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. Author manuscript; available in PMC: 2021 Jan 1.
Published in final edited form as: Atherosclerosis. 2019 Nov 4;292:31–36. doi: 10.1016/j.atherosclerosis.2019.10.017

Body Mass Index and Peripheral Artery Disease

Sean P Heffron a,b, Aeshita Dwivedi a, Caron B Rockman c, Yuhe Xia d, Yu Guo d, Judy Zhong d, Jeffrey S Berger a,b,c
PMCID: PMC6981229  NIHMSID: NIHMS1543577  PMID: 31739257

Abstract

Background and aims:

An independent association of body mass index (BMI) with atherosclerotic cardiovascular disease is somewhat controversial and may differ by vascular bed. Sex-specific risk factors for atherosclerosis may further modify these associations. Obesity and peripheral artery disease (PAD) are both more prevalent in women. We sought to determine the association between PAD and BMI using a very large population-based study.

Methods:

Self-referred individuals at >20,000 US sites completed medical questionnaires including height and weight, and were evaluated by screening ankle brachial indices (ABI) for PAD (ABI<0.9).

Results:

Among 3,250,350 individuals, the mean age was 63.1±10.5 years and 65.5% were women. The mean BMI was 27.7±5.8 kg/m2. 27.8% of participants were obese (BMI ≥30kg/m2) – 27.6% females, 28.1% males. Overweight individuals (BMI 25–29.9 kg/m2) exhibited the lowest prevalence of PAD. There was a J-shaped association of BMI with prevalent PAD. After adjustment for age and cardiovascular risk factors, underweight was associated with similarly increased odds of PAD (1.72 vs 1.39, women and men, respectively). The association of obesity with PAD was predominant in women, with only a slight association of increasing BMI with PAD in men (OR=2.98 vs 1.37 for BMI ≥40 kg/m2)

Conclusions:

Our study suggests that increasing BMI is a robust independent risk factor for PAD only in women. This observation requires validation, but highlights the need for further research on sex-specific risk and mechanisms of atherosclerosis.

Keywords: Body Mass Index, Obesity, Peripheral Artery Disease

Graphical Abstract

graphic file with name nihms-1543577-f0001.jpg

Introduction

Obesity is a worldwide epidemic and has been identified as a modifiable risk factor for coronary artery disease (1, 2) and ischemic stroke (3). The association between abdominal aortic aneurysm and body mass index (BMI) is less certain (4–6). Whether a common mechanism links obesity with atherosclerosis and adverse events in varying vascular beds is unclear. For example, although obesity-related metabolic comorbidities such as diabetes and hypertension are common risk factors for both coronary and cerebrovascular disease, obesity in the absence of the metabolic syndrome, is a risk factor for myocardial infarction (1), but not stroke (7).

The association between BMI and lower extremity peripheral artery disease (PAD) is not well-defined and remains controversial. While some studies have suggested that obesity is associated with a higher prevalence (8) or incidence (9) of PAD, others have failed to reproduce these associations (10, 11). In fact, some studies even indicate an inverse association between BMI and prevalent PAD (12). Notably, most prior studies did not include patients at the extremes of the BMI spectrum, i.e severely obese or underweight patients.

Finally, the lack of equivalence of atherosclerosis risk factors among sexes, as well as sex-specific cardiovascular disease risk factors, are being increasingly recognized (13). Obesity and PAD are both more prevalent in women (14, 15). Despite this, the association of obesity with PAD, and further, any sex-specific differences in risk, remain incompletely characterized. We therefore sought to determine the association between PAD and BMI using a very large community-based study including over 3 million participants. We aimed to describe the prevalence of PAD through a broad range of BMI, as well as in men and women separately.

Patients and methods

Study population

This study was performed using data provided by Life Line Screening Inc. (Independence, Ohio USA) to the Society for Vascular Surgery for research purposes. The study sample consists of self-referred individuals who paid out-of-pocket for vascular screening tests. Screenings were performed from 2003 to 2008 at >20,000 sites in the United States. Screening sites were located in public spaces (shopping malls, community centers, and the like) for brief periods and advertised ankle-brachial index (ABI), carotid Doppler, abdominal aorta ultrasound and bone density screening. Advertisement was made with print and radio announcements. Before undergoing the screening procedure, individuals completed an extensive questionnaire that included information on demographics, smoking, physical activity, cardiovascular risk factors, medical comorbidities, and family history of atherosclerosis and vascular disease.

