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Best JR. Individual socioeconomic status, neighborhood disadvantage, and cognitive aging: A longitudinal analysis of the CLSA. J Am Geriatr Soc 2024. [PMID: 39177423 DOI: 10.1111/jgs.19155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/22/2024] [Accepted: 08/01/2024] [Indexed: 08/24/2024]
Abstract
BACKGROUND There are likely many contributors to variation in the rate of cognitive decline in middle and late adulthood, including individual and neighborhood socio-economic factors. This study examines whether individual socio-economic factors, namely income and wealth, correlate with cognitive decline, in part, through neighborhood-level social and material disadvantage. METHODS Using the three waves of data collection from the Canadian Longitudinal Study on Aging (CLSA), this study included 51,338 participants between the age of 45 and 85 years at baseline (51% female). Individual socio-economic status (SES) was assessed by annual household income and by the current value of savings and investments. Neighborhood disadvantage was measured by area-based material and social deprivation indices. Cognition was measured at each wave using verbal fluency, mental alternations, and delayed word recall. Latent change score models, incorporating direct and indirect pathways, were constructed to estimate the indirect effect of individual SES on cognitive change through area-level disadvantage. Multi-group models were constructed on the basis of age-group (45-64 years; 65-74 years; or 75+ years) to allow for varying estimates across age. RESULTS Among 45-64-year-olds, income and wealth had indirect effects on initial cognitive level and on rate of cognitive decline through material disadvantage (standardized indirect effects = 0.01, p < 0.001), but only wealth had an indirect effect through social disadvantage (p = 0.019). Among 65-74-year-olds, income and wealth had indirect effects on initial cognitive level (p < 0.01) but not on rate of cognitive decline (p > 0.05), and among 75+ year-olds, no indirect effects were observed (p > 0.05). Wealth and income had direct effects, independent of neighborhood disadvantage, on cognition in all age groups (p < 0.05). CONCLUSIONS Among middle-aged adults, greater individual SES may mitigate cognitive decline, in part, by allowing individuals to live in more materially and socially advantaged neighborhoods.
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Affiliation(s)
- John R Best
- Department of Gerontology, Simon Fraser University, Vancouver, British Columbia, Canada
- Gerontology Research Centre, Simon Fraser University, Vancouver, British Columbia, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
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Shaheen A, Medeiros FA, Swaminathan SS. Association Between Greater Social Vulnerability and Delayed Glaucoma Surgery. Am J Ophthalmol 2024; 268:123-135. [PMID: 39089357 DOI: 10.1016/j.ajo.2024.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 07/05/2024] [Accepted: 07/23/2024] [Indexed: 08/03/2024]
Abstract
PURPOSE Timing of surgical intervention in glaucoma is crucial to preserving sight. While ocular characteristics that increase surgical risk are known, the impact of neighborhood-level social risk factors such as the Social Vulnerability Index (SVI) and Area Deprivation Index (ADI) on time to glaucoma surgery is unknown. The objective of this study was to evaluate the association between SVI or ADI scores and the timing of glaucoma surgical intervention. DESIGN Retrospective cohort study. METHODS Adult subjects with open-angle glaucoma were identified from the Bascom Palmer Glaucoma Repository using International Classification of Disease-10 codes. Subject demographics, ocular characteristics, and standard automated perimetry data were extracted. Geocoded data were obtained using subject residences and American Community Survey data. Univariable and multivariable time-to-event survival analyses using accelerated failure time models were completed to evaluate whether geocoded SVI and ADI scores accelerated or delayed time to glaucoma surgery from initial glaucoma diagnosis in the electronic health record. RESULTS A total of 10,553 eyes from 6934 subjects were evaluated, of which 637 eyes (6.0%) from 568 subjects (8.2%) underwent glaucoma surgery. Mean age was 68.3 ± 13.5 years, with 57.9% female, 21.5% Black, and 34.5% Hispanic subjects. Mean follow-up time was 5.0 ± 2.1 years, with time to surgery of 3.2 ± 1.9 years. Multivariable accelerated failure time models demonstrated that higher mean intraocular pressure (time ratio [TR] 0.27 per 5 mm Hg higher; 95% confidence interval [CI]: 0.23-0.31, P < .001), faster standard automated perimetry rate of progression (TR 0.74 per 0.5 dB/year faster; 95% CI: 0.69-0.78, P < .001), moderate (TR 0.69; 95% CI: 0.56-0.85, P < .001) or severe baseline severity (TR 0.39; 95% CI: 0.32-0.47, P < .001), and thinner central corneal thickness (TR 0.85 per 50 µm thinner; 95% CI: 0.77-0.95, P = .003) all accelerated time to surgery. In contrast, overall SVI delayed surgery (TR 1.11 per 25% increase; 95% CI: 1.03-1.20, P = .006). Specifically, SVI Themes 1 (TR 1.08; 95% CI: 1.01-1.17, P = .037) and 4 (TR 1.11; 95% CI: 1.03-1.19, P = .006) were significant. Patients from the most deprived neighborhoods (highest national ADI quartile) had a 68% increase in time to surgery compared to the least deprived quartile (TR 1.68; 95% CI: 1.20-2.36, P = .002). CONCLUSIONS Residence in areas with higher SVI or ADI scores was associated with delayed glaucoma surgery after controlling for demographic and ocular parameters. Awareness of such disparities can guide initiatives aimed at achieving parity in health outcomes.
