International Journal ofEnvironmental Researchand Public Health

ArticleGender Difference in Fear and Anxiety about and Perceived
Susceptibility to COVID-19 in the Third Wave of Pandemic
among the Japanese General Population: A Nationwide
Web-Based Cross-Sectional Survey
Rio Sasaki 1 , Atsuhiko Ota 1, * , Hiroshi Yatsuya 2
1
2

3

*

Citation: Sasaki, R.; Ota, A.; Yatsuya,
H.; Tabuchi, T. Gender Difference inFear and Anxiety about andPerceived Susceptibility to COVID-19
in the Third Wave of Pandemic
among the Japanese General
Population: A Nationwide
Web-Based Cross-Sectional Survey.
Int. J. Environ. Res. Public Health 2022,
19, 16239. https://doi.org/10.3390/
ijerph192316239
Academic Editors: Lon Jeffrey Van
Winkle and Paul B. Tchounwou

and Takahiro Tabuchi 3

Department of Public Health, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
Department of Public Health and Health Systems, Nagoya University Graduate School of Medicine,
Nagoya 466-8550, Japan
Cancer Control Center, Osaka International Cancer Institute, Osaka 541-8567, Japan
Correspondence: ohtaa@fujita-hu.ac.jp; Tel.: +81-562-93-2452

Abstract: Existing research suggested gender differences in fear and anxiety about and perceived
susceptibility to COVID-19 and previous infectious disease pandemics. We analyzed whether womenfelt fear and anxiety about and perceived susceptibility to COVID-19 more frequently than men in
Japan. We conducted a cross-sectional analysis using internet survey data collected during the third
wave of the pandemic in Japan. The subjects were enrolled from the Japanese general population:
11,957 men and 11,559 women. Fear and anxiety specifically related to COVID-19 were evaluated with
the Japanese version of the Fear of COVID-19 Scale (FoCS). The question “How likely do you think
you will be infected with COVID-19?” was used to assess the perceived susceptibility to COVID-19.
Women had higher mean (standard deviation) FoCS scores [18.6 (5.6) vs. 17.5 (5.9), d = 0.190] andreported the median or higher FoCS score (57.4% vs. 51.4%, ϕ = 0.060) and perceived susceptibility(13.6% vs. 11.5%, ϕ = 0.032) more frequently than men. The odds ratios (95% confidence intervals)
adjusted for age, having a spouse, comorbidities, watching commercial TV stations’ news programs,
employment status, and household income were 1.24 (1.17–1.32) and 1.27 (1.16–1.38), respectively.
We observed that women were more anxious and fearful about and perceived the susceptibility toinfectious diseases more frequently than men even one year after the pandemic occurred in Japan,
although the effect size was small.
Keywords: anxiety; COVID-19; fear; gender difference; infectious disease pandemic; perceived
susceptibility

Received: 18 October 2022
Accepted: 30 November 2022
Published: 4 December 2022
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Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
Women were reported to feel fear and anxiety about COVID-19 more frequently thanmen in many countries, such as the U.S. [1,2], China [3], and Pakistan [4]. Researchersdeveloped questionnaires to assess the fear and anxiety specifically related to COVID-19,
such as the Fear of COVID-19 Scale (FoCS) [5] and the Anxiety and Fear of COVID-19(AMICO) Assessment Scale [6]. In Brazil [7] and Spain [8], women had higher FoCS scoresthan men. In Japan, Midorikawa et al. reported a similar finding based on data collectedin early August 2020 [9]. In Spain, women had higher AMICO scores than men [10].
A similar tendency was found in previous infectious disease pandemics. In Asian countries,
women felt fear and anxiety more frequently than men about the pandemic of severe acuterespiratory syndrome (SARS) [11,12] and Middle East respiratory syndrome (MERS) [13].
Unlike fear and anxiety, perceived susceptibility may not show the prominent genderdifference. Women were reported to perceive greater susceptibility to COVID-19 more
frequently than men in the U.S. [14] and Iran [15] but not in Israel [16,17]. The inconsistency

Int. J. Environ. Res. Public Health 2022, 19, 16239. https://doi.org/10.3390/ijerph192316239

