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The COVID-19 pandemic means that many of us are staying at home and sitting down more than we usually do. It’s hard for a lot of us to do the sort of exercise we normally do. It’s even harder for people who don’t usually do a lot of physical exercise. But at a time like this, it’s very important for people of all ages and abilities to be as active as possible. WHO’s Be Active campaign aims to help you do just that - and to have some fun at the same time. Remember - Just taking a short break from sitting, by doing 3-4 minutes of light intensity physical movement, such as walking or stretching, will help ease your muscles and improve blood circulation and muscle activity. Regular physical activity benefits both the body and mind. It can reduce high blood pressure, help manage weight and reduce the risk of heart disease, stroke, type 2 diabetes, and various cancers - all conditions that can increase susceptibility to COVID-19.It also improves bone and muscle strength and increases balance, flexibility and fitness. For older people, activities that improve balance help to prevent falls and injuries. Regular physical activity can help give our days a routine and be a way to stay in contact with family and friends. It’s also good for our mental health - reducing the risk of depression, cognitive decline and delay the onset of dementia - and improve overall feelings.

Participant Recruitment and Study Design In early COVID , a convenience sample of participants was recruited through social media platforms to complete a brief survey about their PA habits before and during the COVID-19 shutdowns in INDIA(JAMMU AND KASHMIR). A brief description of the survey was included in the invitation. The researchers posted the survey link on their social media ids with the link open for others to share it. This allowed the link to be accessible to anyone on these social media outlets. The consent form was available to participants when they opened the link to the survey. To begin the survey, participants agreed to a statement of consent by selecting an agreement box. Participants were required to be older than 18 yr and residing in Jammu and Kashmir. No other inclusion or exclusion criteria were used. Pre-shutdown was defined for participants as “early April 2020,” and during shutdown was defined for participants as “early June 2020.” After consent to participate, the survey began with demographic questions such as gender identity, race and ethnicity, age, state of residence, annual income, and highest level of education achieved. Demographic questions were included to characterize participants and identify any potential relationships between demographic factors and changes in PA. Additional questions about perceived neighborhood safety and type of residence location (rural, suburban, urban) were included to identify factors that may influence outdoor exercise because of fitness center closures. For both pre- and during-shutdown time periods, participants were asked to indicate the average number of days each week they participated in PA, average number of minutes per session (0; 1, 1–30 min; 2, 31–60 min; 3, 61–90 min; 4, 91–120 min; 5, 120+ min), and average intensity per session (0, no activity; 1, very light; 2, light; 3, moderate; 4, high; 5, maximal intensity activity). For each time period, participants were asked if there was any other information they wanted to share about their PA habits during that time. In addition, participants were asked if there were any other wellness habits they changed during the COVID-19 pause. These open-ended questions provided an opportunity for participants to elaborate on their responses. Finally, participants were asked how likely they were to maintain their during-shutdown PA habits (1, very likely; 2, likely; 3, unlikely). All survey questions were developed by the researchers and pilot tested with a small sample for clarity. No questions were altered as a result of pilot testing.

Descriptive statistics such as mean, SD, and frequencies were used to describe the survey data. Paired-samples t-tests were used to compare differences between pre-shutdown and during-shutdown responses to questions about PA habits. Cohen’s d was calculated for effect size following significant paired-samples t-tests. Participants were then categorized into one of three groups for both pre- and during-shutdown PA levels. Groups were defined as 1) not meeting the PA guidelines, 2) just meeting the PA guidelines, and 3) exceeding the PA guidelines. Alignment with the PA guidelines was determined by the product of days per week of exercise and average minutes per week of exercise. Movement between groups from pre- to during-shutdown periods was analyzed using frequency data. Bivariate correlations were used to examine relationships between PA habits and likeliness for maintaining during exercise habits . Bivariate correlations were also used to examine relationships between PA habits, change in PA habits, and demographic data. Gender differences were examined among all variables using frequency analysis and independent-samples t-tests. When the Levene’s test for equality of variances was significant, adjusted degrees of freedom were used. Because of the very small sample of nongender binary respondents (n = 3), we chose to focus on respondents identifying as male or female. A one-way ANOVA was used to determine differences in perceived neighborhood safety across areas of residence. Hedges’ g was used to determine the effect size of pairwise comparisons because of unequal group size. Cohen’s d and Hedges’ g were interpreted using levels described by Cohen (25). Values of 0.2 indicate small effect, values of 0.5 indicate medium effect, and values of 0.8 indicate a large effect. An α value of 0.05 was used to evaluate significant differences. All data are reported as mean ± SD unless otherwise noted.

