eCommons@AKU

Department of Paediatrics and Child Health Division of Woman and Child Health

2011

Pakistan National Nutrition Survey, 2011

Zulfiqar A Bhutta Aga Khan University

Sajid Bashir Soofi Aga Khan University

S. Shujaat H Zaidi Aga Khan University

Atif Habib Aga Khan University, [email protected]

Imtiaz Hussain Aga Khan University

Follow this and additional works at: https://ecommons.aku.edu/ pakistan_fhs_mc_women_childhealth_paediatr

Recommended Citation Bhutta, Z., Soofi, S., Zaidi, S., Habib, A., Hussain, I. (2011). akistanP National Nutrition Survey, 2011. Available at: https://ecommons.aku.edu/pakistan_fhs_mc_women_childhealth_paediatr/262

Forward

National economic planning has a key role in socio economic development of any country, which requires accurate and current data and statistics. The Planning Commission maintains updated national socio economic statistics - an important element of sustained planning process. The nutrition status which is both the cause and consequence of poverty is a key challenge for any country. Malnutrition, particularly in mothers and children leads to many adverse consequences for development. It impacts learning abilities in children and put them at disadvantage in life. Nutrition remains a difficult area to gauge and monitor by virtue of its multiple dimensions and vulnerability to the changes in allied sectors. The present National Nutrition Survey (NNS) Report, based on information collected and managed through cross sectional population survey, is fourth in the series since 1980. The Report provides an important input for policy planning with priorities aligned in line with the present time challenges. The Survey not only analyses data and information about existing nutritional status of the population but also co-relates these to the course of action to be developed. It also identifies underlying causes like food security, dietary behaviours, breastfeeding and complementary feeding practices, literacy level, etc. contributing towards present level of malnutrition.

The work on the fourth National Nutrition Survey was initiated during 2010-11 with the objective of assessing the nutritional status of the population particularly women and children. The task was assigned to Aga Khan University (AKU) Karachi with the technical & financial support of development partners. The exercise was overseen and ratified by the Federal Steering Committee while detailed micro planning was carried out by a Technical Committee comprising relevant stakeholders; from Federal and Provincial Governments, International NGOs, the UN Agencies, Pakistan Bureau of Statistics (PBS) and Pakistan Medical and Research Council (PMRC). The agreed survey manual covering sampling procedure, questionnaire and consent form was reviewed and approved by the National Bioethics Committee (NBC) of the Government of Pakistan and the AKU’s Research Ethics Review Committee. The field work was conducted during the first half of 2011.

The survey implementation was closely monitored by the AKU University, UNICEF and external monitors.The results were disseminated at federal level in September 2011, with subsequent information sharing and dissemination workshops organized for the provincial governments and regions. Following their inputs and endorsement, the report has been finalized. This is the first nutrition survey that provides key nutrition data for the provinces and the regions.

The NNS 2011 presents the current nutrition situation, analysis of the trends in indicators and gauges progress towards the targets set for the Millennium Development Goals (MDGs) and beyond. The survey also assesses the severity and geographical scope of nutrition related issues. Furthermore, it sets the platform for policy and strategy development to prioritize the programs for short, medium and long term interventions at the national and provincial level.

The survey reports that in past decade there has been marginal improvement in the core maternal and childhood indicators, universal salt iodization, while other key indicators like stunting, wasting, anaemia, and vitamin A deficiency have shown declining trends which is more prominent in the rural areas. Government of Pakistan wishes to thank all concerned for undertaking this survey, which is the one of largest survey of this kind in Pakistan. We are committed to a vigorous policy response to the findings of this survey in order to make malnutrition history in Pakistan.

(AHSAN IQBAL) Federal Minister/Deputy Chairman Ministry of Planning & Development Acknowledgement

The completion of the NNS 2011 is an important achievement supporting the Government of Pakistan in its quest to set priorities for the development of the country in the post devolution scenario. This is the first national nutrition survey conducted after a decade of the last survey and provides essential information on the actual scale and magnitude of under-nutrition in Pakistan. It gives critical information on determinants, differentials and provides information for policy guidance to the federal and provincial Governments. The completion of the survey is the outcome of concerted efforts of a well guided and technically robust survey team supervised by Ministry of Health, whose members worked tirelessly and continuously under exceptionally difficult circumstances. We wish to express our deep gratitude for all those that contributed to the completion of this enormous task.

Firstly, we deeply acknowledge the participating families, mothers, and the children for their willingness and cooperation with the survey team, provision of the required information, samples and valuable insights during the survey. Without their support, this survey would not have been possible.

We wish to express our sincere gratitude to government institutions, including representatives of the former Ministry of Health and its pre-devolution Nutrition Wing, represented by Dr. Abdul Baseer Khan Achakzai, Director Nutrition (Former Deputy Director General/National Nutrition Focal Person for the Survey, Mr Mohammed Ayub and Mr Muhammad Aslam Shaheen of the Planning Commission, Dr. Ali Nasir Bugti, Dr. Mehmood Ahmad, Dr. Dure Shehwar, Dr. Qaisar Ali, Dr. Shabir Dar, Dr. Fawad Khan, Mr. M.Abbas, Mr. Khair ul Bashar of the Provincial Nutrition Cells, and Mr. Muhammad Ramzan Khan of the PBS, for supporting this ambitious survey in Pakistan. We would like to express our sincere appreciation to the National Steering Committee for its directives and guidance. We are most appreciative of the invaluable technical inputs provided by the National Technical Committee members which included representatives from Federal and Provincial Departments of Health, the Nutrition Wing of the Ministry of Health, Pakistan Bureau of Statistics, Planning Commission, Agricultural University Peshawar, National Institute of Health, WHO, UNICEF, WFP, AusAID, DFID, USAID, World Bank, and the Micronutrient Initiative.

Special thanks to UNICEF for taking overall responsibility for supporting and coordination of the survey through the Aga Khan University and Pakistan Medical Research Council. We wish to acknowledge Prof. Zulfiqar A Bhutta, Dr. Sajid Soofi and their team from the Aga Khan University, Dr. Assad Hafeez of HSA and Dr. Huma Qureshi from the Pakistan Medical Research Council, for conducting the survey in a highly professional manner, including in- depth survey preparation, data collection, analysis, and dissemination and completion of the report.

We are grateful to DFID and AusAID for the core financial support without which this valuable survey would not have been possible. At the end I urge all the nutrition partners to come forward for their technical and resources support in the planning of nutrition interventions for the provinces and regions in Pakistan to address the issues of malnutrition, specifically of mothers and children.

(Imtiaz Inayat Elahi) SECRETARY CREDITS

Principal Survey Lead Institution: Aga Khan University, Pakistan

Principal Investigator: Professor Zulfiqar A Bhutta, FCPS, FRCPCH, PhD Founding Chair Division of Women and Child Health & Director Center of Excellence in Women and Child Health, Aga Khan University, Pakistan

National Survey Coordinator: Dr. Sajid Bashir Soofi, MBBS, FCPS Assistant Professor, Department of Paediatrics & Child Health, Aga Khan University, Pakistan

Survey Coordinators Dr. Muhammad Atif Habib, Senior Instructor, Research Mr. Imtiaz Hussain Hilbi, Senior Social Scientist, Research Mr. S. Shujaat H. Zaidi, Senior Social Scientist, Research Dr. Noushad Ali, Research Supervisor

Regional Coordinators Mr. Maswar Hussain, Dr. Abdul Razzaq Lasi, Mr. Gul Nawaz, Dr. Azam Baber, Dr. Tariq Samejo, Dr. Mushtaq Dero, Mr. Mushtaq Mirani, Dr. Aftab Bhatti and Mr. Asmatullah Khan

Data Management Analyst Mr. Imran Ahmed, Data Manager, Mr. Zaid Shakoor Bhatti, Data Analyst & Mr. Najeebur Rehman, Data Coordinator

Management and Administration Mir Asghar Ali Khan, Senior Manager, Research and Grants Mr. Ishrat Abbas, Manager, Budget and Finance Mr. M. Siddique, Shukurullah Baig, Fida H. Choghtai, Logistic Management Mr. Rashid Khan and Mr. Khuram Noorani, Financial Management Mr. Didar Alam, Laboratory Coordinator

Collaborators: Pakistan Medical Research Council (PMRC) Dr. Huma Qureshi, Deputy Director Dr. Arif Munir, Mr. Mehmood and Mr. Rizwanullah

Federal Bureau of Statistics Mr. Muhammad Ramzan Khan, Ex-Director, Sample Design

Planning Commission, Government of Pakistan Federal & Provincial Nutrition Wing, Ministry of Health, Government of Pakistan

UNICEF, Pakistan

ii | National Nutrition Survey 2011 May 2013

INDEX A. Acronyms------vi B. General definitions ------viii C. Reference ranges for biochemical assessments------ix D. Executive summary ------xi CHAPTER 1: Introduction ------1 1.1 Introduction ------1 1.2 Context of malnutrition ------1 1.3 Need for a National Nutrition Survey ------5 1.4 Survey duration ------6 CHAPTER 2: Survey Design and Methods------7 2.1 Survey Objectives ------7 2.2 Methodology ------7 2.3 Sample size and its allocation ------7 2.3.1 Sample size estimation for household survey and biochemical assessment ------7 2.3.2 Sampling frame and design ------9 2.3.3 Sample selection procedure ------10 2.3.4 Target population ------10 2.3.5 Description of questionnaire ------10 2.3.6 Description of qualitative research ------11 2.3.7 Biochemical analysis ------11 2.3.8 FATA specific data ------11 2.3.9 Project pre implementation steps ------12 2.3.10 Plan of operation, training and monitoring ------14 2.3.11 Data management, transfer and analysis ------14 2.3.12 Ethical approval and confidentiality ------15 RESULTS OF THE NATIONAL NUTRITION SURVEY ------16 CHAPTER 3: Background and Household Characteristics------17 3.1 Completion of data collection ------17 3.1.1 Blood and urine specimen ------18 3.2 Background and household characteristics ------18 3.3 Formal education – head of household and mothers ------18 3.4 Occupation – head of household ------18 3.5 Nature of dwelling by type of floor, roof and walls ------19 3.6 Type of cooking fuel ------20 CHAPTER 4: Food Insecurity in Pakistan ------21 4.1 Food secure ------21 4.2 Food insecure without hunger ------21 4.3 Food insecure with hunger (moderate) ------22 4.4 Food insecure with hunger (severe) ------22 CHAPTER 5: Maternal Health and Nutrition ------23 5.1: Basic data – age, education and marital status of mothers------23 5.1.1 Age distribution ------23 5.1.2 Marital status and current pregnancy status ------23 5.2: Reproductive history and antenatal care ------23 iii | National Nutrition Survey 2011 5.2.1 Reproductive history ------23 5.2.2 Antenatal care ------23 5.3: Knowledge of micronutrients and micronutrient rich foods ------25 5.3.1 Knowledge of micronutrients ------25 5.3.2 Knowledge of vitamin rich foods ------26 5.3.3 Knowledge about iodized salt and its usage------26 5.4: Clinical examination ------27 5.5: Anthropometry ------28 5.6: Micronutrient deficiency ------29 5.6.1 Urinary iodine excretion of mother ------29 5.6.2 Night blindness ------29 5.7: Biochemical analysis ------30 5.7.1 Anaemia (haemoglobin levels)------30 5.7.2 Ferritin concentration ------31 5.7.3 Vitamin A deficiency ------31 5.7.4 Zinc deficiency ------32 5.7.5 Vitamin D deficiency ------33 5.7.6 Calcium Status ------34 CHAPTER 6: Child Health and Nutrition ------35 6.1: Nutrition status of children ------35 6.1.1 Children 0–59 months ------35 6.1.2 Anthropometry (children under 5 years of age) ------35 6.1.3 Stunting (children under 5 years of age) ------36 6.1.4 Wasting (children under 5 years of age) ------36 6.1.5 Underweight (children under 5 years of age) ------36 6.1.6 Education of mothers and its effect on nutritional status of children ------37 6.1.7 Malnutrition trends in children under 5 years of age – comparison of SAARC countries ----- 37 6.2: Biochemical assessment ------39 6.2.1 Anaemia ------39 6.2.2 Iron deficiency (low ferritin levels) ------40 6.2.3 Vitamin A deficiency in children (under 5 years) ------40 6.2.4 Zinc deficiency ------41 6.2.5 Vitamin D deficiency ------42 6.2.6 Urinary iodine excretion in children 6–12 years ------42 6.2.7 Clinical examination of children under 5 years of age ------43 6.3: Child morbidity ------43 6.3.1 Prevalence of acute respiratory infections ------44 6.3.2 Prevalence of diarrhoea ------44 CHAPTER 7: Infant and Young Child Feeding Practices ------45 CHAPTER 8: Food Intake and Practices ------50 CHAPTER 9: Elderly Persons Health and Nutritional Status ------54 Chapter 10: National Nutrition Survey – Qualitative Findings------56 Chapter 11: What Next? ------63 Bibliography ------67 Annex: NNS Detailed Tables , Sample Design and Sample Weight ------69

iv | National Nutrition Survey 2011 CONTENT OF FIGURES AND TABLES Table 2.1: Sample size and allocation plan 8 Table 2.2: Region wise sample size and its distribution 8 Table 2.3: Description of biochemical analysis/tests 11 Table 2.4: Pre-implementation steps 12 Table 2.5: Details of the training agenda 13 Fig 3.1: Population density 17 Fig 3.2: National Nutrition Survey coverage 17 Table 3.1: Details of sample size coverage (Number of PSUs and SSUs by Province / Region 17 Fig 3.3: Formal education of mothers of children under five years of age. 18 Fig 3.4 (a-c): Nature of dwelling – materials used 19 Fig 3.5: Nature of dwelling – urban/rural comparison of materials used for construction 20 Fig 3.6: Source of fuel for cooking 20 Fig 4.1: Food insecurity situation 22 Fig 5.1: Antenatal care during last pregnancy 24 Fig 5.2: Seeking ANC from skilled care provider 24 Fig 5.3: Micro-nutrient supplementation during last pregnancy 25 Fig 5.4: Knowledge about micronutrients 25 Fig 5.5: Level of Iodine content in salt 27 Fig 5.6: Clinical examination of mothers (comparison NNS 2001-02 and NNS 2011) 28 Fig 5.7: Body Mass Index 28 Fig 5.8: Median urinary iodine excretion in mothers 29 Fig 5.9: Comparison of night blindness in women 30 Fig 5.10: Maternal anemia 30 Fig 5.11: Comparison of anemia in mothers 31 Fig 5.12: Ferritin concentration 31 Fig 5.13: Vitamin A deficiency (pregnant women) 32 Fig 5.14: Comparison of vitamin A deficiencies among non-pregnant women (urban/rural) 32 Fig 5.15: Zinc deficiency (pregnant women) 33 Fig 5.16: Comparison of Zinc deficiency among non-pregnant women (urban/rural) 33 Fig 5.17: Vitamin-D deficiency (pregnant women) 34 Fig 5.18: Calcium deficiency (pregnant women) 34 Fig 6.1: Households with children under 5 years of age 35 Fig 6.2: Prevalence of malnutrition in Pakistan (children under 5 years of age) 35 Fig 6.3: National stunting rates for children under 5 years of age 36 Fig 6.4: National wasting rates (children under 5 years of age) 36 Fig 6.5: Underweight (children under 5 years of age) national 37 Fig 6.6: Education of mothers and its association with nutritional status of children 37 Fig 6.7: SAARC countries national stunting trends 38 Fig 6.8: SAARC countries national wasting trends 38

v | National Nutrition Survey 2011 Fig 6.9: SAARC Countries national underweight trends 38 Fig 6.10: Anaemia in children under 5 years of age 39 Fig 6.11: Trends of prevalence of anemia in children under 5 years of age 39 Fig 6.12: Iron deficiency among children 40 Fig 6.13: Vitamin A deficiency 40 Fig 6.14: Trend of vitamin A deficiency in children under 5 years 41 Fig 6.15: Zinc deficiency in children (0–5 years) 41 Fig 6.16: Comparison of zinc deficiency in children under 5 years of age 42 Fig 6.17: Vitamin D Deficiency 42 Fig 6.18: Median urinary iodine excretion in children 6-12 years 43 Fig 6.19: Current ARI status 43 Fig 6.20: Reported Prevalence of diarrhoea 44 Fig 7.1: Exclusive breastfeeding of children 0-23 months (reported by mothers) 45 Fig 7.2: Predominant breastfeeding of children 0-6 months (24 Hours dietary recall) 45 Fig 7.3: Initiation of breastfeeding within one hour 46 Fig 7.4: Continued breastfeeding practices 46 Fig 7.5: Introduction of Semi-Solid (6-8 months) 47 Fig 7.6: Minimum dietary diversity (6-23 months) 47 Fig 7.7: Minimum meal frequency (6-23 months) 48 Fig 7.8: Minimum acceptable diet (6-23 months) 48 Fig 7.9: Age appropriate breastfeeding (0-23 months) 49 Table 8.1: Food groups consumed by 0-23 months children (based on 24 Hours food recall) 51 Table 8.2: Frequency of Daily Intake of Food Groups (Children 0 – 23 months) 51 Table 8.3: Frequency of Daily Intake of Food Groups among Children by their Age Group 52 Table 8.4: Food groups consumed by mothers of children 0 – 23 months (based on 24 Hours 52 food recall) Table 8.5: Average Frequency of daily intake of food groups (mothers of children) 53 Fig 9.1 Age distribution of elderly persons 54 Table 9.2: Detail data according to the WHO classifications 55

vi | National Nutrition Survey 2011 ACRONYMS

AGP Alpha-1-Acid Glycoprotein AJK Azad Jammu and Kashmir AKU Aga Khan University ANC Antenatal care ARI Acute respiratory infection BMI Body Mass Index CF Complementary feeding CHW Community health worker CRP C-Reactive Protein DHS Demographic health survey DMU Data management unit EB Enumeration block ERC Ethical Review Committee FATA Federally Administered Tribal Areas FBS Federal Bureau of Statistics FGD Focus group discussion FHI Family Health International GB Gilgit Baltistan GAIN Global Alliance for Improved Nutrition Gm. Gram HH Household IDA Iron deficiency anaemia IDI In-depth Interview IYCF Infant and young child feeding K. Cal Kilocalories KAP Knowledge, attitude and practice KP Khyber Pakhtunkhwa LBW Low birth weight LHV Lady Health visitor LHW Lady Health worker MDG Millennium Development Goal Mg Milligram Ml Millilitre MOH Ministry of Health MUAC Mid-upper arm circumference MWRA Married women of reproductive age NGO Non-governmental organization NID National Immunization Day NNS National Nutrition Survey

vii | National Nutrition Survey 2011 ORS Oral rehydration salt PCO Population Census Organization PDHS Pakistan Demographic Health Survey PMRC Pakistan Medical Research Council PPS Proportion to population size PRSP Punjab Rural Support Program PSU Primary sampling unit RDA Recommended dietary allowance SAARC South Asia Association of Regional Cooperation SSU Secondary sampling unit TBA Traditional birth attendant UIE Urinary iodine excretion UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD Vitamin A deficiency WHO World Health Organization WRA Women of reproductive age

viii | National Nutrition Survey 2011 General Definitions

Body mass index (BMI): Statistical measure of weight scaled according to height, determined by dividing a person’s weight by the square of their height in metric units. For adults, a BMI of less than 18.5 typically indicates under nutrition, while a BMI of more than 40 indicates morbid obesity.

Complementary feeding: This is the period starting when breast milk alone is no longer sufficient to meet the nutritional requirements of infants. Other foods and liquids are needed to complement breast milk at this stage. This transition from exclusive breastfeeding to family foods typically covers the period from 6 months to 18-24 months of age.

Exclusive breastfeeding: The practice of only feeding breast milk to an infant with no supplementation of any kind (e.g. no water, juice, food, or non-human milk). Exclusive breastfeeding has been shown to provide improved protection against many diseases. According to the World Health Organization, on a population basis, exclusive breastfeeding for six months is the optimal way of feeding infants. Thereafter infants should receive complementary foods with continued breastfeeding up to two years of age or beyond.

Malnutrition: Various forms of poor nutrition leading to both underweight and overweight conditions caused by a complex array of issues, including dietary inadequacy, infections, and socio-cultural factors. Malnutrition can lead to wasting and stunting, micronutrient deficiencies, as well as diabetes and other diseases.

Micronutrients: Nutrients needed for life in miniscule amounts. These substances enable the body to produce enzymes, hormones and other substances essential for proper growth and development. Micronutrients are used to improve nutrition through processes such as bio fortification and supplementation.

Stunting: Failure to reach linear growth potential because of inadequate nutrition or poor health, also defined as a chronic restriction of growth in height indicated by low height-for- age. Stunting is usually a reliable indicator of long-term under nutrition among young children.

Supplementation: Process of supplying nutrients – in forms such as bars, capsules, and powders – those missing or not consumed in a person’s diet. Typical supplements include vitamin A, iron, and zinc.

Under-nutrition: According to the 2008 Lancet series on maternal and child under nutrition, under nutrition includes a wide array of effects including intrauterine growth restriction resulting in low birth weight, underweight, stunting, wasting and less visible micronutrient deficiencies. Under nutrition is caused by poor dietary intake that may not provide sufficient nutrients, and/or by common infectious diseases such as diarrhoea. These conditions are most significant during the first two years of life.

ix | National Nutrition Survey 2011

Underweight: This indicates a person has a low weight for their age and implies stunting or wasting. The rate of underweight children is the percentage of children who have low weight for their age.

Wasting: Acute weight loss indicated by a low weight for height ratio. Wasting is usually a result of acute starvation or severe disease. Often more chronic during the first two years of life, wasting is part of a pattern of under nutrition.

Reference ranges for biochemical assessments Women of Reproductive Age

Women of Reproductive Age Pregnant

Biochemical Test Children under 5 years Non-pregnant

Severe (<0.35 µmol/L) Severe (<0.35 µmol/L) Severe (<0.35 µmol/L) Vitamin A Mild (0.35 - 0.70 µmol/L) Mild (0.35 - 0.70 µmol/L) Mild (0.35 - 0.70 µmol/L)

Non-deficient (>0.70µmol/L) Non-deficient (>0.70µmol/L) Non-deficient (>0.70µmol/L)

Severe deficiency (<8.0 ng/mL) Severe deficiency (<8.0 ng/mL) Severe deficiency (<8.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL)

Vitamin D

Desirable (>20.0 - 30.0 ng/mL) Desirable (>20.0 - 30.0 ng/mL) Desirable (>20.0 - 30.0 ng/mL)

Sufficient (>30.0 ng/mL) Sufficient (>30.0 ng/mL) Sufficient (>30.0 ng/mL)

Deficient (<60 µg/dL)

Deficient (<60 µg/dL) Deficient (<60 µg/dL)

Zinc

Non-deficient (60 - 150 µg/dL) Non-deficient (>=60 µg/dL) Non-deficient (60 - 150 µg/dL)

Severe deficiency (<7 gm./dL) Severe deficiency (<7 gm./dL) Severe deficiency (<7 gm./dL)

Moderate deficiency (7 - 10.99 Moderate deficiency (7 - 11.99 Moderate deficiency (7 - 10.99

Haemoglobin gm./dL) gm./dL) gm./dL)

Normal (>= 11 gm./dL) Normal (>= 12 gm./dL) Normal (>= 11 gm./dL)

Low Ferritin (<12 ng/mL) Low Ferritin (<12 ng/mL) Low Ferritin (<12 ng/mL)

Ferritin

Normal (>=12 ng/mL) Normal (>=12 ng/mL) Normal (>=12 ng/mL)

Hypocalcaemia (<8.4 mg/dL) Hypocalcaemia (<8.4 mg/dL)

Calcium Not conducted with children Normocalcaemia (8.4 - 10.2 mg/dL) Normocalcaemia (8.4 - 10.2 mg/dL)

Hypercalcaemia (>10.2 mg/dL) Hypercalcaemia (>10.2 mg/dL)

x | National Nutrition Survey 2011 Executive Summary

The Pakistan’s National Nutrition Survey 2011 was conducted by Aga Khan University’s Division of Women and Child Health, Pakistan’s Ministry of Health and UNICEF. The major objective of NNS 2011 was to assess the population nutritional status (especially of women and children and/or other target groups), and key micronutrient indicators in comparison with the last survey in 2001.

The findings of NNS 2011 provide relevant information for planning, implementation and monitoring appropriate population based interventions in Pakistan. Population groups surveyed included: pre-school children (0–59 months old), school aged children (6–12 years old), women of childbearing age (15–49 years old), and elderly persons (50 years and above). This was the first time a National Nutrition Survey provided provincial specificity with representative population based samples. However, it does not offer district level estimates. A two stage stratified sampling design was adopted and an overall sample size of 30,000 households was selected and calculated on the basis of major nutrition indicators used in the 2001 NNS. These included: 1. stunting in children and 2. Anaemia among women of reproductive age (WRA) and in children. In all, 27,963 households interviewed; 24,421 blood samples were taken (women 12,282; children 12,139); and 2,917 urine samples were collected from women (1,460) and children 6-12 years (1,457) for urinary iodine assessments.

The NNS 2011 covered all provinces: Gilgit Baltistan (GB), Balochistan, Khyber Pakhtunkhwa (KP), Sindh, Punjab, Azad Jammu and Kashmir (AJK) and the Federally Administered Tribal Areas (FATA). This included 1,500 enumeration blocks (EBs)/villages and 30,000 households, with a 49% urban and 51% rural distribution. Renewed listing of all households in each enumeration block was conducted and twenty households were selected randomly using a computer automated selection process. Twenty-two survey teams conducted field activities included data collection, biochemical samples and physical examination across Pakistan.

Results from the 2011 National Nutrition Survey (NNS) indicated little change over the last decade in terms of core maternal and childhood nutrition indicators. With regard to micronutrient deficiencies, while iodine status had improved nationally, vitamin A status had deteriorated and there had been little or no improvement in other areas linked to micronutrient deficiencies. The ratio of males to females was approximately 50.4% to 49.6% across Pakistan. A total of 45.7% of household heads were illiterate and 38.7% were workers or laborers. 15.5% of the population was unemployed – with higher rates in the urban population (18.9% urban unemployment, 14.0% rural unemployment). Using a standard questionnaire, the NNS 2011 indicated that 58.1% of households were food insecure nationally.

xi | National Nutrition Survey 2011

Overall, In Pakistan, 51.9% mothers were having normal weight, 14.1% thin and 33.9% overweight while thin mothers were highest (16.4%) in rural areas compare to urban (9.0%) and overweight mothers were higher (48.4%) in urban areas compare to rural (27.4%). Among the regions and provinces the ratio of overweight mothers was highest (38.2%) in KP and thin mothers were highest (20.6%) in Sindh.

Night blindness prevalence reported by women who were pregnant at the time of this survey was 12.7% while night blindness prevalence reported by women during their last pregnancy was 15.6%. Approximately 42.8% of the population reported awareness of the importance of iodine whereas 64.2% reported awareness about the benefits of iodized salt. Only 39.8% reported using iodized salt whereas kit-testing results confirmed use at 69.1%. This is a significant improvement over the 2001 NNS result of 17%. Overall knowledge of the importance of vitamin A in Pakistan was 24.0%. Knowledge about other micronutrient deficiencies was very low with significant rural and urban differences.

Widespread micronutrient deficiencies were found in women. For example, the survey discovered the following micronutrient deficiency levels in pregnant women: Anaemia 51.0%, iron deficiency anaemia 37.0%, vitamin A deficiency 46.0%, zinc deficiency 47.6%, vitamin D deficiency 68.9%. The prevalence of micronutrient deficiencies in non-pregnant women were as follows: Anaemia 50.4%, iron deficiency anaemia 26.8%, vitamin A deficiency 42.1%, zinc deficiency 41.3%, and vitamin D deficiency 66.8%. Adequate iodine status was documented at national level and in most of the provinces. Balochistan, AJK and

GB were the only provinces that documented inadequate levels (<100 μg/l median iodine excretion) of iodine status.

The proportion of women who were breastfeeding was estimated on the basis of feeding practices in the past 24 hours dietary recall. Data indicated 63.5% of mothers predominantly breastfed children from 0–6 months of age and 77.3% of mothers continued breastfeeding up to 12–15 months.

Anthropometry status has not changed much over the past decade. Among children under 5, 43.7% were stunted in 2011 as compared to 41.6% in the 2001 National Nutrition Survey. 15.1% were wasted compared to 14.3% in 2001, which has not changed since 2001 (NNS 2001). The anthropometric indices were relatively better in urban areas.

Micronutrient deficiencies were also widespread in children. Biochemical analysis revealed the prevalence of various micronutrient deficiencies in children <5 years of age: Anaemia 61.9%, iron deficiency 43.8%, vitamin A deficiency 54.0%, zinc deficiency 39.2% and vitamin D deficiency 40.0%.

xii | National Nutrition Survey 2011

An illustrative sample of 7,612 elderly persons was examined at their residence during the survey. The data revealed that more than half (53.9%) of the Pakistan’s elderly population did not have normal weight; they were either underweight or overweight. Among them 15.8% were thin, 24.2% overweight and 13.9% obese.

The National Nutrition Survey 2011 indicates that stunting, wasting and micronutrient malnutrition are endemic in Pakistan. These are caused by a combination of dietary deficiencies; poor maternal and child health and nutrition; a high burden of morbidity; and low micronutrient content in the soil, especially iodine and zinc. Most of these micronutrients have profound effects on immunity, growth, and mental development. They may underlie the high burden of morbidity and mortality among women and children in Pakistan. Increasing rates of chronic and acute malnutrition in the country is primarily due to poverty, high illiteracy rates among mothers and food insecurity. Such rates can also be attributed to inherent problems in infant feeding practices and lack of access to the age- appropriate foods.

xiii | National Nutrition Survey 2011 Chapter 1: Introduction

1.2 Introduction

Pakistan is a federal parliamentary republic consisting of four provinces – Balochistan, Khyber Pakhtunkhwa, Punjab and Sindh – and four federal territories – the capital Islamabad, the Federally Administered Tribal Areas (FATA), Azad-Jammu and Kashmir (AJK) and Gilgit Baltistan (GB). Bordering India, China, Iran and Afghanistan, the country can be divided into the Indus plain in the East, the mountainous area in the North and Northwest and the Balochistan plateau in the West. [1]

Pakistan is the sixth biggest country in the world, with an estimated population of more than 180 million people. It has the second largest Muslim population of any single country after Indonesia. Ranking 141 out of 182 countries in the Human Development Index (HDI), Pakistan is an impoverished and underdeveloped country. Life expectancy at birth stands at 65 years and the adult literacy rate is 49% (male 63%, female 36%).

Pakistan is a disaster-prone country and is exposed to a multitude of natural disasters including earthquakes, floods, storms and droughts [2-6]. The country was under military dictatorship for 33 of its 64-year existence.

