An abnormally high ankle-brachial index (ABI) is associated with increased all-cause and cardiovascular mortality. The relation of obesity to incident high ABI has not been characterized. The aim of this study was to investigate the hypothesis that increased obesity—quantified by body weight, body mass index, waist circumference, and waist-to-hip-ratio—is positively associated with a high ABI (≥1.3) and with mean ABI increases over a 4-year follow-up. Prevalence and incidence ratios for a high ABI were obtained for 6,540 and 5,045 participants, respectively, in the Multi-Ethnic Study of Atherosclerosis (MESA), using log-binomial regression models adjusted for demographic, cardiovascular, and inflammatory and novel risk factors. Linear regression was used to analyze mean ABI change. The prevalence and incidence of a high ABI were significantly higher for the highest compared to the lowest quartile of every baseline measure of obesity, with weight and body mass index demonstrating the highest incidence ratios (2.7 and 2.4, respectively). All prevalence and incidence ratios were positive and graded across obesity quartiles and were persistent in the subpopulation without diabetes. In those with normal baseline ABI values, 1 MESA standard deviation increase in every baseline measure of obesity was associated with significant increases in mean ABI values. In conclusion, independent, positive, and graded associations of increasing obesity with prevalent and incident high ABI and with mean increases in ABI values over time were found. Weight and body mass index seemed to be at least as strongly, if not more strongly, associated with a high ABI than were measures of abdominal obesity.
An abnormally elevated ankle-brachial index (ABI) has recently been associated with increased cardiovascular disease (CVD) risk. The relation of obesity to high ABI development is unclear. We aimed to examine the longitudinal relationship of various measures of obesity with an abnormally high ABI. Because abdominal obesity is particularly strongly associated with CVD risk, including insulin resistance and vascular stiffness, we hypothesized that waist circumference and waist-to-hip ratio would demonstrate stronger positive associations with high ABI than would more general measures of obesity.
Methods
The Multi-Ethnic Study of Atherosclerosis (MESA) aims to investigate the prevalence, correlates, and progression of subclinical CVD. Details of its design have been reported. The cohort includes 6,814 men and women aged 45 to 84 years, free of clinical CVD, and recruited from 6 United States field centers. Approximately 53% of the cohort is female, and the ethnic distribution is 38% Caucasian, 12% Chinese, 28% African American, and 22% Hispanic. Baseline examinations were performed from 2000 to 2002, and follow-up examinations were performed approximately 4 years later.
Participants completed a self-administered questionnaire on demographics and medical history, and anthropometric measurements were obtained in light clothing during the baseline examination. Body mass index (BMI) was calculated as weight divided by the square of height. Waist circumference was measured horizontally at the level of the umbilicus. Hip girth was measured at the maximum circumference of the buttocks. Systolic blood pressure was measured in a seated position 3 times with a Dinamap Pro 100 automated oscillometric sphygmomanometer (Critikon, Waukesha, Wisconsin); the final 2 measurements’ average was used for analysis. Total cholesterol, high-density lipoprotein cholesterol, serum glucose, and insulin were measured from blood samples after a 12-hour fast.
ABI was calculated from measurements of the bilateral brachial, posterior tibial, and dorsalis pedis arteries performed at baseline and follow-up examinations. After a 5-minute rest in the supine position, systolic blood pressures were obtained using appropriately sized cuffs and a 5-MHz Doppler probe (Nicolet Vascular, Golden, Colorado). The average of the 2 brachial arteries was used as the denominator; if the 2 brachial blood pressures differed by >10 mm Hg, the higher value was used. The ABI numerator was defined as the higher of the dorsalis pedis or posterior tibial pressure in each ankle and was used to calculate left- and right-sided ABIs. The lower of the left- and right-sided ABIs was defined as the “index ABI” for each subject. ABI values from >1.3 to >1.5 have been used previously to define an abnormally elevated ABI. The optimal upper limit of a normal ABI is unknown. Some have suggested that with an ABI ≥1.3, other modalities should be used to evaluate peripheral atherosclerotic disease. Thus, in this study, we defined a “high ABI” to be a left- or right-sided ABI ≥1.3. Incident high ABI was defined as a right or left ABI ≥1.3 on follow-up in participants with bilateral ABIs >0.9 and <1.3 at baseline. ABI changes were calculated by subtracting baseline from follow-up index ABI values. All ABI measurements have intraclass correlation coefficients >0.9 and technical error of measurement <5%.
Baseline and follow-up ABI measurements were available for 6,795 (99.7%) and 5,885 (86.4%) cohort participants, respectively. For prevalence and incidence high ABI analyses, those with ABIs within the normal range (0.9 <ABI <1.3) were chosen as the reference group. The presence of occlusive peripheral atherosclerotic disease may preclude the accurate measurement of distally elevated ABI, and this disease process likely has a risk factor distribution that may confound the analysis of obesity and high ABI. Thus, for the prevalence analysis, those with baseline right- or left-sided ABIs <0.9 were excluded, for a total population of 6,540; for incidence analysis, exclusion of those with abnormal ABIs at baseline (ABI <0.9 and >1.3) and those with follow-up ABIs <0.9 yielded a total population of 5,045.
