Journal of Healthy Eating and Active Living
2021, Vol. 1, No. 4, pgs. 169-185
Effects of the COVID-19 Pandemic on Physical Activity Behavior across Domains and Settings
Gina M. Besenyi1, Oziel Pruneda1, Emily L. Mailey1, Justin A. DeBlauw1, Cassandra M. Beattie1,
Jeanette Gustat2, and Katie M. Heinrich1
1
Department of Kinesiology, College of Health and Human Sciences, Kansas State University, U.S.A.
2
Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, U.S.A.
Abstract
COVID-19 restrictions and alterations to daily living (e.g. working from home, caregiving responsibilities) necessitated changes
in physical activity (PA) behavior. The purpose of this study was to understand how PA within specific domains and behavior
settings changed during the COVID-19 pandemic, as well as the extent to which PA increased or decreased as a function of
participants’ gender, work location (i.e., home vs. jobsite) and caregiving responsibilities. An e-survey, conducted April-June
2020, examined changes in PA across domains and settings in a national sample of 805 adults. Respondents reported domainspecific increases in household and recreational PA, but decreases in active transportation, occupational PA, and public
transportation use. Weekly minutes of PA changed significantly across all behavior settings, with reported increases in homebased, neighborhood, parks/trails, and total PA, and decreases in PA through recreational sports and fitness facilities. Total
weekly PA minutes increased by 10.6%. Those with caregiving responsibilities reported increases in household PA and PA
frequency, whereas those without caregiving responsibilities were more likely to report increases in sitting. Those working from
home reported a larger increase in neighborhood PA. Those working at a jobsite with caregiving responsibilities reported less
weekly PA, while those working from home with caregiving responsibilities reported greater weekly PA. The overall increase in
weekly PA minutes and ability to adapt to different domains/settings was encouraging. Future interventions should capitalize on
domain- and setting-specific changes, while considering work location and caregiving responsibilities to develop innovative PA
promotion strategies.
Keywords: COVID-19, Physical activity, domains, behavior settings, work, caregiving
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2021, Vol. 1, No. 4, pgs. 169-185
The coronavirus disease 2019 (COVID-19) is a novel
form of the coronavirus first identified in 2019 in Wuhan,
China (World Health Organization, 2020). COVID-19 is a
respiratory illness that can spread from person to person via
infected respiratory droplets, with health effects ranging
from asymptomatic to severe including death (CDC, 2019).
Due to exponential increases in cases, the World Health
Organization (WHO) declared the COVID-19 outbreak a
global pandemic in March 2020 (Cucinotta & Vanelli,
2020). To prevent the spread of the disease, public health
agencies such as WHO and the Centers for Disease Control
and Prevention (CDC) developed multiple
recommendations including frequent hand washing,
employing physical ‘social’ distancing of at least 6ft, mask
wearing, business closures, stay-at home orders,
quarantines post exposure, and maintaining a healthy
lifestyle including quitting smoking, eating a proper diet,
and staying physically active (Center for Disease Control
and Prevention, 2020; World Health Organization, 2020).
the Godin PA questionnaire and International Physical
Activity Questionnaire (IPAQ). The pandemic restrictions
altered the way in which university students engaged in PA
with a significant reduction in mild PA of 33.7% post
cancellation of in-person classes, along with a 13.9%
increase in weekly sitting time (Barkley et al., 2020).
Several studies have reported an increase in sedentary
behavior as well as decreases in PA during mandated
restrictions. Individuals who reported being usually active
before pandemic restrictions reported less moderate-tovigorous physical activity (MVPA) and a reduction in
overall PA during restrictions (Barkley et al., 2020; Karuc
et al., 2020; Schuch et al., 2020). Inactive and physically
active persons became less active by 40.5% and 22.4%,
respectively. (Lesser & Nienhuis, 2020). Likewise, a study
of U.S. adults found reductions in walking (-2232
steps/day) and moderate (-92.4min/week) and vigorous (66.9 min/week) PA, particularly in early phases of the
COVID-19 pandemic (Dunton et al., 2020).
Physical activity (PA), in particular, is an important
healthy lifestyle behavior that has a variety of physical,
mental, and social benefits. A wide body of literature
indicates that PA helps prevent and/or treat many physical
and mental health conditions (Powell et al., 2019). PA can
reduce the risk and severity of COVID-19 infection through
several biological processes. For example, PA can improve
the functioning of the immune system, reduce
inflammation, and improve the body’s response to vaccines
(Campbell & Turner, 2018; Jones & Davison, 2019; Lee et
al., 2019; Nieman & Wentz, 2019; Woods et al., 2020).
