Abstract
Background
Secondhand smoke (SHS) exposure has been linked to the development of and morbidity from lung disease. We sought to advance understanding of the impact of SHS on health-related outcomes in individuals with COPD.
Methods
Among COPD participants in SPIROMICS, recent SHS exposure was quantified as, 1) as hours of reported exposure in the past week or 2) reported living with a smoker. We performed adjusted regression for SHS with outcomes, testing for interactions with gender, race, smoking and obesity.
Results
Of 1,580 COPD participants, 20% reported living with a smoker and 27% reported exposure in the last week. Living with a smoker was associated with worse St George’s Respiratory Questionnaire score (SGRQ, β 3.10; 95% CI 0.99, 5.21), COPD Assessment Test score (β 1.43; 95% CI 0.52, 2.35) and increased risk for severe exacerbations (OR 1.51, 95% CI 1.04, 2.17). SHS exposure in the past week was associated with worse SGRQ (β 2.52; 95% CI 0.47, 4.58), nocturnal symptoms (OR 1.58; 95% CI 1.19, 2.10), wheezing (OR 1.34; 95% CI 1.02, 1.77), chronic productive cough (OR 1.77; 95% CI 1.33, 2.35), and difficulty with cough and sputum (Ease of Cough and sputum scale, β 0.84; 95% CI 0.42, 1.25). SHS was associated with increased airways wall thickness on CT but not emphysema. Active smokers, obese individuals and individuals with less severe airflow obstruction also had higher susceptibility to SHS for some outcomes.
Conclusions
Individuals with COPD, including active smokers, have significant SHS exposure, associated with worse outcomes and airways wall thickness. Active smokers and obese individuals may have worse outcomes associated with SHS.
Keywords: COPD epidemiology, secondhand smoke, tobacco and the lung
INTRODUCTION
Since the Surgeon General’s report in 1964 linking tobacco smoke to lung cancer, the recognition of tobacco’s impact on health has grown.[1] There is increasing awareness of the role of secondhand smoke (SHS) exposure in contributing to adverse health outcomes,[1 2] including development of Chronic Obstructive Pulmonary Disease (COPD).[3–6] Moreover, the chemistry of SHS differs from that of primary smoke, creating the possibility of SHS being an additional risk factor even for active smokers.[7] Among those with COPD, a few studies suggest that SHS exposure adversely impacts quality of life, dyspnea and risk for COPD exacerbation, but these studies are limited to former smokers.[8–10] It is not fully known whether SHS is detrimental to health outcomes in COPD, and specifically it has not been shown whether SHS is detrimental in active smokers with COPD. Further highlighting the lack of evidence in this realm, the GOLD consensus report, though noting the possible contribution of SHS to COPD incidence, do not mention SHS as a contributor to COPD morbidity.[11] Additionally, whether there are subgroups of COPD at heightened susceptibility to SHS has not been elucidated, particularly in current smokers with heavy smoke exposure history.
We sought to determine the independent contribution of SHS to clinical characteristics using validated exposure instruments, CT measures, and validated COPD outcomes in a large study of former and current smokers with COPD having a high personal level of primary smoking history. We analyzed the large, well-characterized COPD cohort in SPIROMICS[12] in order to understand if important subgroups of individuals with COPD could be identified who might have heightened susceptibility to the negative impacts of SHS exposure, such as race and gender, given evidence in the literature of heightened susceptibility of African Americans and women[13 14] to the effects of smoking, as well as obesity, given evidence of heightened susceptibility of obese individuals to indoor air pollution.[15] Additionally, of interest was the potential heightened susceptibility of former smokers (compared to current active smokers) to the adverse effects of SHS.
METHODS
SPIROMICS[12] is a multicenter study of current and former smokers (≥ 20 pack-years) with and without COPD and non-smokers without COPD age 40–80 years. The original goals of the study were to determine intermediate outcomes and endpoints in the population with COPD in order to identify subgroups of individuals with COPD who could be targeted for future specific therapeutic strategies and treatments. Current and former smokers with (strata 3–4) and without COPD (stratum 2) were recruited, as were healthy, lifelong nonsmokers (stratum 1). We studied all individuals with COPD (post-bronchodilator FEV1/FVC of <70%) including subjects in strata 3 (FEV1≥50% predicted) and 4 (FEV1<50% predicted) in primary analysis [11]. Secondary analyses incorporated individuals from strata 1–2. Further details on the study population can be found in the online Supplement.
SHS characterization
Participants were asked about smokers in the household. SHS exposure over the past week was quantified in hours using a validated questionnaire for the assessment of exposure in multiple locations including within and outside of the home (including other person’s home, workplace, car or other location while traveling, place of entertainment, or other location).[9 16] Additional questions quantified lifetime SHS exposure in the home in years, as previously utilized by Eisner et al.[4]
CT measures
Participants underwent whole-lung multidetector helical CT at full inspiration and expiration. Measurements of interest included percent emphysema, percent gas-trapping, Pi10 (a measure of airway wall thickness), and airway dimensions including area and diameter of walls and lumens of airways in generations 1–6. Details are provided in the online supplement.
Outcomes (e-Table 1)
Outcomes of interest were respiratory-specific quality of life (St. George’s Respiratory Questionnaire, SGRQ),[17] general quality of life (short-form 12 item questionnaire, SF12),[18] exercise capacity (six minute walk distance in meters, 6MWD),[19] dyspnea (modified Medical Research Council questionnaire, mMRC),[20] and COPD health status (COPD assessment test, CAT).[21] Cough and phlegm over the past day were measured using the total score from the Ease of Cough and Sputum questionnaire.[22] Respiratory Symptoms (cough, phlegm, bronchitis, wheezing and nocturnal symptoms) were measured using the American Thoracic Society Division of Lung Diseases of the National Heart and Lung Institute Questionnaire (ATS/DLD-78-adult).[23] Chronic cough and phlegm status was determined as an affirmative response to the question “Do you usually…?” for the individual symptom and chronic productive cough was determined as an affirmative response to both questions, as described previously.[24] Participants were asked about medication changes or dose adjustments, unscheduled doctor visits, emergency room visits, days hospitalized, and intensive care unit admissions for COPD exacerbations and frequency of these instances over the past year. Severe exacerbations were defined as events requiring emergency room visit or hospitalization. All information was collected at baseline, however additionally we analyzed available data regarding exacerbations noted by participants from the time of study enrollment to most recent follow-up contact.
