Using Observational Methods to Evaluate Public Open Spaces and ...

Journal of Physical Activity and Health, 2010, 7(Suppl 2), S146-S154 © 2010 Human Kinetics, Inc.

Using Observational Methods to Evaluate Public Open Spaces and Physical Activity in Brazil Adriano Akira Ferreira Hino, Rodrigo S. Reis, Isabela C. Ribeiro, Diana C. Parra, Ross C. Brownson, and Rogerio C. Fermino Background: Open public spaces have been identified as important facilities to promote physical activity (PA) at the community level. The main goals of this study are to describe open public spaces user’s characteristics and to explore to what extent these characteristics are associated with PA behavior. Methods: A system of direct observation was used to evaluate the PA levels on parks and squares (smaller parks) and users’s characteristics (gender and age). The 4 parks and 4 squares observed were selected from neighborhoods with different socioeconomic status and environmental characteristics. The settings were observed 3 times a day, 6 days per week, during 2 weeks. Results: More men than women were observed in parks (63.1%) and squares (70.0%) as well as more adults and adolescents than older adults and children. Users were more physically active in parks (men = 34.1%, women = 36.1%) than in squares (men = 25.5%, women 22.8%). Conclusions: The characteristics of public open spaces may affect PA in the observed places. Initiatives to improve PA levels in community settings should consider users’ characteristics and preferences to be more effective and reach a larger number of people. Keywords: physical activity, parks, leisure, measurement, observation Regular physical activity (PA) has been recommended to reduce the risk of chronic diseases and to promote physical and psychological well-being.1–3 In this sense, one of the current priorities for public health organizations is the promotion of physical activity.2 Although there is evidence about the benefits of PA, there is a large prevalence of physical inactivity in both developed and developing countries.4 According to data from the Risk Factors Surveillance System and Protection for Chronic Diseases from Brazil, 24.9 to 32.8% of the adult population (between 18 and 60 years old) in Brazilian capitals are inactive.5 Recent studies have shown that the built environment can influence the practice of regular PA.6,7 Saelens and Handy6 found a positive association between walking as an alternative to other transportation and certain characteristics of the environment such as population density, distance to nonresidential destinations, land use mix, connectivity to destinations, and access to parks and open Hino, Reis, Ribeiro, and Fermino are with the Dept of Physical Education, Pontific Catholic University of Paraná, Curitiba, Brazil. Parra and Brownson are with the Prevention Research Center in St. Louis, George Warren Brown School of Social Work, Washington University in St. Louis. Brownson is also with the Alvin J. Siteman Cancer Center, Washington University School of Medicine, Washington University in St. Louis.

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spaces. Some studies7–11 have also shown associations between proximity and availability of equipments within open public spaces and higher levels of PA. This evidence has increased the importance of public open spaces such as parks to increase PA levels in the community.12–14 One way to evaluate park use, PA levels and users’s characteristics is the observation of public spaces using the System for Observing Play Recreation in Communities (SOPARC).15 Several studies have been conducted using this system in the United States.13,15,16 SOPARC has not been used with Latin American populations, and despite evidence of open spaces’ effects on PA, systematic observations are sparse in the region. Documenting the type of PA performed at parks, its use, and the preferences in terms of age groups and gender can provide useful information to public park administrators and establish priorities to promote PA. This paper is part of Project GUIA (Guide for Useful Interventions for Physical Activity in Brazil and Latin America). The project is coordinated by the Prevention Research Center in St. Louis and the Centers for Disease Control and Prevention, and analyzes and disseminates evidence-based PA strategies in Latin America, especially in Brazil. Project GUIA’s first phase examined community-based PA interventions in Latin America and identified 2 interventions to be evaluated in the second phase. During phase one, project GUIA found 3 new promising intervention categories to increase population levels

Users Characteristics of Parks and Squares   S147

of PA.17 Among these new interventions are “delivery of short PA-related messages” and “PA classes in community settings” used to promote PA and usually delivered through public open spaces. Results from one of the interventions evaluated in project GUIA second phase, “Academia da Cidade,” were published elsewhere.17 The second community intervention evaluated is located in the city of Curitiba, in the southern region of the country. This paper presents the results from a systematic observation conducted in parks in the City of Curitiba, during phase 2 of Project GUIA. Despite the recognized and documented existence of PA programs in the city18–20 and the great potential that parks and squares have to promote PA, no evaluation using systematic observation has been done in Curitiba and it is unknown how the characteristics of these places can affect PA levels. Squares are small parks or plazas with a mean area of 6217m2 of which approximately 70% are equipped with some type of PA facilities such as walking/running tracks, sports courts or stretching/ strength areas.21 These characteristics make the squares suitable settings for PA practice and promotion. A study conducted by the Municipal Health Secretary in 2006 showed that 79.6% of the adult population in Curitiba reported having some type of place to practice PA near the residence, including a square.18 Thus, the current study aims to describe the characteristics of parks and squares users and to explore how these characteristics are associated with the practice of PA in these settings.

