Evidence map›Paper›PMID 38443875›Full record

ArticleBMC public health2024

Evaluating the relationship between conditional cash transfer programme on preterm births: a retrospective longitudinal study using the 100 million Brazilian cohort.

Naiá Ortelan, Márcia Furquim de Almeida, Elzo Pereira Pinto Júnior, Nivea Bispo, Rosemeire L Fiaccone, Ila Rocha Falcão, Aline Dos Santos Rocha, Dandara Ramos, Enny S Paixão, Rita de Cássia Ribeiro-Silva and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 14% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

13 authors at 4 institutions in 2 countries.

Naiá OrtelanCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil. naia.ortelan@fiocruz.br.
Márcia Furquim de AlmeidaSchool of Public Health, University of São Paulo (USP), Sao Paulo, Brazil.
Elzo Pereira Pinto JúniorCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Nivea BispoCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Rosemeire L FiacconeCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Ila Rocha FalcãoCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Aline Dos Santos RochaCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Dandara RamosCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Enny S PaixãoCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Rita de Cássia Ribeiro-SilvaCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Laura C RodriguesCenter for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Mauricio L Barreto *Center for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Maria Yury T Ichihara *Center for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ-BA), Salvador, Bahia, Brazil.
Fundação Oswaldo Cruz · BRLondon School of Hygiene & Tropical Medicine · GBUniversidade de São Paulo · BRUniversidade Federal da Bahia · BR

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundPreterm births increase mortality and morbidity during childhood and later life, which is closely associated with poverty and the quality of prenatal care. Therefore, income redistribution and poverty reduction initiatives may be valuable in preventing this outcome. We assessed whether receipt of the Brazilian conditional cash transfer programme - Bolsa Familia Programme, the largest in the world - reduces the occurrence of preterm births, including their severity categories, and explored how this association differs according to prenatal care and the quality of Bolsa Familia Programme management.

methodsA retrospective cohort study was performed involving the first live singleton births to mothersenrolled in the 100 Million Brazilian Cohort from 2004 to 2015, who had at least one child before cohort enrollment. Only the first birth during the cohort period was included, but born from 2012 onward. A deterministic linkage with the Bolsa Familia Programme payroll dataset and a similarity linkage with the Brazilian Live Birth Information System were performed. The exposed group consisted of newborns to mothers who received Bolsa Familia from conception to delivery. Our outcomes were infants born with a gestational age < 37 weeks: (i) all preterm births, (ii) moderate-to-late (32-36), (iii) severe (28-31), and (iv) extreme (< 28) preterm births compared to at-term newborns. We combined propensity score-based methods and weighted logistic regressions to compare newborns to mothers who did and did not receive Bolsa Familia, controlling for socioeconomic conditions. We also estimated these effects separately, according to the adequacy of prenatal care and the index of quality of Bolsa Familia Programme management.

results1,031,053 infants were analyzed; 65.9% of the mothers were beneficiaries. Bolsa Familia Programme was not associated with all sets of preterm births, moderate-to-late, and severe preterm births, but was associated with a reduction in extreme preterm births (weighted OR: 0.69; 95%CI: 0.63-0.76). This reduction can also be observed among mothers receiving adequate prenatal care (weighted OR: 0.66; 95%CI: 0.59-0.74) and living in better Bolsa Familia management municipalities (weighted OR: 0.56; 95%CI: 0.43-0.74).

conclusionsAn income transfer programme for pregnant women of low-socioeconomic status, conditional to attending prenatal care appointments, has been associated with a reduction in extremely preterm births. These programmes could be essential in achieving Sustainable Development Goals.

Indexed as

Premature BirthBrazilChildFemaleFertilizationHumansInfantInfant, NewbornLongitudinal StudiesPregnancyRetrospective Studies100 million Brazilian cohortBolsa Familia ProgrammeConditional cash transferIncome redistributionPrenatal carePreterm birthPropensity score

Identifiers

PMID38443875
PMCPMC10916064
OpenAlexW4392450849

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.