Background: Previous studies in European populations have identified a large number of genetic variants affecting plasma levels of Olink proteins, but little is known about the non-genetic factors influencing plasma levels of proteins, particularly in Chinese populations. Methods: We measured plasma levels of 2,923 proteins, using Olink Explore platform, in 2,006 participants in the China Kadoorie Biobank. Linear regression analyses were used to assess the cross-sectional associations of individual proteins with 37 exposures across multiple domains (e.g. socio-demographic, lifestyle, environmental, sample processing, reproductive factors, clinical measurements, and health-related indices), adjusted for potential confounders and multiple testing. These were further replicated and compared with similar analyses in Europeans. Results: Overall 31 exposures were associated with at least one protein, with age (n=1,154), sex (n=827), BMI (n=869) showing the highest number of associations, followed by frailty index (n=597), SBP (n=479), RPG (n=387), ambient temperature (n=292), and HBsAg-positivity (n=282), with diet and physical activity showing little associations. Likewise, of the 2,923 proteins examined, 65% were associated with at least one exposure, with three proteins (CDHR2, CKB, and PLAT) showing the largest number of associations with baseline characteristics (n=14). The patterns of associations differed by sex, chiefly due to differences in lifestyle and reproductive factors. Over 90% of proteomic associations with key exposures in the current study were replicated in the UK Biobank. Conclusions: In Chinese adults, the exposome-wide assessment of Olink proteins identified a large number of associations with a wide range of exposures, which could inform future research priorities and analytic strategies.