Environmental Health andPreventive Medicine

Environmental Health and Preventive Medicine
https://doi.org/10.1265/ehpm.23-00281(2023) 28:73

RESEARCH ARTICLE

Vaccination, regular exercise, and prevention of chroniclung disease reduce exacerbation of COVID-19 severity
in northern Okinawa, Japan: A cross-sectional study
Takuji Kishimoto1＊ , Daisuke Tasato2, Yoshitaka Nagasawa3, Yuri Higure2, Michika Setoguti2, Rin Tibana2,
Akihiro Yamashiro1, Tatsuya Miyazato1 and Hayashi Shokita4＊

Correspondence: takuji.kishimoto@nagohp.com
Department of Health Screening, Okinawa North Medical Association Hospital, 1712-3 Nago City, Okinawa 905-8611, Japan. 2Department of Respiratory and
Infectious Diseases, Okinawa North Medical Association Hospital, 1712-3 Nago City, Okinawa 905-8611, Japan. 3Department of Endocrinology, Metabolism andDialysis, Okinawa North Medical Association Hospital, 1712-3 Nago City, Okinawa 905-8611, Japan. 4Department of Gastroenterology, Okinawa North Medical
Association Hospital, 1712-3 Nago City, Okinawa 905-8611, Japan.

1

Abstract
Background: As at June 14, 2023, the coronavirus disease 2019 (COVID-19) pandemic had aﬀected more than 767 million people andcaused more than 6.9 million deaths worldwide. This study aimed to clarify the lifestyle factors that inﬂuence the exacerbation of
COVID-19 severity.
Methods: This was a cross-sectional study of patients with COVID-19 whose severity classiﬁcation of “moderate or severe” (COVID19 exacerbation) was deﬁned as an objective variable. The 1,353 participants were selected from 4,899 patients with COVID-19
between August 10, 2020 and December 10, 2022. Participants who underwent a speciﬁc health checkup before the date for a COVID19 consultation were included. Using binominal logistic regression analysis, we evaluated the odds ratios (ORs) for COVID-19
exacerbation according to lifestyle-related factors. Limitations were discussed using a target trial emulation framework which clariﬁes
problems in observational studies.
Results: The explanatory variables extracted as factors that exacerbated COVID-19 severity were gender (OR [man vs. woman]: 2.533,
95% conﬁdence interval [CI] 1.484–4.322); age (OR [50s vs. 10s, 20s, or 30s]: 4.858, 95% CI 2.319–10.177; OR [60s]: 9.738, 95% CI
4.355–21.777; OR [70s + 80s + 90s]: 8.327, 95% CI 3.224–21.507); and comorbid chronic lung disease (OR [‘yes’ vs. ‘no’]: 2.892,
95% CI 1.227–6.818). The explanatory variables extracted as factors that reduce the severity of COVID-19 were hospital consultation
year (OR [2022, predominantly Omicron variant prevalent vs. 2020, predominantly Alpha variant prevalent]: 0.180, 95% CI
0.058–0.559); number of vaccinations (OR [2 doses vs. 0 or one doses]: 0.223, 95% CI 0.114–0.436; OR [²3 doses vs. 0 or one
doses]: 0.090, 95% CI 0.035–0.229); regular exercise (exercising ²2 days/week ²30 minutes each at an intensity that causes a slightsweat for ²1 year) (OR [‘yes’ vs. ‘no’]: 0.458, 95% CI 0.242–0.866).
Conclusions: These results suggest the importance of vaccination, regular exercise, and prevention of chronic lung disease as measuresagainst exacerbation of COVID-19 severity.

Keywords: COVID-19, Severity, Lifestyle, Vaccine, Regular exercise, Chronic lung disease, Cross-sectional study, Target trial
emulation