Methods Curitiba is the capital of the Paraná state located in the southern region of Brazil, with a population of approximately 1,797,408 inhabitants,22 of which 52% are women.21 Curitiba is a city recognized for its health promotion policies and the special attention to green spaces as means for sustainable development.20 To date there are 18 parks (18,580,617 m2), 33 preservation areas (19,251,878 m2), and 443 squares (2,750,740 m2) dispersed in the 75 neighborhoods of Curitiba.21 Currently, 27 “Sports and Recreational Centers” are distributed throughout the city. These centers are the settings where organized activities are offered to children, adolescents, adults and older adults. These centers house organized and planned activities offered to children, adolescents, adults and older adults.

Observation of Users We used the SOPARC (System for Observing Play and Recreation in Communities) methodology to characterize gender, age and PA levels of parks and squares users. SOPARC was developed to obtain direct information about the PA level of community public spaces users, their characteristics and the contexts in which PA occurs.15 The tool is based on momentary time sampling

to make systematic observations (scans) of target-areas. Target-areas are predetermined observation areas where park users may engage in PA, such as courts, walking or biking trails, playgrounds, etc.

Scan To assess user’s characteristics, the SOPARC system uses momentary time sampling to make systematic scans (an observation sweep moving from left to right) of each subject within target areas.15 PA was coded as sedentary (lying down, sitting or standing), walking (light walking or moving) or vigorous (moderate or vigorous walking, running, strength activities). Age groups were divided into children, adolescents, adults and older adults. PA levels and age group scans were done separately for males and females to be possible identify the possible difference between sexes according the original SOPARC protocol,15 for example, in the first scan observers would record activity level and age only for males, and in the second scan only for females.

Schedule All target areas were assessed during 3 different onehour periods (7:00 AM, 11:00 AM, and 5:00 PM). Data collection was conducted between March and April of 2008. Each park/square was observed for 2 weeks, including both weekends and all weekdays but Fridays was not observed to be possible identify accurately the difference between weekend and weekdays a total of 12 days of observation.

Training Observers Observations were done by 16 trained observers under the supervision of 2 field coordinators. The training was conducted during a 2-day workshop and included classes designed to familiarize trainees with operational definitions, instrument notation, coding conventions and categorization of the PA levels and age groups. Trainees practiced coding and received feedback on their scoring using examples contained in the SOPARC DVD training provided by SOPARC author. Field-based observations during the morning and afternoon hours were conducted in the second day of training using mechanic counters. After the field training, pairs of observers carried 10 more hours of data collection to test for interobserver agreement. Ninety percent agreement was obtained for both PA levels and age group categories.

Parks and Squares Selection Because of the large number of parks and squares in the city, it was necessary to develop a selection method that allowed identifying those parks and squares that could be evaluated. We first classified all the 75 neighborhoods from the city of Curitiba according to the availability

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of facilities for PA, using information provided by the Urban Planning and Research Institute (IPPUC).21 The characteristics used for this classification were park density (park area/total neighborhood area), square density (squares area/total neighborhood area), bike length density (bike lanes length/total neighborhood area) and number of sports and recreational centers per neighborhood. This information was corrected by neighborhood population density. Neighborhoods were then classified by the median income according to the National Institute for Geography and Statistics information provided by IPPUC.21 As a result, all neighborhoods were classified into high, medium and low quality of environment (ENV) for PA, and high, medium and low socioeconomic status (SES) all distributed in 9 different clusters. Neighborhoods located in the 4 extreme clusters (High ENV and High SES; High ENV and Low SES; Low ENV and High SES; and Low ENV and Low SES) were screened to identify all parks and squares available in those areas. Finally, a list with all parks and squares in the selected extreme clusters was sent to program coordinators from the Municipal Secretary of Sports and Leisure and the Municipal Secretary of Health, the 2 secretaries responsible for the majority of the PA interventions in Curitiba. The coordinators provided information on settings where PA programs and activities were more likely to occur. After 3 rounds of consulting, 4 parks and 4 squares were selected for the evaluation.

