Temporal changes in <scp>pre‐existing</scp> health conditions five years prior to pregnancy in British Columbia, Canada, 2000–2019
Bibliographic record
Abstract
BACKGROUND: Pre-existing health conditions increase the risk of obstetric complications during pregnancy and birth. However, the prevalence and recent changes in the frequency of pre-existing health conditions in the childbearing population remain unknown. OBJECTIVES: To estimate the temporal changes in the prevalence of pre-existing health conditions among pregnant women in British Columbia, Canada. METHODS: We carried out a population-based cross-sectional study of 825,203 deliveries in BC between 2000 and 2019 and examined 17 categories of physical and psychiatric health conditions recorded within 5 years before childbirth. We also undertook age-period-cohort analyses to evaluate temporal changes in pre-existing health conditions. RESULTS: The prevalence of any pre-existing health condition was 26.2% (n = 216,214) with overall trends remaining stable during the study period. Between 2000 and 2019, the prevalence rates of anxiety (5.6%-9.6%), bipolar (1.6%-3.4%), psychosis (0.7%-0.8%), and eating disorders (0.2%-0.3%) increased. The prevalence of hypertension increased sharply from 0.06% in 2000 to 0.3% in 2019. Diabetes mellitus and stroke rates increased, as did the prevalence of systemic lupus, multiple sclerosis, and chronic kidney disease. Advanced maternal age was strongly associated with both psychiatric and circulatory/metabolic conditions. A strong birth cohort effect was evident, with rates of psychiatric conditions increasing among women born after 1985. CONCLUSIONS: In British Columbia, Canada, 1 in 4 mothers had a pre-existing health condition 5 years prior to pregnancy. These findings underscore the need for multi-disciplinary care for women with pre-existing health conditions to improve maternal, foetal, and infant health.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".