Ascertainment of peripheral artery disease

The presence of PAD was determined using the ankle brachial index (ABI). To calculate the ABI, hand held Doppler probes were used with appropriate size inflatable sphygmomanometer cuffs to determine the systolic blood pressure in both arms (brachial arteries) and both ankles (posterior tibial arteries). If a posterior tibial Doppler signal was inaudible, the dorsalis pedis artery signal was measured. Left and right ABI measurements were obtained by dividing the ankle systolic blood pressure by the highest arm pressure. PAD was defined as an ABI <0.9 in either leg. Subjects with an ABI >1.4 were excluded as these values may be falsely elevated due to calcification of the artery wall (16).

Assessment of body mass index

Body mass index was calculated by dividing self-reported weight in kilograms by height in meters squared.

Cardiovascular risk factors

Hypertension was defined by reported physician diagnosis or anti-hypertensive medication use at the time of screening. Hypercholesterolemia was defined by reported physician diagnosis or medication use. Diabetes was defined by reported physician diagnosis or the use of diabetes medication. Participants who had smoked ≥100 cigarettes during their lifetime and were still currently smoking were considered smokers. Individuals reporting engagement in some kind of vigorous leisure time exercise at least once per week were considered active and all other subjects were considered sedentary. Age, gender and race/ethnicity were self-reported.

Statistical analyses

Participants were divided into 7 BMI categories according to WHO standard classification (17): underweight (<18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), obese class I (30–34.9 kg/m2), obese class II (35–39.9 kg/m2), obese class III (>40 kg/m2). Within each BMI category, multivariable logistic regression was used to estimate odds of PAD after adjustment for seven demographic, lifestyle and medical variables: age (as a continuous variable), self-reported race/ethnicity, smoking status, hypertension, hypercholesterolemia, diabetes mellitus and family history of cardiovascular disease. We further stratified the above analyses by sex to determine the association of BMI with PAD separately in men and women. The BMI category with lowest PAD prevalence (25–29.9 kg/m2) was chosen as the reference (OR=1).

Results

3,250,350 individuals were present in the entire sample. 94,963 subjects did not report sex, leaving 3,155,387 in our sex-stratified analyses. Overall, the mean age in our sample was 63.1±10.5 years, 63.6% were women and 89% were white. The mean BMI was 27.7±5.8 kg/m2. 3.1% of participants had BMI <18.5 kg/m2, 28.5% had BMI 18.5–24.9 kg/m2, 36% were overweight (BMI 25–29.9 kg/m2),17.3% reported BMI 30–34.9 kg/m2, 6.0% had BMI 35–39.9 kg/m2, and 3.0% were obese class III (BMI ≥40 kg/m2). Characteristics of the entire sample stratified by BMI are presented in Table 1.

Table 1.

Characteristics of Study Population Undergoing Vascular Screening Examinations at over 20 000 US Sites Between 2003 and 2008 by WHO Body Mass Index Categorization

