and rural population was 2094 kcal and 2223 kcal per person per day, respectively and protein intake in urban and rural areas were 58.5g and 56.8g per day, respectively (table 4.12). Intake of carbohydrate, protein, fat and fibre among the rural and urban population has been shown in table 4.12. These values are different compared to the HIES, 2010 because of the use of the updated FCT 2013 in this study.

Table 4.12: Mean per capita energy, protein, carbohydrate, fat and fibre intake of Bangladeshi population (weighted value)

Energy Protein Carbohydrate Fat Fibre kcal/day g/day g/day g/day g/day

Rural 2223±529 56.8±15.4 429±106 26.3±11.9 23.5±11.0

Urban 2094±484 58.5±16.1 368±91 37.5±16.1 26.8±10.0

Total 2190±521 57.2±15.6 413±106 29.3±14.0 24.3±10.8

Table 4.13 shows that 40.3% of the population take more than 75% of total energy from carbohydrate. A high intake of carbohydrate, especially simple and rapidly absorbed carbohydrate increases the risk of coronary heart disease independent of conventional coronary disease risk factors. In a study on rural Bangladeshi population, it was noted that 17% of the studied population was overweight and 26% were obese (Bhowmik et al., 2012, 2013) which may be a reflection of higher carbohydrate intake. Forty percent of the population take less than 10% of total energy from protein sources and 53% of the population take less than 15% of total energy from fat. Low protein and fat intake could be possible factors implicated in the low birth weight prevalence (22%; WHO, 2012), stunting (41%), wasting (16%), under-weight (36%), BDHS, 2011 and thinness (30% of the women have BMI less than 18.5; BDHS, 2007). The data in table 4.13 reflects the presence of both under-nutrition and over-nutrition in Bangladesh attributed to disproportionate consumption of carbohydrate, protein and fat intake according to HIES 2010.

Table 4.13: Distribution ranges of population- nutrient intake goals

Macronutrients Carbohydrate Protein Fat Range of intake <55 55-75 >75 <10 10-15 >15 <15 15-30 >30 (%) % Population 16.3 43.3 40.3 40 50 10 53 44 3

Adult male equivalent (AME) consumption for household members in different age groups according to HIES 2010 data: Adult male consumption unit (kcal) for all the household members in all age groups were calculated using the methodology of Bermudez et al (2012) and are summarizes in table 4.14. Although mean calorie intake is about2190kcal but when it is calculated according to male equivalent consumption 18-29.9yrs males are getting 2594kcal energy and females of the same age group are getting about 2049kcal of energy.

Table 4.14: Adult male equivalent (AME) consumption for household members in different age groups according to HIES 2010 data

Age Male Female range, yrs Energy, kcal/d AME Energy, kcal/d AME <1 571 0.22 571 0.22 1-1.9 804 0.31 726 0.28 2-2.9 960 0.37 882 0.34 3-3.9 1064 0.41 986 0.38 4-4.9 1141 0.44 1064 0.41 5-5.9 1245 0.48 1115 0.43 6-6.9 1349 0.52 1219 0.47 7-7.9 1453 0.56 1323 0.51 8-8.9 1556 0.6 1453 0.56 9-9.9 1686 0.65 1582 0.61 10-10.9 1816 0.7 1712 0.66 11-11.9 1997 0.77 1816 0.7 12-12.9 2179 0.84 1946 0.75 13-13.9 2361 0.91 2023 0.78 14-14.9 2542 0.98 2075 0.8 15-15.9 2698 1.04 2127 0.82 16-16.9 2827 1.09 2127 0.82 17-17.9 2879 1.11 2127 0.82 18-29.9 2594 1 2049 0.79 30-59.9 2516 0.97 1997 0.77 >60 2075 0.8 1790 0.69

Percent energy contribution of carbohydrate, protein and fat to the Bangladeshi diet: When the contribution of energy is calculated from carbohydrate, protein and fat as a percentage of total energy intakes, it has been found that carbohydrate contributed to 78%; protein contributed to 10% of the energy and fat contributed to 12% of the total energy in the diet. Although 57g of protein intake was noted, only few grams come from animal sources. In a balanced diet, the ratio of energy distribution from carbohydrate, protein and fat would need to be: 7:1:2. In South East Asian countries such as Vietnam, and Myanmar as well as Bangladesh, the average citizen consumes 150–200 kg annually, which accounts for two-thirds or more of caloric intake and approximately 60% of daily protein consumption. Even in relatively wealthier countries such as Thailand and Indonesia, rice still accounts for nearly 50% of calories and one-third or more of protein (www.knowledgebank.irri.org).

Figure 4.1: Contribution of energy from carbohydrate, protein and fat of Bangladeshi population

Distribution of carbohydrate intake: When the carbohydrate intake was analyzed, it has been found that 3.7% of the population have taken up to 200g of carbohydrate each day; 31.4% between 201 to 300g, 44% between 301 to 400g; 16.4% between 401 to 500g and 4.5% of the population have taken more than 500g of carbohydrate. About 21% of the population takes more than 400g of carbohydrate per day. Such high nutrient imbalances are associated with insulin resistance and dyslipidaemia, notably seen in South Asians. In adults, a high-carbohydrate meal consumption was reported to cause hyperinsulinaemia and postprandial hyperglycaemia (www.knowledgebank.irri.org).

Figure 4.2: Distribution of carbohydrate intake of Bangladeshi population

Distribution of Protein Intake: Analysis of protein intakes have shown that more than 66% of the population have taken more than 50g of protein whereas only 10% of the population have taken less than40g (figure 4.3). Although mean protein intake is close to the requirements, the quality of protein is poor since 75% of protein comes from plant sources. Although rice protein ranks high in nutritional quality among cereals, the protein content is modest. Intake of pulses can upgrade the proteins from rice sources since limiting amino acids could be mutually improved in these two food grains. Because of the poor pulse intake (14g) it can mutually upgrades only about 25% proteins from rice sources in current Bangladeshi diets.

Figure 4.3: Distribution of protein intake of Bangladeshi population

In terms of total fat intake/day, it was noted that 55.9% of the population had an intake of total fat (visible and non-visible) up to 30g; 39.1% of the population took between 30.1-60g of fat, 3.9% of the population had a fat intake between 60.1-80g of fat and 1.1 % took more than 80g of fat (figure 4.4).

Figure 4.4: Distribution of fat intake of Bangladeshi population

The per capita consumption of oil and fat recommended by the World Health Organization (WHO) and the Food and Agriculture Organization (FAO) is 21 kg a year for maintaining nutritional requirements of the human body. However, the present world average of per capita consumption of oil and fat stands at 16 kg. In neighbouring countries such as India and Pakistan, the consumption of oil and fat is estimated at 11 kg and 16 kg respectively. The consumption of oil and fat in Bangladesh has been showing substantial changes since 1999 till date. The per capita consumption has been increased to10 kg from a previous figure of between 5 to 6 kg per year. This increase has been reportedly encouraging, as it would have positive effects on energy density of currently inadequate diets and have positive impact on national health. Apart from being a compact source of energy, its regular consumption at the required level is essential for normal growth of human body, especially in growth periods.

Diversification in Bangladeshi diets Diversity of Cereal Intake: According to HIES 2010 data, the mean cereal intake was about 465g for Bangladeshi population and it is largely from medium and coarse rice. Other cereals are in very less amounts and are summarized in the following table. Cereal and rice intake is decreased in comparison to the 2005 survey (HIES 2005) which is positive for the well being of health.

Table 4.15 : Cereal intake pattern of Bangladeshi population

Food grains g/person/day Food grains g/person/day Fine Rice 8.9 Flour 1.48 Medium Rice 154 Vermicelli/ Sufi 1.76 Coarse Rice 252 Bread/Bun 1.39

Beaten Rice 1.02 Biscuits 4.34

Pop Rice Cake 1.89 0.17 Puffed Rice 7.5 Other food grains 4.18 Wheat (attar) 25.8

It seems that mean energy intake has been decreased compared to HIES 2005 but current consumption has been calculated using the updated food composition table of INFS (Shaheen, 2013). Food composition could be change with changing of nutrient composition of soils.

Table 4.16: Comparison of energy, cereal and rice intake, HIES 2005 and 2010

Source/year Energy intake (kcal) Cereal (g), % Energy Rice (g), % energy

HIES 2005 2238 452 (70%) 440 (68%)

HIES 2010 2190 442 (69%) 416 (64%)

Mean pulse intake for Bangladeshi population in 2010 survey was 14.68g/person/day and it was mostly from lentil (Mosur) but other different kinds of pulses were also present in the diet which provided some diversity. Pulses are low fat, high fibre, and high protein.

Table 4.17: Diversity of pulse intake in the Bangladeshi population

Item g/person/day Item g/person/day Lentil (Mosur) 6.723 Pea gram (Khesari) 1.23 Chickpea-Vetch 0.484 Maskalai 0.665

(Mug dal) Green gram 3.762 Other pulses 1.753

(Booter dal) Total 14.68 g/person/day

Diversity of Fish Intake: Mean fish intake was 50.3 g/person/day according to the HIES 2010 and the dominant types of fish eaten are rhui /katla, pangash, carp and puti/tilapia but other different types of fish are also found in the menu of Bangladeshi diets which are summarized below.

Table 4.18: Diversity of fish intake of the Bangladeshi population

Name of the Fish g/person/day Name of the Fish g/person/day

Puti/Big puti/Tilapia/Nilotica 9.8 Sea Fish 1.92

Rhui/Katla/Mrigel/Kalibaush 7.50 Other Fishes 1.58

Pangash/Boal/Aire 7.21 Koi 1.14

Silver carp/Grass carp/Miror carp 5.96 Tangra/Eel fish 0.98

Mala/Dhela/Chapila/Batashi 4.27 Dried Fish 0.96

Hilsa 3.43 Magur/Shinghi/Khalisha 0.57

Shrimp 2.46 Baila/Tapashi 0.33

Shoal/Gajar/Taki 1.99 Total Fish intake 50.3

Diversity of Poultry and Meat Intake: Mean poultry and meat intake for Bangladeshi population was about 19 g/person/day in 2010 and mostly contributed by chicken and beef. The distributions of all the types are summarized below.

Table 4.19: Diversity of poultry and meat intake of Bangladeshi population

Item g/person/day Item g/person/day

Chicken 10.77 Other meats 0.40

Duck 0.72 Buffalo 0.063

Beef 6.57 Sheep 0.017

Mutton 0.63 Total 19.14

Diversity of Vegetable Intake: Mean vegetables intake per person per day was 167g whereas leafy vegetables were 36g and non-leafy vegetables were 131g. Intake of vegetables are about half of the recommended allowances which is a risk factor for micro-nutrient deficiency in the country. Distribution of all types of vegetables intake are summarizes in table 4.20.

Table 4.20: Diversity of vegetables intake in the Bangladeshi population

Item g/person/day Item g/person/day Brinjal 21.1 Snake gourd/Ridge gourd 7.85 White gourd/Pumpkin 12.0 Tomato 7.15 Cauliflower/Cabbage 11.5 Radish 5.36 Water gourd 10.9 Balsam apple 4.28 Potal 10.3 Ladies' finger 3.26 Bean/Lobey 9.73 Other vegetables 11.67 Arum/Ol-kachu/Kachur- 8.90 Leafy vegetables (all) 36.1 mukhi Green banana/Green papaya 8.24 Total Vegetables 167

Diversity of Fruit Intake: Fruit intake for Bangladeshi population was about 45g/person/day according to the HIES 2010 and it is less than half of the recommendations which also may be a risk factor for vitamin and mineral deficiency in the population. Among the fruits taken, mango, jackfruit and banana are the dominant types. The distributions of all the fruits are summarized below.

Table 4.21: Diversity of fruit intake among the Bangladeshi population

Item g/person/day Item g/person/day Mango 11.66 Grape 0.72 Jack fruit 10.21 Amra/Kamranga 0.54 Ripe banana 6.38 Litchi 0.33 Guava 2.63 Palm 0.30 Apple 2.50 Black berry 0.28 Melon/Bangi 2.56 Safeda 0.095 Ripe papaya 1.63 Bedana 0.067 Pineapple 1.26 Others 2.95 Orange 0.77 Total Fruit Intake 44.98

Diversity of Oil Intake: Mean oils or visible fat intake was 20.42g/person/day in 2010. Soybean oil was the most commonly consumed oil. Distribution of all the oils and visible fats are summarized below in table 4.22.

Table 4.22: Diversity of oil and visible fat intake of Bangladeshi population

Item g/person/day Item g/person/day

Soybean oil 18.36 Ghee 0.014

Mustard oil 2.06 Others 0.052

Dalda/Vanashpati 0.034 Total 20.52

Diversity of Milk Intake: Mean milk and dairy products‘ intake was only 32g/person/day which are far below the recommendations. Milk taken was mostly in the form of liquid milk. Milk intake is essential to meet the requirement of calcium.

Table 4.23: Diversity of milk and dairy product intake in the Bangladeshi population

Food item ml/person/day Food item ml/person/day Liquid Milk 30.56 Milk drinks 0.069 Powder milk 0.42 Other dairy product 0.050 Curd 0.54

Diversity of Spice Intake: Mean spice intake was 55g/person/day in 2010 for Bangladeshi population and it is mostly contributed by onion, salt and green chilli.

Table 4.24: Diversity of spices intake in the Bangladeshi population

Item g/person/day Item g/person/day Onion 20.52 Ginger 1.47 Green Chilli 7.17 Cummins 0.84 Garlic 2.82 Coriander-seed 0.80 Dried Chilli 2.68 Aromatic-seed 0.34 Turmeric 2.37 Clove/ Black pepper/ Cassia-leaf 0.28 Salt 15.94

4.4. Dietary Diversity Score (DDS) Micronutrient malnutrition remains a problem of public health concern in most developing countries, partly due to monotonous and cereal-based diets that lack diversity. The dietary diversity score (DDS) was used to assess micronutrient adequacy of the diets, based on a simple count of the food groups consumed. DDS is a qualitative measure of food consumption that reflects household access to a variety of foods, and is also a proxy for nutrient adequacy for the diet of individuals. DDS have been found to be positively correlated with adequate micronutrient density of complementary foods for infants and young children (FANTA 2006), and macronutrient and micronutrient adequacy of the diet for non-breast-fed children (Hatloy et al., 1998; Ruel et al., 2004; Steyn et al., 2006; Kennedy et al, 2007), adolescents (Mirmiran et al., 2004) and adults (Ogle et al., 2001; Foote et al., 2004; Arimond et al., 2010). Food and Agriculture Organization (FAO) in 2011 published guidelines for the measurement of DDS at both individual and household levels. FAO suggested a reference period of the previous 24 hours. Using once 24 hour recall period does not provide an indication of an individual‘s habitual diet, but provides an assessment of the diet at the population level and can be useful to monitor progress or target interventions. There are various other valid time frames for recall, such as the previous 3 or 7 days, and in the case of some foods, the previous month. FAO has been suggested the use of a 24 hours recall as it is less subject to recall error, less cumbersome for the respondents and moreover, DDS based on a 24 hour recall period is easier than with longer recall periods; For the DDS of household levels FAO has recommended 16 different food groups of which the intake of foods from each group counts for one score. Households that have consumed <3 food groups have lowest DDS, households who consumed 4 to 5 food groups have medium DDS and households that have consumed >6 food groups have high DDS.

Table 4.25: List of food groups for DDS Calculation

Group Food Group Food

1 Cereals 9 Flesh meat 2 White roots and tubers 10 Egg 3 Vitamin A rich vegetable and tubers 11 Fish and Sea food 4 Dark green leafy vegetables 12 Legumes, nuts and seeds 5 Other vegetables 13 Milk and milk products 6 Vitamin A rich fruits 14 Oils and fats 7 Other fruits 15 Sweets 8 Organ meat 16 Spices, Condiments and beverages In HDDS, foods taken from group 3, 4, 5 considered as one score; foods from group 6, 7 considered as one score; foods from 8, 9also considered as one score

In HIES 2010 data 24hr food intakes were recorded for 14 different days in all the 12240 households. The DDS values were calculated for individual households for all the 14 days and this were summarized and the mean (± SD) valued were derived. The DDS values for Bangladeshi households were 6.6 ±1.4 which is high according to FAO/FANTA Guidelines (2011) See Figure 4.5.

Mean DDS: 6.6±1.4

Fig 4.5: DDS among Bangladeshi households of 14 different days

Frequency distribution of DDS: When the frequency distribution of DDS was summarized it has been found that only 0.2% of the studied households had DDS value less than 3 while 35% had DDS value 3 to 5 and 64.8% had DDS value greater than 6 (Fig 4.6). Therefore, about 35% of the studied household had DDS value less than 6 and are considered at risk of micronutrient deficiency.

Fig 4.6: Distribution of DDS among Bangladeshi households

4.4.1. DDS of Khagrachari, Rangamati and Dhaka city populations In this study 24hr dietary data were collected from 511 households from different areas of Dhaka city and from the districts of Khagrachari and Rangamati. Individual‘s 24hr dietary data were also collected from graduate level students (200) and from slum area (100 adults). HDDS in Dhaka city, Khagrachari and Rangamati have been found as 7.3, 7.7 and 7.9. IDDS for students have been found as 4.6 and for the slum people as 3.7 out of 9 food groups. See Figure 4.6.1.

HDDS, out of 12 food groups IDDS, out of 9 food groups

Fig 4.6.1: HDDS (Dhaka city, Khagrachari and Rangamati) and IDDS (Students and slum peoples)

4.5. Desirable dietary intake for the Bangladeshi population The desirable dietary intake is based on the requirements of energy and nutrients for a healthy life. Using the basis of evaluation of the current patterns of dietary intake (HIES 2010), previous work on desirable intake proposed by Yusuf et al in 1996 and the desirable intake proposed in 2007 by national experts and considering the requirements of energy and nutrients proposed in this study, the desirable dietary intake for the Bangladeshi population has been developed. In this development, energy intake from cereal was proposed to 55% and there is an emphasis on increase in the intake of pulses, fish, vegetables, fruits and milk (table 4.25). Although 130ml of milk intake for the Bangladeshi population is highly ambitious but it could be increased gradually which would help to fulfil the calcium requirement of the population.

Table 4.26 : Desirable intake for Bangladeshi population

Yusuf et al, 1996 National Experts, DDP, 2013 (2430kcal) (2310kcal) 2007 (2350 kcal) Food Desirable % Desirable % Desirable % intake, g Energy intake, g Energy intake, g Energy Total Cereal 372 55 375 55 400 56 Rice 312 46.6 350 51 350 49 Wheat and other 60 8.4 25 4 50 7 cereals Pulses 66 10 60 8.8 50 6.5 Animal foods 126 5 180 7.0 260 10.5 Fish 50 55 2.1 60 3 Poultry and meat 22 35 1.4 40 2 Egg 7 15 0.6 30 2 Milk and milk 47 75 2.9 130 3.5 products Fruits 57 2.5 100 4.2 100 3 Leafy 100 2 Vegetables Non- 132 2.5 200 3.6 200 2 leafy Potato 130 5 60 2.5 100 4 Cooking oil 38 15 40 15.3 30 11 Sugar/Gur/Molasses 28 5 18 3.2 20 3 Spices 10 20 0.4 20 2 Total 959 100 1053 100 1280 100

4.6. Energy and nutrient gap calculation for Bangladeshi population

Energy and nutrient content in foods consumed were calculated using the food composition tables for Bangladeshi foods updated by INFS (Shaheen, 2013). The nutrient content of all the 14 days‘ food consumption was calculated and the mean consumption of energy and nutrients were calculated using database and SPSS software (Statistical Package for Social Science, Chicago, USA). Mean (±SD) of energy, carbohydrate, protein and fat intake for Bangladeshi population have presented in table 4.12. Calcium, iron and thiamine intake for Bangladeshi population according to the HIES 2010 data were 538±241, 29.8±7.0and 2.60±1.02mg/capita/day

The mean energy requirements for Bangladeshi adults were calculated as 2430 kcal as described in the energy requirement section of this chapter. Therefore, according to the HIES 2010 data the current intake is about 240kcal deficient. But compared to the intrahousehold energy distribution (table 4.14) according to adult male equivalent factors it could be stated no energy deficiency for Bangladeshi adults (18yrs and above). Mean vitamin A, riboflavin and calcium intakes are also deficient compared to requirements in the diet of Bangladeshi population on the basis of HIES 2010 data (table 4.27, 4.28). Diets of more than 70% of the population are deficient of vitamin A, calcium and iron, and about 50% of the population have consumed less zinc than the requirements which reflected in the under nutrition situation of the country. Although it seems that vitamin C intake is sufficient, more than 18% of the population is still consuming less than the requirements.

Table 4.27 : Current Intake and RNI of different Vitamins for adult Bangladeshi Population

Vitamins Intake RNI (HIES 2010) Male Female Vitamin-A, retinol Eq 388±291 600 500 (µg/day)

Vitamin-C mg/day 84.8±64.2 45 45

Thiamine (mg/day) 1.0±0.60 1.2 1.1

Riboflavin (mg/day) 0.80±0.35 1.3 1.1

Niacin (mg NEq/day) 17.8±10.2 16 14

Folic acid(µ/day) 197±81 400 400

Calcium (mg/day) 439±227 1000 1000

Table 4.28: Intake and RDA of Zinc and Iron for adult Bangladeshi Population

RDA Minerals Intake (HIES 2010) Bio-availability Male Female High 4.2 3.0 Zinc 10.03±2.62 Moderate 7.0 4.9 (mg/day) Low 14.0 9.8

15% 9.1 19.6

12% 11.4 24.5 Iron 10.96±3.82 (mg/day) 10% 13.7 29.4

5 % 27.4 58.8

4.7. Identification of key foods Key foods for the Bangladeshi diets were identified as discussed in the methodology section. Key foods were identified for the planning of proper menus to fulfil the required energy and other nutrients considering the local habits of the population. Key foods for different nutrients in current Bangladeshi diets have been shown in figures 4.7 – fig 4.22). In the key foods, 30 items were identified where rice, wheat, fish, chicken, vegetables, fruits (mainly jackfruit, mango) and milk were included and listed in table 4.29.

