RURAL-URBAN DIFFERENCES IN
SUBJECTIVE WELL-BEING
by
DAVID ALLEN ARMSTRONG, B.A.
A THESIS
IN
SOCIOLOGY
Submitted to the Graduate Faculty of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
MASTER OF ARTS
Appro~
Accepted
May, 1991
(l.C 8() 5
/3 1CfC1/
'AI tJ . I c.oo:l~
I would like
ACKNOWLEDGEMENTS
to express my thanks to Dr. George Lowe
for the extreme patience that he showed through this
endeavor. He was there when I needed him, and his time
spent went above and beyond what could be expected. I
would also like to thank Drs. Charles Chandler and Yung
Mei Tsai for their.helpful advice. Dr. Charlotte Dunham
also deserves acknowledgment for stepping in at my time
of need. My thanks also go to Russell P.O. Burton for
his assistance with the literature on this subject.
Perhaps most importantly, I would like to thank my
parents, Jack and LaVelle Armstrong, for their support
throughout my academic career. Without their moral and
financial support, I could never have made it this far.
ii
CONTENTS
ACKNOWLEDGEMENTS .
LIST OF TABLES . .
I. INTRODUCTION . .
Review of Literature .
The Negative Impact of Urban Life--Greater Stress . . . • . • . . . • Evidence of Mental Illness in Urban Areas . . . • . • • . . . The Negative Impact of Rural Life--Greater Stress • . . • . . . . . . Evidence of Mental Illness in Rural Areas . . . . . . . . . . . . . . . The Merging of Rural and Urban Life . "The Community Question" - Urbanism and Social Networks . . . . . . . . . Social Support in Rural Areas . . . . Problems With Previous Measurement ...
Subjective Well-Being as a New Approach . . . . . . . .
Social Stability and Subjective Well-Being .
The Research Problem
II. METHODS
III.
IV.
The Sample .
Operationalization of Variables
The Dependent Variable The Independent Variable Control Variables . . . .
FINDINGS .
SUMMARY . . . . . . .
iii
ii
v
1
3
3
5
7
12 13
14 16 18
20
23
25
28
28
30
30 31 31
38
50
REFERENCES 56
APPENDIX 66
iv
1.
2.
3.
4.
5.
6.
7.
8.
LIST OF TABLES
Principal Component Factor Analysis of Subjective Well-Being Items . . . .
Principal Component Factor Analysis of Socioeconomic Status Items . • • . . .
Zero-Order Correlation Coefficients for Subjective Well-Being . . . . . . . .
Mean Level of Subjective Well-Being for Rural and Urban Residents . . . . . .
Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age and Gender . . . . . . . . . .
Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age, Gender, and Socioeconomic Status . . . . . . . . . . . . . .
Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age, Gender, Socioeconomic Status, and Social Stability . . . • . . . . .
Results by Step for Urbanism in Stepwise Multiple Regression on Subjective Well-Being . . • . . . . . . . . .
9. Regression Results for Subjective Well-Being Final Step . . .
10.
11.
12.
Results for step 1 in stepwise Multiple Regression on Subjective Well-Being
Results for Step 2 in Stepwise Multiple Regression on Subjective Well-Being
Results for Step 3 in Stepwise Multiple Regression on Subjective Well-Being
v
36
37
43
44
45
46
47
48
49
67
68
69
13.
14.
Results for Step 4 in Stepwise Multiple Regression on Subjective Well-Being
Results for Step 5 in Stepwise Multiple Regression on Subjective Well-Being
vi
70
71
CHAPTER 1
INTRODUCTION
The relationship between urbanism and mental illness
and psychological distress remains ambiguous. Four
decades ago, there was no controversy about this
relationship. Epidemiological studies consistently
showed lower rates of mental illness in rural areas
(Jaco, 1968; Flax, Wagenfeld, Ivens, and Weiss, 1979;
Cockerham, 1989). These findings were consistent with
Wirth's (1938) theory of urbanism and were considered
major support for his thesis that the stress of city life
affected the people who lived there. In 1960, then, the
fact of higher rates of mental illness in urban areas was
not only a universally accepted empirical generalization,
it had strong grounding in theory.
