Sitakunda Upazila Chittagong District Bangladesh

Home , Chittagong District, Mirsharai Upazila, Pahartali Thana, Sandwip Upazila, Sitakunda, Sitakunda Upazila

Integrated SMART Survey Nutrition, Care Practices, Food Security and Livelihoods, Water Sanitation and Hygiene

January 2018

Funded By

Acknowledgement

Action Against Hunger conducted Baseline Integrated SMART Nutrition survey in Sitakunda Upazila in collaboration with Institute of Public Health Nutrition (IPHN).

Action Against Hunger would like to acknowledge and express great appreciation to the following organizations, communities and individuals for their contribution and support to carry out SMART survey:

 District Civil Surgeon and Upazila Health and Family Planning Officer for their assistance for successful implementation of the survey in Sitakunda Upazila.

 Action Against Hunger-France for provision of emergency response funding to implement the Integrated SMART survey as well as technical support.

 Leonie Toroitich-van Mil, Health and Nutrition Head of department of Action Against Hunger- Bangladesh for her technical support.

 Mohammad Lalan Miah, Survey Manager for executing the survey, developing the survey protocol, providing training, guidance and support to the survey teams as well as the data analysis and writing the final survey report.

 Action Against Hunger Cox’s Bazar for their logistical support and survey financial management.

 Mothers, Fathers, Caregivers and children who took part in the assessment during data collection.

Action Against Hunger would like to acknowledge the community representatives and community people who have actively participated in the survey process for successful completion of the survey.

Finally, Action Against Hunger is thankful to all of the surveyors, supervisor and Survey Manager for their tremendous efforts to successfully complete the survey in Sitakunda Upazila.

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Acronyms ACF Action Contre La Faim ‖ Action Against Hunger ARI Acute Respiratory Infection BBS Bangladesh Bureau of Statistics BDHS Bangladesh Demographic and Health Survey CI Confidence Interval CMAM Community Based Management of Acute Malnutrition DPHE Department of Public Health Engineering ENA Emergency Nutrition Assessment EPI Expanded Program on Immunization FAO Food and Agriculture Organization FSL Food Security and Livelihoods GAM Global Acute Malnutrition HAZ Height-for-Age z-score HDDS Household Dietary Diversity Score HFA Health Facility Assessment HH Household HYSAWA Hygiene Sanitation and Water Supply IDDS Individual Dietary Diversity Score IPC Integrated Food Security Phase Classification IPHN Institute of Public Health Nutrition IYCF Infant and Young Child Feeding MAM Moderate Acute Malnutrition MEB Minimum Expenditure Basket MHCP Mental Health and Care Practice MoHFW Ministry of Health and Family Welfare MUAC Mid-Upper-Arm-Circumference. NGO Non-Governmental Organization ODF Open Defecation Faeces OTP Outpatient Therapeutic Program PLW Pregnant and Lactating Women PPS Probability Proportion to Size rCSI Reduced Coping Strategy Index SAM Severe Acute Malnutrition SD Standard Deviation SFP Supplementary Feeding Program SMART Standardized Monitoring and Assessment of Relief and Transition U5 Under Five WaSH Water, Sanitation and Hygiene WAZ Weight-for-Age Z-score WFH Weight For Height WFP World Food Programme WHO World Health Organization WHZ Weight-for-Height Z-score

Table of Contents Acknowledgement ...... 2 Acronyms ...... 3 Executive Summary ...... 6 1. Introduction ...... 11 1.1Survey Objectives ...... 12 2. Methodology ...... 12 2.1 Survey Area ...... 12 2.2 Type of survey ...... 13 2.3 Sample size ...... 13 2.4 Survey Target Population ...... 13 2.5 Sampling procedure: selecting clusters ...... 14 2.6 Sampling procedure: selecting households and children ...... 14 2.7 Case definitions and inclusion criteria ...... 15 2.8 Questionnaire, Training and supervision ...... 17 2.9 Data Entry, Data management and Analysis ...... 18 3. Results ...... 19 3.1 Household and family composition ...... 19 3.2 Age and Sex Ratio in Children 6-59 Months ...... 19 3.3 Acute Malnutrition (Wasting) based on WHZ: ...... 20 3.4 Acute Malnutrition Based on MUAC ...... 21 3.5 Underweight ...... 22 3.6 Chronic Malnutrition/ Stunting ...... 23 3.7 Childhood Morbidity ...... 25 3.8 Child care practices including Infant and Young Child Feeding (IYCF) ...... 26 3.9 Food Security and Livelihoods ...... 29 3.10 Water and Sanitation ...... 35 4. Discussion and Conclusion ...... 38 4.1 Nutrition and Health ...... 38 4.2 Child Care including Infant and Young Child Feeding (IYCF) Practices ...... 39 4.3 Food Security and Livelihoods ...... 41 4.4 Water, Sanitation and Hygiene ...... 42 5. Limitation and Bias ...... 43 6. Ethical Considerations ...... 43 7. Recommendations and priorities ...... 43 8. Appendices ...... 45 Appendix 1: Plausibility Report ...... 45 Appendix 2: Assignment of Clusters ...... 57 Appendix 3: Evaluation of enumerators (Standardisation test results) ...... 58 Appendix 4: Questionnaire ...... 60 Appendix 5: Event Calender ...... 71

List of Table Table 1: Summary findings of Nutrition and Health indicators based on WHO 2006 growth Standards ...... 7 Table 2: Summary findings of IYCF practices ...... 7 Table 3: Summary findings of Food Security and Livelihoods (FSL) ...... 8 Table 4: Summary findings of Water Sanitation and Hygiene (WASH) ...... 8 Table 5: Details of administrative areas with population ...... 12 Table 6: Sampling parameters-Sitakunda Upazila...... 13 Table 7: Details of proposed and actual sample size achieved ...... 15 Table 8: Calculation of households’ coverage/day/cluster ...... 15 Table 9: Case definitions of Acute Malnutrition, Stunting and Underweight used for analysis ...... 16 Table 10: Case definition for IYCF, morbidity, vitamin A and measles coverage...... 16 Table 11: Case definitions of public health significance level ...... 17 Table 12: IPC classification Global Acute Malnutrition by MUAC ...... 17 Table 13: Thresholds level for Household Dietary Diversity (HDD)...... 17 Table 14: Thresholds level for household Coping Strategy Index (CSI)...... 17 Table 15: Thresholds level for Minimum Dietary Diversity (MDD-W) for women (15-49yrs) ...... 17 Table 16: Overall data quality from plausibility check ...... 18 Table 17: Household and family composition ...... 19 Table 18: Age and sex ratio ...... 19 Table 19: Prevalence of Acute Malnutrition by WHZ score ...... 20 Table 20: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or edema ...... 20 Table 21: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex ...... 21 Table 22: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex ...... 22 Table 23: Prevalence of underweight based on weight-for-age z-scores by sex ...... 23 Table 24: Prevalence of underweight based on weight-for-age z-scores by age...... 23 Table 25: Prevalence of stunting based on height-for-age z-scores and by sex...... 23 Table 26: Prevalence of stunting by age based on height-for-age z-scores ...... 24 Table 27: Mean z-scores, Design Effects and excluded subjects ...... 24 Table 29: Prevalence of childhood (6-59 Months) morbidities...... 25 Table 30: Summary Findings of IYCF practices ...... 26 Table 31: Consumption patterns of different foods groups in the previous day ...... 32 Table 32: Washing behaviour of storage container ...... 36 Table 33: Category of sanitary latrines by percentage of households ...... 37 Table 34: Disposal of children's feces percentage of households ...... 37 Table 35: Hand washing behaviour with soap ...... 37

Table of Figure Figure 1: Maps of SitakundaUpazila ...... 11 Figure 2: WHZ Gaussian Curve ...... 21 Figure 3: MUAC by Age (Combine)...... 22 Figure 4: HAZ Gaussian Curve ...... 24 Figure 5: Treatment received modalities ...... 25 Figure 6: Diet in the previous day (6-23 months) ...... 27 Figure 7: Difficulties or challenges faced during childcare ...... 28 Figure 8: Perception of caregiver for child’s optimum growth and development ...... 28 Figure 9: The source of income of the surveyed households ...... 29 Figure 10: Income category of the households ...... 29 Figure 11: Food Source ...... 30 Figure 12: Dietary Diversity Status ...... 30 Figure 13: Dietary Diversity in Different Income Groups...... 31 Figure 14 : Status of women dietary diversity ...... 32 Figure 15: Consumption patterns of food groups based on nutrient density...... 33 Figure 16: Overall coping strategies...... 34 Figure 17: Coping strategies by income groups ...... 34 Figure 18: Types of coping strategies ...... 34 Figure 19: Distances of water Source ...... 35 Figure 20: Distances of water source from house Figure 21: Distance of water source and latrine facility.36 Figure 22 : Water Collation and Women ...... 36 Figure 23: Hand washing material Figure 24: Soap available in household ...... 38

Executive Summary

Introduction In January 2018, Action Against Hunger (ACF) Bangladesh conducted Integrated SMART survey to provide baseline data on nutrition and morbidity status of children including care practices as well as household’s food security and livelihoods, and WaSH indicators in Sitakunda Upazila. This survey was implemented following the recommendations of Rapid SMART survey conducted in Tripura Para, Sitakunda (August 2017) by Action Against Hunger after a measles outbreak associated with undernutrition in July 2017. During the Rapid assessment, the overall nutrition situation in Sitakunda Upazila could not be assessed due to nature of assessment, which only considered for Tripura communities. The rapid assessment also revealed that there are concerns of high levels of acute malnutrition (GAM-10.1%)1 due to underlying poor nutrition status, exacerbated by measles outbreak in Tripura Para, inadequate maternal and child health care as well as household food insecurity and poor water sanitation and hygiene condition in Sitakunda Upazila.

This survey was conducted using the Standardized Monitoring and Assessment of Relief and Transitions (SMART) Methodology and it was the first integrated nutrition survey conducted in Sitakunda Upazila.

The overall objective of the survey was to determine the nutritional status of children aged 6-59 months, and to assess the care practices behaviours, the food security, WASH situation of Sitakunda Upazila after the July 2017 measles outbreak associated with undernutrition.

Methodology A cross sectional household survey was designed to provide statistically representative of nutrition, food security & livelihoods, and WaSH indicators for Sitakunda Upazila.

A two-stage cluster sampling method following SMART Methodology was used to achieve the desired outcomes of the survey. At the first stage, the required number of clusters were drawn using probability proportional to size (PPS). This PPS methods ensured that every child in the sample universe had an equal chance of being selected taking into account the population size of the villages. The clusters were defined as villages for the most part and in some cases, a village may contain more than one cluster. At the second stage, simple random sampling method was applied to select the households within the cluster.

The sample size was calculated using ENA (Updated July 2015) software, which calculates the sample size; based on various parameters i.e. estimated prevalence, average household size, design effect, desired precision, percentage of children and non-response rate. The sample was then converted into number of households to be surveyed.

A total sample size of 1,187 households were estimated to provide a representative sample (473 children) for the selected anthropometry indicators in Sitakunda Upazila. A total of 66 clusters were selected by PPS method using the ENA for SMART software. Each selected cluster included 18 households, regardless of the number of children interviewed. The study finally surveyed 1,174 households covering 699 children (6-59 months) for non-anthro based indicators and achieved to include 6982 children (6-59 months) for anthropometric indicators.

It should be noted that IYCF indicators require a larger sample size, and therefore the results of the IYCF indicators in the Sitakunda Upazila is only an indication and is NOT representative for the whole population.

1 ACF Nutrition Rapid SMART Survey in Tripura Para, Sitakunda Upazila-August 2017 2 Anthropometric results disaggregated the absent children during data collection, but considered for non-anthro based indicators. 6

Summary Findings: Table 1: Summary findings of Nutrition and Health indicators based on WHO 2006 growth Standards Sitakunda Upazila 10th-28th January 2018 INDICATOR N N=692 Prevalence of Acute Malnutrition by WHZ WHZ- Global Acute Malnutrition 9.4 % 65 scores W/H< -2 z and/or oedema (7.0 - 12.4 95% C.I.) (6-59 Severe Acute Malnutrition 1.0 % months) W/H < -3 z and/or oedema 7 (0.5 – 2.1 95% C.I.) Prevalence of Acute Malnutrition by MUAC N=698 3.4 % MUAC Global Acute Malnutrition (<125mm) 24 (2.4 - 5.0 95% C.I.) (6-59 0.4 % months) Severe Acute Malnutrition (<115mm) 3 (0.1 – 1.3 95% C.I.) Prevalence of Underweight N=690 WAZ- 26.4 % Underweight (<-2 z-score) 182 scores (22.7 - 30.4 95% C.I.) (6-59 4.9 % Severe Underweight (<-3z-score) 34 months) (3.5 - 6.8 95% C.I.) Prevalence of Stunting N=689 HAZ- 31.1 % Stunting (<-2 z-score) 214 scores (27.3 - 35.0 95% C.I.) (6-59 7.1 % Severe Stunting (<-3z-score) 49 months) (5.2 - 9.6 95% C.I.) Morbidity status (6-59 months) –Overall 699 59.4% (415) Diarrhoea 699 9.9% (69)

Fever 699 41.5% (290)

Acute Respiratory Infections (ARI) 699 43.3% (303)

Other Diseases 699 2.1% (15) Measles immunization coverage (9-59 months) 654 91.0% (595) By card 654 82.7% (541)

By Recall 654 8.3% (54) Vitamin A coverage (6-59 months) 699 90.8% (635)

Table 2: Summary findings of IYCF practices IYCF Indicators N Prevalence Early Initiation of Breastfeeding within 1 hour after birth (0-23 months) 334 43.1% (144) Exclusive Breastfeeding for children 0-5 months 84 60.7% (51) Continuation of Breastfeeding at 1 year (12-15 months) 47 97.9% (46) Continuation of Breastfeeding at 2 year (20-23 months) 46 73.9% (34) Mean Dietary Diversity Score (IDDS) 3.0 Minimum Dietary Diversity (6-23 months) (>=4 food groups) 250 37.6% (94) Minimum Meal Frequency (6-23 months) (>=3 full meals) 250 66.8% (167) Minimum Acceptable Diet (6-23 months) 250 30.4% (76)

Table 3: Summary findings of Food Security and Livelihoods (FSL) FSL Indicators N Prevalence Mean Household Income Category N=1174 BDT < 5,000 27 2.3% BDT 5,000 to ≤ 10,000 602 51.3% BDT >10,000 545 46.4% Main Source of Income N=1174 Unskilled wage labour (including agro) 205 17.5% Salaries, wages-employees 316 26.9% Skilled labour 207 17.6% Seller, commercial activity 120 10.2% Remittance 129 11.0% Main Source of Food N=1174 Purchasing 1121 95.5% Own cultivation 53 4.5% Mean Household Dietary Diversity (HDDs) 1174 8.2 Poor (≤3) 0 0.0% Moderate (4 to 5) 48 4.1% Good (≥6) 1126 95.9% Mean Women Dietary Diversity (WDDs) 1149 5.0 Good (≥5) 693 60.3% Poor (0 to 4) 456 39.7% Reduced Coping Strategy Index (rCSI) 1174 6.4 No or low rCSI (0 -3) 1024 87.2% Medium rCSI (4–9) 127 10.8% High Coping (CSI ≥ 10) 23 2.0%

Table 4: Summary findings of Water Sanitation and Hygiene (WASH) WASH Indicators N Prevalence Main Water Source of Drinking Water N=1174 Tubewell (shallow) 831 70.8% Tubewell (deep) 259 22.1% Distance from Drinking Water Source From Home N=1174 0 to 150 feet 841 71.6% More than 150 feet 333 28.4% Distance Between Water Source and Latrine Pit N=1174 0 to 30 feet 653 55.6% 30 to 100 feet 446 38.0% 100+ feet 75 6.4% Main Water Collector N=1174 Adult women 1042 88.8% Girls 101 8.6% Covering and Washing Water Container N=1174 Always cover container during transportation 713 60.7% Washing water container daily 1111 94.6% 8

Type of Sanitation Facilities N=1174 Hygienic sanitary facility 581 49.5% Unhygienic sanitary facility 593 50.5% Hand Washing Behaviour with Soap 1174 95.1% Before cooking 176 15.8% After defecation 1054 94.4% Before eating food 414 37.1% After disposing child's faeces/cleaning child 469 42.0% After working with animals, crops etc. 307 27.5% Before feeding child 140 12.5% General Handwashing Material N=1174 Water only 1021 87.0% Water and ash 2 0.2% Water and sand/mud 2 0.2% Water and soap 149 12.7% Others 0 0.0% Soap Available in Latrine/ Besides Latrine 478 40.7%

Recommendations and Priorities:

Nutrition, Health and Mental Health and Care practices

 Reinforce the Health System in this area while integrating the nutrition treatment into existing health facilities. The results show that there is the percentage of the people who seek treatment from unregistered sources is high (63.1%). This would need to be addressed through health system strengthening. Advocate for a health system strengthening exercise.  Develop a large scale integrated multi-sectorial program to address acute and chronic malnutrition among U5 children and PLW taking into account Nutrition, Health, WASH, MHCP, and FSL.  Reinforce Growth Monitoring and Promotion activities in government health facilities focusing on detection, referral of severe acute malnutrition and promotion of essential nutrition actions.  Continue, scale up and improve the promotion of appropriate infant and young child feeding practices, preparation of nutritious food with local foods at home, dietary diversity, childcare, safe sanitation and hygienic practices through innovative approaches. The activities can be done at community level through reinforcing the capacity of existing service providers of the health facilities in this regards.  Plan for capacity building of partners staff and volunteers on comprehensive maternal and child care package including IYCF, Nutrition practices for children and PLW, improving FSL, WaSH with advocating the MoHFW, stakeholders at beneficiary level.  Sensitizing and mobilizing government and non-government stakeholders at Upazila level for targeting families at risk of undernutrition during programming (nutrition sensitive) through the district multi- sectoral coordination platform.  Follow up SMART nutrition surveys next year at the same time to document progress of the response plan and lessons learnt.

Food Security and Livelihoods (FSL)

 More than half (53.6%) of the surveyed population in Sitakunda Upazila have average monthly income less than or equal to BDT 10,000 and 2.3% of the population are extremely poor and earn in less than BDT 5,000 per month. They are highly food insecure. Livelihoods interventions are very crucial to enhance monthly income as well as access to nutritious food.  Extreme poor households have monthly average income below the Minimum Expenditure Basket (MEB); they need immediate food security support to address the food insecurity.  Around 40.0% of the women have poor dietary diversity. Special attention is needed to improve the dietary diversity among the women.

Water Sanitation and Hygiene (WASH)  It is very important to check the water quality of shallow tube-well, which is the only dominated source of drinking, because it has a potential threat to be contaminated.  Our survey found that nearly half of the latrines did not follow the standard which means potential risk have identified of faecal contamination of water source. Ii is very important findings of the survey in deed. It is very necessary to disseminate information regarding it.  Water Collection, this particular task is very gender biased which need special attention to reduce the burden of female of the area.  Sensitising the community on the importance of covering the container when transporting water should be included in the development of WaSH projects  Put in place faecal sludge management as half of the faecal sludge is unmanaged.  Support vulnerable families to ensure low cost sanitary latrine facilities and its utilization at household level.  When the national coverage of ODF is ‘Zero’ and still the present situation of the targeted community is far from it. It is very important to consider during project design in this specific area.  If we consider hand-washing practice as an indicator of overall sanitation practice of the area it can be concluded that the sanitation practice and knowledge regarding it is not in satisfactory level and have a necessary to improve the situation through multilevel activities.

1. Introduction Figure 1: Map of Sitakunda Upazila Sitakunda Upazila is located in Chittagong District, Bangladesh. The Upazila is bounded on the north by Mirsharai upazila, east by Fatikchhari and Hathazari upazilas, south by Pahartali thana and west by the Sandwip channel, Sandwip Upazila and the Bay of Bengal. Sitakunda Upazila is located between 22º22' and 22º42' north latitudes and between 91º34' and 91º48' east longitudes. Sitakunda Upazila occupies an area of 483.97 square kilometres (186.86 sq. mi), which includes 61.61 square kilometres (23.79 sq. mi) of forest.

Sitakunda Upazila in inhabited by an estimated population of 416,7773 comprising of one Paurashava and nine unions with an. Apart from the Bengali majority, there are a number of small communities of ethnic minorities living in the area. Sitakunda has an average literacy rate of 50.7% for the population of 7 years and above.

Economic development in Sitakunda is largely driven by the Dhaka-Chittagong Highway and railway. Though Sitakunda is predominantly an agricultural area, it also has the largest ship breaking industry in the world. Sitakunda's ecosystems are further threatened by deforestation, over-fishing, and groundwater contamination. The upazila is also susceptible to natural hazards such as earthquakes, cyclones and storm surges. It lies on one of the most active seismic faults in Bangladesh, the Sitakunda–Teknaf fault.

In July, news outlets reported that 10 children died of a mysterious disease in Tripura Para, a village in Sitakunda Upazila. In response to that, GoB Institute of Epidemiology, Disease Control and Research (IEDCR) was sent to area. It was found that the children had died due to measles and undernutrition. Governement of Bangladesh (GoB) initiated a measles vaccination campaign in Kumira and Sonaichari unions in Sitakunda Upazila. In Tripura Para village, MoH established a Community Clinic that is operational 2 days a week.