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Affiliation(s)
- Abdulla Shaheen
- From the Department of Ophthalmology, Bascom Palmer Eye Institute (A.S., F.A.M., S.S.S.), University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Felipe A Medeiros
- From the Department of Ophthalmology, Bascom Palmer Eye Institute (A.S., F.A.M., S.S.S.), University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Swarup S Swaminathan
- From the Department of Ophthalmology, Bascom Palmer Eye Institute (A.S., F.A.M., S.S.S.), University of Miami Miller School of Medicine, Miami, Florida, USA.
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Reuben A, Richmond‐Rakerd LS, Milne B, Shah D, Pearson A, Hogan S, Ireland D, Keenan R, Knodt AR, Melzer T, Poulton R, Ramrakha S, Whitman ET, Hariri AR, Moffitt TE, Caspi A. Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth-cohort geographic analyses. Alzheimers Dement 2024; 20:3167-3178. [PMID: 38482967 PMCID: PMC11095428 DOI: 10.1002/alz.13727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 12/15/2023] [Accepted: 01/11/2024] [Indexed: 04/06/2024]
Abstract
INTRODUCTION Dementia risk may be elevated in socioeconomically disadvantaged neighborhoods. Reasons for this remain unclear, and this elevation has yet to be shown at a national population level. METHODS We tested whether dementia was more prevalent in disadvantaged neighborhoods across the New Zealand population (N = 1.41 million analytic sample) over a 20-year observation. We then tested whether premorbid dementia risk factors and MRI-measured brain-structure antecedents were more prevalent among midlife residents of disadvantaged neighborhoods in a population-representative NZ-birth-cohort (N = 938 analytic sample). RESULTS People residing in disadvantaged neighborhoods were at greater risk of dementia (HR per-quintile-disadvantage-increase = 1.09, 95% confidence interval [CI]:1.08-1.10) and, decades before clinical endpoints typically emerge, evidenced elevated dementia-risk scores (CAIDE, LIBRA, Lancet, ANU-ADRI, DunedinARB; β's 0.31-0.39) and displayed dementia-associated brain structural deficits and cognitive difficulties/decline. DISCUSSION Disadvantaged neighborhoods have more residents with dementia, and decades before dementia is diagnosed, residents have more dementia-risk factors and brain-structure antecedents. Whether or not neighborhoods causally influence risk, they may offer scalable opportunities for primary dementia prevention.
