Participation in the nationwide cervical cancer screening programme in Denmark during the COVID-19 pandemic: An observational study
- The Danish Clinical Quality Program - National Clinical Registries, Denmark
- Department of Pathology, Lillebaelt Hospital, Denmark
- Department of Regional Health Research, University of Southern Denmark, Denmark
- University Research Clinic for Cancer Screening, Department of Public Health Programmes,Randers Regional Hospital, Denmark
- Department of Clinical Medicine, Aarhus University, Denmark
Abstract
Background:
In contrast to most of the world, the cervical cancer screening programme continued in Denmark throughout the COVID-19 pandemic. We examined the cervical cancer screening participation during the pandemic in Denmark.
Methods:
We included all women aged 23–64 y old invited to participate in cervical cancer screening from 2015 to 2021 as registered in the Cervical Cancer Screening Database combined with population-wide registries. Using a generalised linear model, we estimated prevalence ratios (PRs) and 95% CIs of cervical cancer screening participation within 90, 180, and 365 d since invitation during the pandemic in comparison with the previous years adjusting for age, year, and month of invitation.
Results:
Altogether, 2,220,000 invited women (in 1,466,353 individuals) were included in the study. Before the pandemic, 36% of invited women participated in screening within 90 d, 54% participated within 180 d, and 65% participated within 365 d. At the start of the pandemic, participation in cervical cancer screening within 90 d was lower (pre-lockdown PR = 0.58; 95% CI: 0.56–0.59 and first lockdown PR = 0.76; 95% CI: 0.75–0.77) compared with the previous years. A reduction in participation within 180 d was also seen during pre-lockdown (PR = 0.89; 95% CI: 0.88–0.90) and first lockdown (PR = 0.92; 95% CI: 0.91–0.93). Allowing for 365 d to participation, only a slight reduction (3%) in participation was seen with slightly lower participation in some groups (immigrants, low education, and low income).
Conclusions:
The overall participation in cervical cancer screening was reduced during the early phase of the pandemic. However, the decline almost diminished with longer follow-up time.
Funding:
The study was funded by the Danish Cancer Society Scientific Committee (grant number R321-A17417) and the Danish regions.
Editor's evaluation
This article shows how the COVID-19 pandemic affected cervical cancer screening participation in the organized screening program of Denmark. Through registry data covering the entire population, the study shows that while short-term (90 days) participation after invitation dropped, long-term (365 days) participation remained stable. These results will be of interest to public health specialists and researchers working on pandemic recovery efforts related to cancer screening worldwide.
https://doi.org/10.7554/eLife.81522.sa0Introduction
The COVID-19 pandemic is a global health crisis, which has caused extensive disruptions to the society and to the healthcare systems across the world. Population-wide restrictions (‘lockdowns’) were imposed in most countries throughout the pandemic closing down schools and workplaces and restricting travel to reduce the transmission of COVID-19 and to limit the potential burden on the healthcare systems. Within the healthcare system, prioritisations and re-organisations were done to ensure sufficient capacity to take care of patients in need of hospitalisation due to COVID-19. The prioritisations within the healthcare system resulted in a temporary halting of the cervical cancer screening programme in most of the world. On the contrary, in Denmark, the cervical cancer screening programmes remained open throughout the pandemic. At the same time, however, at the national televised press conferences, the health authorities asked the Danish population to stay at home if possible, and concurrently, the Danish College of General Practitioners recommended general practitioners to postpone routine cervical smears during a 4 wk period in March/April 2020 (Dansk Selskab for Almen Medicin, 2020). Nevertheless, the cervical cancer screening programme continued – and invitations and reminders were sent out – throughout the pandemic in Denmark.
It is estimated that the disruptions to the cervical cancer screening programmes in high-income countries because of the pandemic could potentially increase cervical cancer cases by up to 5–6% and increase the number of cervical cancers detected at a higher stage (Smith et al., 2021). Disruptions to the cervical cancer screening programme may therefore be worrisome. Marked reductions in the number of women screened for cervical cancer during the early phase of the pandemic have been reported in many other countries (Castanon et al., 2022; Cancer Registry of Norway, 2020; Meggetto et al., 2021; Ivanuš et al., 2021), whilst the participation in cervical cancer screening during the pandemic in Denmark has not yet been described.
It is well known that participation in cervical cancer screening is generally reduced among women of lower socio-economic status (Harder et al., 2018) and among immigrant women (Hertzum-Larsen et al., 2019; Badre-Esfahani et al., 2020). This divergence in participation may have been exacerbated during the COVID-19 pandemic. However, so far no studies have put spotlight on this.
In this large, population-based nationwide study, we examined the participation in cervical cancer screening during the COVID-19 pandemic in Denmark in comparison with the previous years. Moreover, we examined whether the participation in cervical cancer screening during the pandemic differed across population groups with different socio-economic status.
Methods
Setting
The study was set in Denmark, which has a population of approximately 5.8 million inhabitants (Statistics Denmark, 2021). Denmark has a tax-funded healthcare system, with universal access to healthcare for all residents including national screening programmes for breast, cervical, and colorectal cancer. The population-based administrative and health registries in Denmark can be linked through the unique personal identifier assigned to all residents at birth or immigration (Schmidt et al., 2014, Schmidt et al., 2019).
The cervical cancer screening programme
In Denmark, all women aged 23–64 y old are invited to participate in cervical cancer screening every 3 y (women aged 23–49 y old) or every 5 y (women aged 50–64 y old; Bonde et al., 2022). The women receive an invitation letter (electronic letters via secure digital e-mail since 2018; however, women exempted from digital mail still receive ordinary mail) with an invitation to book an appointment with their general practitioner for a cervical screening test. Reminders to participate in cervical cancer screening are sent out to non-participants after 3 mo and again after 6 mo. The obtained samples are analysed for cytology and/or HPV at a pathology department. The outcome of the test is sent to the woman and her general practitioner.
The COVID-19 pandemic in Denmark
In Denmark, three main waves of the COVID-19 pandemic have occurred that is, in the spring of 2020, in the winter of 2020/2021, and again in the winter of 2021/2022 (Statens Serum Institut, 2021a).
In efforts to minimise the spread of the infection, population-wide restrictions (‘lockdown’) were imposed in Denmark 11 March 2020, and subsequently, large parts of the society were closed down. Within the healthcare system, elective procedures were cancelled or postponed, and resources were reallocated to take care of patients in need of hospitalisation because of COVID-19.
Extensive testing facilities were set up in Denmark from May 2020, providing COVID-19 tests free-of-charge to the whole population (Pottegård et al., 2020). In Denmark, laymen were trained to perform COVID-19 tests, which is in contrast to many other countries where healthcare personnel were allocated to perform COVID-19 tests. Vaccination against COVID-19 began in December 2020 in Denmark, and a high vaccination coverage has been achieved, and by March 2022, approximately 81% of the population had received two doses, and more than 61% had received three doses of the vaccine (Statens Serum Institut, 2021b).
