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Physical Activity Behavior, Motivation and Active Commuting: Relationships with the Use of Green Spaces in Italy



Many benefits of physical activity (PA) are observed with weekly average volumes of 150–300 min at moderate intensity. Public parks may be an attraction for many people living in the city and could help to achieve the recommended dose of PA. The present study aims to understand the motivation that drives people to a park and evaluate the amount of PA practiced by park-goers. A questionnaire was anonymously administered to 383 voluntary visitors to the Arcoveggio park (Bologna), aged 18–70 years. Sixty-one percent of participants practiced outdoor PA. Differences in park use between sexes and age groups were found. PA was higher in men than in women and in the 18–30 age group than in other age groups. Most participants travelled to the park in an active way (86.4%), resulting in easier attainment of the recommended amount of PA (64.5%). The main motivations for using the park were related to relaxation, performing PA, or both. According to a multiple regression model, the time per week spent at the park, the method of getting there, and the kind of PA were significant explanatory variables of the amount of PA practiced. In particular, the highest number of minutes of PA was achieved by those who travelled to the park by running, while those using vehicles presented the lowest number. All initiatives to promote active commuting and activities in the urban park represent an important strategy to improve health, supporting adults to lead an active lifestyle.
Citation: Grigoletto, A.; Loi, A.;
Maietta Latessa, P.; Marini, S.;
Rinaldo, N.; Gualdi-Russo, E.;
Zaccagni, L.; Toselli, S. Physical
Activity Behavior, Motivation and
Active Commuting: Relationships
with the Use of Green Spaces in Italy.
Int. J. Environ. Res. Public Health 2022,
19, 9248.
Academic Editor: Paul B.
Received: 30 June 2022
Accepted: 25 July 2022
Published: 28 July 2022
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Attribution (CC BY) license (https://
International Journal of
Environmental Research
and Public Health
Physical Activity Behavior, Motivation and Active Commuting:
Relationships with the Use of Green Spaces in Italy
Alessia Grigoletto 1, Alberto Loi 2, Pasqualino Maietta Latessa 3, Sofia Marini 3, Natascia Rinaldo 4,
Emanuela Gualdi-Russo 4, Luciana Zaccagni 4, * and Stefania Toselli 1
Department of Biomedical and Neuromotor Sciences, University of Bologna, Via Selmi 3, 40126 Bologna, Italy; (A.G.); (S.T.)
2School of Pharmacy, Biotechnology, and Sport Science, University of Bologna, 40126 Bologna, Italy;
3Department for Life Quality Studies, University of Bologna, 47921 Rimini, Italy; (P.M.L.); (S.M.)
4Department of Neuroscience and Rehabilitation, Faculty of Medicine, Pharmacy and Prevention,
University of Ferrara, Corso Ercole I d’Este 32, 44121 Ferrara, Italy; (N.R.); (E.G.-R.)
Many benefits of physical activity (PA) are observed with weekly average volumes of
150–300 min at moderate intensity. Public parks may be an attraction for many people living in the
city and could help to achieve the recommended dose of PA. The present study aims to understand
the motivation that drives people to a park and evaluate the amount of PA practiced by park-goers.
A questionnaire was anonymously administered to 383 voluntary visitors to the Arcoveggio park
(Bologna), aged 18–70 years. Sixty-one percent of participants practiced outdoor PA. Differences in
park use between sexes and age groups were found. PA was higher in men than in women and in
the 18–30 age group than in other age groups. Most participants travelled to the park in an active
way (86.4%), resulting in easier attainment of the recommended amount of PA (64.5%). The main
motivations for using the park were related to relaxation, performing PA, or both. According to a
multiple regression model, the time per week spent at the park, the method of getting there, and the
kind of PA were significant explanatory variables of the amount of PA practiced. In particular, the
highest number of minutes of PA was achieved by those who travelled to the park by running, while
those using vehicles presented the lowest number. All initiatives to promote active commuting and
activities in the urban park represent an important strategy to improve health, supporting adults to
lead an active lifestyle.
Keywords: active commuting; green urban space; motivation; physical activity; COVID-19
1. Introduction
The World Health Organization guidelines on physical activity (PA) to avoid seden-
tary behavior [
] support the finding that many of the health benefits of PA result from
average weekly volumes of 150–300 min of moderate intensity or 75–100 min of vigorous
intensity, or an equivalent combination of the two. Promoting PA is a well-established
priority, since physical inactivity is one of the five leading global risks for mortality in the
world [
]. Indeed, physical inactivity is believed to be responsible for the death of 3.3 mil-
lion people annually worldwide [
]. Furthermore, the recent emergence of
has influenced the lifestyle of the population, reducing PA and becoming a serious concern,
mainly for older adults who are typically more prone to chronic diseases and less active,
compared to younger people [
]. Strategies are therefore needed to increase PA and
reduce the sedentary lifestyle of the population. One of the strategies that could help
to achieve the goal of the recommended levels of PA could be active transport such as
Int. J. Environ. Res. Public Health 2022,19, 9248.
Int. J. Environ. Res. Public Health 2022,19, 9248 2 of 15
walking or bicycling from home to work, shopping, recreational places, and vice versa [
In this light, a suitable plan for promoting PA [
], maintaining a healthy weight [
], and
improving mental health [
] may be to empower citizens to switch from using pri-
vate motor vehicles to active transportation. In addition, public transportation options
(e.g., buses or trains) can encourage people to walk from and to various public transporta-
tion stops, increasing their PA levels, albeit to a lesser extent. These good habits could
consequently also lead to benefits for the urban environment, decreasing pollution, traffic
noise, and temperature [
]. A worldwide study showed that PA levels are higher in walka-
ble cities [
], because they allow active commuting and allow more frequent to travel from
home to downtown or other destinations within the city by bicycle or on foot. According
to Zijlema et al. [
], the increase of PA may be most successful when integrated into daily
life habits. Another factor that can help people to achieve the right amount of PA is the
use of green parks. Public green spaces provide multiple health benefits by facilitating
PA, contact with nature, and social interaction [
]. In addition, outdoor exercise can
be a viable alternative to indoor exercise; exposure to a natural environment is linked to
triggering a higher amount of PA among residents, and a lower mortality rate [
Some studies have showed that long-term adherence to exercise initiatives conducted in
an outdoor natural environment or urban green space may be superior to that of indoor
exercise interventions [
]. Despite several pieces of evidence on the health benefits
of parks, they are generally underutilized, and visitors are often engaged in low levels
of PA during their park visits [
]. Initiatives created to increase PA in green spaces
have been linked with improvements in social networking and feelings of connectivity
and companionship, an increased appreciation of nature, improvement in self-esteem, and
a means of escape from modern life [
]. Even though there is increasing literature
about the practice of PA, and on the motivations and interventions related to the increase in
outdoor PA in green spaces, few studies have been carried out in Italy [
]. In addition [
the motivations that cause people to use green space are still unclear [
] and, therefore,
it is important to understand how these can be linked to PA practice. As regards the use
of parks, some concerns are about the best distance from residences to urban parks and
greenness to ensure a frequent use of green space. The currently recommended residence
distance to the nearest city parks is 300 m [
]; however, other studies have suggested that
people are willing to walk for an even longer distance to have access to a green urban space
if parks have some attractive features [
]. Understanding the motivations that drive
people to use green urban space is important to implement adequate strategies.