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Affiliation(s)
- Aaron Reuben
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesMedical University of South CarolinaCharlestonSouth CarolinaUSA
| | | | - Barry Milne
- Centre for Methods and Policy Application in Society SciencesUniversity of AucklandAucklandNew Zealand
| | - Devesh Shah
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Amber Pearson
- Department of Geography, Environment, and Spatial SciencesMichigan State UniversityEast LansingMichiganUSA
- Department of Public HealthUniversity of OtagoWellingtonNew Zealand
| | - Sean Hogan
- Dunedin Multidisciplinary Health and Development Research Unit, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - David Ireland
- Brain Health Research Centre, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Ross Keenan
- Brain Health Research Centre, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Annchen R. Knodt
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Tracy Melzer
- Department of MedicineUniversity of OtagoChristchurchNew Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Ethan T. Whitman
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Ahmad R. Hariri
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Terrie E. Moffitt
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
- King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & NeuroscienceLondonUK
- PROMENTA, Department of PsychologyUniversity of OsloOsloNorway
| | - Avshalom Caspi
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
- King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & NeuroscienceLondonUK
- PROMENTA, Department of PsychologyUniversity of OsloOsloNorway
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Melcher EM, Vilen L, Pfaff A, Lim S, DeWitt A, Powell WR, Bendlin BB, Kind AJH. Deriving life-course residential histories in brain bank cohorts: A feasibility study. Alzheimers Dement 2024; 20:3219-3227. [PMID: 38497250 PMCID: PMC11095419 DOI: 10.1002/alz.13773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 03/19/2024]
Abstract
INTRODUCTION The exposome is theorized to interact with biological mechanisms to influence risk for Alzheimer's disease but is not well-integrated into existing Alzheimer's Disease Research Center (ADRC) brain bank data collection. METHODS We apply public data tracing, an iterative, dual abstraction and validation process rooted in rigorous historic archival methods, to develop life-course residential histories for 1254 ADRC decedents. RESULTS The median percentage of the life course with an address is 78.1% (IQR 24.9); 56.5% of the sample has an address for at least 75% of their life course. Archivists had 89.7% agreement at the address level. This method matched current residential survey methodology 97.4% on average. DISCUSSION This novel method demonstrates feasibility, reproducibility, and rigor for historic data collection. To our knowledge, this is the first study to show that public data tracing methods for brain bank decedent residential history development can be used to better integrate the social exposome with biobank specimens. HIGHLIGHTS Public data tracing compares favorably to survey-based residential history. Public data tracing is feasible and reproducible between archivists. Archivists achieved 89.7% agreement at the address level. This method identifies residences for nearly 80% of life-years, on average. This novel method enables brain banks to add social characterizations.
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Affiliation(s)
- Eleanna M. Melcher
- Department of Population Health SciencesUniversity of Wisconsin School of Medicine and Public HealthWarf Office BldgMadisonUSA
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
| | - Leigha Vilen
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
| | - Aly Pfaff
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
| | - Sarah Lim
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
| | - Amanda DeWitt
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
| | - W. Ryan Powell
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
- Department of Medicine Division of Geriatrics and GerontologyUniversity of Wisconsin School of Medicine and Public Health, 1685 Highland Avenue, 5158Medical Foundation Centennial BuildingMadisonUSA
| | - Barbara B. Bendlin
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
- Department of Medicine Division of Geriatrics and GerontologyUniversity of Wisconsin School of Medicine and Public Health, 1685 Highland Avenue, 5158Medical Foundation Centennial BuildingMadisonUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonUSA
| | - Amy J. H. Kind
- Center for Health Disparities ResearchUniversity of Wisconsin School of Medicine and Public HealthUW Hospital and ClinicsMadisonUSA
- Department of Medicine Division of Geriatrics and GerontologyUniversity of Wisconsin School of Medicine and Public Health, 1685 Highland Avenue, 5158Medical Foundation Centennial BuildingMadisonUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonUSA
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Pett L, Li Z, Abrishamcar S, Hodge K, Everson T, Christensen G, Gearing M, Kobor MS, Konwar C, MacIsaac JL, Dever K, Wingo AP, Levey A, Lah JJ, Wingo TS, Hüls A. The association between neighborhood deprivation and DNA methylation in an autopsy cohort. Aging (Albany NY) 2024; 16:6694-6716. [PMID: 38663907 PMCID: PMC11087100 DOI: 10.18632/aging.205764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 03/18/2024] [Indexed: 05/08/2024]
Abstract
Previous research has found that living in a disadvantaged neighborhood is associated with poor health outcomes. Living in disadvantaged neighborhoods may alter inflammation and immune response in the body, which could be reflected in epigenetic mechanisms such as DNA methylation (DNAm). We used robust linear regression models to conduct an epigenome-wide association study examining the association between neighborhood deprivation (Area Deprivation Index; ADI), and DNAm in brain tissue from 159 donors enrolled in the Emory Goizueta Alzheimer's Disease Research Center (Georgia, USA). We found one CpG site (cg26514961, gene PLXNC1) significantly associated with ADI after controlling for covariates and multiple testing (p-value=5.0e-8). Effect modification by APOE ε4 was statistically significant for the top ten CpG sites from the EWAS of ADI, indicating that the observed associations between ADI and DNAm were mainly driven by donors who carried at least one APOE ε4 allele. Four of the top ten CpG sites showed a significant concordance between brain tissue and tissues that are easily accessible in living individuals (blood, buccal cells, saliva), including DNAm in cg26514961 (PLXNC1). Our study identified one CpG site (cg26514961, PLXNC1 gene) that was significantly associated with neighborhood deprivation in brain tissue. PLXNC1 is related to immune response, which may be one biological pathway how neighborhood conditions affect health. The concordance between brain and other tissues for our top CpG sites could make them potential candidates for biomarkers in living individuals.
