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Objective: To identify predictors of unmet dental needs for adults 18 y of age or older in the United States. Method: Using the Aday and Andersen framework and data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS), we ran logistic regression to estimate predictors for adults of not having a dental visit within 5 y and having lost any teeth using a national sample of 155,060 survey respondents. Results: Results showed that predisposing factors (age, race/ethnicity, gender, and educational attainment) and enabling factors (income and health insurance status) are important predictors for losing teeth due to decay or gum disease. Men, the elderly, and less educated and low-income residents were less likely to have seen a dentist within the past 5 y and more likely to have lost their permanent teeth. Compared to non-Hispanic White adults, Hispanics adults were more likely to have had a dental visit within the past 5 y. Unmet dental needs varied across states. People living in states with extensive Medicaid dental care benefit coverage were less likely to lose their teeth and more likely to have had a dental visit within the past 5 y. Conclusion: Efforts to improve oral health should address unmet dental needs of men and adults with low socioeconomic status. Studying the variation between state oral health care programs could further our understanding of how public policy can improve population oral health. Knowledge Transfer Statement: Men, non-Hispanic Blacks, mixed and other race minorities, and low socioeconomic status adults are most at risk of unmet dental needs. States can address these needs by expanding Medicaid coverage for adults.

Objective: The authors conducted an integrative literature review of recent studies that explored the impact of interventions implemented in the U.S. that focused on improving access to dental care for low-income and vulnerable populations. Methods: The authors conducted an integrative literature review of studies published between 2012-2018 that addressed six oral health policy spheres. 1) Community-based dental access programs; (2) Medicaid reimbursement and expansion; (3) Student loan support; (4) Oral health services in non-traditional settings and dental residency programs; (5) Programs to improve oral health literacy; and (6) Use of dental therapists. Results: The authors included 39 articles for qualitative synthesis. Numerous public health initiatives and programs exist in the US aimed at increasing access to quality oral health care. Medicaid expansion, increased Medicaid fee-for-service reimbursement rates, and state loan repayment programs have demonstrated some success in improving access among underserved populations. A diversified dental workforce, with community dental health workers and mid-level providers like dental therapists, as well as interprofessional training of nurses and primary-care physicians in oral health have also shown positive impacts in advancing health equity. Further studies are needed to understand how oral health literacy programs can affect access and utilization of dental services. Conclusions: Improvements to the oral health care safety net will require a holistic and multifaceted approach in order to reduce oral health disparities. Policy levers should work, not in isolation, but rather in complementary fashion to one another.

Racial disparities in hypertension remain a persistent public health concern in the US. While several studies report Black&ndash, White differences in the health impacts of gentrification, little is known concerning the impact of living in a gentrifying neighborhood on hypertension disparities. Data from the American Community Survey were used to identify gentrifying neighborhoods across the US from 2006 to 2017. Health and demographic data were obtained for non-Hispanic Black and White respondents of the 2014 Medical Expenditure Panel Survey (MEPS) residing in gentrifying neighborhoods. Modified Poisson models were used to determine whether there is a difference in the prevalence of hypertension of individuals by their race/ethnicity for those that live in gentrifying neighborhoods across the US. When compared to Whites living within gentrifying neighborhoods, Blacks living within gentrifying neighborhoods had a similar prevalence of hypertension. The non-existence of Black&ndash, White hypertension disparities within US gentrifying neighborhoods underscores the impact of neighborhood environment on race differences in hypertension.

Objective To examine the availability of health care provider offices and facilities in predominantly White, minority, and integrated primary care service areas (PCSA). Methods National data from the American Community Survey and InfoUSA, linked at the PCSA-level, for 2005 (N=7,109) and 2014 (N=7,142). Associations between racial composition of PCSAs and numbers of health care offices and facilities were examined using multiple regression models. Results After adjustment for PCSA socio-demographic characteristics, predominantly minority PCSAs had fewer diagnostic imaging centers and offices for physicians, mental health providers, dentists, and other health practitioners than White PCSAs (Adj IRR range: 0.68-0.80, all pl.01). Availability was also lower for integrated PCSAs, but reductions were smaller and involved fewer service types (Adj IRR range: 0.85-0.91, all pl.05). Conclusion Minority and integrated communities have fewer provider offices and facilities for important health services, which may contribute to the persistent racial/ethnic disparities in health care access and use.

