Global success case analyses have identified factors supporting reductions in stunting across cou... more Global success case analyses have identified factors supporting reductions in stunting across countries; less is known about successes at the subnational levels. We studied four states in India, assessing contributors to reductions in stunting between 2006 and 2016. Using public datasets, literature review, policy analyses and stakeholder interviews, we interpreted changes in the context of policies, programs and enabling environment. Primary contributors to stunting reduction were improvements in coverage of health and nutrition interventions (ranged between 11 to 23% among different states), household conditions (22–47%), and maternal factors (15–30%). Political and bureaucratic leadership engaged civil society and development partners facilitated change. Policy and program actions to address the multidimensional determinants of stunting reduction occur in sectors addressing poverty, food security, education, health services and nutrition programs. Therefore, for stunting reductio...
Introduction and Methods: A community-based cross-sectional, descriptive study was carried out on... more Introduction and Methods: A community-based cross-sectional, descriptive study was carried out on urban adolescents (n = 545, 11–18 years, 62.0% girls) residing in Delhi. Information pertaining to their detailed meal pattern was collected. Results: Approximately 75% adolescents from urban slums (US), low income group (LIG), and middle income group (MIG) were non-vegetarian. Highest percentage of vegetarians (27.4%) and ovo-vegetarians (19.9%) belonged to high income group (HIG). Adolescents from HIG reported the highest mean number of meals (weekdays - 5.16 ± 0.887 and weekends - 4.85 ± 1.026) and adolescents from LIG reported the lowest mean number of meals (weekdays - 4.31 ± 0.777 and weekends - 4.26 ± 0.846). Dinner was the main meal consumed by ≥99% adolescents from all four SES both on weekdays and weekends. Highest proportions of adolescents from LIG were consuming other main meals such as breakfast (97.8%) and lunch (97.0%) on weekdays and weekends. Adolescents from HIG repor...
Optimal infant and young child feeding (IYCF) practices and immunization play a critical role in ... more Optimal infant and young child feeding (IYCF) practices and immunization play a critical role in averting childhood illness and in achieving optimal growth and development among children. This was a cross-sectional study that assessed the morbidity and immunization status of children 6–23 months of age in three income groups in Delhi. The study also assessed feeding practices for children during illness. Results showed that the prevalence of diarrhea in the past 2 weeks preceding the survey was 8.6%, 18.3%, and 17.7% in urban slum, low-income group (LIG), and middle-income group (MIG), respectively. About 50% of children in LIG and MIG and about 45% in the urban slum had fever in the past 2 weeks preceding the survey. About 20% of mothers in urban slum and LIG reported that they were not washing their hands with soap before preparing food for their children. Although most of the children with diarrhea had received oral rehydration salts, they had not received zinc which is critical ...
India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFH... more India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFHS-3 (2005-2006) national report and data [IFPRI estimates] and NFHS-5 (2019-2021) national and state factsheets. Anemia among non-pregnant and pregnant women for 2005-2006 are IFPRI estimates using woman dataset. 1 WHO. Nutrition Landscape Information System (NLiS). Help Topic: Malnutrition in children. Stunting, wasting, overweight, and underweight. (https://apps.who.int/nutrition/landscape/help.aspx?menu=0&helpid=391&lang=EN). 2 In NFHS-3, 87.9% of data were missing and 46.6% of data were missing in NFHS-4. 3 NA refers to the unavailability of data for a particular indicator in the specified NFHS round. UTTAR PRADESH This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings are based on estimates using unit-level data, data from national and state reports from the National Family Health Survey (NFHS)-3 (2005-2006) and NFHS-4 (2015-2016), and data from state factsheets and reports from NFHS-5 (2019-2021). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework to provide evidence that helps identify priority districts and number of districts in the state with public health concern as per the WHO guidelines. 1 The Data Note includes a color-coded dashboard to compare the coverage of nutrition interventions across all the districts in the state. It concludes with key takeaways for children, women, and men, and identifies areas where the state has potential to improve. 25 2 21 2 NA 3
India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFH... more India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFHS-3 (2005-2006) national report and data [IFPRI estimates] and NFHS-5 (2019-2021) national and state factsheets. Anemia among non-pregnant and pregnant women for 2005-2006 are IFPRI estimates using woman. 1 WHO. Nutrition Landscape Information System (NLiS). Help Topic: Malnutrition in children. Stunting, wasting, overweight, and underweight. (https://apps.who.int/nutrition/landscape/help.aspx?menu=0&helpid=391&lang=EN). 2 In NFHS-3, 60.4% of data were missing and 8.0% of data were missing in NFHS-4. 3 NA refers to the unavailability of data for a particular indicator in the specified NFHS round. ODISHA This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings are based on estimates using unit-level data, data from national and state reports from the National Family Health Survey (NFHS)-3 (2005-2006) and NFHS-4 (2015-2016), and data from state factsheets and reports from NFHS-5 (2019-2021). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework to provide evidence that helps identify priority districts and number of districts in the state with public health concern as per the WHO guidelines. 1 The Data Note includes a color-coded dashboard to compare the coverage of nutrition interventions across all the districts in the state. It concludes with key takeaways for children, women, and men, and identifies areas where the state has potential to improve.