Decreases in PA are thought to cause a ‘downregulation’ of
the immune system resulting in harmful ‘second wave’
effects, particularly for those with COVID-19 (Woods et
al., 2020). Additionally, PA is effective for mitigating a
variety of chronic conditions (e.g., heart disease, diabetes,
cancers) that may increase the risk of severe complications
among those with COVID-19. PA can also play an
important role in managing mental health symptoms such
as stress and anxiety resulting from COVID-19 (e.g.,
increased health concerns, job loss, reduced income, social
isolation) (Callow et al., 2020; López-Bueno et al., 2020;
Maugeri et al., 2020; Schuch et al., 2020). Research shows
that PA has a positive impact on mental health disorders
and symptoms such as anxiety, stress, depression, and
emotional well-being (Ammar et al., 2020; Basso &
Suzuki, 2017; Galper et al., 2006) and has been
recommended as a therapeutic treatment for physical and
mental health during the pandemic (Amatriain-Fernández et
al., 2020).
Changes in PA participation may be due to a variety of
influences. Important influences to consider are behavior
settings for PA (e.g., homes, neighborhoods, fitness
facilities) representing different domains of active living
(i.e., active recreation, active transportation, household
activities, occupational activities) (Sallis et al., 2006). For
example, the COVID-19-forced closure of PA facilities
such as gyms and yoga studios limited indoor PA
opportunities. Yet, facility closures prompted increased
opportunities for alternative settings and forms of
recreational PA. Many recommendations to maintain PA
during early stages of COVID-19 shutdowns highlighted
home-based, outdoor, and online activities (Chen et al.,
2020; Jurak et al., 2020). Most Canadian adults opted for
PA in home or neighborhood settings, and those who were
previously active had significantly more outdoor PA during
COVID-19 (Lesser & Nienhuis, 2020). Altered daily
routines also eliminated settings for occupational and
transportation related PA. For example, the percent of the
U.S. population working entirely from home increased
from 8.2% in February 2020 to 35.2% in May 2020 (Bick
et al., 2020), along with surges in telecommuting and
online shopping, as well as increases in risk perception of
using public transportation options (bus, carpool, airplanes)
(Shamshiripour et al., 2020). Another report indicated that
2 out of 3 working parents had to change their childcare
arrangements due to COVID-19, and that 75% had children
at home during work hours (U.S. Chamber of Commerce
Foundation Center for Education and Workforce, 2020).
Despite many benefits, alterations in daily living during
COVID-19 necessitated changes in PA behavior (Knell et
al., 2020). Physical distance recommendations, mask
wearing, stay-at-home orders, quarantine, and closure of
non-essential businesses and public services all contributed
to changes in PA habits. A recent study completed by
Barkley et al. (2020) examined COVID-19 pandemicrelated acute effects on PA and sedentary behaviors. A pool
of 398 university students, faculty, and related personnel
self-reported PA levels, sedentary behavior, and body
weight pre- and post-cancellation of in-person classes via
Because of the numerous forced lifestyle changes during
COVID-19, little is known about how people are
participating in PA during the pandemic, particularly with
respect to PA settings and domains. Therefore, the purpose
of this study is to understand how PA within specific
domains and behavior settings has changed during the
COVID-19 pandemic. Additionally, to better understand
the impact of COVID-19 restrictions on PA behavior
within domains and settings, we explored the extent to
which PA increased or decreased as a function of
participants’ gender, work location (i.e., home vs jobsite)
and caregiving responsibilities.
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2021, Vol. 1, No. 4, pgs. 169-185
Methods
Study Design and Participants
This cross-sectional study assessed PA behavior before
and during the COVID-19 pandemic via an online survey.
The survey took approximately 15-20 minutes to complete
and was open to adults of all racial, ethnic, and income
groups or geographic locations in the U.S. Participants had
to be at least 18 years of age and able to read English. A
convenience sampling strategy was employed and
recruitment materials encouraged participants to aid
snowball sampling by forwarding the survey link on to
others. Recruitment occurred via social media posts,
emails, organizational and news outlets, and listservs. At
the beginning of the survey, participants read a short
description of the study purpose and completed informed
consent by clicking ‘agree’ to continue. Institutional
Review Boards at [blinded] University (#10135) and
[blinded] University (#202-784) approved all study
procedures.
Data Collection
Data was collected from April to June 2020 via an
online survey administered through Qualtrics Online
Survey Software (Provo, UT). During this time period, 42
U.S. states and territories had issued mandatory stay-athome orders resulting in significant decreases in population
movement (Moreland et al., 2020). Participants could either
complete the survey on a computer or mobile device. The
survey queried changes in PA behavior from before to
during COVID-19 including the frequency, duration,
domain, setting, and weekly minutes of PA. Survey
questions were sequenced so primary questions (changes to
PA minutes per week within settings) appeared first.
Measures
minutes of PA before COVID-19 retrospectively for each
setting, and then reported weekly minutes of PA during
COVID-19 (i.e., currently) for each setting. Outliers over
1800 minutes (30 hours) per week were removed. Total
weekly PA minutes before and during COVID-19 were
calculated by summing PA weekly minutes across all five
settings and were recoded into no PA (0 minutes), low
insufficient (1-59 minutes), moderate insufficient (60-149
minutes), sufficient (150-299 minutes), and exceeding
(>300 minutes) by setting.