Study population
The study population comprised all women aged 23–64 y old invited to participate in cervical cancer screening from 1 January 2015 to 30 September 2021, as registered in the Cervical Cancer Screening Database (Rygaard, 2016), which contain information on all women invited to participate in cervical cancer screening in Denmark since 2009. The Cervical Cancer Screening Database comprises population data from the Civil Registration System (Schmidt et al., 2014), including all persons with a permanent address in Denmark; cervical cancer cases are obtained from the Danish Cancer Register (Gjerstorff, 2011), cervical cytology samples are obtained from the Danish Pathology Register (Bjerregaard and Larsen, 2011), and information on invitations and reminders is obtained from the invitation registration system.
We excluded invitations in women who died within 1 y since invitation (N=110), women who emigrated within 1 y since invitation (N=138), women residing in the Faroe Islands or Greenland (N=762), women with an unknown postal address (N=261), women who unregistered from the screening programme within 1 y since invitation (N=56,920), and invitations in women with missing information on region of residence (N=1742; Figure 1).
Figure 1
Flow-chart of the study population.
Exposure of interest
The exposure of interest was the COVID-19 pandemic in Denmark. The different phases of the pandemic were defined, in accordance with the governmental responses to the COVID-19 pandemic in Denmark, as follows:
Pre-pandemic period: 1 January 2015 to 31 January 2020.
Pre-lockdown period: 1 February to 10 March 2020.
First lockdown: 11 March to 15 April 2020.
First re-opening: 16 April to 15 December 2020.
Second lockdown: 16 December 2020 to 27 February 2021.
Second re-opening: 28 February 2021 to 30 September 2021 (end of inclusion period).
When examining each outcome of interest as stated below (participation within 90, 180, and 365 d since invitation), the end of inclusion period varied, that is, the end of inclusion was 31 December 2020 when examining participation in screening within 365 d since invitation meaning that participation within second lockdown could only be observed among women invited until 31 December 2020. To ensure at least 90 d complete follow-up on all tests, the data on cervical cytology samples covered up until 31 December 2021.
Outcome of interest
The main outcome of interest was participation in cervical cancer screening defined as having a cervical cancer screening test performed within 90, 180, and 365 d since invitation, respectively, among women invited to participate in the cervical screening programme. We thus calculated the proportion of women participating in cervical cancer screening within 90, 180, and 365 d since invitation, respectively, among invited women.
Explanatory variables
The following variables were examined independently: age, ethnicity, cohabitation status, educational level, disposable income, and healthcare usage. Age was defined at the date of invitation, as registered in the Cervical Cancer Screening Database (Rygaard, 2016). From Statistics Denmark, 2021, we obtained information on ethnicity, marital status, educational level, and level of income. Ethnicity was categorised as Danish descent, western immigrant, non-western immigrant, and descendants of immigrants. Cohabitation status was categorised as living alone, co-habiting/co-living, and married (i.e. married or registered partnership) in accordance with Statistics Denmark, 2021. Education level was defined in accordance with the International Standard Classification of Education (ISCED) of the United Nations Education, Scientific, and Cultural Organisation (UNESCO) into short (ISCED level 1–2), medium (ISCED level 3–5), and long (ISCED level 6–8; Statistics Denmark, 2021). Income was defined as official disposable income depreciated to 2015 level and categorised into five quintiles. To indicate the level of healthcare use by each patient, we counted the total number of contacts (comprising face-to-face, telephone, and e-mail consultations) to general practitioners, private practising medical specialists, physiotherapists, and chiropractors in the year for invitation as registered in the Danish National Health Service Register (Andersen et al., 2011), which contain information on visits to primary healthcare (e.g., general practitioners and medical specialists) in Denmark since 1990. We categorised healthcare usage into five quintiles of the data as rare (0–3 visits per year), low (4–6 visits per year), average (7–11 visits per year), high (12–18 visits per year), and frequent (≥19 visits per years).
Information on cohabitation status was only available from Statistics Denmark until the end of February 2021, whereas all other socio-economic variables were available until end of the study period.
Statistical analyses
We examined characteristics of women invited to participate in cervical cancer screening during the study period. Thereafter, we examined the participation in cervical cancer screening within 90 d, 180 d, and 365 d since invitation among women invited to participate in screening per month and during the different phases of the pandemic overall and stratifying by the explanatory variables. Additionally, we examined time from invitation to participation in median number of d and interquartile interval overall and during the pandemic phases, in women eventually participating in the screening programme.
Using a generalised linear model with log link for the Poisson family with robust SE, we estimated prevalence ratios (PRs) and 95% CI of participation in cervical cancer screening within 90 d, 180 d, and 365 d, respectively, among women invited to participate in screening during the different phases of the pandemic overall and stratifying by the explanatory variables. Firstly, we calculated unadjusted analyses. Thereafter, the analyses were adjusted for month of invitation to allow for seasonality and year of invitation to take into account the underlying decreasing trend in participation in cervical cancer screening (Regionernes Kliniske Kvalitetsudviklingsprogram, 2022). Finally, the analyses were adjusted for age to take into account the effect of age on the other explanatory variables. Furthermore, to take into account the effect of time on each of the socio-economic variables, we performed an interaction test between time and each of the socio-economic variables using a Wald test. These tests for interaction were statistically significant; however, to allow for interpretation of the estimates within each strata of the socio-economic variables, a stratifying approach was used.
All analyses were conducted using STATA version 17.0.
Ethical considerations
The study is registered at the Central Denmark Region’s register of research projects (journal number 1-16-02-381-20). Patient consent is not required by Danish law for register-based studies.
Results
Descriptive characteristics of the study population
Altogether, 2,220,000 invited women (in 1,466,353 individuals) were included in the study. The median age at invitation was 40 y (interquartile range (IQR) = 30–49 y), the majority of women (82.2%) were of Danish descent, 45.9% were married, and 60.4% of women had a low educational level. The distribution of the descriptive characteristics was broadly similar throughout the study period (Table 1).
