The Relationship Among Body Mass Index, Subjective Reporting of Chronic Disease, and the Use of Health Care Services in Newfoundland and Labrador, Canada
Bibliographic record
Abstract
The purpose of the study was to examine the association of body mass index (BMI) with the prevalence of chronic disease and health services use in adults living in Newfoundland and Labrador (NL). A cross-sectional analysis of 2345 adult respondents to the 2001 Canadian Community Health Survey was performed. Outcome measures included the prevalence of chronic disease and health services use. The sample comprised normal (37%), overweight (39%), obese (17%), and morbidly obese (6%) individuals. Obese and morbidly obese individuals were more likely to report the presence of a chronic disease. Adjusting for age and sex, increasing BMI category was significantly associated with a greater likelihood of cardiovascular, endocrine, and pulmonary diseases (excluding asthma). The majority of survey respondents in each category reported having a regular doctor (>75%), and there were no significant differences across categories. Compared to those with a normal BMI, obese and morbidly obese individuals reported a significantly higher number of visits to a family physician. There were no differences across BMI categories and the use of specialist or hospital services. Almost a quarter of the study sample in NL was classified as morbidly obese or obese. These individuals reported more chronic conditions and more visits to a family physician than the normal-weight group. The greater morbidity and the increased frequency of visits to family physicians suggests greater consideration should be given to channeling financial and human resources to the primary health care of this high-risk population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".