Abstract: Background: Malnutrition and anemia are 2 severe public health concerns, predominantly in low-and middle-income nations. Malnutrition is defined as poor nutritional condition that encompasses both under nutrition and over nutrition. The prevalence of overweight or obesity and anemia has increased in India from 2016 to 2021. The study aims to investigate the spatial clustering and factors responsible for underweight, overweight/obesity, and anemia among reproductive women (15-49 years) in India using the data from National Family and Health Survey-5 (2019-2021). Methods: We conducted hot-spot analysis using Moran's Index (MI) with the help of spatial analysis software (i.e., GeoDa 1.18 and ArcGIS 10.8). It also demonstrates the autocorrelation. Multivariable logistic regression analysis has been performed to examine different determinants and risk associated with underweight, overweight/obesity, and anemia with various dependent variable by using Stata-14 software. Results: Moran's Index for underweight (MI = 0.68), overweight/obesity (MI = 0.72), and anemia (MI = 0.62) indicates a high level of spatial-autocorrelation (P <.001) exists across the districts in India. As a result, a total of 156, 143, and 126 hot-spot districts are detected for underweight, overweight/obesity, and anemia, respectively. The burden of undernutrition and anemia is higher in rural areas. Risk of under nutrition and anemia are both reduced by media exposure and eating habits. Moreover, low income and low education level raises the risk of anemia and undernutrition, while obesity shows an inverse trend with income and education level. Conclusion: The study recommends targeting hot-spot districts for malnutrition and anemia, and policy level initiatives by addressing the responsible risk factors. Plain language title: Spatial Clustering of Malnutrition and Anemia Among Women Across Districts in India Plain language summary: Most of the low-income and middle-income countries are affected by the double burden of malnutrition. Malnutrition and anemia are 2 severe public health concerns, predominantly in low-and middle-income nations. However, the prevalence of undernutrition among women of reproductive age in India has decreased, while the prevalence of overweight or obesity and anemia has also increased in India from 2016 to 2021. The study aims to investigate the spatial clustering and factors responsible for nutritional deficiency and anemia among reproductive women (15-49 years) in India using the data from National Family and Health Survey-5 (2019-2021). This information is expected to help with district-level policy formulation and advocacy, which can, in turn, can play an important role in reducing nutritional deficiency and anemia among women. The results of spatial analysis show the Moran's Index (MI) for underweight (MI = 0.68), overweight/obesity (MI = 0.72), and anemia (MI = 0.62) indicates a high level of spatial-autocorrelation (P <.001) (i.e., districts are similar to each other) exists across the districts in India. A total of 156, 143, and 126 hot-spot districts are detected for underweight, overweight/obesity, and anemia, respectively. The burden of undernutrition and anemia is higher in rural areas. Risk of undernutrition and anemia are both reduced by media exposure and eating habits. Low income and low education level rises the risk of anemia and undernutrition, while obesity shows an inverse trend with income and education level. Based on these findings, the present study recommends to implement a district level policy by targeting hot spot districts. The needful preventive measures as suggested in the study can also be implemented to control the incident and burden of women's malnutrition and anemic status in India. [ABSTRACT FROM AUTHOR]
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