Table 1
Baseline characteristics of women invited to participate in cervical cancer screening in Denmark from 2015 to 2021.
| Pre-pandemic(01 January 2015–31 January 2020) | Pre-lockdown(01 February 2020–10 March 2020) | First lockdown(11 March 2020–15 April 2020) | First re-opening(16 April 2020–15 December 2020) | Second lockdown(16 December 2020–27 February 2021) | Second re-opening(28 February 2021–30 September 2021) | Total | |
|---|---|---|---|---|---|---|---|
| N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | |
| Total | 1,641,199 (73.9) | 41,876 (1.9) | 31,255 (1.4) | 223,386 (10.1) | 69,729 (3.1) | 212,555 (9.6) | 2,220,000 (100.0) |
| Age at invitation | |||||||
| 23–29 y | 384,272 (23.4) | 10,223 (24.4) | 7731 (24.7) | 58,569 (26.2) | 17,624 (25.3) | 56,816 (26.7) | 535,235 (24.1) |
| 30–39 y | 412,249 (25.1) | 10,614 (25.3) | 7712 (24.7) | 56,783 (25.4) | 17,571 (25.2) | 54,367 (25.6) | 559,296 (25.2) |
| 40–49 y | 495,153 (30.2) | 12,690 (30.3) | 9233 (29.5) | 63,872 (28.6) | 19,051 (27.3) | 59,366 (27.9) | 659,365 (29.7) |
| 50–59 y | 246,814 (15.0) | 6665 (15.9) | 5269 (16.9) | 34,841 (15.6) | 11,810 (16.9) | 31,387 (14.8) | 336,786 (15.2) |
| 60–64 y | 102,711 (6.3) | 1684 (4.0) | 1310 (4.2) | 9321 (4.2) | 3673 (5.3) | 10,619 (5.0) | 129,318 (5.8) |
| Median (IQI) | 41 (31; 49) | 40 (30; 48) | 40 (30; 49) | 39 (30; 48) | 40 (30; 49) | 39 (30; 48) | 40 (30; 49) |
| Ethnicity | |||||||
| Danish descent | 1,358,106 (82.8) | 33,975 (81.2) | 25,778 (82.5) | 177,501 (79.5) | 45,340 (81.3) | 132,376 (81.0) | 1,773,076 (82.2) |
| Descendant of immigrant | 31,339 (1.9) | 918 (2.2) | 781 (2.5) | 5723 (2.6) | 1260 (2.3) | 3881 (2.4) | 43,902 (2.0) |
| Western immigrant | 87,100 (5.3) | 2581 (6.2) | 1655 (5.3) | 15,869 (7.1) | 3247 (5.8) | 9710 (5.9) | 120,162 (5.6) |
| Non-western immigrant | 163,638 (10.0) | 4375 (10.5) | 3027 (9.7) | 24,176 (10.8) | 5928 (10.6) | 17,535 (10.7) | 218,679 (10.1) |
| Cohabitation status | |||||||
| Living alone | 529,023 (32.3) | 13,708 (32.8) | 10,300 (33.0) | 76,687 (34.4) | 3867 (35.1) | N/A | 633,585 (32.5) |
| Cohabiting | 351,991 (21.5) | 9225 (22.1) | 6829 (21.9) | 50,379 (22.6) | 2369 (21.5) | N/A | 420,793 (21.6) |
| Married | 759,009 (46.3) | 18,890 (45.2) | 14,088 (45.1) | 96,132 (43.1) | 4794 (43.5) | N/A | 892,913 (45.9) |
| Educational level (ISCED) | |||||||
| ISCED15 level 1–2 | 960,324 (60.6) | 24,481 (59.3) | 18,667 (60.6) | 129,791 (59.3) | 40,565 (60.1) | 122,230 (60.4) | 1,296,058 (60.4) |
| ISCED15 level 3–5 | 393,390 (24.8) | 10,185 (24.7) | 7539 (24.5) | 52,354 (23.9) | 16,772 (24.8) | 48,870 (24.1) | 529,110 (24.7) |
| ISCED15 level 6–8 | 231,157 (14.6) | 6589 (16.0) | 4600 (14.9) | 36,716 (16.8) | 10,173 (15.1) | 31,395 (15.5) | 320,630 (14.9) |
| Disposable income | |||||||
| Lowest quintile | 322,307 (19.9) | 7419 (18.2) | 5869 (19.0) | 43,920 (20.4) | 12,715 (18.6) | 39,486 (19.3) | 431,716 (19.8) |
| Second quintile | 334,113 (20.6) | 7611 (18.7) | 5878 (19.0) | 40,851 (19.0) | 12,137 (17.8) | 36,480 (17.9) | 437,070 (20.0) |
| Third quintile | 338,563 (20.9) | 8066 (19.8) | 5850 (18.9) | 40,863 (19.0) | 11,738 (17.2) | 34,157 (16.7) | 439,237 (20.1) |
| Fourth quintile | 326,174 (20.1) | 8604 (21.1) | 6449 (20.9) | 43,279 (20.1) | 14,025 (20.5) | 40,367 (19.8) | 438,898 (20.1) |
| Highest quintile | 301,566 (18.6) | 9067 (22.2) | 6878 (22.2) | 46,484 (21.6) | 17,742 (26.0) | 53,702 (26.3) | 435,439 (20.0) |
| Healthcare usage | |||||||
| Rare | 319,960 (19.5) | 8519 (20.3) | 5985 (19.1) | 47,619 (21.3) | 13,413 (19.2) | 43,973 (20.7) | 439,469 (19.8) |
| Low | 366,807 (22.3) | 9020 (21.5) | 6774 (21.7) | 48,280 (21.6) | 15,181 (21.8) | 45,102 (21.2) | 491,164 (22.1) |
| Average | 347,589 (21.2) | 8758 (20.9) | 6637 (21.2) | 46,608 (20.9) | 14,364 (20.6) | 44,024 (20.7) | 467,980 (21.1) |
| High | 299,358 (18.2) | 7583 (18.1) | 5727 (18.3) | 40,091 (17.9) | 12,967 (18.6) | 38,760 (18.2) | 404,486 (18.2) |
| Frequent | 307,485 (18.7) | 7996 (19.1) | 6132 (19.6) | 40,788 (18.3) | 13,804 (19.8) | 40,696 (19.1) | 416,901 (18.8) |
| Time from invitation to participation, median (IQI) | 94 (42; 200) | 120 (72; 207) | 122 (53; 201) | 86 (36; 161) | 69 (29; 133) | 51 (28; 101) | 89 (39; 184) |
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IQI = interquartile interval; ISCED = International Standard Classification of Education; Information on cohabitation status was only available from Statistics Denmark until the end of February 2021, whereas all other socio-economic variables were available until end of the study period.
Participation during the COVID-19 pandemic
Figure 1 shows the participation in cervical cancer screening within 90, 180, and 365 d throughout the study period. Before the pandemic, approximately 36% of women participated in cervical cancer screening within 90 d, 54% of women participated within 180 d, and 65% of women participated within 365 d (Supplementary files 1–3).
