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Association Between Race and COVID-19 Outcomes Among 2.6 Million Children in England

Educational Objective
To investigate the association between race and childhood COVID-19 testing and hospital outcomes.
1 Credit CME
Key Points

Question  Is race associated with COVID-19 testing and hospital outcomes in children in England?

Findings  In this cohort study of 2 576 353 children (0-18 years of age) in England with COVID-19 disease, children who were Black, Asian, or of mixed race had lower proportions of SARS-CoV-2 tests and had higher positive results and COVID-19 hospitalizations compared with White children. These results held after key demographic factors and selected comorbidities were accounted for.

Meaning  These findings suggest that race may play an important role in childhood COVID-19 outcomes, which reinforces the continued need for a race-tailored focus on health system performance and targeted public health interventions.

Abstract

Importance  Although children mainly experience mild COVID-19 disease, hospitalization rates are increasing, with limited understanding of underlying factors. There is an established association between race and severe COVID-19 outcomes in adults in England; however, whether a similar association exists in children is unclear.

Objective  To investigate the association between race and childhood COVID-19 testing and hospital outcomes.

Design, Setting, Participants  In this cohort study, children (0-18 years of age) from participating family practices in England were identified in the QResearch database between January 24 and November 30, 2020. The QResearch database has individually linked patients with national SARS-CoV-2 testing, hospital admission, and mortality data.

Exposures  The main characteristic of interest is self-reported race. Other exposures were age, sex, deprivation level, geographic region, household size, and comorbidities (asthma; diabetes; and cardiac, neurologic, and hematologic conditions).

Main Outcomes and Measures  The primary outcome was hospital admission with confirmed COVID-19. Secondary outcomes were SARS-CoV-2–positive test result and any hospital attendance with confirmed COVID-19 and intensive care admission.

Results  Of 2 576 353 children (mean [SD] age, 9.23 [5.24] years; 48.8% female), 410 726 (15.9%) were tested for SARS-CoV-2 and 26 322 (6.4%) tested positive. A total of 1853 children (0.07%) with confirmed COVID-19 attended hospital, 343 (0.01%) were admitted to the hospital, and 73 (0.002%) required intensive care. Testing varied across race. White children had the highest proportion of SARS-CoV-2 tests (223 701/1 311 041 [17.1%]), whereas Asian children (33 213/243 545 [13.6%]), Black children (7727/93 620 [8.3%]), and children of mixed or other races (18 971/147 529 [12.9%]) had lower proportions. Compared with White children, Asian children were more likely to have COVID-19 hospital admissions (adjusted odds ratio [OR], 1.62; 95% CI, 1.12-2.36), whereas Black children (adjusted OR, 1.44; 95% CI, 0.90-2.31) and children of mixed or other races (adjusted OR, 1.40; 95% CI, 0.93-2.10) had comparable hospital admissions. Asian children were more likely to be admitted to intensive care (adjusted OR, 2.11; 95% CI, 1.07-4.14), and Black children (adjusted OR, 2.31; 95% CI, 1.08-4.94) and children of mixed or other races (adjusted OR, 2.14; 95% CI, 1.25-3.65) had longer hospital admissions (≥36 hours).

Conclusions and Relevance  In this large population-based study exploring the association between race and childhood COVID-19 testing and hospital outcomes, several race-specific disparities were observed in severe COVID-19 outcomes. However, ascertainment bias and residual confounding in this cohort study should be considered before drawing any further conclusions. Overall, findings of this study have important public health implications internationally.

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Article Information

Accepted for Publication: April 14, 2021.

Published Online: June 21, 2021. doi:10.1001/jamapediatrics.2021.1685

Corresponding Author: Defne Saatci, MD, Primary Care Epidemiology, Nuffield Department of Primary Care Health Sciences, University of Oxford, Woodstock Road, Oxford OX2 6GG, United Kingdom (defne.saatci@phc.ox.ac.uk).

Author Contributions: Drs Saatci and Hippisley-Cox had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Saatci, Garriga, Clift, Tan, Harnden, Griffin, Khunti, Dambha-Miller, Hippisley-Cox.

