Childhood socioeconomic status and depression in adulthood: systematic review
Bibliographic record
Abstract
Abstract Background Low socioeconomic status (SES) is generally associated with poorer mental health, particularly depression. We carried out a systematic review to address the question of whether childhood SES is associated with depression in adulthood and the potential pathways which may explain this association. Methods We followed a systematic search strategy in PubMed and Scopus with specific inclusion and exclusion criteria. After removing duplicates, studies were screened for eligibility and quality was assessed independently by two assessors using the Newcastle-Ottawa scale. Results After the selection process, 20 observational studies (7 cohort and 13 cross-sectional) that examine the association between SES during childhood and depression in adulthood were included in the systematic review. The most common measures of childhood SES were parental education, occupation or family income, estimated subjectively and/or objectively. In 17 of the studies an inverse relationship between childhood SES and depression was shown. In 17 studies, models were employed to demonstrate the possible pathways which explain the relationship between childhood SES and depressive symptoms. The most important mediators were adult SES, psychosocial factors, childhood trauma and physical health. Conclusions Our findings reveal the long-term association between childhood socioeconomic conditions and depression later in life. Suboptimal childhood SES seems to be an important risk factor for depression in adulthood. Improving childhood socioeconomic conditions can potentially have lasting effects well beyond childhood. Key messages • Protecting children against the effects of socioeconomic adversity could reduce depression in adult life. • Policy makers should direct resources towards alleviating childhood disadvantage for promoting health in adulthood.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".