Background: Evidence suggests that long-term exposure to air pollution may increase the risk of dementia and related cognitive outcomes. A major source of air pollution is automotive traffic, which is modifiable by technological and regulatory interventions.
Objectives: We examined associations of four traffic-related air pollutants with rates of cognitive decline in a cohort of older adults.
Existing studies examining the predictive ability of biomarkers for cognitive outcomes do not account for variance due to measurement error, which could lead to under-estimates of the proportion of variance explained. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1084) to estimate the proportion of variance explained by Alzheimer's disease (AD) imaging biomarkers in four cognitive outcomes: memory, executive functioning, language, and visuospatial functioning. We compared estimates from standard models that do not account for measurement error, and multilevel models that do account for measurement error.
View Article and Find Full Text PDFIntroduction: Loneliness has a rising public health impact, but research involving neuropathology and representative cohorts has been limited.
Methods: Inverse odds of selection weights were generalized from the autopsy sample of Rush Alzheimer's Disease Center cohorts (N = 680; 89 ± 9 years old; 25% dementia) to the US-representative Health and Retirement Study (N = 8469; 76 ± 7 years old; 5% dementia) to extend external validity. Regressions tested cross-sectional associations between loneliness and (1) Alzheimer's disease (AD) and cerebrovascular pathology; (2) five cognitive domains; and (3) relationships between pathology and cognition, adjusting for depression.
Motivation: The Peter Clark (PC) algorithm is a popular causal discovery method to learn causal graphs in a data-driven way. Until recently, existing PC algorithm implementations in R had important limitations regarding missing values, temporal structure or mixed measurement scales (categorical/continuous), which are all common features of cohort data. The new R packages presented here, micd and tpc, fill these gaps.
View Article and Find Full Text PDFObjectives: Sensory impairment is a hypothesized risk factor for cognitive decline; however, the psychosocial pathways are not well understood. We evaluated whether the association between visual impairment (VI) and cognitive decline was partially mediated via depressive symptoms, loneliness, or social activity.
Methods: We used data from 2601 older adults enrolled in the Memory and Aging Project in 1997 and the Minority Aging Research Study in 2004 with neuropsychological tests across five domains measured annually for up to 16 years.
Background: An important epidemiological question is understanding how vascular risk factors contribute to cognitive impairment. Using data from the Cardiovascular Health Cognition Study, we investigated how subclinical cardiovascular disease (sCVD) relates to cognitive impairment risk and the extent to which the hypothesized risk is mediated by the incidence of clinically manifested cardiovascular disease (CVD), both overall and within apolipoprotein E-4 (APOE-4) subgroups.
Methods: We adopted a novel "separable effects" causal mediation framework that assumes that sCVD has separably intervenable atherosclerosis-related components.
The paper examines whether leads to incident mild cognitive impairment and dementia through brain hypoperfusion and white matter disease. We performed inverse odds ratio weighted causal mediation analyses to decompose the effect of diabetes on cognitive impairment into direct and indirect effects, and we found that approximately a third of the total effect of diabetes is mediated through vascular-related brain pathology. Our findings lend support for a common aetiological hypothesis regarding incident cognitive impairment, which is that diabetes increases the risk of clinical cognitive impairment in part by impacting the vasculature of the brain.
View Article and Find Full Text PDFCausal mediation analysis is a useful tool for epidemiologic research, but it has been criticized for relying on a "cross-world" independence assumption that counterfactual outcome and mediator values are independent even in causal worlds where the exposure assignments for the outcome and mediator differ. This assumption is empirically difficult to verify and problematic to justify based on background knowledge. In the present article, we aim to assist the applied researcher in understanding this assumption.
View Article and Find Full Text PDFBackground: The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression.
View Article and Find Full Text PDFPurpose: Regular physical activity is a key component of healthy aging, but few older adults meet physical activity guidelines. Poor aging expectations can contribute to this lack of activity, since negative stereotypes about the aging process can be internalized and affect physical performance. Although prior cross-sectional studies have shown that physical activity and aging expectations are associated, less is known about this association longitudinally, particularly among traditionally underrepresented groups.
View Article and Find Full Text PDF