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OBJECTIVE: To investigate the excess mortality and life-years lost associated with diabetes and prediabetes in China. RESEARCH DESIGN AND METHODS: This national cohort study enrolled 135,405 participants aged 18 years or older from the general population in China. Cox proportional hazards regression models were used to estimate adjusted mortality rate ratio (RR). The life table method was used to estimate life expectancy. RESULTS: Among the 135,405 participants, 10.5% had diabetes and 36.2% had prediabetes in 2013. During a median follow-up of 6 years, 5517 deaths were recorded, including 1428 and 2300 deaths among people with diabetes and prediabetes, respectively. Diabetes and prediabetes were significantly associated with increased risk of all-cause (diabetes: RR, 1.61 [95% CI 1.49, 1.73]; prediabetes: RR, 1.08 [95% CI 1.01, 1.15]), and cardiovascular disease (diabetes: RR, 1.59 [95% CI 1.41, 1.78]; prediabetes: RR, 1.10 [95% CI 1.00, 1.21]) mortality. Additionally, diabetes was significantly associated with increased risks of death resulting from cancer, respiratory disease, liver disease, and diabetic ketoacidosis or coma. Compared with participants with normoglycemia, life expectancy of those with diabetes and prediabetes was shorter, on average, by 4.2 and 0.7 years at age 40 years, respectively. The magnitude of the associations of diabetes and prediabetes with all-cause and cardiovascular disease mortality varied by age and residence. CONCLUSIONS: In this national study, diabetes and prediabetes were significantly associated with reduced life expectancy and increased all-cause and cause-specific mortality risks. The disparities in excess mortality associated with diabetes and prediabetes between different ages and residences have implications for diabetes and prediabetes prevention and treatment programs. [ABSTRACT FROM AUTHOR]

Abstract: The prediction of danger state in mine coal layer spontaneous combustion correctly has an important practical meaning for the mine production safety. There is a kind of complicated nonlinear relation between the danger of coal layer spontaneous combustion and its influencing factors. And the neural network can truly show the nonlinear relation. In this paper, for the purpose of predicting it in mine coal layer correctly, a kind of method combined the advantages of genetic algorithm (GA) and BP neural network is introduced based on the demonstration of the necessity and possibility of combining BP with GA. At first, the notion of using multilayered BP as the representation method of genetic and the searching technique is introduced, and a novel method of using GA to train connection weights of BP neural network is designed. According to the characteristics of mine coal layer spontaneous combustion danger, three key influencing factors are selected as the judging indexes. Then the model for predicting the danger of mine coal layer spontaneous combustion is built. Practical application indicates that the capability of the new method in fast learning of ANN and escaping local optima. And the results show that the model is a very efficient method for predicting the danger of coal layer spontaneous combustion. [Copyright &y& Elsevier]