Study design
The Japan COVID-19 and Society Internet Survey (JACSIS) was designed to investigate the social and health situation related to the COVID-19 pandemic using an epidemiological approach. In 2020, a total of 28,000 respondents, aged 15–79 years, were selected from 224,389 candidates who received an e-mail invitation among the approximately 2.2 million panelists registered with a Japanese internet survey agency (Rakuten Insight, Inc., Tokyo, Japan https://in.m.aipsurveys.com). A random sampling method was used to recruit participants using a computer algorithm; the sample was representative of the official Japanese demographic composition as of October 1, 2019 based on categories of age, sex, and living area (i.e., prefecture).
All participants provided web-based informed consent before responding to the online self-report questionnaire.
More specific information pertaining to the JACSIS, along with a detailed description of the method used to recruit participants is described in the Supplementary Methods. The present study employed a cross-sectional design intended to detect changes in biopsychosocial and socioeconomic factors before and after the COVID-19 outbreak.
Study Population
Of 28,000 participants in the JACSIS, we analyzed data from 25,482 participants (12,809 women and 12,673 men) after excluding 2,518 participants who provided invalid responses or met other exclusion criteria; these measures to consistently validate the data quality were performed as described in previous studies 18,19. The participants with invalid responses were detected through the use of a dummy item, which stated, “Please choose the option second from the bottom.” Participants who selected any option other than the one indicated were excluded (n = 1,955). Participants using all recreational substances and medications (i.e., sleeping pills, anxiolytic agents, legal/illegal opioids, cannabis, cocaine, etc.) were excluded, as were those with all chronic diseases (i.e., diabetes, asthma, stroke, ischemic heart disease, cancer, mental disease, etc.); this resulted in the exclusion of 422 and 141 participants, respectively. The characteristics of the 25,482 participants who were included in the final analysis are shown in Supplementary Table 1.
Main Outcome Measures
Loneliness during the COVID-19 pandemic
A Japanese version of the University of California, Los Angeles Loneliness Scale (Version 3), Short Form 3-item (UCLA-LS3-SF3) was used to assess loneliness; the scale was originally developed in English, although both the English and Japanese versions have previously been determined to be valid and reliable 20,21. The items were as follows: 1) “How often do you feel that you lack companionship?”; 2) “How often do you feel left out?”; and 3) “How often do you feel isolated from others?” Participants were asked to rate the frequency in which these feelings were experienced over the past 30 days using a five-point scale, ranging from 1 to 5 [1 (Never), 2 (Rarely), 3 (Sometimes), 4 (Often), 5 (Always)]; this was modified from the original UCLA-LS3-SF3, which used a four-point frequency scale. The total UCLA-LS3-SF3 scores in the current study ranged from 3 to 15, with higher scores indicating more severe loneliness. We defined those in the first tertile (3 points), the second tertile (4–5 points), and the third tertile (6–15 points) of the UCLA-LS3-SF3 scores as having ‘no loneliness’, ‘mild loneliness’, and ‘moderate-to-severe loneliness’, respectively. The Cronbach’s alpha value of the internal consistency for the three items was 0.93.
Perception of increased social isolation during the COVID-19 pandemic
The following single question was utilized to measure the perception of increased social isolation during the COVID-19 pandemic: “How often do you feel increased isolation from others compared with how you felt before the COVID-19 outbreak (prior to January 2020)?” The ratings were based on the same five-point frequency scale as the UCLA-LS3-SF3, with responses scored as follows: never (1), rarely (2), sometimes (3), often (4), or always (5). This question was an adaptation of the third item of the UCLA-LS3-SF3; it was modified for the JACSIS to better capture changes in the perceived social isolation between the pre- and post-COVID-19 outbreak timepoints.
Pain
Prevalence And Incidence Of Pain
Participants were asked if they had a headache, neck or shoulder pain, upper limb pain, low back pain, or leg pain; for each type of pain, the responses were categorized as follows: “none”, “yes, it developed before the COVID-19 outbreak”, or “yes, it developed during the COVID-19 pandemic.” Based on these responses, the participants were classified based on one of the following three categories: without pain, the presence of pain since before the COVID-19 outbreak, and pain beginning during the COVID-19 pandemic.
