key: cord-0953379-bv6fgltr
authors: Semple, Torran; Fountas, Grigorios; Fonzone, Achille
title: Trips for outdoor exercise at different stages of the COVID-19 pandemic in Scotland
date: 2021-10-15
journal: J Transp Health
DOI: 10.1016/j.jth.2021.101280
sha: 8d747c1b6292a492041e206da1f4393f3d74d209
doc_id: 953379
cord_uid: bv6fgltr

INTRODUCTION: The COVID-19 pandemic has had exceptional effects on travel behaviour in the UK. This paper focuses specifically on the outdoor exercise trips of Scottish residents at several distinct points of the COVID-19 pandemic. Given the negative health consequences of limited exercise, this study aims to determine the sociodemographic and behavioural factors affecting frequency of outdoor exercise trips. METHODS: Using recent public survey data (n=6000), random parameters ordered probit models (with allowances for heterogeneity in the means of random parameters) are estimated for three points during the pandemic: the most stringent lockdown, modest restriction easing and further easing of restrictions. RESULTS: The survey data show frequent outdoor exercise in the early stages of the pandemic, with ∼46% making six or more weekly trips during lockdown, reducing to ∼39% during the first phase of restriction easing, and further to ∼34% during the following phase of easing. The model estimations show that common factors, dominated by socioeconomic and demographic variables, influenced the frequency of outdoor exercise trips across most survey groups. The modelling framework also allowed insights into the impact of unobserved characteristics within several independent variables; for example, the lockdown exercise trip rates of those with a health problem or disability, and those over 65, were both found to be dependent on personal vehicle access. CONCLUSIONS: The findings suggest that those with a health problem or disability, those who live in households’ where the main income earner is employed in a semi-skilled/unskilled manual occupation or is unemployed and ethnic minority groups (i.e., any mixed, Asian, or Black background) were significantly more likely to complete no weekly outdoor exercise trips throughout the pandemic. As a result, we suggest that these groups are at higher risk of the negative health consequences associated with limited physical activity. Policy implications are discussed in terms of mitigating this effect, as well as reducing transport inequity related to vehicle accessibility.

The COVID-19 pandemic has had exceptional effects on travel behaviour in the UK. This 4 paper focuses specifically on the outdoor exercise trips of Scottish residents at several distinct 5 points of the COVID-19 pandemic. Given the negative health consequences of limited exercise, 6 this study aims to determine the sociodemographic and behavioural factors affecting frequency 7 of outdoor exercise trips. 8 9

Methods 10 Using recent public survey data (n=6000), random parameters ordered probit models (with 11 allowances for heterogeneity in the means of random parameters) are estimated for three points 12 during the pandemic: the most stringent lockdown, modest restriction easing and further easing 13 of restrictions. 14 15

Results 16

The survey data show frequent outdoor exercise in the early stages of the pandemic, with ~46% 17 making six or more weekly trips during lockdown, reducing to ~39% during the first phase of 18 restriction easing, and further to ~34% during the following phase of easing. The model 19 estimations show that common factors, dominated by socioeconomic and demographic 20 variables, influenced the frequency of outdoor exercise trips across most survey groups. The 21 modelling framework also allowed insights into the impact of unobserved characteristics 22 within several independent variables; for example, the lockdown exercise trip rates of those 23 with a health problem or disability, and those over 65, were both found to be dependent on 24 personal vehicle access. 25 26

The findings suggest that those with a health problem or disability, those who live in 28 households' where the main income earner is employed in a semi-skilled/unskilled manual 29

The COVID-19 pandemic has had unprecedented effects on human behaviour across the globe. 57

In the context of transportation, significant changes in travel behaviour have been observed 58 during government-enforced lockdowns. Research has shown the trip purposes and mode 59 preferences of individuals to vary significantly from normal, pre-lockdown levels (Abdullah, 60 et al., 2020; Laverty, et al., 2020) . During 2020 in Scotland, significant reductions in bus, rail 61 and car journeys, and significant increases in active travel (walking and cycling) were recorded 62 (Transport Scotland, 2020). However, the overall impact of social distancing measures, and the 63 associated increase of telecommuting (working from home), on physical activity is not clear. 64

