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Record W1969522784 · doi:10.1038/oby.2008.400

Effect of Current and Midlife Obesity Status on Mortality Risk in the Elderly

2008· article· en· W1969522784 on OpenAlexaff
Ian Janssen, Eric Bacon

Bibliographic record

VenueObesity · 2008
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood Institute
KeywordsMedicineObesityGerontologyCurrent (fluid)Internal medicine

Abstract

fetched live from OpenAlex

The primary purpose of this study was to determine whether current and midlife obesity status provide independent information on mortality risk in elderly persons. Analyses were based on 3,238 participants from the original Framingham Heart Study (FHS) cohort who lived to at least 70 years of age and who had BMI measures from when they were in their 50s. Within this group of 70-year olds, obesity based on current BMI was associated with a 21% increased risk of mortality (P = 0.019) whereas obesity in 70-year olds based on BMI measures obtained at around 50 years of age was associated with a 55% increased risk of mortality (P < 0.0001). Compared to 70-year olds who were nonobese at both 50 and 70 years of age, mortality risk was increased by 47% (P < 0.001) in those who were obese at both 50 and 70 years of age, increased by 56% (P < 0.001) in those who were obese at 50 years of age and nonobese at 70 years of age, and not significantly different (P > 0.9) in those who were nonobese at 50 years of age and obese at 70 years of age. In summary, in this cohort of elderly adults, midlife and current BMI had independent effects on mortality risk. Specifically, although mortality risk was increased in obese older adults who were already obese at midlife, this was not the case for newly obese older adults. Conversely, nonobese older adults who were obese at midlife had an increased mortality risk. These observations imply that it is imperative to consider an elderly adult's BMI in context of their BMI at midlife.

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 score0.005
Threshold uncertainty score0.250

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 head0.048
GPT teacher head0.370
Teacher spread0.322 · 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

Citations45
Published2008
Admission routes1
Has abstractyes

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