RESUMO
BACKGROUND: Prediabetes risk assessment models derived from large sample sizes are scarce. AIM: To establish a robust assessment model for prediabetes and to validate the model in different populations. METHODS: The China National Diabetes and Metabolic Disorders Study (CNDMDS) collected information from 47325 participants aged at least 20 years across China from 2007 to 2008. The Thyroid Disorders, Iodine Status and Diabetes Epidemiological Survey (TIDE) study collected data from 66108 participants aged at least 18 years across China from 2015 to 2017. A logistic model with stepwise selection was performed to identify significant risk factors for prediabetes and was internally validated by bootstrapping in the CNDMDS. External validations were performed in diverse populations, including populations of Hispanic (Mexican American, other Hispanic) and non-Hispanic (White, Black and Asian) participants in the National Health and Nutrition Examination Survey (NHANES) in the United States and 66108 participants in the TIDE study in China. C statistics and calibration plots were adopted to evaluate the model's discrimination and calibration performance. RESULTS: A set of easily measured indicators (age, education, family history of diabetes, waist circumference, body mass index, and systolic blood pressure) were selected as significant risk factors. A risk assessment model was established for prediabetes with a C statistic of 0.6998 (95%CI: 0.6933 to 0.7063) and a calibration slope of 1.0002. When externally validated in the NHANES and TIDE studies, the model showed increased C statistics in Mexican American, other Hispanic, Non-Hispanic Black, Asian and Chinese populations but a slightly decreased C statistic in non-Hispanic White individuals. Applying the risk assessment model to the TIDE population, we obtained a C statistic of 0.7308 (95%CI: 0.7260 to 0.7357) and a calibration slope of 1.1137. A risk score was derived to assess prediabetes. Individuals with scores ≥ 7 points were at high risk of prediabetes, with a sensitivity of 60.19% and specificity of 67.59%. CONCLUSION: An easy-to-use assessment model for prediabetes was established and was internally and externally validated in different populations. The model had a satisfactory performance and could screen individuals with a high risk of prediabetes.
RESUMO
This study examined human exposure to polybrominated diphenyl ethers (PBDEs) associated with fish consumption and inhalation in China. The median intake of sigma7 PBDEs via human milk was 48.2 ng/day for nursing infants (0-1 years old) (a range of 23.4-99.1 ng/day). For all other age groups, the median intake of sigma11 PBDEs via fish consumption was 1.7-12.9 ng/day with a range of 0.59-56.3 ng/g. Additionally, human exposure to PBDEs via inhalation was 2.7-9.2 ng/day (a range of 0.72-108 ng/day). The median total sigma11 PBDEs intakes for nursing infants (6874 and 7372 pg/ kg b.w./day for males and females, respectively) were much higher than other age groups (215-608 pg/kg b.w./ day). No significant difference in the total PBDEs intakes was found between males and females. Of the 11 PBDEs congeners, BDE-47 was predominant in the total intake for nursing infants with a mean contribution of 38%, whereas BDE-209 was the dominant congener of total intake for other age groups, varying from 44 to 61%. Currently, the PBDEs levels in Chinese consumer fish and the total intakes of PBDEs via fish consumption were at the lower end of the global range. Compared with similar studies in other countries, however, human exposure to PBDEs via inhalation in China was relatively high. Overall, estimated daily intake of total PBDEs in the Chinese population was far below the LOAEL. However, studies are needed to further understand the fate and impact of PBDEs as PBDE-containing products are still used widely in large quantities in China.