Secular Trends in the Diagnosis and Treatment of Obesity Among US Adults in the Primary Care Setting
Bibliographic record
Abstract
Excess weight afflicts the majority of the US adult population. Research suggests that the role of primary care physicians in reducing overweight and obesity is essential; moreover, little is known about self-care of obesity. This report assessed the secular trends in the care of overweight and investigated the secular association between obesity with care of overweight in primary care and self-care of overweight. Cross-sectional evaluation of the National Health and Nutrition Examination Survey (NHANES) III (1988-1994) and the Continuous NHANES (1999-2008) was employed; the total sample comprised 31,039 nonpregnant adults aged 20-90 years. The relationship between diagnosed overweight, and directed weight loss with time and obesity was assessed. Despite the combined secular increase in the prevalence of overweight and obesity (BMI >25.0 kg/m(2)) between 1994 and 2008 (56.1-69.1%), there was no secular change in the odds of being diagnosed overweight by a physician when adjusted for covariates; however, overweight and obese individuals were 40 and 42% less likely to self-diagnose as overweight, and 34 and 41% less likely to self-direct weight loss in 2008 compared to 1994, respectively. Physicians were also significantly less likely to direct weight loss for overweight and obese adults with weight-related comorbidities across time (P < 0.05). Thus, the surveillance of secular trends reveals that the likelihood of physician- and self-care of overweight decreased between 1994 and 2008 and further highlights the deficiencies in the management of excess weight.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".