The highly contagious Coronavirus Disease of 2019 (COVID-19) has impacted the health and day-to-day life of individuals, especially the elderly and people with certain preexisting medical conditions, including cancer. COVID-19 was declared a worldwide pandemic on March 11, 2020, after its discovery in late December 2019. As of March 10, 2023, 6,881,955 deaths had been reported among 676,609,955 cases worldwide (Dong et al., 2020). Due to the rapid spread and high infectivity rates, stay-at-home orders were decreed to allow for physical distancing and self-isolation. Populations at high risk of contracting COVID-19 and developing severe illness were the elderly and people of all ages with pre-existing medical conditions (such as diabetes, high blood pressure, heart disease, lung disease, or cancer) (WHO, 2020).

Cancer patients were not only at a higher risk of severe illness from COVID-19 but changes in cancer care were also reported. One example is the finding of the COVID-19 and Cancer Outcomes Study, which is a multicenter prospective cohort study comprised of adult patients with a current or history of hematological malignancy or invasive solid tumor, who were scheduled for an outpatient medical oncology visit at the Tisch Cancer Institute in New York City or the Dana-Farber Cancer Institute in Boston. Researchers found that 10% of patients in the cohort had treatment delayed during the pandemic and, of that subset, 48% had treatment delayed due to a COVID-19 diagnosis (Schmidt et al., 2020). In the United States, COVID-19 disproportionately affected racial and ethnic minorities, particularly African Americans, with an observed two-fold higher rate of hospitalization and a greater than two-fold higher rate of death, as compared to Non-Hispanic Whites (Newman et al., 2021). The disparity seen with COVID-19 was consistent with patterns of disparities observed for cancer; it is well-documented that 5-year survival rates for multiple cancers are lower in African Americans compared to White Americans. While cancer is a multifactorial disease that is influenced by genetic and environmental factors, COVID-19 is an infectious disease that is enabled by the cellular expression of angiotensin-converting enzyme 2 (ACE2) receptors. However, preexisting comorbidities, socioeconomic disadvantages, living conditions, health literacy, and access to health care appear to fuel underlying risks for both cancer and COVID-19 disparities (Newman et al., 2021).

In addition, the pandemic has affected access to cancer screenings, especially for colorectal cancer (CRC) and breast cancer. The recommendation for CRC screening among average-risk adults aged 50–75 years is to undergo an annual fecal immunochemical test (FIT) or colonoscopy every 10 years (Corley et al., 2021). Screening and appropriate follow-up can reduce incidence and mortality, which is important because CRC is the second leading cause of cancer death in the United States (Nodora et al., 2021). One study found that CRC screening rates are particularly low in Hispanic and Asian American adults, recent immigrants, those with low incomes, and the uninsured (Nodora et al., 2021). During the COVID-19 pandemic, colorectal cancer screenings were reported to have dropped by 84.5% at a network of 20 United States institutions with more than 28 million patients (London et al., 2020).

For breast cancer, which is the most common non-cutaneous malignancy and the second most lethal tumor among women in the US, the recommendation is biennial mammography in women ages 50–74 years (Corley et al., 2021). In the MEC, Native Hawaiian participants have the highest risk of breast cancer, followed by Japanese American and White participants (Pike et al., 2002). Nationwide, the breast cancer mortality rate is 40% higher for African American patients compared with White patients (Siegel et al., 2020). During the COVID-19 pandemic, breast cancer screenings dropped by 89.2% at a network of 20 United States institutions with more than 28 million patients (London et al., 2020).

Lastly, studies have suggested that educational attainment is associated with adherence to cancer screening. For breast cancer, a positive association was found between education level and adherence to mammography screening (Damiani et al., 2015). For colorectal cancer, a study on United States veterans aged 50–75 years concluded that both education and income show a statistically significant dose-dependent direct association with screening (Rodriguez and Smith, 2016).

In summary, COVID-19 has impacted medical care delivery, access to cancer screening, and the day-to-day life of individuals worldwide. However, the full impact of the pandemic on cancer screenings and cancer care is not entirely known. The purpose of this cross-sectional study was to understand how COVID-19 affected access to cancer screening and treatment, by studying the participants in the Multiethnic Cohort (MEC) study.

