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Erschienen in: BMC Public Health 1/2022

Open Access 29.04.2022 | COVID-19 | Research

The impact of COVID-19 restrictions on perceived health and wellbeing of adult Australian sport and physical activity participants

verfasst von: R. Eime, J. Harvey, M. Charity, S. Elliott, M. Drummond, A. Pankowiak, H. Westerbeek

Erschienen in: BMC Public Health | Ausgabe 1/2022

Abstract

Individuals’ access to sport and physical activity has been hampered due to COVID-19 lockdown restrictions. In Australia participation in community sport was cancelled during lockdowns. There is limited research on the impact of sport participation restrictions on the health and wellbeing of adults.
Aim
The aim of this study was to investigate the perceived health and wellbeing of a sample of predominantly active Australian adults, both during COVID-19 and in comparison with one year earlier (pre COVID-19).
Methods
A survey was conducted during the first COVID-19 restrictions and lockdowns in Australia in May–June 2020. It was distributed by national and state sporting organisations and through researchers’ social media accounts. This particular paper focuses on adults aged 18–59 years. The survey collected information on participant demographics, the sport and physical activity patterns pre- COVID-19, and health and wellbeing outcomes during COVID-19 lockdown and compared to one year earlier. The health measures were cross-tabulated against the demographic and sport and physical activity variables, and group profiles compared with chi-square tests. Scales were derived from three wellbeing questions, and group differences were analysed by t-tests and F-tests.
Results
The survey sample included 1279 men and 868 women aged 18–59 years. Most (67%) resided in metropolitan cities. The great majority (83%) were sport participants. During COVID-19 lockdown men were significantly more likely than women to report worse or much worse general (p = 0.014), physical (p = 0.015) and mental health (p = 0.038) and lower life satisfaction (p = 0.016). The inactive adults were significantly more likely to report poorer general health (p = 0.001) and physical health (p = 0.001) compared to active adults. The younger age cohort (18–29 years) were significantly more likely to report poorer general wellbeing (p < 0.001), and lower life satisfaction (p < 0.001) compared to the older age groups.
Conclusion
It seems that the absence of playing competitive sport and training with friends, teams and within clubs has severely impacted males and younger adults in particular. Sports clubs provide an important setting for individuals’ health and wellbeing which is why clubs require the capacity to deliver sport and individuals may need to regain the motivation to return.
Hinweise

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Abkürzungen
COVID-19
Coronavirus Disease of 2019

