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Research Article Open access CC BY 4.0

Geospatial Analysis of the Heterogeneity in Nutritional Status among Women of Childbearing Age in Nigeria

Ben, E, O., Lasisi K. E., Abdulkadir, A., Abdulrasheed B.

Asian Journal of Advanced Research and Reports · pp. 95–109 · Published 25 Apr 2024

10.9734/ajarr/2024/v18i6656

Abstract

This study employs a geospatial approach to investigate the spatial distribution and heterogeneity of nutritional status among Women of Childbearing Age across Nigeria. We utilize data on various nutritional indicators obtained from National Demographic and Health Survey (NDHS, 2018) alongside relevant geospatial information. By employing spatial statistical methods, we aim to identify geographic clusters and disparities in the various nutritional statuses: normal weight, overweight, and obesity. This analysis will provide valuable insights into the geographical variations in WCBA's nutritional health and inform targeted interventions to address these disparities. This study employs a statistical method, Bayesian Geoadditive Quantile Regression Model (BGQRM) to investigate the impact of various factors on weight categories (normal weight, overweight, obese) among Nigerian women of childbearing age.. Results reveal higher likelihoods of overweight or obesity among urban women, potentially linked to urban living factors like increased income and education, leading to reduced physical activity and higher consumption of calorie-dense foods. The findings highlight complex relationships between socioeconomic factors, urbanization, and weight status, challenging assumptions about the effects of mass media and electricity access on weight, and emphasizing the need for tailored interventions informed by nuanced ethnic and employment-related variations in nutritional patterns among Nigerian women. This study utilizes a novel statistical method (BGQRM) to investigate the impact of various factors on weight categories among women of reproductive age in Nigeria, revealing a higher likelihood of overweight or obesity among urban residents, potentially linked to lifestyle factors such as income and education. The findings challenge assumptions about the relationship between socioeconomic status, media exposure, and weight, highlighting complex interactions that can inform targeted interventions aimed at improving nutrition and well-being among Nigerian women of childbearing age.

Geospatial analysis heterogeneity nutritional status bayesian geoadditive quantile regression model

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