Body Mass Index
Overall < 18.5 18.5–24.9 25–29.9 30–34.9 35–39.9 ≥ 40
n 3,250,350 110,985 994,730 1,242,287 594,066 204,362 103,920
Age (years) 63.1(10.5) 65.2 (11.7) 64.1 (11.1) 63.4 (10.2) 62.0 (9.77) 60.4 (9.5) 58.8 (9.3)
<40 1.3% 1.4% 1.2% 1.1% 1.3% 1.8% 2.4%
41–50 8.6% 7.9% 8.3% 7.8% 9.1% 10.9% 13.3%
51–60 28.1% 22.6% 25.9% 27.1% 30.8% 34.6% 39.0%
61–70 35.2% 31.2% 32.7% 36.5% 37.3% 36.7% 33.8%
71–80 20.2% 24.2% 22.5% 21.3% 17.6% 13.7% 10.0%
>80 6.7% 12.8% 9.5% 6.3% 3.9% 2.3% 1.6%
Women 65.5% 78.8% 75.6% 56.7% 61.5% 69.4% 77.7%
Race/ethnicity
White 88.9% 83.3% 89.8% 89.3% 88.4% 87.5% 86.4%
Black 3.2% 3.7% 1.8% 3.0% 4.3% 5.5% 6.7%
Asian 2.1% 3.6% 2.7% 1.9% 1.5% 1.3% 1.3%
Hispanic 2.5% 3.9% 2.5% 2.5% 2.4% 2.5% 2.5%
Native American 2.7% 4.3% 2.7% 2.7% 2.7% 2.6% 2.5%
Other 0.6% 1.2% 0.6% 0.6% 0.7% 0.6% 0.7%
Risk factors
Current smoker 24.5% 24.0% 24.3% 24.8% 24.6% 24.2% 23.4%
Former smoker 23.5% 21.8% 21.9% 24.7% 24.5% 23.6% 22.5%
Never smoker 52.0% 54.2% 53.9% 50.5% 50.9% 52.2% 54.1%
Diabetes mellitus 9.9% 8.9% 5.2% 8.5% 14.2% 20.7% 27.3%
Hypertension 46.1% 59.5% 49.2% 61.1% 71.8% 79.3% 84.7%
Hypercholesterolemia 51.3% 42.1% 43.8% 54.1% 57.3% 56.9% 53.8%
Family history of CVD 22.6% 20.8% 21.2% 22.0% 24.1% 26.3% 28.4%
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CVD – cardiovascular disease

The prevalence of diabetes and hypertension followed J-shaped relationships with BMI regardless of sex, with the lowest prevalence of PAD in subjects with normal BMI (18.5–24.9 kg/m2) and increasing prevalence with increasing or below-normal BMI (Table 1, Supplemental Figures 1(A) and 1(B)). Hyperlipidemia was more highly prevalent in overweight and obese subjects (~55%) than in underweight and normal weight subjects (~43%, Table 1, Supplemental Figure 1(C)), with no association with obesity severity. Prevalence of family history of cardiovascular disease exhibited a modest association with increasing BMI (Table 1, Supplemental Figure 1(D)). The prevalence of current smokers was similar across all BMI categories. Characteristics of the sample stratified by gender are presented in Supplemental Tables 1(A) and 1(B).

Association of prevalent PAD with BMI

Peripheral artery disease (ABI <0.9) was identified in 4.1% of subjects overall, with a higher prevalence in women than men (Figure 1(A)). When stratified by BMI categories, the prevalence of PAD followed a J-shaped curve in women. Underweight and normal BMI men exhibited a higher prevalence of PAD than did overweight and obese men, with a positive association of prevalent PAD with increasing BMI evident only in severe class III obesity (BMI ≥40kg/m2). These trends were identical when more specific categorization of BMI was performed (Figure 1b). They were present regardless of participant age or race (Supplemental Figures 2(A) – 2(D)).

Figure 1(A).

Figure 1(A).

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Prevalence of Peripheral Artery Disease by WHO categorization BMI – body mass index, PAD – peripheral artery disease, WHO – World Health Organization

Figure 1(B).

Figure 1(B).

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Prevalence of Peripheral Artery Disease by BMI (1 kg/m2 increments)

Logistic regression models incorporating age, race/ethnicity, smoking status, hypertension, hypercholesterolemia, diabetes and family history of cardiovascular disease were used to determine the odds of prevalent PAD by BMI category relative to the category of lowest prevalence in the overall population (25–29.9 kg/m2, Figure 2(A)). BMI <25 and ≥40kg/m2 were associated with modestly increased odds of PAD in males (OR ~1.37 in both categories, Figure 2(B)). In contrast, after multivariable adjustment in women, odds of PAD continued to demonstrate a J-shaped relationship with BMI with similar odds in underweight and class II obesity (1.51 and 1.35, respectively) and a markedly elevated OR for PAD (2.98) in class III obesity (Figure 2(B)). These trends were similar when participants were stratified by age greater than or less than 70 years (Supplemental Figures 3(A) and 3(B)).

