Association Between a 20‐Year Cardiovascular Disease Risk Score Based on Modifiable Lifestyles and Total and Cause‐Specific Mortality Among US Men and Women
The previously validated Healthy Heart Score effectively predicted the 20‐year risk of cardiovascular disease (CVD). We examine whether the Healthy Heart Score may extend to an association with total and cause‐specific mortality.
Methods and results
The prospective cohort study investigated 58 319 women (mean age 50.2 years) in the Nurses’ Health Study (1984–2010) and 29 854 in men (mean age 52.7 years) in the Health Professionals’ Follow‐up Study (1986–2010) free of cancer and CVD at baseline. The Healthy Heart Score included baseline current smoking; high body mass index; low physical activity; no or excessive alcohol intake; low intake of fruits and vegetables, cereal fiber, or nuts; and high intake of sugar‐sweetened beverages or red/processed meats. There were 19 122 total deaths. Compared with participants in the first quintile of the Healthy Heart Score (lowest CVD risk), participants in the fifth quintile (highest CVD risk) had a pooled hazard ratio of 2.26 (95% confidence interval [CI], 1.53–3.33) for total mortality; 2.85 (95 % CI, 1.92–4.23) for CVD mortality, and 2.14 (95% CI, 1.56–2.95) for cancer mortality. Participants in the fifth versus the first quintile also had significantly greater risk of death due to coronary heart disease (3.37; 95% CI, 2.16–5.25), stroke (1.75; 95% CI, 1.02–2.99), lung cancer (6.04; 95% CI, 2.78–13.13), breast cancer (1.45; 95% CI, 1.14–1.86), and colon cancer (1.51; 95% CI, 1.18–1.93).
The Healthy Heart Score, composed of 9 self‐reported, modifiable lifestyle predictors of CVD, is a potentially useful tool for the counseling of healthy lifestyles that was strongly associated with greater risk of all‐cause, CVD, and cancer mortality.
What Is New?
This is a large prospective cohort that extends the association of the Healthy Heart Score, which is composed of 9 self‐reported, modifiable lifestyle predictors of cardiovascular disease, to mortality risk.
Participants in the fifth quintile with a higher predictive cardiovascular disease risk based on the Healthy Heart Score had a 2.2‐fold higher risk of total mortality, 2.9‐fold higher risk of cardiovascular disease mortality, and 2.1‐fold higher risk of cancer mortality over 26 years (women) or 24 years (men).
What Are the Clinical Implications?
The Healthy Heart Score is a potentially useful tool for the counseling of healthy lifestyles that was strongly associated with greater risk of all‐cause, cardiovascular disease, and cancer mortality.
A lifestyle‐only risk score could be used to assess and motivate a larger audience in clinical and population‐wide settings.
Despite the decline in cardiovascular disease (CVD) mortality in the United States, it remains the leading cause of death.1 Several well‐established clinical risk factors for CVD, including high blood pressure, diabetes mellitus, and hypercholesterolemia, are viewed as major risk factors for management and control of subsequent CVD risk.2 The primary prevention of CVD has largely focused on pharmacological treatment plus lifestyle counseling, mostly addressing high‐risk adults identified by risk prediction tools that include in their assessment clinical risk factors (eg, high blood pressure or high cholesterol). Additionally, in the 1990s, dietary guidelines focused on low‐fat diets for prevention of CVD based on little evidence. However, evidence from controlled feeding trials with risk factors as outcome, long‐term epidemiologic studies, and older small randomized trials indicated that the health effects of dietary fats are heavily dependent on the replacement macronutrien.3 Another strategy for CVD prevention is through the primordial prevention of CVD risk factors through lifestyle modification, rather than the treatment or modification of risk factors once they become elevated. Data from epidemiological studies have shown that healthy dietary choices, physical activity, weight maintenance, and not smoking each play an important role in primordial prevention5 and the maintenance of cardiovascular health.7
A primordial prevention strategy may also extend to a lower risk in major cause‐specific deaths and greater longevity. For example, following a healthy lifestyle pattern may prevent more than 50% of deaths due to ischemic strokes,8 80% of sudden cardiac deaths,9 and 75% of all deaths due to CVD.10 Recent data suggest that a 60% lower risk of premature mortality was found in individuals with a body mass index (BMI) <22.4 kg/m2 and with a high score on the Alternate Healthy Eating Index, high level of physical activity, and nonsmoking.11
The previously validated Healthy Heart Score predicted the 20‐year risk of CVD in mid‐adulthood based on modifiable health behaviors (diet, physical activity, alcohol intake, smoking, and body weight) to address both primordial and primary prevention.12 Previously, women in the fifth quintile, with higher predicted CVD risk based on the Healthy Heart Score, had 18, 5, and 3‐fold higher risk of diabetes mellitus, hypertension, and hypercholesterolemia, respectively.13 In addition, the Healthy Heart Score recently showed moderately good performance (C statistic, 0.71; 95% confidence interval [CI], 0.66–0.76) in younger people.14
It remains unclear how well the Healthy Heart Score, a tool that can be potentially translated to a clinical setting, may extend to lower mortality risk. The support that the Healthy Heart Score may be associated with a broad range of outcomes is important clinically because an individual can adopt a set of behaviors to prevent different outcomes. Thus, we assessed the association between the Healthy Heart Score and total and cause‐specific mortality in NHS (Nurses’ Health Study) and HPFS (Health Professionals’ Follow‐up Study).
