Modifiable and non-modifiable risk factors for COVID-19, and comparison to risk factors for influenza and pneumonia: results from a UK Biobank prospective cohort study
Frederick K Ho, Carlos A Celis-Morales, Stuart R Gray, S Vittal Katikireddi, Claire L Niedzwiedz, Claire Hastie, Lyn D Ferguson, Colin Berry, Daniel F Mackay, Jason Mr Gill, Jill P Pell, Naveed Sattar, Dr Paul Welsh
BMJ Open, doi:10.1136/bmjopen-2020-040402
Objectives We aimed to investigate demographic, lifestyle, socioeconomic and clinical risk factors for COVID-19, and compared them to risk factors for pneumonia and influenza in UK Biobank. Design Cohort study. Setting UK Biobank. Participants 49-83 year olds (in 2020) from a general population study. Main outcome measures Confirmed COVID-19 infection (positive SARS-CoV-2 test). Incident influenza and pneumonia were obtained from primary care data. Poisson regression was used to study the association of exposure variables with outcomes. Results Among 235 928 participants, 397 had confirmed COVID-19. After multivariable adjustment, modifiable risk factors were higher body mass index and higher glycated haemoglobin (HbA1C) (RR 1.28 and RR 1.14 per SD increase, respectively), smoking (RR 1.39), slow walking pace as a proxy for physical fitness (RR 1.53), and use of blood pressure medications as a proxy for hypertension (RR 1.33). Higher forced expiratory volume in 1 s (FEV1) and high-density lipoprotein (HDL) cholesterol were both associated with lower risk (RR 0.84 and RR 0.83 per SD increase, respectively). Non-modifiable risk factors included male sex (RR 1.72), black ethnicity (RR 2.00), socioeconomic deprivation (RR 1.17 per SD increase in Townsend Index), and high cystatin C (RR 1.13 per SD increase). The risk factors overlapped with pneumonia somewhat, less so for influenza. The associations with modifiable risk factors were generally stronger for COVID-19, than pneumonia or influenza. Conclusion These findings suggest that modification of lifestyle may help to reduce the risk of COVID-19 and could be a useful adjunct to other interventions, such as social distancing and shielding of high risk.
Ethics approval UK Biobank received ethical approval from the North West Multicentre Research Ethics Committee (REC reference: 11/NW/03820). All participants gave written informed consent before enrolment in the study, which was conducted in accordance with the principles of the Declaration of Helsinki. Direct dissemination of the results to participants is not possible/applicable. This study was performed under UK Biobank application number 7155. Provenance and peer review Not commissioned; externally peer reviewed. Data availability statement Data may be obtained from a third party and are not publicly available. UK Biobank data can be requested by bona fide researchers for approved projects, including replication, through https://www. ukbiobank. ac. uk/ Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Open access This..
References
Almirall, Serra-Prat, Bolíbar, Risk factors for communityacquired pneumonia in adults: a systematic review of observational studies, Respiration,
doi:10.1159/000479089Armstrong, Rudkin, Allen, Dynamic linkage of covid-19 test results between public health england's second generation surveillance system and uk biobank, Microb Genomics,
doi:10.1099/mgen.0.000397Banerjee, Pasea, Harris, Estimating excess 1-year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults,
doi:10.1101/2020.03.22.20040287Batty, Deary, Luciano, Psychosocial factors and hospitalisations for COVID-19: prospective cohort study based on a community sample, Brain Behav Immun,
doi:10.1016/j.bbi.2020.06.021Beun, Kusadasi, Sikma, Thromboembolic events and apparent heparin resistance in patients infected with SARS-CoV-2
Bradbury, Guo, Cairns, Association between physical activity and body fat percentage, with adjustment for BMI: a large cross-sectional analysis of UK Biobank, BMJ Open,
doi:10.1136/bmjopen-2016-011843Celis-Morales, Gray, Petermann, Walking PACE is associated with lower risk of all-cause and cause-specific mortality, Med Sci Sports Exerc,