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was found in the previous infectious disease pandemics. In the 2003 SARS outbreak, women
were more worried about contracting SARS for themselves than men in Hong Kong [11]and the Netherlands [18]. In the outbreak of avian influenza in Asia, women perceived
more susceptibility than men in Korea [19] but not in Hong Kong [20]. No study addressed
the gender difference in perceived susceptibility to COVID-19 in Japan, to our knowledge.
Gender difference does not merely mean biological differences. Socioeconomic statuses (marriage rate, employment rate/status, income, etc.) [21], health statuses such as
the prevalence of non-communicable diseases (NCDs) [22], and lifestyles (exposure to
media, etc.) [23] differ between men and women in Japan. These factors must be consideredsimultaneously when examining the effects of gender differences. In this study, considering
these factors, we analyzed whether women felt fear and anxiety about and perceived
susceptibility to COVID-19 more frequently than men in Japan.
2. Materials and Methods
2.1. Study Design
A cross-sectional study was conducted.
2.2. Subjects
We used data from a follow-up survey of the Japan Society and New Tobacco Internet
Survey (JASTIS) that was conducted between 8 and 26 February 2021: we call it the JASTIS
2021 hereafter [24,25]. The first COVID-19 case was found in January 2020 and the third
wave occurred between November 2020 and March 2021. The JASTIS is an internet-basedlarge-scale cohort study. It was launched in 2015. The original aim was to describe theusage of new tobacco products and their related factors in Japan.
In response to the COVID-19 pandemic, the JASTIS collaborated with the Japan
COVID-19 and Society and New Tobacco Internet Survey (JACSIS). The JACSIS waslaunched in 2020 and aimed to evaluate the health conditions and social determinants of
the COVID-19 pandemic in Japan [26,27]. The baseline examination of the JACSIS (JACSIS2020) was conducted between 25 August and 30 September 2020, i.e., amid the second
wave of the pandemic in Japan. The JACSIS 2020 was a self-administered questionnaire
survey using a survey panel with approximately 2.2 million individuals having diverse
socioeconomic backgrounds, including educational level, household income, the numberof household members, etc. We called for approximately 224 thousand eligible participants
who were stratified by gender, age, and prefecture from the panel to ensure national representation. The enrolment continued until the target number of respondents was reached.
We made the target number 28,000 (12.5% of the eligible participants) and a priori set
regarding the age, gender, and prefectures, referring to the distribution of the general
Japanese population in 2019.
For the JASTIS 2020, we called for the JACSIS 2020 participants and other survey
panelists who were stratified by gender, age, and prefecture like we did for the JACSIS 2020.
The enrolment continued until the target number of respondents, 26,000, was reached.
We set an item “Choose the penultimate option from the following five options” inthe questionnaire to extract the participants who responded honestly to the questionnairewith a correct understanding of language. Those who did not correctly answer the item(n = 2484, 9.6%) were excluded. Finally, the remaining 23,516 respondents, i.e., 11,957 men
and 11,559 women, were analyzed in this study.
2.3. Outcome Variables
The Japanese version of FoCS was used to evaluate fear and anxiety related to
COVID-19 [9,28,29]. Its validity and reliability were confirmed. The FoCS consists ofthe following seven items: “I am most afraid of COVID-19”, “It makes me uncomfortable
to think about COVID-19”, “My hands become clammy when I think about COVID-19”, “I
am afraid of losing my life because of COVID-19”, “When watching news and stories about
COVID-19 on social media, I become nervous or anxious”, “I cannot sleep because I am