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Affiliation(s)
- Lindsay Pett
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Zhenjiang Li
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Sarina Abrishamcar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Kenyaita Hodge
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Todd Everson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Grace Christensen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Marla Gearing
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Michael S. Kobor
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Chaini Konwar
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
| | - Julia L. MacIsaac
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Kristy Dever
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Aliza P. Wingo
- Division of Mental Health, Atlanta VA Medical Center, Decatur, GA 30033, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Allan Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - James J. Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Thomas S. Wingo
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Human Genetics, Emory University, Atlanta, GA 30322, USA
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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Kim B, Yannatos I, Blam K, Wiebe D, Xie SX, McMillan CT, Mechanic‐Hamilton D, Wolk DA, Lee EB. Neighborhood disadvantage reduces cognitive reserve independent of neuropathologic change. Alzheimers Dement 2024; 20:2707-2718. [PMID: 38400524 PMCID: PMC11032541 DOI: 10.1002/alz.13736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/12/2024] [Accepted: 01/16/2024] [Indexed: 02/25/2024]
Abstract
INTRODUCTION Individuals in socioeconomically disadvantaged neighborhoods exhibit increased risk for impaired cognitive function. Whether this association relates to the major dementia-related neuropathologies is unknown. METHODS This cross-sectional study included 469 autopsy cases from 2011 to 2023. The relationships between neighborhood disadvantage measured by Area Deprivation Index (ADI) percentiles categorized into tertiles, cognition evaluated by the last Mini-Mental State Examination (MMSE) scores before death, and 10 dementia-associated proteinopathies and cerebrovascular disease were assessed using regression analyses. RESULTS Higher ADI was significantly associated with lower MMSE score. This was mitigated by increasing years of education. ADI was not associated with an increase in dementia-associated neuropathologic change. Moreover, the significant association between ADI and cognition remained even after controlling for changes in major dementia-associated proteinopathies or cerebrovascular disease. DISCUSSION Neighborhood disadvantage appears to be associated with decreased cognitive reserve. This association is modified by education but is independent of the major dementia-associated neuropathologies.
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Affiliation(s)
- Boram Kim
- Translational Neuropathology Research LaboratoryDepartment of Pathology and Laboratory MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Isabel Yannatos
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kaitlin Blam
- Translational Neuropathology Research LaboratoryDepartment of Pathology and Laboratory MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Douglas Wiebe
- Department of Emergency MedicineDepartment of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Sharon X. Xie
- Department of BiostatisticsEpidemiology and InformaticsPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dawn Mechanic‐Hamilton
- Penn Memory CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Penn Memory CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Edward B. Lee
- Translational Neuropathology Research LaboratoryDepartment of Pathology and Laboratory MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Michael YL, Senerat AM, Buxbaum C, Ezeanyagu U, Hughes TM, Hayden KM, Langmuir J, Besser LM, Sánchez B, Hirsch JA. Systematic Review of Longitudinal Evidence and Methodologies for Research on Neighborhood Characteristics and Brain Health. Public Health Rev 2024; 45:1606677. [PMID: 38596450 PMCID: PMC11002187 DOI: 10.3389/phrs.2024.1606677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 02/20/2024] [Indexed: 04/11/2024] Open
Abstract
Objective: Synthesize longitudinal research evaluating neighborhood environments and cognition to identify methodological approaches, findings, and gaps. Methods: Included studies evaluated associations between neighborhood and cognition longitudinally among adults >45 years (or mean age of 65 years) living in developed nations. We extracted data on sample characteristics, exposures, outcomes, methods, overall findings, and assessment of disparities. Results: Forty studies met our inclusion criteria. Most (65%) measured exposure only once and a majority focused on green space and/or blue space (water), neighborhood socioeconomic status, and recreation/physical activity facilities. Similarly, over half studied incident impairment, cognitive function or decline (70%), with one examining MRI (2.5%) or Alzheimer's disease (7.5%). While most studies used repeated measures analysis to evaluate changes in the brain health outcome (51%), many studies did not account for any type of correlation within neighborhoods (35%). Less than half evaluated effect modification by race/ethnicity, socioeconomic status, and/or sex/gender. Evidence was mixed and dependent on exposure or outcome assessed. Conclusion: Although longitudinal research evaluating neighborhood and cognitive decline has expanded, gaps remain in types of exposures, outcomes, analytic approaches, and sample diversity.