The purposes of this study were: (1) to assess people’s motivations to use the park,
(2) to assess how many people in each sex and age group use the park to do PA, and
therefore to understand how much park use affects PA levels, and (3) to evaluate the
contribution of active, vehicle-free transportation (walking, jogging, bicycling) in achieving
of the recommended levels of PA. To achieve these goals, a new questionnaire designed ad
hoc was developed and administered in Arcoveggio park, in Bologna (North Italy), which
is the capital of the Emilia-Romagna region, with nearly 4.4 million inhabitants over an
area of 22,446 km
]. Arcoveggio park covers nine hectares in the city‘s northern sector.
The park contains outdoor fitness equipment, picnic areas, trails, and bicycle paths. As the
COVID-19 pandemic has changed the lifestyle habits, this research could be a starting point
to understanding the motivation that leads people to use the park and plan interventions
to increase PA.
2. Materials and Methods
2.1. Questionnaire Development and Procedures
A new questionnaire was developed. To design the questionnaire, we drew on our
personal experience and previous studies in the literature [
]. The items were indepen-
dently submitted to the opinion of three researchers with expertise in PA to assess their
clarity and relevance. The questionnaire, administered anonymously, and was divided
into two sections (see Supplementary Materials, Figure S1): the first section was designed
Int. J. Environ. Res. Public Health 2022,19, 9248 3 of 15
to collect demographic information, including age, sex, weight, height, profession, and
level of education. The Body Mass Index (BMI, kg/m
) was calculated from the referred
values of weight and stature, and the weight status was assessed according to the World
Health Organization guidelines [
]. The second part of the questionnaire consisted of
15 questions designed to assess important motivation to use the park, and the quality and
amount of PA practiced. The questionnaire was written and administered in the Italian
language; however, in Figure S1 it is reported in English. The total amount of PA and the
time of active commuting were calculated by multiplying the active time and the journey
time by the number times a week that the participants visited the park. Finally, the two
amounts were summed to calculate the total amount of PA and of active commuting.
2.2. Participants
Three hundred eighty-three individuals were randomly recruited among park-goers.
The same researcher administered a printed questionnaire to all participants at Arcoveggio
Park in Bologna (North Italy). The park, which is one of the largest parks in the city, is
located in a neighborhood of socio-economic variability, representing, therefore a cross-
section of the population of Bologna [
]. Questionnaire administration began in March
2021, during the pandemic, and was completed in April 2021.
The study included a sample of men and women who met the following inclusion
criteria: having signed the informed consent; being a park-goer; and aged between 18 and
70 years. Pregnant women were excluded from the study.
The survey was approved by the Bioethics Committee of the University of Bologna
(prot. N. 0224254 of 9 October 2020).
2.3. Statistical Analysis
The internal consistency of the questionnaire was evaluated by Cronbach’s alpha
coefficient on the answers of the recruited sample. Cronbach’s alpha is considered reliable
for values between 0.5 and 0.9. In addition, a test–retest method was used to assess the
reliability of the questionnaire 15 days later.
Subsequently, to better achieve the objectives of the study, we performed an a pri-
ori power analysis using G*Power (version, Universität Kiel, Kiel, Germany) to
determine sample size, given
, power, and effect size. When ANOVA was performed
= 0.05; 1-
= 0.95; effect size f = 0.25), a sample size of 303 participants was detected. The
outcomes parameters for the multiple regression detected a sample size of 123 participants.
Additional subjects were involved to ensure the availability of data in the case of problems
with data collection. Variables’ normality was verified with the Shapiro–Wilk test. Descrip-
tive statistics (mean and SD for continuous traits, and frequency for discontinuous traits)
were calculated. Differences in frequency distribution between groups were evaluated by
the Chi-squared test. Two-way ANOVAs were carried out to assess differences among
sexes and age classes in anthropometric characteristics and questionnaire items. When a
significant F ratio was obtained, the Tukey post hoc test was used to evaluate the differences
between the groups.
Finally, a multiple regression analysis was carried out to assess possible predictors of
the amount of PA. Before performing the multiple regression, all the assumptions were
verified. The Shapiro–Wilk test and the variance inflation factor (VIF) test were performed
to verify the normal distribution and the multicollinearity of the variables. Anthropometric
and sociodemographic variables and information regarding the use of the park were
included in the model as independent variables. Predictors inputted into the model were
those found to have significant associations with the total minutes of PA (i.e., p< 0.05). The
data analysis was performed using Statistica for Windows, version 8.0 (Stat Soft Italia Srl,
Vigonza, Padua, Italy).
Int. J. Environ. Res. Public Health 2022,19, 9248 4 of 15
3. Results
The questionnaire was validated using the test–retest method and Cronbach’s alpha
was used to provide a measure of the internal consistency. The value was 0.70 which
is acceptable. Twenty-five people were asked to complete the questionnaire twice, at a
distance of two weeks, in order to assess the reliability of the survey. The correlation values
are presented in Table 1.
Table 1. Correlation values and p-value calculated for the validation of the questionnair.
Questions Correlation Value p-Value
Q1. Way to reach the park 0.74 0.00
Q2. Active commuting (min/week) 0.98 0.00
Q3. From 1 to 10, how tired were you when you reached
the park? 0.68 0.00
Q4. How far (in meters, approximately) is your home from
the park? 0.99 0.00
Q5. Do you go to the park to practice PA? 0.83 0.00
Q6. If you do not practice PA at the park, why do you go to the
park? 0.70 0.00
Q7. Kind of PA 0.86 0.00
Q8. How many times per week do you go to the park? 0.88 0.00
Q9. How many hours of PA do you practice at the park? 0.93 0.00
Q10. If there wasn’t this park, would you have practiced PA in
an indoor environment?
How often would you practice indoor PA if there wasn’t a park
0.71 0.00
Q11. Where do you like to exercise the most? 0.88 0.00
Q12. If you practice indoor exercise, in which type of indoor
environment? 0.80 0.00
Q13. Are you satisfied with this park? 0.76 0.00
Q14. I feel more energetic, after practicing PA in the park 0.75 0.00
Q15. I feel more energetic, after visiting the park 0.81 0.00
Most of the respondents were females (n= 215, 56.1%). Since the age range of the
participants was wide (from 18 to 70 years), people were divided into 10-year age class
groups, with the exception of the first group (first group: 18–30 years). The class most
represented was the first (n= 130, 34%), followed by those aged 31–40 years (n= 75, 20.1%),
41–50 years (n= 67, 19.6%), 51–60 years (n= 65, 17%), and 61–70 years (n= 46, 12%).
