Cited by 130Statistical Methods in EpidemiologyGenetic Associations and EpidemiologyHealth, Environment, Cognitive Aging

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

The UK Biobank and selection bias

Open access

Swanson, James M·2012·The Lancet

DOI 10.1016/s0140-6736(12)61179-9

Open this paper in CoChat — free account Open PDF

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1016/s0140-6736(12)61179-9

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
Limitations of the Application of Fourfold Table Analysis to Hospital Data
Berkson, J. (1946) · Biometrics Bulletin · doi:10.2307/3002000 · Cited by 1,810
What makes UK Biobank special?
Collins, R. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60404-8 · Cited by 1,128
New Models for Large Prospective Studies: Is There a Better Way?
Manolio, T. A., Weis, B. K., Cowie, C. C., Hoover, R. N., Hudson, K., Kramer, B. S., Berg, C., Collins, R., Ewart, W., Gaziano, J. M., et al. (2012) · American Journal of Epidemiology · doi:10.1093/aje/kwr453 · Cited by 129

Show all 4 references

Sorted by citations

Multimodal population brain imaging in the UK Biobank prospective epidemiological study
Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4393 · Cited by 2,020
Multimodal biomedical AI
Acosta, J. N., Falcone, G. J., Rajpurkar, P., & Topol, E. J. (2022) · Nature Medicine · doi:10.1038/s41591-022-01981-2 · Cited by 1,365
Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis
Batty, G. D., Gale, C. R., Kivimäki, M., Deary, I. J., & Bell, S. (2020) · BMJ · doi:10.1136/bmj.m131 · Cited by 635
Participation bias in the UK Biobank distorts genetic associations and downstream analyses
Schoeler, T., Speed, D., Porcu, E., Pirastu, N., Pingault, J., & Kutalik, Z. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01579-9 · Cited by 437
Axes of a revolution: challenges and promises of big data in healthcare
Shilo, S., Rossman, H., & Segal, E. (2020) · Nature Medicine · doi:10.1038/s41591-019-0727-5 · Cited by 370
Prevalence and Characteristics of Probable Major Depression and Bipolar Disorder within UK Biobank: Cross-Sectional Study of 172,751 Participants
Smıth, D. J., Nicholl, B. I., Cullen, B., Martin, D. J., Haq, Z. U., Evans, J. J., Gill, J. M. R., Roberts, B. A., Gallacher, J., Mackay, D., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0075362 · Cited by 360
Physical activity, multimorbidity, and life expectancy: a UK Biobank longitudinal study
Chudasama, Y. V., Khunti, K. K., Zaccardi, F., Rowlands, A. V., Yates, T., Gillies, C. L., Davies, M. J., & Dhalwani, N. N. (2019) · BMC Medicine · doi:10.1186/s12916-019-1339-0 · Cited by 353
Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits
Lane, J. M., Liang, J., Vlasac, I., Anderson, S. G., Bechtold, D. A., Bowden, J., Emsley, R., Gill, S., Little, M. A., Luik, A. I., et al. (2016) · Nature Genetics · doi:10.1038/ng.3749 · Cited by 346
Healthy lifestyle and life expectancy in people with multimorbidity in the UK Biobank: A longitudinal cohort study
Chudasama, Y., Khunti, K. K., Gillies, C. L., Dhalwani, N. N., Davies, M. J., Yates, T. E., & Zaccardi, F. (2020) · PLoS Medicine · doi:10.1371/journal.pmed.1003332 · Cited by 327
Genetic analyses identify widespread sex-differential participation bias
Pirastu, N., Cordioli, M., Nandakumar, P., Mignogna, G., Abdellaoui, A., Hollis, B., Kanai, M., Rajagopal, V. M., Parolo, P. D. B., Baya, N., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00846-7 · Cited by 251
The Mayo Clinic Biobank: A Building Block for Individualized Medicine
Olson, J. E., Ryu, E., Johnson, K. J., Koenig, B. A., Maschke, K. J., Morrisette, J. A., Liebow, M., Takahashi, P. Y., Fredericksen, Z. S., Sharma, R. G., et al. (2013) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2013.06.006 · Cited by 212
