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China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up
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BACKGROUND: Large blood-based prospective studies can provide reliable assessment of the complex interplay of lifestyle, environmental and genetic factors as determinants of chronic disease. METHODS: The baseline survey of the China Kadoorie Biobank took place during 2004-08 in 10 geographically defined regions, with collection of questionnaire data, physical measurements and blood samples. Subsequently, a re-survey of 25,000 randomly selected participants was done (80% responded) using the same methods as in the baseline. All participants are being followed for cause-specific mortality and morbidity, and for any hospital admission through linkages with registries and health insurance (HI) databases. RESULTS: Overall, 512,891 adults aged 30-79 years were recruited, including 41% men, 56% from rural areas and mean age was 52 years. The prevalence of ever-regular smoking was 74% in men and 3% in women. The mean blood pressure was 132/79 mmHg in men and 130/77 mmHg in women. The mean body mass index (BMI) was 23.4 kg/m(2) in men and 23.8 kg/m(2) in women, with only 4% being obese (>30 kg/m(2)), and 3.2% being diabetic. Blood collection was successful in 99.98% and the mean delay from sample collection to processing was 10.6 h. For each of the main baseline variables, there is good reproducibility but large heterogeneity by age, sex and study area. By 1 January 2011, over 10,000 deaths had been recorded, with 91% of surviving participants already linked to HI databases. CONCLUSION: This established large biobank will be a rich and powerful resource for investigating genetic and non-genetic causes of many common chronic diseases in the Chinese population.
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“GWAS using siblings (within-sibship GWAS) (Fig. 2) have been previously limited by available data, but are now feasible by combining well-established family studies with recent large biobanks that incidentally or by design contain thousands of sibships35–39.”
From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [38]
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“Similar initiatives have been conducted in other countries, such as the China Kadoorie Biobank 86 and Biobank Japan 87 .”
From Multimodal biomedical AI (2022) · cites this paper as [86]
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“These biobank efforts, pioneered in studies such as the Framingham Cohort70 and the efforts of DeCODE in Iceland71,72, now encompass a growing inventory of national cohorts in North America, Europe, Asia and beyond73–76.”
From A brief history of human disease genetics (2020) · cites this paper as [76]
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Xie, Z., Guo, X., Han, L., Wang, X., Yan, Q., Shu, C., Fan, Z., & Zhao, M. (2023) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2023.102219
“Detailed information about the CKB study design and procedures is available in previous reports (Chen et al., 2011; Chen et al., 2005).”
MethodAssociation of Resting Heart Rate with the Risk of Stroke in Men
Xu, C., Guo, Y., Bian, Z., Chen, Z., Li, L., & Yu, M. (2023) · Iranian Journal of Public Health · doi:10.18502/ijph.v52i8.13406
“CKB approaches, enrollment standards, and other details have been reported in existing studies (12-13).”
BackgroundSelf-citationGenetic Susceptibility in Occupational Health
Stanley, L. A. (2023) · Wiley eBooks · doi:10.1002/0471125474.tox151
Jin, H., Wang, X., Dai, H., Tian, A.-X., Chen, B.-W., Wu, C., Zhang, X.-Y., Cui, J.-L., Wu, Y., Li, X., et al. (2023) · Reviews in cardiovascular medicine · doi:10.31083/j.rcm2410285
“A large-scale study, however, had verified the accuracy of the PA-related questions [ 17].”
MethodResultBiobank participation of persons with epilepsy in South Wales
Baker, M. D. (2023) · doi:10.23889/suthesis.64845
Development of stroke systems of care across the globe
(2023) · Frontiers research topics · doi:10.3389/978-2-8325-3680-3
Dairy consumption and incident cardiovascular disease: a global analysisPreprint
Zhuang, P., Liu, X., Li, Y., Yang, A., Wu, Y., Ye, H., Wan, X., Zhang, L., Meng, D., Tian, Y., et al. (2023) · medRxiv · doi:10.1101/2023.11.14.23298545
Dunneram, Y., Lee, J. Y., Watling, C. Z., Fraser, G. E., Miles, F. L., Prabhakaran, D., Shridhar, K., Kondal, D., Mohan, V., Ali, M. K., et al. (2024) · medRxiv · doi:10.1101/2024.01.15.24301161
Self-citationZhang, Y., Sun, Q., Yu, C., Sun, D., Pang, Y., Pei, P., Du, H., Yang, L., Chen, Y., Yang, X., et al. (2024) · Journal of Hypertension · doi:10.1097/hjh.0000000000003717
“Assessment of blood pressure and other variables Blood pressure measurement was conducted after the on-site registration and physical measurements, including UA-779 digital sphygmomanometer for 2004–2008 baseline survey, Omron HEM-7430 sphygmomanometer for 2013– 2014 resurvey, and UA-767PBT-Ci digital blood pressure m…”
Self-citationZhu, X., Lv, J., Zhu, M., Yan, C., Deng, B., Yu, C., Yu, G., Ni, J., She, Q., Wang, T., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22715418
Self-citationGenetics of Small Vessel Disease
Marini, S., Parodi, L., Malik, R., & Anderson, C. D. (2024) · Springer eBooks · doi:10.1007/978-3-031-41777-1_13
Jiang, Z., Dai, Y., Chang, J. K., Li, N., Lv, J., Chen, Y., Liang, Y., & Sun, Y. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4792348
Song, S., Lv, J., Li, L., & Pang, Y. (2024) · Alimentary Pharmacology & Therapeutics · doi:10.1111/apt.17999
“Moreover, this study collected comprehensive and validated data on UC diagnosis, dietary information, and other relevant risk factors, 3 providing a unique opportunity to yield reliable evidence on the associations of diet with risk of later-onset UC.”
