Body Mass Index And Physical Activity As Predictors Of Mortality In Adult Women
Bibliographic record
Abstract
PURPOSE: Physical inactivity and obesity may be independently related to all cause and cardiovascular mortality. As these conditions continue to increase in the population it is important to assess the independent effect they have in women and other segments of the population that may be disproportionate affected by them. Therefore, the purpose of this study is to examine the effects of body mass index (BMI) and leisure time physical activity (LTPA) on all cause and cardiovascular mortality using a nationally representative sample of Non-Hispanic White, Non-Hispanic Black, and Mexican American women. METHODS: This study uses data from the NHANES III conducted between 1988 and 1994 and the mortality follow up (2002) in adults 20+ yrs/old. Anthropometric measurements were obtained at a mobile examination center and leisure time physical activity was obtained via a questionnaire. Other covariates analyzed were age, education, smoking, and presence of chronic disease conditions. SAS and SUDAAN software programs were used estimate relatives risk of mortality and to take into account the complex sample design. RESULTS:Table: No caption provided.CONCLUSION: Sedentary behavior was an independent predictor of all cause mortality and cardiovascular mortality. Overweight status in women was not a predictor of all-cause mortality or cardiovascular mortality with physical activity or without physical activity in the model. Subsequent statistical analysis, including the combination of BMI and waist-to-hip ratio (WHR) and the division of obesity into categories (Obesity I, II, III) did not alter our findings.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".