The road ahead in genetics and genomics
McGuire, A. L., Gabriel, S., Tishkoff, S. A., Wonkam, A., Chakravarti, A., Furlong, E. E. M., Treutlein, B., Meissner, A., Chang, H. Y., López-Bigas, N., et al. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0272-6 · Cited by 188
Reweighting UK Biobank corrects for pervasive selection bias due to volunteering
van Alten, S., Domingue, B. W., Faul, J. D., Galama, T. J., & Marees, A. T. (2024) · International Journal of Epidemiology · doi:10.1093/ije/dyae054 · Cited by 206
Prediction complements explanation in understanding the developing brain
Rosenberg, M. D., Casey, B. J., & Holmes, A. J. (2018) · Nature Communications · doi:10.1038/s41467-018-02887-9 · Cited by 169
Sleep and cognitive performance: cross-sectional associations in the UK Biobank
Kyle, S. D., Sexton, C. E., Feige, B., Luik, A. I., Lane, J. M., Saxena, R., Anderson, S. G., Bechtold, D. A., Dixon, W. G., Little, M. A., et al. (2017) · Sleep Medicine · doi:10.1016/j.sleep.2017.07.001 · Cited by 149
Diet, Sleep, and Mental Health: Insights from the UK Biobank Study
Hepsomali, P., & Groeger, J. A. (2021) · Nutrients · doi:10.3390/nu13082573 · Cited by 134
Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis
McIntosh, A. M., Hall, L. S., Zeng, Y., Adams, M. J., Gibson, J., Wigmore, E. M., Hagenaars, S. P., Davies, G., Fernandez-Pujals, A. M., Campbell, A., et al. (2016) · PLoS Medicine · doi:10.1371/journal.pmed.1002090 · Cited by 112
Biological Insights Into Muscular Strength: Genetic Findings in the UK Biobank
Tikkanen, E., Gustafsson, S., Amar, D., Shcherbina, A., Waggott, D. M., Ashley, E. A., & Ingelsson, E. (2018) · Scientific Reports · doi:10.1038/s41598-018-24735-y · Cited by 108
Adverse metabolic and mental health outcomes associated with shiftwork in a population-based study of 277,168 workers in UK biobank
Wyse, C. A., Morales, C. A. C., Graham, N., Fan, Y., Ward, J., Curtis, A. M., Mackay, D., Smıth, D. J., Bailey, M. E. S., Biello, S. M., et al. (2017) · Annals of Medicine · doi:10.1080/07853890.2017.1292045 · Cited by 113
Associations of discretionary screen time with mortality, cardiovascular disease and cancer are attenuated by strength, fitness and physical activity: findings from the UK Biobank study
Celis-Morales, C. A., Lyall, D. M., Steell, L., Gray, S. R., Iliodromiti, S., Anderson, J. J., Mackay, D., Welsh, P. I., Yates, T. E., Pell, J. P., et al. (2018) · BMC Medicine · doi:10.1186/s12916-018-1063-1 · Cited by 103
Evaluation of Brain-Body Health in Individuals With Common Neuropsychiatric Disorders
Tian, Y., Biase, M. A. D., Mosley, P. E., Lupton, M. K., Xia, Y., Fripp, J., Breakspear, M. J., Cropley, V., & Zalesky, A. (2023) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2023.0791 · Cited by 96
The limitations of large-scale volunteer databases to address inequalities and global challenges in health and aging
Brayne, C., & Moffitt, T. E. (2022) · Nature Aging · doi:10.1038/s43587-022-00277-x · Cited by 89
Diabetes, Glycated Hemoglobin, and the Risk of Myocardial Infarction in Women and Men: A Prospective Cohort Study of the UK Biobank
de Jong, M., Woodward, M., & Peters, S. A. E. (2020) · Diabetes Care · doi:10.2337/dc19-2363 · Cited by 89
Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the U.K.
Chudasama, Y., Zaccardi, F., Gillies, C. L., Razieh, C., Yates, T. E., Kloecker, D. E., Rowlands, A. V., Davies, M. J., Islam, N., Seidu, S., et al. (2021) · BMC Infectious Diseases · doi:10.1186/s12879-021-06600-y · Cited by 84
Searching for the causal effects of body mass index in over 300 000 participants in UK Biobank, using Mendelian randomization
