ICDS Internship Final Report

Transcription

1 ICDS BIHAR ICDS Internship Final Report Malnutrition in Patna District Andrew R. Bracken MPP Candidate 2013 University of Michigan Gerald R. Ford School of Public Policy 10/8/2012

2 ACKNOWLEDGEMENTS I would like to express my gratitude to all ICDS staff in the State of Bihar for the opportunity to intern in Patna for ten weeks. A special thanks goes to ICDS Director Mr Praveen Kishore for affording me the chance to come to intern for ICDS. Monitoring Officer Ms Abha Prasad helped immensely in understanding ICDS, arranged field visits, and treated me very kindly. Mr Pradeep Joseph helped me focus my research, provided invaluable and insightful feedback, and assisted me with tasks I could not otherwise accomplish. I would like to thank Patna DPO Mr Sudhir Kumar for granting me complete access to any resource and facility I desired in Patna District. I would also like to specially thank the following CDPOs, their Lady Supervisors, and Anganwadi Workers who generously shared their precious time and entertained my every request: Ms Rashmi Chaudari (Fatuha), Ms Anjana Kumari (Masaurhi), Ms Mamta Verma (Dulhin Bazar), Ms Babita Rai (Hajipur Sadar), Ms Madhumita Kumari (Patna Sadar 1), Ms Kanchan Kumari Giri (Patna Sadar 3), and Ms Tarani Kumari (Patna Sadar 4). 1

3 CONTENTS ACKNOWLEDGEMENTS... 1 CONTENTS... 2 ABBREVIATIONS... 3 EXECUTIVE SUMMARY... 4 INTRODUCTION... 7 MALNUTRITION... 7 GROWTH STANDARDS AND MALNUTRITION... 9 DATA COLLECTION DATA ANALYSIS RECOMMENDATIONS CONCLUSION

4 ABBREVIATIONS AC AWC CDC CDPO DPO GHI HIV IA ICDS ISHI LS MIS MGRS NCHS NHS NS SNP THR UNICEF WHO Anthropometric calculator Anganwadi Centre Centers for Disease Control Childhood Development Project Officer District Programme Officer Global Hunger Index Human Immunodeficiency Virus Individual assessment Integrated Child Development Services India State Hunger Index Lady Supervisor Management Information System Multicentre Growth Reference Study National Center for Health Statistics National Health Service (United Kingdom) Nutritional survey Supplementary Nutrition Programme Take Home Ration United Nations Children s Fund World Health Organization 3

5 EXECUTIVE SUMMARY Introduction: Despite Bihar s high growth rate in recent years, malnutrition persists as a barrier to development. The WHO (World Health Organisation) characterises malnutrition as [N]ot enough as well as too much food, the wrong types of food, and the body's response to a wide range of infections that result in malabsorption of nutrients or the inability to use nutrients properly to maintain health. 1 The 2008 India State Hunger Index (ISHI) ranked Bihar 15 th of 17 states surveyed. Bihar notably ranked below average in the proportion of underweight children (56.1% vs. 42.5%). 2 In the WHO found that of Bihari children aged 0-5, 56.4% were -2 standard deviations or more from the ideal weight (mean of 0) and 25.4% were -3 or more standard deviations from the mean. 3 A malnourished child is more susceptible to disease and can suffer permanent mental and physical damage. The first 2-3 years are the most critical for preventing long-term damage. Objective: The objective of this report is to define malnutrition and childhood growth standards; present research about the impact of block and sex on malnutrition, supplementary nutrition (SNP), and Take Home Ration (THR) provision in Patna District; and offer recommendations to reduce malnutrition in Bihari children though ICDS. Data collection: Child growth and malnutrition data are from visits to 34 Anganwadi Centres (AWCs) in Patna and Vaishali Districts. Block-level data are from ICDS s MIS (Management Information System). AWC growth and malnutrition data were analysed with WHO Anthro software and two-tailed t-tests in Excel to determine malnutrition levels and if there was a gender bias in malnutrition. Block-level data from were analysed with chi-squared (X 2 ) tests in Excel to determine if malnutrition rates, SNP, and THR provision were independent of sex. AWC data were not collected from randomly selected AWCs. Block-level data were not available for all blocks in Patna District, nor were all block-wise reports complete. Data analysis and results: The analysis in this report yielded the following results: AWC gender malnutrition independence analysis 3 of 22 AWCs with sufficient data showed malnutrition to be dependent on gender at an alpha of In each case males were more malnourished than females

6 The best AWC had average weight-for-age standard deviations from the ideal mean (11.7 th percentile); the worst AWC had average weight-for-age standard deviations from the ideal mean ( th percentile). A weighted average of weight-for-age standard deviations for the 22 AWCs showed results almost identical to the WHO s for Bihar in : 4 o -2 or more standard deviations below the mean: 57.05% (vs. 56.4% WHO). o -3 or more standard deviations below the mean: 23.28% (vs. 25.4% WHO). Patna District malnutrition, SNP, and THR gender independence analysis SNP provision favoured: o Females 31.75% of the time and males 2.38% (all ages). o Females 21% of the time and males 5% (6 months 1 year). o Females 14% of the time and males 2% (1-3 years). o Females 60% of the time and males 0% (3-6 years). THR provision favoured: o Females 22.62% of the time and males 23.81% (all ages). o Females 19% of the time and males 26% (6 months 3 years). o Females 26% of the time and males 21% (3-6 years). For malnutrition, the sexes worst affected were (Normal, Grade I, Grade II, Grade III, Grade IV), by percentage of statistically significant cases: o Females 19%, 5%, 10%, 14%, 5%; males 0%, 5%, 0%, 0%, 0% (0-1 years). o Females 10%, 5%, 5%, 33%, 24%; males 10%, 33%, 10%, 5%, 5% (1-3 years). o Females 10%, 5%, 10%, 5%, 5%; males 5%, 5%, 5%, 19%, 5% (3-6 years). Conclusions from the analysis: Data analysis yielded the following conclusions: AWC gender malnutrition independence analysis Even the best AWCs had extremely high rates of malnutrition. Weight-for-age data are not uniformly collected by sevikas and thus it is difficult to make firm conclusions. However, the data in this report are very close to the WHO s, although this shows almost no change in malnutrition since Patna District malnutrition, SNP, and THR gender independence analysis SNP: In most cases there is no difference between sexes, but females are more favoured than males, especially at ages 3-6. This is probably because families send older males to private or primary schools while females remain in AWCs