Fig 4.7: Key foods (%) for fibre Fig 4.8: Key foods (%) for protein

Fig 4.9: Key foods (%) for fat Fig 4.10: Key foods (%) for carbohydrate

Fig 4.11: Key foods (%) for calcium Fig 4.12: Key foods (%) for iron

Fig 4.13: Key foods (%) for vit B1 Fig 4.14: Key foods (%) for vit B2

Fig 4.15: Key foods (%) for vitamin C Fig 4.16: Key foods (%) for Vitamin A

Fig 4.17: Key foods (%) for folic acid Fig 4.18: Key foods (%) for zinc

Fig 4.19: Key foods (%) for magnesium Fig 4.20: Key foods (%) for Sodium

Fig 4.21: Key foods (%) for potassium Fig 4.22: Key foods (%) for phosphorus

Table 4.29: List of key foods with nutrient contributions according to HIES 2010

Nutrient Contribution (%) Fre Prot Vit Vit- Vit- Nia Folic Vit- Food name Fat Fibre Iron Zn Mg Ca Na K que CHO ein A B1 B2 cin acid C P ncy

Medium rice 29 17 6 25 15 31 27 12 28 4 10 17 18 13 wheat (Atta) 5 10 10 8 17 13 15 14 3 3 8 8 12 Potato 2 6 9 13 35 14 13 2 4 28 3 10 Coarse rice 46 33 8 30 40 44 48 7 44 10 Liquid milk 4 6 10 13 4 3 5 Chicken 5 4 8 3 4 Rohu 2 13 6 2 4 Green gram (boot) 3 13 6 2 4 Jack fruit 23 4 5 3 4 Brinjal 5 4 3 3 Puti 3 4 3 2 3 Pangash 2 4 4 3 Lentil(musur) 3 11 4 3 Beef 3 3 4 3 Mango 46 9 8 3 Indian Spinach 5 12 2 Chapila 4 2 2 Ripe banana 4 2 2 Bean 4 3 2 Cauliflower 19 4 2 Cabbage 0.34 2.5 2.1 3 Radish 2.3 1 Pumpkin 6 1 Perbol (patal) 6 1 Dried Fish (chapila) 2 2 1 Hilsa 1 Guava 10 1 Tomato 4 1 Bitter gourd 7 1 Shrimp 2 1 Soybean oil 58 1 Mustard oil 6 1

Table 4.29.1: Nutrient values of key foods

(mg)

Name of food

Energy (kcal) Energy(kj) Protein(g) Fat(g) CHO(g) dietary total fibre(g) g Ash, (mg) Calcium Iron (mg) Magnesium (mg) Phosphorus (mg) Potassium (mg) (mg) Sodium zinc(mg) Eq (µg) Ret Thiamine Riboflavin (mg) Niacin Folate(µg) c Vit (mg)

Medium rice 342 1450 6.5 0.4 76 4.2 0.5 9 0.7 43 126 146 2 1.3 0 0.21 0.05 4.6 11 0

3.0 Wheat (Atta) 334 1410 11.3 2.1 62.2 10.7 1.5 52 4.9 151 306 284 16 0 0.49 0.29 6.2 29 0.0 2

0.7 Potato 66 281 1.2 0.2 14.0 2.1 0.9 11 0.5 21 40 286 16 2 0.08 0.09 0.8 18 19.1 9 1.3 Coarse rice 349 1480 7.1 0.2 79.5 0.7 0.5 2 0.7 43 126 146 2 0 0.02 0.6 11 0.0 2 0.4 Liquid milk 63 263 3.1 3.7 4.3 0.0 0.6 103 0.1 22 90 131 51 32 0.06 0.28 0.8 9 2 5 Chicken 106 447 22.3 1.8 0.0 0.0 1.1 15 0.5 32 173 315 37 1.7 25 0.12 0.07 11.4 7

Rohu 95 400 17 3 0 0 1.2 13 1.1 27 141 287 100 0.36 0.05 0.07 4.1 Green gram 0.3 350 1470 20.4 6 44.8 17.4 2.6 203 8.8 179 31 187 69 170 0.02 0.36 0.5 140 51.8 (boot) 5 0.5 74 312 1.2 0.2 13.3 7.2 1.1 13 0.3 42 41 268 1 2 0.11 0.05 [0.9] 24 3.4 Jack fruit 9 0.5 Brinjal 24 100 1.9 0.1 2.0 4.1 0.7 21 0.4 24 47 178 8 4 0.03 0.07 0.9 34 1.3 7 139 582 17.6 7.6 0 0 4.9 967 2.6 620 203 53 3 59.0 0.01 0.03 0.3 Puti 1.8 162 676 15.9 11 0 0 1 14 0.1 29 130 169 46 5 .15 0.06 4.5 Pangash 5 3.8 317 1340 27.7 0.8 43.2 13.2 2.9 23 5.1 72 261 635 37 3 0.77 0.13 6.3 36 Lentil (musur) 9 3.5 103 436 20.7 2.3 0.0 0.0 1.0 4 2.0 15 190 395 52 0 0.06 0.19 10.0 7 0.0 Beef 2 0.6 82 348 0.8 0.4 18.0 1.6 0.8 13 0.2 15 16 181 0 25 0.09 0.10 0.6 71 103.0 Mango 0 Indian 0.3 25 105 2.4 0.3 2.1 2.2 1.2 111 2.2 179 31 187 69 170 0.02 0.36 [0.5] 140 51.8 Spinach 5 106 442 15.4 4.9 0 0 4.4 1060 4.8 37 560 231 57 1.97 6.0 Chapila 95 400 1.3 0.8 19.2 2.6 0.8 11 0.3 23 36 411 10 0.2 2 0.94 0.08 0.9 20 1.0 Ripe banana 4

Continued

(g) dietary dietary

of Name food Energy(kcal) Energy(kj) Protein(g) Fat(g) CHO(g) total Fibre g Ash, Calcium (mg) Iron (mg) Magnesium (mg) Phosphorus (mg) Potassium (mg) (mg) Sodium (µg) Zinc Eq (µg) Ret Thiamine (mg) Riboflavin (mg) (mg) Niacin Folate(µg) c Vit (mg) Bean 54 228 3.9 0.1 8.3 2 0.7 44 1.1 25 34 220 0.5 32 0.05 0.01 60 8.7 Cauliflow 28 119 2.7 0.3 2.7 2.1 0.8 37 0.7 16 42 154 17 0.32 1 0.02 0.02 0.7 30 40.5 er (boiled) Cabbage 24 101 1.5 0.3 2.6 2.5 0.4 30 0.5 27 182 225 115 0.28 0.08 0.9 5 Radish 18 74 0.9 0.1 2.5 1.6 0.6 24 0.4 15 23 142 40 0.38 0.43 Tr 0.5 25 17.3 Pumpkin 18 77 1.4 0.3 1.3 2.4 0.7 52 0.7 10 16 349 8 0.11 369 0.07 0.06 0.8 16 21.1 Perbol [0. 24 102 2.0 0.3 2.2 2.2 0.5 16 1.7 15 18 148 28 0.4 5 0.17 0.03 16 19.4 (patal) 8] Dried Fish 56.6 9.8 570 3.7 104 1798 925 1408 260 (Chapila) 22 16. 926 18 0 0 1.9 86 1.3 26 195 162 52 0.54 0.12 0.14 5.6 Hilsa 3 8 Guava 63 265 1.0 0.5 10.9 5.4 0.7 17 0.7 25 18 261 6 0.31 33 0.21 0.09 1.2 49 228.3 Tomato 23 96 1.9 0.2 2.5 1.7 0.4 16 0.3 7 28 156 7 0.19 0.07 0.01 0.6 9 30.6 Bitter 31 129 2.1 0.3 3.6 2.6 1.1 16 1.8 31 20 182 36 0.35 24 0.05 0.03 0.7 45 90.6 gourd Shrimp 81 341 17 1.4 0 0 2 421 0.6 26 941 503 117 1.36 Tr Soybean 90 oil 0 Mustard 90 oil 0

4.8. Exchange lists of foods based on energy values (kcal) An exchange list is a grouping of foods based on similarities in energy content as well as carbohydrate, protein and fat. It is not possible to refract all the available foods and local habits in the menus but people should have a choice to exchange the foods in the menus with others based on approximately equal energy values. For this purpose, we have grouped all the fishes, vegetables, lentils and fruits according to the calorie contents (table 4.30, 4.31, 4.32, 4.33, and 4.34), therefore, peoples could change their food items without hampering of the total calories.

Table 4.30: Exchange list of fish according to energy content

Name of food Kcal/100g Name of food Kcal/100g 50-70 Kcal/100g 150 -200 Kcal/100g Crabs 59 Bhangon (Fresh) 154 70 -100 Kcal/100g Mullet 155 Bele Fish/Poa 75 Climbing Fish (Koi) 156 Betrongi fish 76 Dragon Fish 161 Black Fish/Baho 76 Sarputi 161 Pumplate (sea fish) 78 Boal 166 Bhetki (Fresh) 79 Salmon 167 Ganges river sprat 84 200-300 Kcal/100g Magur 86 Bream (Sea, Dried) 210 Pomfret (White) 87 Tengra (Dried) 255 Spotted snake head 87 Bhetki (Dried 266 Aire Fish 89 Hilsha Fish 273 Bata fish 89 Bhangon (Dried) 274 Shrimp 89 Prawns whole(Dried) 287 Bream (Sea, Fresh) 92 Pata fish(Dried) 293 Kucha 92 White Fish (Dried) 296 Shark 93 >300 Kcal/100g Sole 94 Parshee Fish (Fresh) 312 Gahira Fish 97 Butter Fish 114 Lota Fish 97 White Fish (Fresh) 120 Rohu 97 Scorpion Fish 124 Mrigal 98 Cat Fish 126 Eel Fish 100 Silver curp 127 100-150 Kcal/100g Tilapia Chapila (Fresh) 103 Parshee Fish (Dried) 140 Folui 103 Bhangon (Powdered) 144 Fesha Fish(Fresh) 104 Tengra (Fresh) 144 Ribbon Fish 104 Bacha Fish 147

Name of food Kcal/100g Name of food Kcal/100g Pama croaker/poa fish 105 Fry (V. Small Fresh) 106 Flat Fish 108 Fesha Fish(Dried) 336 Carp 111 Magur (Dried) 338 Pomfret (Black) 111 Tapse (Dried) 343 Boicha Fish 112 Prawn(dray) 349 Gura Fish 112 Fishmeal 364 Khalisha Fish 112 Ribbon Fish(dried) 383 Mola Fish 112 Hilsha (Salted) 400 Pomfret(Small) 112 Chapila (Dried) 413 Silver Fish 112

Table 4.31: Exchange list of lentils according to energy content

Food Code Name of food Kcal/100g 300-350 Kcal/100g 210 Peas dried/split 315 214 Horse gram 321 215 Moth beans 330 206 Green gram(whole) 334 212 Red gram/Arahar (split) 335 211 Peas fried 340 209 Lentils 343 208 Khesari dal 345 216 Rajmah 346 201 Bean(Field) 347 205 Black gram(split) 347 207 Green gram(split) 348 350-450 Kcal/100g 202 Bengal gram(whole) 360 204 Bengal gram(fried) 369 203 Bengal gram(split) 372 213 Soybean 432

Table 4.32: Exchange list of leafy vegetables according to energy content

Name of food Kcal/100g Name of food Kcal/100g

<20Kcal/100g 50-70Kcal/100g Celery stalks 18 Prawal leaves 55 Ipomoea stems 19 Kheshari leaves 55 20-30Kcal/100g Kongulo aga/taokharong bo 55 Lettuce 21 Chukai leaves 56 Spinach sour 21 Mesta leaves 56 Amaranth(data) leaves 22 Taro/green arum leaves 56 Mollugo 22 Kassava 59 Radish leaves 24 Punornova leaves 61 Purslane 25 Taolingashku 61 Amaranth Leaves(tender) 26 Jute plant tops 62 Cabbage 26 Ghanda batali 62 Bitter gourd 26 Sweet potato leaves 63 Indian spinach 27 Cauliflower leaves 66 Edible fern 29 Turnip leaves 67 Bathua leaves 30 Orai balai 70 Spinach 30 Lawn marsphenny wort 70 30-50Kcal/100g 70-100Kcal/100g Blue commelina/venus bath 31 Soybean leaves 72 Wild coriander 32 Thankuni leaves 73 Safflower leaves 33 Carrot leaves 77 Mustard leaves 34 Taro/black arum leaves 77 Cowpea leaves 36 Yellow saraca 79 Celery leaves 37 Indian ivy-rue 81 Sineiye leaves 37 Drumstick leaves 92 Pumpkin leaves 38 Agathi 93 Roselle 38 Gram leaves 97 Bottle gourd leaves 39 100-150Kcal/100g Potato leaves 40 Curry leaves 108 Helencha leaves 41 Tamarind leaves(green) 115 Amaranth ( red leaf variety) 43 150-200Kcal/100g Coriander leaves 44 Taro/Arum Leaves (dried) 277 Beet leaves 46 >300Kcal/100g Kolmee leaves 46 Tamarind leaves (dry) 305 Susni sak 46 Fenugreek leaves 49 Mint leaves 49

Table 4.33: Exchange list of nonleafy vegetables according to energy content

Name of food Kcal/100g Name of food Kcal/100g <20Kcal/100g 50-70Kcal/100g Fekong 7 Jackfruit(immature) 51 Gourd(ash) 10 Pea eggplant 52 Sigon data 12 Fig(red) 53 Maira bokong 16 Lotus seeds(green) 57 Gourd(snake) 18 Chaltha 59 Yam stem 18 Drumstick/Horseradish 60 Colocasia stem 18 Gourd (bitter) 60 Kovai 18 Gourd(bottle) 66 Amaranth(data) stem 19 70-100Kcal/100g Kolmee 19 Lokooch 73 20-30Kcal/100g Solanum 77 Sea weed(fresh) 20 Kakrol 80 Idurer kaan 20 Plantain 83 Spinach stalks 21 100-150Kcal/100g Cucumber 22 Chilli(green) 103 Tomato (green) 23 Gram (red, unripe) 116 Bean (French) 26 Betagi 120 Cabbage 26 Yam 126 Gourd (bitter) 28 Peas (green) 127 Gourd (ridge) 30 Water lily (white) 142 Gourd (sweet) pumpkin 30 150-200Kcal/100g Red silk/cotton tree 30 Water lily stem (red) 193 200-300Kcal/100g 30-50Kcal/100g Lotus stem (dry) 234 Prawal/potol 31 Gachh oal 32 Berry bamboo 32 Water lily flower 33 Plantain flower 34 Banchalta 35 Papaya (green) 36 Bean 38 Pumpkin flower 39 Cauliflower 41 Onion & garlic stalk 41 Aubergine/Eggplant 42 Plantain stem 42 Karonda (fresh) 42 Lady`s finger/okra 43 Mushroom 43 Bean(red) 44 Mango (green) 44 Sword beans 44 Bean(broad) 48 Bean(immature) 48 Cow pea 50

Table 4.34: Exchange list of fruits according to energy content

Kcal/ Kcal/ Name of food Bengali Name Name of food Bengali Name 100g 100g <20Kcal/100g 70-100 Kcal/100g Orange juice Komolar rosh 6 Breadfruit Madar 71 Blackberry(Indian) Kalo jam 11 Pomegranate juice Bedanar rosh 71 Kheera Kheera 11 Phalsa Folsha 72 Bedana Wild melon Sindera 14 Pomegranate 74 (bichishoho) Watermelon Tarmuz 16 Melon Bangee 17 Apple Apel 76 Melon(musk) Kharmuj 17 Persimmon Gav 76 Amla Amloki 19 Tetul(bilati) Belatee tetul 78 Tomato(ripe) Paka tometo 20 Palm(ripe) Paka tal 87 20-30 Kcal/100g Wood apple Bel 87 Coconut milk Daber pani 23 Custard apple Sharif 90 Bead tree Kusumgulu 28 Mango(ripe) Paka am 90 Palm, Palmyra(green) Kochi tal 29 Grapes Angur 97 Pineapple Anarosh(joldugee) 30 100-150 Kcal/100g 30 -50 Kcal/100g Boroi(bitter plum) Boroy 104 Burmese grape Lotkon 32 Banana Paka kola 109 Lemon(sweet) Mishti lebu 35 Mahua(ripe) Mohua phul 111 Fig(ripe) Dumur(paka) 37 Gab Gab 113 Pommelo(red) Zambura(lal) 38 Dates Khezur (taza) 144 Rose apple Jamrul 39 200 -300 Kcal/100g Papaya (ripe) Paka pepe 42 Tamarind (pulp) Tetul(paka) 283 Pineapple (wild Anarosh (deshee) 42 variety) Lime (sweet) Mushambee 43 >300 Kcal/100g Orange/mandarin Komola 43 Raisins Kishmish 308 Straw berry Straw berry 44 Dates(dry) Khezur (shukna) 324 Lime Lebu 47 Jackfruit (ripe) Paka Kathal 48 Kodobele (ripe) Kodobele (paka) 49 Roshko 49 Bilimbi Kamranga 50 Peaches Peach phal 50 50-70 Kcal/100g Guava Peyara 51 Black berry (deshi) Kalo jam 52 Plum Alubokhara 52

Kusum fruit Kusumphul 53 Orange Malta 54 Lemon Kagogee lebu 59 Lichis Lichi 61 Lichi (bastard) Ash phal 61 Tamarind (immature) Tetul (kacha) 62 Cherries (red) Cherry phal 64 Ambada (hog plum) Amra 66 Kodobele (immature) Kodobele (kacha) 66 Pears Nashpatee 69 Bullocks heart Nona ata/ Atafol 70

4.9. Optimizing Nutrition Returns Money should be spent logically. The money spent on good-quality of food is like money in the bank that is kept for good health. It will decrease the number of hospital visits, lower the medical cost and also improve the physical and mental strength. Good nutrition is often equated with food consumption, but they are not one and the same. Good nutrition also depends on adequate health care and childcare practices. Even if a person consumes enough food, he or she may be undernourished due to a lack of essential vitamins and minerals provided by a diverse diet or to an illness (such as diarrhoea or parasites) that limits the absorption of nutrients. Eating a diverse diet is fundamental to good health. In Bangladesh as much as 70 percent of an individual‘s daily energy comes from a single staple food (such as rice and a little wheat), making it difficult to consume enough vitamins and minerals. Improving the nutrition of women of childbearing age and young children is critical. Poor nutrition during the 1000 day period from conception through the first two years of life adversely affects the development of the child‘s brain and body, severely compromising growth, learning, and future health and productivity. The linkages and leakages in the agriculture-income-nutrition pathway, including household income, agricultural production, agricultural sales, food expenditures, food consumption, feeding practices, intra-household food distribution, child feeding practices, children and women‘s morbidity, and children and women‘s nutritional status are most critical to improving health outcomes. The nutrient returns per 100 taka spent (price of foods as in 2010) has been calculated and tabulated in the appendix section (A9).

4.10. Dietary Guidelines for Bangladesh Dietary guidelines for Bangladeshi population have been developed based on an analysis of dietary and nutrient adequacy of HIES 2010 survey considering qualitative and quantitative messages after extensive reviewing of national and regional dietary guidelines and including the suggestions of stakeholders . These guidelines emphasize the adequacy intake of foods from all food groups for maintenance of optimal health and have been published in a separate document known as ―Dietary Guidelines for Bangladesh‖.

4.11. Menu Planning

Menu has been developed considering energy and nutrient requirements, gender, physiological status and physical activity levels. Factors of macro and micronutrients, seasonal availability, healthy food and nutrient distribution during the day and dietary diversity have also been considered in the menu planning. Energy and nutrient content from edible raw foods have been calculated in the menus. The updated food composition tables (INFS 2013) have been used for computing the nutritive values. Twenty four diet plans have been formulated considering females with an average of 55 kg body weight and males with an average of 60kg body weight engaged in sedentary, moderate and heavy physical activity in poor and non poor categories in urban and rural areas and have been summarized in appendix A 14.

4.12 Conclusions

Dietary habits of Bangladeshi population are changing with decreasing rice dependency and increasing vegetables, fruits and animal products. These are promising although vegetable and fruit intakes are still half of the requirements. Average consumption of energy in Bangladeshi population seems 280kcal less than the requirements of average adults but when the consumption is calculated on the basis of adult male equivalents then it has been found that Bangladeshi adult males are consuming sufficient energy although females are depriving little bit. Although mean dietary diversity score of the diet of Bangladeshi population are satisfactory (more than 6) but still micronutrient intake deficiency specially vitamin A, calcium, iron, zinc, folic acid are still prominent. This study proposes a desirable diet with emphasis on fruits vegetables, pulses, milk and other animal products consumption to fulfil the requirements.

