Elucidating the intersectional effects of race and migration on obstetric anal sphincter injury
Bibliographic record
Abstract
Obstetric anal sphincter injury (OASI) describes severe injury to the perineum and perianal muscles following birth. OASI occurs in 4% to 6.6% of vaginal births in Canada and in approximately 4.4% of vaginal births in the United States (US). However, racial and ethnic inequities in the incidence of OASI have been demonstrated in several high-income countries. The scoping review aimed to assess the literature on the topics of race/ethnicity, migration status, and OASI. The study examined race/ethnicity and migration as risk factors. Causal mechanisms behind race/ethnicity as a risk factor (i.e., perineal length, obesity and Body Mass Index (BMI), and language barrier) were also examined. The study revealed that Asian individuals experience the greatest risk of OASI. Despite this, an updated review on the topic has not been published since 2012. This led me to the second aim of my thesis, which was to conduct a systematic review and meta-analysis to critically summarize the reported incidence of OASI in Asian subgroups, specifically. I identified 27 studies that compared OASI risk of individuals who identify as Asian vs. white. The meta-analysis pooled estimates of OASI from these studies found a 1.6-fold increase in OASI among Asian vs. white individuals (OR 1.64, 95% CI 1.48–1.80). Few studies have explored underlying causal mechanisms responsible for this relationship. This thesis is a valuable addition to the existing scholarship in both women’s health and health equity research. The exploration of core concepts surrounding the topics of race/ethnicity, migration and OASI provide this thesis with a comprehensive understanding of the studies included. The scoping review provides a clear understanding of the state of the currently available literature within the topics of race/ethnicity, migration and OASI. In addition, the systematic review and meta-analysis offers a quantitatively comprehensive understanding of Asian race/ethnicity as a risk factor of OASI. These findings can be used to guide future research in the fields of women’s health and health equity. It will also be a valuable guide when developing future health policy and clinical guidelines that prioritize equitable accessibility and availability within obstetric care.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".