Millard, L. A. C., Davies, N. M., Tilling, K. M., Gaunt, T. R., & Smith, G. D. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1007951 · Cited by 78
Can large surveys conducted on highly selected populations provide valid information on the epidemiology of common health conditions? An analysis of UK Biobank data on musculoskeletal pain
Macfarlane, G. J., Beasley, M., Smith, B. H., Jones, G. T., & Macfarlane, T. V. (2015) · British Journal of Pain · doi:10.1177/2049463715569806 · Cited by 75
Biobanking with genetics shapes precision medicine and global health
Gallagher, C. S., Ginsburg, G. S., & Musick, A. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00794-y · Cited by 87
Walking Pace Is Associated with Lower Risk of All-Cause and Cause-Specific Mortality
Celis-Morales, C. A., Gray, S. R., Petermann-Rocha, F. E., Iliodromiti, S., Welsh, P. I., Lyall, D. M., Anderson, J. J., Pellicori, P., Mackay, D., Pell, J. P., et al. (2018) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001795 · Cited by 72
Associations of ultra-processed food consumption with cardiovascular disease and all-cause mortality: UK Biobank
Chen, X., Chu, J., Hu, W., Sun, N., He, Q., Liu, S., Feng, Z., Li, T., Han, Q., & Shen, Y. (2022) · European Journal of Public Health · doi:10.1093/eurpub/ckac104 · Cited by 80
Physical Frailty, Adherence to Ideal Cardiovascular Health and Risk of Cardiovascular Disease: A Prospective Cohort Study
Chen, L., Li, X., Lv, Y., Tan, X. W., Zhong, V. W., Rong, S., Liu, G., & Liu, L. (2022) · Age and Ageing · doi:10.1093/ageing/afac311 · Cited by 75
MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging
Millard, L. A. C., Munafo, M. R., Tilling, K. M., Wootton, R. E., & Smith, G. D. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1008353 · Cited by 61
10 K: a large‐scale prospective longitudinal study in Israel
Shilo, S., Bar, N., Keshet, A., Talmor‐Barkan, Y., Rossman, H., Godneva, A., Aviv, Y., Edlitz, Y., Reicher, L., Kolobkov, D. S., et al. (2021) · European Journal of Epidemiology · doi:10.1007/s10654-021-00753-5 · Cited by 55
HbA1c and brain health across the entire glycaemic spectrum
Garfield, V., Farmaki, A., Eastwood, S. V., Mathur, R., Rentsch, C. T., Bhaskaran, K., Smeeth, L. L., & Chaturvedi, N. (2021) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14321 · Cited by 60
Comparing Copy Number Variations in a Danish Case Cohort of Individuals With Psychiatric Disorders
Sánchez, X. C., Helenius, D., Bybjerg‐Grauholm, J., Pedersen, C. B., HOUGAARD, D. M., Børglum, A. D., Nordentoft, M., Mors, O. N., Mortensen, P. B., Geschwind, D. H., et al. (2021) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2021.3392 · Cited by 51
Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review and meta-analysis
Sheppard, N., Carroll, M. T. C., Gao, C. X., & Lane, T. J. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.163272 · Cited by 49
The role of depression and physical activity in the association of between sleep quality, and duration with and health-related quality of life among the elderly: a UK Biobank cross-sectional study
Hu, W., Chu, J., Chen, X., Liu, S., Sun, N., Han, Q., Li, T., Feng, Z., He, Q., & Shen, Y. (2022) · BMC Geriatrics · doi:10.1186/s12877-022-03047-x · Cited by 47
Proxy gene-by-environment Mendelian randomization study confirms a causal effect of maternal smoking on offspring birthweight, but little evidence of long-term influences on offspring health
Yang, Q., Millard, L. A. C., & Smith, G. D. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz250 · Cited by 42
Representativeness Is Not Representative
Huang, J. Y. (2020) · Epidemiology · doi:10.1097/ede.0000000000001317 · Cited by 43
