Faculty Bibliography

Longstanding gaps in the detection of Alzheimer's disease and related dementias (ADRD) and biopsychosocial care call for public health action to improve population health. We aim to broaden the understanding of the iterative role state plans have played over the last 20 years in prioritizing improvements in the detection of ADRD, primary care capacity, and equity for disproportionately affected populations. Informed by national ADRD priorities, state plans convene stakeholders to identify local needs, gaps, and barriers and set the stage for development of a national public health infrastructure that can align clinical practice reform with population health goals. We propose policy and practice actions that would accelerate the collaboration between public health, community organizations, and health systems to improve ADRD detection-the point of entry into care pathways that could ultimately improve outcomes on a national scale. HIGHLIGHTS: We systematically reviewed the evolution of state/territory plans for Alzheimer's disease and related dementias (ADRD). Plan goals improved over time but lacked implementation capacity. Landmark federal legislation (2018) enabled funding for action and accountability. The Centers for Disease Control and Prevention (CDC) funds three Public Health Centers of Excellence and many local initiatives. Four new policy steps would promote sustainable ADRD population health improvement.

INTRODUCTION/BACKGROUND:Mild cognitive impairment remains substantially underdiagnosed, especially in disadvantaged populations. Failure to diagnose deprives patients and families of the opportunity to treat reversible causes, make necessary life and lifestyle changes and receive disease-modifying treatments if caused by Alzheimer's disease. Primary care, as the entry point for most, plays a critical role in improving detection rates. METHODS:We convened a Work Group of national experts to develop consensus recommendations for policymakers and third-party payers on ways to increase the use of brief cognitive assessments (BCAs) in primary care. RESULTS:The group recommended three strategies to promote routine use of BCAs: providing primary care clinicians with suitable assessment tools; integrating BCAs into routine workflows; and crafting payment policies to encourage adoption of BCAs. DISSCUSSION/CONCLUSIONS:Sweeping changes and actions of multiple stakeholders are necessary to improve detection rates of mild cognitive impairment so that patients and families may benefit from timely interventions.

OBJECTIVES/OBJECTIVE:The purpose of this study was to assess predictors of health-related quality of life (HRQoL) in elderly Asian American and non-Hispanic White cancer survivors. METHODS:We conducted cross-sectional secondary data analyses using the combined datasets from the Surveillance, Epidemiology, and End Results program and the Medicare Health Outcomes Survey. RESULTS:Elderly Asian American cancer survivors reported a lower mental HRQoL but a comparable physical HRQoL relative to elderly non-Hispanic White cancer survivors. Stress factors, such as comorbidities, difficulties with activities of daily living, and a history of depressive symptoms, along with coping resources like self-rated health and the ability to take the survey in English, were significantly associated with mental and physical HRQoL. Among elderly Asian American cancer survivors, a significantly lower mental HRQoL was observed among those taking the survey in the Chinese language. CONCLUSIONS:The findings suggest that race exerts a differential impact on HRQoL. Interventions should be designed to address the distinct cultural, linguistic, and systemic needs of elderly Asian American cancer survivors. Such an approach could assist in reducing cancer-related health disparities.

Analyzing the large-scale survival data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program may help guide the management of cancer. Detecting and characterizing the time-varying effects of factors collected at the time of diagnosis could reveal important and useful patterns. However, fitting a time-varying effect model by maximizing the partial likelihood with such large-scale survival data is not feasible with most existing software. Moreover, estimating time-varying coefficients using spline based approaches requires a moderate number of knots, which may lead to unstable estimation and over-fitting issues. To resolve these issues, adding a penalty term greatly aids estimation. The selection of penalty smoothing parameters is difficult in this time-varying setting, as traditional ways like using Akaike information criterion do not work, while cross-validation methods have a heavy computational burden, leading to unstable selections. We propose modified information criteria to determine the smoothing parameter and a parallelized Newton-based algorithm for estimation. We conduct simulations to evaluate the performance of the proposed method. We find that penalization with the smoothing parameter chosen by a modified information criteria is effective at reducing the mean squared error of the estimated time-varying coefficients. Compared to a number of alternatives, we find that the estimates of the variance derived from Bayesian considerations have the best coverage rates of confidence intervals. We apply the method to SEER head-and-neck, colon, prostate, and pancreatic cancer data and detect the time-varying nature of various risk factors.

