Spatial Distribution of Various forms of Malnutrition Among Reproductive Age Women in Nepal: A Bayesian Geoadditive Quantile Regression Approach

Background: Confronting the poor nutritional status of women is a major challenge for a developing country like Nepal. This paper presented a critical analysis of factors associated with malnutrition using a Bayesian geoadditive quantile regression approach and assessed spatial variations of malnutrition among Nepalese women. Methods: Data drawn from the 2016 Nepal Demographic and Health Survey was used to assess the spatial distributions of four forms of malnutrition at the provincial level. Spatial and nonlinear components were estimated using Markov random fields and Bayesian P-splines, respectively. Results: Analysis of 6,159 reproductive age-group women suggests the existence of severe thinness and underweight in rural and among women residing in provinces 2, 5, and Sudurpashchim. Similarly, the likelihood of being obese was prominently high in urban residents and women in Bagmati, and Gandaki. Richest quintile women, followed by women in richer households, were more likely to be obese and overweight. Consistent findings were reported for underweight (e.g., women from poorer households, and women from households without improved toilet facility). Accessibility of mass media (e.g. newspaper, radio, TV) had inconsistent association with the forms of malnutrition. As women aged, likelihood of being overweight and obese became higher. Conclusion: Inconsistent distribution of various forms of malnutrition existed across provinces in Nepal, revealing dissimilar influence of other socio-economic variables. Health policy precisely addressing province- and location-specific under- and over-nutrition is, therefore, recommended. Elements of hygiene using mass media could be helpful to reach younger and the most impoverished sect of population.