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Record W2431281911

Body Mass Index (BMI), BMI change and mortality in community-dwelling seniors without dementia.

2006· article· en· W2431281911 on OpenAlexaffabout
Heather Keller, Truls Østbye

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineBody mass indexWeight changeGerontologyMarital statusDemographyDementiaLogistic regressionWeight lossObesityPopulationInternal medicineEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

UNLABELLED: Recently Canada adopted the World Health Organization's (WHO)Weight Classification system for Body Mass Index (BMI). To date, there has been minimal investigation on the predictive ability of BMI on mortality in seniors. This study investigates the predictive ability of the BMI categories identified in this Weight Classification System and change in BMI on mortality in Canadian seniors. METHODS: Canadian Study of Health and Aging (CSHA) participants who completed clinical examination (including body weight measurements) in 1991 (CSHA1) and 1996 (CSHA2) were included (n = 539). BMI change (CSHA1 to CSHA2) was categorized as no change/mild increase (0 to < 2.0 units), mild decrease (-0.1 to < -2.0 units), or significant increase/decrease (> or = +/-2.0 units). The outcome was subsequent 5-year-mortality, i.e. death between CSHA2 and CSHA3 (2001). Logistic regression controlled for age, gender, education level, marital status, smoking and cognitive status. RESULTS: BMI at CSHA1 was not a significant predictor of all-cause mortality between CSHA2 and CSHA3. A significant decrease in BMI regardless of BMI category predicted death (OR 2.10 95% CI 1.17, 3.80). Other factors predictive of death were age and cognitive impairment without dementia. CONCLUSION: A static measure of BMI is a less useful measure of mortality risk than weight change in older adults. Weight change, especially weight loss resulting in a BMI change of at least 2.0 units, is predictive of mortality and should be considered a warning sign.

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 score0.460

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 head0.089
GPT teacher head0.321
Teacher spread0.232 · 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

Citations56
Published2006
Admission routes2
Has abstractyes

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