This analysis on key nutrition indicators from successive rounds of the NFHS (4 and 5) is based o... more This analysis on key nutrition indicators from successive rounds of the NFHS (4 and 5) is based on all-India and State/UT level factsheet released by Ministry of Health and Family Welfare (MoHFW). The analysis includes: 1. National level trends from NFHS-3 (2005-06), NFHS-4 (2015-16) and NFHS-5 (2019-21) data for 44 indicators including outcomes, service delivery and key determinants of nutrition. 2. State level trends of same indicators- number of states showing improvement / worsening (± 0.1 percent point change), /no change for these indicators, spatial maps based on change in prevalence for these indicators; and charting State performance with respect to achieving Sustainable Development Goals (SDG 2030) targets. This presentation will be useful for policy makers, State administrators, public health experts, research scholars and research institutes in the area of maternal and child health & Nutrition.
Nonalcoholic fatty liver disease (NAFLD) is a lifestyle disease. Lack of physical activity can wo... more Nonalcoholic fatty liver disease (NAFLD) is a lifestyle disease. Lack of physical activity can worsen clinical condition of NAFLD patients. Objectives: To assess Physical activity (PA) levels (low, medium and high) among individuals with NAFLD and without NAFLD and to study relationship of PA with NAFLD. Methods: Case Control study with Ultrasound diagnosed NAFLD cases(n=160)and subjects without NAFLD(n=160)was conducted .The PA levels were studied using GPAQ, Version 2 , based on frequency and duration in work, travel and leisure domains. Results: NAFLD cases had significantly higher values of waist and hip circumference and WHR (p<0.05).More than 50 % of NAFLD cases were physically inactive compared to Controls.(p<0.05). Moderate level of PA, (OR 95% CI) ([2.6 (1.04-6.34), p=0.006)] and low PA ([6.0 (2.40-14.85), p<0.001)] were associated as a risk factor for NAFLD. Conclusion: Low and Moderate level of Physical Activity is a risk factor for NAFLD.
The present study was conducted to assess the usefulness of MUAC as a screening tool to assess nu... more The present study was conducted to assess the usefulness of MUAC as a screening tool to assess nutritional status during pregnancy (>20 weeks). Pregnant women (>20 weeks of gestation, n=100) were enrolled from tertiary care ANC clinics in urban areas of Delhi. Data on socio-demographic profile was collected using pre-tested questionnaires. The blood pressure and anthropometric parameters (weight, height and MUAC) were recorded. The mean height, weight and MUAC of pregnant women were 152.15 ± 4.93cm, 56.7 ± 6.7Kgs and 25.5 ± 2.60cm respectively. Weight gain between trimesters and overall weight gain showed no correlation with blood pressure. Maternal weight was positively correlated with MUAC (p=0.00), SBP (p=0.006) and DBP (p=0.02). Maternal height was negatively correlated with MUAC (p=0.012). BMI and MUAC showed a significantly positive correlation (p=0.00), which indicates the versatility of this tool. However, no association was observed between MUAC and blood pressure dur...