The State of Maryland implemented the Health Enterprise Zone Initiative in 2013 to improve access to health care and health outcomes in underserved communities and reduce health care costs and avoidable hospital admissions and readmissions. In each community the Health Enterprise Zone Initiative was a collaboration between the local health department or hospital and community-based organizations. The initiative was designed to attract primary care providers to underserved communities and support community efforts to improve health behaviors. It deployed community health workers and provided behavioral health care, dental services, health education, and school-based health services. We found that the initiative was associated with a reduction of 18,562 inpatient stays and an increase of 40,488 emergency department visits in the period 2013-16. The net cost savings from reduced inpatient stays far outweighed the initiative's cost to the state. Implementing such initiatives is a viable way to reduce inpatient admissions and reduce health care costs.

Objectives To learn dentists' perceptions, attitudes, and concerns about the problems of access to oral health care for low income and rural Marylanders and to ascertain whether the dentists believe dental therapy is a viable solution. Methods We conducted three focus group discussions of 27 dentists during August and September 2018 in three locations in urban and rural areas of Maryland. Results Focus group participants felt that problems with access to dental care for low income and rural Marylander were not due to a shortage of dental providers. They believed there are more than enough dentists in the state. Access problems in Maryland are due in large part to inadequate insurance coverage and low oral health literacy. With the exception of one participant, the dentists would not use dental therapists in their practices to expand access. Conclusions Maryland dentists in our focus group strongly oppose the use of dental therapists to address the state's unmet oral health care needs. Any effort to expand the state's dental workforce using dental therapists must address Maryland dentists' concerns and opinions.

This study&rsquo, s purpose is to determine if neighborhood disadvantage, air quality, economic distress, and violent crime are associated with mortality among term life insurance policyholders, after adjusting for individual demographics, health, and socioeconomic characteristics. We used a sample of approximately 38,000 term life policyholders, from a large national life insurance company, who purchased a policy from 2002 to 2010. We linked this data to area-level data on neighborhood disadvantage, economic distress, violent crime, and air pollution. The hazard of dying for policyholders increased by 9.8% (CI: 6.0&ndash, 13.7%) as neighborhood disadvantage increased by one standard deviation. Area-level poverty and mortgage delinquency were important predictors of mortality, even after controlling for individual personal income and occupational status. County level pollution and violent crime rates were positively, but not statistically significantly, associated with the hazard of dying. Our study provides evidence that neighborhood disadvantage and economic stress impact individual mortality independently from individual socioeconomic characteristics. Future studies should investigate pathways by which these area-level factors influence mortality. Public policies that reduce poverty rates and address economic distress can benefit everyone&rsquo, s health.