Despite availability of GoB health facilities in Sitakunda district, parts like Tripura Para have been deprived from health care including immunisation and treatment of common illnesses. Especially indigenous population living in Sonaichari and Kumira unions have difficulties accessing health services due to the difficult geography (hilly), distance and barriers in language. It’s assumed that, due to the existing poor health and nutrition status and poor access to health facilities of the population in Sitakunda Upazila, the nutrition status of the population is likely to further deteriorate.

IPHN has requested Action Against Hunger to support GoB in the implementation of nutritional assessment in Tripura Para, baseline nutritional survey, training of GoB staff on Inpatient SAM management and establishment of a SAM unit in Sitakunda, training of GoB staff on CMAM and roll out CMAM in all health facilities in Sitakunda Upazila.

As part of CMAM integration, Action against Hunger initially conducted a Rapid SMART Nutrition assessment (August 2017) in Tripura Para after July measles outbreak associated with undernutrition. The assessment revealed concerns of high levels of acute malnutrition (GAM-10.1%)4 due to underlying poor nutrition status, exacerbated by measles outbreak in Tripura Para, inadequate maternal and child health care as well as household food insecurity and poor water sanitation and hygiene condition in Sitakunda Upazila. During the

3 Projected with annual growth rate of 1.45 from 2011 to 2016 ( BBS-2011 : 387832) 4 ACF Nutrition Rapid SMART Survey in Tripura Para, Sitakunda Upazila-August 2017 11

Rapid assessment, the overall nutrition situation associated with other factors e.g. IYCF practices, household FSL and WASH situation in Sitakunda Upazila could not be assessed due to the nature of survey. Therefore, Action Against Hunger conducted an Integrated SMART survey in January 2018 to provide baseline data on nutrition and morbidity status of children, care practices, households Food Security, Livelihoods, and WaSH situation in Sitakunda Upazila.

1.1Survey Objectives

Overall Survey Objective The overall objective of the survey is to determine the nutritional status of children aged 6-59 months, and to assess care practices behaviours, the food security and WASH situation of Sitakunda Upazila after the July 2017 Measles outbreak associated with undernutrition.

Specific Survey Objectives  To determine the current global acute malnutrition rate among children aged 6-59 months.  To determine the level of chronic malnutrition and underweight among children aged 6-59 months.  To estimate the prevalence of morbidity in children aged 6-59 months.  To determine the level of appropriate Infant and Young Child feeding practices.  To assess the minimum dietary diversity for women of reproductive age (15-49 years).  To assess the current level of household dietary diversity (HDDS) and to explore the existing coping mechanism (rCSI).  To identify the current water access, sanitation facility access and hygiene practices at household level.

2. Methodology

In January 2018, Action Against Hunger Bangladesh conducted Integrated SMART Nutrition (including IYCF, MHCP, Food Security, Livelihood and WaSH) survey in Sitakunda Upazila. This survey was conducted using the Standardized Monitoring and Assessment of Relief and Transitions (SMART) Methodology and it was the first integrated nutrition survey conducted in Sitakunda Upazila.

2.1 Survey Area The survey was conducted in Sitakunda Upazila during 10th January to 28rd January 2018, which is considered winter season in Bangladesh. All the villages from 10 unions were included in the survey. Thus, the total population figures5 for each unions were defined as follows:

Table 5: Details of administrative areas with population Total Total Projected Projected U56 Name of Union households Population Population as Children as of (BBS-2011) (BBS-2011) of 2016 2016 Sitakunda Paurash0va 8,764 43,555 46,806 4,400 Banshbaria Union 4,502 21,850 23,481 2,207 Barabkunda Union 7,350 33,724 36,241 3,407 Bariadyala Union 5,668 28,381 30,499 2,867 Bhatiari Union 10,924 55,434 59,571 5,600 Kumira Union 7,586 38,896 41,799 3,929 Muradpur Union 5,844 29,602 31,811 2,990 Salimpur Union 11,037 54,797 58,887 5,535 Sonaichhari Union 8,994 49,346 53,029 4,985 Saidpur Union 6,357 30,655 32,943 3,097

5Population and U5 children are projected as of 2016 with annual growth rate (1.45) and percentage of U5 (9.4%) children (BBS 2011) respectively. 6 Estimated children U5: 9.4% 12

Bhatiari Cantonment Area 253 1,592 1,711 161 Total 77,279 387,832 416,777 39,177

2.2 Type of survey

A cross sectional household survey following SMART methodology with a modified integrated questionnaire was designed. Two stage cluster sampling recommended by SMART methodology was used for sampling and data collection of the survey. The key objective of the survey was to assess the nutrition situation through anthropometry while additional FSL, MHCP and WaSH indicators were incorporated for Integrated Food Security Phase Classification (IPC). Household was considered as the basic sampling unit in the second stage and each villages/segments were selected as primary sampling unit (Cluster) at the first stage.

2.3 Sample size

The following assumptions (based on the given context) were used to calculate the sample size in number of children, which was then converted into number of households to be surveyed. All calculations were made using ENA for SMART software (version 9th July 2015). The sample size calculation takes into consideration the proxy indicator: anthropometry. The parameters for the sample size calculation are as outlined in table below.

Table 6: Sampling parameters-Sitakunda Upazila. Assumptions based on context Parameters for Anthropometry Value (footnote any references used) Chittagong District Prevalence: MICS 2012-2013 , Estimated Prevalence of GAM (%) 10.3% GAM-10.3 % SAM-2.5% Since the prevalence falls between 10-15%, 3.5% ± Desired precision 3.5% precision has been considered as a rule of thumb for SMART. Correcting the effects of heterogeneity of the population under survey. The sample size inflates by Design Effect 1.5 this correction factor to have a representative sampling Children to be included 473 Average HH Size 4.96 BBS 2011 : Sitakunda Upazila % Children under-5 9.4 BBS 2011: Sitakunda Upazila Considering possible absentees due to movement % Non-response Households 5% for livelihood activities. Households to be included 1187

Sample size for additional indicators: For the additional indicators of Infant Young Child Feeding (IYCF) and care practices, food security and WASH, the same sample size as the anthropometric indicators (1187 Households) was used. It should be noted that IYCF indicators require a larger sample size, and therefore the results of the IYCF indicators in the Sitakunda Upazila is only an indication and is NOT representative for the whole population.

2.4 Survey Target Population The anthropometric results for children aged 6-59 months were based on the WHO 2006 standards. All the eligible children aged 6-59 months in the household were included for anthropometric measurements. Infant and Young Child Feeding (IYCF) and Care Practices were assessed by interviewing the mothers or primary care givers and was applicable for children aged below 2 years (under 24 months); morbidity for the preceding 14 days was applicable for children 6-59 months; and Vitamin A supplementation and measles vaccination coverage were applicable for 6-59 and 9-59 months respectively. For Vitamin A and measles, 13

the mother/primary caregivers recall and the child vaccination card were used. All eligible children within the same household were included for the survey. Food security and WASH information were collected for all targeted households. In case there are no children identified in the household, other household information (food security and WASH) were collected. For assessing household dietary diversity (HDDS) and Reduced Coping Strategy Index (rCSI), one adult women who is responsible for household cooking was interviewed whereas one women of reproductive age (15-49yr) was selected randomly (if more than one) for assessing minimum dietary diversity for women (MDD-W).

2.5 Sampling procedure: selecting clusters Sampling procedure: definition of cluster The survey was conducted in Sitakunda Upazila using a 2-stage cluster sampling method where the primary sampling unit were the villages. The basic sampling unit for the survey was the household because there were other indicators like IYCF and care practices, household food security and livelihoods, mental health, WASH and mortality, which were collected from household level. The SMART guideline for selection of clusters has been adapted to assign the required number of clusters for the survey in the Sitakunda Upazila to make it feasible for carrying out the survey with the concept of giving each household an equal opportunity to be selected. Based on Probability to Population Size (PPS), 66 clusters were randomly selected using ENA for SMART (July 2015) software. PPS method ensured that every household in the Upazilas were an equal chance to be selected irrespective the size of the village. Reserved clusters planned to be included only when equal or more than 10% clusters could not be surveyed and if only less than 80% of the sampled households could be reached from separately two districts. Therefore, no reserved clusters were included in the survey since we could access all 66 clusters and reached minimum number of HHs expected (equal or more than 80% of the sampled HHs).

2.6 Sampling procedure: selecting households and children At second stage, households were selected using the simple random sampling within the cluster. In each area, each team updated households list before the day of data collection. If houses were near each other, and less than 250 HHs in number, the survey team gave a number to each house, then they used the random number table to select the HHs to be surveyed. If the houses were scattered throughout a large area, and/or they were more than 250 HH in number, the following method applied: The cluster was divided into segments. As the numbers of household in each segment varied in size, PPS method was used to select a segment in the following manner: the teams drew a table including the different segments and the cumulative number of households per segment. They then used a random number table to select a number between one and the total number of households. The segment contained this number was selected to be the surveyed. Consequently, a random UX mobile application was used to generate a random number table with estimated households selected randomly for each cluster.

The study targeted 1,187 households that covered 473 children under five years. The targeted number of households in each cluster was 18, regardless of the number of children interviewed.

If individuals or children are absent, the team revisited the houses at the end of the day before they leave the village. A household with an absent family was not replaced as non-response is factored into the sample size calculations.

Table 7: Details of proposed and actual sample size achieved Number of Number of % Number of Number of Number of % households households surveyed children 6- children 6-59 children 6- surveyed planned surveyed 59 months months 59 months planned surveyed measured 1187 1174 98.9% 473 699 698 147.5%

The minimum percentage of clusters surveyed (90%) and children measured (80%) stipulated by the SMART methodology to ensure representativeness was achieved for this survey.

Selection of number of household per cluster / per day Based on the following points, a calculation had been done for each team to estimate the number of household to be surveyed per cluster per day at each cluster.

Table 8: Calculation of households’ coverage/day/cluster Calculation of HH coverage/day/cluster Event Time to dedicate Total time remaining Time per day for field work (including 7:30 until 18:00 = 630 min 630 min travel time, round trip) Daily feedback session 30 min 600 min Two breaks of 10 min plus 20 min lunch 10 min X 2 + 20 min = 40 560 min break min Discussion with village leader and 20 min 540 min selection of 1st HH Time to dedicate per HH and reach the 30 min for anthropometric measurements and questionnaire next and walk to next HH Total number of HH’s to be covered by 540/30=18HH each team per day

2.7 Case definitions and inclusion criteria Household definition: In this survey, a household is defined as a group of people who normally live together and eat from the same pot.  Polygamous families counted as one household as long as they were living together and sharing a common cooking pot.  Polygamous families or any other families living in the same house but not sharing a common cooking pot were counted as separate household. In such cases if the house was been selected for the survey, both households were included in the survey with a different household number.

Inclusion criteria of children: All children aged from 6-59 months were included for anthropometry, infant and children 0-23 months for IYCF and care practices, all houses for food security & livelihoods and WaSH related questions.

If age could not be defined by any means i.e. birth certificate, vaccination card, then a local calendars of events was used to estimate age.

For children with unknown age, the cut-off point of height between 65 and 110cm was used as secondary inclusion criteria for anthropometry.

The length of children less than 2 years old was measured lying down while the height of children more than 2 years was measured standing. In the absence of age, height 87cm was used to define whether to measure the child standing (≥87cm) or lying (<87cm).

The WHO growth reference 2006 was used to estimate the prevalence of under nutrition in the area. In addition, rate of acute malnutrition by MUAC criteria was analysed and reported.

Table 9: Case definitions of Acute Malnutrition, Stunting and Underweight used for analysis Nutritional Status Classification Nutritional Acute Malnutrition Chronic Malnutrition Underweight Weight/Age Status Weight/ Height (WHZ) MUAC Height/Age (HAZ) (WAZ) WHZ< -2 SD and/or MUAC< 125 mm Global HAZ< -2 SD WAZ< -2 SD Oedema and /or Oedema 115 mm≤ MUAC< WAZ <- 2SD to ≥ Moderate WHZ <- 2SD to ≥ -3 SD HAZ <- 2SD to ≥ -3 SD 125 mm -3 SD WHZ < -3 SD and/or MUAC< 115 mm Severe HAZ < -3 SD WAZ < -3 SD Oedema and /or Oedema

Table 10: Case definition for IYCF, morbidity, vitamin A and measles coverage. Indicator Definitive criteria Early Initiation of Proportion of children aged 0-23 months who were put to the Breastfeeding breast within one hour of birth. Exclusive Proportion of infants 0–5 months of age who are fed breastfeeding exclusively with breast milk Continued Proportion of children aged 12-15 months who are fed breast breastfeeding at 1 year milk and Proportion of children 20-23 months of age who are fed IYCF7 and 2yr breast milk during the previous day. Minimum dietary Proportion of children 6- 23 months of age who received foods diversity from 4 or more food groups during the previous day. Minimum meal Proportion of breastfed and non-breastfed children 6–23 months frequency of age who receive solid, semi-solid, or soft foods (but also including milk feeds for non-breastfed children) the minimum number of times or more. (at least 3 full meals per day) Minimum acceptable Proportion of children 6–23 months of age who received a diet minimum acceptable diet (apart from breast milk). It is a composite indicator by combining minimum dietary diversity and meal frequency. Coverage Measles vaccination Measles vaccination were assessed among children aged 9-59 months by checking for the measles vaccine on the EPI card if available or by asking the caregiver to recall if no EPI card is available. Vitamin A Coverage Whether the child aged 6-59 months received a vitamin A capsule over the past six months was recorded from the EPI card or health card if available or by asking the caregiver to recall if no card is available.

7WHO 2010: Indicators for assessing infant and young child feeding practices: Part 3, Country profile. 16

Morbidity Morbidity patterns and Morbidity for the preceding 14 days and applied for children 6- treatment status 59 months; for which the mother/primary care givers asked using recall response.

Table 11: Case definitions of public health significance level Global Acute Overall Overall Stunting Severity Malnutrition Underweight Interpretation (HAZ) (WHZ) (WAZ) Very High ≥ 15% ≥ 40% ≥ 30% Critical/ Emergency High ≥ 10% - <15% ≥ 30% - < 40% ≥ 20% - < 30% Serious Medium ≥ 5% - < 10% ≥ 20% - < 30% ≥ 10% - < 20% Poor Low < 5% < 20% < 10% Acceptable

Table 12: IPC classification8 Global Acute Malnutrition by MUAC

Prevalence Global Acute Malnutrition MUAC Extreme Critical >17% Critical 11.0-16.9% Alert-Serious 6-11% Acceptable <6%

Table 13: Thresholds level for Household Dietary Diversity (HDD) Household Dietary Diversity Score (HDDS) Thresholds Low dietary diversity ≤ 3 food groups Medium dietary diversity Between 4 and 5 food groups High dietary diversity ≥ 6 food groups Source: Guidelines for measuring household and individual dietary diversity, FAO

Table 14: Thresholds level for household Coping Strategy Index (CSI) Coping Strategy Index (CSI) Score Thresholds No or low coping 0 - 3 Medium coping 4 - 9 High coping ≥ 10 Source: Guidance note; WFP VAM unit, Afghanistan, December 2012

Table 15: Thresholds level for Minimum Dietary Diversity (MDD-W) for women (15-49yrs) Dietary Diversity (MDD-W) for women Thresholds Good ≥ 5 Poor 0-4 Source: Minimum Dietary Diversity for Women: A Guide to Measurement, FAO, USAID, FANTA, 2016

2.8 Questionnaire, Training and supervision

Questionnaire A modified version of questionnaire including additional indicators of IYCF, morbidity patterns, FSL, WaSH indicators with anthropometry was developed by Action Against Hunger Bangladesh. The survey was incorporated the use of tablets using Android operating system for data collection. The tablets replaced the

8 IPC Acute Malnutrition Addendum 2016 17

paper questionnaires; however, all teams carried hard copies of the questionnaires as back-ups in case the tablet fails at any point. Questionnaires was first developed and adapted on paper and then deployed in KoBo Toolbox by Survey Manager and then uploaded to the ASUS tablet. Team leaders were provided with two tablets including one for back up. The questionnaire was translated into Bangla before training. The questionnaire was pre-tested in the communities by the survey team (Annex 4).

Survey Teams and Supervision The integrated SMART survey implemented by six survey teams, each team consisting of a team leader cum measurer, one measurer assistant, and two interviewers. A well-experienced survey supervisor was recruited to implement and monitor the overall survey activities in the field level. Each team stayed in the field for 18 days (11th Jan -28rd Jan’18) and each team covered one cluster per day. The team leader cum measurer was responsible for day-to-day field supervision, household selection, and taking anthropometric measurements. To ensure the accuracy and consistency of data, joint monitoring and supervision were carried out through regular field visits, cross checking and plausibility checking through ENA software every day. Survey Manager, Nutrition and Health Head of Department and Deputy Head of Department oversaw the whole Integrated SMART survey and provided necessary support to the survey team.

Training The survey team has been trained on SMART methodology in December 2017 for the implementation of Kutubdia SMART survey. Therefore, the survey team received three days refresher training (9th -11th December 2017) which included classroom training, standardization test and field test. The training for enumerators covered survey objectives, household selection techniques, questionnaire, demonstration on anthropometric measurements and standardization test, data collection and interview skills with group works & field-testing of questionnaire. The standardization test included 10 healthy 6-59 months children that took place on the 3rd day of the training. A field test were conducted a day before the actual data collection. During the field-testing, the questionnaire was administered in the local Bengali language, entered into the tab and piloted before the survey.

2.9 Data Entry, Data management and Analysis

The survey incorporated the use of tablets using Android operating system, and KoBo Toolbox software for data collection and entry. Once the data collection was completed, Survey Manager extracted the data from the server into excel format and randomly crosschecked to identify errors and inconsistencies in data collection. Anthropometric data was analysed using ENA software and CDC calculator. All flagged data using SMART flagging criteria (observed mean) was excluded from the analysis. Additionally, IYCF, Care Practices, WASH and Food Security data were analysed using excel software. Eligible but non-respondent samples were excluded from analysis.

Table 16: Overall data quality from plausibility check CRITERI Missin Overall Overall Digit Digit Digit Standard Skewne Kurtosi Poisson Overal A g/ sex age preferen preferen preferen deviation ss WHZ s WHZ distribut l score flagged ratio distributi ce score ce score ce score WHZ ion WHZ WHZ data on Weight Height MUAC SCORE 0 (0.4%) 4(0.041) 0(p=0.123) 0 (4) 2 (8) 0 (7) 0 (0.95) 0(0.16) 0 (0.03) 1 (0.014) 7%

Interpretati Excellent Acceptabl on Excellent Excellent Good Excellent Excellent Excellent Excellent Good Excellent e

3. Results

3.1 Household and family composition Household data revealed only 6.9 % of the total households were led by women. The average household size found 5.0 and percentage of U5 children was 13.5%.

Table 17: Household and family composition Category/Indicator Sample HH Value Proportion/Mean % of Women Headed Household 1174 81 6.9% % of Men Headed Household 1174 1093 93.1% Average age of HH Head 1174 43.7 Mean Family Size 1174 5917 5.0 % of Male members 1174 3069 51.9% % of Female members 1174 2848 48.1% % of Children 0 to 5 months 1174 87 1.5% % of Children 6 to 23 months 1174 252 4.3% % of Children 24 to 59 months 1174 456 7.7% % of Children aged 5-17 years 1174 1478 25.0% % Adult members (18-50y) 1174 3036 51.3% % Elderly members (50 years and above) 1174 608 10.3%

3.2 Age and Sex Ratio in Children 6-59 Months

The overall sex distribution (1.2) of the sampled children has shown significant excess of boys (P=0.041) than girls. The overall age distribution was observed as expected (P=0.228) with significant difference for boys (P=0.021). The overall age ratio of 6-29 months and 30-59 months was also found to be expected (P=0.123).

Table 18: Age and sex ratio Boys Girls Total Ratio AGE (mo.) no. % no. % no. % Boy: Girl 6-17 106 59.6 72 40.4 178 25.5 1.5 18-29 73 44.8 90 55.2 163 23.4 0.8 30-41 96 60.8 62 39.2 158 22.6 1.5 42-53 70 50.4 69 49.6 139 19.9 1.0 54-59 31 51.7 29 48.3 60 8.6 1.1 Total 376 53.9 322 46.1 698 100.0 1.2

Anthropometric results (based on WHO standards 2006): Anthropometric data from a representative sample of 698 children was collected and analysed excluding z- scores from observed mean (SMART flags): WHZ-3 to 3; WAZ -3 to 3; HAZ -3 to 3. Therefore, a total of 3, 8 and 6 children were excluded from the analysis to estimate prevalence of GAM (WHZ), underweight (WAZ) and stunting (HAZ) respectively with SMART flag criteria.

