Despite sustained economic growth and reduction in money metric poverty in last two decades, prevalence of malnutrition remained high in India. During 1992–2016, the prevalence of underweight among children had declined from 53% to 36%, stunting had declined from 52% to 38% while that of wasting had increased from 17% to 21% in India. The national average in the level of malnutrition conceals large variation across districts of India. Using data from the recent round of National Family Health Survey (NFHS), 2015–16 this paper examined the spatial heterogeneity and meso-scale correlates of child malnutrition across 640 districts of India. Moran’s I statistics and bivariate LISA maps were used to understand spatial dependence and clustering of child malnutrition. Multiple regression, spatial lag and error models were used to examine the correlates of malnutrition. Poverty, body mass index (BMI) of mother, breastfeeding practices, full immunization, institutional births, improved sanitation and electrification in the household were used as meso scale correlates of malnutrition. The univariate Moran’s I statistics was 0.65, 0.51 and 0.74 for stunting, wasting and underweight respectively suggesting spatial heterogeneity of malnutrition in India. Bivariate Moran’s I statistics of stunting with BMI of mother was 0.52, 0.46 with poverty and − 0.52 with sanitation. The pattern was similar with respect to wasting and underweight suggesting spatial clustering of malnutrition against the meso scale correlates in the geographical hotspots of India. Results of spatial error model suggested that the coefficient of BMI of mother and poverty of household were strong and significant predictors of stunting, wasting and underweight. The coefficient of BMI in spatial error model was largest found for underweight (β = 0.38, 95% CI: 0.29–0.48) followed by stunting (β = 0.23, 95% CI: 0.14–0.33) and wasting (β = 0.11, 95% CI: 0.01–0.22). Women’s educational attainment and breastfeeding practices were also found significant for stunting and underweight. Malnutrition across the districts of India is spatially clustered. Reduction of poverty, improving women’s education and health, sanitation and child feeding knowledge can reduce the prevalence of malnutrition across India. Multisectoral and targeted intervention in the geographical hotspots of malnutrition can reduce malnutrition in India.

Background: Although hepatitis B vaccinations have been integrated in the Universal Immunization Program (UIP) in India over a decade, only half of the children are immunized against hepatitis B. The national average in hepatitis B vaccination conceals large variations across states, districts and socio-economic groups. In this context, the aim of this paper is to examine the spatial heterogeneity and contextual determinants of hepatitis B vaccination across the districts of India. Methods: Using data of 199,899 children aged 12–59 months from the National Family Health Survey-4 (NFHS-4), 2015–16 we have examined the district level spatial distribution and clustering of hepatitis B vaccination with the help of Moran’s I and Local Indicator of Spatial Autocorrelation (LISA) measures. We investigated the low coverage of HBV vaccination using spatial autoregressive models (SAR) at the meso scale. And we applied multivariate binary logistic regression analysis to understand the micro-level predictors of hepatitis B vaccination. Results: In 2015–16, 45% of the children aged 12–59 months were not vaccinated against hepatitis B in India. The coverage of hepatitis B vaccine across the districts of India showed a highly significant spatial dependence (Moran’s I = 0.580). Bivariate Moran’s I confirmed the spatial clustering of hepatitis B vaccination with mother’s education, full antenatal care (ANC) utilization, post natal care (PNC) utilization, institutional births and registration of births at the district level. Districts with a very low coverage of HBV vaccine are clustered in the western, north-eastern regions and in some parts of central India. At the unit (child) level, children’s hepatitis B immunization status is mostly determined by the socio-economic and demographic characteristics like their mother’s educational status, caste, religion, household’s wealth condition, birth order, year of birth and the region they belong to. Conclusions: District level variation in hepatitis B vaccination is spatially heterogeneous and clustered in India with a strong neighbourhood effect. Uptake of hepatitis B vaccine among Indian children is predominantly dependent upon their socio-economic and demographic characteristics.

Despite the universalization of immunization against the six vaccine-preventable diseases (VPDs), the coverage of full immunization among the children under age five has remained a challenge globally. The 2015–16 National Family Health Survey (NFHS) indicated large disparity in the coverage of different vaccination doses (BCG, Polio, DPT and Measles) including full immunization across the districts of India. The spatial distribution of poor performing districts in terms of vaccination and the district level spatial, contextual determinants contributing to the low coverage have been poorly studied. Using the recent household survey (NFHS, 2015–16), this study examined the spatial heterogeneity and the factors associated with low vaccination coverage among the children aged 12–23 months across India. This study used the data from fourth round of National Family Health Survey conducted in 2015–16. District-level prevalence of each of the vaccination doses including full immunization, were analysed. Moran’s I, Univariate and Bivariate LISA, Ordinary least square (OLS) and spatial models were employed to achieve the overall aim of the study. At the national level, the prevalence of full immunization was 62 percent. Specific vaccination coverage for BCG, three doses of polio, three doses of DPT and measles were 92, 73, 78 and 81 percent, respectively. The value of the bivariate Moran’s I statistics confirmed the spatial dependence between specific vaccination and the set of independent variables. District-level prevalence of the specific vaccine and full immunization showed significant spatial clustering across India. The adjusted coefficients from the spatial error model confirmed that district-level proportion of utilization of post-natal care, institutional births, neonatal tetanus protection of the last birth, women’s education and coverage of health insurance showed statistically significant association with every doses of vaccination coverage. The full and specific immunization coverage was considerably low in the geographical hotspots as compared to the national coverage. Maternal and child health care services utilization, financial assistance to the mothers through JSY scheme and mother’s education were found to determine full immunization as well as the specific vaccination coverage. Appropriate intervention should be designed to reduce the geographical disparity in the coverage of specific and full immunization across India and thus safeguard child health protecting the children from the vaccine preventable diseases across the geography.

The public health burden of nutritional deficiency and child mortality is the major challenge India is facing upfront. In this context, using National Family Health Survey, 2015–16 data, this study estimated rate of composite index of anthropometric failure (CIAF) among Indian children by their population characteristics, across states and examined the multilevel contextual determinants. We further investigated district level burden of infant and child mortality in terms of multiple anthropometric failure prevalence across India. The multilevel analysis confirms a significant state, district and PSU level variation in the prevalence of anthropometric failures. Factors like- place of residence, household’s economic wellbeing, mother’s educational attainment, age, immunization status and drinking water significantly determine the different forms of multiple anthropometric failures. Wealth status of the household and mother’s educational status show a clear gradient in terms of the estimated odds ratios. The district level estimation of infant and child mortality demonstrates that districts with higher burden of multiple anthropometric failures show elevated risk of infant and child mortality. Unlike previous studies, this study does not use the conventional indices, instead considered the CIAF to identify the exact and severe form of undernutrition among Indian children and the associated nexus with infant and child mortality at the district level.