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
  • , Jeremy M.G. Taylor
  • , Rafael Meza
  • , Nancy L. Fleischer

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.

Original languageEnglish
Article number106762
JournalPreventive Medicine
Volume153
DOIs
StatePublished - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Inc.

Funding

This work was supported by grants U54CA229974 ( National Institutes of Health and Food and Drug Administration (FDA)), P30CA046592 ( National Cancer Institute ) and R01CA201415 ( National Cancer Institute ). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, National Cancer Institute or the Food and Drug Administration . This work was supported by grants U54CA229974 (National Institutes of Health and Food and Drug Administration (FDA)), P30CA046592 (National Cancer Institute) and R01CA201415 (National Cancer Institute). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, National Cancer Institute or the Food and Drug Administration.

FundersFunder number
National Cancer Institute or the Food and Drug Administration
National Institutes of Health and Food and Drug Administration
National Institutes of Health (NIH)
U.S. Food and Drug Administration
National Childhood Cancer Registry – National Cancer InstituteU54CA229974, P30CA046592, R01CA201415

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    ASJC Scopus subject areas

    • Epidemiology
    • Public Health, Environmental and Occupational Health

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