Evidence map›Paper›PMID 38743743›Full record

ArticlePloS one2024

Association between location of prenatal care services and non-consented cesarean sections in Mexico: A secondary analysis of the National Survey on the Dynamics of Household Relationships 2016.

Marian Marian, Ramona L Pérez

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Marian MarianHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, United States of America.ORCID 0000-0001-7395-0486
Ramona L PérezDepartment of Anthropology, San Diego State University, San Diego, CA, United States of America.ORCID 0000-0003-0732-0827

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMexico has one of the world's highest rates of cesarean section (C-section). Little is known about Mexico's frequency of and risk factors for non-consented C-sections, a form of obstetric violence. We examined the prevalence of sociodemographic and obstetric-specific characteristics of Mexican women who delivered via C-section, as well as the association between the location of prenatal care services and experiencing a non-consented C-section.

methodsWe conducted a secondary analysis of data collected from Mexico's 2016 National Survey on the Dynamics of Household Relationships (ENDIREH 2016) of women who reported a C-section during their latest delivery. Adjusted logistic regressions were calculated to explore the associations between the location of prenatal care services and experiencing a non-consented cesarean delivery, stratifying by Indigenous belonging.

resultsThe sample size for this analysis was 10,256 ENDIREH respondents, with 9.1% not consenting to a C-section. ENDIREH respondents between the ages of 26 and 35 years old, living in urban settings, living in Central or Southern Mexico, and married or living with a partner experienced a higher prevalence of non-consented C-sections. For both women who identified as Indigenous and those who did not, the odds of experiencing a non-consented C-section were higher when receiving prenatal services in private settings. Receiving more than one type of prenatal service was also associated with increased odds of non-consented C-sections, while ENDIREH 2016 respondents who did not identify as Indigenous and received prenatal care at the State Institute for Social Security and Services for State Workers facility had lower odds of experiencing a non-consented C-section.

conclusionsThis analysis indicates that receiving prenatal care at a private facility or a combination of public and private services increases the risk of experiencing a non-consented C-section in Mexico. Additional research is required to further understand the factors associated with non-consented C-sections in Mexico.

Indexed as

Cesarean SectionPrenatal CareAdolescentAdultFamily CharacteristicsFemaleHumansMexicoPregnancyRisk FactorsSurveys and QuestionnairesYoung Adult

Identifiers

PMID38743743
PMCPMC11093318

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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.