4.13 Recommendations 1. Given the pressing need for updated energy and nutrient requirements, the study is timely and fulfills an important policy requirement in the area of human nutrition, food planning and dietary guidance. 2. It has followed up from the work of previous preliminary desk review, calculations and consultations carried out by stakeholders from academic, research and government institutions. 3. The study provides an update on energy requirements for all ages, based on measurements and estimates of total daily energy expenditure and on energy needs for growth, pregnancy and lactation based on the FAO/WHO recommendations. 4. It has also adapted the latest macro and micronutrient requirements established by FAO/WHO and regional institutions for use in Bangladesh. The study is based on international methodologies and evidence drawn from global and regional recommendations. 5. The diet plans and menu options have been formulated based on an assessment of household and individual food consumption using the HIES 2010. Accordingly, it provides a basis for realistic food and nutrition planning given that it reflects the dietary adequacy and nutrient gaps in Bangladeshi diets. 6. The diets proposed can be adapted for use by both poor and non poor households in urban and rural areas. A variety of foods and food groups has been used in planning the diets so as to achieve a desirable dietary pattern with adequate dietary diversity scores. 7. The study findings can be considered for agriculture, food and diet planning wherein updates on energy and nutrient requirements are needed. Accordingly, the study findings can be used for normative guidance under the national nutrition programmes and interventions as well as for hospital diets. 8. The dietary guidelines have been developed using science based evidence from the study and are recommended in health and nutrition improvement for the general population. 9. The key nutrition messages can be considered for use in policy, programmes and field interventions across food, agriculture and health sectors. 64

Bibliography Ahmad K, Huda MN, Nath PC (1977). Nutrition survey of rural Bangladesh 1975-76. Dhaka: Institute of Nutrition and Food Sciences, University of Dhaka. pp 237.

Ahmed F, Zareen M, Khan MR, Banu CP, Huq N and Jackson AA (1998).Dietary pattern, nutrient intake and growth of adolescent school girls in Urban Bangladesh. Public Health Nutrition. 1 (2): 83-92.

Ahmed F and Khandaker MAI (1997).Dietary pattern and nutritional status of Bangladeshi manual workers (Rickshaw pullers). International Journal of Food Sciences and Nutrition.48: 285-291.

Ali SMK, Malek MA, Jahan K, Salamatullah Q (1992). Deshio khaddodrobber pushtiman, Institute of Nutrition and Food Science, University of Dhaka, Dhaka

Allen LH (2008). To what extent can food-based approaches improve micronutrient status? Asia Pac J Clin Nutr, 17: 103-105.

Arciero PJ, Goran MI, Gardner AM, Ades PA, Tyzbir RS and Poehlman ET (1993). A practical equation to predict resting metabolic rate in older females. J Am Geriatric Soc, 41: 389–395.

Arimond M, Wiesmann D, Becquey E, Carriquiry A, Daniels M, Deitchler M, Fanou-Fogny N, Joseph M, Kennedy G, Martin-Prevel y & Torheim LE (2010). Simple food group diversity indicators predict micronutrient adequacy of women‘s diets in 5 diverse, resource-poor settings. Journal of Nutrition

Bandini LG, Schoeller DA, Fukagawa NK, Wykes LJ and Dietz WH (1991).Body composition and energy expenditure in adolescents with cerebral palsy or myelodysplasia. Pediatr Res, 29: 70–77.

Barker DJP (1998).Mothers, Babies and Health in Later Life. Churchill Livingstone, Edinburgh, U.K.

Bangladesh Bureau of Statistics (2007).Report of the household income and expenditure survey 2005. Dhaka:

BBS (2011).Report of the household income & expenditure survey 2010.

Bermudez OI, Lividini K, Smitz MF, Fiedler JL (2012). Estimating micronutrient intakes from household consumptions and expenditures survey (HCES): An example from Bangladesh. Food Nutr Bull 33 (3): S208- S213.

BDHS (2007). Bangladesh Demographic and Health survey, NIPORT, Dhaka, Bangladesh

BDHS (2011). Bangladesh Demographic and Health survey, NIPORT, Dhaka, Bangladesh

Bhowmik B, Binte Munir S, Ara Hossain I, Siddiquee T, Diep LM, Mahmood S, Mahtab H,

Khan AK, Hussain A (2012). Prevalence of type 2 diabetes and impaired glucose regulation with associated cardio metabolic risk factors and depression in an urbanizing rural community in Bangladesh: a population-based cross-sectional study. Diab Metab J, 36: 422-32.

Bhowmik B, Afsana F, Diep LM, Munir SB, Wright E, Mahmood S, Khan AKA, Hussain (2013). Increasing Prevalence of Type 2 Diabetes in a Rural Bangladeshi Population: A Population Based Study for 10 Years. Diab Metab J, 37: 46-53.

Black RE, Allen LH, Bhutta ZA, Caulfield LE, de Onis M, Ezzati M, et al. Maternal and child undernutrition: global and regional exposures and health consequences. Lancet.2008; 371: 243– 60.

Cole TJ (2002). The Oxford Brookes BMR database – a reanalysis. Report commissioned by FAO for the joint FAO/WHO/UNU Expert Consultation on Energy in Human Nutrition.

Barba CV, Cabrera MIZ (2011). Recommended energy and nutrient intakes for Filipinos 2002, Asia Pac J Clin Nutr, 17 (S2):399-404.

Cruz CM, da Silva AF and dos Anjos LA (1999). A taxa metabolica basal e superestimade pelas equacoes preditivas em universitaras do Rio de Janeiro, Brasil Arch Latinoam Nutr, 49: 232– 237.

De Boer JO, van Es AJH, Voorrips, LE, Blockstra F and Vogt JE (1988). Energy metabolism and requirements in different ethnic groups. Eur J Clin Nutr, 42: 983–997.

Department of Health (1991). Report on health and social subjects 41. Dietary reference values for food, energy and nutrients for the United Kingdom. London. Her Majesty‘s Stationery Office.

Department of Health (1991). Report on health and social subjects 49. Nutrition and Bone Health: with particular reference to calcium and vitamin D. London: the Stationery Office.

Dewey KG, Cohen RJ, Arimond M, Ruel MT (2005). Developing and Validating Simple Indicators of Complementary Food Intake and Nutrient Density for Breastfed Children in Developing Countries. Final Report. The Food and Nutrition Technical Assistance (FANTA) Project, Academy for Educational Development (AED): Washington DC.

Eneroth H, Lars-Åke PerssonLA, Arifeen SA, Ekströ EC (2011). Infant anaemia is associated with infection, low birth weight and iron deficiency in rural Bangladesh. Acta Paediatrica 100: 220-225.

Godfrey KM, Barker D J (2000). Fetal nutrition and adult disease. The American journal of clinical nutrition71 (5 Suppl): 1344S–1352S.

FANTA (2006). Developing and Validating Simple Indicators of Dietary Quality and Energy Intake of Infants and Young Children in Developing Countries: Summary of findings from analysis of 10 data sets.

FANTA-2 (2011).Dietary Diversity as a Measure of the Micronutrient Adequacy of Women‘s Diets in Resource-Poor Areas: Summary of Results from Five Sites. Food and Nutrition Technical Assistance.

FANTA/AED (2006). Working Group on Infant and Young Child Feeding Indicators. Developing and validating simple indicators of dietary quality and energy intake of infants and young children in Developing Countries: Summary of findings from analysis of 10 data sets.

FAO (2004).Human energy requirements. Report of a Joint FAO/WHO/UNU Expert Consultation. FAO Food and Nutrition Technical Report series 1, United Nations University, Rome

FAO (2008). Methodology for the measurement of food deprivation: updating the minimum dietary energy requirements. FAO Statistics Division, Rome, 2008.

FAO (2008). The state of food insecurity in the world: high food prices and food security— threats and opportunities.

FAO (2011).Guidelines for measuring household and individual dietary diversity. Nutrition and Consumer Protection Division, Food and Agriculture Organization of the United Nations

Faruque MO, Khan MR, Rahman, M and Ahmed F (1995).Relationship between smoking and antioxidant nutrient status.Br J Nutr, 73: 625-632.

Foote J, Murphy S, Wilkens L, Basiotis P & Carlson A (2004). Dietary variety increases the probability of nutrient adequacy among adults. Journal of Nutrition 134: 1779-1785.

FPMU (2012).National Food policy Plan of Action and Country Investment Plan, Monitoring Report 2012.FPMU, Ministry of Food and Disaster Management, Government of the Peoples Republic of Bangladesh.

Hales CH & Barker DJP (2001).The thrifty phenotype hypothesis. Brit Med Bull 60: 51–67.

Harding JE (2001). The nutritional basis of the foetal origins of adult disease. Int J Epidemiol 30: 15–23.

Hassan N, Ahmed K. Nutrition survey of rural Bangladesh 1981-82. Dhaka: Institute of Nutrition and Food Sciences, University of Dhaka, 1983. pp 262.

Hatloy A, Torheim L & Oshaug A (1998).Food variety--a good indicator of nutritional adequacy of the diet? A case study from an urban area in Mali, West Africa. European Journal of Clinical Nutrition 52: 891-8.

Hayter J and Henry CJK (1993).Basal metabolic rate in human subjects migrating between tropical and temperate regions – a longitudinal study and review of previous work. Eur J Clin Nutr, 47: 724–734.

Hayter JE and Henry CJK (1994). A re-examination of basal metabolic rate predictive equations: the importance of geographic origin of subjects in sample selection. Eur J Clin Nutr, 48: 702– 707.

Haytowitz DB, Pehrhsson PR, Holden JM, (2002). The Identification of Key foods for food composition Research. J Food Compo Anal, 15: 183-94.

Helen Keller International (1985).Bangladesh nutritional blindness study 1982-83. Dhaka: Helen Keller International, p 23.

Helen Keller International (2000). High anaemia prevalence among Bangladeshi children in urban slums: an ethical and economic rationale for multi-micronutrient supplementation? Nutrition surveillance project bulletin 2000. Dhaka: Helen Keller International, Bangladesh, pp 4.

Helen Keller International (2002). Anaemia is a severe public health problem in pre-school children and pregnant women in rural Bangladesh. Dhaka: Helen Keller International, pp 4.

Helen Keller International (2006). Bangladesh: the burden of anaemia in rural Bangladesh: the need for urgent action. Dhaka: Helen Keller International. 4 p. (Nutritional Surveillance Project bulletin no. 16).

Henry CJK and Rees DG (1991).New predictive equations for the estimation of basal metabolic rate in tropical peoples. Eur J Clin Nutr, 45: 177–185.

Henry CJK (2001). Basal metabolic rate studies in humans: measurement and application. Background document prepared for the joint FAO/WHO/UNU Expert Consultation on Energy in Human Nutrition, 2001.

Hoddinott J & Yohannes Y (2002).Dietary diversity as a food security indicator. FANTA 2002, Washington DC. (Available at http://www.aed.org/Health/upload/dietarydiversity.pdf) http://www.knowledgebank.irri.org/ericeproduction/Importance_of_Rice.htm

Institute of Medicine (1997).Dietary reference intakes for calcium, phosphorus, magnesium, vitamin D and fluoride. Washington DC, National Academy Press

Institute of Medicine (1998).Dietary reference intakes for thiamine, riboflavin, niacin vitamin 6, folate, vitamin B12, Pantothenic acid, biotin and choline. Washington DC, National Academy Press

Institute of Medicine Panel on Micronutrients (2002). Dietary reference intakes: vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium and zinc. Washington DC, National Academy Press.

Institute of Medicine (2004). Dietary reference intakes: Water, potassium, sodium, chloride and sulphate. Washington DC, National Academy Press

Ismail MN, Ng KK, Chee SS, Roslee R and Zawiah H (1998).Predictive equations for the estimations of basal metabolic rate in Malaysian adults. Mal J Nutr, 4: 81–90.

Jahan K, Hossain M (1998). Nature and extent of malnutrition in Bangladesh: Bangladesh national nutrition survey 1995-96. Dhaka: Institute of Nutrition and Food Sciences, University of Dhaka. pp 33

James, WPT. & Schofield, E.C. (1990). Human energy requirements: A manual for planners and nutritionists. Oxford, UK, Oxford Medical Publications under arrangement with FAO

Johnstone AM, Murison SD, Duncan JS, Rance KA, Speakman JR, Koh YO (2005). "Factors influencing variation in basal metabolic rate include fat-free mass, fat mass, age, and circulating thyroxin but not sex, circulating leptin, or triiodothyronine". Am J Clin Nutr 82: 941–948. PMID 2305711.

Kant AK, Schatzkin A, Harris TB, Ziegler RG, Block G (1993). Dietary diversity and subsequent mortality in the First National Health and Nutrition Examination Survey Epidemiologic Follow-up Study.Am J Clin Nutr 57: 434–40.

Kennedy G, Pedro MR, Seghieri C, Nantel G & Brouwer I ( 2007). Dietary diversity score is a useful indicator of micronutrient intake in non breast-feeding Filipino children. Journal of Nutrition 137: 1-6.

Khor GL (2008). Food-based approaches to combat the double burden among the poor: challenges in the Asian context. Asia Pac J Clin Nutr 17 (S1): 111-15.

Klein PD, James WPT, Wong WW et al (1984). Calorimetric validation of the doubly labelled water method for determination of energy requirement in man. Hum Nutr Clin Nutr 35: 95-106.

King JC, Garza C (2007). Harmonization of nutrient intake values. Food and Nutrition Bulletin 28: 3-15.

Lee V, Ahmed F, Wada S, Ahmed T, Ahmed AS, Parvin Banu C, et al (2008). Extent of vitamin A deficiency among rural pregnant women in Bangladesh. Public Health Nutr; 11: 1326–31.

Lifson A, Gordon GB and Macclintock R (1955).Measurement of total carbon dioxide production by means of D218O. J Appl Physiol 7: 704-710.

Lucas A. (1991). Programming by early nutrition in man. In: The Childhood Environment and Adult Disease (Bock GR & Whelan J. eds.), pp.38–55. CIBA Foundation Symposium 156.Wiley, Chichester, U.K.

Mirmiran P, Azadbakht L, Esmaillzadeh, A. & Azizi, F (2004). Dietary diversity scores in adolescents- a good indicator of the nutritional adequacy of diets: Tehran lipid and glucose study. Asia Pacific Journal of Clinical Nutrition 13(1): 56-60.

Mohsin F, Mahbuba S, Begum T, Azad K, Nahar N (2012). Prevalence of impaired glucose tolerance among children and adolescents with obesity. Mymensingh Med J. 16:516-8

Murshid KAS, Khan MNI, Shahabuddin Q, Yunus M, Akhter S, Chowdhury OH (2008). A report on Determination of food availability and consumption patterns and setting up of Nutritional standard in Bangladesh.

NIN (2010). Nutrient requirements and recommended dietary allowances for Indians: A report of the Expert Group of the Indian Council of Medical Research. National Institute of Nutrition, India.

Nishida C and Nocito FM (2007). FAO/WHO Scientific updates on carbohydrate in human nutrition: Introduction. EJCN 61: S1-S4

Nutrient reference values for Australia and New Zealand (2005). Ministry of Health

Piers LS and Shetty PS (1993).Basal metabolic rates of Indian women. Eur. J. Clin. Nutr., 47: 586–591.

Popkin, BM (2001). The e nutrition transition and obesity in the developing world. J Nutr.131: 871S-873S.

Prentice AM, Leavelesley K, Murgatroyd PR, Coward WA, Schorah CJ, Bladon P and Whitehead RG (1989). Is severe wasting in elderly mental patients caused by an excessive energy requirement? Age Aging, 18: 158–167.

Ramirez-Zea M (2002). Validation of three predictive equations for basal metabolic rate. Report commissioned by FAO for the joint FAO/WHO/UNU Expert Consultation on Energy in Human Nutrition, 2002

Ravussin E, Harper IT, Rising R and Bogardus C (1991). Energy expenditure by doubly labelled water: Validation in lean and obese subjects. Am J Physiol, 261: E402–E409.

Ruel MT, Menon P (2002). Child feeding practices are associated with child nutritional status in Latin America: innovative uses of the demographic and health surveys. J Nutr 132: 1180–1187

Ruel M, Graham J, Murphy S & Allen L (2004). Validating simple indicators of dietary diversity and animal source food intake that accurately reflect nutrient adequacy in developing countries. Report submitted to GL-CRSP.

Salam AKMA, Haseen F, Yusuf HKM, Torlesse H. Anaemia survey of urban Bangladesh and the rural Chittagong Hill Tracts, 2003 (abstract).In: Khan MSI, Rahim MA, Ahmed T, editors. Abstracts book of the 8th Commonwealth Congress on Diarrhoea and Malnutrition,

Schofield WN (1985). Predicting basal metabolic rate, new standards and review of previous work.Hum Nutr Clin Nutr, 39C: 5–41.

Schulz LO, Alger S, Harper I, Wilmore JH and Ravussin E (1992). Energy expenditure of elite female runners measured by respiratory chamber and doubly labelled water. J Appl Physiol, 72: 23–28.

Soares MJ, Francis DG and Shetty PS (1993).Predictive equations for basal metabolic rates of Indian males. Eur J Clin Nutr, 47: 389–394.

Soares MJ and Shetty PS (1988).Validity of Schofield‘s predictive equations for basal metabolic rates of Indians. Indian J Med Res, 88: 253–260.

Speakman JR, Król, E, Johnson MS. (2004). "The Functional Signiﬁcance of Individual Variation in Basal Metabolic Rate‖. Physiological and Biochemical Zoology 77: 900–915.

Steyn NP, Nel, JH, Nantel G, Kennedy G& Labadarios D (2006). Food variety and dietary diversity scores in children: are they good indicators of dietary adequacy? Public Health Nutrition 9(5): 644-650.

Swindale A& Bilinsky, P (2006). Household dietary diversity score (HDDS) for measurement of household food access: indicator guide, Version 2. Food and Nutrition Technical Assistance Project, Academy for Educational Development, Washington D.C.

Sukhatme PV and Margen S (1982).Am J Clin Nutr, 35: 355–365.

Thorne-Leyman et al (2010). Household Dietary Diversity and Food Expenditures are closely linked in rural Bangladesh, increasing the risk of malnutrition due to the financial crisis. J Nutr 140: 182S-188S.

Tontisirin K, Nantel G, Bhattacharjee L (2002). Food-based strategies to meet the challenges of micronutrient malnutrition in the developing world. Proc Nutr Soc. 61: 243-50.

Turin TC, Rumana N, Shahana N (2007). Dietary pattern and food intake habit of the underprivileged children residing in the urban slums. Iran J Ped 17: 227-34.

UNICEF (2009). Infant and young child feeding program review case study: Bangladesh. Nutrition Section, UNICEF, New York.

Valencia ME, Moya SY, McNeill G and Haggarty P (1994).Basal metabolic rate and body fatness of adult men in northern Mexico. Eur J Clin Nutr, 48: 205–211.

WFP (2008). Measures of food consumption – Harmonizing methodologies, Rome, 9-10 April, 2008

WHO (1985). Energy and protein requirements: Report of a joint FAO/WHO/UNU expert consultation. WHO Technical Report Series No. 724. Geneva

WHO (2003).Diet, nutrition and the prevention of the chronic diseases. Geneva, World Health Organization

WHO/FAO (2004). Human vitamin and mineral requirements: Report of a joint FAO/WHO Expert consultation, Bangkok, Thailand, FAO.

WHO (2007).Protein and amino acid requirements in human nutrition. Report of a Joint WHO/FAO/UNU Expert Consultation, United Nations University, WHO Technical Report Series 935. World Health Organization.

WHO (2011). Non-Communicable Disease risk factor survey Bangladesh 2010.

WHO, Global Strategy on Diet, Physical Activity and Health, 2012.

WHO (2012).World Health Statistics 2012.World Health Organization.

Yajnik CS (2004). Early life origins of insulin resistance and type 2 diabetes in India and other Asian countries. J Nutr 134: 205-210.

Yusuf HK, Quazi S, Kahn MR, Mohiduzzaman M, Nahar B, Rahman MM et al (1996). Iodine deficiency disorders in Bangladesh. Indian J Pediatr, 63: 105-10.

Yusuf HK, Khatun F, Rahman AKMM (2007). National survey on iodine deficiency disorders and universal salt iodization survey of Bangladesh 2004-5. Dhaka: Institute of Public Health Nutrition. pp 158.

A1: Physical Activity Level (PAL) calculations in different occupations in Bangladeshi population

PAL calculation in different occupations

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL Pcare hr PAL Tcare PAL ECSHr PAL PALEcs HHWhr PAL HHWPAL chathrTV PAL TV_CHAT PAL TT TPAL APAL

Actor 10 1.45 14.5 7 1 7 1 2.3 2.3 2 1.7 3.4 1 1.95 1.95 3 1.4 4.2 24 33.4 1.38 Athletes 6 6.6 39.6 7 1 7 2 2.3 4.6 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 66.1 2.75 Army officer 8 3.37 26.96 6 1 6 2 2.3 4.6 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 50.8 2.11 Brick breaking 8 4 32 8 1 8 1 2.3 2.3 5 1.7 8.5 1 1.95 1.95 1 1.4 1.4 24 54.2 2.25 (Urban) Brick breaking 7 4 28 8 1 8 1 2.3 2.3 5 1.7 8.5 2 1.95 3.9 1 1.4 1.4 24 52.1 2.17 (rural) Banker (Urban) 8 1.3 10.4 7 1 7 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 32.9 1.37 Banker (rural) 8 1.3 10.4 8 1 8 1 2.3 2.3 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 32.2 1.34 Bakery worker 8 2.5 20 6 1 6 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 43.2 1.80 Barber (Urban) 7 1.6 11.2 8 1 8 2 2.3 4.6 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 35.3 1.47 Barber (rural) 8 1.6 12.8 8 1 8 2 2.3 4.6 2 1.7 3.4 2 1.95 3.9 2 1.4 2.8 24 35.5 1.47 Brick field 8 3 24 8 1 8 1 2.3 2.3 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 45.8 1.90 worker Boy, Hotel 8 2.9 23 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 46 1.91

Beating cotton 8 2.4 19 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 42 1.75

Breaking nuts 8 1.9 15 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 38 1.58 Binding sheaves 8 4.2 34 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 56 2.33 WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

Continued.