Contribution of type 2 diabetes to all-cause mortality, cardiovascular disease incidence and cancer incidence in white Europeans and South Asians: findings from the UK Biobank population-based cohort study
Muilwijk, M., Ho, F. K. W., Waddell, H., Sillars, A., Welsh, P. I., Iliodromiti, S., Brown, R., Ferguson, L. D., Stronks, K., van Valkengoed, I. G. M., et al. (2019) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2019-000765 · Cited by 39
NHS Health Check attendance is associated with reduced multiorgan disease risk: a matched cohort study in the UK Biobank
McCracken, C., Raisi‐Estabragh, Z., Szabó, L. E., Robson, J. P., Raman, B., Topiwala, A., Roca‐Fernández, A., Masud Husain, B., Petersen, S. E., Neubauer, S., et al. (2024) · BMC Medicine · doi:10.1186/s12916-023-03187-w · Cited by 32
From GWAS to PheWAS: the search for causality in big data
Huang, J. Y., & Labrecque, J. A. (2019) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30059-7 · Cited by 32
Associations between sleep health and grey matter volume in the UK Biobank cohort (n= 33 356)
Schiel, J. E., Tamm, S., Holub, F., Petri, R., Dashti, H. S., Domschke, K., Feige, B., Goodman, M. O., Jones, S. E., Lane, J. M., et al. (2023) · Brain Communications · doi:10.1093/braincomms/fcad200 · Cited by 32
Plasma proteomic biomarkers and the association between poor cardiovascular health and incident dementia: The UK Biobank study
Beydoun, M. A., Beydoun, H. A., Hu, Y., Vieytes, C. A. M., Hooten, N. N., Song, M., Georgescu, M. F., Kuczmarski, M. F., Meirelles, O., Launer, L. J., et al. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.05.005 · Cited by 33
Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci
Mignogna, G., Carey, C. E., Wedow, R., Baya, N. A., Cordioli, M., Pirastu, N., Bellocco, R., Malerbi, K. F., Nivard, M. G., Neale, B. M., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01632-7 · Cited by 34
Association of physical activity intensity and bout length with mortality: An observational study of 79,503 UK Biobank participants
Millard, L. A. C., Tilling, K. M., Gaunt, T. R., Carslake, D., & Lawlor, D. A. (2021) · PLoS Medicine · doi:10.1371/journal.pmed.1003757 · Cited by 32
The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology
Tan, V. Y., & Timpson, N. J. (2022) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-121321-093606 · Cited by 28
Physical activity, sedentary behaviour and risk of oesophago‐gastric cancer: A prospective cohort study within UK Biobank
Kunzmann, A. T., Mallon, K. P., Hunter, R. F., Cardwell, C. R., McMenamin, Ú. C., Spence, A. D., & Coleman, H. G. (2018) · United European Gastroenterology Journal · doi:10.1177/2050640618783558 · Cited by 29
Low neuroticism and cognitive performance are differently associated to overweight and obesity: A cross-sectional and longitudinal UK Biobank study
Olivo, G., Gour, S., & Schiöth, H. B. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2018.11.014 · Cited by 29
Assessment of Relative Utility of Underlying vs Contributory Causes of Death
Batty, G. D., Galé, C. R., Mika Kivimaki, B., & Bell, S. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.8024 · Cited by 28
Associations between insomnia symptoms and functional connectivity in the UK Biobank cohort (n = 29,423)
Holub, F., Petri, R., Schiel, J. E., Feige, B., Rutter, M. K., Tamm, S., Riemann, D. W., Kyle, S. D., & Spiegelhalder, K. (2022) · Journal of Sleep Research · doi:10.1111/jsr.13790 · Cited by 25
Active recruitment and limited participant-load related to high participation in large population-based biobank studies
van Zon, S. K. R., Scholtens, S., Reijneveld, S. A., Smidt, N., & Bültmann, U. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2016.03.009 · Cited by 23
