Evidence map›Paper›PMID 40279129›Full record

ArticleJAMA network open2025

State and Sociodemographic Trends in US Cigarette Smoking With Future Projections.

Matthew D Stone, John P Pierce, Brian Dang, Sara B McMenamin, Candice D Donaldson, Xueying Zhang, David R Strong, Yuyan Shi, Karen Messer, Dennis R Trinidad

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Matthew D StoneHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
John P PierceHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
Brian DangHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
Sara B McMenaminHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
Candice D DonaldsonTobacco Control Branch, California Department of Public Health, California Health and Human Services Agency, Sacramento.
Xueying ZhangTobacco Control Branch, California Department of Public Health, California Health and Human Services Agency, Sacramento.
David R StrongHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
Yuyan ShiHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
Karen MesserHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.
Dennis R TrinidadHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: There are still significant population-level health consequences of cigarette smoking in US states. Objective: To estimate whether differential sociodemographic trends in smoking prevalence since 1992 will close the prevalence gap between states by 2035. Design, Setting, and Participants: This cross-sectional study included data from 18 repeated, state-representative US Tobacco Use Supplement to the Current Population Surveys (TUS-CPS) from 1992 to 2022. Data were analyzed between June and October 2024. Main Outcomes and Measures: Nonlinear time series trends in smoking prevalence in US states from 1992 to 2022 were projected through 2035 and compared with recommended targets. States were grouped into tertiles using their 1990s prevalence. Differential change in sociodemographic groups were compared across tertiles. Results: The 18 surveys comprised 1 770 442 respondents (997 569 female [56.3%]; 146 865 Hispanic [8.3%], 160 751 non-Hispanic Black [9.1%], and 1 373 454 non-Hispanic White [78.0%]). From 1992 to 2022, all state tertiles experienced significant declines in smoking prevalence, each decreasing by approximately 13 percentage points from 2001 to 2022. In 2022, prevalence was 7.4% (95% CI, 6.9% to 7.9%) in tertile 1 (lowest 1990s prevalence), 10.0% (95% CI, 9.2% to 10.8%) in tertile 2, and 12.7% (95% CI, 11.9% to 13.4%) in tertile 3. Projections to 2035 indicated the prevalence gap closing between tertiles, to 3.8% (95% CI, 2.6% to 5.1%) in tertile 1, to 5.1% (95% CI, 3.2% to 7.2%) in tertile 2, and to 6.6% (95% CI, 4.8% to 9.1%) in tertile 3. The only sociodemographic trend that reduced the gap occurred among individuals aged 18 to 24 year (tertile 3 change, -21.3% [95% CI, -24.5% to -18.2%] vs tertile 1 change, -16.4% [95% CI, -18.5% to -14.4%]; P = .005). Yet age was not a significant factor in projected changes, as the decline in the group aged 50 years and older was greater in tertile 1 than 3 (-4.7% [95% CI, -5.7% to -3.8%] vs -2.3% [95% CI, -3.5% to -1.2%]; P < .001). By 2035, only 4 states (California, Utah, Hawaii, and Colorado) were projected to be significantly under the recommended target of 5% prevalence. Conclusions and Relevance: The findings of these repeated cross-sectional surveys suggest that the difference in cigarette smoking prevalence between historically high vs low prevalence states will shrink by 2035, primarily from much faster declines among young adults in the traditionally highest prevalence states. Slower prevalence declines among older adults are likely to slow the decline in health consequences in these states.

Indexed as

Cigarette SmokingAdolescentAdultAgedCross-Sectional StudiesFemaleForecastingHumansMaleMiddle AgedPrevalenceSociodemographic FactorsSocioeconomic FactorsUnited StatesYoung Adult

Identifiers

PMID40279129
PMCPMC12032569

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.