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL Pcare hr PAL TcarePAL ECSHr PAL PALEcs HHWhr PAL HHWPAL chathrTV PAL TV_CHAT PAL TT TPAL APAL Car mechanic 8 3.6 28.8 7 1 7 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 2 1.4 2.8 24 51.6 2.15 Chemical 8 3.5 28 8 1 8 1 2.3 2.3 4 1.7 6.8 1 1.95 1.95 2 1.4 2.8 24 49.9 2.07 Industry Child care 8 2.2 17.6 6 1 6 2 2.3 4.6 4 1.7 6.8 2 1.95 3.9 2 1.4 2.8 24 41.7 1.73 Cleaning house 8 2.2 18 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 40 1.66 Cowboy 8 2.7 21.6 7 1 7 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 44.1 1.83 Carpenter 8 3.5 28 8 1 8 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 1 1.4 1.4 24 50.4 2.10 (Urban) Carpenter 7 3.5 24.5 8 1 8 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 2 1.4 2.8 24 48.3 2.01 (rural) Cutting trees 8 4.8 38.4 7 1 7 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 60.9 2.53

Cutting grass 5 4.7 23.5 8 1 8 1 2.3 2.3 5 1.7 8.5 2 1.95 3.9 3 1.4 4.2 24 50.4 2.10 Cutting grass 8 4.7 38 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 60 2.5 with machete Cutting fruit 8 3.4 27 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 50 2.08 from tree Chopping wood 8 4.3 34 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 57 22.37 with machete Clearing ground 8 3.8 30 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 53 2.2 Cooking 8 1.8 14 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 37 1.54 Collecting leaves 8 1.9 15 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 38 1.58 Catching fish by 8 3.9 31 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 54 2.25 hand WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

Continued

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL hrPcare PAL TcarePAL ECSHr PAL PAL Ecs HHWhr PAL HHWPAL TV chathr PAL TV_CHA T PAL TT TP APAL Catching crabs 8 4.5 36 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 59 2.5 in coastal area Collecting and spreading 8 5.2 42 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 64 2.66 manure Cutting 8 6.5 52 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 75 33.12 sugarcane Clearing ground (depending types 8 5.4 43 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 66 32.75 of land) Day labouring 8 5.2 41.6 8 1 8 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 63.7 2.65 (Urban) Day labouring 7 5.2 36.4 9 1 9 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 59.5 2.47 (rural) Driver (Urban) 6 2.1 12.6 8 1 8 1 2.3 2.3 5 1.7 8.5 1 1.95 1.95 3 1.4 4.2 24 37.6 1.56

Driver (rural) 7 2.1 14.7 8 1 8 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 2 1.4 2.8 24 38.5 1.60 Driving(Tractor) 8 2.1 17 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 40 1.6 Digging irrigation 8 5.5 44 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 67 2.79 channels Digging holes for 8 5 40 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 63 2.6 posts Digging ground 8 4.6 37 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 60 2.5 Digging holes for 8 4.3 34 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 57 2.3 planting WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

Continued

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL hrPcare PAL TcarePA L ECSHr PAL PAL Ecs HHWhr PAL HHWPA L TV chathr PAL TV_CHA T PAL TT TPAL APAL

Doctor (Urban) 8 1.45 11.6 7 1 7 2 2.3 4.6 3 1.7 5.1 1 1.95 1.95 3 1.4 4.2 24 34.5 1.43 Doctor (rural) 6 1.45 8.7 8 1 8 2 2.3 4.6 3 1.7 5.1 1 1.95 1.95 4 1.4 5.6 24 34 1.41

Deseeding cotton 8 1.8 14 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 37 1.54

Earth cutting 6 6.2 37.2 8 1 8 1 2.3 2.3 5 1.7 8.5 2 1.95 3.9 2 1.4 2.8 24 62.7 2.61 Electrical work 8 3 24 8 1 8 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 46.1 1.92 (Urban) Electrical work 7 3 21 8 1 8 2 2.3 4.6 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 45.4 1.89 (rural) Engineer 8 1.45 11.6 7 1 7 2 2.3 4.6 4 1.7 6.8 1 1.95 1.95 2 1.4 2.8 24 34.8 1.44 Full time made 7 2 14 7 1 7 2 2.3 4.6 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 38.8 1.61 Electrical 8 2 16 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 39 1.6 industry Fisher man 8 2.73 21.84 7 1 7 2 2.3 4.6 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 44.9 1.87 Farmer(Male) 8 5 40 10 1 10 1 2.3 2.3 2 1.7 3.4 1 1.95 1.95 2 1.4 2.8 24 60.5 2.51 Forking dry 8 6.8 54 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 77 3.2 leaves Feeding animals 8 3.6 29 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 52 2.1 Fetching water 8 4.1 33 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 56 2.3 from well Furnishing 8 3.3 26 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 49 2.04 industry Garment worker 8 2.5 20 6 1 6 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 43.2 1.8 WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

Continued

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL hrPcare PAL TcarePAL ECSHr PAL PAL Ecs HHWhr PAL HHWPAL TV chathr PAL TV_CHA T PAL TT TPAL APAL

Gardener 7 4.15 29.05 8 1 8 2 2.3 4.6 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 53.2 2.21 Grinding grain 8 3.8 30 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 53 2.2 on millstone Harvesting root 8 3.1 25 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 48 2 crops Hoeing 8 4.4 35 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 58 2.4

Handloom 8 1.5 12 8 1 8 1 2.3 2.3 3 1.7 5.1 1 1.95 1.95 3 1.4 4.2 24 33.6 1.39 Ironing clothes 8 3.5 28 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 51 2.12

Journalist 10 2.4 24 6 1 6 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 44.1 1.83 Kneeling sorting 8 1.6 13 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 36 1.5 potatoes Laundry work 8 3.4 27.2 6 1 6 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 50.4 2.10 Lab worker 10 2 20 7 1 7 1 2.3 2.3 3 1.7 5.1 1 1.95 1.95 2 1.4 2.8 24 39.2 1.63 Loading Sacks 8 4.7 38 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 60 2.5 Loading manure 8 6.4 51 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 74 3.08 Loading earth 8 2.6 21 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 44 1.83 oven with food Lifting grain sacks for 8 3.7 30 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 52 2.1 weighing Loading sacks on 8 7.4 59 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 82 3.4 lorry Light cleaning 8 2.7 22 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 44 1.83

WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

PAL

Occupation

Whr PAL W_ Sleeping hr PAL S_PAL hrPcare PAL TcarePAL ECSHr PAL PAL Ecs HHWhr PAL HHWPAL TV chathr PAL TV_CHA T PAL TT TPAL APAL Milking cows by 8 2.9 23 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 46 1.91 hand Moderate cleaning (Polishing, 8 3.7 30 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 52 2.16 Window cleaning etc.) Machine tool 8 2.7 22 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 44 1.83 industry Making fence 8 3.6 29 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 52 2.16 Making tortillas 8 2.1 17 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 40 1.66 in restaurant Nurse (Urban) 8 1.6 12.8 7 1 7 2 2.3 4.6 3 1.7 5.1 1 1.95 1.95 3 1.4 4.2 24 35.7 1.48

Nurse (rural) 6 1.6 9.6 8 1 8 2 2.3 4.6 4 1.7 6.8 2 1.95 3.9 2 1.4 2.8 24 35.7 1.48 Office worker 8 1.3 10.4 8 1 8 1 2.3 2.3 2 1.7 3.4 1 1.95 1.95 4 1.4 5.6 24 31.7 1.31 (M) Pulling carts 6 5.6 33.6 7 1 7 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 4 1.4 5.6 24 59.2 2.46 Picking tea 8 3.4 27.2 7 1 7 1 2.3 2.3 4 1.7 6.8 2 1.95 3.9 2 1.4 2.8 24 34.8 2.08 Player, Football 6 6.6 39.6 7 1 7 2 2.3 4.6 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 66.1 2.75 (Urban) Player, Football 5 6.6 33 8 1 8 2 2.3 4.6 4 1.7 6.8 1 1.95 3.9 4 1.4 5.6 24 61.9 2.57 (rural) Player, cricket 6 3.3 19.8 8 1 8 2 2.3 4.6 4 1.7 6.8 1 1.95 3.9 3 1.4 4.2 24 47.3 1.97 (Urban) WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

Continued

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL hrPcare PAL TcarePAL ECSHr PAL PAL Ecs HHWhr PAL HHWPAL TV chathr PAL TV_CHAT PAL TT TPAL APAL Player, cricket 6 3.3 19.8 7 1 7 2 2.3 4.6 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 46.3 1.92 (rural) Pilot 6 1.6 9.6 6 1 6 2 2.3 4.6 5 1.7 8.5 2 1.95 3.9 3 1.4 4.2 24 36.8 1.53

Part time maid 8 2.5 20 7 1 7 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 42.5 1.77

Painting, wall 8 2.9 23 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 46 1.91 Planting root 8 3.9 31 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 54 2.25 crops Printing press 8 2 16 7 1 7 2 2.3 4.6 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 39.1 1.62 Preparing 8 1.5 12 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 35 1.45 tobacco Pounding (rice) 8 4.6 37 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 60 2.5 Peeling sweet 8 1.4 11 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 34 1.41 potato Rickshaw 5 7.9 39.5 8 1 8 1 2.3 2.3 5 1.7 8.5 1 1.95 1.95 4 1.4 5.6 24 65.9 2.74 (Urban) Rickshaw 6 7.9 47.4 7 1 8 1 2.3 2.3 5 1.7 8.5 1 1.95 1.95 4 1.4 5.6 24 73.8 3.07 (rural) Repairing fences 8 5 40 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 63 2.62 Rice / wheat 8 2.1 17 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 40 1.66 harvest-cutting Removing beans 8 1.5 12 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 35 1.45 from pod Roasting corn 8 1.3 10 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 33 1.37 WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

Continued

Occupation L

Whr PAL W_PAL Sleeping hr PAL S_PAL hrPcare PAL TcarePAL ECSHr PAL PAL Ecs HHWhr PAL HHWPAL TV chathr PAL TV_CHA T PAL TT TPA APAL

Student (Urban) 8 1.45 11.6 8 1 2 2.3 4.6 3 1.7 5.1 1 1.95 1.95 2 1.4 2.8 24 33.1 1.37

Student (rural) 7 1.45 10.15 7 1 7 2 2.3 4.6 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 35 1.45

Sowing 8 4 32 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 55 2.29

Sewing cloth 9 1.4 12.6 7 1 7 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 33.7 1.40 Sweeping house 8 3 24 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 47 1.95 Sweeping yard 8 3.5 28 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 51 2.1 Shopkeeper 8 1.3 10.4 8 1 8 2 2.3 4.6 2 1.7 3.4 1 1.95 1.95 3 1.4 4.2 24 32.6 1.35 (Urban) Shopkeeper 7 1.3 9.1 8 1 8 2 2.3 4.6 3 1.7 5.1 1 1.95 1.95 3 1.4 4.2 24 33 1.37 (rural) Sweeper 7 3.25 22.75 7 1 7 2 2.3 4.6 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 47.6 1.98

Sheaf/ cook 8 1.8 14.4 8 1 8 2 2.3 4.6 2 1.7 3.4 1 1.95 1.95 3 1.4 4.2 24 36.6 1.52 Shoemaker 8 2.6 20.8 8 1 8 1 2.3 2.3 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 42.6 1.77 (Urban) Shoe maker 7 3.6 25.2 8 1 8 1 2.3 2.3 2 1.7 3.4 3 1.95 5.85 3 1.4 4.2 24 49 2.03 (rural) Spinning cotton 8 1.4 11 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 34 1.4 Stirring porridge 8 3.7 30 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 52 2.16 Squeezing 8 2.4 19 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 42 1.7 coconut Splitting wood 8 4.2 34 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 56 2.33 for posts Sharpening posts 8 4 32 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 55 2.29

Continued

Occupation

Whr PAL W_PAL Sleeping hr PAL S_PAL hrPcare PAL TcarePAL ECSHr PAL PAL Ecs HHWhr PAL HHWPAL TV chathr PAL TV_CHAT PAL TT TPAL PAL/hr Tailoring 10 2.5 25 6 1 6 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 45.1 1.87 (Urban) Tailoring (rural) 8 2.5 20 7 1 7 2 2.3 4.6 3 1.7 5.1 2 1.95 3.9 2 1.4 2.8 24 43.4 1.80 Teacher (Urban) 7 1.45 10.15 6 1 6 2 2.3 4.6 4 1.7 6.8 2 1.95 3.9 3 1.4 4.2 24 36.7 1.52 Teacher (rural) 6 1.45 8.7 7 1 7 2 2.3 4.6 4 1.7 6.8 3 1.95 5.85 2 1.4 2.8 24 28.8 1.19 Traffic police 8 1.6 12.8 7 1 7 1 2.3 2.3 3 1.7 5.1 2 1.95 3.9 3 1.4 4.2 24 35.3 1.47

Threshing corn 8 5 40 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 63 2.6 Tying fences 8 2.7 22 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 44 1.8 posts Uprooting sweet 8 3.5 28 8 1 8 2 2.3 4.6 4 1.7 6.8 1 2.8 3 2 1 2.8 25 53 2.2 potatoes Village house 9 2.7 24.3 6 1 6 2 2.3 4.6 2 1.7 3.4 2 1.95 3.9 3 1.4 4.2 24 46.4 1.93 wife Winnowing corn 8 3.9 31 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 54 2.25 or rice Washing clothes 8 3 24 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 47 1.95

Washing dishes 8 1.7 14 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 36 1.5 Weeding 8 2.9 23 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 46 1.95 Weeding in 8 3.8 30 8 1 8 1 2.3 2.3 4 1.7 6.8 1 2.8 3 2 1 2.8 24 53 2.2 nursery WPAL=Working PAL; SPAL=Sleeping PAL; Pcare PAL= Personal care PAL; Tcare PAL=Total Care PAL; ECS PAL= Eating, Cooking, Sitting PAL HHWPAL=House hold, Walking PAL; TV chathr PAL=TV, Chatting PAL; TT=Total time; TPAL=Total PAL.

A2: List of occupations in different PAL group Sedentary Moderate Heavy PAL < 1.69 PAL 1.7 - 1.99 PAL < 1.69 (1.5) PAL >2.0 (2.32) PAL >2.0 (2.32) PAL >2.0 (2.32) PAL >2.0 (2.32) (1.5) (1.85) Athletes Clearing ground Player Football (rural Actor Nurse (rural) Bakery work Doctor (rural & urban) and urban) Office worker Army officer Deseeding cotton Cooking Stirring Painting Banker (Urban) Brick field worker (M) porridge Brick breaking Collecting leaves for Planting root crops Banker (rural) Picking tea Child care Earth cutting (Urban) flavouring Picking coffee Electrical industry Catching fish by hand Pounding (rice) Barber (Urban) Cowboy Brick breaking (rural) /tea Pilot Electrical work Brewery work (wine) Catching crabs in Peeling taro Barber (rural) Farmer(Male) (Urban) coastal area Printing press Electrical work Beating cotton Forking dry leaves Collecting and Driver (Urban) Rickshaw (Urban) (rural) spreading manure Preparing Breaking nuts (like Feeding animals Cutting sugarcane Driver (rural) Fisher man Rickshaw (rural) tobacco peanuts) Binding sheaves Fetching water from well Clearing ground Repairing fences Peeling sweet Engineer Journalist Car mechanic Light cleaning (depending types of potato land) Removing Making fence Furnishing industry, Weeding in nursery Rice / wheat harvest- Player cricket Full time made beans from pod Making tortillas in Pulling carts cutting ears (Urban) restaurant Garments worker Roasting corn Chemical Industry Gardener, Milking cows Day labouring Sowing, Squeezing Sweeper by hand Milk maid/man (Urban) coconut Shoe maker Cleaning house, Grinding grain on Sweeping house Hotel boy Student (Urban) Day labouring (rural) (Urban) Weeding millstone Handloom Student (rural) Tailoring (Urban) Carpenter (Urban) Harvesting root crops Driving (Tractor) Tying fences posts Ironing clothes Hoeing, Digging irrigation Uprooting sweet Sewing cloth Tailoring (rural) Carpenter (rural) Threshing channels potatoes Kneeling sorting Village house Digging holes for Winnowing corn or rice Sheaf/ cook Cutting trees Laundry work sweet potatoes wife posts Lab worker Spinning cotton Player cricket Loading Sacks Digging ground Washing clothes Cutting grass (rural) Teacher Cutting grass with Loading manure Digging holes for Washing dishes Nurse (Urban) Part time maid (Urban) machete planting Cutting fruit from tree Loading earth oven with Moderate cleaning Splitting wood for posts Shopkeeper Teacher (rural) food (Polishing, Window (Urban) cleaning etc.) Chopping wood with Lifting grain sacks for Sweeping yard Sharpening posts Traffic police machete weighing Shopkeeper (rural) Machine tool industry Loading sacks on lorry Shoe maker (rural)

A3: PAL values for different type works

Male Work PAL Work PAL Work PAL Sleeping 1.0 Sitting activities Standing activities Lying 1.2 stringing loom 1.9 Chopping Firewood 4.1 Sitting quietly 1.2 Sharpening axe 1.7 Singing firewood 3.2 Personal care(dressing, 2.3 cooking 1.8 Washing clothes 2.2 Showering) Eating 1.5 House-building Making bows and arrows, bags, etc. 2.7 Light leisure activities (watching 1.2 Weaving bamboo wall 2.9 Walking TV, chatting) Standing quietly 1.4 Roofing house 2.9 Around or strolling 2.5 Sitting activities Cutting bamboo 3.2 Downhill Playing cards 1.4 Cutting palm tree trunks 4.1 Slowly 2.8 Sewing 1.5 Digging holes for posts 6.2 At normal pace 3.1 Office work Laying floor 4.1 Fast 3.6 Sitting at desk 1.5 Nailing 3.3 Uphill Standing and moving around 1.6 Coconut activities Slowly 4.7

Transport Collecting(including 4.6 At normal pace 5.7 climbing trees) Driving lorry 1.4 Husking 6.3 Fast 7.5 Harvesting Putting in bags 4 At normal pace with 10-kg load 6.7 Kneeling sorting sweet Potatoes 1.6 Pedalling rickshaws Sitting activities Helicopter pilots Without passengers 7.2 Weaving 2.1 Normal and low-level flying 1.5 With passengers 8.5 Carving Plates, combs, etc. 2.1

Hovering 1.6 Pulling carts Sharpening machete Household tasks 2.2 Helicopter pilots Without load 5.3 Light cleaning 2.7 Normal and low-level flying 1.5 With load 5.9 3.7

Work PAL Work PAL Work PAL

Pushing wheelbarrow sawing 4.8 Light industry

Hand saw 7.5 Mining Printing 2

Power saw 4.2 Working with pick 6.0 Tailoring 2.5 Wood planning 5 Shovelling mud 5.7 Shoemaking 2.6 Brick-making Erecting roof supports Motor vehicle repairs 4.9 3.6 Making mud bricks-squatting 3 Armed services Carpentry 3.5 Kneading clay 2.7 Cleaning kit 2.4 Electrical work 3.1 Digging earth to make mud 5.7 Drill 3.2 Machine tool industry 3.1 Shovelling mud 4.4 Route marching 4.4 Chemical industry 3.5 Earth cutting 6.2 Assault course 5.1 Laboratory work 2 Brick breaking 4 Jungle march 5.7 Harvesting Building industry Hunting and fishing Sorghum harvest-cutting ears 2.1 Labouring 5.2 Paddling canoe 3.4 Uprooting sweet potatoes 3.5

Bricklaying 3.3 Fishing from canon 2.2 Winnowing 3.9 joinery 3.2 Fishing with line 2.1 Lifting grain sacks for weighing 3.7 Decorating and painting 2.8 Fishing with spear 2.6 Loading sacks on lorry 7.4 Agriculture(mechanized) Hunting flying-fox 3.3 Cutting sugarcane 6.5 Driving tractor 2.1 Hunting pig 3.6 Clearing ground (depending on type of land) 2.9-7.9 Forking 6.8 Hunting birds 3.4 Weeding 2.5-5.0 Loading sacks 4.7 Forestry Cutting trees 4.8 Feeding animals 3.6 In nursery 3.6 Tying fence posts 2.7 Repairing fences 5 Trimming branches off trees 7.3 Making fence 3.6 Recreation Felling with axe 7.5 Splitting wood for posts 4.2 Sedentary(playing cards, etc.) 2.2 Planting tree 4.1 Sharpening posts 4 Moderate (dancing, swimming, tennis, Agriculture(tropical) Digging holes for posts etc.) 4.4-6.6 5 Light (billiards, bowls, cricked, golf, Milking cows by hand Planting 2.2-4.4 2.9 2.9 sailing, etc.) Heavy (football, athletics, jogging, Collecting and spading Cutting grass with machete 6.6+ 5.2 4.7 rowing, etc.) manure Loading manure 6.2 Digging irrigation channels 5.5 Feeding animals 3.6

A4: Physical Activity Level (PAL) value of different work for females

Work PAL Work PAL Work PAL Sleeping 1.0 Household tasks Waking Lying 1.2 Washing dishes 1.7 "Around" or strolling 2.4 Sitting quietly 1.2 Food preparation and cooking Slowly 3 Sewing clothes 1.4 Deseeding cotton 1.8 At normal pace 3.4 Sewing pendants mat 1.5 Office work 1.7 With load 4 Weaving carrying bag 1.5 Collecting leaves for flavouring 1.9 Uphill: Preparing rope 1.5 Winnowing corn or rice 1.7 At normal pace 4.6 Standing 1.5 Cleaning ground 3.8 Fast 6.6 Household tasks Digging ground 4.6 With load 6 Ironing clothes 1.4 Digging holes for planting 4.3 Downhill: Preparing tobacco 1.5 Planting root crops 3.9 Slowly 2.3 Spinning cotton 1.4 Weeding 2.9 At normal pace 3 Food preparation and cooking Hoeing 4.4 Fast 3.4 Removing beans from pod 1.5 Cutting grass with machete 5 With load 4.6 Roasting corn 1.3 Sowing 4 Food preparation and cooking Agriculture (non-mechanized) Threshing 5 Catching fish by hand 3.9 Picking coffee 1.5 Binding sheaves 4.2 Catching crabs 4.5 Household tasks Harvesting root crops 3.1 Grinding grain on millstone 3.8 Cooking 2.1 Cutting fruit from tree 3.4 Pounding 4.6 Light cleaning 2.7 Light industry String porridge 3.7 Moderate cleaning (polishing, Bakery work Making tortillas 2.1 window Cleaning, etc.) 3.7 2.5 2.1

Sweeping house 3 Brewery work 2.9 Loading earth oven with food 2.6 Sweeping yard 3.5 Chemical industry 2.9 Recreations Washing clothes 3 Electrical industry 2 Sedentary (playing cards, etc.) 2.1 Cleaning house 2.2 Furnishing industry 3.3 Light(billiards, bowls, cricket, golf) 2.1-4.2 Child care 2.2 Laundry work 3.4 Moderate (dancing, swimming, 4.2-6.3 tennis, etc.) Chopping wood with machete 4.3 Machine tool industry 2.7 Heavy(football, athletics, jogging, 6.3+ rowing,) Beating cotton 2.4

Appendix A5: BMR in male and females according to age and body weight (FAO, 2004)

18-29.9yrs 30-59.9yrs >60yrs

Male Female Male Female Male Female

BW, BMR, BW, BMR, BW, BMR, BW, BMR, BW, BMR, BW, BMR, kg kcal/kg kg kcal/kg kg kcal/kg kg kcal/kg kg kcal/kg kg kcal/kg

50 29 45 26 50 29 45 27 50 23 45 24

55 28 50 25 55 27 50 25 55 22 50 22

60 27 55 24 60 26 55 24 60 22 55 21

65 26 60 23 65 25 60 22 65 21 60 20

70 25 65 22 70 24 65 21 70 20 65 19

75 24 70 22 75 23 70 20 75 20 70 18

80 24 75 21 80 22 75 19 80 19 75 18

85 23 80 21 85 22 80 19 85 19 80 17

90 23 85 21 90 21 85 18 90 18 85 17

BW. Body weight; BMR, basal metabolic rate

A6: Rich sources of Energy, Carbohydrate, Protein and Fat (per 100g) Carbohydrate Energy rich foods Protein rich foods Fat rich foods rich foods Energy Food CHO, Protein, Fat, Food Name Food Name Food Name kcal Name g g g Cooking oil 900 Molasses 99 Fishmeal 88.4 Cooking 100 Ribbon fish Fish liver oil 900 Sugar 99 76.1 Fish liver oil 100 (dried) Fesha fish Ghee (buffalo) 900 Sugar candy 99 70.9 Ghee (buffalo) 100 (dried) Ghee (cow) 900 Sago 87 Magur (dried) 69.7 Ghee (cow) 100 Ghee Molasses Ghee 900 86 Prawn (dry) 68.1 100 (vegetable) (date) (vegetable) Oils mustard Rice Parshee fish Oils mustard 900 81 65 100 etc (puffed) (dried) etc Butter 729 Honey 80 Chapila dried) 64.8 Butter 81 Rice Pata fish Walnut 687 parboiled 79 64.5 Walnut 65 (dried) (milled) Bhangon Coconut (dry) 662 Vermicelli 78 61.5 Coconut (dry) 62 (dried) Rice sunned Nuts 655 78 Bhetki (dried) 60.2 Nuts 59 (milled) Prawns whole Pistachio 626 Dates (dry) 78 60 Pistachio 54 (dried) Rice Sunflower White fish Sunflower 620 parboiled 77 58.9 52 seeds (dried) seeds (husked) Rice Chilgoza (nut) 615 77 Tapse (dried) 58.5 Chilgoza (nut) 49 (flattened) Pumpkin/swee Cashew nuts 596 Makhana 77 Tengra (dried) 54.9 47 t gourd seed Pumpkin/swee Rice sunned 584 77 Soybean 43.2 Cashew nuts 47 t gourd seed (husked) Groundnut/ Oil cakes 570 Semolina 75 40.9 Sesame 43 peanut (fried) (groundnut) Groundnut/ Wheat flour Bream (sea, Coconut 567 74 38.6 42 peanut (refined) dried) (mature) Rice (fried Groundnut/ Sesame 563 74 Hilsha (salted) 38 41 paddy) peanut Appricot Powdered milk Mustard 541 73 38 Coconut milk 40 (dry) (skim, cow) Groundnut/ Biscuit (salted) 534 Sorghum 73 Khesari dal 28.2 40 peanut (fried) Mahua Groundnut/ Linseed 530 72 26.2 Mustard 40 flower peanut (fried) Powdered milk Biscuit 496 72 Fenugreek 26.2 Linseed 37 (whole, cow) (sweet) Wheat Nutmeg 472 71 Chicken 25.9 Nutmeg 36 (whole)

Continued Carbohydrate rich Energy rich foods Protein rich foods Fat rich foods foods Energy, Food Name Food Name CHO, g Food Name Protein, g Food Name Fat, g kcal Millet Powdered milk Hilsha Biscuit (sweet) 450 70 25.8 35 (French) (whole, cow) (salted) Coconut - Barley(whol Groundnut/ Biscuit 444 70 25.3 32 mature e) peanut (salted) Wheat flour Yogurt Mace 437 69 Cat fish 25.2 31 (coarse) (buffalo) Powdered Soybean 432 Turmeric 69 Lentils 25.1 milk (whole, 27 cow) Millet Yogurt Coconut milk 430 68 Bean (field) 24.9 26 (pearl) (cow) Yogurt Tamarind(p Green 421 66 24.5 Cheese 25 (buffalo) ulp) gram(split) Maize/ Pumpkin/sweet Chapila (dried) 413 66 24.3 Mace 24 (mature) gourd seed Black Yogurt (cow) 403 Achar 64 24 Omum 22 gram(split) Lotus seeds Green Cow milk Hilsha (salted) 400 64 24 21 (ripe) gram(whole) solids Bengal Molasses 398 61 Pigeon 23.3 Soybean 20 gram(whole) Tamarind Sugar 398 61 Peas fried 22.9 Hilsha fish 19 leaves (dry) Sugar candy 398 Bean (field) 60 Scorpion fish 22.8 Popy seed 19 Green Chapila Rice husk/ bran 393 60 Beef 22.6 17 gram(split) (dried) Tamarind seed Bengal Bengal Rice husk/ 387 60 22.5 16 (dried) gram(split) gram(fried) bran Ribbon fish Yogurt (buff, Biscuit 383 Lentils 59 22.3 15 (dried) skim mik) (sweet) Bengal 372 Peas fried 59 Mustard 22 Cumin seed 15 gram(split) Bengal Bengal Mixed 369 58 Hilsha fish 21.8 15 gram(fried) gram(fried) spices Lotus seeds Fishmeal 364 58 Popy seed 21.7 Duck egg 14 (dry) Red gram/ Mutton Omum 363 58 Duck 21.6 14 arahar(split) (lamb) Green Millet (pearl) 361 57 Shark 21.6 Hen egg 13 gram(whole) Bengal Milk 360 Khesari dal 57 Goat 21.4 12 gram(whole) (condensed) Powdered milk Peas 357 57 Cashew nuts 21.2 Salmon 12 (skim, cow) dried/split

A7: Rich sources of Thiamine, β-carotene and Vitamin-C contents per 100g

Thiamine rich foods β-carotene rich foods Vitamin-C rich foods Thiamin Β carotene Food name Food name Food name Vit-C mg e mg mcg Rice husk/ bran 2.7 Helencha leaves 13700 Amla 463 Taro/black arum Chilli, red (dry) 0.93 12000 Drumstick leaves 220 leaves Groundnut/ Amaranth (red leaf Neem leaves, yellow 0.9 11940 218 peanut var.) (ripe) Taro/green arum Pepper (black) 0.9 10278 Guava 210 leaves Sunflower seeds 0.86 Turnip leaves 9396 Turnip leaves 180 Kodobele (ripe) 0.8 Mango (ripe) 8300 Agathi 169 Sweet potato Soybean 0.73 7800 Radish leaves 148 leaves Green Amaranth 0.72 7715 Coriander leaves 135 gram(split) leaves(tender) Pistachio 0.67 Indian spinach 7440 Chilli (green) 125 Gourd(sweet)/pum Mustard 0.65 7200 Tetul (bilati) 108 pkin Cashew nuts 0.63 Bottle gourd leaves 7196 Pommelo (red) 105 Cumin seed 0.55 Jute plant tops 6918 Neem leaves (green) 104 Mixed spices 0.55 Coriander leaves 6918 Spinach 97 Pork 0.54 Drumstick leaves 6780 Gourd (small bitter) 96 Bean (field) 0.52 Cowpea leaves 6072 Ambada (hog plum) 92 Amaranth (data) Gahira fish 0.5 5998 Cauliflower 91 leaves Wheat 0.49 Beet leaves 5862 Bottle gourd leaves 90 flour(coarse) Bengal 0.48 Betel leaves 5760 Orange 84 gram(split) Green 0.47 Carrot leaves 5700 Carrot leaves 79 gram(whole) Peas dried/split 0.47 Spinach 5580 Amaranth (data) leaves 78 Peas fried 0.47 Agathi 5400 Beet leaves 70 Barley (whole) 0.47 Radish leaves 5295 Gourd(bitter) 68 Wheat (whole) 0.45 Jackfruit (ripe) 4700 Orange juice 64 Powdered milk 0.45 Celery leaves 3990 Indian spinach 64 (skim, cow) Red gram/arahar(split 0.45 Spinach sour 3660 Taro/black arum leaves 63 ) Lentils 0.45 Amaranth (spiny) 3564 Lemon 63 Walnut 0.45 Safflower leaves 3540 Celery leaves 62 Radish 0.43 Liver (goat) 3030 Gram leaves 61 Black 0.42 Mace 3027 Pumpkin leaves 61 gram(split) Maize/ (mature) 0.42 Khesari leaves 3000 Bilimbi 61 Papaya(green/im 0.4 Thankuni leaves 2998 Blackberry (Indian) 60 mature)

Continued

Thiamine rich foods β-carotene rich foods Vitamin-C rich foods Food Thiamine mg Β carotene mcg Food name Vit-C mg name Khesari dal 0.39 Mesta leaves 2898 Papaya (ripe) 57 Groundnut/ 0.39 Neem leaves (green) 2760 Ole kopi 53 peanut (fried) Sorghum 0.37 Spinach stalks 2630 Fenugreek leaves 52 Liver (mutton) 0.36 Mustard leaves 2622 Boroi (bitter plum) 51 Tamarind leaves Fenugreek 0.34 2510 Chilli, red (dry) 50 (green) Nutmeg 0.33 Chilli(green) 2340 Lime (sweet) 50 Millet (pearl) 0.33 Fenugreek leaves 2340 Lime 47 Neem leaves, yellow Chilgoza (nut) 0.32 1998 Drumstick/horse radish 45 (ripe) Turnip leaves 0.31 Kolmee leaves 1980 Amaranth (red leaf var.) 43 Powdered milk 0.31 Pumpkin leaves 1940 Kolmee leaves 42 (whole, cow) Bengal 0.3 Carrot 1890 Khesari leaves 41 gram(whole) Pumpkin/sweet 0.3 Liver (mutton) 1830 Pickles 41 gourd seed Prawal /potol 0.3 Bathua leaves 1740 Mango (ripe) 41 Ambada (hog 0.28 Mint leaves 1620 Mahua (ripe) 40 plum) Rice parboiled 0.27 Cabbage 1200 Orange/mandarin 40 (husked) Cumin seed 1080 Fishmeal 22.6 Fig (red) 6.4 Parshee fish Neem leaves, yellow 1050 Crabs 21.2 6.2 (fresh) (ripe) Yogurt (buff, 990 Cowpea leaves 20.1 Tamarind (pulp) 5.6 skim mik) Pata fish (dried) 988 Rice (flattened) 20 Bullocks heart 5.2 Yogurt (cow) 956 Turmeric 18.6 Guava 5.2 Powdered milk 950 Coriander leaves 18.5 Pomegranate 5.1 (whole, cow) Bhetki (dried) 939 Punornova leaves 18.4 Kodobele (ripe) 5 Ribbon fish 890 Fesha fish (dried) 18 Linseed 4.8 (dried) Snails (large) 870 Coriander seed 17.9 Drumstick/ horse radish 4.8 Tengra (dried) 843 Mustard 17.9 Peas dried/split 4.5 Amaranth 800 Parshee fish (dried) 17.4 Peas fried 4.4 (Spiny) Cheese 790 Pappadom 17.2 Rice husk/ bran 4.3 Neem leaves, yellow Bata fish 790 17.1 Bakul flower 4.3 (ripe) Cloves (dry) 740 Pepper (black) 16.8 Prawal leaves 4.2 Lemon/ lime 710 Fenugreek leaves 16.5 Green gram(whole) 4.1 peel Turnip leaves 710 Mustard leaves 16.3 Peas (green) 4 Scorpion fish 670 Beet leaves 16.2 Barley (whole) 3.9 Punornova 667 Mint leaves 15.6 Bengal gram(whole) 3.9 leaves Yogurt (buffalo) 650 Mahua flower 15 Dates (dry) 3.9 Rohu 650 Bhetki (dried) 15 Blackberry (Indian) 3.8

A8: Rich sources of Calcium, Iron and Fibre (per 100g)

Calcium rich foods Iron rich foods Fibre rich foods Ca Iron Fibre Food Name Food Name Food Name mg mg gm Bhangon (dried) 6235 Tengra (dried) 100.8 Coriander seed 32.6 Prawn (dry) 4384 Pata fish (dried) 51.7 Chilli, red (dry) 30.2 Prawns whole 3847 Prawns whole (dried) 49.6 Omum 21.2 (dried) Chapila (dried) 3590 Pickles 45.2 Cardamom 20.1 Parshee fish (dried) 2231 Ribbon fish (dried) 43.7 Tamarind leaves (dry) 20.1 Taro/arum leaves Magur (dried) 1804 Tapse (dried) 41.2 16 (dried) Fesha fish (dried) 1676 Cauliflower leaves 40 Pepper (black) 14.9 Tapse (dried) 1597 Taro/black arum leaves 38.7 Pickles 13.7 Popy seed 1584 Rice husk/ bran 35 Cumin seed 12 Taro/arum leaves 1546 Cumin seed 31 Lotus seeds (dry) 11.8 (dried) Omum 1525 Mixed spices 31 Nutmeg 11.6 Tamarind leaves 1485 Turnip leaves 28.4 Betel/areca nut 11.2 (dry) Sesame 1450 Omum 27.7 Cloves (dry) 9.5 Powdered milk 1370 Amaranth (data) leaves 25.5 Popy seed 8 (skim, cow) Crabs 1370 Neem leaves (green) 25.3 Fenugreek 7.2 Snails (small) 1321 Gram leaves 23.8 Chilli (green) 6.8 Agathi 1130 Amaranth (Spiny) 22.9 Coconut (dry) 6.6 Cumin seed 1080 Fishmeal 22.6 Fig (red) 6.4 Neem leaves, yellow Parshee fish (fresh) 1050 Crabs 21.2 6.2 (ripe) Yogurt (buff, skim 990 Cowpea leaves 20.1 Tamarind (pulp) 5.6 mik) Pata fish (dried) 988 Rice (flattened) 20 Bullocks heart 5.2 Yogurt (cow) 956 Turmeric 18.6 Guava 5.2 Powdered milk 950 Coriander leaves 18.5 Pomegranate 5.1 (whole, cow) Bhetki (dried) 939 Punornova leaves 18.4 Kodobele (ripe) 5 Ribbon fish (dried) 890 Fesha fish (dried) 18 Linseed 4.8 Snails (large) 870 Coriander seed 17.9 Drumstick/ horse radish 4.8 Tengra (dried) 843 Mustard 17.9 Peas dried/split 4.5 Amaranth (Spiny) 800 Parshee fish (dried) 17.4 Peas fried 4.4 Cheese 790 Pappadom 17.2 Rice husk/ bran 4.3 Neem leaves, yellow Bata fish 790 17.1 Bakul flower 4.3 (ripe) Cloves (dry) 740 Pepper (black) 16.8 Prawal leaves 4.2 Lemon/ lime peel 710 Fenugreek leaves 16.5 Green gram(whole) 4.1 92

Ca Iron Fibre Food Name Food Name Food Name mg mg mg Turnip leaves 710 Mustard leaves 16.3 Peas (green) 4 Scorpion fish 670 Beet leaves 16.2 Barley (whole) 3.9 Bengal Punornova leaves 667 Mint leaves 15.6 3.9 gram(whole) Yogurt (buffalo) 650 Mahua flower 15 Dates (dry) 3.9 Rohu 650 Bhetki (dried) 15 Blackberry (Indian) 3.8 Gahira fish 650 Fenugreek 14.1 Mace 3.8 Coriander seed 630 Ribbon fish 13.9 Cow pea 3.8 Cauliflower leaves 626 Millet (pearl) 13.3 Soybean 3.7 Lota fish 610 Mace 12.6 Dates 3.7 Folui 590 Wheat flour (coarse) 11.5 Coconut (mature) 3.6 Chapila (fresh) 590 Soybean 11.5 Amla 3.4 Oil cakes White fish (fresh) 590 Lotus seeds (dry) 11.1 3.2 (groundnut) Bhangon 580 Spinach 10.9 Groundnut/ peanut 3.1 (powdered) Groundnut/ peanut Prawal leaves 531 Tamarind (pulp) 10.9 3.1 (fried)

A 9: Nutrients return per 100 Taka spend

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otassium Food Na / Price 100g_Tk Amount of food(g) /100 Tk Fibre _g Energy Protein Fat CHO, Calcium mg Iron Thiamine mg Riboflavin_ mg Vit Vitamin A µg Niacin Folic acid Zinc Magnesium mg Sodium P mg Phosphorus mg Rice(flattened) 5 2000 26 7114 130 23 1584 502 136 4.2 1 0 0 80 0 27 939 40 2995 2592 Rice(puffed) 8 1316 18 4755 88 1 1089 121 9 2.8 2 0 0 46 153 11 598 8553 2026 1753 Vermicelli 8 1333 43 4627 119 8 999 293 27 2.5 1 0 0 45 240 0 560 107 1867 1227 Wheat(whole) 3 3704 452 12741 415 107 2296 1519 181 14.1 4 0 0 204 1407 103 5259 667 10852 11704 Wheat flour(coarse) 4 2857 306 9545 323 60 1777 1492 140 14.0 8 0 12 177 829 86 4313 468 8114 8743 Wheat flour(refined) 4 2451 66 8480 240 24 1792 314 66 2.9 2 0 0 105 490 38 1419 241 5154 3431 Bengal gram(whole) 7 1423 248 4982 290 85 638 2890 125 4.3 4 0 43 70 2648 38 1851 470 10192 5238 Bengal gram(split) 11 909 11 3405 184 55 538 509 80 4.4 2 0 30 22 1341 30 1000 355 6591 3009 Black gram(split) 9 1104 10 3867 249 13 682 584 36 4.6 2 0 52 22 1457 27 1567 390 8720 4249 Green gram(whole) 13 800 130 2544 190 10 358 1096 63 3.8 3 0 24 53 1120 21 1512 224 14240 2608 Green gram(split) 8 1215 9 4259 288 14 740 839 87 4.4 2 0 39 80 1701 33 1791 370 15796 3831 Khesari dal 5 2217 49 7805 629 20 1253 1349 118 8.2 5 0 112 64 4583 75 2229 787 18022 8296 Lentils 8 1182 156 3749 328 9 510 272 60 9.1 2 0 33 75 426 46 846 437 7506 3085 Other pulses 8 1182 156 3749 328 9 510 272 60 9.1 2 0 33 75 426 46 846 437 7506 3085 Amaranth(data) leaves 2 4219 184 1056 84 12 62 7214 354 1.3 8 1565 31359 68 3586 41 7650 1519 13544 1968 Amaranth( red leaf var) 3 3571 151 1125 162 12 17 9132 214 1.1 5 1501 28330 57 3036 34 6475 2107 9321 1143 Bottle gourd leaves 2 4717 207 1237 118 27 27 4430 147 3.3 8 2249 9319 66 3443 23 3240 1930 13024 1342 Helencha leaves 4 2500 13 1214 51 12 220 775 47 1.0 4 1075 13250 24 1125 13 667 1225 5750 1300 Indian spinach 2 4651 101 1167 110 15 98 5171 102 0.9 17 2410 7884 23 6512 16 8326 3227 8696 1442 Jute plant tops 2 5000 288 1619 144 13 87 5983 485 5.0 27 2722 15263 80 6150 74 2092 2999 11245 2999 Kolmee leaves 3 3333 124 1422 64 13 201 3567 73 4.7 13 1013 6621 30 1900 17 647 3567 6907 1215 Radish leaves 5 2000 52 644 37 14 67 2939 57 1.6 2 1377 3118 32 1400 10 404 1398 5193 823 Spinach 3 3413 100 887 101 17 30 3061 77 1.0 3 723 13955 48 6621 31 1768 5836 16075 1536 Taro/black arum leaves 4 2500 93 1553 140 31 133 9792 53 1.5 11 1575 17479 65 3150 25 3250 1200 19075 975 Taro/green arum leaves 4 2500 93 1264 101 27 109 5867 123 5.5 7 1203 14889 65 3150 17 1534 1169 19100 997 Garlic 6 1770 37 2602 122 11 488 442 28 2.3 2 427 0 43 71 19 442 195 9044 2867 spices 3 3472 66 8438 326 243 1042 833 31 1.7 5 156 69 10 660 14 833 382 7292 1007 Potato 2 4950 102 3284 59 8 693 567 25 4.0 5 946 112 40 891 39 1018 807 14172 1980 Radish 2 4132 66 727 37 4 102 988 16 17.8 0 713 0 21 1033 16 620 1668 5887 945

