Cigarette Smoking and Incident Heart Failure: Insights From the Jackson Heart Study
Abstract
Background:
Cigarette smoking has been linked with several factors associated with cardiac dysfunction. We hypothesized that cigarette smoking is associated with left ventricular (LV) structure and function, and incident heart failure (HF) hospitalization.
Methods:
We investigated 4129 (never smoker n=2884, current smoker n=503, and former smoker n=742) black participants (mean age, 54 years; 63% women) without a history of HF or coronary heart disease at baseline in the Jackson Heart Study. We examined the relationships between cigarette smoking and LV structure and function by using cardiac magnetic resonance imaging among 1092 participants, cigarette smoking and brain natriuretic peptide levels among 3325 participants, and incident HF hospitalization among 3633 participants with complete data.
Results:
After adjustment for confounding factors, current smoking was associated with higher mean LV mass index and lower mean LV circumferential strain (P<0.05, for both) in comparison with never smoking. Smoking status, intensity, and burden were associated with higher mean brain natriuretic peptide levels (all P<0.05). Over 8.0 years (7.7–8.0) median follow-up, there were 147 incident HF hospitalizations. After adjustment for traditional risk factors and incident coronary heart disease, current smoking (hazard ratio, 2.82; 95% confidence interval, 1.71–4.64), smoking intensity among current smokers (≥20 cigarettes/d: hazard ratio, 3.48; 95% confidence interval, 1.65–7.32), and smoking burden among ever smokers (≥15 pack-years: hazard ratio, 2.06; 95% confidence interval, 1.29–3.3) were significantly associated with incident HF hospitalization in comparison with never smoking.
Conclusions:
In blacks, cigarette smoking is an important risk factor for LV hypertrophy, systolic dysfunction, and incident HF hospitalization even after adjusting for effects on coronary heart disease.
Introduction
Clinical Perspective
What Is New?
•
Cigarette smoking is a well-known risk factor for atherosclerotic cardiovascular disease; however, less is known about the risk for heart failure (particularly in blacks).
•
We found that current cigarette smoking status, smoking intensity (cigarettes per day), and smoking burden (pack-years) were independently associated with higher left ventricular mass, lower left ventricular strain, higher brain natriuretic peptide levels, and higher risk of incident heart failure hospitalization in blacks.
•
These relationships were significant after adjustment for coronary heart disease, suggesting mechanisms beyond atherosclerosis probably contribute to myocardial dysfunction and increased risk of heart failure in smokers.
What Are the Clinical Implications?
•
Blacks are disproportionately affected by cardiovascular diseases, including heart failure and they are more likely to die of smoking-related diseases than whites.
•
Our findings suggest that smoking is associated with structural and functional left ventricular abnormalities that lead to heart failure in blacks and that smoking cessation should be encouraged in those with risk factors for heart failure.
Cigarette smoking is a risk factor for heart failure (HF) independent of traditional risk factors.1–5 Whereas cigarette smoking increases the risk of coronary heart disease (CHD), a major cause of HF, there may be other effects of smoking that result in cardiac dysfunction and HF.6 For example, smoking acutely increases systolic and diastolic blood pressure, total systemic vascular resistance, pulmonary artery pressure, and pulmonary vascular resistance, all known risk factors for HF.7 Furthermore, smoking is associated with carbon monoxide exposure, which has been reported to increase oxidative stress and lead to impaired mitochondrial function, inflammation, impaired endothelial function, and worsening renal function, all of which have been implicated in the pathophysiology of HF.8–13
Blacks have a doubling in the incidence of HF in comparison with other races.14 The prevalence of current cigarette smoking among blacks has declined in recent years, but remains ≈18% among adults.15 Although some epidemiological studies have demonstrated a significant association of current cigarette smoking with risk of developing HF, there are limited data specific to blacks who are substantially affected by cardiovascular diseases.
We hypothesized that cigarette smoking is associated with cardiac remodeling, left ventricular dysfunction, and incident HF hospitalization in blacks. To test this hypothesis, we examined the association of cigarette smoking status, intensity, and burden with cardiac structure and function and incident HF hospitalization in the JHS (Jackson Heart Study).
Methods
The data, analytic methods, and study materials can be made available to other researchers for purposes of reproducing the results or replicating the procedure by following the Jackson Heart Study publications procedures and data use agreements.
Study Participants
The JHS is a large prospective community-based observational study designed to investigate risk factors for cardiovascular diseases in blacks. Details of the JHS study design, recruitment, and data collection have been described previously.16 In brief, 5301 black participants residing in the Jackson, Mississippi, tricounty area (Hinds, Rankin, and Madison) were recruited for the baseline examination between 2000 and 2004 and completed 3 subsequent study follow-up visits (visit 1, 2000–2004; visit 2, 2005–2008; visit 3, 2009–2012). The JHS was approved by the institutional review boards of Jackson State University, Tougaloo College, and the University of Mississippi Medical Center in Jackson, Mississippi. All study participants provided written informed consent.