Table 2
Prevalence ratios and 95% CIs of participation in cervical cancer screening in Denmark within 365 d since invitation from 2015–2021*.
| N | Pre-pandemic(01 January 2015–31 January 2020) | Pre-lockdown(01 February 2020–10 March 2020) | First lockdown(11 March 2020–15 April 2020) | First re-opening(16 April 2020–15 December 2020) | Second lockdown(16 December 2020–31 December 2020) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| N=164,1199 | N=41,876 | N=31,255 | N=223,386 | N=69,729 | |||||||
| PR | (95% CI) | PR | (95% CI) | PR | (95% CI) | PR | (95% CI) | PR | (95% CI) | ||
| Overall | 2,220,000 | 1.00 | - | 0.97 | (0.96; 0.98) | 0.97 | (0.96; 0.98) | 1.01 | (1.00; 1.01) | 0.99 | (0.97; 1.00) |
| Age at invitation | |||||||||||
| 23–29 y | 535,235 | 1.00 | - | 0.96 | (0.94; 0.98) | 0.98 | (0.95; 1.00) | 0.99 | (0.98; 1.00) | 1.00 | (0.96; 1.04) |
| 30–39 y | 559,296 | 1.00 | - | 0.97 | (0.95; 0.99) | 0.99 | (0.97; 1.01) | 1.01 | (1.00; 1.02) | 1.00 | (0.97; 1.04) |
| 40–49 y | 659,365 | 1.00 | - | 0.95 | (0.93; 0.96) | 0.94 | (0.92; 0.95) | 1.00 | (0.99; 1.01) | 0.93 | (0.90; 0.96) |
| 50–59 y | 336,786 | 1.00 | - | 1.01 | (0.99; 1.03) | 1.00 | (0.98; 1.02) | 1.02 | (1.01; 1.03) | 1.05 | (1.01; 1.08) |
| 60–64 y | 129,318 | 1.00 | - | 0.95 | (0.92; 0.99) | 0.93 | (0.90; 0.97) | 0.98 | (0.96; 1.00) | 0.93 | (0.87; 0.99) |
| Ethnicity | |||||||||||
| Danish descent | 1,773,076 | 1.00 | - | 0.96 | (0.95; 0.97) | 0.96 | (0.95; 0.97) | 1.00 | (1.00; 1.01) | 0.97 | (0.96; 0.99) |
| Descendant of immigrant | 43,902 | 1.00 | - | 0.95 | (0.86; 1.05) | 0.88 | (0.79; 0.98) | 0.97 | (0.92; 1.02) | 0.93 | (0.78; 1.12) |
| Western Immigrant | 120,162 | 1.00 | - | 1.03 | (0.98; 1.09) | 1.04 | (0.98; 1.11) | 1.09 | (1.06; 1.12) | 1.06 | (0.95; 1.17) |
| Non-western immigrant | 218,679 | 1.00 | - | 0.99 | (0.95; 1.02) | 0.98 | (0.94; 1.02) | 1.04 | (1.02; 1.06) | 1.07 | (1.00; 1.14) |
| Cohabitation status | |||||||||||
| Living alone | 633,585 | 1.00 | - | 0.97 | (0.95; 0.98) | 0.96 | (0.94; 0.98) | 1.02 | (1.01; 1.02) | 0.98 | (0.95; 1.02) |
| Cohabiting | 420,793 | 1.00 | - | 0.96 | (0.94; 0.98) | 0.97 | (0.95; 0.99) | 1.00 | (0.99; 1.01) | 1.00 | (0.96; 1.04) |
| Married | 892,913 | 1.00 | - | 0.97 | (0.96; 0.98) | 0.97 | (0.96; 0.99) | 1.00 | (1.00; 1.01) | 0.98 | (0.96; 1.01) |
| Educational level (ISCED) | |||||||||||
| ISCED15 level 1–2 | 1,297,050 | 1.00 | - | 0.96 | (0.95; 0.97) | 0.96 | (0.95; 0.98) | 1.01 | (1.00; 1.01) | 0.99 | (0.97; 1.01) |
| ISCED15 level 3–5 | 529,165 | 1.00 | - | 0.96 | (0.95; 0.98) | 0.97 | (0.95; 0.99) | 1.00 | (0.99; 1.01) | 0.97 | (0.94; 1.00) |
| ISCED15 level 6–8 | 319,925 | 1.00 | - | 1.00 | (0.98; 1.02) | 0.99 | (0.97; 1.02) | 1.04 | (1.03; 1.05) | 1.06 | (1.01; 1.10) |
| Disposable income | |||||||||||
| Lowest quintile | 419,122 | 1.00 | - | 0.95 | (0.93; 0.98) | 0.96 | (0.93; 0.98) | 1.02 | (1.01; 1.04) | 1.02 | (0.97; 1.07) |
| Second quintile | 422,225 | 1.00 | - | 0.95 | (0.92; 0.97) | 0.94 | (0.91; 0.96) | 1.00 | (0.99; 1.01) | 1.00 | (0.95; 1.04) |
| Third quintile | 424,081 | 1.00 | - | 0.96 | (0.94; 0.98) | 0.95 | (0.93; 0.97) | 0.99 | (0.98; 1.00) | 0.94 | (0.91; 0.98) |
| Fourth quintile | 425,069 | 1.00 | - | 0.96 | (0.95; 0.98) | 0.96 | (0.95; 0.98) | 1.00 | (0.99; 1.01) | 0.96 | (0.93; 0.99) |
| Highest quintile | 424,457 | 1.00 | - | 0.98 | (0.96; 0.99) | 0.96 | (0.95; 0.98) | 1.00 | (0.99; 1.00) | 0.97 | (0.95; 1.00) |
| Healthcare usage | |||||||||||
| Rare | 439,469 | 1.00 | - | 0.97 | (0.95; 0.99) | 0.97 | (0.95; 1.00) | 1.02 | (1.01; 1.03) | 0.99 | (0.94; 1.04) |
| Low | 491,164 | 1.00 | - | 0.97 | (0.95; 0.99) | 0.95 | (0.93; 0.97) | 1.00 | (0.99; 1.01) | 0.95 | (0.91; 0.99) |
| Average | 467,980 | 1.00 | - | 0.95 | (0.94; 0.97) | 0.95 | (0.93; 0.97) | 1.00 | (0.99; 1.01) | 1.00 | (0.97; 1.04) |
| High | 404,486 | 1.00 | - | 0.97 | (0.95; 0.98) | 0.96 | (0.94; 0.98) | 1.01 | (1.00; 1.02) | 0.99 | (0.96; 1.03) |
| Frequent | 416,901 | 1.00 | - | 0.97 | (0.95; 0.99) | 0.98 | (0.97; 1.00) | 1.00 | (0.99; 1.01) | 0.96 | (0.93; 1.00) |
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*Adjusted for month, year, and age at invitation; PR = prevalence ratio; ISCED = International Standard Classification of Education.
In March and April 2020, the participation in cervical cancer screening within 90 d dropped markedly to approximately 20% after which the participation resumed to normal levels (Figure 1). This was also reflected in a PR of 0.58 (95% CI: 0.56–0.59) during pre-lockdown and a PR of 0.76 (95% CI: 0.75–0.77) during first lockdown, resuming to PRs of 0.96–0.99 throughout the rest of the study period (Supplementary file 4).