BACKGROUND:Current clinical guidelines recommend a coronary artery calcium (CAC) score of 100 Agatston Units or demographic-specific 75th percentile as high-risk thresholds for guiding atherosclerotic cardiovascular disease preventive therapy. Meanwhile, low CAC can help derisk individuals who may safely defer statin therapy. However, limited data from the early 2000s, including just 208 older Black individuals, inform CAC percentiles for adults aged 75 to 85 years, and none have been established in adults aged ≥85 years. This study aims to characterize the distribution of CAC and establish demographic-specific CAC percentiles in the population aged ≥75 years. METHODS:We assessed 2886 participants aged ≥75 years without clinical coronary heart disease from the ARIC study (Atherosclerosis Risk in Communities) visit 7 (2018-2019; n=2217) and the MESA (Multi-Ethnic Study of Atherosclerosis) visit 5 (2010-2011; n=669). Prevalence of any CAC >0 and sex- and race-specific CAC percentiles across age were estimated nonparametrically with locally weighted regression models and pooled residual ranking. RESULTS:The median age was 80 (interquartile interval, 77-83) years, and 60% were female. The prevalence of zero CAC was lowest in White males (4%), followed by Black males (13%), White females (14%), and highest in Black females (18%). Regardless of sex and race, most participants had CAC>100 (62.5%). CAC scores increased with age, with CAC identified in ≈95% of participants aged ≥90 years across sex-race subgroups. The 75th percentile corresponded to higher CAC scores for Black older adults (n=741), especially females, than currently used thresholds. CONCLUSIONS:In community-dwelling adults aged ≥75 years free of clinical coronary heart disease, the prevalence of zero CAC was 11%, and CAC >100 as a threshold for high ASCVD risk would categorize most of this older population as high risk. Demographic-specific CAC percentiles from this study are a valuable tool for interpreting CAC in the population aged ≥75 years.

OBJECTIVES:There are inconsistencies in the South Africa HIV mortality data reported by Institute of Health Metrics and Evaluation (IHME), Joint United Nations Programme on HIV/AIDS (UNAIDS), and Statistics South Africa (StatsSA) platforms. Between 2006 and 2016, these global data sets (IHME and UNAIDS) show that HIV-related mortalities were improving in South Africa, whereas StatsSA argues the opposite. We explain the causes of this differing stands and highlight areas that may be improved to address such inconsistencies. METHODS:This observational analysis uses data from IHME, UNAIDS, and StatsSA platforms. RESULTS:We demonstrate that IHME and UNAIDS data sets are based on a mathematical compartmental model, which is not dynamic to all HIV epidemiological aspects. Such limitation may cause inflated improvement in HIV mortality outcomes that are not in line with HIV mortality evidence recorded at the household level as demonstrated by StatsSA. CONCLUSION:There is a need to streamline the IHME, UNAIDS, and StatsSA data on HIV to improve the quality of HIV research and programming in South Africa.

BACKGROUND:Underserved and minoritized patients with cancer often experience more psychosocial concerns and inferior quality of life (QOL) compared with majority populations. This study compared patient-reported psychosocial characteristics and QOL among self-identified sexual and gender minority patients with cancer vs cisgender-heterosexual patients with cancer treated at a National Cancer Institute-designated comprehensive cancer center in the United States. METHODS:Self-report data from 51 503 patients were obtained from an institutional standard-of-care electronic patient questionnaire that was completed prior to, or on the day of, the patient's initial visit. The electronic patient questionnaire collects demographic information, including sexual orientation and gender identity, psychosocial variables, and QOL using the validated Short Form Health Survey-12. Sexual orientation and gender identity information was used to identify self-identified sexual and gender minority and cisgender-heterosexual persons (ie, non-self-identified sexual and gender minority). Using parametric analyses, psychosocial variables and QOL measures were compared for self-identified sexual and gender minority vs non-self-identified sexual and gender minority patients with cancer. RESULTS:Compared with non-self-identified sexual and gender minority patients (n = 50 116), self-identified sexual and gender minority patients (n = 1387, 2.7%) reported statistically significantly greater concerns regarding getting help during treatment (2.6% vs 4.3%, respectively; P = .001) and concerns with ability to seek care (16.7% vs 21.6%, respectively, P < .001). Self-identified sexual and gender minority patients reported statistically significantly elevated mental health concerns and daily emotional and pain interference (all P < .001), whereas there was no statistically significant difference in daily interference due to physical functioning. CONCLUSION:These data reveal real-world disparities among self-identified sexual and gender minority patients with cancer, which can be used to develop psychosocial interventions tailored to address the unique psychosocial and QOL needs of this underserved and minoritized population and to ultimately improve cancer care.

