Analysis of Nutritional Status of Women of Child-Bearing Age Using Modified Bayesian Geoadditive Quantile Regression Model.

Abstract

In a recent research endeavour, an evaluation was conducted to gauge the nutritional status (well-being) of women in Nigeria who are of reproductive age. Utilizing a modified Bayesian Geoadditive Quantile Regression Model, the study delved into data sourced from the 2018 Nigeria Demographic and Health Survey (NDHS), with computational analysis carried out through the R-software. The findings illuminated several pivotal determinants impacting the nutritional health of these women. Specifically, variables such as age, residential location, professional engagement, and the size of the household exerted a favorable influence on their nutritional status. This emphasizes the multifaceted nature of factors influencing nutritional outcomes among Nigerian women of reproductive age. Given these insights, there emerges a palpable imperative for concerted efforts aimed at ameliorating the prevalence of malnutrition in this demographic group. Both governmental bodies and non-governmental entities are thus called upon to formulate and implement targeted interventions. Such interventions could encompass the design and delivery of tailored nutritional education initiatives and other pertinent programs. By aligning interventions with the unique requirements and circumstances of women of reproductive age in Nigeria, it becomes feasible to foster improved nutritional outcomes and overall well-being in this critical demographic.