Int. J. Environ. Res. Public Health 2022, 19, 16239

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worried about getting COVID-19”, and “My heart races or palpitates when I think about
getting COVID-19.” The subjects responded to each item on a five-point option ranging
from “strongly disagree (score of 0)” to “strongly agree (score of 5)”. The FoCS scores wereanalyzed both as a continuous variable and as a categorical variable. For the latter purpose,the subjects were dichotomized at the median, 18, of the total score.
The question “How likely do you think you will be infected with COVID-19?” wasused to assess perceived susceptibility [15]. They chose one of the five options: 1. Certainly
not (0%), 2. Possibly (25%), 3. Maybe (50%), 4. Probably (75%), and 5. Certainly (100%).
Respondents who chose 4 or 5 were considered perceiving susceptibility to COVID-19.
2.4. Potential Confounding Factors
We considered the following factors as potential confounding factors: gender, age,having a spouse, comorbidities (NCDs and depression), time spent watching news programs broadcasted by commercial TV stations, employment status, and household income [2,7,30–34]. Ages were categorized as 15–19, 20–29, 30–39, 40–49, 50–59, 60–69, and
70–80 years old. Spouses were defined as a wife/husband or a person who was living
together as a de facto couple but had not officially been registered as a married couple. Timespent watching news programs broadcasted by commercial TV stations was classified as follows: none, once to 3 times per month, 1 day per week, 2 to 3 days per week, 4 to 5 days per
week, and almost every day. In this study, NCDs included hypertension, diabetes, asthma,pneumonia/bronchitis, angina pectoris, myocardial infarction, stroke (cerebral infarction or
hemorrhage), chronic obstructive pulmonary disease, chronic kidney disease, chronic liverdisease (excluding fatty liver or chronic hepatitis), immune deficiency disease (including
those under steroid administration), and cancer. Regarding employment status, respondents were asked whether they were regularly working (self-employed, employed), notregularly working (dispatched/contract/outsourced worker, part-timer, in-house worker),or not working (student, retired, housewife/househusband, unemployed). Householdincome was categorized as less than 3, 3 or more and less than 5, 5 or more and less than 8,
8 or more and less than 10, 10 or more million Japanese Yen (JPY), and missing response.
As of 14 November 2022, 100 JPY was equivalent to 0.72 US dollars.
2.5. Statistical Analysis
The characteristics of the subjects were compared by gender using t-test and chisquare test. We examined whether gender and the potential confounding factors wereassociated with the FoCS score and perceived susceptibility to COVID-19 using t-test,
analysis of variance, and chi-square test. Effect sizes were calculated. The standardsof effect sizes are introduced in Supplementary Table S1 [35–37]. Using multiple linear
regression analysis, standardized betas of gender and the potential confounding factors
for FoCS score were calculated. Using multiple logistic regression analysis, we calculated
the odds ratios of gender for having a FoCS score above the median and perceiving
susceptibility to COVID-19. The potential confounding factors were adjusted for calculating
the standardized betas and odds ratios. In the multivariable analyses, age was used asa continuous variable for avoiding multicollinearity. As sensitivity analyses, statisticalanalyses were also performed for all respondents (n = 28,000). Statistical significance wasset at p < 0.05. Analytic calculations were performed using IBM SPSS 24.0.
3. Results
The characteristics of the subjects are shown in Table 1. Women had a higher mean
FoCS score than men (18.6 vs. 17.5) and a higher proportion of having the median or
higher score (57.4% vs. 51.4%) than men. They also perceived susceptibility to COVID-19
more frequently than men (13.6% vs. 11.5%). Age was higher in men than in women,
but the difference was slight. The prevalence of comorbidities was higher in men than
women. Men had a spouse more frequently than women. Women were more likely towatch commercial TV stations’ news programs, irregularly or never work, and have low

Int. J. Environ. Res. Public Health 2022, 19, 16239

4 of 13household income than men. Women gave missing responses regarding household income
more frequently than men.
Table 1. Characteristics of subjects.

Age
15–19
20–29
30–39
40–49
50–59
60–69
70–80
Score of the Fear of COVID-19 Scale
Having a median or higher score
Perceived susceptibility to COVID-19
Comorbidity
Non-communicable diseases
Depression
Having a spouse
Frequency of watching commercial TV
stations’ news programs
None
Once to 3 times/month
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing response

Men (n = 11,957)

Women (n = 11,559)

p Value50.5 (16.4)
234 (2.0%)1355 (11.3%)
1687 (14.1%)2404 (20.1%)
2229 (18.6%)
2187 (18.3%)
1861 (15.6%)
17.5 (5.9)
6145 (51.4%)
1370 (11.5%)

49.8 (17.1)
385 (3.3%)
1467 (12.7%)
1559 (13.5%)
2183 (18.9%)2048 (17.7%)2127 (18.4%)
1790 (15.5%)
18.6 (5.6)
6635 (57.4%)
1569 (13.6%)

0.001<0.0013932 (32.9%)497 (4.2%)
7454 (62.3%)2336 (20.2%)
399 (3.5%)6815 (59.0%)<0.001
0.005<0.0012357 (19.7%)
929 (7.8%)
927 (7.8%)1452 (12.1%)
1520 (12.7%)
4772 (39.9%)

