Investigating the impact of important risk factors and geographical location on child morbidity and malnutrition is of high relevance for developing countries. Previous research has usually carried out separate regression analyses for certain diseases or types of malnutrition, neglecting possible association between them. Based on data from the Nigeria Demographic and Health Survey of 2003, we apply recently developed geoadditive latent variable models, taking cough, fever and diarrhea as well as stunting and underweight as observable indicators for the latent variables morbidity and mortality. This allows to study the common impact of risk factors and geographical location on these latent variables, thereby taking account of association within a joint model. Our analysis identi?es socio-economic and public health factors, nonlinear e?ects of age and other continuous covariates as well as spatial e?ects jointly in?uencing morbidity and malnutrition.