Evidence map›Paper›PMID 41310927›Full record

ArticleWomen's health (London, England)

The impact of excessive caesarean deliveries on gestational age at birth in Mexico: National-level trends, 2010-2023.

Héctor Lamadrid-Figueroa, Jimena Fritz

Abstract read
In one paragraph

Article in Women's health (London, England). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Héctor Lamadrid-FigueroaDepartment of Perinatal Health, National Institute of Public Health, Cuernavaca, Mexico.ORCID 0000-0001-8775-8399
Jimena FritzCentre for Research in Nutrition and Health, National Institute of Public Health, Cuernavaca, Mexico.ORCID 0000-0002-4157-5981

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCaesarean section (C-section) rates in Mexico have risen dramatically over the past decade, reaching 55% by 2023. While life-saving when correctly indicated, excessive use may alter the natural timing of childbirth and shift population-level birth outcomes.

objectivesTo examine national trends in gestational age, birth weight and birth length from 2010 to 2023, and evaluate their association with mode of delivery.

designPopulation-based repeated cross-sectional analysis using national birth certificate data.

methodsWe analysed a 1-in-1000 random sample of birth certificates from Mexico's national registry (

resultsThe C-section rate rose from 45% in 2010 to 55% in 2023. Over the same period, full-term births (⩾39 weeks) declined from 66.5% to 57.7%, while early-term births (37-38 weeks) rose from 26.6% to 34.2%. Gestational age declined over time for both vaginal and C-section deliveries. A sharp rise in C-section rates beginning around 2015 coincided with abrupt downward trends in gestational age, birth weight, and length across delivery modes. In adjusted models, birth by C-section was associated with a reduction of 0.5 weeks in gestational age at birth (

conclusionThe rising prevalence of C-sections in Mexico aligns with a broader shift towards earlier deliveries, driven primarily by an increase in early-term births. This shift affects both surgical and spontaneous deliveries and may have long-term implications for children health.

Indexed as

Cesarean SectionGestational AgeAdultBirth WeightCross-Sectional StudiesDelivery, ObstetricFemaleHumansInfant, NewbornMaternal AgeMexicoPregnancyPregnancy OutcomeYoung Adultbirth outcomescaesarean sectiongestational age

Identifiers

PMID41310927
PMCPMC12660652

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.