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High Prevalence of Prediabetes and Associated Risk Factors in Urban Areas of Pontianak, Indonesia: A Cross-Sectional
Indah Budiastutik1, Martha I Kartasurya2, Hertanto W Subagio3
1Doctoral Program, Faculty of Public Health, Diponegoro University, Semarang 50275, Indonesia.
Abstract:
Uncontrolled prediabetes can develop into Type 2 Diabetes mellitus (T2DM). The incidence of T2DM among adults in Pontianak, Indonesia was reported remarkably high. Therefore, this study aimed to investigate the risk factors for prediabetes in adults living in urban areas of Pontianak, Indonesia. A cross-sectional study was conducted in 5 subdistricts of Pontianak. A total of 506 adults underwent screening to obtain subjects with fasting blood glucose (FBS) of ≤124 mg/dL and aged >30 years. Blood pressure and body mass index (BMI) were measured. Interview using a structured questionnaire were performed to obtain data on predictor variables (age, sex, education, income, health insurance, tobacco use, history of hypertension, gout, high cholesterol level, frequency of exercise per week, and diabetic education). The prevalence of prediabetes among subjects was significantly high (76.4%). Subjects were predominantly above 40 years, female, had low income, low education level, and had health insurance. About a third of the subjects had a history of hypertension, gout, and high cholesterol level, respectively. The exercise frequency was mostly less than 3 times/week, and the BMI was mainly classified as overweight and obese. The result of spearman's rho correlation showed that age (r = 0.146; p=0.022) and BMI (r = 0.130; p=0.041) significantly correlated with prediabetes incidence. Moreover, the chi-square analysis demonstrated that health insurance ownership (OR = 4.473; 95% CI 1.824-10.972; p ≤ 0.001), history of hypertension (OR = 3.096; 95% CI 1.542-6.218; p=0.001), and history of gout (OR = 2.419; 95% CI 1.148-5.099; p=0.018), were associated with prediabetes incidence. For all these significant risk predictors except BMI, the significant associations were found only among female subjects after specific sex analysis. Moreover, multivariate logistic regression showed that health insurance ownerships (OR = 5.956; 95% CI 2.256-15.661; p ≤ 0.001) and history of hypertension (OR = 3.257; 95% CI 1.451-7.311; p=0.004), and systolic blood pressure (OR = 2.141; 95% CI 1.092-4.196; p=0.027) were the risk factors for prediabetes. It is concluded that the prevalence of prediabetes is probably high especially among urban people in Pontianak, Indonesia. Health insurance ownership and hypertension may have an important role in prediabetes management. The risk factors might be different between male and female.
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