3.3 Acute Malnutrition (Wasting) based on WHZ:

Acute malnutrition or wasting occurs when an individual suffers from current, severe nutritional restrictions, a recent bout of illness, inappropriate childcare practices or a combination of various factors (flooding, cyclones, limited income opportunities etc.) in any context as weight changes rapidly compared to height. It is characterised by extreme weight loss, resulting in low weight-for-height. Wasting is a reflection of present malnutrition and is therefore used as a proxy of the current nutritional status of the population.

Table 19: Prevalence of Acute Malnutrition by WHZ score All Boys Girls P Value n = 692 n = 374 n = 318 Prevalence of global (65) 9.4 % (50) 13.4 % (15) 4.7 % malnutrition (7.0 - 12.4 (10.2 - 17.4 95% (2.9 - 7.6 95% 0.000 (<-2 z-score and/or oedema) 95% C.I.) C.I.) C.I.) Prevalence of moderate (58) 8.4 % (45) 12.0 % (13) 4.1 % malnutrition (6.1 - 11.3 (8.9 - 16.0 95% (2.4 - 6.9 95% 0.000 (<-2 z-score and >=-3 z-score, 95% C.I.) C.I.) C.I.) no oedema) Prevalence of severe (7) 1.0 % (5) 1.3 % (2) 0.6 %

malnutrition (0.5 - 2.1 95% (0.6 - 3.1 95% (0.2 - 2.6 95% 0.163 (<-3 z-score and/or oedema) C.I.) C.I.) C.I.)

Anthropometrics of 692 children were considered (flags excluded). The assessment found 65 children 6-59 months to be acutely malnourished. The prevalence of GAM by Weight for Height Z score and/or oedema was found to be 9.4 % (7.0 - 12.4 95% C.I.) with SAM rate of 1.0 % (0.5 - 2.1 95% C.I.). The prevalence of acute malnutrition can be interpreted as poor according to WHO thresholds. Further analysis revealed significant difference in the prevalence of GAM (P=0.000) where boys (13.4%) are more malnourished than girls (4.7%). No oedema cases found during the assessment.

Table 20: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema Severe wasting Moderate wasting Normal Oedema (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) Total Age (mo.) No. % No. % No. % No. % no. 6-17 176 3 1.7 16 9.1 157 89.2 0 0.0 18-29 160 1 0.6 10 6.3 149 93.1 0 0.0 30-41 157 2 1.3 15 9.6 140 89.2 0 0.0 42-53 139 1 0.7 10 7.2 128 92.1 0 0.0 54-59 60 0 0.0 7 11.7 53 88.3 0 0.0 Total 692 7 1.0 58 8.4 627 90.6 0 0.0

The assessment findings revealed that the prevalence of acute malnutrition considering WHZ found to be higher among younger children for SAM and MAM. About 72% (47 out of 65) of those identified as malnourished either with MAM or with SAM were below 42 months and almost 90% (58 out of 65) aged less than 54 months. It is remarkable to see that the Z scores were lowest (10.8%; 7 out of 65) in the 54-59 age groups.

Figure 2: WHZ Gaussian Curve The sampled population curve (red curve) shows a displacement to the left of the reference curve (green curve) representing the WHO standards. This is an indication of poor nutritional status. The overall mean standard deviation (SD) is 0.95 and falls within the acceptable range of 0.8-1.2. Therefore, we can statistically say with confidence that on average the children are below the average weight for height of the WHO average. This means that population as a whole is undernourished.

3.4 Acute Malnutrition Based on MUAC

A child is identified as malnourished if the circumference is less than 125 millimetres and severely malnourished if it is less than 115 millimetres. In Bangladesh as in other countries, MUAC is the primary admission criteria for nutrition treatment for children who are less than 59 months old despite WHO recommendation to use both WH and or MUAC as admission criteria for SAM children. The Global Acute Malnutrition prevalence by MUAC is found to be “acceptable” according to IPC Acute Malnutrition classification.

Table 21: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex All Boys Girls P Value n = 698 n = 376 n = 322 Prevalence of global (24) 3.4 % (12) 3.2 % (12) 3.7 % malnutrition (2.4 - 5.0 95% (1.9 - 5.4 95% (2.3 - 6.0 95% 0.679 (< 125 mm and/or oedema) C.I.) C.I.) C.I.) Prevalence of moderate (21) 3.0 % (11) 2.9 % (10) 3.1 % malnutrition (2.0 - 4.5 95% (1.7 - 5.1 95% (1.8 - 5.4 95% 0.861 (< 125 mm and >= 115 mm, C.I.) C.I.) C.I.) no oedema) Prevalence of severe (3) 0.4 % (1) 0.3 % (2) 0.6 % malnutrition (0.1 - 1.3 95% (0.0 - 2.0 95% (0.2 - 2.5 95% 0.477 (< 115 mm and/or oedema) C.I.) C.I.) C.I.)

The prevalence of Global Acute Malnutrition by MUAC was found to be 3.4% (2.4 - 5.0 95% C.I.) with a low level of SAM prevalence of 0.4 % (0.1 - 1.3 95% C.I.) in Sitakunda Upazila. According to GAM prevalence based on MUAC, there was no statistical difference between boys and girls (p=0.679).

Figure 3: MUAC by Age (Combined) The assessment findings revealed that the prevalence of GAM by MUAC [3.4% (2.4 - 5.0 95% C.I.)] is lower when compared to the prevalence of GAM by WHZ [9.4 %: 7.0 - 12.4 95% C.I.].

MUAC also identified younger children for SAM and MAM. About 75% (18 out of 24) of those identified as malnourished either with MAM or SAM were in the age group of 6-17 months and all of the children were in the age group of less than 29 months.

Being an absolute measure, MUAC mostly detects younger children. This discrepancy has been reported as a general phenomenon by Grellety and M. H Golden9 based on survey data from 47 countries. The discrepancy of rates of GAM across age groups and sex supports the conclusion that MUAC is dependent on age and sex. MUAC overestimates acute malnutrition among younger children and underestimates among older children10. Low MUAC for girls compared to boys was observed and reported by LT Hop, R Gross, S Sastroamidjojo, T GiaY and W Schultink11, which is similar to this survey finding.

Table 22: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex Moderate wasting Severe wasting Normal (>= 115 mm and < 125 Oedema (< 115 mm) (> = 125 mm ) mm) Age Total No. % No. % No. % No. % (mo.) no. 6-17 178 1 0.6 17 9.6 160 89.9 0 0.0 18-29 163 2 1.2 4 2.5 157 96.3 0 0.0 30-41 158 0 0.0 0 0.0 158 100.0 0 0.0 42-53 139 0 0.0 0 0.0 139 100.0 0 0.0 54-59 60 0 0.0 0 0.0 60 100.0 0 0.0 Total 698 3 0.4 21 3.0 674 96.6 0 0.0

3.5 Underweight

Underweight is an effect of both wasting and stunting, and is therefore a composite indicator of general malnutrition. It is measured by low weight-for-age in children, and is an outcome of either past or present undernutrition. The index does not indicate whether the child has a low weight-for-age because of inadequate weight or because of a small stature for his or her age, and therefore cannot distinguish between chronic and acute malnutrition.

9 Emmanuel Grellety and M H Golden: Weight-for-height and mid-upper-arm circumference should be used independently to diagnose acute malnutrition: policy implications 10 de Onis M., Yip R., and Mei Z., "The development of MUAC-for-age reference data recommended by a WHO Expert Committee," Bull World Health Organization, vol. 75, pp. 11–8, 1997. PMID: 9141745 11 Hop le T., Gross R., Sastroamidjojo S., Giay T., and Schultink W., "Mid-upper-arm circumference development and its validity in assessment of undernutrition. 22

Table 23: Prevalence of underweight based on weight-for-age z-scores by sex All Boys Girls P Value n = 690 n = 371 n = 319 (182) 26.4 % (105) 28.3 % (77) 24.1 % Prevalence of underweight (22.7 - 30.4 (23.7 - 33.4 (19.6 - 29.3 0.223 (<-2 z-score) 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of moderate (148) 21.4 % (86) 23.2 % (62) 19.4 % underweight (18.1 - 25.3 (18.4 - 28.7 (15.3 - 24.4 0.266 (<-2 z-score and >=-3 z-score) 95% C.I.) 95% C.I.) 95% C.I.) (34) 4.9 % (19) 5.1 % (15) 4.7 % Prevalence of severe underweight (3.5 - 6.8 95% (3.4 - 7.7 95% (2.8 - 7.9 95% 0.801 (<-3 z-score) C.I.) C.I.) C.I.)

The overall prevalence of underweight, based on WAZ was found to be 26.4 % (22.7 - 30.4 95% C.I.) with 4.9 % (3.5 - 6.8 95% C.I.) of the children assessed being severely underweight which is considered high according to WHO thresholds. There was no significant difference (p=0.223) in the prevalence of underweight between boys and girls.

Table 24: Prevalence of underweight based on weight-for-age z-scores by age Severe underweight Moderate underweight Normal (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) Age Total Age (mo.) Total no. No. % No. % (mo.) no. 6-17 174 5 2.9 30 17.2 139 79.9 18-29 159 8 5.0 30 18.9 121 76.1 30-41 158 13 8.2 35 22.2 110 69.6 42-53 139 5 3.6 40 28.8 94 67.6 54-59 60 3 5.0 13 21.7 44 73.3 Total 690 34 4.9 148 21.4 508 73.6

3.6 Chronic Malnutrition/ Stunting

Stunting is an adaptation to chronic malnutrition, and reflects the negative effects of nutritional deprivation on a child’s potential growth, over time. Stunting can occur when a child suffers from long-term nutrient deficiencies and/or chronic illness, so that not only weight gain but also height is affected. It can also be an outcome of repeated episodes of acute infections, or acute malnutrition.

Table 25: Prevalence of stunting based on height-for-age z-scores and by sex All Boys Girls P Value n = 689 n = 370 n = 319 (214) 31.1 % (116) 31.4 % (98) 30.7 % Prevalence of stunting (27.3 - 35.0 (26.7 - 36.4 (25.7 - 36.2 0.846 (<-2 z-score) 95% C.I.) 95% C.I.) 95% C.I.) (165) 23.9 % (89) 24.1 % (76) 23.8 % Prevalence of moderate stunting (20.7 - 27.5 (19.6 - 29.2 (19.2 - 29.2 0.931 (<-2 z-score and >=-3 z-score) 95% C.I.) 95% C.I.) 95% C.I.) (49) 7.1 % (27) 7.3 % (22) 6.9 % Prevalence of severe stunting (5.2 - 9.6 95% (5.0 - 10.6 95% (4.3 - 10.8 95% 0.850 (<-3 z-score) C.I.) C.I.) C.I.)

The prevalence of stunting, based on HAZ was 31.1 % (27.3 - 35.0 95% C.I.) with severely stunted rate of 7.1 % (5.2 - 9.6 95% C.I.). This can be interpreted as large number of children in Sitakunda Upazila suffer from chronic malnutrition and many of them are probably at risk of permanently damaging their mental, physical health, growth, undermining their future productivity and therefore income, with many of them at risk of permanently damaging their mental, physical health, growth, undermining their future productivity and therefore income. There was no significant difference in prevalence of stunting found between boys and girls (P=0.846). Sitakunda Upazila can be categorized as an Upazila with very high level of stunting rate, a serious public health concern.

Figure 4: HAZ Gaussian Curve

The sampled population curve (red curve) indicates a displacement to the left of the reference curve (green curve). This is an indication of poor nutritional status. The overall mean standard deviation (SD) of 1.01 and falls within the acceptable range of 0.8-1.2.

Table 26: Prevalence of stunting by age based on height-for-age z-scores Severe stunting Moderate stunting Normal

(<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) Total Age (mo.) No. % No. Age (mo.) Total no. No. no. 6-17 175 9 5.1 27 15.4 139 79.4 18-29 159 16 10.1 42 26.4 101 63.5 30-41 156 11 7.1 49 31.4 96 61.5 42-53 139 10 7.2 33 23.7 96 69.1 54-59 60 3 5.0 14 23.3 43 71.7 Total 689 49 7.1 165 23.9 475 68.9

It is alarming to find that the prevalence of stunting does not reduce as the children age. This indicates that once a child is malnourished, the child remains malnourished and does not show improvement even after 18 months.

Table 27: Mean z-scores, Design Effects and excluded subjects Mean z- Design Effect z-scores not z-scores out of Indicator n scores ± SD (z-score < -2) available* range

Weight-for-Height 692 -0.76±0.95 1.46 3 3 Weight-for-Age 690 -1.39±0.97 1.31 0 8 Height-for-Age 689 -1.53±1.01 1.20 3 6

3.7 Childhood Morbidity Table 28: Prevalence of childhood (6-59 Months) morbidities. Type of Morbidity N=415 Percentage Diarrhoea 69 9.9% Fever 290 41.5% Acute Respiratory Infection (ARI) 303 43.3% Other diseases 15 2.1%

A total of 699 children were assessed to determine the morbidity status of children aged 6-59 month whereas 59.4% (415) children reported illness from infectious diseases. Overall 9.9% children had diarrhoea; 41.5% children had fever; and 43.3% had Acute Respiratory Infection (ARI) and 2.1% of the children suffered from other diseases reported as skin diseases, mouth and eye infections, tumour etc.

Figure 5: Treatment received modalities The assessment revealed that an estimated 87.7% (364) parents/caregivers of ill children 12.3% (415) received treatment from different sources whereas 12.3% children did not receive any kind 9.9% of treatment. However, a low rate of children 14.7% received treatment from Government hospital 63.1% (9.9%) and private clinic (14.7%) and alarmingly high percentage of children (63.1%) were managed by unregistered sources through untrained village doctors, traditional healers, Did not receive Treatment Government Hospital imam, and nearest pharmacy etc. Private Clinic Others sources

On the other hand, the coverage of vitamin A and measles vaccination found quite good, but still below than the Sphere Standard’s recommendation of 95 % coverage. Overall, 90.8% (635/699) children aged 6-59 months received vitamin A in the last six months. In addition, an estimated 91.0% (595/654) of children who were 9 months old received a good coverage of measles immunization through verifying card (82.7) and recall response (8.3%).

3.8 Child care practices including Infant and Young Child Feeding (IYCF) 12

Optimal infant and young child feeding entails the initiation of breastfeeding within one hour of birth; exclusive breastfeeding for the first six months; and continued breastfeeding for two years or more, together with safe, age-appropriate feeding of solid, semi-solid and soft foods starting at 6 months of age following recommended dietary diversity and meal frequency. During the survey period, it was challenging to get adequate sample for IYCF indicators within the framework of SMART methodology. However, these results can provide an overview of the situation especially on IYCF practices in lieu of generalizing the whole population.

Table 29: Summary Findings of IYCF practices Total Indicator N Prevalence Initiation of breastfeeding within 1 hour of birth (0-23 months) 334 43.1% (144) Exclusive breastfeeding for the first six months (0-5 months) 84 60.7% (51) Continuation of breastfeeding at 1 year (12-15 months) 47 97.9% (46) Continuation of breastfeeding at 2 year (20-23 months) 46 73.9% (34) Mean Dietary Diversity Score (IDDS) - 3 Minimum Dietary Diversity (6-23 months) (>=4 food groups) 250 37.6% (94) Minimum meal frequency (6-23 months) 250 66.8% (167) Minimum acceptable diet (6-23 months) 250 30.4% (76)

3.8.1 Early Initiation of Breastfeeding A total 334 child aged 0-23 months from Sitakunda Upazila were considered to assess the percentage of early initiation of breastfeeding after birth. An estimated 43.1% mothers initiated breast-feeding within one hour after birth. This result indicated that a significant number of mothers did not initiated breast-feeding within 1 hour after giving birth, which represents an alarming situation in Sitakunda Upazila. This practice should be improved as it is one of the recommended practices of IYCF components and contributes to decrease neonatal mortality by up to 22%13.

3.8.2 Exclusive Breastfeeding The sample size for exclusively breast-feeding aged 0-5 months was too small to statistically validate these results. The findings can be used as an indicative estimation for exclusive breastfeeding among infants. The assessment findings revealed that about 60.7% of infants were exclusively breastfed during the first six months. Therefore, more focus should be placed on behaviour change activities should be implemented to encourage the practices of exclusive breastfeeding, which is requisite for optimal growth and development, as well as to protect the child from various forms of disease.

3.8.3 Continued Breast feeding (at 1 year and 2 year) The findings analysed depicts an idea of the situation of continued breast-feeding of Sitakunda Upazila although the sample size for this indicators was too small to validate the findings. The results showed that almost all of the children (97.9%) continued breastfeeding at 1 year and 73.9% of children continued breastfeeding at 2 years. This is a very good sign, since breast milk is full of natural nutrition and is essential to form an optimal immune system against disease and illness for the children.

12 Sample size for IYCF indicators is too small to validate the results: ONLY an indication, NOT a representative. 13World Health Organisation. Infant and young child feeding. [press release] July 2010. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385257/#CR3 26

3.8.4 Complementary feeding patterns in the previous day Adequate complementary feeding from 6 months following recommended dietary diversity and meals frequency prevent undernutrition and decrease the risk of infectious diseases, such as diarrhoea and pneumonia by strengthening the child’s self-immune system. The feeding patterns showed that most of the children (94.0%) received grain, roots and tubers as staple foods and followed by 46.0% children consumed flesh foods in the previous day. On the other hand, only one third of the children received their diet as both vitamin A rich fruits and vegetables in the previous day. Consistently, food intake of dairy products, legumes or nuts were very low meaning that children were not receiving adequate diversified foods that are essential for proper growth and development.

Figure 6: Diet in the previous day (6-23 months) Dietary Patterns in the Previous Day (N=250) 100.0% 94.0% 90.0% 80.0% 70.0% 60.0% 46.0% 50.0% 41.2% 40.0% 30.0% 31.2% 28.4% 26.4% 30.0% 20.0% 10.0% 0.0% Grains, Roots, Legumes or Nuts Dairy Products Flesh foods Vitamin A rich Eggs Other fruits and Tubers fruits & Vegetables vegetables

3.8.5. Minimum Dietary Diversity The mean individual dietary diversity score for children aged 6-23 months was 3.0 whereas minimum dietary diversity was 37.6% that indicates almost two third of children aged 6-23 months did not received recommended at least four category of food groups.

3.8.6. Minimum Meal Frequency The survey findings indicated that overall minimum meal frequency rate for children aged 6-23 months was 66.8%.This indicates a good percentage of children received complementary food from 6 months as per the recommendation for optimal feeding frequency.

3.8.7 Minimum Acceptable Diet The overall minimum acceptable diet was 30.4% meaning that most of the children within age bracket of 6- 23 months were not feeding recommended at least minimum four food groups following minimum meal frequency that are essential for proper growth and development.

3.8.6 Knowledge of mothers on child care practices Figure 7: Difficulties or challenges faced during childcare Caregivers were asked to share their Do not know 0.6% difficulties or challenges in terms of Others 35.9% childcare practices that is linked to Criticism from others for child care… 5.1% health and nutrition practices. Among Lack of knowledge or clarity about… 9.6% the total study participants (649), 86.1% (559) mothers shared that they faced Lack of interest to take care of child 5.2% difficulties to feed their child and most of Running out of energy 24.8% the participants 57.9% (376) reported Lack of support from husband or… 31.7% about constraints of time to care their Managing time 57.9% children. In some of the cases (31.7%), Difficulties to feed 86.1% mothers did not get support from their

0.0% 20.0% 40.0% 60.0% 80.0% 100.0% husbands or other family members on childcare. Sometimes they (24.8%) got easily tired or run out of energy to take care of their child. About 5.2% caregivers felt lack of interest to take care of their children and 5.1% mothers faced criticism, as family and neighbours have perceived them not fully capable as a caregiver. Few mothers (9.6%) reported of having lack of knowledge on necessary childcare practices also

Figure 8: Perception of caregiver for child’s optimum growth and development 100.0% 94.1% 90.0% 83.8% 76.7% 80.0% 70.0% 61.2% 60.0% 50.0% 40.0% 34.7% 30.0% 20.6% 24.3% 20.0% 12.3% 10.2% 10.0% 0.2% 0.0% Feeding Seeking Interaction Play with Giving Clean and Giving love, Discipline and Others Do not know enough food support of with child child opportunity safe warm and explanation health to explore environment assurance professionals new things while child is sick

Mothers were asked about necessary childcare actions for their child’s optimum growth and development in this study to understand existing knowledge. Most of the caregivers (94.1%) shared about the need of adequate feeding to their child. A significant number of mothers (83.8%) reported the importance of treatment of child sickness, which shows good awareness about child health care. About 20.6% reported the importance of interaction with child and 24.3% participants reported the need of play with the children. Among them 12.3% caregivers reported of having knowledge about giving the opportunity to the child about exploration of new things, which is one of the key facilitating factors for child’s cognitive development. Total, 76.7% mothers reported the need of clean and safe environment. However, 34.7% mothers reported about the importance of giving affectionate love, warm and assurance to their child. Most of the caregivers (61.2%) stated about the need of discipline and necessary explanation as an important action for child’s optimum growth and development.

3.9 Food Security and Livelihoods

3.9.1 Household Source of Income Head of the households or whosoever was the head of the house at the time of the interview were asked about the household’s main income source and monthly income. Given the complexity of calculating the average monthly income of household, the total monthly income from all sources for the previous 12 months was asked and then the main source of income was identified. It was believed that there could be more than one source of income and therefore the question was specifically asked in a way that the respondent would understand that they need to give the total income from all sources of for the month.