Because of the sensitive nature of the data collected for this study, requests to access the data set from qualified researchers trained in human subject confidentiality protocols may be sent to the Channing Division of Network Medicine at nhsaccess@channing.
We conducted analyses in NHS, a prospective cohort of 121 700 female nurses aged 30–55 years at baseline in 197615 and in HPFS, a cohort of 51 529 US male health professionals, aged 40 to 75 years, in 1986.16 Participants in both cohorts provided information on medical history, lifestyle factors, and newly diagnosed diseases on self‐reported questionnaires throughout follow‐up every 2 to 4 years. In the current investigation, 1984 was used as baseline for NHS and 1986 for HPFS, when we first obtained detailed information on diet and lifestyle, to calculate the 20‐year CVD risk score. We excluded participants with a history of CVD (myocardial infarction, angina, stroke, transient ischemic attack, and coronary revascularization) or cancer, or who were missing information on alcohol, physical activity, BMI, or smoking at baseline, and those who were outside of the predefined limits of energy intake levels (<800 or >4200 kcal/d for men and <500 or >3500 kcal/d for women) at baseline. The final study population consisted of 58 319 women in NHS (1984–2010) (mean age 50.2 years in 1984) and 29 854 in men in HPFS (1986–2010) (mean age 52.7 years in 1986). The institutional review boards at the Harvard T.H. Chan School of Public Health and Brigham and Women's Hospital approved the study protocols and return of the questionnaire implied informed consent.
Assessment of Healthy Lifestyle
The Healthy Heart Score is a CVD risk prediction model that estimates the 20‐year risk of CVD (nonfatal MI, fatal coronary heart disease [CHD], and ischemic stroke) based on lifestyle factors and was developed among a random two thirds of participants separately within 2 cohorts (HPFS and NHS)15 free of CVD, diabetes mellitus, and cancer at baseline.12 The sex‐specific risk scores were validated in the remaining one third of participants in each cohort and demonstrated good discrimination (Harrell C Index: 0.72; 95% CI, 0.71–0.74 [women]; 0.77; 95% CI, 0.76–0.79 [men]), fit, and calibration. While numerous lifestyle predictors of CVD were considered, the final parsimonious model included the 9 factors that best estimated CVD risk: current smoking; higher BMI; low physical activity; no or excessive alcohol consumption; low intake of fruits, vegetables, cereal fiber, or nuts; and high intake of sugar‐sweetened beverages or red/processed meats (Figure S1). A higher Healthy Heart Score reflected a higher risk of CVD.12 In addition, we set age as a constant (age=50) in the prediction model for this analysis because we were interested in the modifiable components of the Healthy Heart Score. Additionally, age is predictive of all disease, and specifically mortality. Because it is the strongest component of the score, it would have driven any observed association with mortality. We also adjusted for age separately by including it as a covariate in our Cox models. In sensitivity analysis we also conducted the analysis with the original equation.
Smoking status was self‐reported and categorized as “never,” “past,” or “current.” BMI (kg/m2) was calculated from self‐reported height and weight, which was highly correlated with previously directly measured weight (r=0.96).17 For physical activity, we used a previously validated physical activity questionnaire18 to estimate the average hours per week spent in moderate‐ or vigorous‐intensity activity (≥3 metabolic equivalent task). For each food item, participants were asked how often on average a specified portion was consumed during the past year.20 Cereal fiber and alcohol intake was calculated by multiplying the nutrient content of each food item (from the Harvard University Food Composition Database) by the frequency of intake and summed across all food items. We used the residual method to adjust cereal fiber for total energy.21 We calculated average grams per day of alcohol intake, assuming 12.8 g of alcohol in 12 oz of beer, 11.0 g of alcohol in 4 oz of wine, and 14.0 g of alcohol in 1.5 oz of liquor.
Data were obtained on family history of myocardial infarction, cancer, or diabetes mellitus; aspirin use; vitamin supplement use; new physician‐diagnosed hypertension, hypercholesterolemia, or diabetes mellitus; and menopausal status and postmenopausal hormone therapy and oral contraceptives use (in women).
Ascertainment of Mortality
Deaths through 2010 from any cause were the primary outcome of this analysis. Deaths were identified from the state vital statistics records and the National Death Index, or reported by families and the postal system.22 Using these methods, 98% of deaths in each cohort were able to be ascertained.22 For all deaths, we sought death certificates and, when appropriate, requested permission from the next of kin to review medical records. The underlying cause of death was assigned by a physician who was unaware of the data on diet quality after reviewing death certificates and medical records according to the International Classification of Diseases, Eighth Revision (ICD‐8).
