Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden.

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 µg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 µg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Considerations for Use of Blood-Based Biomarkers in Epidemiologic Dementia Research.

Dementia represents a growing public health burden with large social, racial, and ethnic disparities. The etiology of dementia is poorly understood, and the lack of robust biomarkers in diverse, population-representative samples is a barrier to moving dementia research forward. Existing biomarkers and other measures of pathology-derived from neuropathology, neuroimaging, and cerebrospinal fluid samples-are commonly collected from predominantly White and highly educated samples drawn from academic medical centers in urban settings. Blood-based biomarkers are noninvasive and less expensive, offering promise to expand our understanding of the pathophysiology of dementia, including in participants from historically excluded groups. Although largely not yet approved by the Food and Drug Administration or used in clinical settings, blood-based biomarkers are increasingly included in epidemiologic studies on dementia. Blood-based biomarkers in epidemiologic research may allow the field to more accurately understand the multifactorial etiology and sequence of events that characterize dementia-related pathophysiological changes. As blood-based dementia biomarkers continue to be developed and incorporated into research and practice, we outline considerations for using them in dementia epidemiology, and illustrate key concepts with Alzheimer's Disease Neuroimaging Initiative (2003-present) data. We focus on measurement, including both validity and reliability, and on the use of dementia blood-based biomarkers to promote equity in dementia research and cognitive aging. This article is part of a Special Collection on Mental Health.

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.

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.

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.

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.

The Association Between Physical Activity and Cognition in a Racially/Ethnically Diverse Cohort of Older Adults: Results From the Kaiser Healthy Aging and Diverse Life Experiences Study.

OBJECTIVE: Most prior research on physical activity (PA) and cognition is based on predominantly white cohorts and focused on associations of PA with mean (average) cognition versus the distribution of cognition. Quantile regression offers a novel way to quantify how PA affects cognition across the entire distribution. METHODS: The Kaiser Healthy Aging and Diverse Life Experiences study includes 30% white, 19% black, 25% Asian, and 26% Latinx adults age 65+ living in Northern California (n = 1600). The frequency of light or heavy PA was summarized as 2 continuous variables. Outcomes were z-scored executive function, semantic memory, and verbal episodic memory. We tested associations of PA with mean cognition using linear regression and used quantile regression to estimate the association of PA with the 10th-90th percentiles of cognitive scores. RESULTS: Higher levels of PA were associated with higher mean semantic memory (b = 0.10; 95% CI: 0.06, 0.14) and executive function (b = 0.05; 95% CI: 0.01, 0.09). Associations of PA across all 3 cognitive domains were stronger at low quantiles of cognition. CONCLUSION: PA is associated with cognition in this racially/ethnically diverse sample and may have larger benefits for individuals with low cognitive scores, who are most vulnerable to dementia.

Race, community disadvantage, and cognitive decline: Findings from KHANDLE and STAR.

INTRODUCTION: Community disadvantage is associated with late-life cognition. Few studies examine its contribution to racial disparities in cognition/cognitive change. METHODS: Inverse probability weighted models estimated expected mean differences in cognition/cognitive change attributed to residing in less advantaged communities, defined as cohort top quintile of Area Deprivation Indices (ADI): childhood 66-100; adulthood ADI 5-99). Interactions by race tested. RESULTS: More Black participants resided in less advantaged communities. Semantic memory would be lower if all participants had resided in less advantaged childhood (b = -0.16, 95% confidence interval [CI] = -0.30, -0.03) or adulthood (b = -0.14, 95% CI = -0.22, -0.04) communities. Race interactions indicated that, among Black participants, less advantaged childhood communities were associated with higher verbal episodic memory (interaction p-value = 0.007) and less advantaged adulthood communities were associated with lower semantic memory (interaction p-value = 0.002). DISCUSSION: Examining racial differences in levels of community advantage and late-life cognitive decline is a critical step toward unpacking community effects on cognitive disparities.

Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk.

INTRODUCTION: Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS: In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS: Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION: Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. HIGHLIGHTS: We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

Timing and level of educational attainment and late-life cognition in the KHANDLE study.

