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.
Highlights
An inverse association between socioeconomic status and smoking exists, the overall mechanisms remain unclear [1,2,3,4,5]
We developed five latent variables and tested the measurement model using confirmatory factor analysis (CFA) that specified the relationships between the observed indicators and their underlying latent constructs
We examined the interrelationships among the latent constructs and found that the socioeconomic status construct was inversely correlated with financial strain, sleep disturbance, and psychological distress and positively correlated with social cohesion
Summary
An inverse association between socioeconomic status and smoking exists, the overall mechanisms remain unclear [1,2,3,4,5]. [14,15,16] most original studies use theoretical and statistical models that examine these risk factors individually rather than simultaneously, which allows consideration of both independent and dependent effects of multiple factors.[17,18] Few studies have used path analysis or structural equation modeling (SEM) to test these relationships concurrently to disentangle and separately estimate the direct and indirect pathways to smoking.[6,7,19,20] These studies have been limited to samples of low socioeconomic status smokers to better understand the pathways to smoking cessation rather than smoking prevalence, which would be a better measure of differences in smoking uptake and cessation combined. As a statistical tool to evaluate complex relationships, SEM has the potential to significantly contribute to epidemiological studies that examine multiple factors that are often inter-related and not disentangled through traditional epidemiological methods.[18,21]
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