Participants Demographics

A total of 873 Indian  residents older than 18 yr completed the survey. The sample was 85.3% female (n = 745) with an average age of 38.7 ± 12.9 yr. and 87.6% earned a bachelor’s degree or higher   (Table 1).

TABLE 1 - Demographic Information for 873 Participants

Changes in PA between the Pre- and During-Shutdown Periods

Before the shutdown, 52.7% of participants reported meeting or exceeding the guidelines of 150 min of moderate-to-vigorous PA per week. The percentage of participants meeting the PA guidelines increased by 7.8% from pre-shutdown to during the shutdown. The percentage of participants exceeding the PA guidelines increased by 11.3% . More than half (66.8%) of individuals not meeting the PA guidelines before the shutdown increased PA during the shutdown, and 50.1% increased enough to meet the PA guidelines . Less than half (46.3%) of individuals meeting or exceeding the PA guidelines before the shutdown decreased PA during the shutdown, and 30% fell below the PA guidelines . Overall, days per week of PA significantly increased from pre-shutdown to during the shutdown (3.75 ± 1.9 to 4.27 ± 2.1 d, P < 0.001; 95% confidence interval (CI), −0.68 to −0.37; d = 0.26), whereas minutes of activity per session remained relatively the same (1.87 ± 0.95 to 1.93 ± 0.98 min, P = 0.10; 1, 1–30 min; 2, 31–60 min; 95% CI, −0.13 to 0.01). Average intensity of exercise sessions significantly decreased from pre-shutdown to during the shutdown by −6.76% (2.81 ± 1.16 to 2.62 ± 1.14, P < 0.001; 95% CI, 0.1 to 0.28; d = 0.017; Table 2. Weekly PA dose was calculated by the product of average intensity per session (e.g., 1, very light; 2, light, etc.), range of minutes of activity per day (e.g., 1, 1–30 min; 2, 31–60 min, etc.), and days per week of activity, to create a composite score. During-shutdown dose (29.4 intensity·(min·wk−1)) was significantly greater than pre-shutdown dose (26.9 intensity·(min·wk−1); t(872) = −2.79; P = 0.005; 95% CI, −4.27 to −0.75; d = 0.10). Based on the criteria set by Cohen (25) results for all Cohen’s d and Hedges’ g values indicate small effects. Open-ended responses indicated that lack of access to fitness facilities and exercise classes as well as more aerobic walking outdoors were related to the decrease in exercise intensity.

TABLE 2 - Differences in PA Level between Pre-Shutdown  and During-Shutdown

 

Males experienced a significantly greater change than did females in minutes per exercise session (males, −0.136 ± 1.06 min; females, +0.09 ± 1.07 min; P = 0.028; 95% CI, −0.43 to −0.02; g = 0.21; Table 3. Males experienced a significantly smaller change in days of exercise per week than did females (males, −0.024 ± 2.0 d; females, +0.615 ± 2.36 d; t(187.18) = −3.21; P = 0.002; 95% CI, −1.08 to −0.20; g = 0.28). Levene’s test indicated unequal variances (F = 8.75, P = 0.003), so degrees of freedom were adjusted from 868 to 187.18. Changes in exercise intensity from pre-shutdown to during the shutdown were not significantly different between males and females (males, −0.35 ± 1.16; females, −0.16 ± 1.42; P = 0.155; 95% CI, −0.45 to 0.07). Based on the criteria set by Cohen (25), results for all Cohen’s d and Hedges’ g values indicate small effects.