For the present analysis, we excluded all individuals with a history of CHD or HF (n=717), missing CHD/HF data (n=5), missing information on smoking status (n=33), or missing information on study covariates (n=422) at visit 1 (Figure 1).

Smoking Information
Smoking information was obtained via questionnaire at both visits 1 and 3. Participants who smoked >400 cigarettes in their lifetime were defined as ever smokers. Participants who gave a positive response to the question, “Do you now smoke cigarettes?” were classified as current smokers. Those who responded negatively to both of these questions were classified as never smokers.12 Participants who smoked >400 cigarettes but no longer smoked at the time of the examination were classified as former smokers. Cigarettes per day (smoking intensity) and pack-years (smoking burden) were also collected. Smoking burden and data related to time since quitting in former smokers is available in Table I in the online-only Data Supplement.
Clinical Covariates
At each examination, systolic and diastolic blood pressures were measured in the right arm of participants twice using the random-0 blood pressure sphygmomanometer (Hawksley and Sons Limited). The first blood pressure was obtained after allowing the participant to rest for 5 minutes in a seated position, and the second blood pressure was obtained after waiting 1 additional minute. The average of the 2 measurements was used. Body mass index was calculated as body weight (kg)/height (m2). Self-reported antihypertensive medication use was collected at the time of each examination. Venous blood samples were drawn from each participant after >12 hours of fasting. Fasting plasma glucose, hemoglobin A1c, and serum creatinine levels were assessed by using standard laboratory techniques. Diabetes mellitus was defined as the use of diabetes medications, a hemoglobin A1c ≥6.5%, or a fasting blood glucose ≥126 mg/dL at baseline. Estimated glomerular filtration rate was calculated by using the Modification of Diet in Renal Disease Study equation.17
Cardiac and Aortic Magnetic Resonance Imaging
Cardiac magnetic resonance (CMR) images were obtained with 1.5T MR Siemens Espree scanner (Siemens Medical Solutions) at visit 3 (Figure 1) in a randomly selected subset of 1092 participants without incident CHD between visits 1 and 3. Cine and tagged imaging were performed to assess LV mass, volumes, and deformation parameters. LV mass and volumes were indexed to body surface area measured at visit 3. LV peak midwall circumferential strain was assessed at the apex, middle, and base of the LV, and these 3 variables were averaged to determine total LV circumferential strain. All strain variables are negative values; more negative values indicate greater circumferential shortening. The coefficients of variation of each LV strain variable are as follows: base strain, 19.0%; mid strain, 20.2%; apex strain, 18.3%; and total strain, 15.5%. CMR aortic pulse wave velocity was calculated as follows: pulse wave velocity (m/s) = distance (mm)/transit time between ascending to the diaphragm level of descending aorta (ms). Transit time was calculated as the average time difference using the least-squares estimate between all data points on the systolic upslope of the ascending and descending aortic flow curves after peak flow normalization, and distance from ascending to descending aorta was measured using the oblique sagittal image through the thoracic aorta.
Brain Natriuretic Peptide Measurements
Plasma brain natriuretic peptide (BNP) levels were measured at visit 1 using a chemiluminescent immunoassay performed on the Siemens Advia Centaur (Siemens Medical Solutions) (Figure 1).18 The coefficient of variation of the assay was previously described.18 We included the histogram of raw BNP data in the Figure in the online-only Data Supplement.
Outcomes of the Longitudinal Study
The primary outcome was time to HF hospitalization. In the JHS cohort, HF hospitalization surveillance began January 1, 2005. Among participants who survived to January 1, 2005, we assessed the cumulative incidence of HF hospitalization from January 1, 2005, through December 31, 2012 (Figure 1). Potential HF hospitalizations were identified and adjudicated as previously described.19 In brief, hospitalization data were obtained from the hospital discharge index from all catchment area hospitals and annual follow-up information. Hospitalization data from noncatchment area hospitals were obtained after participant consent. The self-reported data from annual follow-up were confirmed with the hospital discharge index data. The primary diagnoses based on International Classification of Diseases, Ninth Revision, Clinical Modification codes were reviewed by trained medical personnel and adjudicated by trained adjudicators based on signs and symptoms, clinical documentation, laboratory tests, chest x-ray films, and other imaging modalities including echocardiography, multiple gated acquisition scans, and magnetic resonance imaging.20 Incident CHD was ascertained through directed patient queries during an annual telephone follow-up and ongoing surveillance of hospitalizations, and subsequently confirmed through the review of hospital records.
Statistical Analysis
Data are presented as mean with SDs for normally distributed continuous variables, median with interquartile ranges for nonnormally distributed continuous variables, and frequencies and proportions for categorical variables. ANOVA with post hoc Bonferroni test, Mann-Whitney U test, and χ2 test were used for comparison of variables between smoking status groups if applicable. Relationships between smoking variables and BNP levels and cardiac structure and function were examined as cross-sectional analyses at visit 1 and visit 3, respectively. Relationships between smoking variables and incident HF hospitalization were assessed as prospective longitudinal analyses.
