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Record W2127634770 · doi:10.1177/0898264311408419

Body Mass Index and Long-Term Mortality in an Elderly Mediterranean Population

2011· article· en· W2127634770 on OpenAlexaff
Marı́a Victoria Zunzunegui, María T. Sánchez-Santos, Angela Garcia, José Manuel Ribera Casado, À. Otero

Bibliographic record

VenueJournal of Aging and Health · 2011
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsQueen's UniversityUniversité de Montréal
FundersNational Heart, Lung, and Blood InstituteNational Research Foundation
KeywordsUnderweightMedicineBody mass indexOverweightDemographyInterquartile rangeHazard ratioObesityGerontologyPopulationCohortMortality rateNational Death IndexProportional hazards modelConfidence intervalInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe the relationship of body mass index and mortality in older adults, examining the influence of sex and cardiovascular morbidity. METHODS: Sixteen-year cohort of a population sample of 1,008 people aged 65 and over. BMI mortality hazard ratios are estimated controlling for age, sex, education, physical activity, smoking, chronic conditions, and ADL (activities of daily living) disability. RESULTS: At baseline the median BMI is 26.8 (Interquartile range: 24.2-29.7 Kg/m(2)). Findings show that during 16 years there were 672 deaths. The U-shaped curve of the mortality hazard by BMI is wide. The minimum mortality occur at BMI = 30.5 Kg/m(2). Findings show that men had lower mortality risk with increasing BMI and that cardiovascular disease was associated with high mortality in the low-BMI category. DISCUSSION: Underweight is a risk factor for mortality among elderly people, whereas overweight and mild obesity are associated with the lowest mortality particularly among men and those with cardiovascular morbidity.

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)0.000
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 score0.175
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.075
GPT teacher head0.349
Teacher spread0.274 · 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.

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

Citations27
Published2011
Admission routes1
Has abstractyes

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