7 THR: There is not obvious district-wide gender bias in THR. In some blocks females are favoured, in others males, but overall there is not a large difference. This is probably because families benefit equally from females and males receiving THR. Malnutrition: While females and males suffer high rates of malnutrition, females tend to be overrepresented in the worst grades (III and IV). Only at ages 3-6 do males show higher levels of malnutrition in Grade III. This is probably because the males remaining in AWCs are the poorest of the poor because wealthier males attend private or primary schools. Females remaining in AWCs are from all income levels. Recommendations: This report makes the following recommendations: Use standard growth measures: Sevikas do not use standard growth measures. Each AWC follows its own procedures. ICDS must train sevikas to all use the same measures which will allow for improved data analysis at block, district, and state levels. Properly train AWWs (Anganwadi Workers) on growth measurements: AWWs do not take growth measurements correctly. The WHO provides a Training Course on Child Growth Assessment 5 which could serve as a model. Without good growth data, ICDS will not know the situation in AWCs and will not properly intervene in this the most important of its focus areas, nutrition. Provide each AWC with scales and use them correctly: Most AWCs do not have proper scales for weighing babies and older children, nor do they know how to use them. This results in unreliable growth data which again constrains ICDS s ability to provide proper interventions in nutrition. Investigate differences in SNP and THR distribution: It appears some differences exist in SNP and THR provision between sexes. ICDS should investigate why this occurs and ensure that the children with the greatest need receive SNP and THR. Males should be better served by SNP and females better served by THR. Focus interventions on younger children, especially ages 0-2: Children are most vulnerable to permanent mental and physical damage from ages 0-2. ICDS interventions should focus on these children to get the highest return on limited ICDS resources. Universalise ICDS in Bihar: The best way to combat malnutrition in Bihari children is to universalise ICDS as some Indian states have done. Properly dispose used needles: At several AWCs used needles were observed. This is a public health hazard and must never be allowed. Adjust AWC rental allowance by location and select healthier locations: Rental allowance should be based on location, with urban AWCs receiving a higher allowance than rural AWCs. Many urban AWCs are clearly bad for the children s health near garbage dumps, open sewers, and standing water

8 INTRODUCTION For my research under the ICDS internship programme for international graduate students I chose to focus on nutrition, which is related to my interest and experience in food security. I used my experiences as a graduate student at the University of Michigan s Gerald R. Ford School of Public Policy MPP programme and in international development as a Peace Corps Volunteer in the African countries of Cape Verde and Mozambique from 2008 to After visiting Anganwadi Centres (AWCs) in Patna Sadar 1 and Masaurhi blocks in Patna District, I decided to focus on malnutrition in children who receive supplementary nutrition or Take Home Ration (THR). Sevikas are required to keep growth charts, which give the best measurement of malnutrition available at the Anganwadi level and form the basis of reports which they submit. I visited 34 AWCs in different blocks of Patna District, and Hajipur in Vaishali District, to gather data and study the blocks, learn how AWCs function, and witness the performance of the blocks. I visited about 10 additional AWCs where I did not gather data. I decided to focus on Fatuha and urban Patna based on communication problems as a non-hindi speaker and logistical constraints. The objectives of this report are to introduce malnutrition, analyse malnutrition in and between the AWCs and blocks and between females and males, and offer recommendations which ICDS can use to improve the serious nutritional situation of children in the State of Bihar. Whenever possible I used sound statistical methods to analyse data and make useful recommendations. To save precious space for analysis, I will not include a general description of ICDS, as the reader should have a good grasp of the organisation. I refer readers unfamiliar with ICDS in Bihar to the website or to the many publications about ICDS. MALNUTRITION Malnutrition in India: According to the World Health Organization (WHO), malnutrition: [C]oncerns not enough as well as too much food, the wrong types of food, and the body's response to a wide range of infections that result in malabsorption of nutrients or the inability to use nutrients properly to maintain health. 6 India mostly suffers from malnutrition as a lack of food and proper nutrients in available or consumed food. Other factors that cause malnutrition include poor hygiene, poor sanitation, and unsafe water supply. Malnutrition weakens its victim and leaves him or her more vulnerable to illnesses like hepatitis or malaria. Untreated, malnutrition can cause permanent mental and 6 7

9 physical disability, and even death. Children are especially vulnerable to malnutrition and thus require special attention. 7 It is critical to target children from 0-3 years. 8 Stunting and wasting are two interrelated aspects of malnutrition. Stunting means low height-forage, and wasting means low weight-for-height. Stunting generally occurs before the age of two, and leads to reduced mental and physical capacity. Stunted children are less likely to perform well at school or be capable of physical labour. Wasting strongly predicts under-five mortality. According to UNICEF, India ranks third worst in the world for wasting rate at 20% of children (2005), behind the African nations of Burkina Faso and Djibouti. 9 The 2008 India State Hunger Index (ISHI) 10 demonstrated dire malnutrition levels in Indian states. The ISHI is based on the Global Hunger Index (GHI), which measured malnutrition in 88 countries. The ISHI measured the prevalence of calorie undernourishment (%), proportion of underweight amongst children <5 years (%), and under-five mortality (% of live births). Of the 17 states ranked in the index in 2008, Bihar ranked 15 th, ahead of only Jharkhand and Madhya Pradesh. It ranked 15 th in 1994, at the time the worst state ranked in the ISHI. In 2008 Bihar ranked better than the Indian average in caloric undernourishment (17.3% vs. 20.0%), but ranked below average in the other two categories, most notably in the proportion of underweight children 56.1% vs. 42.5%). 11 This suggests the nutritional quality of food Bihari children eat is a more serious problem than the quantity of food they consume, in comparison to Indian averages. In the five categories of malnutrition severity used by the study (low, moderate, serious, alarming, extremely alarming), no states achieved a rank of low or moderate. Four states ranked serious; one ranked extremely alarming (Madhya Pradesh); and 12 ranked alarming, including Bihar. If Bihar were a country, it would rank between the West African nations of Mali (73 of 88) and Guinea-Bissau (74 of 88) on the GHI. 12 Many factors influence a state s performance. States with stronger economies, like Gujarat, did not necessarily perform well on the ISHI. Assam improved greatly from 1994 to 2008 despite having the lowest growth rate in India. These results suggest that improvement in Bihar is not guaranteed by its excellent recent economic growth rate, nor does its persistent poverty mean it will always be one of the hungriest Indian states. Much depends on good policy decisions and effective implementation of those decisions Ibid. p Ibid. p. 21 8

10 GROWTH STANDARDS AND MALNUTRITION There are several ways to categorize malnutrition, including by standards developed by the Centers for Disease Control s (CDC) National Center for Health Statistics (NCHS) from the United States and the WHO, amongst others. I use WHO standards based on standard deviations and percentiles, although the ICDS MIS (Management Information System) uses a different classification with grades Normal to IV. Dr Dilek A. Bishku of the University of Chicago explained the Gomez definition of malnutrition by grades, using weight as a percentage of the reference weight, which is the 50 th percentile. In this scale normal weight is 1, and grades are expressed as a percentage of normal: Normal: % Grade I (mild malnutrition): 75-89% Grade II (moderate malnutrition): 60-74% Grade III (severe malnutrition): <60% Dr Bishku noted that 3-5% of the population will be -2 standard deviations (z-score of -2) from the ideal weight, although they are not malnourished. Some children are naturally small, and Bihar is no exception. 13 The following WHO table explains z-score measurements for four childhood growth indicators. ICDS only collects weight-for-age data. Grey areas are considered normal measurements. 14 z-scores for various growth indicators