Continued

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Food Name / Price 100g_Tk Amount of food/100 (g) Tk Fibre, Energykcal , g Protein , Fat,g g CHO, Calcium mg mg Iron, Thiamine Riboflavin_m g Vit C , mg Vitamin A, µg mgNiacin, Folic µg acid, Zinc, µg Magnesium mg Sodium, mg Potassium , mg Phosphorus mg Taro/arum 4 2857 117 2884 62 5 590 1143 27 4.2 1 177 0 31 629 7 943 257 16886 943 Taro/Arum tubers 3 2941 121 3024 66 5 618 1024 21 3.5 1 179 110 32 647 7 971 324 17382 2471 Yem (Elephant) 3 3333 137 2480 40 4 503 1667 20 2.0 2 150 0 37 733 8 1100 300 19700 2800 Amaranth(data) stem 2 4219 51 886 38 4 154 4810 76 0.4 8 1511 1076 0 0 22 0 0 0 1266 Aubergine/Eggplant 3 2959 120 714 56 2 58 625 11 0.8 2 38 112 28 1006 17 703 226 5257 1391 Bean 5 2222 96 650 54 3 55 1556 20 1.8 2 214 421 11 1378 8 1131 223 3789 1089 Chilli(green) 6 1592 134 605 44 2 33 351 26 0.5 1 1628 152 21 159 31 690 191 4486 478 Cow pea 4 2717 163 1048 82 10 77 1467 14 3.8 1 0 229 54 4565 27 1386 625 11712 1440 Drumstick/Horseradish 5 1905 91 823 54 4 97 454 3 0.8 1 1331 494 11 838 3 533 800 4933 2095 Prawal/potol 4 2793 62 683 57 9 62 444 47 4.6 1 543 150 22 447 11 419 787 4131 492 Gourd(bitter) 4 2451 64 756 50 8 88 392 44 1.2 1 2221 583 17 1103 9 766 882 4462 483 Gourd(ridge) 4 2770 30 796 35 10 127 574 35 3.0 1 127 60 14 194 14 388 1080 3850 886 Gourd(small bitter) 4 2469 0 0 0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0 Gourd(snake) 4 2793 22 680 14 8 126 874 11 1.1 2 524 0 22 447 9 475 1089 4330 782 Gourd(sweet)pumpkin 4 2740 66 504 38 8 36 1420 19 1.9 2 577 10114 22 438 3 274 219 9562 438 Jackfruit(immature) 5 2000 56 1020 52 6 188 600 34 1.0 1 280 0 4 0 0 0 700 6560 800 Kakrol 3 3067 34 1874 58 14 361 828 80 2.5 2 4380 417 25 491 15 613 1595 5706 794 Kolmee 5 2105 0 400 19 4 72 1684 17 0.0 0 0 0 0 0 0 0 0 0 632 Lady`s finger/okra 3 3096 96 1209 65 5 178 2868 28 1.2 5 541 585 43 1858 10 609 1149 5516 862 Papaya(green/immature) 2 4525 68 1342 35 3 259 660 27 1.4 1 840 26 9 0 10 2534 317 5840 695 Peas(green) 5 1852 94 1688 129 6 231 798 29 7.4 3 142 701 52 1204 23 873 93 4519 2000 Plantain 4 2857 66 2207 57 9 443 629 17 2.6 2 207 1610 26 629 4 813 114 6903 586 Tomato(green) 4 2294 39 525 44 5 58 372 7 1.6 0 702 0 14 206 4 161 161 3578 642 Cardamom 66 152 37 395 15 3 57 197 7 0.3 0 0 0 1 0 4 262 24 1479 242 Chilli, Red(dry) 37 272 72 852 43 17 96 436 6 2.5 1 129 2034 24 289 7 414 82 5472 798 Cloves(dry) 190 53 15 141 3 5 14 389 3 0.0 0 0 3 1 11 1 113 121 446 45 Coriander seed 11 930 380 3126 131 150 125 5860 167 2.0 3 0 0 20 0 43 2995 316 11442 3702 Cumin seed 64 157 17 633 29 28 59 1598 70 0.9 1 12 101 6 16 6 636 233 2173 798 Fenugreek 24 426 31 1417 111 25 188 681 60 1.4 1 0 68 5 357 0 528 81 2255 1574

Continued

ron, mgron, Food Name / Price 100g_Tk Amount of food/100 (g) Tk Fibre, _g Energykcal , g Protein , Fat,g g CHO, Calcium , mg I Thiamine mg Riboflavin_ mg Vit C , mg Vitamin A, µg mgNiacin, Folic acid, µg Zinc, µg Magnesium mg Sodium, mg Potassium , mg Phosphorus mg Ginger 8 1307 26 941 25 10 174 222 14 0.4 0 65 0 13 144 5 523 157 5059 418 Mace 350 29 1 125 2 7 14 51 4 0.1 0 0 144 0.4 0 0 61 0 0 29 Mixed spices 59 169 0 603 32 25 62 1831 53 0.9 0 0 148 0 0 0 0 0 0 0 Mixed spices(hot) 100 100 0 229 10 2 42 130 5 0.2 0 0 0 0 0 0 0 0 0 0 Nutmeg 130 77 9 363 6 28 22 92 4 0.3 0 0 0 1 0 0 176 0 0 185 Omum 25 400 85 1452 68 87 98 6100 111 0.8 1 0 47 8 0 0 564 0 0 1772 Pepper(black) 104 96 24 290 11 3 42 426 16 0.1 0 0 26 1 13 1 178 35 1231 161 Turmeric 15 664 140 2226 46 56 314 1116 221 0.6 1 0 7 29 259 25 1276 233 18073 1854 Ambada(hog plum) 8 1250 20 633 13 11 111 709 35 3.5 1 963 0 4 0 2 494 13 2187 138 Amla 10 1000 34 442 8 1 83 320 9 0.2 1 4534 8 2 0 3 280 40 2250 250 Apple(with skin, raw) 14 724 17 449 2 1 98 43 1 0.6 0 29 20 1 22 0 36 7 774 80 Apple(with skin, 14 724 17 449 2 1 98 43 1 0.6 0 29 20 1 22 0 36 7 774 80 raw)Safeda Banana, ripe, combined 6 1555 40 1477 20 13 299 171 5 14.6 1 16 31 14 311 4 358 156 6392 560 different varieties, raw Bilimbi 8 1250 35 513 7 9 84 119 10 1.5 1 618 84 6 150 5 238 50 1598 288 Blackberry 11 952 33 371 8 5 58 217 8 0.9 0 706 883 2 0 2 349 267 1641 151 Boroi(bitter plum) 10 1000 0 598 19 2 126 140 8 0.2 1 661 20 10 0 3 245 65 3535 330 Custard apple 20 500 22 423 9 1 83 86 5 0.4 1 190 2 5 70 2 125 45 1831 235 Coconut water 4 2500 28 492 14 7 80 505 4 1.5 1 82 0 3 75 3 613 2388 6500 442 Dates(dry) 15 683 57 2098 15 3 473 429 50 0.7 0 3 50 9 134 0 303 14 4624 437 Guava, combined varieties, 13 769 42 485 8 4 84 134 5 1.6 1 1756 254 9 377 2 193 42 2010 136 green, raw Grapes, pale green, raw 30 333 10 314 2 2 67 73 2 0.3 0 97 9 1 26 0 273 7 637 100 Kheera 3 3300 0 363 30 3 53 594 0 0.3 1 99 0 0 0 0 0 0 0 0 Kodobele(immature) 2 6667 0 4400 207 0 900 3733 0 2.7 1 1000 681 0 0 0 0 0 0 0 Kodobele(ripe) 2 5000 177 3210 153 20 517 3685 35 40.0 1 638 0 0 0 0 2000 100 17995 3200 Lemon(sweet) 15 667 5 233 5 2 49 200 5 0.0 0 300 0 0 0 0 0 0 1400 133 Lichis 37 270 15 167 4 1 28 29 1 0.1 0 30 0 2 0 1 39 2 353 47

Continued

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Food Name / Price 100g_Tk Amount of food/100 (g) Tk _g Fibre, Energykcal , g Protein , Fat, g CHO, Calcium , mg mg Iron, Thiamine Riboflavin_mg Vit C , mg Vitamin A, µg mgNiacin, Folic µg acid, Zinc, µg mgMagnesium Sodium, mg Potassium mg , Phosphorus mg Lime 6 1704 29 801 5 12 170 681 39 0.0 1 801 0 2 0 0 0 0 0 341 Lime(sweet) 15 667 19 254 5 3 41 287 3 0.3 0 332 11 2 143 0 64 22 1029 118 Mango, combined 7 1370 22 918 12 7 189 132 4 5.1 1 324 1599 25 973 0 122 19 1881 206 varieties, ripe, raw Melon 3 3333 33 567 10 7 103 567 7 3.7 3 1130 3500 17 711 2 700 100 7033 467 Olive(wild) 5 2000 32 1400 20 2 324 440 62 0.6 0 780 637 0 0 0 0 0 0 0 Orange 15 690 17 340 1 1 74 214 1 1.0 0 372 77 3 319 0 69 14 1248 97 Orange juice 15 667 1 60 1 1 11 33 5 0.4 0 427 13 2 40 0 53 67 1000 87 Orange/mandarin 12 858 21 379 6 2 75 201 2 0.3 0 463 160 4 257 1 146 39 1132 214 Palm, Palmyra(green) 20 500 2 157 3 1 34 215 3 0.1 0 20 0 1 0 0 0 0 0 100 Palm(ripe) 6 1634 11 1281 9 6 291 257 27 0.7 0 574 3404 5 0 4 236 33 3905 948 Papaya(ripe) 14 714 12 236 4 1 46 205 2 0.6 0 441 429 4 414 1 74 29 1301 79 Pears 15 667 24 410 4 2 82 40 3 0.2 0 25 0 1 53 0 53 40 876 73 Pineapple 4 2740 38 1178 22 11 227 548 44 3.0 1 573 0 11 329 16 329 1151 3342 192 Pineapple(wild var) 6 1667 23 777 16 2 162 298 11 3.3 2 565 85 7 202 4 526 217 2923 150 Pomegranate 31 328 13 220 5 1 42 69 1 0.1 0 85 10 2 125 3 144 3 436 230 Pommelo(red) 4 2762 28 1038 12 9 213 983 6 1.7 1 3361 91 8 718 2 414 28 6504 580 Rose apple 25 400 5 160 3 1 32 36 1 0.0 0 89 0 2 0 0 16 0 417 120 Tamarind(pulp) 16 625 32 1688 20 3 380 794 25 2.2 1 70 8 12 91 0 540 117 4376 747 Tetul(bilati) 17 588 6 459 16 2 94 82 6 1.3 0 635 0 0 0 0 0 0 0 0 Tomato(ripe) 6 1667 28 267 18 4 24 216 3 0.6 1 205 144 10 250 7 124 113 2605 400 Wood apple 8 1250 87 1391 36 3 261 518 5 0.4 0 141 0 14 0 3 166 87 6160 625 Watermelon 3 3333 54 534 16 7 76 415 13 0.7 1 377 977 11 100 0 367 582 3558 400 Black berry(deshi) 8 1250 14 650 8 3 146 334 22 1.1 3 820 0 0 0 0 150 632 1336 146 Melon(musk) 20 500 2 85 2 1 18 160 7 0.6 0 130 0 2 0 0 155 523 1705 70 Burmese grape 10 1000 42 401 16 25 7 521 15 0.0 0 121 0 0 0 0 113 72 1985 171 Aire Fish 28 357 0 318 61 8 0 39 3 0.3 0 0 0 2 39 1 129 300 968 364 Bacha Fish 35 286 0 420 52 16 17 1486 2 0.0 0 37 0 2 0 0 0 0 0 514 Bata fish 41 242 0 257 39 11 0 1195 3 0.2 0 0 0 13 0 2 80 201 487 485

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, mg ,

olic µg acid, Food Name / Price 100g_Tk Amount of food/100 (g) Tk _g Fibre, Energykcal , g Protein , Fat,g g CHO, Calcium , mg mg Iron, Thiamine Riboflavin_mg Vit C , mg Vitamin A, µg mgNiacin, F Zinc, µg mgMagnesium Sodium, mg Potassium mg , Phosphorus mg Bele Fish/Poa 26 382 0 309 56 10 0 1515 5 0.1 0 0 0 12 0 4 46 302 1027 1279 Bhangon (Powdered) 30 333 0 480 65 15 22 1933 4 0.0 0 0 0 2 0 0 0 0 0 1033 Bhetki (Fresh) 31 323 0 255 48 3 10 1710 3 0.0 0 32 0 2 0 0 18 259 779 605 Bhetki (Bried) 120 83 0 222 50 2 2 783 13 0.0 0 0 0 0 0 0 0 0 0 0 Boal 24 417 0 333 64 9 0 346 3 0.3 0 0 4 16 0 1 154 263 608 558 Black Fish/Baho 16 625 0 594 106 19 0 81 7 0.3 0 0 0 26 0 2 169 625 1794 881 Boicha Fish 25 400 0 448 73 18 0 700 0 0.0 0 0 0 0 0 0 0 0 0 0 Bream (Sea, Fresh) 90 111 0 102 22 0 0 102 0 0.0 0 2 33 0 0 0 0 0 0 0 Bream (Sea, Dried) 50 200 0 420 77 12 0 296 0 0.0 0 0 0 0 0 0 0 0 0 0 Butter Fish 63 160 0 182 31 0 7 496 2 0.0 0 0 0 0 0 0 27 553 49 453 Carp 24 422 0 435 84 11 0 2236 3 0.3 0 0 13 19 0 2 152 236 1236 992 Cat Fish 80 125 0 158 32 3 1 163 5 0.0 0 0 106 3 0 0 0 0 0 350 Indian river shad, raw 30 333 0 353 51 16 0 3533 16 0.0 0 0 20 0 0 7 123 190 770 1867 Chapila (Dried) 53 190 0 785 123 32 0 6838 13 0.0 0 0 0 0 0 0 0 0 2724 1608 Climbing Fish (Koi) 29 339 0 471 59 26 0 217 4 0.1 1 0 729 9 0 4 180 176 726 546 Tilapia cooked 29 339 0 471 59 26 0 217 4 0.1 1 0 729 9 0 4 180 176 726 546 Dragon Fish 12 826 0 1339 131 91 0 116 1 1.2 0 0 41 37 0 15 240 380 1397 1074 Eel Fish 45 222 0 222 36 2 15 733 2 0.0 0 7 2006 2 0 0 27 27 249 357 Fesha Fish(Fresh) 26 392 0 408 72 7 13 1725 5 0.0 0 0 0 0 0 0 78 214 416 901 Fesha Fish(Dried) 60 167 0 560 118 8 3 2793 30 0.0 0 0 0 0 0 0 0 0 0 0 Fishmeal 50 200 0 728 177 2 0 194 45 0.0 0 0 0 0 0 0 0 0 0 0 Flat Fish 70 143 0 154 27 3 4 257 4 0.0 0 0 43 0 0 0 0 49 170 357 Folui 26 392 0 404 78 4 15 2314 7 0.5 0 24 118 3 0 0 118 159 605 1045 Fry (V. Small Fresh) 26 392 0 545 69 30 0 3792 10 0.0 0 0 231 1 0 12 0 208 796 2431 Gahira Fish 40 250 0 243 42 4 11 1625 3 0.1 0 55 0 0 0 0 0 0 0 0 Gura Fish 35 286 0 320 52 13 0 500 0 0.0 0 0 0 0 0 0 0 0 0 0 Hilsha Fish 91 110 0 245 20 18 0 94 1 0.1 0 0 0 6 0 1 29 57 178 214 Hilsha (Salted) 100 100 0 400 38 35 6 310 4 0.0 0 0 0 0 0 0 20 1023 146 58

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, mg , A, µg

Food Name / 100g_TkPrice Amount of food (g) Tk /100 _g Fibre, Energykcal , g Protein , Fat,g g CHO, Calcium , mg mg Iron, Thiamine Riboflavin_mg Vit C , mg Vitamin mgNiacin, Folic µg acid, Zinc, µg mgMagnesium Sodium, mg Potassium mg , Phosphorus mg kasha Fish 6 1667 0 1750 263 77 0 7033 15 21.7 4 0 650 43 0 23 600 567 3350 8300 Magur 46 217 0 224 34 10 0 59 2 0.1 0 0 33 4 0 1 54 154 748 391 Magur (Dried) 30 333 0 1127 232 18 9 6013 74 0.0 0 0 311 0 0 0 0 0 0 0 Mola Fish 25 400 0 432 68 18 0 3068 15 0.0 0 0 10720 0 0 13 120 172 712 1760 Mrigal 29 351 0 358 65 11 0 2298 6 0.2 0 0 39 3 60 1 133 221 828 982 Mullet 40 250 0 388 48 20 5 893 11 0.0 0 0 0 7 0 0 0 0 0 438 Parshee Fish (Fresh) 50 200 0 624 130 9 6 4462 35 0.0 0 12 0 2 0 0 0 0 0 792 Pata fish(Dried) 60 167 0 488 108 5 4 1647 86 0.0 0 0 0 0 0 0 0 0 0 0 Pomfret (Black) 30 333 0 370 68 9 5 953 8 0.0 0 0 0 0 0 0 252 209 514 2454 Pomfret (White) 90 111 0 97 19 1 2 222 1 0.0 0 0 0 3 0 0 0 0 0 322 Pomfret(Small) 43 233 0 260 42 10 0 407 16 0.0 0 0 0 0 0 0 0 0 0 0 Prawns whole(Dried) 38 267 0 765 160 9 12 10259 132 0.0 0 0 0 0 0 0 0 0 0 0 Prawn( dray) 43 235 0 821 160 20 0 10315 0 0.0 0 0 0 0 44 0 0 0 0 2729 Pump late(sea fish) 70 143 0 111 22 1 3 343 2 0.0 0 0 0 0 0 0 0 0 0 0 Ribbon Fish(dried) 120 83 0 319 63 7 0 0 36 0.0 0 0 0 0 0 0 0 0 0 583 Rohu 26 384 0 404 64 10 0 2496 4 0.2 0 0 0 14 0 4 46 388 1106 672 Saputo 38 263 0 424 43 25 6 579 1 0.0 0 37 0 0 0 0 0 0 0 316 Scorpion Fish 60 167 0 168 29 6 0 532 4 0.1 0 0 27 1 0 1 0 138 723 507 Shrimp 29 346 0 280 59 5 0 1458 2 0.0 0 0 0 0 0 5 90 405 1742 3258 Silver Fish 20 500 0 560 91 22 0 875 0 0.0 0 0 0 0 0 0 0 0 0 1125 Sole 38 267 0 269 47 9 0 277 3 0.1 0 0 0 5 0 1 115 133 965 347 Tapse (Dried) 50 200 0 686 117 24 0 3194 82 0.0 0 38 0 0 0 0 0 0 0 1190 Tengra (Fresh) 48 211 0 240 38 10 0 1320 6 0.0 0 0 91 11 0 2 46 114 680 733 Tengra (Dried) 60 167 0 425 92 7 0 1405 168 0.0 0 30 0 0 0 0 187 1572 110 2431 White Fish (Dried) 100 100 0 296 59 6 1 0 0 0.0 0 0 0 0 0 0 0 0 0 0 White Fish (Fresh) 30 333 0 400 60 10 17 1967 2 0.0 0 0 0 2 0 0 0 0 0 733 Tilapia 20 500 0 552 104 15 0 97 2 4.9 0 0 10 40 120 7 179 275 1703 1750 Pama croaker/poa fish 20 500 0 525 78 17 14 3 8 0.0 0 0 0 0 0 0 62 699 1354 36 99

Continued

, mg ,

vin_mg

Food Name / 100g_TkPrice Amount of food (g) Tk /100 _g Fibre, Energykcal , g Protein , Fat,g g CHO, Calcium , mg mg Iron, Thiamine Ribofla Vit C , mg Vitamin A, µg mgNiacin, Folic µg acid, Zinc, µg mgMagnesium Sodium, mg Potassium mg , Phosphorus mg Ganges river sprat (sweet 30 333 0 310 54 11 0 1630 8 0.1 0 0 127 12 23 10 87 127 450 1500 water, fresh, bony) Ganges river sprat(sweet 30 333 0 0 183 31 0 920 11 0.0 0 0 0 0 0 0 344 4292 120 4663 water, dry) Yellow tail mullet(marine, 50 200 0 0 139 20 0 866 4 0.0 0 0 0 0 0 0 250 763 122 5607 dry) Silver curp 12 855 0 1051 150 51 0 188 13 0.7 8 0 0 43 0 2 231 983 1923 1556 Spotted snake head 25 400 0 364 69 10 0 2496 6 0.2 0 0 764 8 0 4 140 272 980 1760 Chapila(Dry) 50 200 0 0 113 20 0 1141 7 0.0 0 0 0 0 0 0 209 2816 1850 3597 Mottlet nandus/mud perch 30 333 0 0 0 6 0 110 1 0.0 0 0 0 0 0 0 46 41 202 468 deboned Skipjack 40 250 0 0 62 6 0 6 4 0.0 0 0 0 0 0 0 28 328 1038 785 Rita 30 333 0 0 55 14 0 2 0 0.0 0 0 0 0 0 0 12 410 0 509 Indian potasi (Fresh) 50 200 0 0 0 11 0 86 1 0.0 0 0 0 0 0 0 52 445 93 806 Cotio(Fresh) 15 667 0 0 0 12 0 286 4 0.0 0 0 0 0 0 0 114 140 380 1771 Papper red loach/guntea 30 333 0 0 0 12 0 386 4 0.0 0 0 0 0 0 0 112 156 788 1473 loach(bony) Jamuna ailia (fresh, bony) 30 333 0 0 0 16 0 852 2 0.0 0 0 0 0 0 0 90 113 484 1033 Freshwater gar fish/niddle 25 400 0 0 0 6 0 102 1 0.0 0 0 0 0 0 0 134 288 856 1415 fish(fresh, bony) Giant snake head 20 500 0 0 0 28 0 231 2 0.0 0 0 0 0 0 0 129 159 972 1168 Giant river/fresh water 80 125 0 0 0 1 0 50 2 0.0 0 0 0 0 0 0 34 45 71 197 prawn(fresh, deboned) Reba(Fresh) 40 250 0 0 0 9 0 176 2 0.0 0 0 0 0 0 0 63 108 300 529 Yellow shrimp(fresh, 40 250 0 0 0 3 0 62 2 0.0 0 0 0 0 0 0 65 312 346 395 deboned)