1999 (17.3%)
691 (6.0%)
718 (6.2%)
1281 (11.1%)1470 (12.7%)
5400 (46.7%)<0.0017377 (61.7%)
1327 (11.1%)
3253 (27.2%)3053 (26.4%)2816 (24.4%)5690 (49.2%)<0.001

1923 (16.1%)
2699 (22.6%)2834 (23.7%)
1219 (10.2%)
1442 (12.1%)
1840 (15.4%)2247 (19.4%)
2476 (21.4%)
2222 (19.2%)
770 (6.7%)
906 (7.8%)2938 (25.4%)<0.001<0.001<0.001<0.001Figures are presented as the mean (standard deviation) or the number (proportion). p values were calculated witht-test or chi-square test.

Women significantly had higher FoCS scores than men, although the effect size wassmall. Table 2 indicates the mean (standard deviation: SD) FoCS score by gender and thepotential confounding factor. All the variables were significantly associated with the FoCS
scores. When using multiple linear regression analysis, the association between gender andthe FoCS scores remained significant (Table 3). Having NCDs, depression, and a spouse,frequently watching commercial TV stations’ news programs, and household income weresignificantly associated with the FoCS scores, while age and employment status were not.
Table 2. Mean (standard deviation: SD) of Fear of COVID-19 Scale score.

Gender
Men
Women
Age
15–19

Mean (SD)p Value

Effect Size

17.5 (5.9)
18.6 (5.6)<0.001

0.190

18.6 (6.1)<0.0010.004

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Table 2. Cont.
p Value

Effect Size

17.9 (5.9)
18.6 (5.5)<0.0010.121

18.0 (5.7)
19.5 (6.4)<0.001

0.253

17.8 (5.9)
18.2 (5.7)<0.001

0.073

17.4 (6.7)
18.4 (6.2)
18.4 (5.7)
18.1 (5.6)
18.1 (5.4)
18.3 (5.4)<0.001

0.003

17.6 (6.0)
18.3 (5.7)
18.5 (5.6)<0.001

0.005

18.3 (5.9)
18.2 (5.6)
17.7 (5.6)
17.5 (5.7)
17.2 (5.8)
18.8 (5.8)<0.001

0.007

Mean (SD)
20–29
30–39
40–49
50–59
60–69
70–80
Comorbidity
Non-communicable diseases
AbsentPresent
Depression
AbsentPresent
Having a spouseNot applicable
Applicable
Frequency of watching commercial TV
stations’ news programs
None
Once to 3 times/month
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing response

17.8 (6.2)
17.6 (6.1)
17.8 (6.0)
18.0 (5.6)
18.4 (5.4)
18.7 (5.3)

Effect size is expressed by Cohen’s d (gender, comorbidity, having a spouse) or η2 (age, frequency of watching
news, employment status, and household income).

Table 3. Standardized betas for Fear of COVID-19 Scale scores: multiple linear regression analysis.
Standardized Beta
Gender
Men
Women
Age
Comorbidity
Non-communicable diseases
AbsentPresent
Depression
AbsentPresent
Having a spouseNot applicable
Applicable
Frequency of watching commercial TV
stations’ news programs
None

Reference
0.092 ***
0.012

Reference
0.050 ***
Reference
0.048 ***
Reference
0.045 ***

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Table 3. Cont.
Standardized Beta
Once to 3 times/month
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing response

0.046 ***
0.046 ***
0.041 ***
0.035 ***
0.051 ***
Reference−0.0020.001
Reference−0.018 *−0.045 ***−0.039 ***−0.058 ***0.025 ***All independent variables were included in the multiple linear regression model for calculating adjusted odds
ratios. *: p < 0.05 ***: p < 0.001.

Women reported a median or higher FoCS score more frequently than men (Table 4).
The effect size was small. All the variables were significantly associated with reportinga median or higher FoCS score. Even in multiple logistic regression analysis, gender was
significantly associated with reporting a median or higher FoCS score (Table 5). Having
NCDs, depression, and a spouse, and a low frequency of watching commercial TV stations’news programs were associated with reporting a median or higher FoCS score. Highhousehold income had a low probability of reporting a median or higher FoCS score. Highfrequency of watching commercial TV stations’ news programs and employment status
were not associated with reporting a median or higher FoCS score.
Table 4. Proportions of reporting a median or higher Fear of COVID-19 Scale score.