Table 2summarizes the anthropometric characteristics of the study participants.
Table 2. Anthropometric characteristics of participants (n= 383) by sex and age classes.
Females (n= 215) Males (n= 168)
Age (years) 18–30 31–40 41–50 51–60 61–70 18–30 31–40 41–50 51–60 61–70
N70 36 43 34 32 60 39 24 31 14
%32.6 16.7 20 15.8 14.9 35.7 23.2 14.3 18.5 8.3
Weight (kg) 58.2 68.1 66.9 78.3 74.7 63.4 67.8 73.3 76.1 85.9
SD 9.2 16.6 13.5 12.6 10.6 10.3 13.4 11.7 9.4 12.5
Height (cm) 165.8 164.8 164.1 164.2 162.4 177.9 178.5 175.8 175 177.4
SD 8.1 6.7 5.3 7.2 5.2 8 5.1 7.1 7.7 7.9
BMI (kg/m2)21.2 25.4 25.3 25 25.3 23.1 24.5 24.6 24.4 27.2
SD 2.8 3.8 5.8 4 4.8 2.9 3.1 2.7 2.8 3.5
Weight status (%)
Underweight 17.3 11.2 4.7 - 3.1 5 - - - -
Normal weight 75.6 69.5 53.5 56 59.4 73.3 64.1 66.6 70.9 21.4
Overweight 4.3 5.5 27.8 25.6 28.1 20 30.7 33.4 22.6 55.2
Obese 2.8 13.8 14 18.4 9.4 1.7 5.2 - 6.5 21.4
N (%) for categorical data; mean and standard deviation (SD) for continuous data.
Int. J. Environ. Res. Public Health 2022,19, 9248 5 of 15
As expected, men had significantly higher mean values of weight and height
11.8 kg and 176.9
7.3 cm) than women (63.9
13.1 kg and 164.3
7.6 cm)
(p< 0.001). In both sexes, the youngest age class had the lowest mean weight values, while
males of the oldest age class and females of the age class of 51–60 years had the highest
values. Regarding BMI, both women and men presented a significantly higher incidence of
overweight and obesity with age (p< 0.001 for both women and men). In particular, the
men belonging to the age class 61–70 years had the highest value while those belonging
to the age class of 18–30 years had the lowest. Females showed higher frequencies of
underweight than males, but also of obesity. An exception is represented by the oldest age
group, where males showed a higher prevalence of overweight and obesity.
Table 3summarizes the demographic and socio-economic characteristics of the sub-
jects who participated in the study and the categorical questionnaire items. Most of the
participants were employed (n = 285, 74.4%), followed by students (n = 45, 11.7%), retired
(n = 37, 9.7%), and, finally, unemployed (n = 16, 4.2%). A large proportion of the sample
reached the park by walking (n = 151, 39.4%), followed by running (n = 86, 22.5%), using a
motor vehicle (n = 69, 18%) or a bicycle (n = 43, 11.1%). Most of the participants preferred
outdoor PA (88.9%), perhaps because outdoor PA was considered safer than gym training
during the COVID-19 pandemic [39,40].
Significant differences among the age groups separately by sex were observed in all
items, except for Q12, “If you practice indoor exercise, in which type of indoor environ-
ment?” in both sexes, for Q5, “Do you go to the park to practice PA?” in females and, for
Q6, “If you do not practice PA, why do you go to the park?” in males. Regarding the way to
reach the park, females of all ages preferred to walk and secondarily to use a motor vehicle;
males also preferred to walk and using a vehicle was their last preference. Men of all age
classes frequented the park to practice outdoor PA, except the oldest ones. Regarding the
kinds of exercise practiced in the park, women showed an increase in walking with an
increase in age, while men presented a bigger variability among the different age classes.
With increasing age, both sexes preferred to practice outdoor PA instead of indoor PA. To
the Q6, “why do you go to the park?” young women generally answered that they go to
the park to relax or to socialize, but increasing age increased the percentage of women who
go to the park to get in touch with nature or to relax, while the percentage of those who
go there to socialize decreased. For men, the percentage of those visiting the park to relax
decreased with the increasing age.
In particular, considering the sub-categories, some differences emerged. As regards
occupation, differences between sexes were observed for all the categories. In particular,
in females there were fewer employed subjects in the youngest and oldest age categories
and a greater number of students in the youngest. No significant difference was observed
between sexes in educational level, and, as expected, the distribution of different levels of
education differed significantly among each age class. For Q1, the differences between sexes
were always significant, except for running; significant differences were almost always
observed among age classes, but the majority of people preferred walking. The use of the
park to do physical activity (Q5) differed between sexes, as the majority of males went
to the park to do PA at every age, as opposed to females. No differences were observed
between sexes for Q6 because the majority went to the park to relax; differences among age
classes were more marked in females. The kind of PA practiced (Q7) differed between sexes
because the majority of females preferred walking, whilst men gave more heterogeneous
results. Q10 did not show differences between sexes, while differences were observed
among age classes, as with increasing age, more subjects would not have practiced PA
indoors. No significant differences were shown for Q12, both between sexes and age
Int. J. Environ. Res. Public Health 2022,19, 9248 6 of 15
Table 3. Sociodemographic characteristics and questionnaire responses of participants (n = 383): comparisons among age groups and sexes.
Females Males Females Males
18–30 years 31–40 years 41–50 years 51–60 years 61–70 years p-Value 18–30 years 31–40 years 41–50 years 51–60 years 61–70 years p-Value 18–70 years 18–70 years p-Value
N (%) 70
(32.6) 36
(16.7) 43
(20.0) 34
(15.8) 32
(14.9) 60
(35.7) 39
(23.2) 24
(14.3) 31
(18.5) 14
(8.3) 215
(56.1) 168
Occupation 0.00 0.00 0.00
Employed 61.5 91.6 95.4 79.5 18.7 0.00 75.0 94.9 95.9 96.8 28.6 0.12 67.9 82.7 0.00
Student 37.1 2.8 - - - 0.00 16.7 - - - - 0.00 16.3 6.0 0.00
Unemployed 1.4 5.6 4.6 11.7 - 0.29 8.3 5.1 - 3.2 - 0.00 3.7 4.8 0.00
Retired - - - 8.8 81.3 0.00 - - 4.1 - 71.4 0.00 12.1 6.5 0.00
Education level 0.06 0.07 0.23
High school 40.0 50.0 46.5 67.7 62.5 0.00 45.0 61.5 41.7 58.1 92.9 0.00 49.7 55.4 0.75
Bachelor’s degree 48.6 16.7 11.6 14.7 25.0 0.00 26.7 15.4 12.5 16.1 - 0.07 27.9 17.3 0.10
Master’s degree 10.0 30.6 32.6 17.6 9.4 0.01 28.3 15.4 41.7 22.6 7.1 0.01 19.1 24.4 0.53
PhD 1.4 2.7 9.3 - 3.1 0.00 - 7.7 4.1 3.2 - 0.00 3.3 2.9 0.98
Q1. Way to reach the park 0.00 0.00 0.00
Walking 52.8 83.3 60.4 79.4 65.6 0.02 40.0 43.5 45.8 54.8 50.0 0.00 65.6 56.7 0.01
Running 11.4 - 2.3 2.9 - 0.09 35.0 17.9 29.1 9.6 7.1 0.16 4.7 24.6 0.24
Bicycle 18.5 11.1 13.9 11.7 3.1 0.05 15.0 33.3 20.8 25.8 14.2 0.00 13.0 11.2 0.00
Vehicle 17.1 5.6 23.3 5.8 31.2 0.74 10.0 5.1 4.1 9.6 28.5 0.04 16.7 7.5 0.04
Q5. Do you go to the park to practice PA? 0.29 0.01 0.00
No 41.4 50 55.8 55.9 62.5 0.04 20.0 23.1 16.7 25.8 64.3 0.04 51.2 25.0 0.00
Yes 58.6 50 44.2 44.1 37.5 0.15 80.0 76.9 83.3 74.2 35.7 0.00 48.8 75.0 0.00
Q6. If you do not practice PA at the park, why do you go to the park? 0.01 0.15 0.60
Get in touch with
nature 11.9 19.4 29.3 25.8 16.7 0.02 7.4 14.3 13.0 7.7 53.8 0.00 19.8 17.3 0.60
Relax 67.8 74.2 46.3 61.3 83.3 0.20 77.8 67.9 73.9 92.3 30.8 0.48 65.6 70.7 0.57
Socializing 20.3 6.5 24.4 12.9 - 0.00 14.8 17.9 13.0 - 15.4 0.16 14.6 12.0 0.52
Q7. Kind of PA 0.00 0.00 0.00
Light running 23.2 18.7 10.6 - - 0.40 18.2 24.2 36.8 22.7 14.3 0.00 7.0 17.9 0.07
Outdoor fitness
equipment 7.7 - 10.6 - 7.1 0.01 68.2 27.6 - - - 0.00 5.5 36.9 0.00
Skating 3.7 - 10.6 - - 0.00 - - - - - 0.05 1.3 - 0.27
Walking 38.7 81.3 47.2 100 71.4 0.03 4.5 24.2 42.1 59.1 57.1 0.00 75.3 32.3 0.00
Football - - - - 7.1 0.00 2.3 10.4 - - - 0.00 1.3 1.2 0.90
Bicycling 19.3 - 5.2 - - 0.02 - 13.7 - 18.2 28.6 0.00 7.0 8.3 0.54
Stretching 3.7 - 10.6 - - 0.00 6.9 - 10.5 - - 0.00 1.3 2.4 0.67
Nordic walking 3.7 - 5.2 - 14.4 0.42 - - 10.5 - - 0.00 1.3 1.0 0.28
Q10. If there wasn’t this park, would you have practiced PA in an
indoor environment? 0.01 0.00 0.75
Yes 51.4 50.0 37.2 32.4 21.9 0.19 58.3 28.2 66.7 29.0 21.4 0.02 40.9 44.0 0.89
No 38.6 25.0 39.5 55.9 68.8 0.05 31.7 59.0 33.3 51.6 42.9 0.27 43.7 42.9 0.99
I don’t know 10.0 25.0 23.3 11.8 9.4 0.14 10.0 12.8 - 19.4 35.7 0.05 15.4 13.1 0.84
Q11. Where do you like to exercise the most? 0.01 0.03 0.00
Outdoor 77.1 82.9 95.3 94.1 90.6 0.79 91.5 89.7 91.7 93.5 91.7 0.08 86.9 91.5 0.63
Indoor 22.9 17.1 2.3 5.9 9.4 0.00 8.5 10.3 8.3 6.5 8.3 0.09 13.1 8.5 0.00
Q12. If you practice indoor exercise, in which type of indoor environment? 0.53 0.19 0.75
Home 37.9 28.1 28.9 46.4 47.8 0.56 35.8 37.5 29.2 32.0 27.3 0.56 39.9 33.8 0.64
Gym 59.1 59.4 63.2 50.0 52.2 0.95 62.3 56.3 70.8 48.0 54.5 0.86 57.8 59.3 0.85
Swimming pool 3.0 12.5 7.9 3.6 - 0.28 1.9 6.3 - 20.0 18.2 0.01 2.3 6.9 0.57
Note. Differences between the overall categories are reported in bold.
Int. J. Environ. Res. Public Health 2022,19, 9248 7 of 15
In addition, since the distance between home and the park could be an important
factor that influences the decision on the way to reach the park, a Chi-squared test was
conducted between these two variables. The distance was divided into the following five
categories: less than 300 m, from 300 m to 1000 m. from 1000 m to 2000 m, from 2000 m to
4000 m and over 4000 m. The p-value of the Chi-squared test was statistically significant
for the total sample (0.00) and for all the other subcategories.
The results of the two-way ANOVAs to evaluate sex and age group differences are
reported in Table 4.
Significant differences were found in Q10, “How often would you practice indoor
PA if there wasn’t a park (h/week)?”, in the preference to practice indoor PA, the level of
satisfaction with the park, and in the level of fatigue when reaching the park. From what
the question, “How often would you practice indoor PA if there wasn’t a park (h/week)”,
the respondents of age class 51–60 years would have practiced little activity, while the
youngest ones would have practiced it anyway. Participants in the age class 31–40 years
showed the highest preference for indoor PA. Most participants in all the age groups were
satisfied with the park, but the most satisfied were those in the age class 41–50 years. The
respondents in the age class 18–30 years took the longest time to reach the park, because
they came from more distant places. Regarding sexes, significant differences were found
in levels of fatigue when reaching the park: women reported higher levels of fatigue than
men. The oldest men used the park more often (3.75
1.94 times a week), while the
oldest women used it less (2.33
1.22 times a week). Generally, the participants felt more
energetic and more peaceful after visiting the park.