Human oral microbial communities are diverse, with implications for oral and systemic health. Oral microbial communities change over time; thus, it is important to understand how healthy versus dysbiotic oral microbiomes differ, especially within and between families. There is also a need to understand how the oral microbiome composition is changed within an individual including by factors such as environmental tobacco smoke (ETS) exposure, metabolic regulation, inflammation, and antioxidant potential. Using archived saliva samples collected from caregivers and children during a 90-month follow-up assessment in a longitudinal study of child development in the context of rural poverty, we used 16S rRNA gene sequencing to determine the salivary microbiome. A total of 724 saliva samples were available, 448 of which were from caregiver/child dyads, an additional 70 from children and 206 from adults. We compared children's and caregivers' oral microbiomes, performed "stomatotype" analyses, and examined microbial relations with concentrations of salivary markers associated with ETS exposure, metabolic regulation, inflammation, and antioxidant potential (i.e., salivary cotinine, adiponectin, C-reactive protein, and uric acid) assayed from the same biospecimens. Our results indicate that children and caregivers share much of their oral microbiome diversity, but there are distinct differences. Microbiomes from intrafamily individuals are more similar than microbiomes from nonfamily individuals, with child/caregiver dyad explaining 52% of overall microbial variation. Notably, children harbor fewer potential pathogens than caregivers, and participants' microbiomes clustered into two groups, with major differences being driven by Streptococcus spp. Differences in salivary microbiome composition associated with ETS exposure, and taxa associated with salivary analytes representing potential associations between antioxidant potential, metabolic regulation, and the oral microbiome. IMPORTANCE The human oral cavity is a multi-environment habitat that harbors a diversity of microorganisms. This oral microbiome is often transmitted between cohabitating individuals, which may associate oral and systemic health within family members. Furthermore, family social ecology plays a significant role in childhood development, which may be associated with lifelong health outcomes. In this study, we collected saliva from children and their caregivers and used 16S rRNA gene sequencing to characterize their oral microbiomes. We also analyzed salivary biomeasures of environmental tobacco smoke exposure, metabolic regulation, inflammation, and antioxidant potential. We show there are differences in individuals' oral microbiomes mainly due to Streptococcus spp. that family members share much of their microbes, and several bacterial taxa associate with the selected salivary biomeasures. Our results suggest there are large-scale oral microbiome patterns, and there are likely relationships between oral microbiomes and the social ecology of families.

BACKGROUND AND OBJECTIVES:Disability after stroke occurs across ischemic stroke subtypes, with a suggestion that embolic strokes are more devastating. Whether this difference is as a result of differences in comorbidities or differences in severity at the time of the stroke event is not known. The primary hypothesis was that participants with embolic stroke would have more severe stroke at the time of admission and a higher risk of mortality, compared with thrombotic stroke participants even with consideration of confounders over time, with a secondary hypothesis that this association would differ by race and sex. METHODS:Atherosclerosis Risk in Communities (ARIC) study participants with incident adjudicated ischemic stroke, stroke severity and mortality data, and complete covariates were included. Multinomial logistic regression models determined the association between stroke subtype (embolic vs thrombotic) and admission NIH Stroke Scale (NIHSS) category (minor [≤5], mild [6-10], moderate [11-15], severe [16-20], and very severe [>20]) adjusted for covariates from visits most proximal to the stroke. Separate ordinal logistic models evaluated for interaction by race and sex. Adjusted Cox proportional hazard models estimated the association between stroke subtype and all-cause mortality (through December 31, 2019). RESULTS:interaction = 0.03, per severity category, females OR 2.38, 95% CI 1.55-3.66; males OR 1.75, 95% CI 1.09-2.82). The risk of death (median follow-up 5 years, interquartile range 1-12) was also increased for embolic vs thrombotic stroke patients (hazard ratio 1.66, 95% CI 1.41-1.97). DISCUSSION:Embolic stroke was associated with greater stroke severity at the time of the event and a higher risk of death vs thrombotic stroke, even after careful adjustment for patient-level differences.