Introduction

Australia had its first reported COVID-19 case in January 2020, and on March 11th the World Health Organisation declared COVID-19 a pandemic, and following this, all Australian borders were closed on March 25th [1]. From March to October 2020 there was widespread cancellation of elite and community sport in Australia. In May 2020 ‘return to sport guidelines’ were developed by National and State Governments, and by mid-October 2020 restrictions were significantly eased in the Australian state most impacted thus far, Victoria [1]. In October 2021, participation in competitive sport was still not allowed with a full return to competitive sport once vaccination rates have increased [2]. In Australia, the state of Victoria has been more impacted by restrictions and lockdowns than any other state, in terms of both length and intensity of restrictions, and the state capital Melbourne has become the world’s most locked-down city [3].
Restrictions on physical movement and limitations on social connections have been shown to significantly affect physical and mental wellbeing [46]. A systematic review investigated the impact of COVID-19 on mental health in the general population across 8 countries and reported relatively high rates of anxiety, depression, post-traumatic stress disorder, psychological distress [4]. Other studies have reported that social distancing, self-isolation, and lockdown are among the major contributing factors towards high feelings of sadness, fear, frustration, feelings of helplessness, loneliness, and nervousness [5]. A multi country study of over 1,000 study participants reported that COVID-19 home confinement had a negative effect on both mental health as well as on mood and feelings compared to pre-COVID-19 restrictions [6].
The impacts can also be exacerbated in many cases due to limits on participation in sport and other leisure activities [710], which can also be dependent on the type of sport or physical activity that people were involved in pre-COVID-19 as well as during-COVID-19. The restrictions across the globe included limits on time spent outdoors and resulted in reductions in leisure-time sport and physical activity [8]. However, while sport was cancelled, the government in Australia encouraged people to be active, and being active was one of a very few reasons people could leave their homes [2]. The World Health Organisation provided recommendations on how individuals could still meet the recommended physical activity guidelines of 150 min/wk of moderate to vigorous physical activity (MVPA) or 75 min/wk of vigorous physical activity (VPA) for adults, even at home with no special exercise equipment and with limited space [11].
Globally, individuals are more likely to be active in non-sporting activities like walking, running, cycling and swimming rather than participation in sport [12]. Further, children and youth are far more likely to participate in sport than adults and older adults [1214]. Internationally popular sports for adults include soccer, basketball, golf and tennis [12]. For adults, in Australia popular sport activities include swimming, soccer, tennis, basketball, golf and netball [15, 16].
In terms of restrictions on activity, when easing the restrictions out of total lockdown, some constraints with regard to participation in sport were lifted for children and youth but not for adults [17]. For example, in Regional Victoria children could return to playing sport outdoors, including team-based competitive contact sport, but adults could only train. Indoor sports and physical activities remained prohibited at this time, so that sports such as football and tennis resumed for children and youth, but not basketball or other gym-based activities [17]. COVID-19 restrictions will continue to impact children and youth differently compared to adults and older adults.
The impact on physical, social and mental health, as well as the economic impact, of COVID-19 varies across individuals and families, according to demographic factors such as gender, age and residential region (metropolitan versus regional and rural) [5, 18, 19].
Regarding gender, there is evidence that women may suffer greater psychological strain and stress and anxiety and depression compared to men. This can be attributed to a lockdown situation where all family members are at home and where women, more than men, had to juggle home duties with work commitments, which can be mentally and physically demanding [5]. This is consistent with another study reporting that women had higher rates of mental health problems than men [18]. This can relate to physical activity and work status. For example, sport participants are much more likely to be male than female, and this is consistent internationally [14, 20, 21]. However, in terms of impact of COVID-19 on gender, an international study investigated COVID-19 impacts on gender gaps in economic outcomes, and reported that women were more likely to permanently lose their job than men [22]. This study was conducted across 6 countries including China, South Korea, Japan, Italy, the United Kingdom and four of the largest states in the United States [22]. Further, there are also reports that the closure of schools across many nations might have a differential impact on women as they provide most of the informal care within families and as a consequence may have to limit their work [23]. Further, women are less likely to have decision making power in context of pandemic related matters and therefore their opinions and needs are less considered [23].
There are also age-related trends in the impact of COVID-19 on mental health with an Austrian study of adults reporting that mental health problems were higher in adults aged under 35 years, as well as among people who were out of work or on low incomes [18]. The requirement to socially distance during lockdown and other restrictions on the number of people congregating outside the home or the ability to visit people in their home has placed insurmountable pressure on social relationships and therefore social health and wellbeing. This in turn also affects mental health. For example, economic hardship can impact the quality and stability of couples’ relationships [24]. Further, in a UK study among younger adults, those separated or divorced were more likely to suffer poorer mental health [25].
In Australia participation in community sport is much more popular in regional and rural areas compared to metropolitan [14]. More specifically, the metropolitan growth areas have lower than average participation compared to longer established suburbs [26]. This can be explained by many factors including the (important) social nature of community sport in regional and rural areas, the availability of traditional club-based community sport versus other leisure-time activities and socio-economic status, as well as population density [26, 27].
In terms of impact of COVID-19 by region, to date there have been considerable differences across states and also within states. Regional and rural areas had lower numbers of COVID-19 cases and were less impacted by social restrictions and lockdowns than metropolitan areas, and most specifically Melbourne in Victoria [28]. Therefore, the ability of people to be active and return to activities including sport and indoor leisure varied considerably across regions and across timepoints [2]. There was also a significant seasonal impact in Australia in 2020 with summer sports like cricket and tennis largely unaffected. However, most winter sports like Australian football, soccer and netball, which generally run April-August had to cancel their competitions for almost the whole season.
Internationally, there were different impacts of COVID-19 between regions, which can be attributed to population density but also demographic factors such as age. In Australia, pre-COVID-19 there were already differences in health status according to residential location. For example, a lack of health care services in regional and rural areas, poor internet leading to limited telehealth, and a lack of social capital and availability of social services makes rural communities particularly vulnerable compared to metropolitan cities [19]. However, metropolitan populations were at risk due to community spread from higher population density [19].
There is limited research on adults in regard to their community level sport involvement. Most research has targeted the young and the elite sport participants, the majority of which tend to focus on general physical activity and not specifically on sport. In this paper we seek to determine the association between perceived health and wellbeing of adults and the impact of COVID-19 related restrictions on different types and settings of participation in sport and physical activity, together with different genders, age groups and regions.

