Associations between maternal stressful life events and child health outcomes in indigenous and non-indigenous groups in New Zealand
Bibliographic record
Abstract
Exposure to stressful life events (SLE) around the time of pregnancy is associated with adverse health outcomes for mothers and children. Previous New Zealand research found Indigenous Māori women are more likely to be exposed to SLE than non-Māori, and are exposed to a higher number of SLE. The consequences of this for ethnic inequities in child health outcomes are unknown. This paper examines the relationship between patterns of maternal SLE exposure with child health and development outcomes at age 3 years, for Indigenous and non-Indigenous children. We found most children had a stressful early life environment at least sometimes, but more than a quarter of Māori children had a mother experiencing multiple SLE on all occasions measured. We found a clear association between maternal experiences of SLE and disordered child sleep and development concerns. While not able to fully assess the contribution of maternal SLE to ethnic inequities in child health outcomes, we did clearly demonstrate that more Māori children have mothers exposed to multiple SLE, and that these maternal SLE are associated with poorer child outcomes. The impacts of chronic SLE exposure need to be better understood, especially given the large ethnic disparity in chronic SLE exposure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".