Acquisition, analysis, or interpretation of data: Saatci, Ranger, Garriga, Clift, Zaccardi, Tan, Patone, Coupland, Griffin, Dambha-Miller, Hippisley-Cox.

Drafting of the manuscript: Saatci, Ranger, Garriga, Hippisley-Cox.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Saatci, Ranger, Garriga, Clift, Patone, Coupland, Hippisley-Cox.

Obtained funding: Griffin, Khunti, Dambha-Miller, Hippisley-Cox.

Administrative, technical, or material support: Saatci, Ranger, Zaccardi, Tan, Hippisley-Cox.

Supervision: Ranger, Harnden, Griffin, Hippisley-Cox.

Conflict of Interest Disclosures: Dr Tan reported receiving personal fees from AstraZeneca and Duke-NUS outside the submitted work. Dr Griffin reported receiving grants from the Medical Research Council during the conduct of the study. Dr Khunti reported serving as chair of the Ethnicity Subgroup and as a member of the Scientific Advisory Group for Emergencies. Dr Hippisley-Cox reported receiving grants from the Medical Research Council, Wellcome Trust, Health Data Research UK, Cancer Research UK, the John Fell Fund, and the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre; receiving nonfinancial support from EMIS Health during the conduct of the study; and serving as director of the QResearch database, a not-for-profit collaboration between EMIS Health (commercial supplier of GP Systems) and Oxford University. No other disclosures were reported.

Funding/Support: Dr Khunti is supported by the NIHR Applied Research Collaboration East Midlands and the NIHR Leicester Biomedical Research Centre. Dr Griffin is supported by the Medical Research Council. The University of Cambridge has received salary support in respect of Dr Griffin from the National Health Service (NHS) in the East of England through the Clinical Academic Reserve.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: EMIS Practices contributed to QResearch, and EMIS Health, the University of Nottingham, and the University of Oxford provided expertise in establishing, developing, or supporting the QResearch database.

Additional Information: This project involves data derived from patient-level information collected by the NHS as part of the care and support of patients with cancer. The COVID-19 test data are collated, maintained, and quality assured by Public Health England (PHE). Access to the data was facilitated by the PHE Office for Data Release. The Hospital Episode Statistics and mortality data used in this analysis are reused with permission of NHS Digital, which retains copyright of those data. NHS Digital and PHE bear no responsibility for the analysis or interpretation of the data.