Person‐years were calculated from the date of return of the baseline questionnaire to the date of diagnosis of death or the end of follow‐up (January 31, 2010, for HPFS and June 30, 2010, for NHS), whichever occurred first. We categorized the Healthy Heart Score into quintiles based on the distribution in each study population.
The hazard ratios (HRs) and 95% CIs for all‐cause and cause‐specific mortality according to quintiles of the Healthy Heart Score were estimated using Cox proportional hazards models using calendar year as the underlying time scale, and adjusting for age, race (white versus others), family history of myocardial infarction, aspirin use, multivitamin use, menopausal status and hormone use in women, total energy, and last time of physical checkup examination (first multivariable model). Since diagnoses of some conditions may encourage a participant to change their diet or other lifestyles, we additionally adjusted for history of hypertension, hypercholesterolemia, or type 2 diabetes mellitus (yes versus no) in a separate model. As the inclusion of these covariates did not change the HRs, we reported only the age‐adjusted and first multivariable model above.
We conducted a test for linear trend across quintiles of the Healthy Heart Score by assigning the median value to each quintile and modeling this as a continuous variable.23
We tested for interaction by age (<median versus ≥median), BMI status (<25 versus ≥25 kg/m2, ie, normal versus overweight/obesity), smoking status (never smoker versus ever smoker), alcohol intake (nondrinker, moderate drinker, heavy drinker), physical activity (<150 minutes versus ≥150 minutes), and diet score (above and below the median). For each potential modifier, we created a cross‐product term between the modifier and quintiles of the Healthy Heart Score. We used the quintile cut points established in the combined NHS and HPFS population to maintain consistency in the distribution of the Healthy Heart Score across categories of each modifier. We used likelihood ratio tests to compare models with and without the cross‐product terms to test formally for an interaction. All analyses were performed separately in each cohort and then pooled using an inverse, variance‐weighted meta‐analysis with fixed‐effects model. All analyses were performed using SAS statistical software, version 9.3 (SAS Institute Inc).
During 7 789 315 participant‐years of follow‐up, we documented 19 122 total deaths, including 11 403 in women and 7719 in men.
Baseline and lifestyle characteristics by quintiles of the Healthy Heart Score are shown in Table 1. In both cohorts, participants with the higher predictive CVD risk (top quintile) were more likely to have a higher BMI, be a current smoker, have higher energy intake, have a higher prevalence of diabetes mellitus or hypertension, and have a family history of diabetes mellitus. In addition, participants with the highest quintile had lower diet score, physical activity, and multivitamin use, and were less likely to undergo physical checkup examinations.
|Quintile 1||Quintile 2||Quintile 3||Quintile 4||Quintile 5|
|Nurses’ Health Study|
|Healthy Heart Score (20‐y risk)a||2.1 (0.2)||2.6 (0.1)||3.1 (0.2)||4.2 (0.6)||7.3 (3.0)|
|Healthy Heart Score components|
|Age, y||50.0 (7.3)||50.1 (7.3)||50.4 (7.2)||50.7 (7.0)||50.0 (6.9)|
|BMI, kg/m2||21.5 (1.8)||23.3 (2.2)||25.3 (2.6)||27.4 (5.1)||27.0 (6.4)|
|Current smoker, %||0||0||0.1||27.1||86.0|
|Fruits and vegetables, servings per d||5.9 (2.6)||5.5 (2.5)||5.2 (2.6)||5.2 (2.6)||4.5 (2.5)|
|Sugar‐sweetened beverages, servings per d||0.2 (0.3)||0.2 (0.4)||0.3 (0.5)||0.3 (0.6)||0.4 (0.8)|
|Red and processed meats, servings per d||0.9 (0.5)||1.1 (0.6)||1.2 (0.7)||1.3 (0.7)||1.3 (0.8)|
