Search

BACKGROUND: Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE: We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS: We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (N[O.sub.2]), nitrogen oxides (N[O.sub.x]), and 8-and 24-h ozone ([O.sub.3]) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS: Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher N[O.sub.2] and N[O.sub.x] and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION: Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, N[O.sub.x], and N[O.sub.2] and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906, Introduction Growing evidence links air pollution to late-life cognitive health. Currently, the strongest evidence supports an effect of particulate matter (PM) air pollution. (1) In comparison with PM, fewer studies [...]

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.

Background: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. Objectives: Our objective is to compare particulate matter with aerodynamic diameter [less than or equal to]2.5 [micro]m (P[M.sub.2.5]) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. Methods: We assigned annual P[M.sub.2.5] exposure estimates from 1999 to 2004 derived from 11 different approaches to Women's Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between P[M.sub.2.5] and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. Results: With a few exceptions, relative agreement of approach-specific P[M.sub.2.5] exposure estimates was high for P[M.sub.2.5] concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near P[M.sub.2.5] monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for P[M.sub.2.5]. There was no evidence of large differences in health effects associations with P[M.sub.2.5] among estimation approaches in analyses adjusted for climate region. Conclusions: Different estimation approaches produced similar spatial patterns of P[M.sub.2.5] concentrations across the contiguous US and in areas with dense monitoring data, and P[M.sub.2.5]-health effects associations were similar among estimation approaches. P[M.sub.2.5] estimates and P[M.sub.2.5]-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about P[M.sub.2.5] estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest. https://doi.org/10.1289/EHP12995, Introduction Routine air pollution monitoring is primarily conducted for regulatory purposes. While existing monitor networks provide useful information on air pollution exposures, they do not necessarily provide the spatial resolution [...]

IntroductionTo examine associations of history of traumatic brain injuries (TBIs) with loss of consciousness (LOC) with dementia incidence and memory decline.MethodsWe studied 2718 participants from the 1992 enrollment cohort of the Health and Retirement Study (HRS) aged 65 years or older in 2000. History of TBI with LOC was self-reported in 1992. Dementia was assessed using four algorithms established in HRS. Participants were followed from 2000 to 2014 with repeated measures of dementia and memory performance. Cox models and linear mixed-effects models were used.ResultsIn 1992, 11.9% of the participants reported a history of TBI with LOC. In fully adjusted models for all four algorithms, participants with a history of TBI with LOC had no statistically significant difference in dementia incidence nor in memory decline, compared to participants without TBI history.DiscussionOur study did not find evidence of a long-term association between history of TBI with LOC (of unknown frequency and severity) and dementia incidence or memory decline.

ObjectiveOur objectives were to characterize the inter-relation of known dementia-related neuropathologies in one comprehensive model and quantify the extent to which accumulation of neuropathologies accounts for the association between age and dementia.MethodsWe used data from 1,362 autopsied participants of three community-based clinicopathological cohorts: the Religious Orders Study, the Rush Memory and Aging Project, and the Minority Aging Research Study. We estimated a series of structural equation models summarizing a priori hypothesized neuropathological pathways between age and dementia risk individually and collectively.ResultsAt time of death (mean age, 89 years), 44% of our sample had a clinical dementia diagnosis. When considered individually, our vascular, amyloid/tau, neocortical Lewy body, and TAR DNA-binding protein 43 (TDP-43)/hippocampal sclerosis pathology pathways each accounted for a substantial proportion of the association between age and dementia. When considered collectively, the four pathways fully accounted for all variance in dementia risk previously attributable to age. Pathways involving amyloid/tau, neocortical Lewy bodies, and TDP-43/hippocampal sclerosis were interdependent, attributable to the importance of amyloid beta plaques in all three. The importance of the pathways varied, with the vascular pathway accounting for 32% of the association between age and dementia, wheraes the remaining three inter-related degenerative pathways together accounted for 68% (amyloid/tau, 24%; the Lewy body, 1%; and TDP-43/hippocampal sclerosis, 43%).InterpretationAge-related increases in dementia risk can be attributed to accumulation of multiple pathologies, each of which contributes to dementia risk. Multipronged approaches may be necessary if we are to develop effective therapies. Ann Neurol 2018;84:10-22.