Target Areas Assessment Before data collection, all potential target areas for leisure PA in each selected park and square were visited, measured, and mapped. Contextual characteristics of the target areas were also collected and coded before data collection including type of facility (court space, track, field,

gymnasium, grass court, etc), permanent facilities (lines painted on the ground, football goal-posts, basketball hoops, etc) and surface area (grass, sand, concrete, etc). Three observers who were previously trained conducted this assessment; inconsistencies were discussed until they reached agreement. The SOPARC protocol was then applied for data collection.15

Statistical Analysis To describe contextual and user’s characteristics, descriptive statistics were used (frequency and relative frequency distribution, mean, and standard deviation). Target areas (quantity, size, and type) and user’s characteristics (gender, age group and PA level) were analyzed by type of public space (parks and squares). Users’s characteristics were also analyzed by days of the week and period (time) of the day. All comparisons were tested using Chi-square test considering 5% of significance using the SPSS version 11.0 and Microsoft Excel version 2007 for Microsoft.

Results A total of 109 target areas were mapped and observed in 4 parks and 4 squares during 2 weeks (Table 1). Thirty four target areas and 5 walking/running tracks were observed in parks. The average size of target areas was 1,183.4 m2 (ranging from 78.5 m2 to 7,480.0 m2). Sports areas were the most common target area found (56.4%), followed by playground areas (15.4%) and walking/running tracks (13.1%). In squares, 66 target areas were observed and 4 walking/running tracks. The average size of these target areas was 310.1 m2 (ranging from 33.7 m2 to 1,132.0 m2). The majority of target areas in squares were sports areas (51.4%) followed by playground areas (25.7%) and others (10%).

Table 1  Characteristics of Parks and Squares Target Areas Characteristics

Parks (n = 4)

Squares (n = 4)

Walking/running tracks (number)

5

4

Target area (number)

34

66

1183.4

310.1

Target area size (m2)   Average   Standard Deviation

1605.3

218.5

78.5–7480.0

33.7–1132.0

  Sports areas

56.4

51.4

  Strength/stretching exercise areas

7.7

7.1

  Open areas

7.7

0.0

  Walking/running track

12.8

5.7

  Others (skating, athletics, roller, others)

0.0

10.0

  Playground areas

15.4

25.7

  Minimum—Maximum Target area type (%)

Users Characteristics of Parks and Squares   S149

A total of 5536 individuals were observed in parks (63.1% men) and 2401 in squares (70% men). Individuals in parks were less sedentary (women = 22.8%, men = 25.6%) than in squares (women = 36.1%, men = 34.1%). More women were observed walking in the parks (32.2%) than in the squares (15.6%), while more men were vigorously active in parks (47.4%) when compared with squares (38%) (Figure 1). Overall, we observed more adults in parks (women = 67.6%, men = 60.4%) and squares (women = 55.4%, men 39.1%) than other age groups (Table 2). More male adolescents (17.9%) were observed in parks as compared with females (11%). In squares, 55.4% of users were adult females and 17.8% were adolescent females. Among men, 39.1% were adults and 37.2% were adolescents. In parks, more adults were observed during weekdays (women = 78.6%, men = 64.9%) as compared with weekend days (women = 60.5%, men = 57.3%). More female children and adolescents were observed in weekend days (children = 19.5%, adolescents = 14.3%) than in weekdays (children = 7.8%, adolescents = 5.9%). In squares, the proportions of children, adolescents, and adults were similar during weekdays and weekend days. Older adult women were observed more often during weekdays (15.3%) as compared with weekend days (9.3%). Among park users observers found more children at 11:00 AM (women = 19.3%, men = 21.6%) and adolescents at 5:00 PM (women = 17.3%, men = 28.4%), while adults (women = 81%, men = 82.5%) and older adults (women = 14.7, men = 14.4%) were more frequently observed at 7:00 AM. Users of squares followed the same pattern. Among park users, more people were vigorously active during weekdays (women = 59.3%, men = 57.9%) as compared with weekend days (women = 35.8%, men = 40.3%) (Table 3). Women were more sedentary at 11:00 AM (26.2%), walked more at 5:00 PM (37.8%), and were

more vigorously active in the morning period (7:00 AM) (67%). A similar pattern was observed among men, with the exception of walking, which had a higher frequency at 11:00 AM (30.7%). Users of squares were more sedentary (women = 48.2%, men = 39.3%) and walked more (women = 18.4%, men = 28.8%) during weekend days, but during weekdays, users were more vigorously active (women = 58.8%, men = 45.6%). In terms of period of the day, vigorous activity was more frequent in the morning (7:00 AM) for both women (81.4%) and men (76.1%).

