Faculty Bibliography

BACKGROUND:People who have been incarcerated have high rates of cardiovascular risk factors, such as hypertension and smoking, and cardiovascular disease (CVD) is a leading cause of hospitalizations and mortality in this population. Despite this, little is known regarding what pathways mediate the association between incarceration exposure and increased rates of CVD morbidity and especially what incarceration specific factors are associated with this risk. The objective of this study is to better understand CVD risk in people exposed to incarceration and the pathways by which accumulate cardiovascular risk over time. METHODS AND ANALYSIS/METHODS:The Justice-Involved Individuals Cardiovascular Disease Epidemiology (JUSTICE) study is a prospective cohort study of individuals released from incarceration with known cardiovascular risk factors. We are recruiting 500 individuals within three months after release from jail/prison. At baseline we are assessing traditional risk factors for CVD, including diet, exercise, and smoking, and exposure to incarceration-related policies, psychosocial stress, and self-efficacy. Cardiovascular risk factors are measured at baseline through point of care testing. We are following these individuals for the 12 months following the index release from incarceration with re-evaluation of psychosocial factors and clinical risk factors every 6 months. Using these data, we will estimate the direct and indirect latent effects of incarceration on cardiovascular risk factors and the paths via which these effects are mediated. We will also model the anticipated 10-year burden of CVD incidence, health care use, and mortality associated with incarceration. DISCUSSION/CONCLUSIONS:Our study will identify factors associated with CVD risk factor control among people released from incarceration. Our measurement of incarceration-related exposures, psychosocial factors, and clinical measures of cardiovascular risk will allow for identification of unique targets for intervention to modify CVD risk in this vulnerable population.

BACKGROUND:Public health measures to control the COVID-19 pandemic have led to feelings of loneliness among older adults, which, prior to COVID, has been associated with subsequent morbidity and mortality. We sought to identify differences in feelings of loneliness, sadness, and social disconnection early in the pandemic across racial groups, and possible mitigating factors. METHODS:We performed a cross-sectional analysis using the weighted nationally-representative Medicare Current Beneficiaries Survey COVID-19 supplement, collected summer 2020. We included all Medicare beneficiaries aged 65 years and older who did not respond by proxy. We examined changes in loneliness, sadness, or feelings of social disconnection. Multivariable logistic regression models accounted for sociodemographic variables, access to primary care and the internet, and history of depression or dementia. RESULTS:Among 8125 beneficiaries, representative of 43.7 million Medicare beneficiaries, 22.6% reported loneliness or sadness, and 37.1% feeling socially disconnected. In fully-adjusted models, Hispanic/Latinx beneficiaries were most likely to report loneliness or sadness (OR = 1.3, CI: 1.02-1.65; p = 0.02) and Black beneficiaries were least likely to report feeling socially disconnected (OR = 0.55; CI: 0.42-0.73; p < 0.001). Internet access was associated with increased odds of both (OR = 1.29, 95 CI: 1.07-1.56; p = 0.009; and OR = 1.42, 95 CI: 1.24-1.63; p < 0.001, respectively). Access to primary care was associated with lower odds of both (OR = 0.77, 95 CI: 0.61-0.96; p = 0.02; and OR = 0.72, 95 CI: 0.61-0.87; p < 0.001). CONCLUSIONS:Loneliness, sadness, and feelings of social disconnection were common among older Medicare beneficiaries early in the COVID-19 pandemic. Differences by race/ethnicity may be driven by different living structures and social networks, and warrant further study. Policy makers and clinicians should consider facilitating connection by phone or in person, as internet access did not diminish feelings of loneliness, particularly for those living alone. Access to primary care, and tools for clinicians to address loneliness should be prioritized.