Methods

This study is part of a broader program of research in Australia, which involves the longitudinal measurement of sport and physical activity participation and the physical, mental and social health and wellbeing outcomes of this participation. This study was conducted via two waves of online surveying (Qualtrics) during the COVID-19 period (2020 and 2021), the first of which also included participation and health data that related to the pre-COVID-19 baseline in 2019. Ethics approval was obtained by Flinders University (project number 8654) and Victoria University (project number HRE20-049) human research ethics committees.
The present study is based on data collected in the first wave using an online survey of sport participants conducted during May and June 2020. Recruitment to the survey was primarily facilitated by sports including Australian football, bowls, cricket, golf, tennis and football. The present study is one of three age-based studies, each focusing on a different stage of the lifespan. The other studies are focused on adolescence (13–17 years) and older adulthood (60 + years). The present study is focused on early and middle adulthood. The target population for this paper was adults aged 18–59 years at the time of the survey who were registered in the 2019 and/or 2020 playing seasons to participate in one or more sports. Separate analysis and papers are being developed for youth and older adults. The sports organisations that sent out the invitation to the survey to their registered participants represent major sports in Victoria and Australia [16, 29]. The research team has extensive research experience in working with these sports at national, state and local levels [10, 3035].
In order to broaden the scope of the survey sample to include people who participate in recreational physical activity only in settings other than sports clubs, and potentially also people who do not participate in any recreational physical activity, the primary recruitment strategy was supplemented by the use of snowball sampling, through social media pages of sports organisations and research-oriented social media pages (e.g. research team social media pages, university social media pages and websites).
The first wave, or baseline, of the longitudinal survey included, among others, questions about:
  • Demographic characteristics – gender, date of birth, and residential postcode
  • Types of sports and other recreational physical activities participated in
  • Settings in which the participation occurred – sports clubs and other less structured informal settings
  • Modes of participation – team and individual modes of activity
  • Self-assessed general health, physical health and mental health.
  • Measures of wellbeing – general wellbeing, resilience and life satisfaction.
Date of birth was used to determine age in years at the time the survey was completed. Age was then recoded into three age cohorts (18–29 years, 30–49 years, and 50–59 years), broadly aligning with ‘young and free’, ‘homebuilding and child rearing’, and ‘empty nesting’. Residential postcode concordances [36] were used to assign each postcode to one of two broad geographical zones or regions: Metropolitan, comprising the capital cities of the Australian states; and Non-metropolitan, comprising regional cities, towns and rural areas.
Regarding sport and physical activity, two separate sections of the survey dealt respectively with two ‘sport and physical activity settings’: organised club sport involving membership and registration (designated ‘club’), and less structured sport and recreational physical activity (designated ‘informal’). In each section, a list of the most common activities was presented – 16 for club sports and 26 for informal (which also included 12 of the 16 club sports). Respondents indicated the activities in which they participated, with provision for adding other activities that were not listed. Based on these responses, a combined list of 88 activities was established. Further, each of the 88 activities was classified as either ‘team’ or ‘individual’, which we refer to as ‘sport and physical activity modes’. Each respondent was then assigned a single overall category for each of settings (club only, club and informal, informal only, and inactive) and modes (team only, team and individual, individual only, inactive).
Six survey items were devoted to self-assessed health – three pertaining to the time of the survey (during COVID-19 lockdown) and three comparing current health to health 12 months prior to the survey (before COVID-19). The general health item was a 5-point Likert scale item (poor, fair, good, very good, excellent) derived from the Short-form Health Survey (SF-36) instrument [37]. The same format was used for the assessment of physical health and mental health. The three comparative items used a 5-point Likert scale (much worse, somewhat worse, about the same, somewhat better, much better).
General wellbeing was assessed using a scale derived by averaging the responses to a battery of 14 items regarding frequency of positive and negative feelings, derived from [38]. Each item was scored on a 5-point scale (all of the time, most, some, a little, none), with reverse coding of the negative items, so that higher average scores represented greater wellbeing.
Resilience was similarly assessed using a scale derived by averaging the responses to a battery of 4 items derived from [39]. Each item consisted of a statement about the respondent, with responses on a 5-point scale (strongly agree, agree, neutral or unsure, disagree, strongly disagree).
Life satisfaction was assessed using a direct question {Women's Health Australia, 2008 #2448} with the response on a 10-point scale from 1 (least satisfied) to 10 (most satisfied).

Statistical analysis

Data analysis was conducted using SPSS Version 25. For the purpose of tabulation and statistical analysis of responses, each of the six 5-category health items were recoded into three categories (poor/fair, good, very good/excellent; and much/somewhat worse, about the same and somewhat/much better). Similarly, the variable ‘settings of sport and physical activity’ was recoded from four categories (club only, club and informal, informal only, inactive) to three (club including club and informal, informal only, inactive) and the variable ‘modes of sport and physical activity’ was recoded from four categories (team only, team and individual, individual only, inactive) to three (team including team and individual, individual only, inactive).
The six recoded health items were each cross-tabulated against five respondent characteristics: gender, age cohort, region, settings of sport and physical activity, and modes of sport and physical activity. Chi-square tests of independence were conducted to identify differences in the health profiles of the groups defined by each of the characteristics.
For the measures of general wellbeing, resilience and life satisfaction, mean values for the groups defined by each of the five characteristics were tabulated, and group differences were analysed using independent samples t-tests (for two groups) and F-tests (for three groups).

