Faculty Bibliography

Background Disparities in cardiovascular disease (CVD) outcomes persist across the United States. Social determinants of health play an important role in driving these disparities. The current study aims to identify the most important social determinants associated with CVD mortality over time in US counties. Methods and Results The authors used the Agency for Healthcare Research and Quality's database on social determinants of health and linked it with CVD mortality data at the county level from 2009 to 2018. The age-standardized CVD mortality rate was measured as the number of deaths per 100 000 people. Penalized generalized estimating equations were used to select social determinants associated with county-level CVD mortality. The analytic sample included 3142 counties. The penalized generalized estimating equation identified 17 key social determinants of health including rural-urban status, county's racial composition, income, food, and housing status. Over the 10-year period, CVD mortality declined at an annual rate of 1.08 (95% CI, 0.74-1.42) deaths per 100 000 people. Rural counties and counties with a higher percentage of Black residents had a consistently higher CVD mortality rate than urban counties and counties with a lower percentage of Black residents. The rural-urban CVD mortality gap did not change significantly over the past decade, whereas the association between the percentage of Black residents and CVD mortality showed a significant diminishing trend over time. Conclusions County-level CVD mortality declined from 2009 through 2018. However, rural counties and counties with a higher percentage of Black residents continued to experience higher CVD mortality. Median income, food, and housing status consistently predicted higher CVD mortality.

Objective: To compare hospitalization rates between African American (AA) and European American (EA) deceased-donor (DD) kidney transplant (KT) recipients during over a10-year period. Method: Data from the Scientific Registry of Transplant Recipients and social determinants of health (SDoH), measured by the Social Deprivation Index, were used. Hospitalization rates were estimated for kidney recipients from AA and EA DDs who had one kidney transplanted into an AA and one into an EA, leading to four donor/recipient pairs (DRPs): AA/AA, AA/EA, EA/AA, and EA/EA. Poisson-Gamma models were fitted to assess post-transplant hospitalizations. Result: Unadjusted hospitalization rates (95% confidence interval) were higher among all DRP involving AA, 131.1 (122.5, 140.3), 134.8 (126.3, 143.8), and 102.4 (98.9, 106.0) for AA/AA, AA/EA, and EA/AA, respectively, compared to 97.1 (93.7, 100.6) per 1000 post-transplant person-years for EA/EA pairs. Multivariable analysis showed u-shaped relationships across SDoH levels within each DRP, but findings varied depending on recipients"™ race, i.e., AA recipients in areas with the worst SDoH had higher hospitalization rates. However, EA recipients in areas with the best SDoH had higher hospitalization rates than their counterparts. Conclusions: Relationship between healthcare utilization and SDoH depends on DRP, with higher hospitalization rates among AA recipients living in areas with the worst SDoH and among EA recipients in areas with the best SDoH profiles. SDoH plays an important role in driving disparities in hospitalizations after kidney transplantation.

BACKGROUND:Hypertension has been identified as a risk factor of dementia, but most randomized trials did not show efficacy in reducing the risk of dementia. Midlife hypertension may be a target for intervention, but it is infeasible to conduct a trial initiating antihypertensive medication from midlife till dementia occurs late life. OBJECTIVE:We aimed to emulate a target trial to estimate the effectiveness of initiating antihypertensive medication from midlife on reducing incident dementia using observational data. METHODS:The Health and Retirement Study from 1996 to 2018 was used to emulate a target trial among non-institutional dementia-free subjects aged 45 to 65 years. Dementia status was determined using algorithm based on cognitive tests. Individuals were assigned to initiating antihypertensive medication or not, based on the self-reported use of antihypertensive medication at baseline in 1996. Observational analog of intention-to-treat and per-protocol effects were conducted. Pooled logistic regression models with inverse-probability of treatment and censoring weighting using logistic regression models were applied, and risk ratios (RRs) were calculated, with 200 bootstrapping conducted for the 95% confidence intervals (CIs). RESULTS:A total of 2,375 subjects were included in the analysis. After 22 years of follow-up, initiating antihypertensive medication reduced incident dementia by 22% (RR = 0.78, 95% CI: 0.63, 0.99). No significant reduction of incident dementia was observed with sustained use of antihypertensive medication. CONCLUSION/CONCLUSIONS:Initiating antihypertensive medication from midlife may be beneficial for reducing incident dementia in late life. Future studies are warranted to estimate the effectiveness using large samples with improved clinical measurements.

