Cigarette smoking and metabolic syndrome components: a cross-sectional study from Maracaibo City, Venezuela.

Background: A growing body of evidence suggests that cigarette smoking can cause the onset of metabolic syndrome prior to cardiovascular diseases. Therefore, the objective of this study was to evaluate the relationship between smoking habit and metabolic syndrome components in an adult population from Maracaibo city, Venezuela. Methods: The Maracaibo City Metabolic Syndrome Prevalence Study is a descriptive, cross-sectional study with random and multi-stage sampling. In this sub-study, 2212 adults from both genders were selected. On the basis of their medical background, they were classified as smokers, non-smokers and former smokers. Metabolic syndrome was defined according to Harmonizing 2009 criteria, using population-specific abdominal circumference cut-off points. The association between risk factors was evaluated using a logistic regression model. Results: In the studied population, 14.8% were smokers, 15.4% were former smokers. In the multivariate analysis, the presence of metabolic syndrome (smokers: OR, 1.54; 95% CI, 1.11-2.14; p=0.010) and its components were related to cigarette smoking, with the exception of hyperglycemia. High blood pressure was inversely associated with current smoking status (smokers: OR, 0.70 (0.51-0.95); p=0.025). Conclusion: Cigarette smoking represents a related factor with metabolic syndrome, being associated with low high-density lipoprotein-cholesterol, increased abdominal circumference and elevated triacylglyceride levels. Former smokers did not present a greater risk for developing this metabolic disease when compared to non-smokers. The effect of avoiding this habit should be evaluated in future studies in our population.

Sensitivity and Specificity Improvement in Abdominal Obesity Diagnosis Using Cluster Analysis during Waist Circumference Cut-Off Point Selection.

INTRODUCTION: The purpose of this study was to analyze the influence of metabolic phenotypes during the construction of ROC curves for waist circumference (WC) cutpoint selection. MATERIALS AND METHODS: A total of 1,902 subjects of both genders were selected from the Maracaibo City Metabolic Syndrome Prevalence Study database. Two-Step Cluster Analysis (TSCA) was applied to select metabolically healthy and sick men and women. ROC curves were constructed to determine WC cutoff points by gender. RESULTS: Through TSCA, metabolic phenotype predictive variables were selected: HOMA2-IR and HOMA2-ßcell for women and HOMA2-IR, HOMA2-ßcell, and TAG for men. Subjects were classified as healthy normal weight, metabolically obese normal weight, healthy and metabolically disturbed overweight, and healthy and metabolically disturbed obese. Final WC cutpoints were 91.50 cm for women (93.4% sensitivity, 93.7% specificity) and 98.15 cm for men (96% sensitivity, 99.5% specificity). CONCLUSIONS: TSCA in the selection of the groups used in ROC curves construction proved to be an important tool, aiding in the detection of MOWN and MHO which cannot be identified with WC alone. The resulting WC cutpoints were <91.00 cm for women and <98.00 cm for men. Furthermore, anthropometry is insufficient to determine healthiness, and, biochemical analysis is needed to properly filter subjects during classification.

Epidemiologic Behavior and Estimation of an Optimal Cut-Off Point for Homeostasis Model Assessment-2 Insulin Resistance: A Report from a Venezuelan Population.

Background. Mathematical models such as Homeostasis Model Assessment have gained popularity in the evaluation of insulin resistance (IR). The purpose of this study was to estimate the optimal cut-off point for Homeostasis Model Assessment-2 Insulin Resistance (HOMA2-IR) in an adult population of Maracaibo, Venezuela. Methods. Descriptive, cross-sectional study with randomized, multistaged sampling included 2,026 adult individuals. IR was evaluated through HOMA2-IR calculation in 602 metabolically healthy individuals. For cut-off point estimation, two approaches were applied: HOMA2-IR percentile distribution and construction of ROC curves using sensitivity and specificity for selection. Results. HOMA2-IR arithmetic mean for the general population was 2.21 ± 1.42, with 2.18 ± 1.37 for women and 2.23 ± 1.47 for men (P = 0.466). When calculating HOMA2-IR for the healthy reference population, the resulting p75 was 2.00. Using ROC curves, the selected cut-off point was 1.95, with an area under the curve of 0.801, sensibility of 75.3%, and specificity of 72.8%. Conclusions. We propose an optimal cut-off point of 2.00 for HOMA2-IR, offering high sensitivity and specificity, sufficient for proper assessment of IR in the adult population of our city, Maracaibo. The determination of population-specific cut-off points is needed to evaluate risk for public health problems, such as obesity and metabolic syndrome.