Reducing child malnutrition is a key goal of most developing countries. To combat child malnutrition with the right set of interventions, policymakers need to have a better understanding of its economic, social and policy determinants. While there is a large literature that investigates the determinants of child malnutrition, it focuses almost exclusively on mean effects of these determinants. However, socioeconomic background variables and policy interventions may affect child nutrition differently at different points of the conditional nutritional distribution. Using quantile regressions, this paper explores the effects of variables such as a child?s age, sex and birth order; household expenditure per capita; parental schooling; and infrastructure on child weight and height at different points of the conditional distributions of weight and height using data from Sri Lanka?s Demographic and Health Survey. Results indicate that OLS estimates can be misleading in predicting the effects of determinants at the lower end of the distributions of weight and height. For example, even though on average Sri Lankan girls are not nutritionally-disadvantaged relative to boys, among children at the highest risk of malnutrition girls are disadvantaged relative to boys. Likewise, although expenditure per capita is associated with strong nutritional improvement on average, it is not a significant determinant of child height or weight at the lower end of the distribution. Similarly, parental education, electricity access, and the availability of piped water have larger effects on child weight and height at the upper quantiles than at the lower quantiles. The policy implication is that general interventions?parental schooling, infrastructure and income growth?are not as effective for children in the lower tail of the conditional weight and height distributions. These children, who are at the highest risk of malnutrition, are likely to need specialized nutritional interventions.. child health, child nutrition, malnutrition, child weight, child height, quantile regression, Sri Lanka