Variation in Maternal Co‐morbidities and Obstetric Interventions across Area‐Level Socio‐economic Status: A Cross‐Sectional Study
Bibliographic record
Abstract
BACKGROUND: Multiple studies indicate a significant association between area-level socio-economic status (SES) and adverse maternal health outcomes; however, the impact of area-level SES on maternal co-morbidities and obstetric interventions has not been examined. OBJECTIVE: To examine the variation in maternal co-morbidities and obstetric interventions across area-level SES. METHODS: This study used data from the Discharge Abstract Database that comprised birth data in Alberta between 2005-2007 (n = 120 285). Co-morbidities and obstetric interventions were identified using validated case-definitions. Material deprivation index was obtained for each dissemination area through linkage of hospitalisation and census data. Multilevel logistic regression was used to analyse the data adjusting for potential confounding variables. RESULTS: The prevalence of any co-morbidity varied across area-level SES. Drug abuse odds ratio (OR) 2.5 (95% confidence interval (CI) 1.8, 3.5), pre-existing diabetes OR 1.7 (95% CI 1.1, 2.6), and prolonged hospital stay OR 1.5 (95% CI 1.4, 1.6) were significantly more likely to occur in the most deprived areas compared to the least deprived areas. In contrast, caesarean delivery OR 0.9 (95% CI 0.8, 0.9) was less likely to occur in the most deprived areas compared to the least deprived areas. Area-level deprivation explained area-level variance of drug abuse, HIV, and other mental diseases only. CONCLUSION: Many co-morbidities and obstetric interventions vary at the area-level, but only some are associated with area-level SES, and few of them vary due to the area-level SES. This indicates that other area-level factors, in addition to area-level SES, need to be considered when investigating maternal health and use of health interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".