Pain Intensity
Table 3 indicates the differences in reported pain intensity according to the UCLA-LS3-SF3 scoring groups and the frequency with which participants reported an increase in feelings of social isolation. Compared to participants who did not experience loneliness or increased social isolation, those who did reported more severe pain intensity. In Model 2, for individuals who reported any pain symptoms, the adjusted mean pain intensity values among those reporting a lack of loneliness, mild loneliness, and moderate-to-severe loneliness were 1.5, 1.6, and 1.8, respectively; among those reporting increased feelings of social isolation during the COVID-19 pandemic, the adjusted mean pain intensity values for the five frequencies were 1.6, 1.7, 1.8, 1.9, and 2.0.
Table 3
The association of loneliness and a feeling of increased social isolation with pain intensity
|
Degree of loneliness
|
|
|
|
|
|
|
None
3 points
n = 14,277
|
Mild
4–5 points
n = 3,250
|
Moderate-to-severe
6–15 points
n = 7,955
|
P for trend
|
|
|
|
|
|
Adjusted mean
|
SE
|
Adjusted mean
|
SE
|
Adjusted mean
|
SE
|
|
|
|
|
Pain intensity for total participants, n = 25,482
|
|
|
|
|
Model 1
|
1.3
|
0.01
|
1.5***
|
0.01
|
1.7***
|
0.01
|
< 0.001
|
|
|
|
|
Model 2
|
1.3
|
0.01
|
1.5***
|
0.01
|
1.6***
|
0.01
|
< 0.001
|
|
|
|
|
Pain intensity for individuals with any pain symptoms, n = 15,541
|
|
|
|
|
Model 1
|
1.5
|
0.01
|
1.6***
|
0.02
|
1.8***
|
0.01
|
< 0.001
|
|
|
|
|
Model 2
|
1.5
|
0.01
|
1.6***
|
0.01
|
1.8***
|
0.01
|
< 0.001
|
|
|
|
|
|
Frequency of feelings of increased social isolation
during the COVID-19 pandemic
|
|
Never
n = 18,168
|
Rarely
n = 3,188
|
Sometimes
n = 2,454
|
Often
n = 1,033
|
Always
n = 639
|
P for trend
|
|
Adjusted mean
|
SE
|
Adjusted mean
|
SE
|
Adjusted mean
|
SE
|
Adjusted mean
|
SE
|
Adjusted mean
|
SE
|
|
Pain intensity total participants, n = 25,482
|
|
|
|
Model 1
|
1.4
|
0.01
|
1.5***
|
0.01
|
1.6***
|
0.01
|
1.8***
|
0.02
|
2.0***
|
0.03
|
< 0.001
|
Model 2
|
1.4
|
0.01
|
1.5***
|
0.01
|
1.6***
|
0.01
|
1.7***
|
0.02
|
1.8***
|
0.03
|
< 0.001
|
Pain intensity for individuals with any pain symptoms, n = 15,541
|
|
|
Model 1
|
1.5
|
0.01
|
1.7***
|
0.02
|
1.8***
|
0.02
|
2.0***
|
0.03
|
2.1***
|
0.03
|
< 0.001
|
Model 2
|
1.6
|
0.01
|
1.7***
|
0.01
|
1.8***
|
0.02
|
1.9***
|
0.03
|
2.0***
|
0.03
|
< 0.001
|
Model 1: Adjusted for age and sex. |
Model 2: Adjusted for age, sex, educational level, marital status, living alone, employment status, equivalized household income, smoking status, alcohol consumption, physical activity, sleep duration, history of depression, and history of mental illnesses other than depression. |
History And Prevalence Of Chronic Pain
Table 4 indicates that loneliness and a feeling of increased social isolation were both positively associated with the history and prevalence of chronic pain.
