Bioelements and Clustering of Preschool Children Suffering From Recurrent Respiratory Infections

Abstract

Background. Bioelements are essential components for the effective functioning of cellular and humoral immune mechanisms in the human body. There is a direct relationship between the impaired status of many bioelements and increased susceptibility of children, in particular, to respiratory infections.
 Aim: to identify clusters of preschool children with different frequency of episodes of acute respiratory infections in combination with their bioelemental status.
 Materials and methods. A total of 41 children (22 boys and 19 girls) aged 1-6 years, undergoing inpatient treatment on acute respiratory infection, were involved in the clinical study. The integral indicator of acute respiratory infections recurrence, i.e. the infectious index, was taken into account for each patient. The hair of 30 children was tested for the content of 13 bioelements – Zn, Fe, Cu, Se, Mn, Cr, Co, Br Ni, Ca, K, S, and Cl. Besides, the serum concentration of Mg was examined in 40 children. The statistical processing of the obtained digital material was performed with IBM SPSS Statistics 28 licensed software. A combination of factor and cluster hierarchical analysis was used.
 Results. The particular micro- and macroelements demonstrate a statistically significant direct or inverse relationship. The most closely correlated are the following pair combinations: S*Co (ρ=0.645; p<0.001; 95% CI [0.362-0.820]); K*Mn/Cr (ρ=-0.547; p=0.002; 95% CI [-0.763–(-0.222)]) and Ca*Mn (ρ=0.500; p=0.005; 95% CI [0.160-0.734]). The conducted factor analysis shows the presence of 5 new combinations including all 14 studied bioelements. The most influential bioelements in these combinations are S, Cu, Zn, Mg, and Fe. The cluster distribution of the examined children according to their bioelemental status has no clear relationship with the infectious index values.
 Conclusion. The information on the interdependence between the studied bioelements can be used in planning of further scientific studies of immune mechanisms. The data obtained clarify the requirements for the most effective application of factor and cluster analysis in the study of risk predictors of recurrent respiratory infections in pediatric practice.