Results

The survey was completed by 2,146 adults aged 18–59 years. Table 1 shows profiles of gender, age groups and region of residence, for the survey sample and for the corresponding age cohort of the Australian population. Men were over-represented and women under-represented in the survey, which is consistent with the known higher rate of sports participation by men, and the fact that the distribution of survey invitations was facilitated predominantly by the organisations of male-dominated sports. The younger and middle-aged adults (18–49 years), were also under-represented, which is consistent with the known drop in sports participation during adolescence, with lower participation continuing through the years of higher education, the pursuit of careers and the establishment and raising of families. Participation rates rose again during the “empty nest” ages of 50–59 years. The two types of region were close to proportionately represented in the survey sample, with a slight over-representation of non-metropolitan areas which may reflect the more central role of traditional forms of sport in these areas.
Table 1
Demographic profiles of survey sample, compared to Australian population aged 18–59 years
 
Survey Sample
Australian Populationa
%
%
Gender
  Male
59.6
49.7
  Female
40.4
50.3
Age (years)
  18–29
25.0
29.3
  30–49
44.9
49.0
  50–59
30.1
21.7
Region
  Metropolitan
67.0
70.5
  Non-metropolitan
33.0
29.5
aSource: Australian Bureau of Statistics. Regional population by age and sex, 2020 [40]
Consistently with the methods of recruitment, the great majority of survey repondents were participants in club sport (n = 1779, 83%). Fewer played only informally (n = 356, 17%), and very few were inactive (n = 20, < 1%). The majority played team sport (n = 1455, 68%), and fewer participated in only individual activities (n = 680, 32%).

Reported health status during COVID-19 restrictions/lockdowns

There were significant gender differences in reported general health (p < 0.001), physical health (p = 0.006) and mental health (p = 0.23) during COVID-19 restrictions/lockdowns. Men were more likely than women to report poor/fair general health (22%, 16%), poor/fair physical health (26%, 21%) and poor/fair mental health (34%, 28%), whereas women were more likely than men to report very good or excellent general health (51%, 42%), physical health (43%, 37%) and mental health (35%, 33%) (Table 2).
Table 2
Self-assessment of current health: by respondent characteristics
Health assessments
Characteristics
p-valuea
 
Genderb
 
 
Male
Female
  
 
N
%
N
%
   
General health
      
 < .001
  Poor or fair
279
21.8
142
16.4
   
  Good
463
36.2
283
32.6
   
  Very good or excellent
536
41.9
443
51.0
   
Total
1278
100.0
868
100.0
   
Physical health
      
.006
  Poor or fair
332
26.0
182
21.0
   
  Good
477
37.3
314
36.3
   
  Very good or excellent
469
36.7
369
42.7
   
Total
1278
100.0
865
100.0
   
Mental health
      
.023
  Poor or fair
429
33.6
243
28.0
   
  Good
431
33.8
319
36.8
   
  Very good or excellent
415
32.5
305
35.2
   
Total
1275
100.0
867
100.0
   
 
Age (years)
 
 
18–29
30–49
50–59
 
 
N
%
N
%
N
%
 
General health
  Poor or fair
123
22.8
201
20.8
100
15.5
.017
  Good
183
34.0
335
34.6
228
35.2
 
  Very good or excellent
233
43.2
432
44.6
319
49.3
 
Total
539
100.0
968
100.0
647
100.0
 
Physical health
  Poor or fair
131
24.4
250
25.8
136
21.1
.115
  Good
184
34.3
361
37.3
246
38.1
 
  Very good or excellent
222
41.3
357
36.9
264
40.9
 
Total
537
100.0
968
100.0
646
100.0
 
Mental health
  Poor or fair
214
39.7
304
31.5
157
24.3
 < .001
  Good
177
32.8
355
36.8
220
34.1
 
  Very good or excellent
148
27.5
306
31.7
269
41.6
 
Total
539
100.0
965
100.0
646
100.0
 
 
Region
 
 
Metropolitan
Non-metropolitan
  
 
N
%
N
%
   
General health
      
.432
  Poor or fair
291
20.3
129
18.3
   
  Good
486
33.8
255
36.1
   
  Very good or excellent
660
45.9
322
45.6
   
Total
1437
100.0
706
100.0
   
Physical health
  Poor or fair
346
24.1
166
23.6
  
.066
  Good
505
35.2
282
40.1
   
  Very good or excellent
585
40.7
256
36.4
   
Total
1436
100.0
704
100.0
   
Mental health
  Poor or fair
465
32.4
207
29.5
  
.090
  Good
480
33.4
268
38.2
   
  Very good or excellent
492
34.2
227
32.3
   
Total
1437
100.0
702
100.0
   
 
Sport and physical activity settings
 
 
Clubc
Informal onlyd
Inactive
 
 
N
%
N
%
N
%
 
General health
      
.143
  Poor or fair
356
19.9
61
17.7
7
35.0
 
  Good
616
34.4
121
35.1
9
45.0
 
  Very good or excellent
817
45.7
163
47.2
4
20.0
 
Total
1789
100.0
345
100.0
20
100.0
 
Physical health
      
.023
  Poor or fair
430
24.1
77
22.3
10
50.0
 
  Good
660
37.0
123
35.7
8
40.0
 
  Very good or excellent
696
39.0
145
42.0
2
10.0
 
Total
1786
100.0
345
100.0
20
100.0
 
Mental health
  Poor or fair
571
32.0
96
27.9
8
40.0
.286
  Good
615
34.4
133
38.7
4
20.0
 
