Factors Associated with the Development of Depression and the Influence of Obesity on Depressive Disorders: A Narrative Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Depression affects several aspects of life, including socioeconomic status, relationships, behavior, emotions, and overall health. The etiology of depression is complex and influenced by various factors, with obesity emerging as a significant contributor. This narrative review aims to investigate the factors associated with the development of depression, with a particular focus on the role of obesity. The literature search was conducted on PubMed, Embase, and PsycINFO from May to July 2024. The review highlights the impact of environmental and socioeconomic conditions; lifestyle choices, including physical activity and dietary habits; stress; traumatic experiences; neurotransmitter imbalances; medical and psychological conditions; hormone fluctuations; and epigenetic factors on depression. A key emphasis is placed on the inflammatory processes linked to obesity, which may drive the bidirectional relationship between obesity and depression. The findings suggest that obesity is associated with an increased risk of depression, potentially due to chronic inflammation, neurochemical dysregulation, and the emotional and social challenges related to weight stigma and obesity management. Understanding these interconnected factors is important for developing targeted interventions to address both obesity and depression, leading to improved quality of life for those affected.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it