Out of total 19 income sources, 7 are identified as most common sources of income (sources those represent at least 5% of the total surveyed household) representing 94.0% of the surveyed households. The most common income sources are salaries and wages – employees, skilled labour, unskilled wage labour, remittance, seller or small commercial activities, agriculture and sales of crop, fishing (in open/common waterbody). Rest of the income sources (12 income sources) are very insignificant and represents only 6.0% of the surveyed households. Those income sources are mainly – petty trade, livestock and sales of animals, handicrafts, collection of natural resources, begging, gift, government allowances, land broker, agriculture and sales of crop, remittance, gift, land renting etc.

Figure 9: The source of income of the surveyed households

Source of Income (N=1174) Agriculture and sales of crops Livestock and sales of animals 0.5% 5.7% 0.2% 0.4% 0.2% Fishing (open /common water) 5.0% Aquaculture((in a pond) 0.4% Unskilled wage labour (including agro 0.1% 11.0% Skilled labour Handicrafts/cottage industry Collection of natural resources 17.5% Petty trading-less than 10,000 monthly income Seller, commercial activity 26.9% Salaries, wages-employees Begging Gift 17.6% Remittance Government allowance 10.2% Land renting 0.1% Money Lender Salt cultivation 0.3% 3.9% Others

Salaried or wage employee is the main source of income for 26.9% of the surveyed households that is highest among the income sources. Skilled/unskilled wage labour is the second highest income source that represent total 35.1% (skilled - 17.6% and unskilled – 17.5%) of the surveyed households. Other remarkable income sources are remittance (11.0%), sellers or small commercial activities (10.2%), fishing in open or common water bodies (5.0%), agriculture and sales of crop (5.7%).

Figure 10: Income category of the households Household Monthly Income (N=1174) 60.0% 51.3% 50.0% 46.4% 40.0% 30.0% 20.0% 10.0% 2.3% 0.0% BDT < 5000 BDT 5000 to 10000 BDT >10000

The monthly average income of surveyed households is BDT 12,771 in Sitakunda Upazila under Chittagong district. To have deeper insight of the income level, surveyed households are categorized in three income groups – monthly income BDT 10,000. 97.7% of the surveyed household have average monthly income BDT 5,000 or above. Only 2.3% of them have monthly income less than BDT 5000 that is less than the emergency Minimum Expenditure Basket (MEB), meaning that they are highly food insecure. Out of surveyed households, 51.3% have monthly income in between BDT 5000 to BDT 10,000 and 46.4% have monthly income above BDT 10,000.

3.9.2 Source of Food Figure 11: Food Source There are only two sources of food – purchase and Main Source of Food ( N=1174) own production as mentioned by the survey respondents in Sitakunda Upazila. Out of the total 4.5% Own cultivation surveyed households 95.5% mentioned that Cash loan purchase is their main food source. Only 4.5% household’s food source is own production. There is Borrowing no other food source. As most of the household’s Food Aid food source is purchase, meaning that market access Purchaging 95.5% is very crucial for food security in the surveyed areas. Begging Food price hike or drop of income due to any man Exchanging made or natural disasters would have big negative Others impact on the food security of the low-income groups in the survey area.

3.9.3 Household Dietary Diversity

Households were asked to identify the foods that were consumed in the previous 24 hours by the family members. Due to the shorter recall time, the data can provide a clearer picture of the variety of foods consumed at the household level. In measuring the household dietary diversity, food items are grouped in 12 food groups.

Figure 12: Dietary Diversity Status

Household Dietary Diversity (N=1174)

4.1%

95.9%

Poor (≤3) Moderate (4 to 5) Good (≥6)

Mean Household dietary diversity Score (HDDS) of the surveyed households is 8.3 that indicates overall good dietary diversity status among the surveyed households in Sitakunda Upazila. Out of total surveyed households, 95.9% have good dietary diversity and 4.1% households have medium dietary diversity. None of the surveyed household found with poor dietary diversity.

Figure 13: Dietary Diversity in Different Income Groups

Relationship Between Income Level and HDDs (N=1174) Corelation Coefficient 'r'=0.23

120.0% 95.2% 97.6% 100.0% 77.8% 80.0% 60.0% 40.0% 22.2% 20.0% 4.8% 2.4% 0.0% 0.0% 0.0% 0.0% Good Diet Diversity (N=1126) Medium Diet Diversity (N=48) Low Diet Diversity (N=0)

BDT <5,000 BDT 5,000 BDT To 10,000 BDT > 10,000

Percentage of households with good dietary diversity is highest among the households having monthly average income above BDT 10,000. In contrast, percent of households with medium dietary diversity is highest among the households whose monthly average income is less than BDT 10,000. That means dietary diversity is directly interrelated with income level. Households with lower income have lower dietary diversity.

3.9.4 Minimum Dietary Diversity for Women (MDD-W)

The women dietary diversity score (WDDS) reflects the probability of micronutrient adequacy of the diet and therefore the food groups included in the score are tailored towards this purpose. Vegetables and fruits were further segregated into specific categories based on their content of micronutrients’ availability. Consumption of foods were grouped into 10 categories proposed by FAO Guidelines for measuring individual dietary diversity to estimate the WDDS scores. Women dietary diversity score below five was considered as poor dietary intake that recommends diversified micronutrient needs from both plant and animal source of food. Additional variable for the consumption of diversified food groups considering nutrient density of food was analysed to understand the dietary adequacy of micronutrients in their diet.

Figure 14 : Status of women dietary diversity

In Sitakunda Upazila, mean women dietary Women Dietary Diversity (N=1149) diversity was 5.0. The minimum dietary diversity was reported as poor among 39.7% of women of reproductive age as consumed less diversified 39.7% foods in their diet lacking adequate nutrition for this 60.3% age group. 60.3% of women of reproductive age consumed food in line with the good dietary diversity. This means that in Sitakunda Upazila, majority of the women are more likely to have higher (more adequate) micronutrient intakes. Good (≥5) Poor (0 to 4)

Table 30: Consumption patterns of different foods groups in the previous day Food Groups N=1149 Overall % of Women Grains, Roots, Tubers 1148 99.9% Pulse 512 44.6% Nuts and Seeds 271 23.6% Dairy Products 764 66.5% Meat or Fish 918 79.9% Organ Meat 129 11.2% Egg 381 33.2% Dark Green Leafy Vegetables 219 19.1% Vitamin A rich fruits & vegetables 217 18.9% Vitamin C rich fruits & vegetables 910 79.2% Other fruits 332 28.9% Other vegetables 962 83.7% Fats, Oil 1148 99.9%

Staple foods (99.9%), meat and fishes (79.9%) and pulses (44.6%) dominated the food consumption in last 24 hours. Consumption status of nutrition dense foods are - dark green leafy vegetables (19.1%), Vitamin A rich fruits and vegetables (18.9%), milk and dairy foods (66.5%), legumes, nuts and seeds (23.6%), egg consumption (33.2%) and organ meat consumption (11.2%) by the women in the households.

Figure 15: Consumption patterns of food groups based on nutrient density Consumption Patterns For Specific Food Group (N=1149) 120.0%

100.0%

80.0%

60.0% 93.5% 99.9% 99.7% 40.0% 84.1% 57.2% 20.0%

0.0% Animal Source Food Pulses, Nuts and Fruits and Grains, Roots, Fats and Oils (Meat,Fish,Egg, Milk Seeds Vegetables Tubers Product) Nutrient rich foods Low nutrient rich foods

Data was further analysed to explore the consumption patterns for specific food groups considering the nutrient density in their diets. It was identified that overall 93.5% of women consumed animal protein from either meat, fish, eggs or dairy products in the previous day, whereas 57.2% women consumed either pulses, nuts or seeds and 84.1% women consumed fruits and vegetables (including Vitamin A rich and dark green leafy vegetables) from plant sources. In contrast, grains, roots and tubers (99.9%), fats and oils (99.7%), mostly dominated the consumption of low nutrient density foods.

3.9.5. Household Reduced Coping Strategy Index (rCSI)

Reduced Coping Strategy Index (rCSI) was employed to understand the different behaviours related to food consumption as a coping strategy with food shortage induced from inadequate income of access related problems. It provides information on the way households respond when they face limited access to sufficient food. The analysis of these behaviours helps understanding the food insecurity situation. The r-CSI helps identifying areas and population groups at risk or suffering from food insecurity. It also allows estimating the impact of an intervention. In addition, the r-CSI can be used as an early warning indicator. It also helps to understand the level of food insecurity among the targeted beneficiaries’ households. Higher the Coping Strategy Index (CSI) score indicates higher level of food insecurity and vice versa.

Figure 16: Overall coping strategies. Overall Coping Strategies (N=1174) 100.0% 87.2% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.8% 10.0% 2.0% 0.0% No or low coping (CSI score 0 -3) Medium coping (CSI score 4 – 9) High Coping (CSI score ≥ 10

The average rCSI (reduced Coping Strategy Index) score of the sample households is 1.1 among the surveyed households in Sitakunda Upazila. Majority of the households (87.2%) have no or low rCSI score, which indicates good food security status among the surveyed households.

Figure 17: Coping strategies by income groups Relationship Between Income Level and rCSI (N=1174) Corelation Coefficient 'r'=-0.31 120.0% 98.3% 100.0% 78.9% 80.0%

60.0% 48.1% 40.0% 29.6% 22.2% 18.3% 20.0% 2.8% 1.7% 0.0% High rCSI (N=23) Medium rCSI (N=127) Low rCSI (N=1024) BDT <5,000 BDT 5,000 BDT To 10,000 BDT >10,000

Among the surveyed households whose monthly income is comparatively low have higher coping strategy index score meaning that they have to rely on different negative coping strategies to adjust with access related problems. In contrast, percent of households is very low (only 2.8%) who have relatively higher income level but relied on high coping strategies. Figure 17 shows coping strategies different income groups.

Figure 18: Types of coping strategies Overall Copping Strategies (n=1174)

Reduce the number of meal eaten per day 8.6%

Restrict consumption by adults so that small 7.1% children can eat

Reduce meal size at meal times 14.1%

Borrow food or rely on help from 21.3% neighbour/relatives

Rely on less preferred & less expensive foods 15.8%

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% A large number of surveyed households mentioned that they had to rely on severe coping strategies such as “restrict food consumption by adults so that small children can eat” (7.1%) and “borrow food or rely on help from neighbour or relatives” (21.3%).

3.10 Water and Sanitation

3.10.1 Main sources of water The main source of drinking water was shallow tube-well as reported by the respondents (70.8%) and deep tube-well is only 22.1%. There is no other dominated source of drinking water in the area. As the main source of drinking water is shallow tube-well, so it is very important to check the water quality of shallow tube-well because it has a potential threat to be contaminated.

Figure 19: Main Source of Drinking water

Source of Water (N=1174) Tubewell (shallow)

1.1% 3.1% 3.0% Tubewell (deep)

Protected well

Unprotected well

22.1% Rainwater harvesting Surface water (river, stream, pond)

Pond Sand Water 70.8% Piped network

Arsenic, Iron removal plant (AIRP)

Others

3.10.2 Distance to water source Just over 70% of the households are close the water source i.e. within 150 feet. On the other hand, 28.4% households had to collect drinking water from the source, which is more than 150 feet. Therefore, it is necessary to install more water points to meet the national standard (DPHE/HYSAWA). The Bangladesh 35

standard of safe distance between water source and nearest latrine is at least 30 feet. Survey findings revealed that more than half (55.6%) of the latrine did not follow the standard that means potential risk is there for faecal contamination of water source. It is very important findings of the survey in deed.

Figure 20: Distances of water source from house Figure 21: Distance of water source and latrine facility

80.0% 71.6% 60.0% 55.6% 70.0% 50.0% 60.0% 38.0% 50.0% 40.0% 40.0% 30.0% 28.4% 30.0% 20.0% 20.0% 6.4% 10.0% 10.0% 0.0% 0.0% 0 to 150 feet More than 150 0 to 30 feet 30 to 100 100+feet feet feet

Figure 22 : Water Collation and Women 1.9% 0.8% 8.6% In addition, it is interesting to note that 97.4% of the households’ women including girls and adult women were solely responsible to collect water from source of drinking. This particular task is very gender biased which 88.8% needs special attention to reduce the burden of women.

Adult women Girls Adult man Boys

3.10.3 Water Transport and Storage For the most part water is stored and transported properly. Most people wash their water storage containers daily.

Table 31: Washing behaviour of storage container Frequency N=1174 Overall % of HH Everyday 1111 94.6% Twice per week 58 4.9% Once per week 5 0.4% Less than once per week 0 0.0%

More than half of the respondents reported that they covered their water containers either always (60.7%) or sometimes (11.24%) during transport of water and 28.1% of the respondents did not cover their container.

Water transport and storage is an important component of hygiene promotion activities and should be considered as a component in future projects in Sitakunda Upazila.

3.10.4 Sanitation and Hygiene About 50.5% of the households were using latrines with unmanaged faecal sludge, which is very dangerous, and below the national average. On the other hand, though about 49.5% of the households were using hygienic latrine but the so-called septic tank was not properly designed according to observation, which has also a potential threat to contamination of ground water. Therefore, it is very necessary to focus on this particular area of faecal sludge management.

Table 32: Category of sanitary latrines by percentage of households Type of Latrine N=1174 Overall % of HH Status Piped with sewerage system 1 0.1% Latrine with septic tank 184 15.7% Hygienic Latrine Ring slab latrine with water seal 396 33.7% (49.5%) Ring slab latrine without water seal 426 36.3% Latrine with broken pit 154 13.1% Hanging latrine 4 0.3% Un Hygienic Latrine Open defecation (nearby roads, river, (50.5%) 9 0.8% field, jungle etc.) Others 0 0.0%

The situation of child faeces management of the survey community was not comfortable. About 17.5% of the respondents just threw child faeces out of compound (in open) and 24.8% faeces put into solid waste that indicating most of child faeces were not properly managed. When the national coverage of ODF is ‘Zero’ and still the present situation of the targeted community is far from it. It is very important to consider during project design in this specific area.

Table 33: Disposal of children's faeces percentage of households Child defecation and disposal N=650 Overall % of HH Child used latrine 202 31.1% Picked up and threw in latrine 122 18.8% Left in the open where child defecated 51 7.8% Buried or covered with soil/ash 0 0.0% Picked up and thrown in solid waste pile 161 24.8% Picked up and thrown out of compound (in open) 114 17.5%

3.10.5 Hand washing Behaviour

Table 34: Hand washing behaviour with soap Handwashing behaviour N=1117 % in surveyed HH Before cooking 176 15.8% After defecation 1054 94.4% Before eating food 414 37.1% After disposing child's faeces/cleaning child 469 42.0% After working with animals, crops etc. 307 27.5% 37

Before feeding child 140 12.5% Before breast-feeding to child 17 1.5% After sneezing 0 0.0% After handing money 0 0.0% Others 557 49.9%

The interviewees were asked about the hand washing practices and sanitation practices in general. About 94.4% of the respondents mentioned that they washed their hands with soap after defecation followed by 37.1% of them washing hands with soap before eating foods. After disposing child’s faeces or cleaning child, only 42.0% caregivers washed their hand with soap, which is very alarming. It is very alarming that only 12.5% of the respondents washed their hands with soap before child feeding. It was also identified that only 12.7% respondents used soap as hand washing materials and most of the respondents (87%) used only water for hand washing. Only 40.7% of the surveyed households, the enumerators confirmed presence of soap nearby latrine. If we consider it as an indicator of overall sanitation practice of the area it can be concluded that the sanitation practice and knowledge regarding it is not in satisfactory level and demands focus to improve the situation.

Figure 23: Hand washing material Figure 24: Soap available in household

What materials used to wash hands? (N=1174) Was soap available in HH? (N=1174)

100.0% 87.0% 90.0% 80.0% 70.0% 60.0% 40.7% 50.0% 40.0% 59.3% 30.0% 20.0% 12.7% 10.0% 0.2% 0.2% 0.0% Water only Water and Water and Water and ash sand/mud soap Yes No

4. Discussion and Conclusion

4.1 Nutrition and Health

 The prevalence of Global Acute Malnutrition percentage by WHZ and/or oedema was found to be poor according to the WHO emergency thresholds. If we are to estimate the prevalence of acute malnutrition in the Upazila, it represents nearly 3,683 SAM and MAM children (39177 under 5 children *9.4% GAM) and 392 SAM children (39,177 under 5 children * 1.0% SAM). Severely acute malnourished children are in need of immediate life-saving treatment for their recovery and to prevent sudden risk of death. The survey GAM prevalence also recommends to continue and reinforce the community-based management of acute malnutrition linked with government health facilities to treat and prevent acute malnutrition among children and returns to normal growth and development.

 The prevalence of Global Acute Malnutrition by MUAC was found to be 3.4% (2.4 - 5.0 95% C.I.) in Sitakunda Upazila. The assessment findings also revealed that the prevalence of GAM (3.4%) by MUAC was found to be lower compared to the prevalence of GAM (9.4%) by WHZ score. MUAC also identified 38

younger children for SAM and MAM. About 75% (18 out of 24) of those identified as malnourished either with MAM or SAM were in the age group of 6-17 months and all of the children (24 out of 24) were in the age group of less than 29 months. Being an absolute measure, MUAC mostly detects younger children. According to MUAC, gender based analysis found no significant difference (p= 0.679) in the GAM prevalence although MUAC instrument is biased to detect both more girls than boys and younger children.

 The overall prevalence of underweight, based on WAZ was found to be 26.4 % (22.7 - 30.4 95% C.I.) with 4.9 % (3.5 - 6.8 95% C.I.) of the children assessed being severely underweight; this is nearly close to the critical mark of 30% as set by WHO thresholds for nutritional emergency. There was no significant difference (p=0.223) in the prevalence of underweight between boys and girls. This indicates chronic episodes of hunger, insufficient food intake, access, and could point towards a historically bad state of household food security. Moreover, with such high numbers, where one in every three children are underweight, requires immediate intervention and assessment on the ground on food security and nutrition intake within the households. It also calls for an immediate Nutritional Causal Analysis on the

ground.

 The prevalence of stunting in Sitakunda Upazila found to be quite high (31.1%) with almost one in every three children are stunted. Nearly 12,184 children (39,177 under five children* 31.1% stunted) aged 6-59 months are shorter compared to their age with an estimated 4,897 severely stunted (39,177 under five children* 12.5% stunted). This can be interpreted as large population of children in Sitakunda Upazila are suffering from chronic malnutrition and many of them are probably at risk of permanently damaging their mental, physical health, growth, undermining their future productivity and therefore income. This might indicate that deficiency of continued nutritious food intake even after two years, which is a serious concern for the child’s appropriate growth to the fullest possible potentials. There was no significant difference (P=0.846) in prevalence of stunting found between boys and girls.

 The morbidity patterns among the children indicated that more than half (59.4%) of the children suffered from infectious diseases in the last 14 days which is very alarming and that might be attributed to the poor nutritional status. More than one third of the children vastly reported fever (41.5%) and ARI (43.3%) and followed by diarrhoea (9.9%) and other diseases (2.1%) reported as skin diseases, mouth and eye infections, tumour etc. Among the illness reported children, most of the parents/caregivers (87.7%) had treatment seeking behaviour and received treatment from different sources. The study also revealed that nearly two third of the illness reported children (63.1%) were managed by traditional healers, imam, untrained village doctors and nearest pharmacy that representing a low percentage of children received treatment from government hospitals (9.9%) and private clinic (14.7%).

 On the other hand, the coverage of vitamin A and measles vaccination found remarkably good but still below than the Sphere Standard’s recommendation of 95 % coverage at Sitakunda Upazila as assessed by 90.8% children (6-59months) who received vitamin A in the last six months and 91.0% children (9-59 months) who received measles immunization.

4.2 Child Care including Infant and Young Child Feeding (IYCF) Practices14

First two years of life is the critical window of opportunity for ensuring children's appropriate growth and development through optimal feeding and care practices. Poor nutrition during this window can lead new- born and child morbidity, mortality, and irreversible damage in child that are attributed to IYCF practices.

14 Sample size for IYCF indicators is too small to validate the results: ONLY an indication, NOT a representative. 39

During this study, IYCF results as assessed by inadequate sample size could not generalize the entire population; it can be an indication for future planning and further in-depth analysis.

 The IYCF results revealed that more than half of the mothers did not initiated (early initiation of BF- 43.1%) breast-feeding within 1 hour after birth and the prevalence of exclusively breast feeding (EBF) found almost similar (60.7%) with national prevalence of EBF (55%; BDHS 2014) where approximately 73.9% mothers continued breastfeeding their children at 2 years. Proper breast-feeding is a positive practice that helps to increase immunity of child as well as prevent post-partum haemorrhage, maternal morbidity and so on. It also works to increase emotional bonding very quickly between mother and child. More focused behaviour change activities should be implemented to encourage the practices of exclusive breastfeeding, which is requisite for optimal growth and development, as well as to protect the child from various forms of disease.

