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Hajiebrahimi M, Shihan H, Bratt O, Li H, Nyberg F, Wettermark B. Sociodemographic characteristics and health status of women with breast cancer and COVID 19 diagnosis by menopausal status a cross sectional study. Sci Rep 2025; 15:2648. [PMID: 39837931 PMCID: PMC11751173 DOI: 10.1038/s41598-025-86710-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 01/13/2025] [Indexed: 01/23/2025] Open
Abstract
The goal of this work is to investigate the sociodemographic characteristics and health status of women with breast cancer (BC) in association with COVID-19 by menopausal status. In a Swedish register-based cross-sectional study, we compared women with BC and with or without a positive COVID-19 test, stratified by menopausal status (age ≥ 51 years). Socioeconomic characteristics and health status (represented by diagnoses registered in 5 years- and prescription dispensed in 2 years preceding Jan 2020) were considered in association with COVID-19 diagnosis. The study population included 38,523 women with BC. Median age at BC diagnosis was 45 years (IQR = 40-48) for premenopausal- and 67 (IQR = 60-73) for postmenopausal BC. A logistic regression model was used and found the significant covariate effects (adjusted odds ratios, ORs) for a positive COVID-19 test among women with premenopausal BC to be being born outside of Europe: 1.29, (1.13-1.46), being married: 1.23, (1.12-1.36), being unemployed 1.92 (1.59-2.30), having upper secondary school education 1.25 (1.01-1.54), having > 15 outpatient visits: 1.31, (1.07-1.61), and a history of being admitted to hospital 1-5 times: 1.12 (1.01-1.25). Corresponding significant covariate effects among women with postmenopausal BC were being born outside of Europe: 1.61 (1.41-1.83), being married: 1.12 (1.04-1.21), and being unemployed 1.54 (1.40-1.69). Postmenopausal women furthermore had more outpatient visits or hospital admissions before the pandemic in COVID-19 positive patients compared to patients without a COVID-19 positive test, e.g. 1.47 (1.26-1.71) for > 15 outpatient visits compared with no visit and 6.35 (3.33-12.11) for > 15 hospital admissions compared with no admission. Varied socioeconomical and clinical conditions were more frequent among patients with a positive COVID-19 test compared to patients without a positive test among women with BC in pre- or post-menopausal status. We conclude that some characteristics of women such as unemployment, country of birth or health status measured by number of prescribed drugs were more prevalent among women who developed COVID-19 compared to women without COVID-19 diagnosis and either of menopausal status of breast cancer.
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Affiliation(s)
- Mohammadhossein Hajiebrahimi
- Department of Pharmacy, Faculty of Pharmacy, Uppsala University, Uppsala, Sweden.
- Biomedicinskt Centrum BMC, Husargatan 3, 752 37, Uppsala, Sweden.
| | - Hussam Shihan
- Clincal Studies Department, University Hospital, Linköping, Region Östergötland, Sweden
| | - Ola Bratt
- Department of Urology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Huiqi Li
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Björn Wettermark
- Department of Pharmacy, Faculty of Pharmacy, Uppsala University, Uppsala, Sweden
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Tan YY, Chang WH, Katsoulis M, Denaxas S, King KC, Cox MP, Davie C, Balloux F, Lai AG. Impact of the COVID-19 pandemic on health-care use among patients with cancer in England, UK: a comprehensive phase-by-phase time-series analysis across attendance types for 38 cancers. Lancet Digit Health 2024; 6:e691-e704. [PMID: 39332853 DOI: 10.1016/s2589-7500(24)00152-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 03/15/2024] [Accepted: 07/07/2024] [Indexed: 09/29/2024]
Abstract
BACKGROUND The COVID-19 pandemic resulted in the widespread disruption of cancer health provision services across the entirety of the cancer care pathway in the UK, from screening to treatment. The potential long-term health implications, including increased mortality for individuals who missed diagnoses or appointments, are concerning. However, the precise impact of lockdown policies on national cancer health service provision across diagnostic groups is understudied. We aimed to systematically evaluate changes in patterns of attendance for groups of individuals diagnosed with cancer, including the changes in attendance volume and consultation rates, stratified by both time-based exposures and by patient-based exposures and to better understand the impact of such changes on cancer-specific mortality. METHODS In this retrospective, cross-sectional, phase-by-phase time-series analysis, by using primary care records linked to hospitals and the death registry from Jan 1, 1998, to June 17, 2021, we conducted descriptive analyses to quantify attendance changes for groups stratified by patient-based exposures (Index of Multiple Deprivation, ethnicity, age, comorbidity count, practice region, diagnosis time, and cancer subtype) across different phases of the COVID-19 pandemic in England, UK. In this study, we defined the phases of the COVID-19 pandemic as: pre-pandemic period (Jan 1, 2018, to March 22, 2020), lockdown 1 (March 23 to June 21, 2020), minimal restrictions (June 22 to Sept 20, 2020), lockdown 2 (Sept 21, 2020, to Jan 3, 2021), lockdown 3 (Jan 4 to March 21, 2021), and lockdown restrictions lifted (March 22 to March 31, 2021). In the analyses we examined changes in both attendance volume and consultation rate. We further compared changes in attendance trends to cancer-specific mortality trends. Finally, we conducted an interrupted time-series analysis with the lockdown on March 23, 2020, as the intervention point using an autoregressive integrated moving average model. FINDINGS From 561 611 eligible individuals, 7 964 685 attendances were recorded. During the first lockdown, the median attendance volume decreased (-35·30% [IQR -36·10 to -34·25]) compared with the preceding pre-pandemic period, followed by a median change of 4·38% (2·66 to 5·15) during minimal restrictions. More drastic reductions in attendance volume were seen in the second (-48·71% [-49·54 to -48·26]) and third (-71·62% [-72·23 to -70·97]) lockdowns. These reductions were followed by a 4·48% (3·45 to 7·10) increase in attendance when lockdown restrictions were lifted. The median consultation rate change during the first lockdown was 31·32% (25·10 to 33·60), followed by a median change of -0·25% (-1·38 to 1·68) during minimal restrictions. The median consultation rate decreased in the second (-33·89% [-34·64 to -33·18]) and third (-4·98% [-5·71 to -4·00]) lockdowns, followed by a 416·16% increase (409·77 to 429·77) upon lifting of lockdown restrictions. Notably, across many weeks, a year-over-year decrease in weekly attendances corresponded with a year-over-year increase in cancer-specific mortality. Overall, the pandemic period revealed a statistically significant reduction in attendances for patients with cancer (lockdown 1 -24 070·19 attendances, p<0·0001; minimal restrictions -19 194·89 attendances, p<0·0001; lockdown 2 -31 311·28 attendances, p<0·0001; lockdown 3 -43 843·38 attendances, p<0·0001; and lockdown restrictions lifted -56 260·50 attendances, p<0·0001) compared with before the pandemic. INTERPRETATION The UK's COVID-19 pandemic lockdown affected cancer health service access negatively. Many groups of individuals with cancer had declines in attendance volume and consultation rate across the phases of the pandemic. A decrease in attendances might lead to delays in cancer diagnoses, treatment, and follow-up, putting such groups of individuals at higher risk of negative health outcomes, such as cancer-specific mortality. We discuss the factors potentially responsible for explaining changes in service provision trends and provide insight to help inform clinical follow-up for groups of individuals at risk, alongside potential future policy changes in the care of such patients. FUNDING Wellcome Trust, National Institute for Health Research University College London Hospitals Biomedical Research Centre, National Institute for Health Research Great Ormond Street Hospital Biomedical Research Centre, Academy of Medical Sciences, and the University College London Overseas Research Scholarship.
