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Determining the Prevalence of Childhood Hypertension and Its Concomitant Metabolic Abnormalities Using Data Mining Methods in the Northeastern Region of Hungary

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Abstract

Objective: Identifying hypertension in children and providing treatment for it have a marked impact on the patients' long-term cardiovascular outcomes. The global prevalence of childhood hypertension is increasing, yet its investigation has been rather sporadic in Eastern Europe. Therefore, our goal was to determine the prevalence of childhood hypertension and its concomitant metabolic abnormalities using data mining methods.

Methods: We evaluated data from 3 to 18-year-old children who visited the University of Debrecen Clinical Center's hospital throughout a 15-year study period ( = 92,198; boys/girls: 48/52%).

Results: We identified a total of 3,687 children with hypertension (2,107 boys and 1,580 girls), with a 4% calculated prevalence of hypertension in the whole study population and a higher prevalence in boys (4.7%) as compared to girls (3.2%). Among boys we found an increasing prevalence in consecutive age groups in the study population, but among girls the highest prevalences are identified in the 12-15-year age group. Markedly higher BMI values were found in hypertensive children as compared to non-hypertensives in all age groups. Moreover, significantly higher total cholesterol (4.27 ± 0.95 vs. 4.17 ± 0.88 mmol/L), LDL-C (2.62 ± 0.79 vs. 2.44 ± 0.74 mmol/L) and triglyceride (1.2 (0.85-1.69) vs. 0.94 (0.7-1.33) mmol/L), and lower HDL-C (1.2 ± 0.3 vs. 1.42 ± 0.39 mmol/L) levels were found in hypertensive children. Furthermore, significantly higher serum uric acid levels were found in children with hypertension (299.2 ± 86.1 vs. 259.9 ± 73.3 μmol/L), while glucose levels did not differ significantly.

Conclusion: Our data suggest that the calculated prevalence of childhood hypertension in our region is comparable to data from other European countries and is associated with early metabolic disturbances. Data mining is an effective method for identifying childhood hypertension and its metabolic consequences.

Citing Articles

Assessment of Hypertensive Patients' Complex Metabolic Status Using Data Mining Methods.

Kovacs B, Nemeth A, Daroczy B, Karanyi Z, Maroda L, Dioszegi A J Cardiovasc Dev Dis. 2023; 10(8).

PMID: 37623358 PMC: 10455679. DOI: 10.3390/jcdd10080345.

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