Gender
Men
Women
Age
15–19
20–29
30–39
40–49
50–59
60–69
70–80
Comorbidity
Non-communicable diseases
AbsentPresent
Depression
AbsentPresent
Having a spouseNot applicable
Applicable
Frequency of watching commercial TV
stations’ news programs
None
Once to 3 times/monthn (%)

p Value

Effect Size

6145 (51.4%)6635 (57.4%)<0.0010.060

366 (59.1%)
1507 (53.4%)
1645 (50.7%)2426 (52.9%)2263 (52.9%)2428 (56.3%)
2145 (58.8%)<0.001

0.053

9170 (53.2%)
3610 (57.6%)<0.0010.039

12208 (54.0%)572 (63.8%)<0.0010.038

4921 (53.2%)
7859 (55.1%)

0.005

0.018

2262 (51.9%)910 (56.2%)

0.006

0.026

Int. J. Environ. Res. Public Health 2022, 19, 16239

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Table 4. Cont.
n (%)
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing responsep Value

Effect Size

5343 (51.2%)2339 (56.5%)
5098 (57.0%)<0.001

0.056

2366 (56.7%)
2843 (54.9%)2588 (51.2%)
974 (49.0%)1122 (47.8%)2887 (60.4%)<0.0010.084

924 (56.2%)
1494 (54.7%)
1608 (53.8%)5582 (54.9%)

Effect size is expressed by ϕ (gender, comorbidity, having a spouse) or Cramer’s V (age, frequency of watching
news, employment status, and household income).

Table 5. Odds ratios for reporting a median or higher Fear of COVID-19 Scale score: multiple logistic
regression analysis.
Odds Ratio (95% Confidence Interval)

Gender
Men
Women
Age
Comorbidity
Non-communicable diseases
AbsentPresent
Depression
AbsentPresent
Having a spouseNot applicable
Applicable
Frequency of watching commercial TV
stations’ news programs
None
Once to 3 times/month
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing response

Crude

Adjusted 1

Reference
1.27 (1.21–1.34) ***1.00 (1.00–1.00) ***Reference
1.24 (1.17–1.32) ***1.00 (1.00–1.00)

Reference
1.20 (1.13–1.27) ***Reference
1.18 (1.11–1.26) ***Reference
1.51 (1.31–1.73) ***Reference
1.49 (1.29–1.71) ***Reference
1.08 (1.02–1.14) **Reference
1.14 (1.07–1.21) ***Reference
1.19 (1.06–1.33) **1.19 (1.06–1.33) **1.12 (1.01–1.23) *1.08 (0.98–1.18)
1.13 (1.05–1.21) **Reference
1.22 (1.09–1.37) ***1.23 (1.09–1.38) ***1.13 (1.03–1.25) *1.06 (0.97–1.17)
1.06 (0.98–1.14)

Reference
1.23 (1.15–1.33) ***1.26 (1.19–1.34) ***Reference
1.04 (0.96–1.12)
1.03 (0.96–1.10)

Reference
0.93 (0.86–1.01)
0.80 (0.74–0.87) ***0.73 (0.66–0.81) ***0.70 (0.63–0.77) ***1.16 (1.07–1.27) ***Reference
0.92 (0.85–1.00)
0.80 (0.73–0.88) ***0.74 (0.66–0.83) ***0.70 (0.63–0.79) ***1.15 (1.06–1.26) **All independent variables were included in the multiple logistic regression model included for calculating adjusted
odds ratios. *: p < 0.05; **: p < 0.001; ***: p < 0.001.

Int. J. Environ. Res. Public Health 2022, 19, 16239

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The proportions of and odds ratios for perceived susceptibility to COVID-19 areshown in Tables 6 and 7, respectively. Women perceived the susceptibility to COVID-19
approximately 1.3-fold more frequently than men. The statistical significance remainedeven after adjustment for the potential confounding factors. Having NCDs and depression
and a low frequency of watching commercial TV stations’ news programs were associatedwith perceived susceptibility to COVID-19. Not working regularly had a low probability ofperceived susceptibility to COVID-19. We failed to find an association between householdincome classes and perceived susceptibility prominent.
Table 6. Proportions of perceived susceptibility to COVID-19.