100

Continued

, mg ,

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Food Name / 100g_TkPrice Amount of food (g) Tk /100 _g Fibre, Energykcal , g Protein , Fat,g g CHO, Calcium , mg mg Iron, Thia Riboflavin_mg Vit C , mg Vitamin A, µg mgNiacin, Folic µg acid, Zinc, µg mgMagnesium Sodium, mg Potassium mg , Phosphorus mg Yellow shrimp(fresh, 40 250 0 0 0 2 0 57 2 0.0 0 0 0 0 0 0 89 100 227 403 bony)) Yellow shrimp 50 200 0 0 130 9 0 1150 3 0.0 0 0 0 0 0 0 428 1397 1361 1679 Beef 28 361 0 373 75 8 0 15 7 0.2 1 0 0 36 25 13 55 188 1426 686 Beef (Buffalo) 23 442 0 419 86 8 0 53 7 0.2 1 0 0 27 35 9 142 235 1314 836 Chicken(deshi) 41 242 0 256 54 4 0 36 1 0.3 0 0 61 28 17 4 77 89 764 419 Duck 48 211 0 131 45 10 0 8 5 0.8 3 12 51 19 53 4 40 156 571 495 Goat 43 232 0 273 50 8 0 28 7 0.3 1 0 0 9 12 9 63 190 892 447 Liver (Goat) 33 308 0 329 64 9 0 52 0 0.0 0 0 43551 0 542 0 0 225 492 858 Liver (Mutton) 30 333 0 500 64 25 4 33 21 1.2 6 67 28509 59 627 0 0 0 0 1267 Lamb 34 294 0 575 54 40 0 37 6 0.5 0 2 26 12 17 12 55 121 401 441 Pigeon 100 100 0 137 23 5 0 12 0 0.0 0 0 0 0 0 0 0 0 0 290 Chicken (farm) 16 607 0 765 99 34 14 15 10 0.0 0 0 0 0 0 0 73 713 1220 40 Duck Egg 17 580 0 1092 78 83 8 377 14 0.7 2 0 2097 27 464 8 62 777 1287 1275 Hen Egg(deshi) 21 485 0 764 64 56 0 291 8 0.9 2 0 1030 16 242 10 51 653 469 1067 Hen Egg(Farm) 18 566 0 787 82 51 0 164 8 1.0 2 0 936 22 283 13 119 657 625 1246 Cheese 30 333 0 823 82 84 18 2633 1 0.1 2 0 683 22 133 12 73 1697 277 1380 Curd 10 1000 0 940 32 40 114 1030 1 0.5 2 10 320 8 90 5 220 510 1310 900 Milk(condensed) 25 400 0 704 28 49 38 1552 0 0.5 1 12 181 0 0 0 0 0 0 0 Powdered milk (skim, 41 241 0 502 91 2 120 3305 3 1.1 4 12 0 23 51 11 265 1049 3860 2306 cow) Powdered milk (whole, 39 256 0 1008 68 68 96 2453 2 0.8 4 27 609 17 97 9 235 934 3018 1939 cow) Whole milk (Buffalo) 6 1667 0 1450 63 125 78 3433 3 0.8 4 28 783 2 100 4 300 867 2967 4100 Whole milk (Cow) 6 1639 0 1034 51 61 70 1689 1 1.0 5 33 517 13 139 7 361 839 2150 1475 Whole milk (Goat) 8 1250 0 688 44 51 54 1900 3 0.6 1 14 400 13 13 4 175 625 2550 1388 Yogurt(Buffalo) 20 500 0 2105 73 156 103 3250 29 0.0 0 0 0 0 0 0 0 0 0 2100

101

Continued

, mg ,

Food Name / 100g_TkPrice Amount of foo (g) Tk /100 _g Fibre, Energykcal , g Protein , Fat,g g CHO, Calcium , mg mg Iron, Thiamine Riboflavin_mg Vit C , mg Vitamin A, µg mgNiacin, Folic µg acid, Zinc, µg mgMagnesium Sodium, mg Potassium mg , Phosphorus mg Yogurt (Cow) 20 500 0 2015 100 130 125 4780 0 1.2 2 30 746 2 0 0 0 0 0 3065 Butter 90 111 0 814 1 90 0 27 0 0.0 0 0 703 0 3 0 2 793 27 27 Soya bean oil 15 679 0 6114 0 679 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0 Ghee(Cow) 84 119 0 1069 0 119 0 1 0 0.0 0 0 764 0 0 0 0 2 1 0 Biscuit(Salted) 25 400 0 2136 25 130 218 0 0 0.0 0 0 0 0 0 0 0 0 0 0 Biscuit(Sweet) 30 333 8 1150 19 33 189 277 7 0.2 0 0 0 3 23 3 107 277 387 437 Horlicks 30 333 8 1150 19 33 189 277 7 0.2 0 0 0 3 23 3 107 277 387 437 Bread(Loaf) 150 67 0 163 6 1 33 12 1 0.1 0 0 0 0 0 0 0 0 0 0 Bread(White) 4 2857 6 7000 223 20 1483 314 31 2.0 0 0 0 0 0 0 0 0 0 0 Date juice 7 1538 0 4769 0 0 0 615 63 0.0 0 0 0 0 0 0 0 0 0 0 Honey 100 100 0 319 0 0 80 5 1 0.0 0 4 0 0 0 0 0 0 0 16 Jackfruit seed 29 345 6 459 23 1 89 172 5 0.9 0 38 7 0 0 0 0 0 0 334 Molasses 7 1350 0 5196 7 1 1287 81 4 0.0 1 0 0 0 0 0 0 54 13 148 Molasses (Date) 8 1220 4 4293 18 4 1045 159 5 0.0 0 0 0 0 0 4 183 390 902 585 Pappadom 25 400 0 1132 75 1 210 320 69 0.0 0 0 0 0 0 0 0 0 0 0 Sago 25 400 0 1404 1 1 348 40 5 0.0 0 0 0 0 0 0 0 0 0 40 Sugar 6 1675 0 6667 0 0 1667 0 0 0.0 0 0 0 0 0 0 0 0 0 0 Sugarcane juice 7 1538 0 508 11 0 115 123 17 0.6 0 0 0 0 0 0 154 108 385 92 Sugarcane juice(Soft 7 1538 0 508 11 0 115 123 17 0.6 0 0 0 0 0 0 154 108 385 92 drinks) Tea 7 1538 0 508 11 0 115 123 17 0.6 0 0 0 0 0 0 154 108 385 92 Coffee 7 1538 0 508 11 0 115 123 17 0.6 0 0 0 0 0 0 154 108 385 92 Water Chestnut(dry) 8 1250 0 4125 168 10 861 875 30 0.0 0 0 0 0.0 0 0 0 0 0 5500

102

A10: Vegetable calendar for Bangladesh from January to June

January February March April May June Cabbage, Cabbage , Amaranth (red leaf Amaranth(data), Amaranth(data), Amaranth(data), Carrot, Carrot, var) Amaranth (red leaf var.), Amaranth (red leaf var.), Amaranth (red leaf var.), Cauliflower, Cauliflower, Cabbage , Cabbage , Eggplant, Eggplant, Ole kopi, Ole kopi, Potato, Cauliflower, Eggplant, Cucumber, Cucumber, Potato, Prawal, Gima kolmee, Cucumber, Gima kolmee, Gimakolmee Radish, Radish, Pumpkin, Gimakolmee, Gourd(Ash), Gourd(Ash), Gourd(bitter), Spinach, Spinach, Eggplant, Gourd(Ash), Gourd(bitter), Gourd(Bottle), Tomato, Tomato, Cucumber, Gourd(Bottle), Gourd(bitter), Gourd(Small bitter) Gourd(Small bitter) Turnip, Broccoli, Gourd(Ash), Gourd(Small bitter) Gourd(Bottle), Green chilli, Indian Spinach, Cucumber, Gourd(Bottle), prawal, Gourd (Ridge), Gourd (Ridge), Gourd (Ridge), Eggplant, Turnip, Green chilli, Green chilli, Green chilli, Prawal, Green chilli, Green chilli, Lady‘s Finger, Kakrol, Kakrol, Kakrol, Cucumber, Indian Spinach, Broccoli, Lady`s Finger, Lady`s Finger, Lady`s Finger,, Gourd(Bottle), Carrot, Turnip, Prawal, prawal, Pumpkin, Bean, Eggplant, Spinach, Pumpkin, Pumpkin, Snake gourd, Lettuce, Pumpkin, Carrot, Broccoli, Snake gourd, Snake gourd , Papaya, Gourd(Bottle), Tomato, Carrot, Snake gourd , Yard long bean, Sitalau, Bean, Bean, Bean, Indian spinach, Indian spinach, Humming bird Lettuce, Potato Snake gourd , Kolmee, Kolmee, flower, Papaya, Amaranth(data), Potato, Papaya, Papaya, Moringa, Sitalau, Indian spinach, Indian spinach, Sitalau, Sitalau, Amaranth (red leaf Moringa, Kolmee, Kolmee, Moringa. Moringa, var.) Air potato, Moringa, Lettuce, Cowpea, Cowpea, Gourd(Small bitter), Peas(Green), Papaya, Moringa, Yam stem, Yam stem, Gourd(bitter), Motor shak, Lettuce, Papaya, Taro/Arum tubers, Water taro. Lady‘s finger, Onion Stalk, Air potato, Air potato, Water taro. Spinach, Lau shak, China shak, Sitalau, Sitalau. Marrow. Gima kolmee, Peas(Green), Bati shak, Ole kopi, Cowpea, Marrow. Motor shak, Beet, Peas(Green), Yam stem, Taro/Arum tubers Onion Stalk, Gourd(Small bitter), Motor shak, Arum tubers, China shak, Gourd(bitter), Onion Stalk, Water taro. Bati shak, Lady‘s finger, China shak, Marrow. Beet, Lau shak, Gourd(Small bitter), Drumstick, Broccoli. Amaranth (red leaf var.) Gourd(bitter), Jute plant tops. Lau shak, Radish, Bati shak, Beet, 103

A11: Vegetable calendar for Bangladesh from July to December

July August September October November December Amaranth (data), Amaranth (data), Amaranth (red leaf Bean, Cabbage, Amaranth (red leaf var.), Amaranth (red leaf Amaranth (red leaf var.), var.), Cabbage , Carrot , Bean, var.), Eggplant, Amaranth (data), Carrot , Cauliflower, Eggplant, Eggplant, Cucumber, Bean, Cauliflower, Tomato, Cabbage, Cucumber, Gourd(Ash), Eggplant, Ole kopi, Ole kopi, Cauliflower, Gourd(Ash), Gima kolmee, Cucumber, Potato, Potato, Cucumber, Gourd(bitter), Gourd(bitter), Gima kolmee, Radish, Radish, GimaKolmi, Gourd(Small bitter) Gourd(Small bitter) Gourd(Ash), Tomato, Broccoli, Gourd(Ash), Gourd(Bottle), Gourd(Bottle), Gourd(bitter), Broccoli, Turnip, Gourd(bitter), Gima kolmee, Gourd(Ridge), Gourd(Small bitter) Turnip, Spinach, Gourd(Small bitter), Gourd(Ridge), Indian spinach, Gourd(Bottle), Spinach, Radish , Gourd(Bottle), Indian spinach, Lady`s Finger, Gourd(Ridge), Radish, Carrot, Ole kopi, Lady`s Finger, Pumpkin, Indian spinach, Carrot, Eggplant, Potato, Pumpkin, Snake gourd, Potato, Eggplant, Cucumber, Pumpkin, Snake gourd, Tomato, Pumpkin, Cucumber, Gourd(Bottle), Tomato, Tomato, Kakrol, Spinach, Gourd(Bottle), Bean, Spinach, Kakrol, Yard long bean, Snake gourd, Yard long bean, Lettuce, Radish, Yard long bean, Kolmee, Kakrol, Lady`s Finger, Papaya, Carrot, Kolmee, Papaya, Yard long bean, Indian spinach, Sitalau, Snake gourd , Papaya, Sitalau, Lady`s Finger, Kolmee, Humming bird flower, Yard long bean, Sitalau, Moringa, Kolmee, Papaya, Moringa, Kolmee, Moringa, Prawal. Papaya, Lettuce, Peas(Green), Moringa, Prawal. Cowpea, Sitalau, Sitalau, Gourd(Small bitter), Lettuce, Cowpea, Yam stem, Moringa, Humming bird flower, Gourd(bitter), Indian spinach, Yam stem, Taro/Arum tubers, Prawal. Moringa. Lady‘s finger, Papaya, Taro/Arum tubers, Water taro, Yam stem, Peas(Green), Lau shak, Sitalau, Water taro, Marrow. Cowpea, Gourd(Small bitter), Radish, Humming bird flower, Marrow. Taro/Arum tubers, Gourd(bitter), Indian spinach, Broccoli, Water lily. Water taro, Amaranth (red leaf Amaranth (red leaf Turnip, Marrow. var.), var.), Peas(Green), Motor shak, Motor shak, Lady‘s finger, Onion Stalk, Onion Stalk, Lau shak, China shak, China shak, Amaranth (red leaf var.), Bati shak, Bati shak, Motor shak, Onion Stalk, Beet, Beet, China shak, Bati shak, 104 Coriander seed, Coriander seed, Beet, Coriander seed, Mint leaves. Mint leaves. Mint leaves. A12: Seasonal fruit calendar from January to June

January February March April May June

Boroi (Bitter Boroi (Bitter plum), Boroi (Bitter plum), Bullock‘s heart, Blackberry, Mango, plum), Wood apple, Wood apple, Wood apple, Jackfruit, Blackberry, Orange, Pomegranate, Water melon, Water melon, Pineapple(Joldhu Jackfruit, Water melon , Sapota, Carambola, Carambola, pi), Lichi, Melon, Melon, Rose apple, Rose apple, Lichi, Pineapple(Joldhupi), Pomegranate, Water melon, Tamarind, Passion fruit, Guava, Pineapple(Ghurasal), Amla, Carambola, Passion fruit, Phalsa, Monkey jack, Olive, Lime (Sweet), Rose apple, Mulberry, Bilimbi, Wax apple, Guava, Lemon, Tamarind, Fig, Litchi (Kalipuri), Cashew nut, Monkey jack, Banana, Banana, Melon, Mulberry, Karanda, Wax apple, Papaya, Papaya, Lemon, Fig, Phalsa, Cashew nut, Coconut, Coconut, River ebony, Melon, Bilimbi, Karonda, Carambola, Custard apple, Banana, Lemon, Melon (futi), Phalsa, Sapota, Elephants foot apple, Papaya, River ebony (Local), Lemon, Bilimbi, Custard apple, Dragon fruit, Coconut, Mango, Mango, Date palm, Sweet orange, Strawberry Sapota, Banana , Banana, Coconut, Dragon fruit, Sugarcane, Bullocks heart, Papaya, Papaya, Burmese grape, Tamarind, Custard apple, Coconut, Coconut, Pomegranate, Strawberry, Satkara, Custard apple, Bullocks heart, Melon (futi), Sugarcane. Elephants foot apple, Satkara, Custard apple, Lemon, Dragon fruit, Elephants foot apple, Satkara, Jamum, Strawberry. Date palm, Date palm. Almond, Wax apple, Cowa(Mangosteem), Strawberry. Banana, Papaya, Custard apple, Peach,

105

A13: Seasonal fruit calendar from July to December

July August September October November December Mango, Mango, Olive, Olive, Olive, Boroi (Bitter plum), Blackberry, Blackberry, Custard apple, Custard apple, Amla, Amla, Jackfruit, Jackfruit , Palmyara palm, Palmyara palm, Orange, Orange, Pineapple(Ghurasal) Pineapple Hogplum, Hogplum, Elephant‘s foot Elephant‘s foot , (Jauntkew), Passion fruit, Elephant‘s foot apple, apple, Pineapple(Jauntkew) Olive, Pummelo, apple, Fig, Pomegranate, , Custard apple, Lemon, Indian dellenia, Sweet orange, Sweet orange, Olive, Hogplum, Flacouritia, Fig, Lime (Sweet), Lime (Sweet), Hogplum, Palmyara palm, Stargareberry, Lemon, Satkara, Satkara, Karanda, Monkey jack, Longan, Flacouritia, Indian dellenia, Banana, Monkey jack, Wax apple, Pears, Velvety apple, Papaya, Papaya, Wax apple, Karanda, Grape, Papaya, Banana, Coconut, Guava, Guava, Banana, Banana, Coconut, Carambola, Phalsa, Passion fruit, Papaya, Coconut, Carambola, Custard apple, Bilimbi, Bilimbi, Coconut, Carambola, Pummelo, Olive, Date palm, Pummelo, Indian dellenia, Pummelo, Lemon, Mandarin, Coconut, Lemon, Karanda. Amla. Custard apple, Dragon fruit, Burmese grape, Stargareberry, Strawberry. Strawberry Pomegranate, Grape, Pummelo, Banana, Lemon, Papaya, Stargareberry, Coconut, Jamum, Jamum, Almond, Indian dellenia, Cowa Burmese grape, (Mangosteem), Rambutan, Papaya, Daophal. Lichi, Sugar cane Banana,Custard apple,Rambutan, 106

A14: Menu Plan

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Tk 114

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121

122

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126

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130

A15: Scientific name of all the available Bangladeshi foods

Food English Name Scientific Name Food English Name Scientific Name Code Code 101 Barley (whole) Hordeum vulgare 212 Red gram/ arahar(split) Cajanus cajan 102 Maize/ corn(immature) Zea mays 213 Soybean Glycine max merr. 103 Maize/ (mature) Zea mays 214 Horse gram Dolichos biflorus 104 Millet (French) Pennisetum miliaceum 215 Moth beans Phaseolus aconitisolius 105 Millet (pearl) Pennisetum glaucum 216 Rajmah Phaseolus vulgaris 106 Rice (fried paddy) Oryza sativa 301 Agathi Sesbania grandiflora 107 Rice husk/ bran Oryza sativa 302 Amaranth (data) leaves Amaranthus gangeticus 108 Rice parboiled (husked) Oryza sativa 303 Amaranth leaves(tender) Amaranthus gangeticus 109 Rice parboiled (milled) Oryza sativa 304 Amaranth (red leaf var) Amaranthus gangeticus 110 Rice sunned (husked) Oryza sativa 305 Amaranth (spiney) Amaranthus spinosus 111 Rice sunned (milled) Oryza sativa 306 Bathua leaves Chenopodium album 112 Rice (flattened) Oryza sativa 307 Beet leaves Beat vulgaris 113 Rice (puffed) Oryza sativa 308 Bottle gourd leaves Lagenaria vulgaris 114 Semolina Triticum aestivum 309 Cabbage Brassica oleracea var capitata 115 Sorghum Sorghum bicolor 310 Carrot leaves Daucus carota 116 Vermicelli Triticum aestivum 311 Cauuflower leaves Brassica oleracea var. 117 Wheat (whole) Triticum aestivum 312 Celery leaves Apium graveolens var. Dulce 118 Wheat flour (coarse) Triticum aestivum 313 Chukai leaves 119 Wheat flour(refined) Triticum aestivum 314 Coriander leaves Coriandrum sativum 120 Ragi Eleusine coracana 315 Cowpea leaves Vigna catjang 121 Wheat germ Triticum aestibum 316 Drumstick leaves Morinba oleifera 122 Oatmeal Avenabyzantina 317 Fenugreek leaves Trigonella foenum graecum 201 Bean (field) Phaseolus vulgaris 318 Folwal leaves 202 Bengal gram(whole) Cicer arietinum 319 Gram leaves Cicer arietinum 203 Bengal gram(split) Cicer arietinum 320 Helencha leaves Enhydra fluctuans 204 Bengal gram(fried) Cicer arietinum 321 Indian spinach Spinacia oleracea 205 Black gram(split) Phaseolus mungo roxb. 322 Jute plant tops Corchorus capsularis 206 Green gram(whole) Phaseolus aureus roxb. 323 Khesari leaves Lathyrus sativa 207 Green gram(split) Phaseolus aureus roxb. 324 Kolmee leaves Ipomoea reptans 208 Khesari dal Latyyrus sativus 325 Lettuce Lactuca sativa 209 Lentils Lens esculenta 326 Mesta leaves Polygonum chinense 210 Peas dried/split Pisum sativum 327 Mustard leaves Brassica capestris var. Sarason 211 Peas fried Pisum sativum 328 Neem leaves (green) Azadirachta indica