Daily Living
As noted above, changes in daily living due to the
pandemic and related restrictions may influence PA
behaviors and the domains and settings in which they
occur. Therefore, respondents were asked information
about their daily life during the COVID-19 pandemic
including work location (home or jobsite), and whether
they had school-aged children or infant/toddlers at home or
other caregiving responsibilities (e.g., elderly or sick family
members). For analyses, two dichotomous variables were
created for work location (working exclusively from home
vs. doing any work at jobsite) and caregiving (“yes” to any
caregiving responsibilities vs. “no” to all).
Demographic Information
Demographics were assessed using standard questions
from national surveillance systems (e.g., Behavioral Risk
Factor Surveillance Systems, BRFSS; National Health and
Nutrition Examination Survey, NHANES). Demographics
captured included gender (male (M)/female (F)), age, race
(categorized as white/non-white), ethnicity (Spanish,
Hispanic, or Latino), education, income, marital status,
employment status (categorized as working/not working),
number of people and children under 18 in the household,
housing type (categorized as single- or multi-family
housing or other), and country and state of residence.
Physical Activity
Analysis
PA questions were developed to capture self-reported
change in PA behavior within specific settings due to the
COVID-19 pandemic. Perceived changes in PA domains,
duration, frequency, and sedentary time were collected via
a 5-point Likert scale ranging from much lower (1) to much
higher (5) with a three indicating ‘about the same’. PA
domains captured were based on active living domains that
included recreational PA, occupational PA, active
transportation, public transportation, and household PA
(Sallis et al., 2006). Data was recoded as lower (1), same
(2), and higher (3). Changes in PA mode, location, and
reason were captured by a 5-point Likert scale from
strongly disagree (1) to strongly agree (5). If participants
agreed that their PA behavior had changed during the
pandemic, they were asked to complete an open-ended
question describing how their PA had changed. PA
participation before and during COVID-19 was assessed in
five different settings (i.e., parks/trails, recreational sports,
in neighborhoods, at home, or in fitness facilities).
Participants also reported weekly minutes of PA before and
during COVID-19. Participants first reported weekly
Data was analyzed in SPSS 27 (SPSS, Chicago, IL).
Descriptive statistics were assessed using mean and
standard deviation (SD) for continuous variables and count
(n) and absolute frequencies (%) for categorical variables.
Chi-square analyses were conducted to explore whether the
percentages of participants with increased or decreased PA
in various domains differed by gender, work location or
caregiving status. Given the non-parametric nature of
weekly minutes of PA within settings, paired sample t-tests
and Wilcoxon signed-rank tests examined changes in PA
from before to during COVID-19. Repeated measures
ANOVAs and ANCOVAs explored differences in PA
categories across settings before and during COVID-19 and
between-subject interactions with work location (home vs
jobsite), caregiving (yes [Y]/no [N]), and gender (M/F).
Open-ended questions were assessed using a constructivist
grounded theory approach allowing participant comments
to add experiential meaning and context to indicated
changes to PA behavior (Charmaz, 2006).
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2021, Vol. 1, No. 4, pgs. 169-185
Results
A total of 1224 survey respondents completed informed
consent. Of these, 955 completed PA questions. For the
current analysis, we removed respondents with incomplete
demographic information (n = 136) and those living outside
of the U.S. (n = 14), resulting in a final sample of 805
participants. Of these, the majority were white (84.7%) and
female (78.0%), with a mean age of 38.7 years (SD = 14.9).
For further insights, see Table 1. Most respondents had a
graduate degree (53.0%) and were employed (78.2%), and
35.2% had an income of $100,000 or more. The majority
(64.5%) reported being in a relationship (either married or
as an unmarried couple) and living in single-family housing
(67.3%), with an average of 2.8 (SD = 1.4) people in the
household, with 0.6 (SD = 1.0) persons under the age of 18.
Respondents represented 42 out of 50 states across the
U.S., with the majority from the Midwest (67.0%) or South
(21.2%). Daily life questions indicated that that majority
were working exclusively from home (66.3%) rather than
at a traditional job site (16.1%). Just under one third of
participants (31.6%) indicated they had caregiving
responsibilities such as school aged children at home
(20.9%), infants or toddlers at home (10.1%) or other
caregiving responsibilities (8.1%).
Figure 1a displays self-reported changes in PA during
the COVID-19 pandemic across the five domains. The
greatest number of respondents indicated higher amounts of
recreational (44.9%) and household PA (55.9%) during
COVID-19, but reported decreases in occupational PA
(55.1%), active transportation (57.1%), and public
transportation use (25.7%). Respondents also reported
changes in PA and sedentary behavior. As shown in Figure
1b, many respondents reported higher time sitting (60.7%),
but many also indicated increases in PA duration (46.2%)
and frequency (43.9%). Around one-fourth of the sample
(19.1% - 35.8%) indicated no change in PA domain or
participation. The majority of respondents also agreed or
strongly agreed that changes occurred in their mode
(76.8%), location (79.0%), and reasons for PA (53.5%)
(Figure 1c).