A reduction in the participation in cervical cancer screening within 180 d was also observed among women invited at the start of the pandemic (Figure 2) reflected in a PR of 0.89 (95% CI: 0.88–0.90) during pre-lockdown and a PR of 0.92 (95% CI: 0.91–0.93) during first lockdown. From first re-opening and onwards, the level of participation within 180 d returned to pre-pandemic levels (Supplementary file 5).
Figure 2
Participation in cervical cancer screening in Denmark within 90, 180, and 365 d since invitation from 2015 to 2021.
The participation in cervical cancer screening within 365 d among women invited at the early phase of the pandemic was only slightly reduced (Figure 1), reflected in overall PRs of 0.97 (95% CI: 0.96–0.98) during both pre-lockdown and first lockdown where after the participation increased to the same level as before the pandemic (Table 2).
Participation during the COVID-19 pandemic by socio-economic variables
Before the pandemic, the participation in cervical cancer screening within 365 d was lowest among the youngest age group (57%), among immigrants (44–50% in immigrants and 38% in descendants of immigrants), among women living alone (56%), among women with the lowest income level (52%), and among women who rarely use the healthcare system (52%; Supplementary files 1-3).
During pre-lockdown and first lockdown, the participation in screening within 365 d was reduced among women aged 40–49 y old, 60–64 y old, among descendants of immigrants, among women with a low educational level, and a low income (Table 2).
Time to participation
The median time from invitation to participation was 94 d (IQR = 42–200) before the pandemic; however, this increased to 120 d (IQR = 72–207) among women invited during pre-lockdown and to 122 d (IQR = 53–201) during first lockdown. Thereafter, the time to participation resumed to 86 d during the first re-opening (Table 1).
Discussion
Main findings
In this population-based study, comprising 2,220,000 women invited for cervical cancer screening from 2015 to 2021 (in 1,466,353 individuals), we found a large decline in participation within 90 d since invitation during the early phase of the pandemic, a smaller decline in participation within 180 d, and only a slight reduction in participation within 365 d. The reduction in participation within 365 d was most pronounced among descendants of immigrants, among women with a low educational level, and a low income.
Comparison with previous studies and explanation of findings
In most countries, population-based screening for cervical cancer was halted at the start of the pandemic. This led to pronounced reductions in the number of women screened for cervical cancer during the early phase of the pandemic (Castanon et al., 2022; Cancer Registry of Norway, 2020; Meggetto et al., 2021). To our knowledge, no studies have described the long-term participation in cervical cancer screening during the pandemic. We found a marked reduction (42% in pre-lockdown and 24% in first lockdown) in the short term (within 90 d) cervical cancer screening participation at the start of the pandemic compared with the previous years. This reduction in participation could be explained either by a change in health behaviour or could perhaps reflect inconsistent messages from the health authorities at the start of the pandemic. The screening programme was open, and invitations and reminders were sent out; however, at the same time, the health authorities asked the population to stay at home at the national televised press conferences, and simultaneously, the College of General Practitioners recommended general practitioners to postpone routine cervical screening samples during a 4 wk period in March/April 2020 (Dansk Selskab for Almen Medicin, 2020). The inconsistent health messages could thus have led women to not participate in screening. Congruently, a Danish qualitative study found that inconsistent health communication from the authorities led women to postpone or cancel their screening appointments (Kirkegaard et al., 2021). With the longer follow-up time, we observed a less reduced participation (11% in pre-lockdown and 8% in first lockdown within 180 d and only 3% in both pre-lockdown and first lockdown within 365 d), which was reflected by the longer time to participation (>120 d versus approximately 89 d) at the early phase of the pandemic. The disruption to the cervical cancer screening programme in Denmark thus appear only to have a temporary effect with most women resuming cervical cancer screening with a longer follow-up period. This is in accordance with findings in a qualitative study showing that women were concerned about visiting healthcare settings during the pandemic but were willing to participate when screening programmes resumed (Wilson et al., 2021). The marked reduction in participation in screening during pre-lockdown and first lockdown could thus also reflect fear of infection among women at the early phase of the pandemic. During second lockdown, no overall change in participation was seen, indicating that the population had been accustomed to navigating the healthcare system during the pandemic. In the Danish cervical cancer screening programme, reminders are mailed to non-participants after 3 and 6 mo, and this could have prompted women postponing or cancelling their screening appointments at the start of the pandemic to participate at a later time point. Furthermore, the general health communication from the authorities changed throughout the pandemic initially, asking the population to stay at home and then later on reminding the population to seek healthcare when needed.
The severity of the pandemic and the pandemic response varied across the world with Denmark managing to keep the number of hospitalisations due to COVID-19 at relatively low level (Statens Serum Institut, 2021a). The pandemic response in Denmark included periodic lockdowns, extensive COVID-19 testing free-of-charge to the whole population (Pottegård et al., 2020), and a high COVID-19 vaccination coverage. The cervical cancer screening participation may therefore be different in other countries with a different pandemic response and a more severe impact of the pandemic.
Women of lower socio-economic position (Harder et al., 2018) and immigrant women Hertzum-Larsen et al., 2019; Badre-Esfahani et al., 2020 have earlier been shown to have a lower participation in cervical cancer screening. This was evident from our study also in that immigrants, women living alone, and women with a low-income level had the lowest participation in cervical cancer screening throughout the study period. A concern is that the pandemic may have affected socially disadvantaged individuals disproportionally. We found an overall 3% reduction in participation within 365 d; however, among descendants of immigrants and among women with a low income, a 5% reduction was seen, and among women with a low educational level, a 4% reduction was found. It is therefore important to ensure that all women – regardless of socio-economic position – resume participation in cervical cancer screening at the aftermath of the pandemic. To our knowledge, our study is the first to describe cervical cancer screening participation during the pandemic according to socio-economic groups.
A few previous studies have examined the participation in cervical cancer screening during the pandemic according to age groups. One study found that women aged 30–39 y old (Ivanuš et al., 2021) had the lowest participation in screening during the first 6 mo of the pandemic, whilst another study showed that the oldest age groups (50–59 and 60–69 y old; Walker et al., 2021) had the lowest cervical cancer screening participation during the first year of the pandemic. Additionally, a study by Castañon et al. estimated that women aged 40–49 y old would have the greatest burden of excess cervical cancer diagnoses due to a delay in screening because of the pandemic (Castanon et al., 2022). We found that women aged 40–49 y old and 60–64 y old had a lower than usual participation in cervical cancer screening at the start of the pandemic. The pandemic thus appears to affect different age groups differently; however, this finding could also be due to chance. Women aged 60–64 y old may have been hesitant to come into contact with the healthcare system because of fear of infection, possibly explaining the lower participation in this age group. Older individuals and individuals with underlying health conditions have a higher risk of a worse outcome if exposed to COVID-19 and the level of comorbidity increases with age, which could explain the lower participation in the oldest age group because of fear of infection. Surprisingly, this effect lasted even when examining participation within 365 d since invitation. A concern is therefore that some women did not resume screening even with the longest follow-up time. The lower participation among women aged 40–49 y old cannot be easily explained and could thus be due to chance.
