Body Mass Index (BMI), BMI change and mortality in community-dwelling seniors without dementia.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".