In the 1970s, Fischer (1972, 1973) raised serious
questions about Wirth's theory, especially the idea that
urban life is especially stressful. Fischer also
presented evidence that rural life may be more malaise
inducing than is urban life.
During the same period, the epidemiological evidence
showing lower rates of mental illness in rural areas was
brought into question (Fischer, 1973; Webb and Collette,
1
2
1977; Flax et al., 1979). Further, new theories arose
which suggest that rural life may in fact be more stress
inducing than city life. Some recent findings
(Granoveter, 1973; Garbarino, 1977) appear to support
this position.
Recent research on subjective well-being has shown
that social support, particularly when measured as social
stability, has a strong negative association with
psychological distress (eg., Hellinghausen, 1984; Kunkel,
1981). This association tends to be as strong or
stronger than socioeconomic status. Traditional wisdom
suggests that rural communities may be higher in social
support.
The question then is whether stress or social
support (or both) affects subjective well-being and the
relationship of these to place of residence. Previous
studies have dealt strictly with differences in mental
illness rates and have virtually ignored the contribution
that the subjective well-being measure is able to
provide. This thesis will attempt to answer the question
by utilizing the data available in the General Social
surveys to measure subjective well-being, social
stability, and size of place of residence.
Review of Literature
The Negative Impact of Urban Life--Greater Stress
An early comparison of rural and urban life is
Ferdinand Tennies' (1887) Community and Association.
Rather than simply comparing rural and urban life,
Tennies contrasts the traditional, preindustrial society
which is characteristic of rural areas with modern
industrial society which is generally urban. Tennies'
term Gemeinschaft, meaning community, refers to the
traditional rural society. In this type of society,
people maintain close personal relations with their
neighbors and are acquainted with almost everyone that
3
they are likely to encounter. Trust is high in this type
of community.
Tennies' term Gesellschaft, which literally means
association, refers to the modern, industrial, urban
society. Tennies says that people in urban areas are
largely driven by economic self-interests. They have a
tendency to work with their own goals in mind and are,
thus, less likely to know and care about other people.
For this reason, urban areas are characterized by a more
impersonal, isolated atmosphere.
Georg Simmel (1964) speculates that the reason for
these differences is that the city contains so many
people and situations that a single person is not able to
become familiar with everyone. To cope with this
overstimulation, Simmel says that people withdraw and
only pay attention to the things that are of personal
importance. Milgram (1970) elaborates on Simmel's
argument and states that people in cities are faced with
immense sensory and mental demands which lead to
psychological distress.
4
In "Urbanism as a Way of Life" {1938), Louis Wirth
proposes a theory of urbanism based on the negative
effect that urban life has on the individual. This is
called "determinist theory" by Fischer (1976). Wirth
defines a city as a "relatively large, dense and
permanent settlement of socially heterogenous
individuals." The heterogeneity, size, and density of
the population are central to Wirth's argument in that he
asserts that these factors contribute to the problem of
developing intimate personal relationships. According to
Wirth, these factors lead to isolation, impersonality and
superficial relationships which, in turn, contribute to
poor interpersonal relationships.
Wirth also says that while urban residents may be
acquainted with a larger group of people, they are more
likely to "have a less intensive knowledge" of these
people. Thus, urban life is characterized by "secondary
rather than primary contacts." He cites Simmel (1903)
and Weber (1925) to substantiate his argument.
Another effect that Wirth attributes to density is
that of a high division of labor. In this argument, he
cites Durkheim's The Division of Labor in Society (1933),
asserting that an increase in density produces
differentiation and specialization because this is the
only way that the greater numbers can be supported.
5
This, in turn, results in diversification among residents
and increasing complexity of the social structure which
may alienate one from fellow residents.
Another point central to Wirth's theory is that of
"nervous stimulation" or "information overload" which he
says are characteristic in urban areas because of the
increasing population size and density. This idea is
drawn largely from Simmel (1964). Thus, urban residents
are the (unwilling) recipients of increasing amounts of and increasing diversity in sensory stimuli calling for response--both physical and social: other people, public messages, pleas for attention and concern. This raises the problem of "information overload" in the urban setting: more inputs than the human organism can handle. (Fischer, 1972, p. 193).