MethodSelf-citationTan, W., Shujun, L. I., Ping, F. A. N., JIANG, L., Lei, C. H. E. N., & Huang, W. C. (2024) · Scientia Sinica Vitae · doi:10.1360/ssv-2023-0206
Pharmacogenomics of an Australian Indigenous populations
Shankar, A. J. (2024) · Queensland University of Technology · doi:10.5204/thesis.eprints.248734
Xia, X., Chan, K. H., Niu, Y., Liu, C., Guo, Y., Ho, K., Yim, S. H. L., Wang, B., Doherty, A., Avery, D., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4547455/v1
Self-citationOEHR: An Orthopedic Electronic Health Record Dataset
Xie, Y., Wang, K., Zheng, J., Liu, F., Wang, X., & Huang, G. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657885
“Recently, there have been several publicly available EHR datasets, such as MIMIC-III [15], MIMIC-IV [16], eICU-CRD [26], PCORnet [8], CinC2019 [29], PIC [43], CHNS [44], CHARLS [46], and CKB [4].”
Mendelian Randomization of Sleep and Circadian Traits
Sonti, S., & Grant, S. F. A. (2024) · Springer eBooks · doi:10.1007/978-3-031-62723-1_9
The Relationship Between Dietary Fiber Intake and the Risk of Type 2 Diabetes
Zhong, H. (2024) · Highlights in Science Engineering and Technology · doi:10.54097/xwxr0m05
“The China Kadoorie Biobank (CKB) involves surveys in 10 regions across the country, divided into five urban and five rural sites, with Weifang being one of the study sites [8].”
BackgroundComputational disease-risk prediction: Tools and statistical approaches
Chimusa, E. R. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-18546-5.00006-1
Metadata
- Authors
- Chen, Z., Chen, J., Collins, R., Guo, Y., Peto, R., Wu, F., Li, L., & on behalf of the China Kadoorie Biobank (CKB) collaborative group
- Affiliations
- Chinese Center For Disease Control and Prevention (CN)
- Corresponding author
- Chen, Z.
- Li, L.
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-09-21
- Volume
- 40
- Issue
- 6
- Pages
- 1652-1666
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- PMC
- PMC3235021
- OpenAlex
- W2105079646
- Cited by
- 1,034
- References
- 43
- Citations by year
- 2026: 109 · 2025: 122 · 2024: 134 · 2023: 110 · 2022: 107 · 2021: 116 · 2020: 75 · 2019: 66 · 2018: 55 · 2017: 51 · 2016: 30 · 2015: 26 · 2014: 14 · 2013: 12 · 2012: 6
- FWCI
- 7.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Epidemiology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Wellcome Trust (088158/Z/09/Z)
- Cancer Research UK
- British Heart Foundation
- Chinese Center for Disease Control and Prevention
- Kadoorie Charitable Foundation
- Centers for Disease Control and Prevention
- Medical Research Council
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- China Kadoorie Biobank, prospective cohort, biobanks, baseline characteristics, smoking prevalence, blood pressure, body mass index, diabetes prevalence, cause-specific mortality, hospitalization, chronic disease, Chinese adults
- MeSH terms
- Adult, Age Factors, Aged, Blood Pressure, Body Weights and Measures, China, Chronic Disease, Data Collection, Environment, Female, Follow-Up Studies, Genetic Testing, Humans, Life Style, Male, Middle Aged, Prospective Studies, Surveys and Questionnaires, Residence Characteristics, Rural Population, Sex Factors, Smoking, Socioeconomic Factors, Health Behavior, Body Mass Index, Databases, Factual, Genetic Predisposition to Disease, Databases, Genetic
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