|Cereal fiber, g/d||5.2 (2.8)||4.5 (2.4)||4.0 (2.0)||3.8 (2.0)||3.4 (1.8)|
|Nuts, servings per d||0.2 (0.3)||0.1 (0.3)||0.1 (0.2)||0.1 (0.3)||0.1 (0.2)|
|Alcohol intake, g/d||8.6 (9.3)||6.0 (8.8)||4.7 (8.6)||6.7 (11.4)||8.5 (15.7)|
|Physical activity, MET‐h/wk||4.3 (2.2)||3.2 (2.1)||2.7 (1.9)||2.9 (2.1)||2.6 (1.9)|
|Energy intake, kcal||1736 (489)||1735 (511)||1747 (531)||1765 (544)||1754 (554)|
|Baseline diabetes mellitus, %||1.2||1.6||2.5||4.5||3.9|
|Baseline hypertension, %||13.1||15.9||21.6||27.9||25.3|
|Baseline hypercholesterolemia, %||6.3||7.3||8.4||9.5||8.6|
|Family history of MI, %||17.0||17.7||19.7||20.7||20.5|
|Family history of cancer, %||15.9||15.4||15.3||15.5||14.1|
|Family history of diabetes mellitus, %||24.7||27.4||31.7||32.8||31.9|
|Aspirin use (yes), %||71.5||72.6||71.6||71.0||70.1|
|Underwent physical examination for screening purposes||63.3||61.5||59.5||56.9||53.9|
|Health Professionals’ Follow‐up Study|
|Healthy Heart Score (20‐y risk)†||2.7 (0.3)||3.3 (0.1)||3.8 (0.2)||4.5 (0.2)||6.6 (3.1)|
|Healthy Heart Score components|
|Age, y||53.1 (9.8)||52.5 (9.6)||52.7 (9.5)||52.8 (9.3)||52.2 (8.9)|
|BMI, kg/m2||22.5 (1.6)||24.0 (1.4)||25.1 (1.5)||26.4 (1.9)||29.2 (4.1)|
|Current smoker, %||0.4||0.9||2.8||9.6||32.7|
|Fruits and vegetables, servings per d||5.4 (2.8)||4.9 (2.5)||4.6 (2.4)||4.4 (2.4)||4.2 (2.4)|
|Sugar‐sweetened beverages, servings per d||0.2 (0.3)||0.3 (0.4)||0.3 (0.5)||0.4 (0.6)||0.6 (0.8)|
|Red and processed meats, servings per d||0.8 (0.6)||1.0 (0.7)||1.2 (0.7)||1.3 (0.8)||1.6 (0.9)|
|Cereal fiber, g/d||7.4 (3.6)||6.2 (3.2)||5.6 (2.9)||5.1 (2.6)||4.5 (2.3)|
|Nuts, servings per d||0.8 (0.9)||0.6 (0.7)||0.6 (0.7)||0.6 (0.7)||0.5 (0.6)|
|Alcohol intake, g/d||14.0 (14.7)||12.1 (14.1)||11.0 (14.1)||10.4 (14.6)||10.0 (15.2)|
|Physical activity, MET‐h/wk||5.7 (6.1)||3.2 (3.7)||2.4 (3.0)||1.8 (2.6)||1.3 (2.2)|
|Energy intake, kcal||2076 (587)||2037 (593)||2044 (617)||2065 (628)||2145 (668)|
|Baseline diabetes mellitus, %||2.0||2.2||2.2||2.3||3.2|
|Baseline hypertension, %||13.9||16.3||17.8||21.0||26.0|
|Baseline hypercholesterolemia, %||11.2||9.6||10.0||9.7||11.0|
|Family history of MI, %||32.5||31.5||31.7||31.6||32.0|
|Family history of cancer, %||36.3||34.1||34.9||34.4||32.8|
|Family history of diabetes mellitus, %||17.8||17.6||19.0||20.1||21.6|
|Aspirin use (yes), %||25.4||25.6||27.1||27.0||29.7|
|Currently uses multivitamins, %||50.2||45.5||41.4||39.4||36.9|
|Underwent physical examination for screening purposes||53.3||51.9||50.9||49.8||42.6|
Both age‐ and multivariable‐adjusted analyses showed a significant association across quintiles of the Healthy Heart Score and total mortality, as well as cause‐specific mortality for CVD or cancer in both men and women (all P trend<0.05), across quintiles, and per 5% increase in the 20‐year risk of CVD (Table 2). The pooled HR comparing participants in the highest quintile (median, 6.6 in Healthy Heart Score) versus participants in the lowest quintile (median, 2.1) was 2.26 (95% CI, 1.53–3.33) for total mortality, 2.85 (95% CI, 1.92–4.23) for CVD mortality, and 2.14 (95% CI, 1.56–2.95) for cancer mortality. Those results were stronger for women than men especially in the fourth and fifth quintiles (Table 2).
|Quintile 1||Quintile 2||Quintile 3||Quintile 4||Quintile 5||P Trend||Per 5% Increase in the Score|
|Person‐years||284 421||284 321||284 031||283 160||282 278|
|Age‐adjusted model||1 [Reference]||1.08 (1.00–1.15)||1.21 (1.13–1.30)||1.92 (1.80–2.04)||2.99 (2.81–3.17)||<0.0001||3.42 (3.25–3.60)|
|MV‐adjusted model||1 [Reference]||1.06 (0.99–1.14)||1.15 (1.08–1.23)||1.74 (1.63–1.85)||2.75 (2.59–2.92)||<0.0001||3.17 (3.01–3.34)|
|Person‐years||132 506||132 475||132 282||132 063||131 594|
|Age‐adjusted model||1 [Reference]||1.07 (0.99–1.15)||1.17 (1.08–1.26)||1.32 (1.3–1.42)||1.99 (1.86–2.13)||<0.0001||3.07 (2.77–3.39)|
