Supplementary Material for: Impact of Disability, Psychological Status, and Comorbidity on Health-Related Quality of Life Perceived by Subjects with Obesity
Bibliographic record
Abstract
Obesity is a rapidly growing public health problem affecting an increasing number of countries worldwide and creating substantial financial and health burdens. Obesity has a negative impact on health-related quality of life (HRQoL) with reference to physical and mental health status, social relationships, and economic factors. The aim of the present study is to investigate the association of number of comorbidities, psychological status, and disability level with HRQoL in a sample of subjects with obesity. <b><i>Methods:</i></b> A total of 273 subjects with obesity (199 women and 74 men) were recruited. Medical history and anthropometric measurements were carried out. The Italian version of the Laval questionnaire, the TSD-OC (SIO test for obesity-related disabilities), and SCL-90 (Symptom Checklist-90) tests were administered. The association between HRQoL (global and different domains scores of the Laval questionnaire – dependent variable) and age, body mass index (BMI), comorbidity, TSD-OC, and SCL-90 was analysed using a stepwise linear regression model. <b><i>Results:</i></b> BMI, disability (TSD-OC global score), and psychological symptoms (SCL-90 global severity index) were found to be the main determinants of HRQoL. Single domains of HRQoL (symptoms, activity/mobility, personal hygiene/clothing, emotions, social interaction, and sexual life) showed different patterns of associations with each domain of the Laval questionnaire. BMI, pain, and social life disruptions were found to be significantly associated with most of the HRQoL domains while age, comorbidities, psychological problems (depression, interpersonal symptoms, somatization), and disability were associated with only some domains of the Laval questionnaire. Education, psychological symptoms (obsessive-compulsive, anxiety, hostility, phobic anxiety, paranoid ideation), and disability domains (stiffness, housework, outdoor activities, occupational activities) were not associated with any of the dimensions of the Laval questionnaire. <b><i>Discussion/Conclusion:</i></b> The present study identified key determinants of QoL in subjects with obesity, which could help in refining the multidimensional diagnostic assessment of obesity as well as designing more effective interventions to improve HRQoL in these patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.150 | 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 teacher head, 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".