Strengths and limitations
A major strength of the study is the high quality of data covering the entire population of women invited to participate in the cervical screening programme in Denmark. Danish national registers are known to be reliable and to have high completeness (Thygesen et al., 2011), which also confers to the Cervical Cancer Screening Database (Rygaard, 2016). While the quality of the Danish registers is high, some limitations relate to the data, for example, the study did not include data on comorbidities, which may affect participation in screening during the pandemic as individuals with underlying disease where advised to self-isolate at the height of the pandemic. However, as age is strongly associated with the level of comorbidity, the inclusion of age in the statistical model reduces the theoretical impact of comorbidity on the results.
Implications of the findings
Our findings show that the overall participation in cervical cancer screening was almost at the same level as the previous years when allowing for the longest follow-up time; however, some groups had slightly lower participation (descendants of immigrants, women with a low educational level, and women with a low income), and it is therefore important to ensure that all women re-enter the cervical cancer screening programme at the aftermath of the pandemic. Our results also show that some age groups (women aged 40–49 y old and 60–64 y old) had a lower participation in screening than usual, possibly indicating that the restrictions within a society affects different age groups disproportionally, although this finding may be due to chance. It is thus important to take this information into account when planning a pandemic response and ensure that all women have access to screening.
Contrasting health messages may have been conveyed by the cervical cancer screening programme being open, the general practitioners recommending a postponement of cervical cancer screening tests, and at the same time, the health authorities recommending people to stay at home. Inconsistent health communication from the authorities may therefore have led some women to refrain from participating in screening. The health communication therefore needs to be precise and consistent.
Conclusion
The cervical cancer screening programme continued throughout the COVID-19 pandemic in Denmark. The participation was reduced at the early phase of the pandemic; however, most women resumed screening with the longest follow-up time, although women of lower socio-economic position had slightly lower participation than usual.
Data availability
Data availability statement In order to comply with the Danish regulations on data privacy, the datasets generated and analysed during this project are not publicly available as the data are stored and maintained electronically at Statistics Denmark, where it only can be accessed by pre-approved researchers using a secure VPN remote access. Furthermore, no data at a personal level nor data not exclusively necessary for publication are allowed to be extracted from the secure data environment at Statistics Denmark. Access to the data can; however, be granted by the authors of the present study upon a reasonable scientific proposal within the boundaries of the present project and for scientific purposes only.
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Decision letter
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Talía MalagónReviewing Editor; McGill University, Canada
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Diane M HarperSenior Editor; University of Michigan, United States
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Maarit LeinonenReviewer; Finnish Institute for Health and Welfare, Finland
Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.
Decision letter after peer review:
Thank you for submitting your article "Participation in the nation-wide cervical cancer screening programme in Denmark during the COVID-19 pandemic: An observational study" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Diane Harper as the Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: Maarit Leinonen (Reviewer #2).
The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.
Essential revisions:
1) Please consider including a formal test of the time*socioeconomic variable interaction to address both reviewers' concerns regarding the role of chance when seeing differences of effect across groups.
2) Address requests for clarifications in methods by reviewers below.
3) Consider discussing the role that fear may have played in determining cervical cancer screening participation during the pandemic.
Reviewer #1 (Recommendations for the authors):
Overall great study, I have very few comments:
• Please consider having the 90-day results as the main outcome presented in the main text for the model regression; I think these are most informative as the potentially highest impact that COVID-19 can have on screening participation.
• Please consider including a formal test of the time*socioeconomic variable interaction in the Poisson regression to assess whether there are differences between groups of women in their screening participation over time. This would allow for example assessing whether there is good support for women of different ages being differently impacted by the pandemic in their screening participation.
• It would be worth mentioning if there was any effort made by the screening program to incite women to screen which would explain why 90-day participation dropped but 365-day participation did not, ex. were any reminders sent to women who do not participate by a certain time or were there any public health messaging campaigns?
• For the median and IQI time from invitation to participation, it is not clear whether this statistic is calculated among all women invited, or only among the invited women who eventually participated in screening (excludes women who do not respond to invitation). Please clarify.
Reviewer #2 (Recommendations for the authors):
I recommend publishing this paper, but I have a few concerns which I summarize here.
My major concern is the study methods which are occasionally a bit hard to follow. The authors write that the study population comprised all screening-aged women from 1 January 2015 to 30 September 2021. Thus, was data on cervical cytology samples from the Danish Pathology Register extracted up to 30 September 2020? Also, the exposure of interest was the COVID-pandemic is a bit unclear. I assume that exposure is invitation to screening during the pre-pandemic period and COVID-pandemic. If that is the case, authors should make it clear that time periods refer to the time on invitation and not the time of outcome i.e. cervical cancer screening test. Also, the authors write that pre-lockdown and 1st lockdown was the start of the pandemic. There cannot be two starting points unless there are sensitivity analyses in which the onset varies. Thus, define clearly what is the starting point 1st February or 11 March 2020. In supplementary tables 1 to 3 time period for 2nd lockdown varies which is confusing. Please clarify the periods for exposure, outcome, and covariates.
Authors write that women who unregistered from the screening programme within 1 year since invitation (n=56,920) were excluded. Is there any information on who are these women and what are the reasons for unregistration? If those who are at higher risk of cancer and with lower participation rates unregister themselves, the compliance to screening could be overestimated.
Authors find that some age groups i.e. women aged 40-49 and those aged 60-64 years had a lower participation rate and conclude that it could indicate that the restrictions within a society affect different age groups disproportionally. The authors do not try to explain the finding and it should be scrutinized to rule out a chance. Comorbidity is strongly associated with age so if this is attributed to self-isolation, there should be a gradient. Why 50-59 years old would be different from 60-64 years? Have e.g. possible interactions between demographic and socioeconomic variables been taken into account in the analyses? The number of average health care visits 7-11 visits per year seems extremely high average for the mainly working-age population which in general is quite healthy. How these categories were decided? A priori or after exploring the data? If former, is there a reference that provides information on the average use of health care services?