Figure 2(A).

Figure 2(A).

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Adjusted odds of prevalent PAD by WHO categorization

Model adjusted for age, gender, race/ethnicity, smoking status, hypertension, hypercholesterolemia, diabetes mellitus and family history of cardiovascular disease.

Figure 2(B).

Figure 2(B).

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Adjusted odds of prevalent PAD in males and females by WHO categorization

Discussion

In this analysis of a very large community-dwelling sample of adults self-referred for vascular screening examinations, we noted a J-shaped association of BMI with prevalent PAD. This relationship was most robust in women with only a slight association of increasing BMI with PAD in men. These associations persisted after adjustment for multiple established atherosclerotic cardiovascular disease risk factors. Our data suggest that increasing BMI may be a strong independent risk factor for PAD in women alone, in contrast to men, who are at increased odds of PAD only with very severe obesity (BMI > 42kg/m2). This observation requires validation, but highlights the need for further research on sex-specific risk and mechanisms of atherosclerosis.

Peripheral artery disease, is a highly prevalent, but under-diagnosed disease (18). The fact that it is more prevalent in women (14, 15), is also not widely appreciated. Although use of ABI as a diagnostic criterion for PAD is likely responsible for some degree of the reported female predominance (ABI is 0.02 less in women than men without PAD)(19), this cannot completely account for the degree of increased prevalence in women. Several possible reasons for the sex-difference in PAD prevalence have been suggested (20), including maternal placental syndromes which seem to increase risk of PAD more so than for coronary and cerebrovascular disease (21). However, the reasons for the unique female-predominance for this specific atherosclerotic disease remain obscure. Our study suggests that obesity may present a significant risk factor for PAD particular to women.

The notion that individual atherosclerosis risk factors may not be equivalent among sexes, and that sex-specific cardiovascular disease risk factors exist, has gained acceptance (13, 22, 23). For example, while smoking and diabetes increase the risk for cardiovascular disease in both sexes, the risk to women from both risk factors appears greater than in men (24, 25). Although prior analyses have not found obesity-associated risk of coronary heart disease and stroke to differ by sex (13), sex-stratified analyses of PAD-risk associated with increasing BMI have not previously been performed. A recent Mendelian Randomization analysis supports increasing BMI as an independent risk factor for PAD in both sexes (26). However, this study was limited significantly in that it was confined nearly completely to individuals with BMI <30 kg/m2.

Our finding of a positive association of BMI with PAD in women only was not anticipated. However, given that among atherosclerotic cardiovascular disease, PAD is unique in its female predominance, perhaps the observation should not be so surprising. The biological basis for a sex-specific association of increasing BMI with prevalent PAD is currently unclear. One possible explanation may lie with the differences in plaque histology in the periphery versus other arterial beds. Lower extremity atherosclerosis is characterized by greater degrees of calcification than plaques from other territories, and likewise expresses genes related to bone development (27). Elevated estrogen levels, such as those present in obesity (28), act to stimulate bone growth. It may be that high levels of estrogen, particularly characteristic of obese women (but also found in severely obese men (29)) have a heretofore unrecognized accelerating influence on PAD development, in contrast to atheroprotective functions generally felt to occur in other territories. Of note, female sex is a strong risk factor for calcification of the mitral valve annulus calcification, with increasing BMI also, albeit less strongly, associated with the condition (30, 31).

Our study provides an additional notable finding. We observed the lowest odds for PAD in both men and women who were overweight (BMI 25–29.9 kg/m2). Others have reported reduced all-cause mortality in association with overweight previously (32), but have been challenged as spurious due to confounding or reverse causality (33). However, investigations of PAD-specific outcomes have been minimal. Of note, a similar observation to ours was recently made for peripheral vascular disease-related mortality in an analysis of 3.6 million patients in a primary care database from the United Kingdom (5). These authors found the hazard ratio for peripheral vascular mortality to be lower in overweight individuals (HR=0.79) compared to the reference BMI (18.5–25 kg/m2) even after extensive adjustment for confounders. These authors additionally reported increasing risk for peripheral vascular-related mortality in association with greater BMI, but did not stratify their published analyses by sex. Similar to our female-specific association of increasing BMI with prevalent PAD, the biological basis for a possible protective effect of overweight remains unclear.