 The survey findings indicated that overall minimum dietary diversity was 37.6% whereas minimum meal frequency for children aged 6-23 months was 66.8%.This indicates a good percentage of children received complementary food from 6 months following recommended feeding frequency though they were not receiving adequate diversified food. The study also revealed that one in every three children (30.4%) had an acceptable diet meaning that most of the children were not feeding from recommended minimum four food groups following minimum meal frequency that are essential for proper growth and development.

 The perceived difficulties or challenges of the mothers on childcare practices in this study refer to poor resources and practices linked to parenting, family support and maternal stress rather than lack of knowledge. Strong evidences are found about difficulties to child feeding practices (86.1 %) which might contribute to force feeding or lack of consistency of feeding according to children’s needs. Poor family support system (31.7%) was also found in this study which can result due to cultural practices or perceptions towards mother as the main caregiver, lack of knowledge of the father or family members regarding the impact of not helping the mother in the child care and also lack of psychological empowerment of the mothers’ to ask for support. Feeling lack of interest in childcare (5.2%) and feeling of running out of energy (24.8%) both are core symptoms linked to depression or stress, which might result poor childcare as well as poor child nutrition also. Therefore, it can be said that poor maternal mental health, lack of childcare skills and family support all might contribute to poor child’s nutrition status in the surveyed area.

 The question refers to a holistic knowledge of a mother, which is necessary as a caregiver for child’s optimum growth and development. The knowledge includes the need of food, health care, parental stimulation and encouragement, safe environment and discipline. The result referred that they felt the need of adequate feeding but was not aware about child stimulation through play that might limit child’s motor development. However, specific actions like talking to the child was found lesser. It means that the population has poor knowledge about verbal stimulation that might limit children’s language as well as cognitive development. Another cognitive developmental stimulation is encouragement to child to explore things; this knowledge was found also low (12.3 %) which is associated with reinforcement of child’s intelligence. Giving love, warm and support for emotional development was also lower (34.7%) which might have an impact on mother-child relationship. Evidence shows that poor mother child relationship may lead to poor childcare practice and contribute to develop child’s undernutrition problem (ACF MHCP Policy, 2011). Need of discipline for better development of children reported by most of the survey respondents, which is an essential component of parenting. However, good knowledge for the need of clean and safe environment might indicate good hygienic environment and practice. Regarding rest of 40

the participants who do not have a clear knowledge of good hygienic environment might indicate that there is a risk factor for children’s sickness as well as malnutrition.

4.3 Food Security and Livelihoods  Overall, the monthly average income of the surveyed households was BDT 12,771 in Sitakunda Upazila. Salaried or wage labourer is the main source of income that accounts for 26.9% of the surveyed households that is highest among the income sources. Skilled or unskilled wage labour is the second highest income source that accounts for 17.6% and 17.5% of the surveyed households respectively. Other remarkable income sources are remittance (11.0%), small commercial activities (10.2%), agriculture or sales of crops (5.7%) and fishing in open water bodies (5.0%).

 During the study, seven occupations (salaried job or wage employee, skilled/unskilled labour, remittance, small commercial activities, agriculture & sales of crops and fishing) were identified as most common and representing 94.0% of the surveyed households whereas only 6.0% of the surveyed household’s main income source were petty trade, sales of livestock, handicrafts, collection of natural resources, gift, etc.  Around 2.3% of the surveyed households in Sitakunda Upazila have monthly income less than BDT 5,000 that is less than the emergency Minimum Expenditure Basket (MEB), meaning that they are highly food insecure. Out of surveyed households, 51.3% have monthly income in between BDT 5,000 to BDT 10,000 and 46.4% have monthly income above BDT 10,000.

 The most common food sources in Sitakunda Upazila were reported as purchase (95.5%) and own production (4.5%). As most of the household’s food source is purchase, meaning that market access is very crucial for food security in the surveyed areas. Food price hike or drop of income due to any man made or natural disasters have big negative impact on the food security of the low-income groups in the survey area.

 Mean Household dietary diversity Score (HDDS) was found 8.3 that indicates very good dietary diversity status among the surveyed households. Overall, 95.9% have good dietary diversity and 4.1% households have medium dietary diversity. None of the surveyed households has low or poor dietary diversity. A direct correlation between household dietary diversity and income level was found among the surveyed households. The percent of households with good dietary diversity is highest among the households having monthly average income above BDT 10,000. In contrast, percent of households with medium to low dietary diversity is highest among the households whose monthly average income is less than BDT 10,000.Households with lower income have lower dietary diversity.

 39.7% of women of reproductive age (15-49yrs) with poor dietary diversity meaning that these women did not consume food items from at least 5 out of 10 defined food groups during the previous 24 hours. That means, probably women did not manage to consume animal proteins, pulses and fruits or vegetables that might be reflected inadequacy of micronutrient in their diets. 60.3% of women achieved minimum dietary diversity meaning that a good percentage of women are more likely to have higher (more adequate) micronutrient intakes.

 The average rCSI (reduced Coping Strategy Index) score of the sample households is 1.1 among the surveyed households in Sitakunda Upazila. Majority of the households (87.2%) have no or very low coping strategy, which indicates good food security situation among the surveyed households. Number of surveyed households who mentioned that they had to rely on sever coping strategies such as “restrict

food consumption by adults so that small children can eat” and “borrow food or rely on help from neighbour or relatives” was respectively 7.1% and 21.3%.

 Among the surveyed households whose monthly income is less than BDT 5,000 have high coping strategy index score meaning that they have to rely on different negative coping strategies to adjust with access related problems.

4.4 Water, Sanitation and Hygiene  The main source of drinking water was shallow tube-well as reported by the respondents (70.8%) As the main source of drinking water is shallow tube-well, so it is very important to check the water quality of shallow tube-well. We should keep in mind that it has a potential threat to be contaminated from secondary source. It is also very interesting findings female including both girls and adult women were solely responsible to collect water from source of drinking which was about 97.4%. This particular task is very gender biased which need special attention to reduce the burden of female.

 About 71.6% households are close the water source within 150 feet which is a very good picture indeed. On the other hand, 28.4% households have to collect drinking water from the source that is more than 150 feet. Therefore, it has a necessity to install more water point to meet the national standard (DPHE/HYSAWA).

 On the other hand, the Bangladesh standard of safe distance between water source and nearest latrine is at least 30 feet. Survey findings revealed that more than half (55.6%) of the latrine did not follow the standard which means potential risk is there for faecal contamination of water source. Ii is very important findings of the survey in deed.

 More than half of the respondents reported that they covered their water containers either always (60.7%) or sometimes (11.2%) during transport of water and 28.1% of the respondents did not cover their container. As it is very important for hygiene promotion activities, so, we should keep it in mind during design of project

 It was revealed from the analysis that about 50.5% of the households were using latrines with unmanaged faecal sludge, which is very dangerous, and below the national average. On the other hand, though about 49.5% of the households were using unhygienic latrines but the so-called septic tank was not properly designed according to observation, which has also a potential threat to contamination of ground water. Therefore, it is very necessary to focus on this particular area of faecal sludge management.

 The situation of child faeces management of the survey community was not comfortable. About 17.5% of the respondents just threw child faeces out of compound (in open) and 24.8% caregivers put the child faeces into solid waste that indicating most of child faeces were not properly managed. When the national coverage of ODF is ‘Zero’ and still the present situation of the targeted community is far from it. It is very important to consider during project design in this specific area.

 It was a very important question to know the behaviour of hand washing as well as sanitation behaviour in general. About 94.4% of the respondents mentioned that they washed their hands with soap after defecation followed by 15.8% of them washing hands with soap before eating foods. After disposing child’s faeces or cleaning child, only 42% caregivers washed their hand with soap, which is very alarming indeed. It is very alarming that only 12.5% of the respondents washed their hands with soap before child feeding. It was also found that only 12.7% respondents used soap as hand washing materials and most of the respondents (87%) used only water for hand washing. Only 40.7% of the surveyed households, the enumerators confirmed presence of soap nearby latrine. If we consider it as an indicator of overall 42

sanitation practice of the area it can be concluded that the sanitation practice and knowledge regarding it is not in satisfactory level and demands focus to improve the situation.

5. Limitation and Bias The team strived to overcome all biases by strictly following SMART methodology and tools. Sitakunda Upazila is located in the industrial belt region with small communities of ethnic minorities in the hilly area and some clusters required long travel time; however, thanks to the strong supervision and cooperation from local government authorities, no security incident was reported during the survey. SMART methodology recommends calculating the sample size for anthropometric indicators and therefore, no separate sample size was calculated for IYCF indicators. It should be noted that IYCF indicators require a larger sample size, and therefore the results of the IYCF indicators in Sitakunda Upazila is only an indication for future planning and direction and is NOT representative for the whole population.

6. Ethical Considerations

During the survey, children found to be wasted (MUAC < 125 mm and/or presence of bilateral oedema) were referred to the community nutrition centre run by action Against Hunger in close collaboration with Upazila health complex for the management acute malnourished children. Two forms were completed: one copy was given to caregiver and the other was used for follow-up. Any refusal household was not replace by another.

7. Recommendations and priorities

Nutrition, Health and Mental Health and Care practices

Food Security and Livelihoods (FSL)

8. Appendices

Appendix 1: Plausibility Report Standard/Reference used for z-score calculation: WHO standards 2006 (If it is not mentioned, flagged data is included in the evaluation. Some parts of this plausibility report are more for advanced users and can be skipped for a standard evaluation)

Overall data quality

Criteria Flags* Unit Excel. Good Accept Problematic Score

Flagged data Incl % 0-2.5 >2.5-5.0 >5.0-7.5 >7.5 (% of out of range subjects) 0 5 10 20 0 (0.4 %)

Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 4 (p=0.041)

Age ratio(6-29 vs 30-59) Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 0 (p=0.123)

Dig pref score - weight Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (4)

Dig pref score - height Incl # 0-7 8-12 13-20 > 20 0 2 4 10 2 (8)

Dig pref score - MUAC Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (7)

Standard Dev WHZ Excl SD <1.1 <1.15 <1.20 >=1.20 . and and and or . Excl SD >0.9 >0.85 >0.80 <=0.80 0 5 10 20 0 (0.95)

Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (0.16)

Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (0.03)

Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 1 (p=0.014)

OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 7 %

The overall score of this survey is 7 %, this is excellent.

There were no duplicate entries detected.

Missing or wrong data:

HEIGHT: Line=6/ID=1, Line=202/ID=1, Line=625/ID=1 Percentage of children with no exact birthday: 2 %

Anthropometric Indices likely to be in error (-3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 for WAZ, from 45

observed mean - chosen in Options panel - these values will be flagged and should be excluded from analysis for a nutrition survey in emergencies. For other surveys this might not be the best procedure e.g. when the percentage of overweight children has to be calculated):

Line=6/ID=1: WAZ (-6.159), Weight may be incorrect Line=16/ID=1: HAZ (-4.806), Height may be incorrect Line=35/ID=1: WAZ (1.710), Age may be incorrect Line=206/ID=1: WHZ (2.404), WAZ (1.955), Weight may be incorrect Line=291/ID=2: HAZ (-6.093), WAZ (-5.043), Age may be incorrect Line=353/ID=1: HAZ (-6.260), WAZ (-4.647), Age may be incorrect Line=388/ID=1: WHZ (2.434), WAZ (1.905), Weight may be incorrect Line=464/ID=2: HAZ (1.468), WAZ (1.905), Age may be incorrect Line=579/ID=1: WHZ (2.411), Weight may be incorrect Line=625/ID=1: WAZ (-6.969), Weight may be incorrect Line=661/ID=1: HAZ (-5.057), Age may be incorrect Line=678/ID=1: HAZ (-4.643), Age may be incorrect

Percentage of values flagged with SMART flags:WHZ: 0.4 %, HAZ: 0.9 %, WAZ: 1.1 %

Age distribution:

Month 6 : ##### Month 7 : ################ Month 8 : ################# Month 9 : ############## Month 10 : ################# Month 11 : ###################### Month 12 : ################ Month 13 : ######### Month 14 : ############## Month 15 : ######## Month 16 : ################# Month 17 : ############### Month 18 : ############### Month 19 : ############ Month 20 : ########## Month 21 : ######### Month 22 : ######### Month 23 : ##################### Month 24 : ########## Month 25 : ############## Month 26 : ################### Month 27 : ############### 46

Month 28 : ############## Month 29 : ############### Month 30 : ################# Month 31 : ####### Month 32 : ########### Month 33 : ##################### Month 34 : ############### Month 35 : ############ Month 36 : ############### Month 37 : ############# Month 38 : ########### Month 39 : ################## Month 40 : ############# Month 41 : ######### Month 42 : ####### Month 43 : ########### Month 44 : ########## Month 45 : ########### Month 46 : ############# Month 47 : ############ Month 48 : ############## Month 49 : ########### Month 50 : ############### Month 51 : ############ Month 52 : ############### Month 53 : ######### Month 54 : ########### Month 55 : ############# Month 56 : ########### Month 57 : ####### Month 58 : ############# Month 59 : ##### Month 60 : ###

Age ratio of 6-29 months to 30-59 months: 0.96 (The value should be around 0.85).: p-value = 0.123 (as expected)

Statistical evaluation of sex and age ratios (using Chi squared statistic):

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 106/87.2 (1.2) 72/74.7 (1.0) 178/161.9 (1.1) 1.47 18 to 29 12 73/85.1 (0.9) 90/72.8 (1.2) 163/157.9 (1.0) 0.81 30 to 41 12 96/82.4 (1.2) 62/70.6 (0.9) 158/153.0 (1.0) 1.55 42 to 53 12 70/81.1 (0.9) 69/69.5 (1.0) 139/150.6 (0.9) 1.01 54 to 59 6 31/40.1 (0.8) 29/34.4 (0.8) 60/74.5 (0.8) 1.07 ------47

6 to 59 54 376/349.0 (1.1) 322/349.0 (0.9) 1.17

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.041 (significant excess of boys) Overall age distribution: p-value = 0.228 (as expected) Overall age distribution for boys: p-value = 0.021 (significant difference) Overall age distribution for girls: p-value = 0.197 (as expected) Overall sex/age distribution: p-value = 0.000 (significant difference)

Digit preference Weight:

Digit .0 : ######################################### Digit .1 : #################################### Digit .2 : ###################################### Digit .3 : ############################## Digit .4 : ################################ Digit .5 : ######################################## Digit .6 : #################################### Digit .7 : ################################## Digit .8 : ############################### Digit .9 : ##############################

Digit preference score: 4 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.535

Digit preference Height:

Digit .0 : ############## Digit .1 : ############################################### Digit .2 : ###################################### Digit .3 : ############################################ Digit .4 : ########################################## Digit .5 : ############################## Digit .6 : #################################### Digit .7 : ################################ Digit .8 : #################################### Digit .9 : #############################

Digit preference score: 8 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.000 (significant difference)

Digit preference MUAC:

Digit .0 : ########################## Digit .1 : ################################ Digit .2 : ################################# Digit .3 : ################################## Digit .4 : ################################################# Digit .5 : ######################## Digit .6 : ######################################## Digit .7 : ################################### Digit .8 : ######################################### Digit .9 : ##################################

Digit preference score: 7 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.001 (significant difference)

Evaluation of Standard deviation, Normal distribution, Skewness and Kurtosis using the 3 exclusion (Flag) procedures

. no exclusion exclusion from exclusion from . reference mean observed mean . (WHO flags) (SMART flags) WHZ Standard Deviation SD: 0.97 0.97 0.95 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: calculated with current SD: calculated with a SD of 1:

HAZ Standard Deviation SD: 1.06 1.03 1.01 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 31.5% 31.3% 31.1% calculated with current SD: 33.9% 33.0% 32.2% calculated with a SD of 1: 32.9% 32.4% 32.1%

WAZ Standard Deviation SD: 1.05 1.01 0.97 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 26.6% 26.4% calculated with current SD: 28.2% 27.1% calculated with a SD of 1: 27.3% 26.8%

Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.006 p= 0.006 p= 0.116 HAZ p= 0.000 p= 0.231 p= 0.468 WAZ p= 0.000 p= 0.040 p= 0.799 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed)

Skewness 49

WHZ 0.26 0.26 0.16 HAZ -0.35 -0.16 -0.09 WAZ -0.22 0.10 0.05 If the value is: -below minus 0.4 there is a relative excess of wasted/stunted/underweight subjects in the sample -between minus 0.4 and minus 0.2, there may be a relative excess of wasted/stunted/underweight subjects in the sample. -between minus 0.2 and plus 0.2, the distribution can be considered as symmetrical. -between 0.2 and 0.4, there may be an excess of obese/tall/overweight subjects in the sample. -above 0.4, there is an excess of obese/tall/overweight subjects in the sample

Kurtosis WHZ 0.25 0.25 0.03 HAZ 0.91 0.21 -0.04 WAZ 1.89 0.59 0.09 Kurtosis characterizes the relative size of the body versus the tails of the distribution. Positive kurtosis indicates relatively large tails and small body. Negative kurtosis indicates relatively large body and small tails. If the absolute value is: -above 0.4 it indicates a problem. There might have been a problem with data collection or sampling. -between 0.2 and 0.4, the data may be affected with a problem. -less than an absolute value of 0.2 the distribution can be considered as normal.

Test if cases are randomly distributed or aggregated over the clusters by calculation of the Index of Dispersion (ID) and comparison with the Poisson distribution for:

WHZ < -2: ID=1.42 (p=0.014) WHZ < -3: ID=0.91 (p=0.686) GAM: ID=1.42 (p=0.014) SAM: ID=0.91 (p=0.686) HAZ < -2: ID=1.20 (p=0.133) HAZ < -3: ID=1.26 (p=0.079) WAZ < -2: ID=1.26 (p=0.076) WAZ < -3: ID=0.97 (p=0.545)

Subjects with SMART flags are excluded from this analysis.

The Index of Dispersion (ID) indicates the degree to which the cases are aggregated into certain clusters (the degree to which there are "pockets"). If the ID is less than 1 and p > 0.95 it indicates that the cases are UNIFORMLY distributed among the clusters. If the p value is between 0.05 and 0.95 the cases appear to be randomly distributed among the clusters, if ID is higher than 1 and p is less than 0.05 the cases are aggregated into certain cluster (there appear to be pockets of cases). If this is the case for Oedema but not for WHZ then aggregation of GAM and SAM cases is likely due to inclusion of oedematous cases in GAM and SAM estimates.

