Undernutrition among children and its determinants across the parliamentary constituencies of India: a geospatial analysis.

In India, undernutrition among children has been extremely critical for the last few decades. Most analyses of undernutrition among Indian children have used the administrative boundaries of a state or a district level as a unit of analysis. This paper departs from such a practice and focuses instead on the political boundaries of a parliamentary constituency (PC) as the unit of analysis. The PC is a critical geopolitical unit where political parties and party candidates make election promises and implement programmes to improve the socio-economic condition of their electorate. A focus on child undernutrition at this level has the potential for greater policy and political traction and could lead to a paradigm shift in the strategy to tackle the problem by creating a demand for political accountability. Different dimensions and new approaches are also required to evaluate the socio-economic status and generate concrete evidence to find solutions to the problem. Given the significance of advanced analytical methods and models embedded into geographic information system (GIS), the current study, for the first time, uses GIS tools and techniques at the PC level, conducting in-depth analysis of undernutrition and its predictors. Hence, this paper examines the spatial heterogeneity in undernutrition across PCs by using geospatial techniques such as univariate and bivariate local indicator of spatial association and spatial regression models. The analysis highlights the high-low burden areas in terms of local hotspots and identifies the potential spatial risk factors of undernutrition across the constituencies. Striking variations in the prevalence of undernutrition across the constituencies were observed. Most of these constituencies that performed poorly both in terms of child nutrition and socio-economic indicators were located in the northern, western, and eastern parts of India. A statistically significant association of biological, socio-economic, and environmental factors such as women's body mass index, anaemia in children, poverty, household sanitation facilities, and institutional births was established. The results highlight the need to bring in a mechanism of political accountability that directly connects elected representatives to maternal and child health outcomes. The spatial variability and pattern of undernutrition indicators and their correlates indicate that priority setting in research may also be greatly influenced by the neighbourhood association.

Stillbirth rates and its spatial patterns in India: an exploration of HMIS data.

Background: High prevalence of stillbirths is a significant concern for the health system of India. This necessitates a closer scrutiny of the prevalence, spatial pattern and the risk factors of stillbirth at both national and local level. Methods: We analysed stillbirth data of three financial years (April 2017-March 2020) from Health Management Information System (HMIS) of India which provides majorly public facility level data for stillbirths up to the district level on a monthly basis. National and state level prevalence of stillbirth rate (SBR) were estimated. Spatial patterns of SBR at district level was identified using local indicator of spatial association (LISA). Risk factors of stillbirths were studied by triangulation of HMIS and National Family Health Survey (NFHS-4) data using bivariate LISA. Findings: National average of SBR in 2017-18, 2018-2019 and 2019-2020 are 13.4 [4.2-24.2], 13.1 [4.2-22.2] and 12.4 [3.7-22.5] respectively. Districts of Odisha, Madhya Pradesh, Rajasthan and Chhattisgarh (OMRC) form a contiguous east-west belt of high SBR. Body mass index (BMI) of the mother, antenatal care (ANC), maternal anemia, iron-folic acid (IFA) supplementation and institutional delivery show significant spatial autocorrelation with SBR. Interpretation: Maternal and child health programme delivery should prioritise targeted intervention in the hotspot clusters of high SBR, considering the locally significant determinants. The findings show inter alia, the need to focus on ANC to reduce stillbirth in India. Funding: The study is not funded.

Region matters: Mapping the contours of undernourishment among children in Odisha, India.

BACKGROUND: Levels of child undernutrition and its correlates exhibit considerable spatial variation at different levels of granularity. In India, such variations and their interrelation have not been studied at the sub-district level primarily due to the non-availability of good quality granular data. Given the sheer regional diversity in India, it is essential to develop a region-specific evidence base at the micro-level. DATA AND OBJECTIVES: The current study utilised, for the first time, a sub-district level survey data (Concurrent Child Monitoring Survey-II, 2014-15) to investigate the statistically significant clusters and spatial patterns of burden of undernutrition among children. The emergence of distinct patterns at the level of natural geographical regions of the state-coastal, southern and northern regions, lead to a region-specific analysis to measure the impact of various demographic, socio-economic and maternal factors on the prevalence of undernutrition specific to the three regions, using the National Family Health Survey-IV unit-level data. METHODS: The spatial dependence and clustering of child undernourishment across sub-districts in Odisha were studied using various spatial statistical techniques, including spatial econometric models. Binary logistic regression was applied in the region-specific analysis. RESULTS: Findings indicated statistically significant spatial clustering of undernutrition among children in specific geographic pockets with poor sanitation, low institutional and skilled deliveries, poor maternal health reinforcing the need for inter-sectoral coordination. Disparities across the three natural-regions, suggest that the parameters requiring priority for intervention may differ across levels of overall development. CONCLUSION: The spatial clustering of different socio-demographic indicators in specific geographic pockets highlights the differential impact of these determinants on child undernutrition thereby reinforcing a strong need for targeted intervention in these areas. Present analysis and the evidence-based micro-level analysis can be utilised as a model for other Indian states and low-resource countries, making interventions more effective through multiple, synergistic and a multi-sectoral approach.