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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 [...]

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 [...]

Background: Observational studies link high midlife systolic blood pressure to increased dementia risk. However, the synthesis of evidence from randomized controlled trials has not definitively demonstrated that antihypertensive medication use reduces dementia risk. Here, we emulate target trials of antihypertensive medication initiation on incident dementia using three cohort studies, with attention to potential violations of necessary assumptions. Methods: We emulated trials of antihypertensive medication initiation on incident dementia using data from the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, and Health and Retirement Study. We used data-driven methods to restrict participants to initiators and noninitiators with overlap in propensity scores and positive control outcomes to look for violations of positivity and exchangeability assumptions. Results: Analyses were limited by the small number of cohort participants who met eligibility criteria. Associations between antihypertensive medication initiation and incident dementia were inconsistent and imprecise (Atherosclerosis Risk in Communities: HR = 0.30 [0.05, 1.93]; Cardiovascular Health Study: HR = 0.66 [0.27, 1.64]; Health and Retirement Study: HR = 1.09 [0.75, 1.59]). More stringent propensity score restrictions had little effect on findings. Sensitivity analyses using a positive control outcome unexpectedly suggested antihypertensive medication initiation increased the risk of coronary heart disease in all three samples. Conclusions: Positive control outcome analyses suggested substantial residual confounding in effect estimates from our target trials, precluding conclusions about the impact of antihypertensive medication initiation on dementia risk through target trial emulation. Formalized processes for identifying violations of necessary assumptions will strengthen confidence in target trial emulation and avoid inappropriate confidence in emulated trial results. [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: 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). [...]

Dietary copper intake may be associated with cognitive decline and dementia. We used data from 10,269 participants of the Atherosclerosis Risks in Communities Study to study the associations of dietary copper intake with 20-year cognitive decline and incident dementia. Dietary copper intake from food and supplements was quantified using food frequency questionnaires. Cognition was assessed using 3 cognitive tests at study visits; dementia was ascertained at study visits and via surveillance. Multiple imputation by chained equations was applied to account for the missing information of cognitive function during follow-up. Survival analysis with parametric models and mixed-effect models were used to estimate the associations for incident dementia and cognitive decline, respectively. During 20 years of follow-up (1996–1998 to 2016–2017), 1,862 incident cases of dementia occurred. Higher intake of dietary copper from food was associated with higher risk of incident dementia among those with high intake of saturated fat (hazard ratio = 1.49, 95% confidence interval: 1.04, 1.95). Higher intake of dietary copper from food was associated with greater decline in language overall (beta = −0.12, 95% confidence interval: −0.23, −0.02). Therefore, a diet high in copper, particularly when combined with a diet high in saturated fat, may increase the risk of cognitive impairment. [ABSTRACT FROM AUTHOR]

Introduction: Clinic‐based study samples, including the Alzheimer's Disease Neuroimaging Initiative (ADNI), offer rich data, but findings may not generalize to community‐based settings. We compared associations in ADNI to those in the Atherosclerosis Risk in Communities (ARIC) study to assess generalizability across the two settings. Methods: We estimated cohort‐specific associations among risk factors, cognitive test scores, and neuroimaging outcomes to identify and quantify the extent of significant and substantively meaningful differences in associations between cohorts. We explored whether using more homogenous samples improved comparability in effect estimates. Results: The proportion of associations that differed significantly between cohorts ranged from 27% to 34% across sample subsets. Many differences were substantively meaningful (e.g., odds ratios [OR] for apolipoprotein E ε4 on amyloid positivity in ARIC: OR = 2.8, in ADNI: OR = 8.6). Discussion: A higher proportion of associations differed significantly and substantively than would be expected by chance. Findings in clinical samples should be confirmed in more representative samples. [ABSTRACT FROM AUTHOR]