Discussion This study aimed to describe user characteristics and PA levels in parks and squares in Curitiba, Brazil. Adults and men were the groups most frequently observed. Number of users observed was different according to gender and type of location, parks, or squares. Low PA levels were more observed in parks than squares and vigorous activity was frequent during weekdays and also during morning periods in both parks and squares. According to a population study of the Brazilian state capitals, walking is the most common type of PA during leisure time both among men (28%) and women (61%).23 Despite the fact that the cost benefit of this types of structures has already been demonstrated,24,25 we found walking/running tracks not to be the most present structures. Higher proportions of men were observed both in parks and squares. Various studies in the literature support these findings.11,19,21,31 Reed et al16 highlight that although census data show 51% of the population residing in the studied areas as females, they represent only 37% of parks users. A similar pattern was observed in this study. Although the proportion of men and women in the city is relatively the same (52 and 48%, respectively),21 a higher proportion of men was observed in the target evaluation

Figure 1 — Physical activity levels in parks and squares according to gender.

7.7

19.4

  Weekdays (%)

* P < .001.

Total

14.8

16.0

  5–6 PM (%)

  χ2 test value

0.0

19.3

  7–8 AM (%)

  11–12 AM (%)

Day period

  χ2 test value

Parks (n = 4) Men (n = 3,495)

Women (n = 721)

Squares (n = 4) Men (n = 1,680)

11.0

125.0*

17.3

7.7

4.3

101.8*

14.3

5.9

67.6

63.9

66.1

81.0

60.5

78.6

6.6

2.8

7.0

14.7

5.8

7.8

13.8

11.6

21.5

0.4

19.3

5.6

17.9

420.3*

28.4

11.3

2.7

181.7*

18.5

17.1

60.4

54.2

59.3

82.5

57.3

64.9

7.9

5.8

7.9

14.4

4.9

12.4

13.7

17.5

19.2

0.0

13.4

14.0

5.8

17.8

130.5*

26.7

19.2

1.1

19.3

16.9

55.4

49.0

52.8

69.5

58.0

53.8

13.1

6.8

8.8

29.4

9.3

15.3

15.6

16.3

20.0

0.0

17.6

14.3

2.5

37.2

376.4*

49.9

27.8

5.2

34.9

38.6

39.1

31.1

43.2

66.0

40.0

38.6

8.1

2.7

9.0

31.5

7.5

8.5

Older Older Older Older Children Adolescents Adults adults Children Adolescents Adults adults Children Adolescents Adults adults Children Adolescents Adults adults

  Weekend days (%)

Week period

Period

Women (n = 2,041)

Table 2  Characteristics of Parks and Squares Users According to Day of the Week and Period of the Day

S150

S151

24.5

  Weekend days

26.2 22.9

  11–12 AM

  5–6 PM

*P < .001.

2

  χ test value

13.4

  7–8 AM

Day period

2

  χ test value

20.3

Sedentary

  Weekdays

Week period

Period

125.0*

37.8

31.4

19.6

119.7*

39.7

20.4

Walking

39.3

42.4

67.0

35.8

59.3

26.6

28.0

16.3

26.4

24.5

420.3*

28.8

30.6

11.7

133.8*

33.3

17.6

Walking

Men (n = 3495) Sedentary

Parks (n = 4) Vigorous

Women (n = 2041)

44.6

41.4

72.0

40.3

57.9

Vigorous

44.9

46.8

6.2

48.2

27.5

Sedentary

130.5*

19.9

12.9

12.4

46.4*

18.4

13.7

Walking

35.2

40.3

81.4

33.4

58.8

34.7

40.9

12.2

39.2

27.5

376.4*

34.0

23.3

11.7

37.5*

28.8

26.9

Walking

Men (n = 1680) Sedentary

Squares (n = 4) Vigorous

Women (n = 721)

31.3

35.8

76.1

32.0

45.6

Vigorous

Table 3  Physical Activity Level in Parks and Squares According to Day of the Week and Period of the Day, by Gender (Relative Frequency)

