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Non-PR, IFPRI1; CRP2; CRP4; R5N Operational Research; 2 Promoting Healthy Diets and Nutrition for all; DCA, PHND; A4NH; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM); CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), Little is known about how the COVID-19 pandemic (C19) has affected food security and farmers' livelihoods in Sri Lanka, a country which has experienced multiple C19 waves with an increasing caseload over time. We examined food insecurity experience, perceived effects of C19 on health and livelihoods, and coping mechanisms employed among rural farming households at two timepoints during the pandemic.

Non-PR, IFPRI1; POSHAN; CRP4; 2 Promoting Healthy Diets and Nutrition for all; DCA, SAR; PHND; A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings here are based on data from the National Family Health Survey (NFHS) 3 (2005-2006), 4 (2015-2016), and 5 (2019-2020). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework and uses data from NFHS-5 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.

Non-PR, IFPRI1; POSHAN; CRP4; 2 Promoting Healthy Diets and Nutrition for all; DCA, SAR; PHND; A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings here are based on data from the National Family Health Survey (NFHS) 3 (2005-2006), 4 (2015-2016), and 5 (2019-2020). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework and uses data from NFHS-5 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.

Non-PR, IFPRI1; POSHAN; CRP4; 2 Promoting Healthy Diets and Nutrition for all; DCA, SAR; PHND; A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), This Data Note describes the trends for a set of key nutrition and health outcomes, determinants, and coverage of interventions. The findings here are based on data from the National Family Health Survey (NFHS) 3 (2005-2006), 4 (2015-2016), and 5 (2019-2020). In addition to standard prevalence-based analyses, this Data Note includes headcount-based analyses aligned to the POSHAN Abhiyaan monitoring framework and uses data from NFHS-5 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.

PR, IFPRI3; ISI; 2 Promoting Healthy Diets and Nutrition for all; Capacity Strengthening; POSHAN; CRP4, PHND; A4NH; SAR, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), Rapid urban expansion has important health implications. This study examines trends and inequalities in undernutrition and overnutrition by gender, residence (rural, urban slum, urban non-slum), and wealth among children and adults in India. We used National Family Health Survey data from 2006 and 2016 (n = 311,182 children 0-5y and 972,192 adults 15-54y in total). We calculated differences, slope index of inequality (SII) and concentration index to examine changes over time and inequalities in outcomes by gender, residence, and wealth quintile. Between 2006 and 2016, child stunting prevalence dropped from 48% to 38%, with no gender differences in trends, whereas child overweight/obesity remained at ~7–8%. In both years, stunting prevalence was higher in rural and urban slum households compared to urban non-slum households. Within-residence, wealth inequalities were large for stunting (SII: -33 to -19 percentage points, pp) and declined over time only in urban non-slum households. Among adults, underweight prevalence decreased by ~13 pp but overweight/obesity doubled (10% to 21%) between 2006 and 2016. Rises in overweight/obesity among women were greater in rural and urban slum than urban non-slum households. Within-residence, wealth inequalities were large for both underweight (SII -35 to -12pp) and overweight/obesity (+16 to +29pp) for adults, with the former being more concentrated among poorer households and the latter among wealthier households. In conclusion, India experienced a rapid decline in child and adult undernutrition between 2006 and 2016 across genders and areas of residence. Of great concern, however, is the doubling of adult overweight/obesity in all areas during this period and the rise in wealth inequalities in both rural and urban slum households. With the second largest urban population globally, India needs to aggressively tackle the multiple burdens of malnutrition, especially among rural and urban slum households and develop actions to maint

Non-PR, IFPRI5; CRP4, PHND; A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), Objectives: Little is known about how the COVID-19 pandemic (C19) has affected food security and farmers’ livelihoods in Sri Lanka. In this study, we assessed food security, perceived impacts of C19 and coping mechanisms to deal with these impacts. Methods: As part of a baseline survey for an evaluation of the World Food Programme's Nutrition-Sensitive Food Assistance for Assets Program in Sri Lanka, we conducted ∼1300 quantitative household phone surveys across five districts between December 2020 and February 2021. Food insecurity was assessed using the 8-item Food Insecurity Experience Scale and categorized as moderate or severe using the Rasch model. Perceived impacts of C19 and the coping mechanisms used to deal with these shocks were assessed via questionnaire. Additionally, we explored how these experiences varied by wealth quintile, highest attained education level in the household, and district. Results: Despite having had a relatively low burden of C19 cases in Sri Lanka compared to other countries, 85% of respondents in our sample reported being affected in some way by C19 or its associated control measures. Reported impacts include those on income (77% overall, 89% in lowest quintile, 62% in highest quintile) and agriculture activities (76% overall, 65% in lowest quintile, 87% in highest quintile), among others. Normal crop cultivation and harvesting was adversely impacted due to being advised to stay home (42%), being unable to purchase inputs (33%) and poor demand in the market (56%). In response to COVID shocks, about 30% of respondents in the lowest two wealth quintiles reported selling their livestock and about 20% of respondents across all wealth quintiles reported selling other assets. Half of the households interviewed were either moderately (36%) or severely (14%) food insecure. The proportion of households experiencing food insecurity varied by wealth quintile (mod: 55%-21%; sev: 27%-5%) and district (mod: 46%-29%; sev: 21%-10%). Conclusions: H

PR, IFPRI3; ISI; DCA, PHND

Non-PR, IFPRI5; CRP4, PHND; A4NH, CGIAR Research Programs on Agriculture for Nutrition and Health (A4NH), South Asia carries the largest burden of malnutrition globally. Tracking coverage of nutrition interventions is a critical step in designing effective nutrition policies and monitoring progress in the region. This paper examines coverage, trends, and inequities in nutrition interventions in South Asia.

Non-PR, IFPRI1; POSHAN; 2 Promoting Healthy Diets and Nutrition for all, PHND; SAR