Evidence of Mental Illness in Urban Areas
Traditional wisdom supports the belief that urban
living is more stressful than living in rural areas (Flax
et al., 1979). Jaco's (1960) conclusion of higher rates
6
of psychosis in urban areas is typical, but his findings
are based on treatment rates, resulting in methodological
problems. Many early studies of treatment rates show the
same relationships (see the more than 20 studies cited by
Dohrenwend, 1975), but they all have the same
methodological weakness. As Dohrenwend (1975) notes, the
differentials could be due to the low availability of
treatment facilities in rural areas and migration to
urban centers rather than actual mental health
differences.
Dohrenwend's 1975 study also reviews eight studies
that compare urban and rural rates of psychiatric
disorders, rather than treatment rates, and concludes
that urban residents show more disorder in all but two
cases. In one of the studies, the total rate for all
psychiatric disorders is higher for rural residents and
one study shows a tie. The differences shown, though,
are not large. Certain disorders, specifically
functional psychoses, are found to be more prevalent in
rural settings while anxiety and personality disorders
show to be more predominant in urban settings.
Dohrenwend agrees that these results are consistent with
the idea that the excess stress in urban areas may result
in higher rates of disorder, but he also proposes an
alternative explanation. He says that the added
7
attractions that cities offer may lure people from rural
areas and that, of the migrants that move to the city,
some of them must be ill.
Peek and Lowe (1977) report that alcohol use, viewed
as a means to cope with stress, increases with city size.
Although this is influenced by the greater availability
of alcohol in urban areas, it is also related to the
problems of excess nervous stimulation and the greater
difficulty in establishing primary relationships.
The Negative Impact of Rural Life--Greater Stress
As we have seen, there is a position that argues
that there is greater stress for residents of urban
areas. There is some research support for this stance.
There is a second view that argues that there is greater
stress in rural areas. As opposed to the excess sensory
stimulation that is considered to be characteristic of
urban life, rural life is seen as more socially isolated
(Taylor, 1933; Sims, 1940; Webb and Collette, 1977).
Smith and Coward (1981) report that "geographic and
social isolation are characteristic of much of rural
America." This isolation, while perhaps sheltering one
from sensory overload, limits the number of persons that
one may turn to in times of need.
Webb and Collette (1977) argue that this isolation
could lead to routinization and a lack of stimulation
which may be associated with greater amounts of stress.
They also propose that the mass media, which is
predominantly urban, promotes an ideal lifestyle that is
not readily attainable by rural residents, leading to
feelings of frustration and isolation.
8
Sorokin et al. (1931) said that in rural areas it is
"much more difficult to find other than family shelters
against isolation and loneliness." In the first half of
this century, this was due largely to poor roads and the
absence of telephones (Lowe et al, 1987). This is
congruent with recent findings that size of community of
residence is positively related to frequency of
socializing with friends who are not neighbors (Glenn and
Hill, 1977; Tsai and Sigelman, 1982). Tsai and Lai
(1988) also report that rural residents are more likely
to identify neighbors in their social network than are
urban residents.
While isolation from neighbors and the rest of the
surrounding community has been identified as a possible
factor in influencing rural stress, rural homes tend to
have more occupants than urban dwellings. It has been
proposed that crowding in the home may be a more
important factor in residents' mental health than
crowding or isolation on the macro level (Cockerham,
1989; Gave, Hughes, and Galle, 1979; Webb and Collette,
1977).
9
Family therapists, educators and researchers also
report that farm men and women are subject to stress
(Bennett, 1982; Hedlund and Berkowitz, 1979; Jurich and
Russell, 1987; Keating, 1987; Keating, Doherty, and
Munroe, 1986, 1987; Rosenblatt and Anderson, 1981; Walker
and Walker, 1987; Walker, Walker, and MacLennan, 1986).
