[Poverty profile regarding households participating in a food assistance program]

This study was aimed at establishing subgroups having specific socioeconomic characteristics by using latent class analysis as a method for segmenting target population members of the MANA-ICBF supplementary food program in the Antioquia department of Colombia and determine their differences regarding poverty and health conditions in efficiently addressing pertinent resources, programs and policies.

The target population consisted of 200,000 children and their households involved in the MANA food assistance program; a representative sample by region was used. Latent class analysis was used, as were the expectation-maximization and Newton Raphson algorithms for identifying the appropriate number of classes.

The final model classified the households into four clusters or classes, differing according to well-defined socio-demographic conditions affecting children's health.

Some homes had a greater depth of poverty, therefore lowering the families' quality of life and affecting the health of the children in this age group.