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Elias D, Campaña H, Poletta FA, Heisecke SL, Gili JA, Ratowiecki J, Pawluk M, Santos MR, Cosentino V, Uranga R, Saleme C, Rittler M, Krupitzki HB, Lopez Camelo JS, Gimenez LG. Preterm birth etiological pathways: a Bayesian networks and mediation analysis approach. Pediatr Res 2022; 91:1882-1889. [PMID: 34282276 DOI: 10.1038/s41390-021-01659-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/02/2021] [Accepted: 06/30/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND The aim of this study was to determine the mediating effect of spontaneous preterm birth (PTB) main predictors that would allow to suggest etiological pathways. METHODS We carried out a case-control study, including sociodemographic characteristics, habits, health care, and obstetric data of multiparous women who gave birth at a maternity hospital from Tucumán, Argentina, between 2005 and 2010: 998 women without previous PTB who delivered at term and 562 who delivered preterm. We selected factors with the greatest predictive power using a penalized logistic regression model. A data-driven Bayesian network including the selected factors was created where we identified pathways and performed mediation analyses. RESULTS We identified three PTB pathways whose natural indirect effect was greater than zero with a 95% confidence interval: maternal age less than 20 years mediated by few prenatal visits, vaginal bleeding in the first trimester mediated by vaginal bleeding in the second trimester, and urinary tract infection mediated by vaginal bleeding in the second trimester. The effect mediated in these pathways showed greater sensitivity to confounders affecting the variables mediator-outcome and exposure-mediator in the same direction. CONCLUSION The identified pathways suggest PTB etiological lines related to social disparities and exposure to genitourinary tract infections. IMPACT Few prenatal visits (<5) and vaginal bleeding are two of the main predictors for spontaneous preterm birth in the studied population. Few prenatal visits mediates part of the risk associated with maternal age less than 20 years and vaginal bleeding in the second trimester mediates part of the risk associated with vaginal bleeding in the first trimester and with urinary tract infection. Social disparities and exposure to genitourinary tract infections would be etiological lines of spontaneous preterm birth.
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Affiliation(s)
- Dario Elias
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.
| | - Hebe Campaña
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Comisión de Investigaciones Científicas, Buenos Aires, Argentina
| | - Fernando A Poletta
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Instituto Nacional de Genética Médica Populacional (INAGEMP), CEMIC-CONICET, Ciudad Autónoma de Buenos Aires, Argentina
| | - Silvina L Heisecke
- Dirección de Investigación, CEMIC-CONICET, Ciudad Autónoma de Buenos Aires, Argentina
| | - Juan A Gili
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Instituto Académico Pedagógico de Ciencias Humanas, Universidad Nacional de Villa María, Córdoba, Argentina
| | - Julia Ratowiecki
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina
| | - Mariela Pawluk
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina
| | - Maria R Santos
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Comisión de Investigaciones Científicas, Buenos Aires, Argentina.,Instituto Multidisciplinario de Biología Celular, Buenos Aires, Argentina
| | - Viviana Cosentino
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Hospital Interzonal General de Agudos Luisa C. de Gandulfo, Buenos Aires, Argentina
| | - Rocio Uranga
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Hospital San Juan de Dios, Buenos Aires, Argentina
| | - Cesar Saleme
- Instituto de Maternidad y Ginecología Nuestra Señora de las Mercedes, Tucumán, Argentina
| | - Monica Rittler
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Hospital Materno Infantil Ramón Sardá, Ciudad Autónoma de Buenos Aires, Argentina
| | - Hugo B Krupitzki
- Dirección de Investigación, CEMIC-CONICET, Ciudad Autónoma de Buenos Aires, Argentina.,Instituto Universitario, Centro de Educación Médica e Investigaciones Clínicas (CEMIC-IUC), Ciudad Autónoma de Buenos Aires, Argentina
| | - Jorge S Lopez Camelo
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Instituto Nacional de Genética Médica Populacional (INAGEMP), CEMIC-CONICET, Ciudad Autónoma de Buenos Aires, Argentina
| | - Lucas G Gimenez
- Estudio Colaborativo Latino Americano de Malformaciones Congénitas (ECLAMC), Centro de Educación Médica e Investigaciones Clínicas-Consejo Nacional de Investigaciones Científicas y Técnicas (CEMIC-CONICET), Ciudad Autónoma de Buenos Aires, Argentina.,Instituto Nacional de Genética Médica Populacional (INAGEMP), CEMIC-CONICET, Ciudad Autónoma de Buenos Aires, Argentina
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Ratowiecki J, Santos MR, Poletta F, Heisecke S, Elias D, Gili J, Gimenez L, Pawluk M, Uranga R, Cosentino V, Campaña H, Rittler M, Camelo JSL. [Social inequities in teenage mothers and the relationship to adverse perinatal outcomes in South American populations]. CAD SAUDE PUBLICA 2021; 36:e00247719. [PMID: 33440423 DOI: 10.1590/0102-311x00247719] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Accepted: 05/26/2020] [Indexed: 11/22/2022] Open
