Racial/Ethnic Residential Segregation, Neighborhood Health Care Provision, and Choice of Pediatric Health Care Provider Across the USA.

Much research has been conducted that demonstrates a link between racial/ethnic residential segregation and health care outcomes. We suggest that minority segregated neighborhoods may have diminished access to organizations and that this differential access may contribute to differences in health care outcomes across communities. We analyze this specifically using the case of pediatric health care provider choice. To examine this association, we estimate a series of multinomial logistic regression models using restricted data with ZIP code level geoidentifiers from the 2011-2012 National Survey of Children's Health (NSCH). We find that racial/ethnic residential segregation is related to a greater reliance on non-ideal forms of health care, such as clinics, and hospital outpatient departments, instead of pediatric physician's offices. This association is at least partially attenuated by the distribution of health care facilities in the local area, physician's offices, and health care practitioners in particular. Additionally, families express greater dissatisfaction with these other forms of care compared to physician's offices, demonstrating that the lack of adequate health care provision is meaningful for health care outcomes. This study expands the literature by examining how the siting of health organizations has consequences for individuals residing within these areas.

Ordered Regression Models: a Tutorial.

Ordinal outcomes are common in the social, behavioral, and health sciences, but there is no commonly accepted approach to analyzing them. Researchers make a number of different seemingly arbitrary recoding decisions implying different levels of measurement and theoretical assumptions. As a result, a wide array of models are used to analyze ordinal outcomes, including the linear regression model, binary response model, ordered models, and count models. In this tutorial, we present a diverse set of ordered models (most of which are under-utilized in applied research) and argue that researchers should approach the analysis of ordinal outcomes in a more systematic fashion by taking into consideration both theoretical and empirical concerns, and prioritizing ordered models given the flexibility they provide. Additionally, we consider the challenges that ordinal independent variables pose for analysts that often go unnoticed in the literature and offer simple ways to decide how to include ordinal independent variables in ordered regression models in ways that are easier to justify on conceptual and empirical grounds. We illustrate several ordered regression models with an empirical example, general self-rated health, and conclude with recommendations for building a sounder approach to ordinal data analysis.

Racial-Ethnic Residential Clustering and Early COVID-19 Vaccine Allocations in Five Urban Texas Counties.

Previous research has indicated that racial-ethnic minority communities lack a wide variety of health-related organizations. We examine how this relates to the early COVID-19 vaccine rollout. In a series of spatial error and linear growth models, we analyze how racial-ethnic residential segregation is associated with the distribution of vaccine sites and vaccine doses across ZIP codes in the five largest urban counties in Texas. We find that Black and Latino clustered ZIP codes are less likely to have vaccine distribution sites and that this disparity is partially explained by the lack of hospitals and physicians' offices in these areas. Moreover, Black clustering is also negatively related to the number of allocated vaccine doses, and again, this is largely explained by the unequal distribution of health care resources. These results suggest that extant disparities in service provision are key to understanding racial-ethnic inequality in an acute crisis like the COVID-19 pandemic.

Combining Global Positioning System (GPS) with saliva collection among sexual minority adults: A feasibility study.

BACKGROUND: This is the first study, of which we are aware, to evaluate the feasibility and accessibility of simultaneous use of Global Positioning System (GPS) and saliva collection for biomarker assessment as an objective measure of stress physiology among sexual minority (lesbian, gay, bisexual, queer, and other non-heterosexual identities) individuals. The principal motivation for pairing GPS and saliva collection was to investigate how characteristics of the built and social environments along with participants' daily activity paths affect stress. This can contribute to a better understanding of health and health behaviors in the sexual minority community. METHODS: A convenience sample of enrolled participants (N = 124) from Houston, Texas was asked to complete questionnaires, carry with them a GPS unit daily, and collect and store 6 samples of saliva at specific times across the span of a day prior to a second visit around one week later. RESULTS: Of 124 participants, 16 participants (12.90%) provided no useable GPS data and 98 (79.03%) provided at least 4 days of data. More than three-fourths (n = 98, 79.03%) also provided complete saliva samples. CONCLUSIONS: Our results show that the simultaneous use of GPS and saliva collection to assess sexual minority individuals' activity paths and stress level is feasible.

Racial/Ethnic Residential Segregation and the First Wave of SARS-CoV-2 Infection Rates: A Spatial Analysis of Four U.S. Cities.

Previous research has linked racial/ethnic residential segregation to a number of poor health conditions, including infectious disease. Here, we examine how racial/ethnic residential segregation is related to the novel coronavirus, SARS-CoV-2. We examine infection rates by zip code level segregation in four major cities across the U.S.: New York City, Chicago, Houston, and San Diego. We also include a number of area-level Census variables in order to analyze how other factors may help account for the infection rate. We find that both Black and Latino residential clustering are significantly and positively related to a higher SARS-CoV-2 infection rate across all four cities, and that this effect is strong even when accounting for a number of other social conditions and factors that are salient to the transmission of infectious disease. As a result, we argue that neighborhood-level racial/ethnic patterning may serve as an important structural mechanism for disparities in SARS-CoV-2 infection.