SynthesisPreventing chronic disease2026
Reducing Rates of Cesarean Delivery in Rural US Communities: A Systematic Review of Interventions and Approaches to Care.
Synthesis in Preventing chronic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Introduction: Cesarean deliveries are the most common major surgery in the US, with rates rising disproportionately in rural communities. While sometimes medically necessary, unnecessary cesarean births increase risks for maternal death, long-term complications, and intergenerational health effects that contribute to the burden of chronic disease. This systematic review examined studies describing interventions and approaches to care that reported outcomes related to reducing cesarean delivery rates in rural US communities. Methods: We searched 4 databases in September 2025. Studies were eligible if they were conducted in rural US settings and reported cesarean-related outcomes associated with an intervention or care approach. We categorized interventions as patient level, provider level, or health system level. Two reviewers independently screened articles for inclusion, extracted data, and assessed study quality using the Newcastle-Ottawa Scale and the Joanna Briggs Institute checklist. Results: Nine studies met inclusion criteria. Of the 2 patient-level interventions, psychosocial education was associated with lower cesarean delivery rates (21% in intervention vs 40% in control), whereas a mobile health application showed only a marginal difference (27.1% among application users vs 27.7% among nonusers). None were categorized at the provider level. Seven interventions tested system-level models, primarily comparing hospitals with different staffing patterns; family medicine-led hospitals had lower rates of low-risk nulliparous, term, singleton, vertex cesarean delivery than hospitals staffed by both family medicine physicians and obstetricians (23% vs 28%), certified nurse-midwife-managed births had lower cesarean delivery rates than family medicine physician-managed births (8% vs 14%), and collaborative maternity care models integrating midwives, nurses, and obstetricians were associated with cesarean delivery rates declining from 26.2% to 11.2%. Conclusion: System-level approaches, particularly those that restructure maternity care teams, emphasize family medicine physician-led models, and integrate midwifery and culturally grounded childbirth practices, are more consistently associated with lower cesarean delivery rates in rural US settings than patient-level interventions alone. Future efforts to reduce unnecessary cesarean deliveries should prioritize strategies tailored to the variability of rural care capacity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.