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Affiliation(s)
- Yvonne L. Michael
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Araliya M. Senerat
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Channa Buxbaum
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Ugonwa Ezeanyagu
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Timothy M. Hughes
- Department of Internal Medicine, Medical Center Boulevard, Winston-Salem, NC, United States
| | - Kathleen M. Hayden
- Department of Social Sciences and Health Policy, Bowman Gray Center for Medical Education, Winston-Salem, NC, United States
| | - Julia Langmuir
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Lilah M. Besser
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Brisa Sánchez
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Jana A. Hirsch
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
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Zuelsdorff M, Limaye VS. A Framework for Assessing the Effects of Climate Change on Dementia Risk and Burden. THE GERONTOLOGIST 2024; 64:gnad082. [PMID: 37392416 PMCID: PMC10860581 DOI: 10.1093/geront/gnad082] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Indexed: 07/03/2023] Open
Abstract
Alzheimer's disease and related dementias (ADRD) represent a public health crisis poised to worsen in a changing climate. Substantial dementia burden is modifiable, attributable to risk rooted in social and environmental conditions. Climate change threatens older populations in numerous ways, but implications for cognitive aging are poorly understood. We illuminate key mechanisms by which climate change will shape incidence and lived experiences of ADRD, and propose a framework for strengthening research, clinical, and policy actions around cognitive health in the context of climate change. Direct impacts and indirect risk pathways operating through built, social, interpersonal, and biomedical systems are highlighted. Air pollution compromises brain health directly and via systemic cardiovascular and respiratory ailments. Flooding and extreme temperatures constrain health behaviors like physical activity and sleep. Medical care resulting from climate-related health shocks imposes economic and emotional tolls on people living with dementia and caregivers. Throughout, inequitable distributions of climate-exacerbated risks and adaptive resources compound existing disparities in ADRD incidence, comorbidities, and care burden. Translational research, including work prioritizing underserved communities, is crucial. A mechanistic framework can guide research questions and methods and identify clinical- and policy-level intervention loci for prevention and mitigation of climate-related impacts on ADRD risk and burden.
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Affiliation(s)
- Megan Zuelsdorff
- School of Nursing, University of Wisconsin–Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Vijay S Limaye
- Science Office, Natural Resources Defense Council, New York City, New York, USA
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Peterson RL, Pejak R, George KM, Gilsanz P, Ko M, Meyer OL, Mayeda ER, Kind A, Whitmer RA. Race, community disadvantage, and cognitive decline: Findings from KHANDLE and STAR. Alzheimers Dement 2024; 20:904-913. [PMID: 37817548 PMCID: PMC10917037 DOI: 10.1002/alz.13511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/24/2023] [Accepted: 09/19/2023] [Indexed: 10/12/2023]
Abstract
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.