It may be anticipated that the significant decline in commuting trips and use of public transport 65 during COVID-19 lockdowns also reduced levels of physical activity. In fact, before COVID-66 19, commuting journeys made by public transport in England were shown to generate on 67 average 21 minutes of physical activity through walking or cycling from the origin or 68 destination of the trip to stops or hubs (Patterson, et al., 2019) . 34% of public transport 69 commuters achieved the recommended level of physical exercise while travelling to and from 70 work. The UK Government's "stay-at-home" guidance significantly limits this daily 71 component of physical activity. This limitation should be compensated for through adjusted 72 behavioural patterns, thus avoiding the well-known negative consequences of limited exercise. 73

For instance, past research has shown reliable causal relationships between reduced rates of 74 exercise and increased incidence of serious physiological disorders, such as diabetes and 75 cardiovascular disease (Anderson & Durstine, 2019) and increased rates of mental illness, 76 including anxiety and depression (Camacho, et al., 1991) . The MRS Code of Conduct provides a set of ethical and professional standards, based on the 140 GDPR, that research practitioners must maintain (MRS, 2019). Telephone numbers (80% 141 landline and 20% mobile) were chosen randomly from the households with a landline in the 142 selected postcode areas. Any numbers that were identified as non-response, a business or 143 refusal to participate were discarded. 144

The purpose of these surveys, which are still ongoing, is to monitor the impact of COVID-145 19 restrictions on travel behaviour in Scotland, as well as exploring perceptions regarding 146 future travel intentions. We study the weekly rate of outdoor exercise trips, via respondents' 147 answers to mobility-related questions during three distinct periods of the pandemic. The 148 periods will be referred to as Survey Groups 1, 2 and 3, and can be defined as follows: Survey 149 Group 1 includes two "survey waves" conducted during the most stringent lockdown (24 th 150

March 2020 -27 th May 2020); Survey Group 2 includes two survey waves conducted during 151 "Phase 1" (28 th May -17 th June 2020) and "Phase 2" (18 th June -8 th July 2020) of the Scottish 152 Government's "COVID-19 route map"; and Survey Group 3 contains five survey waves during 153 "Phase 3" (9 th July -8 th October 2020) of the route-map. 154

To contextualise the survey groups further, lockdown and subsequent phases can be outlined 155 as follows: "lockdown" refers to the most stringent restrictions, where people living in Scotland 156 were advised to stay at home with the exception of "essential work or travel"; "Phase 1" refers 157 to the first phase of restriction easing, where the most significant alteration to restrictions was 158 to allow those who could not work from home to return to work; "Phase 2" included further 159 relaxations regarding the reopening of workplaces and physical distancing with people from 160 other households; and "Phase 3" refers to the furthest stage of restriction easing, where many 161 small businesses, workplaces and gyms reopened (Scottish Government, 2020). Throughout 162 the pandemic, the Scottish Government promoted outdoor exercise within an individual's local 163 area, which was initially limited to one trip per day during lockdown, however, this limit was 164 removed during subsequent phases (Scottish Government, 2020). Table 1 shows the matching 165 of survey waves into survey groups, where dates in parentheses are the duration of survey 166 window (i.e., the period in which respondents were consulted) or the duration of a given phase 167 of restrictions, while Table 2 shows the number of initial responses and complete responses for 168 each survey group. 169 J o u r n a l P r e -p r o o f