Although the elimination of health disparities and the prevention of disability in late life are top public health priorities (Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, 2002; U.S. Department of Health and Human Services, 1991), little progress has been achieved as Black older adults consistently exhibit higher rates of disability than White older adults (D. O. Clark & Maddox, 1992; Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, 2002; Coppin et al., 2006; Kelley-Moore & Ferraro, 2004; Kington & Smith, 1997; Koster et al., 2005; Mendes de Leon, Barnes, Bienias, Skarupski, & Evans, 2005; Schoeni, Martin, Andreski, & Freedman, 2005; Thorpe, Bell, LaVeist, & Simonsick, 2009; Thorpe, Kasper, et al., 2008; Thorpe et al., 2012). A number of explanations such as socioeconomic status (SES), health behaviors, and health status have been tested; yet, racial differences in disability persist. Because of the expected growth in the aging population, which includes a substantial increase in minorities and decrease in the number of Whites by 2050 (Federal Interagency Forum on Aging-Related Statistics, 2008), elucidating factors that underlie the racial-related inequalities in disability is paramount. Efforts to improve the understanding of racial disparities in disability are limited by two issues. First, race and SES are inextricably linked with Blacks having considerably fewer socioeconomic resources than Whites (Braveman et al., 2005; LaVeist, 2005; Thorpe, Brandon, & LaVeist, 2008; Williams & Collins, 1995). Because of this strong relationship between race and SES, the ability to determine how race and SES operate to produce disparities in disability is complicated (LaVeist, Pollack et al., 2011; LaVeist et al., 2008). Typically to address race and SES confounding, a multivariate approach is used whereby SES is included in the regression model. This is a well-recognized approach; however, it may not always be sufficient (see LaVeist, Thorpe, Mance, & Jackson, 2007, for details). The second problem in understanding racial disparities in disability is the confounding between race and residential segregation. The United States is very racially segregated; as a result, African Americans and Whites generally live in separate communities, where they have different social and environmental risk exposures. According to segregation theories such as Risk Exposure Theory and Resource Deprivation Theory (LaVeist, 2005), minority communities have social and environmental risks typically characterized by high crime (Lee, 2000) and poor housing (Black & Macinko, 2008; Williams & Collins, 2001), and are less likely to have as many health-promoting resources as White communities (Gaskin, Dinwiddie, Chan, & McCleary, 2012a, 2012b). This differential exposure to neighborhood stressors can contribute to a person’s ability to perform certain social roles and tasks. Specifically, neighborhoods that contain fewer healthy food choices, parks, sidewalks, recreational spaces, and medical facilities may negatively affect the adoption of health-promoting behaviors that can impede the progression or delay the onset of disability. Prior work examining race and disability has largely focused on individual measures such as SES (D. O. Clark, 1993; D. O. Clark & Maddox, 1992; Coppin et al., 2006; Koster et al., 2005; Liao, McGee, Cao, & Cooper, 1999; Peek, Coward, Henretta, Duncan, & Dougherty, 1997; Schoenbaum & Waidmann, 1997; Thorpe, Bowie, Wilson-Frederick, Coa, & LaVeist, 2013; Thorpe, Brandon, & LaVeist, 2008; Thorpe et al., 2012; White-Means & Hammond, 1993) or health-related factors (Kelley-Moore & Ferraro, 2004; Kington & Smith, 1997; Koster et al., 2007; Mendes de Leon, 1997). However, other investigators have sought to understand the interrelationships among key individual factors such as sex, SES, and disability (Johnson & Wolinsky, 1994; Mendes de Leon et al., 2005; Thorpe, Szanton, Bell, & Whitfield, 2013; Wray & Blaum, 2001) Findings from all of these studies highlight the importance of disentangling key confounders such as sex, SES, and health factors to advance our understanding of race differences in disability. In addition to individual-level factors, there is a growing body of literature that focuses on the association between neighborhood factors and disability (Balfour & Kaplan, 2002; Beard et al., 2009; C. R. Clark et al., 2009; Freedman, Grafova, Schoeni, & Rogowski, 2008; Glass & Balfour, 2003; Lang, Llewellyn, Langa, Wallace, & Melzer, 2008; Nordstrom et al., 2007; Pruchno, Wilson-Genderson, & Cartwright, 2012; White et al., 2010). These studies have consistently demonstrated that neighborhood indicators, including social vulnerability, wealth, violence, presence of physicians, traffic, trash, and litter, are related to disability in older adults. Also, studies assessing the impact of where one resides on race disparities in disability have found that geographic area affect disability (Lin, 2000). However, we are unaware of any study that has sought to determine whether social and environmental conditions contribute to racial differences in disability. Accounting for social context in health disparities research has demonstrated a substantial reduction or lack of racial differences in health outcomes, such as hypertension (Thorpe, Kasper, et al., 2008), obesity (Bleich, Thorpe, Sharif-Harris, Fesahazion, & LaVeist, 2010), health services use (Gaskin, Price, Brandon, & LaVeist, 2009), and diabetes (LaVeist, Thorpe, Galarraga, Bower, & Gary-Webb, 2009) in a racially integrated community without racial differences in income. This evidence suggests that social context is an important, yet understudied, determinant of health (LaVeist, Pollack et al., 2011; LaVeist et al., 2007; Williams & Collins, 2001). However, the extent to which racial disparities in disability are manifestations of differential social contexts rather than race is largely unknown. Furthermore, data sources available to disentangle race, SES, and segregation simultaneously are sparse. Thus, the purpose of this study was to examine racial disparities in disability within a sample of White and African American community-dwelling older adults living in the same social context with similar socioeconomic resources.