|MV‐adjusted model||1 [Reference]||1.06 (0.98–1.14)||1.14 (1.06–1.23)||1.28 (1.19–1.37)||1.86 (1.73–2.00)||<0.0001||2.75 (2.48–3.05)|
|Age‐adjusted model||1 [Reference]||1.08 (1.02–1.14)||1.19 (1.13–1.25)||1.59 (1.11–2.29)||2.43 (1.63–3.64)||<0.0001||3.27 (2.94–3.63)|
|MV‐adjusted model||1 [Reference]||1.06 (1.01–1.12)||1.15 (1.09–1.21)||1.48 (1.09–2.02)||2.26 (1.53–3.33)||<0.0001||2.97 (2.59–3.41)|
|Age‐adjusted model||1 [Reference]||1.32 (1.11–1.56)||1.63 (1.39–1.92)||2.67 (2.30–3.11)||4.23 (3.66–4.89)||<0.0001||4.23 (3.78–4.73)|
|MV‐adjusted model||1 [Reference]||1.25 (1.06–1.48)||1.42 (1.20–1.66)||2.09 (1.79–2.43)||3.49 (3.01–4.04)||<0.0001||3.63 (3.23–4.08)|
|Age‐adjusted model||1 [Reference]||1.14 (0.99–1.32)||1.22 (1.06–1.40)||1.58 (1.38–1.81)||2.65 (2.33–3.01)||<0.0001||4.95 (4.13–5.94)|
|MV‐adjusted model||1 [Reference]||1.11 (0.97–1.28)||1.17 (1.01–1.34)||1.47 (1.28–1.68)||2.33 (2.05–2.65)||<0.0001||4.05 (3.37–4.87)|
|Age‐adjusted model||1 [Reference]||1.23 (1.09–1.38)||1.41 (1.06–1.87)||2.06 (1.23–3.43)||3.34 (2.11–5.29)||<0.0001||4.50 (3.87–5.24)|
|MV‐adjusted model||1 [Reference]||1.18 (1.06–1.32)||1.28 (1.06–1.55)||1.75 (1.25–2.46)||2.85 (1.92–4.23)||<0.0001||3.75 (3.39–4.13)|
|Age‐adjusted model||1 [Reference]||0.99 (0.89–1.10)||1.14 (1.03–1.27)||1.67 (1.51–1.84)||2.62 (2.39–2.87)||<0.0001||3.08 (2.84–3.34)|
|MV‐adjusted model||1 [Reference]||0.99 (0.88–1.10)||1.13 (1.01–1.25)||1.62 (1.47–1.79)||2.52 (2.29–2.76)||<0.0001||2.95 (2.72–3.20)|
|Age‐adjusted model||1 [Reference]||1.11 (0.98–1.27)||1.15 (1.01–1.31)||1.38 (1.21–1.56)||1.87 (1.65–2.10)||<0.0001||2.74 (2.30–3.25)|
|MV‐adjusted model||1 [Reference]||1.11 (0.97–1.26)||1.14 (1.00–1.30)||1.37 (1.21–1.55)||1.82 (1.61–2.06)||<0.0001||2.63 (2.20–3.12)|
|Age‐adjusted model||1 [Reference]||1.05 (0.93–1.18)||1.14 (1.06–1.24)||1.51 (1.24–1.85)||2.21 (1.59–3.09)||<0.0001||2.98 (2.68–3.31)|
|MV‐adjusted model||1 [Reference]||1.04 (0.93–1.17)||1.13 (1.04–1.23)||1.49 (1.25–1.77)||2.14 (1.56–2.95)||<0.0001||2.86 (2.58–3.17)|
In addition, we evaluated specific causes of CVD, cancer, and non‐CVD and noncancer deaths. Participants in the top quintile versus the first quintile of the Healthy Heart Score had significantly higher risk of death due to CHD (pooled HR, 3.37; 95% CI, 2.16–5.25), stroke (pooled HR, 1.75; 95% CI, 1.02–2.99), lung cancer (pooled HR, 6.04; 95% CI, 2.78–13.13), breast cancer (pooled HR, 1.45; 95% CI, 1.14–1.86), and colon cancer (pooled HR, 1.51; 95% CI, 1.18–1.93) (Table 3).
|Quintile 1||Quintile 2||Quintile 3||Quintile 4||Quintile 5||P Trend|
|Coronary heart disease|
|MV‐adjusted model||1 [Reference]||1.20 (1.06–1.37)||1.35 (1.19–1.53)||2.00 (1.37–2.91)||3.37 (2.16–5.25)||<0.0001|
|MV‐adjusted model||1 [Reference]||1.13 (0.93–1.37)||1.06 (0.55–2.04)||1.26 (0.80–1.97)||1.75 (1.02–2.99)||<0.0001|
|MV‐adjusted model||1 [Reference]||1.26 (0.89–1.79)||1.38 (1.10–1.73)||2.84 (2.16–3.75)||6.04 (2.78–13.13)||<0.0001|
|Breast cancer (women)|
|MV‐adjusted model||1 [Reference]||1.14 (0.89–1.47)||1.13 (0.88–1.46)||1.53 (1.21–1.95)||1.45 (1.14–1.86)||0.0009|
|Prostate cancer (men)|
|MV‐adjusted model||1 [Reference]||1.10 (0.81–1.49)||1.08 (0.79–1.47)||0.99 (0.72–1.37)||1.13 (0.82–1.57)||0.64|
|MV‐adjusted model||1 [Reference]||0.95 (0.72–1.24)||1.26 (0.98–1.63)||1.48 (1.16–1.89)||1.51 (1.18–1.93)||0.005|
|MV‐adjusted model||1 [Reference]||1.01 (0.91–1.13)||1.09 (1.00–1.18)||1.29 (0.75–2.22)||1.92 (1.02–3.60)||0.006|
In analyses stratified by dichotomous categories of risk factors of the Healthy Heart Score, the association between quintiles of the Healthy Heart Score and total mortality was significantly higher for participants in the top quintile for each category studied, for both cohorts (Table 4).
