Temporal Changes in the Contribution of Chronic Disease to Maternal Mortality in the United States
Bibliographic record
Abstract
BACKGROUND: Increases in maternal age, obesity and other factors have led to an increase in hypertension, diabetes, and other chronic diseases among pregnant women. However, the impact of chronic diseases on maternal mortality has not been adequately studied. OBJECTIVES: To quantify the contribution of maternal mortality associated with chronic disease to maternal mortality in the United States in 1999-2002 and 2018-2022. METHODS: The study was based on maternal deaths in the United States in 1999-2002 and 2018-2022, with data obtained from the mortality and live birth files of the National Center for Health Statistics. Maternal deaths and maternal deaths associated with chronic disease were identified based on the presence of pregnancy-related causes and chronic diseases among the multiple causes of death. Maternal mortality ratios (MMR) and ratios of MMRs and their 95% confidence intervals (CI) were estimated to assess period change. Temporal changes in MMRs were adjusted for maternal age using direct standardisation. RESULTS: Although overall MMRs were stable, direct obstetrical deaths decreased by 14% (95% CI 9, 23) from 1999-2002 to 2018-2022. Maternal deaths associated with chronic disease increased by 28% (95% CI 17, 40) from 5.41 in 1999-2002 to 6.92 per 100,000 live births in 2018-2022. The temporal increases in chronic disease-related maternal deaths were attenuated but not abolished following adjustment for maternal age (age-adjusted increase 16%, 95% CI 10, 23). MMRs associated with chronic disease increased in all age groups, especially among women aged < 20 and 30-39 years (57% and 17% increase, respectively). Non-Hispanic Black women had the highest MMRs associated with chronic disease (15.8 per 100,000 live births in 2018-2022), while age-adjusted MMRs increased among non-Hispanic White women (45% increase, 95% CI 33, 59). CONCLUSIONS: A substantial fraction of maternal deaths in the United States is associated with chronic disease, although patterns vary by race/ethnicity.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".