Study Of Two Indian Cities Health And Social Care Essay

Dr. Sangeeta Khullar

Address: 1-E, Laxmi Road, Dehradun – 248001

Tel. +91-9411339033

Email: sangeetakhullar@gmail.com

&

Ms. Anjali Bhatia

(Faculty member at ICFAI University, Dehradun and Life skills trainer, Eupsychia)

Address: 249, Indira Nagar Colony, P.O. New Forest, Dehradun – 248006

Tel. +91-9897347663

Email: bhatia.anjali82@gmail.com

The Effect of Urban Green Cover and Age on Subjective Well-Being:

A Study of Two Indian Cities

Abstract:

When political or economic changes lead to accelerated urbanization, people’s evaluations of their life can also be expected to undergo major changes. In India, urban growth often takes place in a disorganized manner, with some areas undergoing swift development, and others remaining relatively untouched. The state of Uttarakhand is an example. Previously its two major cities—Dehradun and Haridwar—had abundant greenery and a gradual, steady pace of urbanization. However, since the formation of the state in the year 2000, these two cities have witnessed a population influx, rapid construction, encroachment and proliferation of slums. All this has led to a sharp decline in the amount of green cover in several residential neighbourhoods. The present study investigated whether areas with different levels of green cover, in the above-mentioned cities, would have residents with differing amounts of Subjective Well-Being. Data was collected from residents who had been staying in their locality since or before the formation of the state. Using the Subjective Well-Being Inventory, areas having low, medium and high levels of green cover and three age groups—25-35, 35-45, and 45-55—were compared. Significant differences were found amongst the three green cover areas on SWB; however, differences amongst the age groups on SWB were not found significant.

Keywords: Subjective wellbeing, urbanization, green cover, age

Introduction

In India and other developing countries, urbanization has had both desirable and adverse consequences. People migrate in large numbers to cities for better job opportunities, basic amenities and improved living conditions. However, the last of these—better living conditions—may not be accessible to all. As cities grow not only in size but in density, residents have to encounter crowding, encroachment, pollution, crime and intolerance. In order to balance out the effects of such stressful conditions, people need opportunities for cognitive and affective restoration.

The amount of green cover in one’s neighbourhood may play an important role in providing such opportunities. Accessible green spaces can reduce stress and provide psycho-physiological health benefits. Moreover, they create a setting for non-competitive human interaction—which can become a means of social support for individuals. Over the long term, people’s evaluations of their well-being can be affected positively by the availability of such stress-buffering resources in their environment. The present study investigates the effect of the amount of green cover in people’s localities on their subjective well-being.

Subjective Well-Being:

People’s evaluations of their lives may be understood by an assessment called ‘subjective wellbeing’ (SWB) consisting of three components: life satisfaction, presence of positive mood, and the absence of negative mood. A person's evaluation of his or her life may be in the form of cognitions (e.g., when a person gives conscious evaluative judgments about his or her satisfaction with life as a whole, or evaluative judgments about specific aspects of his or life); or in the form of affect (people experiencing unpleasant or pleasant moods and emotions in reaction to their lives). The cognitive and affective components of SWB are highly interrelated. Researchers in the field strive to understand not just undesirable clinical states, but also differences between people in positive levels of long-term well-being.

Demographic Variables related to Subjective Well-Being:

There are substantial differences in self-reports of SWB between rich and poor nations. People in poor nations show average SWB scores close to, or slightly below, the neutral point. Countries that are wealthier possess greater freedom and human rights, and an emphasis on individualism, and have citizens with higher SWB. Income has a positive relationship with wellbeing (particularly amongst low income groups) but with diminishing marginal returns to income after a certain point. In contrast, SWB reports have not changed at all in wealthy nations such as the U.S.A., Japan, and France as they have gained more income over the last 20 years (Diener, Diener & Diener, 1995).

Variables such as education, ethnic status, and age often correlate at very low levels with reports of SWB. Nevertheless, some demographic variables do consistently predict SWB. For example, married people of both sexes report more happiness than those who are never married, divorced, or separated (e.g., Lee, Seccombe, & Shehan, 1991). Age has a U-shaped relationship with wellbeing and is lowest amongst the age range of 35-50. There is some evidence that unemployment, lower income and lack of close relationships have a greater impact during middle age. Although there is mixed evidence on adaptation to unemployment, there is agreement that it has severe and long lasting negative impact on wellbeing.