Introduction
According to World Health Organization data available on
June 14, 2023, the COVID-19 pandemic has aﬀected morethan 767 million people and caused more than 6.9 million
deaths worldwide [1]. Attenuation of mutant strains, vaccination, and the development of treatments are reducing
the health problems caused by COVID-19. However, clarifying the lifestyle factors that inﬂuence the exacerbationof COVID-19 severity is extremely important for managing the care of older people and people with comorbidities,

as well as managing potential new virulent variants. The
development of eﬀective vaccines and therapeutics is also
extremely important. Clarifying lifestyle risk factors andestablishing countermeasures that emphasize lifestylerelated factors may help to mitigate symptoms even if
infection occurs.
Many factors have been reported to exacerbate the severity of COVID-19, including older age, man gender,
underlying comorbidities such as hypertension; diabetes;
chronic lung diseases; heart, liver and kidney diseases;
tumors; clinically apparent immunodeﬁciencies; and preg-© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution andreproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate
if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to thematerial. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Environmental Health and Preventive Medicine (2023) 28:73

nancy [2–11]. Unhealthy diet and smoking are lifestylerisk factors [12–15]; however, lifestyle habits have notbeen suﬃciently examined. Therefore, we conducted across-sectional study of patients with COVID-19 with theaim of clarifying the lifestyle factors that inﬂuence theexacerbation of COVID-19 severity.

Methods
Study design and population
This study was conducted at Okinawa North Medical Association Hospital that is one of the core hospitals in northern Okinawa Prefecture, Japan. This was a cross-sectional
study of patients diagnosed with COVID-19. From August
10, 2020 to December 10, 2022, patients who had undergone a speciﬁc health checkup at our hospital before thedate that they presented to the hospital for a consultation
were included in this study.

COVID-19 severity classiﬁcation
Severity classiﬁcation was performed based on the “NewCoronavirus Infectious Disease COVID-19 Clinical Practice Guide” supported by the Fiscal 2020 Health, Laborand Welfare Administration Promotion Survey Subsidy.
Brieﬂy, the severity classiﬁcation describes “asymptomatic” as a positive test for SARS-CoV-2 using virologicaltesting but no symptoms consistent with COVID-19;“mild” as an oxygen saturation of ²96% or clinical status
of no respiratory symptoms or cough only, with no dyspnea; “moderate I” as an oxygen saturation of between 93%
and 96% or clinical status of no dyspnea, no evidence ofpneumonia, or respiratory failure; “moderate II” as oxygen
saturation of ¯93% or clinical status of respiratory failure
requiring supplemental oxygen; and “severe” as a clinicalstatus of intensive care unit (ICU) admission or ventilator
required. In this study, severity was classiﬁed into two categories: “asymptomatic or mild” and “moderate or severe.”

2 of 9iant prevalent, respectively), number of vaccinations, bodymass index, smoking habit, comorbidities (including hypertension, dyslipidemia, diabetes, chronic lung disease,chronic kidney disease, heart disease, and malignant tumor), and immunosuppression status. Comorbidities andimmunosuppression status were captured by history of
current disease during treatment. Chronic lung disease includes chronic obstructive pulmonary disease, asthma, interstitial lung disease, etc. Chronic kidney disease includes
renal disorders that persist for 3 months or longer and areunder treatment. Immunosuppression status include organtransplantation or autoimmune diseases, and those receiving immunosuppressive therapy.
The vaccines administered to the participants were themRNA vaccines BNT16262 (Pﬁzer/BioNTech) or mRNA1273 (Moderna). Vaccinations during this research period
were carried out ﬁve times based on national guidelines.
The 1st to 3rd rounds were held in 2021, and the 4th and5th rounds were held in 2022.
Explanatory variables obtained from the results of themost recent speciﬁc health checkup before the hospitalconsultation for COVID-19 included the following lifestyle-related items: (1) “having an evening meal 2 hours
or less before bedtime 3 days or more per week,” (2)“eating snacks and sweet beverages outside of breakfast,
lunch, and dinner,” (3) “eating faster than others,” (4)“skipping breakfast at least three times a week,” (5) “walking for at least 1 hour per day or having equivalent physical activities,” (6) “exercising at least 2 days per week forat least 30 minutes each session at an intensity that causesa slight sweat for at least 1 year,” (7) “frequency of drinking,” (8) “regular smoker,” and (9) “feeling refreshed after
a night’s sleep”.

Adjusted variables
The adjusted variables were all explanatory variables,
which were applied to the binominal logistic regression
analysis and analyzed using backward stepwise regression.

