Evidence map›Paper›PMID 32717778›Full record

ArticleInternational journal of environmental research and public health2020

Population-Based Birth Cohort Studies in Epidemiology.

Cristina Canova, Anna Cantarutti

Abstract readEditorial
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
–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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  18. Intrapartum Quality of Care among Healthy Women: A Population-Based Cohort Study in an Italian Region.International journal of environmental research and public health · 2024
    Article
  19. The indispensableScandinavian journal of work, environment & health · 2024
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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.

Cristina CanovaUnit of Biostatistics, Epidemiology and Public Health, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy.
Anna CantaruttiLaboratory of Healthcare Research & Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, 20126 Milan, Italy.ORCID 0000-0002-3700-780X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Birth cohort studies are the most appropriate type of design to determine the causal relationship between potential risk factors during the prenatal or postnatal period and the health status of the newborn up to childhood and potentially adulthood. To date, there has been a growth in interest regarding observational population-based studies which are performed to provide answers to specific research questions for defined populations, for instance, assessing the exposure to environmental pollutants or drugs on the risk of developing a disease. Birth cohorts based on the recruitment and active follow-up of mothers and children allow the collection of biological material, and specific clinical and genetic information. However, they require a considerable amount of time and resources and, besides being usually of limited size, they are exposed to the risk of the loss of subjects to follow-up, with decreased statistical power and possible selection bias. For these reasons, linking the medical birth register with administrative health records for mothers and babies is increasingly being used in countries with a universal healthcare system, allowing researchers to identify large and unselected populations from birth, and to reconstruct relevant traits and care pathways of mothers and newborns. This Special Issue of the International Journal of Environmental Research and Public Health focuses on the current state of knowledge on perinatal and postnatal exposures and adverse pregnancy, maternal, fetal and neonatal outcomes through population-based birth cohort studies, with a specific focus on real-word data. The 12 accepted articles covered a wide range of themes that can be addressed specifically through birth cohort study design; however, only three were based on real word data with record-linkage to health administrative databases. In particular, two papers have addressed the topic of socioeconomic status considering several indicators both at the individual and contextual level. Two papers focused on inflammatory bowel diseases, both as an outcome of perinatal and antibiotic exposure in early life and as a condition associated with asthma, among children identified in a birth cohort based on a Regional Medical Birth Register. Three articles focused on medication use during pregnancy and its impact on maternal and fetal health. The effect of exposure to prenatal environmental risk factors on perinatal and childhood outcomes has been considered in two papers. Two papers analyzed ad hoc nationwide prospective birth cohorts set in Japan and UK. Finally, we included a systematic review with meta-analysis to evaluate the relation between growth restriction at birth and congenital heart defects. We think that this Special Issue may contribute to enriching the discussion of future challenges, opportunities, strengths and limitations for all research topics that can be investigated using a population-based birth cohort study design.

Indexed as

Cohort StudiesEnvironmental PollutantsFemaleHumansInfant, NewbornJapanPregnancyRisk FactorsEnvironmental Pollutantsbirth cohort studyenvironmental exposureepidemiologyperinatal and postnatal exposurepharmacoepidemiologyreal-world datarecord linkage

Identifiers

PMID32717778
PMCPMC7432312

What OpenQuestion holds

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LicenceCC BY
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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.