Effect of Urban green cover on Subjective Well-Being:

A large body of research points out that a vista of nature is of high importance for well-being, restoration and aesthetical pleasure (e.g. Hartig et al., 2003; Herzog et al., 2003). In addition, passive and active encounters with nature in cities generate psychosocial benefits. Scientific evidence confirms that experiences of nature are associated with enhanced worker productivity (Kaplan, 1992), traffic stress reduction (Parsons et al., 1998), emotional stress mitigation (Ulrich, 1986) and restoration of cognitive capacities needed for basic functioning and productivity (Kaplan & Kaplan, 1989).

It appears that people in urbanized societies commonly believe that contact with nature provides them with restoration from stress and fatigue and improves their health and well-being. For example, in a nationwide survey among inhabitants of the Netherlands, 95 percent of the respondents indicated that they believed that a visit to nature is a useful way of obtaining relief from stress (Frerichs, 2004). In a large survey of residents in nine Swedish towns and cities, Grahn and Stigsdotter (2003) found that, when asked what they would recommend to a friend who was feeling stressed and worried, most respondents gave the first rank to taking a walk in the forest.

People’s belief in the stress-reducing powers of nature can also be inferred from research on motives for outdoor recreation (e.g., Driver, Nash, & Haas, 1987). This research has found that stress reduction, clearing the head, escape from civilization, and reflection on important life issues are among the most dominant motives. This type of motive has come to be identified with psychological restoration.

People surrounded by concrete in urban centers may experience environmental grief when deprived of natural spaces (Feral, 1998). Pigram (1993) argues that humans have a "genetically coded pre-disposition to respond positively to natural-environment content’. There is considerable research supporting the beneficial effects of nature on human physical and psychological health (Laumann, Gärling, & Morten Stormark, 2001). Therefore, it is logical to hypothesize that feelings of connectedness to nature should be positively correlated with levels of subjective well-being (SWB) or happiness.

Based on the above evidence, one can postulate that levels of urban green cover would predict the subjective well-being of residents. For the purpose of urban ecological studies, "urban" has generally been defined using estimates of population density, energy use or land use (McIntyre et al. 2000). A broad definition of ‘green spaces’ includes woodlands and forests, agricultural land, rural landscapes (both man-made and natural), nature reserves and parks, and a range of urban green landscapes including gardens, parks, allotments and tree-lined walkways (Newton, 2007). Urban green cover is an area within an urban environment which is dedicated to nature. It includes highly modified parks, gardens and recreation venues, as well as informal green space. One of the most familiar forms of urban green cover is a recreational park. Trees in woodlands and streets are also important elements of such green areas.

The present study investigated the effect of different levels of green cover in residential areas on Subjective Wellbeing, in two rapidly-urbanizing Indian towns—Dehradun and Haridwar.

The state of Uttaranchal had come into being on November 9, 2000, from the erstwhile Uttarakhand region of Uttar Pradesh. Dehradun is the capital of the newly formed state. Haridwar is rapidly developing as an important industrial township of. Construction activity in both cities has led to depletion of urban green cover. Many localities that used to be semi-forested are now devoid of greenery. Trees have given way to houses and commercial establishments.

The amount of Green Cover in the locality (low, medium and high), and the age of the residents (25-35, 35-45, 45-55 years) were taken as independent variables. It was hypothesized that there will be significant differences amongst residents of low, medium and high green cover areas and between the three age groups on subjective well-being.

Method

Sample:

Three hundred and six participants, from ages 25 to 55, were selected by random sampling from 3 localities each in Dehradun and Haridwar showing different amounts of green cover. To distinguish different localities on the basis of their green cover, maps and data were obtained from the Forest Survey of India and the Indian Institute of Remote Sensing, as well as from Google Earth.

Low green cover (LGC): Khurbura Mohalla (Dehradun); Kankhal (Haridwar)

Medium green cover (MGC): Dalanwala (Dehradun); Gurukul Kangri Vishwavidyalaya (Haridwar)

High green cover (HGC): Forest Research Institute (FRI) campus (Dehradun), and Bharat Heavy Electricals Limited (BHEL) campus (Haridwar)

The age group selected for the study ranged from 25-55 years. The rationale behind selecting this particular swathe was that these are the most productive years of an individual’s life in terms of professional growth. Consequently, this is the group subjected to the maximum work demands and urban pressures. The long-term restorative and regenerative effects of urban green cover are therefore likely to be most observable in this group. This sample was further divided into 3 age groups: 25-35 years, 35-45 years and 45-55 years.