References
1.
Centers for Disease Control and Prevention. CDC COVID Data Tracker. Accessed December 20, 2020. https://covid.cdc.gov/covid-data-tracker/#demographics
2.
European Centre for Disease Prevention and Control. COVID-19 in children and the role of school settings in COVID-19 transmission: first update. Accessed December 20, 2020. https://www.ecdc.europa.eu/en/publications-data/children-and-school-settings-covid-19-transmission
3.
Kim  L , Whitaker  M , O’Halloran  A ,  et al; COVID-NET Surveillance Team.  Hospitalization rates and characteristics of children aged <18 years hospitalized with laboratory-confirmed COVID-19—COVID-NET, 14 States, March 1-July 25, 2020.   MMWR Morb Mortal Wkly Rep. 2020;69(32):1081-1088. doi:10.15585/mmwr.mm6932e3 PubMedGoogle ScholarCrossref
4.
Swann  OV , Holden  KA , Turtle  L ,  et al; ISARIC4C Investigators.  Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study.   BMJ. 2020;370:m3249. doi:10.1136/bmj.m3249 PubMedGoogle Scholar
5.
Bailey  LC , Razzaghi  H , Burrows  EK ,  et al.  Assessment of 135794 pediatric patients tested for severe acute respiratory syndrome coronavirus 2 across the United States.   JAMA Pediatr. 2021;175(2):176-184. doi:10.1001/jamapediatrics.2020.5052PubMedGoogle Scholar
6.
Parri  N , Lenge  M , Buonsenso  D ; Coronavirus Infection in Pediatric Emergency Departments (CONFIDENCE) Research Group.  Children with Covid-19 in pediatric emergency departments in Italy.   N Engl J Med. 2020;383(2):187-190. doi:10.1056/NEJMc2007617 PubMedGoogle ScholarCrossref
7.
Garazzino  S , Montagnani  C , Donà  D ,  et al; Italian SITIP-SIP Pediatric Infection Study Group; Italian SITIP-SIP SARS-CoV-2 Paediatric Infection Study Group.  Multicentre Italian study of SARS-CoV-2 infection in children and adolescents, preliminary data as of 10 April 2020.   Euro Surveill. 2020;25(18):2000600. doi:10.2807/1560-7917.ES.2020.25.18.2000600 PubMedGoogle Scholar
8.
Dong  Y , Mo  X , Hu  Y ,  et al.  Epidemiology of COVID-19 among children in China.   Pediatrics. 2020;145(6):e20200702. doi:10.1542/peds.2020-0702 PubMedGoogle Scholar
9.
Rankin  DA , Talj  R , Howard  LM , Halasa  NB .  Epidemiologic trends and characteristics of SARS-CoV-2 infections among children in the United States.   Curr Opin Pediatr. 2021;33(1):114-121. doi:10.1097/MOP.0000000000000971PubMedGoogle Scholar
10.
Loomba  RS , Villarreal  EG , Farias  JS , Bronicki  RA , Flores  S .  Pediatric intensive care unit admissions for COVID-19: insights using state-level data.   Int J Pediatr. 2020;2020:9680905. doi:10.1155/2020/9680905 PubMedGoogle Scholar
11.
Götzinger  F , Santiago-García  B , Noguera-Julián  A ,  et al; ptbnet COVID-19 Study Group.  COVID-19 in children and adolescents in Europe: a multinational, multicentre cohort study.   Lancet Child Adolesc Health. 2020;4(9):653-661. doi:10.1016/S2352-4642(20)30177-2 PubMedGoogle ScholarCrossref
12.
Ludvigsson  JF , Engerstrom  L , Nordenhall  C , Larsson  E .  Open schools, Covid-19, and child and teacher morbidity in Sweden.   N Engl J Med. 2021;384(7):669-671. doi:10.1056/NEJMc2026670 Google Scholar
13.
Williamson  EJ , Walker  AJ , Bhaskaran  K ,  et al.  Factors associated with COVID-19-related death using OpenSAFELY.   Nature. 2020;584(7821):430-436. doi:10.1038/s41586-020-2521-4 PubMedGoogle ScholarCrossref
14.
Office for National Statistics. Coronavirus (COVID-19) related deaths by ethnic group, England and Wales. Published 2020. Accessed December 12, 2020. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/articles/coronavirusrelateddeathsbyethnicgroupenglandandwales/2march2020to10april2020
15.
Hippisley-Cox  J , Young  D , Coupland  C ,  et al.  Risk of severe COVID-19 disease with ACE inhibitors and angiotensin receptor blockers: cohort study including 8.3 million people.   Heart. 2020;106(19):1503-1511. doi:10.1136/heartjnl-2020-317393 PubMedGoogle ScholarCrossref
16.