Sources of stress which have been identified include (1)
vagaries of weather, interest rates, markets and consumer
demands (Rosenblatt and Anderson, 1981); (2) multiple
work-roles which compete for limited amounts of time and
money (Hedlund and Berkowitz, 1979; Keating et al.,
1987); ( 3) combined familial and economic roles (Bennett,
1982); and ( 4) irregular cash flow, large capital
investment and financial risk (Keating et al., 1986;
Rosenblatt and Anderson, 1981; Walker et al., 1986;
Walker and Walker, 1987). Most of these studies do not
include comparisons with stress in nonfarm or urban
areas. However, a report on occupational stress states
that farm managers ranked twelfth of 130 occupations
studied (Hedlund and Berkowitz, 1987).
There is also evidence that people in rural areas
experience higher levels of stress from sources other
10
than farming. Financial problems contribute to stress in
rural areas, too. This stress may be exhibited in
marital difficulties, depression, physical aggression
against family and friends, increased smoking and
drinking, and loss of appetite (Hargrove, 1986; Heffernan
and Heffernan, 1986). "Stress related disorders are much
more prevalent among rural than urban residents,"
according to Webb and Collette (1977, p. 706). The
factors that they attribute to producing a stressful
rural environment are "the crowding of rural housing, an
inability to escape easily to distracting amusements, and
the stifling social pressures of small towns "
Webb and Collette (1977) use the amount of stress
relieving drugs prescribed in rural and urban areas in
New Zealand as an indicator of amount of stress. They
find that the larger the locality, the lower the mean
monthly amount of prescriptions filled, with rural areas
having almost double the amount of prescriptions of the
largest cities. This leads them to the conclusion that
rural residents are a high-risk group with regard to
mental health.
The explanation offered by Webb and Collette (1977)
that overcrowding in rural housing could lead to worse
mental health is consistent with previous findings in the
area of overcrowding. Although Webb and Collette
11
concentrate on crowding in the home, there are two types
of crowding that must be considered. Krupat (1985)
identifies two different levels where overcrowding
occurs, crowding on the molar and molecular levels. From
a molar point of view, crowding occurs on a large scale,
one outside of the household. Crowding from a molecular
point of view occurs on a smaller scale, crowding on the
inside.
While Baldassare (1978) finds overcrowding on the
macro level to be detrimental to mental health, it has
also been reported (e.g., Galle and Gave, 1979) that
crowding at this level may have some minor effects but it
is not a variable of "major substantive importance."
Later, Gave et al. (1979) found that both objective
(persons per room) and subjective (excessive social
demands and lack of privacy) crowding are strongly
related to poor mental health, poor social relationships
in the home, and poor child care. Carnahan, Gave, and
Galle (1974) found serious overcrowding to be found on
farms more than other locations lending support to Webb
and Collette's explanation. As opposed to the crowding
in the home that is found in rural areas, overcrowding on
the macro level tends to be associated with city life.
After reviewing the past research, Cockerham suggests
that overcrowding in the home may be "much more
12
significant than overcrowding in the neighborhood"
(Cockerham, 1989, p. 208). There is mixed evidence as to
whether crowding on the macro or micro level is more
stressful, but there is evidence to support the fact that
both have a negative effect on mental health (Galle and
Gave, 1979; Galle, Gave, and McPherson, 1972; Mitchell,
1971; Schmitt, 1957).
Evidence of Mental Illness in Rural Areas
Fischer (1973) argues that "rural malaise," a
subjective psychological state of dissatisfaction,
unhappiness, despair and melancholy, may be predominant
worldwide. This relationship is demonstrated only after
controlling for social class, race, region, and
especially migration. Malaise in urban areas is found to
dissipate after controlling for those who move from
smaller communities to larger communities and vice versa.
He concludes that while Americans generally express a
preference for smaller communities, people in cities seem
to be more content.
Lowe and associates (1987) take issue with Fischer's
conclusion, though, arguing that he misinterprets his
data. Two of the surveys that Fischer analyzed show
rural respondents to be more satisfied than urban
residents in ten of thirteen categories. Further, two of
13
the exceptions ("your future" and "people's honesty") are
not standard indicators of mental well-being. Lowe and
his associates interpret this to mean that although they
may be more pessimistic about the future, rather than
exhibiting "rural malaise," rural residents tend to be
more satisfied than urban residents.
