Frequency of Metabolic Syndrome According to Optimal CutPoints for Body Mass Index in Saudi Population

Background and Objective: The prevalence of metabolic syndrome (MetS) are increasing worldwide. Body mass index (BMI) cut-off for MetS can vary. The objective of this study is to identify the optimal BMI cut-off that is associated with MetS. Methods: For the present study, we analyzed participants who are equal to or older than 18 years old. A total of 5498 were analyzed at the present study. Patients were recruited from the population of the primary health care department at King Fahad Armed Forces Hospital. Metabolic risk factors were defined using the 2006 International Diabetes Federation criteria. We collected data personal interview and electronic medical chart review. Physician and nurse interviewers measured the weight (kg) and height (cm) of the participants and BMI was calculated. Receiver operating characteristic curve analysis was used to obtain the optimal sensitivity and specificity using different BMI cut-off values to predict the presence of diabetes. Results: Of the 5498 participants analyzed, 2049 (37.3%) were male and 3449 (62.7%) were female with female to male ratio 1.7:1. Age was 42.7 ± 15.8 (minimum 18 years and maximum 105 years). MetS was present in 1967 cases (35.8%) where 673 cases (38.8%) were male and 1204 cases (61.2%) were female with female to male ratio 1.6:1, P=0.08. Males were significantly older than females in MetS patients (45.5±12.8 vs. 36.1±13.3 respectively, p<0.0001). BMI was significantly higher in MetS patients (31.9±6.6 vs. 28.3±6.7 respectively, p<0.0001). Optimal BMI cut-off values ranged from 28.50 to 29.50 in total population, 27.50 to 28.50 in male and from 28.50 to 29.50 in female. The AUC was 0.615 (95% CI, 0.590-0.639) in male and 0.686 (95% CI, 0.668-0.704) in female. Regression analysis showed that the risk of MetS was significantly increased at BMI values as low as ≤15.0 kg/m2 and increased progressively as BMI increased for both genders. Applying this criterion to identify the cut-off values resulted in improvements in sensitivity, false negative rate and worsening in specificity and false positive rate. A very small false negative rate ranging from 0.001 to 0.005 resulted by using these lower BMI cut-offs. Conclusion: The diagnostic usefulness of BMI alone in defining obesity in patients with MetS is limited among men and women Saudi adults.