Of the total of 383 participants, 232 (60.6%) usually practiced outdoor PA. Figure 1
shows the amount of PA practiced in the park and active commuting to reach the park
by sex and age classes. The figure shows that, generally, men practiced more PA than
women, except for the age group 61–70 years, in which women practiced more PA than
men. However, only men in the age class 18–30 years achieved the goal of 150 min/week
of moderate PA, on average, while men in the age class 61–70 years showed the lowest
PA level.
Figure 1. Amount of PA and active commuting in the park by sex and age classes.
Int. J. Environ. Res. Public Health 2022,19, 9248 8 of 15
Table 4. Descriptive statistics and ANOVA by sex, age groups, and interaction between sexes and age groups.
Females Males ANOVA
18–30 yrs 31–40 yrs 41–50 yrs 51–60 yrs 61–70 yrs 18–30 yrs 31–40 yrs 41–50 yrs 51–60 yrs 61–70 yrs Age Class Sex Age Class * Sex
Variable Mean
(SD) FpFpFp
Q2. Active commuting (min/week) 72.85
(48.25) 65.13
(42.27) 68.61
(50.63) 56.41
(46.67) 64.18
(43.41) 81.80
(47.31) 76.12
(56.43) 53.41
(42.26) 68.14
(34.00) 75.86
(38.80) 1.58 0.17 0.77 0.37 0.82 0.50
Q3. From 1 to 10, how tired were you when you reached the park?
(0.88) 1.94
(0.75) 1.57
(0.81) 2.53
(1.43) 2.58
(1.08) 1.53
(0.67) 1.42
(0.51) 1.13
(0.35) 1.10
(0.32) 1.40
(0.55) 2.45 0.04 34.64 0.00 1.57 0.18
Q4. How far (in meters, approximately) is your home from the park?
(3034.0) 2582.7
(5512.7) 2110.2
(4662.4) 1962.1
(2344.3) 2422.8
(2024.0) 2631.6
(2819.9) 2311.5
(1265.6) 1706.2
(1903.7) 3220.9
(3910.2) 2342.3
(3001.3) 0.80 0.53 0.00 0.97 0.76 0.55
Q8. How many times per week do you go to the park?
(1.54) 3.22
(1.57) 3.37
(1.62) 3.53
(1.95) 2.33
(1.22) 2.71
(1.44) 2.35
(1.42) 3.06
(1.59) 2.60
(1.57) 3.75
(1.94) 2.07 0.08 0.24 0.61 4.96 0.00
Q9. How many hours of PA do you practice at the park?
(0.61) 1.33
(0.49) 1.29
(0.73) 1.47
(0.64) 1.83
(1.70) 1.65
(0.63) 1.27
(0.45) 1.63
(0.67) 1.35
(0.57) 1.20
(0.45) 1.16 0.32 3.48 0.06 1.39 0.23
Q10. How often would you practice indoor PA if there wasn’t a park (h/week)?
(1.12) 2.11
(0.76) 1.94
(0.44) 1.91
(0.30) 2.00
(0.00) 2.57
(1.07) 2.45
(0.82) 2.19
(0.66) 2.11
(0.60) 2.67
(0.58) 3.42 0.01 2.50 0.11 0.65 0.62
Q11. Where do you like to exercise the most?
Indoor 2.54
(0.94) 3.19
(0.98) 2.90
(0.55) 2.55
(0.82) 2.14
(0.90) 2.30
(0.88) 2.48
(0.73) 2.63
(1.06) 2.00
(0.85) 3.00
(0.00) 2.40 0.05 0.97 0.32 1.34 0.25
Outdoor 3.00
(1.38) 2.89
(1.41) 2.04
(1.46) 2.05
(1.47) 2.50
(1.54) 2.58
(1.50) 2.66
(1.52) 2.50
(1.55) 2.56
(1.53) 2.71
(1.60) 1.51 0.19 0.08 0.77 1.12 0.34
Q13. Are you satisfied with this park? 4.20
(0.83) 4.11
(0.87) 4.42
(0.88) 4.29
(1.14) 4.38
(0.75) 3.78
(0.99) 4.08
(1.16) 4.42
(0.58) 4.50
(0.63) 3.77
(1.59) 3.33 0.01 2.12 0.14 1.75 0.13
Q14. I feel more energetic, after practicing PA in the park
(1.36) 3.72
(1.32) 3.57
(1.35) 3.94
(1.58) 3.34
(1.73) 3.08
(1.34) 3.10
(1.65) 3.25
(1.36) 3.45
(1.71) 3.46 (1.66) 0.51 0.19 2.52 0.11 0.69 0.59
Q15. I feel more peaceful, after visiting the park
(1.33) 3.69
(1.37) 3.55
(1.43) 4.09
(1.36) 3.69
(1.53) 3.98
(1.25) 3.35
(1.34) 3.88
(1.45) 3.32
(1.28) 3.85 (1.46) 0.24 0.91 0.02 0.87 3.32 0.01
Amount of PA (min/week) 79.76
(36.50) 80.00
(29.10) 77.37
(43.95) 88.00
(38.40) 110.00
(101.80) 98.75
(37.62) 76.00
(26.99) 97.50
(39.98) 80.87
(34.37) 72.00
(26.83) 0.62 0.65 0.09 0.76 2.18 0.07
PA and active commuting (min/week) 117.12
(73.32) 107.49
(63.33) 111.08
(76.15) 111.46
(78.14) 125.00
(91.51) 155.20
(69.21) 134.12
(75.18) 132.44
(63.95) 139.30
(62.09) 92.90
(55.30) 1.16 0.32 3.48 0.06 1.39 0.23
Note. F = F test, p=p-value, * = interaction between the two variables, yrs = years.
Int. J. Environ. Res. Public Health 2022,19, 9248 9 of 15
Considering only the amount of PA in the park, only seven participants (3.0%) achieved
the goal of the 150 min/week moderate PA. On the other hand, if the time to actively reach
the park, through walking, running, or bicycling, was considered as a part of PA, the
amount of PA increased, and the participants who achieved the goal of 150 min/week
increased to 118 (64.5%). Most of those who achieved the goal were men (n = 70, 59.3%),
and the most represented age class was 18–30 years (n = 50, 42.4%). Concerning people
who did not achieve 150 min/week, the largest number of these people reached the park by
walking, running or bicycling (n = 95, 83.3%), and only a few people used motor vehicles
(n = 19, 16.7%). Fifty-one percent of these participants were women (n = 59) and were in
the age class 18–30 years (n = 31, 27.2%).
A multiple regression model was carried out to quantify the relationship between the
dependent variable (total minutes of PA including active commuting) and the explanatory
variables. The VIF was less than 10 for all the variables considered, so there was no
multicollinearity. The results of the multiple regression are shown in Table 5.
Table 5. Multiple regression model for total minutes of PA.
