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Record W3042782894 · doi:10.1016/j.pmedr.2020.101167

Body shape and pants size as surrogate measures of obesity among males in epidemiologic studies

2020· article· en· W3042782894 on OpenAlexafffundabout
Eric Vallières, Marie‐Hélène Roy‐Gagnon, Marie‐Élise Parent

Bibliographic record

VenuePreventive Medicine Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of OttawaUniversité de MontréalInstitut National de la Recherche Scientifique
FundersFonds de Recherche du Québec - SantéMinistère du Développement Économique, de l’Innovation et de l’ExportationCenter for Creative Photography, University of ArizonaCanadian Cancer SocietyCanadian Institutes of Health ResearchCancer Research Society
KeywordsBody mass indexObesityContext (archaeology)AnthropometryDemographyMedicineWaistAbdominal obesityEpidemiologyGerontologyPopulationEnvironmental healthInternal medicineGeography

Abstract

fetched live from OpenAlex

This study aimed at characterizing anthropometric indicators that can be used as alternatives to measurements for assessing overall obesity over adulthood and abdominal obesity among men. We used data from a population-based case-control study of prostate cancer conducted in Montreal, Canada in 2005-2012. It included men aged ≤ 75 years, 1872 of which were newly diagnosed with prostate cancer, and 1918 others randomly selected from the electoral list. In-person interviews elicited reports of height as well as of weight, pants size and Stunkard's silhouette at 5 time points over adulthood, i.e., for the ages of 20, 40, 50 and 60 years, if applicable, and at the time of interview. Waist and hip circumferences were measured by interviewers following a validated protocol. Analyses were conducted on the overall sample of 3790 subjects, after having confirmed that results did not differ according to disease status. Stunkard's silhouette scale proved to be an easy-to-administer tool that reflects well reported body mass index, either recently or decades in the past among adult males. It was discriminatory enough to classify individuals according to commonly-used obesity categories. We observed that a model including age, reported pants size, silhouette and weight can reasonably predict current abdominal obesity. In conclusion, alternative anthropometric indicators can serve as valuable means to assess overall and abdominal obesity when measurements cannot be envisaged in the context of epidemiological studies.

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 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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.122
GPT teacher head0.377
Teacher spread0.255 · 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 teacher head, not a consensus.

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

Citations7
Published2020
Admission routes3
Has abstractyes

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