Global success case analyses have identified factors supporting reductions in stunting across cou... more Global success case analyses have identified factors supporting reductions in stunting across countries; less is known about successes at the subnational levels. We studied four states in India, assessing contributors to reductions in stunting between 2006 and 2016. Using public datasets, literature review, policy analyses and stakeholder interviews, we interpreted changes in the context of policies, programs and enabling environment. Primary contributors to stunting reduction were improvements in coverage of health and nutrition interventions (ranged between 11 to 23% among different states), household conditions (22–47%), and maternal factors (15–30%). Political and bureaucratic leadership engaged civil society and development partners facilitated change. Policy and program actions to address the multidimensional determinants of stunting reduction occur in sectors addressing poverty, food security, education, health services and nutrition programs. Therefore, for stunting reductio...
Introduction and Methods: A community-based cross-sectional, descriptive study was carried out on... more Introduction and Methods: A community-based cross-sectional, descriptive study was carried out on urban adolescents (n = 545, 11–18 years, 62.0% girls) residing in Delhi. Information pertaining to their detailed meal pattern was collected. Results: Approximately 75% adolescents from urban slums (US), low income group (LIG), and middle income group (MIG) were non-vegetarian. Highest percentage of vegetarians (27.4%) and ovo-vegetarians (19.9%) belonged to high income group (HIG). Adolescents from HIG reported the highest mean number of meals (weekdays - 5.16 ± 0.887 and weekends - 4.85 ± 1.026) and adolescents from LIG reported the lowest mean number of meals (weekdays - 4.31 ± 0.777 and weekends - 4.26 ± 0.846). Dinner was the main meal consumed by ≥99% adolescents from all four SES both on weekdays and weekends. Highest proportions of adolescents from LIG were consuming other main meals such as breakfast (97.8%) and lunch (97.0%) on weekdays and weekends. Adolescents from HIG repor...
Optimal infant and young child feeding (IYCF) practices and immunization play a critical role in ... more Optimal infant and young child feeding (IYCF) practices and immunization play a critical role in averting childhood illness and in achieving optimal growth and development among children. This was a cross-sectional study that assessed the morbidity and immunization status of children 6–23 months of age in three income groups in Delhi. The study also assessed feeding practices for children during illness. Results showed that the prevalence of diarrhea in the past 2 weeks preceding the survey was 8.6%, 18.3%, and 17.7% in urban slum, low-income group (LIG), and middle-income group (MIG), respectively. About 50% of children in LIG and MIG and about 45% in the urban slum had fever in the past 2 weeks preceding the survey. About 20% of mothers in urban slum and LIG reported that they were not washing their hands with soap before preparing food for their children. Although most of the children with diarrhea had received oral rehydration salts, they had not received zinc which is critical ...
India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFH... more India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFHS-3 (2005-2006) national report and data [IFPRI estimates] and NFHS-5 (2019-2021) national and state factsheets. Anemia among non-pregnant and pregnant women for 2005-2006 are IFPRI estimates using woman dataset. 1 WHO. Nutrition Landscape Information System (NLiS). Help Topic: Malnutrition in children. Stunting, wasting, overweight, and underweight. (https://apps.who.int/nutrition/landscape/help.aspx?menu=0&helpid=391&lang=EN). 2 In NFHS-3, 87.9% of data were missing and 46.6% of data were missing in NFHS-4. 3 NA refers to the unavailability of data for a particular indicator in the specified NFHS round. UTTAR PRADESH This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings are based on estimates using unit-level data, data from national and state reports from the National Family Health Survey (NFHS)-3 (2005-2006) and NFHS-4 (2015-2016), and data from state factsheets and reports from NFHS-5 (2019-2021). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework to provide evidence that helps identify priority districts and number of districts in the state with public health concern as per the WHO guidelines. 1 The Data Note includes a color-coded dashboard to compare the coverage of nutrition interventions across all the districts in the state. It concludes with key takeaways for children, women, and men, and identifies areas where the state has potential to improve. 25 2 21 2 NA 3
India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFH... more India average Undernutrition among children (<5y) Undernutrition among women (15-49y) Source: NFHS-3 (2005-2006) national report and data [IFPRI estimates] and NFHS-5 (2019-2021) national and state factsheets. Anemia among non-pregnant and pregnant women for 2005-2006 are IFPRI estimates using woman. 1 WHO. Nutrition Landscape Information System (NLiS). Help Topic: Malnutrition in children. Stunting, wasting, overweight, and underweight. (https://apps.who.int/nutrition/landscape/help.aspx?menu=0&helpid=391&lang=EN). 2 In NFHS-3, 60.4% of data were missing and 8.0% of data were missing in NFHS-4. 3 NA refers to the unavailability of data for a particular indicator in the specified NFHS round. ODISHA This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings are based on estimates using unit-level data, data from national and state reports from the National Family Health Survey (NFHS)-3 (2005-2006) and NFHS-4 (2015-2016), and data from state factsheets and reports from NFHS-5 (2019-2021). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework to provide evidence that helps identify priority districts and number of districts in the state with public health concern as per the WHO guidelines. 1 The Data Note includes a color-coded dashboard to compare the coverage of nutrition interventions across all the districts in the state. It concludes with key takeaways for children, women, and men, and identifies areas where the state has potential to improve.