Predictors βTp-Value
Sex (female) –0.11 0.12 0.90
BMI 0.04 0.51 0.61
Distance from the park 0.15 1.56 0.12
Times per week at the park 0.18 2.12 0.04
Age class
18–30 years –0.01 –0.08 0.93
31–40 years 0.01 0.06 0.95
41–50 years –0.01 –0.11 0.92
51–60 years 0.04 0.38 0.17
Student –0.05 –0.45 0.66
Employed 0.07 0.55 0.58
Unemployed –0.17 –1.45 0.15
Education level
High school 0.01 0.02 0.98
Bachelor’s degree 0.07 0.87 0.38
Master’s degree 0.08 0.93 0.36
Way to reach the park
Walking 0.14 1.19 0.24
Motor vehicle –0.36 –2.94 0.04
Running 0.22 1.98 0.04
Kind of PA at the park
Light running –0.13 –1.36 0.18
Outdoor fitness equipment 0.07 0.64 0.52
Skating 0.30 2.95 0.03
Walking 0.28 2.17 0.03
Football 0.06 0.68 0.49
Bicycling 0.07 0.67 0.50
Stretching 0.04 0.47 0.64
Adjusted R20.14
This model explained 14% of the variance. The number of visits per week tot the
park, reaching the park by running, and skating or walking at the park showed a positive
relationship with the total minutes of PA, while using a vehicle (car, scooter, or public
transport) showed a negative relationship.
Int. J. Environ. Res. Public Health 2022,19, 9248 10 of 15
4. Discussion
The purposes of the present study were to assess people’s motivations to use the
park, and among the motivation, particular attention should be paid to PA, to understand
how much park use affects PA levels. The final purpose was to evaluate how active
vehicle-free transportation (walking, jogging, bicycling) influences the achievement of
the recommended levels of PA. These aspects have become particularly important in
relation to the lifestyle changes imposed by COVID. Regarding the participants of the
present study, there were slightly more women than men. This is in accordance with the
results of other studies [
] which have reported that women have a greater willingness to
participate in surveys than men and have a greater engagement with the neighborhood
environment [
]. Regarding age classes, the oldest people presented the highest
values in weight, BMI, and overweight/obesity, highlighting the greatest health risk of
these groups, since overweight/obesity is a potential risk factor for the occurrence of
cardiovascular diseases [
], although their involvement in PA is a healthy habit to be
maintained and strengthened. The youngest age class is the group that took the most time
to reach the park. This is in accordance with previous studies, which have suggested that
young people are willing to walk for longer distances than the recommended 300 m, to
have access to green urban space, if parks have some attractive features [
]. At the same
time, the age class 18–30 years was the most likely to carry out PA, regardless of where it
takes place. Regarding the interaction between age classes and sexes, it is noteworthy that
men in the age class 61–70 years were the ones who used the park the most. According
to previous studies, people of the oldest age group usually have a better perception of
the green urban space and often spend their leisure time in this kind of environment [
On the contrary, in the present study, women aged 61–70 years had the lowest score for
time spent in the park. These data are in contrast with the study by de Vries et al. (2003),
which found that women over 65 generally showed a higher frequency of use of a park,
in comparison with men or people belonging to other age groups [
]. This result could
be linked to the COVID-19 pandemic situation, since the oldest people could have been
more afraid about going out and visiting public spaces, due fear of becoming infected with
the virus.
As regards the study’s first purpose, the two main motivations to reach the park
were to relax and to practice PA. The opportunity to perform PA, by promoting leisure
walking, walking through the space when running errands, active playing, and sports,
is another mechanism that has been proposed to explain the beneficial effects of a green
environment [
]. Several studies have observed the efficacy of outdoor PA, but
it is still unclear what might be the best kind of PA [
]. For this reason, we investigated
the relationship between BMI and PA, since the results are not consistent in the literature.
While some studies have suggested an inverse relationship between BMI and PA [
other studies have demonstrated a weaker association [
]. The present study did not
show any relationship between the two parameters (pvalue = 0.10), suggesting that the
practice of PA is independent of BMI.
Another motivation to reach the park was to relax. Although there is increasing lit-
erature about the beneficial effects of the outdoor natural environment, the mechanisms
that explain this relationship are still unclear. Thinking of the park as a place in which it is
possible to relax is consistent with the “restoration theory”, which explains the beneficial
effects by the intrinsic quality of the natural outdoor environment. So, health perception
and well-being are influenced by watching a green space [
]. The results of the
present study could be linked to other studies that have found that short-term exposure to
forests, urban parks, gardens, and other natural environment reduces stress and depres-
sive symptoms, restores attention fatigue, increases self-reported positive emotions, and
improves self-esteem, mood and perceived mental and physical health [
]. The
result relating to the use of the park to relax is important because it highlights how the
population perceives the use and the benefits of this park. It can be considered a “safe place”
in which they can stay and relax without other problems or thoughts, and it demonstrates
Int. J. Environ. Res. Public Health 2022,19, 9248 11 of 15
the success of the project carried out by the city of Bologna to improve the use of green
urban space [
]. After visiting the park, the largest part of the sample reported positive
sensations, such as feeling “more energetic”, and “more peaceful”, which are in accordance
with previous studies that observed a beneficial association between exposure to green
space and mental health, using a wide range of measures [
]. The largest proportion
of the participants who used the park to relax were women and people belonging to the
youngest age class group (18–30 years). The effects of urban parks could be especially
important for women [
] because they are disproportionately affected by common mental
health issues [40].
Regarding the second purpose of this study, 232 (60.6%) out of 383 participants usually
practiced outdoor PA. These data are in contrast with previous studies that found that parks
were generally underutilized to perform PA [
]. In this case, the park seemed to be a
facilitator of PA, due to the large numbers of people that used it as a training environment.
However, even in this study, the PA performed in the park was not sufficient to achieve
the goal of 150 min/week. In fact, when only PA in the park was considered, the majority
of the sample did not achieve the goal of 150 min/week. This could mean that people
did not do enough PA in the park, as reported in previous studies, showing that parks
are more of a destination for light activities and low levels of PA, rather than a venue for
moderate or vigorous PA [
], perhaps due to insufficient education regarding PA [
So, even if performing PA is one of the main motivations that drives people to use the
park, the level or the intensity of PA were still not sufficient. Moreover, considering the
third purpose of this study (to assess how active commuting influences the achievement of
recommended levels of PA), the scenario changes. In fact, considering active commuting as
a part of the PA, an increasing number of people who achieved the goal of recommended
PA was observed. Active commuting is an important aspect to consider for the daily level
of PA. Incorporating PA into daily life habits may make it easier to be physically active [
To our knowledge, even though the importance of active commuting is well established,
few studies have analyzed together the minutes to reach the place of training by active
commuting and the minutes of PA practiced. This result is particularly interesting because,
while the PA carried out in green urban space alone is not enough to reach the goal of
150 min/week, the combination of this PA with active commuting makes it possible to
reach this goal.
