Evidence map›Paper›PMID 36775754›Full record

ArticleAmerican journal of preventive medicine2023

Mortality Relative Risks by Smoking, Race/Ethnicity, and Education.

Jihyoun Jeon, Maki Inoue-Choi, Yoonseo Mok, Timothy S McNeel, Jamie Tam, Neal D Freedman, Rafael Meza

Abstract read
In one paragraph

Article in American journal of preventive medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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

7 authors.

Jihyoun JeonDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan. Electronic address: jihjeon@umich.edu.
Maki Inoue-ChoiMetabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland.
Yoonseo MokDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada.
Timothy S McNeelInformation Management Services, Inc., Calverton, Maryland.
Jamie TamDepartment of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut.
Neal D FreedmanMetabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland.
Rafael MezaDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada.

Funding

Research Project 3: Modeling the Impact of Tobacco Control Policies on Polytobacco Use and Associated Health DisparitiesU54CA229974 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI David Mendez Emilien · 2018 to 2026
$39.2M
Comparative Modeling of Lung Cancer Prevention, Early Detection and Treatment InterventionsU01CA253858 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DE KONING, HARRY J, HOLFORD, THEODORE R · 2020 to 2025
$8.4M
Comparative Modeling of Lung Cancer Prevention and Control PoliciesU01CA199284 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DE KONING, HARRY J, HOLFORD, THEODORE R · 2015 to 2019
$8.4M
NCI NIH HHS U01 CA199284NCI NIH HHS U01 CA253858NCI NIH HHS U54 CA229974
6 · The paper itself

Abstract

introductionThe impact of cigarette smoking on mortality is well studied, with estimates of the relative mortality risks for the overall population widely available. However, age-specific mortality estimates for different sociodemographic groups in the U.S. are lacking.

methodsUsing the 1987-2018 National Health Interview Survey Linked Mortality Files through 2019, all-cause mortality relative risks (RRs) were estimated for current smokers or recent quitters and long-term quitters compared with those for never smokers. Stratified Cox proportional hazards regression models were used to estimate RRs by age, gender, race/ethnicity, and educational attainment. RRs were also assessed for current smokers or recent quitters by smoking intensity and for long-term quitters by years since quitting. The analysis was conducted in 2021-2022.

resultsAll-cause mortality RRs among current smokers or recent quitters were generally highest for non-Hispanic White individuals than for never smokers, followed by non-Hispanic Black individuals, and were lowest for Hispanic individuals. RRs varied greatly by educational attainment; generally, higher-education groups had greater RRs associated with smoking than lower-education groups. Conversely, the RRs by years since quitting among long-term quitters did not show clear differences across race/ethnicity and education groups. Age-specific RR patterns varied greatly across racial/ethnic and education groups as well as by gender.

conclusionsAge-specific all-cause mortality rates associated with smoking vary considerably by sociodemographic factors. Among high-education groups, lower underlying mortality rates for never smokers result in correspondingly high RR estimates for current smoking. These estimates can be incorporated in modeling analyses to assess tobacco control interventions' impact on smoking-related health disparities between different sociodemographic groups.

Indexed as

EthnicitySmokingEducational StatusHumansProportional Hazards ModelsRisk FactorsUnited States

Identifiers

PMID36775754
PMCPMC11186465

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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.