Rosdiana Mus
* Corresponding Author Technology of Medical Laboratory, Faculty of Pharmacy, Hospital Technology and Informatics, Universitas Mega Rezky, Makassar
Ahmad Hamim Sadewa Department of Biochemistry, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta
Pramudji Hastuti Department of Biochemistry, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta
Anggelia Puspasari Department of Biochemistry, Faculty of Medicine and Health Science, Universitas Jambi, Jambi
Citra Maharani Department of Biochemistry, Faculty of Medicine and Health Science, Universitas Jambi, Jambi
Ika Setyawati Department of Biochemistry, Faculty of Medicine and Health Science, Universitas Muhammadiyah Yogyakarta, Yogyakarta, Indonesia
(1) Technology of Medical Laboratory, Faculty of Pharmacy, Hospital Technology and Informatics, Universitas Mega Rezky, Makassar (2) Department of Biochemistry, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta (3) Department of Biochemistry, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta (4) Department of Biochemistry, Faculty of Medicine and Health Science, Universitas Jambi, Jambi (5) Department of Biochemistry, Faculty of Medicine and Health Science, Universitas Jambi, Jambi (6) Department of Biochemistry, Faculty of Medicine and Health Science, Universitas Muhammadiyah Yogyakarta, Yogyakarta, Indonesia (*) Corresponding Author
Abstract
The prevalence of metabolic syndrome (MetS) is high worldwide which it can increase the risk of some diseases such as cardiovascular disease, type 2 diabetes mellitus even mortality. The prevalence pattern and determinants of MetS risk factors might differ among ethnics in Indonesia. This study aimed to determine the anthropometry and metabolic measurements determinants to predict the MetS prevalence of the Javanese population in Yogyakarta. It was a case control study conducted from December 2018 to March 2019 involving 214 Javanese subjects aged 20-74 years resided in Yogyakarta Special Region, Indonesia. NCEP ATP III criteria were used to identify MetS as case and not diagnosed with MetS as control. The results showed that BMI, WC, BP, total cholesterol and HDL-C were significantly different between MetS and non MetS patients (p<0.005). In MetS subjects, prevalence of obesity was 75.3%, visceral fat was 75.3%, WC 92.95%, WHtR 97.64% and total cholesterol/HDL-C ratio 553%, which independently increased the risk of MetS 7.30, 5.32, 13.37, 20.75, and 7.16 times, respectively. Result of logistic regression analysis showed central obesity based on WC increased the risk of Met-S by 17.62 time and the ratio of total cholesterol/HDL-C>5 by 9.54 time. In conclusion, WHtR is a better marker for MetS prediction independently. However, the WHtR in combination with WC and total cholesterol/HDL-C ratio are better for MetS prediction in the Javanese population.
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