Cited by 1,034Cardiovascular Health and Risk FactorsHealth, Environment, Cognitive AgingStatistical Methods in Epidemiology

China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up

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Chen, Z., Chen, J., Collins, R., Guo, Y., Peto, R., Wu, F., Li, L., on behalf of the China Kadoorie Biobank (CKB) collaborative group·2011·International Journal of Epidemiology

Abstract

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 have been previously limited by available data, but are now feasible by combining well-established family studies with recent large biobanks.

    “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]

    The Additional information section (page not supplied) reports that the China Kadoorie Biobank recruited 512,891 people and stored blood samples, supporting its identification as a large biobank. The Discussion describes its potential for genetic research, but our copy does not report thousands of sibships or address the feasibility of within-sibship GWAS; searches for “sibling” and “sibship” found no relevant passage. (LLM, conf=0.83)

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  • Similar initiatives have been conducted in other countries, such as the China Kadoorie Biobank and Biobank Japan.

    “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]

  • Biobank efforts pioneered in Framingham and DeCODE now encompass a growing inventory of national cohorts in North America, Europe, Asia and beyond.

    “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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Research works printed but not linked: 2

  1. Yang GH, Murray CJL, Zhang Z (eds). Exploring Adult Mortality in China: Levels, Patterns and Causes. Beijing: Hua Xia Press, 1991.
  2. Chen JS, Peto R, Pan WH, Liu B, Campbell TC (eds). Mortality, Biochemistry, Diet and Lifestyle in Rural China: Geographic Study of the Characteristics of 69 Counties in Mainland China and 16 Areas in Taiwan. Oxford: Oxford University of Press, 2006.

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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
Published
2011-09-21
Volume
40
Issue
6
Pages
1652-1666
ISSN
  • 0300-5771 (ISSN-L)
  • 1464-3685
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
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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