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A structural equation modeling approach to understanding pathways that connect socioeconomic status and smoking

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  • Sydney A Martinez
  • Laura A Beebe
  • David M Thompson
  • Theodore L Wagener
  • Deirdra R Terrell
  • Janis E Campbell

Abstract

The inverse association between socioeconomic status and smoking is well established, yet the mechanisms that drive this relationship are unclear. We developed and tested four theoretical models of the pathways that link socioeconomic status to current smoking prevalence using a structural equation modeling (SEM) approach. Using data from the 2013 National Health Interview Survey, we selected four indicator variables (poverty ratio, personal earnings, educational attainment, and employment status) that we hypothesize underlie a latent variable, socioeconomic status. We measured direct, indirect, and total effects of socioeconomic status on smoking on four pathways through four latent variables representing social cohesion, financial strain, sleep disturbance, and psychological distress. Results of the model indicated that the probability of being a smoker decreased by 26% of a standard deviation for every one standard deviation increase in socioeconomic status. The direct effects of socioeconomic status on smoking accounted for the majority of the total effects, but the overall model also included significant indirect effects. Of the four mediators, sleep disturbance and psychological distress had the largest total effects on current smoking. We explored the use of structural equation modeling in epidemiology to quantify effects of socioeconomic status on smoking through four social and psychological factors to identify potential targets for interventions. A better understanding of the complex relationship between socioeconomic status and smoking is critical as we continue to reduce the burden of tobacco and eliminate health disparities related to smoking.

Suggested Citation

  • Sydney A Martinez & Laura A Beebe & David M Thompson & Theodore L Wagener & Deirdra R Terrell & Janis E Campbell, 2018. "A structural equation modeling approach to understanding pathways that connect socioeconomic status and smoking," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-17, February.
    • Handle: RePEc:plo:pone00:0192451
    DOI: 10.1371/journal.pone.0192451
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    References listed on IDEAS

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    1. N. Dardenne & B. Pétré & E. Husson & M. Guillaume & A. F. Donneau, 2020. "Assessing Quality of Life in an Obesity Observational Study: a Structural Equation Modeling Approach," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 15(4), pages 1117-1133, September.
    2. Celina I. Valencia & Francine C. Gachupin & Yamilé Molina & Ken Batai, 2022. "Interrogating Patterns of Cancer Disparities by Expanding the Social Determinants of Health Framework to Include Biological Pathways of Social Experiences," IJERPH, MDPI, vol. 19(4), pages 1-11, February.
    3. Adam Hege & Michael K. Lemke & Yorghos Apostolopoulos & Brian Whitaker & Sevil Sönmez, 2019. "Work-Life Conflict among U.S. Long-Haul Truck Drivers: Influences of Work Organization, Perceived Job Stress, Sleep, and Organizational Support," IJERPH, MDPI, vol. 16(6), pages 1-19, March.

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