Depressive symptoms, neuroticism, and participation in breast and cervical cancer screening: Cross‐sectional and prospective evidence from UK Biobank
Niedzwiedz, C. L., Robb, K. A., Katikireddi, S. V., Pell, J. P., & Smıth, D. J. (2019) · Psycho-Oncology · doi:10.1002/pon.5272 · Cited by 25
Evidence for shared genetics between physical activity, sedentary behaviour and adiposity‐related traits
Schnurr, T. M., Stallknecht, B. M., Sørensen, T. I. A., Kilpeläinen, T. O., & Hansen, T. F. (2020) · Obesity Reviews · doi:10.1111/obr.13182 · Cited by 25
Morbidity, risk of cancer and mortality in 3645 HFE mutations carriers
Hagström, H., Ndegwa, N., Jalmeus, M., Ekstedt, M., Posserud, I., Rorsman, F., Nyhlin, N., Klintman, D., Werner, M., Marschall, H., et al. (2021) · Liver International · doi:10.1111/liv.14792 · Cited by 23
EAT‐Lancet Diet Pattern, Genetic Predisposition, Inflammatory Biomarkers, and Risk of Lung Cancer Incidence and Mortality
Liu, F., Si, C., Chen, L., Peng, Y., Wang, P., Wang, X., Gong, J., Zhou, H., Gu, J., Qin, A., et al. (2024) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202400448 · Cited by 21
Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research
Cai, N., Verhulst, B., Andreassen, O. A., Buitelaar, J. K., Edenberg, H. J., Hettema, J. M., Gandal, M. J., Grotzinger, A. D., Jonas, K. G., Lee, P., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02878-x · Cited by 18
Understanding the inter‐relationships of type 2 diabetes and hypertension with brain and cognitive health: A UK Biobank study
Newby, D., & Garfield, V. (2022) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14658 · Cited by 20
Generalisability of Results from UK Biobank: Comparison With a Pooling of 18 Cohort StudiesPreprint
Batty, G. D., Galé, C. R., Mika Kivimaki, B., Deary, I. J., & Bell, S. (2019) · medRxiv · doi:10.1101/19004705 · Cited by 20
Assessment of causal associations between handgrip strength and cardiovascular diseases: A two sample mendelian randomization study
Zhuo, C., Zhao, J., Wang, Q., Lin, Z., Cai, H., Pan, H., Chen, L., Jin, X., Jin, H. L., Xu, L., et al. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.930077 · Cited by 19
Plant-based dietary patterns, genetic predisposition and risk of colorectal cancer: a prospective study from the UK Biobank
Liu, F., Lv, Y., Peng, Y., Qiao, Y., Wang, P., Si, C., Wang, X., Gong, J., Zhou, H., Zhang, M., et al. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04522-8 · Cited by 21
Lifetime risk and genetic predisposition to post-traumatic OA of the knee in the UK Biobank
Hollis, B. W., Chatzigeorgiou, C., Southam, L., Hatzikotoulas, K., Kluzek, S., Williams, A., Zeggini, E., Jostins-Dean, L., & Watt, F. E. (2023) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2023.05.012 · Cited by 16
White cell count in the normal range and short-term and long-term mortality: international comparisons of electronic health record cohorts in England and New Zealand
Shah, A. D., Thornley, S., Chung, S., Denaxas, S., Jackson, R., & Hemingway, H. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-013100 · Cited by 16
Alzheimer’s Disease polygenic risk, the plasma proteome, and dementia incidence among UK older adults
Beydoun, M. A., Beydoun, H. A., Li, Z., Hu, Y., Hooten, N. N., Ding, J., Hossain, S. A., Vieytes, C. A. M., Launer, L. J., Evans, M. K., et al. (2024) · GeroScience · doi:10.1007/s11357-024-01413-8 · Cited by 15
Strategies to Increase Response Rate and Reduce Nonresponse Bias in Population Health Research: Analysis of a Series of Randomized Controlled Experiments during a Large COVID-19 Study
Atchison, C. J., Gilby, N., Pantelidou, G., Clemens, S., Pickering, K., Chadeau‐Hyam, M., Ashby, D., Barclay, W., Cooke, G., Darzi, A. W., et al. (2025) · JMIR Public Health and Surveillance · doi:10.2196/60022 · Cited by 15