Cross-Sectional Study
Relationships between smoking status (current, former, never), intensity among current smokers (cigarettes/d), and burden among ever smokers (pack-years), and cardiac structure and function measured using CMR (LV volume variables, LV ejection fraction, LV mass index, LV mass/volume, and LV systolic strain variables) and BNP levels were assessed by using linear regression analysis. Two models, minimally and further adjusted models, were constructed to evaluate the associations of smoking and cardiac structure and function. Model 1 included adjustment for age and sex, whereas model 2, in addition, included body mass index, systolic blood pressure, use of antihypertension medication, and history of diabetes based on a previous meta-analysis, and we additionally included estimated glomerular filtration rate to determine if the effect of smoking is independent of its effect on renal function.12,21 Medication use may affect the relationship between smoking status and LV structure and function. Thus, we created another model to examine the relationship between smoking status and LV structure and function assessed by cardiac magnetic resonance imaging with additional adjustment for classes of medications (calcium channel blocker use, β-blocker use, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker use, and diuretics use; Table II in the online-only Data Supplement) instead of antihypertensive medication use. To examine the possibility of unmeasured differences in blood pressure that may affect the associations, we additionally included average ambulatory systolic blood pressure instead of office systolic blood pressure (model 3). Ambulatory systolic blood pressure monitoring was performed as previously described.22 Ambulatory systolic blood pressure was evaluated only at visit 1, and the number of included participants who underwent ambulatory systolic blood pressure monitoring was small (n=711). Therefore, we were only able to examine the relationship between smoking status and BNP levels (model 3). Aortic valve stenosis and mitral valve regurgitation can increase LV load and promote LV hypertrophy. Thus, we additionally adjusted for aortic valve stenosis and mitral valve regurgitation severity evaluated by echocardiography at visit 1. Analyses of smoking status and BNP levels (Table III in the online-only Data Supplement, model 4), and smoking status and incident HF hospitalization (Table IV in the online-only Data Supplement, model 5) were additionally performed with adjustment for the grade of aortic valve stenosis and mitral valve regurgitation. Detailed information on the echocardiographic methods is described in the online-only Data Supplement. BNP levels were natural log transformed because they were not normally distributed. To visualize the relationship between smoking intensity and burden and BNP levels, restricted cubic spline curves were used. The analysis was adjusted using multiple covariates (model 2), and we used 3 knots. Knots were located at 10 (half-pack), 20 (pack), and 40 cigarettes (2 packs)/d for intensity, and 7.5, 15, and 30 pack-years for burden. For this analysis, the y axes were expressed as adjusted geometric mean ratios with 95% confidence interval (CI).
Longitudinal Study
We constructed Kaplan-Meier curves for cumulative survival free from incident HF for smoking status (current, former, never), intensity among current smokers (cigarettes/d), and burden among ever smokers (pack-years), and compared by using log-rank tests. Cox proportional hazards models were used to estimate the hazard ratios (HRs) of incident HF by using smoking status, intensity, and burden category groups. Censoring was applied to both loss to follow-up and deaths. The assumption of proportionality was tested by using Schoenfeld residuals. No significant deviations from proportionality were observed. Several models were constructed to evaluate associations of smoking information with outcomes. The same models that were used in the cross-sectional analyses were used, with the exception of model 2, in which incident CHD was additionally included as a time-dependent variable to evaluate the influence of incident CHD on incident HF. All statistical analyses were performed with STATA version 14 (STATA Corp). A 2-sided P value of <0.05 was considered significant.
Results
Baseline Characteristics
Among the study participants (n=4129), 503 (12%) were current smokers, 742 (18%) were former smokers, and 2884 (70%) were never smokers. Never smokers were more likely to be women than the other smoking status groups. Former smokers were older and had a higher prevalence of hypertension and diabetes mellitus than the other smoking status groups. Current smokers had a higher prevalence of current drinking, a lower prevalence of achieving the recommended physical activity level, and a higher mean estimated glomerular filtration rate than the other smoking status groups. The prevalence of taking calcium channel blockers, β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and diuretics was higher in former smokers than in the other groups, and the prevalence of taking these antihypertensive medications in current smokers was lower than in never smokers (Table 1).
