Faculty Bibliography

BACKGROUND:Studies have examined the association between dual sensory impairment and late-life cognitive outcomes in the U.S with inconsistent findings. OBJECTIVE:To examine the associations between sensory impairment and 10-year risk of dementia or Alzheimer's disease among U.S. adults aged ≥ 50. METHODS:A prospective cohort study based on the Health and Retirement Study from 2010 to 2020. Individuals aged ≥ 50 years without self-reported dementia and Alzheimer's disease in 2010 were included in the analysis. Self-reported visual and hearing impairments were measures in 2010. Main failure events included self-reported incident dementia and Alzheimer's disease over a 10-year follow-up period. Participants were categorized as having no visual or hearing impairment, visual impairment only, hearing impairment only, and dual sensory impairment. Fine-Gray competing risk regression model was applied to estimate the associations of sensory impairment with incident dementia and Alzheimer's disease, adjusted for demographic characteristics, health behaviors, and health conditions at baseline. RESULTS:Of 20,248 identified individuals, 14.6% had visual impairment only, 11.2% had hearing impairment only, and 9.1% had dual impairment at baseline. After adjusting for all covariates, dual sensory impairment was associated with higher risk of dementia (HR = 1.46, 95% CI: 1.23-1.73) and Alzheimer's disease (HR = 1.35, 95% CI: 1.03-1.76). Visual impairment only was also associated with incident dementia and Alzheimer's disease among individuals <65 years. CONCLUSION/CONCLUSIONS:Older adults in the U.S. with visual and hearing impairments simultaneously had a particularly greater risk of dementia and Alzheimer's disease, indicating the needs of targeted screening for timely treatment and further prevention of dementia and Alzheimer's disease.

BACKGROUND/UNASSIGNED:Telehealth has emerged as an effective tool for managing common chronic conditions such as hypertension, especially during the COVID-19 pandemic. However, the impact of state telehealth payment and coverage parity laws on hypertension medication adherence remains uncertain. METHODS/UNASSIGNED:Data from the 2016 to 2021 Merative MarketScan Commercial Claims and Encounters Database were used to construct the study cohort, which included nonpregnant individuals aged 25 to 64 years with hypertension. We coded telehealth parity laws related to hypertension management in all 50 US states and the District of Columbia, distinguishing between payment and coverage parity laws. The primary outcomes were measures of antihypertension medication adherence: the average medication possession ratio; medication adherence (medication possession ratio ≥80%); and average number of days of drug supply. We used a generalized difference-in-differences design to examine the impact of these laws. RESULTS/UNASSIGNED:Among 353 220 individuals (mean [SD] age, 49.5 (7.1) years; female, 45.55%), states with payment parity laws were significantly linked to increased average medication possession ratio by 0.43 percentage point (95% CI, 0.07-0.79), and an increase of 0.46 percentage point (95% CI, 0.06-0.92) in the probability of medication adherence. Payment parity laws also led to an average increase of 2.14 days (95% CI, 0.11-4.17) in prescription supply, after controlling for state-fixed effects, year-fixed effects, individual sociodemographic characteristics and state time-varying covariates including unemployment rates, gross domestic product per capita, and poverty rates. In contrast, coverage parity laws were associated with a 2.13-day increase (95% CI, 0.19-4.07) in days of prescription supply but did not significantly increase the average medication possession ratio or probability of medication adherence. CONCLUSIONS/UNASSIGNED:State telehealth payment parity laws were significantly associated with greater medication adherence, whereas coverage parity laws were not. With the increasing adoption of telehealth parity laws across states, these findings may support policymakers in understanding potential implications on management of hypertension.

BACKGROUND:Medicare supplement insurance, or Medigap, covers 21% of Medicare beneficiaries. Despite offsetting some out-of-pocket (OOP) expenses, remaining OOP costs may pose a barrier to medication adherence. This study aims to evaluate how OOP costs and insurance plan types influence medication adherence among beneficiaries covered by Medicare supplement plans. METHODS:We conducted a retrospective analysis of the Merative MarketScan Medicare Supplement Database (2017-2019) in Medigap enrollees (≥65 years) with hypertension. The proportion of days covered (PDC) was a continuous measure of medication adherence and was also dichotomized (PDC ≥0.8) to quantify adequate adherence. Beta-binomial and logistic regression models were used to estimate associations between these outcomes and insurance plan type and log-transformed OOP costs, adjusting for patient characteristics. RESULTS:Among 27,407 patients with hypertension, the average PDC was 0.68 ± 0.31; 47.5% achieved adequate adherence. A mean $1 higher in 30-day OOP costs were associated with a 0.06 (95% confidence intervals [CIs]: -0.09 to -0.03) lower probability of adequate adherence, or a 5% (95% CI: 4%-7%) decrease in PDC. Compared with comprehensive plan enrollees, the odds of adequate adherence were lower among those with point-of-service plans (odds ratio [OR]: 0.69, 95% CI: 0.62-0.77), but higher among those with preferred provider organization (PPO) plans (OR: 1.08, 95% CI: 1.01-1.15). Moreover, the association between OOP costs and PDC was significantly greater for PPO enrollees. CONCLUSIONS:While Medicare supplement insurance alleviates some OOP costs, different insurance plans and remaining OOP costs influence medication adherence. Reducing patient cost-sharing may improve medication adherence.