From the multiple regression, it emerged that the number of visits per week t at the
park had a positive relationship with the amount of PA. If people have to walk more times
in a week to reach the park, obviously their amount of PA increases. Regarding the way
to reach the park, running was mostly associated with the total minutes of PA, while the
use of motor vehicles presented a negative association. In any case, it is interesting to note
that only 13.6% (n = 52) of the participants reached the park by motor vehicle. This pattern
depends on the good walkability to reach the Arcoveggio park, thus providing evidence in
favor of Bologna city policies.
This study is not without limits: the anthropometric measurements were self-reported
by participants, and, in addition, this study was carried out only in one park in the city
of Bologna, so the continuation of the study in other city parks may lead to a better
understanding of the analyzed aspects. In addition, behavioral heterogeneity was not
considered in the present study. For future research, it could be an important issue to
consider [6668].
This study also has numerous strengths. There is an increasing interest in active
commuting and its importance in combination with PA. Active commuting is not only
considered “an active way” to reach a place but it is considered a part of PA. To our
knowledge, there have been no similar studies in the Italian setting, and this could be an
important forerunner for future research.
Int. J. Environ. Res. Public Health 2022,19, 9248 12 of 15
5. Conclusions
Understanding the motivations that lead people to use an urban park is fundamental,
since this allows the design of an appropriate project to encourage the use of this environ-
ment. At the same time, it is important to create a successful strategy to help the population
to achieve the recommended levels of PA. The results of the present study suggest that
there are two main reasons to visit the park, to relax and to practice PA. These are important
aspects because they are useful to create appropriate projects or events to improve the use
of green urban space. People showed that they were influenced by the restorative effects of
the park and understood the importance of performing PA. Regarding PA, the people in the
present study did not reach the minimum levels recommended by the WHO inside the park,
but when active commuting was added, more people achieved the goal. This indicates the
great importance of active transportation in an urban environment. Urban dwellers are
largely physically inactive, and active methods of transport could be an important helper
to include in their daily life habits. This represents an important point of reflection and may
suggest the need to promote active commuting to raise awareness of the population about
this important topic. In addition, it could be helpful to create a type of program for urban
park users, such as putting signs inside the park, with tips and information about different
kinds of outdoor exercise or examples of possible exercises (with explanatory drawings),
facilitating the practice of more intensive PA.
Supplementary Materials:
The following supporting information can be downloaded at: https:
//, Figure S1: Park and Recreation Users Survey
Anonymous Questionnaire.
Author Contributions:
Conceptualization, A.L. and S.T.; methodology, S.T. and P.M.L.; software,
N.R. and L.Z.; validation, N.R., L.Z. and E.G.-R.; formal analysis, A.G. and P.M.L.; investigation, S.M.;
resources, A.L.; data curation, S.M.; writing—original draft preparation, A.G.; writing—review and
editing, A.L., P.M.L., S.M., N.R., E.G.-R., L.Z. and S.T.; visualization, E.G.-R.; supervision, S.T.; project
administration, A.G. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
The study was conducted according to the guidelines of the
Declaration of Helsinki and approved by the Bioethics Committee of the University of Bologna (prot.
N. 022254).
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement:
Authors will provide data to all interested parties upon reasonable request.
Conflicts of Interest: The authors declare no conflict of interest.
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... Many studies have attempted to determine the impact of the COVID-19 pandemic on various areas of life. The COVID-19 pandemic, through a series of introduced restrictions and limitations, has changed the way people use public space; this has become particularly apparent in the case of green spaces [25][26][27][28][29][30][31][32]. Urban open space played a positive role in allowing people to stay connected with their neighbors, to feel reassured, and to maintain or increase their physical activity levels during the pandemic. ...
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As the COVID-19 pandemic continues, an increasing number of different research studies focusing on various aspects of the pandemic are emerging. Most of the studies focus on the medical aspects of the pandemic, as well as on the impact of COVID-19 on various areas of life; less emphasis is put on analyzing the influence of socio-environmental factors on the spread of the pandemic. In this paper, using the geographically weighted regression method, the extent to which demographic, social, and environmental factors explain the number of cases of SARS-CoV-2 is explored. The research was performed for the case-study area of Poland, considering the administrative division of the country into counties. The results showed that the demographic factors best explained the number of cases of SARS-CoV-2; the social factors explained it to a medium degree; and the environmental factors explained it to the lowest degree. Urban population and the associated higher amount and intensity of human contact are the most influential factors in the development of the COVID-19 pandemic. The analysis of the factors related to the areas burdened by social problems resulting primarily from the economic exclusion revealed that poverty-burdened areas are highly vulnerable to the development of the COVID-19 pandemic. Using maps of the local R2 it was possible to visualize how the relationships between the explanatory variables (for this research—demographic, social, and environmental factors) and the dependent variable (number of cases of SARS-CoV-2) vary across the study area. Through the GWR method, counties were identified as particularly vulnerable to the pandemic because of the problem of economic exclusion. Considering that the COVID-19 pandemic is still ongoing, the results obtained may be useful for local authorities in developing strategies to counter the pandemic.
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The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system. By analyzing the impact of the pandemic on the transportation system, the impact of the pandemic on the social economy can be reflected to a certain extent, and the effect of anti-pandemic policy implementation can also be evaluated. In addition, the analysis results are expected to provide support for policy optimization. Currently, most of the relevant studies analyze the impact of the pandemic on the overall transportation system from the macro perspective, while few studies quantitatively analyze the impact of the pandemic on individual spatiotemporal travel behavior. Based on the license plate recognition (LPR) data, this paper analyzes the spatiotemporal travel patterns of travelers in each stage of the pandemic progress, quantifies the change of travelers' spatiotemporal behaviors, and analyzes the adjustment of travelers' behaviors under the influence of the pandemic. There are three different behavior adjustment strategies under the influence of the pandemic, and the behavior adjustment is related to the individual's past travel habits. The paper quantitatively assesses the impact of the COVID-19 pandemic on individual travel behavior. And the method proposed in this paper can be used to quantitatively assess the impact of any long-term emergency on individual micro travel behavior.
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Green spaces are defined as open spaces of ground, covered by vegetation, including parks and gardens. This kind of environment is linked to many positive effects and its importance is growing due to increasing urbanization. Understanding what drives people to use green urban space is fundamental to creating appropriate campaigns to develop the use of such spaces and improve the citizens' quality of life. A questionnaire on the attitude towards green space was developed and submitted to people from two Italian regions. Emilia-Romagna and Veneto are two regions in the North of Italy with different territorial policies. Three hundred and ten surveys were collected (167 in Emilia-Romagna and 143 in Veneto). Significant differences were observed between regions, age groups and in relation to the kind of work (p < 0.05). People from Emilia-Roma-gna have higher scores of attitudes towards green space than people from Veneto, underlining the importance of territorial policies. Moreover, younger participants (18-30 years) seem to be less attracted to green urban space. Being an employee seems to influence the attitude towards green space. Particular attention should be given to subjects of the younger age groups and to the number of hours spent at work. This could be an important element for future research, so that political action can be implemented with these categories in mind.
