Adverse Childhood Experiences and the Risk of Diabetes: Examining the Roles of Depressive Symptoms and Cardiometabolic Dysregulations in the Whitehall II Cohort Study
Bibliographic record
Abstract
OBJECTIVE Adverse childhood experiences (ACEs) are associated with an increased risk of diabetes in adulthood. However, the potential mediating roles of depression and cardiometabolic dysregulations in this association are not clear. RESEARCH DESIGN AND METHODS Prospective data were from the Whitehall II cohort study, with the phase 5 assessment (1997–1999) serving as baseline (n = 5,093, age range = 44–68 years, 27.3% female). ACEs were retrospectively reported at phase 5. Depressive symptoms (Center for Epidemiologic Studies Depression Scale) and cardiometabolic dysregulations (inflammation, central obesity, HDL cholesterol, triglycerides, impaired fasting glucose, and hypertension) were examined at phase 7 (2002–2004). Incident diabetes was examined at phases 8–11 (2006–2013) via self-report and blood samples. Participants reporting diabetes prior to phase 8 were excluded. Statistical mediation was examined with path analysis using structural equation modeling. ACEs were modeled as an observed continuous variable, whereas depressive symptoms and cardiometabolic dysregulations were modeled as latent variables. Unstandardized probit regression coefficients with 95% CI are reported for mediation analysis. RESULTS ACEs were associated with an increased likelihood of diabetes, with every addition of ACE associated with an ∼11% increase in odds of diabetes (odds ratio 1.11 [95% CI 1.00, 1.24], P = 0.048). In mediation analysis, ACEs were indirectly associated with diabetes via depressive symptoms (indirect effect 0.03 [95% CI 0.02, 0.04], P < 0.001) and cardiometabolic dysregulations (indirect effect 0.03 [95% CI 0.01, 0.05], P = 0.03). CONCLUSIONS This study provides further evidence of the detrimental psychological and physiological effects of ACEs and suggests that depression and cardiometabolic dysregulations may be pathways linking ACEs with diabetes 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".