The security situation in Pakistan is complex. There are a number of overlapping threats, including the presence of non-state actors targeting government installations and security forces, especially in the areas bordering Afghanistan. [4, 6]

1.2 Context of malnutrition

Estimates suggest that more than 150 million malnourished children around the world are under 5 years of age. It is also well recognized that half of the 12 million deaths among children under 5, or almost 54% of young child mortality in developing countries, can be linked to malnutrition. [8] Studies suggest that malnutrition has a multiplicative effect on the risk of mortality from infectious diseases. [9]

Like other major health issues, malnutrition is a prevalent problem in the South Asian region. Half of the world’s malnourished women and children are found in just three countries: Bangladesh, India and Pakistan. South Asia is the worst affected region and presents what has been termed an “Asian Enigma” due to high rates of low birth weight (LBW), unhygienic conditions, unsatisfactory breastfeeding and weaning practices and the poor status of women. [10]

Malnutrition is a recognized health problem in Pakistan and plays a substantial role in the country’s elevated child morbidity and mortality rates. Due to its correlation with infections, malnutrition in Pakistan currently threatens maternal and child survival, especially in poor and

1 | National Nutrition Survey 2011 underdeveloped areas. However, there are concrete solutions, which depend on political will, economic advancement and viable targeted research. [7]

The number of underweight children and women is very high in the South Asian region. About one third of babies are underweight and more than half of women of reproductive age weigh less than 45 kg. [11] It is believed that malnourished adult women have a much higher risk of giving birth to low birth weight infants. Infants born with a low birth weight are at a higher risk of morbidity and mortality in the neonatal period or later infancy, especially in developing countries. [12] The infants who survive are often poorly breastfed and weaned, resulting in stunted and malnourished children. These conditions result in children growing into adults who are less prepared to contribute to society and productivity, thus adding to poverty and unemployment in the country. Low birth weight women also develop into malnourished mothers who give birth to LBW babies and perpetuate this cycle.

Stunting is used as a reliable indicator of growth retardation in developing countries. The stunting rates in Pakistan fell from 47% in 1980 to about 33% in 2000. [13] It is estimated that the most important factors associated with lower prevalence of stunting are the availability of high-energy nutrients, female literacy and gross national product. [16] Challenges linked to these factors are still serious in Pakistan and particularly affect children, young girls and women. [16] Like other developing countries in South Asia, with the exception of Sri Lanka, the situation in Pakistan linked to maternal and child under nutrition is serious. [18] Pakistan’s prevalence of stunting declined from 67% in 1977 to an estimated 40-50% and remained at such levels until the end of the 1990s. However, these rates are still very high when compared to the global average. [19] According to the national survey (1990-94), among the urban middle to lower economic group, the prevalence of stunting was approximately 30-36% and as high as 35-45% in the same economic group in rural areas. [20] The national survey categorized economic status on the basis of material possessions and facilities owned by the household. However, it used different criteria for urban and rural households. Thus, Pakistan’s urban-rural difference may be partially explained by the relatively higher level of education among the urban population as well as their access to basic health services. [21]

Malnourished children begin to fall behind on their regular growth at around six months of age. This is the time when an infant starts receiving complementary foods in addition to breast milk. [22] The divergence from normal growth is linked to a combination of poor nutrition and intra- uterine growth. [23] This problem is aggravated by the burden of morbidity. [24] Poor quality and quantity of complementary foods and inadequate caring practices are the key determinants for this early phase of childhood growth retardation, [25] which can lead to late onset of the childhood growth spurt and subsequent retardation. [26] Growth faltering is linked to a series of occurrences a child suffers, including repeated illnesses, inadequate appetite, insufficient food intake and poor standard care. Many of these children die before their first birthday and those who survive suffer long-term consequences such as weak stature and challenged mental capacity. [27]

2 | National Nutrition Survey 2011 Pakistan’s economy is largely dependent on agricultural output. The country’s farmers cultivate sufficient amounts of diverse crops to feed most of the population, which makes the degree of malnutrition even more distressing. However, the issue of malnutrition has been a constant challenge in Pakistan for decades. The micronutrient survey in 1976-1977 revealed that 60% of children under 5 were malnourished. Widespread malnutrition in younger infants was further highlighted by a survey of children under 2 years of age. [28] The results of these surveys were confirmed by high rates of early childhood malnutrition from studies conducted in Lahore. [29,30] The National Nutrition Survey that was conducted in 1985-87 further revealed that 48% of children were malnourished and 10% were severely malnourished. The 2001-2002 National Nutrition Survey also showed a dire malnutrition situation in Pakistan. This was the first time a NNS highlighted the true extent and burden of macronutrient and micronutrient malnutrition in the country. [31]

Widespread macronutrient malnutrition coupled with subclinical micronutrient deficiencies prevail in South Asia and have been largely ignored in the region and in Pakistan. “Subclinical deficiency” is micronutrient malnutrition without visible signs of deficiency, also termed as the

“hidden hunger”. It is estimated that more than seven million people suffer from clinical forms of these micronutrient deficiencies and another 2 billion from subclinical forms. [32]

Various studies and surveys from Pakistan indicate that subclinical micronutrient deficiencies such as iron-deficiency, zinc deficiency and vitamin A deficiency are widespread among pre- school children and women of reproductive age, particularly pregnant women. [31] A survey conducted with pre-school children in the North West Frontier Province (now Khyber Pakhtunkhwa) revealed that about 50% of the children showed evidence of significant anaemia and zinc deficiency. [33] Data on micronutrient malnutrition are scarce and limited. Only a few studies have been conducted on a local scale and these cannot be relied upon to measure larger scale issues. [34]

To implement successful strategies and sustainable interventions, the direct and indirect causes of Pakistan’s huge malnutrition burden must be identified. The analysis below identifies some of the determinants of malnutrition in Pakistan and the impact these factors have on the status of malnutrition in the country.

More than 30% of Pakistan’s population lives below the poverty line. [35] The Gini coefficient, used to measure economic inequality in a society (using the range of 0 to 1, “0” indicating complete equality and “1” indicating complete inequality), is 0.410 in Pakistan. This shows a very high rate of inequality. The poorest 20% of the population earn 6.2% of the country’s total income and most households in Pakistan spend almost half of their income on food. Poor food availability, poor quality of diet, and limited knowledge about nutritious foods all contribute to a vicious cycle of malnutrition. Political issues, security issues linked to non-state actors and unemployment in the country have amplified this problem. Another important risk factor contributing to malnutrition is a high and repeated burden of infections.

3 | National Nutrition Survey 2011 Repeated acute respiratory infections (ARI), diarrhoea and other infections lead to a decrease in dietary intake and nutrient use due to loss of appetite and reduced absorption. [36]

Poor breastfeeding and weaning practices are also common in Pakistan. As a result, infants do not consume adequate calories, proteins and micronutrients. While almost 90% of women breastfeed their children, very few start breastfeeding within one hour of birth and most of them discard colostrum considering it as waste or impure milk that is not suitable for their babies. The rate of exclusive breastfeeding in the first four months is only 16%. The current number of mothers introducing complementary foods at the right time is low and poor food choices commonly result in increased risk of diarrhoea and malnutrition. It is well known that lack of awareness about proper nutrition and feeding practices, coupled with poor food choices, trigger the widespread use of weaning diets with poor micronutrient content and bioavailability. [37]

The fertility rate in Pakistan is very high. On average, Pakistani women give birth 6.8 times in their lives. Approximately only 28% of women between 15 and 49 years of age use contraception. A high fertility rate and lack of birth spacing result in a continuous cycle of pregnancy and lactation. Such a cycle can deplete the body reserves of an already malnourished mother.

The adult literacy rate in 2011 in Pakistan was low, 67% for males and 42% for females. It is believed such low levels of education among women in Pakistan influence their reproductive behaviour. It also makes reproduction related decisions in families and in society at large principally dependent on men’s knowledge and practices. In general, women in Pakistan have very little control over areas of life such as food distribution within household and family planning. [38, 39]

Antenatal care plays a vital role in the wellbeing of mothers and growing children. The care a mother receives during pregnancy and after delivery determines how well she will be able to feed and care for her child. This includes breastfeeding, food preparation, general care, hygiene and home health care. In Pakistan most pregnant mothers are unaware of the importance of antenatal care and have limited access to health facilities. The use of antenatal health care facilities is very low in the country and access has remained static over the years. To make matters worse, in 2011 trained health personnel attended only 39% of births. [40]

The rates of malnutrition in children under 5 determined by the 2001 National Nutrition Survey (NCHS standard) were as follows: wasting 13%, underweight 38% and stunting 37%. In the same survey about 13% of non-pregnant and 16% of pregnant women were reported to be malnourished (BMI<18.5). Similarly high estimates for micronutrient deficiencies shocked both the Pakistani population and the world. In terms of Iodine deficiency about 7% of school going children (6 -12 years) had either palpable or visible goitres on clinical examination. Vitamin A deficiency, as measured by serum retinol levels, quoted 6% of mothers and 12.5% of pre-school children to be deficient.

4 | National Nutrition Survey 2011 Evaluation for iron deficiency showed 45% prevalence in mothers and 66.5% in children. Caring practices were also recognized as poor in the same survey. Many of these indicators are well above the World Health Organization (WHO) cut off points and warrant putting in place immediate public health measures and programs.

The direct and indirect factors that lead to malnutrition contribute to nearly 35% of all under 5 deaths in Pakistan and affect the future health, socioeconomic development and productive potential of the society. Despite an increase in food availability over the past 20 years there has been little change in the prevalence of malnutrition in the population. This may be related to the cross-sectoral and complex nature of malnutrition, which includes issues related to poverty, intra-household food security and contemporary socio-cultural factors determining dietary patterns in pregnancy and early childhood.

1.3 Need for a National Nutrition Survey

National Nutrition Surveys provide an estimate of the severity and geographical scope of nutrition related challenges in a country. They also expose problems closely linked to nutrition issues and identify the most-at-risk groups. Nutrition surveys assess the likely evolution and impact of nutrition levels on the health and nutritional status of the population at large while taking into account secondary information such as food security and food distribution. They also help identify what types of nutrition interventions would be most effective to prevent or minimize the problem in the future. Governments use national surveys when deciding whether or not to establish or expand existing nutrition surveillance and to ensure effectiveness and monitor progress over time. To assess the magnitude of the problem, governments and partners also look at the population size, demographic characteristics of the population and distribution of malnutrition cases therein.

To understand the underlying causes of under nutrition and to plan and implement appropriate interventions and programs to improve the situation, the government and partners must identify the current nutritional status of both the population at large and vulnerable groups, recognize changes in nutritional status over time, and acknowledge the context in which challenges have surfaced. Sources of information that promote a deeper understanding of this context and help identify potential responses include formal nutrition surveys, food security surveys and records of malnutrition cases. Formal nutrition surveys are still the best way to accurately estimate prevalence of malnutrition because they reveal trends in the number of malnutrition cases and identify opportunities for action.

The last National Nutrition Survey was conducted in 2001/2002, almost 15 years after the 1985/1987 National Nutrition Survey. Almost a decade later, the current survey was undertaken with the following goals:

Establish the current nutrition benchmark and related indicators for gauging progress toward the targets set for the Millennium Development Goals (MDGs);

5 | National Nutrition Survey 2011 Establish a benchmark for missing data/indicators, especially since the recent Demography and Health Survey (DHS) did not include anthropometric indicators.

Prioritize the programs and initiatives at the national and provincial level and refine the planning and implementation of initiatives on the basis of identified priorities.

1.4 Survey duration

Data collection began in January 2011 and was completed on 30th June 2011. The survey teams underwent five days of extensive training led by senior and experienced staff from The Aga Khan University who had experience conducting similar surveys in Pakistan and also abroad (Sri Lanka and Maldives). Training sessions and refreshers were conducted in Karachi, Faisalabad, Lahore, Rawalpindi, Peshawar, Abbottabad, Quetta and Gawadar.

6 | National Nutrition Survey 2011 Chapter 2: Survey Design and Methods

2.1 Survey Objectives

The specific objectives of the National Nutrition Survey 2011 were:

Assess the population’s nutritional status, especially children under 5, women of reproductive age, adults and elderly on a national and provincially representative sample.

Collect specific representative data on height, weight and age of children under 5 years of age, women of reproductive age, adults and elderly.

Collect blood specimens for micronutrient status assessments of children and women of reproductive age – mainly vitamin A, zinc, calcium and vitamin D, and iron.

Collect urine samples to assess the iodine status of women of reproductive age and children between 6–12 years of age.

Assess infant and young child feeding and care practices, including breastfeeding, complementary feeding and morbidity of children.

2.2 Methodology

The survey was conducted at national scale through a representative cross-sectional survey at household level. Cross-sectional surveys are useful in providing an overall estimate of prevalence and coverage in a geographic area. The survey used both quantitative and qualitative methods to achieve the objectives. The survey consisted of interviews, measurement of anthropometric indices, collection and testing of biologic specimens. A multi stage cluster methodology was de- signed so as to provide national and provincial representative data. This survey was conducted in all the four provinces (Sindh, Punjab, Balochistan and KP) plus Azad Jammu and Kashmir (AJK), Gilgit Baltistan and Federally Administered Tribal Areas (FATA) as defined by the 1998 population census.

2.3 Sample Size and its Allocation

2.3.1 Sample size estimates for household survey After considering a variety of characteristics including population distribution and field resources available, a sample size of 30,000 households was calculated as a sufficient number of households to provide representative results. An exercise to compute the sample size based on the prevalence rate of three key variables – wasting in children under 5 years of age, stunting in children under 5 and maternal iron deficiency – was undertaken. The sample is estimated to have a 95% confidence interval and a 5% margin of error. A 5% non- response rate was also considered. The design effect of 1.6 was used to finalize and fix the overall sample size. The entire sample of 30,000 households (SSUs) was fixed comprising of 1,500 (PSUs) out of which 618 were urban and 882 were rural. As the urban population was more heterogeneous, a larger proportion of the sample size was allocated to urban domain. As KP and Balochistan are smaller provinces, a higher proportion of the sample size was allocated to these two provinces in order to obtain reliable estimates. After fixing the sample size at provincial level, further distribution of sample PSUs into different strata in rural and urban 7 | National Nutrition Survey 2011 domains in each province was made proportionately. The distribution of PSUs and SSUs enumerated in the urban and rural domain of the provinces and regions is indicated below:

Table 2.1: Sample size and allocation plan Number of sample PSUs Number of sample SSUs Province/Region Total Urban Rural Total Urban Rural Punjab* 682 307 375 13,640 6,140 7,500

Sindh 323 157 166 6,460 3,140 3,320

KP 218 67 151 4,360 1,340 3,020

Balochistan 110 44 66 2,200 880 1,320

FATA 67 0 67 1,340 0 1,340

AJK 66 28 38 1,320 560 760

GB 34 15 19 680 300 380

Total 1,500 618 882 30,000 12,360 17,640

* Including Islamabad

A-Biochemical Assessment: For biochemical analysis prevalence of Anemia in women and chil- dren was taken as an indicator for sample size estimation. For 51% Prevalence of anemia in women and 29% in children (NNS 2001), with a precision of 2%, design effect of 1.6 and power of 90% the sample size achieved was 8534 for WRA and 7032 for children under five years of age. 15% attrition rate was added to the sample size achieved and the final sample size came to 9836 for WRA and 8100 for children under five years.

For biochemical assessment we selected households where having a pair of mother and under five children, the youngest child (under five) was selected for blood sampling from selected households. The below table describes the sample size and its distribution among the WRA and Children under five years of age in various regions.

Table 2.2 Region wise sample size and its distribution

Rural Urban Sample Sample

Population children WRA

Proportion Distribution Distribution proportion N=8004 N=9836

Urban Rural Urban Rural Urban Rural

AJK 2.1 12.88 87.12 168 22 146 207 27 180

Balochistan 4.8 23.9 76.1 384 92 292 472 113 359

FATA 2.3 2.7 97.3 194 15 179 226 6 220

GB 0.7 32.34 67.66 52 18 34 69 22 47

KP 13 16.9 83.1 1061 186 875 1279 216 1063

Punjab 54.7 97 103 4398 1387 3011 5380 1704 3676

Sindh 22.4 48.8 51.2 1843 885 958 2203 1075 1128

100 32.5 67.5 8100 2605 5495 9836 3197 6639

B. Sampling Frame and Design

A-Universe of the survey: The universe for this survey was comprised of all urban and rural areas of all four provinces of Pakistan, the Federally Administered Tribal Areas (FATA), Azad

8 | National Nutrition Survey 2011 Jammu Kashmir (AJK) and Gilgit Baltistan (GB) defined as such by the 1998 Population Census, and the subsequent changes made by the provincial governments periodically. The population of the military restricted areas was excluded from the scope of this survey.

B-Sampling frame: For National Nutrition Survey in Pakistan the sampling frame of Federal Bureau of Statistics (FBS) was used. The Federal Bureau of Statistics (FBS) has its own sampling frame for all urban and rural areas of Pakistan in the form of enumeration block. Each enumeration block consists of about 200 to 250 households with well-defined boundaries, which are recorded on forms and maps that also include physical features of the area and important landmarks.

B.1: Urban areas: In urban areas each enumeration block has been classified into low, middle or high income groups depending on what income group the majority of the households located in that particular enumeration block belonged to. This information was then used to formulate sub-stratification. This sampling frame covers all urban areas of Pakistan Due to rapid growth in these areas; the frame is regularly updated every 5 to 7 years. It was entirely updated in 2004. There are 26,753 enumeration blocks in all urban areas of the country.

B.2: Rural areas: The Enumeration blocks in In rural areas consists of mouzas, dehs and villages.

A mouza, deh or village can be defined as the smallest “revenue estate” and FBS has used these as rural Enumeration blocks. The rural sampling frame is comprised of 50,572 mouzas/dehs/villages and has been used to draw the sample for this survey.

C-Role of Federal Bureau of Statistics in Sample design and Frame: FBS was one of the main collaborators in the implementation of National Nutrition Survey; FBS provided the sample size estimation, sample design and the sampling frame providing the provincial representativeness. The Sampling frame for NNS was comprised of 1500 PSU (618 Urban and 882 Rural) randomly selected from their main sampling frame. FBS also provided support for the listing of households in each PSU.

D-Listing of Households (SSU) in each enumeration Block (PSU): Fresh listing of households was undertaken in all enumeration blocks (PSU) after a comprehensive training of the quantitative survey team. The sketch map of enumeration blocks drafted by the Federal Bureau of Statistics (FBS) in urban areas was used to perform listings. In rural areas, villages were taken as the PSUs, in line with the 1998 Population Census. Large sample villages that have a population of more than 2,000 (according to the 1998 Population Census) were split into hamlets/blocks of equal size. One of these blocks was selected randomly for data collection. Small villages were completely listed. The listing of households was used to select a specified number of households from urban and rural sample areas.

2.3.3 Sample selection procedure a) Selection of primary sampling units (PSUs)

Enumeration blocks in urban domain and mouzas/dehs/villages in rural domain were taken as PSUs. In the urban domain, sample PSUs from each ultimate stratum/sub-stratum were selected

9 | National Nutrition Survey 2011 using the PPS method of the sampling scheme. In the rural domain, the number of households in the enumeration block from the 2004 Economic Census and the population from the 1998 census for each village/mouza/deh were considered as the measure of size. b) Selection of secondary sampling units (SSUs)

Households within the sample PSUs were taken as SSUs. Twenty Households from each urban and rural sample PSU were selected with equal probability using a systematic sampling technique with a random start. Complete household lists freshly prepared during the listing activities was used to draw the required SSUs from the list of households.

2.3.4 Target population

The target population included women of reproductive age (15–49 years), children 0–59 months and elderly persons (>50 years).

2.3.5 Description of questionnaire (quantitative)

A structured questionnaire was used to obtain the data. The questionnaire was developed using standard components from previous and recent surveys undertaken nationally and internationally. All the data collection tools were thoroughly assessed by the technical committee established to oversee the NNS 2011. Three iterations of the survey instrument were reviewed and the final version was approved in December 2010.

In Section 1 of module “A”, all members of each household were listed by their gender, age, education, occupation and marital status. Besides such information, anthropometry (height, weight and clinical examination for anaemia, jaundice, cyanosis, edema and goitre) was conducted for anyone who was present at the time of the survey. Data corresponding to the name of each member was recorded. Section 2 of module “A” was exclusively designed for obtaining socioeconomic data along with health and hygiene characteristics. Knowledge, attitudes and practices about micronutrients (iron, iodine, and vitamins A, B, C and D) were recorded in the module “B” while module “C” focused on reproductive history, intra-birth interval, antenatal care, night blindness, worm infestation, iron supplementation and morbidities. Additionally, module “C” assessed dietary intake and food practices using a 24-hour dietary recall to determine patterns of eating habits and variety of foods consumed over a longer period of time by WRA.

The infant and young child feeding (IYCF) Module “D” was used to capture several indicators including data on birth, newborn weight, resuscitation, breastfeeding initiation, complementary feeding, micronutrients, and 24-hour dietary recall and food practices for the youngest child. A separate Module “E” was developed to determine the health status, immunization, physical examination and lab investigation of children under-5 years of age. The appetite, movement, mobility and morbidities of elderly persons were also investigated in Module “F”. The poverty assessment and food security Module “G” was also completed.

10 | National Nutrition Survey 2011 2.3.6 Description of qualitative research

The overall aim was to identify food consumption patterns, nutrition and food behaviour as well as to gain insight into the factors affecting decision-making. These factors include, the connection between diet, disease and health, beliefs about certain foods, dietary practices, food intake patterns, consumption of local versus imported foods, and other factors relating to food choices.

A-Qualitative research sample and target population

In qualitative research, purposive sampling is the dominant strategy and purposive sample size is often determined on the basis of theoretical saturation (FHI, 2005). A total of 40 focus group discussions and 16 in-depth interviews were conducted. Participants were identified and selected through the community recruiters at their living sites.

2.3.7 Biochemical analysis

Biochemical assessment for micronutrient deficiencies was performed on children under 5 years of age and women of reproductive age. Children between 6–12 years of age and WRA were also assessed for urinary iodine. Details of the biochemical test that were done for NNS are shown in table below.

Table 2.3: Description of biochemical analysis/tests

Biochemical Test Children 0 to 59 months Children 6 – 12 years WRA

Vitamin A Yes - Yes

Vitamin D Yes - Yes

Zinc Yes - Yes

Haemoglobin Yes - Yes

Ferritin Yes - Yes

Calcium - - Yes

Urinary Iodine Yes Yes Yes

AGP and CRP Yes Yes

AGP and CRP were done to adjust the concentrations of micronutrients.

2.3.8 FATA Specific Data

The sample size for the National Nutrition Survey was calculated to be representative at regional level. However, in FATA higher refusal rate (about 32%) was recorded. Therefore data from FATA lost its regional specificity considering this fact we have presented the data of FATA in the report at National level but not at regional level. We presented FATA specific data in the annexes along with other regions but have recommend caution in its use and interpretations. Furthermore, the refusal rate for collection of blood samples was even higher. Considering this fact the biochemical assessments of FATA have not been presented.

11 | National Nutrition Survey 2011 2.3.9 Project pre-implementation steps

Before launching the field activities the following steps were undertaken:

Table 2.4 Pre-implementation steps

Activities /Steps Description of steps

Formation of Technical Technical committees – with representatives from the relevant stakeholders to

Committee oversee technical aspects of the NNS 2011 – were notified.

Liaison with partners:

Liaison with the local • Federal Bureau of Statistics (FBS)

partners • Ministry of Health (MoH) and provincial health departments

• Pakistan Medical and Research Council (PMRC) – data collection in KP and FATA

A detailed manual of operations for survey procedures was developed. This

Development of survey encompasses qualitative and quantitative data collection strategies, manual anthropometry guidelines, sample collection and transportation guidelines, and

data management strategies.

Development Instruments The relevant consent forms and instruments were developed. The instruments

and consent forms have different modules relevant to study participants.

Ethical Review Committee Ethical review applications were submitted to National Bioethics and to AKU ethics application submission committees for approval of the methodology and consent forms.

Worked closely with the FBS to develop the research design and sampling frame. A Acquisition of sample frame

sample size of 30,000 households and 1,500 enumeration blocks was proposed

and design from FBS

and agreed to.

Survey hubs were established for the operational movement of field teams in the Establishment of survey

following locations:

hubs: Punjab=8 (average 85

Sindh: Karachi, Hyderabad, Mirpurkhas and Sukkur

enumeration blocks per one

Punjab: RY Khan, Multan, DG Khan, Bahawalpur, Faisalabad, Lahore & Rawalpindi

Hub), Sindh=5 (65), KP and

KP and FATA: Abbottabad, Peshawar, Swat, D I Khan and Kohat

FATA=5 (57), Balochistan=5

AJK: Muzaffarabad, Bagh and Mirpur

(22), AJK=3 (22) and Gilgit

Gilgit Baltistan: Gilgit and Skardu

Baltistan=2 (17)

Balochistan: Gawadar, Khuzdar, Bella, Quetta, Dalbandin and Jaffarabad

A-Identification and recruitment of field staff: Advertisements (in-house and in the national daily newspapers) were placed and candidates were shortlisted and interviewed in Karachi, Faisalabad, Rawalpindi, Peshawar and Quetta.

B-Survey teams Initially 15 survey teams were established and more teams inducted as the survey progressed to keep the momentum and to meet the time target. At one point, 22 teams were simultaneously operating in different parts of the country. Each team consisted of 1 field supervisor, 1 team leader, 4–5 data collectors, 3 registered nurses (with 1 phlebotomist), 2 logistic assistants and 2 community facilitators. Separate teams consisting of moderators and facilitators, observers, note-takers and community recruiters were also established.

C-Staff profile: The staff team included a national survey coordinator, a senior survey coordinator and survey coordinators. All the team supervisors were senior medical doctors and lead social scientists with over ten years of experience in nutrition related surveys nationally and internationally. The team included experienced female team leaders who were trained in social

12 | National Nutrition Survey 2011 sciences. They helped gain access to households to ensure the quality and validity of data. All data collectors were at least university graduates supported by logistics assistants and local community facilitators.

D-Separate teams for mapping and listing: Each team consisted of a FBS representative and a logistic assistant and were supported by local community facilitators as they visited each EB/village prior to data collection for demarcation of the EB/village as per FBS maps. During this exercise, all structures and households were listed and allotted a unique ID (NNS 1, 2, 3 for structures and HH 1, 2, 3 for households). Additionally, basic data including that of children under 5 years of age, the household head, women of reproductive age and elderly persons above 50 years of age were obtained. From each of the listed HHs in the EB, 20 HHs were randomly selected through a computerized process using Microsoft Excel.

E. Training: Training sessions and refreshers were conducted in Karachi, Faisalabad, Lahore, Peshawar, Abbottabad, Quetta and Gawadar. These sessions took place over a period of five days and were carried out by staff from the department of paediatrics and child health of Aga Khan University who had prior experience in similar surveys. Some of the details of the training agenda are shown in Table 2.5.

Table 2.5: Details of the training agenda

Staff Training Components

All Staff Introduction to NNS Research design survey methodology

Community rapport building, counselling techniques, research basics, interviewing

techniques, dress code, consent procedures, interpersonal skills, ensuring high

Team Leaders response, sampling methodology, question by question explanation, mock interviews,

operational procedures, field procedures, daily documentation, log sheet completion,

dealing with refusals, spot checking, random checking and desk editing

Community rapport building, research basics, interviewing techniques, dress code,

consent procedures, interpersonal skills, ensuring high response sampling

Data Collectors

methodology, question by question explanation, mock interviews, operational

procedures, field procedures, daily documentation, log sheet completion

Nurses Physical examination, anthropometry, field practice and urine sampling

Blood sampling, safe injection practices, labelling and storage, transportation of

Phlebotomists samples and field practice

F-Piloting/pre-testing: A pre-test was undertaken to pilot the questionnaire and to identify and solve unforeseen problems before actual data collection. The objectives of the pre-test were to improve the language of the questionnaire; establish the order of questions; check accuracy and adequacy of the questionnaire instructions such as “skip” and “go to”; clarify the instructions to the interviewers; eliminate unnecessary questions and add necessary ones; endeavour to lessen discomfort, harm, or embarrassment to the respondent; improve translation of technical terms; and estimate the time needed to conduct an interview.

13 | National Nutrition Survey 2011 Both the “participating” and “undeclared” pre-tests were undertaken. Participating pre-tests were done in the classroom among the interviewers themselves while undeclared pre-tests were done in the field without informing respondents that it was a pre-test.

About 100–150 respondents with reasonably similar characteristics from the survey population were interviewed in different parts of Karachi. The questionnaire was then revised and finalized on the basis of the pre-test results and direct observations by survey supervisors. The survey coordinators also closely monitored the pre-testing.

G-Coding scheme for assigning processing: A seven-digit coding scheme was developed in order to provide processing codes to primary sampling units [i.e. enumeration blocks/villages (PSUs)] and secondary sampling units [i.e. households (SSUs)].

2.3.10. Plan of operation, training and monitoring

In order to ensure timely completion of the survey, effective tools were developed for periodic field activity checks. A one step forward strategy was developed instead of the conventional approaches of monitoring. Additionally, internal monitoring survey stakeholders including Federal and Provincial Nutrition Wings, the Ministry of Health, the Government of Pakistan and UNICEF were proactively engaged in the training sessions as well as in monitoring and evaluating the progress of the survey activities. Besides this, independent and experienced monitors were also engaged.

A-Data Collection: On the day of survey the team identified each selected household using the listing being recently done by the listing team and proper informed consent was taken before the data collection. A total of twenty households from each enumeration areas were selected and data collection on the structured instrument was done. The team leader ensured the completion of data collection and quality of data in each cluster. For Biochemical assessment every third household was selected for Biochemical assessment. A Mother and her youngest child under five years were selected for blood draw. Blood samples were collected by trained phlebotomists ensuring safe injection practice. The blood samples were sent to Nutrition Research Lab of Aga Khan University through the national network of Clinical labs of Aga Khan University. Cold chain was ensured during the transportation of the samples

2.3.11 Data management, transfer and analysis

The filled-in questionnaires were first desk-edited at the field sites for completeness and checked for major errors by the team leaders. Once this was complete, the questionnaires were sent through a courier service to Aga Khan University’s Data Management Unit (DMU) in Karachi, where a full time desk was established to receive the survey questionnaires, maintain log registers and check for completeness. Where there was inconsistency or missing responses, the editors flagged the errors/omissions and consulted the team leaders for clarification. Before data entry, all questionnaires were coded for open-ended responses.

A-Software for data entry and analysis: Visual Fox Pro was used for designing the databases, data entry software and procedures for data quality assurance. Range and consistency checks as well as skip patterns were built in the data entry program to minimize entry of erroneous data.

14 | National Nutrition Survey 2011 Special arrangements were made to enforce referential integrity of the database so that all data tables were related to each other. Analysis of data was undertaken using SPSS version 18.

B-Data entry and quality checks: Two pass verification or double data entry was carried out for each filled-in questionnaire to minimize keypunch errors. An error check program was also incorporated into the data entry system to ensure quality of data. Data entry started after one week of data collection following clearance by the survey coordinator and requisite data quality assurance.

