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Examining of Socio-Economic Status (SES) of participants in Tehran parks

Dr. Mohsen Shafiei1, Asistant professor of Islamic Azad University(IAU)- Islamshahr branch

ABSRACT:

We know that participating in physical activity is one of the main factors to maintain people and our society healthy, accordingly we need some information to make facilitate participating in these kind of activities for instance; social level of participants (job category, educational level, region of residency), economic status (yearly income, type of residency such as landlord or leaseholder, bungalow or apartment, types of transportation, types of using civil facilities, health care, etc).

In order to determine the Socio-Economic Status (SES) of participants in park activities, 10 percents of total people (were about 900) from all geographical regions of Tehran who had taken part in park activities regularly, were selected randomly and a suitable questionnaire which made by researcher, distributed among them. The results were as follow:

1- 27.9% of subjects were in age group of 36-45 years old as the major frequency and 6.6% of them as the minor frequency were above 66 years old.

2- 78.6% of subjects as a majority group were landlord and 4.6% of them as a minority group were leaseholder.

3- About 90% of subjects were married and just 10% of them were single.

4- In respect of SES, 75% of subjects were from the medium level, and there was a significant correlation between SES and their participating.

Accordingly, it has been concluded that the most frequent participants were from middle age category, as they might feel discomfort due to the lack of activity in their life, while the younger groups might feel healthy and be optimized physically forever, so they didn't feel the important aspect of participating in this kind of activities.

The other factor which may affect in numbering of participation was the type of possession of their house as it was the main problem in the subject's society. And finally, the subjects who were from the category of middle or higher in SES, because of feeling comfort and fortune in their life, participated in park activities.

Keywords: Park activity, Socio-economic status.

INTRODUCTION Studying leisure activities might lead to both humanitarian and managerial outcomes. From a humanitarian point of view, it would be valuable to understand the reasons of participating to the activities, because participation, even the moderate forms of it, could lead to various benefits such as: high level of self-esteem, prevention from diseases, high quality of life, and promotion the cardiac health (Strauss, 2000). From a managerial point of view, probing the source of leisure facilitating might ultimately help to organizing and promoting leisure activities better than before. In order to facilitate participation in leisure activity, leisure constraints should be investigated, since it seems that it has an extent role in determining the rate of participating in leisure activities. Researches might also become valuable in developing of leisure policies and strategies that every institute or company could provide organized leisure activities.

Furthermore, a thorough understanding of what keeps people away from physical activities, is essential for identifying of appropriate points of intervention to promote

1- mshafiei@srttu.edu

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active lifestyles and health benefits which they offer (Davison & Lawson, 2006). Additionally, as Larson (2000) noted, leisure was a crucial developmental context for young people and adolescents. From this point of view, investigating leisure constraints among all age-groups was vital. The knowledge could improve the implementation of leisure services for all participants—the future, hopefully healthier society.

In order to facilitate participation to physical activity, it could be valuable to investigate leisure constraints, since they seemed to determine a great degree of participation in activities (Alexandria, Tsorbatzoudis & Grouios, 2002). Moreover, identifying the strongest constraints might provide effective information in facilitating of participating and creating strategies to promote leisure and sport activities. Understanding differences of perceived constraints associated with gender, age, occupation, yearly income, and socio-economic status (SES), should be useful for planning, promoting, and managing organized leisure park activities.

The present study aimed to (a) identify and comparing the distribution of participants in Tehran parks; (b) studying the demographical data of participants such as: gender, age, marital, educational degree, occupational category, type of residency, and yearly income; (c) Scaling SES index; (d) Determining SES of participants in Tehran Parks.

LITERATURE REVIEW

Leisure constraints began to be systematically investigated in the 1980s. At that time, they were closely related to participation, presenting “barriers” that existed between a person’s desire to participate actively in a leisure activity and his/her actual participation. (Jackson, 2005). The optic angle changed greatly throughout the 1980s and 1990s (Jackson & Scott, 1999), as the variety of constraints acknowledged to wield an influence grew. This was the outcome of such new methodological approaches as factor analysis and cluster analysis (Hawkins & Freeman, 1993; Norman, 1996; Norman, 1995; Stodolska, 1998). Constraints, however, were no longer considered the only factors that mightily influence participation. In other words, a person’s experience of constraints didn’t not necessarily lead to non-participation (Jackson, 2005). Time- and cost-related constraints ranked among the most frequent and powerful constraints on leisure activities generally (Jackson, 2005). Walker and Virden (2004) noted that constraints on time were the strongest ones, and the ones most common in relevant studies.