IMPORTANCE/UNASSIGNED:Economic policies have the potential to impact management and control of hypertension. OBJECTIVES/UNASSIGNED:To review the evidence on the association between economic policies and hypertension management and control among adults with hypertension in the US. EVIDENCE REVIEW/UNASSIGNED:A search was carried out of PubMed/MEDLINE, Cochrane Library, Embase, PsycINFO, CINAHL, EconLit, Sociological Abstracts, and Scopus from January 1, 2000, through November 1, 2023. Included were randomized clinical trials, difference-in-differences, and interrupted time series studies that evaluated the association of economic policies with hypertension management. Economic policies were grouped into 3 categories: insurance coverage expansion such as Medicaid expansion, cost sharing in health care such as increased drug copayments, and financial incentives for quality such as pay-for-performance. Antihypertensive treatment was measured as taking antihypertensive medications or medication adherence among those who have a hypertension diagnosis; and hypertension control, measured as blood pressure (BP) lower than  140/90 mm Hg or a reduction in BP. Evidence was extracted and synthesized through dual review of titles, abstracts, full-text articles, study quality, and policy effects. FINDINGS/UNASSIGNED:In total, 31 articles were included. None of the studies examined economic policies outside of the health care system. Of these, 16 (52%) assessed policies for insurance coverage expansion, 8 (26%) evaluated policies related to patient cost sharing for prescription drugs, and 7 (22%) evaluated financial incentive programs for improving health care quality. Of the 16 studies that evaluated coverage expansion policies, all but 1 found that policies such as Medicare Part D and Medicaid expansion were associated with significant improvement in antihypertensive treatment and BP control. Among the 8 studies that examined patient cost sharing, 4 found that measures such as prior authorization and increased copayments were associated with decreased adherence to antihypertensive medication. Finally, all 7 studies evaluating financial incentives aimed at improving quality found that they were associated with improved antihypertensive treatment and BP control. Overall, most studies had a moderate or low risk of bias in their policy evaluation. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The findings of this systematic review suggest that economic policies aimed at expanding insurance coverage or improving health care quality successfully improved medication use and BP control among US adults with hypertension. Future research is needed to investigate the potential effects of non-health care economic policies on hypertension control.

INTRODUCTION/BACKGROUND:Home blood pressure monitoring is more convenient and effective than clinic-based monitoring in diagnosing and managing hypertension. Despite its effectiveness, there is limited evidence of the economic impact of home blood pressure monitoring. This study aims to fill this research gap by assessing the health and economic impact of adopting home blood pressure monitoring among adults with hypertension in the U.S. METHODS:A previously developed microsimulation model of cardiovascular disease was used to estimate the long-term impact of adopting home blood pressure monitoring versus usual care on myocardial infarction, stroke, and healthcare costs. Data from the 2019 Behavioral Risk Factor Surveillance System and the published literature were used to estimate model parameters. The averted cases of myocardial infarction and stroke and healthcare cost savings were estimated among the U.S. adult population with hypertension and in subpopulations defined by sex, race, ethnicity, and rural/urban area. The simulation analyses were conducted between February and August 2022. RESULTS:Compared with usual care, adopting home blood pressure monitoring was estimated to reduce myocardial infarction cases by 4.9% and stroke cases by 3.8% as well as saving an average of $7,794 in healthcare costs per person over 20 years. Non-Hispanic Blacks, women, and rural residents had more averted cardiovascular events and greater cost savings related to adopting home blood pressure monitoring compared with non-Hispanic Whites, men, and urban residents. CONCLUSIONS:Home blood pressure monitoring could substantially reduce the burden of cardiovascular disease and save healthcare costs in the long term, and the benefits could be more pronounced in racial and ethnic minority groups and those living in rural areas. These findings have important implications in expanding home blood pressure monitoring for improving population health and reducing health disparities.

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.

BACKGROUND:Epidemiological evidence on different classes of antihypertensives and risks of Alzheimer's disease and related dementias (ADRD) is inconclusive and limited. This study examined the association between antihypertensive use (including therapy type and antihypertensive class) and ADRD diagnoses among older adults with hypertension. METHODS:A retrospective, cross-sectional study was conducted, involving 539 individuals aged ≥ 65 years who used antihypertensives and had ADRD diagnosis selected from 2013 to 2018 Medical Expenditure Panel Survey (MEPS) data. The predictors were therapy type (monotherapy or polytherapy) and class of antihypertensives defined using Multum Lexicon therapeutic classification (with calcium channel blockers [CCBs] as the reference group). Weighted logistic regression was used to assess the relationships of therapy type and class of antihypertensives use with ADRD diagnosis, adjusting for sociodemographic characteristics and health status. RESULTS:We found no significant difference between monotherapy and polytherapy on the odds of ADRD diagnosis. As to monotherapy, those who used angiotensin-converting enzyme inhibitors (ACEIs) had significantly lower odds of developing AD compared to those who used CCBs (OR 0.36, 95 % CI 0.13-0.99). CONCLUSIONS:Findings of the study suggest the need for evidence-based drug therapy to manage hypertension in later adulthood and warrant further investigation into the mechanism underlying the protective effect of antihypertensives, particularly ACEIs, against the development of AD among older adults with hypertension.

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.

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.