Heterogeneity in the effect of type 2 diabetes on dementia incidence in a diverse cohort of Asian American and non-Latino White older adults.

Dementia incidence is lower among Asian Americans than Whites, despite higher prevalence of type 2 diabetes, a well-known dementia risk factor. Determinants of dementia, including type 2 diabetes, have rarely been studied in Asian Americans. We followed 4,846 Chinese, 4,129 Filipino, 2,784 Japanese, 820 South Asian, and 123,360 non-Latino White members of a California-based integrated healthcare delivery system from 2002-2020. We estimated dementia incidence rates by race/ethnicity and type 2 diabetes status, and fit Cox proportional hazards and Aalen additive hazards models for the effect of type 2 diabetes (assessed 5 years before baseline) on age of dementia diagnosis controlling for sex/gender, educational attainment, nativity, height, race/ethnicity, and a race/ethnicity*diabetes interaction. Type 2 diabetes was associated with higher dementia incidence in Whites (hazard ratio [HR] 1.46, 95% confidence interval [CI] 1.40-1.52). Compared with Whites, the estimated effect of diabetes was larger in South Asians (2.26 [1.48-3.44]), slightly smaller in Chinese (1.32 [1.08-1.62]) and Filipino (1.31 [1.08-1.60]), and similar in Japanese (1.44 [1.15-1.81]) individuals. Heterogeneity in this association across Asian subgroups may be related to type 2 diabetes severity. Understanding this heterogeneity may inform prevention strategies to prevent dementia for all racial and ethnic groups.

Estimating dementia incidence in insured older Asian Americans and Pacific Islanders in California: an application of inverse odds of selection weights.

Literature shows heterogeneous age-standardized dementia incidence rates across US Asian American, Native Hawaiian, and Pacific Islanders (AANHPI), but no estimates of population-representative dementia incidence exist due to lack of AANHPI longitudinal probability samples. We compared harmonized characteristics between AANHPI Kaiser Permanente Northern California members (KPNC cohort) and the target population of AANHPI 60+ with private or Medicare insurance using the California Health Interview Survey. We used stabilized inverse odds of selection weights (sIOSW) to estimate ethnicity-specific crude and age-standardized dementia incidence rates and cumulative risk by age 90 in the target population. Differences between the KPNC cohort and target population varied by ethnicity. sIOSW eliminated most differences in larger ethnic groups; some differences remained in smaller groups. Estimated crude dementia incidence rates using sIOSW (versus unweighted) were similar in Chinese, Filipinos, Pacific Islanders and Vietnamese, and higher in Japanese, Koreans, and South Asians. Unweighted and weighted age-standardized incidence rates differed for South Asians. Unweighted and weighted cumulative risk were similar for all groups. We estimated the first population-representative dementia incidence rates and cumulative risk in AANHPI ethnic groups. We encountered some estimation problems and weighted estimates were imprecise, highlighting challenges using weighting to extend inferences to target populations.

School racial composition, effect modification by caring teacher/staff presence, and mid/late-life depressive symptoms: findings from the Study of Healthy Aging among African Americans.

For Black students in the United States, attending schools with a higher proportion of White students is associated with worse mental and physical health outcomes in adolescence/early adulthood. No prior studies evaluate K-12 school racial composition and later-life mental health. In a cohort of Black adults ages 50+ in Northern California who retrospectively self-reported school racial composition for grades 1, 6, 9, and 12, we assessed the association between attending a school with mostly Black students vs. not and mid/late-life depressive symptoms (8-item PROMIS depression score, standardized to US adult population) using age-, sex/gender-, southern US birth-, and parental education-adjusted generalized estimating equations, and assessed effect modification by caring teacher/staff presence. Later-life depressive symptoms were lower among those who attended schools with mostly Black students in grades 1 and 6 (b=-0.12, 95% CI: -0.23, 0.00 and b=-0.11, 95% CI: -0.22, 0.00, respectively). In grade 6, this difference was larger for students without an adult at school who cared about them (b=-0.29, 95% CI: -0.51, -0.07 vs. b=-0.04, 95% CI: -0.17, 0.09). Among Black Americans, attending early school with mostly Black students may have later life mental health benefits; this protective association appears more important for students without caring teachers/staff.

Representativeness of Participants in the ACCORD Trial Compared to Middle-aged and Older Adults Living with Diabetes in the United States.

BACKGROUND: We evaluated whether participants in the landmark Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial represent US adults aged ≥40 with diabetes. METHODS: Using the nationally representative 2017-2020 prepandemic National Health and Nutrition Examination Survey data, we made operational definitions of ACCORD eligibility criteria. We calculated the percentage of individuals aged ≥40 with diabetes and HbA1c ≥ 6.0% or ≥ 7.5% who met operational ACCORD eligibility criteria. RESULTS: Applying survey sampling weights to 715 National Health and Nutrition Examination Survey participants aged ≥40 with diabetes and HbA1c ≥ 6.0% (representing 29,717,406 individuals), 12% (95% confidence interval [CI] = 8%, 18%) met the operational ACCORD eligibility criteria. Restricting to HbA1c ≥ 7.5%, 39% (95% CI = 28%, 51%) of respondents met the operational ACCORD eligibility criteria. CONCLUSIONS: ACCORD represented a minority of US middle-aged and older adults with diabetes. Given the differential risk profile between ACCORD participants and the general population with diabetes, extrapolating the trial findings may not be appropriate.

Comparison of Imputation Strategies for Incomplete Longitudinal Data in Life-Course Epidemiology.

