Impact of healthy pregnancy and lifestyle in mothers on developmental delay in their offspring: a strength-based analysis of a longitudinal study among indigenous children in Australia
Bibliographic record
Abstract
INTRODUCTION: Extensive literature has investigated the prenatal risk factors of developmental delay in children, with evidence highlighting the impact of prenatal health, mental health, and behavioural factors. While a deficit discourse has underscored Indigenous health research and policies, strengths-based approaches provide an opportunity to reframe this discourse, to illustrate and celebrate the strength and resilience of Australian Indigenous families. As such, this study aimed to identify the protective impact of healthy pregnancy and lifestyle in mothers on developmental delay in Indigenous Australian children; and whether it varies by child birthweight adjusted for gestational age. Further, we also tested whether child birthweight for adjusted gestational age mediates the association between a healthy pregnancy and lifestyle in mothers and developmental delay in their Indigenous offspring. METHODS: Strength-based analysis was conducted using data from 8 longitudinal waves of LSIC study in Australia. Random-effect models were used to longitudinally measure the impact of maternal healthy pregnancy and lifestyle on developmental delays in their children between 2008 and 2018. A composite score (ranging from 0 to 3, score = 3 refers to most healthy pregnancy) was created for a healthy pregnancy and lifestyle variable using three criteria - (1) a lack of medical conditions, (2) no substance use including smoking/alcohol/illicit drugs, and (3) intake of iron/folic acid during pregnancy. All models were adjusted for potential covariates. RESULTS: Of the 780 mother-child dyads analysed, 65.4% of mothers reported healthy pregnancy and lifestyle; while 73.5% of children born with a recommended appropriate birthweight adjusted for gestational age, and 91.4% reported no developmental delays. In children born in the recommended range of appropriate birthweight adjusted for gestational age, healthy pregnancy in mothers (most healthy, aOR: 4.76, 95% CI: 1.12-20.18; and 2nd most healthy, aOR: 4.02, 95% CI: 1.09-14.83) was protective against development delay compared to maternal unhealthy pregnancy. Living in remote areas (vs. major city, and regional) was also found to be protective against developmental delay in those who were born within the recommended range of birthweight adjusted for gestational age. Further, the current study found that child birthweight for adjusted gestational age does not have any mediating effect on the association between healthy pregnancy in mothers and developmental delay in their children. CONCLUSION: This strengths-based study suggests healthy pregnancy in mothers should be advocated to prevent developmental delay in their offspring in the Australian Indigenous population. The findings also found living in remote areas has a protective effect against developmental delay in Indigenous children who born within the recommended range of birthweight adjusted for gestational age. These findings have implications for challenging and reframing the deficit discourse surrounding Indigenous Australian health research and policymaking. Further studies are needed to investigate the positive relationship between Indigenous Australians' health and social and emotional well-being (SEWB) and their connection to their country and culture.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".