E-cigarettes have surged in popularity over the last few years, particularly among youth and young adults. These battery-powered devices aerosolize e-liquids, comprised of propylene glycol and vegetable glycerin, typically with nicotine, flavors, and stabilizers/humectants. Although the use of combustible cigarettes is associated with several adverse health effects including multiple pulmonary and cardiovascular diseases, the effects of e-cigarettes on both short- and long-term health have only begun to be investigated. Given the recent increase in the popularity of e-cigarettes, there is an urgent need for studies to address their potential adverse health effects, particularly as many researchers have suggested that e-cigarettes may pose less of a health risk than traditional combustible cigarettes and should be used as nicotine replacements. This report is prepared for clinicians, researchers, and other health care providers to provide the current state of knowledge on how e-cigarette use might affect cardiopulmonary health, along with research gaps to be addressed in future studies.

Rationale: Rural residence is associated with poor outcomes in several chronic diseases. The association between rural residence and chronic obstructive pulmonary disease (COPD) exacerbations remains unclear.Objectives: In this work, we sought to determine the independent association between rural residence and COPD-related outcomes, including COPD exacerbations, airflow obstruction, and symptom burden.Methods: A total of 1,684 SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) participants with forced expiratory volume in 1 second/forced vital capacity < 0.70 had geocoding-defined rural-urban residence status determined (N = 204 rural and N = 1,480 urban). Univariate and multivariate logistic and negative binomial regressions were performed to assess the independent association between rurality and COPD outcomes, including exacerbations, lung function, and symptom burden. The primary exposure of interest was rural residence, determined by geocoding of the home address to the block level at the time of study enrollment. Additional covariates of interest included demographic and clinical characteristics, occupation, and occupational exposures. The primary outcome measures were exacerbations determined over a 1-year course after enrollment by quarterly telephone calls and at an annual research clinic visit. The odds ratio (OR) and incidence rate ratio (IRR) of exacerbations that required treatment with medications, including steroids or antibiotics (total exacerbations), and exacerbations leading to hospitalization (severe exacerbations) were determined after adjusting for relevant covariates.Results: Rural residence was independently associated with a 70% increase in the odds of total exacerbations (OR, 1.70 [95% confidence interval (CI), 1.13-2.56]; P = 0.012) and a 46% higher incidence rate of total exacerbations (IRR 1.46 [95% CI, 1.02-2.10]; P = 0.039). There was no association between rural residence and severe exacerbations. Agricultural occupation was independently associated with increased odds and incidence of total and severe exacerbations. Inclusion of agricultural occupation in the analysis attenuated the association between rural residence and the odds and incidence rate of total exacerbations (OR, 1.52 [95% CI, 1.00-2.32]; P = 0.05 and IRR 1.39 [95% CI, 0.97-1.99]; P = 0.07). There was no difference in symptoms or airflow obstruction between rural and urban participants.Conclusions: Rural residence is independently associated with increased odds and incidence of total, but not severe, COPD exacerbations. These associations are not fully explained by agriculture-related exposures, highlighting the need for future research into potential mechanisms of the increased risk of COPD exacerbations in the rural population.

The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories.

Background

Body composition measures, specifically low weight or reduced muscle mass, are associated with mortality in COPD, but the effect of longitudinal body composition changes is undefined.

Research question

Is the longitudinal loss of fat-free mass (FFM) associated with increased mortality, including in those with initially normal or elevated body composition metrics?

Study design and methods

Participants with complete data for at least one visit in the COPDGene study (n = 9,268) and the ECLIPSE study (n = 1,760) were included and monitored for 12 and 8 years, respectively. Pectoralis muscle area (PMA) was derived from thoracic CT scans and used as a proxy for FFM. A longitudinal mixed submodel for PMA and a Cox proportional hazards submodel for survival were fitted on a joint distribution, using a shared random intercept parameter and Markov chain Monte Carlo parameter estimation.

Results

Both cohorts demonstrated a left-shifted distribution of baseline FFM, not reflected in BMI, and an increase in all-cause mortality risk associated with longitudinal loss of PMA. For each 1-cm² PMA loss, mortality increased 3.1% (95% CI, 2.4%-3.7%; P < .001) in COPDGene, and 2.4% (95% CI, 0.9%-4.0%; P < .001) in ECLIPSE. Increased mortality risk was independent of enrollment values for BMI and disease severity [BODE (body mass, airflow obstruction, dyspnea, and exercise capacity) index quartiles] and was significant even in participants with initially greater than average PMA.

Interpretation

Longitudinal loss of PMA is associated with increased all-cause mortality, regardless of BMI or initial muscle mass. Consideration of novel screening tests and further research into mechanisms contributing to muscle decline may improve risk stratification and identify novel therapeutic targets in ever smokers.