11 WHO growth charts measure children either by z-scores or percentiles. It can be easier to think of malnutrition in percentiles than in z-scores. The following table shows the relationship between the two: Percentile z-score >99 th 3 97 th 2 85 th 1 50 th 0 15 th -1 3 rd -2 <1 st -3 The following are growth charts using both measurements for girls, and excerpts from simplified field tables. All are for ages 0-5; though they are available for various age ranges, both sexes, and in more detailed measurements. 15 WHO weight-for-age chart for girls, by z-score

12 16 WHO weight-for-age chart for girls, by percentile 17 WHO weight-for-age simplified field table for girls, by z-score

13 18 WHO weight-for-age simplified field table for girls, by percentile The following image is of the new WHO growth charts used in AWCs. This particular chart is from Patna Sadar 1. The charts come in a book separated by gender (blue pages for boys, pink pages for girls), each page with one chart. The graph s colour-coding in green, yellow, and red clearly shows a child s nutritional status. It shows a male of 25 months in the red area, although he seems to be growing fast enough to move into the less malnourished yellow area in several months. New WHO colour-coded growth chart (Male, 2 years 1 month)

14 WHO child growth standards: 19 I used WHO standards to determine malnutrition in children ages 0-5. While children up to six years old attend AWCs, the WHO standards only apply to age five. The WHO developed growth standards based on its Multicentre Growth Reference Study (MGRS) from 1997 to 2003, based on data from approximately 8,500 children in six countries: Brazil, Ghana, India, Norway, Oman, and the United States. While some argue that India should use a different measurement or that WHO measures do not apply to Indians, these guidelines are considered the global standard. According to the WHO: The standards describe normal child growth from birth to 5 years under optimal environmental conditions and can be applied to all children everywhere, regardless of ethnicity, socioeconomic status and type of feeding. 20 The MGRS used a variety of measurements to determine growth, including head circumferencefor-age, weight-for-age, and weight-for-height. While it is not necessary to use every measurement to determine malnutrition, it is best to collect as much information as possible. The WHO website also provides materials for a Training Course on Child Growth Assessment to train healthcare workers in monitoring child growth. DATA COLLECTION At each AWC I collected the best available data for malnutrition: Growth cards, new WHO growth charts, old WHO growth charts, personally weighing children, THR records. Given the type of data sevikas collect, the best way to measure malnutrition rates is to use the WHO s guidelines based on weight-for-age, as other data like head circumference and height are not collected by sevikas. I also downloaded data from the ICDS MIS for each block in Patna District to analyse the role of gender in malnutrition, supplementary nutrition, and THR provision. Data collection challenges: The quality of data I encountered in Patna and Vaishali Districts varied widely. Some AWCs have no growth data on children ages 0-5, while other centres use the newest WHO growth charts each month for every child. Most centres I visited do not use the new colour-coded WHO charts, even though some have them and should all use them. I was not able to visit randomly selected AWCs for various reasons. I faced difficulties explaining statistical methods to CDPOs. I believe they took me to good centres, partly because they reflect well on the CDPO but also because a bad centre is not likely to have

15 useful data. Even if I had visited randomly selected centres, I believe data collection would have been more difficult, not to mention the logistical challenges of traveling to spread out AWCs. Many sevikas monitor children s weight occasionally but not every month, which reduces the growth charts usefulness. If a sevika consistently plots a child s weight, a z-score (or percentile) far below the mean (or 50 th percentile) can be shown graphically to result from an illness and a deviation from a normally healthy growth trajectory. If a sevika only plotted weight once every six months, if many children were ill during that time they would appear more malnourished than they really are. Also, if a child has oedema, his/her malnutrition status may not be valid, though according to previous studies oedema is not as large a problem in India as it is in other countries. Sevikas do not test for oedema. Each sevika has a different system of records. Some keep records for all 40 registered students, some keep records for students and children 0-3, although many do not have complete records for either group. Many sevikas combine children 0-3 and students in the WHO growth charts or a THR notebook. Very few sevikas keep a register of children in the community who are on the AWC s waiting list. The lack of a visible student list makes it difficult or impossible to determine which children in attendance are actually registered. It is impossible to tell if the most deserving children attend the AWC or receive THR. Sevikas do not use a consistent format for recording growth data. For age, some sevikas use dateof-birth, others use months, still others use the year.month format (e.g. 16 months is 1.4, or 1 year 4 months). In the date-of-birth format, it is necessary to know when the sevika recorded the child s weight, because it is necessary to know how old the child was at the date of measurement to determine if she or he is malnourished. Sevikas always record weight in kilograms, though it is clear that they do not take accurate measurements because so many records end in 0 or 5 (e.g kg or 5.0 kg), but rarely in other digits (e.g. 3.7 kg or 11.4 kg). Finally, many AWCs do not have equipment for measuring children, or if they do, sevikas do not know how to properly use the equipment. Therefore it is difficult to know how the sevika got the data she plotted. It could simply be data reused from a different year, or a guess. A good sevika intuitively knows if a child is relatively healthy or not, but it is necessary to record this data. In some cases I could not determine if the sevika had correctly plotted or recorded growth data, even if she had done the measurements correctly. If I believed data to be incorrect or extremely flawed I excluded it from my analysis. This is why my analysis does not include all 34 AWCs I visited. It was not possible to conduct a random sample of AWCs in either district, so for malnutrition I will not make broad conclusions about blocks based on the data I collected at AWCs, only about the individual AWCs. On the MIS, data was only available for one month from for each block in Patna District. This could be because CDPOs did not submit reports, or the data centre staff did not enter data. The strength of my analysis depends on the accuracy of the data in the MIS. I 14

