Association between preterm birth and economic and educational outcomes in adulthood: A population-based matched cohort study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Preterm birth (PTB) affects ~10% of births worldwide; however, most literature focused on short-term clinical outcomes, with much less focus on long-term socioeconomic outcomes after PTB. We examined associations between PTB and individuals' income, employment, and educational outcomes during early adulthood. METHODS: We conducted a population-level matched cohort study including all live births in Canada between 1990 and 1996, followed until 2018. Outcomes included Employment income per year in 2018 CAD and employment between ages 18 and 28 years, postsecondary education enrollment (18-22 years), and maximum educational attainment at age 22-27 years. Mean differences and risk ratios (RR) and differences (RD) were estimated using generalized estimating equation regression models for economic outcomes and multinomial logistic regression models for educational outcomes. RESULTS: Of 2.4 million births, 7% were born preterm (0.3%, 0.6%, 0.8%, and 5.4% born extremely preterm (24-27 weeks), very preterm (28-31 weeks), moderately preterm (32-33 weeks), and late preterm (34-36 weeks) respectively). After matching on baseline characteristics (e.g., sex, province of birth, and parental demographics) and adjusting for age and period effects, preterm-born individuals, on average, had $958 CAD less employment income per year (95% CI: $854-$1062), 6% lower income per year, than term-born individuals, and were 2.13% less likely to be employed (1.98-2.29%). PTB was also negatively associated with university enrollment (RR 0.93 (0.91-0.94) and graduation with a university degree (RR 0.95 (0.94-0.97)). Mean income differences for those born 24-27 weeks were -$5,463 CAD per year (17% lower), and adjusted RR were 0.55 for university enrollment and graduation. CONCLUSION: In this population-based study, preterm birth was associated with lower economic and educational achievements at least until the late twenties. The associations were stronger with decreasing GA at birth. Policymakers, clinicians, and parents should be aware that the socioeconomic impact of PTB is not limited to the early neonatal period but extends into 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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".