The verbatim survey question, which is the key dependent variable for this paper, was as 173 follows: "In the past 7 days how many times have you left your home to go for outdoor exercise 174 (e.g. going for a walk or hike, run or cycle, dog walking)". The weekly trip rates were recorded 175 as discrete, ordered outcomes (zero, one, two-three, four-five, six-seven, and more than seven 176 trips). To account for low variability for several of these categories across the sample, the 177 outcomes of the dependent variables (i.e., the weekly trip frequencies across survey groups) 178 were aggregated as follows: Level 1 (no trips), Level 2 (one, two or three trips), Level 3 (four 179 or five trips) and Level 4 (six or more trips). Kolmogorov-Smirnov tests were conducted to 180 verify the assumption that the distribution of responses for grouped waves (as shown in Table  181 1) was similar. All test results were insignificant, therefore, there is no significant variation in 182 the distributions of grouped waves (e.g., in Survey Group 1, there is no significant variation in 183 the distributions of survey waves 1 and 2). Further Kolmogorov-Smirnov tests were conducted 184 for the distributions of the survey groups; all results were statistically significant (p-value < 185 0.05) as shown in Table 3 , hence, there is significant variation in the distribution of outdoor 186 exercise trips among the survey groups. 187 captures information for the household's main income earner, it will be referred to as 221 "household social grade" from here on. The surveys used SIMD quota restraints to return 222 samples that were almost exactly representative of Scotland's demographic strata, for example, 223 the gender, ethnic background, household social grade and regional data for Scottish residents 224 were all accurately represented among the survey groups. Statistical methods are widely adopted to analyse survey data in transportation research (Eker, 229 et al., 2020a; Barbour, et al., 2020) and, specifically, trip rate data (Sultana, et al., 2018) . In 230 recent years, an increasing number of studies have shown the merits of accounting for the 231 potential effects of unobserved heterogeneity in survey data (Eker, et Given the discrete, ordered nature of the dependent variable, discrete outcome modelling, 239 in particular the ordered probit modelling framework, was deemed appropriate for the 240 statistical analysis (Washington, et al., 2020) . In this study, the random parameters technique is 241 also incorporated in the ordered modelling framework; this integrated approach differs from the 242 standard ordered probit, as it allows for the potential effects of unobserved heterogeneity within 243 the observed independent variables to be captured (Mannering, et al., 2016) . From here on, the 244 methodological formulation of the modelling framework is in accordance with Washington et 245 al., 2020. The ordered probit model can be defined as follows: 246

where is a vector of estimable parameters, X is a vector of independent variables dictating 248 the discrete ordering for an observation, n, and  is random disturbanceassumed to be 249 normally distributed across observations, with mean = 0 and variance = 1. Using the previous 250 equation, the ordered data, y, for each observation can be defined as follows: 251 

where is a vector of estimable parameters that may vary across observations, n, is the 273 vector of mean parameter estimates across the dataset, is a vector of explanatory variables 274 from observation n, that influence the mean of , is a vector of estimable parameters and 275 is a vector of random distributed terms. The calculation of the probabilities for RPOP models 276 is particularly cumbersome, therefore, a simulation-based maximum likelihood is used for 277 model estimation (Washington, et al., 2020) . For this process, Halton draws are often 278 considered a more effective alternative to random draws (Halton, 1960) , as such we use Halton 279 draws for model calibration in this paper. 280

The average marginal effects, which are the change in the levels of the dependent variable 281 as a result of a one unit change in the independent variable, can be calculated to gauge the 282 influence of independent variables on interior categories (Washington, et al., 2020) . For 283 variables that generate statistically significant random parameters, observation-specific 284 parameters ( ) can be used for the calculation of the marginal effects, significantly enhancing 285 their robustness (Anastasopoulos, 2016) . Observation-specific parameters can be derived 286 through a built-in capability of the modelling software (R package: 'Rchoice' (Sarrias, 2020) 

Tables 5, 6 and 7 show that a wide range of factors significantly affected the rates of outdoor 310 exercise trips made by Scottish residents throughout the COVID-19 pandemic. Influential 311 independent variables capture mainly socioeconomic (e.g., household social grade and current 312 working situation), demographic (e.g., disability, ethnic background and age) and behavioural 313 (e.g., mode of travel choices) features of the respondents. 314

Several instances of significant heterogeneity in the means of random parameters were 315 found in Survey Group 1 (Table 5 ) and Survey Group 3 (Table 7) . We also estimate marginal 316 effects for variables capturing heterogeneity in the means of random parameters; this is 317 achieved by calculating the impact of a unit change of these variable on the means of the 318 random parameters, and subsequently on the probabilities of the outcomes of the dependent 319 variable. For example, in the model for Survey Group 1 (Table 5) 

For the random parameters across the survey groups, model coefficients and marginal effects 352 cannot reveal the unobserved heterogeneity in the effects of the corresponding variable, 353 therefore, the distributional effects of the random parameters are shown in Table 8 . The values 354

in Table 8 can be interpreted as in the following example: for the health problem and disability 355 variable in Survey Group 1, 88.18% of respondents with a health problem or disability are 356 likely to make no outdoor exercise trips (i.e., the attribute increases the likelihood of the lowest 357 outcome of the dependent variable), while the remaining 11.82% are likely to make outdoor 358 exercise trips frequently (i.e., the attribute increases the likelihood of the highest outcome of 359 the dependent variable). The positive (>0) and negative (<0) distributional effects of the 360 random parameters can be visualised in Figures 2, 3 and 4 The discovery of multiple random parameters across all models suggests highly heterogeneous 379 effects on outdoor exercise trip rates throughout the pandemic for the variables shown in Table  380 8. The health problem or disability and age indicator (over 65) variables were consistently 381 significant as random parameters in all survey groups. Interestingly 

