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Record W4285007296 · doi:10.1177/14034948221110019

Social class and the risk of dementia: A systematic review and meta-analysis of the prospective longitudinal studies

2022· review· en· W4285007296 on OpenAlexaffabout
Yuliya Bodryzlova, Alexie Kim, Xavier Michaud, Emmanuelle Bélanger, Grégory Moullec

Bibliographic record

VenueScandinavian Journal of Public Health · 2022
Typereview
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsCanadian Sleep & Circadian NetworkCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de Montréal
Fundersnot available
KeywordsDementiaMeta-analysisProspective cohort studyGerontologyLongitudinal studyMedicineSocial classPopulationCohort studyDemographyPsychologyDiseaseInternal medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Background: The association between belonging to a disadvantaged socio-economic status or social class and health outcomes has been consistently documented during recent decades. However, a meta-analysis quantifying the association between belonging to a lower social class and the risk of dementia has yet to be performed. In the present work, we sought to summarise the results of prospective, longitudinal studies on this topic. Methods: We conducted a systematic review and meta-analysis of prospective, longitudinal studies measuring the association between indicators of social class and the risk of all-cause/Alzheimer’s dementia. The search was conducted in four databases (Medline, Embase, Web of Science and PsychInfo). Inclusion criteria for this systematic review and meta-analysis were: (a) longitudinal prospective study, (b) aged ⩾60 years at baseline, (c) issued from the general population, (d) no dementia at baseline and (e) mention of social class as exposure. Exclusion criteria were: (a) study of rare dementia types (e.g. frontotemporal dementia), (b) abstract-only papers and (c) articles without full text available. The Newcastle–Ottawa scale was used to assess the risk of bias in individual studies. We calculated the overall pooled relative risk of dementia for different social class indicators, both crude and adjusted for sex, age and the year of the cohort start. Results: Out of 4548 screened abstracts, 15 were included in the final analysis (76,561 participants, mean follow-up 6.7 years (2.4–25 years), mean age at baseline 75.1 years (70.6–82.1 years), mean percentage of women 58%). Social class was operationalised as levels of education, occupational class, income level, neighbourhood disadvantage and wealth. Education (relative risk (RR)=2.48; confidence interval (CI) 1.71–3.59) and occupational class (RR=2.09; CI 1.18–3.69) but not income (RR=1.28; CI 0.81–2.04) were significantly associated with the risk of dementia in the adjusted model. Some of the limitations of this study are the inclusion of studies predominantly conducted in high-income countries and the exclusion of social mobility in our analysis. Conclusions: We conclude that there is a significant association between belonging to a social class and the risk of dementia, with education and occupation being the most relevant indicators of social class regarding this risk. Studying the relationship between belonging to a disadvantaged social class and dementia risk might be a fruitful path to diminishing the incidence of dementia over time. However, a narrow operationalisation of social class that only includes education, occupation and income may reduce the potential for such studies to inform social policies.

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)0.019
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.038
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.035
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.307
GPT teacher head0.477
Teacher spread0.170 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations57
Published2022
Admission routes2
Has abstractyes

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