Socioeconomic status, negative affect, and modifiable cancer risk factors in African-American smokers

Darla E. Kendzor, Ludmila M. Cofta-Woerpel, Carlos A. Mazas, Yisheng Li, Jennifer Irvin Vidrine, Lorraine R. Reitzel, Tracy J. Costello, Michael S. Businelle, Jasjit S. Ahluwalia, Paul M. Cinciripini, David W. Wetter

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

The purpose of the present study was to describe the prevalence, patterns, and predictors of cooccurring modifiable cancer risk factors among African-Americans seeking smoking cessation treatment and to evaluate previously hypothesized models of the relationship between socioeconomic status (SES) and health behavior. Overweight/obesity, at-risk alcohol consumption, and insufficient physical activity were measured in 399 African-American smokers. Analyses indicated that 92.8% of participants had at least one cancer risk factor in addition to smoking. Univariate ordinal logistic regression analyses revealed that female gender, unemployment, lower positive affect, and greater negative affect were associated with having a greater number of cancer risk factors. Multivariate analyses yielded similar findings. A structural equation modeling approach indicated that stress/negative affect may function as one pathway linking SES and modifiable cancer risk factors among African-American smokers and that gender has a direct effect on modifiable cancer risk factors. Thus, risk patterns identified within each gender group may guide the development of multiple risk factor interventions for African-American smokers. Stress and negative affect may be an important treatment target within behavioral interventions for African-American smokers of low SES.

Original languageEnglish (US)
Pages (from-to)2546-2554
Number of pages9
JournalCancer Epidemiology Biomarkers and Prevention
Volume17
Issue number10
DOIs
StatePublished - Oct 2008

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

MD Anderson CCSG core facilities

  • Assessment, Intervention, and Measurement
  • Biostatistics Resource Group

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