Statistical methods
Recent SHS exposure was determined by two exposure metrics including i) report of living with a smoker (yes/no), referred to as “living with a smoker”, and ii) SHS exposure reported in any location over the past week, dichotomized as 0–1 hour of exposure (non-exposed) or 2 or more hours of exposure (exposed) as in previous publications[25], referred to as “recent SHS exposure.” Years of lifetime SHS exposure were also studied and modeled as quartiles of exposure, to evaluate possible dose response.[4] Participant characteristics were compared based upon SHS exposure using t-tests and χ2 tests.
We analyzed the relationship between SHS exposures and outcomes using linear and logistic regressions, adjusting for age, gender, race (African American vs. other), education (high school education or less vs. more than high school), current smoking and pack-years smoked. Cross-sectional data were analyzed using linear or logistic regression models (in which coefficients and log odds were the modeled effects) with the exception of analyses of longitudinal exacerbations over follow-up, which were analyzed as count data using adjusted Poisson regression (in which relative risk was the modeled effect) and analysis of mean differences in airway wall and lumen area and diameter as well as wall area percent for generation 1 to 6, for which we used generalized estimating equations (GEE). [26] Further detail on statistical methods can be found in online supplement.
Of interest was possible effect modification of current smoking, such that non-smokers might have relatively higher susceptibility to SHS. In sensitivity analyses, we additionally adjusted these models for the daily number of cigarettes actively smoked to further isolate the effects of SHS over active smoking. We also tested for interactions between SHS exposure and race, gender, severity of airflow obstruction (GOLD 1,2 as less severe vs. GOLD 3,4 as more severe) and obesity (defined dichotomously as BMI>30 kg/m2), as noted above.
All analyses were conducted with Stata 12.[27] 0.05 was the threshold for significance for main effects and 0.10 for interactions.[15 28 29] SPIROMICS was approved by Institutional Review Boards at each center and all participants provided written informed consent (clinicaltrials.gov: NCT01969344).
RESULTS
At the time of analysis, 1,580 participants had spirometric evidence of COPD. Of these, 20% (n=313) reported living with a smoker, 54 % (n=170) of whom were current smokers and 46% (n=143) were former smokers. 428 participants (27%) with COPD reported recent SHS exposure (i.e. 2 or more hours of exposure within the past week), while 1,152 (73%) reported 0–1 hours of exposure. Participants reporting recent SHS exposure had a median of 7 hours of SHS exposure (25th percentile 3, 75th percentile 21, e-Figure 1). Participants reporting recent SHS exposure were younger (mean age 61.9 vs. 66.8 years), more likely to be African American (23% vs. 12%), had less education, and lower household income (Table 1). Although there were minimal differences in pack-years smoked, there were more current smokers in the recent SHS exposure group (64% vs. 20%). Individuals reporting recent SHS had significantly better lung function (FEV1 percent predicted 63.5 vs. 60.2) and less emphysema and gas-trapping on CT (4.8% vs. 8.1%, and 63.5% vs. 66.9%, respectively). SHS exposure data was missing in only 38 of 1,580 participants, who were excluded from analyses. There were strong correlations between metrics of recent SHS exposure (e-Table 2), such that individuals with more reported hours of SHS exposure in the past 7 days were more likely to live with a smoker. Additionally, mean years of SHS exposure reported before and after the age of 18 were significantly higher in the groups reporting more hours of SHS exposure in the past week and living with a smoker. Median follow-up time for exacerbation data was 594 days (25th pctile 292, 75th pctile 995) in the cohort with COPD (stratum 3–4).
Table 1.
Characteristics of GOLD 1–4 participants, by hours of secondhand smoke exposure per week. All values are mean (SD) unless otherwise indicated.
| 0–1 hours SHS exposure in a week (N=1,152) | 2+ hours SHS exposure per week (N=428) | p-value | |
|---|---|---|---|
|
| |||
| Age (years) | 66.8 (7.41) | 61.9 (8.27) | <0.0001 |
|
| |||
| Female, n(%) | 506 (44%) | 165 (39%) | 0.055 |
|
| |||
| African American, n(%) | 136 (12%) | 98 (23%) | <0.0001 |
|
| |||
| Hispanic ethnicity, n(%) | 42 (4%) | 19 (4%) | 0.467 |
|
| |||
| FEV1 % predicted | 60.19 (23.75) | 63.53 (21.66) | 0.013 |
|
| |||
| GOLD categories, n (%) | 0.016 | ||
| 1 | 248 (22%) | 103 (24%) | |
| 2 | 491 (43%) | 208 (49%) | |
| 3 | 288 (25%) | 84 (20%) | |
| 4 | 125 (11%) | 33 (8%) | |
|
| |||
| Oxygen use, n(%) | 268 (23%) | 55 (13%) | <0.0001 |
|
| |||
| Current inhaled steroid use | 555 (49%) | 192 (45%) | 0.237 |
|
| |||
| BMI | 27.49 (5.20) | 27.17 (5.58) | 0.301 |
|
| |||
| Pack-years smoked* | 48.5 (36, 66) | 48 (37, 64.5) | 0.557 |
|
| |||
| Current smoker, n(%) | 229 (20%) | 276 (64%) | <0.0001 |
|
| |||
| > high school education, n(%) | 749 (65%) | 219 (51%) | <0.0001 |
|
| |||
| Income $75K/year or more, n(%) | 215 (24%) | 55 (15%) | 0.001 |
|
| |||
| Obesity, n(%) | 358 (31%) | 138 (32%) | 0.657 |
|
| |||
| % gas trapping | 66.93 (13.73) | 63.52 (14.43) | <0.0001 |
|
| |||
| % emphysema* | 8.07 (2.73, 19.1) | 4.82 (1.82, 12.59) | <0.0001 |
|
| |||
| Pi 10 all airways | 3.71 (0.08) | 3.73 (0.09) | 0.011 |
GOLD- Global initiative for obstructive lung disease
SD- standard deviation
SHS- secondhand smoke
FEV1- Forced expiratory volume in 1 second
SPIROMICS- subpopulations and intermediate outcomes of COPD Study
BMI- body mass index
Values displayed are median (25th percentile, 75th percentile).
