Tobacco Consumption and High‐Sensitivity Cardiac Troponin I in the General Population: The HUNT Study

Background Cardiac troponins represent a sensitive index of subclinical myocardial injury and are associated with increased risk of cardiovascular events in the general population. Despite positive associations with cardiovascular risk of both cardiac troponins and cigarette smoking, concentrations of cardiac troponin I measured by high‐sensitivity assays (hs‐cTnI) are paradoxically lower in current smokers than in never‐smokers. The impact of smoking intensity and time from smoking cessation on hs‐cTnI remains unknown. Methods and Results hs‐cTnI concentrations were measured in 32028 subjects free from cardiovascular disease enrolled in the prospective, population‐based HUNT (Trøndelag Health Study). Tobacco habits were self‐reported and classified as never (n=14 559), former (n=14 248), and current (n=3221) smokers. Current smokers exhibited significantly lower concentrations of hs‐cTnI than never‐smokers ( P <0.001). In adjusted models, both current smoking (−17.3%; 95% CI, −20.6 to −13.9%) and former smoking (−6.6%; 95% CI, −8.7 to −4.5%) were associated with significantly lower hs‐cTnI concentrations. Among former smokers, higher smoking burden (>10 pack‐years) were associated with lower concentrations of hs‐cTnI. Time since smoking cessation was associated with increasing concentrations of hs‐cTnI in a dose‐dependent manner ( P for trend<0.001), and subjects who quit smoking >30 years ago had concentrations of hs‐cTnI comparable with those of never‐smokers. Conclusions In the general population, both current and former cigarette smoking is associated with lower concentrations of hs‐cTnI. In former smokers, there was a dose‐response relationship between pack‐years of smoking, and hs‐cTnI. Time since smoking cessation was associated with increasing concentrations of hs‐cTnI, indicating a continuum of hs‐cTnI from current smoker to never‐smokers.

Clinical Outcomes of Patients with Combined Idiopathic Pulmonary Fibrosis and Emphysema in the IPF-PRO Registry

Purpose To assess the impact of concomitant emphysema on outcomes in patients with idiopathic pulmonary fibrosis (IPF). Methods The IPF-PRO Registry is a US registry of patients with IPF. The presence of combined pulmonary fibrosis and emphysema (CPFE) at enrollment was determined by investigators’ review of an HRCT scan. Associations between emphysema and clinical outcomes were analyzed using Cox proportional hazards models. Results Of 934 patients, 119 (12.7%) had CPFE. Compared with patients with IPF alone, patients with CPFE were older (median 72 vs 70 years); higher proportions were current/former smokers (88.2% vs 63.7%), used oxygen with activity (49.6% vs 31.9%) or at rest (30.8% vs 18.4%), had congestive heart failure (13.6% vs 4.8%) and had prior respiratory hospitalization (25.0% vs 16.7%); they had higher FVC (median 71.8 vs 69.4% predicted) and lower DLco (median 35.3 vs 43.6% predicted). In patients with CPFE and IPF alone, respectively, at 1 year, rates of death or lung transplant were 17.5% (95% CI: 11.7, 25.8) and 11.2% (9.2, 13.6) and rates of hospitalization were 21.6% (14.6, 29.6) and 20.6% (17.9, 23.5). There were no significant associations between emphysema and any outcome after adjustment for baseline variables. No baseline variable predicted outcomes better in IPF alone than in CPFE. Conclusion Approximately 13% of patients in the IPF-PRO Registry had CPFE. Physiologic characteristics and comorbidities of patients with CPFE differed from those of patients with IPF alone, but the presence of emphysema did not drive outcomes after adjustment for baseline covariates. Trial registration ClinicalTrials.gov, NCT01915511; registered August 5, 2013.

Smoking history and adherence to cancer-related recommendations in a primary care setting

Public health prevention efforts have led to overall reductions in mortality from screening-preventable cancers. We explored cancer screening behaviors of smokers, former smokers, and nonsmokers among patients of large primary care practices to discover the relationship between smoking status and previous adherence to the United States Preventive Services Task Force breast, cervical, and colorectal cancer screening recommendations. Our descriptive study of electronic medical record data included 6,029 established primary care patients. Multi-predictor log-binomial regression models yielded prevalence ratios (PRs) and 95% confidence intervals (CIs) to determine associations between smoking status and the likelihood of nonadherence. All models were adjusted for race/ethnicity, age, insurance, primary care specialty, number of comorbidities, and sex. Smoking history was obtained from all participants in January 2020. Current smokers accounted for 4.8%, while 22.7% were former smokers, and 72.5% were never smokers. Current smokers (compared to never smokers) were 63% more likely to be mammogram nonadherent (PR: 1.63, 95% CI: 1.31 to 2.02), 26% more likely to be Pap smear nonadherent (PR: 1.26, 95% CI: 1.04 to 1.53), and 39% more likely to be colonoscopy nonadherent (PR: 1.39, 95% CI: 1.16 to 1.66). Current smokers and former Powered by Editorial Manager and ProduXion Manager from Aries Systems Corporation smokers had on average 2.9 comorbidities while never smokers had on average 2.1 comorbidities. Our findings showed that current smokers experienced significantly lower rates of cancer screening compared to never smokers. Further research is needed to investigate and identify best practices for increasing cancer screening uptake in this population.