Table 1 presents the number of COVID-19 survey participants by various characteristics. A total of 6,974 MEC members answered the baseline survey, 6,068 via the online survey, and 906 via the paper survey. Fewer men (43.5%) than women (56.5%) responded. 76.6% of COVID survey participants were from Hawai‘i and 23.6% were from Los Angeles. The survey response rate was 7.2% for men and 6.3% for women. The racial/ethnic group with the highest response rates was White (13.2%) for men; 12% for women, followed by Japanese American (8.9; 7.4), Native Hawaiian (7.3; 7.5), Other (2.7; 4.5), African American (2.7; 2.8), and Latino (2.2; 2.0). In Supplementary file 1, the distribution of the MEC cohort survivors in 2019 is compared with the distribution of the COVID survey participants in 2020 by race and education. For both males and females, the COVID survey respondents included a larger representation of Whites and Japanese Americans and a smaller representation of Latinos, African Americans, and Others compared to the entire 2019 surviving cohort. The proportion of the sample that was Native Hawaiians was similar to the MEC survivors. For education, a greater percentage of COVID-19 survey respondents had at least some college education compared to the entire 2019 surviving cohort. This pattern of higher attained education was observed for each racial/ethnic group.

Among participants in the baseline COVID-19 survey, the most common race/ethnicity reported was White (45.2% of men; 42.7% of women), followed by Japanese American (34.9%; 30.3%), Latino (7.9%; 7.4%), Native Hawaiian (6.4%; 8.1%), African American (3.5%; 6.5%), and Other (2.0%; 4.9%). The ethnicity category of Other comprised a majority of Chinese Americans (38.1%) and Filipino (36.6%). The mean age and education were similar in both sexes; however, men were more often smokers and alcohol drinkers and had a higher BMI than women. Women had a greater mean Healthy Eating Index-2010 score than men as reported in the MEC baseline questionnaire (1993–1996).

Overall, 78.8% of men and 84.4% of women reported making changes to their lifestyle or daily activities due to COVID-19 since March 2020. Examples of activities were specifically about COVID-19 prevention measures such as covering a cough or sneeze, more frequent hand washing, and social distancing. Among men, 4.2% and 6.3% reported drinking more and drinking less during the COVID-19 pandemic, respectively. The corresponding %’s for women were 4.3 and 5.2%. Only 3.7% of men and 2.6% of women were current smokers.

Regarding the participant’s health status, 3.5% and 19.7% of men had health problems that require them to stay at home and limit their activities, respectively, at the time of the COVID-19 baseline survey (Supplementary file 2). The corresponding %’s for women were 4.9 and 19.3%. In addition, the survey respondents had a wide range of comorbidities in 2020, with hypertension (48% of men; 47.1% of women) being the most prevalent, followed by diabetes (18.3%; 14.4%), and heart disease (20.8%; 10.6%). Lastly, the most frequently used medication was aspirin (37.9% of men; 28.1% of women), followed by Blood Pressure Medication ending in –sartan (29.3%; 26.0%), and Blood Pressure Medication ending in -pril (25.8%, 16.4%).

Overall, 54.2% of men and 61.2% of women participants reported that they had to postpone their regular healthcare visits due to COVID-19. Primary care physician and dentist visits were the most frequently postponed with 858 and 954 reports for men and 1188 and 1453 reports for women, respectively (Table 2).

Similarly, 5.7% of men and 11.0% of women reported having to postpone a cancer screening or procedure due to COVID-19 (Table 3). The screening procedure the most frequently missed was mammography (n=264), followed by skin examination (n=207) and colorectal cancer screening (n=114). In the past five years, 917 survey participants had been diagnosed with cancer (Supplementary file 2). Of note, 103 men (3.4%) and 135 women (3.4%) reported that they were currently receiving any of the following cancer treatments: chemotherapy (31 men; 30 women); immunotherapy: (22 and 19) and radiation therapy (16 and 8). Among cancer patients still receiving treatment, 11.5% of men and 6.9% of women had to cancel at least one treatment session due to COVID-19 (Table 3).