As seen in Table 2, participants working at a jobsite
were less likely to report reductions in occupational PA
(2=41.83, p < 0.001), active transportation (2=26.08, p <
0.001), and public transportation use (2=10.71, p = 0.005)
than those working exclusively from home, but participants
working from home were more likely to report increases in
recreational PA (2=9.80, p = 0.007). Participants with
caregiving responsibilities were more likely to report
increases in household PA (2=9.82, p = 0.007) and
frequency of PA (2=8.21, p = 0.02) than participants
without caregiving responsibilities, whereas participants
without caregiving responsibilities were more likely to
report increases in sitting than those with caregiving
responsibilities (2=20.55, p < 0.001). Caregivers were also
more likely to report that their reasons for PA had changed
(2=13.44, p = 0.001). Finally, females were more likely
than males to report that their recreational PA (2=16.61, p
< 0.001), PA frequency (2=10.52, p = 0.005), PA duration
(2=20.38, p < 0.001) and PA mode (2=5.97, p = 0.05) had
increased or changed, whereas males were more likely to
report that they had stayed the same.
Based on the Wilcoxon signed-rank tests, weekly
minutes of PA behavior across all settings significantly
changed from before to during COVID-19 (p<0.05 for all
settings) (Figure 2). Increased weekly minutes of PA were
reported for parks/trails, neighborhoods, and home-based
settings, while fewer minutes of PA were reported for
recreational sports and fitness facilities. Weekly minutes of
home-based PA had the largest increase at 101.0% (Z =
18.9, p < 0.001), while fitness facilities showed the largest
decrease during COVID-19 restrictions compared to before
at 98.1 % (Z = -19.0, p < 0.000). Overall, weekly minutes
of total PA significantly increased by 10.6% from 391.9
min/week before to 433.5 min/week during COVID-19 (Z=
4.428, p < .000).
To reduce sample skewness and kurtosis, weekly
minutes of PA within settings were categorized as shown in
Table 3. Despite this, sample skewness and kurtosis was
still too great to examine main or interaction effects for
fitness facility PA. Results of the repeated measures
ANCOVAs comparing differences in PA across remaining
settings before and during COVID-19 by work location
(home vs jobsite), caregiving (Y/N), and gender (M/F) are
shown in Table 4. Significant main effects were found for
recreational sports (F(1,641) = 66.00, p < 0.001),
neighborhood PA (F(1,638) = 26.44, p < 0.001), and homebased PA (F(1,641) = 120.31 p < 0.001). Recreational sport
PA decreased, while neighborhood and home-based PA
increased from before to during COVID-19. Multiple
significant between-subject interactions were noted. Males
experienced a greater decline in recreational sport PA than
females from before to during COVID-19 (F(1,641) =
10.80, p = 0.001). Those working from home saw a larger
increase in neighborhood PA from before to during the
pandemic (F(1,638) = 4.93, p = 0.027). Those without
caregiving responsibilities reported a greater increase in
home-based PA than those with caregiving responsibilities
(F(1,641) = 6.31, p = 0.012), though those with caregiving
responsibilities reported more home-based PA at both time
points. Those working at a jobsite experienced a decline in
total PA, while those working from home reported an
increase in total PA (F(1,641) = 9.85, p = 0.002). In
particular, those working at a jobsite that also had
caregiving responsibilities reported less weekly PA, while
those working from home with caregiving responsibilities
reported greater weekly PA (F(1, 646) = 4.23, p = 0.04).
Responses to the open-ended survey questions provided
additional context to describe the changes reported in the
quantitative results. Table 5 displays seven themes
identified in the quantitative data related to changes in
physical activity, with exemplar quotes for each. Themes
included (a) decreases in occupational activity, (b)
decreases in active transportation, (c) increased sitting time,
(d) no PA at fitness facilities, (e) increases in outdoor PA,
(f) increases in home-based activity, and (g) new modes of
PA. Many participants described reductions in occupational
and transport-related activity as a function of working from
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2021, Vol. 1, No. 4, pgs. 169-185
home (i.e. their reason for PA changed due to changes in
settings). Even if they did not have physically active
occupations, most incidental activity they had accumulated
by walking to meetings, talking to colleagues, taking the
stairs, etc. was eliminated with the shift to remote work.
These changes also contributed to an increase in sitting
time, as participants were spending long hours in front of a
computer in virtual meetings.
Many participants also described how the closures of
fitness facilities had influenced their PA behaviors. Without
the option of going to a fitness facility, individuals were
forced to develop creative solutions to stay active at home
or outdoors. Often these changes in settings necessitated a
change in PA mode (e.g., doing outdoor or home-based PA
such as walking or yoga rather than using gym-based
weight and cardio machines), as participants did not have
access to the same resources and exercise equipment in the
home environment. However, many participants shared
positive experiences associated with these changes; they
engaged in new types of PA that they would not have
otherwise tried, tackled indoor and outdoor home projects,
took frequent walks in the neighborhood, and explored
outdoor parks and trails they had not had time to visit
before the pandemic. As a result, the majority of
individuals were able to maintain or increase their PA
frequency (73.6%) and duration (66.1%) in spite of the
COVID-19 pandemic.
