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BACKGROUND: Care for Black patients is concentrated at a relatively small proportion of all US hospitals. Some previous studies have documented quality deficits at Black-serving hospitals, which may be due to inequities in financial resources for care. OBJECTIVE: To assess disparities in funding between hospitals associated with the proportion of Black patients that they serve. PARTICIPANTS: All Medicare-participating hospitals, 2016-2018. MAIN MEASURES: Patient care revenues and profits per patient day at Black-serving hospitals (the top 10% of hospitals ranked by the share of Black patients among all Medicare inpatients) and at other hospitals, unadjusted and adjusted for differences in case mix and hospital characteristics. KEY RESULTS: Among the 574 Black-serving hospitals, an average of 43.7% of Medicare inpatients were Black, vs. 5.2% at the 5,166 other hospitals. Black-serving hospitals were slightly larger, and were more often urban, teaching, and for-profit or government (vs. non-profit) owned. Patient care revenues and profits averaged $1,736 and $-17 per patient day respectively at Black-serving hospitals vs. $2,213 and $126 per patient day at other hospitals (p<.001 for both comparisons). Adjusted for patient case mix and hospital characteristics, mean revenues were $283 lower/patient day (p<.001) and mean profits were $111/patient day lower (p<.001) at Black-serving hospitals. Equalizing reimbursement levels would have required $14 billion in additional payments to Black-serving hospitals in 2018, a mean of approximately $26 million per Black-serving hospital. CONCLUSIONS: US hospital financing effectively assigns a lower dollar value to the care of Black patients. To reduce disparities in care, health financing reforms should eliminate the underpayment of hospitals serving a large share of Black patients.
Subject(s)
Healthcare Financing , Hospitals , Medicare , Systemic Racism , Aged , Humans , Diagnosis-Related Groups , United States , Black or African American , Economics, Hospital , Healthcare DisparitiesABSTRACT
There is no established method for processing data from commercially available physical activity trackers. This study aims to develop a standardized approach to defining valid wear time for use in future interventions and analyses. Sixteen African American women (mean age = 62.1 years and mean body mass index = 35.5 kg/m2) wore the Fitbit Charge 2 for 20 days. Method 1 defined a valid day as ≥10-hr wear time with heart rate data. Method 2 removed minutes without heart rate data, minutes with heart rate ≤ mean - 2 SDs below mean and ≤2 steps, and nighttime. Linear regression modeled steps per day per week change. Using Method 1 (n = 292 person-days), participants had 20.5 (SD = 4.3) hr wear time per day compared with 16.3 (SD = 2.2) hr using Method 2 (n = 282) (p < .0001). With Method 1, participants took 7,436 (SD = 3,543) steps per day compared with 7,298 (SD = 3,501) steps per day with Method 2 (p = .64). The proposed algorithm represents a novel approach to standardizing data generated by physical activity trackers. Future studies are needed to improve the accuracy of physical activity data sets.
Subject(s)
Exercise , Fitness Trackers , Algorithms , Body Mass Index , Female , Heart Rate , HumansABSTRACT
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the world. Given the role of immune cells in atherosclerosis development and progression, effective methods for characterizing immune cell populations are needed, particularly among populations disproportionately at risk for CVD. RESULTS: By using a variety of antibodies combined in one staining protocol, we were able to identify granulocyte, lymphocyte, and monocyte sub-populations by CD-antigen expression from 500 µl of whole blood, enabling a more extensive comparison than what is possible with a complete blood count and differential (CBC). The flow cytometry panel was established and tested in a total of 29 healthy men and women. As a proof of principle, these 29 samples were split by their race/ethnicity: African-Americans (AA) (N = 14) and Caucasians (N = 15). We found in accordance with the literature that AA had fewer granulocytes and more lymphocytes when compared to Caucasians, though the proportion of total monocytes was similar in both groups. Several new differences between AA and Caucasians were noted that had not been previously described. For example, AA had a greater proportion of platelet adhesion on non-classical monocytes when compared to Caucasians, a cell-to-cell interaction described as crucially important in CVD. We also examined our flow panel in a clinical population of AA women with known CVD risk factors (N = 20). Several of the flow cytometry parameters that cannot be measured with the CBC displayed correlations with clinical CVD risk markers. For instance, Framingham Risk Score (FRS) calculated for each participant correlated with immune cell platelet aggregates (PA) (e.g. T cell PA ß = 0.59, p = 0.03 or non-classical monocyte PA ß = 0.54, p = 0.02) after adjustment for body mass index (BMI). CONCLUSION: A flow cytometry panel identified differences in granulocytes, monocytes, and lymphocytes between AA and Caucasians which may contribute to increased CVD risk in AA. Moreover, this flow panel identifies immune cell sub-populations and platelet aggregates associated with CVD risk. This flow cytometry panel may serve as an effective method for phenotyping immune cell populations involved in the development and progression of CVD.
