Previous studies focused on identifying the determinants of mortality in US counties have examined the relationships between mortality and explanatory covariates within a county only, and have ignored the well-documented spatial dependence of mortality. We challenge earlier literature by arguing that the mortality rate of a certain county may also be associated with the features of its neighboring counties beyond its own features. Drawing from both the spillover (i.e., same direction effect) and social relativity (i.e., opposite direction effect) perspectives, our spatial Durbin modeling results indicate that both theoretical perspectives provide valuable frameworks to guide the modeling of mortality variation in US counties. Our empirical findings support that mortality rate of a certain county is associated with the features of its neighbors beyond its own features. Specifically, we found support for the spillover perspective in which the percentage of the Hispanic population, concentrated disadvantage, and the social capital of a specific county are negatively associated with the mortality rate in the specific county and also in neighboring counties. On the other hand, the following covariates fit the social relativity process: health insurance coverage, percentage of non-Hispanic other races, and income inequality. Their direction of the associations with mortality in the specific county is opposite to that of the relationships with mortality in neighboring counties. Methodologically, spatial Durbin modeling addresses the shortcomings of traditional analytic approaches used in ecological mortality research such as ordinary least squares, spatial error, and spatial lag regression. Our results produce new insights drawn from unbiased estimates.

Drawing from both the place stratification and ethnic enclave perspectives, we use multilevel modeling to investigate the relationships between women’s race/ethnicity (i.e., non-Hispanic white, non-Hispanic black, Asian, and Hispanic) and maternal smoking during pregnancy; and examine if these relationships are moderated by racial segregation in the continental United States. The results show that increased interaction with whites is associated with increased probability of maternal smoking during pregnancy for Asian and Hispanic mothers. In addition, racial segregation moderates the relationships between race/ethnicity and maternal smoking. Specifically, living in a less racially segregated area is related to a lower probability of smoking during pregnancy for black women, but it could double and almost triple the probability of smoking for Asian women and Hispanic women, respectively. Our findings provide empirical evidence for both the place stratification and ethnic enclave perspectives.

Neighborhood is an important context in which individuals and families are embedded. Yet family studies researchers have been relatively slow to incorporate spatial approaches into family science. Although limited theoretical and methodological attention has been devoted to families in neighborhood-effects research, family scholars can contribute greatly to theories about neighborhood effects, and neighborhood-effects research can help move the field of family studies forward. This article reviews the theories, applications, and limitations of research on neighborhood effects and discusses how family studies can benefit from incorporating a spatial perspective from neighborhood-effects research. I then present an innovative methodology—referred to as activity spaces—emerging in neighborhood-effects research, and I discuss how this approach can be used to better understand the complexity and heterogeneity of families. Last, I highlight ways to incorporate space into family studies by “putting families into place.”

Lifespans are both shorter and more variable for blacks than for whites in the United States. Because their lifespans are more variable, there is greater inequality in length of life—and thus greater uncertainty about the future—among blacks. This study is the first to decompose the black-white difference in lifespan variability in America. Are lifespans more variable for blacks because they are more likely to die of causes that disproportionately strike the young and middle-aged, or because age at death varies more for blacks than for whites among those who succumb to the same cause? We find that it is primarily the latter. For almost all causes of death, age at death is more variable for blacks than it is for whites, especially among women. Although some youthful causes of death, such as homicide and HIV/AIDS, contribute to the black-white disparity in variance, those contributions are largely offset by the higher rates of suicide and drug poisoning deaths for whites. As a result, differences in the causes of death for blacks and whites account, on net, for only about one-eighth of the difference in lifespan variance.

BACKGROUND Blacks have lower life expectancy than whites in the United States. That disparity could be due to racial differences in the causes of death, with blacks being more likely to die of causes that affect the young, or it could be due to differences in the average ages of blacks and whites who die of the same cause. Prior studies fail to distinguish these two possibilities. OBJECTIVE In this study we determine how much of the 2000–10 reduction in the racial gap in life expectancy resulted from narrowing differences in the cause-specific mean age at death for blacks and whites, as opposed to changing cause-specific probabilities for blacks and whites. METHOD We introduce a method for separating the difference-in-probabilities and difference-inage components of group disparities in life expectancy. RESULTS Based on the new method, we find that 60% of the decline in the racial gap in life expectancy from 2000 to 2010 was attributable to reduction in the age component, largely because of declining differences in the age at which blacks and whites die of chronic diseases. CONCLUSION Our findings shed light on the sources of the declining racial gap in life expectancy in the United States, and help to identify where advances need to be made to achieve the goal of eliminating racial disparities in life expectancy.