Numerous studies have examined associations between fat patterning and mortality and morbidity.
Since fat distribution is correlated with age as well other risk factors for disease, such as smoking, alcohol consumption, physical activity, and menopause in women, it is important to control for the effects of these variables in order to obtain an estimate of the independent effect of central obesity on morbidity. The impact of some of these correlates of fat distribution may be subtle and unlikely to seriously distort relationships between fat patterning and disease. However, age, the ultimate risk factor for disease and death, is sufficiently highly correlated with fat distribution to result in substantial distortion. Similarly, cigarette smoking is related adequately strongly to fat patterning and to various diseases and outcomes to make analyses that do not adjust for smoking difficult to interpret.
The large correlation between fat patterning and overall adiposity also influences the interpretation of results, making it difficult to differentiate between the two effects. Some researchers compare the size of the correlation between fat distribution (usually measured as WHR) and total adiposity (usually measured as BMI) in an attempt to show the relative importance of each. Others examine effects within tertiles (or other categories) of BMI and WHR simultaneously or test for an independent effect of WHR or BMI in multiple regression models that include both variables. In the latter type of analysis, the associations of both WHR and BMI with an outcome can be greatly reduced or even disappear because of collinearity between the two measures.
Researchers have found positive correlations between fasting glucose, insulin, blood pressure, total cholesterol, LDL cholesterol, and triaclyglycer-ols using imaging techniques, sagittal diameter, waist circumference, and WHR in most, but not all, studies. Visceral fat and HDL cholesterol are inversely associated. The strength of the associations varies but tends to be largest for triaclyglycerols. Associations are reduced after controlling for BMI and age.
There is strong evidence to link waist circumference and WHR with the risk of developing type 2 diabetes, even after eliminating the effects of age, smoking, BMI, and other important correlates. An individual who is obese (>150% ideal body weight) and has an elevated WHR (>0.8) may have as much as a 10-fold increased risk for developing type 2 diabetes compared with an individual who is of normal weight (<120% ideal body weight) and has a low WHR (<0.72).
Elevated WHR has been positively associated with cardiovascular disease in some population studies, although not as consistently as diabetes. Scientists have recognized that several of the cardiovascular disease risk factors, including abdominal obesity, cluster in individuals. This cluster of risk factors is referred to as metabolic syndrome. The other risk factors in metabolic syndrome are insulin resistance/ glucose intolerance, dyslipidemia (high triaclygly-cerols and low HDL cholesterol), and high blood pressure.
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