While Dohrenwend (1975) finds that some disorders
such as neurosis, personality disorders, and
schizophrenia are more prevalent in urban areas, he also
reports that all functional psychoses combined are more
prevalent in rural areas. This is also true for the
manic-depressive subtype. Therefore, the rural setting
may lead to higher rates of certain disorders such as
functional psychosis and manic-depression.
Webb and Collette's (1977) study compares the amount
of stress-relieving drugs that are prescribed in rural
and urban areas. Their analysis shows that people in
rural areas are prescribed almost twice the amount of
stress-relieving drugs as those in urban areas. This
provides support for the idea that rural stress is
detrimental to residents' mental health.
The Merging of Rural and Urban Life
There is the possibility of an argument somewhat
less dramatic than the two opposing views previously
presented. Srole (1972) suggests that technology has
brought the two communities together. By the use of
modern transportation, such as the automobile, the
boundary between the city and the countryside is not so
strict. It is possible for people to live in the
14
country, work in the city, and commute to suburban areas
as need for affairs such as shopping (Srole, 1972).
Srole comes to the conclusion that the impact of a
person's place of residence has little etiological impact
on one's mental health. Rather, there may be some sort
of self-selection involved in who makes the decision to
live in a certain type of environment.
In a later study, Srole (1980) finds evidence to
support his view. In an analysis of previous studies and
data collected by the National Center for Health
Statistics (NCHS), Srole determines that there is no
difference in psychiatric disorder in rural and urban
areas. Further, in review of a previous study of
"General Psychological Well-Being," Srole comes to the
conclusion that there is no significant variation in
psychological well-being among people on farms, in large
cities, or in places in between.
"The Community Question" -Urbanism and Social Networks
Much of the justification for each of the opposing
views of differentials in mental illness is based on
15
primary and secondary relationships (or the lack of such
relationships). A logical question, then, is how
urbanism actually affects these relationships.
Wellman (1979) proposes "the community question" of
whether, and if so, how the large scale division of labor
in modern urban society affects a person's primary
relationships. Wellman proposes three possibilities from
the existing literature. The first proposition, the
"community lost" position, suggests that urbanites are
members of multiple social networks, but are only
involved to a limited degree. These relationships are
characterized by "webs of secondary affiliations." Polar
to this view is that of the "community saved" argument
which sees that residents of cities are equally likely to
socialize with friends neighbors and relatives as
residents of small towns and rural areas are. The
"community liberated" perspective asserts that residents
of cities are less likely to socialize with relatives and
neighbors, but they are more likely to associate with
people outside of the neighborhood. Wellman's data
provide more support for the "liberated" perspective than
the other two.
Support for Wellman's (1979) propositions has been
mixed. Tsai and Seligman (1982) utilize national survey
data to test Wellman's propositions through use of
16
sociability questions concerning respondents' interaction
with relatives, neighbors and friends. They find strong
support for the "liberated" perspective, partial support
for the "lost" perspective, and none for the "saved"
perspective. Later, Tsai and Lai (1988) took advantage
of newly obtained network data in the General Social
Surveys to test Wellman's propositions. The new network
data fail to show more than partial support for any of
the three hypotheses, suggesting that there may be no
differentials in the amount and strength of primary ties.
Social Support In Rural Areas
The idea that there is better social support in
rural areas goes at least as far back as Tennies (1887).
This support comes from increased contact with neighbors
and family. Tennies' term Gemeinschaft refers to this
type of society where people maintain close relations
with neighbors and family members. These are potential
sources of strong social support.
Tsai and Sigelman (1982) found that rural residents
have more contact with neighbors and less interaction
with friends than urban residents, but, more importantly,
they have much more contact with relatives than with
either neighbors or friends. There is additional
evidence to support the idea of greater contact with
relatives (Straus, 1969; Mirande, 1970; Glenn and Hill,
17
1977) although it has been debated as to whether this is
more beneficial than having greater amounts of less
personal contact with non-relatives (Granovetter, 1973).