Compared to White men, Native Hawaiian men were 41% (95% CI: 0.42, 0.84; p=0.003) and Other men were 56% (95% CI: 0.25, 0.78, p=0.004) less likely, and African American men were 154% (95% CI: 1.30, 4.99; p=0.007) more likely, to make any changes to their lifestyle or daily activities, such as covering a cough or sneeze, more frequent hand washing, and social distancing, since the COVID-19 pandemic (Table 4). Compared to White women, Native Hawaiian women were 56% (95% CI: 0.33, 0.60; p<.0001) and Other women were 38% (95% CI: 0.41, 0.92; p=0.02) less likely, to make any changes to their lifestyle or daily activities since the COVID-19 pandemic.

Each additional year of age was associated with less likelihood to make any changes to their lifestyle or daily activities by 2% per year of age for men (OR = 0.98, 95% CI: 0.96, 1.00; p=0.02) and by 3% per year of age for women (OR = 0.97, 95% CI: 0.96, 0.99; p=0.0005) (Table 4). Compared to men, women were 62% (95% CI: 1.42, 1.84; p<0.0001) more likely to make any changes to their lifestyle or daily activities. Each additional year of education was associated with more likelihood to make changes to their lifestyle or daily activities, by 12% per year of education in men (OR = 1.12, 95% CI: 1.07, 1.17; p<0.0001), and by 10% per year in women (OR = 1.10, 95% CI: 1.06, 1.15; p<0.0001).

Compared to men with no comorbidity, men with heart disease were 41% (95% CI: 1.11, 1.80; p=0.006), those with hypertension 34% (95% CI: 1.11, 1.62; p=0.002), and those with lung disease, COPD, or asthma 41% (95% CI: 1.01, 1.96; p=0.04), more likely to make changes to their lifestyle or daily activities (Table 4). Compared to women with no comorbidity, women with hypertension were 21% (95% CI: 1.00, 1.47; p=0.05), and those with lung disease, COPD, or asthma 65% (95% CI: 0.70, 1.76; p=0.001), more likely to make changes to their lifestyle or daily activities.

Similarly, compared to White men, Latino men were 26% (95% CI: 0.55, 0.99; p=0.04) and Native Hawaiian men 36% (95% CI: 0.47, 0.88; p=0.005) less likely to postpone regular health care visits due to the COVID-19 pandemic (Table 5). Compared to White women, Native Hawaiian women were 40% (95% CI: 0.47, 0.78; p=0.0001) less likely to postpone regular healthcare visits due to the COVID-19 pandemic.

Each additional year of age in women was associated with a lower likelihood to postpone regular healthcare visits by 2% per year (OR = 0.98, 95% CI: 0.97, 0.99; p=0.0006) (Table 5). Each additional year of education in men was associated with a higher likelihood to postpone regular health care visits, by 45% per year (OR = 1.04, 95% CI: 1.00, 1.08; p=0.04). Compared to men, women were 43% (95% CI: 1.29, 1.58; p<0.0001) more likely to postpone regular health care visits.

Compared to men with no comorbidity, men with heart disease were 37% (95% CI: 1.13, 1.65; p=0.0011) more likely to postpone regular health care visits (Table 5). Compared to women with no comorbidity, women with hypertension were 16% (95% CI: 1.00, 1.33; p=0.04), those with kidney disease 49% (95% CI: 1.05, 2.11; p=0.03), and those diagnosed with cancer in the past 5 years 51% (95% CI: 1.21, 1.88; p=0.0003), more likely to postpone regular health care visits.

Compared to White men, Japanese American men were 72% (95% CI: 0.18, 0.45; p<0.0001) less likely to postpone any cancer screening test/procedure due to the COVID-19 pandemic (Table 6). Compared to White women, Japanese American women were 40% (95% CI: 0.46, 0.78; p=0.0002) less likely to postpone any cancer screening test/procedure due to the COVID-19 pandemic.

Women were 4% less likely for each additional year of age (95% CI: 0.94, 0.98; p=0.001) to postpone any cancer screening test/procedure (Table 6). Women were 10% more likely for each additional year of education (95% CI: 1.05, 1.16; p=0.0004) to postpone any cancer screening test/procedure. Compared to men, women were 137% (95% CI: 1.95, 2.88; p<0.0001) more likely to postpone any cancer screening test/procedure.

Compared to men with no comorbidity, men diagnosed with cancer in the past 5 years were 254% (95% CI: 2.52, 4.95; p<0.0001) more likely to postpone any cancer screening test/procedure (Table 6). Compared to women with no comorbidity, women with lung disease, COPD, or asthma were 50% (95% CI: 1.14, 1.98; p=0.004) and those diagnosed with cancer in the past 5 years were 222% (95% CI: 2.50, 4.14; p<0.0001) more likely to postpone any cancer screening test/procedure.

The results of this study suggest unique relationships between participant characteristics, such as sex, age, years of education, race/ethnicity, and comorbidities with the likelihood of making changes to lifestyle or daily activities and of postponing regular health care visits and cancer screenings/treatments during the COVID-19 pandemic. Responses were compared between males and females and by race/ethnicity to describe the differences between these groups.

African American men (compared to White men), women (compared to men), men and women with more education, men and women with heart disease, hypertension, or lung disease, COPD, or asthma (compared to men or women with no comorbidity) were more likely to make changes to their lifestyle or daily activities during the COVID-19 pandemic. As expected, participants with one or more risk factors, such as cancer or lung disease, were more likely to make changes to their lifestyle during the pandemic as they were reported to be at increased risk of severe illness from COVID-19.

Men with more education, women (compared to men), men with heart disease, and women with hypertension, kidney disease, and diagnosed with cancer in the past 5 years were more likely to postpone regular health care visits. As expected, participants with comorbidity were more likely to postpone healthcare visits, as they were recommended to avoid public places to protect themselves from the virus.

Lastly, women with more education, women (compared to men), women and men diagnosed with cancer in the past 5 years, and women with lung disease, COPD, or asthma were more likely to postpone any cancer screening test/procedure.

Native Hawaiian men and women and those of Other race/ethnicity (compared to White men or women), and older men and women were less likely to make changes to their lifestyle or daily activities during the COVID-19 pandemic. Latino and Native Hawaiian men, Native Hawaiian women, and older women were less likely to postpone regular healthcare visits during the COVID-19 pandemic. Lastly, Japanese American men and women and older women were less likely to postpone any cancer screening test/procedure during the COVID-19 pandemic.

The Multiethnic Cohort welcomes applications from researchers to maximize the utility of the MEC data and/or specimens for prevention and etiological research on cancer and other chronic diseases. For access, a research application is required. To request access to the MEC resource for data analyses or ancillary studies, and to submit an application, please visit https://www.uhcancercenter.org/for-researchers/mec-data-sharing for further instructions. You will need to request an account in the system if you do not already have one. Proposals for access to MEC data or biospecimen are reviewed quarterly by the MEC Research Committee (MECRC) and must be submitted by the following deadlines: December 1, March 1, June 1, and September 1. All applications are reviewed by the MECRC following a standard procedure. The Statistical Analysis System (SAS), version 9.4 codes used for this study are available at https://github.com/MEC-COVID/eLife-Manuscript (copy archived at Mak et al., 2023). If you have questions please contact Gail Ichida at gichida@cc.hawaii.edu.

1. Website

   1. Cent Dis Control Prev

   (2023) Incidence and Relative Survival by Stage at Diagnosis for Common Cancers

   USCS Data Brief. Accessed May 15, 2023.

   https://www.cdc.gov/cancer/uscs/about/data-briefs/no25-incidence-relative-survival-stage-diagnosis.htm
2. 1. Corley DA
   2. Sedki M
   3. Ritzwoller DP
   4. Greenlee RT
   5. Neslund-Dudas C
   6. Rendle KA
   7. Honda SA
   8. Schottinger JE
   9. Udaltsova N
   10. Vachani A
   11. Kobrin S
   12. Li CI
   13. Haas JS

   (2021) Cancer screening during the Coronavirus Disease-2019 pandemic: A perspective from the National Cancer Institute’s PROSPR consortium

   Gastroenterology 160:999–1002.

   https://doi.org/10.1053/j.gastro.2020.10.030

   • Google Scholar
3. 1. Damiani G
   2. Basso D
   3. Acampora A
   4. Bianchi C
   5. Silvestrini G
   6. Frisicale EM
   7. Sassi F
   8. Ricciardi W

   (2015) The impact of level of education on adherence to breast and Cervical cancer screening: evidence from a systematic review and meta-analysis

   Preventive Medicine 81:281–289.

   https://doi.org/10.1016/j.ypmed.2015.09.011

   • PubMed
   • Google Scholar
4. 1. Dong E
   2. Du H
   3. Gardner L

   (2020) An interactive web-based dashboard to track COVID-19 in real time

   The Lancet Infectious Diseases 20:533–534.

   https://doi.org/10.1016/S1473-3099(20)30120-1

   • Google Scholar
5. Website

   1. FDA

   (2021) FDA Approves First COVID-19 Vaccine

   Accessed May 15, 2023.

   https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine
6. 1. Hajek A
   2. De Bock F
   3. Huebl L
   4. Kretzler B
   5. König HH

   (2021a) Determinants of postponed cancer screening during the COVID-19 pandemic: evidence from the nationally representative COVID-19 Snapshot monitoring in Germany (COSMO)

   Risk Management and Healthcare Policy 14:3003–3011.

   https://doi.org/10.2147/RMHP.S297326

   • PubMed
   • Google Scholar
7. 1. Hajek A
   2. De Bock F
   3. Kretzler B
   4. König HH

   (2021b) Factors associated with postponed health Checkups during the COVID-19 pandemic in Germany

   Public Health 194:36–41.

   https://doi.org/10.1016/j.puhe.2021.02.023

   • Google Scholar
8. 1. Kolonel LN
   2. Henderson BE
   3. Hankin JH
   4. Nomura AM
   5. Wilkens LR
   6. Pike MC
   7. Stram DO
   8. Monroe KR
   9. Earle ME
   10. Nagamine FS

   (2000) A Multiethnic cohort in Hawaii and Los Angeles: baseline characteristics

   American Journal of Epidemiology 151:346–357.

   https://doi.org/10.1093/oxfordjournals.aje.a010213

   • PubMed
   • Google Scholar
9. 1. London JW
   2. Fazio-Eynullayeva E
   3. Palchuk MB
   4. Sankey P
   5. McNair C

   (2020) Effects of the COVID-19 pandemic on cancer-related patient encounters

   JCO Clinical Cancer Informatics 4:657–665.

   https://doi.org/10.1200/CCI.20.00068

   • PubMed
   • Google Scholar
10. Software

    1. Mak VP
    2. White K
    3. Wilkens LR
    4. Cheng I
    5. Haiman CA
    6. Le Marchand LL

    (2023) The impact of COVID-19 on cancer screening and treatment in older adults: the Multiethnic cohort study, version swh:1:rev:a0250c111aa9d2a740c25a751fbfd11f7884641c

    Software Heritage.

    https://archive.softwareheritage.org/swh:1:dir:67450b9f4b4b7cd4f328e6ff43f7b7513b249bf6;origin=https://github.com/MEC-COVID/eLife-Manuscript;visit=swh:1:snp:375cf59db6dc7a43ffa7e8bb892df7644838e687;anchor=swh:1:rev:a0250c111aa9d2a740c25a751fbfd11f7884641c
11. Website

    1. Martin K
    2. Kurowski D
    3. Given P
    4. Kennedy K
    5. Clayton E

    (2022) The Impact of COVID-19 on the Use of Preventive Health Care

    Accessed March 15, 2022.

    https://healthcostinstitute.org/hcci-research/the-impact-of-covid-19-on-the-use-of-preventive-health-care
12. Book

    1. Mehrotra A
    2. Chernew M
    3. Linetsky D
    4. Hatch H
    5. Cutler D

    (2020) The Impact of the COVID-19 Pandemic on Outpatient Visits: A Rebound Emerges Commonweath Fund

    The Commonwealth Fund.

    https://doi.org/10.26099/DS9E-JM36

    • Google Scholar
13. 1. Newman LA
    2. Winn RA
    3. Carethers JM

    (2021) Similarities in risk for COVID-19 and cancer disparities

    Clinical Cancer Research 27:24–27.

    https://doi.org/10.1158/1078-0432.CCR-20-3421

    • PubMed
    • Google Scholar
14. 1. Nodora JN
    2. Gupta S
    3. Howard N
    4. Motadel K
    5. Propst T
    6. Rodriguez J
    7. Schultz J
    8. Velasquez S
    9. Castañeda SF
    10. Rabin B
    11. Martínez ME

    (2021) The COVID-19 pandemic: identifying adaptive solutions for colorectal cancer screening in Underserved communities

    Journal of the National Cancer Institute 113:962–968.

    https://doi.org/10.1093/jnci/djaa117

    • PubMed
    • Google Scholar
15. 1. Patel SY
    2. Mehrotra A
    3. Huskamp HA
    4. Uscher-Pines L
    5. Ganguli I
    6. Barnett ML

    (2021) Trends in outpatient care delivery and Telemedicine during the COVID-19 pandemic in the US

    JAMA Internal Medicine 181:388–391.

    https://doi.org/10.1001/jamainternmed.2020.5928

    • PubMed
    • Google Scholar
16. 1. Pike MC
    2. Kolonel LN
    3. Henderson BE
    4. Wilkens LR
    5. Hankin JH
    6. Feigelson HS
    7. Wan PC
    8. Stram DO
    9. Nomura AMY

    (2002)

    Breast cancer in a Multiethnic cohort in Hawaii and Los Angeles: risk factor-adjusted incidence in Japanese equals and in Hawaiians exceeds that in whites

    Cancer Epidemiology, Biomarkers & Prevention 11:795–800.

    • PubMed
    • Google Scholar
17. 1. Rodriguez N
    2. Smith J

    (2016) The association between education and colorectal cancer screening among United States veterans aged 50-75 years old: 286

    American Journal of Gastroenterology 111:S134.

    https://doi.org/10.14309/00000434-201610001-00286

    • Google Scholar
18. 1. Schmidt AL
    2. Bakouny Z
    3. Bhalla S
    4. Steinharter JA
    5. Tremblay DA
    6. Awad MM
    7. Kessler AJ
    8. Haddad RI
    9. Evans M
    10. Busser F
    11. Wotman M
    12. Curran CR
    13. Zimmerman BS
    14. Bouchard G
    15. Jun T
    16. Nuzzo PV
    17. Qin Q
    18. Hirsch L
    19. Feld J
    20. Kelleher KM
    21. Seidman D
    22. Huang H-H
    23. Anderson-Keightly HM
    24. Abou Alaiwi S
    25. Rosenbloom TD
    26. Stewart PS
    27. Galsky MD
    28. Choueiri TK
    29. Doroshow DB

    (2020) Cancer care disparities during the COVID-19 pandemic: COVID-19 and cancer outcomes study

    Cancer Cell 38:769–770.

    https://doi.org/10.1016/j.ccell.2020.10.023

    • PubMed
    • Google Scholar
19. 1. Siegel RL
    2. Miller KD
    3. Jemal A

    (2020) Cancer statistics, 2020

    CA 70:7–30.

    https://doi.org/10.3322/caac.21590

    • PubMed
    • Google Scholar
20. Website

    1. WHO

    (2020) Coronavirus disease (COVID-19): Risks and safety for older people

    Accessed November 11, 2020.

    https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-covid-19-risks-and-safety-for-older-people
21. 1. Yong JH
    2. Mainprize JG
    3. Yaffe MJ
    4. Ruan Y
    5. Poirier AE
    6. Coldman A
    7. Nadeau C
    8. Iragorri N
    9. Hilsden RJ
    10. Brenner DR

    (2021) The impact of episodic screening interruption: COVID-19 and population-based cancer screening in Canada

    Journal of Medical Screening 28:100–107.

    https://doi.org/10.1177/0969141320974711

    • PubMed
    • Google Scholar

Author details

1. Victoria P Mak

   Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, United States

   Contribution

   Data curation, Formal analysis, Visualization, Writing – original draft, Writing – review and editing

   For correspondence

   vmak@hawaii.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0908-5018

2. Kami White

   Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, United States

   Contribution

   Data curation, Formal analysis, Writing – review and editing

   Competing interests

   No competing interests declared

3. Lynne R Wilkens

   Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, United States

   Contribution

   Conceptualization, Supervision, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

4. Iona Cheng

   Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, United States

   Contribution

   Conceptualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Christopher A Haiman

   Center for Genetic Epidemiology, University of Southern California, Los Angeles, United States

   Contribution

   Conceptualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0097-9971

6. Loic Le Marchand

   Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, United States

   Contribution

   Conceptualization, Supervision, Funding acquisition, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5013-980X

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