Are the data of the same quality at the beginning and the end of the clusters? Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 1.03 (n=66, f=0) ########## 02: 1.04 (n=66, f=1) ########## 03: 1.02 (n=66, f=0) ######### 04: 1.12 (n=66, f=1) ############# 50

05: 0.81 (n=64, f=0) 06: 0.96 (n=63, f=1) ####### 07: 1.01 (n=58, f=0) ######### 08: 0.79 (n=54, f=0) 09: 0.90 (n=44, f=0) #### 10: 0.88 (n=42, f=0) ### 11: 0.91 (n=37, f=0) #### 12: 1.11 (n=28, f=0) ############# 13: 0.90 (n=18, f=0) OOOO 14: 1.00 (n=10, f=0) ~~~~~~~~ 15: 1.03 (n=06, f=0) ~~~~~~~~~ 16: 0.85 (n=03, f=0) ~~

(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)

Analysis by Team

Team 1 2 3 4 5 6 n = 97 138 100 97 130 136 Percentage of values flagged with SMART flags: WHZ: 2.1 0.7 1.0 1.0 0.0 0.7 HAZ: 1.0 0.0 2.0 0.0 2.3 2.2 WAZ: 0.0 0.7 1.0 1.0 2.3 1.5 Age ratio of 6-29 months to 30-59 months: 1.37 1.09 0.89 1.02 0.76 0.81 Sex ratio (male/female): 0.80 1.06 1.38 1.31 1.20 1.34 Digit preference Weight (%): .0 : 8 14 17 6 14 10 .1 : 12 11 12 9 9 9 .2 : 11 8 9 12 15 9 .3 : 10 8 8 6 10 10 .4 : 5 9 6 15 6 13 .5 : 8 14 11 12 12 11 .6 : 11 11 11 9 9 11 .7 : 9 9 8 11 11 11 .8 : 11 9 11 8 7 7 .9 : 12 8 7 9 7 10 DPS: 7 7 10 9 10 5 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 6 1 6 4 5 4 .1 : 11 14 11 23 8 16 .2 : 11 12 14 6 9 12 .3 : 6 15 14 8 16 13 .4 : 10 19 10 10 10 10

.5 : 13 2 10 6 15 8 .6 : 9 13 10 5 9 13 .7 : 10 7 8 13 10 9 .8 : 13 12 8 11 11 7 .9 : 9 6 8 12 7 9 DPS: 7 19 8 17 10 11 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference MUAC (%): .0 : 6 3 14 3 9 10 .1 : 8 13 5 4 11 11 .2 : 9 9 7 10 8 12 .3 : 9 8 6 11 14 10 .4 : 13 20 7 10 13 17 .5 : 10 3 11 10 5 4 .6 : 10 13 17 14 11 6 .7 : 9 13 11 4 12 9 .8 : 12 12 16 14 8 10 .9 : 11 6 6 18 8 12 DPS: 7 17 14 15 9 11 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 0.99 0.97 0.93 1.02 0.96 0.95 Prevalence (< -2) observed: % 8.2 Prevalence (< -2) calculated with current SD: % 9.9 Prevalence (< -2) calculated with a SD of 1: % 9.3 Standard deviation of HAZ: SD 1.09 0.99 1.07 1.08 1.08 1.08 observed: % 35.4 41.4 23.7 35.4 25.2 calculated with current SD: % 34.5 35.8 31.9 38.3 30.3 calculated with a SD of 1: % 33.1 34.8 30.6 37.4 28.8

Statistical evaluation of sex and age ratios (using Chi squared statistic) for:

Team 1:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 14/10.0 (1.4) 16/12.5 (1.3) 30/22.5 (1.3) 0.88 52

18 to 29 12 13/9.7 (1.3) 13/12.2 (1.1) 26/21.9 (1.2) 1.00 30 to 41 12 11/9.4 (1.2) 12/11.8 (1.0) 23/21.3 (1.1) 0.92 42 to 53 12 4/9.3 (0.4) 10/11.7 (0.9) 14/20.9 (0.7) 0.40 54 to 59 6 1/4.6 (0.2) 3/5.8 (0.5) 4/10.4 (0.4) 0.33 ------6 to 59 54 43/48.5 (0.9) 54/48.5 (1.1) 0.80

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.264 (boys and girls equally represented) Overall age distribution: p-value = 0.048 (significant difference) Overall age distribution for boys: p-value = 0.066 (as expected) Overall age distribution for girls: p-value = 0.632 (as expected) Overall sex/age distribution: p-value = 0.018 (significant difference)

Team 2:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 17/16.5 (1.0) 12/15.5 (0.8) 29/32.0 (0.9) 1.42 18 to 29 12 14/16.1 (0.9) 29/15.2 (1.9) 43/31.2 (1.4) 0.48 30 to 41 12 19/15.6 (1.2) 10/14.7 (0.7) 29/30.3 (1.0) 1.90 42 to 53 12 13/15.3 (0.8) 11/14.5 (0.8) 24/29.8 (0.8) 1.18 54 to 59 6 8/7.6 (1.1) 5/7.2 (0.7) 13/14.7 (0.9) 1.60 ------6 to 59 54 71/69.0 (1.0) 67/69.0 (1.0) 1.06

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.733 (boys and girls equally represented) Overall age distribution: p-value = 0.191 (as expected) Overall age distribution for boys: p-value = 0.842 (as expected) Overall age distribution for girls: p-value = 0.003 (significant difference) Overall sex/age distribution: p-value = 0.002 (significant difference)

Team 3:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 11/13.5 (0.8) 12/9.7 (1.2) 23/23.2 (1.0) 0.92 18 to 29 12 15/13.1 (1.1) 9/9.5 (0.9) 24/22.6 (1.1) 1.67 30 to 41 12 15/12.7 (1.2) 10/9.2 (1.1) 25/21.9 (1.1) 1.50 42 to 53 12 11/12.5 (0.9) 10/9.1 (1.1) 21/21.6 (1.0) 1.10 54 to 59 6 6/6.2 (1.0) 1/4.5 (0.2) 7/10.7 (0.7) 6.00 ------6 to 59 54 58/50.0 (1.2) 42/50.0 (0.8) 1.38

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.110 (boys and girls equally represented) Overall age distribution: p-value = 0.773 (as expected) Overall age distribution for boys: p-value = 0.858 (as expected) 53

Overall age distribution for girls: p-value = 0.490 (as expected) Overall sex/age distribution: p-value = 0.138 (as expected)

Team 4:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 21/12.8 (1.6) 8/9.7 (0.8) 29/22.5 (1.3) 2.63 18 to 29 12 8/12.4 (0.6) 12/9.5 (1.3) 20/21.9 (0.9) 0.67 30 to 41 12 13/12.1 (1.1) 6/9.2 (0.7) 19/21.3 (0.9) 2.17 42 to 53 12 8/11.9 (0.7) 12/9.1 (1.3) 20/20.9 (1.0) 0.67 54 to 59 6 5/5.9 (0.9) 4/4.5 (0.9) 9/10.4 (0.9) 1.25 ------6 to 59 54 55/48.5 (1.1) 42/48.5 (0.9) 1.31

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.187 (boys and girls equally represented) Overall age distribution: p-value = 0.644 (as expected) Overall age distribution for boys: p-value = 0.079 (as expected) Overall age distribution for girls: p-value = 0.543 (as expected) Overall sex/age distribution: p-value = 0.008 (significant difference)

Team 5:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 23/16.5 (1.4) 9/13.7 (0.7) 32/30.2 (1.1) 2.56 18 to 29 12 11/16.1 (0.7) 13/13.3 (1.0) 24/29.4 (0.8) 0.85 30 to 41 12 17/15.6 (1.1) 13/12.9 (1.0) 30/28.5 (1.1) 1.31 42 to 53 12 16/15.3 (1.0) 13/12.7 (1.0) 29/28.1 (1.0) 1.23 54 to 59 6 4/7.6 (0.5) 11/6.3 (1.7) 15/13.9 (1.1) 0.36 ------6 to 59 54 71/65.0 (1.1) 59/65.0 (0.9) 1.20

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.293 (boys and girls equally represented) Overall age distribution: p-value = 0.860 (as expected) Overall age distribution for boys: p-value = 0.197 (as expected) Overall age distribution for girls: p-value = 0.274 (as expected) Overall sex/age distribution: p-value = 0.015 (significant difference)

Team 6:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 20/18.1 (1.1) 15/13.5 (1.1) 35/31.6 (1.1) 1.33 18 to 29 12 12/17.6 (0.7) 14/13.1 (1.1) 26/30.8 (0.8) 0.86 30 to 41 12 21/17.1 (1.2) 11/12.7 (0.9) 32/29.8 (1.1) 1.91 42 to 53 12 18/16.8 (1.1) 13/12.5 (1.0) 31/29.3 (1.1) 1.38 54 to 59 6 7/8.3 (0.8) 5/6.2 (0.8) 12/14.5 (0.8) 1.40 ------54

6 to 59 54 78/68.0 (1.1) 58/68.0 (0.9) 1.34

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.086 (boys and girls equally represented) Overall age distribution: p-value = 0.772 (as expected) Overall age distribution for boys: p-value = 0.527 (as expected) Overall age distribution for girls: p-value = 0.949 (as expected) Overall sex/age distribution: p-value = 0.125 (as expected)

Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).

Team: 1

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 1.46 (n=12, f=1) ############################ 02: 1.38 (n=11, f=1) ######################## 03: 0.66 (n=10, f=0) 04: 0.83 (n=10, f=0) # 05: 1.00 (n=08, f=0) ######## 06: 0.76 (n=09, f=0) 07: 0.70 (n=10, f=0) 08: 1.21 (n=08, f=0) ################# 09: 0.71 (n=06, f=0) 10: 0.77 (n=05, f=0) 11: 0.61 (n=03, f=0) 12: 1.32 (n=03, f=0) OOOOOOOOOOOOOOOOOOOOOO

Team: 2

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.98 (n=11, f=0) ######## 02: 0.97 (n=11, f=0) ####### 03: 0.82 (n=11, f=0) # 04: 1.22 (n=11, f=1) ################## 05: 0.69 (n=11, f=0) 06: 0.83 (n=11, f=0) # 07: 1.26 (n=11, f=0) ################### 08: 0.68 (n=11, f=0) 09: 1.02 (n=11, f=0) ######### 10: 0.93 (n=10, f=0) ##### 11: 0.87 (n=09, f=0) ### 12: 1.15 (n=08, f=0) ############### 13: 0.90 (n=06, f=0) OOOO 14: 1.06 (n=03, f=0) ~~~~~~~~~~~ 15: 2.01 (n=02, f=0) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Team: 3 55

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.86 (n=11, f=0) ## 02: 1.05 (n=11, f=0) ########### 03: 1.01 (n=11, f=0) ######### 04: 1.11 (n=11, f=0) ############# 05: 0.72 (n=11, f=0) 06: 1.08 (n=10, f=0) ############ 07: 1.09 (n=10, f=0) ############ 08: 1.06 (n=08, f=0) ########### 09: 0.81 (n=05, f=0) 10: 0.62 (n=05, f=0) 11: 0.73 (n=04, f=0)

Team: 4

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.87 (n=11, f=0) ### 02: 0.81 (n=11, f=0) 03: 1.14 (n=11, f=0) ############## 04: 1.07 (n=11, f=0) ########### 05: 0.64 (n=11, f=0) 06: 1.20 (n=10, f=1) ################# 07: 1.10 (n=07, f=0) ############# 08: 0.62 (n=06, f=0) 09: 0.69 (n=04, f=0) 10: 1.04 (n=04, f=0) OOOOOOOOOO 11: 1.65 (n=04, f=0) OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO 12: 1.89 (n=03, f=0) OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO 13: 0.03 (n=02, f=0)

Team: 5

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.98 (n=11, f=0) ####### 02: 0.92 (n=11, f=0) ##### 03: 1.31 (n=11, f=0) ###################### 04: 1.17 (n=11, f=0) ############### 05: 1.02 (n=11, f=0) ######### 06: 0.90 (n=10, f=0) #### 07: 0.85 (n=10, f=0) ## 08: 0.57 (n=10, f=0) 09: 0.86 (n=08, f=0) ## 10: 0.69 (n=08, f=0) 11: 0.72 (n=08, f=0) 12: 0.99 (n=08, f=0) ######## 13: 1.17 (n=04, f=0) OOOOOOOOOOOOOOOO 14: 1.42 (n=03, f=0) OOOOOOOOOOOOOOOOOOOOOOOOOO

Team: 6

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.88 (n=12, f=0) ### 02: 1.23 (n=12, f=1) ################## 03: 1.25 (n=12, f=0) ################### 04: 1.05 (n=12, f=0) ########### 05: 0.88 (n=12, f=0) ### 06: 0.65 (n=12, f=0) 07: 1.16 (n=09, f=0) ############### 08: 0.57 (n=10, f=0) 09: 1.00 (n=10, f=0) ######## 10: 0.85 (n=10, f=0) ## 11: 0.88 (n=09, f=0) ### 12: 0.71 (n=05, f=0) 13: 0.87 (n=04, f=0) OOO 14: 0.56 (n=03, f=0) 15: 0.64 (n=02, f=0)

(for better comparison it can be helpful to copy/paste part of this report into Excel)

Appendix 2: Assignment of Clusters Population Geographica Populatio Geographical unit size Cluster l unit n size Cluster *Madhya Yakubnagar 1454 1 *Tulatali 2611 29 (Part) *Madhya Yakubnagar 3042 2 Bhater Khil 5257 30 (Part) *Madhya Mohadebpur 1779 3 Goptakhali 1814 31 (Part) *Madhya Mohadebpur 1499 4 *Guliakhali 3422 32 (Part) *Bhuiyan Para 496 5 Purba 10037 33 Muradpur *Dakshin Mohadebpur 3778 6 Paschim 6182 34 Muradpur *Paschim Mohadebpur 1730 7 *Daskhin 12902 35,36,37 (Part Salimpur *Dakshin Edilpur 2638 8 *Jungle 11999 38,39 Salimpur *Shibpur 3327 RC *Latifpur 10640 40,41 Uttar Banshbaria 8297 9 *Uttar 21520 42,43,RC,4 Salimpur 4 Mill Area 1353 10 Uttar 4453 45 Bagachatar South Banshbaria 5355 11 Moha Nagar 3379 46 Akil Pur 2862 12 Bag Khali 6478 47 Uttar Mahmudabad 6668 13 *Kedarerkhil 3431 48 Ali Chowdhury Para 1621 14 Purba 4102 49 Saidpur

Olinagar 1560 15 Pashim 5632 50 Saidpur *Mandaritola 3707 16 Boro Kumira 8046 51 Dakshin Mahmudpur 7743 17 Lat 21 Chato 2184 52 Kumir Charail Kandi 1297 18 Mosjida 16773 53,54,55 *Baharpur 2010 19 Uttar 14006 56,57 Sonaichari Pashim Lalanagar 3694 20 Dhakkhin 12356 58,59 Sonaichari *Dharmapur 2473 RC Keshobpur 6013 60,61 *Mahalanga 2609 21 Maddham 12950 62,63 Sonaichari Dakshin Fedinagar 5635 22 Shitalpur 8408 64,65 Bhatiari 28245 23,24,RC,25,R *Uttar 7349 66 C Sonaichhari Imam Nagar 4955 26 Jahanabad 8922 27,28 Kadam Rosul 6187 RC *Jungle Bhatiari 3455 RC

Appendix 3: Evaluation of enumerators (Standardisation test results) Standardisation test results Precision Accuracy OUTCOME subje me S m Technical TEM/m Coef of Bias from Bias from cts an D ax error ean reliability superv median result TEM # kg kg kg TEM (kg) (%) R (%) Bias (kg) Bias (kg) 12. 2. 0. TEM Supervisor 10 2 3 3 0.09 0.7 99.9 - -0.03 acceptable R value good Bias good Enumerator 12. 2. 0. 1 10 1 1 3 0.12 1 99.7 -0.1 -0.13 TEM poor R value good Bias good Enumerator 12. 2. 0. 2 10 1 1 2 0.11 0.9 99.7 -0.09 -0.13 TEM poor R value good Bias good Enumerator 12. 2. 0. TEM 3 10 2 3 3 0.09 0.7 99.9 0 -0.03 acceptable R value good Bias good Enumerator 2. 0. 4 10 12 1 3 0.13 1.1 99.6 -0.13 -0.16 TEM poor R value good Bias good Enumerator 11. 3. 14 R value 5 10 3 3 .5 3.24 28.7 4.4 -0.88 -0.92 TEM reject reject Bias good Enumerator 12. 2. 0.

6 10 1 1 5 0.15 1.3 99.5 -0.08 -0.11 TEM poor R value good Bias good Enumerator 12. 2. 0.

Weight 7 10 1 1 2 0.1 0.8 99.8 -0.1 -0.14 TEM poor R value good Bias good Enumerator 2. 0. TEM 8 10 12 1 3 0.07 0.6 99.9 -0.15 -0.19 acceptable R value good Bias good Enumerator 12. 1. 0. TEM 9 10 3 8 1 0.07 0.6 99.8 0.18 0.14 acceptable R value good Bias poor Enumerator 12. 2. 0. TEM 10 10 1 1 1 0.07 0.6 99.9 -0.09 -0.13 acceptable R value good Bias good Enumerator 12. 2. 0. TEM 11 10 1 1 1 0.07 0.6 99.9 -0.07 -0.11 acceptable R value good Bias good Enumerator 12. 2. 0. TEM 12 10 1 1 1 0.04 0.4 100 -0.1 -0.13 acceptable R value good Bias good Enumerator 11. 2. 0. TEM 13 10 9 1 2 0.06 0.5 99.9 -0.22 -0.26 acceptable R value good Bias good Enumerator 12. 1. 0. R value Bias 14 10 2 8 7 0.19 1.5 98.9 0.08 0.05 TEM poor acceptable acceptable Enumerator 2. 0. TEM 15 10 12 1 3 0.08 0.7 99.9 -0.13 -0.16 acceptable R value good Bias good 58

Enumerator 2. 0. TEM 16 10 12 1 2 0.06 0.5 99.9 -0.16 -0.2 acceptable R value good Bias good Enumerator 12. 0. TEM 17 10 1 2 2 0.06 0.5 99.9 -0.02 -0.05 acceptable R value good Bias good Enumerator 20. 26 18 10 5 .6 0 0 0 100 8.33 8.29 TEM good R value good Bias reject enum inter 18x1 12. 6. R value 1st 0 5 7 - 6.32 50.4 11.6 - - TEM reject reject enum inter 18x1 12. 6. R value 2nd 0 5 8 - 6.41 51.3 10.9 - - TEM reject reject inter enum 19x1 12. 6. R value + sup 0 5 6 - 6.19 49.5 16 - - TEM reject reject TOTAL 18x1 R value intra+inter 0 - - - 6.41 51.2 9.7 0.35 0.29 TEM reject reject Bias reject TOTAL+ 19x1 R value sup 0 - - - 6.23 49.9 10.4 - - TEM reject reject subje me ma Technical TEM/m Coef of Bias from Bias from cts an SD x error ean reliability superv median result

# cm cm cm TEM (cm) TEM (%) R (%) Bias (cm) Bias (cm) 92. Supervisor 10 2 9.3 0.2 0.08 0.1 100 - -0.19 TEM good R value good Enumerator 1 10 92 9.4 0.5 0.12 0.1 100 -0.24 -0.43 TEM good R value good Bias good Enumerator 92. TEM 2 10 1 9.3 2.1 0.48 0.5 99.7 -0.15 -0.35 acceptable R value good Bias good Enumerator 92. 3 10 2 9.3 0.2 0.08 0.1 100 0 -0.19 TEM good R value good Bias good Enumerator 92. 4 10 1 9.1 0.9 0.28 0.3 99.9 -0.07 -0.26 TEM good R value good Bias good Enumerator 91. 5 10 8 9.3 0.6 0.17 0.2 100 -0.44 -0.64 TEM good R value good Bias good Enumerator TEM 6 10 92 9.2 1.8 0.52 0.6 99.7 -0.25 -0.44 acceptable R value good Bias good Enumerator 91. 7 10 9 9.3 0.3 0.09 0.1 100 -0.29 -0.48 TEM good R value good Bias good Enumerator 8 10 92 9.4 4.1 0.92 1 99 -0.24 -0.43 TEM poor R value good Bias good Enumerator 90. 13. 30. 9 10 5 6 3 6.78 7.5 75 -1.67 -1.86 TEM reject R value reject Bias good Enumerator 92. 10 10 1 9.5 0.2 0.14 0.2 100 -0.14 -0.33 TEM good R value good Bias good

Height Enumerator 92. 11 10 1 9.4 0.2 0.14 0.2 100 -0.16 -0.35 TEM good R value good Bias good Enumerator 91. 12 10 9 9.3 0.2 0.14 0.2 100 -0.29 -0.48 TEM good R value good Bias good Enumerator 92. 13 10 1 9.2 0.2 0.06 0.1 100 -0.13 -0.32 TEM good R value good Bias good Enumerator 87. 20. 90. 14 10 5 3 9 20.33 23.2 -0.7 -4.75 -4.94 TEM reject R value reject Bias good Enumerator 91. 15 10 9 9.4 4.2 0.94 1 99 -0.28 -0.47 TEM poor R value good Bias good Enumerator 92. 16 10 5 8.6 0.2 0.11 0.1 100 0.32 0.13 TEM good R value good Bias good Enumerator 92. 17 10 9 7.5 0.3 0.12 0.1 100 0.68 0.49 TEM good R value good Bias poor Enumerator 83. 25. 18 10 7 7 0.2 0.1 0.1 100 -8.5 -8.69 TEM good R value good Bias good enum inter 91. 11. 1st 18x10 4 2 - 6.73 7.4 63.8 - - TEM reject R value reject enum inter 91. 12. 2nd 18x10 1 3 - 9.29 10.2 43.1 - - TEM reject R value reject inter enum + 91. 11. sup 19x10 3 6 - 7.8 8.5 55.9 - - TEM reject R value reject TOTAL intra+inter 18x10 - - - 9.56 10.5 33.7 -0.92 -1.06 TEM reject R value reject Bias good

TOTAL+ sup 19x10 - - - 9.31 10.2 35.8 - - TEM reject R value reject

subje me ma Technical TEM/m Coef of Bias from Bias from

MUAC cts an SD x error ean reliability superv median result 59

m m # mm m m TEM (mm) TEM (%) R (%) Bias (mm) Bias (mm) 140 R value Supervisor 10 .3 7.3 3 1.02 0.7 98 - -2.75 TEM good acceptable Bias good Enumerator 140 R value 1 10 .7 6.7 4 1.1 0.8 97.3 0.45 -2.3 TEM good acceptable Bias good Enumerator 143 R value 2 10 .1 6.7 1 0.67 0.5 99 2.9 0.15 TEM good acceptable Bias good Enumerator 140 R value 3 10 .3 7.3 3 1.02 0.7 98 0 -2.75 TEM good acceptable Bias good Enumerator 142 R value 4 10 .4 8.2 3 1.07 0.8 98.3 2.1 -0.65 TEM good acceptable Bias good Enumerator 141 5 10 .1 7.8 2 0.63 0.4 99.3 0.85 -1.9 TEM good R value good Bias good Enumerator 140 TEM 6 10 .6 7.1 8 2.31 1.6 89.4 0.4 -2.35 acceptable R value reject Bias good Enumerator 140 R value 7 10 .3 7.3 2 0.81 0.6 98.8 0 -2.75 TEM good acceptable Bias good Enumerator 139 8 10 .6 6.6 2 0.63 0.5 99.1 -0.65 -3.4 TEM good R value good Bias good Enumerator 142 9 10 .3 7.7 8 3.5 2.5 79.5 2 -0.75 TEM reject R value reject Bias good Enumerator 140 R value 10 10 .6 7.4 4 1.38 1 96.6 0.35 -2.4 TEM good acceptable Bias good Enumerator 141 R value 11 10 .3 6.7 1 0.71 0.5 98.9 1.05 -1.7 TEM good acceptable Bias good Enumerator 140 12 10 .8 7.1 4 1.9 1.3 92.9 0.55 -2.2 TEM good R value poor Bias good Enumerator 141 TEM 13 10 .4 8 9 2.56 1.8 89.7 1.2 -1.55 acceptable R value reject Bias good Enumerator 142 TEM 14 10 .5 7 8 2.68 1.9 85.4 2.25 -0.5 acceptable R value reject Bias good Enumerator 140 15 10 .1 7.1 5 1.64 1.2 94.6 -0.15 -2.9 TEM good R value poor Bias good Enumerator 140 TEM 16 10 .6 7.6 10 2.67 1.9 87.6 0.4 -2.35 acceptable R value reject Bias good Enumerator 141 TEM 17 10 .6 7.5 7 2.62 1.8 87.9 1.4 -1.35 acceptable R value reject Bias good Enumerator 141 TEM 18 10 .8 7 7 2.42 1.7 87.9 1.5 -1.25 acceptable R value reject Bias good enum inter 141 TEM 1st 18x10 .4 7.2 - 2.43 1.7 88.7 - - acceptable R value reject enum inter 2nd 18x10 141 7.1 - 1.87 1.3 93.1 - - TEM good R value poor inter enum + 141 TEM sup 19x10 .1 7.2 - 2.12 1.5 91.1 - - acceptable R value poor TOTAL intra+inter 18x10 - - - 2.88 2 83.8 0.92 -1.88 TEM poor R value reject Bias good