INTRODUCTION:Communities are seeking to learn if and how they can improve the well-being of their residents. We therefore examined the impact of a community-led, collective-impact initiative, deployed through Blue Zones Project by Sharecare, aimed at improving health and well-being in one set of US communities. METHODS:We used data from cross-sectional surveys of the Well-Being Index (2010-2017) to assess how the Life Evaluation Index (LEI) in Hermosa Beach, Manhattan Beach and Redondo Beach in California (Beach Cities) changed over time and how this change compares with change for similar cities (Beach Cities-like) and for the USA as a whole. We examined types of interventions, perceived impacts, and relationships between intervention type and change in LEI. RESULTS:The Beach Cities experienced greater increases in LEI than Beach Cities-like communities and the nation. The entire portfolio of interventions was positively associated with change in LEI in the Beach Cities (+1.12, p=0.012), with process-oriented interventions most closely associated with improvement. CONCLUSIONS:Community-led collective action that leverages community engagement and activation, strategic use of programming and large-scale built-environment and policy change can improve health and well-being at scale.

Importance:Black and Latinx communities have faced disproportionate harm from the COVID-19 pandemic. Increasing COVID-19 vaccine acceptance and access has the potential to mitigate mortality and morbidity from COVID-19 for all communities, including those most impacted by the pandemic. Objective:To investigate and understand factors associated with facilitating and obstructing COVID-19 vaccine access and acceptance among Black and Latinx communities. Design, Setting, and Participants:This community-partnered qualitative study conducted semistructured, in-depth focus groups with Black and Latinx participants from March 17 to March 29, 2021, using a secure video conferencing platform. Participants were recruited through emails from local community-based organizations, federally qualified health centers, social service agencies, the New Haven, Connecticut, Health Department, and in-person distribution of study information from community health workers. A total of 8 focus groups were conducted, including 4 in Spanish and 4 in English, with 72 participants from a diverse range of community roles, including teachers, custodial service workers, and health care employees, in New Haven, Connecticut. Data were analyzed from March 17 to July 30, 2021. Main Outcomes and Measures:Interviews were audio-recorded, transcribed, translated, and analyzed using an inductive content analysis approach. Themes and subthemes were identified on the acceptability and accessibility of the COVID-19 vaccine among participants who identified as Black and/or Latinx. Results:Among 72 participants, 36 (50%) identified as Black, 28 (39%) as Latinx, and 8 (11%) as Black and Latinx and 56 (78%) identified as women and 16 (22%) identified as men. Participants described 3 major themes that may represent facilitators and barriers to COVID-19 vaccinations: pervasive mistreatment of Black and Latinx communities and associated distrust; informing trust via trusted messengers and messages, choice, social support, and diversity; and addressing structural barriers to vaccination access. Conclusions and Relevance:The findings of this qualitative study may impact what health care systems, public health officials, policy makers, health care practitioners, and community leaders can do to facilitate equitable uptake of the COVID-19 vaccine. Community-informed insights are imperative to facilitating COVID-19 vaccine access and acceptance among communities hardest hit by the pandemic. Preventing the further widening of inequities and addressing structural barriers to vaccination access are vital to protecting all communities, especially Black and Latinx individuals who have experienced disproportionate death and loss from COVID-19.