Association Between Initiation, Intensity, and Cessation of Smoking and Mortality Risk in Patients With Cardiovascular Disease: A Cohort Study

Objectives: To examine the effect of smoking status, smoking intensity, duration of smoking cessation and age of smoking initiation on the risk of all-cause and cause-specific mortality among cardiovascular disease (CVD) patients.Design: A population-based prospective cohort study.Setting: The National Health Interview Survey (NHIS) in the U.S. that were linked to the National Death Index (NDI).Participants: 66,190 CVD participants ≥ 18 years of age who were interviewed between 1997 and 2013 in the NHIS linked to the NDI through December 31, 2015.Outcome Measures: The primary outcome was all-cause mortality and the secondary outcome was cause-specific mortality including CVD mortality and cancer mortality.Results: During the mean follow-up of 8.1 years, we documented 22,518 deaths (including 6,473 CVD deaths and 4,050 cancer deaths). In the overall CVD population, former and current smokers had higher risk of all-cause (Former smokers: hazard ratios (HRs), 1.26; 95% confidence interval (CI), 1.21–1.31, P &lt; 0.001; Current smokers: HRs, 1.96; 95%CI, 1.86–2.07, P &lt; 0.001), CVD (Former smokers: HRs, 1.12; 95%CI, 1.05–1.21, P = 0.001; Current smokers: HRs, 1.80; 95%CI, 1.64–1.97, P &lt; 0.001) and cancer mortality (Former smokers: HRs, 1.49; 95%CI, 1.35–1.64, P &lt; 0.001; Current smokers: HRs, 2.78; 95%CI, 2.49–3.09, P &lt; 0.001) than never smokers. Furthermore, similar results were observed when the study subjects were stratified according to the type of CVD. Among current smokers, the risk for cancer mortality increased as the daily number of cigarettes increased, regardless of the specific type of CVD. However, the association of the risk for all-cause and CVD mortality with smoking intensity did not present a dose-response relationship. In participants with angina pectoris or stroke, smoking intensity was inversely associated with deaths from CVD. In addition, the risk for all-cause, CVD and cancer mortality declined as years of smoking cessation increased. Finally, the relative risk of all-cause mortality was not significantly different in individuals with a younger age of smoking initiation.Conclusions: CVD patients who are smokers have an increased risk of all-cause, CVD and cancer mortality, and the risk decreases significantly after quitting smoking. These data further provide strong evidence that supports the recommendation to quit smoking for the prevention of premature deaths among individuals with CVD.

The effects of smoking, regular drinking, and unhealthy weight on health care utilization in China

Background Preventive risk factors such as smoking, drinking, and unhealthy weight have contributed to the accelerated rise in noncommunicable chronic diseases, which are dominant drivers of health care utilization and spending in China. However, few studies have been conducted using a large longitudinal dataset to explore the impact of such preventive risk factors on health care utilization. Therefore, this study aimed to ascertain the effects of smoking, regular drinking, and unhealthy weight on health care utilization in China. Methods This research was a longitudinal study using data from five waves of the China Family Panel Studies (CFPS) conducted between 2010 and 2018, and the final sample consisted of 63,260 observations (12,652 participants) across all five waves of data collection. Health care utilization was measured from two perspectives: outpatient utilization and inpatient utilization. Smoking status was categorized as never smoker, former smoker, or current smoker. Unhealthy weight was classified based on the participants’ body mass index. A fixed effects logistic regression model was used for the analysis. Results The results of fixed effects logistic regression showed that current and former smokers were approximately 1.9 times and 2.0 times more likely to use outpatient care than those who never smoked, respectively (odds ratio (OR) = 1.88, p < 0.05; OR = 2.03, p < 0.05). Obese people were approximately 1.3 times more likely to use outpatient care than healthy weight people (OR = 1.26, p < 0.05). Moreover, the results show that compared to those who never smoked, for current and former smokers, the odds of being hospitalized increased by 42.2 and 198.2%, respectively (OR = 1.42; p < 0.1, OR = 2.98; p < 0.05). Compared to healthy weight people, overweight and obese people were also more likely to be hospitalized (OR = 1.11; p < 0.1, OR = 1.18; p < 0.1, respectively). Conclusion Among Chinese adults, current and former smokers were more likely to use outpatient and inpatient care than those who had never smoked. Moreover, compared to healthy weight people, obese people were more likely to use outpatient and inpatient care, and overweight people were more likely to use inpatient care. These results may have important implications that support the government in making health care resource allocation decisions.

Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk

Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

Epigenetic modelling of former, current and never smokers

Background DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices. Results We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers. Conclusions Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary.