Model Prediksi Persen Lemak Tubuh Remaja Putri: Studi Cross Sectional
DOI:
https://doi.org/10.21580/ns.2020.4.1.4367Keywords:
Adolescent girls, body fat percentage, nutritional status, prediction model, model prediksi, persen lemak tubuh, remaja putri, status giziAbstract
The purpose of this study was to get the prediction model which had optimum validity for estimating body fat percentage of adolescent girls. The design of this study was a Cross Sectional. The sampels were 110 school girls which taken by Stratified Proportional technique. Anthropometric measurements consisted of measurements of age, weight, and height (to obtain the BMI (kg/ m2) and BMI (WHO Z Score)), waist circumference, and skinfold thickness. Body fat percentage was measured using various predictive models. Bivariate analysis used was the correlation test. Multivariate analysis used was multiple linear regression test. The ROC test was used for the validation test to determine the Area Under Curve (AUC) value, sensitivity, specificity, Positive Predictive Value (PVP), Negative Predictive Value (PVN), Likelihood Ratio + or (LR +), and LR-. The result of the study showed that the average of body fat percentage of samples was 26,51% ± 5,48%. The prediction model which obtained from multivariate analysis was BFP= 0,991 BMI +0,069 ST+0,249 A -1,703. Based on the validation test, the prediction model of this study had optimum validity in compared with other prediction models.
Tujuan dari penelitian ini adalah untuk mendapatkan model prediksi yang memiliki validitas optimal untuk memperkirakan persen lemak tubuhremaja putri. Desain penelitian adalah Cross Sectional. Sampel yang diambil sebanyak 110 siswi dengan menggunakan teknik Stratifikasi Proporsi. Pengukuran antropometri terdiri dari pengukuran usia, berat badan dan tinggi badan (untuk mendapatkan nilai IMT (kg/m2) dan IMT WHO Z Score), lingkar pinggang, dan skinfold thickness. Persen lemak tubuh diukur dengan menggunakan berbagai model prediksi. Analisis bivariat menggunakan uji korelasi. Analisis multivariat menggunakan uji regresi linier ganda. Uji ROC digunakan untuk uji validasi untuk mengetahui nilai Area Under Curve (AUC), sensitivitas, spesifisitas, Predictive Value Positif (PVP), Predictive Value Negative (PVN), Likelihood Ratio + atau (LR+), dan LR-. Hasil penelitian menunjukkan bahwa rerata persen lemak tubuh responden adalah 26,51 % ± 5,48 %. Model prediksi yang didapatkan dari hasil multivariat adalah PLT= 0,991 IMT + 0,069 ST + 0,249 U -1,703. Berdasarkan hasil uji validasi, model prediksi tersebut memiliki validitas optimal jika dibandingkan dengan model prediksi lainnya.
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