  Very good or excellent
600
33.6
115
33.4
8
40.0
 
Total
1786
100.0
344
100.0
20
100.0
 
 
Sport and physical activity modes
 
 
Teame
Individual onlyf
Inactive
 
 
N
%
N
%
N
%
 
General health
      
.096
  Poor or fair
291
20.0
126
18.5
7
35.0
 
  Good
510
35.1
227
33.4
9
45.0
 
  Very good or excellent
653
44.9
327
48.1
4
20.0
 
Total
1454
100.0
680
100.0
20
100.0
 
Physical health
  Poor or fair
344
23.7
163
24.0
10
50.0
.034
  Good
539
37.1
244
35.9
8
40.0
 
  Very good or excellent
568
39.1
273
40.1
2
10.0
 
Total
1451
100.0
680
100.0
20
100.0
 
Mental health
  Poor or fair
452
31.2
215
31.7
8
40.0
.646
  Good
505
34.8
243
35.8
4
20.0
 
  Very good or excellent
494
34.0
221
32.5
8
40.0
 
Total
1451
100.0
679
100.0
20
100.0
 
aChi-square test of independence
bSeven respondents who reported their gender as’Other’ were excluded from the gender breakdowns because the small sample size provided inadequate statistical power to enable reliable conclusions to be drawn about this population
cThose who participated in club sports, including those who also participated in informal sport or other recreational physical activities
dThose who participated in informal sport or other recreational physical activities, but not in club sports
eThose who participated in team sports or activities, including those who also participated in individual sports or activities
fThose who participated in individual sports or physical activities, but not in team sports or activities
When broken down by age categories there were significant differences for general health (p = 0.017) and mental health (p < 0.001). In both cases, the younger cohort (18–29 years) were more likely to report poor/fair general health (23%) and poor/fair mental health (40%) compared to older adults, with those aged 50–59 years being more likely to report very good/excellent general health (50%) and very good/excellent mental health (42%) (Table 2).
There were no significant regional differences in the three health measures (Table 2).
With regard to the level physical activity, inactive adults were significantly more likely to report poor/fair physical health compared to active adults in either informal activities or club-based sport (p = 0.02). Further, inactive adults were significantly more likely to report poor/fair physical health compared to those active within team or individual activities (p = 0.034).

Reported changes in health status: before and during COVID-19 restrictions/lockdowns

Table 3 summarises the results of self-assessed health during COVID-19 lockdown compared to a year before (and pre-COVID-19). Men were more likely than women to report worse/much worse general health (33%, 30%; p = 0.014), worse/much worse physical health (38%, 33%; p = 0.15) and worse/much worse mental health (42%, 37%; p = 0.038).
Table 3
Self-assessment of current health compared to one year ago: by respondent characteristics
Health assessments
Characteristics
p-value1
 
Gender2
 
 
Male
Female
  
 
N
%
N
%
   
General health
  Worse or much worse
425
33.2
242
27.9
  
.014
  About the same
582
45.5
407
46.9
   
  Better or much better
272
21.3
219
25.2
   
Total
1279
100.0
868
100.0
   
Physical health
  Worse or much worse
478
37.5
285
32.9
  
.015
  About the same
517
40.5
348
40.1
   
  Better or much better
281
22.0
234
27.0
   
Total
1276
100.0
867
100.0
   
Mental health
  Worse or much worse
532
41.6
320
36.9
  
.038
  About the same
532
41.6
372
42.9
   
  Better or much better
215
16.8
176
20.3
   
Total
1279
100.0
868
100.0
   
 
Age (years)
 
 
18–29
30–49
50–59
 
 
N
%
N
%
N
%
 
General health
  Worse or much worse
205
38.0
313
32.3
153
23.6
 < .001
  About the same
191
35.4
437
45.1
362
56.0
 
  Better or much better
143
26.5
219
22.6
132
20.4
 
Total
539
100.0
969
100.0
647
100.0
 
Physical health
  Worse or much worse
219
40.7
365
37.7
183
28.3
 < .001
  About the same
163
30.3
377
39.0
326
50.5
 