Subject(s)
Blood Volume , Cardiovascular Diseases , Black or African American , Cardiovascular Diseases/diagnosis , Female , Granulocytes , Humans , Male , Monocytes , Pilot Projects , White PeopleABSTRACT
BACKGROUND: Little is known about the associations between perceived neighborhood social environment (PNSE) and depressive symptoms among African Americans. Furthermore, the role of physical activity (PA) as a mediator of this association has not been investigated. The two-fold objectives of this study, therefore, were (1) to examine the associations between PNSE and depressive symptoms among African Americans, and (2) to test the degree to which these associations were mediated by total PA. METHODS: We used baseline data from the Jackson Heart Study (JHS), a single-site, prospective, community-based study of African-American adults (n = 2209) recruited from Jackson, Mississippi. PNSE variables included scores for neighborhood violence (i.e., higher score = more violence), problems (higher score = more problems), and social cohesion (higher score = more cohesion). Depressive symptoms were measured by the 20-item Center for Epidemiological Studies Depression (CES-D) score. First, multilevel modeling, controlling for census tract clustering effects, was used to estimate associations between each PNSE variable and CES-D score, adjusting for covariates, including demographic, health-related, and population density. Second, validated, self-reported total PA, based on active living, sport, and home indices, was tested as the mediator. Multivariable linear regressions with bootstrap-generated 95% bias-corrected confidence intervals (BC CIs) were estimated to test for significant unstandardized indirect effects, controlling for all covariates. RESULTS: Our participants were 64.2% female with a mean age of 52.6 (SD = 12.2) and a mean CES-D score of 10.8 (SD = 8.1). In the fully-adjusted model, neighborhood violence and problems were positively related to depressive symptoms (B = 3.59, 95%CI = 0.93, 6.26, and B = 3.06, 95%CI = 1.19, 4.93, respectively). Neighborhood violence and problems were also indirectly related to depressive symptoms via total PA (B = 0.26, 95%BC CI = 0.05, 0.55; and B = 0.15, 95%BC CI = 0.02, 0.34, respectively). Social cohesion was neither directly nor indirectly related to depressive symptoms. CONCLUSIONS: We found that higher levels of perceived neighborhood problems and violence were directly and positively associated with depressive symptoms. These associations may be explained in part by lower total PA levels. Future interventions to reduce depressive symptoms attributed to neighborhood features should consider emphasizing built environment features that facilitate PA increases in conjunction with community efforts to reduce neighborhood violence and problems.
Subject(s)
Depression/epidemiology , Exercise/psychology , Residence Characteristics , Social Environment , Adult , Black or African American , Aged , Female , Humans , Longitudinal Studies , Male , Middle Aged , Mississippi/epidemiology , Prospective Studies , ViolenceABSTRACT
Importance: In the US, Black individuals die younger than White individuals and have less household wealth, a legacy of slavery, ongoing discrimination, and discriminatory public policies. The role of wealth inequality in mediating racial health inequities is unclear. Objective: To assess the contribution of wealth inequities to the longevity gap that exists between Black and White individuals in the US and to model the potential effects of reparations payments on this gap. Design, Setting, and Participants: This cohort study analyzed the association between wealth and survival among participants in the Health and Retirement Study, a nationally representative panel study of community-dwelling noninstitutionalized US adults 50 years or older that assessed data collected from April 1992 to July 2019. Participants included 7339 non-Hispanic Black (hereinafter Black) and 26â¯162 non-Hispanic White (hereinafter White) respondents. Data were analyzed from January 1 to September 17, 2022. Exposures: Household wealth, the sum of all assets (including real estate, vehicles, and investments), minus the value of debts. Main Outcomes and Measures: The primary outcome was all-cause mortality by the end of survey follow-up in 2018. Using parametric survival models, the associations among household wealth, race, and survival were evaluated, adjusting for age, sex, number of household members, and marital status. Additional models controlled for educational level and income. The survival effects of eliminating the current mean wealth gap with reparations payments ($828â¯055 per household) were simulated. Results: Of the 33â¯501 individuals in the sample, a weighted 50.1% were women, and weighted mean (SD) age at study entry was 59.3 (11.1) years. Black participants' median life expectancy was 77.5 (95% CI, 77.0-78.2) years, 4 years shorter than the median life expectancy for White participants (81.5 [95% CI, 81.2-81.8] years). Adjusting for demographic variables, Black participants had a hazard ratio for death of 1.26 (95% CI, 1.18-1.34) compared with White participants. After adjusting for differences in wealth, survival did not differ significantly by race (hazard ratio, 1.00 [95% CI, 0.92-1.08]). In simulations, reparations to close the mean racial wealth gap were associated with reductions in the longevity gap by 65.0% to 102.5%. Conclusions and Relevance: The findings of this cohort study suggest that differences in wealth are associated with the longevity gap that exists between Black and White individuals in the US. Reparations payments to eliminate the racial wealth gap might substantially narrow racial inequities in mortality.