An overview of the effects identified in all models is displayed in Table 9 . A range of 397 socioeconomic, demographic and behavioural factors significantly affected weekly outdoor 398 exercise trip frequencies throughout the COVID-19 pandemic in Scotland. As discussed in 399 'Data', the outdoor exercise trip rates of Scottish residents varied significantly at distinct points 400 of the pandemic, hence the three separate models estimated for lockdown (Survey Group 1), 401

Phases 1 and 2 (Survey Group 2), and Phase 3 (Survey Group 3). Table 9 allows the changes 402 in significant independent variables affecting outdoor exercise trips at distinct points of the 403 pandemic to be better understood. Additionally, the relative magnitude of the marginal effects 404 per independent variable are given in Table 9 , such that one arrow indicates a moderate effect, 405 two arrows a strong effect and three arrows a very strong effect. (male)' variable, induces heterogeneous effects in Survey Group 1, has no effect in Survey 417

Group 2, and has a strong negative effect in Survey Group 3. The behavioural variability of 418 these demographics throughout the pandemic is likely the result of changing government 419 restrictions, however, it may also be related to other factors. For example, in how the risk of 420 COVID-19 infection is perceived may lead to altered behaviour (restriction easing is typically 421 preceded by lower infection rates in the community), or variation in weather (which may be 422 captured as unobserved variations in some of the random parameters generated by the 423 demographic characteristics). 424 Influential socioeconomic factors include household social grade and current working 425 situation. If the extremities of the dependent variable are described as no outdoor exercise (y=1) 426 and frequent outdoor exercise (y=4), their specific effects were as follows: those who live in 427 households where the main income earner is employed in a managerial/professional occupation 428 were found to be significantly more likely than those with other occupation types to complete 429 frequent outdoor exercise in all survey groups, while respondents who live in households where 430 the main income earner is employed in a semi/unskilled manual occupation or is unemployed 431 were significantly more likely to complete no outdoor exercise. 432

This difference between these household types emphasises experiential disparities of 433 COVID-19 that are based on occupational factors. A possible explanation may be that those in 434 managerial/professional occupations are more able to telecommute, and as a result, have 435 greater freedom to exercise frequently. Similarly, furloughed respondents were significantly 436 more likely to complete outdoor exercise frequently compared to other groups with different 437 working situations (i.e., key workers, retired, in full-time education or self-employed). 438

Intuitively, this may be explained by the fact that furloughed respondents had greater freedom 439 and availability to exercise than the remaining respondents. A pre-COVID-19 study by Cook 440 & Gazmararian (2018) found similar trends in the US, as those who worked fewer hours had 441 more time for physical activity and were less likely suffer from obesity. The socioeconomic 442 influences identified in this study reiterate the stark inequalities in British society, which have 443 been highlighted and exacerbated by the pandemic (Office for National Statistics, 2020). The 444 long-term effects of this are hard to predict, however, it is within reason to suggest that those 445 who live in households where the main income earner is employed in a semi/unskilled manual 446 occupation or is unemployed are more likely to suffer the mental and physical health issues 447 associated with limited exercise (Anderson & Durstine, 2019; Camacho, et al., 1991) . 448 A variety of demographic characteristics, including: health problem or disability, age, ethnic 449 background and gender were found to significantly affect outdoor exercise trip frequencies. 450

