Use of anthropometric measurements in assessing risk for coronary heart disease: a useful tool in worksite health screening?

The study examined the association between the anthropometric measurements body mass index (BMI), waist/hip ratio (WHR), and waist/thigh ratio (WTR) and cardiovascular risk factors, and assessed whether a combination of BMI and WHR could be used in routine screening of risk for cardiovascular arteriosclerotic disease at worksites. The data were obtained from a cross-sectional survey designed to assess the nutritional situation, with special reference to cardiovascular risk factors. The study population comprised 372 healthy men working on platforms in the North Sea. Serum cholesterol, triglyceride, fibrinogen, and blood pressure were positively related to the anthropometric variables, while high-density lipoprotein (HDL) was inversely related with them. The relations remained after adjusting for possible confounders, such as age, smoking, physical activity, and an indicator of dietary fat intake. In stepwise multiple linear regression models, BMI, WHR, and WTR were positively related to serum cholesterol, triglycerides, fibrinogen, diastolic blood pressure, and systolic blood pressure, and inversely related to HDL. When controlling for the anthropometric variables WHR and WTR, BMI was not independently related to fibrinogen and risk score. WHR and WTR were not independently related to systolic and diastolic blood pressure, and WTR was in addition not related to triglycerides when controlling for BMI. Overall, the anthropometric variables BMI and WHR were considered the best predictors for CAD risk when taking several risk factors into consideration. A joint variable between BMI and WHR, called "body score", constituted the four categories lean, lean android, overweight gynoid, and overweight ovoid. This body score was positively associated with levels of serum lipids, fibrinogen, and blood pressure, and inversely associated with HDL. In stepwise multiple linear regression models, controlling for possible confounding variables, body score was positively related to CAD risk. Dividing the risk score into tertiles, about 51% of the lean were in the first, while 46% of the overweight ovoid were in the third tertile. Those classified as lean android or overweight gynoid had about the same distribution, namely between 31% and 39% in each tertile if the two categories were combined. These data support the hypothesis that BMI, WHR, and WTR are independent predictors for risk factors for CAD among oil workers, and that combinations of BMI and WHR are strong enough predictors to be useful in routine screening for CAD risk at worksites. Based on these findings, supported by data from the literature, a matrix aimed at screening for follow-up at worksites is proposed.