Although previous studies have reported an association between height and cardiovascular disease, it is unclear whether height is associated with the risk of heart failure (HF). We hypothesized that height would be inversely associated with HF risk. We used prospective data from 22,042 male physicians (mean age 53.8 years) from the Physicians’ Health Study. Height was self-reported at baseline. Incident HF was ascertained using follow-up questionnaires and validated through review of the medical records in a subsample. The Cox proportional hazard model was used to compute the hazard ratio (HR) and corresponding 95% confidence interval (CI). The mean height ± SD was 1.78 ± 0.07 m. A total of 1,444 HF cases occurred during a mean follow-up of 22.3 years. Compared to subjects in the lowest height category (1.40 to 1.73 m), the HR for HF was 0.86 (95% CI 0.74 to 0.99), 0.82 (95% CI 0.70 to 0.95), and 0.76 (95% CI 0.63 to 0.91) for the height categories of 1.74 to 1.78 m, 1.79 to 1.83 m, and 1.84 to 2.08 m, respectively, after adjustment for age, weight, hypertension, and diabetes mellitus (p for trend = 0.0023). The HR per SD increment in height was 0.92 (95% CI 0.86 to 0.98) in a fully adjusted model. The exclusion of those with prevalent atrial fibrillation, left ventricular hypertrophy, valvular heart disease, and a history of coronary artery bypass grafting yielded similar results (HR per SD 0.88, 95% CI 0.83 to 0.94). In conclusion, our data demonstrated an inverse association between height and incident HF in United States male physicians. Additional studies to elucidate the underlying biologic mechanisms are warranted.
The effects of gravity on the cardiovascular system of an upright person are predominantly due to a reduction in vascular pressure and increased compliance within the venous system, resulting in the translocation of the vascular volume away from the heart. Gravity also increases the compliance of the arterial tree, resulting in reduced peripheral resistance and, hence, a reduction in afterload. Finally, the effect of gravity on the cardiovascular system increases as height increases. Also, there are findings of an inverse association between height and pulse pressure (PP) , which is a risk factor for heart failure (HF). However, despite the beneficial effects of height on the HF risk factors such as coronary heart disease and PP, no previous study has examined the relation between height and HF. Therefore, our objective was to determine whether adult height is inversely associated with the risk of HF in a prospective cohort of United States male physicians.
Methods
Data from the Physicians’ Health Study (PHS) was used in the present analysis. A detailed description of the PHS has been previously published. In brief, this is a completed randomized controlled trial using a 2 × 2 factorial design of low-dose aspirin and β-carotene in the primary prevention of cardiovascular disease and cancer. Each participant gave written informed consent, and the institutional review board at the Brigham and Women’s Hospital approved the study protocol. Of the 22,071 participants recruited into the PHS, 29 were excluded because of missing information on height (n = 6), baseline myocardial infarction (n = 1), and baseline HF (n = 22). Hence, a total sample of 22,042 participants was used in the present analyses.
At baseline, self-reported questionnaires were used to assess the information on height, which was reported in inches. We multiplied by a factor of 0.0254 to convert inches to meters.
Incident HF ascertainment in the PHS was achieved through the use of follow-up questionnaires. A questionnaire was mailed out every 6 months for the first year and yearly thereafter to obtain information on the outcomes of interest, including HF. A detailed description of HF validation in the PHS has been previously published. In the present analyses, HF and death ascertained through March 2010 was used.
Each participant provided information on weight, age, prevalent atrial fibrillation (yes or no), and hypertension (reported blood pressure values or the use of antihypertensive medication; yes or no), valvular heart disease (yes or no), history of coronary artery bypass grafting (yes or no), diabetes mellitus (yes or no), regular vigorous exercise enough to break into sweat (yes or no), cigarette smoking (never, past, or current), and alcohol consumption (daily, weekly, monthly, or rarely/never).
Because we did not assume a linear association between height and HF, we initially created categories of height using cutpoints that were close to the quartile distribution of height in this population (<1.74, 1.74 to 1.78, 1.79 to 1.83, and >1.83 m) for analysis. We presented the baseline characteristics across the categories of height. The person-time of follow-up was computed from baseline until the first occurrence of HF, death, or date of last known contact. Within each category of height, the crude incidence rates were calculated as new HF cases divided by person-time of follow-up. We fitted Cox proportional hazard models to estimate the hazard ratios (HRs) with corresponding 95% confidence intervals (CIs). Potential confounding was investigated by assessing whether the regression coefficient for height (continuous) changed by >10% when adding potential confounders to a model singly or jointly. We considered the factors that could influence height, as well as influence the risk of HF, in building our parsimonious model. We then tested the proportional hazard assumptions by including an interaction term between the follow-up time (log-transformed) and the variables in our parsimonious model. When the proportional hazard assumption was violated (p <0.05) for a given variable, we thus accounted for the nonproportionality of such variables by stratification.
The initial model (model 1) adjusted for age (continuous) and weight (continuous) and the parsimonious model (model 2) controlled for age (continuous), weight (continuous), hypertension (yes or no), and prevalent diabetes mellitus (yes or no). An additional model (model 3) was then created to assess the effect of smoking, exercise, and alcohol intake on the observed association between height and the risk of HF.