|Quintile 1||Quintile 2||Quintile 3||Quintile 4||Quintile 5||P Trend||P for interaction|
|Age younger than the mediana|
|Person‐years, NHS||140 303||140 671||134 535||131 542||145 491|
|Person‐years, HPFS||65979||68 955||67 785||66 214||71 837|
|MV‐adjusted model, NHS||1 [Reference]||1.01 (0.85–1.19)||1.16 (0.98–1.36)||1.65 (1.42–1.92)||2.84 (2.48–3.26)||<0.0001||0.083|
|MV‐adjusted model, HPFS||0.91 (0.73–1.13)||1.20 (0.98–1.47)||1.31 (1.07–1.60)||2.19 (1.83–2.62)||<0.0001||0.002|
|Age older than or equal to the median|
|Person‐years, NHS||144 073||143 730||149 461||151 576||136 749|
|Person‐years, HPFS||66 527||63 520||64 497||65 849||59 757|
|MV‐adjusted model, NHS||1 [Reference]||1.07 (0.99–1.16)||1.15 (1.07–1.24)||1.76 (1.64–1.88)||2.73 (2.55–2.92)||<0.0001|
|MV‐adjusted model, HPFS||1.09 (1.01–1.18)||1.13 (1.05–1.23)||1.26 (1.17–1.37)||1.78 (1.64–1.92)||<0.0001|
|BMI <25 kg/m2|
|Person‐years, HPFS||92 744||66 143||39 413||19 721||104 412|
|MV‐adjusted model, NHS||1 [Reference]||1.05 (0.97–1.14)||1.12 (1.03–1.23)||2.56 (2.37–2.77)||2.80 (2.61–3.01)||<0.0001||<0.001|
|MV‐adjusted model, HPFS||1 [Reference]||1.21 (1.08–1.36)||1.40 (1.24–1.58)||2.10 (1.84–2.39)||3.34 (2.88–3.86)||<0.0001||0.07|
|BMI ≥25 kg/m2|
|Person‐years, NHS||274 811||227 442||132 590||92 408||141 142|
|Person‐years, HPFS||18 481||44 129||70 497||87 758||93 902|
|MV‐adjusted model, NHS||1 [Reference]||1.02 (0.79–1.30)||1.08 (0.85–1.37)||1.31 (1.03–1.66)||2.51 (1.98–3.18)||<0.0001|
|MV‐adjusted model, HPFS||1 [Reference]||0.87 (0.67–1.12)||1.15 (0.91–1.44)||1.26 (1.00–1.58)||2.06 (1.66–2.57)||<0.0001|
|Person‐years, NHS||203 965||171 480||149 074||98 894||17 689|
|Person‐years, HPFS||88 898||78 604||69 681||59 849||42 990|
|MV‐adjusted model, NHS||1 [Reference]||1.05 (0.96–1.14)||1.16 (1.06–1.27)||1.43 (1.30–1.58)||2.37 (2.03–2.76)||<0.0001||0.007|
|MV‐adjusted model, HPFS||1 [Reference]||1.05 (0.94–1.17)||1.12 (1.01–1.25)||1.17 (1.05–1.31)||1.56 (1.39–1.76)||<0.0001||0.11|
|Person‐years, NHS||80 411||112 821||134 981||184 225||264 551|
|Person‐years, HPFS||43 608||53 871||62 601||72 214||88 605|
|MV‐adjusted model, NHS||1 [Reference]||1.01 (0.90–1.13)||1.04 (0.93–1.16)||1.68 (1.51–1.85)||2.41 (2.19–2.65)||<0.0001|
|MV‐adjusted model, HPFS||1 [Reference]||1.04 (0.93–1.16)||1.08 (0.98–1.20)||1.23 (1.11–1.37)||1.77 (1.60–1.95)||<0.0001|
|Person‐years, NHS||134 666||185 892||213 637||193 055||188 171|
|Person‐years, HPFS||66 957||74 694||81 561||87 986||92 204|
|MV‐adjusted model, NHS||1 [Reference]||1.05 (0.95–1.15)||1.12 (1.02–1.23)||1.59 (1.45–1.74)||2.79 (2.56–3.04)||<0.0001||<0.001|
|MV‐adjusted model, HPFS||1 [Reference]||1.05 (0.96–1.16)||1.05 (0.96–1.16)||1.15 (1.05–1.27)||1.68 (1.54–1.84)||<0.0001||0.04|
|Person‐years, NHS||94 480||65 904||47 772||50 249||51 844|
|Person‐years, HPFS||47 833||42 893||38 191||32 638||27 917|
|MV‐adjusted model, NHS||1 [Reference]||1.11 (0.97–1.27)||1.19 (1.03–1.38)||2.10 (1.85–2.39)||2.58 (2.28–2.92)||<0.0001|
|MV‐adjusted model, HPFS||1 [Reference]||1.00 (0.87–1.15)||1.17 (1.01–1.34)||1.34 (1.17–1.55)||1.97 (1.71–2.26)||<0.0001|
|Person‐years, NHS||44 460||22 068||12 461||22 107||14 900|
