Excess use of general practitioners by obese adults: Does health-related quality of life account for the association?
Bibliographic record
Abstract
As general practitioners (GP) are seeing, and are likely to continue to see, increasing numbers of obese patients in their practices, it is relevant to know with which needs these patients enter general practice. The present study aims to determine whether besides physical comorbidities, health-related quality of life (HRQOL) accounts for associations of obesity with GP use. In a general population survey in Augsburg, Germany (KORA-Survey S4 1999/2001), anthropometric body mass (BMI in kg/(m(2))), physical comorbidities, HRQOL (the 12-item Short Form; SF-12), and visits to GP were assessed, and analyzed by logistic and zero-truncated negative binomial regressions (two-part model). Gender, age, socio-economic status, marital status, health insurance, and place of residence were adjusted for. The sample consisted of N = 942 residents aged 25 - 74, who had been randomly sampled from 17 cluster-sampled communities, and were either normal-weight, overweight, moderately obese, or severely obese. The moderately obese group had higher odds than the normal-weight to report any GP use; however, while being predictive, neither physical comorbidity nor HRQOL mediated this. In contrast, with regard to number of GP visits among users, the severely obese group (BMI >/= 35) reported significantly more visits than the normal-weight group, and both physical comorbidity and physical (but not mental) HRQOL accounted for this. In conclusion, physical comorbidity and HRQOL mediate excess use of GP by severely obese users in terms of number of visits. Thus, for this group, subjective physical health seems to be important besides physical comorbidities, suggesting for general practice to focus both on evaluated and perceived needs of these patients.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".