Table 4
The association of loneliness and a feeling of increased social isolation with the history/prevalence of chronic pain during the COVID-19 pandemic
|
Degree of loneliness
|
P for trend
|
|
|
|
None
3 points
n = 14,277
|
Mild
4–5 points
n = 3,250
|
Moderate-to-Severe
6–15 points
n = 7,955
|
|
|
Number with history of chronic pain but already recovered
|
734
|
241
|
622
|
|
|
|
Number with presence of chronic pain
|
1,134
|
396
|
1,118
|
|
|
|
Model 1
|
|
OR (95% CI)
|
OR (95% CI)
|
|
|
|
History of chronic pain but already recovered vs. without history of chronic pain
|
1
|
1.60 (1.37–1.86)***
|
2.02 (1.80–2.27)***
|
< 0.001
|
|
|
Presence of chronic pain vs. without history of chronic pain
|
1
|
1.71 (1.51–1.93)***
|
2.44 (2.23–2.68)***
|
< 0.001
|
|
|
Model 2
|
|
|
|
|
|
|
History of chronic pain but already recovered vs. without history of chronic pain
|
1
|
1.42 (1.22–1.66)***
|
1.56 (1.38–1.77)***
|
< 0.001
|
|
|
Presence of chronic pain vs. without history of chronic pain
|
1
|
1.54 (1.36–1.74)***
|
1.81 (1.64–2.00)***
|
< 0.001
|
|
|
|
Frequency of feeling of increased social isolation during the COVID-19 pandemic
|
|
|
Never
n = 18168
|
Rarely
n = 3188
|
Sometimes
n = 2454
|
Often
n = 1033
|
Always
n = 639
|
P for trend
|
Number with history of chronic pain but already recovered
|
1,007
|
265
|
170
|
103
|
52
|
|
Number with presence of chronic pain
|
1,707
|
392
|
282
|
163
|
104
|
|
Model 1
|
|
OR (95% CI)
|
OR (95% CI)
|
OR (95% CI)
|
OR (95% CI)
|
|
History of chronic pain but already recovered vs. without history of chronic pain
|
1
|
1.69 (1.47–1.95)***
|
1.54 (1.30–1.83)***
|
2.65 (2.12–3.30)***
|
2.14 (1.59–2.88)***
|
< 0.001
|
Presence of chronic pain vs. without history of chronic pain
|
1
|
1.48 (1.32–1.67)***
|
1.55 (1.35–1.78)***
|
2.47 (2.07–2.94)***
|
2.63 (2.11–3.29)***
|
< 0.001
|
Model 2
|
|
|
|
|
|
|
History of chronic pain but already recovered vs. without history of chronic pain
|
1
|
1.44 (1.25–1.67)***
|
1.32 (1.11–1.58)**
|
1.91 (1.51–2.41)***
|
1.48 (1.09–2.02)**
|
< 0.001
|
Presence of chronic pain vs. without history of chronic pain
|
1
|
1.26 (1.12–1.43)**
|
1.28 (1.11–1.48)*
|
1.73 (1.42–2.10)***
|
1.55 (1.21–1.97)*
|
< 0.001
|
Model 1: Adjusted for age and sex. |
Model 2: Adjusted for age, sex, educational level, marital status, living alone, employment status, equivalized household income, smoking status, alcohol consumption, physical activity, sleep duration, history of depression, and history of mental illnesses other than depression. |
Potential Confounders
Potential confounders were mainly adapted from previous population-based cohort studies that have examined the associations between psychosocial factors and pain experience [35–37]. These included demographic factors, socioeconomic factors, lifestyle factors, and a history of diseases related to the explanatory and outcome variables.
Demographic factors
We collected data on age (15–19, 20–29, 30–39, 40–49, 50–59, 60–69, or 70–79 years), sex (women or men), and body mass index (quintiles).
Socioeconomic factors
We collected data on the level of education completed (less than high school, high school, vocational school, junior or technical college, university, graduate school, or other), marital status (married or common-law, single, divorced, or widowed), whether the individual was living alone (yes or no), employment status (company executive, owner of a family-operated business, employee of a family-operated business, management-level employee, full-time employee, contract employee, part-time employee/on-the-side worker, student, retired, full-time homemaker, or unemployed), and equivalized household income (categorized into quintiles).
Equivalized household income was calculated by dividing the median value of the multiple-choice annual household income before-tax by the square root of the number of people living in the household. We defined poverty as an annual equivalized household income of less than 1.22 million JPY, which was the poverty line in 2018 as defined by the Organisation for Economic Co-operation and Development 22.
Life style
We collected data on smoking status (non-smoker, ex-smoker, or current smoker), alcohol consumption (never, ex-drinker, social drinker, < 23 g per day, 23–45 g per day, or ≥ 46 g per day), changes in physical activity before and after the COVID-19 outbreak (decreased, no change, or increased), and sleep duration (< 4 hours, 4–5 hours, 6–7 hours, 8–9 hours, ≥ 10 hours, or hard to respond/unsure). We defined any individual with alcohol consumption ≥ 46 g per day as a heavy drinker.