Leisure constraints and gender

Arnold and Shinew (1998) studied the role of gender, race, and income on constraints to park use. A stratified sample of parks in the Chicago Metropolitan area was used to depict community areas representing black, white, and racially mixed population areas. They reported that income, race, and gender each one of them was significantly associated with constraints in park use. Arnold and Shinew argued that privileged members of society (i.e., Whites, males, high-income earners) had greater

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expectations for their leisure experiences compared to those less privileged. They also suggested research be done to examine not only race, gender and income, but also education and age as factors that influence constraints to park use.

Leisure constraints, educational level, age and marital status

Leisure constraints had also been found to be related to demographic data other than gender, such as education, age, and marital status (Alexandris & Carroll, 1997; Jackson & Henderson, 1995; Witt & Goodale, 1981). People with more education had been found to experience a lower level of constraints, while older people reported greater time constraints and married people reported more constraints related to family responsibilities.

Leisure constraints and residence

The direct relationship between leisure constraints and residence had not previously been investigated. However, in a national survey in the United States (Klepeis et al., 1996) concerning energy expenditure for leisure-time physical activity, differences were reported among the regions of the country. Inhabitants of the Pacific region (California, Nevada, Arizona, and Hawaii) were more physically active than those who were in the Central region (Nebraska, Kansas, Iowa, and Missouri), for example.

Leisure constraints and Socio-Economic Status (SES)

Since the present study was an extension of these investigations, they were reviewed in detail. Lee et al. (2001) tested the multiple hierarchy perspective of outdoor recreation participation. Using three dependent variables, respondents were asked about recreation participation away from home, close to home, and their use of Texas state parks. Their results were the same as previous studies that found people from lower socioeconomic backgrounds, members of a minority group, older adults and females had less outdoor recreation involvement. These results supported the idea that socioeconomic status, race, age, and gender exerted a cumulative effect on outdoor recreation participation.

Floyd et al. (2006) explored the combined effects of age, race and ethnicity, gender and socioeconomic status of recreational fishing. The variables of participation were comprised with questions which were related to whether respondents had ever been fishing and if so, whether they had done it during the last five years ago, and the last 12 months. In examining the individual effects, they reported that race and ethnicity, gender, and age were significantly related to fishing participation over the twelve-month period prior of the survey.

A similar result was obtained by Lee et al. (2001) in the analysis of participating in recreation and state park use. Floyd et al. (2006) suggested the effects of multiple hierarchy stratification might be less pronounced in fishing due to its widespread appeal, making it a less potent status marker.

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The multiple hierarchy perspective had also been used to examine leisure constraints. The same as Arnold and Shinew (1998), Shores et al. (2007) investigated about the combinations of conditions which could affect the constraints to of outdoor recreation. Five independent variables were consisted for analyzing, such as; (race/ethnicity, gender, age, income, and education) representing the four variables, needed to test the multiple hierarchy perceptively; (race/ethnicity, gender, age, and SES). The results indicated that for most constraints, a greater number of disadvantage statuses were related to higher probabilities of experiencing outdoor recreation constraints.

Timia Danise Thompson (2008) examined the effects of race and ethnicity, gender, age, and socioeconomic status on visits to U.S. national parks. It was hypothesized that these variables would individually exert a negative influence on park visitation. Cross tabulations with Chi-Square and multi variety of logistic regression showed that individuals in singular disadvantaged statuses as well as multiple disadvantaged statuses were less likely to visit national parks. This is consistent with previous studies. And finally, education was the strongest predictor of visitor status.

METHODOLOGY The method of this research is descriptive.

Instrument Information was gathered by the questionnaire.

Subjects In this research, 10% of the statistical populations who were 900, and participated regularly in park activities of Tehran, selected randomly and questionnaires were distributed among participants. About 668 questionnaires were returned (about 74.2%).

Delphi method was used in selecting factors of socio-economic status. In this method, the accuracy of each variable was evaluated by specialists and final results were gathered to prepare the research questionnaire.

For the validity of questionnaire, some specialists who were faculty members of universities were selected and their viewpoints were gathered. For the reliability of the questionnaire, 15 specialists in field of sport for all, were selected randomly. The reliability was calculated by Cronbach alpha (α= 0.930). Additional information about participants such as level of education, age, job, marital status, gender, yearly income, type of residence, etc. was analyzed.