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Affiliation(s)
- Yen Yi Tan
- Institute of Health Informatics, University College London, London, UK.
| | - Wai Hoong Chang
- Institute of Health Informatics, University College London, London, UK
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
| | - Kayla C King
- Department of Biology, University of Oxford, Oxford, UK; Department of Zoology, University of British Columbia, Vancouver, BC, Canada; Department of Microbiology & Immunology, University of British Columbia, Vancouver, BC, Canada
| | - Murray P Cox
- Department of Statistics, University of Auckland, Auckland, New Zealand; School of Natural Sciences, Massey University, Auckland, New Zealand
| | | | | | - Alvina G Lai
- Institute of Health Informatics, University College London, London, UK
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Harris M, Hart J, Bhattacharya O, Russell FM. Risk factors for SARS-CoV-2 infection during the early stages of the COVID-19 pandemic: a systematic literature review. Front Public Health 2023; 11:1178167. [PMID: 37583888 PMCID: PMC10424847 DOI: 10.3389/fpubh.2023.1178167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 07/10/2023] [Indexed: 08/17/2023] Open
Abstract
Introduction Identifying SARS-CoV-2 infection risk factors allows targeted public health and social measures (PHSM). As new, more transmissible variants of concern (VoC) emerge, vaccination rates increase and PHSM are eased, it is important to understand any potential change to infection risk factors. The aim of this systematic literature review is to describe the risk factors for SARS-CoV-2 infection by VoC. Methods A literature search was performed in MEDLINE, PubMed and Embase databases on 5 May 2022. Eligibility included: observational studies published in English after 1 January 2020; any age group; the outcome of SARS-CoV-2 infection; and any potential risk factors investigated in the study. Results were synthesized into a narrative summary with respect to measures of association, by VoC. ROBINS-E tool was utilized for risk of bias assessment. Results Of 6,197 studies retrieved, 43 studies were included after screening. Common risk factors included older age, minority ethnic group, low socioeconomic status, male gender, increased household size, occupation/lower income level, inability to work from home, public transport use, and lower education level. Most studies were undertaken when the ancestral strain was predominant. Many studies had some selection bias due to testing criteria and limited laboratory capacity. Conclusion Understanding who is at risk enables the development of strategies that target priority groups at each of the different stages of a pandemic and helps inform vaccination strategies and other interventions which may also inform public health responses to future respiratory infection outbreaks. While it was not possible to determine changes to infection risk by recent VoC in this review, the risk factors identified will add to the overall understanding of the groups who are at greatest risk of infection in the early stages of a respiratory virus outbreak. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022330706, PROSPERO [CRD42022330706].
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Affiliation(s)
- Matthew Harris
- Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
- Asia-Pacific Health Group, Infection, Immunity and Global Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - John Hart
- Asia-Pacific Health Group, Infection, Immunity and Global Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
| | - Oashe Bhattacharya
- Asia-Pacific Health Group, Infection, Immunity and Global Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Fiona M. Russell
- Asia-Pacific Health Group, Infection, Immunity and Global Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Centre for International Child Health, Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
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Zhang W, Ge J, Qu Z, Wu W, Lei H, Pan H, Chen H. Evaluation for causal effects of socioeconomic traits on risk of female genital prolapse (FGP): a multivariable Mendelian randomization analysis. BMC Med Genomics 2023; 16:125. [PMID: 37296408 PMCID: PMC10251634 DOI: 10.1186/s12920-023-01560-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND Although observational studies have established some socioeconomic traits to be independent risk factors for pelvic organ prolapse (POP), they can not infer causality since they are easily biased by confounding factors and reverse causality. Moreover, it remains ambiguous which one or several of socioeconomic traits play predominant roles in the associations with POP risk. Mendelian randomization (MR) overcomes these biases and can even determine one or several socioeconomic traits predominantly accounting for the associations. OBJECTIVE We conducted a multivariable Mendelian randomization (MVMR) analysis to disentangle whether one or more of five categories of socioeconomic traits, "age at which full-time education completed (abbreviated as "EA")", "job involving heavy manual or physical work ("heavy work")", "average total household income before tax (income)", "Townsend deprivation index at recruitment (TDI)", and "leisure/social activities" exerted independent and predominant effects on POP risk. METHODS We first screened single-nucleotide polymorphisms (SNPs) as proxies for five individual socioeconomic traits and female genital prolapse (FGP, approximate surrogate for POP due to no GWASs for POP) to conduct Univariable Mendelian randomization (UVMR) analyses to estimate causal associations of five socioeconomic traits with FGP risk using IVW method as major analysis. Additionally, we conducted heterogeneity, pleiotropy, and sensitivity analysis to assess the robustness of our results. Then, we harvested a combination of SNPs as an integrated proxy for the five socioeconomic traits to perform a MVMR analysis based on IVW MVMR model. RESULTS UVMR analyses based on IVW method identified causal effect of EA (OR 0.759, 95%CI 0.629-0.916, p = 0.004), but denied that of the other five traits on FGP risk (all p > 0.05). Heterogeneity analyses, pleiotropy analyses, "leave-one-out" sensitivity analyses and MR-PRESSO adjustments did not detect heterogeneity, pleiotropic effects, or result fluctuation by outlying SNPs in the effect estimates of six socioeconomic traits on FGP risk (all p > 0.05). Further, MVMR analyses determined a predominant role of EA playing in the associations of socioeconomic traits with FGP risk based on both MVMR Model 1 (OR 0.842, 95%CI 0.744-0.953, p = 0.006) and Model 2 (OR 0.857, 95%CI 0.759-0.967, p = 0.012). CONCLUSION Our UVMR and MVMR analyses provided genetic evidence that one socioeconomic trait, lower educational attainment, is associated with risk of female genital prolapse, and even independently and predominantly accounts for the associations of socioeconomic traits with risk of female genital prolapse.
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Affiliation(s)
- Wei Zhang
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430023, Hubei Province, People's Republic of China
| | - Jing Ge
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430023, Hubei Province, People's Republic of China
| | - Zhaohui Qu
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430023, Hubei Province, People's Republic of China
| | - Wenjuan Wu
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430023, Hubei Province, People's Republic of China
| | - Hua Lei
- Department of Tuberculosis, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong, University of Science and Technology, Wuhan, 430023, Hubei Province, People's Republic of China
| | - Huiling Pan
- Department of Tuberculosis, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong, University of Science and Technology, Wuhan, 430023, Hubei Province, People's Republic of China
| | - Honggu Chen
- Department of Orthopedics, the Affiliated Hospital of Jiangsu University, Zhenjiang, 212000, Jiangsu Province, People's Republic of China.
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Estupiñán Fdez de Mesa M, Marcu A, Ream E, Whitaker KL. Relationship between intersectionality and cancer inequalities: a scoping review protocol. BMJ Open 2023; 13:e066637. [PMID: 36707112 PMCID: PMC9884887 DOI: 10.1136/bmjopen-2022-066637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 01/19/2023] [Indexed: 01/28/2023] Open
Abstract
INTRODUCTION Persistent inequalities in cancer care and cancer outcomes exist within and between countries. However, the evidence pertaining to the root causes driving cancer inequalities is mixed. This may be explained by the inadequate attention paid to experiences of patients with cancer living at the intersection of multiple social categories (eg, social class, ethnicity). This is supported by the intersectionality framework. This framework offers an alternative lens through which to analyse and understand how these interlocking systems of oppression uniquely shape the experiences of patients with cancer and drive inequalities. In this protocol, we outline a scoping review that will systematically map what is known about the relationship between intersectionality and inequalities in care experience and cancer outcomes of patients with cancer; and to determine how the intersectionality framework has been applied in studies across the cancer care pathway and across countries. METHODS AND ANALYSIS This study will be guided by Arksey and O'Malley's, and Levac et al's frameworks for scoping reviews. We will identify and map the evidence on cancer inequalities and intersectionality from 1989 to present date. Electronic databases (EMBASE, PsychINFO, CINAHL, Medline, Web of Science, ProQuest) and a systematic search strategy using a combination of keywords and Boolean operators AND/OR will be used to identify relevant studies. Screening of eligible papers and data extraction will be conducted by two independent reviewers, and disagreements resolved by discussion with the research team. We will use an iterative process to data charting using a piloted form. Findings will be collated into a narrative report. ETHICS AND DISSEMINATION Ethical approval is not required since data used are from publicly available secondary sources. Findings will be disseminated through peer-reviewed journals, conferences and stakeholder meetings. Further, findings will inform the next phases of a multistage research project aimed at understanding inequalities among patients with breast cancer.
