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Record W2887912285 · doi:10.2337/dc18-0932

Adverse Childhood Experiences and the Risk of Diabetes: Examining the Roles of Depressive Symptoms and Cardiometabolic Dysregulations in the Whitehall II Cohort Study

2018· article· en· W2887912285 on OpenAlexafffund
Sonya S. Deschênes, Eva Graham, Mika Kivimäki, Norbert Schmitz

Bibliographic record

VenueDiabetes Care · 2018
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersNational Institute on AgingMedical Research CouncilCanadian Institutes of Health Research
KeywordsMedicineMediationDiabetes mellitusOdds ratioInternal medicineDepression (economics)Cohort studyCohortCenter for Epidemiologic Studies Depression ScaleProspective cohort studyEndocrinologyDepressive symptoms

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.246
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2018
Admission routes2
Has abstractyes

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