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Diarrhoea is an important health issue in low-and middle-income countries, including Indonesia. We applied a multilevel regression analysis on the Indonesian Demographic and Health Survey to examine the effects of drinking water and sanitation facilities at the household and community level on diarrhoea prevalence among children under five (n = 33,339). The role of the circumstances was explored by studying interactions between the water and sanitation variables and other risk factors. Diarrhoea prevalence was reported by 4820 (14.4%) children, who on average were younger, poorer and were living in a poorer environment. At the household level, piped water was significantly associated with diarrhoea prevalence (OR = 0.797, 95% CI: 0.692-0.918), improved sanitation had no direct effect (OR = 0.992, 95% CI: 0.899-1.096) and water treatment was not related to diarrhoea incidence (OR = 1.106, 95% CI: 0.994-1.232). At the community level, improved water coverage had no direct effect (OR = 1.002, 95% CI: 0.950-1.057) but improved sanitation coverage was associated with lower diarrhoea prevalence (OR = 0.917, 95% CI: 0.843-0.998). Our interaction analysis showed that the protective effects of better sanitation at the community level were increased by better drinking water at the community level. This illustrates the importance of improving both drinking water and sanitation simultaneously. ARTICLE HISTORY

We develop a new theoretical framework that explains the engagement in child labor of children in developing countries. This framework distinguishes three levels (household, district and nation) and three groups of explanatory variables: Resources, Structure and Culture. Each of the three groups refers to another strand of the literature; economics, sociology and anthropology. The framework is tested by applying multilevel analysis on data for 239,120 children living in 221 districts of 18 developing countries. This approach allows us to simultaneously investigate effects of household and context factors. At the household level, we find that resources and structural characteristics influence child labor, whereas cultural characteristics have no effect. With regard to context factors, we find that children work more in rural areas, especially if there are more unskilled manual jobs, and in more traditional urban areas. In more developed regions, girls tend to work significantly less.