Abstract
BackgroundIn view of the costly methods currently available for the assessment of body adiposity, anthropometric obesity indicators have proven effective in predicting cardiovascular risk.ObjectiveTo investigate the discriminatory power of body fat indicators for cardiovascular risk screening among shift workers.MethodsCross-sectional study with male employees of an iron ore extraction company. The predictive power of body fat indicators relative to cardiovascular risk was analyzed based on the Framingham risk score and metabolic syndrome by means of receiver operating characteristic curves, sensitivity, specificity, positive and negative predictive values, area under the receiver operating characteristic curve and Youden’s index.ResultsThe prevalence of cardiovascular risk was 14.2% in the metabolic syndrome risk model. According to the Framingham score, 95.0%, 4.1% and 0.9% of the participants exhibited low, moderate and high risk, respectively. All the analyzed body fat indicators exhibited satisfactory discriminatory power for the tested cardiovascular risk models.ConclusionWaist-height ratio exhibited the highest ability to predict cardiometabolic risk in both risk models.
Highlights
Obesity, understood as excess body fat, is a multifactorial disease that causes inflammation, which eventually leads to metabolic disorders.[1]
metabolic syndrome (MS) was detected in approximately 14.2% of the sample, and the following distribution of cardiovascular risk according to Framingham risk score (FRS) was found: low 95.0%, moderate 4.1% and high 0.9% (Table 1)
For MS, the Hanley and McNeil test results indicated that body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR) were statistically similar and superior to neck circumference (NC)
Summary
Understood as excess body fat, is a multifactorial disease that causes inflammation, which eventually leads to metabolic disorders.[1] Obesity has a direct relationship with cardiovascular (CV) disease and risk factors, including dyslipidemia, high blood pressure (BP), insulin resistance and diabetes.[1] While several methods are available to measure body fat, as a rule they involve expensive and sophisticated equipment, which hinders their applicability and accessibility in clinical practice and epidemiological studies.[1] Screening for CV risk requires less expensive methods. Shift workers are more prone to obesity due to changes in dietary habits, sedentary lifestyle and circadian rhythm disruption, which suggests they are at higher risk of CV disease.[9]
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