Brazilian Maternal and Child Nutrition Consortium: establishment, data harmonization and basic characteristics

• Autor(a) principal: Carrilho, Thaís Rangel Bousquet
• Data de Publicação: 2020
• Outros Autores: Farias, Dayana Rodrigues, Batalha, Mônica Araújo, Costa, Nathalia Cristina Freitas, Rasmussen, Kathleen M., Reichenheim, Michael E., Ohuma, Eric O., Hutcheon, Jennifer A., Kac, Gilberto, Oliveira, Adauto Emmerich, Esteves-Pereira, Ana Paula, Sato, Ana Paula Sayuri, da Silva, Antônio Augusto Moura, Costa, Bárbara Miranda Ferreira, de Moraes, Claudia Leite, Saunders, Claudia, Parada, Cristina Maria Garcia de Lima [UNESP], Rocha, Daniela da Silva, Gigante, Denise Petrucci, dos Santos-Neto, Edson Theodoro, Lacerda, Elisa Maria de Aquino, Fujimori, Elizabeth, Surita, Fernanda Garanhani, Gomes-Filho, Isaac Suzart, Bierhals, Isabel Oliveira, Capelli, Jane de Carlos Santana, Cecatti, José Guilherme, Vaz, Juliana dos Santos, Cesar, Juraci Almeida, Mastroeni, Marco Fábio, Carvalhaes, Maria Antonieta de Barros Leite [UNESP], da Silveira, Mariângela Freitas, Domingues, Marlos Rodrigues, Fernandes, Mayra Pacheco, Drehmer, Michele, Gonzalez, Mylena Maciel, Padilha, Patrícia de Carvalho, Junior, Renato Passini, Souza, Renato Teixeira, Alves, Ronaldo Fernandes Santos, Batista, Rosângela Fernandes Lucena, Mastroeni, Silmara Salete de Barros Silva, Saldiva, Silvia Regina Dias Medici, da Cruz, Simone Seixas, Morais, Sirlei Siani, Mengue, Sotero Serrate
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1038/s41598-020-71612-8; http://hdl.handle.net/11449/228849

Pooled data analysis in the field of maternal and child nutrition rarely incorporates data from low- and middle-income countries and existing studies lack a description of the methods used to harmonize the data and to assess heterogeneity. We describe the creation of the Brazilian Maternal and Child Nutrition Consortium dataset, from multiple pooled longitudinal studies, having gestational weight gain (GWG) as an example. Investigators of the eligible studies published from 1990 to 2018 were invited to participate. We conducted consistency analysis, identified outliers, and assessed heterogeneity for GWG. Outliers identification considered the longitudinal nature of the data. Heterogeneity was performed adjusting multilevel models. We identified 68 studies and invited 59 for this initiative. Data from 29 studies were received, 21 were retained for analysis, resulting in a final sample of 17,344 women with 72,616 weight measurements. Fewer than 1% of all weight measurements were flagged as outliers. Women with pre-pregnancy obesity had lower values for GWG throughout pregnancy. GWG, birth length and weight were similar across the studies and remarkably similar to a Brazilian nationwide study. Pooled data analyses can increase the potential of addressing important questions regarding maternal and child health, especially in countries where research investment is limited.