Deriving Sex-Specific Anthropometric Cut-Points for Obesity and Cardiovascular Disease Risk in Qatari Adults

Objective: Obesity, defined using body mass index, is a key risk factor for cardiovascular disease (CVD), diabetes, and dyslipidemia. However, global anthropometric thresholds like those established by the World Health Organization (WHO) may inadequately capture the health risks associated with obesity in specific populations. This study aimed to derive population- and sex-specific anthropometric cut-points to better predict obesity and CVD risk and assess obesity misclassification among Qatari adults. Methods: Using a cross-sectional sample of 6,000 participants from the Qatar Biobank (QBB), we applied receiver operating characteristic (ROC) curve analyses to identify cut-points for anthropometric indices that align with body fat percentage (%BF) and disease-specific thresholds for elevated blood pressure (EBP), diabetes, and dyslipidemia. Misclassification analyses examined the limitations of WHO-recommended cut-points compared to ROC-derived thresholds. Results: The study sample consisted of relatively young adults with high levels of adiposity (BMI: 28.6±5.18 kg/m² males, 29.6±6.27 kg/m² females; Waist Circumference (WC): 93.2±13.1 cm males, 84.1±13.4 cm females). %BF-defined obesity prevalence (87% males, 91% females) exceeded BMI-based estimates (34% males, 44% females). Findings revealed that the optimal BMI cut points were 25.2 kg/m² for males and 24.8 kg/m² for females. Similarly, WC cut-points were 84.3 cm for males and 74.5 cm for females, also lower than global standards. Disease-specific thresholds varied, highlighting the unique biological pathways underlying EBP, diabetes, and dyslipidemia Misclassification analyses showed that 54.6% of males and 43.0% of females were misclassified using the WHO BMI cut point. Higher misclassification rates were observed for WC in females, where 87.5% of females with obesity by %BF were misclassified without obesity using WHO WC thresholds. Conclusion: These results highlighted the limitations of global anthropometric thresholds and the need for population-specific measures to improve obesity and CVD risk classification in an Arab sample.