In social categorization the variables were calculated as follow (Nakhoda, Nastaran, 1994):

1) Education: The years and field of educating calculated as indicated in table 1:

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Table 1- Calculating of educational score

2) Occupation: Job classification had been done according to IRIB broadcast organization during a survey of about 100 job title among 800 people. In this study, it had been used a five point Likert-type scale ranging from “1” to “5.”The average of each item estimated, and finally it had been indicated in table 2. (Nakhoda, Nastaran, 1994)

Table 2- Calculating of occupational score

Occupation Score

Unemployed and Job Category 5 10

Job Category 4 20

Job Category 3 30

Job Category 2 40

Job Category 1 50

3) Economical Status (ES): According to the declaration of participants’ yearly income it had been calculated. In this study, it had been classified to five Point Likert-type scales ranging from “1” to “5.”The average of each domain estimated, and finally it had been indicated in table 3.(Nakhoda, Nastaran, 1994)

Education status Score

Diploma or less 19

Bachelor Degree 25

Master Degree 35

Ph.D. Degree 45

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Table 3- Calculating of economical status

Economic Status scorre

Excellent 60

Good 50

Medium above 40

Medium 30

Medium below 20

Weak 10

4): Residency: This scale according to square feet of foundation, land measurement, and type of possession was calculated. This amount handled by the Ministry of Finance and Economy separately according in worth land of different local of Tehran annually (Nakhoda, Nastaran, 1994).Thus, this scale estimated as follow:

Rsd. = ,

+ (Coef icient of possession)

Other details of evaluating about Rsd. Indicated in the table 4 and 5.

Table 4- Coefficient of ownership type

Landlord 3

Rental & Lease holder 2

Others 1

Table 5- Average value of regional land

Average value of the regional land Region

9 North

8 West

7 East

6 Center

5 South

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Accordingly, the scale of SES would be calculated as follow (Cuper Adam. Jessica, 1985):

= . + +ES4 +

Rsd.10

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Scores obtained from this scale, was an indicator of individual status in social classification system. Thus, the maximum and minimum score of each of four above was as follow:

Table 6- Scaling Socio-Economic Status (SES)

Rsd. … … … 0.3 ………… 9

Job 10………...50 10 …………. 50

Edu. 19………….45 19 …………. 45

E.S. … … … . 2.5 ……….. 15

SES . < SES < 7.95 …… 29.75

Therefore, the median of (7.95) to( 29.75) was,( 21.8) units, which were divided into five parts.

29.75- 7.95 =21.8 21.8÷5=5.45 classification distance

Table 7- Categorizing of Socio-Economic Status (SES) scale

SES Category SES Score

High Classification 24.3 _ 29.75

Upper int.mediate Classification

18.85 _ 24.29

Intermediate Classification 13.4 _ 18.84

Lower int.mediate Classification

7.95 _ 13.39

Low Classification 2.5 _ 7.94

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Data Analysis

Descriptive Statistics

First, descriptive statistics were used for each factors of demographic section of the survey. This information included the age, educational background, gender, yearly income, marital status, SES. Next, descriptive statistics of the composite scores were calculated for each of the individual items in the survey and the means were combined for the entire items.

Nonparametric Statistics

The correlations between variables were determined by Chi-square test as follows: Age, Gender, Educational degree, Occupational category, Yearly income, Type of residence, and Socio-Economic Status.

The Statistical Package for Social Sciences 17.0 (SPSS) was used to conduct the statistical analysis.

RESULTS

Of the surveyed people, 73.4% were men and 26.6% were women. The mean age of men was 45.60 years, women were 51 years old and the mean age of total was 48.9 years. As to residence, 28.3% and 24.1% were in turn belonged to north and west as a majority in Tehran parks, while 10.9% as a minority group belonged to the center of Tehran. 28.3% of participants as a minority group was in north of Tehran while 10.9% of them as a minority group was in the center of Tehran. The majority group of male participants was also in north and after that in west of Tehran, while the majority group of female participants was from south of Tehran. In addition the minority of male participants was from the center of Tehran, while the minority group of female participants was from west of Tehran.