In a sensitivity analysis, we repeated the main analysis after the exclusion of participants with conditions known to predispose to HF (prevalent atrial fibrillation, left ventricular hypertrophy [LVH], valvular heart disease, and a history of coronary artery bypass grafting). The probability value for linear trend was computed by fitting a continuous variable that assigned the median height in each height category in a Cox regression model. The linearity of the relation between height and HF risk was satisfied on visual inspection of a plot of martingale residuals. We then fitted height as a continuous variable and computed HRs per each SD increment in height (0.07 m). All analyses were performed using SAS, version 9.2 (SAS Institute, Cary, North Carolina). The significance level was set at 0.05, and all p values were 2 tailed (α = 0.05).
Results
Among the 22,042 men in the PHS with baseline information on height, the mean age at randomization was 53.8 ± 9.5 years (range 40 to 86) and the mean height was 1.78 m (range 1.40 to 2.08). During a mean follow-up of 22.26 years, a total of 1,444 incident HF cases were reported. The baseline characteristics of the participants according to height category are listed in Table 1 . The incidence of HF ranged from 28.3/10,000 person-years to 30.4/10,000 person-years from the shortest to tallest height category. In the multivariate Cox regression model, height was inversely associated with the risk of HF. We observed up to a 24% reduction in the risk of HF when the tallest category was compared to the shortest category of height (p for trend = 0.0023; model 2; Table 2 ). For each SD increment in height, the multivariate adjusted HR for HF was 0.89 (95% CI 0.84 to 0.95). Similar results were obtained after the exclusion of prevalent atrial fibrillation, left ventricular hypertrophy, valvular heart disease, and a history of coronary artery bypass grafting: HR for each SD increment in height was 0.88 (95% CI 0.83 to 0.94). On evaluating the effect of modifiable behavioral risk factors (smoking, exercise, and alcohol intake) on our observed result, a similar trend in the risk of HF across height categories was noted (p for trend = 0.038).
| Characteristic | Height Category (m) | |||
|---|---|---|---|---|
| 1.40–1.73 (n = 5,636) | 1.74–1.78 (n = 5,921) | 1.79–1.83 (n = 6,566) | 1.84–2.08 (n = 3,919) | |
| Height (m) | 1.70 ± 0.04 | 1.77 ± 0.01 | 1.82 ± 0.01 | 1.88 ± 0.03 |
| Weight (kg) | 71.29 ± 8.45 | 77.29 ± 8.43 | 81.79 ± 9.16 | 87.91 ± 10.20 |
| Age (years) | 54.88 ± 10.35 | 54.41 ± 9.55 | 53.23 ± 9.21 | 52.10 ± 8.57 |
| Prevalent atrial fibrillation | 0.87% | 1.62% | 1.74% | 2.09% |
| Prevalent left ventricular hypertrophy | 0.34% | 0.25% | 0.11% | 0.18% |
| Prevalent valvular heart disease | 0.18% | 0.17% | 0.15% | 0.18% |
| Prevalent diabetes mellitus | 3.67% | 3.01% | 2.86% | 2.27% |
| Prevalent coronary artery bypass grafting | 0.73% | 0.54% | 0.56% | 0.54% |
| Vigorous exercise | 67.60% | 72.06% | 74.29% | 75.81% |
| Cigarette smoker | ||||
| Never | 50.31% | 49.05% | 49.63% | 49.23% |
| Past | 39.15% | 39.38% | 39.13% | 39.94% |
| Current | 10.54% | 11.56% | 11.24% | 10.83% |
| Alcohol use | ||||
| Rarely | 22.51% | 25.51% | 25.00% | 27.23% |
| Monthly | 47.14% | 48.91% | 50.25% | 50.06% |
| Weekly | 12.91% | 11.31% | 10.34% | 9.79% |
| Daily | 17.43% | 14.27% | 14.41% | 12.92% |
| Hypertension or taking hypertensive medication | 25.59% | 24.80% | 23.30% | 20.68% |
| Height Category (Range [m]) | HF (n) | Crude Incidence Rate (cases/1,000 PY) | HR (95% CI) | ||
|---|---|---|---|---|---|
| Model 1 ⁎ | Model 2 † | Model 3 ‡ | |||
| Q1 (1.40–1.73) | 346 | 2.83 | 1.0 | 1.0 | 1.0 |
| Q2 (1.74–1.78) | 394 | 3.0 | 0.84 (0.72–0.97) | 0.86 (0.74–0.99) | 0.89 (0.77–1.04) |
| Q3 (1.79–1.83) | 431 | 2.93 | 0.77 (0.66–0.89) | 0.82 (0.70–0.95) | 0.86 (0.74–1.01) |
| Q4 (1.84–2.08) | 273 | 3.04 | 0.68 (0.57–0.82) | 0.76 (0.63–0.91) | 0.83 (0.69–1.00) |
| p for Trend | <0.0001 | 0.0023 | 0.038 | ||
| Height modeled as continuous variable § | 0.85 (0.80–0.91) | 0.89 (0.84–0.95) | 0.92 (0.86–0.98) | ||
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