Log-binomial regression models were fitted using a generalized linear model with log link and binomial error distribution. Linear assumptions were checked, and diabetes demonstrated the only significant interaction. Comparison among anthropometric measures was performed by calculating prevalence or incidence ratios for the highest versus the lowest quartile of each measure in separate models. Mean index ABI change per 1 standard deviation of baseline difference for each anthropometric measure was calculated using linear regression. Participants missing relevant covariates were excluded from regression models. The distributions of other covariates were similar in those missing or not missing data. The only exception was missing smoking pack-years, for which imputation was performed on the basis of current or former smoking, ethnicity, age, BMI, and gender.
Regression covariates were identified a priori to adjust for basic demographics, traditional cardiovascular risk factors, and novel risk factors, including markers of inflammation and dyslipidemia. Adjustment for albuminuria was based on its association with CVD and abnormal ABI, and glomerular filtration rate was included for the role of kidney disease in vascular abnormality. A process of backward selection with assessment of statistical significance and model goodness of fit was used to establish covariates. All regression models included age, gender, ethnicity, smoking status (never, former, current), smoking pack-years, systolic blood pressure, education (high school or more, less than high school), interleukin-6, homocysteine, high-sensitivity C-reactive protein, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, urinary albumin/creatinine ratio, and estimated glomerular filtration rate calculated using the Modification of Diet in Renal Disease (MDRD) study equation. Diabetes was defined as fasting glucose ≥126 mg/dl, previous diagnosis by self-report, or the use of antidiabetic medication and was included as a covariate in all regression models except the high ABI incidence model in subjects without diabetes. In this model, the natural log of the homeostasis model assessment of insulin resistance (HOMA-IR) ([fasting insulin (mU/L) × fasting glucose (mg/dl)]/405) was included as a covariate instead of diabetes. Diabetes was maintained as a covariate in other models because the inclusion of baseline fasting glucose, insulin, or natural log–transformed HOMA-IR generally did not improve model fit. Interleukin-6, homocysteine, and C-reactive protein were all skewed and thus natural log transformed. Inclusion of height, pulse pressure, and the presence or absence of the metabolic syndrome (per the National Cholesterol Education Program Adult Treatment Panel III definition) did not affect inferences, and none was significantly associated with outcomes; they were excluded from analysis. All analyses were performed using Stata version 10.0 (StataCorp LP, College Station, Texas).
Results
High ABI baseline prevalence was 8.8%. Participants with high ABIs were more likely to be male; to be Caucasian; to have lower mean systolic blood pressure, total cholesterol, high-density lipoprotein, and low-density lipoprotein; and to have and higher HOMA-IR ( Table 1 ).
| Variable | ABI ⁎ | p Value | |
|---|---|---|---|
| Normal (n = 5,944) | High (n = 596) | ||
| Age (years) | 61.9 ± 10.1 | 61.2 ± 10.2 | 0.117 |
| Men | 44.8% (2,660) | 71.5% (426) | <0.001 |
| Ethnicity | <0.001 | ||
| Caucasian | 37.7% (2,243) | 49.2% (293) | |
| Chinese | 12.5% (743) | 7.7% (46) | |
| African American | 27.8% (1,650) | 18.5% (110) | |
| Hispanic | 22.0% (1,308) | 24.7% (147) | |
| BMI (kg/m 2 ) | 28.2 ± 5.4 | 29.6 ± 5.8 | <0.001 |
| Waist circumference (cm) | 97.6 ± 14.2 | 102.6 ± 14.9 | <0.001 |
| Diabetes mellitus † | |||
| Impaired fasting glucose | 12.1% (718) | 13.6% (81) | 0.47 |