Background: A number of studies show an association between long‐term exposure to ambient particulate matter ≤ 2.5 um (PM2.5) and late‐life cognitive impairment. Mechanistic models suggest that PM2.5 may influence cognitive health through promotion of Alzheimer's disease, which is characterized by brain amyloid accumulation. However, the association between long‐term PM2.5 exposure and brain amyloid deposition remains poorly characterized in epidemiological studies. Method: We used data from the Atherosclerosis Risk in Communities (ARIC) study cohort. We used a chemical transport model with data fusion to estimate mean PM2.5 concentrations (ug/m3) in 36‐, 12‐, 4‐, and 1‐km grid cells in ARIC study areas. We linked the concentrations to geocoded participant addresses and calculated mean PM2.5 concentrations from 2000 to 2007. We estimated amyloid deposition using florbetapir amyloid positron emission tomography (PET) scans in 346 ARIC‐PET participants with normal cognition or mild cognitive impairment in 2011‐2014. We defined amyloid positivity as a global cortical standardized uptake value ratio (SUVR) ≥ the sample median of 1.2. We used logistic regression models to quantify the association between amyloid positivity and mean 2000‐2007 PM2.5 concentration after adjusting for potential confounders. We additionally explored effect measure modification by APOE e4 allele status and tested whether effect estimates were consistent using alternate PM2.5 exposure methods. Result: After restricting to participants with non‐missing exposure and confounder data and excluding one participant with dementia, the analytic sample included 279 participants. At the time of amyloid‐PET scans, their mean age was 78 years, 56% were female, 42% were Black, and 26% had mild cognitive impairment. After adjusting for age, sex, education, and race‐study center, we found no significant association between brain amyloid positivity and long‐term mean PM2.5 exposure. We also found no evidence of effect measure modification by APOE e4 allele status. Results were consistent when we used alternate PM2.5 estimation methods. Conclusion: Our findings suggest that ambient PM2.5 may induce neurotoxic effects through non‐amyloid, potentially vascular pathways, though we note the small sample size may have made us underpowered to detect a significant association. [ABSTRACT FROM AUTHOR]

The article focuses on the Central Hudson-plus test developed by the U.S. Supreme Court in Sorrell v. IMS Health, Inc. for evaluating viewpoint discriminatory commercial speech restriction. It explores the evolution of the commercial speech doctrine, and also discusses Central Hudson Gas & Electric Corp. v. Public Service Commission of New York. It suggests that the U.S. Food & Drug Administration (FDA) should align its regulatory policies with the Supreme Court-s First Amendment ideology

Introduction: Ensuring adequate and equitable distribution of resources to support persons living with dementia relies on understanding the burden and distribution of dementia in a population. Our goal was to develop an approach to estimate dementia prevalence at the local level in the United States using publicly available data., Methods: Our approach combines publicly available data on dementia prevalence and demographic data from the US Census to estimate dementia prevalence. We illustrate this approach by estimating dementia prevalence in persons aged 65 and older in Philadelphia, PA; Chicago, IL; and Atlanta, GA., Results: Overall, we estimate the prevalence of dementia among those 65 and older to be 11.9% in Philadelphia, 11.8% Chicago, and 12.3% in Atlanta. Estimates across Philadelphia localities vary from 9.3% to 15.9%., Discussion: Our approach provides a cost-effective method to generate estimates of dementia prevalence at the local level., Highlights: Brain health needs assessments require understanding of local dementia prevalence.Our approach can be used to estimate dementia prevalence in individual communities.This information can inform decisions about distribution of resources., Competing Interests: Melinda C. Power reports grants from the United States National Institutes of Health (NIH), Department of Defense (DOD), and DC Health. N Maritza Dowling reports grants from the United States National Institutes of Health (NIH). All authors were supported by a grant from DC Health., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Introduction: Clinic-based study samples, including the Alzheimer's Disease Neuroimaging Initiative (ADNI), offer rich data, but findings may not generalize to community-based settings. We compared associations in ADNI to those in the Atherosclerosis Risk in Communities (ARIC) study to assess generalizability across the two settings., Methods: We estimated cohort-specific associations among risk factors, cognitive test scores, and neuroimaging outcomes to identify and quantify the extent of significant and substantively meaningful differences in associations between cohorts. We explored whether using more homogenous samples improved comparability in effect estimates., Results: The proportion of associations that differed significantly between cohorts ranged from 27% to 34% across sample subsets. Many differences were substantively meaningful (e.g., odds ratios [OR] for apolipoprotein E ε4 on amyloid positivity in ARIC: OR = 2.8, in ADNI: OR = 8.6)., Discussion: A higher proportion of associations differed significantly and substantively than would be expected by chance. Findings in clinical samples should be confirmed in more representative samples., (© 2021 the Alzheimer's Association.)