Association of living with a smoker and outcomes
After adjustment, living with a smoker was associated with worse outcomes (Table 2) including SGRQ, SF12, CAT and higher ease of cough and sputum scores (i.e. more impaired). Living with a smoker was also associated with severe exacerbations in the past year and chronic productive cough. Additionally, living with a smoker was associated with increased airways wall thickness measured by Pi10, but not with emphysema or gas trapping.
Table 2.
Associations of living with a smoker and COPD outcomes in SPIROMICS
| Linear regression models | Absolute difference | 95% CI | p-value |
|---|---|---|---|
|
| |||
| 6MWD, meters | −7.68 | (−23.50, 8.15) | 0.341 |
|
| |||
| FEV1 % predicted | −2.13 | (−4.87, 0.62) | 0.129 |
|
| |||
| SGRQ score | 3.10 | (0.99, 5.21) | 0.004 |
|
| |||
| SF12 GH score | −1.53 | (−2.90, −0.16) | 0.029 |
|
| |||
| CAT score | 1.43 | (0.52, 2.35) | 0.002 |
|
| |||
| MMRC score | 0.07 | (−0.05, 0.20) | 0.223 |
|
| |||
| Ease of cough and sputum in past day | 0.76 | (0.34, 1.19) | <0.0001 |
|
| |||
| % emphysema | 0.35 | (−0.92, 1.55) | 0.573 |
|
| |||
| % gas-trapping | 0.06 | (−1.65, 1.88) | 0.946 |
|
| |||
| PI 10 (all airways) | 0.16 | (0.03, 0.29) | 0.020 |
|
| |||
| Airway dimensions (5th generation airways) | |||
| Wall area percent | 0.431 | (0.023, 0.840) | 0.039 |
| Wall area | −0.79767 | (−1.64367, 0.04832) | 0.065 |
| Lumen area | −1.08644 | (−2.00936, −0.16352) | 0.021 |
| Lumen diameter | −0.0799 | (−0.1697, 0.0098) | 0.081 |
|
| |||
| Logistic regression models | OR | 95% CI | p-value |
|
| |||
| Nocturnal symptoms | 1.17 | (0.87, 1.57) | 0.295 |
|
| |||
| Any wheezing | 1.16 | (0.86, 1.54) | 0.325 |
|
| |||
| Chronic cough | 1.41 | (1.06, 1.87) | 0.019 |
|
| |||
| Chronic productive cough | 1.71 | (1.28, 2.30) | <0.0001 |
|
| |||
| Exacerbation risk in past year | 1.11 | (0.81, 1.51) | 0.511 |
|
| |||
| Severe exacerbation risk in past year | 1.51 | (1.04, 2.17) | 0.029 |
|
| |||
| Poisson models | RR | 95% CI | p-value |
|
| |||
| Exacerbations experienced over follow-up | 1.04 | (0.84, 1.30) | 0.696 |
|
| |||
| Severe exacerbations experienced over follow-up | 1.11 | (0.82, 1.52) | 0.497 |
Adjusted for age, gender, race, FEV1% predicted (except for analysis of FEV1 % predicted), education level, current smoking status, oxygen use, pack-years smoked. Measures of airway dimensions additionally adjusted for total lung volume achieved at CT. Poisson models of exacerbations and severe exacerbations over follow-up additionally adjusted for follow-up time.
SPIROMICS- subpopulations and intermediate outcomes of COPD Study
COPD- Chronic Obstructive Pulmonary Disease
β-coefficient for modeled estimate
OR- odds ratio
IRR- incidence rate ratio
CI- confidence interval
6MWD- six-minute walk distance
FEV1- forced expiratory volume in 1 second
SGRQ- St George’s Respiratory Questionnaire
SF12 GH- Medical outcomes short form-12 item questionnaire general health score
CAT- COPD assessment test
MMRC- modified medical research council questionnaire
Association of recent SHS exposure (2 or more hours of SHS exposure in the past week) and outcomes
Recent SHS exposure was associated with worse short-term outcomes after adjustment. (Table 3, Figure 1) Recent SHS was associated with worse SGRQ score, nocturnal symptoms, wheezing, worse ease of cough and phlegm, and less exercise capacity. To account for possible influences from occupational exposures,[30] models were additionally adjusted for report of exposure to vapors, dusts, gases or fumes in the longest held job, and results were similar. Measures of recent SHS exposure (hours of SHS exposure in the past 7 days and living with a smoker) were associated with differences in airway dimensions (Tables 2 and 3). In generation 5 airways, wall area and lumen area and diameter were smaller in those with SHS exposure compared to those without, the wall area was thicker relative to lumen size, as indicated by significantly higher wall area percent. Results for other airway generations (1–4, 6) did not have significant results (data not shown).
Table 3.
