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Mapping changes in district level prevalence of childhood stunting in India 1998-2016: An application of small area estimation techniques
Authors: Swati Srivastava, Hukum Chandra, Shri Kant Singh, and Ashish Kumar Upadhyay
Source: SSM: Population Health, Vol. 14
Topic(s): Child height
Data models
Spatial analysis
Country: Asia
Published: JUN 2021
Abstract: The four rounds of National Family Health Survey (NFHS) conducted during 1992–93, 1998–99, 2005-06 and 2015-16 is main source to track the health and development related indicators including nutritional status of children at national and state level in India. Except NFHS-4, first three rounds of NFHS were unable to provides district-level estimates of childhood stunting due to the insufficient sample sizes. The small area estimation (SAE) techniques offer a viable solution to overcome the problem of small sample size. Therefore, this study uses SAE techniques to derive district level prevalence of childhood stunting corresponding to NFHS-2 (1998–99). Study further estimated GIS maps, univariate Local indicator of spatial autocorrelation (LISA) and Moran's I to understand the trend in district level childhood stunting between NFHS-2 and NFHS-4. Estimates obtained by SAE techniques suggest that prevalence of childhood stunting ranges from 20.7% (95% CI: 18.8–22.7) in South Goa district of Goa to 64.4% (95%CI: 63.1–65.7) in Dhaulpur district of Rajasthan during 1998–99. The diagnostic measures used to validate the reliability of estimates obtained by SAE techniques indicate that the model-based estimates are reliable and representative at district level. Results of geospatial analysis indicates substantial reduction in childhood stunting between 1998 and 2016. Out of 640 district,about 81 district experience reduction of more than 50%. At the same time 60 district experience less than 10% of reduction between 1998 and 2016. Spatial clustering of childhood stunting remains same over the study period except few additional cluster in Maharashtra, Andhra and Meghalaya in 2016. The district level estimates obtained from this study might be helpful in framing decentralized policies and implementation of vertical programs to enhance the efficacy of various nutrition interventions in priority districts of the country.