Prevalence and correlates of multidimensional child poverty in India during 2015–2021: A multilevel analysis

Abstract

Despite increasing research and programs to eradicate poverty, poverty still exists and is a far greater concern for children than adults, leading child poverty to become a political, economic, and social issue worldwide and in India. The current study aims to find variations in the prevalence of child poverty and associated factors in India during 2015–21. In the current study, we used two consecutive rounds of the National Family Health Survey (NFHS-4, 2015–16 & NFHS-5, 2019–21) to estimate child poverty (aged 0–59 months) using the Alkire-Foster method. The multilevel logistic regression analyses were performed to find the important cofounder and cluster level variation in child poverty. The results show that about 38 percent of children were multidimensionally poor in 2015–16, which reduced to 27 percent in 2019–21. The decomposition analysis suggests that contribution of nutrition domain to child poverty increases over time, whereas the standard of living substantially declines from NFHS-4 to NFHS-5. The multilevel analysis results show that the age and sex of the child, age and years of schooling of the mother, children ever born, religion, caste, wealth quintile and central, northeast, north and west regions are significantly associated with child poverty over time. Further, the variance participation coefficient statistics show that about 12 percent of the variation in the prevalence of child poverty could be attributed to differences at the community level. The prevalence of child poverty significantly declines over time, and the community-level variation is higher than the district-level in both surveys. However, the community-level variation shows increases over time. The finding suggests a need to improve the nutritional status and standard of living of most deprived households by promoting a child-centric and dimension-specific approach with more focus on PSU-level intervension should adopt in order to lessen child poverty in India.

The Spatial Effects of Regional Poverty: Spatial Dependence, Spatial Heterogeneity and Scale Effects

“…For example, the terrain type, per capita cultivated land area, and labor force ratio were significant at the village level, while the per capita income, vegetation coverage, and terrain relief were significant at the county level [35]. The multilevel analysis of multidimensional child poverty in India showed that the age and sex of the child, age and years of schooling of the mother, children ever born, religion, caste, wealth quintile, and central, northeast, north and west regions are significantly associated with child poverty [36].…”