Associations of 2 or more hours of SHS exposure in past week with COPD outcomes in SPIROMICS
| Linear regression models Hours of SHS smoke in the past 7 d 0–1 Hr (REF) 2+ hours |
Absolute difference | 95% CI | p-value |
|---|---|---|---|
|
| |||
| 6MWD, meters | −15.9 | (−31.33, −0.65) | 0.041 |
|
| |||
| SGRQ score | 2.52 | (0.47, 4.58) | 0.016 |
|
| |||
| SF12 GH score | −1.17 | (−2.50, 0.16) | 0.084 |
|
| |||
| CAT score | 0.82 | (−0.06, 1.71) | 0.068 |
|
| |||
| MMRC score | 0.097 | (−0.018, 0.21) | 0.098 |
|
| |||
| Ease of cough and sputum total score | 0.84 | (0.42, 1.25) | <0.0001 |
|
| |||
| Pi10 (all airways) | 0.18 | (0.05, 0.31) | 0.006 |
|
| |||
| Airway dimensions (5th generation airways) | |||
| Wall area percent | 0.432 | (0.048, 0.816) | 0.027 |
| Wall area | −0.67611 | (−1.47355, 0.12133) | 0.097 |
| Lumen area | −0.89061 | (−1.76076, −0.02046) | 0.045 |
| Lumen diameter | −0.07514 | (−0.1597, 0.00939) | 0.081 |
|
| |||
| Logistic regression models | OR | 95% CI | p-value |
|
| |||
| Nocturnal symptoms | 1.58 | (1.19, 2.10) | 0.001 |
|
| |||
| Any wheezing | 1.34 | (1.02, 1.77) | 0.039 |
Adjusted for age, gender, race, FEV1% predicted (except for analysis of FEV1 % predicted), education level, current smoking status, pack-years smoked, oxygen use. Measures of airway dimensions also adjusted for total lung volume achieved at CT.
REF- reference group
β-coefficient for modeled estimate
OR- odds ratio
CI- confidence interval
SPIROMICS- subpopulations and intermediate outcomes of COPD Study
COPD- Chronic Obstructive Pulmonary Disease
SHS- secondhand smoke
6MWD- six-minute walk distance
FEV1- forced expiratory volume in 1 second
SGRQ- St George’s Respiratory Questionnaire
SF12 GH- Medical outcomes short form-12 item questionnaire general health score
CAT- COPD assessment test
MMRC- modified medical research council questionnaire
Figure 1.
Impact of hours of secondhand smoke exposure in the past week on health outcomes in all participants with COPD. Modeled estimates shown are for 2 or more hours of recent SHS exposure compared to participants with 0–1 hours of exposure.
Years of SHS exposure and outcomes
Lifetime exposure to SHS was highly prevalent, with 82.1% reporting home exposure before age 18, and 77.8% reporting home exposure after age 18. Participants were divided into quartiles based upon years of home SHS exposure during their lifetime, (median (range): 1st quartile 18 years (0–18), 2nd quartile 21 years (19–23), 3rd quartile 33 years (24–40) and 4th quartile 52 years.(41–90) We found minimal contribution of years of cumulative exposure reported with health outcomes in participants with COPD when testing the associations of quartiles 2–4 compared to the 1st quartile using disjoint categories for each quartile (e-Table 3). When we tested the overall contribution of years of SHS exposure using likelihood ratio testing of nested models, only the model of SGRQ reached statistical significance (p=0.047) in its overall contribution to the model.
Subgroups with increased susceptibility to SHS
We found interactions between SHS metrics and smoking status, obesity, and severity of airflow obstruction. Current smoking modified the effect of SHS exposure on several outcomes (Figure 2, Table 4), such that in most cases current smokers appeared to have higher susceptibility to adverse outcomes than former smokers. Living with a smoker was linked to a higher risk of a severe COPD exacerbation in the past year in current smokers compared to former smokers (OR 2.33 vs. 1.12, interaction p=0.055). Recent SHS exposure had a greater negative impact on 6MWD in current smokers compared to former smokers (−27.41 vs −5.96, interaction p=0.071); however only general quality of life was worse in former smokers compared to active smokers (SF12 −2.93 vs 0.68, interaction p=0.006). Models including adjustment for number of daily cigarettes smoked did not appreciably change the effect of SHS among those still smoking (data not shown).
Figure 2.
Interactions between current smoking and secondhand smoke exposure in COPD.
Table 4.
Significant interactions between secondhand smoking exposure and smoking status, obesity, severity of airflow obstruction.
| β | 95% CI | p-value | β | 95% CI | p-value | ||
|---|---|---|---|---|---|---|---|
| Interactions with current smoking (correspond to Figure 2) | |||||||
| Impact of 2+ hours recent SHS exposure on current smokers | Impact of 2+ hours recent SHS exposure on former smokers | P(int) | |||||
| Six Minute walk distance | −24.41 | (−44.81, −4.01) | 0.019 | −5.96 | (−27.90, 15.97) | 0.594 | 0.071 |
| SF12 GH quality of life score | 0.68 | (−1.22, 2.59) | 0.481 | −2.93 | (−4.76, −1.08) | 0.002 | 0.006 |
| Chronic cough, OR | 2.00 | (1.32, 3.02) | <0.0001 | 1.26 | (0.86, 1.85) | 0.238 | 0.083 |
| Impact of living with a smoker on current smokers | Impact of living with a smoker on former smokers | P(int) | |||||
| Severe exacerbation risk past yr, OR | 2.33 | (1.30, 4.18) | 0.004 | 1.12 | (0.67, 1.86) | 0.665 | 0.055 |
| SF12GH quality of life score | −3.42 | (−5.76, −1.09) | 0.004 | −0.06 | (−1.68, 1.57) | 0.945 | 0.085 |
| Interactions with obesity (correspond to Figure 3) | |||||||
| Impact of 2+ hours recent SHS exposure on obese participants | Impact of 2+ hours recent SHS exposure on nonobese participants | P(int) | |||||
| SF12GH quality of life score | −3.42 | (−5.76, −1.09) | 0.004 | −0.06 | (−1.68, 1.57) | 0.945 | 0.085 |
| Impact of living with a smoker on obese participants | Impact of living with a smoker on nonobese participants | ||||||
| Nocturnal symptoms, OR | 1.78 | (1.04, 3.04) | 0.036 | 0.97 | (0.68, 1.38) | 0.863 | 0.030 |
| Chronic cough, OR | 2.10 | (1.23, 3.58) | 0.007 | 1.16 | (0.83, 1.64) | 0.384 | 0.035 |
| Interactions with disease severity (correspond to Figure 4) | |||||||
| Impact of living with a smoker on GOLD 1–2 participants | Impact of living with a smoker on GOLD 3–4 participants | ||||||
| Six Minute walk distance | −20.13 | (−38.34, −1.91) | 0.030 | 10.05 | (−21.79, 41.89) | 0.535 | 0.027 |
| Total CAT score, measure of health status | 2.04 | (0.86, 3.22) | 0.001 | 0.23 | (−1.34, 1.80) | 0.774 | 0.075 |
| Any wheezing, OR | 1.42 | (1.00, 2.02) | 0.050 | 0.84 | (0.53, 1.33) | 0.457 | 0.040 |
Adjusted for age, gender, race, FEV1% predicted, education level, current smoking status, oxygen use, pack-years smoked. Refer to Table 2 legend for all abbreviations. P(int) is defined as p-value for interaction term in the models.
