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Record W4312086202 · doi:10.1002/alz.068217

Allostatic load and the influence of economic adversity and neighborhood disadvantage on cognitive function in a multiethnic cohort

2022· article· en· W4312086202 on OpenAlexaboutno aff
Anthony Longoria, Zabecca Brinson, Anne R. Carlew, C. Munro Cullum, James A. de Lemos, William Goette, Laura H. Lacritz, Heidi Rossetti

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsGerontologyEthnic groupDisadvantagePsychologyDementiaCognitionAllostatic loadCohortDemographyMedicineDiseasePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Previous research has demonstrated a link between objective socio‐economic indicators and cognitive test performance. Although some studies include subjective indicators, such as perceived neighborhood environment, little is known about which specific factors are most strongly associated with cognitive performance and whether these measures are useful beyond traditional SES proxies. Further, in addition to being disproportionately at risk of experiencing neighborhood disadvantage and lower SES, racial/ethnic minorities are more likely to be diagnosed with dementia and receive less timely care compared with White individuals. This study aims to investigate how perceived neighborhood environment and neighborhood disadvantage are related to cognitive performance within a large diverse sample. Method A probability‐based sample of participants (N = 3858; Female = 59%; Black = 51%; Hispanic = 14%) from the Dallas Heart Study Phase 2 (DHS‐2; Mean: Age = 50, Education = 13) were administered the Montreal Cognitive Assessment (MoCA), in addition to measures of perceptions of neighborhood physical environment and violence, and perceived SES. Multiple regression was used to determine associations of these variables with MoCA scores relative to traditional SES measures (i.e., income, education), controlling for demographic and relevant health factors. Post‐hoc analyses stratified by racial/ethnic group were conducted to determine whether indicators differentially influenced test scores. Result After controlling for socio‐demographic and health factors, reporting lower quality neighborhood resources and difficulty paying for “very basics like food and heating” and “medical care” were associated with lower MoCA scores in the overall sample. Post‐hoc analyses revealed significant relationships between MoCA scores and quality of neighborhood resources, “food and heating,” and “medical care” only in Black participants, while “violence” was significantly associated with lower MoCA scores in Hispanics. There were no significant relationships found in Whites. Overall, subjective measures of SES and neighborhood environment contributed modest variance in the overall model, specifically for Black and Hispanic participants (R 2 = 3% to 5%). Conclusion Experiencing neighborhood and economic adversity was associated with lower scores on a cognitive screening measure and accounted for more variance than income or education in Black individuals and income in Hispanic individuals, while no relationship was seen in White participants. Future research is needed to determine whether these allostatic stressors influence cognitive impairment or dementia later in life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.298
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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