Life Course Financial Hardship and Fecundability in a North American Preconception Cohort Study
Bibliographic record
Abstract
BACKGROUND: The effects of life course financial hardship on fertility have not been well studied. METHODS: We examined the association between life course financial hardship and fecundability in Pregnancy Study Online (PRESTO), a preconception cohort study of US and Canadian pregnancy planners aged 21-45 years who identified as female (2013-2023; N = 6,377). We followed participants up to 12 months or until pregnancy. Participants reported financial hardship in childhood (≤11 years), adolescence (12-17 years), and adulthood (≥18 years) via three questions: not having enough money for living expenses; needing to borrow money for medical expenses; or receiving public assistance. We used inverse probability-weighted proportional probabilities models to estimate fecundability ratios (FRs) and 95% confidence intervals (CIs), accounting for time-dependent confounding and selection bias. RESULTS: Compared with no financial hardship, financial hardship during any life stage was associated with slightly reduced fecundability (FR = 0.93, 95% CI: 0.86, 1.0). Associations were similar for financial hardship during childhood and adolescence; however, those experiencing financial hardship during adulthood had lower fecundability (FR = 0.83, 95% CI: 0.77, 0.90). The association between adolescent financial hardship and fecundability was similar among those with and without childhood financial hardship. However, the association of adult financial hardship with fecundability was stronger among those who experienced hardship earlier in life (i.e., adult financial hardship among those with child/adolescent financial hardship: FR = 0.77; 95% CI: 0.64, 0.93). CONCLUSION: Adulthood is a sensitive period for the effects of financial hardship on fecundability. Moreover, cumulative financial hardship across the life course was associated with greater reductions in fecundability.
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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".