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areas. This discrepancy could be explained by the type of areas available in the observation sites: 56.4% and 51.4% of parks and squares areas, respectively, were designed for structured sport activities (football, volleyball, basketball, etc.), while a smaller proportion of the areas were intended for walking/running (parks = 12.8%, squares = 5.7%). Evidence shows that in Brazil men prefer to play soccer during leisure time, while women prefer to walk.23 These characteristics could partially explain the larger number of men as compared with women in the studied settings.16 Regardless of gender, people tend to be more sedentary in the squares when compared with parks. One of the possible explanations is the presence of fewer walking and running trails in the squares than in parks. The presence of walking trails has been associated with higher levels of PA26 as well as higher use.13,16Another explanation is the higher number of playgrounds in the squares, taking into account that children need to be accompanied by an adult who the majority of times remains seated or standing. This study found that women were more vigorously active in the squares than men, and no significant differences were found in parks. This evidence contradicts findings from the majority of studies conducted in this field in the United States, which indicates that men are more active than women in places that are comparable to the squares in Curitiba. McKenzie et al15 found that men were more physically active than women and almost twice as much involved in vigorous PA (18.8% versus 10.2% for females). Reed et al16 and Cohen et al13 also found that men were 2 times more engaged in vigorous activities when compared with women (42% versus 20%; 19% versus 10%). This study found that parks and squares were predominantly used more by adults. Users tend to visit more frequently in the morning periods. This evidence matches what has been found by other studies in the United States.13,16 Although more adults were observed in squares, the proportion of teenager users was almost the same, and it was higher for males in the afternoon periods. Squares might be more easily accessible to teenagers who do not drive, because they are found in larger numbers and are more evenly distributed around the city as compared with parks. In a study conducted among 1718 adolescents in Curitiba, Reis et al26 reported that perception of lack of spaces and lack of adequate equipment for PA was associated with a lower likelihood of open public spaces use.27 For adults and teenagers there was little variation in terms of parks and squares use during weekdays or weekend days. Among children the frequency of park use was higher during the weekends as compared with weekdays. In addition, higher accessibility to the squares seems to favor its utilization by children, considering that parents do not need to cover long distances to accompany their children in the mornings and late afternoons. These periods are those typically used by parents and caregivers to take children to parks and squares in Brazil. In

fact, studies have shown that the proximity to recreation areas11,28 and type of structures available in these areas29 are positively associated with a higher level of PA among children. The proportions of physically active and sedentary individuals vary considerably according to the periods of the day and the days of the week. Mornings and weekdays presented a higher proportion of vigorously active people than other periods of the day or weekend days. Different characteristics in these spaces did not seem to affect this pattern. However, individuals tend to be more sedentary at noon and walk more during late afternoon. A few limitations of our study should be noted. Firstly the cross sectional design employed in this study does not provide causal relationships in all significant associations found. Secondly, all locations are in the city of Curitiba, Brazil, and were observed in the autumn which comprises their own environmental, cultural, political, and social characteristics. For example, the subtropical humid climate of the city provides mild summers and relatively cold winters, but generally, the climate is quite pleasant. However, in this season, the daily variation of temperature is more intense and frequent, which could prevent the practice of PA during all day in open spaces This study has several strengths to be highlighted. Although SOPARC is based on momentary samples, providing only instantaneous information about the environment, we conducted a systematic number of observations increasing the validity of the measures.15 The observers were rigorously trained to achieve a high inter observer agreement level, providing adequate confidence on the measures. Although some information about parks usage and its association with PA levels is currently available this is the first study conducted in a developing country.

Conclusion Specific information on park users and the context in which they are physically active can be an important strategy for city planners and staff responsible for designing and implementing PA programs to better target population needs and preferences.15 Between 79.5% and 88.7% of the population in Brazil is inactive during leisure time.5 The lack of resources to attend gymnasiums and other paid PA facilities is one of the main barriers for PA.30 In this sense, the creation and improvement of public spaces for leisure activities such as parks and squares can be an important strategy for the promotion of PA. Public parks play an important role in facilitating PA and increasing social interaction between individuals.12,13 According to the evidence from the 8 public open spaces observed in this study, officials who are responsible for PA promotion should consider the time and day of the week when implementing programs to increase their effectiveness. Programs targeting children could be offered on the weekends in the early afternoon period, while those targeting older adults should be organized on the weekdays during the morning periods. Further studies should explore what specific characteristics of the parks

Users Characteristics of Parks and Squares   S153

and squares are associated with specific age groups so that future interventions can increase the participation in physical activities in open spaces according to its characteristics. Longitudinal research is needed to increase the strength of the evidence in studies about parks and PA. Programs to promote PA should take into account the preferences and differences among target populations, and focus on children and older adults—populations observed the less in the current study. Acknowledgments This study was funded through the Centers for Disease Control and Prevention contract U48/DP000060-01 (Prevention Research Centers Program). The authors are thankful for the contribution of staff from Curitiba’s Municipal Secretaries of Sport & Leisure, Health, Education, Urban Planning, Transportation, Social Action, and Environment, particularly the program coordinators Marcia Krempel (SMS) and Dalton Grande (SMEL). We are also grateful for the administrative support of Madalena Soares, Diva Brunieri and the Research Group of Physical Activity and Quality of Life (GPAQ).

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