Dyslipidaemia and undernutrition in children from impoverished areas of Maceió, state of Alagoas, Brazil

Abstract

Chronic undernutrition causes reduced growth and endocrine adaptations in order to maintain basic life processes. In the present study, the biochemical profiles of chronically undernourished children were determined in order to test the hypothesis that chronic undernutrition also causes changes in lipid profile in pre-school children. The study population comprised 80 children aged between 12 and 71 months, including 60 with moderate undernutrition [height-for-age Z (HAZ) scores ≤ -2 and > -3] and 20 with severe undernutrition (HAZ scores ≤ -3). Socioeconomic, demographic and environmental data were obtained by application of a questionnaire, and anthropometric measurements and information relating to sex, age and feeding habits were collected by a trained nutritionist. Blood samples were analysed for haemoglobin, vitamin A, insulin-like growth factor 1 (IGF-1) and serum lipids, while cortisol was assayed in the saliva. Faecal samples were submitted to parasitological investigation. Analysis of variance and χ² methods were employed in order to select the variables that participated in the multivariate logistic regression analysis. The study population was socioeconomically homogeneous, while the lack of a treated water supply was clearly associated with the degree of malnutrition. Most children were parasitised and anaemia was significantly more prevalent among the severely undernourished. Levels of IGF-1 decreased significantly with increasing severity of undernutrition. Lipid analysis revealed that almost all of the children had dyslipidemia, while low levels of high-density lipoprotein were associated with the degree of undernutrition. It is concluded that chronic malnutrition causes endocrine changes that give rise to alterations in the metabolic profile of pre-school children.

Keywords: anaemia; childhood undernutrition; cortisol; dyslipidemia; insulin-like growth factor 1; metabolic disorders; multivariate logistic regression analysis; parasitosis.