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Affiliation(s)
- Rachel L. Peterson
- School of Public and Community Health SciencesUniversity of MontanaMissoulaMontanaUSA
| | - Rebecca Pejak
- School of Public and Community Health SciencesUniversity of MontanaMissoulaMontanaUSA
| | - Kristen M. George
- Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Paola Gilsanz
- Division of ResearchKaiser Permanente Northern CaliforniaOaklandCaliforniaUSA
| | - Michelle Ko
- Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Oanh L. Meyer
- Department of NeurologyUniversity of California DavisDavisCaliforniaUSA
| | - Elizabeth Rose Mayeda
- Fielding School of Public HealthUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Amy Kind
- University of Wisconsin Center for Health Disparities ResearchMadisonWisconsinUSA
| | - Rachel A. Whitmer
- Departments of Public Health Sciences and NeurologyUniversity of California DavisDavisCaliforniaUSA
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Golden BP, Block L, Benson C, Cotton QD, Wieben A, Kaiksow F, Gilmore-Bykovskyi A. Experiences of in-hospital care among dementia caregivers in the context of high neighborhood-level disadvantage. J Am Geriatr Soc 2023; 71:3435-3444. [PMID: 37548026 PMCID: PMC10841110 DOI: 10.1111/jgs.18541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/16/2023] [Accepted: 06/25/2023] [Indexed: 08/08/2023]
Abstract
BACKGROUND Persons living with dementia (PLWD) experience high rates of hospitalization and rehospitalization, exposing them to added risk for adverse outcomes including delirium, hastened cognitive decline, and death. Hospitalizations can also increase family caregiver strain. Despite disparities in care quality surrounding hospitalizations for PLWD, and evidence suggesting that exposure to neighborhood-level disadvantage increases these inequities, experiences with hospitalization among PLWD and family caregivers exposed to greater levels of neighborhood disadvantage are poorly understood. This study examined family caregiver perspectives and experiences of hospitalizations among PLWD in the context of high neighborhood-level disadvantage. METHODS We analyzed data from the Stakeholders Understanding of Prevention Protection and Opportunities to Reduce HospiTalizations (SUPPORT) study, an in-depth, multisite qualitative study examining hospitalization and rehospitalization of PLWD in the context of high neighborhood disadvantage, to identify caregiver perspectives and experiences of in-hospital care. Data were analyzed using rapid identification of themes; duplicate transcript review was used to enhance rigor. RESULTS Data from N = 54 individuals (47 individual interviews, 2 focus groups with 7 individuals) were analyzed. Sixty-three percent of participants identified as Black/African American, 35% as non-Hispanic White, and 2% declined to report. Caregivers' experiences were largely characterized by PLWD receiving suboptimal care that caregivers viewed as influenced by system pressures and inadequate workforce competencies, leading to communication breakdowns and strain. Caregivers described poor collaboration between clinicians and caregivers with regard to in-hospital care delivery, including transitional care. Caregivers also highlighted the lack of person-focused care and the exclusion of the PLWD from care. CONCLUSIONS Caregiver perspectives highlight opportunities for improving hospital care for PLWD in the context of neighborhood disadvantage and recognition of broader issues in care structure that limit their capacity to be actively involved in care. Further work should examine and develop strategies to improve caregiver integration during hospitalizations across diverse contexts.
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Affiliation(s)
- Blair P Golden
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Laura Block
- University of Wisconsin-Madison School of Nursing, Madison, Wisconsin, USA
| | - Clark Benson
- University of Wisconsin-Madison School of Nursing, Madison, Wisconsin, USA
| | - Quinton D Cotton
- Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Ann Wieben
- University of Wisconsin-Madison School of Nursing, Madison, Wisconsin, USA
| | - Farah Kaiksow
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Andrea Gilmore-Bykovskyi
- University of Wisconsin-Madison School of Nursing, Madison, Wisconsin, USA
- Berbee Walsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
- University of Wisconsin Center for Health Disparities Research, Madison, Wisconsin, USA
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11
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Lewis A, Gupta A, Oh I, Schindler SE, Ghoshal N, Abrams Z, Foraker R, Snider BJ, Morris JC, Balls-Berry J, Gupta M, Payne PRO, Lai AM. Association Between Socioeconomic Factors, Race, and Use of a Specialty Memory Clinic. Neurology 2023; 101:e1424-e1433. [PMID: 37532510 PMCID: PMC10573139 DOI: 10.1212/wnl.0000000000207674] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 06/06/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The capacity of specialty memory clinics in the United States is very limited. If lower socioeconomic status or minoritized racial group is associated with reduced use of memory clinics, this could exacerbate health care disparities, especially if more effective treatments of Alzheimer disease become available. We aimed to understand how use of a memory clinic is associated with neighborhood-level measures of socioeconomic factors and the intersectionality of race. METHODS We conducted an observational cross-sectional study