OBJECTIVE:
To estimate the prevalence of malnutrition in children for all Brazilian municipalities.
METHODS:
A multilevel logistic regression model was used to estimate the individual probability of malnutrition in 5,507 Brazilian municipalities in 2006, in terms of predictive factors grouped according to hierarchical levels. The response variable was child malnutrition (children aged from six to 59 months with height for age and sex below -2 z-scores, according to the World Health Organization standard). The predictive variables were determinants of malnutrition measured similarly by the National Demographics and Health Survey-2006 and the Sample from the 2000 Demographic Census. At level 1 (individual): sex and age, level 2 (household): socioeconomic variables, water and indoor plumbing, urban or rural area and level 3 (municipal): location of the municipality and coverage of the Family Health Strategy (FHS) in 2006.
RESULTS:
The study detected a statistically significant chance of malnutrition in male children, those living in households with two or more individuals per room, those belonging to the lowest quintiles of the socioeconomic score, those with three or more children under five in the household, those with no access to running water or located in the North. There was a negative dose-response association between FHS coverage and the chance of malnutrition (p = 0.007). FHS coverage in the municipality equal to or greater than 70% showed a 45% reduction in the chance of infant malnutrition. Estimates of the prevalence of child malnutrition show that most of the cities have the risk of malnutrition under control, very low or low. Risks of greater magnitude exist only in 158 municipalities in the North Region.
CONCLUSIONS:
Childhood malnutrition as a public health problem is concentrated in the cities of the North region, where FHS coverage is lower. A protective effect of FHS in relation to child malnutrition was found in the country as a whole, irrespective of other determinants of the problem.
Child Nutrition Disorders, epidemiology; Socioeconomic Factors; Health Inequalities; Multilevel Analysis; Family Health Program