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Food English Name Scientific Name Food English Name Scientific Name Code Code 329 Neem leaves, yellow (ripe) Azadirachta indica 365 Solanum tuberosum 330 Potato leaves 366 331 Mint leaves Mentha spicata 367 Blue commelina/venus bath Commelina benghalensis 332 Pumpkin leaves Cucurbita maxima 368 Edible fern Diplazium esculentum 333 Punornova leaves 369 Lawn marshpenny wort Hydrocotyle sibthorpioides 334 Radish leaves Raphanus sativus 370 335 Safflower leaves Carthamus tinctorius 401 Beet root Beta vulgaris 336 Soybean leaves Glycine max merr. 402 Carrot Daucus carota sativus 337 Spinach Spinacia oleracea 403 Garlic Allium sativum 338 Spinach sour Rumex acetosa 404 Ground potato Solanum tuberosum 339 Sweet potato leaves Ipomoea batatas 405 Ole kopi (german turnip) Brassica oleracea 340 Tamarind leaves (green) Tamarindus Indica 406 Onion Allium cepa 341 Tamarind leaves (dry) Tamarindus Indica 407 Potato Solanum tuberosum 342 Taro/arum leaves (dried) Colocasia esculenta 408 Radish Raphanus sativus 343 Taro/black arum leaves Arum palestinum 409 Sweet potato Ipomoea batatas 344 Taro/green arum leaves Peltandravirginica 410 Taro/arum Colocasia esculenta

345 Thankuni leaves Centella japonica 411 Taro/arum tubers Amorphophallus paeoniifolius 346 Turnip leaves Brassica rapa 412 Turnip Brassica rapa 347 Celery stalks Apium graveolens 413 Yam(elephant) Dioscorea elephantipes 348 Curry leaves Murraya keonigll 414 Yam(wild) Dioscorea villosa 349 Ipomoea stems Ipomoea reptans 415 Moor sanga Butea frondosa 350 Kuppameni Acalypha indica 416 Water lilt(red) Nymphea nouchali 351 Susni sag Marsilea minuta 501 Amaranth (data) stem Amaranthus mangostanus l 352 Bitter gourd Momordica charantia 502 Aubergine/eggplant Solanum melongena 353 (Sabarang) Ajuga macrosperma 503 Bean Phaseolus lunatus 354 Roselle Hibiscus sabdariffa 504 Bean (broad) Vicia faba 355 (Lemon pata) Premna obtusifolia 505 Bean (French) Phaseolus vulgaris 356 India ivy-rue Xanthoxylum rhetsa 506 Bean (immature) Phaseolus lunatus 357 (Ojam shak) Spilanthes calva 507 Bean (red) Phaseolus Vulgaris 358 (Ghanda batali) Paederia foetida 508 Cabbage Brassica oleracea var capitata 359 (Orai balai) Premna esculenta 509 Cauliflower Brassica oleracea var. botrytis 360 Purslane Portulaca oleracea 510 Chilli (green) Capsicum annuum. 361 Yellow saraca Saraca thaipingensis 511 Cow pea Vigna unguiculata 362 Mollugo Glinus Oppositifolius 512 Cucumber Cucumis sativus 363 Wild coriander Eryngium foetidum 513 Drumstick/horserradish Moringa oleifera. 364 Kassava Manihot esculenta 514 Drumstick flower Moringa oleifera

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Food English Name Scientific Name Food English Name Scientific Name Code Code 515 Fig (red) Stenoderma rufum darioi 552 Chaltha Dillania indica 516 Folwal/potol/parwar Trichosanthes dioica 553 Lotus seeds(green) Nelumbium nelumbo 517 Gourd (ash) Benincasa hispida 554 Mashroom Agaricus bisporus 518 Gourd(bitter) Momordica Charantia L. 555 Sea weed(fresh) 519 Gourd (bottle) Lagenaria siceraria 556 Sea weed(dry) 520 Gourd (ridge) Luffa acutangula 557 Silk cotton flowers Bombax malabaricum 521 Gourd (small bitter) Momordica charantia 558 Water lily flower Nymphea nouchali 522 Gourd (snake) Trichosanthes cucumerina 559 Pea eggplant Solanum spinosa 523 Gourd (sweet)/pumpkin Cucurbita maxima 560 Solanum Solanum virginianum 524 Gram (red, unripe) Artocarpus camansi 561 Sigon data Lasia spinosa 525 Jackfruit (immature) Artocarpus heterophyllus 562 Yam Dioscorea pentaphylla 526 KAKROL(Teasle gourd) Momordica dioica 563 Banchatta Dillenia pentagyna 527 Kolmee 564 Fekong Alpinia nigra 528 Lady's finger/okra Abelmoschus esculentus 565 Agaricua sp 529 Mango (green/immature Mangifera foetida 566 Agaricus sp 530 Marrow 567 Red silk/cotton tree Bombax ceiba 531 Onion& garlic stalk Allium cepa & Allium sativum 568 (Seng e tur/senge/thorai) Amomum corymospachyum 532 Papaya (green/immature) Carica papaya 569 (Betagi) 533 Peas (green) Pisum sativum 570 (Seon sak/gandri) Alpinia sp 534 Plantain Musa paradisiaca 571 Berry bamboo Melocanna baccifera 535 Plantain flower Plantago major 572 (Maira bokong) 536 Plantain stem Musa sapientum 573 (Laigrao bokong) 537 Pumpkin flower Cucurbita pepo 601 Cashew nuts Anacardium occidentale 538 Spinach stalks Spinacia oleracea 602 Chilgoza (nut) Pinus gerardiana 539 Tomato (green) Solanum lycopersicum 603 Coconut (dry) Cocos nucifera L. 540 Waterlily stem (red) Nymphaea odorata 604 Coconut (mature) Cocos nucifera L. 541 Waterlily stem (white) Nymphaea alba 605 Groundnut/ peanut Arachis hypogaea 542 Yam stem Dioscorea villosa 606 Groundnut/ peanut (fried) Arachis hypogaea 543 Colocasia stem Colocasia antiquorum 607 Linseed Linum usitatissimum 544 Karonda(fresh) Carissa carandas 608 Mustard Brassica nigra 545 Karonda (dry) Carissa carandas 609 Nuts 546 Kovai Coccinia cordifolia 610 Oils mustard etc Brassica nigra 547 Lokooch Artocarpus lakoocha 611 Pistachio Pistacia vera 548 Leeks Allium porrum 612 Sunflower seeds Helianthus annuus 549 Lotus stem(dry) Nelumbium nelumbo 613 Sesame Sesamum indicum 550 Sundakai Solanum torvum 614 Walnut Juglans regia 551 Sword beans Canavalia gladista 615 Niger seeds Guizotia abyssinica

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Continued

Food English Name Scientific Name Food English Name Scientific Name Code Code 616 Piyal seeds Buchanania latifolia 811 Breadfruit Anacardium occidentale 617 Sunflower seeds Carthanus tinctorius 812 Bullocks heart Annona reticulata 618 Jangli badam Sterculia foetida 813 Custard apple Annona squamosa 619 Oysternut Telfairea pedata 814 Coconut milk Cocos nucifera L. 620 Roselle seed 815 Dates Phoenix sylvestris 621 Tamarind seed kernel(roasted) Tanarindus indicus 816 Dates (dry) Phoenix sylvestris 622 Okra(whole seed) Abelmoschus esculentus 817 Fig (ripe) Ficus carica 623 Okra (kernel) Abelmoschus esculentus 818 Guava Psidium guajava 701 Cardamom Elettaria cardamomum 819 Grapes Vitis vinifera 702 Chilli, red (dry) Capsicum annum 820 Jackfruit (ripe) Artocarpus heterophyllus 703 Cloves (dry) Syzygium aromaticum 821 Kheera Cucumis sativus 704 Coriander seed Coriandrum sativum 822 Kodobele (immature) Feronia limonia 705 Cumin seed Cuminum cyminum 823 Kodobele (ripe) Feronia limonia 706 Fenugreek Trigonella foenum-graecum 824 Kusum fruit 707 Ginger Zingiber officinale 825 Lemon Citrus limon 708 Lemon/ lime peel Citrus limon 826 Lemon (sweet) 709 Mace Semen Myristicae 827 Lichis Litchi chinensis 710 Mixed spices 828 Lime Citrus aurantifolia 711 Mixed spices (hot) 829 Lime (sweet) Citrus limettioides 712 Nutmeg Myristica 830 Mahua (ripe) 713 Omum Trachyspermum ammi 831 Mango (ripe) Mangifera indica 714 Pepper (black) Piper nigrum 832 Melon Cucumis melo 715 Turmeric Curcuma longa 833 Neem fruit 716 Arisithippili Pimpella anisum 834 Olive (wild) Elaeocarpus floribundus 717 Asafoetida Ferula foetida 835 Orange 718 Mango powder Mangifera indica 836 Orange juice 719 Nutmeg(rind) Myristica fragrans 837 Orange/mandarin 801 Ambada (hog plum) Spondias mombin 838 Palm, palmyra (green) Borassus flabellifer 802 Amla Phyllanthus emblica 839 Palm (ripe) 803 Apple Malus domestica 840 Papeya (ripe) Carica papaya 804 Apricot (boiled) Prunus armeniaca 841 Pears 805 Appricot (dry) Prunus armeniaca 842 Phalsa Grewia asiatica 806 Bakul flower Mimusops elengi 843 Pineapple Ananus comosus 807 Banana Musa 844 Pineapple (wild var) 808 Bilimbi Averrhoa bilimbi 845 Pomegranate juice 809 Backberry (indian) Syzygium cumini 846 Pomegranate Punica granatum 810 Boroi (bitter plum) Oemleria cerasiformis 847 Pommelo (red)

134

Food English Name Scientific Name Food English Name Scientific Name Code Code 848 Rose apple Syzygium jambose 915 Bream (sea, fresh) Cybium commersoni/Scomberomorus commerson Tamarind(immatur Tamarindus indica Cybium 916 Bream (sea, dried) 849 e) Commersoni/scomberomorus commerson 850 Tamarind (pulp) Tamarindus indica 917 Butter fish Callichorus pabo/ompok pabo 851 Tetul (bilati) Tamarindus indica 918 Carp Katla katla/catla catla 852 Tomato (ripe) Solanum lycopersicum 919 Cat fish Arius sona 853 Wood apple Aegle marmelos 920 Chela (fresh) Chela phulo 854 Watermelon Citrullus vulgaris 921 Chela (dried) Chela phulo 855 Black berry(deshi) Syzygium cumini 922 Climbing fish (koi) Anabus testudineus/anabas testudineus 856 Cherries(red) Prunus cerasus 923 Crabs Paratephusa spinigera 857 Lichi(bastard) Nephelium litchi 924 Dragon fish Pangasius pangasius 858 Melon(musk) Cucumis melo 925 Eel fish Mastocembellus armatus 859 Peaches Amygdalis persica 926 Fesha fish (fresh) Setipinna phasa 860 Persimon Doispyros kaki 927 Fesha fish (dried) Setipinna phasa 861 Plum Prunus domestica 928 Fishmeal 862 Raisins Vitis vinifera 929 Flat fish Notopterus chitala/chitala chitala 863 Strawberry Fragaria vesca 930 Folui Notopterus notopterus Doispyros embryopteris Fry (very small Barbus spp/puntius chola 864 Gab 931 fresh) 865 Monkey jack Artocarpus lakoocha 932 Gahira fish Clupisoma garua

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866 Burmese grape Pirardia sapida 933 Gura fish 867 Wild melon Cumis melo 934 Hilsha fish Clupea ilisha 868 (Roshko) Syzygium balsameum 935 Hilsha (salted) Clupea ilisha 869 Bead tree Elaeocarpus angustifolius 936 Khalshe fish Colisa fasciata 901 Aire fish Mystus seenghala 937 Lota fish Ophiocephalus punctatus 902 Bacha fish Eutropiichthys vacha/murius 938 Magur Clarius batrachus 903 Bata fish Labeo bata /ariza 939 Magur (dried) Clarius batrachus 904 Bele fish/poa Glassogobius giuris 940 Mola fish Amblypharyngodon mola Botia dayi Cirrhinus mrigala/ cirrhinus cirrhosus 906 Betrongi fish 941 Mrigal 907 Bhangon (fresh) Labeo bata/boga 942 Mullet Mugil oeur 908 Bhangon (dried) Labeo bata/boga 943 Parshee fish (dried) Mugil parsia/mugil cephalus Bhangon Labeo bata/boga Mugil parsia/mugil cephalus 909 (powdered) 944 Parshee fish (fresh) 910 Bhetki (fresh) Lates calcarifer 945 Pata fish (dried) Solea ovate 911 Bhetki (dried) Lates calcarifer 946 Pomfret (black) Formio miger/parastromateus niger 912 Boal Wallago attu 947 Pomefret (white) Stromateus sinensis/pampus chinensis 913 Blackfish/baoh Labeo calbasu 948 Pomfret ((small) Chanda nama 914 Boicha fish Colisa lalia 949 Prawns whole (dried) Leadrites celebensis

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Continued

Food English Name Scientific Name Food English Name Scientific Name Code Code Leadrites celebensis Chapila/indian river shad(dry, Godusia chapra 975 950 Prawn (dry) bony) 951 Pumplate (sea fish) 976 Golden/red snapper Chrysophrys auratus 952 Ribbon fish Trichiurus spp/ Trichiurus lepturus 977 White grunter Pomadays hasta 953 Ribbon fish (dried) Trichiurus spp/. Trichiurus lepturus 978 Hard tail torpedo trevally Megalaspis cordyla 954 Rohu Labeo rohita 979 Tripple tail Lobotes surinamensis Solonia silondia Mottlet nandus/mud Nandus nandus 955 Salmon 980 perch(deboned) 956 Sarputi Barbus sarana/Puntius sarana 981 Skipjack Euthynnus pelamis 957 Scorpion fish Saccobranchus fossilis/Hetero pneustes fossilis 982 Boggut labeo Labeo boggut 958 Shark Carcharias spp./ Carcharias acutus 983 Rita Rita rita Penaeus latisulcatus Small head hair tail/ribbon Leptura canhus 959 Shrimp 984 fish(dry) Ailia coilia Russell`s smooth-back Brachypleura nova zeelandlac 960 Silver fish 985 herring(dry) 961 Sole Ophiocephalus striatus/Channa striatus 986 Indian potashi (bony) Pseudeutropius atherinoides 962 Tapse (dried) Polynemus paradiseus 987 Cotio(bony) Rohtee cotio Mystus bittafus Papperred loach/guntea Lepidocephalichthys guntea 963 Tengra (fresh) 988 loach(bony) 964 Tengra (dried) Mystus bittafus 989 Jamuna ailia(fresh,bony) Ailiichthys punctata Gonialosa manminna Freshwater gar fish/niddle Xenentodon cancila 965 White fish (dried) 990 fish(fresh, bony) White fish/stripled Gonialosa manminna Large lazor belly Chela bacaila 966 gourami (fresh) 991 minnow(fresh, bony) Tilapia/mozambique Orechromis mossambicus Channamarulius 967 telapia 992 Giant snake head Otolithoides pama Giant river/fresh water Macrobrachium rosenbergii 968 Pama croaker/poa fish 993 prawn(fresh. Deboned) Ganges river sprat(sweet Corica soborna Crossocheilus latius 969 water, fresh, bony) 994 Reba(fresh, deboned) Ganges river sprat(sweet Corica soborna Metapenaeus brevicornis 970 water, dry) 995 Yellow shrimp(fresh, deboned) Yellow tail mullet Sicamugil cascasia Metapenaeus brevicornis 971 (marine, shukna) 996 Yellow shrimp(fresh, bony)) 972 Silver carp Hypophthalmichthys molitrix 997 Yellow shrimp Metapenaeus brevicornis 973 Spotted snake head Channa puncpatus 998 Kucha Amphipnous cuchia Chapila/indian river Gadusia chapra Bos Taurus/Beef cattle 1001 Beef 974 shad(fresh ,bony) 137

Continued

Food English Name Scientific Name Food English Name Scientific Name Code Code 1002 Beef (buffalo) Bulbus bubalis 1304 Ghee (buffalo) 1003 Chicken Gallus bankiva murghi 1305 Ghee (cow) 1004 Duck Anas platyrhyncha 1306 Ghee (vegetable) 1005 Goat Capra hyrchusb 1401 Betel/areca nut Areca catechu 1006 Liver (goat) 1402 Betel leves Piper betel 1007 Liver (mutton) 1403 Biscuit (salted) 1008 Mutton (lamb) 1404 Biscuit (sweet) 1009 Pigeon Columba livia intermedia 1405 Bread (brown) Sus cristatus wagner/Sus serofa 1010 Pork domesticus 1406 Bread (loaf) 1011 Snails (small) Viviparus bengalensis 1407 Bread (white) 1012 Snails (large) Pila globosa 1408 Coconut milk Cocos nucifera 1013 Turtle 1409 Date juice Phoenis dactylifera/Phoenis sylvestris 1014 Chicken (farm) Gallus bankiva murgi 1410 Honey 1015 Yeast dried(deshi) Terula saccharomyces 1411 Jackfruit seed Artocarpus heterophyllus 1016 Yeast dried (food) Terula saccharomyces 1412 Lotus seeds (dry) Nelumbium nelumbo/Nelumbo nucifera 1101 Duck egg Anas platyrhyncha 1413 Lotus seeds (ripe) Nelumbium nelumbo/Nelumbo nucifera 1102 Hen egg Gallus bankiva murghi 1414 Lotus seed (green) Nelumbium nelumbo/Nelumbo nucifera 1201 Buffalo milk solids 1415 Mahua flower Bassia latifolia/Madhuca indica 1202 Butter-milk 1416 Makhana Euvale ferox/Euryale ferox 1203 Cheese 1417 Molassea Saccharum officinarum 1204 Cow milk solids 1418 Molassed (date) Phoenis dactylifera/Phoenis sylvestris 1205 Curd 1419 Oil cakes (groundnut) Arachis hypogeal 1206 Human/breast milk 1420 Pappadom 1207 Milk (condensed) 1421 Pickles 1208 Powdered milk (skim, cow) 1422 Popy seed Papaver somniferum 1209 Powdered milk (whole, cow) 1423 Pumpkin/sweet gourd seed Cucurbita maxima 1210 Skim-milk (liquid) 1424 Sago Metroxylon spp./Metroxylon sagu 1211 Whole milk (buffalo) 1425 Sugar 1212 Whole milk (cow) 1426 Sugar candy 1213 Whole milk (goat) 1427 Sugar cane juice Saccharum officinarum 1214 Yogurt (buffalo) 1428 Tamarind seed (dried) Tamarindus indica 5 Yougurt (buff, skim mik) 1429 Toddy (fermented)

138

A 16: Selected photographs of DDP activities

Photographs of the First Stakeholder Meeting, Venue: BIRDEM, Date July 16, 2012

From left: Prof Nazmun Nahar, DG, BIRDEM, Dr Lalita Bhattacharjee, FAO, Dr MA Mannan, FAO, Ms Shaheen Participants of the meeting Ahmed, Prof Subhagata Choudhury, BIRDEM, Prof Aminul Haque Bhuyan, INFS

From left: Mr Mostafa Faruk Al Banna, Ministry of From left: Dr Monirul Islam, BARC, Prof Nazrul Islam Food, Dr Nur Ahamed Khondaker, FAO Khan, INFS, Prof Sk Nazrul Islam, INFS, Prof SM Keramat Ali, Ex Director, INFS, Dr Quamrun Nahar, BIRDEM and PI, DDP

139

Prof. Aminul Haque Bhuyan, Director of INFS Mr Mostafa Faruq Al Banna, Associate Research discussing about DDP Director, Ministry of Food expressing his opinion

Selected Photographs of Second Stakeholder Meeting, Venue: BIRDEM, Date: April 03, 2013

Prof Nazmun Nahar, DG, BIRDEM, Dr Lalita Bhattacharjee, Nutrition Expert, FAO, Prof Subhagata Choudhury, BIRDEM, Prof SM Keramat Ali, Ex Director, INFS, MA Wahed, Consultant, Health, Nutrition and Management, Dhaka 140

From left: Dr Quamrun Nahar, BIRDEM & PI: DDP project, SS Saleheen Sultana, Home Economics College, Shaheen Ahmed, ex Principal, Home Economics College, Dr MA Mannan, FAO, Mr Mostafa Faruk Al Banna, Ministry of Food, Dr Nur Ahamed Khondaker, FAO, Prof Nazmun Nahar, DG, BIRDEM, Dr Lalita Bhattacharjee, FAO, Prof Subhagata Choudhury, BIRDEM

From left: MA Wahed, Ms Taznin, WFP, Ms Shamsunnahar, BIRDEM,

Ms Aktarun Nahar, BIRDEM, Ms Khaleda Khatun, BIRDEM, Mr

Abdullah, WFP, Dr Shakhaoat Hossain, BIRDEM

141

Selected Photographs of Third Stakeholder Meeting, Venue: BIRDEM, Date: April 16, 2013

After presentation of PI, Prof Ekhlasur Dr Quamrun Nahar, PI of the project answering Rahman, Director of IPHN, discusses about the question of a stakeholder. the guideline.

Prof SM Keramat Ali, discussing about Ms Jillian Waid of HKI discussing about the the guidelines guidelines

142

Dr SK Roy, a famous former Scientist of ICDDR,B explaining the importance of the guideline

Data Collection at Khagrachari and Rangamati District for HDDS calculation

Dr Quamrun Nahar and Dr Omar Faruque interviewing the tribal peoples for the DDS data

143

Ms Maksuda Parvin is collecting data from a tribal Local people Processing Dhekisak to cook at his home premises people

Ms Shamsun Nahar, Research Associate of the project collecting data A research Fellow collecting data from a tribal woman

144

ISBN

978-984-33-7491-2

BIRDEM, Dhaka, June 2013