Determination of the obesity prevalence and its associated factors among community in Selangor, Malaysia: an ordinal logistic regression approach - Noraznie Nordin; Zalina Zahid; Zaliha Ismail; Siti Munira Yassin; Hapizah Mohd Nawawi; Siti Aida Sheikh Hussin (Indonesian Journal of Electrical Engineering and Computer Science, 2020)
Obesity is becoming an epidemic globally as it has been closely linked with a wide variety of chronic diseases. The identification of associated factors for obesity occurrences is still the main interest of many researchers. However, there has been extensive disagreement among researchers over possible factors associated with obesity which commonly involve the demographic factors, socioeconomic status (SES) and environmental factors. Biomarkers are also considered as important possible factors linked with the prevalence of obesity but investigations looking into their associations are still lacking. Therefore, it is important to examine factors that are associated with obesity using biomarkers and common factors to get detailed perspectives on obesity prevalence. The objectives of this study are to determine the prevalence of obesity and to examine the association between the common factors and biomarkers with obesity among community in Selangor, Malaysia. The results showed that the prevalence of obesity among participants was 49% (N=498) and Ordinal regression model with Cauchit built-in link function was the best fitted model to predict obesity. Meanwhile, three types of common factors (i.e. older age, being female and Malay ethnic) and one type of biomarker (i.e. high glucose level) were found to be significantly associated with obesity.