The effect was particularly pronounced among those with a health problem or disability, who 451 were significantly more likely than those without a health problem or disability to complete no 452 outdoor exercise across all survey groups. As mentioned in the previous section, the 'health 453 problem or disability' variable was consistently significant as a random parameter, suggesting 454 highly heterogeneous effects on outdoor exercise among this demographic. Table 9 shows that 455 in one instance (Survey Group 1) significant heterogeneity in the mean of the health problem 456 or disability random parameter was discovered. An exogenous variable, 'mode of travel used 457 prior to lockdownpersonal vehicle', explained some of the unobserved heterogeneity, such 458 that those who have a health problem or disability and access to a personal vehicle were 459 significantly more likely to exercise frequently during lockdown, compared to those with no 460 personal vehicle access. This suggests that features of transport equity, related to personal 461 vehicle ownership and accessibility, influenced the ability of those with a health problem or 462 disability to complete frequent outdoor exercise. For those aged over 65 in Survey Group 1, a 463 similar trend was discovered. Respondents over the age of 65, and with access to a personal 464 vehicle, were significantly more likely to complete frequent outdoor exercise compared to 465 those with no access. A possible explanation is that among those with a health problem or 466 disability and those over 65, there is a hesitancy to exercise in densely populated areas where 467 the risk of contracting COVID-19 is higher. As a result, those with access to a personal vehicle 468 may have driven to more secluded areas to complete their outdoor exercise, while those with 469 no personal vehicle access may have felt uncomfortable exercising in densely populated 470 environments. 471

Ethnic minority groups were found to be significantly more likely to complete no outdoor 472 exercise trips in Survey Groups 1 and 3, in comparison to those from other ethnic backgrounds 473 (White British and any other White background). This may be explained by socioeconomic 474 influences, particularly occupation, or factors related to the quality of built environment 475 characteristics, for example, lower income neighbourhoods often suffer from a lack of high 476 quality, local green space (Sport England, 2015; UK Government, 2020). As discussed in the 477 introduction, ethnic minority groups have experienced disproportionate levels of COVID-19 478 infection and mortality (Office for National Statistics, 2020). These effects are experienced 479 immediately, however, we suggest that ethnic minority groups may also be at increased risk of 480 longer-term mental and physical health problems associated with prolonged periods of limited 481 exercise. 482

Those over the age of 65 were found to be significantly more likely than other age groups 483 to have completed no outdoor exercise during lockdown. As discussed previously, the outdoor 484 exercise trip frequencies of over 65s were found to be significantly influenced by personal 485 vehicle access during lockdown. In Survey Groups 1, 2 and 3 the over 65 variables were 486 significant as random parameters, while in two instances (Survey Group 1 and 3) heterogeneity 487 in the means of the random parameters were discovered. It is worth noting that the coefficients 488 of the over 65 variables were not significantly negative in Survey Group 2 and 3, in other 489 words, the exercise trips of this demographic were most severely affected during Survey Group 490 1 (lockdown). Among over 65s in Survey Group 3, it was found that those from a White British 491 ethnic background were significantly more likely to complete frequent outdoor exercise trips 492 compared to other ethnicities. This finding corroborates with a recent report by Sport England 493 (2015), where it was found that the physical activity levels of different ethnic backgrounds 494 were often dependent on factors, such as the quality of surrounding infrastructure and access 495 to local green space. The same report also found that ethnic minority groups in particular, 496 tended to live in more deprived communities where access to local green space was scarcer or 497 the spaces were of poorer quality (Sport England, 2015). In comparison, more affluent 498 communities, where White British is the most common ethnic background (UK Government, 499 2020), often have a greater abundance of local green space (Sport England, 2015). Particularly 500 in the context of a pandemic, it may be that this availability of local green space allowed White 501

British over 65s to complete frequent outdoor exercise trips. 502

The gender variable was significant as a random parameter in Survey Group 1, suggesting 503 significantly heterogeneous outdoor exercise trip frequencies. In Survey Group 3, males were 504 significantly more likely to complete no outdoor exercise trips compared to other genders 505 (female and non-binary). The varying effect of the gender variable may be the result of 506 changing working situations, for example, women are more likely to be key workers (58% 507 female, 42% male (Office for National Statistics, 2020)), therefore, it is likely that some 508 females were unable or unwilling to exercise frequently in the early stages of the pandemic 509 because of work commitments. During Phase 3 of restriction easing (Survey Group 3), a 510 significant proportion of males may have reverted to more regular daily activity patterns (e.g., 511 returning to work), therefore the need for frequent outdoor exercise may not be as evident as 512 during the more stringent lockdown phases. 513