Variable | Overall(n=4129) | Never Smoker(n=2884) | Former Smoker(n=742) | Current Smoker(n=503) |
---|---|---|---|---|
Age, y | 54±13 | 53±13 | 60±11 | 51±11 |
Female sex, n (%) | 2607 (63) | 1983 (69) | 381 (51) | 243 (48) |
BMI, kg/m2 | 31±7 | 32±7 | 31±6 | 29±7 |
SBP, mm Hg | 127±17 | 126±16 | 128±17 | 128±18 |
DBP, mm Hg | 76±9 | 76±9 | 75±9 | 77±9 |
SBP (ABPM), mm Hg | 135±28 | 135±32 | 136±15 | 137±16 |
DBP (ABPM), mm Hg | 79±27 | 79±32 | 78±10 | 82±10 |
Hypertension, n (%) | 2084 (50) | 1398 (49) | 453 (61) | 233 (46) |
Diabetes, n (%) | 691 (17) | 458 (16) | 168 (23) | 65 (13) |
Current alcohol use, n (%) | 1964 (48) | 1223 (42) | 367 (50) | 374 (74) |
Physical activity, n (%) | ||||
Poor | 1949 (47) | 1321 (46) | 340 (46) | 288 (57) |
Intermediate | 1341 (32) | 955 (33) | 253 (34) | 133 (26) |
Recommended | 839 (20) | 608 (21) | 149 (20) | 82 (16) |
Tc/HDL ratio | 4.1±1.3 | 4.1±1.3 | 4.2±1.4 | 4.2±1.5 |
eGFR, mL·min–1·1.73 m–2 | 87±17 | 87±17 | 85±17 | 93±18 |
Calcium channel blocker use | 650 (16) | 440 (16) | 154 (21) | 56 (11) |
β-Blocker use | 301 (7) | 201 (7) | 68 (9) | 32 (7) |
ACEI or ARB use | 506 (12) | 345 (12) | 126 (17) | 35 (7) |
Diuretic use | 1072 (27) | 739 (26) | 249 (34) | 84 (17) |
Average number of cigarettes/d | 10 (6–20) | 10 (8–20) | ||
Pack-years of cigarettes | 21 (11–39) | 17 (9–31) |
ABPM indicates ambulatory blood pressure; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; BMI, body mass index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure; and Tc/HDL ratio, total cholesterol/high density lipoprotein cholesterol ratio.
Smoking Status and Cardiac Structure and Function Assessed by CMR at Visit 3
After adjustment for confounding factors, current smoking was associated with higher mean LV mass index (β-coefficient, 5.24; 95% CI, 2.71–7.77) and LV mass/volume ratio (β-coefficient, 0.12; 95% CI, 0.06–0.18), whereas smoking status was not associated with mean LV volume measurements or LV ejection fraction (Table 2). However, current smoking was significantly associated with lower mean LV systolic function assessed with LV circumferential strain (total peak systolic circumferential strain: β-coefficient, 0.74; 95% CI, 0.26–1.22). Current smoking also was associated with higher mean pulse wave velocity in model 2 (β-coefficient, 1.25; 95% CI, 0.09–2.41) (Table 2). After additional adjustment for medication class (model 3), the relationship between smoking status and cardiac structure and function was not remarkably changed (Table II in the online-only Data Supplement). However, in this model, former smoking was associated with lower LV mass index.
Variable | Model 1 | Model 2 | ||||
---|---|---|---|---|---|---|
Never Smoker(n=791) | Former Smoker(n=198) | Current Smoker(n=103) | Never Smoker(n=791) | Former Smoker(n=198) | Current Smoker(n=103) | |
β (95% CI) | β (95% CI) | β (95% CI) | β (95% CI) | |||
LVEDVI, mL/m2 | Ref. | –2.27 (–4.55 to 0.14) | –1.86 (–4.81 to 1.08) | Ref. | –2.09 (–4.36 to 0.18) | –2.35 (–5.29 to 0.60) |
LVESVI, mL/m2 | Ref. | –1.06 (–2.55 to 0.43) | 0.12 (–1.80 to 2.05) | Ref. | –1.02 (–1.92 to 1.94) | 0.01 (–1.92 to 1.94) |
SVI, mL/m2 | Ref. | –1.21 (–2.68 to 0.25) | –1.99 (–3.88 to 0.10) | Ref. | –1.07 (–2.53 to 0.39) | –2.35 (–4.24 to –0.47) |
LVEF, % | Ref. | 0.01 (–1.41 to 1.43) | –0.75 (–2.58 to 1.08) | Ref. | 0.09 (–1.33 to 1.51) | –0.82 (–2.66 to 1.02) |
LVMI, g/m2 | Ref. | –2.09 (–4.21 to 0.02) | 4.97 (2.24 to 7.69)†§ | Ref. | –1.73 (–3.69 to 0.22) | 5.24 (2.71 to 7.77)†§ |
LV mass/volume | Ref. | 0.01 (–0.04 to 0.06) | 0.10 (0.04 to 0.17)†§ | Ref. | 0.01 (–0.03 to 0.06) | 0.12 (0.06 to 0.18)†§ |
LV strain‡ | ||||||
Total strain, % | Ref. | 0.02 (–0.36 to 0.41) | 0.56 (0.07 to 1.06)*§ | Ref. | 0.01 (–0.37 to 0.38) | 0.74 (0.26 to 1.22)†§ |
Base strain, % | Ref. | 0.08 (–0.39 to 0.55) | 0.60 (–0.01 to 1.20) | Ref. | 0.08 (–0.38 to 0.55) | 0.71 (0.12 to 1.31)*§ |
Mid strain, % | Ref. | –0.13 (–0.63 to 0.38) | 0.50 (–0.15 to 1.15) | Ref. | –0.16 (–0.66 to 0.33) | 0.71 (0.07 to 1.34)*§ |