INTRODUCTION: There is limited evidence about factors related to the timeliness of dementia diagnosis in healthcare settings. METHODS: In five prospective cohorts at Rush Alzheimer's Disease Center, we identified participants with incident dementia based on annual assessments and examined the timing of healthcare diagnoses in Medicare claims. We assessed sociodemographic, health, and psychosocial correlates of timely diagnosis. RESULTS: Of 710 participants, 385 (or 54%) received a timely claims diagnosis within 3 years prior to or 1 year following dementia onset. In logistic regressions accounting for demographics, we found Black participants (odds ratio [OR] = 2.15, 95% confidence interval [CI]: 1.21 to 3.82) and those with better cognition at dementia onset (OR = 1.48, 95% CI: 1.10 to 1.98) were at higher odds of experiencing a diagnostic delay, whereas participants with higher income (OR = 0.89, 95% CI: 0.81 to 0.97) and more comorbidities (OR = 0.94, 95% CI: 0.89 to 0.98) had lower odds. DISCUSSION: We identified characteristics of individuals who may miss the optimal window for dementia treatment and support. Highlights: We compared the timing of healthcare diagnosis relative to the timing of incident dementia based on rigorous annual evaluation.Older Black adults with lower income, higher cognitive function, and fewer comorbidities were less likely to be diagnosed in a timely manner by the healthcare system. [ABSTRACT FROM AUTHOR]

Bias due to selective mortality is a potential concern in many studies and is especially relevant in cognitive aging research because cognitive impairment strongly predicts subsequent mortality. Biased estimation of the effect of an exposure on rate of cognitive decline can occur when mortality is a common effect of exposure and an unmeasured determinant of cognitive decline and in similar settings. This potential is often represented as collider-stratification bias in directed acyclic graphs, but it is difficult to anticipate the magnitude of bias. In this paper, we present a flexible simulation platform with which to quantify the expected bias in longitudinal studies of determinants of cognitive decline. We evaluated potential survival bias in naive analyses under several selective survival scenarios, assuming that exposure had no effect on cognitive decline for anyone in the population. Compared with the situation with no collider bias, the magnitude of bias was higher when exposure and an unmeasured determinant of cognitive decline interacted on the hazard ratio scale to influence mortality or when both exposure and rate of cognitive decline influenced mortality. Bias was, as expected, larger in high-mortality situations. This simulation platform provides a flexible tool for evaluating biases in studies with high mortality, as is common in cognitive aging research.

Background: In stroke patients with insulin resistance (IR), post-stroke cognitive impairment (PSCI) is associated with higher risk of recurrent stroke, but the effect of pioglitazone on that risk has not been explored. The goal of this study was to compare the secondary stroke prevention effect of pioglitazone against placebo in patients with versus without PSCI. Methods: We studied patients enrolled in the Insulin Resistance Intervention after Stroke (IRIS) trial with a post-stroke modified Mini-Mental State Examination (3MS) cognitive assessment (mean time of assessment: 79 days post-stroke). We considered a baseline score of ⩽ 88 on the 3MS to indicate global PSCI, and domain-specific summary scores in the lowest quartile to indicate attention, language, memory, orientation, and visuospatial impairments. Results: In n = 3338 patients with IR, the effect of pioglitazone versus placebo on secondary stroke significantly differed by initial post-stroke global (interaction p = 0.0127) and memory impairment status (interaction p = 0.0003). Hazard ratios (HRs) were time-dependent such that, among those with either global or memory impairment, pioglitazone has an increasingly stronger protective effect at later timepoints. There was no statistically significant effect of pioglitazone among those without either global or memory impairment. The effect of pioglitazone versus placebo on myocardial infarction (MI) also significantly differed by global impairment status (interaction p = 0.030). Pioglitazone was protective among those with global impairment (HR = 0.23 [95% CI: 0.08, 0.71]) but not among those without (HR = 0.88 [95% CI: 0.59, 1.31]). Conclusion: These data indicate that pioglitazone treatment may be more effective at reducing risk of recurrent stroke and MI in stroke patients with PSCI. Simple cognitive testing 2–3 months post-stroke may identify patients for whom treatment would be most beneficial. [ABSTRACT FROM AUTHOR]

BACKGROUND: Dementia is a devastating neurologic condition that is common in older adults. We previously reviewed the epidemiological evidence examining the hypothesis that long-term exposure to air pollution affects dementia risk. Since then, the evidence base has expanded rapidly. OBJECTIVES: With this update, we collectively review new and previously identified epidemiological studies on air pollution and late-life cognitive health, highlighting new developments and critically discussing the merits of the evidence. METHODS: Using a registered protocol (PROSPERO 2020 CRD42020152943), we updated our literature review to capture studies published through 31 December 2020, extracted data, and conducted a bias assessment. RESULTS: We identified 66 papers (49 new) for inclusion in this review. Cognitive level remained the most commonly considered outcome, and particulate matter (PM) remained the most commonly considered air pollutant. Since our prior review, exposure estimation methods in this research have improved, and more papers have looked at cognitive change, neuroimaging, and incident cognitive impairment/dementia, though methodological concerns remain common. Many studies continue to rely on administrative records to ascertain dementia, have high potential for selection bias, and adjust for putative mediating factors in primary models. A subset of 35 studies met strict quality criteria. Although high- quality studies of fine particulate matter with aerodynamic diameter [less than or equal to]2.5 [micro]m (P[M.sub.2.5]) and cognitive decline generally supported an adverse association, other findings related to P[M.sub.2.5] and findings related to particulate matter with aerodynamic diameter Discussion: Strong conclusions remain elusive, although the weight of the evidence suggests an adverse association between P[M.sub.2.5] and cognitive decline. However, we note a continued need to confront methodological challenges in this line of research. https://doi.org/10.1289/EHP8716, Introduction Dementia erodes the affected person's independence, imposes emotional and financial burdens on care partners, and levies enormous costs to social safety nets (Alzheimer's Association 2018; El-Hayek et al. 2019). [...]

