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THE FACTORS THAT CONTRIBUTE TO DIABETES MELLITUS IN MALAYSIA: ALTERNATIVE LINEAR REGRESSION MODEL APPROACH IN THE HEALTH FIELD INVOLVING DIABETES MELLITUS DATA.

Background: Diabetes mellitus (or diabetes) is a common disease that can cause of morbidity and mortality. Besides that, it is a serious deadly disease that making someone very weak and infirm. In Malaysia, the World Health Organization (WHO) has estimated the number of 0.94 millions of diabetics in...

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Publicado en:International Journal of Public Health & Clinical Sciences (IJPHCS) Vol. 5; no. 1; pp. 146 - 154
Autores principales: M. A., Awang Nawi, Ahmad W. M. A. W., Mamat M.
Formato: algorithm equations & formulas research tables/charts Journal Article
Publicado: Community Health Society Malaysia Jan/Feb2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan/Feb2018
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      pub: Community Health Society Malaysia
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        atl: THE FACTORS THAT CONTRIBUTE TO DIABETES MELLITUS IN MALAYSIA: ALTERNATIVE LINEAR REGRESSION MODEL APPROACH IN THE HEALTH FIELD INVOLVING DIABETES MELLITUS DATA.
      aug:
        au:
          M. A., Awang Nawi
          Ahmad W. M. A. W.
          Mamat M.
        affil: Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin (UniSZA)
      sug:
        subj:
          Diabetes Mellitus Risk Factors
          Diabetic Patients Malaysia
          Models, Statistical Malaysia
          Risk Assessment Malaysia
          Human
          Malaysia
          Multiple Linear Regression
          Linear Regression Methods
          Independent Variable
          Programming Languages
          Data Analysis Software
          Body Mass Index Evaluation
          Cholesterol Analysis
          Body Height Evaluation
          Systolic Pressure Evaluation
          Body Weight Evaluation
      ab: Background: Diabetes mellitus (or diabetes) is a common disease that can cause of morbidity and mortality. Besides that, it is a serious deadly disease that making someone very weak and infirm. In Malaysia, the World Health Organization (WHO) has estimated the number of 0.94 millions of diabetics in 2000 will increase by 164% in the next 30 years which means the total number of diabetics is 2.48 millions in 2030. This study aimed to obtain significant factors associated with diabetes mellitus among patients in Malaysia. Materials and Methods: The study also focused on efficiency model between multiple linear regression and alternative linear regression based on R-Square, adj R-Square, significant risk factors (p-value) and average width of the interval coefficients for each independent variable. Multiple linear regression and alternative linear regression analysis were used to identify risk factors contribute to diabetes mellitus among patients in Malaysia. The accepted level of significance was set below 0.05 (p<0.05) and all these methods are improved the programming language by using SAS 9.3 software. Result: From the linear regression model, there is only one variable that contributes to diabetes mellitus among patients that is high factor (β = 12.82526, p < 0.0351). Whereas, by using alternative linear regression analysis, all independent variables such as mass index (β = -4.44754, p < 0.0001), total cholesterol (β = 0.06689, p < 0.0001), height (β = -1.98315, p < 0.0001), systolic blood pressure (β = 0.06941, p < 0.0001) and the weight (lbs) (β = 0.79864, p < 0.0001) are significant to diabetes mellitus. Average width of former multiple regression was found to be 61188.298 while using alternative linear regression model, the average width are 118.019. Discussion and Conclusion: From this analysis, the most efficient method of obtained relationship between response and explanatory variable is alternative linear regression method compared to linear regression method.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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