Work-family life courses and metabolic markers in mid-life: evidence from the British National Child Development Study
Bibliographic record
Abstract
BACKGROUND: Previous studies have found generally better health among those who combine employment and family responsibilities; however, most research excludes men, and relies on subjective measures of health and information on work and family activities from only 1 or 2 time points in the life course. This study investigated associations between work-family life course types (LCTs) and markers of metabolic risk in a British birth cohort study. METHODS: Multichannel sequence analysis was used to generate work-family LCTs, combining annual information on work, partnership and parenthood between 16 and 42 years for men and women in the British National Child Development Study (NCDS, followed since their birth in 1958). Associations between work-family LCTs and metabolic risk factors in mid-life (age 44-45) were tested using multivariate linear regression in multiply imputed data. RESULTS: Life courses characterised by earlier transitions into parenthood were associated with significantly increased metabolic risk, regardless of attachment to paid work or marital stability over the life course. These associations were only partially attenuated by educational qualifications, early life circumstances and adult mediators. The positive association between weak labour markets ties and metabolic risk was weaker than might be expected from previous studies. Associations between work-family LCTs and metabolic risk factors did not differ significantly by gender. CONCLUSIONS: Earlier transitions to parenthood are linked to metabolic risk in mid-life.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".