SHS- secondhand smoke
FEV1- forced expiratory volume in 1 second
SF12 GH- Medical outcomes short form-12 item questionnaire general health score
CAT- COPD assessment test
OR- Odds ratio
Those with milder airflow limitation and obese individuals had greater adverse effects associated with SHS exposure for some outcomes (Figures 3–4, Table 4). Living with a smoker was associated with worse outcomes among participants with less severe air flow obstruction (GOLD 1–2) compared to those with more severe obstruction (GOLD 3–4), including greater decrement in exercise capacity, worse CAT score, and more wheezing. Among obese individuals, living with a smoker was linked to a higher risk for nocturnal symptoms and chronic cough compared to non-obese individuals. Additionally, recent SHS exposure was associated with worse quality of life among obese individuals compared to non-obese individuals, though no such association was noted for SGRQ. We found no significant interactions with gender or race.
Figure 3.
Interactions between obesity and secondhand smoke exposure in COPD.
Figure 4.
Interactions between severity of COPD and secondhand smoke exposure in COPD.
Impact of SHS exposure on outcomes in nonsmokers and current and former smokers without COPD
Analyses of recent SHS exposure and living with a smoker were also performed similarly in the cohort of healthy nonsmokers (stratum 1, n=193) and the cohort of former and current smokers without COPD (stratum 2, n=803) and results are displayed in e-Table 4 and e-Table 5. There were fewer statistically significant associations of recent SHS exposure and living with a smoker with outcomes in stratum 1, likely reflecting the small size of the cohort and relative low prevalence of reported SHS exposure (only in 12%), however several significant associations were present within stratum 2, illustrating further the importance of SHS in influencing respiratory symptoms in the general population as well as those with COPD.
DISCUSSION
Secondhand smoke is an unfortunately common exposure among individuals with COPD. We have shown that SHS is a significant contributor to adverse outcomes in COPD, even among active smokers, in a large, well-characterized cohort of patients with a wide range of COPD severity. Recent SHS exposure and living with a smoker are associated with worse respiratory symptoms, quality of life and relative airway wall thickness in COPD. Living with a smoker is also associated with risk of severe exacerbations. Importantly, SHS is linked to worse outcomes even among active smokers. In addition, obese individuals and individuals with less severe COPD may be more susceptible to the adverse effects of SHS.
Twenty percent reported living with a smoker and 36% of participants with COPD reported 2 or more hours of recent SHS exposure, significantly higher than the CDC’s estimates that 5.4% of nonsmoking adults are exposed to SHS at home.[31] Such findings highlight the extraordinary prevalence of SHS exposure in COPD. Recent SHS exposure was associated with higher risk for adverse outcomes in COPD, including lower exercise capacity, worse quality of life, and more respiratory symptoms. Owing to the large size of SPIROMICS, our findings lend substantial weight to the findings of previous studies[8 25] which have shown that higher levels of SHS exposure are associated with worse health status, quality of life, dyspnea, exercise capacity, and healthcare utilization in former smokers with COPD. Further, we were able to test these associations in a well-characterized population with COPD with a high burden of smoke exposure (>20 pack years), and also demonstrated that the associations between SHS and negative health outcomes were also present in former and current smokers without COPD, also lending weight to our findings that SHS is an important risk factor for adverse outcomes.
To our knowledge, our results are the first to show the association of SHS with greater relative airway wall thickness in COPD, a novel finding which correlates with chronic bronchitic symptoms.[32 33]. These findings were shown using two distinct techniques, both Pi10, and also using generation-specific airway lumen and wall data. Though these latter findings were only noted in generation 5 airways, previously, Smith et al. reported significant changes in generation 4–6 airways in the population with COPD when compared to stratum 1–2 individuals. It is likely we were unable to see differences in generations other than 5 because of the smaller sample size studied (COPD participants only) and the limited variability in airway dimensions in the population with COPD when compared to studying the larger cohort. Experimental models of SHS exposure in rats have shown heightened pulmonary inflammation leading ultimately to airway and airspace remodeling.[34] The mechanisms for airways and airspace injury due to SHS have not been clearly established among individuals or in animal models where COPD preexists, and would be the next step in order to better explain the findings of our study. Importantly, our findings are consistent with those of general population studies which have shown a higher risk for chronic bronchitis is nonsmokers exposed to SHS.[1 35]
Finally, we have shown that there are possibly subgroups of individuals with COPD that experience higher susceptibility to the health effects of SHS exposure. We hypothesized that former smokers would be more sensitive to SHS than current smokers. This was not the case. For some outcomes such as quality of life, current smokers showed a greater impact of SHS compared to former smokers. One might intuit that SHS exposure would not greatly impact actively smoking individuals given the small burden that SHS represents when compared to the extensive burden of primary smoking. However, our findings suggest that it is possible that current smokers experience worse outcomes related to SHS possibly because they have a longer duration (though no difference in pack-years smoked, there is a possibility of more hours of active and passive smoke exposure in any given day) or concentration of smoke exposure, as opposed to the quantity of exposure. Additionally, it is important to consider that the toxicity of SHS is qualitatively and quantitatively different from direct active smoke exposure and as such has different effects on outcomes in COPD. Though most of the compounds emitted in secondhand smoke are similar to those in mainstream smoke, the quantitative makeup of SHS and mainstream smoke has been shown to differ. In some cases, the concentration of certain compounds in SHS is greater than that of mainstream smoke, i.e. nicotine, ammonia, formaldehyde, and in other cases, i.e. N′-nitrosonornicotine, (methylnitrosamino)-1-(3-pyridyl)-1-butanone(NNK), the opposite is true. Additionally, the makeup of SHS is often greatly impacted by other environmental exposures.[7 36] Such variation in the quantitative burden of certain compounds could potentially explain our paradoxical findings with regards to current and former smokers with COPD. It is also possible that active smokers have heightened airways inflammation and resulting damage to epithelial cells that alters susceptibility to further inflammation and damage due to SHS. It is possible that SHS is a marker for other behaviors such as medication adherence, exercise or other habits which are less favorable to overall health. The mechanism is an important target for further study, but also highlights the clinical and public health importance of minimizing SHS exposure in all individuals regardless of smoking status.
