ArticleBMJ open2026
Comparing adiposity-related predictors of cardiometabolic disease in two Indigenous Guatemalan municipalities: a cross-sectional receiver operating characteristic analysis.
Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Abstract
objectives(1) To compare the ability of body mass index (BMI), waist-to-height ratio and visceral fat, as measured by bioelectrical impedance analysis (BIA), to predict hypertension and diabetes in men and women and (2) to determine whether the correlation between BMI and visceral fat varies by height quantile.
designWe conducted a cross-sectional analysis of a representative survey that included data on anthropometrics, body composition, glycosylated haemoglobin and blood pressure. We used receiver operating characteristic analysis and DeLong CIs to compare the ability of each adiposity measure to predict diabetes and hypertension in each gender.
settingTecpán and San Antonio Suchitepéquez, Guatemala.
participants806 non-pregnant adults from 347 households, primarily of Indigenous ethnicity. PRIMARY OUTCOME MEASURES: Diabetes, defined as a haemoglobin A1c of greater than 6.5% or self-reported history and hypertension, defined as a systolic blood pressure over 140 or a diastolic blood pressure over 90.
resultsAmong the three adiposity measures, visceral fat was the best predictor of diabetes (area under the curve; AUC 0.73 (95% CI 0.66 to 0.81) (men); AUC 0.75 (95% CI 0.7 to 0.8) (women)) and hypertension (AUC 0.7 (95% CI 0.61 to 0.79) (men); AUC 0.76 (95% CI 0.7 to 0.82) (women)), followed by waist-to-height ratio followed by BMI. All three measures better predicted hypertension in women than in men. In sensitivity analysis, visceral fat and waist-to-height ratio better predicted hypertension and diabetes when BMI was below 30 kg/m
conclusionsOf the three adiposity measures studied, BIA-derived visceral fat best predicted cardiometabolic disease in the population. In clinical practice, alternative techniques beyond BMI need to be considered when assessing adiposity, screening for cardiometabolic disease and diagnosing clinical obesity.
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