Authors have cited the work by Wilson et al. (Ref # 22) in which only 4.1% of respondents were worried about catching coronavirus if they went for screening. Authors could add some discussion and references concerning fear and overall healthcare utilization during the early phase of the pandemic.
lines 73-76 authors write that prioritisations and re-organisations were done within the healthcare system to ensure the capacity to take care of patients in need of hospitalization due to COVID-19. While in Denmark laymen were trained for COVID-19 sample taking, in many other countries health care personnel were needed for sample taking and laboratory analytics. Thus, the possible lack of resources in screening programmes was not only due to hospitalized patients.
lines 204-205: Authors have adjusted for the year of invitation due to decreasing trend in screening uptake. Is there a reference for this? Any explanations for the trend? Could it be, for instance, increasing diversity in the screening population?
lines: 360-361: Authors write that women should be well-informed when they can safely participate in cervical cancer screening during the pandemic. When it is safe to participate? What is the definition of safe participation? Service providers can of course do risk mitigation interventions but who can guarantee that nobody will ever catch an infection? Consider rephrasing.
Table 1. Why the cohabitation status is not available for the latest period (2nd re-opening)?
Supplementary Figures. I assume that the authors want to demonstrate monthly variations and the dip in 1st lockdown. That is already provided in Figure 1. The same pattern is seen in all covariates and categories so perhaps not needed to repeat here. Curves are hard to interpret. There is an exhaustive list of supplementary material, that does not seem to provide any important value for the paper.
https://doi.org/10.7554/eLife.81522.sa1Author response
Essential revisions:
1) Please consider including a formal test of the time*socioeconomic variable interaction to address both reviewers' concerns regarding the role of chance when seeing differences of effect across groups.
Thank you for raising the relevant point of interaction. Initially we opted to address the possible effect of interaction by using a stratifying approach. This choice was taken to ease the readability and interpretation for a wide range of readers. However, we do acknowledge that some readers will prefer also to see an explicit statistical test for interaction and we have therefore tested for all interactions between time*socioeconomic variables. These tests are all statistically significant.
Still, that to ease the readability and interpretation, we argue that we will keep only to report the estimates and confidence intervals for the stratified analyses, as this approach provides interpretable estimates. However, to accommodate the request from the reviewers, we have added in manuscript that we have undertaken these formal interaction test, and that these were statistically significant (page 6, lines 221-225).
2) Address requests for clarifications in methods by reviewers below.
We have clarified these requests below.
3) Consider discussing the role that fear may have played in determining cervical cancer screening participation during the pandemic.
Thank you for this comment. We have elaborated on the role of fear of infection in the Discussion section (page 9, lines 315-318 and page 10, line 354-361).
Reviewer #1 (Recommendations for the authors):
Overall great study, I have very few comments:
• Please consider having the 90-day results as the main outcome presented in the main text for the model regression; I think these are most informative as the potentially highest impact that COVID-19 can have on screening participation.
Thank you for this comment. We have opted to present the 365-day participation as the main outcome since we consider the long-term participation as the most important outcome of significance for the population. Cervical cancer screening is about prevention and a relatively short postponement of screening participation is assumed not to cause much harm. We therefore present the 90- and 180-day participation as supplementary tables.
• Please consider including a formal test of the time*socioeconomic variable interaction in the Poisson regression to assess whether there are differences between groups of women in their screening participation over time. This would allow for example assessing whether there is good support for women of different ages being differently impacted by the pandemic in their screening participation.
Thank you for this comment. Please see the response above.
• It would be worth mentioning if there was any effort made by the screening program to incite women to screen which would explain why 90-day participation dropped but 365-day participation did not, ex. were any reminders sent to women who do not participate by a certain time or were there any public health messaging campaigns?
Thank you for this comment. As stated in the Methods section (page 4 lines 117-119) and the Discussion section (page 9 lines 318-321) reminders to participate in cervical cancer screening were mailed as per routine to non-participants after 3 months and again after 6 months. No additional efforts were made at an individual level during the pandemic; however, the general health communication changed during the pandemic reminding the population to continue to seek healthcare. We have added this in the Discussion section (page 9, lines 321-324).
• For the median and IQI time from invitation to participation, it is not clear whether this statistic is calculated among all women invited, or only among the invited women who eventually participated in screening (excludes women who do not respond to invitation). Please clarify.
Thank you for this comment. We have clarified this sentence in the Methods section (page 6, lines 210-211), stating that time to participation was calculated among women eventually participating in the screening program.
Reviewer #2 (Recommendations for the authors):
I recommend publishing this paper, but I have a few concerns which I summarize here.
My major concern is the study methods which are occasionally a bit hard to follow. The authors write that the study population comprised all screening-aged women from 1 January 2015 to 30 September 2021. Thus, was data on cervical cytology samples from the Danish Pathology Register extracted up to 30 September 2020?
Thank you for this comment. To ensure at least 90 days complete follow-up on all tests, the data on cervical cytology samples covered up until 31 December 2021. We have added this in the Methods section (page 5, lines 165-170).
Also, the exposure of interest was the COVID-pandemic is a bit unclear. I assume that exposure is invitation to screening during the pre-pandemic period and COVID-pandemic. If that is the case, authors should make it clear that time periods refer to the time on invitation and not the time of outcome i.e. cervical cancer screening test.
Thank you for this comment. We have clarified this in the Methods section (page 5, lines 175-177).
Also, the authors write that pre-lockdown and 1st lockdown was the start of the pandemic. There cannot be two starting points unless there are sensitivity analyses in which the onset varies. Thus, define clearly what is the starting point 1st February or 11 March 2020.
Thank you for this comment. We have clarified this by using the terms pre-lockdown and 1st lockdown throughout the manuscript instead.
In supplementary tables 1 to 3 time period for 2nd lockdown varies which is confusing. Please clarify the periods for exposure, outcome, and covariates.
Thank you for this comment. The time periods stated in the Supplementary Table 1-3 are correct. This is because of the difference in observation periods that is, participation in screening within 90 days (Supplementary Table 1), within 180 days (Supplementary Table 2) and within 365 days (Supplementary Table 3) since invitation. In Supplementary Table 3, the end of the inclusion period is 31 December 2020 to allow for 365 days of observation. We have clarified this in the Methods section (page 5, lines 165-170).
Authors write that women who unregistered from the screening programme within 1 year since invitation (n=56,920) were excluded. Is there any information on who are these women and what are the reasons for unregistration? If those who are at higher risk of cancer and with lower participation rates unregister themselves, the compliance to screening could be overestimated.
Thank you for this comment. Theoretically we do agree with this point. However, as these 56,920 women only constitutes 2.5% of all invited women, the theoretical bias to the participation rate (compliance to the programme) is minimal. However, as the paper focus on the relationship between the phases of the COVID-19 pandemic and participation rates in cervical cancer screening, for the risk of the number of unregistrations to be troublesome, it has to be associated with the phases of the pandemic. However, the women unregistered throughout both the reference period and the pandemic period, and thus the risk of bias is minimal. So in order to keep our already comprehensive paper as concise and readable as possible, we argue not to provide this to the manuscript as this cannot explain any of our findings.