Speciﬁc health checkup
Since April 1, 2008, a speciﬁc health checkup has been conducted in Japan under the initiative of the Japanese Ministryof Health, Labour and Welfare. The checkup focuses on
preventing metabolic syndrome and cardiovascular disease.
Speciﬁc health checkups are conducted once a year for
people aged 40 to 74 years who have medical insurance.

Objective variable
The severity classiﬁcation in patients with COVID-19 was
divided into two groups (“asymptomatic or mild” and“moderate or severe”) and analyzed. The objective variable was the severity classiﬁcation “moderate or severe”(COVID-19 exacerbation).

Explanatory variables
Explanatory variables obtained at the time of consultation
were gender, age, hospital consultation year (2020, 2021,
and 2022: predominantly Alpha, Delta, and Omicron var-

Statistical analysis
Applying explanatory variables to the binominal logistic
regression analysis, the odds ratios (ORs) of the explanatory variables were calculated using the forced entry method and backward stepwise regression. An ¡ value of 0.05
was used to determine the signiﬁcance of the analyses andvariables. All statistical analyses were performed using
IBM SPSS Statistics version 28 (IBM Corp., Armonk,
NY, USA).

Results
During the study period, 4,899 patients with COVID-19
visited our hospital for a consultation. Of these, the 1,353
patients who underwent a speciﬁc health checkup at our
hospital before the date that they visited it for a consultation were included in this study (Fig. 1). Based on the year
in which patients visited for a consultation (Fig. 1, upper3 of 9Environmental Health and Preventive Medicine (2023) 28:73

COVID-19 patients (hospital admission date: August 10, 2020 - December 10, 2022): n = 4,899
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COVID-19 patients who underwent the heath checkup
within 2 years before the date of hospital admission with COVID-19: n=1,353
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Fig. 1 Selection of study population and severity classiﬁcation by year and sex

section), the initial group of 4,899 patients with COVID19 showed an increasing trend over the 3 years and asubstantial increase in 2022. Over the study period, therate of a “moderate or severe” diagnosis increased slightly
from 34% in 2020 to 39% in 2021, but decreased extensively to 7% in 2022. Among the 1,353 patients includedin the study (Fig. 1, lower section), the number of patients
who visited our hospital for a consultation showed an upward trend from 24 to 1,219 over the 3 years, with asubstantial increase to 1,219 in 2022; the rate of a diagnosis of “moderate or severe” increased from 24% in 2020
to 41% in 2021, but decreased substantially to 3% in 2022.
Table 1 shows the severity of COVID-19 infection bygender and age group. The proportion of “moderate orsevere” COVID-19 diagnoses was 4.2% for women, 9.3%
for men, and 6.8% for both genders. A signiﬁcant relationship was observed between age and severity of infection:
the higher the age, the higher the proportion of “moderateor severe” infections among men and total. A signiﬁcantassociation was observed between gender and number ofvaccinations (Table 2) for men, women, and both genders
combined; the higher the number of vaccinations, the lower the rate of a diagnosis of “moderate or severe” infection.
Table 3 shows the ORs for COVID-19 exacerbationaccording to the study factors after adjusting for confounding factors using backward stepwise regression. The ex-planatory variables extracted as factors that exacerbated
COVID-19 severity were gender (OR [man vs. woman]:
2.533, 95% conﬁdence interval [CI] 1.484–4.322); age(OR [50s vs. 10s, 20s, or 30s]: 4.858, 95% CI 2.319–
10.177; OR [60s]: 9.738, 95% CI 4.355–21.777; OR[70s + 80s + 90s]: 8.327, 95% CI 3.224–21.507); and comorbid chronic lung disease (OR [‘yes’ vs. ‘no’]: 2.892,
95% CI 1.227–6.818). The explanatory variables extracted
as factors that reduce the severity of COVID-19 were hospital consultation year (OR [2022, predominantly Omicron
variant prevalent vs. 2020, predominantly Alpha variant
prevalent]: 0.180, 95% CI 0.058–0.559); number of vaccinations (OR [2 doses vs. 0 or one doses]: 0.223, 95% CI
0.114–0.436; OR [²3 doses vs. 0 or one doses]: 0.090,
95% CI 0.035–0.229); regular exercise (exercising ²2
days/week ²30 minutes each at an intensity that causesa slight sweat for ²1 year) (OR [‘yes’ vs. ‘no’]: 0.458,
95% CI 0.242–0.866).