  Better or much better
156
29.0
225
23.3
137
21.2
 
Total
538
100.0
967
100.0
646
100.0
 
Mental health
  Worse or much worse
236
43.8
399
41.2
220
34.0
 < .001
  About the same
173
32.1
395
40.8
339
52.4
 
  Better or much better
130
24.1
175
18.1
88
13.6
 
Total
539
100.0
969
100.0
647
100.0
 
 
Region
 
 
Metropolitan
Non-metropolitan
  
 
N
%
N
%
   
General health
  Worse or much worse
451
31.4
216
30.6
  
.315
  About the same
647
45.0
340
48.2
   
  Better or much better
340
23.6
150
21.2
   
Total
1438
100.0
706
100.0
   
Physical health
  Worse or much worse
519
36.2
244
34.6
  
.312
  About the same
562
39.2
300
42.6
   
  Better or much better
354
24.7
161
22.8
   
Total
1435
100.0
705
100.0
   
       
.057
Mental health
  Worse or much worse
590
41.0
262
37.1
   
  About the same
580
40.3
323
45.8
   
  Better or much better
268
18.6
121
17.1
   
Total
1438
100.0
706
100.0
   
 
Sport and physical activity settings
 
 
Club3
Informal only4
Inactive
 
 
N
%
N
%
N
%
 
General health
      
.001
  Worse or much worse
583
32.6
79
22.9
9
45.0
 
  About the same
818
45.7
165
47.8
7
35.0
 
  Better or much better
389
21.7
101
29.3
4
20.0
 
Total
1790
100.0
345
100.0
20
100.0
 
Physical health
      
.002
  Worse or much worse
665
37.2
92
26.7
10
50.0
 
  About the same
710
39.8
150
43.5
6
30.0
 
  Better or much better
411
23.0
103
29.9
4
20.0
 
Total
1786
100.0
345
100.0
20
100.0
 
Mental health
      
 < .001
  Worse or much worse
742
41.5
107
31.0
6
30.0
 
  About the same
746
41.7
154
44.6
7
35.0
 
  Better or much better
302
16.9
84
24.3
7
35.0
 
Total
1790
100.0
345
100.0
20
100.0
 
 
Sport and physical activity modes
 
 
Team5
Individual only6
Inactive
 
 
N
%
N
%
N
%
 
General health
  Worse or much worse
465
32.0
197
29.0
9
45.0
.423
  About the same
658
45.2
325
47.8
7
35.0
 
  Better or much better
332
22.8
158
23.2
4
20.0
 
Total
1455
100.0
680
100.0
20
100.0
 
Physical health
  Worse or much worse
529
36.4
228
33.6
10
50.0
.335
  About the same
569
39.2
291
42.9
6
30.0
 
  Better or much better
354
24.4
160
23.6
4
20.0
 
Total
1452
100.0
679
100.0
20
100.0
 
Mental health
  Worse or much worse
576
39.6
273
40.1
6
30.0
.237
  About the same
625
43.0
275
40.4
7
35.0
 
  Better or much better
254
17.5
132
19.4
7
35.0
 
Total
1455
100.0
680
100.0
20
100.0
 
1Chi-square test of independence
2Seven respondents who reported their gender as’Other’ were excluded from the gender breakdowns because the small sample size provided inadequate statistical power to enable reliable conclusions to be drawn about this population
3Those who participated in club sports, including those who also participated in informal sport or other recreational physical activities
4Those who participated in informal sport or other recreational physical activities, but not in club sports
5Those who participated in team sports or activities, including those who also participated in individual sports or activities
6Those who participated in individual sports or physical activities, but not in team sports or activities
When broken down by age, the youngest cohort, aged 18–29 years, were significantly more likely to report worse/much worse general health (38%; p < 0.001), worse/much physical health (41%; p < 0.001) and worse/much mental health (44%; p < 0.001) compared to the older cohorts (Table 3).
There were no significant differences in the reported change in health status for those living in metropolitan cities compared to non-metropolitan regions.
The inactive adults were significantly more likely to report worse/much worse general health (p = 0.001) and worse/much worse physical health (p = 0.001) compared to those active through club or other informal activities. However, the adults who were active through clubs and other informal activities were significantly more likely to report worse/much worse mental health (p < 0.001) compared to the inactive adults (Table 3).

