CHILDHOOD OBESITY IN MACEDONIAN PRESCHOOL CHILDREN, PREVALENCE AND PREVENTION
Assessment of sex-specific differences of anthropometric parameters as indicator of growth and nutritional status in preschool children from Macedonia.The study included a total of 200 healthy preschool children from Macedonian nationality. Thirthteen anthropometric parameters were measured, defining longitudinal, circular and transversal dimensionality of the skeleton using standard technique and instruments for measurement. The following indices were selected and calculated: weight-for –age; height-for-age and BMI. Skin –folds (triceps, scapula, thigh) were also measured. Qualitative examinations were with self-organizing maps. Sex-specific differences for almost all anthropometric parameters were detected, but they were not significant. Girls showed higher values than boys regarding height and weight, but there were no significant differences concerning BMI. Values at the 50th percentile in girls were 20 kg for BW, 108.1 cm for BH and 16.82 kg/m² for BMI. The values of these parameters in boys were 19.75 kg for BW, 108.25 cm for BH and 16.24 for kg/m² for BMI. The values for triceps skin-fold were higher in boys than (13.0 ±3.0) than in girls (12.5 ±3.6).The results obtained can be used as criteria for assessment and detecting deviations in growth and nutritional status in preschool children.
Keywords: anthropometry, growth, nutritional status, preschool children, self organizing maps.
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. Trpkovska et all. Quantitative and qualitative examination of anthropometrical parameters in preschool children with self organizing maps. JMS 2020, 3(1);46-54.
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. Child Growth Charts in the Northern Territory, Discussion Paper, Consideration of the 2006 WHO growth standards. www.nt.gov.au/health.
12. 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.
13. Child Growth Charts in the Northern Territory, Discussion Paper, Consideration of the 2006 WHO growth standards. www.nt.gov.au/health.
14. 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).
15. Grellety E, Golden MH. The Effect of Random Error on Diagnostic Accuracy Illustrated with the Anthropometric Diagnosis of Malnutrition. PlOS One. 2016; 11(12).
16. US CDC International Micronutrient Malnutrition Prevention and Control Program. Micronutrient Survey Toolkit Toronto: Micronutrient Initiative; 2016 Available from: http://surveytoolkit.micronutrient.org/.
17. SMART. ENA Software for SMART: ACF; 2015 Available from: http://smartmethodology.org/survey-planning-tools/smart-emergency-nutrition-assessment/.
18. 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.
19. M.G. Sathias et al. Nutritional status of school children living in Northern part of Sri Lanka. BMC Pediatrics 2021; 21:43
20. Onur Cirak, Haci Omer Yilmaz et al. Nutritional factors in etiology of childhood obesity. Gen. Med. Open 2018, vol 2 (4);1-5.
21. Qazi Iqbal Ahmad et al. Childhood obesity. IJEM 2010;14(1);19:25.
22. Bussiek PV, De Poli C et al. A scoping review protocol to map the evidence on interventions to prevent overweight and obesity in children. BMJ Open 2018, 293:311.