Discussion
To clarify the lifestyle factors that inﬂuence the exacerbation of COVID-19 severity, in this study we analyzed datafor 1,353 patients with COVID-19 who visited our hospital and underwent a speciﬁc health checkup at our hospital
before the date of their hospital consultation. We conduct-

4 of 9Environmental Health and Preventive Medicine (2023) 28:73

Table 1 COVID-19 severity by gender and age over the entire period (2020–2022)
genderage

women

Teens +
20s + 30s
40s
50s
60s
70s
80s + 90s
total

men**

Teens +
20s + 30s
40s
50s
60s
70s
80s + 90s
total

total*

Teens +
20s + 30s
40s
50s
60s
70s
80s + 90s
total

asymptomatic +
mild
229
96.6%
95
96.9%
128
95.5%
118
95.2%
68
93.2%
2
100.0%
640
95.8%
238
96.4%
106
93.0%
113
84.3%
102
84.3%
60
89.6%
2
100.0%
621
90.7%
467
96.5%
201
94.8%
241
89.9%
220
89.8%
128
91.4%
4
100.0%
1,261
93.2%

moderate +severe
8
3.4%
3
3.1%
6
4.5%
6
4.8%
5
6.8%
0
0.0%
28
4.2%
9
3.6%
8
7.0%
21
15.7%
19
15.7%
7
10.4%
0
0.0%
64
9.3%
17
3.5%
11
5.2%
27
10.1%
25
10.2%
12
8.6%
0
0.0%
92
6.8%

total
237
100.0%
98
100.0%
134
100.0%
124
100.0%
73
100.0%
2
100.0%
668
100.0%
247
100.0%
114
100.0%
134
100.0%
121
100.0%
67
100.0%
2
100.0%
685
100.0%
484
100.0%
212
100.0%
268
100.0%
245
100.0%
140
100.0%
4
100.0%
1,353
100.0%*: P < 0.01 (chi-square test)**: P < 0.001 (chi-square test)

ed a cross-sectional study with COVID-19 exacerbation as
the objective variable and identiﬁed gender, age, and coexisting chronic lung disease as factors that exacerbate
COVID-19 severity; year of the hospital consultation,
number of vaccinations, and regular exercise were factorsthat reduced the severity. These results suggest importantfactors in establishing preventive measures against exacerbation of COVID-19 severity.
The factors gender, age, and coexisting chronic lungdisease showed signiﬁcant ORs (Table 3). Many studies
have reported on the rate of severe disease by gender, andTable 2 COVID-19 severity by gender and number of vaccinations
over the entire period (2020–2022)
asymptomatic + moderate +mildseverewomen*
124
19
86.7%
13.3%
once
5
0
100.0%
0.0%
twice
305
7
97.8%
2.2%
3 times or more
206
2
99.0%
1.0%
total
640
28
95.8%
4.2%
men*
0 times
118
43
73.3%
26.7%
once
2
0
100.0%
0.0%
twice
309
14
95.7%
4.3%
3 times or more
192
7
96.5%
3.5%
total
621
64
90.7%
9.3%
total*
0 times
242
62
79.6%
20.4%
once
7
0
100.0%
0.0%
twice
614
21
96.7%
3.3%
3 times or more
398
9
97.8%
2.2%
total
1,261
92
93.2%
6.8%
gendernumber of
vaccinations
0 times

total
143
100.0%
5
100.0%
312
100.0%
208
100.0%
668
100.0%
161
100.0%
2
100.0%
323
100.0%
199
100.0%
685
100.0%
304
100.0%
7
100.0%
635
100.0%
407
100.0%
1,353
100.0%*: P < 0.001 (chi-square test)

the rate of hospitalization, ICU cases, and deaths tend to behigher in men than in women [10, 11]. This has been
attributed to diﬀerences in adaptive immune responses,
eﬀects of sex hormones on inﬂammatory processes, expression levels of angiotensin-converting enzymes, andlifestyle diﬀerences [12–14].
Several cohort studies of patients with COVID-19 haveshown that older age is associated with greater disease
severity [10, 11, 15]. Physiological changes associatedwith aging and comorbidities such as diabetes, hypertension, obesity, cardiovascular disease, and pulmonary disease—commonly seen in older adults—are thought to be
the causes [16]. In addition, the increase in senescent immune cells observed with aging contributes not only todecreased host defenses, but also to an elevated inﬂammatory phenotype in immune dysfunction [17–19].
The main chronic lung diseases include chronic obstructive pulmonary disease, lung cancer, pneumonia, etc. The
main cause and aggravating factor of these lung diseases issmoking [20]. Smoking habits did not show a signiﬁcant
OR in this study; however, an analysis of the amount ofsmoking conducted over a lifetime seems necessary. In

