Metabolic syndrome and life style factors among diabetes patients attending in a teaching hospital, Chitwan

Abstract

Background Metabolic syndrome (MetS) is associated with an increased incidence of chronic complications and mortality of diabetes patients. Prevention and treatment of MetS is important means of lowering the risk of cardiovascular diseases and mortality. Objective This study aimed to find out metabolic syndrome and life style factors among diabetes patients. Methods A cross-sectional survey was carried out among 296 patients with type 2 diabetes mellitus attending Chitwan Medical College Teaching Hospital. Consecutive sampling technique was used to select sample. Data were collected from 15th December 2021 to 15th March, 2022 using Interview Schedule, bio-physiological measurement and record review. Obtained data were analysed in SPSS version 20 for window using descriptive and inferential statistics. Chi-square test was applied to measure the association between the variables. Logistic regression analysis was performed to identify the factors associated with metabolic syndrome. Result Findings revealed that the prevalence of MetS was 66.2% and 58.4% in patients according to International Diabetes Federation (IDF) and National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria respectively. The most common MetS parameters were raised fasting plasma glucose (94.6%) and abnormal waist circumference (78.4% in IDF criteria) while the least prevalent parameter was reduced HDL level (43.2%). Majorities of the patients were non-vegetarian (85.5%), had poor dietary compliance (poor-46.3%, very poor-32.1%), overweight/obese (65.5%), and suffered from moderate stress (90.1%). Bivariate analysis showed that MetS as per NCEP ATP criteria was significantly associated with gender (p = 0.006), occupation (p = 0.007), presence of other co-morbid condition (<0.001) and sleep problem (p = <0.001). However, MetS as per IDF criteria was significantly associated with age (p = <0.028), duration of diabetes (p = <0.001), follow-up visit (p = <0.030), blood sugar monitoring (p = <0.009) and physical activity of diabetes patients (p = <0.001). Further logistic regression analysis revealed that sleep problem (AOR = 21.812;95%CI = 8.512,55.894) and presence of other comorbidities (AOR = 4.024;95%CI = 2.220,7.295) were the significant factors of metabolic syndrome. Conclusion and recommendation Metabolic syndrome is high in patients with type 2 diabetes mellitus. Therefore, treating physicians and other health workers need to monitor MetS parameters regularly to reduce the risk of cardiovascular diseases, stroke and premature death.