Discussion
The purpose of this study was to assess changes in PA
within five domains and five behavior settings during the
COVID-19 pandemic as well as explore how PA changed
as a function of gender, work location, and caregiving
responsibilities. Respondents self-reported domain-specific
increases in household and recreational PA, but decreases
in active transportation, occupational PA, and public
transportation use. These findings are reflective of
increases in working from home and risk perception of
using public transportation previously noted (Bick et al.,
2020; Shamshiripour et al., 2020). Respondents reported
their weekly minutes of PA changed significantly across all
behavior settings, such that there were increases in homebased, neighborhood, parks/trails, and total PA, and
decreases in PA through recreational sports and fitness
facilities. Males in particular reported decreased
recreational sport PA during the pandemic, whereas
females were more likely to report increased recreational
PA overall.
Our results suggest that while the pandemic created a
shift in usage of specific PA domains/settings (e.g., reduced
workplace access, use of active and public transportation,
and access to fitness facilities), respondents were able to
offset these restrictions by increasing recreational and
household PA at home and outdoors, for a 10.6% increase
in total PA. In particular, those working from home
significantly increased their neighborhood and total PA,
while those with and without caregiving responsibilities
saw increases in home-based PA, although more so for
caregivers. Interestingly, those working at a jobsite that
also had caregiving responsibilities saw a decline in total
PA during the pandemic. On the other hand, those working
from home that also had caregiving responsibilities saw an
increase in total PA. A recent study by Del Boca et al.
(2020) found that with the exception of those continuing to
work at a jobsite, all of the women in the study spent more
time on housework than before COVID-19. Although we
found few gender specific interactions, other studies note
the increased burden of childcare on parents during the
pandemic, particularly mothers (Carlson et al., 2020;
Prados & Zamarro, 2020). While some participants
remarked on the loss of incidental workplace activities
(e.g., walking to meetings), active transportation (e.g., no
walking to school), and fitness facility access, other
comments highlighted how respondents had increased their
PA at home (e.g., home workouts, playing with children),
and outdoors (e.g., hiking, gardening), and discovered new
ways to stay active that were affordable and sustainable
(e.g., yoga, high intensity interval training [HIIT]).
The overall increase in PA for our sample is in contrast
with previous research that reported significant decreases in
MVPA and overall PA, which was true for both previously
inactive and physically active adults (Barkley et al., 2020;
Karuc et al., 2020; Schuch et al., 2020; Lesser & Nienhuis,
2020). Another previous study found reduced walking,
moderate, and vigorous physical activity among U.S. adults
(Dunton et al., 2020). However, the same study found that
those who reported at least 30 min of PA per week, also
reported the most common settings for their activity during
COVID-19 as home-based (75.0%), neighborhood (69.9%),
and parks/trails (27.1%), which agrees with previous
research among Canadians as well as our findings for the
same behavior settings (Dunton et al., 2020; Lesser &
Nienhuis, 2020). It is possible that the focus of our study on
ascertaining PA within specific domains and settings may
have allowed for our survey respondents to better recall
their activity based on the contextual cues provided within
our questions rather than having to recall days and minutes
of PA each day of their week for walking, moderate, and
vigorous activities. In essence, that focus allowed us to
examine, and participants to consider, the nuances in where
their PA was taking place and consider various types of PA
that they were doing in different domains and settings
(beyond only recreational PA), which showed an overall
increase.
Our respondents reported significantly more time spent
sitting, especially for those with no caregiving roles. This
agrees with results from a survey by Qi et al. (2020) of
Chinese adults who reported significant increases in
sedentary time during COVID-19 as well as with Barkley
et al. (2020) who reported a 13.9% increase in sedentary
behavior among university students after in-person classes
were cancelled. In our study, many participants remarked
that sitting had displaced PA typically accumulated
throughout the day, especially for work-related tasks. They
commented on increased screen time related to work and
that there was no longer a need to move to attend meetings,
talk to colleagues, etc.
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particularly for those with increased screen time, such as
those working from home.
Study Considerations
Our study recruited a large sample geographically
dispersed across 42 out of 50 states with the majority
residing in the Midwest or South. Similarities between our
sample and those from previous COVID-19 and PA survey
research included the majority of respondents being female,
white, married, and having higher incomes (Barkley et al.,
2020; Dunton et al., 2020; Karuc et al., 2020; Lesser &
Nienhuis, 2020; Schuch et al., 2020). Two-thirds of our
sample reporting working from home (66.3%) compared to
national reports of 35.2% (Bick et al., 2020). Our sample
was highly active and seemed motivated to find ways to
continue to participate in PA. There are also some
limitations to our study that should be mentioned. Although
PA questions were guided by the active living framework,
self-report items are subject to recall and social desirability
bias. Further, we did not objectively collect PA data and
results should be interpreted as perceived change in PA.