|MV‐adjusted model, NHS||1 [Reference]||1.12 (0.91–1.36)||1.60 (1.29–1.99)||1.95 (1.63–2.32)||2.76 (2.29–3.32)||<0.0001|
|MV‐adjusted model, HPFS||1 [Reference]||1.46 (0.96–2.22)||1.28 (0.81–2.02)||1.37 (0.84–2.25)||2.80 (1.69–4.64)||0.0004|
|Physical activity >150 min|
|Person‐years, NHS||217 459||163 657||130 670||137 792||121 665|
|Person‐years, HPFS||90 543||65 995||50 619||39 105||27 926|
|MV‐adjusted model, NHS||1 [Reference]||1.04 (0.96–1.14)||1.10 (1.01–1.21)||1.88 (1.74–2.04)||2.74 (2.53–2.97)||<0.0001||0.008|
|MV‐adjusted model, HPFS||1 [Reference]||1.02 (0.91–1.13)||1.15 (1.02–1.28)||1.28 (1.13–1.44)||1.72 (1.51–1.95)||<0.0001||0.07|
|Physical activity ≤150 min|
|Person‐years, NHS||66 917||120 644||153 326||145 327||160 575|
|Person‐years, HPFS||41 963||66 480||81 662||92 958||103 669|
|MV‐adjusted model, NHS||1 [Reference]||1.08 (0.95–1.22)||1.20 (1.06–1.35)||1.61 (1.43–1.80)||2.78 (2.49–3.10)||<0.0001|
|MV‐adjusted model, HPFS||1 [Reference]||1.06 (0.94–1.18)||1.07 (0.96–1.19)||1.17 (1.05–1.30)||1.73 (1.56–1.91)||<0.0001|
|Diet score above the medianc|
|Person‐years, NHS||114 001||164 323||122 100||115 886||115 886|
|Person‐years, HPFS||90 543||65 995||50 619||39 105||27 926|
|MV‐adjusted model, NHS||1 [Reference]||1.05 (0.97–1.14)||1.14 (1.05–1.24)||1.81 (1.68–1.96)||2.34 (2.15–2.54)||<0.0001||<0.001|
|MV‐adjusted model, HPFS||1.09 (0.99–1.19)||1.08 (0.98–1.19)||1.23 (1.12–1.36)||1.78 (1.61–1.98)||<0.0001||0.008|
|Diet score below the median|
|Person‐years, NHS||59 375||119 978||161 895||167 232||202 255|
|Person‐years, HPFS||41 963||66 480||81 662||92 958||103 669|
|MV‐adjusted model, NHS||1 [Reference]||1.07 (0.92–1.25)||1.18 (1.02–1.36)||1.70 (1.48–1.95)||3.04 (2.66–3.47)||<0.0001|
|MV‐adjusted model, HPFS||1 [Reference]||0.99 (0.85–1.16)||1.13 (0.97–1.30)||1.18 (1.03–1.36)||1.71 (1.49–1.96)||<0.0001|
However, the association was greatest among participants who were younger (below the median [50 years for women and 52 years for men]), were ever smokers, had an alcohol consumption higher than the recommendations (5–14 g for women, 10–25 g for men), and had a diet score below the median (1.83 for women and 0.71 for men) (Table 4).
In this large prospective cohort of women and men, participants in higher quintiles of the Healthy Heart Score, composed of 9 self‐reported, modifiable lifestyle predictors of CVD (higher BMI, current smoking, low physical activity, lack of moderate alcohol consumption, low composite diet score), had a significantly increased risk of total and cause‐specific mortality. Specifically, participants in the fifth quintile with a higher predictive CVD risk based on the Healthy Heart Score had a 2.2‐fold higher risk of total mortality, 2.9‐fold higher risk of CVD mortality, and 2.1‐fold higher risk of cancer mortality over 26 years (women) or 24 years (men). Further, a higher predictive CVD risk was associated with greater risk of death due to specific types of CVD (CHD, stroke) and several site‐specific cancers (lung, breast, and colon). The association appeared to be more pronounced among participants who were younger, had optimal weight, were ever smokers, had alcohol consumption higher than recommended, or had a diet score below the median.