using electronic health record data to compare the neighborhood advantage of patients seen at the Washington University Memory Diagnostic Center with the catchment area using a geographical information system. Furthermore, we compared the severity of dementia at the initial visit between patients who self-identified as Black or White. We used a multinomial logistic regression model to assess the Clinical Dementia Rating at the initial visit and t tests to compare neighborhood characteristics, including Area Deprivation Index, with those of the catchment area. RESULTS A total of 4,824 patients seen at the memory clinic between 2008 and 2018 were included in this study (mean age 72.7 [SD 11.0] years, 2,712 [56%] female, 543 [11%] Black). Most of the memory clinic patients lived in more advantaged neighborhoods within the overall catchment area. The percentage of patients self-identifying as Black (11%) was lower than the average percentage of Black individuals by census tract in the catchment area (16%) (p < 0.001). Black patients lived in less advantaged neighborhoods, and Black patients were more likely than White patients to have moderate or severe dementia at their initial visit (odds ratio 1.59, 95% CI 1.11-2.25). DISCUSSION This study demonstrates that patients living in less affluent neighborhoods were less likely to be seen in one large memory clinic. Black patients were under-represented in the clinic, and Black patients had more severe dementia at their initial visit. These findings suggest that patients with a lower socioeconomic status and who identify as Black are less likely to be seen in memory clinics, which are likely to be a major point of access for any new Alzheimer disease treatments that may become available.
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Affiliation(s)
- Abigail Lewis
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Aditi Gupta
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Inez Oh
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Suzanne E Schindler
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Nupur Ghoshal
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Zachary Abrams
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Randi Foraker
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Barbara Joy Snider
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - John C Morris
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Joyce Balls-Berry
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Mahendra Gupta
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Philip R O Payne
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO
| | - Albert M Lai
- From the Division of Computational and Data Sciences (A.L.), Washington University in St. Louis; Institute for Informatics (A.L., A.G., I.O., Z.A., R.F., P.R.O.P., A.M.L.), Department of Neurology (S.E.S., N.G., B.J.S., J.C.M., J.B.-B.), and Department of Psychiatry (N.G.), Washington University School of Medicine, St. Louis; and Olin Business School (M.G.), Washington University in St. Louis, MO.
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12
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Chu DY, Adluru N, Nair VA, Choi T, Adluru A, Garcia-Ramos C, Dabbs K, Mathis J, Nencka AS, Gundlach C, Conant L, Binder JR, Meyerand ME, Alexander AL, Struck AF, Hermann B, Prabhakaran V. Association of neighborhood deprivation with white matter connectome abnormalities in temporal lobe epilepsy. Epilepsia 2023; 64:2484-2498. [PMID: 37376741 PMCID: PMC10530287 DOI: 10.1111/epi.17702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 06/25/2023] [Accepted: 06/26/2023] [Indexed: 06/29/2023]
Abstract
OBJECTIVE Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality. METHODS Participants including 74 TLE patients (47 male, mean age = 39.2 years) and 45 healthy controls (27 male, mean age = 31.9 years) from the Epilepsy Connectome Project were classified into ADI-defined low and high disadvantage groups. Graph theoretic metrics were applied to multishell connectome diffusion-weighted imaging (DWI) measurements to derive 162 × 162 structural connectivity matrices (SCMs). The SCMs were harmonized using neuroCombat to account for interscanner differences. Threshold-free network-based statistics were used for analysis, and findings were correlated with ADI quintile metrics. A decrease in cross-sectional area (CSA) indicates reduced white matter integrity. RESULTS Sex- and age-adjusted CSA in TLE groups was significantly reduced compared to controls regardless of disadvantage status, revealing discrete aberrant white matter tract connectivity abnormalities in addition to apparent differences in graph measures of connectivity and network-based statistics. When comparing broadly defined disadvantaged TLE groups, differences were at trend level. Sensitivity analyses of ADI quintile extremes revealed significantly lower CSA in the most compared to least disadvantaged TLE group. SIGNIFICANCE Our findings demonstrate (1) the general impact of TLE on DWI connectome status is larger than the association with neighborhood disadvantage; however, (2) neighborhood disadvantage, indexed by ADI, revealed modest relationships with white matter structure and integrity on sensitivity analysis in TLE. Further studies are needed to explore this relationship and determine whether the white matter relationship with ADI is driven by social drift or environmental influences on brain development. Understanding the etiology and course of the disadvantage-brain integrity relationship may serve to inform care, management, and policy for patients.
