Racial/Ethnic Disparities in Consistent Reporting of Smoking-Related Behaviors.

Abstract

This study assessed the effect of race/ethnicity on the prevalence of inconsistent reports regarding ever smoking, time since smoking cessation, and age of initiating regular smoking. We used the Tobacco Use Supplement to the Current Population Survey data, which came from a test-retest reliability study, and considered three racial/ethnic subpopulations, Hispanics, Non-Hispanic (NH) Blacks and NH Whites. Initial exploration of highly disagreeing reports of time since smoking cessation and age of onset of regular smoking initiation indicated that the majority of these reports corresponded to NH Whites. However, the proportion of the extremely discrepant reports was very small (less than 0.8%), and these reports were not included in the main analyses. Univariate analyses revealed that for each smoking measure, NH Whites tended to report most consistently when compared to Hispanics and NH Blacks. However, the only statistically significant result was that Hispanics were more likely to report their regular smoking initiation age inconsistently than were NH Whites. Analyses that adjusted for other factors confirmed this finding, i.e., Hispanics were 1.8 times more likely to provide inconsistent reports of their age of onset of regular smoking than were NH Whites. Furthermore, these analyses showed that the impact of race/ethnicity on the prevalence of inconsistent reporting may depend on other factors, e.g., age and employment status. For example, non-employed NH Blacks were 1.9 times more likely to recant ever smoking than were non-employed NH Whites. The lower consistency in reports by Hispanics and NH Blacks underscores the importance of developing new survey design and research strategies for detecting relatively small differences in reporting among the racial/ethnic minorities. Additional efforts to motivate racial/ethnic minorities to participate in national surveys may not only help increase representation of these subpopulations in study samples but also help improve overall data quality.