doi:10.1249/MSS.0000000000001795Celis-Morales, Welsh, Lyall, Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants, BMJ,
doi:10.1136/bmj.k1651Drummond, Dickinson, Fry, Bed rest impairs skeletal muscle amino acid transporter expression, mTORC1 signaling, and protein synthesis in response to essential amino acids in older adults, Am J Physiol Endocrinol Metab,
doi:10.1152/ajpendo.00603.2011Elliott, Peakman, Biobank, The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine, Int J Epidemiol,
doi:10.1093/ije/dym276Fk, Celis-Morales, Gray, Modifiable and nonmodifiable risk factors for COVID-19: results from UK Biobank, MedRxiv
Fry, Littlejohns, Sudlow, Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population, Am J Epidemiol,
doi:10.1093/aje/kwx246Green, Popham, Interpreting mutual adjustment for multiple indicators of socioeconomic position without committing mutual adjustment fallacies, BMC Public Health,
doi:10.1186/s12889-018-6364-yHamer, Gale, Kivimäki, Overweight, obesity, and risk of hospitalization for COVID-19: a community-based cohort study of adults in the United Kingdom, Proc Natl Acad Sci,
doi:10.1073/pnas.2011086117Klovaite, Benn, Nordestgaard, Obesity as a causal risk factor for deep venous thrombosis: a Mendelian randomization study, J Intern Med,
doi:10.1111/joim.12299Lighter, Phillips, Hochman, Obesity in patients younger than 60 years is a risk factor for Covid-19 hospital admission, Clin Infect Dis,
doi:10.1093/cid/ciaa415Packard, Bezlyak, Mclean, Early life socioeconomic adversity is associated in adult life with chronic inflammation, carotid atherosclerosis, poorer lung function and decreased cognitive performance: a cross-sectional, population-based study, BMC Public Health,
doi:10.1186/1471-2458-11-42Panigada, Bottino, Tagliabue, Hypercoagulability of COVID-19 patients in intensive care unit. A report of thromboelastography findings and other parameters of hemostasis, J Thromb Haemost,
doi:10.1111/jth.14850Parsons, Manor, Power, Physical activity and change in body mass index from adolescence to mid-adulthood in the 1958 British cohort, Int J Epidemiol,
doi:10.1093/ije/dyi291Petrilli, Cm, Jones, Yang, Factors associated with hospitalization and critical illness among 4,103 patients with COVID-19 disease
Razieh, Zaccardi, Davies, Body mass index and the risk of COVID-19 across ethnic groups: analysis of UK Biobank, Diabetes, Obes. Metab,
doi:10.1111/dom.14125Richardson, Hirsch, Narasimhan, Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area, JAMA,
doi:10.1001/jama.2020.6775Sattar, Ho, Gill, BMI and future risk for COVID-19 infection and death across sex, age and ethnicity: preliminary findings from UK Biobank, Diabetes Metab Syndr,
doi:10.1016/j.dsx.2020.06.060Simonnet, Chetboun, Poissy, High prevalence of obesity in severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation, Obesity,
doi:10.1002/oby.22831Sudlow, Gallacher, Allen, UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age, PLoS Med,
doi:10.1371/journal.pmed.1001779Timpson, Nordestgaard, Harbord, C-Reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization, Int J Obes,
doi:10.1038/ijo.2010.137Tu, Tu, Gao, The epidemiological and clinical features of COVID-19 and lessons from this global infectious public health event, J
Welsh, Polisecki, Robertson, Unraveling the directional link between adiposity and inflammation: a bidirectional Mendelian randomization approach, J Clin Endocrinol Metab,
doi:10.1210/jc.2009-1064Woolford, Angelo, Curtis, COVID-19 and associations with frailty and multimorbidity: a prospective analysis of UK Biobank participants, Aging Clin Exp Res,
doi:10.1007/s40520-020-01653-6Wu, Mcgoogan, Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases from the Chinese Center for Disease Control and Prevention, JAMA,
doi:10.1001/jama.2020.2648Zhao, Zhang, Li, Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis
Zhou, Yu, Du, Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study, Lancet,
doi:10.1016/S0140-6736(20)30566-3Zhu, Hasegawa, Ma, Obesity & genetic predisposition with COVID-19, Metabolism
Zou, A modified poisson regression approach to prospective studies with binary data, Am J Epidemiol,
doi:10.1093/aje/kwh090
