No abstract

Environmental factors shared by co-twins affect BMI in childhood, but little evidence for their contribution was found in late adolescence. Our results suggest that genetic factors play a major role in the variation of BMI in adolescence among populations of different ethnicities exposed to different environmental factors related to obesity.

Height variation is known to be determined by both genetic and environmental factors, but a systematic description of how their influences differ by sex, age and global regions is lacking. We conducted an individual-based pooled analysis of 45 twin cohorts from 20 countries, including 180,520 paired measurements at ages 1–19 years. The proportion of height variation explained by shared environmental factors was greatest in early childhood, but these effects remained present until early adulthood. Accordingly, the relative genetic contribution increased with age and was greatest in adolescence (up to 0.83 in boys and 0.76 in girls). Comparing geographic-cultural regions (Europe, North-America and Australia, and East-Asia), genetic variance was greatest in North-America and Australia and lowest in East-Asia, but the relative proportion of genetic variation was roughly similar across these regions. Our findings provide further insights into height variation during childhood and adolescence in populations representing different ethnicities and exposed to different environments.

OBJECTIVETo develop a New Chinese Diabetes Risk Score for screening undiagnosed type 2 diabetes in China.RESEARCH DESIGN AND METHODSData from the China National Diabetes and Metabolic Disorders Study conducted from June 2007 to May 2008 comprising 16,525 men and 25,284 women aged 20–74 years were analyzed. Undiagnosed type 2 diabetes was detected based on fasting plasma glucose ≥7.0 mmol/L or 2-h plasma glucose ≥11.1 mmol/L in people without a prior history of diabetes. β-Coefficients derived from a multiple logistic regression model predicting the presence of undiagnosed type 2 diabetes were used to calculate the New Chinese Diabetes Risk Score. The performance of the New Chinese Diabetes Risk Score was externally validated in two studies in Qingdao: one is prospective with follow-up from 2006 to 2009 (validation 1) and another cross-sectional conducted in 2009 (validation 2).RESULTSThe New Chinese Diabetes Risk Score includes age, sex, waist circumference, BMI, systolic blood pressure, and family history of diabetes. The score ranges from 0 to 51. The area under the receiver operating curve of the score for undiagnosed type 2 diabetes was 0.748 (0.739–0.756) in the exploratory population, 0.725 (0.683–0.767) in validation 1, and 0.702 (0.680–0.724) in validation 2. At the optimal cutoff value of 25, the sensitivity and specificity of the score for predicting undiagnosed type 2 diabetes were 92.3 and 35.5%, respectively, in validation 1 and 86.8 and 38.8% in validation 2.CONCLUSIONSThe New Chinese Diabetes Risk Score based on nonlaboratory data appears to be a reliable screening tool to detect undiagnosed type 2 diabetes in Chinese population.

OBJECTIVEThe study's goal was to evaluate the performance of A1C and fasting capillary blood glucose (FCG) tests as mass screening tools for diabetes and pre-diabetes, as determined by the standard oral glucose tolerance test (OGTT).RESEARCH DESIGN AND METHODSData from 2,332 individuals aged 35–74 years who participated in a population-based cross-sectional diabetes survey in Qingdao, China, were analyzed. A 2-h 75-g OGTT was used to diagnose diabetes. The performance of A1C and FCG was evaluated against the results of the OGTTs by using receiver operating characteristic curve (ROC) analysis.RESULTSThe prevalence of newly diagnosed diabetes and pre-diabetes (impaired fasting glucose and/or impaired glucose tolerance) was 11.9 and 29.5%, respectively. For subjects with newly diagnosed diabetes, the area under the ROC curve was 0.67 for A1C and 0.77 for FCG (P < 0.01) in men and 0.67 and 0.75 (P < 0.01) in women, whereas for pre-diabetes, these values were 0.47 and 0.64 (P < 0.001) in men and 0.51 and 0.65 (P < 0.001) in women. At the optimal A1C cutoff point of ≥5.6% for newly diagnosed diabetes, sensitivities (specificities) were 64.4% (61.6%) for men and 62.3% (63.3%) for women.CONCLUSIONSAs a screening tool for newly diagnosed diabetes and pre-diabetes, the FCG measurement performed better than A1C in this general Chinese population.