Apex strain, % | Ref. | 0.16 (–0.31 to 0.63) | 0.61 (0.01 to 1.21)*§ | Ref. | 0.14 (–0.32 to 0.59) | 0.82 (0.23 to 1.41)†§ |
PWV, m/s | Ref. | 0.23 (–0.65 to 1.12) | 1.42 (0.27 to 2.57)*§ | Ref. | 0.24 (–0.64 to 1.12) | 1.25 (0.09 to 2.41)*§ |
Visit 3 smoking status information was used for the analysis. Model 1 was adjusted for age and sex. Model 2 was further adjusted for systolic blood pressure, antihypertensive medication use, body mass index, diabetes mellitus, and estimated glomerular filtration rate. CI indicates confidence interval; CMR, cardiac magnetic resonance; LV, left ventricular; LVEDVI, left ventricular end-diastolic volume indexed; LVEF, left ventricular ejection fraction; LVESVI, left ventricular end-systolic volume indexed; LVMI, left ventricular mass index; Ref, reference; and PWV, pulse wave velocity from ascending aorta to descending aorta.
*
P<0.05.
†
P<0.01.
‡
Strain indicators represent mean peak systolic circumferential strain.
§
Statistically significant findings.
Smoking Status, Intensity, and Burden and BNP Levels at Visit 1
After adjustment for confounding factors, current smoking (model 2: β-coefficient, 0.182; 95% CI, 0.074–0.290), smoking intensity among current smokers (model 2, ≥20 cigarettes/d versus never smokers: β-coefficient, 0.298; 95% CI, 0.122–0.474), and smoking burden among ever smokers (model 2, ≥30 pack-years versus never smoker: β-coefficient, 0.139; 95% CI, 0.018–0.260) were significantly associated with higher mean BNP levels (Tables 3 through 5). Even after adjustment for mean systolic ambulatory blood pressure instead of office systolic blood pressure, the association was not remarkably changed (Tables 3 through 5, model 3). After adjustment for grade of aortic valve stenosis and mitral valve regurgitation severity, the association was not remarkably changed (Table III in the online-only Data Supplement). Figure 2 shows the restricted cubic spline between smoking intensity (average cigarettes/d), smoking burden (pack-years), and log transformed BNP levels. Log-transformed BNP levels were positively associated with increased smoking intensity and burden.
Model | Never Smoker | Former Smoker | Current Smoker |
---|---|---|---|
β (95% CI) | β (95% CI) | ||
Model 1 | Ref. | 0.000 (–0.094 to 0.095) | 0.218 (0.111 to 0.325)†‡ |
Model 2 | Ref. | 0.042 (–0.053 to 0.137) | 0.182 (0.074 to 0.290)†‡ |
Model 3 | Ref. | 0.165 (–0.026 to 0.357) | 0.329 (0.061 to 0.597)*‡ |
Model 1 was adjusted for age and sex. Model 2 was further adjusted for body mass index, systolic blood pressure, antihypertensive medication use, diabetes mellitus, and estimated glomerular filtration rate. Model 3 was adjusted for model 2, but including mean systolic ambulatory blood pressure instead of office systolic blood pressure. BNP indicates brain natriuretic peptide; CI, confidence interval; and Ref, reference.
*
P<0.05.
†
P<0.01.
‡
Statistically significant findings.
Model | Never Smoker | <10 Cigarettes/d | 10–19 Cigarettes/d | ≥ 20 Cigarettes/d |
---|---|---|---|---|
β (95% CI) | β (95% CI) | β (95% CI) | ||
Model 1 | Ref. | 0.101 (–0.086 to 0.288) | 0.203 (0.038 to 0.367)*† | 0.341 (0.165 to 0.516)† |
Model 2 | Ref. | 0.065 (–0.123 to 0.252) | 0.151 (–0.015 to 0.317) | 0.298 (0.122 to 0.474)† |
Model 3 | Ref. | 0.135 (–0.297 to 0.568) | 0.321 (–0.098 to 0.741) | 0.711 (0.206 to 1.215)† |
Model 1 was adjusted for age and sex. Model 2 was further adjusted for body mass index, systolic blood pressure, antihypertensive medication use, diabetes mellitus, and estimated glomerular filtration rate. Model 3 was adjusted for model 2, but including mean systolic ambulatory blood pressure instead of office systolic blood pressure. Smoking intensity analyses include only never smoker and current smoker. BNP indicates brain natriuretic peptide; CI, confidence interval; and Ref, reference.
*
P<0.01.
†
Statistically significant findings.