Abstract
The aim was to explain differences in the rates of adverse perinatal events in teenage mothers with low and high schooling. The sample was collected from the Latin American Colaborative Study of Congenital Malformations (ECLAMC) database. From a total of 2,443,747 births in 93 hospitals, 66,755 live newborns without congenital malformations were recruited from 2000 to 2017. Teenage mothers were classified according to low, medium, and high schooling. A multivariate model was used that included reproductive history, access to health services, demographic and socioeconomic variables, and ethnic group. The Fairlie decomposition model was applied to quantify the contribution of explanatory variables to the adverse perinatal event rates. Of the 66,755 newborns analyzed, 21.1% (n = 14,078) were born to teenage mothers. Distribution of maternal schooling was 24.2%, 59.8%, and 16% for low, medium, and high schooling, respectively. The highest rates of adverse perinatal events were seen in teenage mothers with low schooling. The variable "access to health services" explained 35%, 37%, and 23% of the disparities in low birthweight, prematurity, and intrauterine growth restriction, respectively, among teenage mother with low and high schooling. Low number of prenatal visits was the only risk factor for the two levels of schooling and the variable that best explained the differences between the rates of adverse perinatal events. From the public health perspective, prenatal care represents a low-cost intervention with the possibility of increased implementation through adequate information for the population and systematic measures in primary care.
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Affiliation(s)
- Julia Ratowiecki
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina
| | - María Rita Santos
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Comisión de Investigaciones Científicas, La Plata, Argentina.,Instituto Multidisciplinario de Biología Celular, Buenos Aires, Argentina
| | - Fernando Poletta
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Instituto Nacional de Genética Médica Populacional, Porto Alegre, Brasil
| | | | - Dario Elias
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina
| | - Juan Gili
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Instituto Académico Pedagógico de Ciencias Humanas, Universidad Nacional de Villa María, Córdoba, Argentina
| | - Lucas Gimenez
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Instituto Nacional de Genética Médica Populacional, Porto Alegre, Brasil
| | - Mariela Pawluk
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina
| | - Rocio Uranga
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Hospital San Juan de Dios, Buenos Aires, Argentina
| | - Viviana Cosentino
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Hospital Interzonal General de Agudos Luisa C. de Gandulfo, Buenos Aires, Argentina
| | - Hebe Campaña
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Comisión de Investigaciones Científicas, La Plata, Argentina
| | - Mónica Rittler
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Hospital Materno Infantil Ramón Sardá, Buenos Aires, Argentina
| | - Jorge S López Camelo
- Laboratorio de Epidemiología Genética, Buenos Aires, Argentina.,Estudio Colaborativo Latinoamericano de Malformaciones Congénitas, Buenos Aires, Argentina.,Instituto Nacional de Genética Médica Populacional, Porto Alegre, Brasil
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Influence of vitamin D serum concentration, prenatal care and social determinants on birth weight: a northeastern Brazilian cohort study. Br J Nutr 2019; 122:284-292. [PMID: 31182171 DOI: 10.1017/s0007114519001004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The relationship among social determinants, vitamin D serum concentration and the health and nutrition conditions is an important issue in the healthcare of pregnant women and newborns. Thus, the present study analyses how vitamin D, prenatal monitoring and social determinants are associated with birth weight. The cohort comprised 329 pregnant women, up to 34 weeks gestational age at the time of admission, who were receiving care through the prenatal services of Family Health Units. Structural equation modelling was used in the statistical analysis. The mean birth weight was 3340 (sd 0·545) g. Each nmol increase in maternal vitamin D serum concentration was associated with an increase in birth weight of 3·06 g. Prenatal healthcare with fewer appointments (β -41·49 g, 95 % CI -79·27, -3·71) and late onset of care in the second trimester or third trimester (β -39·24 g, 95 % CI -73·31, -5·16) favoured decreased birth weight. In addition, low socio-economic class and the practice of Afro-Brazilian religions showed a direct association with high vitamin D serum concentrations and an indirect association with high birth weight, respectively. High gestational BMI (β 23·84, 95 % CI 4·37, 43·31), maternal education level (β 24·52 g, 95 % CI 1·82, 47·23) and length of gestation (β 79·71, 95 % CI 52·81; 106·6) resulted in high birth weight. In conclusion, maternal vitamin D serum concentration, social determinants and prenatal care, evaluated in the context of primary healthcare, directly determined birth weight.
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