There is a body of research that contradicts this
idea of greater contact among kin in rural areas.
Bultena (1969) finds some differences between rural and
urban residents in face-to-face contact with children and
siblings, but they are more among the aged than other age
groups. Lee and Cassidy (1981) review ten studies of the
association between residence and kinship interaction and
conclude that "reported rural-urban differences in
kinship interaction are quite inconsistent, almost
uniformly small, and often attributable to factors other
than residence" (Lee and Cassidy, 1981:67).
There is also the contention that, regardless of
whether familial ties are stronger in rural areas, weak
ties are more important in this instance. Garbarino
(1977) sees these types of relationships as part of
potent support systems which are crucial to an
individual. Granovetter (1973:378) states that " weak
ties, often denounced as generative of alienation (Wirth,
1938) are ... indispensable to individuals'
integration into communities; strong ties, breeding local
cohesion, lead to overall fragmentation."
18
Problems With Previous Measurement
The focus of the literature review to this point has
been the relationship between place of residence and
mental illness. There is reason to be cautious when
reviewing the previous findings, though. The validity of
the previously reported research may be questioned.
Attempts to measure mental illness with treatment
rates have been fraught with methodological problems. It
is not possible to accurately generalize findings drawn
from treatment rates to persons not receiving psychiatric
care. Social class, location of residence, and sex all
influence the probability of seeking professional help
and may, thus, contaminate the results when analyzing
only treatment rates.
Persons of lower social class have been shown to be
more likely to become mentally ill (Hollingshead and
Redlich, 1958; Srole, Langner, Michael, Opler, and
Rennie, 1962) but are less likely to be admitted into
private treatment (Hollingshead and Redlich, 1958).
Myers and Schaffer (1954) also found that social class is
directly related to acceptance to treatment and the type
of treatment received. Race has also been found to
influence the rate of admission to treatment for
alcoholism with blacks being under-represented in the
South (Lowe and Hodges, 1972). Lowe and Hodges also
19
report that admission to treatment does not necessarily
reflect rates of illness. Both diagnosis and admission
can be affected by non-pathological personality factors
(for example, problem drinkers with an unsophisticated
concept of their illness are more likely to be diagnosed
as alcoholic), organizational needs and financial
requirements (incorrect diagnoses are sometimes used in
order to treat andjor bill), and requirements of the
community (agents of social control sometimes slant
commitment papers to influence diagnosis) (Lowe and
Hodges, 1972).
According to Cockerham (1989), social factors
(especially sex roles) may lead to greater rates of
admission to psychiatric treatment for women. In
addition, greater numbers of treatment facilities in
urban areas may contribute to the higher treatment rates
in urban areas. It is easier for urban residents to seek
treatment, and rural residents may migrate to the city in
order to pursue treatment. Flax and his associates
(1979) consider a rural subculture of poverty as one
possible explanation of the low rate of use of treatment
resources for mental illness in rural areas.
An alternative to measuring treatment rates is to
assess the true prevalence of mental illness. A good
example of this type of research is the Stirling County
study (Leighton, Harding, Macklin, Macmillan, and
Leighton, 1963). While this type of research is
efficient, using trained psychiatrists to interview a
representative sample of the population is extremely
costly and, therefore, not practical.
Subjective Well-Being as a New Approach. Many
researchers have attempted to overcome the previous
20
shortcomings by using a softer measure of mental illness,
but with larger samples. Numerous studies have used the
Global Happiness item (eg., Bradburn and Caplovitz, 1965;
Palisi and Ransford, 1987; Phillips, 1967). This
approach has been used less in recent years, partly
because the item does not differentiate well among
populations (most claim to be happy), but also because
multi-item indices appear to make better measures.
Fischer (1973) analyzed several sets of data and
focused on numerous independent items rather than
building an index. These items include such questions
as:
"Do you think that life is getting better or worse in terms of •.. ? (a) honesty, (b) morals, (c) happiness, and (d) peace of mind."
