Data on Rapid Weight Gain in children

This dataset contains clinical and anthropometric data from a prospective cohort study of infants followed from birth to 6 months of age to predict rapid weight gain (RWG). Data were collected at Colima, Mexico. The study evaluated predictors of RWG using multiple modeling approaches: Support Vector Machine (SVM) with linear kernel, Naïve Bayes, Least Absolute Shrinkage and Selection Operator (LASSO), and Generalized Linear Model (GLM). RWG was defined as a change in weight-for-age Z-score > 0.67 standard deviations from birth to 6 months. Variables:- sexo: Infant sex (male/female)- pesoalnacer: Birth weight (grams)- tallaalnacer: Birth length (cm)- rwg06m: Rapid weight gain from birth to 6 months (binary outcome: yes/no)- edadmaterna: Maternal age (years)- imcpregestacional: Pre-pregnancy body mass index (kg/m²)- noembarazos: Number of previous pregnancies (parity)- ef3m: Exclusive breastfeeding at 3 months (yes/no)- fr3m: Formula feeding at 3 months (yes/no)- sr3m: Satiety responsiveness at 3 months (infant eating behavior scale)- se3m: Slowness in eating at 3 months (infant eating behavior scale)- cesarea: Cesarean delivery (yes/no)- peginergrowth_2: Growth classification category- escolaridad_2: Maternal education level (categorical)- alim3m_2: Feeding pattern at 3 months (categorical)- nse_2: Socioeconomic status category (categorical) Data are presented at the individual level with all identifiers removed to protect participant confidentiality. This dataset accompanies the research article: Ortega-Ramírez AD, Sánchez-Ramírez CA, Trujillo-Hernández B, Murillo-Zamora E. (2026). Predicting rapid weight gain in six-month-old infants: an exploratory modeling study. Pediatr Res. doi: 10.1038/s41390-026-04850-7.