Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India

Kim, Rockli; Bijral, Avleen S.; Xu, Yun; Zhang, Xiuyuan; Blossom, Jeffrey; Swaminathan, Akshay; King, Gary; Kumar, Alok; Sarwal, Rakesh; Ferres, Juan M. Lavista; Subramanian, S. V.

doi:10.1073/pnas.2025865118

Cited by 16 publications

(19 citation statements)

References 41 publications

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“…One issue with the NNS, however, is its explicit focus on districts. In the context of child malnutrition, some of the geographic variation is attributable to between-district differences (13), while other studies have shown that a larger share of the variation is attributable to states (14,15) and villages (16)(17)(18), a consequence of the geographic clustering of risk factors (19). Recent studies have also elucidated the small area variation of anthropometric failure within districts.…”

Section: Introductionmentioning

confidence: 99%

Small Area Variations in Dietary Diversity Among Children in India: A Multilevel Analysis of 6–23-Month-Old Children

et al. 2022

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Dietary diversity is an important indicator of child malnutrition. However, little is known about the geographic variation of diet indicators across India, particularly within districts and across states. As such, the purpose of this paper was to elucidate the small area variations in diet indicators between clusters within districts of India. Overall, we found that clusters were the largest source of variation for children not eating grains, roots, and tubers, legumes and nuts, dairy, vitamin A-rich vegetables and fruits, and other vegetables and fruits. We also found positive correlations between the district percent and cluster standard deviations of children not breastfeeding or eating grains, roots, and tubers, but negative correlations between the district percent and cluster standard deviation for the remaining seven outcomes. These findings underscore the importance of targeting clusters to improve child dietary diversity.

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Section: Introductionmentioning

confidence: 99%

Small Area Variations in Dietary Diversity Among Children in India: A Multilevel Analysis of 6–23-Month-Old Children

et al. 2022

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“…Focusing solely on the district-level estimates overlooks any small area variation within districts in the reported outcomes, as anemia prevalence at different geographical levels (states, districts, villages) can differ significantly depending on the area. Recent research shows that in the case of anthropometric failures such as stunting, geographic variation attributable to states ( 13 , 14 ), and villages ( 15 – 17 ) is much higher than variation between districts. ( 18 ).…”

Section: Introductionmentioning

confidence: 99%

Small area variation in severe, moderate, and mild anemia among women and children: A multilevel analysis of 707 districts in India

Rajpal

Kumar

Rana

et al. 2022

Front. Public Health

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India is home to the highest global number of women and children suffering from anemia, with one in every two women impacted. India's current strategy for targeting areas with a high anemia burden is based on district-level averages, yet this fails to capture the substantial small area variation in micro-geographical (small area) units such as villages. We conducted statistical and econometric analyses to quantify the extent of small area variation in the three grades of anemia (severe, moderate, and mild) among women and children across 36 states/union territories and 707 districts of India. We utilized data from the fifth round of the National Family Health Survey conducted in 2019–21. The final analytic sample for analyses was 183,883 children aged 6–59 months and 690,153 women aged 15–49 years. The primary outcome variable for the analysis was the three anemia grades among women and children. We adopted a three-level and four-level logistic regression model to compute variance partitioning of anemia among women and children. We also computed precision-weighted prevalence estimates of women and childhood anemia across 707 districts and within-district, between-cluster variation using standard deviation (SD). For severe anemia among women, small area (villages or urban blocks) account for highest share (46.1%; Var: 0.494; SE: 0.150) in total variation followed by states (39.4%; Var: 0.422; SE: 0.134) and districts (12.8%; Var: 0.156; SE: 0.012). Similarly, clusters account for the highest share in the variation in severe (61.3%; Var: 0.899; SE: 0.069) and moderate (46.4%: Var: 0.398; SE: 0.011) anemia among children. For mild and moderate anemia among women, however, states were the highest source of variation. Additionally, we found a high and positive correlation between mean prevalence and inter-cluster SD of moderate and severe anemia among women and children. In contrast, the correlation was weaker for mild anemia among women (r = 0.61) and children (0.66). In this analysis, we are positing the critical importance of small area variation within districts when designing strategies for targeting high burden areas for anemia interventions.

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“…[ 5 ] The program’s scale is huge – it covers every village in the country’s 36 states and union territories. [ 6 ]…”

Section: Introductionmentioning

confidence: 99%

The Efficiency of Anganwadi Centers Located in Rural Field Practice Area of a Medical College in North India

Sengar

Kunwar

Mishra

2022

Indian Journal of Community Medicine

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Background: The Integrated Child Development Services (ICDS) scheme was launched in 1975 for the improvement in maternal and child health and nutrition. The services under ICDS are implemented through Anganwadi centers (AWCs) and are delivered by Anganwadi workers (AWWs) at grassroots level. To evaluate the efficiency of all AWCs located in the field practice area of the medical college in North India, using data envelopment analysis (DEA) technique. Materials and Methods: A cross-sectional study was conducted in the catchment area of rural health training center. Each of the 15 AWCs was considered a decision-making unit (DMU), and physical structure and logistics were included as input variables; and percentage of beneficiaries receiving supplementary nutrition and health checkups were included as output variables. DEA technique was used to calculate the efficiency score for each DMU with the help of DEAOS free online software. Results: DMU 14th was found to be most efficient (100%) and DMU second was the least efficient (45%). DMU 13 and 14 demonstrated a level of performance that is superior to all other DMUs. DMU 13th and 14th were, therefore, considered 100% efficient. DEA analysis showed that total output increases and/or input reductions were required for making the inefficient DMUs efficient. Conclusion: Most of the AWCs were inefficient and an improvement in the infrastructure and logistics is likely to improve the efficiency of AWCs.

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Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India

Cited by 16 publications

References 41 publications

Small Area Variations in Dietary Diversity Among Children in India: A Multilevel Analysis of 6–23-Month-Old Children

Small Area Variations in Dietary Diversity Among Children in India: A Multilevel Analysis of 6–23-Month-Old Children

Small area variation in severe, moderate, and mild anemia among women and children: A multilevel analysis of 707 districts in India

The Efficiency of Anganwadi Centers Located in Rural Field Practice Area of a Medical College in North India

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