TOTAL+ sup 19x10 - - - 2.84 2 84.3 - - TEM poor R value reject

Appendix 4: Questionnaire

INTEGRATED SMART NUTRITON SURVEY - 2018

DATE (DD/MM/YYYY) (ZvwiL):______TEAM (wUg):______CLUSTER (K¬v÷vi):______HH ID (Lvbv bs): ______HH SERIAL (Lvbv):______

The team should note the answers in PEN not in pencil

(`j‡K Aek¨B DËi¸‡jv Kjg w`‡q †jL‡Z n‡e, †cbwmj w`‡q bq)

1.cwimsL¨vb / HH Demography cwiev‡i ‡gvU ‡g‡q ev gwnjv / Number of cwiev‡i ‡gvU cyil ev ‡Q‡j / Number of Male: Female: cwievi cÖav‡bi wj½ / Male= 1 ; Female= 2 cwievi cÖav‡bi eqm (eQi) / Age of HH Head

Gender of HH Head: (yrs):

2.cwiev‡ii MVb / Family composition cwiev‡ii m`‡m¨i †kÖbx ev aib / Age Categories †gvU m`m¨ msL¨v / Total Number of members শি� (0-<6 gvm) / Infants (0-<6 months): শি� (৬-২৩ মাস)Children (6-23 months): wkï (24 gvm - <5 eQi) / Young Children (24 m – <5yrs): wkï (5-<18 eQi) / Children (5 - <18yrs): cÖvßeq¯‹ (18-50 eQi) / Adults (18-50yrs): e„× (>50 eQi) / Elderly (> 50yrs): Total Number of Children 0-59 month Sex (wj½) Child ID Child Name (শি�র নাম) Date of birth (জন্ম তারিখ) AGE (Months) M/F (শি�র ID) ( বড় থেকে থ োট ) DD/MM/YYYY (রিন /মাস/ বছি) eqm (gvm) (†Q‡j/†g‡q) Child-1 Child-2 Child-3 Child-4 Child-5

3.kixi e„Ëxq cwigvc (6-59 gvm) / Anthropometry (6-59 months)

Child SEX (wj½) Date of birth AGE(Months)/ Weight (Kg) Height or Oedema MUAC If N0 M/F(†Q‡j/†g‡q) (জন্ম তারিখ) eqm (gvm) ±0.1kg Length15(cm) 0.1 (Y/N) (mm) MUAC (wkï DD/MM/YYYY IRb (†KwR) cm/D”PZv ev ˆ`N©¨ BwWgv/ gyqvK <125 b¤^i) (রিন /মাস/ বছি) ±0.1†KwR (‡mwg) ±0.1‡mwg cv‡q cvwb (wg: mm Avmv wg:) (nvu/bv) 1 Go 3.1 2 Go 3.1 3 Go 3.1 4 Go 3.1 5 Go 3.1

3.1 hw` †Kvb wkï gvivZ¡K Zxeª Acywó‡Z (BwWgv/gyqvK <125 wg.wg) AvµvšÍ _v‡K Zvn‡j wb‡Pi cÖkœwU Ki”b / If any child is acutely malnourished then ask caregiver, if she/he is enrolled into nutrition program and receiving treatment ? Avcbvi wkïwU ‡Kvb cywó wPwKrmv †mevq fwZ© Av‡Q wK? wkïi KvW© †`‡L Child-1 Child-2 Child-3 Child-4 Child-5 wbwðZ †nvb (0=bv, 1= IwUwc, 2=GmGdwc, 88 =Rvwb bv) / Is your child admitted into Nutrition feeding program? (0=No, 1= SC (Hospital) 2= Out Patient Therapeutic

15 Height measurement standing when child is ≥24 months (height proxy ≥87 cm) and lying down when child is < 24 months (< 87 cm) 61

Program (OTP), 3= Supplementary Feeding Program (SFP), 88=Don’t know, 99= Not Applicable for >=125 mm)

4. Amy¯’Zvi Z_¨ (6-59 gvm) / Morbidity (6-59 MONTHS) 4. Morbidity Status (ররোগের অবস্থো) wkï b¤^i /Child 4 5 1 2 3 N0 MZ 2 mßv‡ni g‡a¨ Avcbvi wkïwUi wK †Kvb ai‡bi AmyL n‡qwQj? hw` DËi Õn¨vuÕ nq Amy¯’Zvi Z_¨ m¤úwK©Z cÖkœ Kiæb, DËi ÕbvÕ n‡j wb‡b¥v³ Amy¯’Zvi cÖkœ ev` w`‡q cieZ©x (4.2) cÖkœ Kiæb) / In the past 2 WEEKS, has your child had the following illnesses? Put tick sign () if yes, if not then do not ask the following questions and go to next questions. (1=Yes/ 0 =No) MZ 14 w`‡bi g‡a¨, Avcbvi wkïi wK Wvqwiqv n‡qwQj? (nu¨v/bv) Diarrhoea (1=Yes/ 0 =No) MZ 14 w`‡bi g‡a¨, Avcbvi wkïi wK জ্বর n‡qwQj? মা এর তথ্য অনুযায়ী জ্বর (হযাাঁ/না) Fever (1=Yes/

0 =No) MZ 14 w`‡bi g‡a¨, Avcbvi wkïi wK k¦vmZ‡š¿i cÖ`vn (†hgbt Kvwk, k¦vmKó, ey‡Ki LvuPv wfZ‡ii w`‡K †`‡e hvIqv, Nb Nb k¦vm †bIqv) n‡qwQj? (nu¨v/bv) Acute Respiratory Infections (Cough, breathing difficulties, Chest in-drawing, Rapid breathing) (1=Yes/ 0 =No) Ab¨vb¨ (ïaygvÎ nu¨v/bv) Other disease (1=Yes/ 0 =No) Treatment Type (চিচিৎসোi ধরন) 4.1 Avcbvi wkï wK Amy¯’Zvi Rb¨ †Kvb wPwKrmv MÖnY K‡i‡Q? †Kvb RvqMv †_‡K wPwKrmv MÖnb K‡i‡Q? [1 = †Kvb wPwKrmv MÖnb K‡i bvB, 2= ‡emiKvwi wK¬wbK, 3 = miKvwi wK¬wbK,

4=Ab¨vb¨ wPwKrmv (wbw`wó K‡i bvg wjLyb) --- Have your child received treatment for illnesses? [1= did not receive treatment, 2= private clinic, 3= Govt. Clinic, 4= Other source/ Village doctor (specify), 99= Not applicable] Vitamin A and Immunization (綿িো) wkï b¤^i /Child N0 1 2 3 4 5 4.2 wkïwU wK nvg Gi wUKv wb‡q‡Q? ( 1=KvW© Abyhvqx, 2= AbymiY Kiv Z_¨, 3 =bv, 88= Rvwb bv) /

Has the child received measles immunization? (1=by card; 2=by recall; 0=No, 88=Don’t Know, 99= Not applicable) 4.3 MZ Qq gv‡m wkïwU wK wfUvwgb G ‡L‡qwQj? (1=nu¨v, 0=bv 88= Rvwb bv) /

Did the child receive Vitamin A in last six months? (1=yes, 0=No 88=Don’t Know)

5.wkïi Lv`¨vf¨vm (0-23 gvm)/ Infant and Young Child Feeding-IYCF Practices (Only for Children between 0 – 23 Months) wkï b¤^i /Child N0 1 2 3 4 5 AGE বয়স (মাসস) 5.1 Has (NAME) ever been breastfed? (bvg) Zv‡K wK KLbI ey‡Ki `ya LvB‡q‡Qb? (1=yes, 0=No, 88=Don’t Know) 5.2 How long after delivery was [NAME] put to the breast/nipple? R‡b¥i KZ¶Y c‡i (bvg) Zv‡K ey‡Ki `ya †`qv n‡qwQj? (1=Less than 1 hour, 2=1-24 hours, 3=More than 24 hours, 88=Don’t Know) 5.3 Was [NAME] breastfed yesterday during the day or at night? MZKvj w`‡b A_ev iv‡Z (bvg) Zv‡K wK ey‡Ki `ya LvIqv‡bv n‡qwQj? (0=No, 1=yes, 2=Stop feeding) 5.4 Was [NAME] bottle fed with nipple yesterday during the day or at night? (bvg) MZKvj mvivw`b A_ev mvivivZ wbcjmn †evZ‡j (wdWvi) K‡i †Kv‡bv wKQy cvb K‡iwQj? (1=yes, 0=No, 88=Don’t Know)

5.5 Was any liquid/water/food given to child before 6 month of birth? Avcwb (bvg) ‡K R‡b¥i cieZ©x 6 gv‡mi g‡a¨ Zvi gy‡L †Kv‡bv Zij/cvbxq/Lvevi w`‡qwQ‡jb? (1=yes, 0=No, 88=Don’t Know) 5.6 At what age after birth did you start giving foods and liquids other than breast milk? (Including pre-lacteal) wkï‡K †Kvb eqm †_‡K ey‡Ki `ya Qvov Ab¨ †Kvb Lvevi Ges Zij †`qv ïi“K‡iwQ‡jb? (wcÖ-j¨vK‡Uj mn) = 99=Not applicable/ not start) 5.7 Was [NAME] drink liquid/water yesterday during the day or at night? (bvg) wK MZKvj mvivw`b A_ev mvivivZ wbgœwjwLZ Zij/cvbxq/Lvevi cvb †L‡qwQj? 1 2 3 4 5 (1=yes, 0=No, 88=Don’t Know) Water- cvwb Sugar water-wPwbi cvwb Fruit Juice/ juice drinks/Coconut water-d‡ji im/ Rym wWªsKm/Wv‡ei cvwb Container milk, milk powder- wUbRvZ `ya, ¸ov `ya, cÖvYxR `ya Curd- `B

Juice/foods from outside shop(juice, candy, biscuits etc. )-evRv‡ii †evZ‡ji Rym, K¨vwÛ, we®‹zU &&&&&&&BZ¨vw`

5.8 Did [NAME] receive any soft/ semi-solid/ solid food yesterday during the day or at night? MZKvj w`‡b ev iv‡Z (bvg) †m wK ey‡Ki `ya Qvov Ab¨ †Kvb big / Aa© k³/ k³ Lvevi †L‡qwQj? (1=yes, 0=No, 88=Don’t Know) If answer ‘No’ then skip 5.9 question 5.9 If 5.8 Yes, How many times did (NAME) eat solid, semi-solid, or soft foods other than liquids yesterday during the day or at night?

হ্োাঁ হকে , MZKvj w`‡b Ges iv‡Z Avcbvi wkïwU me©‡gvU KZevi (wkïi bvg) k³, Avav-k³ A_ev big evowZ cvwievwiK Lvevi †L‡q‡Q? wb‡b¥v³ cÖkœwU ïaygvÎ 6-23 gvm eqmx wkïi Rb¨ cÖ‡hvR¨ 5.10 MZKvj mvivw`b A_ev mvivivZ Avcbvi wkïwU wb‡b¥ ewY©Z wK ai‡bi Lvevi †L‡q‡Q? / Did your child eat any of the following food groups in the previous day and night 1 2 3 4 5 (1=yes, 0=No) AGE বয়স (মাসস) 1. Grains, roots, tubers (nan, chapatti, parata, bread, rice, potato শস্্,শশেড় এবং েন্দ ( নোন, চোপোশি, পক োটো, 쇁綿, ভোি/চোে, আেু) 2. Legumes or nuts (lentils) শশম জোিীয় বো বোদোম Beans, peas, other lentils, nuts (peanuts) or seeds (pumpkin seed, spinach seed, jackfruit seed) or any foods made from these (chanachur) মট �綿, ডোে বো থেকেোন ডোে, বোদোম বো শবশচ থেমন শমশি-嗁মড়ো শবশচ, শোকে শবশচ, েোাঁঠোকে শবশচ বো এ巁কেো থেকে ি ী থেকেোন খোবো (চোনোচু ) 3. Dairy products (milk, yoghurt, cheese) 駁দ্ধজোিীয় পণ্্ (駁ধ, ইকয়োগোটট , পশন ) 4. Flesh foods (meat, fish, poultry, liver/organ meat) মোংস্জোিীয় খোবো (মো , মোংস্, মু শগ মোংস্ এবং শেভো / অন্োন্ অঙ্গ থেমন- দশপণ্ড, শেডশন, শজহবো, অগ্ন্্োশয়, মগজ ইি্োশদ) 5. Vitamin A rich fruits and vegetables (carrot, pumpkin, orange sweet potato, mango, papaya, dark green leafy vegetables, long beans) শভটোশমন এ স্মৃদ্ধ ফেমূে ও শোেস্বশজ (গোাঁজ, শমশি 嗁মড়ো, েমেো-শমশি আেু, আম, থপাঁকপ, গোঢ় স্বুজ শোে স্বশজ, শশম) 6. Egg শডম

7. Other fruit and vegetables (banana, apples, pineapple, watermelon , eggplant, onion, cucumbers, tomatoes) অন্োন্ ফেমূে ও শোেস্বশজ (েেো, আকপে, আনো স্, ি মুজ, থব巁ন, থপাঁয়োজ, শস্ো, টকমকটো) 8. Any oil, fats, butter, ghee or foods made with any of these থেকেোন তিে, চশবট, মোখন, শি বো এ巁কেো শদকয় তিশ খোবো 9. Any sugary foods such as chocolates, sweets, candies, pastries, cakes, biscuits or just sugar থেকেোন শচশন জোশিয় খোবো থেমন চেকেট, শমশি, ে্োশি, থপশি, থেে, শবস্কু ট বো �ধু শচশন সকালের খাবার সকাে ও দুপুলরর দুপুলরর খাবার দুপুর ও রালতর মাঝামাশঝ রালতর খাবার (Morning Meal) মাঝামাশঝ (Mid of (Lunch) (Mid of Lunch & Dinner) (Dinner) Morning and Lunch)

6. CHILD CARE PRACTICE KNOWLEDGE AND PRACTICES (শি�র যলের অনুিীেন জ্ঞান ও অভ্যাস) 6.1. What are the challenges do you face to take care of a child?/Avcbvi wkïi hZœ Put a Tick sign (√) on the correct †bIqvi †ÿ‡Î Avcwb wK wK Ae¯’vi m¤§yLxb nb ev mgm¨vq c‡ob? responses/mwVK DË‡i wUK wPý (√) w`b 1. Difficulties to feed/wkï‡K LvIqv‡Z mgm¨v ev †L‡Z Pvqbv 2. Managing time/ev”Pvi h‡Zœi mgq g¨v‡bR Kiv 3. Lack of support from husband or other family members/ev”Pvi evev ev cwiev‡ii †jvK‡ì mn‡hvMxZv bv cvIqv 4. Running out of energy/mn‡RB K¬všÍ n‡q hvIqv 5. Lack of interest to take care of child/Avì-hZœ Ki‡Z fv‡jv bv jvMv 6. Lack of knowledge or clarity about child care practices/wKfv‡e hZœ wb‡Z nq Zv bv Rvbv ev bv †evSv 7. Criticism from others for child care issues/wkïi hZœ wb‡q A‡bï mgv‡jvPbv 8. Others / Ab¨vb¨.... 88= Do not know/ Rvwbbv 6.2 What are the actions do you think important for your young child’s optimum growth Put a Tick sign (√) on the correct and development? Tick on the correct responses/ responses/mwVK DË‡i wUK Avcbvi wkïi mwVKfv‡e †e‡o DVvi Rb¨ †Kvb †Kvb welq¸‡jv Kiv ¸iæZ¡c~Y©/ìKvi wPý (√) w`b e‡j g‡b nq? (mwVK DË‡i wUK wPý w`b) 1. Feeding enough food/h‡_ó cwigv‡Y ev †cU f‡i Lvevi LvIqv‡bv 2. Seeking support of health professionals while child is sick/Amy¯’ n‡j wPwKrmK †`Lv‡bv 3. Interaction with child/wkïi mv‡_ K_v ejv 4. Play with child/ wkïi mv‡_ ‡Ljv Kiv 5. Giving opportunity to explore new things/bZyb bZyb wRwbm wkL‡Z mvnvh¨ Kiv 6. Clean and safe environment/cwi”Qbœ Ges wbivc` cwi‡e‡ki e¨ve¯’v Kiv 7. Giving love, warm and assurance/ Avì-fv‡jvevmv I Avk¦vm †Ìqv 8. Discipline and explanation/fv‡jv-g›` wkÿv †Ìqv Ges ‡evSv‡bv 9. Others…./Ab¨vb¨: 64

88. Do not know/ Rvwbbv

HOUSEHOLDS FOOD SECURITY & LIVELIHOODS (পশরবালরর খাদয শনরাপত্তা এবং জীশবকা) 7. Monthly Household Income (cvwievwiK gvwmK Avq) BDT. 8. Main Source of Income for the household /Avcbvi cwiev‡ii g~j Av‡qi Drm wK? (wb‡b¥v³ Drm Abyhvqx †KvWwU wjLyb †hgbt hw` K…wlev Lv`¨km¨ weµq nq Z‡e 1; Dcnvi n‡j 13)

1 = Agriculture and sales of crops 6 = Skilled labour 11= Salaries, wages-employees (K…wl ev Lv`¨km¨ weµq); (`ÿ kÖwgK); (PvKix); 2= Livestock and sales of animals 7 = Handicrafts/cottage industry (n¯Í wkí); 12= Begging (wfÿv); (M„ncvwjZ Mevw`cï weµq); 8= Collection of natural resources 13= Gift (Dcnvi); 3= Fishing (open /common water) (firewood, charcoal, bricks, grass, wild 14= Remittance gvQ aiv (D¤§y³ Rjvkq); foods, honey) (Rv¡jvbx KvV, Kqjv, Nvm, (ê‡`wkK Avq); 4 = aquaculture (in a pond) Mevw` ckyi Lvevi, gay msMÖn); 15= Government allowance (†Ni ev cyKz‡i grm Pvl); 9 = Petty trading-less than 10,000 monthly (miKvwi fvZv ); 5= Unskilled wage labour (including agro) income 16= Land renting (A`ÿ w`b gyRyi K…wl gRywimn); (ÿz`ª eëmv- 10,000 nvRv‡ii wb‡P gvwmK (Rwg eM©v/fvov †Ìqv); Avq ); 17= Money lender (UvKv avi) 10= Seller, commercial activity ১৮= Salt cultivation (েবন চাষ) (বড় eëmv- 10,000 nvRv‡ii উপগর gvwmK ১৯=Others (অনযানয) Avq we‡µZv) 9. Identify Main Food Source(How do you obtain your food) -Multiple answer may come (Avcbvi cwiev‡ii Lv‡`ï cÖavb Drm )(wb‡b¥v³ Drm Abyhvwq †KvWwU wjLyb †hgbt hw` wbR¯^ Pvlvev`/Drcv`b nq Z‡e 1; avi Kiv n‡j 3 BZ¨vw`) 1 = Own Cultivation/production (wbR¯^ Pvl Avev` / Drcv`b ) 5 = Purchasing (†Kbv ) 2 = Cash Loan (bM` FY ev KR©) 6 = Begging (wfÿv) 3 = Borrowing (avi Kiv) 7 = Barter/Exchange (wewbgq) 4 = Food Aid (Lv`¨ mnvqZv) 8 = Other (Ab¨vb¨)

10. পচরবোগরর খোদ্য ববচিত্র্য / Household Dietary Diversity (HDDS)

প্রশ্ন কিাি আসে এই সসকসান সম্পসকেপূবে ধািণা রিন । সেমনআপরন ও আপনাি (েতকাল সািারিন ও সািািাত) েত ২৪ ঘন্টা : পরিবাসিি অনয সেসকান সিসয রক রক খাবাি সখসয়সছন? উত্তি সনয়াি সময় উসেরখত পদ্ধরত অনুসিণ ক쇁ন -সকাল :সেমন) ) ক쇁ন ﶂ িাত ও িুই সবলাি মাঝামারঝ সমসয়ি-িুপুিখাবাসিি তথ্য খাতায় রলখুন ও সকার

Did you or any of your family members consume it yesterday? খাবালরর ধরন খাবালরর উদাহরণ (MZKvj wbb¥ ewY©Z (Type of Meal) (Example of Meal) †Kvb Lvevi †L‡q‡Qb wKbv?) 1= Yes, O= No Rice (fvZ), wheat (iæwU), muri (gywo), maize 1 0 1. kK©iv RvZxq Lv`¨ (Starchy foods) (f’Æv), 2. শিকড় এবং কন্দ জাতীয় (Tubers) (Potatoes (Avjy), Sweet potatoes (wgwó Avjy), 1 0 3. িাক সবশজ (Vegetables) যযলকান িাক এবং সবশজ 1 0 gvsm [Beef (Miæi gvsm), Goat (Lvmxi gvsm) 1 0 4. মাংস(Meat ) and Chicken (gyiMx)] 5. মাছ (Fish/Dry fish ) যযলকান gvQ/ïUKx gvQ 1 0 6. যযলকান শিম (Eggs) gyiMx, nvum, KeyZi, †Kv‡qj cvwLÕi wWg 1 0 7. dj (Fruits) যযলকান dj 1 0 8. Wvj/ mxg RvZxq Lvevi (Pulses & ‡h †Kvb cÖKv‡ii Wvj/mxg/ Any type of dal 1 0 Legumes) 9. িুধ বা িুধ রিসয় ততিী খাবাি `ya ev `ya w`‡q ˆZix Lvevi †hgb- `B, †mgvB, 1 0 (Milk and Milk Product) cv‡qm, wdiwb ev Ab¨ Lvevi `ya w`‡q ˆZix 10. ‡Zj, Pwe©, gvLb (Oil, fat, butter) ‡Zj, Pwe©, gvLb 1 0 11. wPwb/¸uo, gay (Sugar, Honey) (wPwb/¸uo, gay) 1 0 (Tea - Pv, Coffee - Kwd, spices (gwiP I gmjv), 1 0 12. gmjv/Ab¨vb¨ (Condiments/other) etc.