Obese individuals also showed heightened susceptibility to SHS, with a higher risk for nocturnal symptoms, chronic cough and poor quality of life as a result of SHS compared to lean individuals. These findings are consistent with recently published findings showing obesity as a susceptibility factor for adverse health outcomes related to indoor air pollution in both COPD[15] and asthma.[37] To our knowledge this is the first study showing that obesity may be a susceptibility factor for adverse outcomes associated with SHS. The increased inflammation associated with fat, specifically visceral adipose tissue, may lead to higher amounts of systemic and airway inflammation and lead to alterations in immune defenses in the lung leading to worse outcomes as a result of pollutant exposure.[38] Additionally, obesity may be a reflection of more time spent at home (exposed to home SHS), or also a high fat, low antioxidant diet which has been shown to be pro-inflammatory.[39] Whatever the mechanism, our findings lend weight to the necessity for further studies of obesity as a susceptibility factor for pollutant exposure in lung disease. We also found that individuals with less severe airflow limitation (GOLD stage 1–2 participants) had slightly more susceptibility to adverse outcomes due to SHS than participants with more severe airflow limitation (GOLD stage 3–4 participants). Though this finding is seemingly counterintuitive, it is plausible that individuals with worse COPD severity have such negative outcomes that detecting a further negative effect of SHS would be difficult. It is also possible that individuals with more severe COPD adopt avoidance behaviors that would attenuate the burden of SHS exposure despite having the same amount of exposure as gauged by our metrics of SHS exposure.
Our study is subject to some limitations. Our measures of SHS exposure rely upon self-report, and there is a possibility of measurement error. We utilized a questionnaire that has been previously validated and shown to be associated with health outcomes. Additionally, our findings were consistent across two measures of SHS exposure (living with a smoker and SHS over the past week), further demonstrating their robustness. We were unable to find a signal for health outcomes in COPD being influenced by years of previous exposure to SHS; nor an association between SHS and percentage emphysema or gas-trapping. It is not clear why shorter-term exposures seemed to have more impact than longer-term exposures. It is possible that in the short-term individuals with COPD including active smokers are susceptible to the acute inflammatory effects of SHS, but in the long term, primary smoking outweighs the effect of SHS on progression of COPD. It is also possible that longer term measures are more subject to recall bias. In addition, this study is subject to the limitations of a cross-sectional study design including issues of temporality and causality. For example, perhaps individuals with more symptoms or more severe disease are more likely to live with a smoker or have a higher risk for SHS exposure. We utilized available longitudinal data on exacerbations experienced over follow-up, but found no significant associations at this point. It will be important to reconsider this question once more complete follow-up data is available after the conclusion of the study to better understand the risk for longitudinal exacerbations associated with SHS exposure. Additionally, though we controlled our models for active smoking in multiple ways, we acknowledge the possibility of residual confounding. Finally, as with many observational studies with multiple clinical outcomes of interest, we are limited by the number of statistical comparisons made in that this can increase the possibility of a type I error. Despite this, the consistency of our findings for the comparisons made is notable. Limitations can be addressed as more longitudinal data becomes available in SPIROMICS. Our findings are relatively generalizable to the population with COPD in the US owing to the diversity and broad range of disease in SPIROMICS.
In summary, using the well-characterized COPD cohort in SPIROMICS, we have shown that SHS exposure is common, impacting over a quarter of the population with COPD. Such exposure is associated with higher risk for adverse outcomes, not only in former smokers but also in those currently smoking, and also with a distinct pattern on CT indicative of heightened airways inflammation. Finally, we have shown that SHS has important impacts on obese individuals and surprisingly also current active smokers, findings which challenge us to further understand the mechanisms responsible for adverse outcomes in COPD associated with SHS exposure.
Supplementary Material
What is the key question?
“Do individuals with COPD and exposure to secondhand smoke have worse outcomes compared to individuals with COPD not having exposure to secondhand smoke, and are there subgroups of COPD with higher susceptibility to such adverse outcomes?”
What is the bottom line?
Individuals with COPD who are exposed to secondhand smoke have higher risk for worse outcomes including dyspnea, lower exercise capacity and respiratory symptoms, and also have more airways wall thickness on CT.
Why read on?
To the best of our knowledge, this is the first study that shows that secondhand smoke exposure is associated with adverse outcomes in current as well as former smokers with COPD, and the first to demonstrate distinct subgroups (current smokers, obese individuals, less severe airflow obstruction) that have a heightened susceptibility to adverse outcomes associated with secondhand smoke.
