The original TUS-CPS 1995–1996 dataset contained 247,088 observations. We excluded 1,220 observations missing on the smoking status variable (0.49% of sample), as well as Native Americans (1.02%) and Asians (3.12%), for a sample size of 235,654.
As shows, 23% of our sample were current smokers in 1995–1996. Men smoked more than women (25% vs. 20%); native born (23%) more than foreign born (16%); and non-Hispanic whites (23%) more than other racial/ethnic groups (NH Black 22%, Hispanic 17%).
Examination of the data in multidimensional cross tabulations showed marked variability in smoking patterns by race/gender subgroups. For instance, there were stark age patterns, of an inverse-U shape with regard to age, across all racial/gender groups ( not shown). Foreign-born women smoked at much lower rates than foreign-born men across all age groups. There was a much smaller difference in smoking prevalence between native-born women and men than among their foreign-born counterparts, although men are still more likely to smoke than women across both native and foreign-born groups.
displays average smoking prevalence estimates from the two-level logistic regression models stratified by race/ethnicity and gender. These models included all individual-level demographic factors, including age, occupation, income, education, nativity, and marital status (Model 2).
Logistic regression results from gender and racial/ethnic stratified models, odds of current smoking, fixed effect parameters
demonstrates that all demographic variables were significant with smoking in final models for all racial/ethnic and gender groups (although occupation was marginally or non-significant for Hispanics). Even after accounting for all demographic factors in our model, there continue to be differential smoking patterns by race/ethnicity. Among women, a gradient exists, with Hispanic women smoking least, followed by black women, and white women smoking the most. Among men, Hispanic men display the lowest smoking prevalence, followed by white men and black men with approximately comparable smoking prevalence. But as stated prior, the average association for each racial group was modified substantially by demographic characteristics, so one summary estimate of smoking prevalence does not sufficiently capture the variability of smoking for each racial group.
displays the state random effects of smoking in null models (Model 1) and in models adjusted for all demographic variables (Model 2). All Model 1 state variances in smoking are significant from zero for women, suggesting that states display significant variance in smoking for all three racial groups, but for men only whites had significant variance. In final models, Hispanic men and women's variance is not significant from zero, and black men's is only marginally significant. The magnitude of state smoking variance was largest for black and Hispanic women, at approximately twice the size of white women and white men.
Logistic regression results from gender and race/ethnic stratified models, random effects: state intercept variance components of current smoking
provides the predicted probability of smoking, after adjusting for demographic and socioeconomic factors, for the different racial/gender groups, across the states and nationally, based on the state-level residuals from Model 2. The displays these predicted probabilities on U.S. maps. These smoking prevalence estimates were calculated for the reference group (native-born, age 44, married, high school graduate, earning $0–19,000 annually, in sales/tech occupations).
Model 2 residual-based predicted smoking probability by state, race/ethnicity, and gender, TUS-CPS 1995–1996
The highlights states that are significantly different from the gender/race subgroup national predicted probability smoking prevalence average, by mapping the adjusted smoking prevalence from . For instance, in the for whites, we observed four states above the national rate for both men and women for predicted probability of smoking, including Nevada, Michigan, North Carolina, and Texas. White women additionally displayed higher than their U.S. average smoking prevalence in Florida and Indiana, while white men additionally displayed state rates higher than their national average in Illinois, Ohio, and Virginia. White women exhibited lower predicted smoking prevalence rates than expected in Idaho, Nebraska, South Dakota, and Utah, while no states show smoking prevalence rates below the national mean for white men. In all, 10 states differed from the national smoking rate for white women, while seven differed for white men.
The displays fewer states significantly different from the national rate of predicted probability of smoking for racial minorities (compared to the maps for whites). Black women displayed the most variability among minorities, with seven states exhibiting predicted probability of smoking different from the national rate for black women. A clear pattern emerged for black women whereby all six states significantly lower than expected were clustered together in the Southeast: South Carolina, Georgia, Alabama, Mississippi, Louisiana, and Florida. New York was the one state significantly higher than the national mean for black women. Hispanic women, Hispanic men, and black men showed very little variability from the national mean, with only one or two states per group differing from the national rate. Illinois displayed significantly higher adjusted predicted smoking rates than the national rate among black men. California displayed significantly lower adjusted predicted smoking rates than the national rate for Hispanic women and Hispanic men. New Mexico displayed higher-than-expected adjusted rates for Hispanic women. These states are also listed in .
States different from gender and racial/ethnic national estimate of predicted probability of smoking, from Model 2 state-level residuals, TUS-CPS 1995–1996
To examine further smoking patterns across states, we analyzed correlations between men and women for the six racial/ethnic gender groups, using the predicted probability of smoking derived from the residuals of Model 2 (using the estimates in ). We found a pattern here similar to the pattern that resulted when analyzing crude smoking rates (results not shown). For each racial group, men and women's predicted smoking rates were significantly positively correlated. For whites, this association was moderate to large (0.64, p<0.0001), while for blacks (0.37, p=0.0074) and Hispanics (0.44, p=0.0013) it was smaller. So there seems to be a geographic patterning of smoking associated with race/ethnicity, after adjusting for demographic factors. We also found that in no instance are racial/ethnic rates of smoking correlated with any other group (correlations other than these listed were not significant; results not shown).