INTRODUCTION: The timing of educational attainment may modify its effects on late-life cognition, yet most studies evaluate education only at a single time point. METHODS: Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) Study cohort participants (N = 554) reported educational attainment (dichotomized at any college education) at two time points, and we classified them as having low, high, or later-life high educational attainment. Linear mixed-effects models estimated associations between educational attainment change groups and domain-specific cognitive outcomes (z-standardized). RESULTS: Compared to low educational attainment, high (ß= 0.59 SD units; 95% confidence interval [CI]: 0.39, 0.79) and later-life high educational attainment (ß = 0.22; 95% CI: 0.00, 0.44) were associated with higher executive function. Only high educational attainment was associated with higher verbal episodic memory (ß = 0.27; 95% CI: 0.06, 0.48). DISCUSSION: Level and timing of educational attainment are both associated with domain-specific cognition. A single assessment for educational attainment may inadequately characterize protective associations with late-life cognition. HIGHLIGHTS: Few studies have examined both level and timing of educational attainment on cognition. Marginalized populations are more likely to attain higher education in adulthood. Higher educational attainment in late life is also associated with higher cognition.

Invited Commentary: Algorithmic Dementia Classification-Promises and Challenges.

Dementia is a complex, progressive syndrome characterized by cognitive decline and disability. Gold-standard dementia diagnosis requires several hours of cognitive and clinical assessment and review by a panel of clinicians and is infeasible in large population-based cohort studies. Alternatively, algorithmic dementia classification methods, which use models that take into account measures of cognition and functional limitations or cognitive and functional-limitation score cutoffs, have been developed to predict dementia status for participants in large studies. Developing accurate dementia classification algorithms is crucial for high-quality studies of the distribution and determinants of dementia. The accompanying article by Nichols et al. (Am J Epidemiol. 2023;192(4):520-534) assesses differences in associations of measures of cognition and functional limitations with prevalent dementia versus incident dementia and discusses implications for algorithmic dementia classification in research studies. This work highlights important opportunities for tailoring measures of cognition and functional limitations to study goals by selecting optimal measures and developing and validating algorithms specific to study needs. Combining efficient, high-quality assessments of cognition and functional limitations with innovative study designs will facilitate collection of higher-quality measurements in larger samples and support future development of accurate dementia classifications, ultimately leading to more impactful epidemiologic studies.

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.

Association between cancer and dementia risk in the UK Biobank: evidence of diagnostic bias.

Epidemiological studies have identified an inverse association between cancer and dementia. Underlying methodological biases have been postulated, yet no studies have systematically investigated the potential for each source of bias within a single dataset. We used the UK Biobank to compare estimates for the cancer-dementia association using different analytical specifications designed to sequentially address multiple sources of bias, including competing risk of death, selective survival, confounding bias, and diagnostic bias. We included 140,959 UK Biobank participants aged ≥ 55 without dementia before enrollment and with linked primary care data. We used cancer registry data to identify cancer cases prevalent before UK Biobank enrollment and incident cancer diagnosed after enrollment. We used Cox models to evaluate associations of prevalent and incident cancer with all-cause dementia, Alzheimer's disease (AD), and vascular dementia. We used time-varying models to evaluate diagnostic bias. Over a median follow-up of 12.3 years, 3,310 dementia cases were diagnosed. All-site incident cancer was positively associated with all-cause dementia incidence (hazard ratio [HR] = 1.14, 95% CI: 1.02-1.29), but prevalent cancer was not (HR = 1.04, 95% CI: 0.92-1.17). Results were similar for vascular dementia. AD was not associated with prevalent or incident cancer. Dementia diagnosis was substantially elevated in the first year after cancer diagnosis (HR = 1.83, 95% CI: 1.42-2.36), after which the association attenuated to null, suggesting diagnostic bias. Following a cancer diagnosis, health care utilization or cognitive consequences of diagnosis or treatment may increase chance of receiving a dementia diagnosis, creating potential diagnostic bias in electronic health records-based studies.

Generation and age of immigration on later life cognitive performance in KHANDLE.