C-Data Analysis: Data analysis SPSS version 18 was used and data was analysed. Statistical Analysis was performed after the availability of clean and quality data. Each file was converted from Fox Pro into SPSS files so that they could be read into SPSS for further analysis. Descriptive statistics for the subjects was obtained and frequency tables were generated to ascertain the information on various variables. Data was analysed using univariate method. Analysis was done to ascertain and establish an association with the malnutrition of children.

WHO Anthro (version 3.2.2, January 2011) was used for anthropometric analysis. However, ENA- SMART software was used to check the day-to-day consistency of anthropometric data, which helped to address measurement errors at the initial stages of data collection. We used height for age Z scores, weight for height Z scores and weight for age Z score to assess the level of malnutrition. Ranges of -6 to +6, -5 to +5 and -6 to +5 Z scores were used to assess HAZ, WHZ and WAZ re- spectively while we flagged the values of <-6 and >+6, <-5 and >+5 and <-6 and >+5 in HAZ, WHZ and WAZ respectively. The flagged values were excluded from the data analysis to avoid meas- urement bias. We also done weighted analysis to limit the variability among enumeration blocks and region, pre assigned weights from FBS were used to conduct this analysis

2.3.11. Ethical approval and confidentiality The survey design, sampling strategy and analytical plan were reviewed and approved by the Aga Khan University’s Ethics Review Committee as well as by the National Bioethics Committee (NBC) of the Government of Pakistan. Confidentiality of all collected data was assigned high priority during each stage of data handling. All the names and personal information regarding any individual were kept confidential and data sets were kept anonymous for analysis. Only senior staff had access to the data. All data files have been protected by passwords and serum and blood samples were duly secured, as per standard procedures of the institution.

15 | National Nutrition Survey 2011

Results of the

National Nutrition Survey 2011

16 | National Nutrition Survey 2011 Chapter 3: Background and Household Characteristics

3.1 Completion of data collection

The required sample size for data collection was 30,000 households. The survey teams were able to approach the required number of households, however, 6.8% of the sampled households refused to participate in the survey. A total of 27,963 households consented to participate in the survey and interviews were conducted successfully. The refusal rate varied widely between 1 regions – the lowest being in AJK at 1.3% and the highest being FATA at 32.8%. This was possibly related to the prevalent insurgency, security issues and accessibility in the FATA region. A verbal consent was obtained from participating households prior to the interview for permission to collect information and anthropometric measurements through a pre-printed questionnaire. For blood draws, urine samples collection and clinical examination a written consent was obtained. The NNS 2011 coverage and population density maps for comparison of sample distribution and population conglomeration are featured below:

Fig 3.1 Population density Fig 3.2 National Nutrition Survey coverage

Sample size coverage by provinces and regions is listed in the next table.

Table 3.1: Details of sample size coverage (Number of PSUs and SSUs by Province / Region – Household Interviews Completed)

PSUs Household (HH) Interviews

Province / Region

Target Completed HH Visited Consent HH Refusal Rate (%)

Refused Completed

Punjab 682 682 13,640 452 13,188 3.3

Sindh 323 323 6,460 178 6,282 2.8

Khyber Pakhtunkhwa 218 218 4,360 734 3,626 16.2

Balochistan 110 110 2,200 204 1,996 9.3

FATA 67 67 1,340 440 900 32.8

AJK 66 66 1,320 17 1,303 1.3

Gilgit Baltistan 34 34 680 12 668 1.8

All Pakistan 1,500 1,500 30,000 2,037 27,963 6.8

1 Data from FATA are not representative due to high non-response rate.

17 | National Nutrition Survey 2011 3.1.1 Blood and urine specimen Overall 24,421 blood samples (12,282 women and 12,139 children) were collected across Pakistan. The survey teams also collected 2,900 urine samples from women (1,460) and children 6-12 years (1,457) for biochemical assessments.

3.2 Background and household characteristics

The total population counted in the surveyed households was 187,095. Males slightly outnumbered females (approximately 50.4% of the population were males and 49.6% females). The gender breakdown was 101.6 males to 100 females, which differed from the last census conducted in 1998 that found 108.5 males for every 100 females. This is, however, similar to the 2006 Pakistan Demographic and Health Survey statistics, which found 102 males for every 100 females. However, in AJK it was 95.7 males per 100 females. The average household size was 6.6, which is similar to what was found in the 1998 census.

3.3 Formal education – head of household and mothers

In the NNS 2011, 45.7% of the household heads were illiterate. The proportion of illiterate heads of household was lowest in AJK at 27.3%, whereas the proportion was highest in Balochistan at 58.2%. Female literacy in Pakistan has been a challenge for many decades.

The results of the NNS 2011 showed that the proportion of illiterate mothers was 59.3% and the proportion was almost double in rural areas than it urban areas (36.6% urban and 69.4% rural). Only 10.5% of mothers completed their 10 years of schooling and 9.0% managed to complete their studies beyond grade 10. Data from the survey further revealed that about 10.9% of mothers from rural areas received education 9th grade and above while in urban areas 38.8% achieved the same.

Fig 3.3: Formal education of mothers of children under five years of age.

100% 4.0% 5.9% 3.4% 1.0%

9.0% 9.7% 11.2% 12.9% 10.9% 8.3% 12.1% 90% 20.3% 14.5%

16.0% 6.3% 4.6%

80% 19.2% 16.3% 21.7% 20.2% 12.1% 5.9%

70%

10.3% 39.0%

12.5% 29.7% 6.5%

60% 16.0%

50%

13.4%

40% 82.0% 82.3% 17.7%

72.2% 69.4%

59.3%

30% 62.2% 62.4%

52.6%

20%

36.6%

30.4%

10%

0% Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Illiterate 1-5 Years 6-10 Years Above Matric.

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

18 | National Nutrition Survey 2011 3.4 Occupation – head of household

The NNS 2011 data showed that 53.6% of household heads were labourers, workers or farmers. Of these, 35.9% belonged to the urban population and 61.6% to the rural population. In comparison to the previous findings in the NNS 2001, 16.6% of household heads belonged to the labour/worker/farmer groups. Government and private service employees were the second largest group of those in employment (16.4%). The figures showed that the proportion of unemployed heads of households had doubled since 2001 (7.7% in 2001 compared to 15.5% in 2011).

3.5 Nature of dwelling by type of floor, roof and walls

The survey found that a large proportion of people living in urban and rural areas lacked basic civic necessities. The NNS 2011 data show that 64.2% of families were residing in houses that were constructed using bricks and concrete, which was an increase from the NNS 2001 findings (50%). The facilities available differed significantly between urban and rural areas, with less houses constructed with bricks and concrete in the rural areas (53.7%) than in the urban areas (86.9%). In 2011, across Pakistan 20.7% of household walls were made only with bricks and 55.9% houses had cement or tiled floors. 40.8% of houses had mud/sand floors – 10.2 % in urban areas and 54.9% in rural areas. Rural households were more likely than urban households to have sand or mud floors, while urban households were more likely than rural households to have floors made with cement.

Fig 3.4 (a-c) Nature of dwelling – materials used

70% 64.2% 60% 55.9%

60%

50% 45.0% 50.0% 49.0%

43.0% 50%

40.8% 40% 40%

30% 30% 20.7%

20% 15.2% 20%

12.0% 10% 2.0%

10%

3.4% 0%

Cement/lime bricks Brick (not Others 0%

cemented)

Cement/Tiles Mud/sand Others

Type of Floor 2001 Type of Floor 2011

Type of wall 2001 Type of wall 2011

80%

69.1%

70% 60%

50% 43.0%

40% 36.0%

30%

21.0% 19.9%

20%

11.0%

10% 0%

RRC/Tiles Wood Others

Type of Roof 2001 Type of Roof 2011

19 | National Nutrition Survey 2011 Fig 3.5 Nature of dwelling – urban/rural comparison of materials used for construction

Bricks, cement and lime Bricks (Not cement) Other materials

100% 86.9%

84.7% 90%

80%

64.2% 62.3% 70%

49.7% 53.7% 60%

48.7%

50% 35.4%

40%

25.6%

30% 20.7% 20.8%

15.2% 14.5% 20% 10.1%

10% 1.7% 1.4% 3.0% 0.8%

0%

NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

National Urban Rural

3.6 Type of fuel used for cooking

Over the last decade the use of firewood has decreased. At the time the NNS 2011 was being carried out, around 57.9% of the households in Pakistan were still using firewood as the prime source of cooking fuel while the use of firewood was reported to be 66.7% in the NNS 2001. At 35.8%, natural gas was found to be the second main source of cooking fuel. This was available in 83.3% of households in urban areas. Use of animal dung as fuel was observed to have reduced significantly in all parts of Pakistan. Only 6.1% were using animal dung during the NNS 2011 as compared to 14.6% in the NNS 2001. The use of kerosene oil also reduced substantially from 3.3% to 0.2%.

Fig 3.6: Source of fuel for cooking

Wood Gas Kerosene oil Animal dung

100%

87.8% 90% 83.3%

80% 77.4%

69.3% 66.7%

70%

57.9% 60%

50%

40% 35.8%

15.4% 29.2%

30% 20.3%

15.5%

20% 14.6% 13.9%

4.4% 10.2% 8.3%

10% 3.3% 6.1% 3.9% 1.2% 2.9% 0.3% 0.2% 0.0%

0% NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

20 | National Nutrition Survey 2011 Chapter 4: Food Insecurity in Pakistan

According to the FAO Publication, The State of Food Insecurity 2001, “Food security [is] a situation that exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life”2 No single indicator can capture the full range of food insecurity and hunger and the most reliable methods require periods of observation and household food inventories. Instead, most commonly household levels of food insecurity or hunger are determined by obtaining standardized information on a variety of specific conditions, experiences and behaviours that serve as indicators of the varying degrees of severity. While developing the module and data collection data were collected using standard internationally validated food security question; these included:

Anxiety that household food budget or food supply may be insufficient to meet basic needs.

The experience of running out of food, without money to obtain more. Perceptions by the respondent that the food eaten by household members was inadequate in quality or quantity.

Adjustments to normal food use, substituting fewer and cheaper foods than usual. Instances of reduced food intake by adults in the household, or consequences of reduced

intake such as the physical sensation of hunger or loss of weight. Instances of reduced food intake or consequences of reduced intake for children in the household.

The following steps were followed to analyse the food security data considering the guide to measuring household food security as a standard: Converting the survey responses collected using the core-module questionnaire into the data set needed for applying the measurement model;

Applying the model to the data to determine the food security status level of each household; Determining the severity level of the condition experienced in those households that show evidence of food-insecurity/hunger.

In the NNS 2011 the household food security was determined on the basis of four categories: food secure, food insecure without hunger, food insecure with hunger (moderate) and food secure with hunger (insecure). Given that the sample was not powered for provincial estimates, we report national averages.

4.1. Food secure This category include households that show no or minimal evidence of food insecurity.

4.2. Food insecure without hunger Food insecurity is evident in household members’ concerns about adequacy of the household food supply and in adjustments to household food management, including reduced quality of food and increased unusual coping patterns. Little or no reduction in members’ food intake is reported.

2 FAO. 2002. The State of Food Insecurity in the World 2001. Rome 21 | National Nutrition Survey 2011 4.3. Food insecure with hunger (moderate) Food intake for adults in the household has been reduced to an extent that implies that adults have repeatedly experienced the physical sensation of hunger. In most (but not all) food- insecure households with children, such reductions are not observed at this stage for children.

4.4. Food insecure with hunger (severe) At this level, all households with children have reduced the children’s food intake to an extent indicating that the children have experienced hunger. For some other households with children, this already has occurred at an earlier stage of severity. Adults in households with and without children have repeatedly experienced more extensive reductions in food intake.

The results revealed that 41.9% of households were food secure at the national level. 28.4% were food insecure without hunger, 19.8% were food insecure with moderate hunger and 9.8% were food insecure with severe hunger. Rural households were more food insecure (60.6%) as compared to urban households (52.4%).

Fig 4.1: Food insecurity situation

70%

Food Insecure Without Hunger Food Insecure With Hunger (Moderate) Food Insecure With Hunger (Severe)

60%

10.5%

9.8%

50%

8.2%

40% 20.7% 19.8%

17.7%

30%

20%

28.4% 29.3% 26.5%

10%

0%

Pakistan Urban Rural

The food security situation showed no signs of improvement since the last food insecurity 3 assessment conducted by the United Nations in Pakistan , which revealed that 51% of the population was food insecure. The situation has, in fact, deteriorated further. This will have serious implications on the nutrition, growth and health of the Pakistani population.

3 WFP (2009). Food insecurity in Pakistan. 22 | National Nutrition Survey 2011 Chapter 5: Maternal Health and Nutrition

During the National Nutrition Survey 2011, detailed data were collected on basic nutritional indicators including dietary intake, reproductive history, anthropometry, clinical and biochemical micronutrient deficiencies and on knowledge and practices linked to micronutrients.

5.1: Basic data – age and marital status of mothers

5.1.1 Age distribution

The survey revealed that about 63.7% of mothers were between 20–34 years of age, 28.2% were between 25–29 years and 23.9% were between 30–34 years. The data revealed no major differences between urban and rural age group distribution.

5.1.2 Marital status and current pregnancy status

Only 1.3% of mothers were either separated or widowed (2.0% urban; 1.0% rural), the rest of them were currently living with their husbands. Among all married women (24694), 10.0% women were pregnant. Provincial results showed variations; number of currently pregnant women was the highest in Sindh (11.9%) followed by Punjab 11.2%, AJK 9.1%, GB 7.3%, KP 6.0% and Balochistan 5.1%.

5.2: Reproductive history and antenatal care

5.2.1 Reproductive history

29.7% of women surveyed had been pregnant 1 to 2 times, 46.6% had been pregnant 3 to 5 times and 23.7% had been pregnant 6 or more times. The data did not find any major difference in the number of pregnancies between urban and rural areas but provincial variation was observed. Further data regarding outcome of the last pregnancy showed that 93.4% of pregnancies resulted in live births, whereas 5.7% ended as miscarriages and 0.8% in stillbirths.

5.2.2 Antenatal care

A-Antenatal care during last pregnancy: Seeking antenatal care during pregnancy is of great importance as it identifies risk factors. Unfortunately, there has been no improvement in the percentage of women seeking ANC since 2006-07. The PDHS 2006-07 data showed that 65.3% of pregnant women sought care during their last pregnancy while the NNS 2011 results found 62.0% sought ANC. The data revealed a clear difference of ANC seeking behaviour patterns when comparing women living in urban areas, where 81.4% sought ANC, and rural areas, where 53.7% sought ANC. Provincial data revealed that women who sought care during their last pregnancy in Punjab was 66.5%, Sindh 61.6%, KP 55.7%, Balochistan 47.1%, AJK 80.8% and GB 80.0%.

23 | National Nutrition Survey 2011 Fig 5.1: Antenatal care during last pregnancy

90%

81.4% 80.8% 80.0%

80%

66.5%

70%

62.0% 61.6%

55.7%

60% 53.7%

47.1%

50%

40%

27.1%

30%

20%

10%

0%

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

B-Choice of care provider: The selection of a qualified and skilled health care provider ensures quality care during pregnancy. In Pakistan, the percentage of women seeking care from skilled care providers has not significantly improved. The survey showed that in 2011 58.9% of mothers received ANC from a skilled provider. Of those who sought care from a skilled provider, 49.5% received care from a qualified doctor, 7.1% from a nurse and 2.3% from a Lady Health Visitors. The percentage of women who sought care from skilled care provider varied by province: Punjab 63.5%, Sindh 59.9%, KP 50.9%, Balochistan 42.5%, AJK 79.7% and GB 77.0%.

Fig 5.2: Seeking ANC from skilled care provider

90%

80%

70%

60%

50%

40% 78.4%

30% 58.9%

50.5% 20%

10%

0%

Pakistan Urban Rural

C-Micronutrient Supplementation during pregnancy: Data on women’s micronutrient supplementation during their last pregnancy were also collected. 24.4% of pregnant women consumed iron (33.2% in urban areas and 20.4% in rural areas); 25.3% consumed folic acid (35.7% in urban areas and 20.7% in rural areas); 3.9% consumed micronutrients; and 35.6% consumed calcium. The details of the nutrition supplements consumed during last pregnancy are illustrated below in figure 5.3.

24 | National Nutrition Survey 2011

Fig 5.3: Micro-nutrient supplementation during last pregnancy

60%

Pakistan Urban Rural 48.6%

50%

40% 35.7% 35.6%

33.2%

29.9%

30% 24.4% 25.3%

20.4% 20.7%

20%

10%

3.9% 3.5% 4.0%

0%

Iron Folic Acid Micronutrient Calcium

5.3: Knowledge of micronutrients and micronutrient rich foods

Micronutrient deficiencies are an important public health problem in Pakistan. In the NNS 2011, questions were asked to determine respondents’ level of knowledge about micronutrients, micronutrient rich foods and the impact of deficiencies (the education level of the respondents was taken into account).

5.3.1 Knowledge of micronutrients

To obtain information on micronutrient knowledge, survey respondents were asked simple questions such as, “Have you ever heard about (name of micronutrient)?” to determine if they knew what “foods contain (name of micronutrient)” and the “impact on health if deficient.”

Fig 5.4: Knowledge about micronutrients

Iron Iodine Vitamin A Zinc Vitamin D Vitamin B

70%

61.6%

60%

50% 42.0% 41.6% 42.8%

38.0%

40%

34.4% 34.2%

30% 24.0% 24.8%

20.8% 12.5% 19.3%

20% 17.0% 16.0%

12.8% 13.0%

10% 6.1% 3.1%

0%

Pakistan Urban Rural

25 | National Nutrition Survey 2011 The survey found that knowledge about micronutrients was generally low and varied greatly between urban and rural areas. Only 24.8% of mothers had knowledge about iron across Pakistan – 42.0% in urban and 17.0% in rural areas. Only 6.1% of mothers had knowledge about zinc – 12.8% in urban areas and 3.1% in rural areas. 24.0% mothers had knowledge about vitamin A – 41.6% in urban areas and 16.0% in rural areas. 20.8% of mothers had knowledge about vitamin D – 38.0% urban areas and 13.0% in rural areas. 19.3% of mothers had knowledge about vitamin B complex – 34.4% in urban areas and 12.5% in rural areas. Finally, 42.8% of mothers in Pakistan had knowledge about iodine – 61.6% in urban areas and 34.2% in rural areas.

5.3.2 Knowledge of vitamin rich foods

Pregnant women are considered to be a nutritionally vulnerable segment of the population due to their greater need for nutritious foods during pregnancy. Marginal nutrient intake increases the risk of nutritional deficiencies during pregnancy. For this reason, it is concerning that across Pakistan only 24.8% of mothers had heard about iron and half of them did not know which foods contain iron. However, among those who knew, 36.5% mentioned that green leafy vegetables contained iron while 20.1% mentioned meat. Mothers also had poor knowledge about health problems caused by zinc deficiency. Overall, 73.3% of mothers did not know about foods that contain zinc. Only 7.4% mentioned meat and meat products while 2.3% mentioned watermelon seeds as a source of zinc. The majority of mothers (58.4%) in Pakistan did not know which foods contain vitamin A and just a small proportion had knowledge about vitamin A rich foods. The majority of mothers (64.4%) also did not know about Vitamin D rich foods in Pakistan. Only 4.8% mentioned eggs, 9.3% mentioned meat and liver, and 3.7% mentioned sunlight as a source. Approximately 69.6% of mothers were not aware about the vitamin B complex rich foods in Pakistan. 13.4% of women mentioned that they thought fruits contained it and 11.9% mentioned green leafy vegetables were vitamin B complex rich foods.

The national iodine deficiency disorder control program was launched in 1994 to promote use of iodized salt. Nevertheless, across Pakistan mothers had relatively poor knowledge about health problems caused by iodine deficiency. The NNS 2011 survey findings revealed 66.9% of the respondents mentioned iodized salt as the major source of iodine, while just 2.4% were aware of other iodine rich foods like fish and seafood.

5.3.3 Knowledge about iodized salt and its usage

Overall, 64.2% of mothers said they were aware of iodized salt. Knowledge of iodized salt was higher (83.0%) in urban areas than in rural areas (55.6%). The respondents from AJK (82.0%), Gilgit Baltistan (79.5%) and Punjab (71.4%) had excellent awareness as compared to other provinces.

The reported use of iodized salt for cooking was 39.8% across Pakistan. A considerable provincial/regional variation was found between Gilgit Baltistan (94.8%), AJK (71.6%) and Punjab (36.1%). The reported use of iodized salt was higher (46.5%) in urban areas than in rural areas (35.2%).

26 | National Nutrition Survey 2011 Rapid iodized salt test kits were used in the survey to assess iodine content in salt used in households. The kit can test salt with drops of stabilized starch based solution, which causes a chemical reaction leading to colour change. The salt sample was taken on a teaspoon, and, after shaking the reagent (test solution) bottle well, a drop of the test solution was poured on the salt. The salt turned light blue to dark violet depending on the iodine content of the salt. To assess the iodine content, the colour of the salt is compared to that on a chart (0, 15, 25, 50 parts per million, ppm). The cut-off proportion of 15 PPM and above was considered as adequately iodized salt using the WHO/UNICEF reference indicators for the monitoring of iodized salt.

Fig 5.5: Level of Iodine content in salt

100%

80% 40.8%

51.8% 55.1%

63.6%

69.1% 72.4% 67.6%

60% 78.8%

87.9% 84.9%

40%

59.2% 48.2% 44.9%

20% 36.4% 30.9% 27.6% 32.4% 21.2%

15.1% 12.1%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

0 PPM 15 PPM and Above

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

According to the test, the proportion of households using iodized salt in Pakistan was 69.1%. This was higher in urban areas (72.4%) than in rural areas (67.6%). The provinces with the greatest proportion of households using iodized salt were AJK (87.9%) and Gilgit Baltistan (84.9%). The provinces with the lowest rates of usage were Balochistan (40.8%) and Sindh (51.8%).

5 4: Clinical examination

During the NNS 2011, clinical examination of mothers was also performed. Trained nurses conducted this examination. This was a direct assessment of micronutrient deficiencies on the basis of clinical signs and symptoms. The mothers were examined for anaemia, edema, jaundice, goitre and bitot’s spots. Each of these conditions represents a micronutrient deficiency.

The survey revealed that overall, 26.1% mothers had pallor – 20.5% in urban areas and 28.6% in rural areas. The prevalence of clinical anaemia (pallor) amongst the provinces were as follows: 28.0% in Punjab, 33.7% in Sindh, 11.0% in KP, 20.2% in Balochistan, 35.9% in AJK and 16.0% in Gilgit Baltistan. The prevalence of edema was 1.6% with no significant variance among provinces except for Gilgit Baltistan where it was 4.1%. Bitot’s spot was found in 0.4% of mothers, with no urban/rural variance. When assessed by province, Balochistan had the highest prevalence of Bitot’s spot (2.8%).

27 | National Nutrition Survey 2011 The prevalence of clinical anaemia found in the NNS 2001 was 48.7%. The NNS 2011 revealed a reduction to 26.1%. Similar trends were found for edema, jaundice, visible goitre and bitot’s spot.

Fig 5.6: Clinical examination of mothers (comparison between NNS 2001-02 and NNS 2011)

60% 50.0%

48.7%

50% 46.4%

40%

28.6%

26.1% 30% 20.5%

20% 11.8%

10.4%

5.8% 10% 1.6% 2.1% 1.4%

0.0% 2.9% 1.8% 3.4% 1.4% 1.0% 1.6%

0.0%

0% NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

Edema Jaundice Anemia/pallor Goiter Bitot’s spot

5.5: Anthropometry

Data were collected from non-pregnant women of reproductive age (15-49 years old), both married and unmarried, to calculate Body Mass Indices. The BMI were divided into four categories: underweight had a BMI of <18.5, normal had a BMI of 18.5–24.99, overweight had a BMI of 25–29.9 and obese had a BMI of >=30.

The data showed that 18.0% of women had low BMI and were underweight (14.4% from urban areas and 19.7% from rural areas) and about 53.1% had normal BMI (46.0% from urban areas and 56.6% from rural areas). 19.4% of women of reproductive age were overweight and 9.5% of WRAs were obese (15.7% from urban areas compared to 6.5% from rural areas).

Figure 5.7: Body Mass Index 56.6%

60%

53.1% 46.0% 50%

40%

30% 23.9%

18.0% 19.7% 19.4% 20% 15.7% 17.2%

14.4%

9.5%

10% 6.5%

0%

Underweight (<18.5) Normal (18.5-24.9) Overweight (25-29.9) Obese (>29.9)

Pakistan Urban Rural

28 | National Nutrition Survey 2011 5. 6: Micronutrient deficiency

5.6.1. Urinary iodine excretion of mother

In the NNS 2011, urine samples from mothers were collected to assess their urinary iodine excretion. Urinary Iodine excretion is the most appropriate indicator of iodine deficiency in large populations. Adequate iodine nutrition is considered to pertain when the median urinary iodine concentration is 100–199 μg/l.

The median urinary excretion of mothers indicates adequate levels of iodine status at national level, in both urban and rural area, and in most of the provinces (as indicated in the figure below). Balochistan, AJK and Gilgit Baltistan showed <100 μg/l urinary excretion, which indicates that the iodine intake in the population is insufficient.

Fig 5.8: Median urinary iodine excretion in mothers

180

Median UIE

160 149

140

113

120

105 103 102 96

100 90

80 63 64

60

40

20

0

5.6.2: Night blindness among mothers

12.7% of women surveyed had experienced night blindness during their previous pregnancy and 15.6% had experienced night blindness during their current pregnancy. Among provinces of Pakistan, women in Sindh had the highest reported rates of night blindness during their last pregnancy (21.3%) followed by AJK, Balochistan, Punjab, KP and Gilgit Baltistan. Among those women who reported night blindness during their current pregnancy, women in Sindh (22.7%) had the highest rates followed by AJK, Balochistan, Punjab, KP and Gilgit Baltistan.

When comparing this survey with the NNS 2001, night blindness rates during previous pregnancies had gone up (12.7% in the NNS 2011 compared to 7.8% in the NNS 2001). Similar trends were seen in urban and rural areas. The night blindness rates during current pregnancies had also increased (in the NNS 2011 they were 15.6%, while in the NNS 2001 they were 9.9%).

29 | National Nutrition Survey 2011 Fig 5.9: Comparison of night blindness in women

18%

16.1%

15.6%

16% 14.3%

13.2%

14% 12.7% 11.7%

12% 10.0% 9.9%

9.4%

10%

7.8% 7.5% 8.0%

8% 6% 4% 2% 0%

NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

Last pregnancy Current pregnancy

5.7: Biochemical analysis

Blood specimens were collected to assess the biochemical status of micronutrients. These specimens were assessed for hemoglobin, ferritin, vitamin A, zinc, calcium and vitamin D levels. The results are as follows:

5.7.1 Anaemia (haemoglobin levels)

Haemoglobin levels of both pregnant and non-pregnant women were checked during the NNS 2011. 50.4% of non-pregnant women were found to be suffering from anaemia (49.3% in urban areas and 50.9% in rural areas). Provincial data revealed that 62.0% in Sindh were suffering from anaemia, followed by Balochistan (48.9%), Punjab (48.6%), AJK (41.0%), KP (35.6%) and Gilgit Baltistan (23.3%). Similar trends were observed for pregnant women.

Fig 5.10: Maternal anaemia

70%

62.0% 59.7%

60% 50.5% 51.0% 50.3%

49.3%

50.4% 50.9% 48.9% 49.7% 49.3% 48.6% 50% 43.0%

41.0% 40% 33.6% 35.6%

30.2%

30% 23.3%

20%

10%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Non-Pregnant Women Pregnant Women

When the NNS 2011 data for anaemia in pregnant and non-pregnant mothers was compared with that of the NNS 2001, it was found that the prevalence of anaemia in non-pregnant women had worsened in 2011 (28.4% in NNS 2001 compared to 50.4% in the NNS 2011). Similar trends were observed for pregnant women.

30 | National Nutrition Survey 2011 Fig 5.11: Comparison of anaemia in mothers

Severe deficiency (<7 gm/dL) Moderate deficiency (7 - 11.9 gm/dL)

60%

48.9% 48.5% 49.1%

50%

40%

28.3% 29.6% 25.9%

30%

20%

10%

1.1% 1.5% 0.7% 0.8% 1.3% 1.8%

0%

NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

5.7.2 Ferritin concentration

26.8% of non-pregnant women had low ferritin levels (26.8% in urban areas and 26.6% in rural areas). When the data was disaggregated by province, Sindh had the highest proportion of women with low ferritin levels (31.5%), followed by Punjab, AJK, Balochistan, Gilgit Baltistan and KP. Among pregnant women, 37.0% had low ferritin levels at national level whereas it was highest in GB (45.7%) followed by Punjab, Balochistan, Sindh, AJK and KP.

Fig 5.12: Ferritin concentration

50% 45.7%

39.2% 38.1%

40% 37.0% 37.1%

34.5%

34.1% 31.6% 31.5%

30% 26.8% 26.8% 26.8% 27.3% 27.0% 25.2%

21.8%

20% 15.6% 14.9%

10%

Low Ferritin Low (<12 Ferritin ng/dL) Level 0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Non-pregnant Pregnant

5.7.3. Vitamin A deficiency

Retinol levels were tested in women (pregnant and non-pregnant) to determine vitamin A deficiency. Vitamin A deficiency among all married women was prevalent at 42.5% (35.7% in urban areas and 45.4% in rural areas). Provincial variance showed vitamin A deficiency at the following levels in all married women: highest in KP 66.4% followed by Balochistan 54.9%, Punjab 41.8%, GB 39.1%, and Sindh 37.1%. Among the non-pregnant women, vitamin A deficiency was prevalent at 42.1% (34.9% in urban areas and 45.1 in rural areas). Provincial variance showed that VAD remained highest in KP 65.7% followed by 54.5% in Balochistan, 41.5% in Punjab, 38.7% in GB, 35.4% in Sindh and 13.7% in AJK . Among the pregnant women, vitamin A deficiency was prevalent at 46.0% (41.5% in urban areas and 47.8 in rural areas).

31 | National Nutrition Survey 2011 Provincial variance showed that VAD remained highest in KP 76.2% followed by 60.7 in Balochistan, 46.7% in Sindh, 44.1% in GB, 43.7% in Punjab and 32.2% in AJK.

Fig 5.13: Vitamin A deficiency (pregnant women)

100%

Severe (<0.35 µmol/L) Moderate (0.35 - 0.70 µmol/L)

80%

60%

40.7%

34.6% 40%

27.3% 28.1% 24.1% 31.6% 24.1%

25.4%

20%

35.5% 28.9%

26.1%

18.7% 19.7% 19.6% 20.0% 16.1% 15.1%

0% 3.3%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Comparison of Vitamin A Deficiency among all women NNS 2011 vs. NNS 2001: Vitamin A deficiency levels found in the NNS 2011 had significantly increased over the NNS 2001 levels (5.9% in 2001 to 42.5% in 2011). Similar trends were seen in urban and rural areas.