Acknowledgments
The authors thank the SPIROMICS participants and participating physicians, investigators and staff for making this research possible. More information about the study and how to access SPIROMICS data is at www.spiromics.org. We would like to acknowledge the following current and former investigators of the SPIROMICS sites and reading centers: Neil E Alexis, PhD; Wayne H Anderson, PhD; R Graham Barr, MD, DrPH; Eugene R Bleecker, MD; Richard C Boucher, MD; Russell P Bowler, MD, PhD; Elizabeth E Carretta, MPH; Stephanie A Christenson, MD; Alejandro P Comellas, MD; Christopher B Cooper, MD, PhD; David J Couper, PhD; Gerard J Criner, MD; Ronald G Crystal, MD; Jeffrey L Curtis, MD; Claire M Doerschuk, MD; Mark T Dransfield, MD; Christine M Freeman, PhD; MeiLan K Han, MD, MS; Nadia N Hansel, MD, MPH; Annette T Hastie, PhD; Eric A Hoffman, PhD; Robert J Kaner, MD; Richard E Kanner, MD; Eric C Kleerup, MD; Jerry A Krishnan, MD, PhD; Lisa M LaVange, PhD; Stephen C Lazarus, MD; Fernando J Martinez, MD, MS; Deborah A Meyers, PhD; John D Newell Jr, MD; Elizabeth C Oelsner, MD, MPH; Wanda K O’Neal, PhD; Robert Paine, III, MD; Nirupama Putcha, MD, MHS; Stephen I. Rennard, MD; Donald P Tashkin, MD; Mary Beth Scholand, MD; J Michael Wells, MD; Robert A Wise, MD; and Prescott G Woodruff, MD, MPH. The project officers from the Lung Division of the National Heart, Lung, and Blood Institute were Lisa Postow, PhD, and Thomas Croxton, PhD, MD. SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C HHSN268200900019C, HHSN268200900020C), which were supplemented by contributions made through the Foundation for the NIH from AstraZeneca; Bellerophon Pharmaceuticals; Boehringer-Ingelheim Pharmaceuticals, Inc; Chiesi Farmaceutici SpA; Forest Research Institute, Inc; GSK; Grifols Therapeutics, Inc; Ikaria, Inc; Nycomed GmbH; Takeda Pharmaceutical Company; Novartis Pharmaceuticals Corporation; Regeneron Pharmaceuticals, Inc; and Sanofi.
FUNDING
N.P. was supported by the Johns Hopkins University Clinician Scientist Award, the Pearl M. Stetler Research Foundation Award during the conduct of this work and is currently supported by NIH/NHLBI 5K23HL123594-02. SPIROMICS is funded by the National Heart, Lung, and Blood Institute (NHLBI) of the NIH, contract and grant numbers: HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN2682009000019C, and HHSN268200900020C.
Footnotes
COMPETING INTERESTS
DPT has provided consulting services for AstraZeneca, Sunovion, Mylan, Novartis, Glenmark, Theravance, has been a speaker for AstraZeneca, Sunovion, and Boehringer-Ingelheim, and has received research grants from Boehringer-Ingelheim, Sunovion, and GlaxoSmithKlline. The remainder of the authors report no significant interests to disclose.
References
- 1.Samet JM. The Surgeon Generals’ reports and respiratory diseases. From 1964 to 2014 Annals of the American Thoracic Society. 2014;11(2):141–8. doi: 10.1513/AnnalsATS.201311-417PS. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Eisner MD, Wang Y, Haight TJ, et al. Secondhand smoke exposure, pulmonary function, and cardiovascular mortality. Annals of epidemiology. 2007;17(5):364–73. doi: 10.1016/j.annepidem.2006.10.008. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 3.Eisner MD. Secondhand smoke and obstructive lung disease: a causal effect? Am J Respir Crit Care Med. 2009;179(11):973–4. doi: 10.1164/rccm.200903-0320ED. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 4.Eisner MD, Balmes J, Katz PP, et al. Lifetime environmental tobacco smoke exposure and the risk of chronic obstructive pulmonary disease. Environ Health. 2005;4(1):7. doi: 10.1186/1476-069X-4-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Yin P, Jiang CQ, Cheng KK, et al. Passive smoking exposure and risk of COPD among adults in China: the Guangzhou Biobank Cohort Study. Lancet. 2007;370(9589):751–57. doi: 10.1016/S0140-6736(07)61378-6. [DOI] [PubMed] [Google Scholar]
- 6.Sezer H, Akkurt I, Guler N, et al. A case-control study on the effect of exposure to different substances on the development of COPD. Annals of epidemiology. 2006;16(1):59–62. doi: 10.1016/j.annepidem.2004.12.014. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 7.CDC; Health. TOoSa, editor. Toxicology of Secondhand Smoke. Atlanta, GA: Centers for Disease Control and Prevention; 2006. The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. [PubMed] [Google Scholar]
- 8.Eisner MD, Balmes J, Yelin EH, et al. Directly measured secondhand smoke exposure and COPD health outcomes. BMC pulmonary medicine. 2006;6:12. doi: 10.1186/1471-2466-6-12. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Eisner MD, Iribarren C, Yelin EH, et al. The impact of SHS exposure on health status and exacerbations among patients with COPD. International journal of chronic obstructive pulmonary disease. 2009;4:169–76. doi: 10.2147/copd.s4681. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Eisner MD, Jacob P, 3rd, Benowitz NL, et al. Longer term exposure to secondhand smoke and health outcomes in COPD: impact of urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol. Nicotine & tobacco research: official journal of the Society for Research on Nicotine and Tobacco. 2009;11(8):945–53. doi: 10.1093/ntr/ntp091. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Rabe KF, Hurd S, Anzueto A, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2007;176(6):532–55. doi: 10.1164/rccm.200703-456SO. [DOI] [PubMed] [Google Scholar]
- 12.Couper D, LaVange LM, Han M, et al. Design of the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) Thorax. 2014;69(5):491–4. doi: 10.1136/thoraxjnl-2013-203897. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Dransfield MT, Davis JJ, Gerald LB, et al. Racial and gender differences in susceptibility to tobacco smoke among patients with chronic obstructive pulmonary disease. Respir Med. 2006;100(6):1110–6. doi: 10.1016/j.rmed.2005.09.019. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 14.Chatila WM, Wynkoop WA, Vance G, et al. Smoking patterns in African Americans and whites with advanced COPD. Chest. 2004;125(1):15–21. doi: 10.1378/chest.125.1.15. [DOI] [PubMed] [Google Scholar]