One behavioural characteristic, relating to mode usage prior to COVID-19, was also found 514 to significantly affect the frequency of outdoor exercise trips. Those who frequently used active 515 modes (on-foot or by bicycle) prior to lockdown, were significantly more likely to complete 516 frequent outdoor exercise trips in all models, in comparison to those who did not use active 517 travel modes. It is likely that people who already used active modes live in an area, or have 518 access to equipment (e.g. bicycles), that facilitates active travel, hence, these individuals are 519 able to continue with their pre-COVID-19 behavioural patterns. More interestingly, those who 520 travelled frequently by a personal vehicle prior to lockdown were significantly more likely to 521 have completed frequent outdoor exercise trips in Survey Group 2, in comparison to those who 522 did not frequently use a personal vehicle. This may be related to previous findings, which 523 showed that the outdoor exercise trips of those with a health problem or disability, and of those 524 over 65, were dependent on personal vehicle use prior to lockdown. A possible explanation is 525 that among the entire Survey Group 2 sample, vehicle access is a factor determining the 526 frequency of outdoor exercise trips. As discussed previously, it may be that those who have 527 personal vehicle access, but who live in an undesirable exercise area (e.g., because the area is 528 densely populated, there is a lack of active travel routes, or local green space is limited or of 529 poor quality), may travel to a more desirable area to complete outdoor exercise. However, this 530 finding requires deeper investigation, as the original variable gauges personal vehicle use as 531 opposed to ownership, and therefore may include those who car share or rideshare. 532

Finally, those who were "directly affected by COVID-19" were found to be significantly 533 more likely to have completed frequent outdoor exercise trips during lockdown than those who 534 were not directly affected; this factor was also found to induce heterogeneous effects, as it 535 resulted in a statistically significant random parameter. It should be noted that "direct affect" 536 is not strictly defined in the questionnaire, and as a result, it may have been interpreted in 537 different ways by respondents. We make the assumption that "direct affect" is someone who 538 has personally contracted COVID-19, or whose close family or friends have been infected. The 539

propensity of most respondents who feel "directly affected by COVID-19" to complete 540 frequent exercise trips, may reflect their determination to follow the widely circulated advice 541 of various healthcare (e.g., NHS) or scientific (e.g., World Health Organisation) bodies, to stay 542 active and maintain their wellbeing during lockdown. Furthermore, individuals who feel 543 affected by COVID-19 but did not considerably amend their activity patterns during the 544 lockdown, may have done so due to their cultural beliefs or personal attitudes. The 545 heterogeneous effects within this variable could be linked to how people's perceived risk of 546 COVID-19 changed following direct affectation, for example, some individuals belonging to 547 this group may have acted more cautiously as a result of being directly affected by COVID-19, 548 thus making less trips for any reason. Significant heterogeneity in the mean of the random 549 parameter was also detected, suggesting that among directly affected respondents, those from 550 a White British ethnic background were more likely to have completed no outdoor exercise 551 than those directly affected and from other ethnic backgrounds. This finding may be related to 552 the effect of cultural identity (e.g., nationality or religion) on COVID-19 risk perceptions, such 553 that certain groups may act more cautiously after being directly affected. Although recent 554 studies have explored this theory, the factors affecting people's perceived risk of COVID-19 555 were in fact dominated by social values, such as: trust in government advice, trust in science 556 and political ideology (e.g. individualist or collectivist worldviews) (Dryhurst, et al., 2020) . 557 558 CONCLUSION 559

This paper uses public survey data to show how the frequency of outdoor exercise trips made 560 by Scottish residents changed throughout the COVID-19 pandemic. The proportion of 561 respondents who made six or more outdoor exercise trips per week decreased consistently, 562 from 46.4% during lockdown, to 38.8% during Phase 1 & 2, to 33.5% during Phase 3. We 563 suggest that this is most likely the result of an initial conscientiousness, or availabilitydue to 564 increased telecommuting or the introduction of the furlough schemeto complete frequent 565 outdoor exercise trips during lockdown. In Phases 1 and 2, and Phase 3, around 35% of 566 respondents made no weekly outdoor exercise trips, whereas the proportion who made no trips 567 during lockdown was comparatively smaller (28.6%). This also suggests that Scottish residents 568 were more able to exercise in the earlier stages of the pandemic or that their working 569 circumstances facilitated this behaviour. The polarisation of exercise behaviour was also 570 starkest during lockdown, as ~75% of respondents completed either no trips or six or more 571 trips. It may be that the strictness of government restrictions during the lockdown period 572 exacerbated polarisation of exercise behaviour, thus government's may wish to consider ad-573 hoc policies to counteract this effect for potential future lockdowns. 574