Fig 5.14: Comparison of vitamin A deficiencies among non-pregnant women (urban/rural)

30% 25.1% 25.5% 24.0%

25% 19.6%

20% 17.0%

15% 10.9%

10% 6.7% 5.4%

3.4%

5% 0.8% 0.5%

0% NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

Severe (<0.35 µmol/L) Moderate (0.35 - 0.70 µmol/L)

5.7.4 Zinc deficiency

Serum zinc levels were determined in women. The serum analysis of non-pregnant women revealed that 41.3% of women were zinc deficient (38.2% in urban areas and 42.7% in rural areas). Women’s serum zinc levels by province were as follows in 2011: Punjab 40.2%, Sindh 38.5%, KP 48.3%, Balochistan 43.7%, AJK 64.8% and Gilgit Baltistan 63.7%. The data also showed that 47.6% of pregnant women were zinc deficient across the country. The provincial variance for pregnant women was as follows: Punjab 47.3%, Sindh 44.5%, KP 52.6%, Balochistan 43.6%, AJK 95.8% and Gilgit Baltistan 54.4%.

It was also noted that there has not been any change in the prevalence of zinc deficiency in the last ten years. The prevalence was 41.9% in the NNS 2001 and 41.3% in the NNS 2011.

32 | National Nutrition Survey 2011 Fig 5.15: Zinc deficiency (pregnant women) 120% Zinc Deficiency (<60 µg/dL)

100%

80%

60%

95.8%

40%

52.6% 54.8%

20% 47.6% 47.4% 47.7% 47.3% 44.5% 43.6%

0% Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Fig 5.16: Comparison of Zinc deficiency among non-pregnant women (urban/rural)

50% Zinc Deficiency (<60…

45%

40% 44.9%

35% 41.4% 41.3% 42.7%

36.2% 38.2%

30%

25%

20%

15%

10%

5%

0%

NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

5.7.5 Vitamin D deficiency

The NNS 2011 is the first survey in Pakistan assessing Vitamin D deficiency through bio-chemical data at a large a large scale. Widespread deficiency was found among non-pregnant women – 66.8% were vitamin D deficient (72.5% in urban areas and 64.3% in rural areas). On a provincial level, the prevalence of vitamin D deficiency among non-pregnant women in Punjab was 66.4%, in Sindh 71.2%, in KP 61.0%, in Balochistan 54.6%, in AJK 73.3% and in Gilgit Baltistan 80.9%.

The prevalence of vitamin D deficiency was also tested in pregnant women. 68.9% were determined vitamin D deficient (73.5% in urban areas and 67.2%in rural areas). Provincial data revealed vitamin D deficiency among pregnant women in Punjab was 71.1%, in Sindh 66.9%, in KP 63.8%, in Balochistan 43.6%, in AJK 73.4% and in Gilgit Baltistan 76.1%.

33 | National Nutrition Survey 2011 Fig 5.17: Vitamin-D deficiency (pregnant women)

120% Severe deficiency (<8.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL) Desirable (>20.0 - 30.0 ng/mL) 100%

21.1%

80% 15.3% 17.6% 11.2% 17.6% 18.4% 16.1% 23.3%

60% 31.7%

26.7% 39.7% 42.9%

43.6% 51.9%

45.1% 46.1% 40% 45.9%

23.1%

20% 44.4% 33.8%

28.2% 20.8% 17.9% 25.3% 22.1% 20.5% 21.5% 0% Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

5.7.5 Calcium Status:

The NNS 2011 calculated calcium levels for the first time on such a large population of women (non-pregnant and pregnant). The calculated calcium levels were not adjusted for serum albumin. The data revealed that 52.1% of non-pregnant women had hypocalcaemia. Provincial data also showed that 51.7% of non-pregnant women had hypocalcaemia in Punjab, 44.6% in Sindh, 74.0% in KP, 63.1% in Balochistan, 8.2% in AJK and 44.5% in GB.

Data on pregnant women showed that 58.9% had hypocalcaemia. The levels of calcium in pregnant women at the provincial level showed that 63.2% of pregnant women in Punjab, 50.3% in Sindh, 67.6% in KP, 67.4% in Balochistan, 13.3% in AJK and 71.3% in GB had hypocalcaemia.

Fig 5.18: Calcium deficiency (pregnant women)

100% 2.9% 2.2% 0.5% 7.6% 7.7% 7.6% 8.3% 8.1%

28.7% 29.4% 30.4%

80%

30.8% 28.5% 33.5% 34.6%

41.6%

60%

86.2%

40%

71.3%

67.6% 67.4% 58.9% 61.5% 63.2% 57.9% 50.3%

20%

13.3%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Hypo Calcaemia (<8.4 mg/dL) Normo Calcaemia (8.4 - 10.2 mg/dL) Hyper Calcaemia (>10.2 mg/dL)

34 | National Nutrition Survey 2011 Chapter 6: Child Health and Nutrition

6.1: Nutrition status of children

6.1.1 Children 0 – 59 months The percentage of households with children aged 0–59 months was measured in the NNS 2011. 25.6% of households in Pakistan did not have a child in the home that was under 5 while 40.1% had only one child less than 5 years of age. The average number of children living in each household is listed by province and region in the following figure.

Fig 6.1: Households with children under 5 years of age

No children 1 child 2 children 3 children 4 or more children

100%

18.1

23.4

80% 23.1

26.2 27.6 26.9 25.7 27.9 36.7 34.5

60%

37.1 46.4 40.1 38.0 36.0 41.5 40% 78.2

46.3 54.6 47.7

20% 32.5

25.6 22.4 27.5 28.0 27.5

14.7

3.8 0% 0.8 0.2

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB * Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

6.1.2 Anthropometry (children under 5 years of age)

Anthropometric measurement of all children <5 who were present at household at the time of visit was undertaken. Results showed that in Pakistan 43.7% of children were stunted. In rural areas stunting in children was higher (46.3 %) than in urban areas (36.9%). The wasting rate was 15.1% and the proportion of wasted children was lower in urban areas (12.7%) than in rural areas (16.1%). About 31.5% of the children were underweight, with higher rates in rural areas (33.3%). The indicators of malnutrition appeared to be worse in rural areas than in urban areas across country.

Fig 6.2: Prevalence of malnutrition in Pakistan (children under 5 years of age)

50% 43.7% Stunted Wasted Underweight 46.3%

40% 36.9%

33.3%

31.5%

26.6% 30%

20% 16.1% 15.1%

12.7%

10%

0%

Pakistan Urban Rural

| National Nutrition Survey 2011 35 6.1.3 Stunting (children under 5 years of age) Severe stunting in children showed an alarming situation (21.9%) across Pakistan. It was higher in rural areas (24.0 %) than in urban areas (16.4%).

Fig 6.3: National stunting rates for children under 5 years of age

Severe Stunting Moderate Stunting

50%

45%

40%

35% 22.3%

21.8%

30%

20.5%

25%

20%

15%

24.0%

10% 21.9%

16.4%

5%

0%

Pakistan Urban Rural

6.1.4 Wasting (children under 5 years of age)

Overall wasting rates were 5.8% for severe wasting and 9.3% for moderate wasting. The proportion of wasted children was higher in rural areas than in urban areas. In urban areas 4.7% of children under 5 years of age suffered from severe wasting while 8.0% were affected by moderate wasting. In rural areas severe wasting reached 6.3% and moderate wasting was 9.8%.

Fig 6.4: National wasting rates (children under 5 years of age)

18%

Severe wasting Moderate Wasting

16%

14%

12%

9.8% 9.3%

10%

8.0%

8%

6%

4% 5.8% 6.3%

2% 4.7%

0%

Pakistan Urban Rural

6.1.5 Underweight (children under 5 years of age)

Across Pakistan, 11.6% of children were severely underweight while 19.9% were moderately underweight. No significant difference was found between rural and urban areas.

36 | National Nutrition Survey 2011 Fig 6.5: Underweight (children under 5 years of age) national

35% Severely underweight Moderately underweight

30%

25%

20.5%

19.9%

20%

18.2%

15%

10%

11.6% 12.8%

5%

8.4%

0%

Pakistan Urban Rural

6.1.6: Education of mothers and its association with nutritional status of children

It is evident that the employment status and education level of a mother is directly associated with the nutritional status of her children. The findings of the NNS 2011 revealed that a mother’s education level is closely associated with children’s stunting, wasting and underweight status. Malnutrition in children was lower for those whose mothers had a higher education status.

Fig 6.6: Education of mothers and its association with nutritional status of children

30%

27%

25%

19% 20%

17% 15%

15%

12%

10% 8% 10% 8% 9% 6% 6% 5% 5% 7% 5%

4% 0%

Illiterate 1-5 years 6-8 years 9-10 years Above Matric.

% Stunted % Wasted % Underweight

6.1.7 Malnutrition trends in children under 5 years of age – comparison of SAARC countries

Of the South Asia Association of Regional Cooperation (SAARC) countries, Pakistan has the second highest stunting rate (43.7%). It follows Afghanistan, a country that faces extreme social, political and economic complexities. Nepal and India have similar stunting rates (43%). Bhutan has considerably better nutrition indicators than Pakistan.

37 | National Nutrition Survey 2011 Fig 6.7: SAARC countries national stunting trends*

54% 60%

50% 43% 43% 44%

37% 36%

40%

30% 25%

20% 14%

10%

0%

2006

-

NS 2004

DHS2007

-

-

MICS 2001 DHS 2000

NNS 2011

-

-

NS 2009 NS

-

-

DHS2006

- NFHS 2005 -

Afghanistan Bhutan Bangladesh India Maldives Nepal Sri Lanka Pakistan

* These data are based on different standards and references i.e. NCHS reference for earlier assessments & WHO standards for more recent.

Pakistan and Sri Lanka have the third highest wasting rates in the region and Afghanistan has better rates than both.

Fig 6.8 SAARC countries national wasting trends*

25%

20%

20%

17%

15% 15%

15% 13% 13%

9%

10%

5%

5%

-

-

-

-

- -

Sri La nk a DH S2 00 0

-

Pa kist an NN S2 01 1

Ne pal - DH S20 06

Mal div es MIC S20 01

glad esh DHS 2007 Ban

0% -

India NFHS2 005 2006

Bhutan NS2009

tan NS2004 Afghanis

* These data are based on different standards and references i.e. NCHS reference for earlier assessments and WHO standards for more recent.

Pakistan had lower rates of underweight children than half of the other SAARC countries.

Fig 6.9: SAARC Countries national underweight trends*

60%

48% 46% 45%

50% 39%

32%

40% 29% 30%

30%

20% 11%

10%

0%

-

NS NS

NFHS 2006

-

- -

DHS

MICS

NNS NNS

-

-

-

NS 2009

India 2005

Bangladesh DHS2007

-

DHS2006

-

2004 Bhutan Maldives 2001 Nepal Sri Lanka 2000 Pakistan 2011 Afghanistan

* These data are based on different standards and references i.e. NCHS reference for earlier assessments and WHO standards for more recent.

38 | National Nutrition Survey 2011 6.2: Biochemical assessment

Biochemical assessments are one of the established methods used to study the micronutrient status of a given population. Biochemical assessments are much more accurate and precise than most other forms of testing because many micronutrient deficiencies do not produce signs or symptoms until they are quite severe. For this reason, mild micronutrient deficiencies can only be diagnosed using biochemical indicators. Commonly used biochemical assessments include the haemoglobin estimation for anaemia, serum retinol levels for vitamin A deficiency, serum zinc levels for zinc deficiency, and urinary iodine levels for urinary iodine excretion.

6.2.1 Anaemia At the national level, 61.9% of children were found to be anaemic (Hb level <11.00gm/dL) (severe deficiency 5.0% and moderate deficiency 56.9%). Regional differences in the prevalence of anaemia were substantial, ranging from 41.0% in Gilgit Baltistan to 72.5% in Sindh. Prevalence of severe anaemia was comparatively higher in rural areas (5.5%) than in urban (3.6%).

Fig 6.10: Anaemia in children under 5 years of age 80% 72.5% 70% 61.9% 62.9% 61.4%

60.3% 56.8%

60% 47.3% 46.0% 50%

41.0%

40% 30%

20%

10%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Children under 5 years of age with anaemia

Fig 6.11: Trends of prevalence of anaemia in children under 5 years of age 70.0%

59.3%

56.9% 60.0% 55.9%

49.1% 53.2%

49.2% 47.3% 50.0%

44.4% 46.5%

40.0% 38.1% 37.0% 38.6%

30.0%

20.0%

10.0% 3.6% 5.0% 3.6% 4.3% 5.5%

2.4%

0.0% NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011

Pakistan Urban Rural

Severe deficiency (<7 gm/mL) Moderate deficiency (7 - 11.99 gm/mL) Normal (>= 12 gm/mL)

39 | National Nutrition Survey 2011 6.2.2 Iron deficiency (low ferritin concentration) High levels of iron deficiency (low ferritin concentration) were observed in 43.8% of children across Pakistan. Provincial differences in prevalence of low ferritin levels varied ranging from 26.4% in KP to 48.6% in Punjab. Comparatively high prevalence was noted in urban areas (46.1%) as compared to rural areas (42.9%).

Figure 6.12: Iron deficiency among children 60% Iron deficiency among children

48.6% 50%

46.1%

43.8% 43.5%

42.9%

40.6%

40% 36.2%

32.5%

30%

26.4%

20%

10%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

6.2.3 Vitamin A deficiency in children (under 5 years)

During the NNS 2011, vitamin A deficiency was assessed among children. The data showed that overall 54.0% of children in Pakistan were vitamin A deficient. 20.9% were severely deficient and 33.1% were moderately deficient.

Fig 6.13: Vitamin A deficiency

Severe (<0.35 µmol/L) Moderate (0.35 - 0.70 µmol/L)

80%

70%

60%

35.5%

34.6% 50% 44.6%

40% 33.4% 33.1% 34.5% 31.9%

32.3% 30%

36.7%

20%

33.9% 38.0%

27.2% 23.5% 20.9% 19.1% 18.8% 10%

14.6% 7.1% 0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

40 | National Nutrition Survey 2011 Fig 6.14: Trend of vitamin A deficiency in children under 5 years

40%

Severe (<0.35 µmol/L)

35% 33.1% 33.4% 32.3%

Moderate(0.35 - 0.70 µmol/L)

30%

23.5%

25%

20.9%

20%

14.6%

15% 12.6%

11.7% 10.3%

10%

5%

0.8% 0.6% 0.9%

0% Pakistan Urban Rural Pakistan Urban Rural

NNS 2001 NNS 2011

6.2.4 Zinc deficiency The survey revealed that overall prevalence of zinc deficiency among children in Pakistan was 39.2% (39.3% urban and 39.1% rural). Provincial data showed zinc deficiency at 38.4% in Punjab, 38.6% in Sindh, 45.4% in KP, 39.5% in Balochistan, 47.2% in AJK and 32.6% in Gilgit Baltistan.

Fig 6.15: Zinc deficiency in children (0–5 years)

50% Zinc Deficiency (<60 µg/dL) 45%

40%

35%

30%

25%

47.2% 45.4%

20% 38.4% 38.6% 39.2% 39.3% 39.1% 39.5% 32.6%

15%

10%

5%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

When zinc deficiency data from the NNS 2011 was compared with that of NNS 2001, there was a slight change in the proportion of zinc deficient children as measured by serum zinc concentrations.

41 | National Nutrition Survey 2011 Fig 6.16: Comparison of zinc deficiency in children under 5 years of age

Deficient (<60 µg/dL) Non-Deficient (>=60 µg/dL)

80%

67.8%

70%

62.9%

59.8% 60.8% 60.7% 60.9%

60%

50%

40.2% 39.2% 39.3% 39.1% 37.1%

40%

32.2%

30%

20%

10%

0%

Pakistan Urban Rural Pakistan Urban Rural

NNS 2001 NNS 2011

6.2.5 Vitamin D deficiency

The prevalence of vitamin D deficiency among children at national level was 40.0%. A high prevalence of vitamin D deficiency (45.9%) was noted in urban areas. Substantial variations were noted at the provincial level, ranging from 28.9% in KP to 43.4% in Balochistan.

Fig 6.17: Vitamin D Deficiency

Severe Deficiency (<8.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL) Desirable (>20.0 - 30.0 ng/mL)

80%

70%

60%

22.2% 25.4% 23.6% 36.0% 27.3% 27.2%

29.4% 35.3%

50% 31.4%

40%

30% 31.9%

32.6% 34.3%

30.8% 31.0% 30.4%

20% 30.5% 32.9%

23.0%

10%

14.0%

9.2% 9.1% 9.3% 10.7%

0% 7.2% 5.9% 4.1% 4.1% Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

6.2.6 Urinary iodine excretion in children 6-12 years

The main indicator of iodine status in the population is measured by median urinary iodine concentration in a population of children aged 6–12 years. Adequate iodine nutrition is considered to pertain when the median urinary iodine concentration is 100–199 μg/l. Generally, the median urinary excretion of children aged between 6-12 years found in the 2011 survey indicated adequate levels of iodine status at national level, both urban and rural, and in all of the provinces except AJK and GB.

42 | National Nutrition Survey 2011 Fig 6.18: Median urinary iodine excretion in children 6-12 years

180

Median UIE 160

160

146

134 136

140 126

119 117

120

100

80

64 62

60

40

20

0

Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

6.2.7 Clinical examination of children under 5 years of age

During the NNS 2011, trained nurses performed clinical examinations of children. The children were examined for anaemia, edema, jaundice, goitre and bitot’s spot. The survey revealed that overall 22.8% of the children had pallor. Provincial variations were found in the prevalence of clinical anaemia ranging from 31.7% in AJK to 3.4% in KP. The prevalence of edema was 0.4% with no significant variance between provinces except for Gilgit Baltistan, where not a single case was found. Bitot’s spot was present in 0.2% of the children.

6. 3: Child morbidity

Apart from neonatal disorders, diarrhoea and pneumonia are the other major causes of death in children under 5 years of age worldwide. In the NNS 2011, mothers of children under 5 were asked if the children had symptoms associated with acute respiratory illness (cough/flu, pneumonia, severe pneumonia and diarrhoea) on the day of the interview or two weeks preceding the survey.

Fig 6.19: Current ARI status

30%

Severe Pneumonia Pneumonia Cough/Flu

25%

20% 18.0%

15% 16.0%

15.0% 15.0%

12.0%

11.0%

10%

5% 6.0%

5.0% 5.0% 5.0% 5.0% 5.0% 2.0% 1.0% 1.0% 1.0% 1.0% 1.0%

0%

Pakistan Urban Rural Pakistan Urban Rural

By Information By Observation

| National Nutrition Survey 2011 43 6.3.1 Prevalence of acute respiratory infections ARI is a common cause of morbidity and death among children under 5 years of age. Pneumonia is characterized by difficult or rapid breathing. Severe pneumonia is defined as difficult or rapid breathing and chest in-drawing.

According to mothers of children, 4.9% of children had pneumonia on the day of the interview. However upon observation by the community nurse, 5.4% children had signs consistent with pneumonia. The survey findings revealed that either by observation or reported by mother, the ARI (cough/flu, pneumonia and severe pneumonia) were more prevalent in urban areas than in rural areas across Pakistan. Severe pneumonia symptoms were reported in 1.4% of children and the observed proportion was 1.0%.

6.3.2 Prevalence of diarrhoea

Diarrhoea is also a major cause of mortality among children. Childhood diarrhoea has been a serious health problem in Pakistan. Both its prevention, through improved water and sanitation, and management through oral rehydration salts (ORS) and zinc are on the top of the government’s priority list. The prevalence of diarrhoea was determined using the WHO definition. The mother was asked to report whether her child had diarrhoea on the day of the interview or two weeks preceding the survey.

Fig 6.20: Reported Prevalence of diarrhoea

Diarrhoea (last 2 weeks) Current diarrhoea

28.5% 28.5%

30%

26.2%

25% 23.2% 23.4% 22.3% 22.0%

19.2%

20%

15.6%

15% 12.9%

12.0% 11.6% 12.1% 11.7% 11.2%

10% 8.0%

6.4%

4.3%

5% 2.6% 2.4%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Approximately 12.0% of children were reported to be suffering from diarrhoea at the time of the visit and 22.3% had diarrhoea during the previous two weeks. The prevalence of diarrhoea (current and over the previous two weeks) was similar between urban and rural areas.

Current diarrhoea prevalence was highest in Gilgit Baltistan (19.2%) and Punjab (15.6%). Similarly, prevalence of diarrhoea during previous weeks was highest in Punjab (28.5%), Gilgit Baltistan (28.5%), AJK (26.2%) and Sindh (23.4%).

44 | National Nutrition Survey 2011 Chapter 7: Infant and Young Child Feeding Practices

Infant and young child feeding (IYCF) practices directly affect the nutritional status of children under two years of age and impact overall child survival. Improving infant and young child feeding practices in Pakistan for children 0–23 months of age is critical to guaranteeing them better nutrition, health and development. In the NNS 2011, the mothers of the children <24 months of age were queried on exclusive breastfeeding (no intake other than breast milk, including water). The reported frequencies at the national level were 20.9% at 4 months of age and 12.9% at 6 months of age respectively. The corresponding predominant breastfeeding data from 24 hours recall of mothers with children under 6 months of age reflected 69.8% and 63.5% at 4 months and 6 months across Pakistan respectively.

Fig 7.1: Exclusive breastfeeding of children 0-23 months (reported by mothers)

100%

90%

80%

70% 55.5%

60% 52.0%

47.0%

50% 42.0% 42.0%

40%

26.8% 25.7%

30% 20.9% 22.1% 20.4% 23.5%

14.5%

20% 12.9% 12.7% 13.0% 12.9% 9.6% 7.5% 7.7%

10% 4.3%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Upto 4 months Upto 6 months

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Fig 7.2: Predominant breastfeeding of children 0-6 months (24 Hours dietary recall)

100% 89.4%

87.1% 90%

79.2%

80% 72.4% 75.4% 72.2%

69.8% 64.7% 67.3% 63.3% 70% 63.5% 64.3% 66.4% 63.0%

62.1% 61.7%

57.5% 56.9%

60% 48.3%

50%

35.6%

40% 30%

20%

10% 0%

Upto 6 months upto 4 months

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

45 | National Nutrition Survey 2011 Predominant breastfeeding practices were assessed using the past 24 hour dietary recall of 0-6 months old children. The data showed that 69.8% of mothers were predominantly breastfeeding their children who were under 4 months and 63.5% under 6 months. Predominant Breastfeeding practices were higher in rural areas (66.4%) than in urban areas (57.5%).

Fig 7.3: Initiation of breastfeeding within one hour of birth

100%

90%

79.5%

80% 74.3%

70% 63.4% 61.8%

60%

50.5%

50% 40.5% 41.4% 38.4% 38.3%

40% 28.1%

30%

20%

10%

0% Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Within 1 hour

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

NNS 2011 data revealed that 40.5% of mothers had initiated breastfeeding within one hour of birth. The percentage was greater in rural areas (41.4%) than in urban areas (38.4%). The early initiation of breastfeeding was highest in KP 74.3% followed by Balochistan 63.4% and Gilgit Baltistan 61.8%. Trends observed in Punjab (28.1%), Sindh (50.5 %) and AJK (38.3 %) differed.

Fig 7.4: Continued breastfeeding practices

100% 91.9%

87.4%

90% 84.4%

77.3% 79.6%

80% 74.5% 72.3% 73.3% 72.3%

70%

60%

50% 43.4%

40%

30%

20%

10%

0%

Continued Breast Feeding practices

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

46 | National Nutrition Survey 2011 The data showed that in Pakistan 77.3% mothers continued breastfeeding to children up to 12- 15 months. Continued breastfeeding practices were higher in rural areas (79.6%) than in urban areas (72.3%). Provincial and regional differences in the rates of continued breastfeeding practices were substantial, ranging from 72.3 % in the Balochistan to 91.9% in the Gilgit Baltistan.

Fig 7.5: Introduction of Semi-Solid (6-8 months)

100%

90%

80%

68.4%

70%

62.6%

60% 55.0%

51.3% 51.3%

49.2% 48.6%

50% 44.7%

40% 35.3% 35.7%

30%

20%

10%

0%

PakistanUrban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Introduction of Semi-Solid (6-8 months)

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

More than half (51.3%) of the mothers interviewed across Pakistan reported they had started giving semisolid foods to their children at 6–8 months. The proportion was higher (68.4%) in urban areas than in rural areas (44.7%). KP (35.3%) and AJK (35.7%) had lower trends than other provinces.

Fig 7.6: Minimum dietary diversity (6-23 months)

30%

24.0%

25%

20%

15%

10%

6.9%

5.6% 5.1%

3.2% 5% 3.0% 1.9% 2.6% 2.7% 2.1% 0%

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

47 | National Nutrition Survey 2011 Minimum dietary diversity is estimated as the proportion of children 6–23.9 months of age who received foods of 4 or more food groups out of a total number of 7 food groups defined. The NNS 2011 findings revealed that only 3.0% of the children received a diet that meets the minimum standards of dietary diversity. Children in urban areas were more likely to receive a minimum dietary diversity than those in rural areas (5.6% compared to 1.9%). AJK (6.9%) ranked highest in minimum dietary diversity amongst the provinces.

Fig 7.7: Minimum meal frequency (6-23 months)

100%

90% Minimum Meal Frequency (6-23 months)

80%

69.0% 65.4%

70%

59.4% 60.7% 56.4%

60% 54.1% 53.3% 52.4%

50% 45.0%

40%

30.4%

30%

20%

10%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Minimal meal frequency is estimated as the minimum number of times solid, semi-solid or soft foods (including milk for children who are not breastfed) are given to breastfed and non- breastfed children who are 6-23.9 months of age. “Minimum is defined as 2 times for breastfed infants 6-8.9 months, 3 times for breastfed children 9-23.9 months and 4 times for non- 4 breastfed children 6-23.9 months. ” Overall, 56.4% of mothers provided food to their children at an acceptable meal frequency. The minimum meal frequency practice was higher in urban areas (65.4%) than in rural areas (52.4%). About half of all mothers practiced minimal meal frequency in all provinces.

Fig 7.8: Minimum acceptable diet (6-23 months)

40% 36.6%

35%

30%

25%

20%

15.1%

15% 11.2%

10% 7.3% 7.6% 5.6% 5.8% 5.6% 5.1% 3.9%

5%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

4 Indicators for assessing infant and young child feeding practices: conclusions of a consensus meeting held 6– 8 November 2007 in Washingtonm D.C., for acceptable diet of young child indicators 48 | National Nutrition Survey 2011 A minimum acceptable diet is a composite indicator of the adequacy of complementary feeding practices. It is the proportion of children 6–23 months of age who received a minimum acceptable diet (apart from breast milk). Across Pakistan only 7.3% of children received a minimum acceptable diet. Similar trends were observed in all provinces except AJK.

Fig 7.9: Age appropriate breastfeeding (0-23 months)

80% 75.3%

72.4%

65.9%

70% 63.6% 62.7% 64.0% 63.5%

60.5%

60% 54.3%

50%

40.0%

40%

30%

20%

10%

0% Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Age-appropriate breastfeeding was defined as the proportion of children 0–23 months of age who were appropriately breastfed. The proportion of age-appropriately breastfed children was 63.6% in Pakistan. Similar trends were recorded both in urban and rural areas. All provinces showed similar trends with the highest being in Gilgit Baltistan (75.3%).

49 | National Nutrition Survey 2011 Chapter 8: Food Intake and Practices

8.1: Methodologies adopted for Food Intake and Practices

Diet is usually described in terms of its nutrient content however the use of specific foods groups can also describe diet. Three of the most common methods used for assessing dietary intake; are food frequency questionnaires, food records and 24-hours dietary recalls. In the NNS 2011, Food Frequency Question- naire was used to assess the past dietary intake and 24-hour Dietary Recall for the current dietary intake.

8.1.1: Methodology for 24 Hour Recall

An open ended semi quantitative 24-hours dietary recall questionnaire was used to estimate the consumption of various food groups intake. The respondent (mother herself and for her child 0 – 23 months) was asked to report all of the food, beverages and/or supplements that she and her child has consumed during the past 24 hours.

The interview was structured with specific probes to help the mother remember all of the foods eaten. Probing was done in collecting details on different foods and also for in recovering foods that are forgot- ten (e.g., butter on toast) or in retrieving eating occasions not originally reported by the mother such as snacks or tea breaks.

Standard utensils (Cup, plates, spoons, glass, etc.) were given to the specially trained Data Collectors to measure the actual quantity eaten on 7 points in time during the past 24-hours (after wakeup, breakfast, in-between breakfast and lunch, lunch, in-between lunch and dinner, dinner and after dinner before go to bed).

8.1.2: Methodology for Food Frequency Questionnaire

The food frequency questionnaire was administered to ascertain the information on the fre- quency of food consumption and nutrients. The purpose of this questionnaire was to know the frequency of food items usually consumed. The respondent (mother herself and for her child 0 – 23 months) was asked to report listed food items in the table. Food frequency per day, per week and per month was estimated.

8.2: Pattern of Food Consumption among Children 0 – 23 month

The data of food consumption were analyzed on the basis of 24-hours dietary recall. Data showed that the pattern of food consumption in 0–23 months by different food groups in Pakistan was: breast milk 80.9%, followed by grains, roots and tubers 58.2% and dairy products (milk, yogurt, cheese, etc.) 48.2%. Breast milk feeding was higher (82.6%) in rural and lower (77.0%) in urban areas however the consump- tion of other food groups (grains, roots and tubers, legumes and nuts, dairy products (milk, yogurt, cheese), flesh foods (meat, fish, poultry and liver/organ meats), eggs, vitamin -A rich fruits and vegetables & other fruits and vegetables was higher in urban and lower in rural areas. In provincial and regional comparison breastfeeding was highest (92.2%) in Gilgit Baltistan and lowest (73.9%) in Balochistan. Grains, roots and tubers were consumed at the lowest in KP (41.7%) and highest (58.2) in AJK while dairy products were also lowest (41.7%) in KP and but highest (65.1) in Sindh. Details are given in the following table:

50 | National Nutrition Survey 2011 Table 8.1: Proportion of children below 2 years consumed food items of the listed food groups (based on 24 hour recall) Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit

Breast milk 80.9 77.0 82.6 77.6 86.9 90.1 73.9 46.8 79.6 92.2 Grains, roots and tubers 58.2 63.6 55.7 57.6 65.1 41.7 59.6 86.8 59.5 52.4

Legumes and nuts 5.3 7.1 4.5 4.2 7.5 5.4 6.2 6.2 6.5 5.2

Dairy Products(milk, yogurt, 48.2 51.9 46.5 57.7 38.2 22.2 32.6 62.7 58.2 42.1

cheese)

Flesh foods (meat, fish, poul- 2.7 3.4 2.4 2.3 2.3 1.7 5.1 30.1 5.6 3.1 try and liver/organ meats)

Eggs 5.8 10.0 3.9 4.8 5.1 11.8 3.4 13.8 9.6 15.1

Vitamin -A rich fruits and 1.7 1.9 1.5 1.9 0.9 1.0 1.3 11.3 2.4 7.6

Vegetables Other fruits and Vegetables 9.4 13.3 7.6 8.5 8.3 11.2 11.4 32.3 20.0 8.4

N 9083 3665 5418 4457 2179 842 697 65 548 295

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

8.3: Frequency of Daily Intake of Food Groups (Children 0 – 23 months)

The data showed that average daily intake of breast milk by children 0 – 23 months in Pakistan was 7.37 times on an average (Urban 7.01 - Rural 7.53) while it was the highest (10) in Sindh and the lowest (5.94) in Gilgit-Baltistan. All over Pakistan, the average daily intake of dairy products (milk, yogurt, and cheese) was 1.49 times per day and grains, roots and tubers 1.27 while the lowest intake (0.03) was of both food groups of legumes and nuts and vitamin -A rich fruits and vegetables.

