Elsevier

Atherosclerosis

Volume 171, Issue 1, November 2003, Pages 123-130
Atherosclerosis

The hypertriglyceridemic waist phenotype among women

https://doi.org/10.1016/j.atherosclerosis.2003.07.008Get rights and content

Abstract

Background: Elevated plasma triglycerides (TG) and waist girth (hypertriglyceridemic waist (HTGW)) has been associated with elevated insulin, small dense low-density lipoprotein (sLDL) particles, and Apo B in men. The HTGW has not been reported for women and the effect of cardiorespiratory fitness (“fitness”) on associations between HTGW and coronary risk factors is unknown. Purpose: To determine the prevalence of HTGW and the influence of fitness on the relationship between HTGW and coronary risk among 137 healthy women (54±9 year; body mass index (BMI)=28±6 kg/m2). Methods: HTGW was defined as waist girth >88 cm and TG >150 mg/dl. The metabolic triad was defined as insulin >31 pmol/l, Apo B >69 mg/dl and LDL-C >84 mg/dl. Fitness was assessed with a maximal treadmill exercise test. Results: The sample prevalence of HTGW (n=15) was 11% (95% CI=5.7–16.0%). Apo B (P=0.04) and insulin (P=0.0001) increased across quintiles of waist girth, and LDL-C (P=0.004) increased across quintiles of TG. Metabolic triad prevalence was highest (67%, n=10) among HTGW women and lowest (22%, n=26) among non-HTGW women. A trend for higher coronary heart disease CHD risk factors was observed among HTGW compared with non-HTGW women. Among the HTGW group, a trend for lower CHD risk factors was observed among fit (≥6.5 METs, n=7) versus unfit women (<6.5 METs, n=8). Sample size limitations prohibited meaningful tests of significant differences in CHD risk factors when stratified simultaneously on HTGW and fitness status. Conclusions: HTGW is associated with increased coronary risk factors similarly among women as reported for men. Higher fitness may improve the CHD risk profile among women with HTGW.

Introduction

Despite progress in its prevention, detection and treatment, coronary heart disease (CHD) continues to exact an enormous economic and public health toll as the leading cause of death among US adults [1]. The latest report of the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP-III [2]) indicates that all CHD risk factors contribute to coronary disease similarly in women and men, and that most premature CHD in women occurs among those with co-existing risk factors [3]. Additional concern exists over increases in obesity and type 2 diabetes rates among women and minorities [1], [4]. Clustering of CHD risk factors accompanies both conditions [5], [6] and multiplicatively increases the risk of coronary events [7], [8]. For many individuals, sudden death or nonfatal myocardial infarction is the first symptom of CHD [9]. Therefore, leading health organizations have called for the development of clinical assessment strategies to identify high-risk individuals without established CHD in order to initiate aggressive primary preventive therapies [1], [9].

Lemiuex et al. [10] described a hypertriglyceridemic waist phenotype (HTGW) among men in the Quebec Cardiovascular Study, and suggested that this measurement might be an inexpensive clinical method of identifying elevated CHD risk among asymptomatic individuals. Lemiuex et al. [10] characterized the HTGW as a waist girth ≥90 cm and a plasma triglyceride (TG) concentration ≥177 mg/dl. Among 185 healthy Canadian men, the atherogenic metabolic triad of elevated plasma insulin, apolipoprotein B (Apo B), and small dense low-density lipoprotein particles (sLDL) was highly prevalent among men with (84%) versus men without (10%) the HTGW. The presence of angiographically defined CHD was nearly four times more likely among men with the HTGW versus men without HTGW. While elevated TG and waist circumference have previously been associated with increased risk for CHD and diabetes among women [11], [12], [13], it is unknown if the HTGW predicts increased risk for CHD and diabetes similarly in women as men.

The objective of this study was to examine cross-sectional data for the presence of the HTGW phenotype and its relationship with CHD risk factors among a tri-ethnic sample of healthy middle-aged women. We also investigated the influence of cardiorespiratory fitness on the relationship between the HTGW and selected CHD risk factors.

Section snippets

Study participants

This study consisted of 44 African–American (AA), 45 native American (NA), and 46 Caucasian (CA) women enrolled in the Cross-Cultural Activity Participation Study (CAPS). CAPS was a 5-year study funded by the National Institutes of Health and Centers for Disease Control and Prevention as part of the Community Trials arm of the Women’s Health Initiative [14]. The primary objective of CAPS was to develop culturally sensitive physical activity surveys for use in epidemiological studies of health

Results

Participants were middle-aged, overweight, and had relatively low CHD risk factors (Table 1). AA women were older, had larger BMIs, higher systolic blood pressure, insulin, HDL-C and CRP concentrations, and lower fitness compared with NA and CA women. Estrogenic medication use was highest among AA and CA women. Among all women, Spearman correlations revealed waist girth was associated with insulin (r=0.62, P<0.01), TG (r=0.36, P<0.01), HDL-C (r=−0.44, P<0.01), and fitness (r=−0.60, P<0.01). TG

Discussion

The American Heart Association has called for development of clinical methods to identify asymptomatic individuals at high-risk for new onset CHD [9]. Lemieux et al. [10] recently reported that two simple measures, waist girth >90 cm and fasting TG >177 mg/dl (the “hypertriglyceridemic waist phenotype”), might be an inexpensive clinical method for identifying men with elevated insulin, Apo B and sLDL concentrations, and hence, increased CHD and diabetes risk. The current study was undertaken to

Acknowledgements

The authors express gratitude to Drs. Vivian Heyward, Lisa Stolarczyk, Cheryl Addy, Jennifer Hootman, Melinda Irwin, and Melicia Whitt, and Ms. Angela Morgan, for their work in collecting, compiling, and managing the CAPS data set. This work was supported by NIH WHI-SIP # 22W-U48/CCU409664 awarded to Dr. Ainsworth.

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