Subject(s)
Black People , Ethnicity , Adult , Female , Humans , Middle Aged , Male , Cohort Studies , Socioeconomic Factors , IncomeABSTRACT
Neighborhood socioeconomic disadvantage may contribute to depression. This study examined associations between neighborhood socioeconomic disadvantage, measured as deprivation, and depression severity within a broadly representative sample of the U.S. adult population. The sample (n = 6308 U.S. adults) was from the 2011-2014 National Health and Nutrition Examination Survey. Neighborhood deprivation was calculated using the 2010 U.S. Census and shown in tertile form. Depression severity was calculated from responses to the Patient Health Questionnaire-9 (PHQ-9) as a continuous depression severity score and binary Clinically Relevant Depression (CRD). Multilevel modeling estimated the relationship between deprivation and depression (reference = low deprivation). Models were additionally stratified by gender and race/ethnicity. U.S. adults living in high deprivation neighborhoods were more likely to have a higher PHQ-9 score (p < 0.0001). In unadjusted models, living in high deprivation neighborhoods associated with higher PHQ-9 (ß = 0.89, SE = 0.15, p < 0.0001) and higher odds of CRD (OR = 1.35, 95% CI = 1.20-1.51). Living in medium deprivation neighborhoods associated with higher PHQ-9 (ß = 0.49, SE = 0.16, p = 0.0019). Associations between deprivation and depression severity lost significance after adjusting for individual-level SES. The results suggest that, for U.S. adults, the relationship between neighborhood-level disadvantage and depression may be attenuated by individual-level SES.
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Despite the widespread prevalence of cases associated with the coronavirus disease 2019 (COVID-19) pandemic, little is known about the spatial clustering of COVID-19 in the United States. Data on COVID-19 cases were used to identify U.S. counties that have both high and low COVID-19 incident proportions and clusters. Our results suggest that there are a variety of sociodemographic variables that are associated with the severity of COVID-19 county-level incident proportions. As the pandemic evolved, communities of color were disproportionately impacted. Subsequently, it shifted from communities of color and metropolitan areas to rural areas in the U.S. Our final period showed limited differences in county characteristics, suggesting that COVID-19 infections were more widespread. The findings might address the systemic barriers and health disparities that may result in high incident proportions of COVID-19 clusters.
