Mortality among single fathers as compared with single mothers and partnered fathers: a cohort study
Bibliographic record
Abstract
IntroductionSingle-parent families are becoming increasingly common around the world with a particularly steep rise in households headed by single fathers. Research suggests that single parenthood is associated with adverse outcomes, however, little is known about the health profile or risk of death of single fathers compared to other parents. Objectives and ApproachWe aimed to examine mortality risk in single fathers compared to single mothers and partnered parents, which is the first head-to-head comparison of single and partnered parent groups. Our population consisted of 871 single fathers, 4590 single mothers, 16,341 partnered fathers and 18,688 partnered mothers. We combined cross-sectional samples derived from the Ontario component of Statistics Canada’s Canadian Community Health Survey (2001 to 2012) linked to health administrative databases to identify medical conditions, health service use, all-cause mortality and cause of death. We investigated differences in mortality using Cox proportional hazards models adjusted for socio-demographic characteristics, lifestyle and clinical factors. ResultsEach family group was followed up for a median of 11.10 years (IQR 7.36–13.54). Single fathers had a poor risk profile, particularly among lifestyle factors, such as low fruit and vegetable consumption and alcohol consumption. The mortality rate was three-fold higher for single fathers compared to single mothers and partnered fathers (5.81, 1.74 and 1.94, respectively). Even after adjustment, single fathers had a significantly higher risk of death compared to both single mothers (hazard ratio (HR): 2.49 (95% CI: 1.20 – 5.15, p=0.01)) and partnered fathers (HR: 2.06 (95% CI: 1.11 – 3.83, p=0.02). Small sample sizes precluded us from identifying the leading cause of death for single fathers. Conclusion/ImplicationsWe found that single fathers had the least favorable risk factor profile and greatest risk of mortality, which may be mitigated by physician intervention. Our study highlights that through cross-sectoral data linkages we can further advance our knowledge of social factors and their profound effects on health.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 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".