"On the whole, would you say that you are satisfied or dissatisfied with ... ? (a) your income, (b) your work, (c) children's education, (d) your future, (e) people's honesty, and (f) your housing."
Dohrenwend (1975:370) characterizes Fischer's (1973)
attempt to measure malaise as "focusing on mild forms of
psychophysiological distress and personal
dissatisfaction."
21
Rather than using treatment rates, global happiness,
or other independent items, the mental well-being measure
has been increasingly used in the mental health
literature (Beiser, 1974; Beiser, Feldman, and Egelhoff,
1972; Berkman, 1971; Bradburn and Caplowitz, 1965;
Bradburn, 1969; Gaitz and Scott, 1972; Gove, Hughes, and
Style, 1983; Gurin, Veroff, and Field, 1960; Lowe and
Smith, 1987; McLanahan and Adams, 1989; Palisi, 1984;
Phillips, 1967).
Beiser (1974) demonstrated the heuristic value in
using a multidimensional measure of psychological well
being rather than using a single global construct such as
the Global Happiness Item. By using a factor analysis of
a number of items from previously used mental health
scales, he identified three basic components of mental
well-being. Factor I, "Negative Affect," contains items
measuring boredom, unhappiness, and loneliness in the
recent past, while factor II, "Pleasurable Involvement,"
measures pride, pleasure and excitement about the recent
past. Factor III, "Long-Term Satisfaction," measures the
respondent's satisfaction with the way his/her life has
been going and perceived success in work and with family.
Beiser found that all three factors correlate well (r=.38
to .45) with the Global Happiness Item. Further, he
found that both negative affect (r=.42) and long-term
satisfaction (r=-.31) correlate highly with Psychiatric
Caseness, which was a measure of mental illness used in
the Stirling County study (Beiser, 1974). What Beiser
confirmed was that a scale of this sort is able to
provide a more reliable index than the use of a single
item such as the Global Happiness Item.
Lowe and his associates (see Hellinghausen, 1984;
22
Kunkel, 1981; Lowe and Smith, 1987; Lowe and Witt, 1978;
and Witt, 1978) have demonstrated the usefulness of a
related index of mental well-being. Lowe's measure was
developed for use with the General Social Surveys and is
based on the Global Happiness Item, together with
questions about satisfaction with family life,
friendships, health, hobbies, and place of residence.
Studies using this index produce findings consistent with
studies using other measures of mental well-being (see
Beiser, 1974). It is correlated with age (Witt, 1978),
class (Kunkel, 1980; Lowe and Witt, 1978), social stress
(Hellinghausen, 1984; Lowe and Witt, 1978), and marital
status (Lowe and Smith, 1987; Lowe and Witt, 1978).
Social Stability and Subjective Well-Being
23
There is convincing evidence to show that individual
well-being is enhanced by involvement in social
relationships (Umberson, 1987) and that lack of social
ties may contribute to poor psychological well-being and
even death (Berkman and Syme, 1979; Turner, 1981;
Williams, Ware, and Donald, 1981). The study of "social
support" became extremely popular in the 1970s (e.g.,
Caplan, 1974; Cassel, 1976; Cobb, 1976) and has grown
dramatically to the present date (e.g., Cohen and Syme,
1984; Gottlieb, 1983; House, 1981; Kahn and Antonucci,
1980; Lin, Dean, and Ensel, 1986; Thoits, 1982). Though
different definitions of social support exist, it is
generally close to the one proposed by Lin et al. (1986).
Lin and associates define social support as "the
perceived or actual instrumental andjor expressive
provisions supplied by the community, social networks,
and confiding partners (1986, p. 18).
The study of social support, although not termed
social support at the time, may date as far back as
Durkheim's study of suicide in 1897 (Durkheim, 1951).
Durkheim examined the way that social integration in
society effected suicide rates. This led to later
researchers' interest in the way that integration, in the
24
form of social networks and social support, effected such
things as psychiatric disorders (Lin et al., 1986).
