摘要
Background and Purpose: Obesity and Diabetes Mellitus type two (DMII) have a known association. Yet, the socio-demographic predictors of obesity in special populations such as people who have DMII remain unclear. The purpose of this study was to determine the socio-demographic predictors of obesity among adults who have DMII. Materials and Methods: This was a descriptive cross-sectional study targeting 488 adult clients who had the diagnosis of DMII. The participants were asked to complete a survey covering demographic and clinical variables of age, gender, employment, income, education, weight, height, medical insurance, duration of diabetes and type of treatment taken to control diabetes. Besides, Body Mass Index (BMI), the dependent variable, was calculated. Descriptive statistics were used to present clients’ socio-demographic and clinical characteristics. Univariate Binary logistic regression was used to determine the socio-demographic predictors of obesity. Results: Results showed that age, household income and employment were independent predictors of BMI in adults who have DMII. Gender and level of education were not significant predictors of higher BMI. Conclusion: Those results suggest that understanding of the contributing variables of obesity in adults who have DMII can help identify the at-risk groups allowing for early diagnosis and establishment of effective prevention and management plans.
Background and Purpose: Obesity and Diabetes Mellitus type two (DMII) have a known association. Yet, the socio-demographic predictors of obesity in special populations such as people who have DMII remain unclear. The purpose of this study was to determine the socio-demographic predictors of obesity among adults who have DMII. Materials and Methods: This was a descriptive cross-sectional study targeting 488 adult clients who had the diagnosis of DMII. The participants were asked to complete a survey covering demographic and clinical variables of age, gender, employment, income, education, weight, height, medical insurance, duration of diabetes and type of treatment taken to control diabetes. Besides, Body Mass Index (BMI), the dependent variable, was calculated. Descriptive statistics were used to present clients’ socio-demographic and clinical characteristics. Univariate Binary logistic regression was used to determine the socio-demographic predictors of obesity. Results: Results showed that age, household income and employment were independent predictors of BMI in adults who have DMII. Gender and level of education were not significant predictors of higher BMI. Conclusion: Those results suggest that understanding of the contributing variables of obesity in adults who have DMII can help identify the at-risk groups allowing for early diagnosis and establishment of effective prevention and management plans.
