Adolescent pregnancy: Risk factors and their impact on fetal mortality
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Abstract
This quantitative, observational, and retrospective study analyzes the risk factors associated with fetal mortality among adolescent mothers in Ecuador. Secondary data from the National Institute of Statistics and Censuses (INEC, 2022) were used, and binary logistic regression techniques were applied, along with machine learning models such as XGBoost and LightGBM, to develop high-accuracy predictive models.
The results indicate that gestational age is the main protective factor: each additional week reduces the probability of fetal death by 8.5% (OR = 0.915, 95% CI: 0.887–0.943, p < 0.001). Furthermore, a higher risk of fetal mortality was identified in mothers with fewer than five prenatal check-ups (OR = 3.24, 95% CI: 2.17–4.83) and in births that occurred outside the hospital setting (OR = 2.71, 95% CI: 1.88–3.91).
The predictive models showed high performance, with XGBoost being the most accurate (AUC = 1.000), followed by LightGBM (AUC = 0.9997). These findings highlight the need to strengthen prenatal care, improve hospital infrastructure, and use artificial intelligence tools for early detection of high-risk pregnancies in vulnerable populations.
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Norma del Pilar Barreno-Layedra, Universidad Politécnica Estatal del Carchi - Ecuador
https://orcid.org/0000-0003-2910-3217
Norma del Pilar Barreno Layedra has been a professor at the Universidad de las Fuerzas Armadas ESPE, Latacunga campus, since 2010. I hold a Master's degree in Basic Mathematics and a Diploma in Mathematics Teaching. I am interested in education in Algebra and Statistics. I have published studies on the impact of open-source software in teaching, Fourier analysis in engines, and facial recognition with artificial intelligence. My work has been disseminated in scientific journals and conferences.
León Augusto Bourgeat-Terán, Universidad de las Fuerzas Armadas - ESPE - Ecuador
https://orcid.org/0009-0003-2457-7074
Augusto Bourgeat Terán is a professor and researcher at the Universidad de las Fuerzas Armadas - ESPE, with a distinguished career in electronic engineering, applied statistics, and machine learning. He holds a Master's degree in Research and Innovation in Information and Communication Technologies from the Universidad Autónoma de Madrid, a Master's in Applied Mathematics from the Universidad San Francisco de Quito, and an Executive Master's in Business Management with a specialization in Strategic Management. His teaching experience includes mathematics, advanced statistics, and physics, in addition to leading outreach projects and supervising research at the graduate level. He has published articles on project evaluation, global positioning systems, and physics education. Currently, he is responsible for the Graduate Program Management Section at ESPE's Latacunga campus.
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