Rancangan Grafik Ukuran Antropometri, Ketebalan Lemak Dan Kecukupun Gizi Berdasarkan Metode Regresi Spline Sebagai Prediktor Kondisi Stunting Pada Balita

Abstract

In the period of 24-59 months of age, the sensory system of toddlers is ready to face various stimulations and growths, such as learning to speak more fluently and recognizing environmental conditions, physical and psychological growth. Not all toddlers can grow optimally. One form of growth failure during toddlerhood is stunting. Indonesia is the country with the fifth-highest stunting condition in the world in the last decade. Around 37% (nearly 9 million) of children under five in Indonesia are stunted. Stunting can of course be avoided by knowing the possible causes and signs such as 1) Under-standard anthropometric measures, 2) Low nutritional adequacy, 3) Body Mass Index for Parents, 4) Age at high risk during pregnancy, 5) Poor environmental sanitation. well preserved. Anthropometric measurement indicators such as height, weight, and head circumference are used as the main criteria for assessing the adequacy of nutritional intake and physical growth of infants and toddlers. In Indonesia, the growth curve for children under five that is commonly used is KartuMenujuSehat (KMS). The KMS curve is designed based on references from the World Health Organization (WHO) and the Nations International Children's Emergency Fund (NCHS). Based on this mismatch, this study aims to design a graph of physical growth standards for toddlers based on anthropometry (height, weight, head circumference, chest circumference, calf circumference), fat thickness, and nutritional adequacy of toddlers according to the average physical size of toddlers in Indonesia. Also, it assesses the adequacy of nutrition in areas that have inhibiting factors for nutrient intake. This growth standard graph is designed using the spline regression method. This study used a cross-sectional design where measurements were carried out once. The sample in this study were children under five who were in the study who met the inclusion criteria. Based on the results of data analysis and the design of the curve mode, the third-order cubic spline mode is obtained with a combination of two knots, namely 9 and 21 knots, and a minimum GCV value of 2.1267. The linear assumption value is fulfilled with a value of R2 = 82.54. i.e. linearity, normality, and a constant zero residue are met.