Figure 1- Distribution of participants in Tehran parks

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9.913.2

21.4

6.96.3 7.2 6.42.7 4

28.3

17.119.6

24.1

10.9

North South East West Center

perc

ent o

f par

tici

pati

on

Regions of Tehran parks

MenWomenTotal

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According to the findings about 90% of participants were married. About 78% of participants belonged to the intermediate category of job, in addition, the education of 76% of them was diploma or less, while the whom with master degree or above only was 4.05. From the point of residency, more than 78% of participants were landlord. And finally, the population of more than 54% of participants was 4 people or less. From the aspect of economic status, about 69% of participants belonged to the intermediate category, and the category of excellent and weak were in minority frequency.

Table 8: Summary of statistical distribution of participants based on variables

Crowded Family

Residence Education Occupation Marital Status

Variables

Region

5 ≥ 4 ≤

land

lord

Ren

tal &

leaseho

lder

other

Master &

above

Bach

elor

Dip

loma &

less

Low

Cat.

Mid

dle cat.

High

Cat.

Married

Single

12.25 15.8 23 5.25 0 3.15 9.85 13.15 8.60 10.1 12.1 26.5 1.8 28.3 North

9.75 7.4 12.1 4.75 0.15 0 1.05 15.7 11.4 5.1 0.6 13.6 3.4 17.1 South

9.4 10.1 16.3 3.05 0.15 0 2.45 16.9 9.7 7 2.85 18.7 0.9 19.6 East

10.15 14.45 16.9 5.95 1.2 0.3 4.9 18.8 4.6 11.2 4.85 21.1 3 24.1 West

4 6.7 10.1 0.75 0 0.45 1.65 8.75 6.9 3.4 1.6 10 0.9 10.9 Center

45.55 54.45 78.4 19.75 1.5 4.05 19.95 76 41.2 36.8 22 90 10 100 Total

Descriptive statistics derived from the leisure constraints scale in Table 8 indicate the distribution of participants in different region of Tehran. In addition, participants were asked about marital status, occupation, education, residence, and their crowded family.

Figure 2- Socio-Economic Status (SES) of participants in Tehran parks

11.60

20.8

27.1 26.8

13.6

High Class Upper int. Class

Intermediate Class

Lower int. Class

Low Class

SES

stat

us

of p

arti

cip

ants

Classification of SES

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As the figure indicates socioeconomic status of about 75% of participants belonged to the intermediate category and just the minority frequencies belonged to the high and low classes.

Figure 3- Socio-Economic Status (SES) of participants in Tehran parks regions

Table 9: Socio-Economic Status (SES) of participants in Tehran parks regions

Regions SES

Total

Center

West

East

South

North

11.6

1.45

2.55

1.3 0.3 5.9 High Class

20.8

2.05

4.8

3.55

1.05 9.3 Upper Int. Class

27.1

4.0 7.10

6.5 2.5 6.7 Intermediate Class

26.8

2.25

6.5

5.2 8.2 4.5 Lower Int. Class

13.6

1.05

2.95

2.8 4.9 1.75 Low Class

There was a significant correlation between various variables such as; distribution of participants, marital status, occupation category, education level, type of residence, yearly income, and socio-economic status (SES) and number of participating, by using

chi-square (Χ2 ), while in comparison of population family with participating in park activities, no significant correlation with α=0.05 was observed.

0.00

2.00

4.00

6.00

8.00

10.00

North South East West Center

SES

Inde

x

Regions of Tehran

High Class

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Table 10- The summary of non-parametric statistic about the variables of survey in table 10 has been indicated.

Statistical indicator

Variables

α Χ2cri. Χ2obs. Sig.

correlation

Distribution of participants 0/01 4 13.27 18.35 YES

Marital status 0/01 4 13.27 32.71 YES

Occupation category 0/01 8 20.09 24.02 YES

Education level 0/01 8 20.09 37.93 YES

Type of Residence 0/01 8 20.09 43.65 YES

Populated family 0.05 4 13.27 12.21 NO

Yearly income 0/01 16 32 37.39 YES

Socio-Economic Status (SES) 0/01 16 32 38.81 YES

DISCUSSION

In final summary should be pointed out that all researchers have paid attention to importance of participating to park activity in their leisure time. Each of them has scanned some aspects of participating. Generally, it is suggested that each of them has enough effect on promoting of these kinds of activities. In this research was going to examine factors which affected on determining SES of participants in park activities. The results of research showed that each of the aspects and its subgroups had enough valuable separately so that, even, the marital status in this research was enough important in examining of SES of participants in park activity.