BACKGROUND:Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts the mental health and general well-being of individuals and populations over time. OBJECTIVE:This study aimed to obtain information on symptoms and medical conditions self-reported by non-Twitter social media users during the COVID-19 pandemic, to determine how discussion of these symptoms and medical conditions changed over time, and to identify correlations between frequency of the top 5 commonly mentioned symptoms post and daily COVID-19 statistics (new cases, new deaths, new active cases, and new recovered cases) in the United States. METHODS:We used natural language processing (NLP) algorithms to identify symptom- and medical condition-related topics being discussed on social media between June 14 and December 13, 2020. The sample posts were geotagged by NetBase, a third-party data provider. We calculated the positive predictive value and sensitivity to validate the classification of posts. We also assessed the frequency of health-related discussions on social media over time during the study period, and used Pearson correlation coefficients to identify statistically significant correlations between the frequency of the 5 most commonly mentioned symptoms and fluctuation of daily US COVID-19 statistics. RESULTS:Within a total of 9,807,813 posts (nearly 70% were sourced from the United States), we identified a discussion of 120 symptom-related topics and 1542 medical condition-related topics. Our classification of the health-related posts had a positive predictive value of over 80% and an average classification rate of 92% sensitivity. The 5 most commonly mentioned symptoms on social media during the study period were anxiety (in 201,303 posts or 12.2% of the total posts mentioning symptoms), generalized pain (189,673, 11.5%), weight loss (95,793, 5.8%), fatigue (91,252, 5.5%), and coughing (86,235, 5.2%). The 5 most discussed medical conditions were COVID-19 (in 5,420,276 posts or 66.4% of the total posts mentioning medical conditions), unspecified infectious disease (469,356, 5.8%), influenza (270,166, 3.3%), unspecified disorders of the central nervous system (253,407, 3.1%), and depression (151,752, 1.9%). Changes in posts in the frequency of anxiety, generalized pain, and weight loss were significant but negatively correlated with daily new COVID-19 cases in the United States (r=-0.49, r=-0.46, and r=-0.39, respectively; P<.05). Posts on the frequency of anxiety, generalized pain, weight loss, fatigue, and the changes in fatigue positively and significantly correlated with daily changes in both new deaths and new active cases in the United States (r ranged=0.39-0.48; P<.05). CONCLUSIONS:COVID-19 and symptoms of anxiety were the 2 most commonly discussed health-related topics on social media from June 14 to December 13, 2020. Real-time monitoring of social media posts on symptoms and medical conditions may help assess the population's mental health status and enhance public health surveillance for infectious disease.

Physical activity and social support are associated with better outcomes after surviving acute myocardial infarction (AMI), and greater walkability has been associated with activity and support. We used data from the SILVER-AMI study (November 2014-June 2017), a longitudinal cohort of community-living adults ≥ 75 years hospitalized for AMI to assess associations of neighborhood walkability with health outcomes, and to assess whether physical activity and social support mediate this relationship, if it exists. We included data from 1345 participants who were not bedbound, were discharged home, and for whom we successfully linked walkability scores (from Walk Score®) for their home census block. Our primary outcome was hospital-free survival time (HFST) at six months after discharge; secondary outcomes included physical and mental health at six months, assessed using SF-12. Physical activity and social support were measured at baseline. Covariates included cognition, functioning, comorbidities, participation in rehabilitation or physical therapy, and demographics. We employed survival analysis to examine associations between walkability and HFST, before and after adjustment for covariates; we repeated analyses using linear regression with physical and mental health as outcomes. In adjusted models, walkability was not associated with physical health (ß = 0.010; 95% CI: -0.027, 0.047), mental health (ß = -0.08; 95% CI: -0.175, -0.013), or HFST (ß = 0.008; 95% CI: -0.023, 0.009). Social support was associated with mental health in adjusted models. Neighborhood walkability was not predictive of outcomes among older adults with existing coronary disease, suggesting that among older adults, mobility limitations may supercede neighborhood walkability.