5 of 9Environmental Health and Preventive Medicine (2023) 28:73

Table 3 Odds ratios of each factor for exacerbation$ of severity in patients with COVID-19#
95% conﬁdence interval forodds ratio*

95% conﬁdence interval forodds ratio**factorNumber ofpeople

%

woman
man

658
672

49.5%
50.5%

1.000
2.547

1.401

-

4.629

1.000
2.533

1.484

-

4.322

Teens + 20s + 30s
40s
50s
60s
70s + 80s + 90s
hospital consultation year
2020
2021
2022
number of vaccinations
0 times + oncetwice
3 times or morebody mass index (BMI)
BMI Ù 18.5 (thin)
18.5 Ù BMI < 25.0 (standard)
25.0 Ù BMI < 30.0 (overweight)
30.0 Ù BMI (obesity)
hypertension
none
prevalentdiabetesnone
prevalent
chronic lung diseasenone
prevalent
chronic kidney diseasenone
prevalentheart diseasenone
prevalentmalignant tumor
none
prevalent
immunosuppressive statenone
prevalentdyslipidemia
none
prevalent
having an evening meal 2 hours orless before bedtime 3 days or more
per weeknoyeseating snacks and sweet beverages
outside of breakfast, lunch, anddinnernosometimes
every day

473
207
266
241
143

35.6%
15.6%
20.0%
18.1%
10.8%

1.000
1.306
4.203
7.789
6.529

0.518
1.873
3.188
2.257

-

3.294
9.432
19.03218.890

1.000
1.525
4.858
9.738
8.327

0.631
2.319
4.355
3.224

-

3.685
10.17721.77721.507

24
109
1,197

1.8%
8.2%
90.0%

1.000
2.027
0.183

0.623
0.054

-

6.594
0.620

1.000
1.849
0.180

0.617
0.058

-

5.541
0.559

305
626
399

22.9%
47.1%
30.0%

1.000
0.190
0.065

0.093
0.023

-

0.390
0.182

1.000
0.223
0.090

0.114
0.035

-

0.436
0.229

59
753
347
171

4.4%
56.6%
26.1%
12.9%

0.429
1.000
1.916
1.921

0.068

-

2.693

1.049
0.888

-

3.496
4.155

1,048
282

78.8%
21.2%

1.000
1.005

0.477

-

2.119

1,241
89

93.3%
6.7%

1.000
1.956

0.721

-

5.305

1,228
102

92.3%
7.7%

1.000
2.716

1.106

-

6.665

1.000
2.892

1.227

-

6.818

1,327
3

99.8%
0.2%

1.000
0.000

0.000

1,280
50

96.2%
3.8%

1.000
1.201

0.374

-

3.858

1,316
14

98.9%
1.1%

1.000
8.582

1.542

-

47.767

1,318
12

99.1%
0.9%

1.000
0.000

0.000

1,234
96

92.8%
7.2%

1.000
1.821

0.693

-

4.783

888
442

66.8%
33.2%

1.000
0.871

0.484

-

1.567

454
635
241

34.1%
47.7%
18.1%

1.000
0.910
0.702

0.452
0.268

-

1.834
1.842

odds ratio* lower limit

upper limit odds ratio**

lower limit

upper limit

genderage

6 of 9Environmental Health and Preventive Medicine (2023) 28:73

Table 3 (Continued.)
95% conﬁdence interval forodds ratio*
factoreating faster than others
slow
usual
fast
skipping breakfast at least threetimes a weeknoyeswalking for at least 1 hour per day
or having equivalent physicalactivities
noyes
exercising at least 2 days per week
for at least 30 minutes each session
at an intensity that causes a slightsweat for at least 1 yearnoyesfrequency of drinking
neversometimes
every dayregular smokernoyesfeeling refreshed after a night’s
sleep
no
yes