List of Food Items at different Meals: সকালের খাবার সকাে ও দুপুলরর দুপুলরর খাবার দুপুর ও রালতর মাঝামাশঝ রালতর খাবার (Morning Meal) মাঝামাশঝ (Mid of (Lunch) (Mid of Lunch & (Dinner) Morning and Lunch) Dinner)

11. 15-49 বছর বয়সী মশহোলদর খাদয তবশচত্র্্ Minimum Dietary Diversity for Women (MDD-W) of Reproductive Age: 15-49 প্রশ্ন কিাি আসে এই সসকসান সম্পসকে পূবে ধািণা রিন । সেমনআপরন রক রক (েতকাল সািারিন ও সািািাত) েত ২৪ ঘন্টা : খাবাি সখসয়সছন? উত্তি সনয়াি সময় উসেরখত পদ্ধরত অনুসিণ ক쇁ন িাত ও িুই সবলাি মাঝামারঝ -িুপুি-সকাল :সেমন)

ক쇁ন ( Select One Women Per Household randomly/ পশ বোক এে মশহেো শনবটোচন ে쇁ন ﶂ সমসয়িখাবাসিি তথ্য খাতায় রলখুন ও সকার MZKvj wbb¥ ewY©Z †Kvb Lvevi †L‡q‡Qb খোবোক ধ ন খাবাসিি উিাহিণ wKbv? (Type of Meal) ( Example of Meal) (Did you consume it yesterday?) 1= Yes, O= No শস্্, স্োদো শশেড় এবং েন্দ জোিীয় খোবো (Grains, fvZ/iywU/cvDiywU/wPov/gywo/mywR/ 1 0 white roots and tuber) byWyjm/wgwó/ f’Æv / স্োদো Avjy ev G RvZxq Lvevi থেকেোন ডোে জোিীয় খোবো Wvj/ মট �綿 1 0 /gUi fvRv/eyU fvRv ev †h †Kvb ivbœv Wvj RvZxq (Pulses ,Beans, peas and lentils) Lvevi বোদ্োম এবং বীজজোতীয় খোবোর 1 0 বোদ্োম এবং বীজজোতীয় খোবোর (Nuts and Seeds) 駁ধ বো 駁ধ চদ্গয় বতরী খোবোর `ya ev `ya w`‡q ˆZix Lvevi †hgb- `B, †mgvB, cv‡qm, 1 0 (Milk and Milk Product) wdiwb ev Ab¨ Lvevi `ya w`‡q ˆZix থেকেোন মোংস্ এবং মো ‡h †Kvb ai‡bi gvQ ev gvsm †hgb gyiwMi/ †Kv‡qj 1 0 cvwL/Mi“i/Lvmxi gvsm ev gyiwMi Pvgiv, cv, KwjRv, (Meat, poultry and fish) dvciv BZ¨vw` অঙ্গ জোিীয় মোংস্ (Organ Meat: Liver, 1 0 শগেো-েশেজো, শেডশন BZ¨vw` kidney, gizzards) শডম (Eggs) থেকেোন শডম (gyiMx, nvum, KeyZi, †Kv‡qj cvwLÕi wWg) 1 0 গোড় স্বুজ পোিো জোিীয় শোে jvj kvK/Kjgx/ cvjs/WvUv kvK/cyuB kvK (fvwR ev 1 0 (Dark Green Leafy Vegetables) ivbœv ev ZiKvwi) ফলমুল রেমন: পোিো রপেঁগপ, পোিো আম ইতযোচদ্; (fvwR ev ivbœv ev 1 0 Vitamin-A স্ম্মৃদ্ধ স্বশজ এবং ফেমুে ZiKvwi) (Vitamin A rich Vegetables and Fruits) সবচজ- MvRi/Kijv/wgwóKzgov/ ‡cu‡c (fvwR ev ivbœv ev ZiKvwi) Vitamin-A ব্োশিি অন্নোন্ স্বশজ (Other KPzg~Lx/kkv/cUj/PvjKzgov/jvD/eiewU/U‡g‡Uv/kvjMg 1 0 vegetables without Vitamin A enrich) (fvwR ev ivbœv ev ZiKvwi) Vitamin-A ব্োশিি অন্নোন্ ফে (Other fruits †jey/KvgivOv/Kjv/K`‡ej 1 0 without Vitamin A enrich ) Avgov/†cqviv/jUKb/Rv¤^yiv/cvwbdj/†ZuZzj ফল- থপয়ো ,ো িকবশ , থেবু, েমেো, শেচু , আনো স্, েোচো আম, আমড়ো, থিিু ে, 1 0 Vitamin-C স্ম্মৃদ্ধ ফেমুে এবং স্বশজ আঙ্গু / থে থেোন টে জোিীয় ফে . (Vitamin C rich fruits and Vegetables) সবচজ- থরোেশে, ফুেেশপ, টকমকটো, স্বুজ বোাঁধোেশপ ‡Zj, Pwe©, gvLb (Oil, fat, butter) ‡Zj, Pwe©, gvLb 1 0

12. েত সাত রিসন পরিবাসিি খািয ঘাটরত সমাকাসবলাি সকৌশল /Reduced Coping Strategy Index (Consumption based coping) প্রশ্ন করার আলে এই যসকসান সম্পলকে পূবে ধারণা শদন । যযমন: েত সাত(০৭) শদন আপশন অথ্বা আপনার পশরবারলরর অনয সদসযলদর যকান একজলনর খাদয ঘাটশত হলয় থ্াকলে তা শক কারলন ঘলটলছ জানার যচষ্টা ক쇁ন ? অভ্াব/সামথ্েযর কারলন খাদয ঘাটশত হলয় থ্াকলে উলেশখত পদ্ধশত অনুসরণ ক쇁ন (লযমন: কত যবো/ যকান যকান শদন / কত শদন যকাশিং ক쇁ন ) Key (DËi) Never (KLbB bv n‡j) = 0 েত ৭ শদল᷍ আপশন অথ্বা আপনার পশরবারলরর Less than 1 day (GK w`‡bi Kg n‡j) = 0.5 অনয যকান সদসয কতশদন ------শছলেন? 1 – 2 days (GK †_‡K `yB w`b n‡j) = 1.5 In the past 7 days, did you or any household 3 – 6 days (wZb †_‡K Qq w`b n‡j) = 4.5 member. 7 days (mvZ w`b n‡j) = 7

A. Number B. Points according C. Universal Score- of days to the key severity †¯‹vi weight (BxC) 1. Rely on less preferred & less expensive foods? (Kg cQ‡›`i Lvevi ev Kg `vgx 1 Lvev‡ii Dci wbf©i K‡i wQ‡jb?) 2. Borrow food or rely on help from neighbor/relatives? (Lvevi avi K‡i ev 2 cÖwZ‡ekx/AvZ¥x‡qi KvQ †_‡K wb‡q †L‡qwQ‡jb?) 3. Reduce meal size at meal times? (Lvev‡ii Afv‡e cÖ‡qvR‡bi Zzjbvq Kg 1 cwigv‡Y Lvevi MªnY K‡i‡Qb?) 4. Restrict consumption by adults so that small children can eat? (Lvev‡ii Afv‡e 3 eq¯‹iv Kg †L‡q‡Qb, hv‡Z wkïiv †L‡Z cv‡i?) 5. Reduce the number of meal eaten per day? 1 (Lvev‡ii Afv‡e w`‡b 3 †ejvi Zzjbvq Kg‡ejv (2/1 †ejv) Lvevi MªnY K‡i‡Qb?)

13. Water, Sanitation and Hygiene (cvwb cqwb®‹vmb e¨e¯’v I cwiQbœZv) 13.1 MAIN WATER SOURCE FOR DRINKING/ Lvevi cvwbi cÖavb Drm wK ? (GKwU DËi) 6 = Surface water (river, stream pond) SY©v, b`x cyKzi 1 = Tubewell (shallow) bjKzc (AMfxi) 7 = Pond Sand Filter cÛ-m¨vÛ wdëvi 2 = Tubewell (deep) bjKzc (Mfxi) 8 = Piped network mieivnK…Z cvwb 3 = Protected well msiwÿZ Kzc 9 =Arsenic, Iron Removal Plant (AIRP) Av‡m©wbK, Avqib 4 = Unprotected well D¤§y³ Kzc wi‡gvfvj cø¨v›U 5 = Rainwater harvesting e„wói cvwb (msiÿb) 10. Others……………….. 68

13.2 Is this source available round the year cvwbi GB Drm ‡_‡K wK mviv eQi cvwb cvIqv hvq? (1=Yes, 0=No) 13.3 How far is the drinking water source from your home? evwo ‡_‡K LvIqvi cvwbi Dr‡mi `yiZ¡ KZ ?

1= 0-150 ft (1=0-150 dzU) 2= >150 ft (2= 150 dz‡Ui ‡P‡q †ekx) 13.4 How far is the water source from the nearest latrine pit? খাওয়ার পাশনর উৎস যথ্লক শনকটবতী েযাশিলনর 嗁লপর

মধযবতী দুরত্ব কত? 1= 0-30 ft 2= 30 to 100 ft, 3= 100 ft 13.5 Who usually collects the water from 1= Adult Women (1=cÖvßeq¯‹ gwnjv); 2=Girls (2 = evwjKv); the water source?/ 3= Adult Men (3 = cÖvßeq¯‹ cyiæl); 4= Boys (4 = evjK) যক সাধারনত পাশন সংগ্রহ কলর? 1 = Yes, all of them are covered every time (1 = n¨uv, memgq) 13.6 Do you cover containers when 2 = Some are covered some are not (2 = wKQy XvKbv †`qv wKQy Transporting drinking water / খোওয়োর পোচন XvKbv Qvov)

বহসনি সময় পাসে ঢাকনা সিন রকনা? 3 = No, do not cover (3 = bv, XvKbv Qvov) 1 = Same container used for collection/transport (1= msMÖn/enb GKB cvÎ) 2 = Bucket/ pitcher (Kalash)/ container uncovered (2= evjwZ/Kjmx 13.7 How is drinking water stored within XvKbv Qvov) the HH? রকভাসব বাড়ীসত খাবাি পারন 3 = Bucket/ pitcher (Kalash) /container covered (3 = evjwZ/Kjmx (িক্ষন কসি হয়? (Observe alsoﶂস XvKbv ‡`qv) 4 = Bucket/pitcher (Kalash) /container with cover and tap (4 = evjwZ/ Kjmx XvKbvmn †gvov‡bv) 13.8 How often do you wash the container 1= every day (1=cÖwZ w`b) 2= twice per week(2=mßv‡n 2 evi) 3= for storing water? once per week (3= mßv‡n GKevi) 4= less than once per week (িক্ষসনি জনয বযবত পাে কত বাি (4=mß‡n GKw`bI bvﶂপারন স সধায়া হয়?

14. HOUSEHOLD SANITATION AND HYGIENE (cvwievwiK cqwb®‹vmb e¨e¯’v I cwiQbœZv) 1 = Piped with Sewerage system/m¨yqv‡iR jvB‡bi mv‡_ hy³ cvqLvbv Where do the members of 2 = Latrine with Septic Tank/ m¨vwÞK U¨vsKmn cvqLvbv your HH defecate? 3 =Latrine withwater seal/IqvUvi wmj mn cvqLvbv (Observe latrines 4 = Latrine without water seal/IqvUvi wmj Qvov cvqLvbv 14.1 mentioned to confirm) / 5= Latrine which pit is broken/unmanaged/mixed wiht nearby water body পরিবাসিি সলাকজন 6 = Hanging latrine/SzjšÍ cvqLvbv সাধািনত সকাথ্ায় পায়খানা 7 = No latrine (defecate openly nearby roads, river, field, jungle etc.) কসি থ্াসকন? /cvqLvbv bvB (iv¯Ív/b`xi av‡i/‡Lvjv gv‡V/ ‡hLv‡b-†mLv‡b/‡Svc-R½j) 8 = Others (specify)/ Ab¨vb¨ (wbw`©ó Kiæb)

0 = No child under 5/০=৫ বছলরর নীলচ বাচ্চা যনই 1 = Child used latrine Last time your young child (1 = ev”PvwU cvqLvbv e¨envi K‡i‡Q) defecated, what was done 2 = Picked up and threw in latrine (2 = gj wb‡q cvqLvbvq †djv n‡q‡Q) with the feces? (Only one 3 = Left in the open where child defecated answer) 14.2 (3 = †hLv‡b gj Z¨vM K‡i‡Q †m_v‡bB Db¥y³fv‡e †djv Av‡Q) আপনার যছাট বাচ্চা綿 েতবার 4 = Buried or covered with soil/ash যকাথ্ায় মে তযাে কলরলছ এবং (4 = gvwU/QvuB w`‡q XvKv‡bv)

যসটা শক কলরলছন? (�ধুমাত্র 5 = Picked up and thrown in solid waste pile

এক綿 উত্তর) (5 = gj wb‡q gqjv ¯‘‡c †djv n‡q‡Q)

6 = Picked up and thrown out of compound (in open)

(6 = gj wb‡q Qz‡o †djv n‡q‡Q) 15. Hand-washing Behaviour (nvZ avqvi Af¨vm) 69

1 = Water only (1= ïay cvwb) 2 = Water and ash (2 = cvwb Ges QvuB ) 15.1 MOST OFTEN, what do you use to wash your hands? / 3 = Water and sand/mud (3 = cvwb Ges evwj ) আপশন শবিরভ্াে সময় শক শদলয় হাত পশরস্কার কলরন? Ask open ended. 4 = Water and soap (4 = cvwb Ges mvevb) Only one answer representing most frequent behaviour 5 = Other: (specify) ______(5 = Ab¨vb¨, wbw`ó K‡i ejyb)

0 = No, I don’t specifically wash my hands (1 = bv, nvZ 15.2 On a normal day, do you wash your hands with soap? If cwi¯‹vi Kwi bv) yes then ask the following questions/ Avcwb wK স্োবোন শদকয় nvZ cwi¯‹vi/ ? যধৌত কলরন হাাঁ হলে শনলমাক্ত প্রশ্ন巁লো ক쇁ন 1 = Yes, I do wash my hands (n¨uv, Avwg nvZ ay‡q _vwK)

Put a Tick sign (√) on the correct responses/ mwVK DË‡i 15.3 If yes, what times do you wash your hand with soap. যশদ wUK wPý (√) w`b হযাাঁ হয়, কখন আপশন আপনার হাত স্োবোন শদকয় ধুলয় থ্ালকন? (multiple answers possible/ উত্তর অলনক হলত পালর।

DO NOT PROMPT/ উত্তরসমূহ আলে যথ্লক বলে শদলবন না। �ধুমাত্র যয উত্তর巁লো বেলব তার িানপালিে 綿ক শচহ্ন শদলবন। 1 = Before cooking food (1 = nüv, ivbœvi Av‡M) 2 = After defecation (2 = nüv, gj Z¨v‡Mi c‡i) 3 = Before eating food (3= nüv, Lvev‡ii Av‡M) 4 = After disposing of child’s feces/cleaning child ( 4=nüv,

ev”Pvi ‡kŠP KvR Kiv‡bv c‡i) 5 = After working with animals, crops, etc. (5=n¨uv,

Mfvw`cï, km¨ wb‡q KvR Kivi c‡i) 6 = Before feeding child ( 6=n¨uv, ev”Pv‡K Lvevi) 7= Before breastfeeding (বুলকর দুধ খাওয়ালনার আলে) 8= After sneezing (৮ =হযাাঁ, হাশচ যদয়ার পর ) 9= After handling money (৮=হযাাঁ, যখশন টাকা নারাচারা

কলরন) 10= Others

15.4 হাত যধায়া জনয পায়খানার মলধয বা তার পালি সাবান আলছ (1=yes; 0= no) শকনা তা পযেলবক্ষণ ক쇁ন। Observ that Soap is available in Latrine or besides?

Appendix 5: Event Calender

Month 2013 2014 2015 2016 2017 2018 Winter Winter Winter Winter session, Winter Winter session, Eid-E- session, Eid-E- session, Eid-E- English New session, Jan session, Eid- miladunnobi, miladunnobi miladunnobi, Year’s Day English (Poush- E- 48 12 National 36 24 New 0 Magh) miladunnobi Election /// Year’s

Day End of End of End of Winter End of Winter Feb winter, Winter/// Mother Language (Magh- 59 End of Winter 47 35 23 11 maghi Day Falgun) purnima Hervesting Hervesting Hervesting time Hervesting time work brick time work brick work brick field, Mar Hervesting time work brick field on March field, Birth day of (Falgun- time work 58 field, Local 46 34 22 10 31) Bangabandu Chaitra) brick field Upazila Independence election Day Harvesting Harvesting Harvesting Harvesting time, Harvesting April time, New time, New year time, New year Bangla New year time, New year (Chaitra- year day 57 day/ Pohela day (Pohela 21 day (Pohela day(Pohela 45 33 9 Baishakh) (Pohela Boishak (End Boishak). Boishak). Boishak). Boishak). of hot season ) May Summer, Summer, Summer, Summer, Summer, (Baishakh- Cyclone 56 Buddho 44 Buddho 32 Buddho 20 Buddho purnima 8 Jaishtha) mohashen purnima purnima purnima Shab-e-Barat Start of long Start of long Start of long Shobe-e Qadar & June rainy Start of long rainy session, rainy session, Jummatul bida/ (Jaishtha- session, 55 rainy session, 43 Shab-e-Barat 31 Shab-e-Barat 19 Eid-ul Fitr 7 Ashar) buddho Shab-e-Barat purnima Start of Eid-ul fitor, Eid-ul fitor, Rainy session July Ramadan, Eid-ul fitor, Rainy session Rainy session (Ashar- 54 18 Rainy Rainy session 42 30 6 Srabon) session. Rainy Session, Rainy Session, Rainy Session, Aug Eid-ul fitor, Rainy Session, Janmashtami Janmashtami Janmashtami (Srabon- Rainy 53 17 Janmashtami 41 29 5 Vadro) session

Sept end of the End of the long End of the long Eid Ul Adha End of the long (Vadro- long rainy 52 rainy session/ rainy session/ 16 Durgapuja rainy session 40 28 4 Ashshin) session Eid-ul Azha, Eid-ul Azha, (Dashami) Durga Puja, Durga Puja, Durga Puja, Eid-ul Azha, Oct , Go brick Moharram Moharram Moharram Durga Puja, (Ashshin- field up to 51 15 Go brick field 39 27 3 Kartik) march. up to march. Harvesting Harvesting Harvesting time, Nov Start working Start working 2 time, Start time, Start Start working in (Kartik- in salt field, 50 in salt field, 14 38 working in salt 26 working in salt salt field, Agrahayan) Moharram Moharram field, field, Christmas, Christmas, Dec Christmas, Christmas, 1 Starting Starting Christmas, (Agrahayon- Starting 49 Starting 13 37 Winter 25 Winter Starting Winter Pous) Winter Winter