TABLE 3 - Differences in Pre- and During-Shutdown Days of PA, Minutes of PA, and Intensity of PA in Male and Female Participants

 

**Significant difference in change from pre to during between male and female participants (P < 0.05).

Changes in weekly PA, from pre-shutdown to during the shutdown, were not related to education (R = 0.12, P < 0.01), income (R = 0.04, P = 0.22), perceived neighborhood safety (R = −0.07, P = 0.04), or type of area participants lived in (R = 0.021, P = 0.54). Changes in exercise habits were also not related to physical characteristics such as body mass index (R = −0.10, P = 0.002), race or ethnicity (R = −0.11, P = 0.001), and age (R = 0.04, P = 0.22). There was a significant difference in perceived safety of neighborhood across different areas of residence (F(2, 870) = 63.39; P < 0.01). Individuals in rural areas (1.22 ± 0.512) perceived their neighborhoods as safer than did those in urban areas (1.79 ± 0.732, P < 0.01; 95% CI, −0.68 to −0.46; g = 0.91), but not differently from those in suburban areas (1.30 ± 0.519, P = 0.60; 95% CI, −0.18 to 0.00; g = 0.155). Participants in suburban areas perceived their neighborhoods as significantly safer than did those in urban areas (P < 0.01; 95% CI, −0.58 to −0.39; g = 0.83). Based on the criteria set by Cohen (25), Hedges’ g values of 0.8 or greater indicate large effects. Likelihood of Maintaining During-Shutdown PA Behavior Change for 1 Yr Overall, 73.4% of participants indicated they were likely or very likely to maintain the PA habits they adopted during the shutdown (1.89 ± 0.80; . Almost all (93.8%) of those who increased their PA during shutdown reported they were likely or very likely to maintain their habit over the next year. Weekly pre-shutdown PA (R = −0.092) and during-shutdown PA (R = −0.365) were not closely related to 1-yr prediction; however, participants who did not change (1.75 ± 0.82; P < 0.01; 95% CI, −1.02 to −0.68; g = 1.06) or increased PA (1.77 ± 0.63; P < 0.01; 95% CI, −1.02 to −0.63; g = 1.28) during the shutdown were significantly more likely to report they would maintain PA levels for 1 yr compared with those who decreased PA levels during the shutdown (2.6 ± 0.67). Based on the criteria set by Cohen (25) Hedges’ g values of 0.8 or greater indicate large effects.

There was no difference in 1-yr prediction between males (1.97 ± 0.851) and females (1.85 ± 0.792, t = 1.48; P = 0.140; 95% CI, −0.04 to 0.27; g = 0.15). Three participants identified as nonbinary or preferred not to answer. These participants were not included in gender analysis.

Overall, there was no difference in 1-yr prediction across three different areas of residence (F(2, 870) = 2.18; P = 0.114). Using pairwise comparisons, individuals in rural areas were significantly more likely to predict they would maintain their exercise habits 1 yr from now than individuals in urban areas (rural, 1.78 ± 0.82 vs urban = 1.95 ± 0.812; P = 0.04; 95% CI, −0.31 to −0.01; g = 0.21).

Discussion

The primary purpose of this study was to determine if and why exercise habits changed between pre-shutdown (early April 2020) and during (early June 2020) the COVID-19 shutdown among Indian adults. The main finding was an increased percentage of people meeting or exceeding World Health Organization (15) guidelines for PA during the shutdown period. More specifically, days of PA per week increased significantly, whereas minutes of PA per session remained the same and average session intensity decreased. Perhaps the most interesting finding is that the overall weekly dose of exercise significantly increased from pre-shutdown to during shutdown. Increases in PA during the pandemic may have substantial implications for improved health and well-being, especially a decreased risk of chronic diseases (7).

Our main finding was confirmed by similar studies in which researchers reported increased PA during the spring 2020 (19,26). In Belgium, where PA was encouraged during the shutdown, 58% of individuals who were classified as low-active before the shutdown increased PA. Thirty-six percent of individuals classified as high active before the shutdown reported increased activity during the shutdown (19). Di Renzo and colleagues (26) also reported a slight increase in activity in Italy in April 2020 during the country’s strictest shutdown period. Participants who reported exercising five or more times per week increased from 6.1% before the shutdown to 16.4% during the shutdown and indicated more time for activity (26). According to data collected by Strava, countries that limited indoor fitness facility use but allowed outdoor exercise saw large increases in outdoor activities early in the COVID-19 pause (27). Between April and September 2020, women between the ages of 18 and 29 yr reported 45.2% more activities and men reported 27.3% more activity than during the same time period in 2019. Walking was reported as the top new activity between April and June 2020 (27).