16 downloaded data from each block in Patna District except for Naubatpur and Patna Sadar 3, which were not available. I reached conclusions about the effect of gender on three things: malnutrition, the supplementary nutrition programme (SNP), and THR in Patna District. DATA ANALYSIS WHO Anthro software: 21 The WHO developed software called Anthro for personal computers and mobile devices. Anthro can be used to apply WHO growth standards and motor skills development to children ages 0-5. The software includes three modules: Anthropometric calculator (AC), Individual assessment (IA), and Nutritional survey (NS). A healthcare worker can input comprehensive data about the child including birthdate, date, gender, height, oedema status, and weight. Anthro calculates the malnutrition status and magnitude of malnutrition for each child and creates reports for groups of 12 or more children. It creates growth charts for individual children. Data can be exported to Excel, STATA, and other software programmes. AWC malnutrition analysis with Anthro: I entered all relevant data collected from AWCs in Anthro. Some AWCs provided data that appeared incorrect for various reasons; I did not use this data. The data collected was age (in days), sex, and weight in kilograms. Most growth records at AWCs are in months, so I converted them to days using WHO guidelines. Anthro assigns each child a randomised birthdate within his/her age range because I usually did not have their birthdates. For each AWC I created a NS of children ages 0-5. Anthro: user interface Anthro: Individual record

17 For each child Anthro calculates the standard deviations from the mean and which percentile the child falls under, based on the data entered. A mean of 0 (z-score of 0) or the 50 th percentile are considered ideal weight-for-age, with children below undernourished and children above overnourished. I created an NS for each AWC. The data are approximately normally distributed or skewed to the right. The data can be separated by age group and gender. Anthro creates reports with the mean z-score and standard deviation for each NS, for the entire AWC and for age groups or by gender. Anthro calculates 95% confidence intervals for each NS for two and three standard deviations from the mean. All of these data can be exported and analysed with software programmes. Anthro omits values which are considered too extreme, though they could be valid, especially with the poor nutritional status of many AWC children. The following are Anthro outputs which can be used for analysis and are based on the data entered in the software. 16

18 Nutritional survey standard analysis Detailed tables with 95% confidence intervals* Set 1: Sexes combined Age groups N Weight-for-age (%) % < -3SD (95% CI) % < -2SD (95% CI) Mean SD Total: (5.1%, 33.8%) 72.2 (56.2%, 88.2%) (0-5) 2 0 (0%, 25%) 50 (0%, 100%) (6-11) 4 25 (0%, 79.9%) 75 (20.1%, 100%) (12-23) (0%, 38.7%) 76.5 (53.4%, 99.6%) (24-35) (0%, 49.8%) 69.2 (40.3%, 98.2%) (36-47)0 (48-60)0 Set 2: Males Age groups N Weight-for-age (%) % < -3SD (95% CI) % < -2SD (95% CI) Mean SD Total: (16.3%, 71.2%) 75 (50.7%, 99.3%) (0-5) 0 (6-11) (50%, 100%) 100 (50%, 100%) (12-23)6 50 (1.7%, 98.3%) 66.7 (20.6%, 100%) (24-35) (0%, 69.7%) 77.8 (45.1%, 100%) (36-47)0 (48-60)0 Set 3: Females (6-11) 3 0 (0%, 16.7%) 66.7 (0%, 100%) (12-23)11 0 (0%, 4.5%) 81.8 (54.5%, 100%) (24-35)4 0 (0%, 12.5%) 50 (0%, 100%) (36-47)0 (48-60)0 Excerpt from Anthro standard report (Dulhin Bazar AWC 057) 17

19 Anthro: Graph of weight-for-age, by age (Fatuha AWC 026) Anthro: Graph of weight-for-age, by sex (Fatuha AWC 026) 18

20 Anthro: Individual record. Female, days old, 6.10 kg, standard deviations from the mean (Fatuha AWC 026) The following table is the result of extensive AWC visits and analysis using Anthro and Excel. Date Block/AWC Visited Dulhin Bazar /06/12 n= 9 z= sd= /06/12 n= 20 z= sd= 0.47 Total: 2 AWCs Fatuha AWC weight-for-age data (n = number of children, z = z- score, sd = standard deviation) Female Male Total n= 19 z= sd= 0.49 n= 16 z= sd= 1.24 n= 28 z= -2.6 sd= 0.46 n= 36 z= sd= 0.97 Notes (where applicable) Very good records on old growth chart for 80 children (0-3 THR and AWC students). Large AWC in Urdu-language school. More than 40 children. Most children in uniform. Children appear moderately healthy. Good records. Moderately large AWC with outside courtyard. We arrived after 12:00 PM; all children had eaten and left AWC. 19

21 /06/12 n= 8 z= sd= /07/12 n= 25 z= sd= /06/12 n= 19 z= sd= /07/12 n= 35 z= sd= /06/12 n= 9 z= sd= 1.83 n= 13 z= sd= 0.77 n= 22 z= sd= 1.3 n= 20 z= sd= 0.87 n= 19 z= sd= 1.23 n= 4 z= sd= 2.04 n= 21 z= -1.4 sd= 0.92 n= 47 z= -1.6 sd= 1.58 n= 39 z= sd= 0.92 n= 54 z= -2.1 sd= 1.13 n= 13 z= sd= 1.9 Most children in uniform. AWC is well-ventilated. Very good records: Growth cards and new growth charts. Records in new WHO growth chart but sevika has plotted some children incorrectly. Good growth records. Good records in new WHO growth charts. Sevika is very experienced. 35 children present. Some in uniform. Children are wellbehaved. Many flies in AWC, possibly because of the rain. Some children have skin problems. Well-organized AWC. Incomplete records. Most children in uniform. >10 unregistered children present; health appears poor. Children received snack of puffed riced; fruit is not affordable /07/12 No data No data No data No growth data. Sevika keeps age in one notebook and weight in another. She has a new WHO growth chart but does not use it /07/12 n= 48 z= sd= 0.81 n= 33 z= sd= /06/12 No data n= 32 z= sd= 0.84 n= 81 z= sd= 0.73 n= 32 z= sd= 0.84 Good records in new WHO growth chart. 40 children present. Some in uniform. AWC has nice courtyard and veranda. Sevika using new WHO growth chart but all female and some male records did not appear correctly plotted. There were used immunization needles outside the AWC near where food is prepared, a major health concern /06/12 No data No data No data AWC was built with Government funds and community support. 20

22 AWC is closed and the community is angry. LS and CDPO recorded complaints and testimony from community. Used immunization needles outside the AWC, a major health concern /06/12 No data No data No data No growth data recorded. >30 children present. 3 children in uniform. Sevika not distributing THR in correct quantities. LS and CDPO recorded complaints and testimony from community. Total: 10 AWCs Hajipur /06/12 n= 18 z= sd= /06/12 n= 24 z= sd= /06/12 n= 26 z= sd= /06/12 n= 17 z= sd= /06/12 n= 14 z= sd= 1.62 n= 20 z= sd= 1.27 n= 17 z= sd= 1.38 n= 14 z= sd= 1.37 n= 11 z= sd=0.68 n= 25 z= sd= 1.91 n= 38 z= sd= 1.18 n= 41 z= sd= 1.24 n= 40 z= sd= 1.33 n= 28 z= -2.9 sd= 0.49 n= 39 z= sd= 1.79 Growth records from old WHO chart. Complete records. Complete records. Nice, airy AWC. Sevika has started to use new WHO growth charts, but records children using the THR notebook. Children seemed bored or without energy. Good records in THR notebook. Children mostly in uniform. Children using blackboards to learn to write. Total: 5 AWCs Masaurhi /06/12 No data No data No data Met several girls from SABLA scheme who seem empowered and respected in the community. Not all pregnant women take advantage of 21

