Obesity among adolescence: a case study at SMK King George V / Nur Amanina Azmi … [et al.]

Obesity is different from o,erneight. O,erneight is ,,hen a person·s \\eight is more than the nonnal Body Mass Index (BMI) for their respective height, age and sex. Meanwhile, obesity refers to a condition for whom that may score more than 30 kilograms for their BMI and accumulate excessive fat in t...

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Bibliographic Details
Main Authors: Azmi, Nur Amanina, Zakaria, Norulsyuhada, Azlan, Ainatul Mardhiah, Mohd Yazid, Nurul Fatin Haziqah
Format: Student Project
Language:English
Published: 2019
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/50257/1/50257.pdf
https://ir.uitm.edu.my/id/eprint/50257/
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Summary:Obesity is different from o,erneight. O,erneight is ,,hen a person·s \\eight is more than the nonnal Body Mass Index (BMI) for their respective height, age and sex. Meanwhile, obesity refers to a condition for whom that may score more than 30 kilograms for their BMI and accumulate excessive fat in the body. Therefore, this study to identify the profile of obesity among adolescent and to develop logistic model in predicting the obesity among adolescent. A cross-sectional study was conducted on a sample of student in SMK King George V. The total number of student from Form I to forn1 6 was a population and 282 was the sample that involve in our study. This study used self-administered questionnaire as data collection method. There are 274 of students are not obese and only 11 students are obese. Sedentary lifestyle contributes more to obesity among students which is 72.5% change in odds. However, the less contribution are eating pattern, fast food and parental concern which are 7.2%, 8.1% and 9.3% respectively while the pocket money does not contribute to on obesity among students. The logistic model had 96.1% accuracy in predicting the non-obesity of the adolescent. Therefore, the model good enough to be purposed for the use of adolescent in predicting the non-obesity and help them control their life within the knowledge of contributed factor given within the model.