INTRODUCTION:This study aimed to estimate the direct medical costs and out-of-pocket (OOP) expenses associated with inpatient and outpatient care for IHD, based on types of health insurance. Additionally, we sought to identify time trends and factors associated with these costs using an all-payer health claims database among urban patients with IHD in Guangzhou City, Southern China. METHODS:Data were collected from the Urban Employee-based Basic Medical Insurance (UEBMI) and the Urban Resident-based Basic Medical Insurance (URBMI) administrative claims databases in Guangzhou City from 2008 to 2012. Direct medical costs were estimated in the entire sample and by types of insurance separately. Extended Estimating Equations models were employed to identify the potential factors associated with the direct medical costs including inpatient and outpatient care and OOP expenses. RESULTS:< 0.001). CONCLUSIONS:The direct medical costs and OOP expenses for patients with IHD in China were found to be high and varied between two medical insurance schemes. The type of insurance was significantly associated with direct medical costs and OOP expenses of IHD.

BACKGROUND/UNASSIGNED:We aimed to evaluate the effectiveness of a community-based integrative programme in reducing hypertension incidence among populations at high risk for hypertension in Shanghai, Eastern China. METHODS/UNASSIGNED:We conducted a cluster-randomized intervention trial with a total of 607 participants (intervention, n = 303; control, n = 304) between October 2019 and October 2020. A total of 605 participants (intervention, n = 302; control, n = 303) completed the follow-up survey. The intervention group received an integrative programme that included health education, physician follow-up, and self-management, while the control group received usual care only. We used questionnaires to investigate risk factors, knowledge, attitudes, and behaviours regarding hypertension prevention for all participants at baseline and follow-up. We measured the incidence of hypertension according to the predefined protocol based on the national definition during the four follow-ups (only applicable to the intervention group) and the physical examination at the end of the intervention/programme/study. The difference-in-difference (DID) effects of the intervention were estimated using Generalized Estimating Equations. RESULTS/UNASSIGNED:There were no significant differences in age group, gender, and educational level between intervention and control groups at baseline. The integrative programme reduced the incidence of hypertension in the intervention group compared to the control group (odds ratio (OR) = 0.27, 95% confidence interval (CI) = 0.12-0.61). The DID analysis found that the one-year intervention has improved the level of hypertension-related knowledge and attitudes regarding diagnostic criteria, complications of hypertension, and lifestyle modification (P < 0.05). The intervention was also associated with a 3.7% increase in the behaviour change rate of "not smoking" (OR = 2.50, 95% CI = 1.45-4.30) and a 34.8% increase in the rate of "monitoring blood pressure regularly" (OR = 29.61, 95% CI = 13.02-67.35). CONCLUSIONS/UNASSIGNED:The integrative programme could reduce the risk for hypertension and improve the level of hypertension-related knowledge and attitudes, affecting the formation of healthy behaviours in high-risk populations. The community-based management for high-risk groups should be scaled up and incorporated into national hypertension control programmes, which may potentially reduce the substantial burden of hypertension and cardiovascular disease in China. REGISTRATION/UNASSIGNED:ISRCTN registration number: ISRCTN74154693.

