The Influence of Obesity on Quality of Life: A Systematic Review
Bibliographic record
Abstract
Introduction: The relationship between obesity and the quality of life (QoL) or health-related quality of life (HRQoL) has been confounded by several factors, including multi-morbidity. The objective of this study is to review and explore the relationship between obesity and quality of life, controlling for the long-term conditions alongside various demoic, health, and lifestyle factors within the general population. Methodology: To achieve the objective, we have conducted a systematic review of 21 studies published between 2020 and 2024, focusing on the influence of obesity on individuals’ quality of life. This systematic review employed a robust methodology that follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. It included studies published between 2010 and 2024, drawn from various databases, including SCOPUS, PubMed, Embase, and Google Scholar. Results: The findings indicate that obesity is directly associated with reductions in the quality of life, including mental and physical health, activities of daily living, and psychological functioning. Obese persons have higher functional limitations levels than normal and overweight individuals, even as obesity has been linked to the development of various sleep disorders, including obesity hypoventilation syndrome (OHS) and obstructive sleep apnea (OSA). Conclusions: The systematic review has disclosed the existence of a clear inverse relationship between increased weight status and decrease in the quality of life. Obesity significantly influences the quality of life of persons with obesity as it adversely affects individual’s health and affects different aspects of the person’s quality of life, including physical and psychological functioning, mental health and well-being, and body image, among others.
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 | 0.046 | 0.099 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".