The social exposome measures all of the social exposures that a person experiences over a lifetime. Researchers are only beginning to understand the role of upstream, neighborhood-level factors in Alzheimer disease and related dementias (ADRD) risk and their association with biological pathways affecting ADRD.
Neighborhood disadvantage, a social exposome measure reflecting income, educational level, employment status, and housing in a Census-block group or neighborhood, has been associated with markers of ADRD brain health, including amyloid plaque.1 Whether this association extends to neurofibrillary pathology is unknown. This study evaluated the association between neurofibrillary tangles and neighborhood disadvantage.
This cross-sectional study was conducted using a sample of decedents from 2 Alzheimer’s Disease Research Center (ADRC) brain banks with previously assessed neurofibrillary tangle deposition and neighborhood disadvantage ranking from 1993 to 2016. Before death, decedents were recruited by ADRC brain donor programs and consented to brain donation for research purposes. The institutional review boards of University of Wisconsin and University of California, San Diego exempted the study because it was not human participant research. We followed the STROBE reporting guideline.
We abstracted neurofibrillary tangle B scores, per National Institute on Aging and Alzheimer’s Association neuropathological change guidelines,2 from the standardized Neuropathology Data Set form or original autopsy reports (following established methods and neuropathologist guidance from both ADRCs) to measure Alzheimer disease–associated neurofibrillary pathology.1,3 Twenty-five decedents without neurofibrillary tangle assessment were excluded. Decedents’ last address was geolinked to their statewide ranking of neighborhood disadvantage using a time-concordant area deprivation index, with higher values denoting greater neighborhood disadvantage.4 Generalized ordered logistic regression with site-level clustered SEs was used to model the ordinal B score adjusted for covariates regularly available across the 24-year data time frame: age, sex, and year of death of 2005 or later (ie, introductory year for standard reporting using the Uniform Data Set). Data were analyzed from May 3 to November 17, 2021, using Stata/MP version 16.1 (StataCorp LLC).
The sample of 428 decedents had a mean (SD) age of 80.5 (9.1) years (237 men [55.4%] and 191 women [44.6%]) and tended to be from less disadvantaged neighborhoods (mean [SD] area deprivation index decile rank: 3.8 [2.4]) (Table). Nearly all (95.8%) had neurofibrillary tangles, which was consistent with ADRC brain donation samples. Modeled analysis suggested that, for every decile increase in neighborhood disadvantage, there was a 5% increase in the odds of a higher B score (odds ratio [OR], 1.05; 95% CI, 1.01-1.08) after adjustments (Table). This translated into an estimated 56% increased odds of a higher B score for those in the most disadvantaged neighborhood decile (OR, 1.56; 95% CI, 1.09-2.23) (Figure). Sensitivity analysis using Braak staging, instead of B scores, suggested similar estimated odds (OR, 1.04; 95% CI, 1.02-1.06).
With these new findings, neighborhood disadvantage has now been found to be associated with neurofibrillary tangles and amyloid plaques,1 the primary pathological features of Alzheimer disease. Study limitations emphasize the need for additional infrastructure, data, and insight to address selection bias in brain donation, underrepresentation of decedents from disadvantaged neighborhoods, and generalizability.
Neighborhood disadvantage may serve a role in identifying ADRD biological processes and/or be a marker of related adverse exposures. Therefore, a nuanced understanding is needed of the pathways through which neighborhood conditions may associate or interact with other factors to affect ADRD-related brain changes.5 Mechanisms linking neighborhood disadvantage with tau accumulations might include multiple and overlapping factors (eg, stress, depression, sleep disruption, and constraints on health behaviors; pollution; and cardiovascular risks).6 Future work will require coordinated involvement among ADRCs for larger, more generalizable samples and additional data linkages to explore the mediating and moderating risk factors involved.
Neuropathological changes in ADRD accumulate over decades. Life-course approaches to describing neighborhood disadvantage exposure should include testing dose-response associations, identifying critical thresholds that place people at elevated risk, pinpointing sensitive life periods, and uncovering factors that mitigate the impact of exposure.
Accepted for Publication: March 7, 2022.
Published: April 28, 2022. doi:10.1001/jamanetworkopen.2022.8966
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Powell WR et al. JAMA Network Open.
Corresponding Author: W. Ryan Powell, PhD, Center for Health Disparities Research, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI 53792 (rpowell@medicine.wisc.edu).
Author Contributions: Dr Powell had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Powell, Bendlin, Kind.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Powell, Zuelsdorff, Rissman.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Powell.
Obtained funding: Bendlin, Kind.
Administrative, technical, or material support: Powell, Keller, Betthauser, Rissman, Kind.
Supervision: Powell, Kind.
Conflict of Interest Disclosures: Dr Zuelsdorff reported receiving grants from the Alzheimer's Association during the conduct of the study. Dr Kind reported receiving grants from the National Institutes of Health during the conduct of the study. No other disclosures were reported.
Funding/Support: This study was supported by grants RF1AG057784 and R01AG070883 (Drs Bendlin and Kind), P30AG062715, and P30AG062429 from the National Institute on Aging and by grant R01MD010243 (Dr Kind) from the National Institute on Minority Health and Health Disparities. This work was also supported with the resources and facilities at the Center for Health Disparities Research at the University of Wisconsin School of Medicine and Public Health.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: The views expressed herein are those of the authors and do not reflect the official policy or position of the National Institutes of Health.
Additional Contributions: M. Shahriar Salamat, MD, PhD; William R. Buckingham, PhD; and Leigha Vilen, BA, University of Wisconsin, assisted with the acquisition, analysis, and interpretation of data; provided technical expertise; and reviewed the manuscript. These individuals received no additional compensation, outside of their usual salary, for their contributions.