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Niger Med J ; 64(6): 799-815, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38979057

RESUMEN

Background: Obesity is a preventable public health problem associated with a significantly increased risk of non-communicable diseases. This study aimed to find the socio-demographic and nutritional factors associated with obesity amongst adults from high-burden kidney disease areas of Jigawa State, Nigeria. Methodology: A cross-sectional survey was conducted to assess the socio-demographic and nutritional factors associated with obesity among 361 adults from four local government areas (LGAs) of Jigawa state identified to have a high burden of kidney diseases. The Modified WHO STEPS questionnaire and multi-stage sampling technique were employed, and data were analyzed using IBM SPSS version 22.0. Results: The minimum age of the respondents was 18, and the maximum was 102 with a median of 45 (interquartile range = 30-80) years. The prevalence of obesity and overweight in the high-burden LGAs of Jigawa state was 33.0% and 27.1% respectively. Hadejia LGA had the highest (68.1%) prevalence of obesity. The prevalence of overweight was higher in Jahun LGA (38.9%). About one-third (38.2%) had a waist circumference (WC) greater than 88cm. Up to half of the female respondents had a waist-hip ratio (WHR) greater than 0.85. For male respondents, many (74.3%) had a WHR of greater than 0.9, and obesity was significantly higher (39.8%, P s< 0.001) among those ≥40 years of age. Obesity was significantly higher (39.8%,P < 0.001) among those ≥40 years of age, known diabetic, (57.1%, P=0.02), and rare consumption of vegetables, (45.8%, P<0.001).The odds of developing obesity were significantly higher among those who were known diabetics and were 3 times more likely to be obese than those who were not known to be diabetics (adjusted odds ratio [aOR] = 3.1, 95% CI = [1.1-8.9]. Conclusions: The prevalence of obesity was high in the areas with high burdens of kidney disease. The government and relevant stakeholders should develop a cost-effective prevention, early diagnosis, and treatment model.

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