Elsevier

Preventive Medicine

Volume 92, November 2016, Pages 110-117
Preventive Medicine

Co-occurring risk factors for current cigarette smoking in a U.S. nationally representative sample

https://doi.org/10.1016/j.ypmed.2016.02.025Get rights and content

Highlights

  • Study of co-occurring risk factors for cigarette smoking in U.S. adults

  • Eight common risk factors each independently predicted current smoking

  • Educational attainment was the single strongest predictor of smoking status.

  • Effects of risk factors for smoking are often independent, cumulative and summative.

Abstract

Introduction

Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample.

Methods

Data were obtained from 114,426 adults (≥ 18 years) in the U.S. National Survey on Drug Use and Health (years 2011–13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness).

Results

Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥ 65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population.

Conclusions

These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined.

Introduction

There have been substantial decreases in U.S. national smoking prevalence since the mid 1960's, but unfortunately these decreases have been unevenly distributed in the general population (Schroeder and Koh, 2014). Substantial reductions have been noted in some subpopulations (e.g., more affluent non-Hispanic Whites), but relatively little change has occurred in others (e.g., those with substance use disorders), and increases in still others (e.g., economically disadvantaged women) (Chilcoat, 2009, Fiore et al., 2008, Schroeder and Koh, 2014). These uneven changes in smoking prevalence underpin considerable current interest in understanding individual differences in risk for cigarette smoking and other forms of tobacco and nicotine use.

Monitoring the extent to which prevalence of smoking or use of other tobacco products differs by risk factors is now recognized to be an important element of tobacco control (Fiore et al., 2008) and regulatory science (Ashley et al., 2014). The overarching purpose of the present study is to begin characterizing the effects of co-occurring risk factors for cigarette smoking. We focus on cigarette smoking because it remains the most prevalent, toxic, and costly form of tobacco and nicotine use (U.S. DHHS, 2014). We know of no exhaustive set of risk factors for cigarette smoking, although gender, age, race/ethnicity, educational attainment, poverty status, substance use disorders, and mental illness are each well documented in the literature and are examined in the present study (Fiore et al., 2008, Higgins et al., 2015, Higgins and Chilcoat, 2009, Schroeder and Koh, 2014). While each of these risk factors inevitably co-occurs with some arrangement of the others (i.e., gender always co-occurs with chronological age, educational attainment, and race/ethnicity), there has been relatively little research reported explicitly characterizing the combined effects of co-occurring risk factors for cigarette smoking. Knowing whether effects of co-occurring risk factors are independent of each other (i.e., summative), or whether some may offset risks associated with others (i.e., less-than-summative/antagonistic), or perhaps increase risk in a multiplicative (i.e., synergistic) manner is important to the development of evidence-based tobacco policy and is the overarching purpose of the present study. Also of interest is empirically examining the relative strength of these common risk factors and how cumulative risk varies across particular risk factor profiles.

In a prior literature review on gender differences in prevalence of cigarette smoking and use of other nicotine and delivery products in the U.S., gender differences in risk were noted to generally act independently of the influence of other co-occurring risk factors, that is, gender and the other risk factors appeared to act in a cumulative and summative manner (Higgins et al., 2015). However, these were qualitative observations regarding patterns in previously published articles, none of which was explicitly designed to characterize the combined effects of co-occurring risk factors.

The present study was designed to build upon the initial findings described above by examining (a) a broader range of co-occurring risk factors than those involving gender, (b) statistically examining the independent and combined effects of common risk factors for smoking, and (c) identifying particularly low- and high-risk profiles. We know of no prior studies specifically on this topic regarding risk for current cigarette smoking, although studies characterizing effects of co-occurring risk factors are common in other areas of health research (e.g., Park et al., 2009, Schnohr et al., 2002). The present study was conducted using what at the time of study initiation was the most recent three years (2011–2013) of the National Survey on Drug Use and Health (NSDUH) (Substance Abuse and Mental Health Services Administration (, Substance Abuse and Mental Health Services Administration (, Substance Abuse and Mental Health Services Administration (), a cross-sectional survey that has been used effectively in prior studies examining prevalence of cigarette smoking across various socio-demographic and psychiatric risk factors (e.g., Gfroerer et al., 2013, Redner et al., 2014a, Redner et al., 2014b, White et al., 2015).

Section snippets

Data source

The NSDUH is a nationally representative survey of the U.S. non-institutionalized population aged ≥ 12 years that measures prevalence and correlates of drug use (Center for Behavioral Health Statistics and Quality, 2014). Detailed descriptions of survey procedures have been provided for each of the survey years (Substance Abuse and Mental Health Services Administration (, Substance Abuse and Mental Health Services Administration (, Substance Abuse and Mental Health Services Administration ().

Logistic regression analyses

Overall prevalence of current smokers in this adult sample was 21.6% (Table 1, left-most column). Each of the eight risk factors significantly increased the odds of being a current smoker in univariate logistic regression (Table 1, center-most columns). Each of those risk factors also remained significant in a multivariate logistic regression model adjusting for the influence of the others, demonstrating significant independent associations with smoking status (Table 1, right-most columns). The

Discussion

The present study was conducted to follow up on observations reported as part of a literature review on gender differences where risk for cigarette smoking appeared to change in a cumulative and summative manner when gender was considered in combination with other co-occurring risk factors (Higgins et al., 2015). The present results confirm those earlier observations and extend them to additional risk-factor combinations beyond gender. Results from the multiple logistic regression analyses

Funding

This project was supported in part by Tobacco Centers of Regulatory Science (TCORS) award P50DA036114 from the National Institute on Drug Abuse (NIDA) and Food and Drug Administration (FDA), TCORS award P50CA180908 from the National Cancer Institute (NCI) and FDA, Center for Evaluation and Coordination of Training and Research award U54CA189222 from NCI and FDA, Institutional Training Grant award T32DA07242 from NIDA, and Centers of Biomedical Research Excellence P20GM103644 award from the

Competing interests

The authors have no conflicts of interest to report.

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