Mechanism of the association between sleep quality and mortality in middle-aged and older adults: A prospective study analysis of the UK Biobank
Hu, W., Han, Q., Chu, J., Sun, N., Li, T., Feng, Z., He, Q., Ma, Z., Wang, Y., & Shen, Y. (2023) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2023.105051 · Cited by 14
Recontacting biobank participants to collect lifestyle, behavioural and cognitive information via online questionnaires: lessons from a pilot study within FinnGen
Rodosthenous, R. S., Niemi, M., Kallio, L., Perälä, M., Terho, P., Knopp, T., Punkka, E., Makkonen, E., Nurmi, P., Mäkelä, J., et al. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-064695 · Cited by 13
Are infections associated with cognitive decline and neuroimaging outcomes? A historical cohort study using data from the UK Biobank study linked to electronic health records
Muzambi, R., Bhaskaran, K., Rentsch, C. T., Smeeth, L. L., Brayne, C., Garfield, V., Williams, D. M., Chaturvedi, N., & Warren‐Gash, C. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02145-z · Cited by 15
Impact of selection bias on polygenic risk score estimates in healthcare settings
Lee, Y. A., Thaweethai, T., Sheu, Y.-H., Feng, Y. A., Karlson, E. W., Ge, T., Kraft, P. L., & Smoller, J. W. (2023) · Psychological Medicine · doi:10.1017/s0033291723001186 · Cited by 14
Development and Validation of Risk Scores for All-Cause Mortality for a Smartphone-Based “General Health Score” App: Prospective Cohort Study Using the UK Biobank
Clift, A. K., Lannou, E. L., Tighe, C. P., Shah, S. S., Beatty, M., Hyvärinen, A., Lane, S. J., Strauss, T., Dunn, D. D., Lu, J., et al. (2021) · JMIR mhealth and uhealth · doi:10.2196/25655 · Cited by 15
Long-term air pollution exposure, habitual physical activity, and incident chronic kidney disease
Li, Z., Song, W.-Q., Qiu, C.-S., Li, H., Tang, X.-L., Shen, D., Zhang, P., Zhang, X., Ren, J., Gao, J., et al. (2023) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2023.115492 · Cited by 13
Applying a genetic risk score model to enhance prediction of future multiple sclerosis diagnosis at first presentation with optic neuritis
Loginovic, P., Wang, F., Li, J., Ferrat, L. A., Mirshahi, U. L., Rao, H. S., Petzold, A., Tyrrell, J., Green, H., Weedon, M. N., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44917-9 · Cited by 17
Long-term Associations Between Time-varying Exposure to Ambient PM2.5 and Mortality: An Analysis of the UK Biobank
Vanoli, J., Libardi, A. D. L. C., Sera, F., Stafoggia, M., Masselot, P., Mistry, M., Rajagopalan, S., Quint, J. K., Ng, C. F. S., Madaniyazi, L., et al. (2024) · Epidemiology · doi:10.1097/ede.0000000000001796 · Cited by 13
Associations of physical frailty with incidence and mortality of overall and site-specific cancers: A prospective cohort study from UK biobank
Liu, F., Peng, Y., Wang, P., Qiao, Y., Si, C., Wang, X., Zhang, M., Chen, L., & Song, F. (2023) · Preventive Medicine · doi:10.1016/j.ypmed.2023.107742 · Cited by 12
Berkson’s bias in biobank sampling in a specialised mental health care setting: a comparative cross-sectional study
Laliberté, V., Giguère, C., Potvin, S., & LESAGE, A. D. (2020) · BMJ Open · doi:10.1136/bmjopen-2019-035088 · Cited by 12
Patterns of Multimorbidity and Risk of Severe SARS-CoV-2 Infection: an observational study in the U.KPreprint
Chudasama, Y., Zaccardi, F., Gillies, C. L., Razieh, C., Yates, T. E., Kloecker, D. E., Rowlands, A. V., Davies, M. J., Islam, N., Seidu, S., et al. (2020) · medRxiv · doi:10.1101/2020.10.21.20216721 · Cited by 12
Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and incident dementia: The UK Biobank study
