著者

Chu-Wen Ling Haili Zhong Fang-fang Zeng Gengdong Chen Yuanqing Fu Cheng Wang Zhe-Qing Zhang Wen-Ting Cao Ting-Yu Sun Ding ding Yan-Hua Liu Hong-Li Dong Li-Peng Jing Wenhua Ling Ju-Sheng Zheng Yu-Ming Chen

出版者

Japan Epidemiological Association

雑誌

Journal of Epidemiology (ISSN:09175040)

巻号頁・発行日

pp.JE20230108, (Released:2023-10-07)

参考文献数

36

被引用文献数

3

---

Background: The Guangzhou Nutrition and Health Study (GNHS) aims to assess the determinants of metabolic disease in nutritional aspects, as well as other environmental and genetic factors, and explore possible biomarkers and mechanisms with multi-omics integration.Methods: The population-based sample of adults in Guangzhou, China (baseline: 40-83 years old; n = 5118) was followed up about every 3 years. All will be tracked via on-site follow-up and health information systems. We assessed detailed information on lifestyle factors, physical activities, dietary assessments, psychological health, cognitive function, body measurements, and muscle function. Instrument tests included dual-energy X-ray absorptiometry scanning, carotid artery and liver ultrasonography evaluations, vascular endothelial function evaluation, upper-abdomen and brain magnetic resonance imaging, and 14-d real-time continuous glucose monitoring tests. We also measured multi-omics, including host genome-wide genotyping, serum metabolome and proteome, gut microbiome (16S rRNA sequencing, metagenome, and internal transcribed spacer 2 sequencing), and fecal metabolome and proteome.Results: The baseline surveys were conducted from 2008 to 2015. Now, we have completed 3 waves. The 3rd and 4th follow-ups have started but have yet to end. A total of 5118 participants aged 40-83 took part in the study. The median age at baseline was approximately 59.0 years and the proportion of female participants was about 69.4%. Among all the participants, 3628 (71%) completed at least one on-site follow-up with a median duration of 9.48 years.Conclusion: The cohort will provide data that have been influential in establishing the role of nutrition in metabolic diseases with multi-omics.