23 prenatal care at local health facilities. I did not collect data here, but it was available. Total: 1 AWC Patna Sadar /06/12 No data No data No data AWC was closed at 10:30 AM /06/12 n= 19 z= sd= 1.81 n= 10 z= sd= 1.19 n= 29 z= sd= 1.6 Approximately 20 children present. 0 children in uniform. Good growth data /06/12 No data No data No data Approximately 22 children present. Incomplete growth data from growth cards. No growth charts. No money for snacks. Some children in the area attend private school instead of AWC /06/12 No data No data No data Very small AWC located in a garage. AWC smells strongly of oil: Must be bad for the children. Many flies. Environment outside of AWC very poor with trash and standing water. Many children with skin diseases. Approximately 23 children present. 5 children in uniform. Sevika has old and new growth charts but does not know how to use either /06/12 No data No data No data AWC does not have complete registers. Approximately 8 children present. Most children appear unhealthy with skin diseases. Several bags of THR, probably rice and pulses, arrived for distribution. 8 women brought children 0-3 for THR. We weighed them. Sevika did not know how to correctly use the scale /06/12 No data No data No data Very small. Approximately 22 children present. No growth charts. Few children in uniform /06/12 n= 8 n= 10 n= 18 Poor records. Incomplete THR and 22

24 z= sd= 1.12 Total: 7 AWCs Patna Sadar /06/12 n= 13 z= sd= /06/12 n= 21 z= sd= /06/12 n= 13 z= sd= 1.1 Total: 3 AWCs Patna Sadar /06/12 n= 37 z= sd= /06/12 n= 7 z= sd= /06/12 n= 15 z= sd= /06/12 n= 13 z= sd= 0.74 Total: 4 AWCs Chart total: 34 AWCS z= sd= 1.22 n= 29 z= sd=0.77 n= 19 z= sd= 0.93 n= 29 z= sd= 0.79 n= 34 z= sd= 0.95 n= 6 z= sd= 1.56 n= 23 z= sd= 1.65 n= 25 z= sd= 0.93 z= sd= 1.16 n= 42 z= sd= 0.93 n= 40 z= sd= 0.83 n= 42 z= sd= 0.93 n= 71 z= sd= 1.00 n= 13 z= sd= 1.52 n= 38 z= sd= 1.64 n= 38 z= sd= 0.86 other registers. No growth data. <20 children present. Some children in uniform. Good growth data from growth cards. AWC is very small. Many sevikas in Sadar 3 contribute their own money for rent. Good growth records. AWC located in a tiny hallway with small businesses. Good growth data on old charts. Sevika very experienced. Excellent records. AWC small but well-organized. One child is severely malnourished (6 years old, <10 kg, exhibits all classic signs of severe malnourishment). Incomplete data in old WHO growth chart. Sevika does not use her new WHO chart. Excellent records using new WHO growth chart. Children wellbehaved and most in uniforms. AWC is a good environment for children. Excellent records using new growth charts. Children well-behaved and mostly in uniforms. 23

25 The following table summarizes the best and worst results from AWCs in malnutrition: Block AWC z-score Percentile Notes Best females Patna Sadar Questionable data Best males Fatuha Best total Patna Sadar Questionable data Worst females Patna Sadar Worst males Patna Sadar Worst total Patna Sadar The following table shows the percentages of children below -2 and -3 standard deviations from the ideal mean of 0, and a weighted percentage total for the AWCs included. These are AWCs I visited which had sufficient data to analyse. Block AWC <-3 <-2 n Dulhin Bazar , Dulhin Bazar , Fatuha Fatuha , , Fatuha , Fatuha , , Fatuha Fatuha , , Fatuha , Hajipur , Hajipur , Hajipur , Hajipur , , Hajipur , Patna , , Patna Patna , Patna , , Patna , Patna , , Patna , Patna , Patna , Total , , Total %

26 The three tables show the terribly high malnutrition levels in AWCs visited. In the best centres (one of which had questionable data) malnutrition rates are still very high, while the worst centres rates are almost impossibly high. While the centres were not randomly selected and thus impossible to generalise across Patna District, it is likely that malnutrition levels are similarly high everywhere. The majority of AWCs visited had weight-for-age z-scores of below -2 or below the 3 rd percentile, which means 97% of children worldwide have higher weight-for-age. The notes column in the first table shows the irregularity in recordkeeping. Several AWCs had no records, while most had outdated records in incorrect or outdated formats, like the black and white WHO growth charts or only THR registers. However, the consistently low z-scores lead me to believe that even with incomplete and poor recordkeeping the data I found presents an accurate picture of terrible malnutrition in AWCs, although it might not be the most current data. The percentages in the final table match almost exactly the percentages for <-3 and <-2 standard deviations from the ideal mean of 0 found in Bihar by the WHO in : 25.4% and 56.4%, versus the 23.3% and 57.0% I observed. 22 The national figures for India were 24.3% and 50.7%. This lends credibility to the data I collected. It shows a slight worsening in <-2 malnutrition and a slight improvement in <-3 malnutrition since in Bihar. If this data is correct, it shows little progress has been made in improving childhood nutrition. AWC malnutrition gender independence analysis: To determine if there was a statistically significant difference between malnutrition rates in females and males in AWCs visited, I analysed data using independence tests in Excel. I obtained this information by first entering malnutrition data from AWCs into Anthro software. Then I exported the reports and edited them for use in Excel. I used t-tests to test for independence, with two tails to correct for errors in data and data collection. I treated most comparisons as homoscedastic (equal variance) unless the difference in observations for females and males warranted treating them as heteroscedastic (unequal variance). I used the standard alpha level of 0.05 for all statistical analyses, which means that the probability of finding the result I found was less than 5% if the difference between means for females and males was zero as assumed (i.e. there was no difference in malnutrition between the sexes). As I was not able to randomly sample AWCs, I cannot make conclusions about Patna District, only the individual AWCs I visited

