Historical and Recent Changes in Maternal Mortality Due to Hypertensive Disorders in the United States, 1979 to 2018
Bibliographic record
Abstract
We evaluated the contributions of maternal age, year of death (period), and year of birth (cohort) on trends in hypertension-related maternal deaths in the United States. We undertook a sequential time series analysis of 155 710 441 live births and 3287 hypertension-related maternal deaths in the United States, 1979 to 2018. Trends in pregnancy-related mortality rate (maternal mortality rate [MMR]) due to chronic hypertension, gestational hypertension, and preeclampsia/eclampsia, were examined. MMR was defined as death during pregnancy or within 42 days postpartum due to hypertension. Trends in overall and race-specific hypertension-related MMR based on age, period, and birth cohort were evaluated based on weighted Poisson models. Trends were also adjusted for secular changes in obesity rates and corrected for potential death misclassification. During the 40-year period, the overall hypertension-related MMR was 2.1 per 100 000 live births, with MMR being almost 4-fold higher among Black compared with White women (5.4 [n=1396] versus 1.4 [n=1747] per 100 000 live births). Advancing age was associated with a sharp increase in MMR at ≥15 years among Black women and at ≥25 years among White women. Birth cohort was also associated with increasing MMR. Preeclampsia/eclampsia-related MMR declined annually by 2.6% (95% CI, 2.2–2.9), but chronic hypertension–related MMR increased annually by 9.2% (95% CI, 7.9–10.6). The decline in MMR was attenuated when adjusted for increasing obesity rates. The temporal burden of hypertension-related MMR in the United States has increased substantially for chronic hypertension–associated MMR and decreased for preeclampsia/eclampsia-associated MMR. Nevertheless, deaths from hypertension continue to contribute substantially to maternal deaths.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".