Longitudinal Associations of Cigarette Smoking, Smoking Intensity, and Smoking TrajectoriesWith Emergency Room Utilization Among U.S. Adults

Background: Tobacco smoking is a leading cause of morbidity and mortality in the United States, yet its longitudinal association with emergency room (ER) utilization remains understudied. We examined whether cigarette smoking, smoking intensity, and smoking trajectories were associated with subsequent ER use. Methods: We analyzed adult respondents from Waves 1-6 of the Population Assessment of Tobacco and Health Study. Wave 1-3 smoking status, intensity, and cigarettes/day were examined in relation to next-wave ER outcomes. Logistic generalized estimating equation models were used for any ER visit and frequent ER use (>=2 visits), and negative binomial models were used for ER visit count. Trajectory analyses examined Wave 1-5 smoking patterns and Wave 6 ER outcomes, with Wave 1-4 to Wave 5 as sensitivity analysis. Marginal structural models (with IPW) and propensity score matching were used to strengthen causal interpretation. Models adjusted for demographics, insurance, self-rated health, and baseline ER use. Survey weights with balanced repeated replication and Fay's adjustment were used. Results: In adjusted GEE models, current smoking was associated with higher subsequent ER utilization, including any ER visit (OR 1.128, 95% CI [1.068-1.191]), frequent ER use (OR 1.275, 95% CI [1.185-1.372]), and ER visit count (RR 1.264, 95% CI [1.160-1.377]; all p<0.001). Smoking intensity showed a dose-response pattern: smoking <20 cigarettes/day was associated with any ER visit (OR 1.130, 95% CI [1.060-1.204]), frequent ER use (OR 1.231, 95% CI [1.124-1.347]), and ER visit count (RR 1.262, 95% CI [1.110-1.435]), while smoking >=20 cigarettes/day showed stronger associations with any ER visit (OR 1.231, 95% CI [1.127-1.345]), frequent ER use (OR 1.447, 95% CI [1.293-1.618]), and ER visit count (RR 1.368, 95% CI [1.245-1.504]; all p<0.001). Each additional cigarette/day was also associated with higher ER utilization (OR/RR range, 1.007-1.011; all p<0.001). Findings were consistent in marginal structural models and propensity score matched analyses. In trajectory analyses, new/intermittent and persistent smokers had significantly higher ER utilization, while former/intermittent smokers and sustained quitters did not differ from non-smokers, suggesting that this harmful association was eliminated by smoking cessation. Conclusions: Smoking, heavier intensity, and persistent or emerging smoking patterns were associated with higher subsequent ER utilization, while smoking cessation reduces ER risk to the same level as non-smokers. This supports smoking prevention and cessation as strategies to reduce acute healthcare burden.

Authors

Institutions

Publication Details

Journal
medRxiv
Published
2026-11-02
DOI
https://doi.org/10.64898/2026.10.31.26366988
Primary Topic
Smoking Behavior and Cessation
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Longitudinal Associations of Cigarette Smoking, Smoking Intensity, and Smoking TrajectoriesWith Emergency Room Utilization Among U.S. Adults

Curtis M. Tatsuoka, Wanru Guo, Xinyu Yan
2 links
medRxiv
Smoking Behavior and Cessation
preprint

Longitudinal Associations of Cigarette Smoking, Smoking Intensity, and Smoking TrajectoriesWith Emergency Room Utilization Among U.S. Adults

Curtis M. Tatsuoka, Wanru Guo, Xinyu Yan
preprint en

Abstract

Background: Tobacco smoking is a leading cause of morbidity and mortality in the United States, yet its longitudinal association with emergency room (ER) utilization remains understudied. We examined whether cigarette smoking, smoking intensity, and smoking trajectories were associated with subsequent ER use. Methods: We analyzed adult respondents from Waves 1-6 of the Population Assessment of Tobacco and Health Study. Wave 1-3 smoking status, intensity, and cigarettes/day were examined in relation to next-wave ER outcomes. Logistic generalized estimating equation models were used for any ER visit and frequent ER use (>=2 visits), and negative binomial models were used for ER visit count. Trajectory analyses examined Wave 1-5 smoking patterns and Wave 6 ER outcomes, with Wave 1-4 to Wave 5 as sensitivity analysis. Marginal structural models (with IPW) and propensity score matching were used to strengthen causal interpretation. Models adjusted for demographics, insurance, self-rated health, and baseline ER use. Survey weights with balanced repeated replication and Fay's adjustment were used. Results: In adjusted GEE models, current smoking was associated with higher subsequent ER utilization, including any ER visit (OR 1.128, 95% CI [1.068-1.191]), frequent ER use (OR 1.275, 95% CI [1.185-1.372]), and ER visit count (RR 1.264, 95% CI [1.160-1.377]; all p<0.001). Smoking intensity showed a dose-response pattern: smoking <20 cigarettes/day was associated with any ER visit (OR 1.130, 95% CI [1.060-1.204]), frequent ER use (OR 1.231, 95% CI [1.124-1.347]), and ER visit count (RR 1.262, 95% CI [1.110-1.435]), while smoking >=20 cigarettes/day showed stronger associations with any ER visit (OR 1.231, 95% CI [1.127-1.345]), frequent ER use (OR 1.447, 95% CI [1.293-1.618]), and ER visit count (RR 1.368, 95% CI [1.245-1.504]; all p<0.001). Each additional cigarette/day was also associated with higher ER utilization (OR/RR range, 1.007-1.011; all p<0.001). Findings were consistent in marginal structural models and propensity score matched analyses. In trajectory analyses, new/intermittent and persistent smokers had significantly higher ER utilization, while former/intermittent smokers and sustained quitters did not differ from non-smokers, suggesting that this harmful association was eliminated by smoking cessation. Conclusions: Smoking, heavier intensity, and persistent or emerging smoking patterns were associated with higher subsequent ER utilization, while smoking cessation reduces ER risk to the same level as non-smokers. This supports smoking prevention and cessation as strategies to reduce acute healthcare burden.

medRxiv
University of Maryland, Baltimore (US), University of Florida (US)
Good health and well-being
Smoking Behavior and Cessation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon