Acta Scientific Clinical Case Reports

Research Article Volume 2 Issue 12

Spatial Modeling of Overweight and Obesity among Non-Pregnant Women of Reproductive Age in Malawi

Owen Paweni Loss Mtambo*

Department of Public Health, Kamuzu University of Health Sciences, Malawi

*Corresponding Author: Owen Paweni Loss Mtambo, Department of Public Health, Kamuzu University of Health Sciences, Malawi.

Received: October 25, 2021; Published: November 19, 2021

Abstract

  The prevalence of overweight (including obesity) among non-pregnant women of reproductive age (WRA) in Malawi substantially increased from 10% in 1992 to 21% in 2016. The main objective of this study was to assess significant factors of overweight (including obesity) among non-pregnant WRA in Malawi using spatial models implemented in R version 4.0.4. The 2015-16 Malawi Demographic and Health Survey (MDHS) datasets were used in this study. Significant determinants of overweight (including obesity) ranged from socio-demographic characteristics to sedentary lifestyle of non-pregnant WRA. Total number of children ever born had significant nonlinear effects on overweight (including obesity) among non-pregnant WRA. Furthermore, we observed significant structured spatial effects on childhood overweight (including obesity) among non-pregnant WRA. To achieve the sustainable development goals 2.2 and 3 (SDG 2.2 and SDG 3) by 2030 in Malawi, the existing nutrition programmes and nutrition policy makers in this country may as well consider interventions based on socio-demographic determinants and spatial variations presented in this paper.

Keywords: Bayesian Inference; Body Mass Index; Obesity; Overweight; Spatial Models; Women of Reproductive Age

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Citation

Citation: Owen Paweni Loss Mtambo. “Spatial Modeling of Overweight and Obesity among Non-Pregnant Women of Reproductive Age in Malawi". Acta Scientific Clinical Case Reports 2.12 (2021): 38-48.

Copyright

Copyright: © 2021 Owen Paweni Loss Mtambo. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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