Clift  AK , Coupland  CAC , Keogh  RH ,  et al.  Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study.   BMJ. 2020;371:m3731. doi:10.1136/bmj.m3731 PubMedGoogle Scholar
17.
Sze  S , Pan  D , Nevill  CR ,  et al.  Ethnicity and clinical outcomes in COVID-19: a systematic review and meta-analysis.   EClinicalMedicine. 2020;29:100630. doi:10.1016/j.eclinm.2020.100630 PubMedGoogle Scholar
18.
Harman  K , Verma  A , Cook  J ,  et al.  Ethnicity and COVID-19 in children with comorbidities.   Lancet Child Adolesc Health. 2020;4(7):e24-e25. doi:10.1016/S2352-4642(20)30167-X PubMedGoogle ScholarCrossref
19.
QResearch. QResearch. Accessed December 20, 2020. https://www.qresearch.org/
20.
EMIS Health. Products. Accessed December 20, 2020. https://www.emishealth.com/products/emis-web/
21.
Hippisley-Cox  J , Coupland  C , Robson  J , Brindle  P .  Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database.   BMJ. 2010;341:c6624. doi:10.1136/bmj.c6624 PubMedGoogle ScholarCrossref
22.
Vinogradova  Y , Coupland  C , Hippisley-Cox  J .  Use of hormone replacement therapy and risk of breast cancer: nested case-control studies using the QResearch and CPRD databases.   BMJ. 2020;371:m3873. doi:10.1136/bmj.m3873 PubMedGoogle Scholar
23.
Clift  AK , Coupland  CAC , Keogh  RH , Hemingway  H , Hippisley-Cox  J .  COVID-19 mortality risk in Down syndrome: results from a cohort study of 8 million adults.   Ann Intern Med. 2021;174(4):572-576. doi:10.7326/M20-4986PubMedGoogle Scholar
24.
Jack  RH , Hollis  C , Coupland  C ,  et al.  Incidence and prevalence of primary care antidepressant prescribing in children and young people in England, 1998-2017: a population-based cohort study.   PLoS Med. 2020;17(7):e1003215. doi:10.1371/journal.pmed.1003215 PubMedGoogle Scholar
25.
von Elm  E , Altman  DG , Egger  M , Pocock  SJ , Gøtzsche  PC , Vandenbroucke  JP ; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   Lancet. 2007;370(9596):1453-1457. doi:10.1016/S0140-6736(07)61602-X PubMedGoogle ScholarCrossref
26.
Langan  SM , Schmidt  SA , Wing  K ,  et al.  The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE).   BMJ. 2018;363:k3532. doi:10.1136/bmj.k3532 PubMedGoogle Scholar
27.
NHS Digital. About NHS Digital. Accessed December 20, 2020. https://digital.nhs.uk/about-nhs-digital
28.
Office for National Statistics. Births, deaths, and marriages. Accessed December 28, 2020. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages
29.
UK Department of Health and Social Care. Sources of COVID-19 surveillance systems. Accessed December 22, 2020. https://www.gov.uk/government/publications/national-covid-19-surveillance-reports/sources-of-covid-19-systems
30.
UK Department of Health and Social Care. COVID-19 testing data: methodology note. Accessed December 28, 2020. https://www.gov.uk/government/publications/coronavirus-covid-19-testing-data-methodology/covid-19-testing-data-methodology-note
31.
University of Nottingham. Accessed March 7, 2021. http://eprints.nottingham.ac.uk/3153/
33.
Heys  M , Rajan  M , Blair  M .  Length of paediatric inpatient stay, socio-economic status and hospital configuration: a retrospective cohort study.   BMC Health Serv Res. 2017;17(1):274. doi:10.1186/s12913-017-2171-x PubMedGoogle ScholarCrossref
34.
Nuffield Trust and The Health Foundation. Quality Watch Report. Focus on: emergency hospital care for children and young people. Accessed December 27, 2020. https://www.nuffieldtrust.org.uk/qualitywatch
36.
Townsend P, Davidson N. Inequalities in Health: The Black Report. Dept of Health and Social Security; 1982.
37.
Netuveli  G , Hurwitz  B , Levy  M ,  et al.  Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis.   Lancet. 2005;365(9456):312-317. doi:10.1016/S0140-6736(05)17785-X PubMedGoogle ScholarCrossref
38.
Oldroyd  J , Banerjee  M , Heald  A , Cruickshank  K .  Diabetes and ethnic minorities.   Postgrad Med J. 2005;81(958):486-490. doi:10.1136/pgmj.2004.029124 PubMedGoogle ScholarCrossref
40.
