Trends in Obesity and Overweight‐Related Office Visits and Drug Prescriptions in Canada, 1998 to 2004
Bibliographic record
Abstract
OBJECTIVE: Obesity and overweight are affecting increasing numbers of Canadians and have received considerable amounts of medical, governmental, and media attention in recent years. This study sought to determine whether this rise in prevalence and awareness has resulted in an increased frequency of obesity and overweight-related office visits or antiobesity drug prescriptions over the past 5 years. RESEARCH METHODS AND PROCEDURES: Data from IMS Health Canada were used to derive nationally representative estimates of trends in the annual number of obesity and overweight-related office visits (1999 to 2003) and the quarterly prescription volume of antiobesity drugs (July 1998 to March 2003) in Canada. RESULTS: The number of obesity and overweight-related office visits increased by 20% between 1999 and 2000 but then remained constant. The number of antiobesity drug prescriptions peaked in 2001 and has since declined, with parallel trends being observed for all individual agents. In contrast, the overall frequency of office visits and drug prescriptions in Canada (for any reason) progressively increased over the study period. Middle-aged women were the most common type of patient to seek physician advice regarding obesity, and general practitioners were the most common type of physician visited. DISCUSSION: Increases in the prevalence and awareness of obesity have not resulted in major increases in office visits or drug prescriptions for this condition over the past 5 years. A number of patient, physician, and drug-related factors may explain these results, which are likely a reflection primarily of the current lack of effective weight loss strategies for obese individuals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".