Model | Never Smoker | < 7.5 Pack-Years | 7.5–15 Pack-Years | 15–30 Pack-Years | ≥30 Pack-Years |
---|---|---|---|---|---|
β (95% CI) | β (95% CI) | β (95% CI) | β (95% CI) | ||
Model 1 | Ref. | 0.036 (–0.132 to 0.204) | 0.083 (–0.061 to 0.228) | 0.075 (–0.050 to 0.200) | 0.119 (–0.002 to 0.240) |
Model 2 | Ref. | 0.030 (–0.139 to 0.199) | 0.104 (–0.040 to 0.248) | 0.069 (–0.055 to 0.193) | 0.139 (0.018 to 0.260)*‡ |
Model 3 | Ref. | –0.001 (–0.385 to 0.384) | 0.112 (–0.216 to 0.441) | 0.213 (–0.056 to 0.482) | 0.375 (0.124 to 0.626)†‡ |
Model 1 was adjusted for age and sex. Model 2 was further adjusted for body mass index, systolic blood pressure, antihypertensive medication use, diabetes mellitus, and estimated glomerular filtration rate. Model 3 was adjusted for model 2, but including mean systolic ambulatory blood pressure instead of office systolic blood pressure. Smoking burden analyses include never smoker and ever smoker. BNP indicates brain natriuretic peptide; CI, confidence interval; and Ref, reference.
*
P<0.05.
†
P<0.01.
‡
Statistically significant findings.

Smoking Status, Intensity and Burden, and Incident HF Hospitalizations
At the time of January 1, 2005, 3633 participants of 4129 were alive and eligible for the longitudinal analysis. Over a median follow-up of 8.0 years (interquartile range, 7.7–8.0 years), there were 147 incident HF hospitalizations (incidence rate, 5.46/1000 person-years). Both former and current smokers had a higher incidence of HF than never smokers (log-rank P<0.01) (Figure 3). Current smoking was associated with increased incident HF hospitalizations after adjustment for conventional risk factors and incident CHD as a time-dependent variable (HR, 2.82; 95% CI, 1.71–4.64) (Table 6). Furthermore, smoking intensity among current smokers (model 2, ≥20 cigarettes/d versus never smoker: HR, 3.48; 95% CI, 1.65–7.32) was associated with incident HF hospitalization in multivariable analyses (Table 7). Smoking burden among ever smokers was associated with incident HF, albeit not linearly (model 2, ≥15 pack-years versus never smoker: HR, 2.06; 95% CI, 1.29–3.33, P<0.01 and ≥30 pack-years versus never smoker: HR, 1.60; 95% CI, 1.00–2.56) (Table 8). After additional adjustment for valvular heart disease, the association was not remarkably changed (Table IV in the online-only Data Supplement, model 5).
Model | Never Smoker | Former Smoker | Current Smoker |
---|---|---|---|
HR (95% CI) | HR (95% CI) | ||
Model 1 | Ref. (1) | 1.46 (0.99–2.13) | 2.25 (1.39–3.65)†‡ |
Model 2 | Ref. (1) | 1.44 (0.98–2.12) | 2.82 (1.71–4.64)†‡ |
Model 1was adjusted for age and sex. Model 2 was further adjusted for systolic blood pressure, antihypertensive medication use, body mass index, diabetes mellitus, estimated glomerular filtration rate, and incident coronary heart disease as a time-dependent variable. CI indicates confidence interval; HF, heart failure; HR, hazard ratio; and Ref, reference.
*
P<0.05.
†
P<0.01.
‡
Statistically significant findings.
Model | Never Smoker | <10 Cigarettes/d | 10–19 Cigarettes/d | ≥20 Cigarettes/d |
---|---|---|---|---|
HR (95% CI) | HR (95% CI) | HR (95% CI) | ||
Model 1 | Ref. (1) | 1.42 (0.52–3.89) | 2.08 (0.99–4.35) | 2.67 (1.30–5.50)†‡ |
Model 2 | Ref. (1) | 1.57 (0.57–4.35) | 2.64 (1.24–5.62)*‡ | 3.48 (1.65–7.32)†‡ |
Model 1was adjusted for age and sex. Model 2 was further adjusted for systolic blood pressure, antihypertensive medication use, body mass index, diabetes mellitus, estimated glomerular filtration rate, and incident coronary heart disease as a time-dependent variable. Smoking intensity and burden analyses include only never smoker and current smoker. The number of each smoking status is as follows: never smoker, n=2884; former smoker, n=742; and current smoker, n=503. The number of each smoking intensity is as follows: <10 cigarettes/d, n=143; 10–19 cigarettes/d, n=187; ≥20 cigarettes/d, n=162. CI indicates confidence interval; HF, heart failure; HR, hazard ratio; and Ref, reference.
*
P<0.05.
†
P<0.01.
‡
Statistically significant findings.
