Background and Purpose:Type 2 diabetes mellitus patients have an increased fracture risk despite having higher areal bone mineral density (aBMD) measured by DXA. This apparent paradox might be... Show moreBackground and Purpose:Type 2 diabetes mellitus patients have an increased fracture risk despite having higher areal bone mineral density (aBMD) measured by DXA. This apparent paradox might be explained by the overestimation of BMD by DXA due to the higher fat mass in type 2 diabetes mellitus patients. Volumetric BMD (vBMD) as assessed by quantitative CT (QCT) is not influenced by fat mass. We assessed the association of vBMD and fasting plasma glucose in a large cohort of Chinese subjects and compared the vBMD in healthy and diabetic subjects. In addition, we compared the relation between aBMD, vBMD, glucose and fat mass in a subset of this cohort. Materials and Methods:10309 participants from the China Biobank project underwent QCT based on chest low dose CT to compute vBMD of L1 and L2 vertebrae and FPG measurements between 2018 and 2019. Among them, 1037 subjects also had spine DXA scans. Data was analyzed using linear regression models. Results: In the total cohort (5889 men and 4420 women, mean age 53 years, range 30-96), there was no significant association between vBMD and FPG after adjustment for age (women: p=0.774; men: p=0.149). 291 women and 606 men fitted the diagnostic criteria of diabetes. Both women and men with diabetes had lower vBMD compared to non-diabetic subjects, but this became non-significant after adjusting for age in the total cohort (women: p=0.817; men: p=0.288) and after propensity score matching based on age (women: p=0.678; men: p=0.135). In the DXA subcohort, aBMD was significantly higher in men with diabetes after adjusting for age and this difference disappeared after further adjusting for total fat area (p=0.064). Conclusion: We did not find any effect of fasting plasma glucose or diabetes on the volumetric BMD measured with QCT after adjustment for age. Therefore, vBMD measured with QCT might be a more reliable measurement to diagnose osteoporosis and assess fracture risk than aBMD measured with DXA in diabetic patients. Show less
Understanding the spatiotemporal patterns of carbon footprints (CFs) of grains production is important to formulate regional heterogeneous greenhouse gas (GHG) mitigation strategies. This study... Show moreUnderstanding the spatiotemporal patterns of carbon footprints (CFs) of grains production is important to formulate regional heterogeneous greenhouse gas (GHG) mitigation strategies. This study evaluates the CFs, farm CFs (FCFs: CFs of per unit area), and production CFs (PCFs: CFs of per unit yield) of main grains production in China based on a new scale data set: agricultural statistics data of over 300 prefecture-level regions. A comparison of CFs of main grains production between main producing area (MPA) and non-main producing area (NMPA) are firstly discussed on a totally new scale. Results show that the CFs of main grains production of MPA accounts for 54-57% of country's total although the area of farmland of MPA only accounts for 42%. The PCF and FCF of rice production are higher in MPA, while those of wheat and maize production are lower in MPA. It implies that there are less GHG emission of rice (main paddy grain) productions in NMPA and less GHG emission of wheat and maize (main dryland grains) production in MPA. In additional, the PCF of rice shows growth, while that of wheat and maize shows decline from 2008 to 2017. The growth of PCF of rice is mainly driven by the rise of PCF in MPA. Findings are expected to improve the understanding patterns of China's CF of main grains production and subsequently contribute to GHG mitigation. Show less