Number ofpeople

%

115
796
419

8.6%
59.8%
31.5%

1.000
0.760
0.519

0.295
0.189

-

1.957
1.430

854
476

64.2%
35.8%

1.000
1.309

0.736

-

2.330

817
513

61.4%
38.6%

1.000
1.413

0.814

-

2.451

949
381

71.4%
28.6%

1.000
0.454

0.233

-

0.886

454
635
241

34.1%
47.7%
18.1%

1.000
0.642
0.717

0.334
0.322

-

1.233
1.594

1,031
299

77.5%
22.5%

1.000
0.903

0.465

-

1.754

410
920

30.8%
69.2%

1.000
1.033

0.595

-

1.794

odds ratio* lower limit

95% conﬁdence interval forodds ratio**

upper limit odds ratio**

1.000
0.458

lower limit

0.242

upper limit

-

0.866

#: the number of subjects for analysis was 1,330 (23 were excluded due to partial missing values)$: “moderate or severe” severity
odds ratio*: odds ratio by forced entry method for binomial logistic regression analysis
odds ratio**: odds ratio by backward stepwise method for binomial logistic regression analysis

any event, prevention of chronic lung disease appeared toreduce exacerbation of COVID-19 severity.
Factors that reduced the severity of COVID-19 showedsigniﬁcant ORs and included the year of the hospital consultation, number of vaccinations, and regular exercise(Table 3). The years 2020, 2021, and 2022 corresponded
to the periods when mainly the Alpha, Delta, or Omicron
variants, respectively, were prevalent. The OR for 2022
patients to 2020 patients showed a signiﬁcant mitigation
value, possibly due to the diﬀerence in the epidemic’s
mutated strains found in each year. The Omicron mutant
is signiﬁcantly more infectious than the Alpha and Delta
mutants are, but the rate of severe disease is low [21, 22].
The results of our study conﬁrmed this point.
Compared to no vaccination, the ORs of two and threeor more vaccinations showed signiﬁcant reductions in incidence of moderate or severe COVID-19 infection. The
preventive eﬀect of vaccination against the Alpha, Delta,
and Omicron variants, which were prevalent during thestudy period, has been clariﬁed [23, 24]; however, theresults of our study showed that vaccination was extremely
eﬀective in preventing exacerbation of severity. In studies
conducted around the same time in Nara Prefecture, Japan[25, 26], more vaccinations were associated with a lower
risk of COVID-19-related health outcomes, not only for
Delta variants but also for Omicron variants. This wasconsistent with the results regarding the eﬀectiveness of
vaccination shown in this study.
Patients who exercised regularly showed signiﬁcantly
reduced severity of disease compared to patients who did
not exercise regularly. Elevated hemoglobin A1c levels
have been associated with a worse prognosis of COVID19 and hyperglycemia is a factor in the severity of COVID19 [27, 28]. These studies suggest a mechanism by which
regular exercise may improve glucose metabolism and thus
reduce the exacerbation of COVID-19 severity.

Limitations
The limitations of this research method were examinedEnvironmental Health and Preventive Medicine (2023) 28:73

7 of 9Fig. 2 Time relationship among main items of target trial emulation framework in this study

