Evidence map›Paper›PMID 37673446›Full record

ArticleBMJ open2023

Maternal and child nutrition programme of investigation within the 100 Million Brazilian Cohort: study protocol.

Thais Rangel Bousquet Carrilho, Natanael de Jesus Silva, Enny Santos Paixão, Ila Rocha Falcão, Rosemeire Leovigildo Fiaccone, Laura Cunha Rodrigues, Srinivasa Vittal Katikireddi, Alastair H Leyland, Ruth Dundas, Anna Pearce and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 51% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

15 authors at 5 institutions in 3 countries.

Thais Rangel Bousquet CarrilhoNutritional Epidemiology Observatory, Josué de Castro Institute of Nutrition, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.ORCID 0000-0001-5928-6136
Natanael de Jesus SilvaCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil.ORCID 0000-0003-3002-1032
Enny Santos PaixãoCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil.ORCID 0000-0002-4797-908X
Ila Rocha FalcãoCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil.
Rosemeire Leovigildo FiacconeCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil.
Laura Cunha RodriguesCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil.
Srinivasa Vittal KatikireddiMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland, UK.ORCID 0000-0001-6593-9092
Alastair H LeylandMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland, UK.
Ruth DundasMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland, UK.
Anna PearceMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland, UK.
Gustavo Velasquez-MelendezDepartment of Maternal and Child Nursing and Public Health, Nursing School, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.
Gilberto KacNutritional Epidemiology Observatory, Josué de Castro Institute of Nutrition, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
Rita de Cássia Ribeiro SilvaCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil rcrsilva@ufba.br.ORCID 0000-0002-8387-9254
Mauricio L BarretoCentre for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, BA, Brazil.
Nutrition Study Group of the Center for Data and Knowledge Integration for Health (GeNut-CIDACS)
MRC/CSO Social and Public Health Sciences Unit · GBUniversidade Federal da Bahia · BRKnowledge Integration (United Kingdom) · GBUniversidade Federal do Rio de Janeiro · BRUniversidade Federal de Minas Gerais · BR

Funding

Chief Scientist Office SPHSU17Medical Research Council MC_UU_00022/2Wellcome TrustWellcome Trust 202912/Z/16/Z
6 · The paper itself

Abstract

introductionThere is a limited understanding of the early nutrition and pregnancy determinants of short-term and long-term maternal and child health in ethnically diverse and socioeconomically vulnerable populations within low-income and middle-income countries. This investigation programme aims to: (1) describe maternal weight trajectories throughout the life course; (2) describe child weight, height and body mass index (BMI) trajectories; (3) create and validate models to predict childhood obesity at 5 years of age; (4) estimate the effects of prepregnancy BMI, gestational weight gain (GWG) and maternal weight trajectories on adverse maternal and neonatal outcomes and child growth trajectories; (5) estimate the effects of prepregnancy BMI, GWG, maternal weight and interpregnancy BMI changes on maternal and child outcomes in the subsequent pregnancy; and (6) estimate the effects of maternal food consumption and infant feeding practices on child nutritional status and growth trajectories. METHODS AND ANALYSIS: Linked data from four different Brazilian databases will be used: the 100 Million Brazilian Cohort, the Live Births Information System, the Mortality Information System and the Food and Nutrition Surveillance System. To analyse trajectories, latent-growth, superimposition by translation and rotation and broken stick models will be used. To create prediction models for childhood obesity, machine learning techniques will be applied. For the association between the selected exposure and outcomes variables, generalised linear models will be considered. Directed acyclic graphs will be constructed to identify potential confounders for each analysis investigating potential causal relationships. ETHICS AND DISSEMINATION: This protocol was approved by the Research Ethics Committees of the authors' institutions. The linkage will be carried out in a secure environment. After the linkage, the data will be de-identified, and pre-authorised researchers will access the data set via a virtual private network connection. Results will be reported in open-access journals and disseminated to policymakers and the broader public.

Indexed as

Body-Weight TrajectoryPediatric ObesityBrazilChildChild Nutritional Physiological PhenomenaFamilyFemaleHumansInfantInfant, NewbornPregnancyCommunity child healthNUTRITION & DIETETICSPUBLIC HEALTH

Identifiers

PMID37673446
PMCPMC10496662
OpenAlexW4386483438

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.