Model | Never Smoker | <7.5 Pack-Years | 7.5–15 Pack-Years | 15–30 Pack-Years | ≥30 Pack-Years |
---|---|---|---|---|---|
β (95% CI) | β (95% CI) | β (95% CI) | β (95% CI) | ||
Model 1 | Ref. | 0.304 (0.042–2.192) | 1.349 (0.701–2.598) | 2.194 (1.385–3.475)*† | 1.479 (0.928–2.356) |
Model 2 | Ref. | 0.310 (0.043–2.240) | 1.425 (0.735–2.765) | 2.056 (1.290–3.275)*† | 1.601 (1.002–2.557)*† |
Model 1 was adjusted for age and sex. Model 2 was further adjusted for systolic blood pressure, antihypertensive medication use, body mass index, diabetes mellitus, estimated glomerular filtration rate, and incident coronary heart disease as a time-dependent variable. The number of each smoking burden is as follows: <7.5 pack-years, n=234; 7.5–15 pack-years, n=256; 15–30 pack-years, n=362; and ≥30 pack-years, n=393. CI indicates confidence interval; HF, heart failure; and Ref, reference.
*
P<0.05.
†
Statistically significant findings.

Discussion
In our community-based cohort of blacks, current smoking was associated with a higher LV mass and lower LV circumferential strain assessed by CMR. Current smoking status and higher levels of smoking intensity and burden were associated with higher mean BNP levels at baseline. Furthermore, current smoking and higher levels of smoking intensity and burden also were associated with increased risk of incident HF hospitalization after adjusting for possible confounding factors including incident CHD.
Limited evidence on the relationship between smoking and HF currently exists.1–5,23,24 In the Health ABC study (Aging and Body Composition), both current smoking and past smoking were associated with incident HF independently of incident CHD, and smoking burden was associated with incident HF among former smokers, but not among current smokers.1 The impact of current smoking on incident HF was higher in our study (HRs 1.93 versus 2.82 in ours) than in their study. To our knowledge, their study was the first that examined the relationship between smoking status and incident HF with adjustment for incident CHD, and the examination of the relationships between smoking burden and incident HF, as well. Our study results are consistent with the Health ABC Study, and extend the findings to a large cohort of blacks. However, in contrast to the Health ABC Study, our study showed dose-dependent associations of smoking intensity among current smokers on incident HF accounting for incident CHD. This difference may be attributed to the difference in the numbers of current smokers in their study (n=221) and ours (n=503). In their study, past smoking was associated with incident HF, and there was dose dependency between smoking burden and incident HF among former smokers. Thus, the relationship between smoking behavior and incident HF could be different because of other factors including different ethnicities (40% blacks in the Health ABC Study and 100% blacks in our study). Recently published articles reported the relationships between smoking and different phenotypes of incident HF. In the PREVEND study (The Prevention of Renal and Vascular Endstage Disease Intervention Trial), current smoking was associated with incident HF with reduced ejection fraction.4 However, in the Framingham Heart Study, current smoking was associated with incident HF with preserved ejection fraction.3 In the JHS, the information on phenotypes of incident HF is currently not available, and further investigation is warranted to determine whether smoking status is associated with specific phenotypes of incident HF in blacks.
There are several previous studies that examined the relationship between smoking and LV mass.25–30 Many of them showed a positive association; however, there are some studies that showed neutral or negative associations.27,28 We showed a positive association between current smoking and LV mass among those without CHD. These observations are supported by several previous studies that demonstrated a positive relationship between current smoking and LV hypertrophy.25,26 Our study confirmed this finding in a large community-based cohort of blacks. It is important to note that our study used CMR data. CMR is a more accurate technique for assessment of LV wall thickness, volumes, and ejection fraction than echocardiography; therefore, CMR offers diagnostic advantages over echocardiography.31–33 Furthermore, our results are consistent with other studies evaluating risk factors such as smoking and CMR-derived measures of cardiac structure.29 One prior study that showed a negative association between smoking and LV mass or LV mass index used a unique cohort of Army Training Regiment recruits with an average age of 20 years.28 Thus, the results of that study may not be generalizable to the general community or older smokers. In our analysis, after additional adjustment for class of medication use, former smoking was associated with lower LV mass index. The mechanism of this association is unclear at this point, and further investigation on this issue is warranted.
A recently published study showed a significant correlation between current smoking and LV diastolic dysfunction assessed by tissue Doppler echo imaging.26 This study also found a nonsignificant relationship between smoking and global longitudinal strain. Another study showed an adverse association between smoking status and burden on LV circumferential strain assessed by CMR among those without any symptoms or history of cardiovascular disease.34 These study findings are somewhat limited by their cross-sectional design and lack of HF outcomes. Our study builds on this work by using a large cohort of blacks and demonstrating and linking the associations of adverse structural and functional cardiac effects of cigarette smoking with incident HF hospitalizations.