Background Peripheral artery disease (PAD) affects >10 million people in the United States. PAD is associated with poor outcomes, including premature death. Machine learning (ML) has been increasingly used on big data to predict clinical outcomes. This study aims to develop ML models to predict in-hospital mortality in patients hospitalized for PAD based on a national database. Methods and Results Inpatient hospitalization data were obtained from the 2016 to 2019 National Inpatient Sample. A total of 150 921 inpatients were identified with a primary diagnosis of PAD and PAD-related procedures using codes of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS). Four ML models, including logistic regression, random forest, light gradient boosting, and extreme gradient boosting models, were trained to predict the risk of in-hospital death based on a selection of variables, including patient characteristics, comorbidities, procedures, and hospital-related factors. In-hospital mortality occurred in 1.8% of patients. The performance of the 4 models was comparable, with the area under the receiver operating characteristic curve ranging from 0.83 to 0.85, sensitivity of 77% to 82%, and specificity of 72% to 75%. These results suggest adequate predictability for clinical decision-making. In all 4 models, the total number of diagnoses and procedures, age, endovascular revascularization procedure, congestive heart failure, diabetes, and diabetes with complications were critical predictors of in-hospital mortality. Conclusions This study demonstrates the feasibility of ML in predicting in-hospital mortality in patients with a primary PAD diagnosis. Findings highlight the potential of ML models in identifying high-risk patients for poor outcomes and guiding personalized intervention.

The COVID-19 pandemic has precipitated broad and extensive changes in the way people live and work. While the general subject of working from home has recently drawn increased attention, few studies have assessed gender differences in vulnerability to the potential mental health effects of working from home. Using data from 1,585 workers who participated in the Health, Ethnicity, and Pandemic (HEAP) study, a national survey conducted in the U.S. during the COVID-19 pandemic in October 2020, associations of working from home with psychological distress were examined with weighted logistic regression among 1,585 workers and stratified by gender. It was found that workers who worked from home had higher odds of psychological distress (aOR and 95% CI = 2.62 [1.46, 4.70]) compared to workers who did not work from home, adjusting for demographic factors, socioeconomic status, and health behaviors. In gender-stratified analyses, this positive association between working from home and psychological distress was significant in women (aOR and 95% CI = 3.68 [1.68, 8.09]) but not in men. These results have implications for female workers' mental health in the transition towards working from home in the COVID-19 pandemic era.

BACKGROUND:While hate crimes rose during the COVID-19 pandemic, few studies examined whether this pandemic-time racial discrimination has led to negative health consequences at the population level. OBJECTIVE:We examined whether experienced and perceived racial discrimination were associated with mental or behavioral health outcomes during the pandemic. DESIGN/METHODS:In October 2020, we conducted a national survey with minorities oversampled that covered respondents' sociodemographic background and health-related information. PARTICIPANTS/METHODS:A total of 2709 participants responded to the survey (response rate: 4.2%). MAIN MEASURES/METHODS:The exposure variables included (1) experienced and encountered racial discrimination, (2) experienced racial and ethnic cyberbullying, and (3) perceived racial bias. Mental health outcomes were measured by psychological distress and self-rated happiness. Measures for behavioral health included sleep quality, change in cigarette smoking, and change in alcohol consumption. Weighted logistic regressions were performed to estimate the associations between the exposure variables and the outcomes, controlling for age, gender, race and ethnicity, educational attainment, household income, eligibility to vote, political party, COVID-19 infection, and geographic region. Separate regressions were performed in the six racial and ethnic subgroups: non-Hispanic White, non-Hispanic Black, Hispanic, East Asian, South Asian, and Southeast Asian respondents. KEY RESULTS/RESULTS:Experienced racial discrimination was associated with higher likelihood of psychological distress (adjusted odds ratio [AOR] = 2.18, 95% confidence interval [95% CI]: 1.34-3.55). Experienced racial discrimination (AOR = 2.31, 95% CI: 1.34-3.99) and perceived racial bias (AOR = 1.05, 95% CI: 1.00-1.09) were both associated with increased cigarette smoking. The associations between racial discrimination and mental distress and substance use were most salient among Black, East Asian, South Asian, and Hispanic respondents. CONCLUSIONS:Racial discrimination may be associated with higher likelihood of distress, and cigarette smoking among racial and ethnic minorities. Addressing racial discrimination is important for mitigating negative mental and behavioral health ramifications of the pandemic.