Subject(s)
COVID-19 , Cluster Analysis , Humans , Pandemics , SARS-CoV-2 , Spatial Analysis , United States/epidemiologyABSTRACT
Background: Psychosocial stress correlates with cardiovascular (CV) events; however, associations between physiologic measures of stressors and CVD remain incompletely understood, especially in racial/ethnic minority populations in resource-limited neighborhoods. We examined associations between chronic stress-related neural activity, measured by amygdalar 18Fluorodeoxyglucose (18FDG) uptake, and aortic vascular FDG uptake (arterial inflammation measure) in a community-based cohort. Methods: Forty participants from the Washington, DC CV Health and Needs Assessment (DC-CHNA), a study of a predominantly African-American population in resource-limited urban areas and 25 healthy volunteers underwent detailed phenotyping, including 18FDG PET/CT for assessing amygdalar activity (AmygA), vascular FDG uptake, and hematopoietic (leukopoietic) tissue activity. Mediation analysis was used to test whether the link between AmygA and vascular FDG uptake was mediated by hematopoietic activity. Results: AmygA (1.11 ± 0.09 vs. 1.05 ± 0.09, p = 0.004) and vascular FDG uptake (1.63 ± 0.22 vs. 1.55 ± 0.17, p = 0.05) were greater in the DC-CHNA cohort compared to volunteers. Within the DC-CHNA cohort, AmygA associated with vascular FDG uptake after adjustment for Framingham score and body mass index (ß = 0.41, p = 0.015). The AmygA and aortic vascular FDG uptake relationship was in part mediated by splenic (20.2%) and bone marrow (11.8%) activity. Conclusions: AmygA, or chronic stress-related neural activity, associates with subclinical CVD risk in a community-based cohort. This may in part be mediated by the hematopoietic system. Our findings of this hypothesis-generating study are suggestive of a potential relationship between chronic stress-related neural activity and subclinical CVD in an African American community-based population. Taken together, these findings suggest a potential mechanism by which chronic psychosocial stress, such as stressors that can be experienced in adverse social conditions, promotes greater cardiovascular risk amongst resource-limited, community-based populations most impacted by cardiovascular health disparities. However, larger prospective studies examining these findings in other racially and ethnically diverse populations are necessary to confirm and extend these findings.
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Neighborhood environment perception (NEP) has been associated with health outcomes. However, little is known about how NEP relates to routine healthcare utilization. This study investigated the relationship between NEP and independent subfactors with healthcare utilization behavior, as measured by self-reported (1) usual source of healthcare and (2) time since last routine healthcare check-up. We used cross-sectional data from the Dallas Heart Study, which features a diverse, probability-based sample of Dallas County residents ages 18 to 65. We used logistic regression modeling to examine the association of self-reported NEP and routine healthcare utilization. NEP was assessed via a questionnaire exploring residents' neighborhood perceptions, including violence, the physical environment, and social cohesion. Routine healthcare utilization was assessed via self-reported responses regarding usual source of care and time since last routine healthcare check-up. The analytic sample (N = 1706) was 58% black, 27% white, 15% Hispanic, 42% male, and had a mean age of 51 (SD = 10.3). Analysis of NEP by tertile demonstrated that younger age, lower income, and lower education were associated with unfavorable overall NEP (p trend <0.05 for each). After adjustment for potential confounders, including neighborhood deprivation, health insurance, disease burden and psychosocial factors, we found that individuals with more unfavorable perception of their physical environment were more likely to report lack of a usual source of care (p = 0.013). Individuals with more unfavorable perception of the neighborhood physical environment or greater neighborhood violence reported longer time periods since last routine visit (p = 0.001, p = 0.034 respectively). There was no relationship between perceived social cohesion and healthcare utilization. Using a multi-ethnic cohort, we found that NEP significantly associates with report of a usual source of care and time since last routine check-up. Our findings suggest that public health professionals should prioritize improving NEP since it may act as barrier to routine preventive healthcare and ideal health outcomes.
Subject(s)
Patient Acceptance of Health Care , Perception , Social Environment , Adolescent , Adult , Aged , Cardiovascular Diseases/diagnosis , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Odds Ratio , Patient Acceptance of Health Care/statistics & numerical data , Residence Characteristics , Risk Factors , Social Class , Young AdultABSTRACT
Little is known about the spatial clustering of neighborhood deprivation across the United States (U.S.). Using data from the 2010 U.S. Census Bureau, we created a neighborhood deprivation index (NDI: higher NDI indicates higher deprivation/ lower neighborhood socioeconomic status) for each county within the U.S. County level scores were loaded into ArcGIS 10.5.1 where they were mapped and analyzed using Moran's I and Anselin Local Moran's I. Ultimately, NDI varies spatially across the US. The highest NDI scores were found in the Southeastern and Southwestern U.S. states, and inland regions of Southern California. This information is critical for public health initiative development as planners may need to tailor the scale of their efforts based on the higher NDI neighborhoods of the county or geographic region with potentially greater chronic disease burden.