In our study, smoking status, intensity, and burden were associated with higher BNP levels. Nadruz and colleagues35 showed that, among those free of overt CHD and HF, cumulative cigarette exposure assessed by pack-years was associated with higher N-terminal pro-BNP levels, and active smokers had a higher incidence of elevated N-terminal pro-BNP levels after 15 years of follow up. Otsuka and colleagues36 also showed smoking status was positively associated with higher N-terminal pro-BNP levels. Our study results showed that all measures of smoking (status, intensity, and burden) were associated with higher BNP levels, and extended these findings to a large cohort of blacks. Both larger LV mass index and higher BNP levels reflect higher LV wall stress. Based on our findings, it is possible that current smoking, smoking intensity, and smoking burden are associated with higher LV wall stress, increasing the risk of HF.
Cigarette smoking has been associated with higher levels of inflammatory cytokines and dysfunction and death of endothelial cells through increased oxidative stress.9,10,37,38 Endothelial dysfunction and inflammation may affect cardiac structure and function either through direct influences on the myocardium or indirectly by accelerating arterial atherosclerosis and augmented LV afterload. In turn, carbon monoxide exposure may cause LV hypertrophy and systolic dysfunction independently of its effect on endothelial function or blood pressure.11 These collective effects of smoking may result in the larger LV mass and systolic dysfunction seen in our study. Furthermore, cigarette smoking is independently associated with worsening of kidney function.12 Thus, cigarette smoking–related alterations of cardiac structure and function, combined with impairment of renal function, may lead to incident HF independently of CHD. In this study, smoking burden among ever smokers was associated with incident HF, albeit nonlinearly. This may be related to a longer time since quitting in the group with the highest smoking burden (≥30 pack-years). Regardless, higher smoking burdens (both ≥15 pack-years and ≥30 pack-years) were significantly associated with more incident HF hospitalization.
In the current study, former smoking was not associated with adverse cardiac remodeling, impaired cardiac function, BNP levels, or incident HF hospitalization after adjusting for possible confounding factors. These findings suggest that smoking cessation may be an important strategy to reduce the risk of impaired cardiac function and HF in current smokers.
Our study has a few limitations including lack of information about the type of cigarettes (including tar concentration or menthol) that the participants smoked. Self-reported smoking status was not confirmed with cotinine levels, which are currently unavailable in JHS. Our data were obtained from an all-black cohort in Jackson, Mississippi, and may not be generalizable to other ethnic/racial groups or other regions. Unmeasured confounding may have influenced the results. It is also possible that HF cases may have been missed (or misclassified); however, the definition for HF that was used has been previously used and validated in other JHS analyses, and in ARIC (Atherosclerosis Risk in Communities Study), as well. In our study, the relationships between smoking status and BNP levels and cardiac structure and function were assessed at visits 1 and 3, respectively. The longitudinal relationship between smoking status and HF hospitalization was evaluated beginning 5 years after visit 1 (2005). Therefore, time differences of performed examinations may limit the causal inference of the effect of smoking on cardiac structure and function and BNP with the relationship between smoking and HF hospitalization. Finally, because of the lack of follow-up echocardiograms and appropriate clinical data, we were unable to assess the type of HF (ie, HF with preserved versus reduced ejection fraction).
Our study also has several strengths. To our knowledge, this study is the first prospective study to show a dose relationship between cigarette smoking and incident HF in a large cohort of blacks. Blacks have a higher incidence of HF than whites, Hispanics, and Asians.14,39 Thus, smoking cessation may be a potential strategy to attenuate the higher rate of HF in blacks. Because of superior reliability, we used CMR instead of echocardiography to assess cardiac structure and function.40
Cigarette smoking is a well-known risk factor for cardiovascular disease. However, the influences on cardiac structure and function may not be fully recognized because of the strong association with CHD. In our study, cigarette smoking was associated with higher mean LV mass index and LV mass/volume assessed with CMR among those without known CHD. Smoking intensity and burden also are associated with higher mean BNP levels and incident HF in a dose-dependent manner. Therefore, in blacks, cigarette smoking is a strong risk factor for higher LV mass and systolic dysfunction, and incident HF hospitalization independent of its effects on incident CHD.
Acknowledgments
The authors also wish to thank the staff and participants of the JHS. The views expressed in this article are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; the Center for Tobacco Products; or the US Department of Health and Human Services.
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Received: 25 September 2017
Accepted: 15 February 2018
Published online: 16 April 2018
Published in print: 12 June 2018
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Sources of Funding
The JHS is supported and conducted in collaboration with Jackson State University (HHSN268201300049C and HHSN268201300050C), Tougaloo College (HHSN268201300048C), and the University of Mississippi Medical Center (HHSN268201300046C and HHSN268201300047C) contracts from the National Heart, Lung, and Blood Institute and the National Institute for Minority Health and Health Disparities. Research reported in this publication was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (P50HL120163). Dr Hall has also received support from NIH/NIDDK 1K08DK099415-01A1 and NIH/NIGMS P20GM104357.
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