History of mental diseases
We collected data on the history of depression (categorized as none, a history of depression but already recovered, or comorbid depression) and the history of mental illnesses other than depression (categorized as none, a history of mental illness other than depression but already recovered, or comorbid mental illness other than depression).
Statistical analysis
First, we determined the P for trend of the means and proportions of potential confounders according to the severity of loneliness based on the UCLA-LS3-SF3 scoring groups and the frequency in which participants felt increased social isolation during the COVID-19 pandemic using a general linear model.
Second, we examined the association of loneliness and increased social isolation and the prevalence/incidence of pain experienced during the COVID-19 pandemic. The odds ratios (ORs) of the prevalence and incidence of pain (i.e., headache, neck or shoulder pain, upper limb pain, low back pain, or leg pain) according to the UCLA-LS3-SF-3 scoring groups were calculated using a multinomial logistic regression model, with adjustment for potential confounders.
Third, the overall adjusted mean values of pain intensity for all participants and for individuals with any pain symptoms according to the UCLA-LS3-SF3 scoring groups and the frequency in which feelings of increased social isolation were experienced during the COVID-19 pandemic were tested using an analysis of covariance, with Dunnett’s test. Individuals with any pain symptoms were defined as those with headache, neck/shoulder pain, upper limb pain, low back pain, leg pain, or the presence of chronic pain. P values were calculated to compare those reporting a lack of loneliness or those who did not feel an increase in social isolation during the COVID-19 pandemic at all to those of all the other categories.
Finally, we examined the association between the loneliness and increased social isolation felt during the COVID-19 pandemic and the history/prevalence of chronic pain. The ORs of the history and prevalence of chronic pain according to the UCLA-LS3-SF3 scoring groups and the frequency of feelings of increased social isolation were calculated using a multinomial logistic regression model, adjusted for potential confounders.
A multinomial logistic regression analysis is often used to estimate multiple categorical outcomes (i.e., the prevalence/incidence of pain and the history/prevalence of chronic pain).
In addition to the ORs, the P for trends according to the UCLA-LS3-SF3 scoring groups and the frequency of feelings of increased social isolation during the COVID-19 pandemic were calculated using a general linear model.
Model 1 was adjusted for age and sex, whereas Model 2 was adjusted for age, sex, level of education, marital status, living arrangement (living alone or not), employment status, equivalized household income, smoking status, alcohol consumption, physical activity, sleep duration, history of depression, and history of mental illnesses other than depression.
Missing values of potential confounders were used as dummy variables. P values < 0.05 (two-tailed tests) were considered statistically significant. All statistical analyses were performed using Statistical Analysis Software (SAS), Version 9.4 (SAS Institute Inc., Cary, NC, USA).
Ethical Issues
All procedures were conducted in accordance with the ethical standards of the Helsinki Declaration of 1975, as revised in 2013.
The study protocol was reviewed and approved by the Research Ethics Committee of the Osaka International Cancer Institute (approved on June 19, 2020; approval number 20084).
The internet survey agency respected the Act on the Protection of Personal Information in Japan.
All participants provided web-based informed consent before responding to the online questionnaire.
This study was exempted from the obligation to obtain informed consent from the parents/guardians of minors under the age of 18 in Japan. The Ethical Guidelines for Medical and Health Research Involving Human Subjects enforced by Japan’s Ministry of Education, Culture, Sports, Science and Technology and Japan’s Ministry of Health, Labour and Welfare addressed, “When the research subject has completed junior high school or other relevant schooling, or is 16 years or older, and is considered to have enough judgment concerning the research to be implemented on him/herself, as well as the following matters are prescribed in the research protocol and the chief executive of the research implementing entity approves to carry out the research after relevant ethical review committee deliberation, informed consent shall be obtained not from representative but from the said research subject. (i) The research to be implemented does not involve any invasiveness; and (ii) Information concerning implementation of the research, including purpose of the research and how specimens or information will be handled, is made public, and opportunities to refuse that the research is commenced or continued on the research subject are ensured for persons who exercise parental authority over the said research subject and guardians of the minor 23.” All participants completed junior high school, the present study did not involve any invasiveness, and obtained the approval of the Research Ethics Committee of the Osaka International Cancer Institute. A credit point known as “Epoints”, which could be used for internet shopping and cash conversion, was provided to the participants as an incentive.