Gender
Men
Women
Age
15–19
20–29
30–39
40–49
50–59
60–69
70–80
Comorbidity
Non-communicable diseases
AbsentPresent
Depression
AbsentPresent
Having a spouseNot applicable
Applicable
Frequency of watching commercial TV
stations’ news programs
None
Once to 3 times/month
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing responsen (%)

p-Value

Effect Size

1370 (11.5%)
1569 (13.6%)<0.0010.032

123 (19.9%)495 (17.5%)
457 (14.1%)
584 (12.7%)478 (11.2%)
434 (10.1%)
368 (10.1%)<0.001

0.081

2126 (12.3%)
813 (13.0%)

0.186

0.009

2752 (12.2%)
187 (20.9%)<0.0010.050

1302 (14.1%)
1637 (11.5%)<0.0010.039

569 (13.1%)
254 (15.7%)
252 (15.3%)
349 (12.8%)367 (12.3%)
1148 (11.3%)<0.001

0.042

1330 (12.8%)561 (13.5%)
1048 (11.7%)

0.008

0.020

565 (13.5%)
636 (12.3%)
592 (11.7%)250 (12.6%)
265 (11.3%)
631 (13.2%)

0.027

0.023

Effect size is expressed by ϕ (gender, comorbidity, having a spouse) or Cramer’s V (age, frequency of watching
news, employment status, and household income).

Sensitivity analyses using all respondents resulted in similar findings that women had
higher FoCS scores and perceived susceptibility to COVID-19 than men (Supplementary
Tables S2–S7).

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Table 7. Odds ratios for perceived susceptibility to COVID-19: multiple logistic regression analysis.
Odds Ratio (95% Confidence Interval)

Gender
Men
Women
Age
Comorbidity
Non-communicable diseases
AbsentPresent
Depression
AbsentPresent
Having a spouseNot applicable
Applicable
Frequency of watching commercial TV
stations’ news programs
None
Once to 3 times/month
1 day/week
2 to 3 days/week
4 to 5 days/week
Almost every day
Employment status
Regularly working
Not regularly working
Not working
Household income (Japanese Yen)
<3 million
3 million or more and less than 5 million
5 million or more and less than 8 million
8 million or more and less than 10 million
10 million or more
Missing response

Crude

Adjusted 1

Reference
1.21 (1.12–1.31) ***0.99 (0.98–0.99) ***Reference
1.27 (1.16–1.38) ***0.99 (0.98–0.99) ***Reference
1.06 (0.97–1.16)

Reference
1.34 (1.22–1.48) ***Reference
1.90 (1.61–2.24) ***Reference
1.63 (1.37–1.93) ***Reference
0.79 (0.73–0.85) ***Reference
1.00 (0.91–1.10)

Reference
1.24 (1.05–1.45) **1.20 (1.03–1.41) *0.97 (0.84–1.12)
0.93 (0.81–1.07)
0.85 (0.76–0.94) **Reference
1.27 (1.08–1.49) **1.24 (1.06–1.46) **1.05 (0.90–1.21)
1.04 (0.90–1.20)
1.00 (0.89–1.12)

Reference
1.07 (0.96–1.19)
0.91 (0.83–0.99) *Reference
1.00 (0.89–1.12)
0.89 (0.81–0.99) *Reference
0.89 (0.79–1.01)
0.85 (0.75–0.96) **0.92 (0.78–1.08)
0.81 (0.69–0.95) **0.97 (0.86–1.10)

Reference
0.90 (0.79–1.02)
0.81 (0.71–0.92) **0.88 (0.74–1.04)
0.78 (0.66–0.93) **0.94 (0.82–1.06)

All independent variables were included in the multiple logistic regression model for calculating adjusted odds
ratios. *: p < 0.05; **: p < 0.001; ***: p < 0.001.