Measures of wellbeing

The results of general wellbeing, resilience and life satisfaction are presented in Table 4. Men reported significantly lower life satisfaction (mean 6.63; p = 0.16) than women (mean 6.82). The younger age cohort (18–29 years) reported significantly poorer general wellbeing (p < 0.001), and lower life satisfaction (p < 0.001) than the older age groups. There were no significant differences by region, activity setting or activity mode.
Table 4
Measures of wellbeinga: by four respondent characteristics
Measure
Characteristics
p-valueb
N
Mean
SD
N
Mean
SD
N
Mean
SD
 
Genderc
 
 
Male
Female
  
General wellbeing
1219
3.43
0.66
829
3.45
0.66
   
.601
Resilience
1204
3.69
0.67
823
3.68
0.70
   
.610
Life satisfaction
1212
6.63
1.80
830
6.82
1.66
   
.016
 
Age (years)
 
 
18–29
30–49
50–59
 
General wellbeing
511
3.28
0.69
929
3.42
0.65
615
3.58
0.64
 < .001
Resilience
498
3.62
0.72
917
3.70
0.67
618
3.72
0.67
.063
Life satisfaction
501
6.44
1.78
925
6.72
1.70
623
6.91
1.78
 < .001
 
Region
 
 
Metropolitan
Non-metropolitan
  
General wellbeing
1364
3.43
0.67
681
3.44
0.66
   
.664
Resilience
1353
3.71
0.68
670
3.64
0.69
   
.034
Life satisfaction
1364
6.69
1.76
675
6.75
1.74
   
.775
 
Sport and physical activity settings
 
 
Clubd
Informal onlye
Inactive
 
General wellbeing
1700
3.44
0.67
336
3.44
0.62
19
3.20
0.96
.300
Resilience
1684
3.69
0.69
332
3.67
0.67
17
3.56
0.58
.646
Life satisfaction
1698
6.69
1.78
334
6.83
1.57
17
6.47
2.53
.334
 
Sport and physical activity modes
 
 
Teamf
Individual onlyg
Inactive
 
General wellbeing
1381
3.43
0.65
655
3.44
0.68
19
3.20
0.96
.294
Resilience
1360
3.69
0.69
656
3.68
0.69
17
3.56
0.58
.675
Life satisfaction
1373
6.70
1.74
659
6.72
1.77
17
6.47
2.53
.837
aGeneral wellbeing: 14 items, scale 1–5. Resilience: 4 items, scale 1–5. Life satisfaction: 1 item, scale 1–10
bTwo groups: independent samples t-test; three groups: F-test
cSeven respondents who reported their gender as’Other’ were excluded from the gender breakdowns because the small sample size provided inadequate statistical power to enable reliable conclusions to be drawn about this population
dThose who participated in club sports, including those who also participated in informal sport or other recreational physical activities
eThose who participated in informal sport or other recreational physical activities, but not in club sports
fThose who participated in team sports or activities, including those who also participated in individual sports or activities
gThose who participated in individual sports or physical activities, but not in team sports or activities