27 # Statistically significant? Block AWC Alpha 1 Dulhin Bazar No 2 Dulhin Bazar Yes Males 3 Fatuha No 4 Fatuha No 5 Fatuha Yes Males 6 Fatuha No 7 Fatuha No 8 Fatuha No 9 Hajipur No 10 Hajipur No 11 Hajipur No 12 Hajipur No 13 Hajipur No 14 Patna Sadar No 15 Patna Sadar No 16 Patna Sadar Yes Males 17 Patna Sadar No 18 Patna Sadar No 19 Patna Sadar No 20 Patna Sadar No 21 Patna Sadar No 22 Patna Sadar No Which group is more malnourished? This table shows that in the AWCs visited, there were only three where there was a statistically significant difference in malnutrition rates between females and males. In those three AWCs, males were more malnourished than females. This table and the one before it show that while malnutrition rates are extremely high in AWCs, females and males seem to be approximately equally malnourished. However, this result cannot be assumed true for every AWC or block in Patna District. One reason for more highly malnourished males could be that wealthier, older male children are sent by their parents to private or primary schools, leaving only more malnourished males. The females in the AWC would be both poorer and wealthier, more and less malnourished. Therefore the males would be more malnourished, assuming parents are not as likely to send females to private or primary schools, regardless of the family s wealth. Patna District malnutrition, SNP, and THR gender independence analysis: To determine if there was a statistically significant difference in malnutrition and the provision of SNP and THR between females and males in Patna District, I analysed block-level data from the MIS using 26

28 independence tests in Excel. I used the chi-squared (X 2 ) test of independence to analyse data from for every block except Naubatpur and Patna Sadar 3, which had insufficient data. The chi-squared test compares actual values to predicted values. I assumed that females and males would have the same malnutrition rates and equal access to SNP and THR. The predicted values are thus based only on the proportion of children eligible for each programme. For example, if 40 females and 30 males were eligible for THR, and THR was available for 35 children (half of the total of 70 eligible children), I assumed that 20 females and 15 males would receive THR, or half (50%) of each sex. I chose the standard alpha level of 0.05, which means that the probability of finding the result I found was less than 5% if the difference between females and males in malnutrition rates and SNP and THR provision was zero. I used data from all but two blocks in Patna District, though some blocks clearly did not have complete data. I am somewhat confident in making conclusions about Patna District based on my analysis given the large amount and relative completeness of data analysed. Highlighted cells represent a statistically significant result, which suggest that the provision of SNP or THR, or the level of malnutrition, is dependent on sex. If SNP or THR provision favours one sex, it means that sex receives more SNP or THR than expected based on eligibility. If malnutrition rates are worse for one sex, it means that sex has higher levels of malnutrition in a given category than expected by enrolment numbers. The following three tables show the result of independence tests for each block in total SNP and SNP >15 days, and which sex SNP provision favours if there is a statistically significant difference. The final tables show the percentages of favour (no difference, favours females, favours males) as a total and by age group. 27

29 5) Number of beneficiaries for: a) Supplementary nutrition in all reporting AWCs Age group 6 months to 1 year Total SNP Favours >15 days Favours 1 Bakhtiyarpur Barh Boys Boys 3 Bihta Bikram Danapur Girls Girls 6 Dhanarua Dulhin Bazar Fatuha Girls Khusrupur Maner Masaurhi Girls Girls 12 Mokama-Ghoshwari Paliganj Pandarak Patna Girls 16 Patna Girls 17 Patna Girls Girls 18 Patna Patna Gramin Phulwari Sharif Punpun-Sampatchak Age group 1 to 3 years Total SNP Favours >15 days Favours 1 Bakhtiyarpur Barh Bihta Bikram Danapur Girls Girls 6 Dhanarua Dulhin Bazar Fatuha Khusrupur Girls Maner Masaurhi Boys 12 Mokama-Ghoshwari Paliganj Pandarak Patna Patna Patna Girls Girls 18 Patna Patna Gramin Girls 20 Phulwari Sharif Punpun-Sampatchak

30 Age group 3 to 6 years Total SNP Favours >15 days Favours 1 Bakhtiyarpur Girls Girls 2 Barh Bihta Bikram Girls Girls 5 Danapur Girls Girls 6 Dhanarua Girls Girls 7 Dulhin Bazar Fatuha Khusrupur Girls Girls 10 Maner Masaurhi Girls Girls 12 Mokama-Ghoshwari Paliganj Pandarak Girls Girls 15 Patna Girls Girls 16 Patna Patna Girls Girls 18 Patna Girls Girls 19 Patna Gramin Girls Phulwari Sharif Girls Girls 21 Punpun-Sampatchak Girls Girls SNP Favours (all ages) No difference % N/A 0 Girls % % of total 0.00% Boys % Total % Favours 6 mo - 1 year 1-3 years 3-6 years Females 9 21% 6 14% 25 60% Males 2 5% 1 2% 0 0% No difference 31 74% 35 83% 17 40% Total % % % The previous tables show that in most cases SNP does not favour either sex, but in almost 32% of cases it favours females, mostly from ages 3-6. Males are favoured in less than 3% of cases. Females are favoured more as they grow older, which could be because parents send their daughters to free AWCs, but invest more in males and send them to private or primary schools. The 3-6 age group shows the most significant result: Females are favoured in about 60% of blocks for SNP. Males are never favoured, and in 40% of cases neither sex is favoured. 29

31 The following tables show the result of independence tests for each block in single and double THR and which sex THR provision favours if there is a statistically significant difference. The final tables show the percentages of favour (no difference, favours girls, favours boys) as a total and by age group. b) Number of children for THR 6 months to 3 years Single THR Favours Double THR Favours 1 Bakhtiyarpur Barh Bihta Girls 4 Bikram Danapur Girls Girls 6 Dhanarua Boys Dulhin Bazar Fatuha Boys Boys 9 Khusrupur Girls 10 Maner Boys Masaurhi Boys Girls 12 Mokama-Ghoshwari Paliganj Girls Pandarak Patna Patna Boys Patna Boys 18 Patna Girls 19 Patna Gramin Boys Boys 20 Phulwari Sharif Boys Punpun-Sampatchak Boys Girls 30

32 3 to 6 years Single THR Favours Double THR Favours 1 Bakhtiyarpur Girls Barh N/A 3 Bihta N/A 4 Bikram Boys 5 Danapur Girls Boys 6 Dhanarua Boys 7 Dulhin Bazar N/A 8 Fatuha Boys Khusrupur Girls Maner Boys Masaurhi Boys 12 Mokama-Ghoshwari N/A N/A 13 Paliganj N/A N/A 14 Pandarak Girls N/A 15 Patna Girls N/A 16 Patna Girls Boys 17 Patna Boys 18 Patna Girls N/A 19 Patna Gramin Girls N/A 20 Phulwari Sharif Girls Boys 21 Punpun-Sampatchak Girls Girls Favours No difference % N/A 11 Females % % of total 13.10% Males % Total % Favours 6 mo to 3 years 3-6 years Females 8 19% 11 26% Males 11 26% 9 21% No difference 23 55% 22 52% Total % % These tables suggest that THR provision does not favour females or males about 54% of the time, but of the remaining instances about half favour females and half favour males. This is quite a different result from SNP, where females are overwhelmingly favoured. Age group does not seem to be a major factor determining which sex is favoured in THR provision. One possible reason for the difference in SNP and THR favouritism is that parents do not perceive much personal benefit from a child receiving SNP, but send females because it is free. Parents send males to a perceived better school even if they must pay. However, for THR, families directly 31