OBJECTIVES: We examined the association of generational status and age at immigration with later life cognitive outcomes in a diverse sample of Latinos and Asian Americans. DESIGN: Baseline data were obtained from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study, and a prospective cohort is initiated in 2017. SETTING: Older adults in Northern California. PARTICIPANTS: Our cohort consisted of Asians (n = 411) and Latinos (n = 340) who were on average 76 years old (SD = 6.8). MEASUREMENTS: We used multivariable linear regression models to estimate associations between generational status and age at immigration (collapsed into one five-level variable) with measures of verbal episodic memory, semantic memory, and executive function, adjusting for age, gender, race and ethnicity, and own- and parental education. RESULTS: Generational status and age at immigration were associated with cognitive outcomes in a graded manner. Compared to third-generation or higher immigrants, first-generation immigration in adulthood was associated with lower semantic memory (ß = -0.96; 95% CI: -1.12, -0.81) than immigration in adolescence (ß = -0.68; 95% CI: -0.96, -0.41) or childhood (ß = -0.28; 95% CI: -0.49, -0.06). Moreover, immigration in adulthood was associated with lower executive function (ß = -0.63; 95% CI: -0.78, -0.48) than immigration in adolescence (ß = -0.49; 95% CI: -0.75, -0.23). Similarly, compared to third-generation individuals, first-generation immigrants had lower executive functioning scores. CONCLUSIONS: Our study supports the notion that sociocontextual influences in early life impact later life cognitive scores. Longitudinal studies are needed to further clarify how immigration characteristics affect cognitive decline.

Association of primary lifetime occupational cognitive complexity and cognitive decline in a diverse cohort: Results from the KHANDLE study.

INTRODUCTION: Higher occupational complexity has been linked to favorable cognitive outcomes, but rarely examined in racially and ethnically diverse populations. METHODS: In a diverse cohort (n = 1536), linear mixed-effects models estimated associations between main lifetime occupational complexity and domain-specific cognitive decline (z-standardized). Occupational complexity with data, people, and things were classified using the Dictionary of Occupational Titles. RESULTS: For occupational complexity with data, highest tertile (vs. lowest) was associated with higher baseline executive function (ß = 0.11; 95% confidence interval [CI] 0.00-0.22) and slower annual rate of decline (ß = 0.03; 95% CI 0.01-0.06), and higher baseline semantic memory (ß = 0.14; 95% CI 0.04-0.25). Highest tertile of occupational complexity with people was associated with higher baseline executive function (ß = 0.29; 95% CI 0.18-0.40), verbal episodic memory (ß = 0.12; 95% CI 0.00-0.24), and semantic memory (ß = 0.23; 95% CI 0.12-0.34). DISCUSSION: In a diverse cohort, higher occupational complexity is associated with better cognition. Findings should be verified in larger cohorts. HIGHLIGHT: Few studies have examined associations of occupational complexity with cognition in diverse populations. Racial and ethnic minorities are disproportionately exposed to lower occupational complexity. Occupational complexity with data and people are associated with better cognition.

Neighborhood disadvantage and dementia incidence in a cohort of Asian American and non-Latino White older adults in Northern California.

INTRODUCTION: Some evidence suggests that neighborhood socioeconomic disadvantage is associated with dementia-related outcomes. However, prior research is predominantly among non-Latino Whites. METHODS: We evaluated the association between neighborhood disadvantage (Area Deprivation Index [ADI]) and dementia incidence in Asian American (n = 18,103) and non-Latino White (n = 149,385) members of a Northern California integrated health care delivery system aged 60 to 89 at baseline. Race/ethnicity-specific Cox proportional hazards models adjusted for individual-level age, sex, socioeconomic measures, and block group population density estimated hazard ratios (HRs) for dementia. RESULTS: Among non-Latino Whites, ADI was associated with dementia incidence (most vs. least disadvantaged ADI quintile HR = 1.09, 95% confidence interval [CI] = 1.02-1.15). Among Asian Americans, associations were close to null (e.g., most vs. least disadvantaged ADI quintile HR = 1.01, 95% CI = 0.85-1.21). DISCUSSION: ADI was associated with dementia incidence among non-Latino Whites but not Asian Americans. Understanding the potentially different mechanisms driving dementia incidence in these groups could inform dementia prevention efforts.

The impact of attending historically Black colleges and universities on cognitive decline in Black adults: A longitudinal analysis in the KHANDLE and STAR cohorts.