- 15.McCormack MC, Belli AJ, Kaji DA, et al. Obesity as a susceptibility factor to indoor particulate matter health effects in COPD. Eur Respir J. 2015 doi: 10.1183/09031936.00081414. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Eisner MD, Katz PP, Yelin EH, et al. Measurement of environmental tobacco smoke exposure among adults with asthma. Environmental health perspectives. 2001;109(8):809–14. doi: 10.1289/ehp.01109809. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Jones PW, Quirk FH, Baveystock CM, et al. A self-complete measure of health status for chronic airflow limitation. The St. George’s Respiratory Questionnaire. The American review of respiratory disease. 1992;145(6):1321–7. doi: 10.1164/ajrccm/145.6.1321. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 18.Ware J, Jr, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Medical care. 1996;34(3):220–33. doi: 10.1097/00005650-199603000-00003. [DOI] [PubMed] [Google Scholar]
- 19.Holland AE, Spruit MA, Troosters T, et al. An official European Respiratory Society/American Thoracic Society technical standard: field walking tests in chronic respiratory disease. The European respiratory journal. 2014;44(6):1428–46. doi: 10.1183/09031936.00150314. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 20.Bestall JC, Paul EA, Garrod R, et al. Usefulness of the Medical Research Council (MRC) dyspnoea scale as a measure of disability in patients with chronic obstructive pulmonary disease. Thorax. 1999;54(7):581–86. doi: 10.1136/thx.54.7.581. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Jones PW, Harding G, Berry P, et al. Development and first validation of the COPD Assessment Test. Eur Respir J. 2009;34(3):648–54. doi: 10.1183/09031936.00102509. [DOI] [PubMed] [Google Scholar]
- 22.Rubin BK, Ramirez O, Ohar JA. Iodinated glycerol has no effect on pulmonary function, symptom score, or sputum properties in patients with stable chronic bronchitis. Chest. 1996;109(2):348–52. doi: 10.1378/chest.109.2.348. [DOI] [PubMed] [Google Scholar]
- 23.Comstock GW, Tockman MS, Helsing KJ, et al. Standardized respiratory questionnaires: comparison of the old with the new. The American review of respiratory disease. 1979;119(1):45–53. doi: 10.1164/arrd.1979.119.1.45. [DOI] [PubMed] [Google Scholar]
- 24.Putcha N, Drummond MB, Connett JE, et al. Chronic productive cough is associated with death in smokers with early COPD. Copd. 2014;11(4):451–8. doi: 10.3109/15412555.2013.837870. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Eisner MD, Iribarren C, Yelin EH, et al. The impact of SHS exposure on health status and exacerbations among patients with COPD. Int J Chron Obstruct Pulmon Dis. 2009;4:169–76. doi: 10.2147/copd.s4681. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Smith BM, Hoffman EA, Rabinowitz D, et al. Comparison of spatially matched airways reveals thinner airway walls in COPD. The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study and the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) 2014;69(11):987–96. doi: 10.1136/thoraxjnl-2014-205160. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Stata Statistical Software: Release 12. [program] College Station, Texas: Stata Corp; 2011. [Google Scholar]
- 28.Matsui EC, Hansel NN, Aloe C, et al. Indoor pollutant exposures modify the effect of airborne endotoxin on asthma in urban children. Am J Respir Crit Care Med. 2013;188(10):1210–5. doi: 10.1164/rccm.201305-0889OC. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Selvin S. Statistical analysis of epidemiologic data. New York: Oxford University Press; 1996. [Google Scholar]
- 30.Paulin LM, Diette GB, Blanc PD, et al. Occupational exposures are associated with worse morbidity in patients with chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine. 2015;191(5):557–65. doi: 10.1164/rccm.201408-1407OC. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Vital signs: nonsmokers’ exposure to secondhand smoke --- United States, 1999–2008. MMWR Morbidity and mortality weekly report. 2010;59(35):1141–6. [PubMed] [Google Scholar]
- 32.Mair G, Maclay J, Miller JJ, et al. Airway dimensions in COPD: Relationships with clinical variables. Respir Med. 2010 doi: 10.1016/j.rmed.2010.04.021. [DOI] [PubMed] [Google Scholar]
- 33.Grydeland TB, Dirksen A, Coxson HO, et al. Quantitative computed tomography measures of emphysema and airway wall thickness are related to respiratory symptoms. Am J Respir Crit Care Med. 2010;181(4):353–9. doi: 10.1164/rccm.200907-1008OC. [published Online First: Epub Date] [DOI] [PubMed] [Google Scholar]
- 34.Kratzer A, Salys J, Nold-Petry C, et al. Role of IL-18 in second-hand smoke-induced emphysema. American journal of respiratory cell and molecular biology. 2013;48(6):725–32. doi: 10.1165/rcmb.2012-0173OC. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Beatty AL, Haight TJ, Redberg RF. Associations between respiratory illnesses and secondhand smoke exposure in flight attendants: A cross-sectional analysis of the Flight Attendant Medical Research Institute Survey. Environmental health: a global access science source. 2011;10(1):81. doi: 10.1186/1476-069x-10-81. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Humans IWGotEoCRt. Tobacco smoke and involuntary smoking. IARC monographs on the evaluation of carcinogenic risks to humans / World Health Organization, International Agency for Research on Cancer. 2004;83:1–1438. [PMC free article] [PubMed] [Google Scholar]
- 37.Lu KD, Breysse PN, Diette GB, et al. Being overweight increases susceptibility to indoor pollutants among urban children with asthma. The Journal of allergy and clinical immunology. 2013;131(4):1017–23. 23.e1–3. doi: 10.1016/j.jaci.2012.12.1570. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Mancuso P. Obesity and lung inflammation. Journal of applied physiology (Bethesda, Md: 1985) 2010;108(3):722–8. doi: 10.1152/japplphysiol.00781.2009. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Chalkiadaki A, Guarente L. High-Fat Diet Triggers Inflammation-Induced Cleavage of SIRT1 in Adipose Tissue To Promote Metabolic Dysfunction. Cell Metabolism. 2012;16(2):180–88. doi: 10.1016/j.cmet.2012.07.003. [published Online First: Epub Date] [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.