Knowles  RL , Ridout  D , Crowe  S ,  et al.  Ethnic and socioeconomic variation in incidence of congenital heart defects.   Arch Dis Child. 2017;102(6):496-502. doi:10.1136/archdischild-2016-311143 PubMedGoogle ScholarCrossref
41.
Sinha  G , Corry  P , Subesinghe  D , Wild  J , Levene  MI .  Prevalence and type of cerebral palsy in a British ethnic community: the role of consanguinity.   Dev Med Child Neurol. 1997;39(4):259-262. doi:10.1111/j.1469-8749.1997.tb07422.x PubMedGoogle ScholarCrossref
42.
Hickman  M , Modell  B , Greengross  P ,  et al.  Mapping the prevalence of sickle cell and beta thalassaemia in England: estimating and validating ethnic-specific rates.   Br J Haematol. 1999;104(4):860-867. doi:10.1046/j.1365-2141.1999.01275.x PubMedGoogle ScholarCrossref
43.
StataCorp. Stata Statistical Software. Release 16. StataCorp; 2019.
45.
Millett  GA , Jones  AT , Benkeser  D ,  et al.  Assessing differential impacts of COVID-19 on black communities.   Ann Epidemiol. 2020;47:37-44. doi:10.1016/j.annepidem.2020.05.003 PubMedGoogle ScholarCrossref
46.
Rentsch CT, Kidwai-Khan F, Tate JP, et al. Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: a nationwide cohort study. PLoS Med. 2020;17(9):e1003379. doi:10.1371/journal.pmed.1003379
47.
Marlow  LA , Waller  J , Wardle  J .  Barriers to cervical cancer screening among ethnic minority women: a qualitative study.   J Fam Plann Reprod Health Care. 2015;41(4):248-254. doi:10.1136/jfprhc-2014-101082 PubMedGoogle ScholarCrossref
48.
Alvarez-del Arco  D , Monge  S , Azcoaga  A ,  et al.  HIV testing and counselling for migrant populations living in high-income countries: a systematic review.   Eur J Public Health. 2013;23(6):1039-1045. doi:10.1093/eurpub/cks130 PubMedGoogle ScholarCrossref
49.
Fisher  KA , Bloomstone  SJ , Walder  J , Crawford  S , Fouayzi  H , Mazor  KM .  Attitudes toward a potential SARS-CoV-2 vaccine: a survey of U.S. adults.   Ann Intern Med. 2020;173(12):964-973. doi:10.7326/M20-3569 PubMedGoogle ScholarCrossref
50.
Royal Society for Public Health: New poll finds BAME groups less likely to want COVID vaccine. Accessed December 27, 2020. https://www.rsph.org.uk/about-us/news/new-poll-finds-bame-groups-less-likely-to-want-covid-vaccine.html
51.
Dodds  C , Fakoya  I .  Covid-19: ensuring equality of access to testing for ethnic minorities.   BMJ. 2020;369:m2122. doi:10.1136/bmj.m2122 PubMedGoogle Scholar
52.
Mathur R, Rentsch CT, Morton CE, et al. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet. 2021;397(10286):1711-1724. doi:10.1016/S0140-6736(21)00634-6
53.
Rozenfeld Y, Beam J, Maier H, et al. A model of disparities: risk factors associated with COVID-19 infection. Int J Equity Health. 2020;19(1):126. doi:10.1186/s12939-020-01242-z
54.
Lee  EH , Kepler  KL , Geevarughese  A ,  et al.  Race/Ethnicity among children with COVID-19-associated multisystem inflammatory syndrome.   JAMA Netw Open. 2020;3(11):e2030280. doi:10.1001/jamanetworkopen.2020.30280 PubMedGoogle Scholar
55.
Godfred-Cato  S , Bryant  B , Leung  J ,  et al; California MIS-C Response Team.  COVID-19-associated multisystem inflammatory syndrome in children: United States, March-July 2020.   MMWR Morb Mortal Wkly Rep. 2020;69(32):1074-1080. doi:10.15585/mmwr.mm6932e2 PubMedGoogle ScholarCrossref
56.
Iwane  MK , Edwards  KM , Szilagyi  PG ,  et al; New Vaccine Surveillance Network.  Population-based surveillance for hospitalizations associated with respiratory syncytial virus, influenza virus, and parainfluenza viruses among young children.   Pediatrics. 2004;113(6):1758-1764. doi:10.1542/peds.113.6.1758 PubMedGoogle ScholarCrossref
57.
Swann OV, Holden KA, Turtle L, et al. Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study. BMJ. 2020;370:m3249. doi:10.1136/bmj.m3249
58.
Seidu  S , Gillies  C , Zaccardi  F ,  et al.  The impact of obesity on severe disease and mortality in people with SARS-CoV-2: a systematic review and meta-analysis.   Endocrinol Diabetes Metab. 2020;e00176. doi:10.1002/edm2.176 PubMedGoogle Scholar
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