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INTRODUCTION: A mixed-method, co-design approach to studying the adoption of mobile health (mHealth) technology among African-American (AA) women has not been fully explored. Qualitative data may contextualise existing knowledge surrounding perceptions of mHealth among AA women as part of formative work for designing a physical activity application (app). METHODS: A convenience sample of 16 AA women completed an informatics survey prior to participating in focus groups exploring their use of mobile technology and health apps. Survey responses provided frequency data, while iterative transcript analysis of focus groups identified themes. RESULTS: The majority of participants (mean age=62.1 years, SD=6.6) felt comfortable using a tablet/smartphone (75.0%). Most (68.8%) reported using health-related apps, primarily focused on physical activity and nutrition. Focus groups revealed four overarching concepts, including (1) user attachment, (2) technology adoption, (3) potential facilitators and (4) potential barriers. Important features which may serve as facilitators or barriers to future adoption of a mobile app for an mHealth intervention include individual app tailoring and software concerns, respectively. DISCUSSION: Thematic analysis revealed high user attachment to smartphones and described participants' process for adopting new mHealth technology. CONCLUSION: Early engagement of target end users as a part of a broader co-design and community-based participatory research process for developing mHealth technologies may be useful for sustained adoption of these tools in future mHealth behavioural interventions.
Subject(s)
Black People/statistics & numerical data , Community-Based Participatory Research , Exercise/physiology , Health Promotion , Smartphone/trends , Telemedicine/trends , Cardiovascular Diseases/prevention & control , Female , Focus Groups , Humans , Inventions , Middle Aged , Mobile Applications , Qualitative Research , Surveys and QuestionnairesABSTRACT
INTRODUCTION: Although physical activity (PA) reduces cardiovascular disease (CVD) risk, physical inactivity remains a pressing public health concern, especially among African American (AA) women in the USA. PA interventions focused on AA women living in resource-limited communities with scarce PA infrastructure are needed. Mobile health (mHealth) technology can increase access to PA interventions. We describe the development of a clinical protocol for a multilevel, community-based, mHealth PA intervention for AA women. METHODS AND ANALYSIS: An mHealth intervention targeting AA women living in resource-limited Washington, DC communities was developed based on the socioecological framework for PA. Over 6 months, we will use a Sequential Multi-Assignment, Randomized Trial approach to compare the effects on PA of location-based remote messaging (named 'tailored-to-place') to standard remote messaging in an mHealth intervention. Participants will be randomised to a remote messaging intervention for 3 months, at which point the intervention strategy will adapt based on individuals' PA levels. Those who do not meet the PA goal will be rerandomised to more intensive treatment. Participants will be followed for another 3 months to determine the contribution of each mHealth intervention to PA level. This protocol will use novel statistical approaches to account for the adaptive strategy. Finally, effects of PA changes on CVD risk biomarkers will be characterised. ETHICS AND DISSEMINATION: This protocol has been developed in partnership with a Washington, DC-area community advisory board to ensure feasibility and acceptability to community members. The National Institutes of Health Intramural IRB approved this research and the National Heart, Lung, and Blood Institute provided funding. Once published, results of this work will be disseminated to community members through presentations at community advisory board meetings and our quarterly newsletter. TRIAL REGISTRATION NUMBER: NCT03288207.
Subject(s)
Mobile Applications , Telemedicine , Adult , Aged , Exercise , Female , Humans , Middle Aged , Pregnancy , Prospective Studies , Treatment OutcomeABSTRACT
PURPOSE OF REVIEW: Limited physical activity (PA) and obesity are two primary risk factors for cardiovascular disease (CVD). Within a socio-ecological framework, neighborhood social environment may play a key role in influencing PA and obesity. However, the mechanisms underlying this relationship remain ambiguous. Our goals in this review are: (1) to summarize findings from the recent studies on neighborhood social environment in relation to PA and obesity as CVD risk factors, and (2) to briefly describe several innovative approaches to assessing neighborhood social environment. RECENT FINDINGS: Almost all recent studies assessed neighborhood social environment around residential areas. There were consistent associations between neighborhood social environment and PA and obesity, with some exceptions (indicating null associations or paradoxical associations). However, a focus on residential social environment may limit results because these studies did not account for any exposures occurring away from individuals' homes. Additionally, the majority of studies utilized a cross-sectional design, which limits our ability to make inferences regarding the causality of the association between social environment and PA or obesity as CV risk factors. SUMMARY: The majority of the studies on neighborhood social environment characterized factors around residential areas and assessed participant activity via self-reported surveys. Future research should leverage tools to account for the spatial mismatch between environmental exposures and outcomes by using global positioning systems, ecological momentary assessments, virtual neighborhood audits, and simulation modeling. These approaches can overcome major limitations by tracking individuals' daily activity and real-time perceptions of neighborhood social environments linked to CVD events.