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Record W2144639378 · doi:10.1093/geronb/62.6.s415

Perceptions of Body Weight Among Older Adults: Analyses of the Intersection of Gender, Race, and Socioeconomic Status

2007· article· en· W2144639378 on OpenAlexaff
Scott Schieman, Tetyana Pudrovska, Ronald Eccles

Bibliographic record

VenueThe Journals of Gerontology Series B · 2007
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Toronto
FundersNational Institute on Aging
KeywordsSocioeconomic statusOverweightDemographyRace (biology)Multinomial logistic regressionGerontologyObesityPsychologyLogistic regressionBody mass indexMedicinePopulationSociology

Abstract

fetched live from OpenAlex

OBJECTIVES: We examine the effects of gender, race, and socioeconomic status (SES) on perceptions of body weight among older adults and the role of status-based differences in BMI in these processes. METHODS: Data are derived from face-to-face interviews with 1,164 adults aged 65 years and older in the District of Columbia and two counties in Maryland in 2000-2001. RESULTS: With "perceived appropriate weight" as the comparison group, multinomial logistic regression analyses indicate that white adults, women, and high-SES individuals are more likely than black adults, men, and low-SES individuals to describe themselves as overweight or obese. However, these disparities are observed only after statistically adjusting for race, gender, and SES disparities in BMI. Moreover, the positive effect of SES on the likelihood of reporting overweight or obese perceptions is strongest among black women. Among low SES individuals, white women are more likely than men and black women to describe themselves as obese (relative to the "perceived appropriate weight" category). DISCUSSION: Our observations underscore the importance of taking SES contingencies into account when exploring race-gender differences in perceived body weight. This study further contributes to the literature by documenting the important suppression patterns associated with race, gender, and SES differences in BMI.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.456
Teacher spread0.378 · 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

Citations51
Published2007
Admission routes1
Has abstractyes

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