33 benefit because they eat the food, not just the recipient. Thus families invest equally in females and males to get THR. From 6 months to 3 years in 55% of cases there is no favouritism, in 19% females are favoured, and in 26% males are favoured. From 3-6 years in 52% of cases there is no favouritism, in 26% females are favoured, and in 21% males are favoured. This could be consistent with the hypothesis that females are healthier than males at an early age, but after two years males tend to be healthier so females will require more nutrition. AWWs may have a female bias as well. The following tables show the result of independence tests in each block based on weight classification, to determine if weight classification is dependent on sex. There are five categories (from healthiest to most unhealthy): Normal, I, II, III, and IV. For the Normal category a sex would be classified as Worse if there were fewer children than expected. For categories I-IV a sex would be classified as Worse if there were more children than expected. 7) By weight classification Less than 1 year Normal Worse Grade I Worse Grade II Worse Grade III Worse Grade IV Worse 1 Bakhtiyarpur Girls Girls Barh N/A N/A N/A N/A N/A 3 Bihta N/A N/A N/A N/A N/A 4 Bikram Danapur Girls Girls Dhanarua Girls Dulhin Bazar N/A N/A N/A N/A N/A 8 Fatuha Khusrupur Maner Girls Masaurhi Mokama-Ghoshwari N/A N/A N/A 13 Paliganj N/A N/A N/A N/A 14 Pandarak N/A N/A N/A 15 Patna Girls Patna Girls Girls 17 Patna N/A 18 Patna N/A 19 Patna Gramin N/A 20 Phulwari Sharif Boys Girls Punpun-Sampatchak Girls More malnourished <1 No difference % N/A 28 Girls % % of total 26.67% Boys % Total % 32

34 This above table shows that for children under one year, there is no difference about 89% of the time, but where there is a difference females are almost always more malnourished than males. This means that where there is a difference, males are overrepresented in the healthier categories. This is not consistent with the hypothesis that under two years females are healthier than males. 1 to 3 years Normal Worse Grade I Worse Grade II Worse Grade III Worse Grade IV Worse 1 Bakhtiyarpur Girls N/A 2 Barh N/A N/A Bihta N/A N/A 4 Bikram Boys 5 Danapur Boys Boys Boys Girls Girls 6 Dhanarua Boys Girls Dulhin Bazar N/A N/A N/A N/A 8 Fatuha Khusrupur Girls Girls 10 Maner Masaurhi Boys Girls Girls 12 Mokama-Ghoshwari N/A N/A 13 Paliganj N/A 14 Pandarak N/A N/A 15 Patna Girls Patna Girls 17 Patna Boys Boys Boys N/A 18 Patna Boys Boys Girls N/A 19 Patna Gramin N/A 20 Phulwari Sharif Girls Boys Girls Girls Girls 21 Punpun-Sampatchak Boys Girls More malnourished 1-3 No difference % N/A 17 Girls % % of total 16.19% Boys % Total % The table above shows that from ages 1-3, there is still not a difference in most categories (about 73%). However, this is lower than ages 0-1. Females are more malnourished (15%) but males are not significantly better (12%). The table does show, however, that in the worst two categories females are overrepresented (33%, 24%), while males are more represented in the second best category, Grade I (33%). Overall females are worse off because when there is a difference, they are overrepresented in the worst malnourishment categories. 33

35 3 to 6 years Normal Worse Grade I Worse Grade II Worse Grade III Worse Grade IV Worse 1 Bakhtiyarpur N/A 2 Barh N/A Bihta Boys N/A N/A N/A N/A 4 Bikram Boys Girls 5 Danapur Boys 6 Dhanarua Girls Girls Girls Boys Dulhin Bazar N/A N/A 8 Fatuha Khusrupur Maner Boys N/A 11 Masaurhi Girls Girls Mokama-Ghoshwari N/A N/A 13 Paliganj N/A N/A 14 Pandarak N/A N/A 15 Patna Boys Patna Patna N/A 18 Patna Boys N/A 19 Patna Gramin N/A 20 Phulwari Sharif Punpun-Sampatchak Boys Girls N/A More malnourished 3-6 No difference % N/A 19 Girls % % of total 18.10% Boys % Total % The above table shows that in most cases (86%) there is no difference between genders in malnutrition categories. Where there is a difference, males are slightly worse than females. In ages 3-6, unlike the previous age groups, males are overrepresented in the second worst category of malnutrition (19% versus 5% females). One possible explanation is that these males are from the poorest families who cannot send them to a perceived better school. Healthier males are from wealthier families and may attend private or primary school, not AWCs. More females will stay in AWCs, regardless of their malnutrition level or their families wealth because families tend not to invest in daughters. 34

36 Ages 0-1 Worse Normal Grade I Grade II Grade III Grade IV Females 4 19% 1 5% 2 10% 3 14% 1 5% Males 0 0% 1 5% 0 0% 0 0% 0 0% No difference 17 81% 19 90% 19 90% 18 86% 20 95% Total % % % % % Ages 1-3 Worse Normal Grade I Grade II Grade III Grade IV Females 2 10% 1 5% 1 5% 7 33% 5 24% Males 2 10% 7 33% 2 10% 1 5% 1 5% No difference 17 81% 13 62% 18 86% 13 62% 15 71% Total % % % % % Ages 3-6 Worse Normal Grade I Grade II Grade III Grade IV Females 2 10% 1 5% 2 10% 1 5% 1 5% Males 1 5% 1 5% 1 5% 4 19% 1 5% No difference 18 86% 19 90% 18 86% 16 76% 19 90% Total % % % % % This final table above summarizes malnutrition levels by age group and sex across Patna District blocks. For ages 0-1 females are underrepresented in the best category, Normal, and over represented in the worst three categories (10%, 14%, 5%) when there is a difference. For ages 1-3, females and males are equal in the Normal category, males are worse in Grades I and II (33% and 10%), but females are worse in Grades III and IV (33% and 24%). For ages 3-6, females are worse in Normal and Grade II (10% and 10%), males are worse in Grade III, and the sexes are equal in the other categories. Overall these block-level tables show the importance of focusing attention on females, especially in the 1-3 group. While both sexes suffer from high rates of malnutrition, within the four categories females are more often in the most severe categories than males. Older males should also receive special attention because they tend to be more highly malnourished than younger males. 35

