Background: Few longitudinal observational studies quantify multifactorial determinants? effects on children?s health. 
Aims: To identify clustering of determinants and estimate risk of early childhood diseases. 
Methods: This longitudinal cohort study, FAMILY, combined three Canadian pediatric cohorts and families. Early childhood diseases were asthma, allergic rhinitis (AR), and eczema. Latent Class Analysis (LCA) clustered mothers and children by 16 indicators in 3 domains (maternal and newborn; socioeconomic status [SES] and neighbourhood; environment). We used marginal Cox Proportional Hazard (PH) regression to quantify outcomes? hazard ratios (HR) and Poisson regression to estimate rate ratios (RR) of children?s healthcare use.   
Results: We included 15,724 mother-child pairs. LCA identified 4 mother-clusters. Classes 1 and 2 mothers were older (30s-40s), non-immigrants with university education, lived in high SES neighbourhoods with better air quality and more greenspace. Classes 3 and 4 mothers were younger (20s-30s), likely an immigrant/refugee, with high school-to-college education, and lived in lower SES neighborhoods with poorer air quality and less greenspace. Children?s outcomes differed by class. Compared to Class 1, Classes 3 and 4 children had higher risks of asthma (HR=1.24, 95%CI:1.11-1.37 and HR=1.39, 95%CI:1.22-1.59), similar higher risks of AR and eczema, and Class 4 children with asthma had 2-fold risk of asthma hospitalizations and 68% higher rate of asthma emergency department visits.  
Conclusion: Multifactorial LCA mother-clusters may predict children?s health outcomes and care, while adjusting for interrelationships.