Beydoun, H. A., Beydoun, M. A., Hooten, N. N., Weiss, J., Li, Z., Georgescu, M. F., Vieytes, C. A. M., Meirelles, O., Launer, L. J., Evans, M. K., et al. (2024) · GeroScience · doi:10.1007/s11357-024-01202-3 · Cited by 11
Participation bias in the estimation of heritability and genetic correlation
Song, S., Benónísdóttir, S., Liu, J. S., & Kong, A. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2425530122 · Cited by 10
Gene–Environment Analyses in a UK Biobank Skin Cancer Cohort Identifies Important SNPs in DNA Repair Genes That May Help Prognosticate Disease Risk
Jeremian, R., Xie, P., Fotovati, M., Lefrançois, P., & Litvinov, I. V. (2023) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-23-0545 · Cited by 10
Using the global randomization test as a Mendelian randomization falsification test for the exclusion restriction assumption
Millard, L. A. C., Smith, G. D., & Tilling, K. M. (2024) · European Journal of Epidemiology · doi:10.1007/s10654-024-01097-6 · Cited by 9
Perinatal photoperiod associations with diabetes and chronotype prevalence in a cross-sectional study of the UK Biobank
Lewis, P., Morfeld, P., Mohren, J., Hellmich, M., & Erren, T. C. (2021) · Chronobiology International · doi:10.1080/07420528.2020.1849254 · Cited by 8
Prevalence and cardiometabolic correlates of ketohexokinase gene variants among UK Biobank participants
Johnston, J. A., Nelson, D. R., Bhatnagar, P., Curtis, S. E., Chen, Y., & MacKrell, J. G. (2021) · PLoS ONE · doi:10.1371/journal.pone.0247683 · Cited by 8
Dietary flavonoid intake and risk of hormone-related cancers: A population-based prospective cohort study
Liu, F., Xu, J., Wang, X., Peng, Y., Wang, P., Si, C., Gong, J., Zhou, H., Zhang, M., Chen, L., et al. (2024) · Phytomedicine · doi:10.1016/j.phymed.2024.155950 · Cited by 7
Anxiety and Depression in People with Eczema or Psoriasis: A Comparison of Associations in UK Biobank and Linked Primary Care Data
Matthewman, J., Mansfield, K. E., Hayes, J., Adesanya, E., Smith, C. H., Roberts, A., Langan, S., & Henderson, A. D. (2023) · Clinical Epidemiology · doi:10.2147/clep.s417176 · Cited by 9
Mediation of the association between education and dementia by occupational complexity, income, health behaviours and health outcomes
Taylor, K., Marston, L., & Mukadam, N. (2025) · BMC Psychiatry · doi:10.1186/s12888-025-06619-4 · Cited by 6
Detecting Genotype-Population Interaction Effects by Ancestry Principal Components
Yu, C., Ni, G., van der Werf, J. H. J., & Lee, S. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00379 · Cited by 4
Reference values for intake of six types of soluble and insoluble fibre in healthy UK inhabitants based on the UK Biobank data
Shevlyakov, A., Nikogosov, D. A., Stewart, L.-A., & Toribio-Mateas, M. A. (2021) · Public Health Nutrition · doi:10.1017/s1368980021002524 · Cited by 5
Polygenic risk for termination of the ‘healthspan’ and its interactions with lifestyle factors: A prospective cohort study based on 288,359 participants
Liang, S., Wang, N., Wang, Y., Wang, M., Zhao, X., Yang, M., Yi, H., Zhu, M., Wang, C., Hang, D., et al. (2023) · Maturitas · doi:10.1016/j.maturitas.2023.107786 · Cited by 6
Role of individual deprivation and community-level deprivation on suicidal behaviors: Insights from the UK Biobank study
Kim, K., Lee, D. W., & Jung, S. J. (2024) · SSM - Population Health · doi:10.1016/j.ssmph.2024.101654 · Cited by 5
Identification of novel genetic susceptibility loci for calcium-containing kidney stone disease by genome-wide association study and polygenic risk score in a Taiwanese population
Chen, W., Chen, Y.-C., Chen, Y., Liu, T., Tsai, C., & Tsai, F. (2024) · Urolithiasis · doi:10.1007/s00240-024-01577-0 · Cited by 5
Postreproductive disability-free life expectancy – An increasing gender gap