This analysis on key nutrition indicators from successive rounds of the NFHS (4 and 5) is based o... more This analysis on key nutrition indicators from successive rounds of the NFHS (4 and 5) is based on all-India and State/UT level factsheet released by Ministry of Health and Family Welfare (MoHFW). The analysis includes: 1. National level trends from NFHS-3 (2005-06), NFHS-4 (2015-16) and NFHS-5 (2019-21) data for 44 indicators including outcomes, service delivery and key determinants of nutrition. 2. State level trends of same indicators- number of states showing improvement / worsening (± 0.1 percent point change), /no change for these indicators, spatial maps based on change in prevalence for these indicators; and charting State performance with respect to achieving Sustainable Development Goals (SDG 2030) targets. This presentation will be useful for policy makers, State administrators, public health experts, research scholars and research institutes in the area of maternal and child health & Nutrition.
Nonalcoholic fatty liver disease (NAFLD) is a lifestyle disease. Lack of physical activity can wo... more Nonalcoholic fatty liver disease (NAFLD) is a lifestyle disease. Lack of physical activity can worsen clinical condition of NAFLD patients. Objectives: To assess Physical activity (PA) levels (low, medium and high) among individuals with NAFLD and without NAFLD and to study relationship of PA with NAFLD. Methods: Case Control study with Ultrasound diagnosed NAFLD cases(n=160)and subjects without NAFLD(n=160)was conducted .The PA levels were studied using GPAQ, Version 2 , based on frequency and duration in work, travel and leisure domains. Results: NAFLD cases had significantly higher values of waist and hip circumference and WHR (p<0.05).More than 50 % of NAFLD cases were physically inactive compared to Controls.(p<0.05). Moderate level of PA, (OR 95% CI) ([2.6 (1.04-6.34), p=0.006)] and low PA ([6.0 (2.40-14.85), p<0.001)] were associated as a risk factor for NAFLD. Conclusion: Low and Moderate level of Physical Activity is a risk factor for NAFLD.
The present study was conducted to assess the usefulness of MUAC as a screening tool to assess nu... more The present study was conducted to assess the usefulness of MUAC as a screening tool to assess nutritional status during pregnancy (>20 weeks). Pregnant women (>20 weeks of gestation, n=100) were enrolled from tertiary care ANC clinics in urban areas of Delhi. Data on socio-demographic profile was collected using pre-tested questionnaires. The blood pressure and anthropometric parameters (weight, height and MUAC) were recorded. The mean height, weight and MUAC of pregnant women were 152.15 ± 4.93cm, 56.7 ± 6.7Kgs and 25.5 ± 2.60cm respectively. Weight gain between trimesters and overall weight gain showed no correlation with blood pressure. Maternal weight was positively correlated with MUAC (p=0.00), SBP (p=0.006) and DBP (p=0.02). Maternal height was negatively correlated with MUAC (p=0.012). BMI and MUAC showed a significantly positive correlation (p=0.00), which indicates the versatility of this tool. However, no association was observed between MUAC and blood pressure dur...
Uploads
Papers by neena bhatia