AN IMPLICATIVE STATISTICAL VIEW APPLIED TO LOW BIRTH WEIGHT

https://doi.org/10.56274/rcs.2025.4.2.56

Abstract

Introduction: The most significant factor predicting mortality in newborn babies, low birth weight, is undoubtedly a critical issue. Objective: To determine the key factors that may be linked to low birth weight in the municipality of Santiago de Cuba. 2023. Method: An observational, analytical, case-control study was conducted in the municipality of Santiago de Cuba in 2023. The sample consisted of 444 newborns, of whom 148 were underweight and 296 were of normal weight. Different variables were evaluated and two statistical analysis methodologies were applied: binary logistic regression and corroboration of possible multivariate relationships through implicative statistical analysis with implication intensities of 100, 99, 98, and 95, respectively. Results: With high implicative intensity, it was possible to verify the association of low birth weight with factors such as pregnancy in the middle or advanced stages, age limits, and nutritional assessment of low maternal weight. The presence of vaginal infections during pregnancy, a history of hypertension, anemia, and the consumption of harmful substances such as tobacco, alcohol, and coffee could be seen as possible risk factors in the population analyzed. Conclusions: Low birth weight is a global health challenge; harmful habits, low maternal weight, and personal and obstetric history could be connected, without this differing from global figures.