Anthropometric Correlates of Metabolic Syndrome Components in a Diverse Sample of Overweight/Obese Women


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Slide 1 : Anthropometric Correlates of Metabolic Syndrome Components in a Diverse Sample of Overweight/Obese Women Arlette Perry, PhD; Xuewen Wang, PhD; Yi-Tzu Kuo, MS
Slide 2 : Introduction An estimated $117 billion is spent treating overweight and obesity in the US each year. An estimated 112, 000 deaths annually are attributed to obesity with the highest obesity rates observed among African-American (AA) and Hispanic-American (HA) women. Body fat distribution, however, may be more closely related to metabolic risk than total body fat. It also may be more significant in predicting a clustering of cardiometabolic variables associated with the Metabolic Syndrome (METs).
Slide 3 : Purpose The present study examined the relationship between anthropometric surrogates of total body fat and cardiometabolic variables. Body Mass Index (BMI), body fat distribution using waist circumference (WAIST), and waist to hip ratio (WHR) were examined in relation to cardiometabolic variables reflective of the Metabolic Syndrome (METs) in overweight/obese Caucasian American (CA), AA, and HA women.
Slide 4 : Subjects & Methods Volunteers interested in entering a weight reduction program were recruited. All volunteers were either overweight or obese with a BMI = 25 Volunteers had to be free from metabolic disease including heart disease, hypertension, hyperlipidemia, or diabetes. Volunteers were not currently pregnant and were free from taking oral contraceptives. Volunteers could not be on any medications that would affect serum lipids or lipoproteins, blood pressure, metabolism, or body weight. A total of 234 women; 105 CA, 90 AA, 39 HA women met criteria for participating in the study.
Slide 5 : Research Design Mean ± SD were reported on all variables for the entire sample and by race/ethnicity. An analysis of variance was performed on age, body fat measures, and all metabolic variables associated with the METs comparing CA, AA, and HA women. Multiple regression analyses were conducted to determine whether BMI, WAIST or WHR could significantly predict cardiometabolic variables associated with the METs. This was done after adjustment for age for the total sample and by group.
Slide 6 : Table 1. Characteristics of a sample of overweight/obese Caucasian, African American, and Hispanic women (all values are mean ± standard deviation)
Slide 7 : Table 2. Significant cardiometabolic variables predicted by body mass index, after adjusting for age, in a sample of overweight/obese Caucasian, African American, and Hispanic women
Slide 8 : Table 3. Significant cardiometabolic variables predicted by waist circumference, after adjusting for age, in a sample of overweight/obese Caucasian, African American, and Hispanic women
Slide 9 : Table 4. Significant cardiometabolic variables predicted by waist-to-hip ratio, after adjusting for age, in a sample of overweight/obese Caucasian, African American, and Hispanic women
Slide 10 : Findings BMI BMI was a significant predictor of systolic and diastolic blood pressure (SBP and DBP, respectively) in CA and AA women only and did not predict any cardiometabolic variables in HA women. WAIST In CA women, WAIST significantly predicted the cardioprotective HDL cholesterol and triglycerides and was a better predictor of SBP and DBP. In addition, WAIST significantly predicted fasting glucose. In HA women, WAIST significantly predicted serum glucose only.
Slide 11 : Findings WHR In CA women, WHR predicted the same variables as WHR and in addition were significantly related to fasting serum glucose levels. In AA women, WHR predicted the identical variables as WAIST. In HA women, WHR failed to predict any cardiometabolic variables.
Slide 12 : Conclusions Clinically relevant differences by race ethnicity were found in anthropometric correlates of the METs Both WAIST and WHR were better predictors than BMI in cardiometabolic variables associated with the METs. WAIST was the most global anthropometric indicator of metabolic risk across all three racial/ethnic groups. However, WHR was a better predictor of health risk in CA women. Better anthropometric indicators of health risk are needed for HA women of Cuban and South American descent.

 



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