Table 8.2: Frequency of Daily Intake of Food Groups (Children 0 – 23 months)

Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit

Breast Milk 7.37 7.01 7.53 6.26 10.00 8.25 6.59 3.45 6.19 5.94

Grains, roots and tubers 1.27 1.38 1.21 1.24 1.49 0.78 1.33 1.45 1.43 1.14

Legumes and nuts 0.03 0.03 0.03 0.02 0.05 0.04 0.04 0.04 0.05 0.02

Dairy Products (milk, yo-

1.49 1.70 1.39 1.90 1.03 0.58 0.90 0.76 1.86 0.86 gurt, cheese)

Flesh foods (meat, fish, poultry and liver/organ 0.06 0.11 0.04 0.05 0.09 0.02 0.18 0.06 0.06 0.06 meats)

Eggs 0.11 0.19 0.08 0.10 0.10 0.16 0.13 0.27 0.12 0.20

Vitamin A rich fruits and

0.03 0.03 0.03 0.02 0.04 0.02 0.03 0.16 0.04 0.13 vegetables

Other fruits and vegetables 0.28 0.40 0.23 0.28 0.29 0.22 0.21 0.50 0.45 0.16

N 9019 3647 5372 4441 2168 841 680 55 548 286 * Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

8.4: Frequency of Daily Intake of Food Groups among Children by their Age Group

In Pakistan, average daily intake of different foods showed the logical trends in different age groups among children of 0 – 23 months i.e. the higher the age group lowers the feeding of breast milk. The av- erage intake of breast milk was 10.4 times on an average in children <6 months, 8.31 times in children 6 – 11 months and 5.11 times in children 12 – 23 months while on the other hand average of semi-solid foods was lower in children <6 month and gradually increase in higher age i.e. 6-11 and 12-23 moths.

51 | National Nutrition Survey 2011

Table 8.3: Frequency of Daily Intake of Food Groups among Children by their Age Group Average Daily Intake by Age Group (Children) < 6 months 6-11 months 12-23 months

Breast Milk 10.39 8.31 5.10 Grains, roots and tubers 0.11 1.02 2.06 Legumes and nuts 0.01 0.05 0.03 Dairy Products (milk, yogurt, cheese) 0.95 1.41 1.84 Flesh foods (meat, fish, poultry and liver/organ meats) 0.00 0.03 0.11 Eggs 0.01 0.08 0.20 Vitamin A rich fruits and vegetables 0.00 0.01 0.06 Other fruits and vegetables 0.02 0.18 0.49 N 2150 2804 4065

8.5: Pattern of Food Consumption among Mothers of Children below 2 Years of Age

Across the country irrespective of provinces and regions all mothers eat wheat and rice (>99%) however foods also eaten along with wheat and rice were tuber and roots (29.2%), legumes and nuts 29.8%), dairy products (milk, yogurt, cheese) 41.6%, flesh foods (meat, fish, poultry and liver/organ meats) 30.6%, eggs (10.4%), vitamin -A rich fruits and vegetables (13.5%) and other fruits and vegetables (51.4%).

Table 8.4: Proportion of mothers of children below 2 years who consumed food items of the listed food groups (based on 24 hour recall)

Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit

Grains

99.5 99.6 99.4 99.6 99.9 99.5 99.9 94.4 99.8 99.6

(Wheat/Rice)

Tuber & Roots 29.2 25.7 30.7 26.8 41.5 21.5 31.1 12.1 27 11.9

Legumes and nuts 29.8 34.9 27.7 32.1 27 27.5 32.4 25.8 37.5 23.2

Dairy Prod- ucts(milk, yogurt, 41.6 39.2 42.7 50.3 40.2 24.2 28.5 48.8 32.8 37.4

cheese)

Flesh foods (meat, fish, poultry and 30.6 39.4 26.8 28.7 28 33.2 39.6 47.8 31.4 16.5

liver/organ meats)

Eggs 10.4 16.3 7.8 9.5 7.2 17.4 8 13.1 10.6 10.4

Vitamin -A rich fruits and Vegeta- 13.5 14.5 13.1 12.9 10.2 16.9 13.8 21.6 15.9 52.8 bles Other fruits and

51.4 52.8 50.7 59.3 37.3 51.3 49.9 46.7 60.8 52.4

Vegetables

N 19808 7816 11992 8005 5028 3042 1608 891 823 411 * Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

8.5 Frequency of Daily Intake of Food Groups among Mothers of Children below 2 Years of Age

The average daily intake of grains, tuber and roots by mothers of children all over Pakistan was 3.15 times followed by dairy products (milk, yogurt, cheese, etc.) 1.05 times. On an average, other fruits and vegeta- bles apart from vitamin A rich were eaten by 0.85 time in a day.

52 | National Nutrition Survey 2011

Table 8.5: Average Frequency of daily intake of food groups (mothers of children) Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit

Grains, roots and

3.15 3.08 3.18 3.15 3.04 3.35 2.91 3.07 3.46 3.72

tubers

Legumes and nuts 0.03 0.05 0.02 0.03 0.01 0.05 0.02 0.06 0.03 0.03

Dairy Prod-

ucts(milk, yogurt, 1.05 0.98 1.08 1.04 0.79 1.47 0.84 1.81 0.43 0.51

cheese) Flesh foods (meat,

fish, poultry and 0.31 0.4 0.27 0.28 0.33 0.29 0.5 0.40 0.31 0.36

liver/organ meats)

Eggs 0.32 0.4 0.29 0.29 0.2 0.58 0.26 0.58 0.22 0.26

Vitamin A rich fruits and vegeta- 0.29 0.24 0.31 0.2 0.27 0.5 0.31 0.52 0.18 0.9

bles

Other fruits and

0.85 0.97 0.8 0.92 0.71 0.87 0.75 0.98 1.02 1.09

vegetables N 19575 7805 11770 7995 5014 2940 1623 771 821 411

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

53 | National Nutrition Survey 2011 Chapter 9: Elderly Persons Health and Nutritional Status

Studies suggest that people's perceptions of their own health generally give a good indication of their mental and physical condition and are predictors of mortality for those who are 50 years of age and above. There are a number of factors that are known to have an impact on the general health of the population. These factors can contribute to an increased risk of diseases such as cardiovascular disease and cancer. Some of the contributing factors include cigarette smoking; excessive alcohol, excessive fat consumption; high blood pressure, high cholesterol levels, limited exercise and being overweight. In the NNS 2011, elderly persons were interviewed to determine their health and nutritional status. In all, 7,612 elderly persons were interviewed at their residence.

Fig 9.1: Age distribution of elderly persons

100%

3.9% 4.3% 7.3% 5.9% 7.9% 8.4% 5.6% 5.8% 10.9% 10.1%

90% 9.5% 9.3%

13.4% 12.9% 10.3%

15.2% 16.0% 17.4% 12.7%

80% 17.4%

28.8% 70%

32.7% 34.4% 38.2%

35.2% 35.5% 36.4% 60%

36.2% 37.2%

50%

86.4%

40%

30% 57.9%

51.2% 46.3%

20% 42.4% 40.6% 43.4% 40.8% 38.0%

34.5%

10%

0%

Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

50-59 years 60-69 years 70-79 years 80+ years

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

There were 30.4% male and 69.7% female respondents in this sample because mostly women were at their homes during the day. Approximately 42.4% of the elderly population belonged to the age group between 50–59 years (46.3% urban and 40.6% rural).

9.1 Body Mass Index (Elderly Persons):

In all, 69.7% women and 30.4% men were assessed for BMI. The main reason behind this variation was that the data collection conducted mostly from 10 am to 04 pm and menfolk are usually not available at home during this time slot. The data revealed that more than half (53.9%) of the Pakistan’s elderly population does not have normal weight; they were either underweight or overweight. Among them 15.8% were thin, 24.2% overweight and 13.9% obese. In provinces highest thinness was in Balochistan (19.6%) and lowest in KP (7.5%) while about half (49.7%) of the elderly population were overweight and obese in KP. In Gilgit Baltistan 61.6% elderly population maintained normal weight.

54 | National Nutrition Survey 2011 Table 9.2: Detail data according to the WHO classifications

100% 4.3%

7.8%

13.9% 9.9% 12.9% 14.3% 12.9%

90% 19.3%

23.0% 18.3%

33.3% 19.1%

80% 21.1% 19.4%

24.2% 23.8% 22.1%

70%

30.4%

60% 31.4%

50%

51.9% 61.6%

49.8% 48.2% 47.4% 40% 46.3% 46.2% 46.1%

30% 42.8%

37.5%

20%

10% 15.8% 19.3% 17.1% 17.4% 19.6% 19.3% 21.0% 15.8%

8.1% 7.5% 0.0% 0% Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit

Thinness (<=18.49) Normal (18.5-24.99) Over-weight(25-29.99) obese (>=30)

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

About half (49.8%) of the rural elderly population was on normal weight whereas it was only 37.5% in urban areas while thinness was higher (19.3%) in rural and lower (8.1%) in urban. The tendency of overweight was 31.0% in rural areas in comparison of 54.4% in urban areas.

55 | National Nutrition Survey 2011 Chapter 10: National Nutrition Survey – Qualitative Findings

INTRODUCTION

We conducted 40 focus group discussions and 16 in depth interviews at different places to cover almost all provinces/regions of Pakistan. Focus group discussions (FGDs) were conducted with mothers having child less than five years of age, male & female elders of the family and lady health workers. In-depth interviews were conducted with male & female health care professionals.

Around 400 participants attended these FGDs & IDIs. The characteristics of participants were presented below;

10.2: Age 10.1: Gender

25% 100% 20.0% 84.0% 19.0%

18.0% 80% 20%

16.0%

60% 15% 12.0%

8.0% 10%

40%

16.0% 5% 3.0% 3.0%

20%

0%

0% < 21 21 - 24 25 - 29 30 - 34 35 - 39 40 - 45 46 - 49 50+

Male Female Years Years Years Years Years Years Years Years

10.3: Education

28.0%

30%

25%

18.0%

20%

16.0%

15.0%

14.0%

15%

9.0%

10%

5%

0%

No Education Primary Middle Matric Inter Graduation and above

Data were transcribed and translated directly from native language to English. The validity of the transcripts and translations was checked with back translation.

A-PERCEPTION OF HEALTH AND ILLNESS

The majority of rural mothers had opinion that f women lack the freedom to access medical care for themselves and their children unless the household decision maker allows them to do so.

Majority of the participants across the country reported fever, cough, diarrhoea and intestinal worms are ailments of children.

Majority of participants from Baluchistan, rural Sindh and southern Punjab said that we have to collect water from wells located outside the house and store it for our use and there is no proper system of collection and disposal of sewerage in the community/locality. The inability to access

56 | National Nutrition Survey 2011 clean water and unsatisfactory sanitary conditions are important contributors to many childhood illnesses. Waterborne diseases and worm infestation are very common amongst those living in rural areas or where there is improper sanitation coverage.

Regarding perceptions about women’s health, the most common criterion appeared to be the amount of physical work that they were able to do.

Majority of participants of group discussions stated that if a woman is not looking pale and per- forming her routine household work she is considered to be healthy. Rural mother stated “ In laws expect to do the same amount of work even during pregnancy”. One participant remarked that “if a woman is fulfilling all her routine work and her cheeks are rosy, we assume she is well and healthy”.

The majority of participant acknowledged that joint pains and swelling, leucorrhoea, backache, lower body pain, high blood pressure and irregular menstruation were major illnesses of women. However many mothers from Upper Sindh and Southern Punjab perceived that they were suffer- ing from health problem due to low or insufficient diet. The majority of participants also stated that they do not have enough food to eat, poor and cannot afford eating as desired, even they cannot afford medical care except some home remedies. Access to a health facility was identi- fied as a specific barrier to availing health services during discussions. Location of health facili- ties, besides that dependency on male decision makers, transportation cost, long waiting times at the facility etc. were also mentioned by participants as major barriers to access health ser- vices. Majority of participants acknowledged that if the illness is not serious then some self- medication is done from the leftover drugs, however a few participants said that we consult the nearby health care provider and the also lady health workers for taking advice. Apart from lady health workers, traditional birth attendants (TBA’s) were also consulted for minor ailments. For instance, in Balochistan, upper Sindh, Azad Jammu Kashmir and Gilgit a mixture comprising of cardamom, ginger and lemon is used for treatment of leucorrhea. Some mothers of Gilgit Bal- tistan and Khyber Pakhtunkhwa said that women were only permitted to consult ‘lady’ doctors due to the cultural barriers.

Majority of health professionals interviewed had opinion that most patients didn’t follow doc- tors’ advice and instructions. Patients were generally didn’t complete the course of treatment regimens and follow up with medical professionals.

B-DIET DURING PREGNANCY AND LACTATION

The majority of participants of group discussion across country stated that pregnancy was not considered as a special event and no extra dietary consideration was given to it. Although the medical professionals unanimously said that woman should encourage women to eat healthy and extra food during pregnancy and lactation.. Across the regions the majority of participants said that diet was dependent on economic circumstances of family and was not a matter of choice. The majority of participant mothers stated that their usual diet consisted of vegetables and milk. Rice, pulses/lentils was also mentioned as staple food by most of participants. Majori- ty of participants across the country said that they cannot afford to buy meat or chicken. Few

57 | National Nutrition Survey 2011 mothers also stated that they took vitamin or mineral tablets during their pregnancies and lacta- tion period. The majority of health professionals interviewed were stated that malnutrition, anemia and hypertension can cause complications during pregnancy and delivery.

C - INFANT AND YOUNG CHILD FEEDING PRACTICES

1- Breast Feeding

Almost all participants across country were aware of the necessity breast milk as first feed of the child after birth. During the discussion most of mothers stated that, breast milk is healthy and prevent from illnesses. The majority of mothers were not aware the timing of initiation of breast milk and had different opinions, ranged from immediately within half an hour of birth to up to three days after birth. “Breastfeeding should be initiated within 24 hours of child birth” (Urban Mother – FGD). “It should be initiated within first 1 and half hour after child birth” (Rural Mother – FGD). Mother from urban Punjab stated “We think that immediate breastfeeding af- ter delivery is essential otherwise child will not suck properly which can result in child ill health”.

Most of the mothers interviewed believed breastfeeding should be continued up to two years of age of child. Continued breastfeeding was perceived by mothers to protect them from breast cancer and their child from infections. This was also confirmed in the KAP survey where more than 75% of the respondents from all the sectors opined that breastfeeding should be continued for up to 2 years.

During the discussions and interviews, participants were knowledgeable and had many opinions regarding the benefits of the breastfeeding. Mothers from rural areas also perceived some eco- nomic benefits of breastfeeding. The benefits of breastfeeding mentioned for the child during discussion were that it supplied all necessary nutrients, provide antibodies to illnesses, increases child’s mental development digests easily and protects against diarrhea (9%). Other benefits mentioned by the participants in the FGDs were as follows: baby will be healthy and it is good for child’s growth, vital for mental and physical growth, easy to feed and natural and breast milk is not contaminated so it protects against disease and reduces the chance of infection.

However, there were a few mothers who believed that first milk i.e. colostrum should be dis- carded to get rid of the sour taste. They thought that colostrum caused abdominal pain. Another negative practice

Although there are no medical/ scientific advantages attributed to pre-lacteal food yet ‘ghutti’ is very much a tradition first feed of child across Pakistan. This fact was confirmed by most of par- ticipants of group discussions. Honey was identified by most of participant that was commonly used across the country but variation existed as “Gurr” (Jaggery) in Northern Punjab, clarified butter in Northern Punjab/KP /Gilgit-Baltistan, Fennel-flavoured sherbet (Mixture) in Khyber Pakhtunkhwa were also used as first feed after birth of child.. Some mothers from Gilgit Bal- tistan stated that “Donkey’s milk, which is perceived to prevent epilepsy, was also given to child after birth.

Majority of lady health workers acknowledged during discussions that breast feeding is the common norm in rural communities but women still need to know the proper feeding tech-

58 | National Nutrition Survey 2011 niques. Majority of mothers were aware that they should be exclusively breastfeeding up-to 6 months. The vast majority of mothers stated said that they practiced exclusive breast feeding during first six months of their child but many of them admitted that they also gave water to the child during this time period, especially after the age of four months. The duration of the exclu- sive breastfeeding varied from 4 months to 7 months. “Exclusive breastfeeding for five months is sufficient for the child” (Mother – FGD).

The multiple factors were identified as barrier for exclusive breast feeding as lack of milk produc- tion, anxiety, exhaustion, psychosocial issues, delayed initiation of breast feeding. Others factors included promotion of infant commercial formulas leading to misconception in mothers that it is better feed for their babies.

There were some beliefs related to breastfeeding stated by some mothers from rural Sindh that mothers practice to protect their child from disease or the evil eye. To avoid the evil eye, a child should be breastfed separately from everyone. Being watched by others can affect both mother and child. Specifically, it was thought that a child can get indigestion, stomach ache and/or phlegm, if they were observed breastfeeding. It was also believed that the evil eye could dry breast milk. “Children are not given breast milk outside home after sun set because of devil eyes” (Rural Sindh Mother).

Regarding duration of breast feeding, the participants opined from one to two and half years. Most of mothers from Lower Sindh continued to feed till 1.5 to 2 years and similar responses from other provinces. Few mothers from Khyber Pakhtunkhwa stated that duration of lactation as 2 years for male and 2.5 years for female child.

Majority of mother also said that top milk was also introduced during this time. The range of top milk included formula milk, packed milk as well as fresh cow’s milk largely depending on the par- ticipant’s socio economic status. One of the participants stated that “they breastfed their in- fants due to the poverty and unavailability of formula milk in surrounding of rural areas there- fore women or young mothers have no choice other than to breast fed”. The most common reason revealed for stopping breastfeeding was pregnancy, child not sucking and followed by insufficient milk.

2- Complementary Feeding (CF)

Majority of Pakistani children between 6-9 months of age had commenced complementary foods. The age for introduction of complementary foods was varies across the Pakistan but ma- jority had initiated complementary feeding at about 6 months of age.

The most commonly mentioned complementary food that was first introduced to the child was semolina, rice, bread, sago, rice and milk dessert (kheer), buttermilk, egg, banana, tea, porridge, chapatti, potato curry, lentils, meat and broth, fish and vegetables. Almost all the mothers stated that the consistency of the first foods was thin and liquidy. In the FGDs and interviews, mothers

59 | National Nutrition Survey 2011 mentioned that initial CF’s were simply milk mixed in mashed rice. Vegetables are gradually in- troduced. Rarely was meat or dairy products given as complimentary foods.

From 12 months onwards many mothers start giving the child the same diet as the adults. If reg- ular family foods were given, then mothers first washed these with water to remove the spices-a practice that could potentially contaminate the food if untreated water was used. Spices were gradually introduced. Formula milk was not introduced at all by mothers whereas others intro- duced formula milk between first and 12 months of age.

According to the guiding principles of complementary feeding, there are six things that could be considered during the complementary feeding stage: amount/quantity; frequency; densi- ty/consistency; quality/diversity; hygiene; and responsive or active feeding. There was a lack of knowledge about these facts among majority of mothers but a larger proportion of urban moth- ers mentioned the various components of good complementary foods than their rural counter- parts.

Very few mothers were aware that the density/consistency of complementary foods is an im- portant component of CF. Few mothers could not mention any aspects of feeding they need to consider when preparing complementary foods. Very few mothers stated that the characteristics of good complementary foods should be ones that are rich in energy, protein and micronutrients but half of mothers opined that good CF should be clean and safe.

Majority of the urban and rural mothers were not aware that the ideal age to commence com- plementary feeding was at 6 months. Some thought the ideal age to commence complementary feeding was 9 months and few stated that the ideal time was at 4 months of age.

Reasons for early initiation of complementary feeding mentioned by the few who did commence CF before 6 months included employment of mother; perceived insufficiency of the breast milk to meet the needs of infant; infant’s reluctance to take breast milk (urban), maternal illness and early pregnancy; child underweight; family members influence mother to initiate CF (rural); poor sucking by infant and perception that breastfeeding hindered in maintaining mother’s figure (ur- ban and rural).

Delayed initiation of complementary feeding was a more common occurrence in Pakistan. The main reasons of delayed initiation of complementary feeding cited were financial (rural and ur- ban); complementary foods cause allergy (urban); the belief that breast milk was nutritious enough to meet infants needs even beyond 6 months (rural and urban); infant gaining well on exclusive breast milk so why initiate CF.

When asked how mothers can determine if the food they are giving to their child is appropriate, almost half of the mothers mentioned that they would know if their child refuses to eat it. Some mentioned that the child would vomit the food. Mothers also mentioned that signals that indi-

60 | National Nutrition Survey 2011 cated to them that their child was ready to commence CF were the infants’ interest in eating food.

When the participants were asked as to who actually fed the child, the majority of mothers re- sponded that herself or sometimes the grandmother or an older sibling The majority of mothers also stated that they generally fed their children in the living room or veranda.

Majority of women in discussions acknowledged that they washed their hands before prepara- tion of food for their children. When participants were asked regarding hand washing of child before meal very few of them were followed that practice. Majority of mothers acknowledged that they don’t use separate utensils (plate, cup or spoon) to feed their children.

Most of mothers also stated that child left over food was eaten by some other family member. Most of urban mothers pointed out, frequent use of refrigerator for storage of child leftover food.

Majority of health care professional interviewed commented that there was a uniform lack of knowledge about diet and nutrition amongst families, including those belonging to affluent backgrounds. One comment was that “Sometimes we have to tell them to buy Rs.10 worth of rice and lentils instead of spending more money on commercial food”.

D- OTHER DETERMINANTS OF MALNUTRITION

The most of participants of group discussions from both urban and rural areas opined that there was no inequality in distribution of food in terms of proportion and quantity between boys and girls in the family. However a mother of the focus groups was stated that “boys must get more food than girls because they have more responsibilities in future”.

Some participants were said that “the family sat down together at the meal time but that food was served in order of seniority” Mothers from southern Punjab said that. “Feeding the girl child is not a viable deal as she has to go another house after marriage”. Another mother stated that “The male child is an important asset because he will be productive and bring income into the family. He will also be responsible for carrying the name of the family”.

The role of culturally deep rooted food taboos across the provinces also plays its part in affecting health and nutrition. The concept of “Hot” and “Cold” was observed across the country during group discussions..

Majority of participants across all provinces were able to segregate food into the hot and cold variety. The common perception in all regions was that eggplant, bitter gourd and meat have a ‘hot’ effect. Cold food includes vegetables, raw mango, rice and lentils in Lower Sindh, Zucchini,

Okra and Pumpkin in Upper Sindh, spinach, carrot and cucumber in Baluchistan, pumpkin in Southern Punjab, lentils, and dairy products and Apricot extract in Gilgit.

“Hot” foods also included seafood in Lower and Upper Sindh, meat in Upper Sindh, Northern and Southern Punjab and Gilgit Baltistan, okra in Southern Punjab, Azad Jammu Kashmir, green vege-

61 | National Nutrition Survey 2011 tables in Southern Punjab, clarified butter and eggs in GB, lentils in GB/Azad Jammu Kashmir and soup, spinach and spices in Azad Jammu Kashmir. Some mothers said that they avoided giving “hot” food to young girls as it would speed up puberty in them.

Some participants from rural areas also highlighted another interesting myth present within so- ciety elders that taking medicine in the form of “pill/capsule” during pregnancy is harmful. Some lady health workers in pointed that “we cannot convince the women to take vitamin or iron supplements because they are suspicious that it will harm the baby”, while a women partici- pant stated “even if I take the medicine home my mother in law will not allow me to taking it”.

The most of participants across all regions acknowledged the importance of education for their children. Mother from rural area stated. “We know that by educating our children we can build a better life and secure a future for our children”. The major barriers to education stated by most of participants included cultural biases, economic and access issues. A mother from KP stated that “We want our girls to go to school but there is discouragement from our elders and we are unable to convince them”.

62 | National Nutrition Survey 2011 Chapter 11: What Next

A-Implications for interventions and research

The key finding from the NNS 2011 is that very little has changed over the last decade in terms of core maternal and childhood nutrition indicators. The survey does point towards gains in iodine status nationally following the implementation of a universal salt iodization and promotion strategy. However, this is counterbalanced by substantial deterioration in vitamin A status and little to no gains in other areas of micronutrient deficiencies. These are reflective of an insufficient response to the nutrition situation in Pakistan and the lack of coordination in developing and implementing of a coherent nutrition strategy. A draft nutrition strategy was developed in 2003–2004 and was approved by the planning commission. However, its final approval and implementation never took place. Additionally the efforts of the bilateral agencies and the World Bank have not translated into a tangible response. Although the floods of 2010 and 2011 once again highlighted the seriousness of under nutrition in Pakistan, the response was largely reactive with little movement towards a national strategy for addressing under nutrition.

Despite the fact that these aspects of the poor nutritional status of women and children of Pakistan have been known for a long time, and have been the subject of multiple surveys, there is little public awareness at a national level of the importance and impact of nutrition in the social and economic development of society. Several successive governments have failed to recognize the level of importance nutrition has in the health and development of the population. Nutrition has thus remained unrecognized in current social safety nets and income support programs. Given the agrarian nature of the national economy, there has been consistent denial of household food insecurity. This is especially true in the case of girls and women in Pakistan and few effective interventions target them.

There is a widespread perception that malnutrition is closely related to poverty. While the relationship cannot be denied, it is complex and the poverty-nutrition interaction in Pakistan is strongly influenced by the degree and form of female subjugation, which affects the girl child and women alike.

It must also be recognized that nutrition is more than food and poverty is more than mere income or assets. The few nutrition related interventions in Pakistan that have been undertaken over the last fifty years have largely followed the pattern of vertical programs and are largely supported through external aid and grants. These include vitamin A supplementation, wheat flour fortification and promotion of iodized salt use. A huge amount of resources have been invested in therapeutic feeding of malnourished children in the wake of the floods but relatively less in preventive and promotion strategies. Although there have been breastfeeding promotion and support programs at both community and facility level, (through the LHW program and the Baby Friendly Hospital initiative), the comparable rolling out of complementary feeding promotion and education strategies or the provision of fortified nutritious weaning foods has been lacking. Not surprisingly, the net impact of all such interventions has been negligible in

63 | National Nutrition Survey 2011 terms of either nutrition awareness or improvement. In addition to planning nutritional interventions, the creation of a demand at a population level for adequate nutrition is pivotal for the success of any initiative. Neither widespread malnutrition nor poor dietary practices amongst Pakistani women and children have been subjects of national awareness or public education campaigns. In addition to well-designed interventions, Pakistan needs a mass campaign for public awareness on the importance and impact of malnutrition on the nation's health.

There is thus an overwhelming argument for making an investment in adequate nutrition for the families and children of Pakistan, as a means for economic revival and boosting national morale. Although Pakistan has had several national nutrition surveys in the past, none have resulted in a national intervention program aimed at addressing the root causes and effects of malnutrition. To illustrate this, although a food aid initiative has been in place for several years under the management of the World Food Program and Pakistan Bait-ul-Maal, its impact and effectiveness in reaching the most needy has been limited. For any nutrition intervention to succeed, it is imperative that it be part of a community-based intervention targeting some of the underlying determinants of malnutrition such as household food security, culturally acceptable food choices, as well as communal decision making for promotion of health and nutrition. These interventions must be firmly grounded in the principles of equity, community participation and ownership, while retaining scientific validity.

The alarming findings from the NNS 2011 – indicating vast inequities in indicators – suggest the urgent need for action and the implementation of a range of interventions for women and children. These include the review of existing programs for quality, such as the vitamin A supplementation program, micronutrient fortification strategies and interventions to address food insecurity. Some pilot projects are underway and additional strategies need to be identified that may help soil zinc repletion interventions with national staples.

As the NNS 2011 indicates, stunting, wasting and micronutrient malnutrition is endemic in Pakistan, and reflects a combination of dietary deficiency; poor maternal and child health and nutrition; a high burden of morbidity; and low micronutrient content of the soil, especially for iodine and zinc. Most of these micronutrients have profound effects on immunity, growth and mental development, and may underlie the high burden of morbidity and mortality among women and children in Pakistan.

So what can be done? Nutrition is an area that necessitates a multi-sectoral approach for interventions. Some of the activities that could help address the issues are within the domain of the health sector while others merit broad sustained support and collaboration of other sectors and partners. For coherence, the foundation of the nutrition strategic plan has been laid down under the overall framework of the Pakistan Poverty Reduction Strategy (PRSP). This document defines the roles and activities that the production and social sectors must assume in order to attain the overall objective of socio economic improvement, including a better quality of life.

64 | National Nutrition Survey 2011 The strategic territories where multi-sectoral support and coordination is imminently required are institutionalization of nutrition; food safety and regulatory mechanisms; food fortification; and social change communication. The interventions that fall within the umbrella of the health sector are in the areas of maternal, infant, child, adolescent, adult and elderly persons’ nutrition. Collaboration between all partners is essentially required for improving the nutritional status of the target population with synergy. Given the devolution of health to the provinces, it will become even more imperative to develop a concerted and coherent national policy. The need for a central coordination and oversight mechanism to support provinces, especially those with limited capacity is imperative given the wide disparities highlighted by the NNS 2011. Among the various functions, this unit could also be required to form linkages that create social safety nets, address agricultural and food safety, and enforce food industry regulation.

Effective “social change communication” is a vital component of most successful programs and products created to reach and change behaviours in the society at large. Innovative and effective communication strategies can target misconceptions and educate the population about nutrition interventions and practices while still being sensitive to cultural ideas and practices. The integration of child nutrition with child survival becomes imperative. Similarly, given the high rates of maternal and child morbidity and mortality in Pakistan, nutrition interventions should be closely integrated with strategies for maternal, newborn and child health. The role of addressing some of the basic determinants of maternal and child under nutrition in Pakistan cannot be stressed enough. These include addressing issues of maternal education, empowerment and basic rights. It can be argued that some of the maximum gains for maternal education can be achieved by reducing high fertility rates, addressing inappropriate child spacing, and delaying the age of marriage (avoiding early marriages).

We would also like to underscore emerging areas of focus that have hitherto been ignored. One of these is the role of adolescent health and nutrition. As defined by WHO the age group ranging from 10-19 years is considered adolescent and is estimated at about 19% of the total population. Adolescent nutrition has so far been neglected in Pakistan and needs greater attention in the years to come. The NNS 2011 also provides illustrative data on the increasing need to address nutrition issues of the elderly. And, although not yet evident in the under 5 population, there are intriguing indicators in the NNS 2011 suggesting that Pakistan may be witnessing the double burden of under nutrition and obesity within rural and urban women of reproductive age.

