Faculty Bibliography

AIMS/OBJECTIVE:To characterize changes in continuous glucose monitoring (CGM)-derived time in tight range (TIR) measures in individuals with prediabetes or non-insulin-treated type 2 diabetes undergoing dietary weight loss intervention and to quantify the association between weight loss and TIR improvement. METHODS:) were analysed. The association between weight change and TIR change adjusted for demographic and clinical covariates was computed using linear regression. RESULTS:. There were no associations between weight loss and change in any overnight TIR measure. CONCLUSION/CONCLUSIONS:in individuals with prediabetes and non-insulin-treated type 2 diabetes undergoing dietary intervention. The daytime time in tight range measures can complement traditional markers like HbA1c, offering a more comprehensive view of glycaemic variations during dietary weight loss programmes for individuals with prediabetes and type 2 diabetes not on insulin.

IMPORTANCE/UNASSIGNED:SARS-CoV-2 infection has been linked to neurotoxic effects and cognitive deficits. OBJECTIVE/UNASSIGNED:To determine whether decreases in cognitive function were accelerated after SARS-CoV-2 infection compared with individuals not infected. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:Multicenter, prospective cohort study from 2016 to 2022 among 3525 participants alive on March 1, 2020, and enrolled in The Atherosclerosis Risk in Communities (ARIC) study and the Collaborative Cohort of Cohorts for COVID-19 Research study who completed a prepandemic cognitive assessment and a pandemic-era assessment of SARS-CoV-2 infection. Final analyses performed in November 2024. EXPOSURE/UNASSIGNED:SARS-CoV-2 infection determined via self-report of a positive SARS-CoV-2 test or health care professional diagnosis of COVID-19, a positive SARS-CoV-2 antinucleocapsid antibody response, or presence of an administrative code for COVID-19 on medical records. MAIN OUTCOMES AND MEASURES/UNASSIGNED:A neuropsychological battery assessed multiple cognitive domains, and a cocalibrated confirmatory factor analysis generated factor scores for global cognitive function. The primary outcome was the rate of excess change in cognitive function. RESULTS/UNASSIGNED:The 3525 eligible participants had a mean (SD) age of 80.8 (4.7) years, 2085 (59.1%) were female, 752 (21.4%) were Black, and 2773 (78.6%) were White. SARS-CoV-2 infection was detected among 307 participants (8.7%), 103 of whom (33.6%) were hospitalized. Among uninfected participants, the mean annualized change in cognitive function was -0.09 (95% CI, -0.13 to -0.04). Compared with this rate, change was faster (β = -0.06; 95% CI, -0.09 to -0.02) among participants hospitalized for infection, but not different from participants who were infected but not hospitalized (β = 0.00; 95% CI, -0.02 to 0.03). The association among participants hospitalized for infection was evident in the cognitive domains of memory and executive function, but not language. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This cohort study of older participants found accelerated decreases in cognition among individuals hospitalized for SARS-CoV-2 infection, but not nonhospitalized infection, in comparison with individuals not yet infected.

PURPOSE/OBJECTIVE:To assess whether slit-scanning specular microscopy (CellChek C; Konan Medical) can repeatedly image the same corneal location using anatomic landmarks (posterior corneal rings and corneal undulations) and unique cells identified during imaging. METHODS:A total of 203 eyes (113 patients) with and without corneal pathology were imaged to assess the prevalence of anatomic landmarks. A subcohort of 20 healthy eyes was used to identify unique cells adjacent to anatomic landmarks. Landmarks were then used to locate the same cells on repeat imaging approximately 1 week later. Endothelial cell density (ECD), coefficient of variation, and percent hexagonality were calculated. Intraclass correlation coefficient and 95% limits of agreement were used to measure variability and reproducibility of imaging. RESULTS:Approximately 91% of eyes had either posterior corneal rings or undulations present. Undulations were more common than posterior corneal rings in both healthy and diseased corneas. Among subcohort eyes, unique cells were found adjacent to anatomic landmarks in 100% of eyes. Landmarks were used to reimage the same cells in 75% of eyes. There was minimal variation in ECD, coefficient of variation, and hexagonality; intraclass correlation coefficient and 95% confidence intervals were 0.891 [0.715-0.962], 0.612 [0.179-0.849], and 0.793 [0.499-0.925], respectively. The 95% limits of agreement for ECD was -359.9-260.98. CONCLUSIONS:Landmarks identified with slit-scanning specular microscopy allowed reliable reimaging of the same endothelial location, providing a powerful tool to better understand the role of the peripheral endothelium in health and disease.