| Untreated diabetes | 2.5% (150) | 2.9% (17) | |
| Treated diabetes | 9.3% (553) | 10.4% (62) | |
| ln(HOMA-IR) | 0.11 ± 0.83 | 0.21 ± 0.85 | 0.004 |
| Smoking | 0.45 | ||
| Never | 51.0% (3,019) | 50.7% (301) | |
| Former | 36.1% (2,139) | 40.2% (239) | |
| Current | 13.0% (768) | 9.1% (54) | |
| Pack years smoking | 11.0 ± 20.3 | 10.6 ± 19.0 | 0.68 |
| Education (more than high school) | 81.8% (4,844) | 86.9% (516) | 0.28 |
| Family history of myocardial infarction | 42.4% (2,375) | 43.4% (243) | 0.66 |
| Prehypertension ‡ | 31.7% (1,885) | 32.4% (193) | <0.001 |
| Hypertension stage 1 | 18.1% (1,074) | 13.3% (79) | |
| Hypertension stage 2 | 7.0% (418) | 3.5% (21) | |
| SBP (mm Hg) | 126.5 ± 21.2 | 121.5 ± 18.5 | <0.001 |
| Antihypertensive medication use | 32.8% (1,949) | 28.0% (167) | 0.018 |
| Serum creatinine (mg/dl) | 0.94 ± 0.25 | 0.99 ± 0.21 | <0.001 |
| Glomerular filtration rate (ml/min/1.73 m 2 ) | 81.4 ± 18.5 | 81.2 ± 16.2 | 0.75 |
| Total cholesterol (mg/dl) | 194.7 ± 35.8 | 189.1 ± 34.7 | <0.001 |
| High-density lipoprotein (mg/dl) | 51.2 ± 14.9 | 48.4 ± 14.2 | <0.001 |
| Low-density lipoprotein (mg/dl) | 117.4 ± 31.5 | 114.7 ± 30.2 | 0.05 |
| Triglycerides (mg/dl) | 131.7 ± 90.7 | 131.4 ± 76.0 | 0.93 |
| Metabolic syndrome | 32.4% (1,925) | 31.2% (186) | 0.56 |
| Homocysteine (μmol/L) | 9.2 ± 3.5 | 9.8 ± 5.2 | <0.001 |
| C-reactive protein (mg/L) | 3.7 ± 5.7 | 3.5 ± 5.9 | 0.35 |
| Fibrinogen (mg/dl) | 345.6 ± 73.3 | 341.8 ± 72.4 | 0.23 |
| Interleukein-6 (pg/ml) | 1.5 ± 1.2 | 1.5 ± 1.3 | 0.76 |
| Urine albumin/creatinine (mg/g) | 24.7 ± 115.9 | 21.7 ± 79.9 | 0.64 |
⁎ Normal: 0.9 <ABI <1.3; high: ≥1.3.
† American Diabetes Association 2003 criteria: normal if fasting glucose is <100 mg/dl and not taking diabetes medication; impaired fasting glucose if fasting glucose = 100 to 125 mg/dl and not taking diabetes medications; untreated diabetes if fasting glucose ≥126 mg/dl and not taking diabetes medication; treated diabetes if taking diabetes medication.
‡ Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure guidelines: normal: SBP <120 mm Hg, DBP <80 mm Hg; prehypertension: SBP 120 to 139 mm Hg, DBP 80 to 89 mm Hg; stage 1 hypertension: SBP 140 to 159 mm Hg, DBP 90 to 99 mm Hg; stage 2 hypertension: SBP ≥160 mm Hg, DBP ≥100 mm Hg.
In fully adjusted models, the prevalence of a high ABI was significantly higher for the highest compared to the lowest quartile of each baseline anthropometric measure, with body weight demonstrating the highest prevalence ratio (3.7, 95% confidence interval 2.6 to 5.2) of the 4 measures ( Table 2 ). In participants with normal ABIs (0.9 <ABI<1.3) at baseline, increased baseline obesity was positively associated with the development of new-onset high ABI for all anthropometric measures, with body weight and BMI demonstrating the highest fully adjusted incidence ratios ( Table 2 ). All high ABI prevalence and incidence ratios were positive and graded across quartiles for all anthropometric measures ( Figure 1 ).
| Anthropometric Measure | Prevalence Ratio for High ABI ⁎ (95% CI) (n = 6,208) | p Value † | Incidence Ratio for High ABI (95% CI) (n = 4,805) | p Value | Incidence Ratio for High ABI in Subjects Without Diabetes (95% CI) (n = 4,303) | p Value |
|---|---|---|---|---|---|---|
| Body weight: 89.4–158.8 vs 32.7–66.2 kg | 3.7 (2.6–5.2) | <0.001 | 2.7 (1.9–3.8) | <0.001 | 2.3 (1.5–3.4) | <0.001 |
| BMI: 31–62 vs 15–25 kg/m 2 | 2.4 (1.8–3.2) | <0.001 | 2.4 (1.8–3.3) | <0.001 | 2.1 (1.5–3.1) | 0.001 |
| Waist circumference: 107–167 vs 59–88 cm | 2.3 (1.8–3.1) | <0.001 | 2.0 (1.4–2.7) | <0.001 | 1.7 (1.2–2.4) | 0.004 |
| Waist-to-hip ratio: 0.99–1.30 vs 0.65–0.87 | 1.4 (1.0–1.8) | 0.01 | 1.5 (1.1–2.0) | 0.03 | 1.3 (0.9–1.8) | 0.30 |
⁎ High ABI is defined as ≥1.3.
† The p values are for linear trend for all quartiles of each measure.
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