Residential characteristics influence opportunities, life chances and access to health services in the United States but what role does residential segregation play in differential access and mental health service utilization? We explore this issue using secondary data from the 2006 Medical Expenditure Panel Survey, 2006 American Medical Association Area Research File and the 2000 Census. Our sample included 9737 whites, 3362 African Americans and 5053 Latinos living in Metropolitan Statistical Areas. Using logistic regression techniques, results show respondents high on Latino isolation and Latino centralization resided in psychiatrist shortage areas whereas respondents high on African American concentration had access to psychiatrists in their neighborhoods. Predominant race of neighborhood was associated with the type of mental health professional used where respondents in majority African American neighborhoods were treated by non-psychiatrists and general doctors whereas respondents in majority Latino neighborhoods saw general doctors. Respondents high on Latino Isolation and Latino Centralization were more likely to utilize non-psychiatrists. These findings suggest that living in segregated neighborhoods influence access and utilization of mental health services differently for race/ethnic groups which contradicts findings that suggest living in ethnic enclaves is beneficial to health.

BACKGROUND Place of residence, particularly residential segregation, has been implicated in health and health care disparities. However, prior studies have not focused on care for diabetes, a prevalent condition for minority populations. OBJECTIVE To examine the association of residential segregation with a range of access and quality of care outcomes among black and Hispanics with diabetes using a nationally representative US sample. RESEARCH DESIGN Cross-sectional study using data for 1598 adult patients with diabetes from the 2006 Medical Expenditure Panel Survey linked to residential segregation information for blacks and Hispanics on the basis of the 2000 census. Relationships of 5 dimensions of residential segregation (dissimilarity, isolation, clustering, concentration, and centralization) with access and quality of care outcomes were examined using linear, logistic, and multinomial logistic regression models, controlling for respondent characteristics and community utilization and hospital capacity. RESULTS Black and Hispanics with diabetes had comparable or better access to providers, but received fewer recommended services. Living in a segregated community was associated with more recommended services received, but also problems with seeing a specialist. The relationship of residential segregation to diabetes care varied depending on type of segregation and race/ethnic group assessed. CONCLUSIONS Residential segregation influences the care experience of patients with diabetes in the United States. Our study highlights the importance of investigating how different types of segregation may affect diabetes care received by patients from different race and ethnic groups.

