Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/9156
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dc.contributor.authorAndale, Thomas-
dc.contributor.authorOrango, Vitalis-
dc.contributor.authorLwande, Gerald O.-
dc.contributor.authorMwaura, Grace W.-
dc.contributor.authorMugo, Richard-
dc.contributor.author. Limo, Obed K-
dc.contributor.authorMwangi, Ann-
dc.contributor.authorKamano, Jemima H.-
dc.date.accessioned2024-05-28T13:02:36Z-
dc.date.available2024-05-28T13:02:36Z-
dc.date.issued2021-07-08-
dc.identifier.urihttps://doi.org/10.1101/2021.07.07.21258941-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/9156-
dc.description.abstractEmerging data suggest a rise in the incidence rate of hypertension in many countries within Sub-Saharan Africa. This has been attributed to socioeconomic factors that have influenced diet and reduced physical activity further deranging anthropometric measurements. We assessed the predictive power of three anthropometric indicators namely: waist circumference (WC), waist to height ratio (WHtR) and body mass index (BMI) in detecting hypertension. This cross-sectional community survey was conducted in four counties within Western Kenya between October 2018 to April 2019 among 3594 adults. The participants’ sociodemographic data were collected using an interviewer-administered questionnaire and anthropometric measurements taken. We used the R-software for descriptive and inferential statistical analysis. Pearson chi-square test was used to assess the association between anthropometric measurements and hypertension while logistic regressions estimated the likelihood of hypertension. Youden method was used to identify optimal anthropometric cut-offs for sensitivity, specificity and area under the receiver operating characteristics (ROC) curve computation. The crude prevalence of hypertension was 23.3%, however it rose with advancement in age. Furthermore, obese individuals had a three-fold (AOR=2.64; 95% CI: 2.09, 3.35) increased likelihood of hypertension compared to those with a normal BMI. The optimal WC cut-off was 82.5cm for men and 87cm for women, an optimal WHtR of 0.47 for men and 0.55 for women; while the optimal BMI cut-off was 23.7 kg/m2 and 22.6 kg/m2 for men and women respectively. The sensitivity of WC, WHtR and BMI for men was 0.60, 0.65 and 0.39 respectively and 0.71, 0.65 and 0.78 respectively for women. BMI is the best predictor for hypertension among women but a poor predictor for men; WC had a high hypertension predictive power for both gender while WHtR is the best hypertension predictor for men.en_US
dc.language.isoenen_US
dc.publisherBMJen_US
dc.subjectHypertensionen_US
dc.subjectWaist Circumferenceen_US
dc.subjectBMI,en_US
dc.subjectAnthropometricsen_US
dc.subjectPredictorsen_US
dc.titleAnthropometric measurements as predictors of hypertension in Busia, Vihiga, Trans Nzoia and Siaya counties of Western Kenyaen_US
dc.typeArticleen_US
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