Both males and females were chosen, but sex was not accounted for as a variable, as there are no notable differences amongst the sexes with regard to responses to and effects of greenery, in the literature.

The respondents were chosen from the Middle Class—those categorized as "aspirers" and "middle class" by the NCAER (National Council of Applied Economic Research): having annual household income between Rs. 90,000 – Rs. 10,00,000 per annum (Bery, 2006).

Respondents who spend minimal amount of time at home may not be as affected by the amount of green cover in their locality of residence, as much as respondents who spend a sizeable portion of their time at home. To ensure uniformity of this independent variable, only persons who spend an average of 14 hours a day in their residential locality were included in the sample. Since the loss of green cover has accelerated since the year 2000 (formation year of state of Uttarakhand), it was expected that the maximum effect would be observable in those respondents who have been residing in the given localities since before this year.

Tools:

Subjective Well Being (SWB) was measured as the total score on the Subjective Well Being Inventory, which has 36 items asking respondents how they generally feel about themselves. There are 3 response options of each item—positive, neutral and negative—differently worded according to the content of the questions. The scale has been constructed by Brinda Amritraj of Bangalore University. Test-retest reliability of the scale is 0.63. For positively-keyed items, the response "Mostly" was assigned a value of 3, "Sometimes" a value of 2, and "Rarely" a value of 1. The scoring was reversed for negatively-keyed items.

Statistics:

Means, standard deviations and standard errors of the mean were used to describe the data. Analysis of variance (ANOVA) and post-ANOVA t-test have been employed to test differences amongst groups. The criterion for statistical significance was the 0.05 level of confidence.

Results

Overview:

Significant differences have been found amongst Low, Medium and High green cover areas on Subjective Well Being. The medium green cover area has the highest score on SWB, with the high green cover area following closely behind. The 45-55 age group scores higher on SWB than the other two age groups, but the differences are not significant. The interaction effect of urban green cover and age has not been found significant.

Table 1: Means, Standard Deviations and Standard Errors of the Mean of three green cover areas on Subjective Well-Being

Green Cover area

Number of scores

Mean

Standard Deviation

Standard Error of mean

Low Green Cover

102

82.22

10.23

1.01

Medium Green Cover

102

86.52

9.35

0.93

High Green Cover

102

86.14

9.44

0.93

Fig 1: Mean Scores of 3 Green Cover Areas on Subjective Well-Being

Table 2: Summary of One-way ANOVA of Subjective Well-Being scores of three Green Cover areas:

Source of variation

Sums of Squares

Degrees of freedom

Mean Squares

F-ratio

Between groups

1157.65

3 - 1= 2

578.83

6.18**

Within groups

28394.79

3(102-1)= 303

93.71

Total

29552.45

305

**Significant at 0.01 level: F.99 (2, 303) = 4.69

Table 3: Results of Post-ANOVA t-test of differences between Means of three Green Cover areas on Subjective Well-Being:

GREEN COVER AREA

Low green cover

Medium green cover

High green cover

MEAN

82.22

86.52

86.14

DIFFERENCES

Low green cover

82.22

--

4.3**

3.92**

Medium green cover

86.52

--

--

0.38

High green cover

86.14

--

--

--

** Significant at 0.01 level: Critical mean difference = 3.52

Table 1 and figure 1 indicate that the Medium and High green cover areas have nearly equal Mean scores on SWB. The Medium green cover area scores slightly higher than the High.

From the one-way Analysis of Variance (F = 6.18, degrees of freedom=2, 303) it is evident that there is a significant difference at the 0.01 level between the Mean scores of the three green cover areas on Subjective Well Being (table 2). A significant difference (p<0.01) exists between the Mean scores of Low and Medium green cover areas, and between those of Low and High green cover areas—as indicated by the post-ANOVA t-test (table 3). It appears that residents of areas with low levels of green cover would be less likely to make positive evaluations of their lives and be less satisfied.

