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Record W2103212356 · doi:10.1136/jech.56.9.671

Housing and inequalities in health: a study of socioeconomic dimensions of housing and self reported health from a survey of Vancouver residents

2002· article· en· W2103212356 on OpenAlexaffabout
James R. Dunn

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSocioeconomic statusMental healthNeighbourhood (mathematics)Housing tenureMedicineSelf-rated healthGerontologyEnvironmental healthFeelingPsychologySocial psychologyPopulationDemographic economicsPsychiatryEconomics

Abstract

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STUDY OBJECTIVE: To investigate the relation between housing, socioeconomic status, and self reported general and mental health. This study is an empirical investigation of social and economic dimensions of housing, specifically, demand, control, and material (affordability, dwelling type) and meaningful (pride in dwelling, home as a refuge) dimensions of everyday life as they occur in the domestic environment. DESIGN: A cross sectional telephone survey was administered to a random sample of households. Survey items included measures of demand, control, and meaningfulness of the domestic environment, as well as standard measures of socioeconomic status and social support. Main outcome measures were self reported health (excellent, very good, good, fair, poor) and self reported frequency of feeling "downhearted and blue" in the two weeks before interview (from the Rand Mental Health Index). SETTING: Households (n=650) from 12 neighbourhood areas in the city of Vancouver, Canada. PARTICIPANTS: One randomly selected adult from each of 650 households completed the interview and constitute the sample for this study. MAIN RESULTS: In bivariate analyses, measures of housing demand, control and meaningfulness exhibited strong and significantly graded relations with self reported health and somewhat less strong relations with mental health. In logistic regression analyses housing demand and control variables made significant contributions to health both general and mental health. Respondents were more likely to report fair/poor health if they: reported that they couldn't stand to be at home sometimes (OR=2.29, p<0.05); rated their domestic housework as somewhat or quite a strain (OR=5.71, p<0.001); were somewhat or very dissatisfied with their social activities (OR=3.41, p<0.001); and reported that they were constantly under stress a good bit of the time or more (OR=3.56, p<0.05). In terms of mental health, respondents were more likely to report poorer mental health if they: lived longer in their neighbourhood (OR=1.05, p<0.05); reported their housework duties to be somewhat or quite a strain (OR=5.55, p<0.001); reported that they did not have somebody that could help them if they needed it (OR=9.28, p<0.001); and reported that they were constantly under stress a good bit of the time or more in the two weeks before the interview (OR=5.26, p<0.001). One of the main hypotheses investigated-that meaningful dimensions of housing are associated with health status-found support in bivariate analyses without controls, but did not contribute to multivariable models. CONCLUSIONS: The influence of housing demand and control variables superseded a well known correlate of health status, educational attainment, attesting to their importance. The findings of this paper lend support to the hypothesis that features of the domestic environment, especially as they pertain to the exercise of control and the experience of demand, are significant predictors of self reported general and mental health status. Housing is a concrete manifestation of socioeconomic status, which has an important part to play in the development of explanations of the social production of health inequalities.

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)0.000
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 score0.204
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.291
GPT teacher head0.457
Teacher spread0.166 · 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

Citations275
Published2002
Admission routes2
Has abstractyes

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