Background: People in the developing countries are increasingly vulnerable to the worldwide epidemic of obesity. It is a common modifiable risk factor for all the cardiometabolic diseases including type 2 diabetes (T2DM). Population-based data on the prevalence of obesity in rural Bangladeshi adults based on newly proposed cut off points for Asian population have scarce until recently. Objective: To assess the prevalence of general and central obesity in a rural Bangladeshi population and their association with T2DM. Methods: This study data have retrieved from Chandra Rural Diabetes Study, a population-based cross-sectional study which was conducted in a rural community called Chandra, 40 km. north of Bangladesh s capital, Dhaka in 2009. The survey was carried out in two phases. The first phase consisted of household census of the total population residing in the study locations. Based on the census results, a list of all men and women aged 20 years and above was selected in the second phase. Required numbers of individuals were selected following a random procedure. Ten villages were randomly selected from five areas. The total population of these villages was approximately 20,000 aged ≥20 years. For this study, 3000 individuals were randomly selected and among them 2376 (79.2%) participated. Structured questionnaires including socio-demographic parameters, anthropometric measurements, blood pressure (BP), and blood glucose values were recorded. Age adjusted data for anthropometric indices and diabetes risks were assessed and their relationships were examined. Newly proposed cut off points for Asian population had been used to define general obesity defined by body mass index (BMI) and central obesity defined by both waist circumference (WC) and waist hip ratio (WHR). Results: The age standardized prevalence of overweight (BMI 23-<25 kg/m2) and obesity (BMI ≥25 kg/m2) were 17.7 (95% confidence interval (CI): 16.1, 19.2%) and 26.2% (95% CI: 24.4, 27.9%), respectively. The age standardized prevalence of central obesity based on WC (M ≥90 & F ≥80 cm) and WHR (M ≥0.90 & F ≥0.80) were 39.8% (95% CI: 37.9, 41.7%) and 71.6% (95% CI: 69.8, 73.4%) respectively. Among the study population 88% had both high BMI (≥25 Kg/m2) and high WC (M ≥90 & F ≥80 cm) and on the other hand, 92.7% had both high BMI (≥25 Kg/m2) and high WHR (M ≥0.90 & F ≥0.80). The result shows that prevalence of central obesity was more in female than male. Study shows middle age, medium and high socioeconomic status (SES), illiterate, primary and secondary education levels, physical inactivity, high consumption of carbohydrate, protein and fat, were some significant risk indicators for general and central obesity. The adjusted odd ratio (OR) was highest for BMI ≥25 (OR: 2.12, P<0.001) for predicting T2DM compared to BMI ≥23 (OR: 1.26, P = 0.228), BMI ≥27.5 (OR: 1.93, P = 0.0.002) and BMI ≥30 (OR: 1.78, P = 0.098). Study also indicates that WHR predicted better T2DM risk than WC and BMI for both men and women. ROC analysis showed the optimal cut-off points for T2DM detection were at a BMI of 21.2 kg/m2 in men and 21.8 kg/m2 in women, WC 82 cm in men and women and WHR 0.93 and 0.87, respectively. Conclusions: It is apparent that obesity is increasing even in poor rural population. In rural Bangladeshi population, the prevalence of both general and central obesity was high among both sexes with the use of newly proposed cut off points for Asian population. Women presented with more central obesity than men. Gender, diet, physical activity, education level, socioeconomic condition, and smoking were associated with the prevalence of obesity. Compared with BMI, measures of central obesity, WHR and WC showed a better association with the risk of T2DM for both gender. Longitudinal follow-up studies are needed to confirm the risk indicators for obesity found in this study.