QUANTITATIVE AND QUALITATIVE EXAMINATION OF ANTHROPOMETRICAL PARAMETERS  IN PRESCHOOL CHILDREN WITH SELF-ORGANIZING MAPS

Biljana Trpkovska; Biljana Zafirova; Elizabeta Chadikovska; Biljana Bojadzieva Stojanoska

Biljana Trpkovska Institute of Anatomy, Faculty of Medicine, University of ’’St. Cyril and Methodius”, Skopje, R.of North Macedonia
Biljana Zafirova Institute of Anatomy, Faculty of Medicine, University of ’’St. Cyril and Methodius”, Skopje, R.of North Macedonia
Elizabeta Chadikovska Institute of Anatomy, Faculty of Medicine, University of ’’St. Cyril and Methodius”, Skopje, R.of North Macedonia
Biljana Bojadzieva Stojanoska Institute of Anatomy, Faculty of Medicine, University of ’’St. Cyril and Methodius”, Skopje, R.of North Macedonia

Abstract

Growth monitoring and promotion of optional growth are essential components of primary health care for children. Serial measurements of weight, height/length, for all children and measurements of circular and transversal parameters compared with growth of large sample population help to confirm a child's healthy growth and development. It also allows early identification of potential nutritional or health problems and enables prompt action before a child's health is seriously compromised. The aim of the study was to compare quantitative and qualitative examination of anthropometric parameters as indicator of growth and nutritional status in preschool children. Anthropometric parameters were measured on healthy children, defining longitudinal, circular and transversal dimensionality of the skeleton using standard technique and instruments. The qualitative examination was detected with self- organizing maps. The majority of anthropometrical parameters have shown significant age and sex specific differences in favour of female subjects. The height-for-age index values corresponding to the 50^th percentile showed slightly higher values in our female subjects 115.4 cm than in our male subjects 113.2 cm. The values of 50^th percentile of BMI in our male subjects were 15.94 kg/m^²,whereas in our females were 15.64 kg/m². These results show that obesity prevention is recommended, and detected values could be applied for evaluation of deviations in growth and nutritional status in preschool children.

Key words: anthropometry, growth, self-organizing maps,preschool children.

References

1.ML Hughes, Martorell R and Grummer-Strawn LM. Overweight and obesity in preschool children from
developing countries. International Journal of Obesity 2000; (24): 959-967.
2. Fomon SJ, Haschke F, Ziegler EE. Body composition of reference children from birth to age 10 years. Am J Clin
Nutr 1982; (35):1169-75.
3. Dimitrovska Z, Kendrovski V, Ristovska G at el. Nutritional Antropometry 2nd ed. Skopje: Republic Institute of
Health Protection; 2006.
4.Mercedes de Onis, Habicht JP. Anthropometric reference data for international use: recommendation from a
WHO Expert Committee. Am J Clin Nutr 1996; 64 (4): 650-8.
5. Zafirova B, Todorovska L. Anthropometric parameters of growth and nutritional status in children aged 6 to 7
years in R. Macedonia. Advances in Medical Science 2009; Vol.54 (2):289-295.
6. Peinado Doris Maritza, Bedrinana Jorge Isaac. Comparison of NCHS -1977, CDC-2000 and WHO-2006
Nutritional Classification in 32 to 60 month-old children in the central highlands of Peru (1992-2007). Universal
J of Public Health 2013; 3:143-149.
7. M Flegal Katherine, Carrol D Margaret, Ogden L Cynthia. Effects of trimming weight-for-height data on growth
chart percentiles. Am J Clin Nutr 2012; 96: 1051-5.
8. Rong Wei, Katherine Flegal and Cynthia Ogden. Weight-for-stature compared with body mass index-for-age
growth charts for the USA from CDC and prevention. Am J Clin Nutr 2002; 75:761-766.
9. Cole TJ, JV Freeman, Preece MA. Body mass index reference curves for the UK, 1990. Archives of Disease in
Childhood 1995; 73: 25-29.
10. De Onis M, Blossner M. Prevalence and overweight among preschool children in developing countries. Am J
Clin Nutr. 2000; 72 (4): 1032-9.
11. Marcelle M.M. Maia, Maria A Fausto, Erica L. M. Vieira at el. The prevalence of malnutrition and risk factors in
children attending outpatient clinics in the city of Manaus, Amazonas, Brazil. Archivos Latinoamericanos De
Nutricion 2008; (58): 1-8.
12. Child Growth Charts in the Northern Territory, Discussion Paper, Consideration of the 2006 WHO growth
standards. www.nt.gov.au/health.
13. Joel Conkle, Parminder S et all. Improving the qualitu of child anthropometry in the body imaging for
nutritional assesement study (BINA). PLOS One 2017; 12(12).
14. Grellety E, Golden MH. The Effect of Random Error on Diagnostic Accuracy Illustrated with the
Anthropometric Diagnosis of Malnutrition. PlOS One. 2016; 11(12).
15. US CDC International Micronutrient Malnutrition Prevention and Control Program. Micronutrient Survey
Toolkit Toronto: Micronutrient Initiative; 2016 Available from: http://surveytoolkit.micronutrient.org/.
16. SMART. ENA Software for SMART: ACF; 2015 Available from: http://smartmethodology.org/survey-planning-
tools/smart-emergency-nutrition-assessment/.
17. Assaf S, Kothari M., Pullum T. An Assessment of the Quality of DHS Anthropometric Data, 2005–2014. DHS
Methodological Reports No 16. Rockville, MD, USA: ICF International; 2015.