IMPORTANCE/UNASSIGNED:Hearing loss treatment delays cognitive decline in high-risk older adults. The preventive potential of addressing hearing loss on incident dementia in a community-based population of older adults, and whether it varies by method of hearing loss measurement, is unknown. OBJECTIVE/UNASSIGNED:To calculate the population attributable fraction of incident dementia associated with hearing loss in older adults and to investigate differences by age, sex, self-reported race, and method of hearing loss measurement. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This prospective cohort study was part of the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) and had up to 8 years of follow-up (2011-2019). The 4 ARIC field centers in the study included Jackson, Mississippi; Forsyth County, North Carolina; the Minneapolis suburbs, Minnesota; and Washington County, Maryland. Community-dwelling older adults aged 66 to 90 years without dementia at baseline who underwent a hearing assessment at ARIC-NCS visit 6 (2016-2017) were included in the analysis. Data analysis took place between June 2022 and July 2024. EXPOSURES/UNASSIGNED:Hearing loss measured objectively (audiometric) and subjectively (self-reported). MAIN OUTCOMES AND MEASURES/UNASSIGNED:The main outcome was incident dementia (standardized algorithmic diagnosis with expert panel review). The population attributable fractions of dementia from both audiometric and self-reported hearing loss were calculated in the same participants, which quantified the maximum proportion of dementia risk in the population that can be attributed to hearing loss. RESULTS/UNASSIGNED:Among 2946 participants (mean [SD] age, 74.9 [4.6] years; 1751 [59.4] female; 637 Black [21.6%] and 2309 White [78.4%] individuals), 1947 participants (66.1%) had audiometric hearing loss, and 1097 (37.2%) had self-reported hearing loss. The population attributable fraction of dementia from any audiometric hearing loss was 32.0% (95% CI, 11.0%-46.5%). Population attributable fractions were similar by hearing loss severity (mild HL: 16.2% [95% CI, 4.2%-24.2%]; moderate or greater HL: 16.6% [95% CI, 3.9%-24.3%]). Self-reported hearing loss was not associated with an increased risk for dementia, so the population attributable fraction was not quantifiable. Population attributable fractions from audiometric hearing loss were larger among those who were 75 years and older (30.5% [95% CI, -5.8% to 53.1%]), female (30.8% [95% CI, 5.9%-47.1%]), and White (27.8% [95% CI, -6.0% to 49.8%]), relative to those who were younger than 75 years, male, and Black. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This cohort study suggests that treating hearing loss might delay dementia for a large number of older adults. Public health interventions targeting clinically significant audiometric hearing loss might have broad benefits for dementia prevention. Future research quantifying population attributable fractions should carefully consider which measures are used to define hearing loss, as self-reporting may underestimate hearing-associated dementia risk.

Epigenetic aging biomarkers are used for evaluating morbidity and mortality, monitoring therapies, and direct-to-consumer testing. However, the influence of environmental exposures on epigenetic age acceleration (EAA), also known as epigenetic age deviation, has not been systematically evaluated. In this systematic review, we synthesized findings from human epidemiologic studies on chemical and climatic environmental exposures, particularly air pollution, chemicals, metals, climate, and cigarette smoke, and EAA. A total of 102 studies analyzing epigenetic data from over 180,000 subjects were evaluated. Overall, studies in each exposure category frequently included adult participants, used a variety of epigenetic clocks, analyzed whole blood samples, and had a low risk of bias. Exposure to air pollution (15/19 of studies; 79%), cigarette smoke (53/66; 80%), and synthetic and occupational chemicals (5/8; 63%) were notably associated with increased EAA. Results for essential and non-essential metal exposure were more equivocal: 7/13 studies (54%) reported increased EAA. One study reported increased EAA with greater temperature exposure. In summary, we identified environmental exposures, such as air pollution and cigarette smoke, that were strongly associated with increased EAA. Further research is needed with larger and more diverse samples and high-quality exposure assessment.