INTRODUCTION: Black students attending predominantly White institutions (PWIs) versus historically Black colleges and universities (HBCUs) report more harmful discrimination and develop worse mental health outcomes, potentially offsetting the established benefits of college for lowering dementia incidence. METHODS: Black participants in two cohorts (the Kaiser Healthy Aging and Diverse Life Experiences [KHANDLE] and the Study of Healthy Aging in African Americans [STAR]) who had attended college (N = 716) self-reported the college name (classified as HBCU vs. PWI) and completed three waves of executive function (EF) and verbal episodic memory (VEM) assessments. HBCU effects on cognitive level and decline were estimated using adjusted linear mixed-effects models. RESULTS: HBCU (vs. PWI) attendees averaged better EF (ß = 0.05 [-0.22, 0.32]) and VEM (ß = 0.21 [-0.06, 0.46]) at age 70 though neither association was statistically significant. HBCU attendance was associated with slightly faster VEM decline (ß = -0.03 [-0.05, 0.00]). DISCUSSION: Harmonized analyses with larger studies are needed to estimate important effects of HBCU attendance. HIGHLIGHTS: Higher education is robustly linked to lower dementia risk, yet Black-White inequities persist among college-educated adults. Black students attending predominantly White institutions (PWIs) versus historically Black colleges and universities (HBCUs) report more harmful discrimination and develop worse mental health outcomes, which may offset the established benefits of college for lowering dementia incidence. HBCU (vs. non-HBCU) attendees averaged better executive function and verbal episodic memory (VEM) at average age 70, though confidence intervals were wide and associations were not statistically significant, and averaged slightly faster decline in VEM. Harmonized analyses using larger nationally representative studies are likely needed to avoid underestimating the health effects of HBCU attendance.

Digital culturally tailored marketing for enrolling Latino participants in a web-based registry: Baseline metrics from the Brain Health Registry.

INTRODUCTION: This culturally tailored enrollment effort aims to determine the feasibility of enrolling 5000 older Latino adults from California into the Brain Health Registries (BHR) over 2.25 years. METHODS: This paper describes (1) the development and deployment of culturally tailored BHR websites and digital ads, in collaboration with a Latino community science partnership board and a marketing company; (2) an interim feasibility analysis of the enrollment efforts and numbers, and participant characteristics (primary aim); as well as (3) an exploration of module completion and a preliminary efficacy evaluation of the culturally tailored digital efforts compared to BHR's standard non-culturally tailored efforts (secondary aim). RESULTS: In 12.5 months, 3603 older Latino adults were enrolled (71% of the total California Latino BHR initiative enrollment goal). Completion of all BHR modules was low (6%). DISCUSSION: Targeted ad placement, culturally tailored enrollment messaging, and culturally tailored BHR websites increased enrollment of Latino participants in BHR, but did not translate to increased module completion. HIGHLIGHTS: Culturally tailored social marketing and website improvements were implemented. The efforts enrolled 5662 Latino individuals in 12.5 months. The number of Latino Brain Health Registry (BHR) participants increased by 122.7%. We failed to adequately enroll female Latinos and Latinos with lower education. Future work will evaluate effects of a newly released Spanish-language BHR website.

Pragmatic approaches to handling practice effects in longitudinal cognitive aging research.

INTRODUCTION: The challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID-19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory. METHODS: In three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data. RESULTS: APM-based correction for PEs based on balanced, pre-pandemic data, and with current age as the timescale produced the smallest discrepancy between within-person and between-person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used. DISCUSSION: Constraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change. HIGHLIGHTS: The magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age-related cognitive trajectories. Estimated age-related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

Aduhelm, the Newly Approved Medication for Alzheimer Disease: What Epidemiologists Can Learn and What Epidemiology Can Offer.

Alzheimer disease (AD) is a progressive disorder common among older adults and culminating in profound cognitive impairments and high mortality risk. The US Food and Drug Administration (FDA) recently provided accelerated approval for Aduhelm, a medication for AD treatment. Aduhelm (Biogen Inc., Cambridge, Massachusetts) has been described as the first disease-modifying treatment for AD but has not been demonstrated to improve patients' cognitive or functional outcomes. In this commentary, we describe why Aduhelm approval was controversial and aspects of the current evidence of special pertinence to epidemiologists. The FDA decision was based primarily on 2 randomized controlled trials (RCTs), both terminated early, with conflicting findings about the cognitive benefits of Aduhelm. Both RCTs showed important adverse effects of the medication. The FDA cited the documented reduction in brain amyloid, an AD biomarker hypothesized as a surrogate outcome, to justify accelerated approval. Despite lack of racial/ethnic diversity in the RCT participants, concerns about health disparities have been invoked to argue for public funding of this expensive medication. The Centers for Medicare and Medicaid Services recently made a "Coverage with Evidence Development" determination for Aduhelm and similar medications. We end by describing how innovative study designs could accelerate postapproval research and evaluate the proposed surrogate outcomes.