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Affiliation(s)
| | - Afrodita Marcu
- School of Health Sciences, University of Surrey, Guildford, UK
| | - Emma Ream
- School of Health Sciences, University of Surrey, Guildford, UK
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Li Z, Wei Y, Zhu G, Wang M, Zhang L. Cancers and COVID-19 Risk: A Mendelian Randomization Study. Cancers (Basel) 2022; 14:cancers14092086. [PMID: 35565215 PMCID: PMC9099868 DOI: 10.3390/cancers14092086] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/08/2022] [Accepted: 04/13/2022] [Indexed: 02/06/2023] Open
Abstract
Simple Summary During the COVID-19 pandemic, cancer patients are regarded as a highly vulnerable population. Given the unavoidable bias and unmeasured confounders in observational studies, the causal effects of cancers on COVID-19 outcomes are largely unknown. In the study, we tried to evaluate the causal effects of cancers on COVID-19 outcomes using the Mendelian randomization (MR) approach. No strong evidence was observed to support a causal role of cancer in COVID-19 development. Previous observational correlations between cancers and COVID-19 outcomes were likely confounded. Large and well-conducted epidemiological studies are required to determine whether cancers causally contribute to increased risk of COVID-19. Abstract Observational studies have shown increased COVID-19 risk among cancer patients, but the causality has not been proven yet. Mendelian randomization analysis can use the genetic variants, independently of confounders, to obtain causal estimates which are considerably less confounded. We aimed to investigate the causal associations of cancers with COVID-19 outcomes using the MR analysis. The inverse-variance weighted (IVW) method was employed as the primary analysis. Sensitivity analyses and multivariable MR analyses were conducted. Notably, IVW analysis of univariable MR revealed that overall cancer and twelve site-specific cancers had no causal association with COVID-19 severity, hospitalization or susceptibility. The corresponding p-values for the casual associations were all statistically insignificant: overall cancer (p = 0.34; p = 0.42; p = 0.69), lung cancer (p = 0.60; p = 0.37; p = 0.96), breast cancer (p = 0.43; p = 0.74; p = 0.43), endometrial cancer (p = 0.79; p = 0.24; p = 0.83), prostate cancer (p = 0.54; p = 0.17; p = 0.58), thyroid cancer (p = 0.70; p = 0.80; p = 0.28), ovarian cancer (p = 0.62; p = 0.96; p = 0.93), melanoma (p = 0.79; p = 0.45; p = 0.82), small bowel cancer (p = 0.09; p = 0.08; p = 0.19), colorectal cancer (p = 0.85; p = 0.79; p = 0.30), oropharyngeal cancer (p = 0.31; not applicable, NA; p = 0.80), lymphoma (p = 0.51; NA; p = 0.37) and cervical cancer (p = 0.25; p = 0.32; p = 0.68). Sensitivity analyses and multivariable MR analyses yielded similar results. In conclusion, cancers might have no causal effect on increasing COVID-19 risk. Further large-scale population studies are needed to validate our findings.