OBJECTIVE:The Diabetes in Children, Adolescents, and Young Adults (DiCAYA) network seeks to create a nationwide electronic health record (EHR)-based diabetes surveillance system. This study aimed to develop a DiCAYA-wide EHR-based computable phenotype (CP) to identify prevalent cases of diabetes. RESEARCH DESIGN AND METHODS/METHODS:We conducted network-wide chart reviews of 2,134 youth (aged <18 years) and 2,466 young adults (aged 18 to <45 years) among people with possible diabetes. Within this population, we compared the performance of three alternative CPs, using diabetes diagnoses determined by chart review as the gold standard. CPs were evaluated based on their accuracy in identifying diabetes and its subtype. RESULTS:The final DiCAYA CP requires at least one diabetes diagnosis code from clinical encounters. Subsequently, diabetes type classification was based on the ratio of type 1 diabetes (T1D) or type 2 diabetes (T2D) diagnosis codes in the EHR. For both youth and young adults, the sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively) in finding diabetes cases were >90%, except for the specificity and NPV in young adults, which were slightly lower at 83.8% and 80.6%, respectively. The final DiCAYA CP achieved >90% sensitivity, specificity, PPV, and NPV in classifying T1D, and demonstrated lower but robust performance in identifying T2D, consistently maintaining >80% across metrics. CONCLUSIONS:The DiCAYA CP effectively identifies overall diabetes and T1D in youth and young adults, though T2D misclassification in youth highlights areas for refinement. The simplicity of the DiCAYA CP enables broad deployment across diverse EHR systems for diabetes surveillance.

BACKGROUND:Hearing loss is prevalent in older adults and is associated with reduced daily physical activity, but whether hearing intervention attenuates declines in physical activity is unknown. We investigated the 3-year effect of a hearing intervention versus a health education control on accelerometer-measured physical activity in older adults with hearing loss. METHODS:This secondary analysis of the ACHIEVE randomized controlled trial included 977 adults aged 70-84 years with hearing loss. Participants were randomized to either a hearing intervention group or a health education control group. Physical activity was measured using wrist-worn accelerometers at baseline, 1, 2, and 3 years. Linear mixed models assessed the impact of the intervention on changes in total activity counts, active minutes per day, and activity fragmentation. RESULTS:Among 847 participants in the final analysis (mean age 76.2 years; 440 [52%] women; 87 [10%] Black; 5 [0.8%] Hispanic), total activity counts declined by 2.7% annually, and active minutes/day declined by 2.1% annually over 3 years in both intervention and control groups. Activity patterns also became more fragmented over time. No appreciable differences were observed between hearing intervention and health education control in the 3-year change in accelerometry-measured physical activity measures. CONCLUSIONS:Hearing intervention did not appreciably attenuate 3-year declines in physical activity compared to health education control in older adults with hearing loss. Alternative strategies beyond hearing treatment may be needed to enhance physical activity among older adults with hearing loss.

RATIONALE & OBJECTIVE/OBJECTIVE:Despite national efforts, the uptake of home dialysis (peritoneal dialysis or home hemodialysis) remains low. Characteristics of the built environment may differentially impact home dialysis use. STUDY DESIGN/METHODS:Retrospective cohort study (2010-2019). SETTING & PARTICIPANTS/METHODS:1,103,695 adults (aged≥18 years) initiating dialysis in the US Renal Data System. EXPOSURE/METHODS:We examined 3 built environment domains based on residential ZIP code: (1) medically underserved areas (MUAs), defined as neighborhoods with limited primary care access; (2) distance to the nearest dialysis facility; and (3) distribution of housing characteristics (structure and overcrowding). OUTCOME/RESULTS:Uptake of home dialysis modalities at dialysis initiation. ANALYTICAL APPROACH/METHODS:We quantified associations between built environment characteristics and home dialysis initiation using multilevel logistic regression stratified by urbanicity type (urban, suburban, small-town, and rural). RESULTS:Among adults initiating dialysis, 40.8% lived in MUAs. Across ZIP codes, the mean percentage of overcrowded housing was 4.2% (SD, 4.7%), and the percentage of detached housing was 61.1% (SD, 21.1%); mean distance to the nearest dialysis facility was 5.5km (SD, 9.1km). Living in MUAs was associated with reduced home dialysis use only in urban (OR, 0.94; 95% CI, 0.91-0.96) and suburban (OR, 0.92; 95% CI, 0.89-0.94) areas. Similarly, housing overcrowding was associated with decreased home dialysis use only in urban (OR, 0.88; 95% CI, 0.86-0.89) and suburban (OR, 0.91; 95% CI, 0.90-0.93) areas. Longer distance to a dialysis facility was the most salient neighborhood factor associated with increased home dialysis use in small towns (OR, 1.14; 95% CI, 1.12-1.16) and rural areas (OR, 1.17; 95% CI, 1.15-1.19). LIMITATIONS/CONCLUSIONS:Housing characteristics were measured at the ZIP code level. CONCLUSIONS:Built environment characteristics associated with home dialysis uptake vary by urbanicity. Policies should address built environment barriers that are specific to urbanicity level. For example, increasing the frequency of dialysate delivery schedules could address housing space constraints in urban and suburban areas, and promoting home dialysis might be more effective for patients living far from dialysis centers in small-town and rural areas.