Burden of disease study of overweight and obesity; the societal impact in terms of cost-of-illness and health-related quality of life
Bibliographic record
Abstract
BACKGROUND: Little is known about the burden that overweight and obesity impose on Dutch society. The aim of this study is to examine this burden in terms of cost-of-illness and health-related quality of life. METHOD: A bottom-up, prevalence-based burden of disease study from a societal perspective was performed. Cost-of-illness information including healthcare costs, patient and family costs, and other costs was obtained via the Treatment Inventory of Costs in Patients with psychiatric disorders (TiC-P) questionnaire. Health-related quality of life was assessed through the EuroQol (EQ-5D-5L) and the BODY-Q instruments. Non-parametric bootstrapping was applied to test for significant differences in costs. Subgroup analyses were performed on all outcomes. RESULTS: A total of 97 people with overweight and obesity completed the survey. Per respondent, mean healthcare costs were €2907, patient and family costs were €4037, and other costs were €4519, leading to a total societal cost of €11,463 per respondent per year. Total costs were significantly higher for respondents with obesity versus overweight and between low & intermediate versus highly educated respondents. The mean utility score of our population was 0.81. A significantly lower utility score was found for respondents with obesity in comparison with respondents with overweight. BODY-Q results show that respondents with obesity scored a significantly lower Rasch-score than did respondents with overweight in three scales. Respondents with a high education level and having paid work scored significantly higher Rasch-scores in two scales than did those with a low education level and without having paid work. The age group 19-29 have significantly higher Rasch-scores in three scales than respondents in the other two age categories. CONCLUSIONS: Overweight and obesity have a considerable impact on the societal costs and on health-related quality of life. The results show that the impact of overweight and obesity go beyond the healthcare sector, as the other costs have the biggest share of the total costs. Another interesting finding of this study is that obesity leads to significant higher costs and lower health-related quality of life than overweight. These findings draw attention to policy making, as collective prevention and effective treatment are needed to reduce this burden.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.008 |
| 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) | 0.003 | 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".