Mental health and quality of life in different obesity phenotypes: a systematic review
Bibliographic record
Abstract
OBJECTIVES: It has been suggested that obesity phenotypes are related to mental health problems and health-related quality of life (HRQoL). However, there is no certain consensus. This systematic review aimed to evaluate the association between different obesity phenotypes with common psychiatric symptoms and HRQoL. METHODS: Electronic databases i.e. PubMed, Scopus, EMBASE, and google scholar were searched until September 2021, to identify studies that investigated associations between the obesity phenotypes with psychiatric symptoms and/or mental and physical HRQoL. Two researchers independently checked titles and abstracts, evaluated full-text studies, extracted data, and appraised their quality using the Newcastle-Ottawa Scale. RESULTS: Eighteen studies, with a total of 3,929,203 participants, were included. Of the studies included in this systematic review, 10 articles evaluated the association between obesity phenotypes and psychiatric symptoms, while six papers investigated the association between HRQoL and obesity phenotypes, and two studies assessed both. As a whole, the findings of these studies suggest that obese individuals with a favorable metabolic profile have a slightly higher risk of mental health problems and poor quality of life, however, the risk becomes larger when obesity is combined with an adverse metabolic profile. So, metabolically healthy obesity may not be a completely benign condition in relation to mental disorders and poor quality of life. CONCLUSION: According to published research, obesity is likely to increase the risk of mental health problems and poor quality of life when metabolic disturbances are present.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".