Adult nutrition is marred by a complex interplay factors such as industrialization, urbanization, sedentary life styles, imbalanced diets and shifting socio-cultural norms. These give way to diseases such as hypertension, strokes, coronary heart disease, diabetes and cancers, among others. They tip the nutritional balance in many ways and require a multifaceted approach for interventions ranging from surveillance, research, and social change communication to simply healthy eating habits. The growing group of people over fifty years of age faces nutritional depletions and associated problems that are related to the changing and slowing metabolism of the body and inadequate replenishment of these nutrients. These changes bring along a spectrum of health problems including hypertension; strokes; coronary artery disease;

65 | National Nutrition Survey 2011 sarcopenia (loss of muscle mass); glucose intolerance and other metabolic disorders; osteoporosis and bone fractures; and cancers, among others. Efforts should be geared to assimilate and disseminate information on old age health issues and nutrition. Emphasis should also be placed on focusing on this emerging priority area for provision of rehabilitative and consultative services for needy elderly persons.

It is beyond the scope of this report to suggest remedies and discuss nutrition related interventions and strategies in depth. It is envisaged that this NNS 2011 report will provide the basis for further discussion at federal and provincial level for concerted action and strategy development. Pakistan urgently needs a nutrition policy and strategy for a coordinated, interlinked and multi-pronged approach for future endeavours to address malnutrition.

66 | National Nutrition Survey 2011 Bibliography 1. Pakistan Census Organization http://www.census.gov.pk/index.php (as of Jan, 2012) 2. Human Development Report 2010 3. Pakistan Demographic and Health Survey 2007

4. Pakistan Social and Living Standards Measurement Survey 2008 – 2009 5. World Health Statistics 2009 https://www.cia.gov/library/publications/the- worldfactbook/geos/pk.html 6. Human Development Report 2009 http://hdr.undp.org/en/media/HDR_2009_EN_Table_K.pdf 7. Andrew M. Prentice, M. Eric Gershwin, Ulrich E. Schaible, Gerald T. Keusch, Cesar G. Victora, and Jeffrey I. Gordon. New challenges in studying nutrition-disease interactions in the developing world Review series personal perspective. The Journal of Clinical Investigation Volume 118 Number 4 April 2008 8. WHO 2002: http://www.who.int/inf-fs/en/fact119.html, http://www.who.int/nut/nutrition2.htm, http://www.who.int/nut 9. Pelletier D. Potentiating effects of malnutrition on child mortality: Epidemiologic evidence and policy implications. Food and Nutrition Bulletin. 1995; The United Nations University Press. Volume 16, Number 3 10. UNICEF/ROSA 1997: Gillespie S, ed. Malnutrition in South Asia: A regional profile. Kathmandu: UNICEF Regional Office for South Asia, 1997 11. Hunt J. ed. Investing in Child Nutrition in Asia. Asian Development Bank, 2000.Nutrition and Development series No 1. 12. Yasmin S, Osrin, D., Paul, E., Costello, A. d. L. Neonatal mortality of low-birth-weight infants in Bangladesh. Bull. World Health Organ. 2001; 79: 608–614. 13. deOnis M, Frongillo EA, Blossner M. Is malnutrition declining? An analysis of changes in levels of child malnutrition since 1980. Bull World Health Organ 2000; 78:1222-33. 14. Stephenson LS, Latham MC, Ottesen EA. Global malnutrition. Parasitology 2000; 121 Suppl: S5-22. 15. UNICEF. Poverty and Children: Lessons of the 90s for least developed countries. New York: UNICEF, 2001. 16. Frongillo EA, Jr., de Onis M, Hanson KM. Socioeconomic and demographic factors are associated with worldwide patterns of stunting and wasting of children. J Nutrition 1997;127:2302-9. 17. Khan A. Adolescents and Reproductive Health in Pakistan: A Literature Review. In: Fund UNP, ed. Research Report No. 11. Islamabad: The Population Council, 2000:ii-73. 18. Bhutta ZA. Why has so little changed in maternal and child health in south Asia? Bmj 2000; 321:809-12. 19. Pakistan Medical and Dental Council. National Health Survey of Pakistan-1990-94: Network Publishing Service, 1998. 20. FAO. Nutrition country profiles: Pakistan. Rome: FAO, 1998. 21. WHO. Complementary feeding of young children in developing countries: a review of current scientific knowledge. Geneva: World Health Organization, 1998. 22. Fikree FF, Rahbar MH, Berendes HW. Risk factors for stunting and wasting at age six, twelve and twenty-four months for squatter children of Karachi, Pakistan. J Pak Med Assoc. 2000; 50:341-8. 23. Jalil F, Karlberg J, Hanson LA, Lindblad BS. Growth disturbance in an urban area of Lahore, Pakistan related to feeding patterns, infections and age, sex, socio-economic factors and seasons. ActaPaediatrScandSuppl 1989; 350:44-54.

67 | National Nutrition Survey 2011 24. Zaman S, Jalil F, Karlberg J. Early child health in Lahore, Pakistan: IV. Childcare practices. ActaPaediatrSuppl 1993; 82Suppl 390:39-46. 25. Durkin MS, Hasan ZM, Hasan KZ. Prevalence and correlates of mental retardation among children in Karachi, Pakistan. Am J Epidemiol 1998; 147:281-8. 26. Pollitt E, Gorman KS, Engle PL, Rivera JA, Martorell R. Nutrition in early life and the fulfilment of intellectual potential. J Nutrition 1995; 125:1111S-1118S. 27. World Health Organization. A critical link- Interventions for physical growth and psychological development: A review. Geneva: World Health Organization, 1999. 28. Ashfaq A. Infant feeding survey. WHO report. Islamabad. 1984 29. Jalil F, Karlberg J, Hanson LA, Lindblad BS. Growth disturbance in an urban area of Lahore, Pakistan related to feeding patterns, infections and age, sex, socio-economic factors and seasons. ActaPaediatrScandSuppl 1989;350:44-54 30. Karlberg J, Jalil F, Lindblad BS. Longitudinal analysis of infantile growth in an urban area of Lahore, Pakistan. ActaPaediatrScand 1988; 77:392-401 31. Government of Pakistan, National Nutritional Survey of Pakistan, 2001-2, Islamabad 32. Manila forum 2000: Strategies to Fortify Essential Foods in the Asia and Pacific. Asian Development Bank, 2000. Nutrition and Development Series No.2. 33. Paracha P, Jamil A. Assessment of Micronutrient (Iron, vitamin A and zinc) status of preschool children of NWFP, Pakistan, 1998. In collaboration with: Pakistan Institute of Community Ophthalmology, Peshawar; Aga Khan University, Karachi; Institute of Nutrition, Thailand; University of Ulster, North Ireland, UNICEF. 34. Bhutta ZA. The enigma of maternal and childhood malnutrition in Pakistan: can we break the vicious cycle? Journal of College of Physicians and Surgeons Pakistan. 2002 35. Government of Pakistan. Pakistan economic survey 2001-2, economic advisors wing, finance division, Islamabad. 36. Government of Pakistan, Diarrhoeal disorders and feeding practices in Pakistan. Planning and development division, Islamabad 1984. 37. Government of Pakistan. Multiple Indicators Cluster Survey of Pakistan, 1995. Ministry of Health. 38. UNICEF 2002: http://www.childinfo.org/eddb/brfeed/grpcompasia.htm and http://www.pbs.gov.pk/sites/default/files/pslm/publications/pslm_prov2010- 11/tables/2.14b.pdf 39. World Development indicators, 2002: http://devdata.worldbank.org/external/dgcomp.asp?rmdk=110andsmdk=473881andw= 0l; and http://genderstats.worldbank.org/rhealth.pdf 40. WHO, World Health Statistics 2011, available at: http://www.who.int/whosis/whostat/2011/en/index.html

68 | National Nutrition Survey 2011

Annex

Detailed NNS Tables

Sample Design & Sampling Weight

69

ANNEX: NNS Detailed Tables (Tables are numbered according to their corresponding chapters in the NNS) Table 3.1: Details of sample size coverage (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA AJK GB

Number of EBs

Sampled 1500 618 882 682 323 218 110 67 66 34

Completed 1500 618 882 682 323 218 110 67 66 34

Number of households

Sampled 30000 12360 17640 13640 6460 4360 2200 1340 1320 680

Interviewed / Visited 30000 12360 17640 13640 6460 4360 2200 1340 1320 680

Consent Yes 27963 11496 16467 13188 6282 3626 1996 900 1303 668

Refusals 2037 864 1173 452 178 734 204 440 17 12

Refusal Rate 6.8 7.0 6.6 3.3 2.8 16.8 9.3 32.8 1.3 1.8

Table 3.2: Distribution of HHs by Wealth Quintiles (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Lowest 20.9 3.4 29.0 14.4 37.8 13.0 40.3 24.7 11.5 18.3

Second 21.1 7.0 27.6 20.2 12.1 29.9 26.1 51.7 26.2 36.4

Middle 20.2 18.1 21.2 22.7 12.4 25.0 15.5 17.6 22.3 25.9

Fourth 19.4 30.7 14.2 21.8 18.0 18.2 9.8 4.2 23.8 9.3

Highest 18.4 40.8 8.1 20.9 19.7 13.9 8.3 1.8 16.2 10.0

N 27963 11496 16467 13188 6282 3626 1996 900 1303 668

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 3.3: Age and Sex Distribution of Households’ Members (Percent) Gender/Age Group Pakistan Residence Province / Region

70

Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Gender

Male 50.4 50.3 50.5 502.0 50.5 50.9 50.3 55.4 48.6 49.7

Female 49.6 49.6 49.6 49.6 49.6 49.6 49.6 49.6 49.6 49.6

Age (Years)

0-2 6.3 6.2 6.3 6.8 6.2 4.4 6.1 2.6 8.8 6.6

3-4 11.8 10.1 12.6 11.1 11.9 12.6 12.5 19.5 13.4 11.8

5-9 14.3 12.6 15.0 13.1 14.2 16.4 17.4 25.3 12.6 15.5

10-14 11.1 10.8 11.2 10.3 11.8 12.5 12.8 12.1 9.8 12.1

15-19 8.4 9.2 8.0 8.3 9.1 8.3 8.8 3.3 6.9 9.9

20-24 7.5 8.9 6.8 8.0 7.4 6.8 6.1 2.8 7.3 6.7

25-29 8.6 9.1 8.4 8.7 8.0 9.2 7.8 9.6 8.6 8.0

30-34 7.5 7.8 7.3 7.4 7.6 7.4 6.8 9.5 8.1 6.7

35-39 6.3 6.3 6.3 6.2 6.7 5.9 6.5 7.0 7.1 5.5

40-44 4.3 4.5 4.3 4.3 4.6 4.0 4.5 4.0 3.6 3.6

45-49 3.4 3.6 3.3 3.5 3.4 3.6 3.1 2.0 3.1 2.5

50+ 10.6 10.8 10.5 12.2 9.1 9.0 7.6 2.3 10.8 11.0

N 187095 77062 110033 89611 40470 21817 15117 4984 9173 5923

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 3.4: Household Size (Percent) Residence Province / Region Household Members Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

1-4 22.0 22.4 21.8 20.1 26.9 23.1 18.2 23.0 17.6 7.9

5-7 47.9 48.7 47.6 47.7 43.2 56.3 38.0 68.6 45.1 34.2

8+ 30.1 28.9 30.6 32.2 29.9 20.6 43.8 8.4 37.2 58.0

Average Family Size (Mean ± SE) 6.6 ± 0.03 6.6 ± 0.05 6.6 ± 0.04 6.8 ± 0.04 6.4 ± 0.06 6.0 ± 0.06 7.6 ± 0.17 5.6 ± 0.10 7.0 ± 0.11 8.9 ± 0.24

N 27963 11496 16467 13188 6282 3626 1996 900 1303 668

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

71

Table 3.5: Formal Education of Head of the Household (Percent) Residence Province / Region Characteristics Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Illiterate 45.7 33.8 51.1 44.7 47.5 44.6 58.2 48.8 27.3 47.6

1-5 11.8 10.4 12.4 13.3 13.3 6.1 6.4 5.9 14.9 9.2

6-8 11.0 11.3 10.9 12.4 6.5 12.6 6.7 17.3 15.3 10.6

9-10 17.5 21.3 15.7 18.2 13.9 20.7 13.8 16.7 25.8 14.0

Above Matric. 14.1 23.1 9.9 11.4 18.8 16.0 14.9 11.3 16.7 18.6

N 27762 11410 16352 13099 6252 3587 1983 877 1297 667

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 3.6: Occupation of Head of the Household (Percent) Residence Province / Region Occupation Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Business 8.6 15.1 5.7 9.5 6.8 10.5 5.0 2.1 9.7 6.6

Worker/Labor 38.7 33.2 41.2 36.7 45.2 38.7 32.0 40.7 34.0 19.9

Farmer/Land Owner 14.9 2.7 20.4 18.0 11.9 9.5 18.2 12.8 3.3 12.4

Govt./Pvt. Employee 16.4 23.2 13.3 13.5 18.5 19.6 23.1 18.2 23.9 34.3

Small Business / Shop 5.9 7.0 5.4 5.6 4.4 8.1 7.2 12.0 5.6 2.2

Not Working / Unemployed 15.5 18.9 14.0 16.8 13.2 13.6 14.5 14.2 23.4 24.6

N 27566 11305 16261 13040 6219 3544 1956 851 1288 668

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

72

Table 3.7: Occupancy Status of Dwellings and Number of Rooms per Dwelling (Percent) Ownership status of house & No. of Residence Province / Region Pakistan Rooms Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Owned 89.0 76.5 94.8 90.1 84.7 92.1 86.1 87.1 95.9 89.8

Rented 8.6 21.2 2.7 7.2 12.7 7.1 9.3 11.7 2.6 7.1

Living without paying rent 2.3 2.1 2.4 2.6 2.5 0.8 4.2 1.2 1.5 1.8

Other (specify) 0.1 0.2 0.1 0.1 0.1 0.1 0.4 0.0 0.0 1.3

N 27563 11386 16177 13093 6239 3507 1937 835 1295 657 Rooms In HH

1 37.7 31.6 40.6 35.0 56.5 24.5 36.1 13.0 26.6 21.5

2 39.4 40.1 39.0 40.3 29.7 51.1 36.4 47.2 41.0 35.6

3 14.8 18.5 13.1 15.5 9.9 17.4 15.2 25.4 18.9 21.9

>3 8.1 9.8 7.3 9.2 3.9 7.0 12.4 14.5 13.4 21.0

N 27616 11400 16216 13091 6227 3551 1969 821 1293 664 Type of Floor

Cement/Slake lime 46.1 64.7 37.5 49.2 42.9 44.5 31.1 27.9 62.3 69.7

Tiles 9.8 22.3 4.0 11.4 11.4 5.2 1.0 3.0 10.4 0.1

Mud /sand 40.8 10.2 54.9 34.2 44.9 49.2 66.7 63.1 26.1 29.1

Other materials 3.4 2.8 3.6 5.2 0.8 1.1 1.2 6.0 1.2 1.1

N 27746 11402 16344 13086 6256 3597 1979 864 1299 665 Type of Roof

RCC 19.6 41.6 9.5 23.3 19.9 12.0 8.3 3.6 22.8 3.2

Tier- Garter / Roofing tiles 49.5 45.2 51.4 57.1 40.2 48.5 27.5 46.0 28.0 3.7

Wood planks 19.9 6.5 26.1 13.8 25.5 23.0 39.9 31.0 18.9 89.4

Other materials 11.0 6.8 13.0 5.8 14.4 16.5 24.3 19.4 30.3 3.7

N 27823 11465 16358 13160 6264 3597 1983 850 1302 667 Structure of Walls

Bricks, cement and lime 64.2 86.9 53.7 69.9 54.9 69.9 29.0 39.4 80.4 85.1

Bricks (not cemented) 20.7 10.1 25.6 21.9 19.9 18.6 12.8 41.8 5.7 4.6

Other materials 15.2 3.0 20.8 8.2 25.2 11.5 58.2 18.8 13.9 10.3

N 27869 11478 16391 13171 6270 3616 1974 871 1299 668

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

73

Table 3.8: Cooking Fuel (Percent) Residence Province / Region Type of Fuel Used Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Firewood 57.9 15.5 77.4 54.7 48.1 71.7 68.7 84.8 85.4 89.6

Gas 35.8 83.3 13.9 36.4 49.4 24.5 26.2 4.9 14.5 10.2

Kerosene Oil 0.2 0.0 0.3 0.0 0.0 0.9 0.1 2.7 0.0 0.0

Animal Dung 6.1 1.2 8.3 8.8 2.5 2.8 4.7 7.6 0.1 0.1

Other (Specify) 0.0 0.1 0.0 0.0 0.0 0.0 0.3 0.0 0.0 0.2

N 27772 11432 16340 13134 6243 3581 1970 880 1298 666

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 4.1: Food Insecurity Residence Pakistan Urban Rural Food Secure 41.9 47.6 39.4

Food Insecure Without Hunger 28.4 26.5 29.3

Food Insecure With Hunger 19.8 17.7 20.7

FoodModerate Insecure With Hunger Severe 9.8 8.2 10.5

N 15672 6397 9275

74

Table 5.1: Age Distribution of Mothers (Percent) Residence Province / Region Age (Years) Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

15-19 years 1.7 1.5 1.8 1.6 1.9 2.0 1.2 2.2 0.9 1.7

20-24 years 11.6 11.5 11.7 11.9 10.6 11.9 10.5 11.6 16.1 13.9

25-29 years 28.2 27.6 28.5 26.8 25.5 34.1 29.8 41.0 27.9 31.5

30-34 years 23.9 24.1 23.8 24.1 24.5 22.0 23.3 24.3 26.8 24.5

35-39 years 18.6 17.7 19.1 19.1 19.1 16.3 20.9 16.0 18.9 17.6

40-44 years 9.6 11.3 8.8 9.8 11.8 7.9 8.2 2.9 6.9 7.7

45-49 years 6.3 6.3 6.3 6.7 6.8 5.9 6.1 2.0 2.5 3.1

N 24694 9995 14699 11412 5460 3091 1888 894 1288 661

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.2: Formal Education (Mothers) (Percent) Residence Province / Region Characteristics Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Education

Illiterate 59.3 36.6 69.4 52.6 62.2 72.2 82.0 82.3 30.4 62.4

1-5 Years 12.5 13.4 12.1 16.0 10.3 5.9 6.3 4.6 17.7 6.5

6-8 Years 8.7 11.1 7.6 9.5 6.2 9.1 4.8 8.5 19.8 9.2

9-10 Years 10.5 18.5 6.9 12.3 10.2 6.8 3.5 3.5 19.1 10.9

Above Matric. 9.0 20.3 4.0 9.7 11.2 5.9 3.4 1.0 12.9 10.9

N 24459 9928 14531 11364 5437 3030 1875 811 1282 660

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

75

Table 5.3: Marital Status and Current Pregnancy Status (Mothers) (Percent) Residence Province / Region Characteristics Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Marital Status Married 98.7 98.0 99.0 98.5 98.3 99.4 99.0 100.0 99.0 99.8

Widow / Separated 1.3 2.0 1.0 1.5 1.7 0.6 1.0 0.0 1.0 0.2

N 24694 9995 14699 11412 5460 3091 1888 894 1288 661

Pregnancy Status Yes 10.0 9.1 10.5 11.2 11.9 6.0 5.1 4.6 9.1 7.3 N 24694 9995 14699 11412 5460 3091 1888 894 1288 661

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.4: Reproductive History (Mothers) (Percent) Residence Province / Region Characteristics Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Pregnancies

1-2 29.7 30.5 29.3 28.3 26.3 42.4 26.6 22.9 33.0 25.2

3-5 46.6 47.9 46.0 47.3 42.6 48.0 40.4 68.9 45.2 43.6

6+ 23.7 21.6 24.6 24.4 31.1 9.6 33.0 8.2 21.7 31.2

N 24217 9818 14399 11189 5325 3005 1864 890 1287 657 Outcome of Last Pregnancy

Live birth 93.4 91.6 94.2 92.1 91.9 97.9 95.3 99.3 94.5 95.9

Miscarriage 5.7 7.8 4.9 7.0 7.2 1.5 4.4 0.5 4.5 3.6

Still birth 0.8 0.6 0.9 1.0 0.9 0.6 0.2 0.3 1.0 0.5

N 18904 7402 11502 8361 3978 2402 1610 831 1146 576

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

76

Table 5.5: Seeking Antenatal Care from the Skilled & unskilled Provider (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB ANC

No One 37.5 18.1 45.8 33.0 38.3 43.5 52.1 70.5 19.2 20.0

Doctor 49.5 72.1 39.8 51.1 57.7 39.2 38.8 13.0 66.3 60.5

Nurse 7.1 4.5 8.2 11.5 1.9 1.1 2.3 3.4 12.5 11.9

LHV 2.3 1.8 2.5 0.9 0.3 10.6 1.4 4.4 0.9 4.7

CHW 0.4 0.5 0.3 0.3 0.3 0.9 0.2 0.9 0.1 0.4

LHW 1.1 1.0 1.2 0.9 0.4 2.5 1.6 3.1 0.7 2.6

Traditional Birth attendant 1.5 1.5 1.5 1.5 1.1 1.4 2.7 2.3 0.2 0.0

Others Specify 0.1 0.1 0.1 0.2 0.0 0.1 0.0 0.0 0.1 0.0

Don't know 0.5 0.5 0.5 0.5 0.1 0.8 0.8 2.4 0.0 0.0

N 22791 9081 13710 10167 5152 2902 1795 869 1265 641

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.6: Supplementation during Last Pregnancy (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Supplementation

None 37.8 23.0 44.4 35.8 43.3 33.7 54.5 30.2 33.4 30.3

Iron 24.4 33.2 20.4 26.3 26.1 19.3 11.4 11.7 36.4 32.8

Folic Acid 25.3 35.7 20.7 22.5 31.3 28.0 17.4 19.2 37.1 30.4

Micronutrient 3.9 3.5 4.0 2.6 2.2 8.3 5.8 13.6 5.4 0.2

Calcium 35.6 48.6 29.9 39.3 38.0 24.7 15.6 27.5 50.9 25.6

Other Vitamins 8.9 14.4 6.4 6.8 16.4 4.8 4.4 12.2 11.4 4.2

N 24694 9995 14699 11412 5460 3091 1888 894 1288 661

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.7: Knowledge of Micronutrients – Iron (Percent) Pakistan Residence Province / Region 77

Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Iron 24.8 42.0 17.0 29.8 23.6 13.9 8.6 9.5 40.8 22.7

Iron Rich Food

Don't Know 47.6 35.1 61.6 52.6 31.2 39.2 48.7 75.3 65.4 40.4

Liver 6.2 8.5 3.7 5.0 7.6 13.0 11.8 4.0 3.4 1.7

Beef 6.3 7.0 5.6 6.7 5.8 4.9 4.5 1.2 8.2 7.1

Mutton 3.6 4.3 2.9 3.6 4.3 2.4 3.8 0.0 2.6 8.9

Chicken 4.0 4.0 4.0 3.8 3.8 6.7 1.6 1.1 3.0 5.0

Egg yolk 5.0 5.4 4.6 4.4 4.9 10.6 8.1 1.0 2.9 10.9

Green leafy vegetables 36.5 48.1 23.5 34.1 51.7 28.3 29.1 1.9 21.7 39.1

Lentils 5.1 4.7 5.5 4.4 4.6 11.6 3.2 1.1 6.9 5.3

Dairy products 9.7 10.6 8.6 8.5 11.2 14.9 8.1 6.8 10.2 15.1

Fruit 9.7 13.5 5.5 7.6 21.0 0.6 4.4 0.0 6.7 18.8

Apple 4.4 6.6 1.8 3.3 9.8 0.3 3.3 1.1 2.2 0.9

Vegetable 1.1 1.1 1.1 1.4 0.2 0.0 0.0 0.0 2.9 2.4

Fish 0.9 1.3 0.5 0.6 2.4 0.2 0.5 0.0 0.5 3.1

Potato 1.0 1.3 0.6 1.0 1.5 0.2 0.3 0.0 0.6 2.3

Others 2.9 3.0 2.8 3.8 1.5 0.3 0.0 0.0 2.6 6.1

N 7023 4382 2641 4141 1300 529 190 88 592 183 Health problems due to Iron deficiency

Don't Know 60.7 52.1 70.2 64.4 49.5 52.5 54.6 80.4 76.0 55.2

Behavioral problems 0.4 0.4 0.4 0.4 0.3 0.9 1.1 1.1 0.0 0.5

Repeated infections 1.0 1.2 0.7 0.4 2.2 2.2 2.4 1.0 0.0 5.5

Loss of appetite 1.4 1.6 1.1 1.0 1.7 3.9 2.0 1.1 0.1 1.2

Lethargy 7.1 9.5 4.4 6.0 10.7 8.2 8.1 0.9 3.3 8.0

Breathlessness 0.8 0.8 0.7 0.5 1.2 2.0 0.6 1.0 0.1 0.0

Increased sweating 0.4 0.5 0.3 0.0 1.0 1.8 0.7 2.0 0.0 0.0

Strange ‘food’ cravings (pica) 0.3 0.3 0.3 0.3 0.2 0.6 1.0 0.0 0.1 0.0

Failure to grow at expected rate 1.7 2.2 1.2 2.2 0.7 0.9 0.0 0.0 1.1 9.0

Abortions in pregnant women 0.6 0.6 0.5 0.4 0.6 2.0 1.3 1.0 0.0 0.2

Still Births 0.4 0.3 0.5 0.1 0.3 2.4 0.9 3.1 0.0 0.0

Growth retardation of fetus 0.6 0.9 0.3 0.4 0.9 1.0 0.0 1.0 0.6 0.5

Anemia 26.4 33.3 18.6 22.5 38.8 33.0 23.3 2.0 16.3 16.0

Weakness 4.4 4.3 4.5 5.8 2.0 0.1 4.1 0.0 5.0 7.2

Bones Problem/pain/disease 2.5 3.5 1.4 3.0 1.9 0.8 1.6 0.0 2.1 1.9

Others 3.9 4.6 3.0 4.5 3.4 0.7 3.9 1.1 2.3 13.3

N 7023 4382 2641 4141 1300 529 190 88 592 183

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.8: Knowledge of Micronutrients – Iodine (Percent)

78

Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Iodine 42.8 61.6 34.2 47.8 38.4 41.3 17.3 17.3 59.1 37.1

Iodine Rich Food

Don't Know 0.7 1.0 1.0 1.0 1.3 2.1 3.4 8.1 2.4 3.5

Liver 0.5 0.6 0.4 0.3 0.4 1.4 1.8 0.5 0.0 0.0

Meat products 1.5 1.8 1.4 1.4 1.5 2.2 3.9 1.2 0.9 2.4

Dairy Products 1.5 1.6 1.4 1.0 1.6 3.6 2.1 0.0 0.3 0.9

Vegetables 3.8 4.9 2.9 3.8 4.6 3.3 3.1 2.2 3.5 3.1

Fish 2.4 3.1 1.7 1.8 3.7 3.0 1.6 3.6 1.5 0.3

Iodized Salt 66.9 66.2 67.4 67.0 66.5 70.5 53.7 44.8 66.5 57.2

Fruits 0.5 0.7 0.4 0.5 0.8 0.0 0.1 0.0 0.5 0.7

Egg/Egg fry 0.2 0.3 0.2 0.3 0.2 0.0 0.0 0.0 0.6 3.2

Daal / pulses 0.1 0.2 0.1 0.2 0.1 0.0 0.0 0.0 0.1 0.0

Water 0.2 0.1 0.3 0.3 0.0 0.0 0.0 0.0 0.0 0.0

Others 0.9 1.1 0.8 1.2 0.9 0.0 0.6 0.0 0.7 1.2

N 11879 6607 5272 6508 2169 1553 385 149 840 275 Problems due to iodine deficiency

Don't Know 63.7 59.0 67.6 64.9 70.1 48.6 65.0 76.0 65.1 60.6

Goitre 26.0 28.4 24.0 25.2 16.9 42.7 26.0 14.1 27.1 26.2

Mental retardation/IQ loss 2.8 3.5 2.2 2.3 3.9 3.4 3.2 2.0 2.7 3.5

Brain damage 1.0 1.6 0.6 0.7 1.7 1.3 3.3 1.6 0.4 0.3

Impairs growth/development 3.8 5.1 2.8 3.0 4.6 6.9 3.0 1.1 2.3 4.3

Defects of speech & hearing 0.5 0.6 0.4 0.5 0.6 0.4 0.3 1.0 1.0 1.3

Abortions in pregnant women 0.3 0.4 0.2 0.3 0.2 0.5 0.7 1.1 0.0 0.0

Still births 0.2 0.3 0.2 0.1 0.3 0.8 0.5 0.0 0.0 0.0

Congenital anomalies 1.5 2.2 1.0 1.4 2.5 0.5 0.9 0.6 2.4 1.2

Growth retardation of Foetus 0.3 0.5 0.2 0.2 0.6 0.3 0.3 0.5 0.2 0.0

Low Blood Pressure 1.1 0.6 1.5 1.7 0.2 0.0 0.0 0.0 1.8 3.0

Weakness 0.9 1.1 0.8 1.2 0.7 0.0 0.4 0.0 1.0 1.7

Bones Problem/pain/disease 0.7 1.2 0.3 1.0 0.5 0.1 0.7 0.0 0.7 0.0

Anemia 0.4 0.3 0.4 0.5 0.2 0.0 0.0 0.0 0.6 0.5

Dehydration 0.2 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.4 0.0

Others 2.1 2.8 1.6 2.7 2.1 0.1 1.1 0.0 2.1 6.0

N 11879 6607 5272 6508 2169 1553 385 149 840 275

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.9: Knowledge of Micronutrients - Vitamin A (Percent) Pakistan Residence Province / Region

79

Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Vitamin A 24.0 41.6 16.0 28.6 23.5 12.5 10.6 7.5 44.5 28.8

Vitamin A rich Food

Don't Know 58.4 54.7 62.9 63.4 52.3 26.9 55.3 78.1 72.1 47.3

Liver 1.5 1.5 1.5 0.9 1.4 4.8 8.0 8.1 1.1 0.2

Meat product 7.2 7.6 6.6 6.7 6.3 13.7 4.9 2.4 8.1 8.1

Egg yolk 4.7 5.2 4.0 4.1 4.6 9.9 7.8 2.5 2.7 10.2

Green leafy Vegetables 17.0 17.2 16.7 16.2 19.4 20.2 11.3 2.5 14.3 30.4

Lentils/Beans 4.5 4.4 4.7 3.3 5.5 11.8 2.9 0.0 6.7 4.3

Dairy products 9.0 9.7 8.3 8.4 9.8 16.3 3.6 0.0 5.9 7.6

Fruits 20.5 23.3 17.3 18.2 24.3 33.8 20.3 4.8 15.7 19.3

Carrots 7.8 10.1 5.1 5.4 14.7 12.2 9.1 0.0 2.9 2.0

Vegetable 0.9 0.8 0.9 1.2 0.0 0.0 0.4 0.0 1.4 2.1

Fish 0.7 1.0 0.3 0.6 1.2 0.0 0.8 0.0 0.0 1.1

Ghee 0.6 0.4 0.7 0.7 0.1 0.4 0.8 0.0 0.8 2.5

Potato 0.4 0.3 0.4 0.5 0.3 0.0 0.4 0.0 0.0 2.4

Others 2.1 2.1 2.1 2.5 1.8 0.0 0.2 0.0 1.8 5.6

N 6988 4452 2536 4018 1324 480 233 69 648 216 Health problems due to Vitamin A deficiency