4. Discussion
We found in the present study that women had higher FoCS scores than men evenone year after the pandemic occurred in Japan. Women were more likely than men,
approximately 1.3-fold higher, to feel fear and anxiety about COVID-19 when the FoCS
scores were divided at the median score. Women perceived the susceptibility to COVID-19
approximately 1.3-fold higher than men.
An advantage of the present study is showing that the gender differences in the FoCS
scores and perceived susceptibility to COVID-19 remained significant even after adjustment
for age, having comorbidities and a spouse, time spent watching news programs broadcasted by commercial TV stations, employment status, and household income. Genderdifferences do not merely reflect biological differences. They might be a reflection of the differences in socioeconomic and health statuses and lifestyles by gender. In the present study,
women and men showed different proportions of having comorbidities and a spouse, timespent watching news programs broadcasted by commercial TV stations, employment status,and household income. A large sample size of the present study allowed the adjustment ofthese factors.
Our findings regarding fear and anxiety were concordant with those from othercountries [1–4,7,8,10]. We observed in this study that women were more anxious andInt. J. Environ. Res. Public Health 2022, 19, 16239

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fearful about infectious diseases during a pandemic, even approximately one year after
the onset of the COVID-19 pandemic in Japan. Women were reportedly more fearful andanxious about infectious diseases during previous infectious disease pandemics. Hong
Kong experienced the SARS pandemic from 2003 to 2004. Leung et al. [12] reported thatwomen felt more anxiety in the early stages of the SARS pandemic than men, while thedifference disappeared in the late stage of the pandemic. Lau et al. [11] reported that women
were more likely to report mental illness and feel fearful about SARS than men. A study
conducted during the 2018 MERS outbreak in South Korea found that women health care
workers felt psychological distress more frequently than male health care workers [13].
Here, we discuss the trend of the FoCS scores of general adults in Japan. The first patient infected with COVID-19 was found on 15 January 2020 in Japan. Midorikawa et al. [9]addressed a general adult population in Japan in early August 2020, i.e., amid the second
wave of the COVID-19 pandemic. They reported a mean (SD) FoCS score of 15.3 (4.9) for
men, 17.4 (4.6) for women, and 17.3 (5.8) for others. There was a significant difference bygender. The effect size was small to the medium: η2 = 0.042. Our study was conducted in
February 2021, i.e., six months later of their study. We found a mean (SD) FoCS score of
17.5 (5.9) for men and 18.6 (5.6) for women. The effect size was small: d = 0.190. The subjectsof the two studies were not identical. Therefore, strictly saying, it may be inappropriate todirectly compare our findings to theirs. However, both men and women showed higher
mean FoCS scores and the difference in the mean FoCS by gender became smaller in ourstudy than in Midorikawa’s study [9].
In our study, women perceived susceptibility to COVID-19 more frequently thanmen. This finding is concordant with the previous findings regarding COVID-19 [14,15]
and other infectious disease pandemics, such as SARS [11,18] and avian influenza [19].
Conversely, some previous studies found no difference between men and women in theperceived susceptibility to COVID-19 [16,17] and influenza A virus subtype H5N1 in
Asia [20]. Further studies are necessary to determine the gender difference in the perceived
susceptibility to COVID-19 and other infectious disease pandemics.
Regarding the associations with the FoCS scores and perceived susceptibility to
COVID-19, gender showed a low effect size. We consider having NCDs, depression,and a spouse, exposure to media, employment status, and household income in the present
study since they were reported to have potential associations with fear and anxiety about
and perceived susceptibility to COVID-19 [2,7,30–34]. We confirmed in this study that someof them were associated with the FoCS scores and perceived susceptibility to COVID-19.
At the same time, we found their effect sizes small. At least, we could not conclude thatgender was less important than those factors in terms of the impact on fear and anxiety
about and perceived susceptibility to COVID-19.
We here discuss age, having a spouse, and employment status (not working) whose
associations with FoCS scores were different from those with perceived susceptibility to
COVID-19. It was not clearly shown that FoCS scores increased with age. Having a spouse
was significantly associated with high FoCS scores even after adjustment for age and otherpotential confounding factors. On the other hand, perceived susceptibility to COVID-19
was inversely associated with age. A similar finding was observed in a study in Israel [17].
The association between having a spouse and perceived susceptibility to COVID-19 was
not significant in the multivariable analysis. This would suggest that having a spouse
was a confounding factor for the association between age and perceived susceptibility
to COVID-19. In our study, the prevalence of having a spouse was higher in the older
age than in the younger age (Supplementary Table S8). Not working was not associatedwith FoCS scores but with perceived susceptibility to COVID-19. Compared to those who
were working, those who were not working would have fewer opportunities to meet otherpeople outside, leading to less perceived susceptibility to COVID-19.
The present study had some limitations. First, there might be a selection bias thatthe subjects were limited to those interested in this kind of internet survey. We could not
calculate the response rate in this study. This was because the enrollment of subjects closed