The cross-sectional nature of the survey should only be
used to indicate associations and not causation. Finally, we
note there are many variables that influence PA. Although
we focused on gender, caregiving, and work location in
current analyses, future work should further explore and/or
control for additional variables of interest such as age, race,
income, or education.
Conclusion
The overall increase in PA as well as ability of
respondents to adapt to new PA domains and settings
during a global pandemic was encouraging. As telework
and childcare roles extend through the pandemic and
beyond, future interventions should further identify and
capitalize on domain- and setting-specific changes to
promote innovative strategies for staying active.
Correspondence should be addressed to
Gina M. Besenyi
920 Denison Avenue
Manhattan, KS 66506
gbesenyi@ksu.edu
785-532-0836
Gina M. Besenyi: 0000-0002-4538-9510
Emily L. Mailey: 0000-0001-7672-445X
Jeanette Gustat: 0000-0001-5597-1611
Katie M. Heinrich: 0000-0002-6837-408X
Implications
Author Contributions
Findings from this study highlighted the domains and
behavior settings that saw the greatest changes in PA.
Creation of interventions and policies to improve PA
during the pandemic should focus on accessible settings
such as parks and trails, homes, or neighborhood
environments, while taking into account the role that work
location and caregiving responsibilities play in where and
how people are active. Special attention should be made for
those working at jobsites (i.e., essential or frontline
workers) that also have caregiving responsibilities who are
currently experiencing a decline in PA. Additionally,
efforts should be made to reduce sedentary time,
Conceptualization, G.M.B, K.M.H., E.L.M., and J.G.;
Methodology, G.M.B, K.M.H., E.L.M., J.G., O.P., J.D.,
and C.B.; Investigation, G.M.B, K.M.H., E.L.M., J.G., J.D.,
and C.B.; Writing – Original Draft, G.M.B, K.M.H.,
E.L.M., and O.P.; Writing – Review & Editing, G.M.B,
K.M.H., E.L.M., J.G., O.P., J.D., and C.B.; Project
Administration, G.M.B.
Creative Commons License
This work is licensed under a Creative Commons
Attribution-Noncommercial 4.0 License.
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2021, Vol. 1, No. 4, pgs. 169-185
Table 1. Sample Demographics
Total Sample
Gender
Male
Female
Race
White
Nonwhite
Spanish, Hispanic, or Latino (Yes)
Marital Status
Married/Unmarried Couple
Divorced/Separated
Widowed
Never Married
Employment Status
Working
Not Working
Education
High School
Some College
Associates Degree
Bachelor’s Degree
Graduate Degree
Income
< $20,000
$20,000 - $60,000
$60,001 - $100,000
+ $100,000
Housing Type
Detached single family house
Multi-family housing (apt, townhouse)
Other
Daily Life
Working from home
Working at jobsite
Caregiving (yes)
Caregiving (no)
Location
Northeast
Midwest
South
West
aSome categories do not sum to total sample due to missing data
n
805
%
100.0
163
628
20.2
78.0
682
115
54
84.7
14.3
6.7
519
49
8
222
64.5
6.1
1.0
27.6
630
167
78.2
20.8
23
88
32
232
426
2.9
10.9
4.0
28.8
53.0
65
165
206
283
8.1
20.5
25.6
35.2
542
248
12
67.3
30.7
1.5
534
130
254
551
66.3
16.1
31.6
68.4
21
533
169
60
2.6
67.0
21.2
7.5
175
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2021, Vol. 1, No. 4, pgs. 169-185
Table 2. Physical Activity Domain and Participation During COVID-19 compared to Pre-Pandemic as a Function of Gender and Daily Living
n (%)
Lower
Recreational Physical Activity (n=804)
Male (n=163)
Female (n=627)
Working from home (n=534)
Working at jobsite (n=129)
Occupational Physical Activity (n=697)
Working from home (n=475)
Working at jobsite (n=126)
Active Transportation (n=752)
Working from home (n=500)
Working at jobsite (n=120)
Household Physical Activity (n=805)
Caregiving (n=254)
No caregiving (n=551)
Use of Public Transportation (n=372)
Working from home (n=253)
Working at jobsite (n=53)
Duration of Physical Activity (n=801)
Male (n=163)
Female (n=624)
