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Association between preterm births and socioeconomic development: analysis of national data

BACKGROUND: The increasing prevalence of preterm birth, which is a global phenomenon, is attributable to the increased medical indications, artificial gestations, and some socioeconomic factors. This study was conducted to identify whether development and equality indices are associated with the inc...

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Detalles Bibliográficos
Autores principales: Montemor, Marina Sanches, Demarque, Gabriella Ferreira, Rodrigues, Agatha Sacramento, Francisco, Rossana Pulcinelli Vieira, de Carvalho, Mario Henrique Burlacchini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632029/
https://www.ncbi.nlm.nih.gov/pubmed/36329411
http://dx.doi.org/10.1186/s12889-022-14376-2
Descripción
Sumario:BACKGROUND: The increasing prevalence of preterm birth, which is a global phenomenon, is attributable to the increased medical indications, artificial gestations, and some socioeconomic factors. This study was conducted to identify whether development and equality indices are associated with the incidence of preterm birth, specifically, spontaneous and elective preterm births. METHODS: This retrospective observational study comprised an analysis of data on live births from 2019 in Brazil and on socioeconomic indices that were derived from census information in 2017. Data were summarised using absolute and relative frequencies. Spearman’s correlation was used to determine the correlation between socioeconomic factors and the preterm birth rate. Multiple beta regression analysis was performed to determine the best model of socioeconomic covariates and preterm birth rate. The significance level was set at 5%. RESULTS: In 2019 in Brazil, the preterm birth rate was 11.03%, of which 58% and 42% were spontaneous and elective deliveries, respectively. For all preterm births, Spearman’s correlation varied from ρ = 0.4 for the Gini Index and ρ =  − 0.24 for illiteracy. The best fit modelled the spontaneous preterm birth fraction as a negative function of the Human Development Index (HDI). The best-fit model considered the expected elective preterm birth fraction as a positive function of the HDI and as a negative function of the Gini Index, which was used as a precision parameter. CONCLUSIONS: We observed a reduction in the fraction of spontaneous preterm births; however, the distribution was not uniform in the territory: higher rates of spontaneous preterm birth were noticed in the north, northeast, and mid-west regions. Thus, areas with lower education levels and inequal income distribution have a higher proportion of spontaneous preterm birth. The fraction of elective preterm birth was positively associated with more advantaged indices of socioeconomic status. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14376-2.