Objectives:We examined whether support for tobacco control policies varies by demographic group, including nativity status (i.e., immigrant versus US born). Methods. We analyzed 1995 to 2002 data from the Current Population Survey Tobacco Use Supplement (n=543951). The outcome was a summary attitudinal measure assessing support of smoking bans in 4 of 6 venues. Results. US-born respondents, smokers, male respondents, Native Americans, Whites, and those who were unmarried, of lower socioeconomic status, and whose workplaces and homes were not smoke free were less likely to support smoking bans. Immigrants exhibited stronger support for banning smoking in every venue, with a generation-specific gradient in which support eroded with increasing assimilation to the United States. Levels of support were more than twice as high among immigrants as among US-born respondents (odds ratio [OR]=2.16; 95% confidence interval [Cl]= 2.08, 2.23). Naturalized citizens displayed higher support than US-born citizens, which may be relevant for mobilization of the electorate. Differences in population composition and contexts (e.g., smoke-free workplaces) only partially accounted for immigrants' stronger level of support. Conclusions. Immigrants and their children may be valuable tobacco control allies given their supportive attitudes toward smoke-free policies.

Objectives. Tobacco use research has often assumed "average" effects across place, race, and socioeconomic position. We explored and mapped the variation in smoking prevalence for racial/ethnic groups by gender and state after adjusting for demographic factors. Methods. We executed a cross-sectional, weighted, two-level multilevel multiple regression analysis (individuals in states), with current smoking as the outcome, using the 1995-1996 Current Population Survey Tobacco Use Supplement, for non-Hispanic (NH) whites, NH blacks, and Hispanics. We also calculated adjusted smoking prevalence, 95% confidence intervals, Spearman correlations, and state residual-based maps to examine state patterns. Results. We found different smoking patterns for each racial group. Black women's smoking rates were markedly lower than the national subgroup rate in six clustered states in the deep South. Smoking rates for whites were higher than the subgroup national rate in several Great Lakes states, Texas, Nevada, and North Carolina. For white women, several rural Midwest states displayed lower-than-expected smoking rates (Idaho, Utah, South Dakota, and Nebraska). We documented positive correlations for smoking prevalence between men and women within each racial group, but not between racial groups, indicating a race-specific pattern of smoking. We found that state tobacco variables (taxation and agriculture) did not account for remaining state smoking variance after inclusion of demographic variables. Conclusion. Multilevel modeling may enhance surveillance of tobacco use patterns. Focusing on race-specific state smoking patterns may illuminate why racial/ethnic minority groups exhibit lower smoking prevalence compared to their white counterparts, by examining context of smoking that may be race-specific. ©2006 Association of Schools of Public Health.

The authors examine the research evidence on the effect of residential segregation on health, identify research gaps, and propose new research directions. Four recommendations are made on the basis of a review of the sociological and social epidemiology literature on residential segregation: (1) develop multilevel research designs to examine the effects of individual, neighborhood, and metropolitan-area factors on health outcomes; (2) continue examining the health effects of residential segregation among African Americans but also initiate studies examining segregation among Hispanics and Asians; (3) consider racial/ethnic segregation along with income segregation and other metropolitan area factors such as poverty concentration and metropolitan governance fragmentation; and (4) develop better conceptual frameworks of the pathways that may link various segregation dimensions to specific health outcomes.

Economic hardship may lead to a wide range of negative outcomes, including violence. However, existing literature on economic hardship and violence is limited by reliance on official reports of violence and conflation of different measures of economic hardship. The goals of this study are to measure how violence-related injuries are associated with five measures of county-level economic shocks: unemployment rate, male mass layoffs, female mass layoffs, foreclosure rate, and unemployment rate change, measured cross-sectionally and by a 1-year lag. This study measures three subtypes of violence outcomes (child abuse, elder abuse, and intimate partner violence). Yearly county-level data were obtained on violence-related injuries and economic measures from 2005 to 2012 for all 87 counties in Minnesota. Negative binomial models were run regressing the case counts of each violence outcome at the county-year level on each economic indicator modeled individually, with population denominator offsets to yield incidence rate ratios. Crude models were run first, then county-level socio-demographic variables and year were 2 Journal of Interpersonal Violence 00(0) added to each model, and finally fully-adjusted models were run including all socio-demographic variables plus all economic indicators simultaneously. In the fully-adjusted models, a county's higher foreclosure rate is the strongest and most consistently associated with an increase in all violence subtypes. Unemployment rate is the second strongest and most consistent economic risk factor for all violence subtypes. Lastly, there appears to be an impact of gender specific to economic impacts on child abuse; specifically, male mass-lay-offs were associated with increased rates while female mass-lay-offs were associated with decreased rates. Understanding the associations of different types of economic hardship with a range of violence outcomes can aid in developing more holistic prevention and intervention efforts.