INTRODUCTION: The results of the CLARITY‐AD, GRADUATE I and II, and TRAILBLAZER‐ALZ 2 trials have rekindled discussion on the impact of amyloid‐targeting drugs. We use a Bayesian approach to quantify how rational observers would have updated their prior beliefs based on new trial results. METHODS: We used publicly available data from the CLARITY‐AD, GRADUATE I and II, and TRAILBLAZER‐ALZ 2 trials to estimate the effect of reducing amyloid on the clinical dementia rating scale, sum of boxes (CDR‐SB) score. A range of prior positions were then updated according to Bayes' theorem using these estimates. RESULTS: After updating with new trial data, a wide range of starting positions resulted in credible intervals that did not include no effect of amyloid reduction on CDR‐SB score. DISCUSSION: For a range of starting beliefs and assuming the veracity of the underlying data, rational observers would conclude there is a small benefit of amyloid reductions on cognition. This benefit must be weighed against opportunity cost and side‐effect risk. Highlights: The results of recent trials of amyloid‐targeting drugs have rekindled discussion on the impact of amyloid reductions achieved with amyloid‐targeting drugs on cognition.Prior to the announcement of trial results, beliefs about the effects of altering amyloid levels varied.For a range of starting beliefs, one would conclude there is a small benefit of amyloid reductions due to amyloid‐targeting drugs on cognition.The perceived value of individual drugs must balance the magnitude of this benefit against opportunity cost and risk of side effects. [ABSTRACT FROM AUTHOR]

BACKGROUND: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. OBJECTIVES: Our objective is to compare particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. METHODS: We assigned annual PM2.5 exposure estimates from 1999 to 2004 derived from 11 different approaches to Women’s Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between PM2.5 and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. RESULTS: With a few exceptions, relative agreement of approach-specific PM2.5 exposure estimates was high for PM2.5 concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near PM2.5 monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for PM2.5. There was no evidence of large differences in health effects associations with PM2.5 among estimation approaches in analyses adjusted for climate region. CONCLUSIONS: Different estimation approaches produced similar spatial patterns of PM2.5 concentrations across the contiguous US and in areas with dense monitoring data, and PM2.5-health effects associations were similar among estimation approaches. PM2.5 estimates and PM2.5-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about PM2.5 estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest [ABSTRACT FROM AUTHOR]

Background Evidence indicates the health care system disproportionately misses dementia in African American compared to White individuals. In preliminary data, we examined factors related to dementia identification by the health care system among African Americans. Methods We leveraged linked Medicare fee-for-service claims and detailed annual cohort evaluations in African Americans from 4 cohorts at Rush Alzheimer's Disease Center. Results Among 88 African Americans with cognitive impairment (mean = 10 years follow-up), Medicare claims identified dementia <2 years from cohort diagnosis in 55%; 27% were identified 2–9.9 years after cohort diagnosis, and in 18% there was either no claims diagnosis during the study period, or claims identified dementia 10+ years after cohort diagnosis. Claims identification of dementia was related to older age at cohort diagnosis (eg, <2 years between cohort and claims: mean = 82 years; 10+ years/no diagnosis: mean = 77 years, p  = .04), lower Mini-Mental State Examination (MMSE) score (<2 years: mean = 24; 10+ years/no diagnosis: mean = 26, p  = .04), more depressive symptoms (<2 years: mean = 2.1 symptoms; 10+ years/no diagnosis: mean = 1.2, p  = .04), and more comorbidity (<2 years: mean = 5.6 comorbidities; 10+ years/no diagnosis, mean = 3.0, p  = .02). Conclusions Among African Americans, preliminary data indicate the health care system most rapidly identifies dementia in older individuals, with worse cognitive and physical health. The health care system may miss opportunities for early support of African Americans with dementia, and caregivers. [ABSTRACT FROM AUTHOR]

Diagnostic delay in dementia is common in the U.S. Drivers of diagnostic delay are poorly understood, but appear related to misconceptions about dementia, stigma, concerns about autonomy, the nature of the diagnostic process, and provider-related factors. There is little quantitative evidence underlying cited risks and benefits of receiving a diagnosis around the time of dementia onset, including impacts on physical health, impacts on mental health, care partner interactions, costs of care, increased time for care planning, or earlier access to treatment. While various groups continue to push for reductions in diagnostic delay, realization of benefits and mitigation of harms will require new research on potential benefits and harms. Workforce and resource constraints, coupled with the expected growth in the number of persons living with dementia, may be a barrier to realization of potential benefits and mitigation of identified harms, which will require adequate access to providers, services, and supports. [ABSTRACT FROM AUTHOR]