Incomplete longitudinal data are common in life-course epidemiology and may induce bias leading to incorrect inference. Multiple imputation (MI) is increasingly preferred for handling missing data, but few studies explore MI-method performance and feasibility in real-data settings. We compared 3 MI methods using real data under 9 missing-data scenarios, representing combinations of 10%, 20%, and 30% missingness and missing completely at random, at random, and not at random. Using data from Health and Retirement Study (HRS) participants, we introduced record-level missingness to a sample of participants with complete data on depressive symptoms (1998-2008), mortality (2008-2018), and relevant covariates. We then imputed missing data using 3 MI methods (normal linear regression, predictive mean matching, variable-tailored specification), and fitted Cox proportional hazards models to estimate effects of 4 operationalizations of longitudinal depressive symptoms on mortality. We compared bias in hazard ratios, root mean square error, and computation time for each method. Bias was similar across MI methods, and results were consistent across operationalizations of the longitudinal exposure variable. However, our results suggest that predictive mean matching may be an appealing strategy for imputing life-course exposure data, given consistently low root mean square error, competitive computation times, and few implementation challenges.

Identification of distinct blood-based biomarkers in early stage of Parkinson's disease.

Parkinson's disease (PD) is a slowly progressive geriatric disease, which can be one of the leading causes of serious socioeconomic burden in the aging society. Clinical trials suggest that prompt treatment of early-stage Parkinson's disease (EPD) may slow down the disease progress and have a better response. Therefore, conducting proteomics study to identify biomarkers for the diagnosis and disease-modifying therapies of EPD is vital. We aimed at identifying distinct protein autoantibody biomarkers of EPD by using the database of GSE62283 based on the platform GPL13669 downloaded from Gene Expression Omnibus database. Differentially expressed proteins (DEPs) between the EPD group (n = 103) and the normal control (NC) group (n = 111) were identified by protein-specific t test. Cluster analysis of DEPs was conducted by protein-protein interaction network to detect hub proteins. The hub proteins were then evaluated to determine the distinct biomarkers by principal component analysis, as well as functional and pathway enrichment analysis. Their biological functions were confirmed by gene ontology functional (GO) and Kyoto encyclopedia of genes and genomes pathway enrichment (KEGG). Two biomarkers, mitochondrial ribosome recycling factor (MRRF) and ribosomal protein S18 (RPS18), distinguished the EPD samples from the NC samples, and they were regarded as high-confidence distinct protein autoantibody biomarkers of EPD. The most significant GO function was protein serine/threonine kinase activity (GO: 0004674) and most of DEPs were enriched in ATP binding in molecular function category (GO: 0005524). These results may help in establishing the prompt and accurate diagnosis of EPD and may also contribute to develop mechanism-based treatments.

Early detection of Alzheimer's disease by peptides from phage display screening.

Alzheimer's disease (AD) is the most common neurodegenerative disorder without effective treatment so far. As clinical trials show that early-stage patients are more likely to respond to potential interventions, various technologies have been used to search blood biomarkers for the early diagnosis of AD. Phage display could be used to select specific peptides against desired target and here, we established a peptide binding assay based on phage display peptide library to detect early-stage AD patients. We first selected peptides from phage display library against plasmas from AD patients (n = 10) and normal healthy controls (n = 10), respectively, in the discovery set. Then, we further characterized one AD-specific peptide (AD#1 peptide) and one control-specific peptide (Con#1 peptide), and evaluated their diagnostic performance in independent validation set (35 AD patients, 45 MCI, 45 controls and 20 PD patients). Our results show that both AD#1 peptide and Con#1 peptide could distinguish AD/MCI patients from controls and combination of these two peptides could greatly improve the diagnostic performance (AUC is above 0.80 in ROC curve analysis). In addition, we found that AD#1 peptide stained Aß-treated primary astrocyte and bound to recombinant human YKL-40 protein in in-vitro assay. It supports that AD#1 peptide detects AD inflammation related cytokine. Thus, the detection assay based on phage-derived peptides may offer a novel blood biomarker test for the early diagnosis of AD.

A path analysis model suggesting the association of information and beliefs with self-efficacy in osteoporosis prevention among middle-aged and older community residents in urban Shanghai, China.

BACKGROUND: Osteoporosis is a chronic disease whose prevention is more effective than treatment, but it may be necessary to change people's self-efficacy to prevent this condition. This article aimed to study the pathway among information, beliefs and self-efficacy in osteoporosis prevention, and support further intervention. METHODS: A cross-sectional study was conducted among community residents over 40 years old from two volunteer communities in urban Shanghai, China. Of 450 middle-aged and older community residents who volunteered to participate in the study, 421 (93.5%) finished the field survey effectively. RESULTS: 62.9% of the residents were females. Their mean age was 64.4 ± 11.2 years. The residents showed low knowledge of osteoporosis-related information, and the mean percentage of correct response was just 61.2%. In univariate analysis, information (univariate ß = 0.27, 95% CI = 0.15-0.38) and beliefs (univariate ß = 0.31, 95% CI = 0.25-0.38) were associated with self-efficacy. Multivariate analysis showed that information (multiple ß = 0.19, 95% CI = 0.09-0.36) and belief (multiple ß = 0.30, 95% CI = 0.23-0.36) remained significant. And in the path analysis, self-efficacy was significantly predicted by beliefs (ß = 0.81, p<0.001). CONCLUSIONS: The study highlighted the urgency of conducting the osteoporosis preventive health promotion among middle-aged and older people as their lack of information and low level of beliefs and self-efficacy about osteoporosis prevention. Future interventions should focus on improving beliefs, especially perceived benefits, perceived threats, and action clues, on osteoporosis prevention in this group.