A Scoping Review of Risk Factors of Hypertensive Disorders of Pregnancy in Black Women Living in High-Income Countries
Bibliographic record
Abstract
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are maternity-related increases in blood pressure (eg, gestational hypertension, preeclampsia, and eclampsia). Compared with women of other races in high-income countries, Black women have a comparatively higher risk of an HDP. Intersectionality helps to provide a deeper understanding of the multifactorial identities that affect health outcomes in this high-risk population. OBJECTIVE: In this review, we sought to explore the literature on HDP risk factors in Black women living in high-income countries and to assess the interaction of these risk factors using the conceptual framework of intersectionality. METHODS: We conducted this review using the Arksey and O'Malley methodology with enhancements from Levac and colleagues. Published articles in English on HDP risk factors with a sample of not less than 10% of Black women in high-income countries were included. Six databases, theses, and dissertations were searched from January 2000 to July 2021. A thematic analysis was used to summarize the results. RESULTS: A final total of 36 studies were included from the 15 480 studies retrieved; 4 key themes of HDP risks were identified: (1) biological; (2) individual traditional; (3) race and ethnicity, geographical location, and immigration status; and (4) gender related. These intersectional HDP risk factors intersect to increase the risk of HDP among Black women living in high-income countries. CONCLUSION: Upstream approaches are recommended to lower the risks of HDP in this population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| 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 | 0.001 |
| 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".