Article

Type 2 diabetes in Asians: prevalence, risk factors, and effectiveness of behavioral intervention at individual and population levels.

Nutrition and Health Sciences Department, Division of Biological and Biomedical Sciences, Emory University, Atlanta, Georgia 30322, USA.
Annual Review of Nutrition (Impact Factor: 10.46). 04/2012; 32:417-39. DOI: 10.1146/annurev-nutr-071811-150630
Source: PubMed

ABSTRACT This review summarizes the current data on diabetes risk factors, prevalence, and prevention efforts in Asia and Asian migrant populations. Studies indicate that type 2 diabetes mellitus is a large and growing threat to public health in Asian populations. Furthermore, Asian subgroups (e.g., South Asians/Asian Indians, Chinese) have unique risk factor profiles for developing diabetes, which differ from other populations and between Asian ethnic groups. Lifestyle intervention programs are effective in preventing diabetes in Asians, as with other ethnicities. The strength of these findings is lessened by the lack of systematically collected data using objective measurements. Large epidemiologic studies of diabetes prevalence and risk factor profiles and translational trials identifying sustainable and culturally acceptable lifestyle programs for Asian subgroups are needed.

0 Bookmarks
 · 
125 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: The aims of this study were to determine recruitment and retention feasibility, changes in self-efficacy for diet and exercise, and weight and fasting insulin level change after a lifestyle intervention in a community park. A randomized wait-list control design was used to recruit 50 Filipino American participants into a flexible eight-week curriculum. The retention rate was 88%. A weight loss of 1.52 kg (p < .05) and a waist reduction of 5.46 cm (p < .05) were found in the intervention group. Significant predictors for weight loss were gender and marital status. The intervention showed promise for this community program.
    Journal of Community Health Nursing 10/2014; 31(4):225-37. DOI:10.1080/07370016.2014.926674 · 0.63 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The association of the fat mass and obesity-associated gene (FTO) rs11642015 polymorphism with prediabetes, type 2 diabetes and obesity in certain populations has not been previously reported. A population-based study was conducted that included 490 type 2 diabetic, 471 prediabetic and 575 normal subjects. The main outcomes of the study were prediabetes, type 2 diabetes and obesity. Binary logistic regression was performed to estimate the association of FTO rs11642015 with the risk of prediabetes, type 2 diabetes and obesity following adjustment for the corresponding confounders. A meta-analysis was also conducted to evaluate the association between FTO rs11642015 and obesity. FTO rs11642015 was significantly associated with prediabetes in the whole sample under the additive model [odds ratio (OR), 1.50; 95% confidence interval (CI), 1.17-1.93; P=0.002], particularly in females. The polymorphism remained consistently significant following adjustment for age and body mass index (BMI), showing an increased prediabetes risk with an additive effect (OR, 1.55; 95% CI, 1.19-2.01; P=0.001). In addition, a significant association was found for rs11642015 with prediabetes and type 2 diabetes under the dominant model. However, under the stringent Bonferroni's correction there was no evidence of positive associations for FTO rs11642015 with obesity in the whole sample, females or males. Findings of the meta-analysis showed that FTO rs11642015 was not predisposed to obesity. In conclusion, the T allele of FTO rs11642015 is positively associated with an increased risk of prediabetes, even after adjustment for age and BMI, particularly in females. Subjects carrying the CT + TT genotype are predisposed to prediabetes and type 2 diabetes. Therefore, results of the population-based study and follow-up meta-analysis suggested that FTO rs11642015 is not significantly associated with susceptibility to obesity.
    09/2014; 2(5):681-686. DOI:10.3892/br.2014.293
  • [Show abstract] [Hide abstract]
    ABSTRACT: A simulation based computational method was conducted to reflect the effect of intervention for those at high risk of type 2 diabetes. Hierarchy Support Vector Machines (H-SVMs) were used to classify high risk. The proportion transitioning from the high risk state to moderate state, low state or the normal state was calculated. When Body Mass Index (BMI) decreased by 5% (weight loss: 3–5 kg), the proportion of class A transferring to a lower state was 15–25%, and risk also appeared reduced for class B1. In class C, when cholesterol (CHOL) was decreased by 2.5% (0.13–0.34 mmol/L), 10–25% transitioned to a lower risk state. The method could help determine risk transition by the adjustment of sensitive risk factors. This might provide the basis for implementing intervention in cases in a high risk state.
    Computers in Biology and Medicine 10/2014; 53. DOI:10.1016/j.compbiomed.2014.05.015 · 1.48 Impact Factor