Participants’profile The majority of the participants in the sample were diploma and less. As far as participation in physical activities, the majority participated in leisure or sports programs regularly (95%). However, almost one-half of them did regularly visit local parks, and most spent from seven to nine or more hours per week in individually organized physical activities. These results seem to be in accord with similar studies (Pitsavos et al., 2005; Rimal, 2002; Schnohr et al., 2004)

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According to the founds of survey, about 75% of participants were men and could be concluded that because of cultural reason, women couldn’t participated freely such as men in outdoor activities, unless the place was beyond the sight of others, or keeps their hijab according their culture, and it is one of the main constraints that makes them feel unease. Therefore, it is necessary to identify the strongest constraints may provide information helpful in facilitating to participate equally and creating strategies to promote leisure and sport activities for this part of society, otherwise we should be waiting a giant catastrophe in the near future as the women is base and foundation of every society in our and every culture. Thus, if we look for healthy and fresh society, we need along with paying to physical activity, eliminate the constraint of participating for women. These results supported the idea that gender exerts a cumulative effect on outdoor recreation participation. A similar result was obtained by Lee et al. (2001), Arnold and Shinew (1998), Shores et al. (2007), Floyd et al. (2006). These results supported the idea that exerts a cumulative effect on outdoor recreation participation.

It seems that single people have enough time to participate in leisure park activity than married ones, while the founds of this survey astonishingly showed that about 90% of participants were married. Perhaps it is because of their age that they are in pick of strength and healthy and think that it would be along with them lifetime, therefore there is no necessity to participate this kind of activities. But as the people who were over 35 years old and they are going far away from young age, concerned to it till keep themselves young, healthy, freshness, and strength full. This idea didn’t confirm by reports of (Alexandris & Carroll, 1997; Jackson & Henderson, 1995; Witt & Goodale, 1981) which found that marital status report more constraints related to family responsibilities.

By description of the occupational status of statistical samples could be concluded that, only 22% of them as a minority frequency belonged to the high class and the rest of them were from middle category or less. As participating in this kind of activities has low cost, so many people with the occupation of middle category or less could participate on it, but the people from high category of job prefer to participate the leisure activities which cost more, such as: golf, tennis, horse riding, skiing, and so on. This part of survey confirmed by reports of Arnold and Shinew (1998), Shores et al. (2007), Floyd et al. (2006), Lee et al. (2001)

Everybody, especially educated people know the advantages of physical activities and disadvantages of leaving it. Although many surveys have been done about the role of the education in selecting of physical activity, but surprisingly, the educational level of 76% of participants were diploma or less which it could be confirmed by observation of no significant correlation between participating and level of education. This founds didn’t’ confirm other surveys which reported that the people with more education experience a lower level of constraints. (Alexandris & Carroll, 1997; Jackson & Henderson, 1995; Witt & Goodale, 1981).

Tehran as a capital city has many problems for its settlers such as; types of pollutions, traffic jam, inflation of cost, etc. Type of settling is one of the main problems in Tehran. The people who live there, pay the most part of their yearly income for their settling. In order to balance their living, have to work harder for long hours per day. Accordingly, it

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is logical that these groups of people haven’t enough time to pay themselves by participating to park activities, as they have work more than 16 hours per day. Therefore, it is logical that who participates in leisure activities, isn’t worry about it, and this claim could be confirmed by this findings which refer to amount of 78.4% of samples who participated in the survey as a landlord. This finding differed from report of (Klepeis et al., 1996).

The direct relationship between leisure activity and family population of participants has not previously been investigated. According to the founds of this survey, about 55% of participants had family population four or less while population family five and more was 45% and didn’t seem enough difference between these groups, and finally, there was no significant correlation between number family of them and participation in leisure activity.

Finally, investigating of socio-economic status (SES) which was the most important object of this survey, was concerned. As indicated before, the most frequencies could be observed in intermediate category of SES, and minority groups belonged to the highest or lowest of this category. On the other hand, as participating to this leisure activity didn’t need much cost, the middle classes of society could participated, but minority groups such as the highest category, prefer to participate to much more expensive activity such as: golf, skiing, horse riding, tennis, and the lowest category, as hadn’t enough time, had no chance to participate to any kind of leisure activity. A similar result was obtained by Lee et al. (2001), Arnold and Shinew (1998), Shores et al. (2007), Floyd et al. (2006). These results supported the idea that exerts a cumulative effect on outdoor recreation participation.

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