37 RECOMMENDATIONS Use standard growth measures: Sevikas do not use consistent growth measures. Each AWC has a different method of recordkeeping. Most sevikas record some growth measures, but every sevika needs to use the same format. If every AWC collects growth data in a consistent format, it will be easier for ICDS to aggregate data to know accurate malnourishment levels and respond appropriately. New WHO colour-coded growth charts must be distributed to every AWC. Decide which children will be entered in the new growth charts: Children 0-3 who receive THR AWC students Unregistered children/children on the AWC waiting list Plot the growth data every month. Monitor children in the yellow chart area and take action for the children in the red chart area. Hold all staff accountable for keeping updated registers: LSs must ensure that sevikas follow consistent standards. CDPOs must ensure that LSs properly supervise sevikas. DPO staff must hold CDPOs accountable for the staff they supervise. Properly train AWWs on growth measurements: While it will not be possible for AWCs to take every growth measurement suggested by the WHO, they should know how to correctly take some measurements. The WHO s Training Course on Child Growth Assessment 23 includes materials for a 3½ day training, and also a video. The materials are not available in Hindi, but trainers could translate the information. If AWWs do not take growth measures correctly, ICDS will not know the true nutritional status of children, and will not be able to intervene properly. Of ICDS s focus areas, nutrition should be a priority because a child s nutrition in the critical first years largely determines his or her future health and success. Provide each AWC with scales and use them correctly: Many AWCs do not have scales to weigh children. Even in AWCs which do have scales, AWWs need better training to use scales for collecting weight data. Some AWCs only have bathroom scales, which are inappropriate for measuring babies. Every AWC should have access to a hanging scale for babies, as well as a bathroom-type scale for children who can stand still. AWWs also need training on how to zero a scale, so the correct weight is taken. If a scale is not zeroed correctly, all weight-for-age data will be incorrect. I witnessed this in Patna Sadar 2, where the sevika set the scale incorrectly by almost 5 kg and tried to weigh struggling babies on it. Investigate differences in SNP and THR distribution: It appears that there is sometimes a difference in SNP provision between females and males, which favours females. ICDS should investigate why that might be, and focus on better serving males with SNP. Conversely, it does

38 appear that while both females and males suffer from high malnutrition rates, females are represented more highly in categories III and IV. Thus for THR, ICDS should focus more on females than males. Focus interventions on younger children, especially ages 0-2: Children aged 0-2 are most vulnerable to the effects of malnutrition. If they do not develop correctly in this period, their physical and mental potential will be greatly reduced, limiting their quality of life and ability to contribute to society. Older children are less vulnerable to malnutrition. Sevikas must focus on proper education for lactating mothers, because if children are not properly breastfed and nourished for at least the first six months of life, by the time they enter the AWC they will already be at large risk of permanent damage due to malnutrition. My informal observations in Masaurhi suggest that young mothers do not have proper education and do not use free resources available at local health centres and hospitals. Since ICDS provides sevikas with limited resources, sevikas should focus what they do have on the younger children. If there is money available for a snack, sevikas should ensure that the youngest children eat it, which will require extra supervision so stronger and older children do not take from younger children. Sevikas should ensure that the youngest children get plenty of SNP, even if they eat more slowly than old children and thus do not appear hungry. According to my analysis of all block-level data for Patna District, the highest statistically significant rates and differences in malnutrition between females and males occur from ages 1-3. Therefore ICDS should particularly focus on those children, as explained previously. Universalise ICDS in Bihar: There is no simple way to follow this recommendation. It requires cooperation from the Centre and State governments to fund universalization. However, according to my AWC analysis, malnutrition rates in Bihar have essentially remained the same since , based on the WHO study. There are still many unregistered children and waiting lists for every AWC. Many AWCs distribute THR to unregistered children who are in need but cannot attend the local AWC because of non-universalization. Therefore ICDS should urgently expand its fight against malnutrition though SNP, THR, and education. Bihar s impressive economic growth may not help the poorest of the poor, but good policies like universalization of ICDS can. Properly dispose used needles: I observed improper disposal of immunisation needles twice. According to the British National Health Service (NHS) hepatitis B and C, and HIV (Human Immunodeficiency Virus) can be transmitted through used needles. 24 It is the responsibility of the Primary Health Centre staff giving the immunisation to remove and properly dispose used needles, but all AWWs must ensure that nurses and doctors follow the correct procedures. This is

39 a grave public health issue for the entire community. Everyone in the community must know the dangers of used needles, and demand that the health authorities properly dispose of them. Used needles (Fatuha AWC 127) Used needles (Fatuha AWC 128) Adjust AWC rental allowance by location and select healthier locations: The quality of AWCs varies greatly across blocks. While space for rent is available in Patna city, it is expensive and the rental allowance does not pay for acceptable centres. Sevikas use their own money to rent a better space, or use unacceptable centres. Patna Sadar 2 had the worst centres I observed. Many AWCs in Patna are located near trash dumps or standing water, which put children and AWWs at high risk of hepatitis, malaria, and typhoid, amongst other diseases. In blocks outside Patna, spaces for AWCs may not be as easily available, though they should be more affordable. In Dulhin Bazar, Fatuha, Hajipur, and Masaurhi AWCs seemed more spacious and healthier. ICDS should adjust the rental allowance by location, giving urban AWCs more money for rent and demanding it is used to rent healthy spaces away from open sewers, standing water, and trash. Rural blocks should receive a lower allowance than urban blocks. AWWs should be held accountable for providing health spaces for children. AWC in Patna Sadar 1, metres from trash dump 38

40 CONCLUSION My research in Patna District showed high levels of malnutrition in every AWC visited and block which had data available on the ICDS MIS. It is well known, however, that Bihari children, and Indian children in general, suffer terribly from malnutrition. To decrease malnutrition, there are a few things ICDS can do. AWWs need better training to catalogue malnutrition. Otherwise ICDS will not know where malnutrition is most dire and requires the strongest response. ICDS should be universal in Bihar. It should focus more resources on malnutrition, even if it means reducing resources for other parts of its mission. ICDS should focus on the youngest children, especially from 0-2, who are most vulnerable to the lasting damage of malnutrition and cannot defend themselves. ICDS should determine why SNP and THR sometimes favour one sex over the other, and ensure that children with the highest need benefit the most. Urban AWCs should have a higher rental allowance to reflect the higher cost of rent necessary to have healthy spaces for children and AWWs. Finally, ICDS must ensure proper disposal of used immunisation needles to protect public health. I believe these findings and recommendations can help ICDS to better use and focus its limited resources on nutrition, arguably the most important area of intervention. If children are severely malnourished at a young age they will not be able to benefit fully from pre-school education, reach their mental and physical potential, or contribute fully to the development of Bihar and India. ICDS can make an impact on millions of children if focuses its resources wisely on the nutrition of the youngest and most vulnerable children. 39