The findings in the current study are consistent with the scientific literature that an excess of adiposity,11 insufficient physical activity,25 cigarette smoking,26 and poor diet27 are independently associated with a greater risk of mortality. Studies analyzing a set of different lifestyles are difficult to compare because the estimates vary according to the lifestyle definition and the lifestyle factors selected.28 For example, prior studies in the NHS and the HPFS cohorts compared 5 versus 0 lifestyle risk factors (cigarette smoking, lack of physical activity, low diet quality, alcohol intake of 0 or ≥15 g/d, and overweight) and reported significant relative risks of 3.26, 8.17, and 4.31 for cancer, cardiovascular, and total mortality, respectively.10 In a Dutch study, the relative risks of total mortality for the least versus the most healthy lifestyle score were 4.07 for women and 2.61 for men.30
In our study that comprised the 9 most predictive modifiable lifestyle factors for CVD risk, the observed estimates were higher when we included age in the risk equation, as expected. A recent study that compared the contribution of changes in modifiable risk factors versus aging in a cohort of black participants showed that aging alone accounted for 60% of the development of 10‐year predicted atherosclerotic CVD risk.31 In our study, by observing significant associations exclusive of age, we showed that modifiable risk factors have an important contribution to CVD risk and, thus, these factors should be targeted for primary and primordial prevention strategies. Although our results were stronger in women than in men in the categorical analysis, that difference was less in the continuous analysis (per 5% increment in the risk score). That might be because the range of the score was greater among women than men.
This set of lifestyle behaviors may decrease CVD risk,12 the development of clinical risk factors,13 and, based on the present study, total, CVD, and cancer mortality. Based on data from the National Health and Nutrition Examination Survey 1988 to 2006, individuals with 6 or 7 ideal metrics, compared with individuals with 0 metrics, had significant relative risks of 0.49 for all‐cause mortality and 0.24 for CVD mortality over 14.5 years of follow‐up. The Healthy Heart Score extends upon this range as a 20‐year risk assessment, which uniquely focuses on risk factors for the primordial prevention of CVD. In addition, in our study, a higher predictive CVD risk was associated with cause‐specific mortality, due to CHD, stroke, lung cancer, breast cancer, or colon cancer. However, no effect was found for the Healthy Heart Score on prostate cancer mortality. Prior studies in the NHS and the HPFS cohorts showed that 82% of CHD,32 47% of total stroke,8 54% of ischemic stroke,8 and 81% of sudden cardiac death9 could be attributed to poor adherence to a low‐risk lifestyle pattern (defined as not smoking, healthy weight, daily exercise at moderate intensity, moderate alcohol intake, and prudent diet). Among men in the HPFS, 62% of CHD (79% among men younger than 65 years),33 35% of total stroke8 and 52% of ischemic stroke8 deaths may have been prevented with adherence to a low‐risk lifestyle. With regard to prostate cancer incidence, a previous meta‐analysis found no association with a healthy dietary pattern; however, an association may be observed with advanced cancer rather than total prostate cancer.34 More studies are needed to clarify these results. In our study, the associations were slightly more pronounced among participants who were younger (<50 years), had optimal weight, were ever smokers, had alcohol consumption higher than the recommendations, and had a diet score below the median. A recent study showed that adults with a BMI <22.4 kg/m2 and unhealthy lifestyles had a significantly higher risk of mortality than overweight individuals.11 The authors found that the lowest risk of premature mortality was in people with a BMI <22.4 kg/m2 with a healthy diet, physical activity, moderate alcohol consumption, and who did not smoke.
Study Strengths and Limitations
Our study includes a large sample size, a long and high follow‐up rate, large number of deaths, and the inclusion of overall as well as cause‐specific mortality. We studied a combination of 9 key modifiable lifestyle factors previously determined to predict CVD risk,12 which may have a stronger additive impact in behavioral lifestyle strategies and outcomes. In addition, recognizing that physicians now have less time to assess or advise patients on healthy lifestyle behaviors,35 this evidence‐based tool (web/online calculator: https://healthyheartscore.sph.harvard.edu/) can simplify the incorporation of health behavior assessment and counseling during clinical visits. Additionally, a lifestyle‐only risk score could be used to assess and motivate a larger audience in clinical and population‐wide settings, who may not have laboratory‐based measures available because of irregular checkups or lack of healthcare resources.
Some limitations need to be considered. The study may not be generalizable to the broader population as it included mostly white, well‐educated male and female health professionals, although the resulting homogeneity by socioeconomic status, education, or healthcare access helps reduce confounding. Measurement error in self‐reported lifestyle variables is inevitable; however, the data were collected prospectively and this error may be independent of study outcome ascertainment and, therefore, are more likely to attenuate associations towards the null.
The Healthy Heart Score, composed of 9 self‐reported, modifiable lifestyle predictors of CVD, is a potentially useful tool for the counseling of healthy lifestyles that was strongly associated with greater risk of all‐cause, CVD, and cancer mortality.
Sources of Funding
The study was supported by research grants UM1 CA186107, UM1 CA167552, HL60712, P01 CA87969, P01 CA55075, R01 HL034594, R01 HL088521, and R01 HL35464 from the National Institutes of Health.
Sotos‐Prieto formulated the study question and design, performed the statistical analyses, interpreted the results, and drafted the article. Cook and Chiuve contributed to the statistical modeling and interpretation of the results. Mattei and Sesso contributed to drafting of the article. Chiuve, Hu, Rimm, Willett, and Sesso contributed to the conception and design of the study and acquisition of the data. All authors contributed to the interpretation of data and critical revision of the article and approved the final version.
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