Evidence map›Paper›PMID 34358593›Full record

ArticlePreventive medicine2021

Latent class analysis of use frequencies for multiple tobacco products in US adults.

Ritesh Mistry, Irina Bondarenko, Jihyoun Jeon, Andrew F Brouwer, Delvon T Mattingly, Jana L Hirschtick, Evelyn Jimenez-Mendoza, David T Levy, Stephanie R Land, Michael R Elliott and 3 more

Open access · greenAbstract read
In one paragraph

Article in Preventive medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

13 authors at 3 institutions in 1 country.

Ritesh MistryUniversity of Michigan, Department of Health Behavior and Health Education, Ann Arbor, MI, United States of America. Electronic address: riteshm@umich.edu.
Irina BondarenkoUniversity of Michigan, Department of Biostatistics, Ann Arbor, MI, United States of America.
Jihyoun JeonUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
Andrew F BrouwerUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
Delvon T MattinglyUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
Jana L HirschtickUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
Evelyn Jimenez-MendozaUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
David T LevyGeorgetown University, School of Medicine, Washington, DC, United States of America.
Stephanie R LandNational Institutes of Health, National Cancer Institute, Bethesda, MD, United States of America.
Michael R ElliottUniversity of Michigan, Department of Biostatistics, Ann Arbor, MI, United States of America.
Jeremy M G TaylorUniversity of Michigan, Department of Biostatistics, Ann Arbor, MI, United States of America.
Rafael MezaUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
Nancy L FleischerUniversity of Michigan, Department of Epidemiology, Ann Arbor, MI, United States of America.
University of Michigan–Ann Arbor · USGeorgetown University · USNational Cancer Institute · US

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Eric R. Fearon · 1988 to 2026
$178.2M
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 Jihyoun Jeon · 2018 to 2026
$39.2M
Longitudinal Study of Adolescent Tobacco Use and Tobacco Control Policy in IndiaR01CA201415 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MISTRY, RITESH I, PEDNEKAR, MANGESH SURYAKANT · 2016 to 2021
$2.7M
NCI NIH HHS P30 CA046592NCI NIH HHS R01 CA201415NCI NIH HHS U54 CA229974
6 · The paper itself

Abstract

A persistent challenge is characterizing patterns of tobacco use in terms of product combinations and frequency. Using Wave 4 (2016-17) Population Assessment of Tobacco and Health Study adult data, we conducted latent class analyses (LCA) of past 30-day frequency of use for 9 tobacco products. One-step LCA with joint multinomial logistic regression models compared sociodemographic factors between users (n = 13,716) and non-users (n = 17,457), and between latent classes of users. We accounted for survey design and weights. Our analyses identified 6 classes: in addition to non-users (C0: 75.7%), we found 5 distinct latent classes of users: daily exclusive cigarette users (C1: 15.5%); occasional cigarette and polytobacco users (C2: 3.8%); frequent e-product and occasional cigarette users (C3: 2.2%); daily smokeless tobacco (SLT) and infrequent cigarette users (C4: 2.0%); and occasional cigar users (C5: 0.8%). Compared to C1: C2 and C3 had higher odds of being male (versus female), younger (especially 18-24 versus 55 years), and having higher education; C2 had higher, while C3 and C4 had lower, odds of being a racial/ethnic minority (versus Non-Hispanic White); C4 and C5 had much higher odds of being male (versus female) and heterosexual (versus sexual minority) and having higher income; and C5 had higher odds of college or more education. We identified three classes of daily or frequent users of a primary product (cigarettes, SLT or e-products) and two classes of occasional users (cigarettes, cigars and polytobacco). Sociodemographic differences in class membership may influence tobacco-related health disparities associated with specific patterns of use.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsTobacco, SmokelessAdultEthnicityFemaleHumansLatent Class AnalysisMaleMinority GroupsTobacco UseUnited States

Identifiers

PMID34358593
PMCPMC8595688
OpenAlexW3188318840

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.