BACKGROUND AND AIMS/OBJECTIVE:Heart failure (HF) patients are at risk of developing type 2 diabetes. This study examined the association between adherence to the Dietary Approaches to Stop Hypertension (DASH) diet and insulin resistance among U.S. adults with HF. METHODS AND RESULTS/RESULTS:Using data from National Health and Nutrition Examination Survey 1999-2016 cycles, we included 348 individuals aged 20+ years with HF and no history of diabetes. DASH diet adherence index quartile 1 indicated the lowest and quartile 4 indicated the highest adherence. The highest level of insulin resistance was defined by the upper tertile of the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). Associations between level of insulin resistance and DASH diet adherence and its linear trends were examined using logistic regressions. Trend analyses showed that participants in upper DASH diet adherence index quartiles were more likely older, female, non-Hispanic White, of normal weight, and had lower levels of fasting insulin than those in lower quartiles. Median values of HOMA-IR from lowest to highest DASH diet adherence index quartiles were 3.1 (interquartile range, 1.8-5.5), 2.9 (1.7-5.6), 2.1 (1.1-3.7), and 2.1 (1.3-3.5). Multivariable logistic analyses indicated that participants with the highest compared to the lowest DASH adherence showed 77.1% lower odds of having the highest level of insulin resistance (0.229, 95% confidence interval: 0.073-0.716; p = 0.017 for linear trend). CONCLUSION/CONCLUSIONS:Good adherence to the DASH diet was associated with lower insulin resistance among community-dwelling HF patients. Heart healthy dietary patterns likely protect HF patients from developing type 2 diabetes.

Racial discrimination has intensified in the U.S. during the COVID-19 pandemic, but how it disrupted healthcare is largely unknown. This study investigates the association of racial discrimination with delaying or forgoing care during the pandemic based on data from a nationally representative survey, the Health, Ethnicity and Pandemic (HEAP) study (n = 2552) conducted in October 2020 with Asians, Hispanics and non-Hispanic Blacks oversampled. Racial discrimination during the pandemic was assessed in three domains: experienced racial discrimination, race-related cyberbullying, and Coronavirus racial bias beliefs. Respondents answered whether they had delayed or forgone any type of healthcare due to the pandemic. Overall, 63.7% of respondents reported delaying or forgoing any healthcare during the pandemic. About 20.3% East/Southeast Asians, 18.6% non-Hispanic Blacks and 15.9% Hispanics reported experiences of racial discrimination, compared with 2.8% of non-Hispanic Whites. Experienced racial discrimination was associated with delaying/forgoing care among non-Hispanic Blacks (Adjusted odds ratios[AOR] = 4.58, 95% confidence interval[CI]: 2.22-9.45), Hispanics (AOR = 3.88, 95%CI: 1.51-9.98), and East/Southeast Asians (AOR = 2.14, 95%CI: 1.22-3.77). Experiencing race-related cyberbullying was significantly associated with delaying/forgoing care among non-Hispanic Blacks (AOR = 1.34, 95%CI: 1.02-1.77) and East/Southeast Asians (AOR = 1.51, 95%CI: 1.19-1.90). Coronavirus racial bias was significantly associated with delaying/forgoing care among East/Southeast Asians (AOR = 1.55, 95%CI: 1.16-2.07). The three domains of racial discrimination were consistently associated with delayed or forgone health care among East/Southeast Asians during the COVID-19 pandemic; some of the associations were also seen among non-Hispanic Blacks and Hispanics. These results demonstrate that addressing racism is important for reducing disparities in healthcare delivery during the pandemic and beyond.