Frequency of Physical Activity (n=801)
Male (n=163)
Female (n=624)
Caregiving (n=252)
No caregiving (n=549)
Time Sitting (n=803)
Caregiving (n=254)
No caregiving (n=549)
Same
288 (35.8)
154 (19.1)
53 (32.5)
50 (30.7)
231 (36.8)
104 (16.6)
186 (34.8)
88 (16.5)
47 (36.4)
35 (27.1)
411 (51.1)
229 (28.4)
296 (62.3)
155 (32.6)
46 (36.5)
55 (43.7)
379 (47.1)
234 (29.1)
275 (55.0)
134 (26.8)
37 (30.8)
58 (48.3)
67 (8.4)
288 (35.8)
15 (5.9)
77 (30.3)
52 (9.4)
211 (38.3)
207 (25.7)
164 (20.4)
147 (58.1)
105 (41.5)
18 (35.8)
35 (66.0)
269 (33.4)
160 (19.9)
45 (27.6)
53 (32.5)
219 (35.1)
104 (16.7)
208 (25.8)
239 (29.7)
36 (22.1)
66 (40.5)
169 (27.1)
171 (27.4)
58 (23.0)
64 (25.4)
150 (27.3)
175 (31.9)
121 (15.1)
193 (24.0)
58 (22.8)
65 (25.6)
63 (11.5)
128 (23.3)
Disagree
Neither
Mode Changed (n=805)
95 (11.8)
92 (11.4)
Male (n=163)
21 (12.9)
27 (16.6)
Female (n=628)
74 (11.8)
63 (10.0)
Location Changed (n=805)
89 (11.1)
80 (9.9)
Reason Changed (n=805)
185 (23.0)
189 (23.5)
Caregiving (n=254)
45 (17.7)
49 (19.3)
No caregiving (n=551)
140 (25.4)
140 (25.4)
a
Only statistically significant results (p < .05) from chi-squared analyses are included in table
Higher
362 (44.9)
60 (36.8)
292 (46.6)
260 (46.8)
47 (36.4)
57 (7.0)
24 (5.1)
25 (19.8)
139 (17.2)
91 (18.2)
25 (20.8)
450 (55.9)
162 (63.8)
288 (52.3)
1 (0.1)
1 (0.04)
0 (0)
372 (46.2)
65 (40.0)
301 (48.2)
354 (43.9)
61 (37.4)
284 (45.5)
130 (51.6)
224 (40.8)
489 (60.7)
131 (51.6)
358 (65.2)
Agree
618 (76.8)
115 (70.6)
491 (78.2)
636 (79.0)
431 (53.5)
160 (63.0)
271 (49.2)
2
P value
16.61
<0.001
9.80
0.007
41.83
<0.001
26.08
<0.001
9.82
0.007
10.71
0.005
20.38
<0.001
10.52
0.005
8.21
0.02
20.55
<0.001
5.97
0.05
13.44
0.001
176
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2021, Vol. 1, No. 4, pgs. 169-185
Table 3. Physical Activity Across Settings Before and During COVID-19
No PA (0
Low
Moderate
Min)
Insufficient (1Insufficient (6059 Min)
149 Min)
n (%)
n (%)
n (%)
Parks/Trails
Before
246 (30.6)
250 (31.1)
211 (26.2)
During
290 (36.0)
168 (20.9)
199 (24.7)
Recreational Sports
Before
583 (72.4)
86 (10.7)
90 (11.2)
During
748 (92.9)
25 (3.1)
15 (1.9)
Neighborhoods
Before
114 (14.2)
245 (35.2)
283 (35.2)
During
82 (10.2)
160 (19.9)
283 (35.2)
Home
Before
135 (16.8)
214 (26.6)
298 (37.0)
During
33 (4.1)
92 (11.4)
277 (34.4)
Fitness Facilities
Before
307 (38.1)
68 (8.4)
157 (19.5)
During
787 (97.8)
4 (0.5)
6 (0.7)
Total
Before
14 (1.7)
45 (5.6)
93 (11.6)
During
6 (0.7)
40 (5.0)
90 (11.2)
Sufficient
(150-299
Min)
n (%)
Exceeds (>300
Min)
48 (6.0)
80 (9.9)
31 (3.9)
61 (7.6)
28 (3.5)
4 (0.5)
14 (1.7)
8 (1.0)
95 (11.8)
176 (21.9)
52 (6.5)
101 (12.5)
88 (10.9)
220 (27.3)
67 (8.3)
178 (22.1)
147 (18.3)
3 (0.4)
123 (15.3)
2 (0.2)
209 (26.0)
171 (21.2)
443 (55.0)
497 (61.7)
n (%)
177
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Table 4. Physical Activity Across Settings Before and During COVID and Interactions with Work Location, Caregiving,
and Gender
Source
F
df
sig
ηp2
Parks/Trails PA
1.78
1
.183
.003
Recreational Sports PA
66.00
1
.000
.093
Recreational Sports * Gender
10.80
1
.001
.017
Neighborhood PA
26.44
1
.000
.040
Neighborhood PA * Work Location
4.93
1
.027
.008
Home-based PA
120.31
1
.000
.158
Home-based PA * Caregiving
6.31
1
.012
.010
Total PA
0.26
1
.608
.000
Total PA * Work Location
9.85
1
.002
.015
Total PA * Work Location * Caregiving
4.23
1
.040
.006
178
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Table 5. Open-Ended Survey Reponses
Effect on PA
Exemplar quotes
Decrease in
occupational
activity
•
•
•
Decrease in active
transportation
•
•
•
Increased sitting
time
•
•
•
No PA at fitness
facilities
•
•
•
Increase in
outdoor PA
•
•
•
I use to walk a lot more in the office and take the stairs multiple times per day. I also used to stand at
my desk
As a teacher I am on my feet walking around the classroom and hallways all day long. Being online
forces me to sit in front of a screen way too many hours of the day.