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Affiliation(s)
- Daniel Y Chu
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Nagesh Adluru
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Veena A Nair
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Timothy Choi
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Anusha Adluru
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Camille Garcia-Ramos
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Kevin Dabbs
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Jedidiah Mathis
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Andrew S Nencka
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Carson Gundlach
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Lisa Conant
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Jeffrey R Binder
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Mary E Meyerand
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Aaron F Struck
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- William S. Middleton Veterans Hospital, Madison, Wisconsin, USA
| | - Bruce Hermann
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Vivek Prabhakaran
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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13
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Becerril A, Pfoh ER, Hashmi AZ, Mourany L, Gunzler DD, Berg KA, Krieger NI, Krishnan K, Moore SE, Kahana E, Dawson NV, Luezas Shamakian L, Campbell JW, Perzynski AT, Dalton JE. Racial, ethnic and neighborhood socioeconomic differences in incidence of dementia: A regional retrospective cohort study. J Am Geriatr Soc 2023; 71:2406-2418. [PMID: 36928611 DOI: 10.1111/jgs.18322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND Evidence on the effects of neighborhood socioeconomic disadvantage on dementia risk in racially and ethically diverse populations is limited. Our objective was to evaluate the relative extent to which neighborhood disadvantage accounts for racial/ethnic variation in dementia incidence rates. Secondarily, we evaluated the spatial relationship between neighborhood disadvantage and dementia risk. METHODS In this retrospective study using electronic health records (EHR) at two regional health systems in Northeast Ohio, participants included 253,421 patients aged >60 years who had an outpatient primary care visit between January 1, 2005 and December 31, 2015. The date of the first qualifying visit served as the study baseline. Cumulative incidence of composite dementia outcome, defined as EHR-documented dementia diagnosis or dementia-related death, stratified by neighborhood socioeconomic deprivation (as measured by Area Deprivation Index) was determined by competing-risk regression analysis, with non-dementia-related death as the competing risk. Fine-Gray sub-distribution hazard ratios were determined for neighborhood socioeconomic deprivation, race/ethnicity, and clinical risk factors. The degree to which neighborhood socioeconomic position accounted for racial/ethnic disparities in the incidence of composite dementia outcome was evaluated via mediation analysis with Poisson rate models. RESULTS Increasing neighborhood disadvantage was associated with increased risk of EHR-documented dementia diagnosis or dementia-related death (most vs. least disadvantaged ADI quintile HR = 1.76, 95% confidence interval = 1.69-1.84) after adjusting for age and sex. The effect of neighborhood disadvantage on this composite dementia outcome remained after accounting for known medical risk factors of dementia. Mediation analysis indicated that neighborhood disadvantage accounted for 34% and 29% of the elevated risk for composite dementia outcome in Hispanic and Black patients compared to White patients, respectively. CONCLUSION Neighborhood disadvantage is related to the risk of EHR-documented dementia diagnosis or dementia-related death and accounts for a portion of racial/ethnic differences in dementia burden, even after adjustment for clinically important confounders.
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Affiliation(s)
- Alissa Becerril
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Elizabeth R Pfoh
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
- Center for Value-Based Care Research, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ardeshir Z Hashmi
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
- Center for Geriatric Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Lyla Mourany
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
| | - Douglas D Gunzler
- Center for Healthcare Research and Policy, Case Western Reserve University at MetroHealth, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Kristen A Berg
- Center for Healthcare Research and Policy, Case Western Reserve University at MetroHealth, Cleveland, Ohio, USA
| | - Nikolas I Krieger
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
| | - Kamini Krishnan
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Scott Emory Moore
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio, USA
| | - Eva Kahana
- Sociology Department, Case Western Reserve University, Cleveland, Ohio, USA
| | - Neal V Dawson
- Center for Healthcare Research and Policy, Case Western Reserve University at MetroHealth, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | | | | | - Adam T Perzynski
- Center for Healthcare Research and Policy, Case Western Reserve University at MetroHealth, Cleveland, Ohio, USA
| | - Jarrod E Dalton
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
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