biostudies-literatureMartins-Silva TWellcome Trust881-895https://www.ebi.ac.uk/biostudies/studies/S-EPMC10126565biostudies-literatureUnknown33(3)Conduct problems are associated with an increased risk of a wide range of physical, mental, and social problems. However, there is still uncertainty about how early risk factors differentiate different developmental patterns of conduct problems and whether findings replicate across diverse social contexts. We aimed to identify developmental trajectories of conduct problems, and test early risk factors, in the 2004 Pelotas Birth Cohort in Brazil. Conduct problems were measured at ages 4, 6, 11, and 15 years from caregiver reports on the Child Behaviour Checklist (CBCL) and Strengths and Difficulties Questionnaire (SDQ). Conduct problem trajectories were estimated using group-based semi-parametric modeling (n = 3938). Multinomial logistic regression was used to examine associations between eEuropean child & adolescent psychiatryEarly risk factors for conduct problem trajectories from childhood to adolescence: the 2004 Pelotas (BRAZIL) Birth Cohort.PMC10126565210735210735_Z_18_ZSantos ISBauer AMunhoz TNMatijasevich AMartins-Silva TBarros AJDMurray JTovo-Rodrigues LfalseEarly risk factors for conduct problem trajectories from childhood to adolescence: the 2004 Pelotas (BRAZIL) Birth Cohort.Conduct problems are associated with an increased risk of a wide range of physical, mental, and social problems. However, there is still uncertainty about how early risk factors differentiate different developmental patterns of conduct problems and whether findings replicate across diverse social contexts. We aimed to identify developmental trajectories of conduct problems, and test early risk factors, in the 2004 Pelotas Birth Cohort in Brazil. Conduct problems were measured at ages 4, 6, 11, and 15 years from caregiver reports on the Child Behaviour Checklist (CBCL) and Strengths and Difficulties Questionnaire (SDQ). Conduct problem trajectories were estimated using group-based semi-parametric modeling (n = 3938). Multinomial logistic regression was used to examine associations between e2024-01-01T00:00:00Z2024 Mar2026-07-14T20:11:28.174Z2025-04-19T14:46:29.571ZS-EPMC101265653709734510.1007/s00787-023-02178-9