Discussion

This study reports on the perceived health of Australian adults during the first period of COVID-19 restrictions and lockdowns in 2020, and compared those health status measures to pre-COVID status. The study sample was predominantly physically active, and most were active through team-based sports. This bias was due to the nature of the survey distribution through State Sporting Associations which had a higher uptake than the general social media post invitations.
Globally, individuals were impacted by COVID-19 restrictions, including limits on their ability to leave the home and on the amount and types of physical activity and sport that they could undertake. These restrictions differed in different regions and at different times, with restrictions often changing rapidly. However, in Australia at least, governments realised the importance of people being physically active and this remained one of very few legitimate reasons for people to leave their homes [2]. There were public awareness campaigns, including media campaigns, which were similar to previous public health measures. Further, there was widespread availability of many online activities (such as yoga and Pilates). However, the COVID-19 enforced home confinement was unprecedented, and in a first, public health advice included recommendations for maintaining and increasing physical activity while confined at home [6].
Important findings were that the men reported significantly poorer health outcomes (general, physical, and mental) and life satisfaction than the women. Further, the men reported that their health (general, physical and mental) was significantly worse during COVID-19 lockdowns compared to a year previously, than was the case for women. These findings were surprising, especially given that there is consistent evidence that women across many different countries reported poorer health during COVID-19 [22, 23, 4143]. This international finding can be due to women being more likely to lose jobs than men due to COVID-19 [22] and more likely to be impacted by school closures and more likely to assist with remote learning of children compared to men [23]. In other multi-national studies including adults from the UK, the US, Canada and Australia, women have been impacted greater through caregiving responsibilities and have reported higher distress and anxiety than men [42]. This is consistent with another UK study which reported that women were at risk of worse mental health during COVID-19 compared to men, and that men had a relatively stable trajectory of mental health across the pandemic compared to women [43]. It is not known why the men in this Australian study reported poorer health and that their health was more heavily impacted negatively during COVID-19 than women. The sample in this study consisted of almost exclusively physically active adults, as opposed to other international health studies, where samples were a more general cross section of the population. Why men seemed to be more negatively impacted than women may relate to this fact that the sample consisted of mostly active men, and that their actual levels of physical activity during COVID-19 were more severely affected or interrupted than activity levels of men in studies that included more inactive respondents. A study of twins reported that a perceived decrease in physical activity or exercise was associated with higher stress and anxiety [44], and it is possible that in our predominantly active sporting sample the men were more likely to have higher physical activity levels pre-COVID and be less active during-COVID than the women. This is also in line with a study reporting that individuals who were in a sports club were likely to exercise less during lockdown [45]. The authors stated that the interests and goals of people who exercise in a sports club compared to those in non-organised forms of physical activity differ [45], and perhaps sports club participants were less likely to be active during lockdown.
Younger (active) adults were significantly more likely than the older adults to report poorer health outcomes and worse health during COVID-19 lockdown compared to a year ago. This is consistent with other studies showing that younger adults’ mental health is more impacted than older adults [41, 46, 47]. A UK study measured mental health during COVID-19 lockdown and found that young adults (18–29 years) were more likely to report worse mental health outcomes [47]. Similarly, an Italian study of adults reported that younger age was associated with increased depression, anxiety and high perceived stress [41]. The authors report that these health outcomes were associated with discontinued work [41]. Further, another UK study reported that psychological distress during lockdown was worse for young adults [46]. However, these studies did not go into any further detail as to why this was the case.
There were no significant differences in the health outcomes for those living in regional areas compared to metropolitan cities. In Victoria, Australia where most of the study participants resided, the COVID-19 lockdown restrictions were harsher and longer in metropolitan Melbourne which may have impacted more heavily on individuals’ health. It could therefore be anticipated that rural residents may have reported better health outcomes than their metropolitan counterparts. However, in Australia the pre-COVID health of non-metropolitan individuals was generally poorer than metropolitan individuals, which can be related to large disparities in access to health care and health services, and to geographical isolation [48], and this may have contributed to the results reported in this study. In an American study of working adults aged 18–64 years, those rural residents reported worse health outcomes related to COVID-19 experiences such as physical and mental health than metropolitan residents [49].
When the physical activity type was broken down by setting (club and informal) and mode (team or individual) there were limited differences in health outcomes. Inactive adults were more likely than active adults to report worse general and physical health compared to a year earlier. However, club sport participants were more likely to report a decline in mental health than those active only in informal settings or those who were inactive. On the one hand, compared to inactive adults, those who were active seemed to have a ‘health buffer’ during the COVID-19 restrictions and lockdowns. On the other hand, the mental health of club sport participants was perhaps more specifically impacted by the loss of the psycho-social benefits of club sport [5052].

Limitations

This study is based on data from a convenience sample, predominantly of Australian sports participants recruited with the assistance of NSOs and SSOs of four sports, in May and June 2020. The primary sample was supplemented by recruitment through social media, which resulted in an additional smaller sample of participants in only informal sport or other physical activity settings, and an even smaller sample of physically inactive people. Consequently, the sample is subject to both known and unknown sources of bias, and caution must be exercised in generalising the results. Even within the primary club sport sample, the geographical coverage was uneven, depending on the strength of the relationships between the research team and the SSOs in the various states, and the capacities and priorities of different SSOs in the context of the unfolding COVID-19 situation. Nevertheless, on the other side of the ledger, the sample obtained was extremely large, and because respondents provided information about the multiple sports and other physical activities that they engaged in, there was comprehensive representation of the sporting codes and other types of recreational physical activity that are available in Australia.

Conclusion

In conclusion, this study of mainly active sporting adults indicates that health and wellbeing of men was significantly more impacted than that of women through the absence of participation in sport due to COVID-19 lockdown restrictions. Further, the younger active sporting adults were more likely to report poorer health outcomes during lockdown than the older adults. Participation in team and club-based sport can play an important role not only for physical health but also for social and psychological health and wellbeing [50]. It seems that the absence of playing competitive sport and training with friends, teams and within clubs has severely impacted men and younger adults in particular. Sports clubs provide an important setting for individuals’ health and wellbeing and sport organisations need to focus on ensuring that clubs have the capacity to rebound and that individuals, both volunteers and participants, are given support and encouragement to return. Clubs may need to also consider how they pay particular attention to re-engaging at-risk men who have experienced worse mental health.

Acknowledgements

We would like to thank the sporting organisations that assisted with the distribution of the survey, and to also thank all survey participants.

Declarations

Flinders University and Victoria University human research ethics committees approved this study. Informed consent was obtained from participants. All experiment protocol for involving humans was in accordance to guidelines of national, international and institutional standards.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Metadaten
Titel
The impact of COVID-19 restrictions on perceived health and wellbeing of adult Australian sport and physical activity participants
verfasst von
R. Eime
J. Harvey
M. Charity
S. Elliott
M. Drummond
A. Pankowiak
H. Westerbeek
Publikationsdatum
29.04.2022
Verlag
BioMed Central
Schlagwort
COVID-19
Erschienen in
BMC Public Health / Ausgabe 1/2022
Elektronische ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-022-13195-9

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