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when the respondents reached the target number that was set to reflect the gender, age,and geographical distribution of the Japanese general population. The subjects might belimited to those who had an interest in this survey and could go through a large numberof questions, which is called the volunteer effect [38]. In addition, the availability of theinternet differed by age and household income, which could limit the representativeness ofthe subjects. According to the latest white paper on information and communications inJapan [39], those in their sixties (82.7%) and seventies (59.6%) were using the internet lessfrequently than younger adults (more than 95%), and household income was positively
correlated with the availability of the internet. The distribution of the household income ofthe present subjects did not appear different from the latest national survey finding [40],although it must be noted that a considerable proportion of the present subjects, especiallywomen, did not disclose their household income. Second, we did not collect data on
nationality, ethnicity, or religious affiliation. Such information might have contributed tothe discussion regarding the impact of cultural differences on the gender difference in fear
and anxiety about and perceived susceptibility to COVID-19.
5. Conclusions
In this cross-sectional study, we clarified that women felt fear and anxiety about andperceived susceptibility to COVID-19 more frequently than men, using the data collected
through a web-based survey during the third wave of the COVID-19 pandemic in Japan.
Supplementary Materials: The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijerph192316239/s1, Supplementary Table S1: Standards of effectsizes; Supplementary Table S2: Mean (standard deviation: SD) of Fear of COVID-19 Scale score:sensitivity analysis (n = 28,000); Supplementary Table S3: Standardized beta for Fear of COVID-19
Scale scores: multiple linear regression analysis, sensitivity analysis (n = 28,000); Supplementary Table
S4: Proportions of reporting a median or higher Fear of COVID-19 Scale score: sensitivity analysis(n = 28,000); Supplementary Table S5: Odds ratios for reporting a median or higher Fear of COVID-19
Scale score: multiple logistic regression analysis, sensitivity analysis (n = 28,000); Supplementary
Table S6: Proportions of perceived susceptibility to COVID-19 Scale score: sensitivity analysis(n = 28,000); Supplementary Table S7: Odds ratios for perceived susceptibility to COVID-19: multiple
logistic regression analysis, sensitivity analysis (n = 28,000); Supplementary Table S8: Age and having
a spouse (n = 23,516).
Author Contributions: All authors conceived the study plan. T.T. was responsible for data collection.
R.S., A.O. and H.Y. analyzed the data. All authors interpreted the analytic findings. R.S. and A.O.
wrote the manuscript. All the authors critically revised the draft and approved the final manuscript.
A.O. and T.T. obtained grants for the present study. All authors have read and agreed to the publishedversion of the manuscript.
Funding: This work was granted by Fujita Health University School of Medicine and by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grants (grant numbers: 18H03062 and 21H04856).
The research funders had no role in the design of the study; the collection, analysis, or interpretationof data; the writing of the manuscript; or the decision to publish the results. The findings andconclusions of this article are the sole responsibility of the authors and do not represent the official
views of the research funders.
Institutional Review Board Statement: The study protocol was reviewed and approved by the
Research Ethics Committee of the Osaka International Cancer Institute (approval number: 20084).
All procedures in this study were performed following the ethical standards of the Declaration of
Helsinki. The internet survey agency respected the Act on the Protection of Personal Informationin Japan.
Informed Consent Statement: All subjects provided their web-based informed consent before responding to the online questionnaire. A credit point known as “Epoints”, which could be used forinternet shopping and cash conversion, was provided to the subjects as an incentive.
Data Availability Statement: The data used in this study are not available in a public repository
because they contain personally identifiable or potentially sensitive patient information. Based on theInt. J. Environ. Res. Public Health 2022, 19, 16239

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regulations for ethical guidelines in Japan, the Research Ethics Committee of the Osaka International
Cancer Institute has imposed restrictions on the dissemination of the data collected in this study. Alldata inquiries should be addressed to the person responsible for data management, Takahiro Tabuchi
at the following e-mail address: tabuchitak@gmail.com.
Acknowledgments: We thank Editage Group (https://www.editage.com (accessed on 14 November2022)) for editing the manuscript.
Conflicts of Interest: The authors declare no conflict of interest.

Abbreviations
NCD
FoCS
SD

Non-communicable disease
Fear of COVID-19 Scale
Standard deviation

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