The use of ulnar length as an alternative method for growth assessment of girls from 3 to 6 years of age

• Grant number: 18/15788-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2019
• End date: May 31, 2020
• Field of knowledge: Health Sciences - Medicine - Maternal and Child Health
• Principal Investigator: Carla Maria Ramos Germano
• Grantee: Érica Letícia Angelo Liberato
• Host Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Growth is a dynamic and continuous biological process, and the monitoring of child growth, particularly the assessment of height, is an important component of nutritional adequacy and general health. Thus, several studies indicate the need for alternative methods for its assessment in patients whose physical limitations preclude traditional gauging. Therefore, the present study aims to evaluate if it is possible to use ulna growth as an alternative method to monitor the growth of pre-school girls. This is a descriptive and longitudinal study that will be developed in public pre-schools of São Carlos city, on a convenience sample. 150 pre-school girls (with ages between 3 and 6 years old) will be selected from São Carlos' municipal pre-schools. They will have their weight, height, arm span, upper and lower segments and ulnar length measured on the following months: 0, 3 and 6, with the help of standard measurement tools. The measurement of ulna length will be performed with the children sitting, with the left forearm in full pronation and with the elbow flexed at an angle that can vary from 90 to 100 degrees to be measured with standard goniometer. Ulna measurement will be determined in two ways: 1) Using a certified caliper (Techno-tools®) and 2) A3 millimeter paper. The data will be presented as mean ± standard deviation with significance level set at 5%. The statistical significance of the differences between the variables will be determined by the nonparametric T test. The chi-square test will be used to compare categorical variables and the Spearman test will be used to evaluate the correlation level between the variables, to be performed with the help of GraphPad Prism® program. The data analysis for height prediction will be used considering multiple linear regression methods, but machine learning technique will also be used to create a prediction model.