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Affiliation(s)
- Zengbin Li
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China; (Z.L.); (Y.W.); (G.Z.); (M.W.)
| | - Yudong Wei
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China; (Z.L.); (Y.W.); (G.Z.); (M.W.)
| | - Guixian Zhu
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China; (Z.L.); (Y.W.); (G.Z.); (M.W.)
| | - Mengjie Wang
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China; (Z.L.); (Y.W.); (G.Z.); (M.W.)
| | - Lei Zhang
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China; (Z.L.); (Y.W.); (G.Z.); (M.W.)
- Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC 3053, Australia
- Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC 3800, Australia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Correspondence: ; Tel.: +86-29-8265-5135
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Lo CH, Nguyen LH, Drew DA, Warner ET, Joshi AD, Graham MS, Anyane-Yeboa A, Shebl FM, Astley CM, Figueiredo JC, Guo CG, Ma W, Mehta RS, Kwon S, Song M, Davies R, Capdevila J, Sudre CH, Wolf J, Cozier YC, Rosenberg L, Wilkens LR, Haiman CA, Marchand LL, Palmer JR, Spector TD, Ourselin S, Steves CJ, Chan AT. Race, ethnicity, community-level socioeconomic factors, and risk of COVID-19 in the United States and the United Kingdom. EClinicalMedicine 2021; 38:101029. [PMID: 34308322 PMCID: PMC8285255 DOI: 10.1016/j.eclinm.2021.101029] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/29/2021] [Accepted: 06/29/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND There is limited prior investigation of the combined influence of personal and community-level socioeconomic factors on racial/ethnic disparities in individual risk of coronavirus disease 2019 (COVID-19). METHODS We performed a cross-sectional analysis nested within a prospective cohort of 2,102,364 participants from March 29, 2020 in the United States (US) and March 24, 2020 in the United Kingdom (UK) through December 02, 2020 via the COVID Symptom Study smartphone application. We examined the contribution of community-level deprivation using the Neighborhood Deprivation Index (NDI) and the Index of Multiple Deprivation (IMD) to observe racial/ethnic disparities in COVID-19 incidence. ClinicalTrials.gov registration: NCT04331509. FINDINGS Compared with non-Hispanic White participants, the risk for a positive COVID-19 test was increased in the US for non-Hispanic Black (multivariable-adjusted odds ratio [OR], 1.32; 95% confidence interval [CI], 1.18-1.47) and Hispanic participants (OR, 1.42; 95% CI, 1.33-1.52) and in the UK for Black (OR, 1.17; 95% CI, 1.02-1.34), South Asian (OR, 1.39; 95% CI, 1.30-1.49), and Middle Eastern participants (OR, 1.38; 95% CI, 1.18-1.61). This elevated risk was associated with living in more deprived communities according to the NDI/IMD. After accounting for downstream mediators of COVID-19 risk, community-level deprivation still mediated 16.6% and 7.7% of the excess risk in Black compared to White participants in the US and the UK, respectively. INTERPRETATION Our results illustrate the critical role of social determinants of health in the disproportionate COVID-19 risk experienced by racial and ethnic minorities.
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Affiliation(s)
- Chun-Han Lo
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Long H Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - David A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Erica T Warner
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Harvard/MGH Center on Genomics, Vulnerable Populations, And Health Disparities, Massachusetts General Hospital, Boston, MA, USA
| | - Amit D Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mark S Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Adjoa Anyane-Yeboa
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Fatma M Shebl
- Medical Practice Evaluation Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christina M Astley
- Computational Epidemiology Lab and Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jane C Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles California, USA
| | - Chuan-Guo Guo
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Wenjie Ma
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Raaj S Mehta
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sohee Kwon
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mingyang Song
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | | | - Carole H Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | - Yvette C Cozier
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Lynn Rosenberg
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Lynne R Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Ageing and Health, Guy's and St Thomas's NHS Foundation Trust, London, UK
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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