Don't Know 78.1 75.1 81.5 82.5 74.4 47.8 64.6 83.7 91.4 76.6

Abortions in pregnant women 0.5 0.4 0.7 0.2 0.7 2.9 2.2 1.3 0.0 0.9

Still Births 0.6 0.4 0.8 0.2 0.7 3.2 2.1 3.7 0.3 0.2

Growth retardation of foetus 0.3 0.4 0.3 0.1 0.4 2.0 0.4 0.0 0.0 0.2

Night Blindness 7.2 9.8 4.2 5.2 12.2 11.9 17.4 1.2 1.3 1.7

Rough and Dry Skin 2.1 3.0 1.0 1.2 3.5 6.3 2.1 3.8 0.1 0.4

Vulnerable to infections 0.8 0.7 0.8 0.6 0.7 1.8 1.2 0.0 1.1 1.1

Growth retardation 8.8 9.3 8.2 5.8 9.3 34.9 9.0 5.0 4.5 5.6

Weakness 2.0 1.9 2.0 2.5 1.0 0.4 4.5 0.0 1.2 4.4

Anemia 1.0 0.8 1.2 1.4 0.2 0.0 0.2 0.0 0.6 7.4

Eye sight Problem 0.3 0.4 0.2 0.3 0.2 0.0 0.4 0.0 0.0 0.0

Others 1.9 2.2 1.6 2.2 1.6 0.6 2.4 0.0 1.6 3.7

N 6988 4452 2536 4018 1324 480 233 69 648 216

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

80

Table 5.10: Knowledge of Micronutrients – Zinc (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Zinc 6.1 12.8 3.1 6.6 7.5 4.2 2.8 0.9 9.7 4.5

Zinc Rich Food

Don't Know 73.3 73.4 73.1 77.6 77.1 35.7 63.6 47.8 89.8 66.9

Liver 2.5 2.7 2.2 1.7 3.1 5.2 6.4 20.1 0.4 0.0

Meat product 4.9 4.6 5.4 4.7 2.8 13.1 5.4 0.0 1.7 1.2

Egg yolk 2.6 2.7 2.3 1.9 2.0 8.7 2.8 0.0 0.5 0.0

Vegetables 8.0 9.0 6.0 7.5 8.0 12.3 11.0 0.0 1.7 13.1

Lentils/beans 4.3 4.5 4.0 4.0 3.3 10.7 1.3 0.0 1.9 2.5

Dairy products 4.9 4.0 6.5 2.2 3.5 25.9 2.8 0.0 0.0 0.0

Fruits 9.8 9.7 9.9 6.9 10.0 27.9 10.3 0.0 4.5 2.5

Watermelon seeds 2.3 1.9 3.1 0.9 2.1 10.3 7.4 10.7 0.0 0.0

Others 2.5 2.5 2.6 2.9 2.7 3.5 0.0 1.6 9.9

N 1861 1355 506 1002 413 168 66 9 161 42 Health problems due to Zinc deficiency

Don't Know 78.9 78.7 79.2 83.9 80.5 45.6 63.5 69.2 90.7 72.0

Growth retardation 7.5 6.8 8.8 4.6 6.3 28.5 9.6 20.1 1.8 4.8

Loss of appetite 1.9 1.9 1.9 1.1 0.9 8.5 5.7 0.0 1.2 0.0

Impaired immune functions 1.2 0.8 1.9 1.0 0.3 4.6 1.5 0.0 0.4 0.0

Diarrhea 5.0 5.2 4.5 2.6 9.4 6.7 5.3 10.7 2.8 11.0

Skin problems 5.5 5.7 5.1 3.5 5.0 20.2 6.3 0.0 0.4 5.3

Others 3.3 3.6 2.6 4.2 2.6 0.8 0.6 0.0 2.7 0.0

N 1861 1355 506 1002 413 168 66 9 161 42

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

81

Table 5.11: Knowledge of Micronutrients - Vitamin D (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Vitamin D 20.8 38.0 13.0 24.3 22.5 9.9 6.4 3.8 41.6 16.7

Vitamin D Rich Food

Don't Know 64.4 60.0 70.3 70.8 58.1 25.2 54.7 64.6 74.1 63.1

Sea Food 1.3 1.8 0.7 0.6 2.9 2.3 4.5 0.0 0.1 0.0

Cod liver oil 4.2 5.1 3.0 3.7 4.5 9.8 5.2 0.0 1.6 1.0

Liver 2.0 2.0 1.9 1.5 1.9 6.8 3.3 2.3 1.6 0.3

Meat product 7.3 7.1 7.7 6.3 7.0 18.7 4.5 2.5 6.4 12.4

Egg yolk 4.8 5.5 3.9 3.3 5.4 15.7 7.3 17.3 2.5 6.0

Green Leafy Vegetables 11.5 11.4 11.6 10.1 12.4 20.2 11.6 5.0 11.4 28.1

Lentils/ Beans 4.5 4.5 4.5 3.4 4.8 12.9 7.2 5.2 4.1 3.9

Dairy Products 10.6 12.3 8.3 7.4 16.3 22.7 9.3 0.0 7.6 8.4

Fruits 12.9 14.1 11.4 11.1 14.1 24.5 13.0 2.9 14.1 15.2

Sunlight 3.7 5.4 1.4 3.9 4.8 1.1 1.7 0.0 0.4 0.3

Vegetable 0.5 0.2 1.0 0.7 0.1 0.0 0.7 0.0 0.7 0.6

Others 2.2 2.5 1.8 2.4 2.2 0.3 1.5 0.0 2.0 10.4

N 6059 4014 2045 3480 1257 393 143 37 609 140 Health problems due to Vitamin D deficiency

Don't Know 78.2 72.5 85.9 82.7 72.4 54.2 64.0 60.5 91.4 83.2

Abortions in pregnant women 0.6 0.5 0.7 0.3 0.5 2.9 0.6 0.0 0.6 0.7

High Blood pressure in pregnant 0.3 0.3 0.2 0.2 0.2 0.9 1.0 2.5 0.3 0.7 women Still Births 0.6 0.5 0.7 0.1 0.5 4.7 0.3 2.5 0.3 0.0

Growth retardation of foetus 0.4 0.5 0.4 0.4 0.4 0.9 3.2 0.0 0.3 0.3

Bone Disease 13.3 18.9 5.9 9.3 21.6 24.6 17.5 24.6 4.3 7.5

Diarrhea 0.9 0.7 1.1 0.3 1.0 5.4 1.0 0.0 0.6 1.1

Skin problems 3.9 4.4 3.1 3.1 3.2 14.6 4.6 2.8 1.9 1.1

Weakness 1.5 1.5 1.4 1.5 1.7 0.5 2.4 0.0 0.5 5.5

Anemia 0.7 0.6 1.0 1.0 0.3 0.5 0.0 0.0 0.3 1.5

Others 2.4 3.2 1.5 3.0 1.9 0.0 5.5 0.0 1.3 1.4

N 6059 4014 2045 3480 1257 393 143 37 609 140

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

82

Table 5.12: Knowledge of Micronutrients - Vitamin B (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Vitamin B 19.3 34.4 12.5 23.2 19.2 9.7 5.8 3.6 40.1 15.6

Vitamin B rich Food

Don't Know 69.6 66.5 73.4 75.3 65.8 28.9 55.3 64.6 79.9 57.8

Sea Food 1.0 1.4 0.6 0.6 1.7 2.4 3.9 0.0 0.3 0.4

Cod liver oil 1.9 1.9 1.8 1.7 2.1 3.4 2.1 2.9 0.1 1.4

Liver 1.4 1.6 1.0 0.9 1.5 2.8 5.5 0.0 3.2 0.7

Meat product 6.9 7.2 6.5 6.3 6.2 15.6 9.6 0.0 4.9 17.9

Egg yolk 3.4 3.7 3.0 2.3 3.4 12.0 8.1 8.0 1.1 10.8

Green Leafy Vegetables 11.9 13.5 9.8 10.0 15.9 18.6 10.1 2.9 7.3 24.1

Lentils/Beans 5.7 6.2 5.2 4.2 7.4 15.3 10.9 5.3 3.1 5.1

Dairy Products 8.4 8.6 8.1 6.2 9.9 24.3 7.4 2.3 6.9 12.1

Fruits 13.4 16.3 9.8 11.6 16.1 22.2 14.9 8.4 11.5 13.0

Others 1.4 1.3 1.6 1.9 0.5 0.0 2.1 0.0 0.8 10.0

N 5674 3723 1951 3296 1100 385 130 36 592 135 Health problems due to Vitamin B deficiency Don't Know 79.1 76.0 83.0 84.3 76.5 39.8 59.5 64.8 91.4 73.4

Anemia 9.2 10.3 7.8 6.2 10.4 30.2 23.9 21.0 5.3 8.7

Mouth ulcers 0.9 1.1 0.7 0.3 2.0 3.3 1.6 0.0 0.4 0.4

Angular Stomatitis 0.4 0.5 0.4 0.3 0.4 2.0 0.4 0.0 0.0 0.0

Growth retardation 2.7 3.4 1.8 1.4 3.3 12.9 5.6 0.0 0.4 2.2

Bone Disease 4.8 5.9 3.5 3.0 7.0 15.0 10.6 5.9 1.4 4.3

Skin problems 3.1 3.8 2.2 2.0 4.1 10.9 3.2 2.8 0.4 0.4

Irritability and restlessness 1.0 1.2 0.7 0.6 1.8 2.5 1.3 0.0 0.6 0.4

Weakness 1.0 1.1 0.9 1.3 0.4 0.5 2.7 0.0 0.2 7.4

Others 1.8 2.4 1.1 2.2 1.5 0.3 1.8 0.0 0.1 5.5

N 5674 3723 1951 3296 1100 385 130 36 592 135

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

83

Table 5.13: Knowledge of Iodized Salt and Its Usage (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Knowledge about Iodized Salt

Yes 64.2 83.0 55.6 71.4 59.9 58.5 29.3 29.8 82.0 79.5

No 35.8 17.0 44.4 28.6 40.1 41.5 70.7 70.2 18.0 20.5

N 26933 11026 15907 12720 5840 3572 1960 873 1300 668 Use of Iodized salt for cooking

Yes 39.8 46.5 35.2 36.1 39.2 49.0 45.4 14.1 71.6 94.8

No 56.2 51.4 59.4 63.2 59.5 26.2 50.0 82.1 28.1 3.0

Don't know 4.1 2.0 5.4 0.6 1.3 24.8 4.6 3.8 0.3 2.2

N 17306 8818 8488 9349 3413 2098 579 219 1108 540

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.14: Salt Test Results (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Not iodized (0 PPM) 30.9 27.6 32.4 21.2 48.2 36.4 59.2 44.9 12.1 15.1

15 PPM 13.4 12.3 13.9 11.6 14.0 19.0 15.2 29.2 14.9 14.8

25 PPM 17.6 16.3 18.1 19.0 11.8 24.4 9.2 15.6 22.6 16.5

50 PPM 38.2 43.9 35.5 48.2 26.0 20.2 16.5 10.4 50.4 53.5

N 23894 9924 13970 11977 5517 2701 1710 82 1272 635

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

84

Table 5.15: Clinical Examination (Mother) (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Clinical Examination

Edema 1.6 2.1 1.4 2.1 0.8 0.9 1.7 1.6 1.5 4.1

Jaundice 1.4 1.0 1.6 1.7 1.4 0.7 1.3 0.4 1.8 0.1

Anemia / Pallor 26.1 20.5 28.6 28.0 33.7 11.0 20.2 10.3 35.9 16.0

Goiter 2.9 1.8 3.4 4.1 1.3 1.2 1.1 0.7 9.8 1.2

Bitot’s spot 0.4 0.3 0.4 0.1 0.2 0.3 2.8 3.9 0.0 0.5

Cyanosis 0.2 0.2 0.2 0.2 0.1 0.4 0.5 0.1 0.3 0.0

N 24694 9995 14699 11412 5460 3091 1888 894 1288 661

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.16: Body Mass Index – Non Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB BMI (kg/m2) <16 2.3 1.7 2.6 2.2 3.6 0.7 4.2 0.5 2.6 0.9 16-16.99 3.0 1.8 3.5 2.8 4.8 0.9 4.0 0.1 3.7 3.0 17-18.49 8.8 5.5 10.3 8.9 12.2 4.1 10.3 2.2 12.0 10.7 18.5-24.99 51.9 42.5 56.1 50.4 51.2 56.1 56.3 49.0 56.3 65.3 25-29.99 22.4 28.5 19.7 22.3 18.3 28.1 17.7 38.4 18.8 17.3 30-34.99 8.7 14.5 6.0 9.9 7.3 8.0 5.7 9.2 5.3 2.2 35-39.99 2.1 3.9 1.3 2.6 2.1 1.5 1.5 0.5 1.1 0.6 >=40 0.7 1.5 0.4 0.9 0.6 0.6 0.3 0.1 0.0 0.0 N 21907 8909 12998 9967 4768 2866 1695 836 1165 610

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

85

Table 5.17: Body Mass Index (Women 15 – 49 Married & Unmarried) (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB BMI (kg/m2) <16 3.5 3.1 3.7 3.2 4.9 2.0 5.4 0.5 4.1 1.9 16-16.99 4.0 3.3 4.3 4.0 5.7 1.5 4.6 0.1 4.9 3.7 17-18.49 10.5 8.0 11.7 10.5 13.5 5.5 12.1 2.5 12.5 11.5 18.5-24.99 53.1 46.0 56.5 52.4 51.9 56.9 55.0 48.6 55.1 66.2 25-29.99 19.4 23.9 17.2 19.2 15.8 24.9 16.3 38.3 17.7 14.3 30-34.99 7.1 11.4 5.1 7.8 6.1 7.2 4.9 9.2 4.9 2.1 35-39.99 1.8 3.2 1.1 2.1 1.6 1.4 1.3 0.8 0.8 0.4 >=40 0.6 1.1 0.3 0.7 0.5 0.5 0.4 0.1 0.1 0.0 N 36225 15301 20924 17262 8095 4258 2770 887 1826 1127

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 5.18: Night Blindness of Mother (Last and Current Pregnancy) (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Night blindness Last pregnancy

Yes 12.7 11.7 13.2 11.7 21.3 4.1 12.5 10.5 14.5 3.7 No 82.1 84.6 81.0 86.1 76.8 76.7 82.9 77.0 84.4 94.9 Don't know 5.2 3.7 5.8 2.2 1.9 19.2 4.5 12.5 1.2 1.4 N 20480 8217 12263 8997 4474 2739 1700 831 1145 594 Night blindness Current pregnancy

Yes 15.6 14.3 16.1 12.6 22.7 9.7 14.1 35.4 16.8 6.5 No 81.5 82.6 81.1 86.2 76.2 68.9 84.1 62.3 79.1 92.7 Don't know 2.9 3.1 2.8 1.2 1.1 21.4 1.8 2.3 4.1 0.8 N 2247 835 1412 1157 617 173 98 43 113 46

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

86

Biochemical assessments data from FATA has not been presented due to low number of specimens collected (Table 5.17 – 5.33).

Table 5.19: Hemoglobin Level - Non Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe deficiency (<7 gm/dL) 1.5 0.8 1.8 1.1 2.8 0.7 1.7 0.4 0.6

Moderate deficiency (7 - 11.99 48.9 48.5 49.1 47.5 59.2 34.9 47.2 40.6 22.7

Normalgm/dL) (>= 12 gm/dL) 49.6 50.7 49.1 51.4 38.0 64.4 51.0 59.0 76.7

N 10787 4415 6372 5438 2468 792 881 720 337

Table 5.20: Hemoglobin Level - Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe deficiency (<7 gm/dL) 2.3 1.6 2.6 1.0 5.3 2.0 1.4 0.0 0.0

Moderate deficiency (7 - 10.99 48.7 48.7 48.7 48.3 54.4 28.2 48.3 43.0 33.6

Normalgm/dL) (>= 11 gm/dL) 49.0 49.7 48.7 50.6 40.3 69.8 50.3 57.0 66.4

N 1363 497 866 731 397 67 63 77 25

Table 5.21: Ferritin Level - Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Low Ferritin (<12 ng/mL) 28.0 27.6 28.2 28.7 31.9 16.3 22.9 25.8 17.4

Normal (>=12 ng/mL) 72.0 72.4 71.8 71.3 68.1 83.7 77.1 74.2 82.6

N 9143 3533 5610 4649 2279 741 590 471 353

87

Table 5.22: Ferritin Level - Non Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Low Ferritin (<12 ng/mL) 26.8 26.8 26.8 27.3 31.5 15.6 21.8 25.2 14.9

Normal (>=12 ng/mL) 73.2 73.2 73.2 72.7 68.5 84.4 78.2 74.8 85.1

N 8092 3158 4934 4080 1955 696 547 427 327

Table 5.23: Ferritin Level - Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Low Ferritin (<12 ng/mL) 37.0 34.1 38.1 39.2 34.5 27.0 37.1 31.6 45.7

Normal (>=12 ng/mL) 63.0 65.9 61.9 60.8 65.5 73.0 62.9 68.4 54.3

N 1051 375 676 569 324 45 43 44 26

88

Table 5.24: Vitamin A Deficiency - Mothers

(Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Severe (<0.35 µmol/L) 17.2 11.5 19.6 18.4 10.5 32.4 21.6 1.1 8.7

Mild (0.35 - 0.70 µmol/L) 25.3 24.2 25.8 23.4 26.6 34.0 33.3 14.5 30.4

Non deficient (>0.70 µmol/L) 57.5 64.3 54.6 58.2 63.0 33.6 45.0 84.5 60.8

N 9052 3554 5498 4673 2260 633 623 471 339

Table 5.25: Vitamin A Deficiency - Non-Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe (<0.35 µmol/L) 17.0 10.9 19.6 18.2 9.7 32.2 21.3 0.8 7.8

Mild (0.35 - 0.70 µmol/L) 25.1 24.0 25.5 23.3 25.7 33.5 33.2 12.9 30.9

Non deficient (>0.70 µmol/L) 58.0 65.1 54.9 58.5 64.5 34.2 45.5 86.3 61.2

N 8001 3166 4835 4096 1943 593 577 424 315

Table 5.26: Vitamin A Deficiency - Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB

Severe (<0.35 µmol/L) 18.7 16.1 19.7 19.6 15.1 35.5 26.1 3.3 20.0

Mild (0.35 - 0.70 µmol/L) 27.3 25.4 28.1 24.1 31.6 40.7 34.6 28.9 24.1

Non deficient (>0.70 µmol/L) 54.0 58.4 52.2 56.4 53.3 23.8 39.3 67.8 55.9

N 1051 388 663 577 317 40 46 47 24

89

Table 5.27: Zinc Deficiency - Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Deficient (<60 µg/dL) 42.1 39.2 43.3 41.1 39.3 48.6 43.7 67.9 62.9

Non-Deficient (60 - 150 µg/dL) 57.9 60.8 56.7 58.9 60.7 51.4 56.3 32.1 37.1

N 8453 3365 5088 4266 2222 468 614 470 353

Table 5.28: Zinc Deficiency - Non Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Deficient (<60 µg/dL) 41.3 38.2 42.7 40.2 38.5 48.3 43.7 64.8 63.7

Non-Deficient (60 - 150 µg/dL) 58.7 61.8 57.3 59.8 61.5 51.7 56.3 35.2 36.3

N 7459 3003 4456 3740 1903 437 569 423 327

Table 5.29: Zinc Deficiency - Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Deficient (<60 µg/dL) 47.6 47.4 47.7 47.3 44.5 52.6 43.6 95.8 54.4

Non-Deficient (60 - 150 µg/dL) 52.4 52.6 52.3 52.7 55.5 47.4 56.4 4.2 45.6

N 994 362 632 526 319 31 45 47 26

90

Table 5.30: Vitamin D Deficiency - Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe Deficiency (<8.0 ng/mL) 23.2 33.2 19.1 24.9 24.2 14.3 16.6 22.4 21.5

Deficiency (8.0 - 20.0 ng/mL) 43.8 39.4 45.7 42.1 46.4 46.9 37.2 50.9 59.0

Desirable (>20.0 - 30.0 ng/mL) 18.6 14.8 20.2 17.8 16.8 25.2 25.7 19.1 11.1

Sufficient (>30.0 ng/mL) 14.4 12.6 15.1 15.2 12.6 13.6 20.5 7.6 8.4

N 9711 3829 5882 5095 2326 843 609 476 304

Table 5.31: Vitamin D Deficiency - Non-Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe Deficiency (<8.0 ng/mL) 23.0 33.2 18.6 24.4 24.7 14.0 16.3 22.5 19.2

Deficiency (8.0 - 20.0 ng/mL) 43.8 39.3 45.7 42.0 46.5 47.0 38.3 50.8 61.7

Desirable (>20.0 - 30.0 ng/mL) 18.7 14.7 20.5 17.8 16.9 25.4 25.6 19.9 10.1

Sufficient (>30.0 ng/mL) 14.5 12.8 15.2 15.8 11.8 13.7 19.8 6.8 9.0

N 8578 3412 5166 4464 1995 788 563 430 280

Table 5.32: Vitamin D Deficiency - Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe Deficiency (<8.0 ng/mL) 25.3 33.8 22.1 28.2 20.8 17.9 20.5 21.5 44.4

Deficiency (8.0 - 20.0 ng/mL) 43.6 39.7 45.1 42.9 46.1 45.9 23.1 51.9 31.7

Desirable (>20.0 - 30.0 ng/mL) 17.6 15.3 18.4 17.6 16.1 23.3 26.7 11.2 21.1

Sufficient (>30.0 ng/mL) 13.5 11.2 14.4 11.3 17.0 13.0 29.7 15.5 2.8

N 1133 417 716 631 331 55 46 46 24

91

Table 5.33: Calcium Deficiency - Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Hypocalcaemia (<8.4 mg/dL) 52.9 52.9 53.0 53.1 45.4 73.6 63.4 8.7 46.7

Normocalcaemia (8.4 - 10.2 mg/dL) 38.3 38.5 38.2 35.9 48.1 20.6 35.5 84.0 52.3

Hypercalcaemia (>10.2 mg/dL) 8.8 8.7 8.8 11.0 6.5 5.8 1.1 7.3 1.1

N 9672 3793 5879 4940 2263 983 598 485 350

Table 5.34: Calcium Deficiency - Non Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Hypocalcaemia (<8.4 mg/dL) 52.1 51.8 52.3 51.7 44.6 74.0 63.1 8.2 44.5

Normocalcaemia (8.4 - 10.2 mg/dL) 39.0 39.4 38.8 36.9 49.2 20.1 35.9 83.7 54.4

Hypercalcaemia (>10.2 mg/dL) 8.9 8.8 9.0 11.4 6.2 6.0 1.0 8.1 1.1

N 8549 3377 5172 4324 1935 922 554 437 324

Table 5.35: Calcium Deficiency - Pregnant Mothers (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Hypocalcaemia (<8.4 mg/dL) 58.9 61.5 57.9 63.2 50.3 67.6 67.4 13.3 71.3

Normocalcaemia (8.4 - 10.2 mg/dL) 33.5 30.8 34.6 28.5 41.6 29.4 30.4 86.2 28.7

Hypercalcaemia (>10.2 mg/dL) 7.6 7.7 7.6 8.3 8.1 2.9 2.2 0.5 0.0

N 1123 416 707 616 328 61 44 48 26

92

Table 6.1: Households with Children Under 5 Years (Percent) Residence Province / Region Number of Children Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB None 25.6 32.5 22.4 27.5 28.0 27.5 14.7 0.8 0.2 3.8

1 40.1 37.1 41.5 36.0 38.0 46.4 46.3 78.2 54.6 47.7

2 26.2 23.1 27.6 26.9 25.7 23.4 27.9 18.1 36.7 34.5

3 6.4 5.5 6.8 7.2 7.0 2.6 7.9 2.8 6.5 9.1

4+ 1.8 1.8 1.7 2.3 1.3 0.1 3.2 0.1 1.9 4.9

N 27963 11496 16467 13188 6282 3626 1996 900 1303 668

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 6.2: Sex and Age Distribution of Children Under 5 Years of age (Percent) Residence Province / Region Characteristics Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Sex

Male 51.1 50.8 51.2 51.2 50.0 51.3 50.4 57.9 50.1 51.6

Female 48.9 49.2 48.8 48.8 50.0 48.7 49.6 42.1 49.9 48.4

Age (month)

< 6 months 8.5 9.1 8.2 8.9 8.3 7.9 7.8 4.0 9.5 8.5

6-11 months 10.1 10.3 10.0 10.9 10.8 7.2 9.9 1.2 11.0 10.0

12-23 months 16.1 18.7 15.1 18.2 15.0 10.7 14.9 6.8 19.1 17.5

24-35 months 20.1 20.3 20.1 20.3 19.6 21.7 18.2 18.9 19.5 18.9

36-47 months 20.9 20.0 21.2 19.8 20.5 23.1 21.5 34.8 19.6 19.4

48-59 months 24.3 21.6 25.4 21.8 25.8 29.4 27.7 34.3 21.3 25.7

N 34073 13162 20911 15990 7396 3582 2833 1102 2068 1102

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

93

Table 6.3: Anthropometry of All Children under 5 years (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Height for Age – Stunted Severe Stunting (-6 to -3) 21.9 16.4 24.0 17.9 27.7 24.5 31.1 33.8 11.8 26.0 Moderate Stunting (-2.99 to -2) 21.8 20.5 22.3 21.3 22.1 23.3 21.1 23.8 19.9 24.6 Mild Stunting (-1.99 to -1) 24.4 26.4 23.5 26.4 22.6 19.7 19.1 21.1 30.0 24.5 Normal (>-1 to +6) 32.0 36.7 30.2 34.3 27.6 32.5 28.7 21.3 38.3 24.9 N 28825 11090 17735 13378 6605 2962 2142 805 1946 987 Weight for Height – Wasted Severe Wasting (-5 to -3) 5.8 4.7 6.3 4.8 6.6 8.7 7.0 5.8 6.9 2.7 Moderate Wasting (-2.99 to -2) 9.3 8.0 9.8 8.9 10.9 8.6 9.1 4.2 10.7 4.1 Mild Wasting (-1.99 to -1) 22.1 22.7 21.9 23.4 26.1 12.8 18.5 6.3 23.8 12.7 Normal (>-1 to +5) 62.8 64.7 62.0 62.9 56.4 69.9 65.5 83.7 58.5 80.5 N 28312 10919 17393 13210 6553 2826 2102 717 1920 984 Weight for Age - Under weight Severely under-Weight (-6 to -3) 11.6 8.4 12.8 9.9 16.3 10.1 17.8 7.2 6.1 8.1 Moderate Under-Weight (-2.99 to 19.9 18.2 20.5 19.9 24.2 14.0 21.8 6.5 19.7 18.1 -2)Mild Under-Weight (-1.99 to 0) 29.7 30.8 29.4 31.9 30.7 23.6 24.8 11.7 34.1 33.0 Normal (>0 to +5) 38.8 42.5 37.3 38.3 28.8 52.4 35.6 74.7 40.1 40.9 N 29525 11257 18268 13532 6707 3113 2277 941 1956 999

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

94

Table 6.4: Factors Associated with Stunting (<-2 SD) (Percent) Stunted Characteristics N Normal Severe Moderate Mild Age

< 6 months 2173 11.0 12.8 20.5 55.7 6-11 months 2886 14.8 15.5 22.6 47.1 12-23 months 4172 24.7 23.2 25.3 26.8 24-35 months 3874 30.1 24.6 22.3 23.0 36-47 months 2935 25.2 27.1 22.4 25.3 48-59 months 3042 17.8 20.6 26.6 35.0

Sex

Male 9949 23.9 20.3 23.8 31.9 Female 9133 19.4 22.4 23.1 35.1

Age Groups

0-23 months 9231 18.3 18.3 23.3 40.0 24-59 months 9851 24.9 24.1 23.6 27.4

Mother's Education

Illiterate 10726 26.6 21.6 21.7 30.1 1-5 2347 19.1 22.6 26.3 31.9 6-8 1625 17.1 26.8 24.2 31.9 9-10 2044 11.5 19.4 26.9 42.2 Above Matric. 1817 8.5 13.9 26.2 51.4

Diarrhea in last two weeks

Yes 4233 21.6 21.7 24.5 32.1

Wealth Quintiles

Quintile I 4121 31.4 22.6 19.3 26.7 Quintile II 4033 25.8 23.9 22.3 28.0 Quintile III 3866 20.5 21.9 24.9 32.7 Quintile IV 3697 15.9 20.7 25.9 37.6 Quintile V 3365 10.7 15.8 26.4 47.1

95

Table 6.5: Factors Associated with Wasting (<-2SD) (Percent) Wasted Characteristics N Normal Severe Moderate Mild Age

< 6 months 2045 12.5 13.8 18.0 55.7 6-11 months 2828 9.8 13.4 22.1 54.6 12-23 months 4161 6.3 9.5 21.3 62.9 24-35 months 3824 6.1 8.4 20.8 64.6 36-47 months 2869 4.3 6.9 20.4 68.5 48-59 months 2918 4.8 9.1 23.8 62.3

Sex

Male 9667 7.2 10.5 20.9 61.4 Female 8978 6.6 9.2 21.6 62.6

Age Groups

0-23 months 9034 8.8 11.7 20.8 58.7 24-59 months 9611 5.2 8.2 21.6 65.1

Mother's Education

Illiterate 10426 8.1 11.0 21.4 59.5 1-5 2318 5.8 9.1 22.8 62.2 6-8 1601 4.9 8.6 20.2 66.3 9-10 2007 6.4 7.9 21.0 64.8 Above Matric. 1790 4.0 7.4 20.2 68.4

Diarrhea in last two weeks

Yes 4179 7.3 11.9 22.5 58.3

Wealth Quintiles

Quintile I 4013 9.5 12.3 22.5 55.7 Quintile II 3911 7.0 9.6 18.1 65.2 Quintile III 3775 6.7 9.4 22.3 61.6 Quintile IV 3633 5.8 10.1 21.8 62.3 Quintile V 3313 4.7 7.0 21.6 66.7

96

Table 6.6: Factors Associated with Under Weight (<-2 SD) (Percent) Under Weight Characteristics N Normal Severe Moderate Mild Age

< 6 months 2233 12.6 16.4 25.8 45.2 6-11 months 2966 14.2 19.1 26.2 40.5 12-23 months 4308 12.7 19.4 29.5 38.4 24-35 months 3992 14.6 20.7 29.2 35.6 36-47 months 3023 10.4 18.2 27.1 44.3 48-59 months 3099 8.3 18.8 29.9 43.0

Sex

Male 10254 13.2 19.3 27.7 39.8 Female 9367 11.2 18.7 28.7 41.4

Age Groups

0-23 months 9507 13.1 18.6 27.6 40.7 24-59 months 10114 11.4 19.4 28.8 40.4

Mother's Education

Illiterate 11127 15.5 21.0 27.8 35.7 1-5 2381 9.8 21.2 31.0 38.0 6-8 1661 8.0 15.8 28.7 47.5 9-10 2068 6.5 14.4 31.4 47.7 Above Matric. 1841 5.0 11.7 25.0 58.3

Diarrhea in last two weeks

Yes 4305 15.3 21.4 30.1 33.1

Wealth Quintile

Quintile I 4263 20.5 23.5 26.3 29.8 Quintile II 4198 12.5 18.5 27.1 42.0 Quintile III 3992 11.2 19.7 29.6 39.5 Quintile IV 3754 8.0 19.1 31.4 41.5 Quintile V 3414 6.2 12.2 27.0 54.6

97

Biochemical assessments data from FATA has not been presented due to low number of specimens collected (Table 6.7 – 6.11).

