Health and Economic Value of Eliminating Socioeconomic Disparities in US Youth Physical Activity.

Importance: There are considerable socioeconomic status (SES) disparities in youth physical activity (PA) levels. For example, studies show that lower-SES youth are less active, have lower participation in organized sports and physical education classes, and have more limited access to PA equipment. Objective: To determine the potential public health and economic effects of eliminating disparities in PA levels among US youth SES groups. Design and Setting: An agent-based model representing all 6- to 17-year-old children in the US was used to simulate the epidemiological, clinical, and economic effects of disparities in PA levels among different SES groups and the effect of reducing these disparities. Main Outcomes and Measures: Anthropometric measures (eg, body mass index) and the presence and severity of risk factors associated with weight (stroke, coronary heart disease, type 2 diabetes, or cancer), as well as direct and indirect cost savings. Results: This model, representing all 50 million US children and adolescents 6 to 17 years old, found that if the US eliminates the disparity in youth PA levels across SES groups, absolute overweight and obesity prevalence would decrease by 0.826% (95% CI, 0.821%-0.832%), resulting in approximately 383 000 (95% CI, 368 000-399 000) fewer cases of overweight and obesity and 101 000 (95% CI, 98 000-105 000) fewer cases of weight-related diseases (stroke and coronary heart disease events, type 2 diabetes, or cancer). This would result in more than $15.60 (95% CI, $15.01-$16.10) billion in cost savings over the youth cohort's lifetime. There are meaningful benefits even when reducing the disparity by just 25%, which would result in $1.85 (95% CI, $1.70-$2.00) billion in direct medical costs averted and $2.48 (95% CI, $2.04-$2.92) billion in productivity losses averted. For every 1% in disparity reduction, total productivity losses would decrease by about $83.8 million, and total direct medical costs would decrease by about $68.7 million. Conclusions and Relevance: This study quantified the potential savings from eliminating or reducing PA disparities, which can help policymakers, health care systems, schools, funders, sports organizations, and other businesses better prioritize investments toward addressing these disparities.

A Mixed-Methods Study of Social Determinants and Self-care in Adults With Heart Failure.

BACKGROUND: The burden of heart failure (HF) is unequally distributed among population groups. Few study authors have described social determinants of health (SDoH) enabling/impeding self-care. AIM: The aim of this study was to explore the relationship between SDoH and self-care in patients with HF. METHODS: Using a convergent mixed-methods design, we assessed SDoH and self-care in 104 patients with HF using the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) and the Self-Care of HF Index v7.2 with self-care maintenance, symptom perception, and self-care management scales. Multiple regression was used to assess the relationship between SDoH and self-care. One-on-one in-depth interviews were conducted in patients with poor (standardized score ≤ 60, n = 17) or excellent (standardized score ≥ 80, n = 20) self-care maintenance. Quantitative and qualitative results were integrated. RESULTS: Participants were predominantly male (57.7%), with a mean age of 62.4 ± 11.6 years, with health insurance (91.4%) and some college education (62%). Half were White (50%), many were married (43%), and most reported adequate income (53%). The money and resources core domain of PRAPARE significantly predicted self-care maintenance ( P = .019), and symptom perception ( P = .049) trended significantly after adjusting for other PRAPARE core domains (personal characteristics, family and home, and social and emotional health) and comorbidity. Participants discussed social connectedness, health insurance coverage, individual upbringing, and personal experiences as facilitators of self-care behavior. CONCLUSION: Several SDoH influence HF self-care. Patient-specific interventions that address the broader effects of these factors may promote self-care in patients with HF.

Social determinants of health, health disparities, and adiposity.