using a target trial emulation framework which examined
four items: (1) eligibility, (2) treatment assignment, (3)time zero (timing to start follow-up), and (4) outcome
evaluation (per-protocol eﬀect, intention-to-treat eﬀect)[29, 30]. In a target trial (an ideal randomized controlled
trial), participants are ﬁrst screened based on a series of
eligibility criteria, assigned to an intervention group (treatment assignment), and then followed up (time zero). Finally, the outcomes are evaluated (Fig. 2). In this study,
treatment assignment (allocation by presence/absence ofthe explanatory variables) was performed ﬁrst, then eligibility (selection of patients with COVID-19), time zero (nofollow up), and outcome evaluation (ORs of study factors
on COVID-19 exacerbation calculated) were implemented
simultaneously at time zero.
Eligibility for inclusion in this study may have introduced selection bias. We calculated the ORs of study factors on COVID-19 exacerbation as outcome evaluations;however, two conditions must be met in order for the OR toapproximate the Relative Risk [31]. The ﬁrst condition isthat the frequency of occurrence of “moderate or severe”
severity must be low, and the second condition is that the
samples selected for the study must be representative of the“asymptomatic or mild” and “moderate or severe” populations. Regarding the ﬁrst condition, the incidence of
COVID-19 itself was low, and the proportion of “moderateor severe” severity was 6.8% of the total, which seemed tosatisfy the ﬁrst condition (Table 1). Regarding the second
condition, whether the samples selected for the study wereselected to represent the “asymptomatic or mild” and “moderate or severe” populations is unclear, and the possibilityof selection bias cannot be denied. In the area in which thestudy was conducted—in 2022, comprising one city, one
town, seven villages, and approximately 102,000 people—

two hospitals, including ours, provided beds for patientswith infectious diseases. These two hospitals account forthe majority of COVID-19 cases in the region. The 1,353
study participants were extracted from 4,899 patients who
visited our hospital. The distribution of severity among the4,899 cases seems likely to be representative of that of thelocal population. As the severity distribution of the 4,899
patients who visited our hospital and the severity distribution of the extracted 1,353 patients was similar (Fig. 1), theextent of the selection bias seemed to be small.
Information on explanatory variables (treatment assignment) were obtained from the most recent health checkups
before the hospital consultation for COVID-19. A major
problem with cross-sectional studies is that whether thefactors precede the outcome is unclear. Since the captureof factors in this study was obtained from health checkups
performed prior to the incidence of COVID-19, the factors
clearly preceded the outcome events. The duration forwhich the explanatory variables were maintained fromthe time of the health checkup to the evaluation of the
COVID-19 exacerbation was unclear, making per-protocol
analysis impossible. The explanatory variables were analyzed under the assumption that they were maintained
throughout the observation period. The method of thisstudy seems to correspond to the intention-to-treat analysis
of a target trial. Since the validity of the intention-to-treat
analysis in a target trial has been conﬁrmed, the analysis in
this study appears to be valid [32].

Conclusion
We conducted a cross-sectional study of 1,353 patientswith COVID-19 to clarify the lifestyle factors that inﬂuence exacerbation of COVID-19 severity. Exacerbating

Environmental Health and Preventive Medicine (2023) 28:73

factors included gender, age, and chronic lung disease,
while mitigating factors included which year patients visited our hospital for consultation, the number of vaccinations patients had been administered, and patient regularexercise. The results suggest that vaccination, regular exercise, and prevention of chronic lung disease are importantfactors for preventing exacerbation of COVID-19 severity.
Abbreviations
CI: conﬁdence interval; COVID-19: coronavirus disease 2019; COVID-19 exacerbation: severity classiﬁcation “moderate or severe”; OR: odds ratio.

Declarations
Ethics approval and consent to participate
This study was approved by the institutional review board of Okinawa North
Medical Association Hospital. We obtained written and online consent from theparticipants to use their anonymized personal data for research.
Consent for publication
Not applicable.
Availability of data and material
The data analyzed in this study are not publicly available.
Competing interests
The authors declare that they have no competing interests.
Funding
Not applicable.
Authors’ contributions
TK: Conceptualization, Resources, Data analysis, Writing – original draft.
DT: Conceptualization, Resources. YN: Conceptualization, Reviewing. YH:
Resources. MS: Resources. RT: Resources. AY: Resources. TM: Resources.
HS: Supervision.
Acknowledgments
We would like to thank Nurses Junko Shibayama, Noriko Kishimoto, Akinori
Tamaki, and Yasuko Oshiro from the COVID-19 Task Force at Okinawa North
Medical Association Hospital for managing the data. We deeply appreciate Drs.
Yoshihisa Nakamura, Tomoko Oshiro, Miwa Churiki, and Yasuko Kishimoto for
their support in conducting the health checkups. We would like to express our
sincere gratitude to Dr. Hitoshi Oshiro (DATA MILL LLC, Yonago, Japan) for
valuable suggestions regarding statistical analyses.
Received: 2 October 2023, Accepted: 27 October 2023
Published online: 25 November 2023

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