Table 6.7: Hemoglobin Level - Index Child (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe deficiency (<7 gm/dL) 5.0 3.6 5.5 4.2 4.9 6.8 8.3 1.8 0.6

Moderate deficiency (7 - 10.99 56.9 59.3 55.9 56.1 67.6 40.5 48.5 44.2 40.4

Normalgm/dL) (>= 11 gm/dL) 38.1 37.0 38.6 39.7 27.5 52.7 43.2 54.1 59.1

N 11786 4731 7055 6116 2851 794 752 800 363

Table 6.8: Ferritin Level - Index Child (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Low Ferritin (<12 ng/mL) 43.8 46.1 42.9 48.6 40.6 26.4 32.5 43.5 36.2

Normal (>=12 ng/mL) 56.2 53.9 57.1 51.4 59.4 73.6 67.5 56.5 63.8

N 8575 3297 5278 4449 2122 661 459 484 344

Table 6.9: Vitamin A Deficiency - Index Child (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe (<0.35 µmol/L) 20.9 14.6 23.5 19.1 18.8 33.9 38.0 7.1 27.2

Mild (0.35 - 0.70 µmol/L) 33.1 32.3 33.4 31.9 34.5 34.6 35.5 36.7 44.6

Non deficient (>0.70 µmol/L) 46.0 53.1 43.1 48.9 46.8 31.5 26.5 56.2 28.2

N 8634 3303 5331 4437 2204 678 438 491 333

Table 6.10: Zinc Deficiency - Index Child (Percent)

98

Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Deficient (<60 µg/dL) 39.2 39.3 39.1 38.4 38.6 45.4 39.5 47.2 32.6

Non-Deficient (>=60 µg/dL) 60.8 60.7 60.9 61.6 61.4 54.6 60.5 52.8 67.4

N 8503 3274 5229 4358 2187 690 414 452 345

Table 6.11: Vitamin D Deficiency - Index Child (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB Severe Deficiency (<8.0 ng/mL) 9.2 14 7.2 9.3 10.7 5.9 9.1 4.1 4.1

Deficiency (8.0 - 20.0 ng/mL) 30.8 31.9 30.4 31.0 32.6 23.0 34.3 30.5 32.9

Desirable (>20.0 - 30.0 ng/mL) 27.3 22.2 29.4 27.2 25.4 31.4 23.6 35.3 36.0

Sufficient (>30.0 ng/mL) 32.7 31.9 33.0 32.6 31.3 39.6 33.1 30.0 26.9

N 8608 3324 5284 4337 2203 709 539 467 297

Table 6.13: Clinical Examination Children (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Clinical Examination

Edema 0.4 0.2 0.4 0.2 0.1 1.3 1.2 0.1 0.2 0.0

Jaundice 0.4 0.4 0.4 0.4 0.4 0.4 0.9 0.7 0.1 0.0

Pallor / Anemia 22.8 17.6 24.9 27.4 28.9 3.4 13.1 4.5 31.7 15.0

Goiter 0.2 0.1 0.3 0.3 0.2 0.2 0.2 0.4 0.2 0.0

Bitot's Spot 0.2 0.1 0.3 0.0 0.1 0.1 0.8 3.8 0.1 0.0

N 20537 7929 12608 9174 4409 2458 1677 888 1292 639

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 6.16: Morbidities (Index Child) (Percent)

99

Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB ARI by Information

Pneumonia 5.4 6.4 5.0 5.1 9.6 1.7 2.8 2.7 5.2 4.1

Severe Pneumonia 1.4 1.5 1.3 1.4 2.1 0.4 1.0 0.6 0.2 2.3

Only cough 15.9 18.3 15.0 19.0 18.1 4.4 11.7 2.5 26.0 13.4

N 20435 7899 12536 9127 4401 2431 1673 875 1291 637

ARI by Observation

Pneumonia 4.9 5.3 4.8 3.5 8.9 3.5 4.4 7.9 3.2 1.5

Severe Pneumonia 1.0 1.1 1.0 1.0 2.0 0.1 0.4 0.7 0.2 0.8

Only cough 12.1 14.6 11.2 12.7 17.2 4.3 7.7 4.6 18.2 9.0

N 20278 7853 12425 9090 4392 2427 1670 773 1291 635

Diarrhea in Past 2 Weeks 22.3 23.2 22.0 28.5 23.4 4.3 12.9 6.4 26.2 28.5

N 20383 7883 12500 9118 4390 2428 1663 861 1287 636

Current Diarrhea 12.0 11.6 12.1 15.6 11.7 2.6 8.0 2.4 11.2 19.2

N 20280 7866 12414 9110 4391 2423 1660 770 1289 637

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

100

Table 7.1: Initiation of Breast Feeding and Practicing Pre-Lacteal Feed (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB How long after birth did you first put to the breast?

Immediately after birth 24.6 21.4 25.9 16.3 32.5 46.1 48.1 31.9 12.4 23.5

Within 1 hour 15.9 17.0 15.5 11.8 18.0 28.2 15.3 47.6 25.9 38.3

1-12 hours 27.6 32.5 25.4 26.3 32.2 22.8 25.5 16.6 35.1 33.2

13-24 hours 0.5 0.8 0.4 0.5 0.5 0.3 0.7 0.1 0.4

> 24 hours 31.4 28.3 32.8 45.1 16.7 2.5 10.4 4.0 26.5 4.6

N 9562 3875 5687 4738 2144 852 735 88 678 327 What was the first thing the child was fed directly after birth?

Honey 41.0 52.6 35.9 54.1 22.5 16.0 28.6 23.5 43.2 4.4

Breast milk 28.2 23.6 30.2 9.0 58.2 61.0 48.7 33.4 23.5 51.7

Water (Plain/Flavored/Sugar 9.5 7.1 10.6 13.0 2.6 5.7 6.5 19.4 6.3 25.0

Added)Fresh Animal Milk 5.5 1.6 7.3 6.6 5.6 0.0 0.2 0.0 11.7 0.6

Commercial Formula/Liquid Milk 3.9 4.5 3.6 3.8 5.5 1.1 1.6 0.8 6.3 1.6

Commercial Ghutti 3.5 3.7 3.4 5.2 1.5 0.3 0.2 3.4 1.6 0.0

Tea 2.0 2.2 1.9 0.6 1.5 10.4 7.0 0.0 0.5 0.0

Gurr (Jaggery) 1.7 0.5 2.2 2.6 0.5 0.0 0.2 0.0 0.0 0.0

Others 4.7 4.4 4.9 5.0 2.0 5.5 7.0 19.6 6.8 16.7

N 9685 3929 5756 4825 2166 819 746 98 705 326

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

101

Table 7.2: Exclusive Breast Feeding (recall of mothers) (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Upto 1 month 45.8 48.5 44.6 31.2 61.4 83.3 76.7 86.1 23.7 49.0 n 9772 3962 5810 4837 2181 857 770 99 697 331

Upto 2 months 30.9 31.4 30.6 20.0 40.9 65.7 50.2 72.5 12.8 33.3 n 9259 3783 5476 4634 2035 791 741 97 648 313

Upto 3 months 25.3 27.0 24.5 16.3 30.4 59.6 45.4 60.8 10.2 30.7 n 8662 3567 5095 4350 1903 732 689 88 614 286

Upto 4 months 20.9 22.1 20.4 12.9 23.5 55.5 42.0 52.2 7.5 25.7 n 8355 3423 4932 4200 1833 698 674 87 590 273

Upto 5 months 16.3 16.1 16.4 9.9 16.3 50.3 33.1 44.2 5.7 17.8 n 7658 3155 4503 3860 1664 638 606 82 553 255

Upto 6 months 12.9 12.7 13.0 7.7 9.6 47.0 26.8 42.0 4.3 14.5 n 7349 3017 4332 3704 1596 609 595 82 526 237 * Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

102

Table 7.3: IYCF Indicators (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Predominant Breastfeeding under 6 63.5 57.5 66.4 56.9 67.3 87.1 62.1 35.6 61.7 64.7 months N 2299 924 1375 1083 587 252 158 6 128 85

Predominant Breastfeeding under 4 69.8 64.3 72.4 63.0 75.4 89.4 72.2 48.3 63.3 79.2 months N 1391 556 835 647 351 164 89 5 86 49

Continued Breast Feeding 12-15 77.3 72.3 79.6 73.3 84.4 87.4 72.3 43.4 74.5 91.9 months N 1616 666 950 731 375 179 140 30 103 58

Introduction of Semi-Solid (6-8 51.3 68.4 44.7 49.2 62.6 35.3 48.6 55.2 35.7 51.3 months) N 1591 620 971 780 402 148 130 93 38 1591

Minimum Dietary Diversity (6-23 3.0 5.6 1.9 2.6 3.2 2.7 2.1 23.6 6.9 5.1 months) N 6909 2800 4109 3431 1621 604 543 59 429 222

Minimum Meal Frequency (6-23 56.4 65.4 52.4 59.4 54.1 45.0 53.3 68.8 60.7 30.4 months) N 6909 2800 4109 3431 1621 604 543 59 429 222

Minimum Acceptable Diet (6-23 7.3 11.2 5.6 7.6 5.8 5.6 5.1 36.6 15.1 3.9 months) N 6909 2800 4109 3431 1621 604 543 59 429 222

Continued Breastfeeding at 2 years 54.3 50.4 56.5 50.9 66.8 58.3 42.9 46.3 48.1 62.8

N 753 351 402 433 131 55 49 6 52 27

Age-appropriate Breastfeeding 63.6 62.7 64.0 60.5 72.4 63.5 54.3 40.0 65.9 75.3 Children (0-23 months) N 9083 3665 5418 4457 2179 842 697 65 548 295

` * Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

103

Table 8.1: Proportion of children below 2 years consumed food items of the listed food groups (based on 24 hour recall) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Breast Milk 80.9 77 82.6 77.6 86.9 90.1 73.9 46.8 79.6 92.2

Grains, roots and tubers 58.2 63.6 55.7 57.6 65.1 41.7 59.6 86.8 59.5 52.4

Legumes and nuts 5.3 7.1 4.5 4.2 7.5 5.4 6.2 6.2 6.5 5.2

Dairy Products(milk, yogurt, cheese) 48.2 51.9 46.5 57.7 38.2 22.2 32.6 62.7 58.2 42.1

Flesh foods (meat, fish, poultry and 2.7 3.4 2.4 2.3 2.3 1.7 5.1 30.1 5.6 3.1

Eggsliver/organ meats) 5.8 10 3.9 4.8 5.1 11.8 3.4 13.8 9.6 15.1

Vitamin -A rich fruits and Vegetables 1.7 1.9 1.5 1.9 0.9 1 1.3 11.3 2.4 7.6

Other fruits and Vegetables 9.4 13.3 7.6 8.5 8.3 11.2 11.4 32.3 20 8.4

N 9083 3665 5418 4457 2179 842 697 65 548 295

* Data from FATA are not representative due to high non - response rate and must be interpreted with caution.

Table 8.2: Average Frequency of daily intake of food groups (0-23 months children) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Breast Milk 7.4 7.0 7.5 6.3 10.0 8.3 6.6 3.5 6.2 5.9

Grains, roots and tubers 1.3 1.4 1.2 1.2 1.5 0.8 1.3 1.5 1.4 1.1

Legumes and nuts 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.1 0.0

Dairy Products (milk, yogurt, cheese) 1.5 1.7 1.4 1.9 1.0 0.6 0.9 0.8 1.9 0.9

Flesh foods (meat, fish, poultry and 0.1 0.1 0.0 0.1 0.1 0.0 0.2 0.1 0.1 0.1

Eggsliver/organ meats) 0.1 0.2 0.1 0.1 0.1 0.2 0.1 0.3 0.1 0.2

Vitamin A rich fruits and vegetables 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.1

Other fruits and vegetables 0.3 0.4 0.2 0.3 0.3 0.2 0.2 0.5 0.5 0.2

N 9019 3647 5372 4441 2168 841 680 55 548 286

* Data from FATA are not representative due to high non -response rate and must be interpreted with caution.

104

Table 8.3 Average Frequency of daily intake of food groups (0-24 months children) 6-11 12-23 < 6 months months months Breast Milk 10.39 8.31 5.10 Grains, roots and tubers 0.11 1.02 2.06 Legumes and nuts 0.01 0.05 0.03 Dairy Products 0.95 1.41 1.84 (milk, yogurt, cheese) Flesh foods (meat, fish, poultry and liver/ 0.00 0.03 0.11 organ meats) Eggs 0.01 0.08 0.20 Vitamin A rich fruits and vegetables 0.00 0.01 0.06 Other fruits and vegetables 0.02 0.18 0.49 N 2150 2804 4065

Table 8.4: Proportion of mothers of children below 2 years who consumed food items of the listed food groups (based on 24 hour recall) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Grains (Wheat/Rice) 99.5 99.6 99.4 99.6 99.9 99.5 99.9 94.4 99.8 99.6

Tuber & Roots 29.2 25.7 30.7 26.8 41.5 21.5 31.1 12.1 27 11.9

Legumes and nuts 29.8 34.9 27.7 32.1 27 27.5 32.4 25.8 37.5 23.2

Dairy Products(milk, yogurt, cheese) 41.6 39.2 42.7 50.3 40.2 24.2 28.5 48.8 32.8 37.4

Flesh foods (meat, fish, poultry and 30.6 39.4 26.8 28.7 28 33.2 39.6 47.8 31.4 16.5

Eggsliver/organ meats) 10.4 16.3 7.8 9.5 7.2 17.4 8 13.1 10.6 10.4

Vitamin -A rich fruits and Vegetables 13.5 14.5 13.1 12.9 10.2 16.9 13.8 21.6 15.9 52.8

Other fruits and Vegetables 51.4 52.8 50.7 59.3 37.3 51.3 49.9 46.7 60.8 52.4

N 19808 7816 11992 8005 5028 3042 1608 891 823 411

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

105

Table 8.5: Average Frequency of daily intake of food groups (Mothers of children)

Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

Grains, roots and tubers 3.2 3.1 3.2 3.2 3 3.4 2.9 3.1 3.5 3.7

Legumes and nuts 0 0.1 0 0 0 0.1 0 0.1 0 0

Dairy Products(milk, yogurt, cheese) 1.1 1 1.1 1 0.8 1.5 0.8 1.8 0.4 0.5

Flesh foods (meat, fish, poultry and liver/organ 0.3 0.4 0.3 0.3 0.3 0.3 0.5 0.4 0.3 0.4 meats) Eggs 0.3 0.4 0.3 0.3 0.2 0.6 0.3 0.6 0.2 0.3

Vitamin A rich fruits and vegetables 0.3 0.2 0.3 0.2 0.3 0.5 0.3 0.5 0.2 0.9

Other fruits and vegetables 0.9 1 0.8 0.9 0.7 0.9 0.8 1 1 1.1

N 19575 7805 11770 7995 5014 2940 1623 771 821 411

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

106

Table 9.1: Elderly Persons by Gender (Percent) Residence Province / Region Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB Gender

Male 30.4 28.6 31.2 30.6 28.3 29.0 27.3 80.4 32.2 39.0

Female 69.6 71.4 68.8 69.4 71.7 71.0 72.7 19.6 67.8 61.0

N 7612 3135 4477 4289 1118 1053 417 83 392 260

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

Table 9.2: Age distribution of Elderly Persons (Percent) Residence Province / Region Age Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

50-59 years 42.4 46.3 40.6 38.0 43.4 57.9 51.2 86.4 34.5 40.8

60-69 years 35.2 34.4 35.5 36.2 38.2 28.8 32.7 9.3 37.2 36.4

70-79 years 15.2 13.4 16.0 17.4 12.9 9.5 10.3 4.3 17.4 12.7

80+ years 7.3 5.9 7.9 8.4 5.6 3.9 5.8 0.0 10.9 10.1

N 7612 3135 4477 4289 1118 1053 417 83 392 260

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

107

Table 9.3: Body Mass Index of Elderly Persons (Percent) Residence Province / Region Age Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB

<16 4.7 2.5 5.7 5.1 5.7 2.4 4.7 0.0 5.4 2.3

16-16.99 3.4 1.6 4.2 3.6 4.0 1.2 5.7 0.0 5.7 1.6 17-18.49 7.7 4.0 9.4 8.4 7.7 3.9 9.2 0.0 9.9 11.9 18.5-24.99 46.1 37.5 49.8 46.3 46.2 42.8 48.2 19.3 51.9 61.6 25-29.99 24.2 31.4 21.1 23.8 22.1 30.4 19.4 47.4 19.1 18.3 30-34.99 10.1 16.2 7.4 9.2 11.2 13.9 8.8 27.4 5.9 3.3

35-39.99 2.8 4.8 1.9 2.6 2.3 4.5 1.7 5.9 1.8 0.3

>=40 1.0 2.0 0.6 1.1 0.8 0.9 2.4 0.0 0.1 0.7

N 6700 2717 3983 3776 1048 924 294 30 378 250

* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.

108

SAMPLE DESIGN &SAMPLING WEIGHT

SAMPLE ESTIMATION PROCEDURE

ESTIMATION PROCEDURE ADOPTED FOR NNS 2011

NOTATIONS:

Nh = Total number of Primary Sampling Units (PSUs) in the hth stratum ofBalochistan province.

nh = Total number of sample PSUs in the hth stratum of Balochistanprovince.

Mhi = Total number of Secondary Sampling Units (SSUs) in the ith samplePSU of hth stratum of Balochistan province.

mhi = Number of sample SSUs in the ith sample PSU of hth stratum ofBalochistan province.

Phi = Assigned probability of selection of ith PSU of the hth stratum ofBalochistan province.

yhij = Value of any characteristic y of jth SSU within ith PSU of hth stratumof Balochistan province.

xhij = Value of any characteristic x of jth SSU within ith PSU of hth stratum

109

(i): ESTIMATION FORMULAE FOR TOTALS AND THEIR VARIANCES

L N =  N h h=1

L n =  nh h=1

nh 1 Yhi Yh =  p nh i=1 hi

OR

For X, another variable of interest, we have

nh mhi 1 1 M hi Yh = yhij  p  nh i=1 hi mhi j=1

L L nh   1 Yhi Y = Yh =    p h=1 h=1 nh i=1 hi

1 nh  1 nh 1 mhi  X hi M hi X h =  =   xhij nh i=1 Phi nh i=1 Phi mhi j=1

L L nh   1 X hi X = X h =    p h=1 h=1 nh i=1 hi

110

Y R =  X

 nh yˆ   ( hi )2  L L nh ˆ 2  ˆ 1 2 1  Y hi i1 Phi  v(Y )   s ht    2  n n (n 1) P hi n  h1 h h1 h h  i1 h   

(ii): FORMULA FOR RATIO ESTIMATES

Y r = X where Y^ and X^ can be estimated by equations under item (i) given above.

L L nh 2 - 1 1 2 1 1 M hi  M hi mhi 2 Rel V(r)= s hb + s hw  2  2   2 X h=1 nh x h=1 nh i=1 p hi mhi M hi

111

ALLOCATION PLAN FOR NATIONAL NUTRITION SURVEY 2010-11(AGHA KHAN UNIVERSITY)

NO. OF SAMPLE PSUS

LARGE SIZE CITIES Other Total Urban SL.NO. STRATUM LOW MIDDLE HIGH TOTAL Urban Urban Rural +Rural

1 2 3 4 5 6 7 8 9 10

PUNJAB 41 92 28 161 146 307 375 682 1 ISLAMABAD 4 10 6 20 0 20 10 30 1.RAWALPINDI DIVISION 3 8 3 14 15 29 31 60 1 Attock 4 4 7 2 Rawalpindi 3 8 3 14 5 19 11 3 Jhelum 4 4 6 4 Chakwal 2 2 7

2.SARGODHA DIVISION 3 3 0 6 13 19 32 51 1 Sargodha 3 3 0 6 4 10 13 2 Bhakkar 3 3 6 3 Khushab 3 3 6 4 Mianwali 3 3 7

3.FAISALABAD DIVISION 10 14 4 28 19 47 50 97 1 Faisalabad 10 14 4 28 5 33 22 2 Jhang 6 6 11 3 T.T.Singh 4 4 10 4 Chiniot 4 4 7

4.GUJRANWALA DIVISION 6 11 5 22 24 46 57 103 112

1 Gujranwala 4 8 3 15 5 20 12 2 Gujrat 6 6 11 3 Sialkot 2 3 2 7 4 11 13 4 Hafiza Abad 3 3 6 5 Mandibahauudn 3 3 7 6 Narowal 3 3 8

5.LAHORE DIVISION 7 34 5 46 19 65 38 103 1 Lahore 7 34 5 46 2 51 8 2 Kasur 6 6 12 3 Sheikhupura 8 8 10 4 Nankana 3 3 8

6.MULTAN DIVISION 5 7 3 15 14 29 45 74 1 Vehari 4 4 13 2 Multan 5 7 3 15 2 17 13 3 Khanewal 5 5 12 4 Lodhran 3 3 7

7.DERA GHAZI KHAN DIVISION 12 12 40 52 1 D.G.Khan 4 4 9 2 Rajanpur 4 4 7 3 Leiah 4 4 7 4 Muzaffargarh 17

8.BAHAWALPUR DIVISION 3 5 2 10 16 26 42 68 1 Bahawalpur 3 5 2 10 4 14 12 2 Bahawalnagar 5 5 12 3 R. Y. Khan 7 7 18

113

9.SAHIWAL DIVISION 14 14 30 44 1 Sahiwal 4 4 10 2 Pakpattan 4 4 8 3 Okara 6 6 12

S I N D H 33 64 15 112 45 157 166 323

1.SUKKUR DIVISION 3 5 0 8 11 19 40 59 1 Khairpur 3 3 10 2 Sukkur 3 5 0 8 2 10 5 3 Nawab Shah 2 2 8 4 NesheroFeroz 2 2 8 5 Ghotki 2 2 9

2.LARKANA DIVISION 11 11 34 45 1 Jacobabad 2 2 6 2 Kashmore 2 2 6 3 Shikarpur 2 2 7 4 Larkana 3 3 7 5 ShahdadKot 2 2 8

3.HYDERABAD DIVISION 4 8 3 15 11 26 53 79 1 Dadu 2 2 8 2 Jamshoro 1 1 5 3 Hyderabad 4 8 3 15 1 16 6 4 Matiari 1 1 5 5 TandoAllahyar 1 1 5 6 Tando Mohammad Khan 1 1 6

114

7 Badin 2 2 8 8 Thatta 2 2 10

4 MIRPUR KHAS DIVISION 12 12 33 45 1 Sanghar 5 5 10 2 MirpurKhas 4 4 8 3 Tharparkar 0 0 8 4 UmerKot 3 3 7

5.KARACHI DIVISION 26 51 12 89 0 89 6 95 1 Karachi South 0 0 0 2 Karachi West 0 0 3 3 Karachi Central 0 0 0 4 Karachi Malir 0 0 3 5 Karachi East 0 0 0

KHYBER/PK 2 13 3 18 49 67 151 218

1.MALAKAND DIVISION 7 7 39 46 1 Swat 2 2 10 2 Upper Dir 0 0 6 3 Lower Dir 2 2 7 4 Chitral 2 2 4 5 Shangla 0 0 4 6 Malakand Agency 1 1 4 7 Bonair 0 0 4

2.PESHAWAR DIVISION 2 13 3 18 9 28 26 54 1 Charsada 4 4 8

115

2 Noshehra 5 5 9 3 Peshawar 2 13 3 18 0 22 9

3.KOHAT DIVISION 8 8 12 20 1 Kohat 3 3 4 2 Karak 3 3 4 3 Hangu 2 2 4

4.D. I. KHAN DIVISION 5 5 10 15 1 Tank 2 2 4 2 D.I.Khan 3 3 6

5.HAZARA DIVISION 7 7 32 39 1 Mansehra 2 2 9 2 Abbottabad 3 3 7 3 Haripur 2 2 6 4 Batagram 0 0 4 5 Kohistan 0 0 6

6.BANNU DIVISION 5 5 11 16 1 Bannu 3 3 6 2 LakkiMarwat 2 2 5

7.MARDAN DIVISION 8 8 21 29 1 Mardan 5 5 11 2 Swabi 3 3 10

BALOCHISTAN 3 6 2 11 33 44 66 110

116

1.QUETTA DIVISION 3 6 2 11 4 15 14 29 1 Quetta 3 6 2 11 4 11 3 2 Pishin 2 1 5 3 Q.Abdullah 1 1 4 4 Chaghi 0 0 1 5 Nushki 1 1 1

2.SIBBI DIVISION 4 4 7 11 1 Sibbi 2 2 1 2 Kohlu Agency 0 0 1 3 DeraBugti 0 0 2 4 Ziarat 1 1 0 5 Harnai 1 1 1

3.KALAT DIVISION 8 8 14 22 1 Kalat 1 1 3 2 Khuzdar 4 4 4 3 Kharan 0 0 1 4 Lasbela 3 3 3 5 Mustung 1 1 2 6 Awaran 0 0 2 7 Washuk 0 1

4.MEKRAN DIVISION 6 6 8 14 1 Turbat 3 3 4 2 Gawadar 3 3 1 3 Panjgur 0 0 3

5. ZHOB DIVISION 6 6 11 17

117

1 Zhob 2 2 2 2 Loralai 2 2 3 3 Barkhan 0 0 1 4 Musakhel 1 1 2 5 QilaSaifullah 1 1 2 6 Sherani 0 1

6.NASIRABAD DIVISION 5 5 12 17 1 Kachhi\Bolan 1 1 3 2 JhalMagsi 0 0 1 3 Jafar Abad 3 3 5 4 Tamboo/Nasirabad. 1 1 3

TOTAL: 79 175 48 302 273 575 758 1333

GILGIT/BALTISTAN 15 15 19 34

1 Baltistan 4 4 4 2 Daimir 2 2 3 3 Gilgit 5 5 9 4 Ghizer 2 2 3 5 Ghanche 2 2 2 6 Astore 0 0 3

A J & K 28 28 38 66

1 Kotli 3 3 5 2 Mirpur 5 5 3 3 Muzaffarabad 5 5 6

118

HattianBala 2 2 3 4 Bhimber 2 2 4 5 Bagh 2 2 4 6 Haveli 2 2 3 6 Rawalakot/Poonch 3 3 4 7 Sudhnoti 2 2 3 8 Neelum 2 2 3

FATA 0 0 67 67 1 Bajaur Agency 0 0 10 2 Khyber Agency 0 0 8 3 Kurram Agency 0 0 7 4 Mohmand Agency 0 0 6 5 North Waziristan 0 0 6 6 Orakzai Agency 0 0 5 7 South Waziristan 0 0 7 8 TA AdjLakkiMarwat 0 0 3 9 TA AdjBannu 0 0 2 11 TA AdjD.I.Khan 0 0 4 12 TA AdjKohat 0 0 3 13 TA Adj Peshawar 0 0 3 15 TA Adj Tank 0 0 3 GRAND TOTAL: 79 175 48 302 316 618 882 1500

119

Residence Province / Region

Pakistan Urban Rural Punjab Sindh KPK Balochistan FATA AJK GilgitBaltistan

Number of Sample Areas

Sampled 1500 618 882 682 323 218 110 67 66 34

Completed 1500 618 882 682 323 218 110 67 66 34

Number of Sample households

Sampled 30000 12360 17640 13640 6460 4360 2200 1340 1320 680

Interviewed / Visited 30000 12360 17640 13640 6460 4360 2200 1340 1320 680

Consent Yes 27963 11496 16467 13188 6282 3626 1996 900 1303 668

Refusals 2037 864 1173 452 178 734 204 440 17 12

Refusal Rate 6.8 7 6.6 3.3 2.8 16.8 9.3 32.8 1.3 1.8

120

SAMPLING WEIGHT

ESTIMATION PROCEDURE

ESTIMATION PROCEDURE ADOPTED FOR NATIONAL NUTRITION SURVEY 2011

NOTATIONS:

Nh = Total number of Primary Sampling Units (PSUs) in the h-th stratum of a province/region.

nh = Total number of sample PSUs in the h-th stratum of a province/region.

Mhi = Total number of Secondary Sampling Units (SSUs) in the i-th sample PSU of h-th stratum of a province/region.

mhi = Number of sample SSUs in the ith sample PSU of h-th stratum of a province/region.

Phi = Assigned probability of selection of ith PSU of the h-th stratum of a province/region.

yhij = Value of any characteristic y of j-th SSU within ith PSU of h-th stratum of a province/region.

xhij = Value of any characteristic x of j-th SSU within i-th PSU of h-th stratum of a province with whose respect proportion is required.

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(i): ESTIMATION FORMULAE FOR TOTALS AND THEIR VARIANCES

L 1 nh 1 mhi N =  M hi  N h Yh =   yhij h=1 nh i=1 phi mhi j=1

L L L n = nh OR 1 nh     Yhi h=1 Y = Yh =   h=1 h=1 nh i=1 phi 1 nh   Yhi Yh =  nh i=1 phi

1 nh  1 nh 1 mhi  X hi M hi X h =  =   xhij nh i=1 Phi nh i=1 Phi mhi j=1

L L 1 nh    X hi X =  X h =   h=1 h=1 nh i=1 phi

Y R =  X

For X, another variable of interest, we have

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 nh y   ( hi ) 2  nh  2  1 2 1  Y hi i1 Phi  v(y ) s ht   h  2 n n (n  1)  P hi n  h h h  i1 h   

 nh y   ( hi ) 2  L L nh  2  1 2 1  Y hi i1 Phi  v(Y)  s ht      2 n n (n  1) P hi n  h1 h h1 h h  i1 h   

(ii): FORMULA FOR RATIO ESTIMATES

Y r =  X

where Y^ and X^ can be estimated by equations under item (i) given above.

L L nh 2 - 1 1 2 1 1 M hi  M hi mhi 2 Rel V(r)= s hb + s hw  2  2   2 X h=1 nh x h=1 nh i=1 p hi mhi M hi

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