Childhood Abuse Is Associated With Adiposity in Midlife Women: Possible Pathways Through Trait Anger and Reproductive Hormones
Bibliographic record
Abstract
Objective: To examine the association between childhood abuse/neglect and central adiposity and obesity in a sample of 311 women (n = 106 black, 205 white) from the Pittsburgh site of the Study of Women’s Health Across the Nation (SWAN). Methods: SWAN included a baseline measurement of women in midlife (mean age = 45.7 years) and eight follow-up visits during which waist circumference (WC) and body mass index (BMI) were measured. The Childhood Trauma Questionnaire retrospectively assessed emotional, physical, and sexual abuse, and emotional and physical neglect in childhood. Results: Analyses of covariance showed that women with a history of any abuse/neglect, and specifically physical and sexual abuse, had significantly higher WC and BMI at baseline than women with no abuse history. A significant interaction between abuse and BMI showed that among women with BMI of <30, any abuse/neglect and certain subtypes of abuse predicted greater increases in WC over time. Additional analyses showed that Trait Anger scores and sex hormone-binding globulin (SHBG) attenuated cross-sectional relationships between abuse/neglect and WC and BMI. Conclusion: This study suggests that abused/neglected women seem to have greater anger and lower levels of SHBG, which are associated with adiposity in midlife. SWAN = Study of Women’s Health Across the Nation; BMI = body mass index; WC = waist circumference; SHBG = sex hormone-binding globulin; FSH = follicle stimulating hormone; FEI = free estrogen index; FAI = free androgen index; CTQ = Childhood Trauma Questionnaire; SES = socioeconomic status.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".