We show through statistical modelling that a variety of socioeconomic, demographic and 575 behavioural variables affected weekly rates of outdoor exercise trips. The most consistent 576 respondent characteristics that significantly increased the likelihood of frequent outdoor 577 exercise trips (six or more) across all survey groups were as follows: households where the 578 main income earner is employed in a managerial/professional occupation, those who were 579 furloughed, and those who frequently used active travel modes prior to COVID-19. All of the 580 aforementioned groups have in fact benefitted from high exercise rates during the pandemic. 581

Conversely, those with a health problem or disability, ethnic minority groups and those who 582 live in households where the main income earner is employed in a semi-skilled/unskilled 583 manual occupation or is unemployed were all significantly more likely to have completed no 584 weekly outdoor exercise, in at least two, if not all survey groups. As a result, these groups are 585 likely to be at higher risk of the mental and physical illnesses associated with limited physical 586 activity. 587

It is the recommendation of this paper that policymakers use public information campaigns to 590 promote exercise among the previously identified low activity groups. Future research may 591 also be conducted to determine the barriers preventing these groups from exercising frequently. 592

A conduit for further research may explore whether these low exercise rates are attributable to 593 the pandemic, or whether they are in fact an endemic social issue related to infrastructural 594 impediments, such as a lack of local green space or active travel infrastructure. This is 595 particularly important among groups who may require additional provision to complete 596 outdoor exercise, for example, those with mobility limiting conditions. Issues of transport 597

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inequity discovered in this paper, specifically, that the lockdown outdoor exercise trip rates of 598 those with a health problem or disability, and of those over 65, were both dependent on personal 599 vehicle access, may provide similarly intriguing areas for further research. It is the 600 recommendation of this study that these inequities are investigated further through targeted 601 consultation of disabled and/or elderly individuals, thereby informing the direction of future 602 policy with regards to an equitable transport system. 603Future research may also investigate the relationship between future commuting intentions 604 and physical activity. For example, if more people telecommute following the pandemic there 605 may be detrimental effects on physical activity levels, which in the past have been incorporated 606 into commuting trips (i.e. walking to a workplace, or walking to a public transport connection). 607If this proves to be the case, walk and cycle to work schemes are likely to be less effective 608 methods for encouraging physical activity, therefore, we recommend that governments take 609 pre-emptive action to ensure exercise levels do not suffer as telecommuting increases in 610 popularity. This may come in the form of government policies to enhance built environment 611 characteristics (e.g., creation of new, high-quality green space, improving the walkability of 612 streets and enhancing active travel infrastructure), particularly in lower income 613 neighbourhoods. The government may also consider subsidisation schemes for equipment that 614 facilitates active lifestyles (e.g., gym memberships and bike ownership). 615

Several limitations should be noted. Firstly, the survey data gauged respondents' region of 618 residence, however, it did not contain in-depth details about the areas of residence (e.g., 619postcodes or local neighbourhood information). As a result, built environment characteristics, 620 such as, the prevalence of public transport links, availability of cycle paths and access to green 621 space, which have all previously been shown to significantly affect physical activity levels, 622 cannot be accurately accounted for in the analysis. Secondly, the relative impact of COVID-19 623 on outdoor exercise levels cannot be accurately gauged, as limited data exist for the pre-624 pandemic exercise patterns of Scottish residents. As a result, it cannot be inferred whether the 625 pandemic has improved or hindered general levels of physical activity in Scotland. Finally, 626given that the survey was conducted telephonically, the sample does not include those who do 627 not have access to a landline or a mobile phone. 628 629 ACKNOWLEDGMENTS 630The authors would like to thank Transport Scotland, and in particular, Mr. Paul Sloan, for 631 providing access to this detailed and timely dataset. 632 633 APPENDIX 634 Directly affected by COVID-19: Yes, No 10Most frequently used modes of travel before COVID-19: Public transport (bus, train or tram), Personal vehicle (car, van or taxi), Active travel (on-foot, by wheelchair or by bicycle) 11Mode of travel before and during COVID-19: E.g. Public transport frequently used before COVID-19 but used less during COVID-19We the undersigned declare that this manuscript is original, has not been published before and is not currently being considered for publication elsewhere.We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.We confirm that each author has disclosed on the form below any conflict of interest, in accordance with Elsevier's standard guidelines. These are summarized below, a and given in full at: www.elsevier.com/authors/author-rights-and-responsibilities#responsibilities.We understand that the Corresponding Author is the sole contact for the Editorial process. He/she is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs.Sincerely,