In addition to changes in behavior, the pandemic increased interest and intention to participate in PA (11). In a large data analysis of Google Trends, Ding and colleagues (11) found that community interest in PA increased as shutdowns began, peaked within the first 2 wk then declined but remained at a higher level than pre-shutdown in Australia, the United Kingdom, and the United States. Interest in PA, determined by Google Search Rates, was at an all-time high in April 2020. The researchers suggested that restrictions caused by the pandemic disrupted typical habits and allowed individuals to create new habits (11). Increases in Internet search rates do not necessarily indicate PA behavior changes but could indicate intention to participate in PA, which is an important first step toward behavior change.

In the present study, open-ended responses indicated that individuals generally had more time available for PA and increased schedule flexibility. Several participants reported more outdoor activity and an increased desire to be outside of their homes during the COVID-19 shutdown. Outdoor activity may have been easier for people in rural versus urban areas based on opportunities to be in socially distanced open spaces. Interestingly, although individuals in rural areas perceived their neighborhoods as more safe than those in urban areas, perceived neighborhood safety or type of area had no correlation with changes in PA over the surveyed time frame. Ding and colleagues (11) suggested that fewer scheduled activities, more leisure time, increased health awareness, and messaging about the importance of PA for health could all contribute to increased interest in PA.

Results from the current study showed that intensity of PA decreased significantly (−6.76%) from pre-shutdown to during the COVID-19 shutdown. A loss of access to fitness facilities, especially resistance training equipment, as well as a lack of personal accountability inherent to exercise with personal trainers and group classes were noted as reasons for decreased exercise intensity in open-ended responses. More aerobic walking outdoors were also reported as an additional reason for decreased intensity. The researchers found an increase in body weight training, which may have affected intensity of activity. They suggest this finding is likely as a result of fitness center closures (26). Kinnafick and colleagues (16) noted a lack of accountability, decreased social dynamics, and lack of encouragement as potential contributors to decreased intensity. A decrease in observed intensity may actually be a positive finding during the pandemic. Rahmati-Ahmadabad and Hosseini (28) recommended moderate intensity rather than high intensity PA as an approach to cope with COVID-19. This recommendation is based on evidence that suggests that high-intensity exercise may cause an increase in oxidant production and inflammation, thus suppressing immune health (28).

Not all previous research aligns with the results of the current study. In the United Kingdom, researchers found a 37% reduction in weekly minutes of PA within the first week of lockdown, especially in younger individuals (20). Overall, 63% of people decreased activity (20). In addition, a global group of 35 research organizations found COVID-19 shutdowns had a negative effect on PA at all levels of intensity from participants around the world. The group also found daily sitting increased from 5 to 8 h·d−1 (29). Individuals with self-reported reductions in PA noted fewer resources for PA, less available time, and missing competitive elements of PA as primary reasons for PA reduction (19).

The global fitness tracking company Fitbit examined the effect of COVID-19 by comparing step counts from users around the world during the week ending March 22, 2020, to the same week in 2019 (30). European countries experienced a 7% to 38% decline in step counts, with the largest declines in Spain, Italy, Portugal, Romania, and France. The United States experienced a 12% decline in step count, with the largest decreases in major metropolitan areas, especially San Francisco and New York, which were under full shutdowns during that week in March (30). Similar decreased step counts were also found in an analysis performed with Garmin users (31). Interestingly, indoor cardio, yoga, and high-intensity interval training–tagged activities increased in a year-to-year comparison (31). Tison and colleagues (32) analyzed data collected by the Argus app for Apple and Android smartphones. Within 10 d of the start of the pandemic, researchers found a 5.5% decrease in mean steps and a 27.3% decrease in mean steps within the first 30 d. These decreases were observed worldwide, despite large regional variability in the data due to socioeconomic disparities and variations in access to recreational physical activities (32).