IMPORTANCE/OBJECTIVE:The elimination of racial and ethnic differences in health status and health care access is a US goal, but it is unclear whether the country has made progress over the last 2 decades. OBJECTIVE:To determine 20-year trends in the racial and ethnic differences in self-reported measures of health status and health care access and affordability among adults in the US. DESIGN, SETTING, AND PARTICIPANTS/METHODS:Serial cross-sectional study of National Health Interview Survey data, 1999-2018, that included 596 355 adults. EXPOSURES/METHODS:Self-reported race, ethnicity, and income level. MAIN OUTCOMES AND MEASURES/METHODS:Rates and racial and ethnic differences in self-reported health status and health care access and affordability. RESULTS:The study included 596 355 adults (mean [SE] age, 46.2 [0.07] years, 51.8% [SE, 0.10] women), of whom 4.7% were Asian, 11.8% were Black, 13.8% were Latino/Hispanic, and 69.7% were White. The estimated percentages of people with low income were 28.2%, 46.1%, 51.5%, and 23.9% among Asian, Black, Latino/Hispanic, and White individuals, respectively. Black individuals with low income had the highest estimated prevalence of poor or fair health status (29.1% [95% CI, 26.5%-31.7%] in 1999 and 24.9% [95% CI, 21.8%-28.3%] in 2018), while White individuals with middle and high income had the lowest (6.4% [95% CI, 5.9%-6.8%] in 1999 and 6.3% [95% CI, 5.8%-6.7%] in 2018). Black individuals had a significantly higher estimated prevalence of poor or fair health status than White individuals in 1999, regardless of income strata (P < .001 for the overall and low-income groups; P = .03 for middle and high-income group). From 1999 to 2018, racial and ethnic gaps in poor or fair health status did not change significantly, with or without income stratification, except for a significant decrease in the difference between White and Black individuals with low income (-6.7 percentage points [95% CI, -11.3 to -2.0]; P = .005); the difference in 2018 was no longer statistically significant (P = .13). Black and White individuals had the highest levels of self-reported functional limitations, which increased significantly among all groups over time. There were significant reductions in the racial and ethnic differences in some self-reported measures of health care access, but not affordability, with and without income stratification. CONCLUSIONS AND RELEVANCE/CONCLUSIONS:In a serial cross-sectional survey study of US adults from 1999 to 2018, racial and ethnic differences in self-reported health status, access, and affordability improved in some subgroups, but largely persisted.

OBJECTIVES:Well-being is a holistic, positively framed conception of health, integrating physical, emotional, social, financial, community and spiritual aspects of life. High well-being is an intrinsically worthy goal for individuals, communities and nations. Multiple measures of well-being exist, yet we lack information to identify benchmarks, geographical disparities and targets for intervention to improve population life evaluation in the USA. DESIGN:Using data from the Gallup National Health and Well-Being Index, we conducted retrospective analyses of a series of cross-sectional samples. SETTING/PARTICIPANTS:We summarised select well-being outcomes nationally for each year, and by county (n=599) over two time periods, 2008-2012 and 2013-2017. MAIN OUTCOME MEASURES:We report percentages of people thriving, struggling and suffering using the Cantril Self-Anchoring Scale, percentages reporting high or low current life satisfaction, percentages reporting high or low future life optimism, and changes in these percentages over time. RESULTS:Nationally, the percentage of people that report thriving increased from 48.9% in 2008 to 56.3% in 2017 (p<0.05). The percentage suffering was not significantly different over time, ranging from 4.4% to 3.2%. In 2013-2017, counties with the highest life evaluation had a mean 63.6% thriving and 2.3% suffering while counties with the lowest life evaluation had a mean 49.5% thriving and 6.5% suffering, with counties experiencing up to 10% suffering, threefold the national average. Changes in county-level life evaluation also varied. While counties with the greatest improvements experienced 10%-15% increase in the absolute percentage thriving or 3%-5% decrease in absolute percentage suffering, most counties experienced no change and some experienced declines in life evaluation. CONCLUSIONS:The percentage of the US population thriving increased from 2008 to 2017 while the percentage suffering remained unchanged. Marked geographical variation exists indicating priority areas for intervention.

BACKGROUND:COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. OBJECTIVE:The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic. METHODS:Natural language processing (NLP) algorithms were used to identify COVID-19-related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States. RESULTS:The final sample size included 9,065,733 posts, 70% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69%), compared with COVID-19 in general (n=3,390,139, 37%) and COVID-19 public health measures (n=1,836,200, 20%). CONCLUSIONS:There was a decline in COVID-19-related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue.