District-Level Analysis of Inequality in Malnutrition Among Children: Evidence from Maharashtra, India

Abstract

Background and Objective: India currently faces the triple burden of malnutrition characterized by the coexistence of undernutrition and overnutrition along with micronutrient deficiencies. The unequal distribution of child health outcomes in the population may affect the goal of a ‘malnutrition free world’. The nutritional status and its inequalities among post under-five age have rarely been assessed in the country. This study examines the degree and extent of asset-based household wealth inequalities in malnutrition among preschool and school children in the Maharashtra state of India. Methods: The study utilizes the fourth round of the District Level Health Survey 2012-2013 to provide district-level estimates of the inequalities in five malnutrition indicators-stunting, wasting, underweight, overweight, and anemia among children. Concentration curves, normalized concentration index, geographical maps and correlation matrix are used to analyze the data by districts, rural-urban residence and gender. Results: Considerable proportion of children are malnourished in Maharashtra, even with its advanced economic status. Malnutrition levels among school going children are as high as those of children under six years of age. The findings indicate that malnutrition inequalities manifest primarily among the weaker sections of society. However, children from affluent households are more likely to suffer from overweight and obesity issues. The prevalence of malnutrition is higher in rural areas, but inequality is significantly higher in urban regions. The nutritionally backward areas are concentrated in the tribal districts of the Marathwada division and a few others from Vidarbha and Amravati. Many districts of Maharashtra have multiple burdens of malnutrition and have high inequalities on more than one indicator. A negative correlation is observed between the prevalence of malnutrition and human development indicators. Conclusion: There is a need to capture broader age groups in the nutrition monitoring frameworks. Recognizing the regional heterogeneity in the malnutrition prevalence and distribution calls for unique health intervention strategies to specific district targets.