Social determinants of health (SDoH), or the socioeconomic, environmental, and psychosocial conditions in which individuals spend their daily lives, substantially influence obesity as a cardiovascular disease (CVD) risk factor. The coronavirus disease 2019 (COVID-19) pandemic highlighted the converging epidemics of obesity, CVD, and social inequities globally. Obesity and CVD serve as independent risk factors for COVID-19 severity and lower-resourced populations most impacted by adverse SDoH have the highest COVID-19 mortality rates. Better understanding the interplay between social and biologic factors that contribute to obesity-related CVD disparities are important to equitably address obesity across populations. Despite efforts to investigate SDoH and their biologic effects as drivers of health disparities, the connections between SDoH and obesity remain incompletely understood. This review aims to highlight the relationships between socioeconomic, environmental, and psychosocial factors and obesity. We also present potential biologic factors that may play a role in the biology of adversity, or link SDoH to adiposity and poor adipo-cardiology outcomes. Finally, we provide evidence for multi-level obesity interventions targeting multiple aspects of SDoH. Throughout, we emphasize areas for future research to tailor health equity-promoting interventions across populations to reduce obesity and obesity-related CVD disparities.

By what molecular mechanisms do social determinants impact cardiometabolic risk?

While it is well known from numerous epidemiologic investigations that social determinants (socioeconomic, environmental, and psychosocial factors exposed to over the life-course) can dramatically impact cardiovascular health, the molecular mechanisms by which social determinants lead to poor cardiometabolic outcomes are not well understood. This review comprehensively summarizes a variety of current topics surrounding the biological effects of adverse social determinants (i.e., the biology of adversity), linking translational and laboratory studies with epidemiologic findings. With a strong focus on the biological effects of chronic stress, we highlight an array of studies on molecular and immunological signaling in the context of social determinants of health (SDoH). The main topics covered include biomarkers of sympathetic nervous system and hypothalamic-pituitary-adrenal axis activation, and the role of inflammation in the biology of adversity focusing on glucocorticoid resistance and key inflammatory cytokines linked to psychosocial and environmental stressors (PSES). We then further discuss the effect of SDoH on immune cell distribution and characterization by subset, receptor expression, and function. Lastly, we describe epigenetic regulation of the chronic stress response and effects of SDoH on telomere length and aging. Ultimately, we highlight critical knowledge gaps for future research as we strive to develop more targeted interventions that account for SDoH to improve cardiometabolic health for at-risk, vulnerable populations.

The Impact of a Place-Tailored Digital Health App Promoting Exercise Classes on African American Women's Physical Activity and Obesity: Simulation Study.

BACKGROUND: The increasing prevalence of smartphone apps to help people find different services raises the question of whether apps to help people find physical activity (PA) locations would help better prevent and control having overweight or obesity. OBJECTIVE: The aim of this paper is to determine and quantify the potential impact of a digital health intervention for African American women prior to allocating financial resources toward implementation. METHODS: We developed our Virtual Population Obesity Prevention, agent-based model of Washington, DC, to simulate the impact of a place-tailored digital health app that provides information about free recreation center classes on PA, BMI, and overweight and obesity prevalence among African American women. RESULTS: When the app is introduced at the beginning of the simulation, with app engagement at 25% (eg, 25% [41,839/167,356] of women aware of the app; 25% [10,460/41,839] of those aware downloading the app; and 25% [2615/10,460] of those who download it receiving regular push notifications), and a 25% (25/100) baseline probability to exercise (eg, without the app), there are no statistically significant increases in PA levels or decreases in BMI or obesity prevalence over 5 years across the population. When 50% (83,678/167,356) of women are aware of the app; 58.23% (48,725/83,678) of those who are aware download it; and 55% (26,799/48,725) of those who download it receive regular push notifications, in line with existing studies on app usage, introducing the app on average increases PA and decreases weight or obesity prevalence, though the changes are not statistically significant. When app engagement increased to 75% (125,517/167,356) of women who were aware, 75% (94,138/125,517) of those who were aware downloading it, and 75% (70,603/94,138) of those who downloaded it opting into the app's push notifications, there were statistically significant changes in PA participation, minutes of PA and obesity prevalence. CONCLUSIONS: Our study shows that a digital health app that helps identify recreation center classes does not result in substantive population-wide health effects at lower levels of app engagement. For the app to result in statistically significant increases in PA and reductions in obesity prevalence over 5 years, there needs to be at least 75% (125,517/167,356) of women aware of the app, 75% (94,138/125,517) of those aware of the app download it, and 75% (70,603/94,138) of those who download it opt into push notifications. Nevertheless, the app cannot fully overcome lack of access to recreation centers; therefore, public health administrators as well as parks and recreation agencies might consider incorporating this type of technology into multilevel interventions that also target the built environment and other social determinants of health.