Cusack, J., & Mander, T. (2021) · Post Reproductive Health · doi:10.1177/20533691211019017 · Cited by 5
Modifiable risk factors and excess mortality in depression: Data from the UK Biobank
Barros, V. B., & Filho, A. D. P. C. (2024) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2024.08.010 · Cited by 5
Creating a Surgical Biobank: The Hershey Medical Center Experience
Mankarious, M. M., Connelly, T. M., Harris, L., Deiling, S. M., Yochum, G. S., & Koltun, W. A. (2023) · Diseases of the Colon & Rectum · doi:10.1097/dcr.0000000000002944 · Cited by 5
Searching for the causal effects of BMI in over 300 000 individuals, using Mendelian randomizationPreprint
Millard, L. A. C., Davies, N. M., Tilling, K. M., Gaunt, T. R., & Smith, G. D. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/236182 · Cited by 4
Association of Time-of-Day Physical Activity With Incident Cardiovascular Disease: The UK Biobank Study
Ma, T., Sirard, J. R., & Jennings, L. (2023) · Journal of Physical Activity and Health · doi:10.1123/jpah.2022-0505 · Cited by 3
Ethical considerations of use of hold-out sets in clinical prediction model management
Chislett, L., Aslett, L. J. M., Davies, A. R., Vallejos, C. A., & Liley, J. (2024) · AI and Ethics · doi:10.1007/s43681-024-00561-z · Cited by 3
Cross-sectional relationships of circadian misalignment and rest-activity rhythms with occupational attainment in UK Biobank participants
Walker, B., Gibson, J., Jackson, C., Blaikley, J., Jones, S. E., Rutter, M. K., & Sutton, M. (2024) · Chronobiology International · doi:10.1080/07420528.2024.2441192 · Cited by 5
Screening for diabetes mellitus in the US population using neural network-based modeling and complex survey designs
Matabuena, M., Vidal, J. C., Ghosal, R., & Onnela, J.-P. “. (2026) · Statistical Methods in Medical Research · doi:10.1177/09622802261442893 · Cited by 3
Genetic architecture of DCC and influence on psychological, psychiatric and cardiometabolic traits in multiple ancestry groups in UK Biobank
Forsyth, L., Aman, A., Cullen, B., Graham, N., Lyall, D. M., Lyall, L. M., Pell, J. P., Ward, J., Smıth, D. J., & Strawbridge, R. J. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.07.052 · Cited by 2
On Biases in a UK Biobank-Based Retinal Image Classification Model
Alloula, A., Mustafa, R., McGowan, D. R., & Papież, B. W. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72787-0_14 · Cited by 3
The Trilogy of GxE : Conceptualization, Operationalization, and Application
Grigorenko, E. L., Bick, J. R., Campbell, D. J., Lewine, G., Abrams, J., Nguyen, V. T., & Chang, J. T. (2016) · Wiley eBooks · doi:10.1002/9781119125556.devpsy208 · Cited by 2

Authors: Swanson, J. M.
Affiliations: University of California, Irvine (US)
Corresponding author: Swanson, James M
Venue: The Lancet
Publisher: Elsevier BV
Published: 2012-07
Volume: 380
Issue: 9837
Pages: 110
ISSN: 0099-5355 (ISSN-L)
0140-6736
DOI: 10.1016/s0140-6736(12)61179-9
OpenAlex: W2019221205
Cited by: 130
References: 4
Citations by year: 2026: 9 · 2025: 7 · 2024: 22 · 2023: 18 · 2022: 17 · 2021: 14 · 2020: 11 · 2019: 11 · 2018: 6 · 2017: 6 · 2016: 5 · 2015: 2 · 2013: 2
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: The Lancet (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
Keywords: UK Biobank, selection bias, sample selection bias, response rate, comorbidities, spurious association, model misspecification, generalizability
MeSH terms: Chronic Disease, Female, Humans, Male, National Health Programs, Biological Specimen Banks, Databases as Topic, Translational Research, Biomedical

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

The UK Biobank and selection bias

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks