Abstract： Objective:To describe the baseline characteristics of the subjects enrolled in the China Quantitative CT (QCT) big data program in 2018—2019.Methods:Based on baseline data from the Chinese health big data project from January 2018 to December 2019 from the eligible enrolled population, measurements of bone mineral density (BMD) and visceral adipose tissue (VAT) were performed using Mindways′ QCT Pro Model 4 system. The baseline data of age, gender, regional distribution, height, weight, abdominal circumference, blood pressure, blood routine and blood biochemical tests were analyzed. And the single factor analysis of variance (ANOVA) was used to check the age related trend of BMD and VAT in both genders.Results:After screening the inclusion exclusion criteria and outliers of the main indicators, 86 113 people were enrolled in the project. The enrollment rate was 92.47%, including 35 431 (41.1%) women and 50 682 (58.9%) men, and the ratio of men to women was 1.43. The mean age was (50.3±12.7) years in all the subjects, and it was (50.2±12.8) years and (50.4±12.5) years in men and women, respectively, and there was no statistical difference between the two genders ( P>0.05). Total of 43 833 people were enrolled in east China, it was the largest group by region (50.90%), it was followed by central China (16 434 people, 19.08%), and the number of people enrolled in Northeast China was the lowest (2 914 people, 3.38%). The rate of completing of health information indicators related to the main outcome of the study were all above 70%, and there were significant differences between men and women (all P<0.05). The mean BMD was (139.33±46.76) mg/cm 3 in women, (135.90±36.48) mg/cm 3 in men, which showed a decreasing trend with age in both gender (both P<0.001); the mean intra-abdominal fat area was (116.39±56.23) cm 2 in women, (191.67±77.07) cm 2 in men, and there was an increasing trend with age in both men and women (both P<0.001). Conclusions:There are gender differences in BMD and VAT measured by QCT with different age tendency, and there are gender differences in health information index. Regional factors should also be taken into account for regional differences in the inclusion of data.