It cannot be denied that the city is a stressful environment for its residents. Green spaces provide an element of escapism, a release from the predictable urban environment into a more spontaneous one (Gilbert, 1991) where one can feel as if "being away" (Turner, 1996). The opportunity to visit natural green space to release stress and gain a perspective on life can be particularly important for people suffering from everyday hardships and social pressure (Ward Thompson, 2004). Thus, urban green spaces are seen as restorative environments (O’Brien and Tabbush, 2005). Accessible green space creates opportunities for recreation and exercise and the affiliation with nature, necessary for maintaining mental health and vitality of city people (Kellert, 1996) (as cited in Kazmierczak & James, 2007). When deprived of these opportunities, residents of rapidly-urbanized localities like the ones in the present study would be less likely to make positive evaluations of their wellbeing.

Burns (2006) explains that in comparison to human-made environments, natural environments have softer, more pleasing stimuli that have a better ‘biological fit’. He concludes that the psychological or mental benefits gained from human-nature interactions can be found at the cognitive, affective and behavioural levels.

Table 4: Means, Standard Deviations and Standard Errors of the Mean of three age groups on Subjective Well-Being

Age Group

Number of scores

Mean

Standard Deviation

Standard Error of Mean

25-35

102

84.13

8.4

0.83

35-45

102

84.47

10.8

1.07

45-55

102

86.27

10.14

1

Figure 2: Mean Scores of 3 Age Groups on Subjective Well-Being

Table 5: Summary of 3 X 3 ANOVA of Subjective Well-Being scores of three Green Cover areas and three Age groups:

Source of variation

Sums of Squares

Degrees of freedom

Mean Squares

F-ratio

Green cover

1157.65

3 - 1= 2

578.83

6.25**

Age group

271.38

3 - 1=2

135.69

1.46 (NS)

Green cover X Age group

607.03

(3 - 1)(3 -1)=4

151.76

1.64 (NS)

Within groups

27516.38

(3 X 3)(34-1)= 297

92.65

Total

29552.45

305

**Significant at 0.01 level: F.99(2, 297) = 4.69; NS= Not significant

Table 4 and figure 2 show that the 45-55 age group scores highest on Subjective Well-Being. However, when subjected to a 3 X 3 ANOVA (table 5), neither the main effect of age nor the interaction effect of urban green cover and age were found to be significant.

This goes contrary to the evidence that age has a U-shaped relationship with wellbeing and is lowest amongst the age range of 35-50. There is some evidence that unemployment, lower income and lack of close relationships have a greater impact during middle age (van Hoorn, 2007). However, according to Diener et al (1999)’s summary of several studies, life satisfaction seems to stay the same, if not increase with age. This finding countered earlier conventional wisdom that older people were less satisfied because they were unhappy with their unfulfilled lives as they reached the uselessness of old age. There seems to be a slight increase in life satisfaction from age 20 to age 80 with negative affect held constant. Considering that life satisfaction stays the same or increases in old age, Diener et al. suggest that people become better at adapting to their conditions as they get older.

Conclusion:

People who live in areas with medium to high amount of green cover appear to make more positive evaluations about their well-being. Residents aged between 45 to 55 years score higher than the other two age groups (25-35, 35-45) on Subjective Well-Being, although the difference is not significant.

The ever-increasing population in most Third World countries, particularly India, has given rise to a host of social problems as well as problems associated with the physical aspects of space. Because of increasing urbanization, combined with a spatial planning policy of vertical design, more people face the prospect of living in residential environments with fewer green resources. People from low socioeconomic groups are affected the most, as their living areas are often overcrowded and encroached upon. This can lead to adverse psychological effects such as maladjustment, anxiety, feelings of isolation and prolonged stress. Accessible green areas mediate the effects of such stressful conditions by providing relaxation and restoration, and by generating opportunities for social contact and cohesion.

The modern world economy is driven by high levels of consumption and (often) unsustainable use of natural resources. These are considered by environmentalists as a threat to the wellbeing of the planet. However, it is apparent that the wellbeing of individuals is also adversely affected if they are deprived of the regenerative effects of nature. Conversely, the experience of nature in an urban environment is a source of positive feelings; it also fulfills important non-material and non-consumptive human needs. Moreover, contact with green areas enhances general health and workplace productivity. Over the long-term, urban planners must take into account the psychosocial implications of their development models, based on the results of this and other similar studies.