Beyond the association of increasing BMI with prevalent PAD, we also observed elevated odds for PAD in underweight individuals. This association persisted after multivariable correction – notable given the prevalence of individuals greater than 70 years of age in this group (37%). Given the cross-sectional nature of the study, it was possible that existing, symptomatic PAD contributing to impaired functional status and nutrition may have been disproportionately represented in the underweight participants in the sample, and partly explain the association. However, when we assessed claudication symptoms in the cohort, we found prevalence in the underweight group to be no different than in the complete cohort. The observation of elevated risk of PAD (in addition to cerebrovascular disease) in underweight individuals has notably been reported previously and found to persist even after correcting for smoking and other cardiovascular risk factors (34, 35). Similar to our study, prior reports have had low representation within the underweight group (<3%), leaving the rare, very large study such as ours and the recent analysis by Caleyachetty et al. (35) with adequate power to detect such an association. Importantly, the present study is at least the third recent report of an independent risk for PAD for underweight individuals, supporting the value of investigations into possible mechanisms underlying the association.

Our study has a number of limitations, the primary being its use of self-reported height and weight for the determination of BMI. This is obviously prone to inaccuracy and reporting bias. While there is some evidence of variation in accuracy of self-reported height and weight by sex (36), the reported differences are small and could not account for the marked differences in associations seen between sexes in our study. Self-reported disease status relied upon in our sample is another possible limitation (37–40). However, our survey employed the same validated questions regarding diabetes, hypertension and hypercholesterolemia used in NHANES, and given the similar rates of vascular disease risk factors and objective rates of PAD in our cohort and others, overall we feel that our sample is generalizable to middle aged and older American adults. Further, the potential miscategorization introduced by self-report would serve to bias our observations toward the null and underestimate the size of the actual effect size.

Further, our study’s cross-sectional nature does not allow for detection of incident disease or provide information on duration of obesity (41) or stability of weight (42), which have been reported to impact atherosclerotic cardiovascular disease. Our study is also limited to self-referred individuals which presents the potential for selection bias. This bias may affect findings in opposing ways, as persons who are aware of health risks may be more likely to seek out screening tests, whereas others who are particularly concerned about their health, avoid high risk behavior and actively seek ways to reduce risk may also pursue screening. Similarly, the cost of the screening exam, while modest, may have introduced further selection bias by underrepresenting individuals with low socioeconomic status. However, we have previously published an analysis supportive of a wide range of socioeconomic status within this sample (43). Further, review of other survey data collected around the time of the screenings included in our study suggest that the risk factor profile of the sample is similar to that of the general U.S. population (44–48). Additionally, the prevalence of PAD in our cohort is similar to other representative cohorts, demonstrating excellent external validity (49). Finally, although we corrected for multiple established risk factors, there are likely confounders that were not measured with our limited survey.

Despite its limitations, our study provides a novel and important finding of largely female-specific obesity-associated PAD risk. This observation should serve as additional impetus for large, prospective studies of PAD that are desperately needed, and further highlight the necessity of attention to enrolling representative numbers of women in these studies.

Supplementary Material

1
2

Highlights.

  • In >3 million persons, there was a J-shaped association of BMI with prevalent PAD

  • Overweight individuals (BMI 25–29.9 kg/m2) exhibited the lowest PAD prevalence

  • The association of obesity with PAD was markedly stronger in women than men

Acknowledgments:

This work has used computing resources at the High Performance Computing Facility of the Center for Health Informatics and Bioinformatics at New York University Langone Health. We gratefully acknowledge the participation and generosity of Life Line Screening (Cleveland, OH), who provided these data free of charge for the purposes of research and with no restrictions on its use for research or resultant publications.

Financial support: SPH and JSB were partially supported by the National Heart and Lung Blood Institute of the National Institutes of Health (HL135398 and HL114978, respectively).

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflict of interests: All authors declare no conflicts of interest relevant to the manuscript.

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NIHMS1543577-supplement-1.docx (326.5KB, docx)
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