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Record W4323074876 · doi:10.1186/s12884-023-05443-6

Unwinding the tangle of adolescent pregnancy and socio-economic functioning: leveraging administrative data from Manitoba, Canada

2023· article· en· W4323074876 on OpenAlexafffundabout
Aleksandra Jakubowski, Leslíe L. Roos, Elizabeth Wall‐Wieler

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsPregnancyMedicineFertilityAbortionDemographyLive birthPropensity score matchingObstetricsPopulationEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Understanding the relationship between adolescent pregnancy and adult education and employment outcomes is complicated due to the endogeneity of fertility behaviors and socio-economic functioning. Studies exploring adolescent pregnancy have often relied on limited data to measure adolescent pregnancy (i.e. birth during adolescence or self-reports) and lack access to objective measures of school performance during childhood. METHODS: We use rich administrative data from Manitoba, Canada, to assess women's functioning during childhood (including pre-pregnancy academic performance), fertility behaviors during adolescence (live birth, abortion, pregnancy loss, or no history of pregnancy), and adult outcomes of high school completion and receipt of income assistance. This rich set of covariates allows calculating propensity score weights to help adjust for characteristics possibly predictive of adolescent pregnancy. We also explore which risk factors are associated with the study outcomes. RESULTS: We assessed a cohort of 65,732 women, of whom 93.5% had no teen pregnancy, 3.8% had a live birth, 2.6% had abortion, and < 1% had a pregnancy loss. Women with a history of adolescent pregnancy were less likely to complete high school regardless of the outcome of that pregnancy. The probability of dropping out of high school was 7.5% for women with no history of adolescent pregnancy; after adjusting for individual, household, and neighborhood characteristics, the probability of dropping out of high school was 14.2 percentage points (pp) higher (95% CI 12.0-16.5) for women with live birth, 7.6 pp. higher (95% CI 1.5-13.7) for women with a pregnancy loss, and 6.9 pp. higher (95% CI 5.2-8.6) for women who had abortion. They key risk factors for never completing high school are poor or average school performance in 9th grade. Women who had a live births during adolescence were much more likely to receive income assistance than any other group in the sample. Aside from poor school performance, growing up in poor households and in poor neighborhoods were also highly predictive of receiving income assistance during adulthood. DISCUSSION: The administrative data used in this study enabled us to assess the relationship between adolescent pregnancy and adult outcomes after controlling for a rich set of individual-, household-, and neighborhood-level characteristics. Adolescent pregnancy was associated with higher risk of never completing high school regardless of the pregnancy outcome. Receipt of income assistance was significantly higher for women having a live birth, but only marginally higher for those who had a pregnancy that ended in loss or termination, underlining the harsh economic consequences of caring for a child as a young mother. Our data suggest that interventions targeting young women with poor or average school marks may be especially effective public policy priorities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.239
GPT teacher head0.385
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2023
Admission routes3
Has abstractyes

Explore more

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