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.

Over the past decade, interest in exploring how health care system distrust is associated with individual health outcomes and behaviors has grown substantially, and the racial difference in distrust has been well documented, with African Americans demonstrating higher distrust than whites. However, relatively little is known about whether the individual-level determinants of distrust differ by various dimensions of distrust, and even less is understood regarding whether the race-distrust association could be moderated by the neighborhood social environment. This study used a dual-dimensional distrust scale (values and competence distrust), and applied social disorganization theory to address these gaps. We combined the 2008 Philadelphia Health Management Corporation’s household survey (N=3,746 adult respondents, 51% of which are of African American race) with neighborhood-level data (N= 45 neighborhoods) maintained by the 2000 US Census and the Philadelphia Police Department. Using multilevel modeling, we found that first, after controlling for individual- and neighborhood-level covariates, African American residents have greater values distrust than whites, but no racial difference was found in competence distrust; second, competence distrust is more likely to be determined by personal health status and access to health care services than is values distrust; and third, ceteris paribus, the association between race and values distrust was weakened by the increasing level of neighborhood stability. These results not only indicate that different aspects of distrust may be determined via different mechanisms, but also suggest that establishing a stable neighborhood may ameliorate the level of distrust in the health care system among African Americans. As distrust has been identified as a barrier to medical research, the insight provided by this study can be applied to develop a health care system that is trusted, which will, in turn, improve population health.

IMPORTANCE Federal emergency authorities were invoked during the COVID-19 pandemic to expand use of telehealth for new and continued care, including provision of medications for opioid use disorder (MOUD).OBJECTIVE To examine receipt of telehealth services, MOUD (methadone, buprenorphine, and extended-release [ER] naltrexone) receipt and retention, and medically treated overdose before and during the COVID-19 pandemic.

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.

We use a geographically weighted regression (GWR) approach to examine how the relationships between a set of predictors and prenatal care vary across the continental US. At its most fundamental, GWR is an exploratory technique that can facilitate the identification of areas with low prenatal care utilization and help better understand which predictors are associated with prenatal care at specific locations. Our work complements existing prenatal care research in providing an ecological, place-sensitive analysis. We found that the percent of the population who was uninsured was positively associated with the percent of women receiving late or no prenatal care in the global model. The GWR map not only confirmed, but also demonstrated the spatial varying association. Additionally, we found that the number of Ob-Gyn doctors per 100,000 females of childbearing age in a county was associated with the percentage of women receiving late or no prenatal care, and that a higher value of female disadvantage is associated with higher percentages of late or no prenatal care. GWR offers a more nuanced examination of prenatal care and provides empirical evidence in support of locally tailored health policy formation and program implementation, which may improve program effectiveness.