I have a desk job and have lost the casual movement around the office and walking from meeting to
meeting. Now all my meetings are at one desk. I am making effort to pace during calls and take a
walk around the block when I can.
Rather than walking on campus to get from meeting to meeting, I've had to focus on taking time
every day to ensure I get similar amounts of physical activity
I used to walk to and from campus nearly every day, now I barely leave my apartment.
Instead of walking my child to school and back twice a day or scootering I need to take him out to
scooter so he gets exercise and this cuts out about 40 minutes of walking or scootering Monday
through Friday. Which was unavoidable exercise and now it's so far much less because I'm busy or
tired
I'm working remotely on COVID-19 response. In the past I would do this by physically responding
to response but am spending 16+ hours a day at a computer usually in virtual coordination meetings.
I would like to go outside to exercise but I don't have time.
My gym is closed so I no longer go to fitness classes and I work 100% at home remotely now so I sit
all day at my desk.
I need to get out for a walk to keep me sane as I am stuck at a computer for way too long each day
now that I work from home.
I used to go to the athletic club @ 5am nearly every work day (M-F) to run on the indoor track or
treadmill, lift weights, or swim. I cannot do any of that now. Now I'm doing yoga/stretching in my
apartment most mornings and short runs outside 2-3 times/week.
I can no longer go to the gym and with 2 little kids at home it makes it nearly impossible to get a
workout in. Instead we take walks and go on family disc golf outings.
I typically workout at the gym, and now that the gyms are closed, I have to work out in my own
home, which is not as motivating for me.
Our family is using the weekends to travel to different hiking areas and historical areas in [our state].
The reason is that we are bored of home, we have less work to complete over the weekends, and we
can still socially distance. This is a more active routine that usual.
Since working remotely, I have begun almost daily morning hikes. When working in an office I was
unable to participate in morning physical activities due to time constraints. Because if this my
physical activity has increased
Lots of playing with my 4 year old son, gardening, playing in the water, biking and walking that I
wasn't able to do while working.
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2021, Vol. 1, No. 4, pgs. 169-185
Increased homebased activity
•
•
•
New modes of PA
•
•
•
I am home more so I am naturally more active because of the small children and the 'spring'
cleaning/organizing that I'm getting into. My Fitbit says I am doing more, but that it’s not official
PA, just doing stuff around the house and yard and with the kids. Way more active, way less
sedentary.
Less walking around for work than when I was physically going into my office but I'm spending
more time during the day doing things around the house such as cleaning and yardwork when I break
from work stuff.
Working from home allows me to have more time to work to do housework, work in yard, plant
garden, trim trees, etc. due to time gained in not commuting, no physical meetings and minimal trips
to store.
I went from doing weight training to purely cardio/HIIT training since being at home.
I have started trying different exercises, especially ones that do not require equipment or space. For
example, instead of lifting weights, I have been doing yoga.
No longer able to access a gym; so have been doing more hiking/walking/jogging and utilizing free
weights at home
180
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2021, Vol. 1, No. 4, pgs. 169-185
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Appendix
Figure 1a
Self-reported Changes in Physical Activity Participation Across Domains
100.0%
% OF PEOPLE
80.0%
56.0%
60.0%
51.4%
47.7%
44.7%
40.0%
35.7%
35.1%
28.6%
27.9%
27.7%
19.3%
17.3%
19.4%
20.0%
7.0%
8.8%
0.1%
0.0%
Recreational
Occupational
Lower
Household
Active
Transportation
Stayed Same
Use of Public
Transit
Higher
Note. These changes are across all demographics and domains.
Figure 1b
Self-reported Changes in Physical Activity Duration, Frequency, and Sitting
100.0%
% OF PEOPLE
80.0%
60.5%
60.0%
44.9%
40.0%
43.4%
33.9%
26.7% 29.2%
24.5%
20.5%
14.8%
20.0%
0.0%
Duration
Frequency
Lower
Stayed Same
Time Sitting
Higher
Note. These changes are across all demographics and domains.
184
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2021, Vol. 1, No. 4, pgs. 169-185
Figure 1c
% OF PEOPLE
Self-reported Changes in Physical Activity Participation Mode Location and Reason
100.0%
90.0%
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
79.0%
76.8%
53.5%
23.0% 23.5%
11.8% 11.4%
Mode
Disagree/Strongly Disagree
11.1% 9.9%
Location
Neither
Reason
Agree/Strongly Agree
Note. These changes are across all demographics and domains.
Figure 2
Self-reported Changes in Weekly Minutes of Physical Activity Across Settings Before and During COVID-19
Note. These changes are across all demographics and domains.
185