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This systematic review aimed to investigate the type of physical activity carried out in green urban spaces by the adult population and to value its impact on the population's health. Additionally, another purpose was to examine if the presence of outdoor gyms in green urban spaces can promote participation in physical activity among adults. Searches of electronic databases, with no time restrictions and up to June 2020, resulted in 10 studies meeting the inclusion criteria. A quantitative assessment is reported as effect size. Many people practiced walking activity as a workout, which showed improvements in health. Walking is the most popular type of training due to its easy accessibility and it not requiring equipment or special skills. Outdoor fitness equipment has been installed in an increasing number of parks and has become very popular worldwide. Further, outdoor fitness equipment provides free access to fitness training and seems to promote physical activity in healthy adults. However, other studies about outdoor fitness equipment efficiency are needed. People living near to equipped areas are more likely to perform outdoor fitness than those who live further away. The most common training programs performed in green urban spaces included exercises with free and easy access, able to promote physical health and perception.
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This study aims to examine the extent to which SARS-Cov-2 and associated governmental interventions to mitigate virus transmission has affected daily travel decisions in Bangladesh. A questionnaire survey was used to record opinions of respondents hailing from diverse socioeconomic backgrounds on trip number and mode preferences for a variety of trip purposes for "before" and "during" COVID-19 situation. This was used to assess changes in (i) trip frequencies, and (ii) travel mode preferences using contingency tables, ordinal logistic regression and Sankey diagrams. Analyses revealed that COVID-19 caused large variation in mode preferences but small variation in trip frequencies. Males still go outside for work and shopping, putting them at greater risk than females. COVID-19 has drastically cut recreational trips, but not so many work trips. Although online work or education (950%) and shopping (170%) has risen, this seems to be limited to urban areas. Besides, buses continue to be preferred the most during pandemic for trips involving short distance recreation (26.75%), markets (43.18%), and long distance recreation (35.66%). Results suggest the lack of online penetration in rural and suburban areas have prevented worktrip reductions in those places, putting the inhabitants at heightened risk from virus. Moreover, majority of the people continue to use buses at the expense of their health for lack of cheaper alternatives. Results imply that the government need to ensure proper hygiene practices in public transit and non-motorised paratransit vehicles. Moreover, Information and Communication Technology (ICT), pedestrian and bicycle facilities need to be improved.
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Objectives To describe new WHO 2020 guidelines on physical activity and sedentary behaviour. Methods The guidelines were developed in accordance with WHO protocols. An expert Guideline Development Group reviewed evidence to assess associations between physical activity and sedentary behaviour for an agreed set of health outcomes and population groups. The assessment used and systematically updated recent relevant systematic reviews; new primary reviews addressed additional health outcomes or subpopulations. Results The new guidelines address children, adolescents, adults, older adults and include new specific recommendations for pregnant and postpartum women and people living with chronic conditions or disability. All adults should undertake 150–300 min of moderate-intensity, or 75–150 min of vigorous-intensity physical activity, or some equivalent combination of moderate-intensity and vigorous-intensity aerobic physical activity, per week. Among children and adolescents, an average of 60 min/day of moderate-to-vigorous intensity aerobic physical activity across the week provides health benefits. The guidelines recommend regular muscle-strengthening activity for all age groups. Additionally, reducing sedentary behaviours is recommended across all age groups and abilities, although evidence was insufficient to quantify a sedentary behaviour threshold. Conclusion These 2020 WHO guidelines update previous WHO recommendations released in 2010. They reaffirm messages that some physical activity is better than none, that more physical activity is better for optimal health outcomes and provide a new recommendation on reducing sedentary behaviours. These guidelines highlight the importance of regularly undertaking both aerobic and muscle strengthening activities and for the first time, there are specific recommendations for specific populations including for pregnant and postpartum women and people living with chronic conditions or disability. These guidelines should be used to inform national health policies aligned with the WHO Global Action Plan on Physical Activity 2018–2030 and to strengthen surveillance systems that track progress towards national and global targets.
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Promoting the use of green space is a fundamental way to improve physical and mental health and to enhance the quality of life of urban residents. In response to increasing demand for green space in cities, the impact of perception of green space for health promotion on willingness to use parks and actual use among young urban residents was investigated in this study. A total of 1135 young residents (ages 18–35) in three cities in China were surveyed by online questionnaire. A group of multiple regression models was constructed to investigate the influencing perception factors of participants’ willingness to use parks and actual use. The results revealed that the young residents’ perception of green space components for health promotion (green space access, types, sizes, plants, water, sensory features, microclimate environments and amenity facilities) had a greater effect on their willingness to use parks and to promote health, while it was less influential with respect to their actual park use behavior (frequency and duration). Among these variables, green space access is a critical concern for willingness to use toward parks. The disparities of perception of green space for health promotion effect on willingness to use a park and actual use provide a better understanding of the psychological factors affecting park use among young residents. The findings also provided some implications for public health policymakers, urban planners and landscape architects in designing parks to encourage visitation by young people.
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There is a close relationship between urban green space and the physical and mental health of individuals. Most previous studies have discussed the impact of the structure of green space and its elements. This study focused on the emotional changes caused by common behaviors in urban green space (walking and sitting). We recruited 40 college students and randomly assigned them to walking and sitting groups (20 students per group). The two groups performed the same 8-min high-pressure learning task indoors and then performed 8-min recovery activities in a simulated urban green space (a bamboo-lawn space). We used the Emotiv EPOC+ EEG headset to dynamically measure six neural emotional parameters: “engagement,” “valence,” “meditation,” “frustration,” “focus,” and “excitement.” We conducted a pretest and posttest and used analysis of covariance (ANCOVA) to analyze the posttest data (with the pretest data as covariates). The results of the comparison of the two behaviors showed that the “valence” and “meditation” values of the walking group were higher than those of the sitting group, which suggests that walking in urban green space is more favorable for stress reduction. The sitting group had a higher “focus” value than did the walking group, which suggests that sitting in urban green space is better for attention restoration. The results of this study can provide guidance for urban green space planning and design as well as health guidance for urban residents.
Background The prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear. Objective This study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS). Methods We used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts. Results We identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI –823 to –21) and 1437 (95% CI –2084 to –790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI –773 to 10) and group 3 took 1120 (95% CI –1766 to –475) fewer steps, compared with group 1. Conclusions In this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.