In the current study, inactive individuals tended to increase activity (66.8%), whereas active individuals tended to decrease activity (46.3%) during the shutdown. These findings are contrary to Lesser and Nienhuis (21), who examined how PA participation before the shutdown affected well-being during the shutdown. They found that more individuals who were inactive tended to decrease activity further (40.5%) than increase activity (33%). Alternatively, more individuals who were active tended to increase activity (40.3%) than decrease activity (22.4%). Inactive participants with mild to moderate anxiety who increased outdoor PA during the shutdown were more likely to be classified as flourishing on the mental health continuum (21). Although the current study did not specifically ask participants to note changes in dependent care because of the pandemic, open-ended responses revealed that changes in family obligations including child care limited participation in PA. In addition, the lack of social and entertainment opportunities due to the shutdown likely changed how people spent their leisure time. Many participants in the current study reported increased outdoor activity because it was one of the few activities they could do outside of their living space while maintaining social distance. The findings from the current study have important implications for how adverse lifestyle disruptions could be leveraged for behavior modification to increase PA and improve well-being.

Associations between PA and other demographic variables were also examined in the current study. With respect to gender differences, males participated in more PA than did females before the shutdown. During the shutdown, however, females increased PA significantly more than did males to reach the pre-shutdown male PA levels. Males and females experienced similar decreases in intensity. Attunes and colleagues (24) found that males experienced higher values for total energy expenditure than did females during the pandemic. In the current study, changes in PA were not associated with income, education, area of residence, or race/ethnicity.   Although no relationships have been identified, more intense investigations into demographic variables could help identify which groups of individuals to target for PA interventions.

Observing changes in PA during the pandemic provides insight into how to affect positive long-term change with respect to PA behavior modification. It is clear that the pandemic has had an effect on individuals’ routines. What remains to be seen is whether or not change will be maintained long-term. A major issue with behavior modification is that individuals tend to easily revert back to old habits. People generally do not maintain behavior changes once the disruption is removed or when the initial intervention wears off (33); however, because the pandemic caused major life changes, it is possible that participants who indicated that they would maintain their increased PA levels for 1 yr actually will follow through.

An additional purpose of this study was to determine the likelihood of maintaining during-shutdown PA behavior change for 1 yr. Participants who increased PA were optimistic about maintaining PA habits for 1 yr (90% responded likely or very likely). Those who decreased PA were less optimistic about maintaining their new habit for 1 yr (40.9% responded likely or very likely), perhaps with the hope that they would regain their pre-shutdown PA level. In their analysis of Google search rates, Ding and colleagues (11) found increased interest in home-based exercise and high-intensity interval training, which indicates intent for home-based activities during the fitness center closures. Individuals were either considering engaging in PA or searching for new avenues to support their already existing PA habit (11). These actions correspond with the contemplation and planning phases of the Tran theoretical Model (33). The action phase, which occurred as many increased PA during shutdowns, is just as important as the maintenance and termination phases, which will determine long-term adoption of PA habits. Regular exercisers who decreased PA during the shutdown generally have high intrinsic motivation for activity, which may prove helpful for return after disruptions (16,34).

Wood and Neal (35) noted that successful behavior changes come when people capitalize on major life events to adopt different routines and habits. According to their framework, the pandemic served as a cue disrupter, the first of three main habit-breaking interventions. Shutdowns caused major life changes that reduced exposure to familiar cues, which initiate unhealthy behaviors. The second intervention, environmental engineering, either adds friction to unhealthy behaviors or reduces friction to allow for healthy behaviors. The shutdown inherently created friction when access to gyms and fitness facilities was limited and modes of public transportation were discouraged. The pandemic also inherently reduced friction when exercise classes became more available online in people’s homes, active modes of transportation such as walking increased, and more resources were available encouraging PA and providing information for staying healthy during the shutdown. The pandemic now creates an opportunity for the third of the habit-breaking interventions, vigilant monitoring. Vigilant monitoring is an opportunity for policy makers to implement behavior modification strategies to maximize the potential for individuals to limit unhealthy behaviors and maintain the healthy behaviors they adopted during the shutdown (35). Ding and colleagues (11) suggested that pervasive messaging about the importance of PA during the COVID shutdown from the media, government, and health officials helped increase interest in PA during the shutdown. Government and health officials should leverage the pandemic to implement the framework, intentionally create policy, and promote strategies that encourage individuals to continue to engage in healthy behaviors such as regular PA (7,36).

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