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Record W2108910971 · doi:10.1093/pubmed/fdn104

Association of individual network social capital with abdominal adiposity, overweight and obesity

2008· article· en· W2108910971 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Public Health · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversité de MontréalMcGill UniversityQueen's University
FundersCanadian Institutes of Health Research
KeywordsWaistOverweightOdds ratioBody mass indexDemographyObesitySocial capitalMedicineOddsAbdominal obesityConfidence intervalGerontologyLogistic regressionInternal medicineSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Limited research has examined the association of individual trust, participation and social capital with obesity using objective measures of waist circumference (WC), body mass index (BMI) and network measures of social capital. METHODS: Data were obtained from a representative sample of Montreal residents. Participants completed questionnaires that included a position generator for collecting network social capital data. Measures of WC, height and weight were collected by registered nurses. To estimate associations with cardiometabolic risk, data on WC for individuals with BMI between 18.5 and 34.9 were extracted for analysis (n = 291). Using a proportional odds model with clustered robust standard errors, we evaluated the association of three different measures of individual social capital with elevated and substantially elevated WC and overweight and obesity categories of BMI. These measures were then evaluated in their associations with elevated WC and BMI, adjusting for socio-demographic and behavioral covariates. RESULTS: Network social capital was inversely associated with the likelihood of being in an elevated WC risk category (odds ratio (OR) = 0.81, 95% confidence intervals (CI: 0.69, 0.96) and higher BMI category (OR = 0.81, 95% CI: 0.71, 0.92). CONCLUSION: Higher individual network social capital is associated with a lower likelihood of elevated WC risk and overweight and obesity.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.046
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.317
Teacher spread0.270 · 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