Authors find that some age groups i.e. women aged 40-49 and those aged 60-64 years had a lower participation rate and conclude that it could indicate that the restrictions within a society affect different age groups disproportionally. The authors do not try to explain the finding and it should be scrutinized to rule out a chance. Comorbidity is strongly associated with age so if this is attributed to self-isolation, there should be a gradient. Why 50-59 years old would be different from 60-64 years? Have e.g. possible interactions between demographic and socioeconomic variables been taken into account in the analyses?
Thank you for this comment. We have elaborated on both age, comorbidity and chance findings in the Discussion section (page 10, line 353-363 and page 11, line 384). As stated in the Methods section, all analyses were adjusted for age to take into account the effect of age on the other explanatory variables (page 6, lines 219-221).
The number of average health care visits 7-11 visits per year seems extremely high average for the mainly working-age population which in general is quite healthy. How these categories were decided? A priori or after exploring the data? If former, is there a reference that provides information on the average use of health care services?
Thank you for this comment. As stated in the Methods section (page 6, lines 191-198), the number of healthcare visits comprise the total number of contacts to general practitioners, private practising medical specialists, physiotherapists, and chiropractors. It is understandable that 7-11 visits per year may seem quite high for a non-Danish reader. However, a woman aged 30-64 years in Denmark contacts their general practitioner (primary care physician) just over 8 times per year (reference in Danish: https://www.sdu.dk/da/sif/ugens_tal/04_2017). The reason these numbers are high is that healthcare contacts covers both face-to-face, telephone, and e-mail consultations in Denmark. The categories were made using the nearest number of contacts to 20th, 40th, 60th, and 80th percentiles in the data, thus the categories broadly reflects the quintiles. We have clarified this in the Methods section (pages 5-6, lines 191-198).
Authors have cited the work by Wilson et al. (Ref # 22) in which only 4.1% of respondents were worried about catching coronavirus if they went for screening. Authors could add some discussion and references concerning fear and overall healthcare utilization during the early phase of the pandemic.
Thank you for this comment. We have elaborated on the role of fear of infection in the Discussion section (page 9, lines 315-318 and page 10, line 354-361).
lines 73-76 authors write that prioritisations and re-organisations were done within the healthcare system to ensure the capacity to take care of patients in need of hospitalization due to COVID-19. While in Denmark laymen were trained for COVID-19 sample taking, in many other countries health care personnel were needed for sample taking and laboratory analytics. Thus, the possible lack of resources in screening programmes was not only due to hospitalized patients.
Thank you for this comment. We have clarified this in the Methods section (page 4, lines 132-134).
lines 204-205: Authors have adjusted for the year of invitation due to decreasing trend in screening uptake. Is there a reference for this? Any explanations for the trend? Could it be, for instance, increasing diversity in the screening population?
Thank you for this comment. We have added a reference to the annual report from the Cervical Cancer Screening Database in the Methods section (page 6, line 219), which on page 16 shows the decreasing participation in cervical cancer screening in Denmark. We have not elaborated on the reason for the decreasing participation in cervical cancer screening as this is beyond the scope of our study; however, this could be due to an increasing diversity in the population or due to the implementation of the HPV vaccination programme.
lines: 360-361: Authors write that women should be well-informed when they can safely participate in cervical cancer screening during the pandemic. When it is safe to participate? What is the definition of safe participation? Service providers can of course do risk mitigation interventions but who can guarantee that nobody will ever catch an infection? Consider rephrasing.
Thank you for this comment. We have re-phrased this sentence in the Discussion section (page 11, lines 392-394).
Table 1. Why the cohabitation status is not available for the latest period (2nd re-opening)?
Thank you for this comment. These data were unfortunately not available at Statistics Denmark at the time of the study, as this information is only updated yearly for research purposes. We have stated this in the Methods section (page 6, lines 200-202) and in a foot note to Table 1 and Supplementary Tables 1, 2, 4 and 5.
Supplementary Figures. I assume that the authors want to demonstrate monthly variations and the dip in 1st lockdown. That is already provided in Figure 1. The same pattern is seen in all covariates and categories so perhaps not needed to repeat here. Curves are hard to interpret. There is an exhaustive list of supplementary material, that does not seem to provide any important value for the paper.
Thank you for this comment. We have omitted Supplementary Figure 2-4.
https://doi.org/10.7554/eLife.81522.sa2Article and author information
Author details
Funding
The Danish Cancer Society (R321-A17417)
- Tina Bech Olesen
The Danish regions
- Tina Bech Olesen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Acknowledgements
We would like to thank Flemming Bro, MD, PhD, GP, Senior researcher from the Research Unit for General Practice, Aarhus for his valuable comments to the manuscript.
Ethics
Human subjects: Ethical considerations The study is registered at the Central Denmark Region's register of research projects (journal number 1-16-02-381-20). Patient consent is not required by Danish law for register-based studies.
Senior Editor
- Diane M Harper, University of Michigan, United States
Reviewing Editor
- Talía Malagón, McGill University, Canada
Reviewer
- Maarit Leinonen, Finnish Institute for Health and Welfare, Finland
Publication history
- Received: June 30, 2022
- Preprint posted: August 23, 2022 (view preprint)
- Accepted: January 17, 2023
- Accepted Manuscript published: January 20, 2023 (version 1)
- Version of Record published: February 7, 2023 (version 2)
Copyright
© 2023, Olesen et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Participation in the nationwide cervical cancer screening programme in Denmark during the COVID-19 pandemic: An observational study
eLife 12:e81522.
https://doi.org/10.7554/eLife.81522
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Background:
Affectionate touch, which is vital for mental and physical health, was restricted during the Covid-19 pandemic. This study investigated the association between momentary affectionate touch and subjective well-being, as well as salivary oxytocin and cortisol in everyday life during the pandemic.
Methods:
In the first step, we measured anxiety and depression symptoms, loneliness and attitudes toward social touch in a large cross-sectional online survey (N = 1050). From this sample, N = 247 participants completed ecological momentary assessments over 2 days with six daily assessments by answering smartphone-based questions on affectionate touch and momentary mental state, and providing concomitant saliva samples for cortisol and oxytocin assessment.
Results:
Multilevel models showed that on a within-person level, affectionate touch was associated with decreased self-reported anxiety, general burden, stress, and increased oxytocin levels. On a between-person level, affectionate touch was associated with decreased cortisol levels and higher happiness. Moreover, individuals with a positive attitude toward social touch experiencing loneliness reported more mental health problems.
Conclusions:
Our results suggest that affectionate touch is linked to higher endogenous oxytocin in times of pandemic and lockdown and might buffer stress on a subjective and hormonal level. These findings might have implications for preventing mental burden during social contact restrictions.
Funding:
The study was funded by the German Research Foundation, the German Psychological Society, and German Academic Exchange Service.