Use of a community advisory board to build equitable algorithms for participation in clinical trials: a protocol paper for HoPeNET.

INTRODUCTION: Participation from racial and ethnic minorities in clinical trials has been burdened by issues surrounding mistrust and access to healthcare. There is emerging use of machine learning (ML) in clinical trial recruitment and evaluation. However, for individuals from groups who are recipients of societal biases, utilisation of ML can lead to the creation and use of biased algorithms. To minimise bias, the design of equitable ML tools that advance health equity could be guided by community engagement processes. The Howard University Partnership with the National Institutes of Health for Equitable Clinical Trial Participation for Racial/Ethnic Communities Underrepresented in Research (HoPeNET) seeks to create an ML-based infrastructure from community advisory board (CAB) experiences to enhance participation of African-Americans/Blacks in clinical trials. METHODS AND ANALYSIS: This triphased cross-sectional study (24 months, n=56) will create a CAB of community members and research investigators. The three phases of the study include: (1) identification of perceived barriers/facilitators to clinical trial engagement through qualitative/quantitative methods and systems-based model building participation; (2) operation of CAB meetings and (3) development of a predictive ML tool and outcome evaluation. Identified predictors from the participant-derived systems-based map will be used for the ML tool development. ETHICS AND DISSEMINATION: We anticipate minimum risk for participants. Institutional review board approval and informed consent has been obtained and patient confidentiality ensured.

Geospatial Analysis of Neighborhood Environmental Stress in Relation to Biological Markers of Cardiovascular Health and Health Behaviors in Women: Protocol for a Pilot Study.

BACKGROUND: Innovative analyses of cardiovascular (CV) risk markers and health behaviors linked to neighborhood stressors are essential to further elucidate the mechanisms by which adverse neighborhood social conditions lead to poor CV outcomes. We propose to objectively measure physical activity (PA), sedentary behavior, and neighborhood stress using accelerometers, GPS, and real-time perceived ecological momentary assessment via smartphone apps and to link these to biological measures in a sample of White and African American women in Washington, DC, neighborhoods. OBJECTIVE: The primary aim of this study is to test the hypothesis that living in adverse neighborhood social conditions is associated with higher stress-related neural activity among 60 healthy women living in high or low socioeconomic status neighborhoods in Washington, DC. Sub-aim 1 of this study is to test the hypothesis that the association is moderated by objectively measured PA using an accelerometer. A secondary objective is to test the hypothesis that residing in adverse neighborhood social environment conditions is related to differences in vascular function. Sub-aim 2 of this study is to test the hypothesis that the association is moderated by objectively measured PA. The third aim of this study is to test the hypothesis that adverse neighborhood social environment conditions are related to differences in immune system activation. METHODS: The proposed study will be cross-sectional, with a sample of at least 60 women (30 healthy White women and 30 healthy Black women) from Wards 3 and 5 in Washington, DC. A sample of the women (n=30) will be recruited from high-income areas in Ward 3 from census tracts within a 15% of Ward 3's range for median household income. The other participants (n=30) will be recruited from low-income areas in Wards 5 from census tracts within a 15% of Ward 5's range for median household income. Finally, participants from Wards 3 and 5 will be matched based on age, race, and BMI. Participants will wear a GPS unit and accelerometer and report their stress and mood in real time using a smartphone. We will then examine the associations between GPS-derived neighborhood variables, stress-related neural activity measures, and adverse biological markers. RESULTS: The National Institutes of Health Institutional Review Board has approved this study. Recruitment will begin in the summer of 2021. CONCLUSIONS: Findings from this research could inform the development of multilevel behavioral interventions and policies to better manage environmental factors that promote immune system activation or psychosocial stress while concurrently working to increase PA, thereby influencing CV health. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/29191.