Numerous studies have explored the relationship between residential segregation and racial disparities in health. Some scholars have concluded that segregation is a fundamental cause of health disparities (Acevedo-Garcia 2000, 2001; Williams and Collins 2001; Morello-Frosch and Jesdale 2006). Prior research has found associations between residential segregation and infant mortality, adult mortality, poor health status, smoking during pregnancy, poor birth outcomes, TB and other infectious diseases, and exposure to cancer-causing air toxins (Yankauer 1950; LaVeist 1989, 1993, 2003; Polednak 1991, 1996a,b; Morello-Frosch and Jesdale 2006; Bell, Zimmerman, and Mayer 2007; Osypuk and Acevedo-Garcia 2008). The impacts of segregation are not limited to the United States, researchers have found that racial and economic segregation negatively affect health in South Africa, Rio De Janeiro, London, and Helsinki (Wyndham 1981; Christopher 1993; Szwarcwald et al. 2002; Myer, Ehrlich, and Susser 2004; Stafford et al. 2004). The association between residential segregation and health care resources is not well studied. We hypothesize that the impact of segregation on minority access to health care is similar to its negative impact on minority access to quality jobs, education, safety, and social networks (Smith 1999; Charles 2003). Morrison and colleagues found an association between segregation and the availability of pharmacy services to minority communities (Morrison et al. 2000). Nursing homes and hospitals serving minority communities were at greater risk of closure and reductions in services compared to those serving white communities (Gaskin 1997; Feng et al. 2011) and segregation resulted in the concentration of blacks in poor-performing nursing homes (Smith et al. 2007). Similarly, residential segregation is correlated with racial segregation of elderly minority black patients in relatively fewer hospitals resulting in black patients receiving lower quality care for some hospital services (Smith 1998; Jha, Orav, and Epstein 2007; Gaskin et al. 2011). Racial and ethnic disparities in primary care are well documented (U.S. Department of Health, Human Services, Agency for Healthcare Research and Quality 2008). In addition to socioeconomic factors, disparities in primary care may be due in part to geographic barriers to care (Shi 1999; Smedley, Stith, and Nelson 2003; Mayberry, Mili, and Ofili 2005; Gaskin et al. 2009). However, not much is known about the extent to which minorities face geographic barriers to care in comparison to whites. Disparities in health care may be caused by higher proportions of minorities living in “medical deserts,” that is, communities with limited health care resources. However, minorities may have better geographic access to care because they tend to live in the center cities near major teaching hospitals and federally qualified community health centers. Prior research has found that minorities relied more on community health centers, hospital outpatient departments and emergency rooms for their usual source of care in comparison to whites (Lillie-Blanton, Martinez, and Salganicoff 2001; Gaskin et al. 2007). These providers are more accessible to low-income minorities because they receive federal and state government subsidies to finance indigent care, whereas private physicians must absorb most of the cost of free or discounted services. Nationally, there is a shortage of primary care physicians (Bodenheimer 2006; Dill and Salsberg 2008). The proportion of physicians practicing primary care has steadily declined and interest among U.S. medical school graduates in entering primary care has dropped (Freed and Stockman 2009; Lakhan and Laird 2009). Lower reimbursement for primary care relative to specialty care is listed as a primary cause for this trend (Freed and Stockman 2009; Steinbrook 2009). To supply our current demand for primary care services, the United States is reliant on internationally trained physicians, especially minority communities (Dill and Salsberg 2008). Foreign-born and internationally trained physicians disproportionately serve minority and underserved communities. This study explores whether minorities differentially face geographic barriers to primary care physicians.

Objectives. We compared the strength of association between average 5-year county-level mortality rates and area-level measures, including air quality, sociodemographic characteristics, violence, and economic distress. Methods. We obtained mortality data from the National Vital Statistics System and linked it to socioeconomic and demographic data from the Census Bureau, air quality data, violent crime statistics, and loan delinquency data. We modeled 5-year average mortality rates (1998–2002) for all-cause, cancer, heart disease, stroke, and respiratory diseases as a function of county-level characteristics using ordinary least squares regression models. We limited analyses to counties with population of 100 000 or greater (n = 458). Results. Demographic and socioeconomic characteristics, particularly the percentage older than 65 years and near poor, were top predictors of all-cause and condition-specific mortality, as were a high concentration of construction and service workers. We found weaker associations for air quality, mortgage delinquencies, and violent crimes. Protective characteristics included the percentage of Hispanics, Asians, and married residents. Conclusions. Multiple factors influence county-level mortality. Although county demographic and socioeconomic characteristics are important, there are independent, although weaker, associations of other environmental characteristics. Future studies should investigate these factors to better understand community mortality risk.

Using data from the 2006 Medical Expenditure Panel Survey and the 2000 Census, the authors explored whether race/ethnic disparities in health care use were associated with residential segregation. They used five measures of health care use: office-based physician visits, outpatient department physician visits, visits to nurses and physician’s assistants, visits to other health professionals, and having a usual source of care. For each individual, the authors controlled for age, gender, marital status, insurance status, income, educational attainment, employment status, region, and health status. The authors used the racial–ethnic composition of the zip code to control for residential segregation. The findings suggest that disparities in health care utilization are related to both individuals’ racial and ethnic identity and the racial and ethnic composition of their communities. Therefore, efforts to improve access to health care services and to eliminate health care disparities for African Americans and Hispanics should not only focus on individual-level factors but also include community-level factors.