Search

Objective: To describe blood pressure and glycemic control by racial/ethnic group in the US Community Health Center (CHC) patient population, and whether center characteristics, proxying for higher resource levels and better quality of care, were associated with greater rates of controlled cardiometabolic conditions. Methods: Data came from the Uniform Data System, representing aggregate patient clinical data for individual health centers in 2019. Descriptive analyses were conducted weighting by health center patient populations to produce race-specific national rates of blood pressure and glycemic control, and linear regression is used to test whether cardiometabolic control rates varied by center characteristics. Results: Hypertension was controlled for 67.2% of non-Hispanic White, 66.9% of Hispanic, and 56.7% of non-Hispanic Black patients. Diabetes was controlled for 70.7% of non-Hispanic White, 65.7% of Hispanic, and 66.1% of non-Hispanic Black patients. The rate of blood pressure control was 2.54 to 3.99 percentage points higher across racial/ethnic groups in health centers that adopted a patient-centered medical home (PCMH) model of care relative to non-PCMH centers, while glycemic control was 1.08 to 2.27 pp. higher as a function of PCMH certification. Results for other center characteristics did not show consistent patterns across racial groups or outcomes. Conclusion: This study documented racial and ethnic health disparities in the CHC patient population after major expansion of the CHC program. CHCs with PCMH certification have improved clinical outcomes among patients with hypertension and diabetes across racial/ethnic groups relative to centers without this certification. [ABSTRACT FROM AUTHOR]

Policy PointsPolicies that increase county income levels, particularly for middle‐income households, may reduce low birth weight rates and shrink disparities between Black and White infants.Given the role of aggregate maternal characteristics in predicting low birth weight rates, policies that increase human capital investments (e.g., funding for higher education, job training) could lead to higher income levels while improving population birth outcomes.The association between county income levels and racial disparities in low birth weight is independent of disparities in maternal risks, and thus a broad set of policies aimed at increasing income levels (e.g., income supplements, labor protections) may be warranted. Context: Low birth weight (LBW; <2,500 grams) and infant mortality rates vary among place and racial group in the United States, with economic resources being a likely fundamental contributor to these disparities. The goals of this study were to examine time‐varying county median income as a predictor of LBW rates and Black‐White LBW disparities and to test county prevalence and racial disparities in maternal sociodemographic and health risk factors as mediators. Methods: Using national birth records for 1992–2014 from the National Center for Health Statistics, a total of approximately 27.4 million singleton births to non‐Hispanic Black and White mothers were included. Data were aggregated in three‐year county‐period observations for 868 US counties meeting eligibility requirements (n = 3,723 observations). Sociodemographic factors included rates of low maternal education, nonmarital childbearing, teenage pregnancy, and advanced‐age pregnancy; and health factors included rates of smoking during pregnancy and inadequate prenatal care. Among other covariates, linear models included county and period fixed effects and unemployment, poverty, and income inequality. Findings: An increase of $10,000 in county median income was associated with 0.34 fewer LBW cases per 100 live births and smaller Black‐White LBW disparities of 0.58 per 100 births. Time‐varying county rates of maternal sociodemographic and health risks mediated the association between median income and LBW, accounting for 65% and 25% of this estimate, respectively, but racial disparities in risk factors did not mediate the income association with Black‐White LBW disparities. Similarly, county median income was associated with very low birth weight rates and related Black‐White disparities. Conclusions: Efforts to increase income levels—for example, through investing in human capital, enacting labor union protections, or attracting well‐paying employment—have broad potential to influence population reproductive health. Higher income levels may reduce LBW rates and lead to more equitable outcomes between Black and White mothers. [ABSTRACT FROM AUTHOR]

Objectives: To examine changes in sleep problems over a 1.5-year period among Black or African American (AA) and White or European American (EA) college students and to consider the role of racial discrimination as a mediator of race differences in sleep problems over time.Method: Students attending a large, predominantly White university (N = 133, 41% AA, 57% female, mean age = 18.8, SD = .90) reported on habitual sleep characteristics and experiences of racial discrimination at baseline and follow-up assessments. A latent variable for sleep problems was assessed from reports of sleep latency, duration, efficiency, and quality. Longitudinal models were used to examine race differences in sleep problems over time and the mediating role of perceived discrimination. Covariates included age, gender, parent education, parent income, body mass index, self-rated physical health, and depressive symptoms. Each of the individual sleep measures was also examined separately, and sensitivity analyses were conducted using alternative formulations of the sleep problems measure.Results: AAs had greater increases in sleep problems than EAs. Perceived discrimination was also associated with increases in sleep problems over time and mediated racial disparities in sleep. This pattern of findings was similar when each of the sleep indicators was considered separately and held with alternative sleep problems measures.Conclusions: The findings highlight the importance of racial disparities in sleep across the college years and suggest that experiences of discrimination contribute to group disparities. (PsycINFO Database Record [ABSTRACT FROM AUTHOR]