Lowe (1971), attempting to index "the amount of
social support available to the individual, especially in
times of adversity," developed the concept of social
stability, which refers to social support from structural
sources. It is a foundation that is accessible for the
person to draw upon when coping with social stress. This
social support may be present in the form of ties to
family, friends, employment, or voluntary groups. There
is also an aspect of social support that is artificial in
nature. This is support available only to an individual
who is playing a client role. While treatment facilities
are sources of such support, they are primarily located
in the city. Psychologists, psychiatrists, and social
workers also tend to be concentrated in urban areas
(Rogers, Burdge, Korsching, and Donnermeyer, 1988).
Lowe (1971) says that every social system that a
person is involved in provides some amount of support.
Some groups do provide more support than others, but
rather than attempting to account for all groups that an
individual belongs to, Lowe's measure of social stability
attempts to measure "a combination of (1) the presence of
links to the social structure, (2) the strength of those
links, and (3) the amount of support available within the
group" (Lowe, 1971, p. 130). Social support and social
stability have been found to be positively correlated
with mental well-being (Hellinghausen, 1984; Kunkel,
1981; Lee, 1978; Lowe, 1971; Lowenthal et al., 1967;
Moriwaki, 1973; and Wood and Robertson, 1978).
The Research Problem
Considering the previous research on rural life,
25
urban life, and the effects on the mental state of their
residents, there are two immediate hypotheses that may be
drawn. Poor interpersonal relationships, a high division
of labor, and excess sensory stimulation may lead to
higher stress for residents of urban areas, resulting in
poor subjective well-being for urban residents. The
first hypothesis states this thesis for test.
Hypothesis I: Subjective Well-Being is better among persons residing in rural areas.
However, there is also research indicating that, due to
increased stress from sources such as social isolation
and overcrowding in the home, urban residents will have
better subjective well-being.
Hypothesis II: Subjective Well-Being is better among persons residing in urban areas.
It is possible that with the growing technology in
our society, there may not be such a strong division
between the city and the country. People are now able to
use the telephone to communicate more easily and the
26
automobile to travel away from the place of residence for
whatever reason necessary. Thus, people are not bound to
their place of residence as much as may have been the
case earlier in this century. Further, while there may
be stressful factors involved in both types of
environment, the stress may be equal, resulting in no
difference in level of subjective well-being. This leads
to Hypothesis III.
Hypothesis III. There is no difference in degree of subjective well-being in urban and rural residents.
Several variables have previously been found to
affect mental well-being and its components: social
class (Clemente and Saur, 1976; Kunkel, 1980; Lowe and
Witt, 1978), gender (Lowe and Smith, 1987), race (Alston,
Lowe, and Wrigley, 1974; Thomas and Hughes, 1986), and
age (Witt, 1978). Further, Campbell, Converse, and
Rogers (1976) report that age should be controlled when
examining mental well-being because of differentials in
health and career patterns. This analysis will control
for all four factors.
After the initial control variables have been taken
into account, social stability will be controlled. If
rural stress results in better subjective well-being in
urban areas, and social stability is higher in rural
areas, a control for social stability should increase the
27
positive association between urbanism and subjective
well-being. If social stability is higher in urban
areas, the strength of this association should decrease.
In the General Social Surveys (the data set used in
this study), there is no means of measuring artificial
social support, such as that available through treatment
facilities, which is potentially more readily available
in the city. If subjective well-being is shown to be
better in urban areas after controlling for social
stability, it will not be possible to ascertain whether
these differences are due to greater stress in rural
areas or if they are due to the greater levels of
artificial support available in cities.
If, on the other hand, rural residents are initially
shown to have better subjective well-being, and if rural
residents have higher social stability, a control for
social stability should decrease the negative
relationship between urbanism and subjective well-being.
If rural areas are lower in stress, resulting in better
subjective well-being, and urban residents have higher
social stability, controlling for social stability should
increase the negative association between urbanism and
subjective well-being.
CHAPTER II
METHODS
In this chapter, a research design will be created
in order to answer the question of whether subjective
well-being is better in rural or urban areas. The
discussion will include a description of the national
surveys which comprise the data base, operationalization
of subjective well-being, location of residence, and all
control variables.
The Sample
The data used in this analysis were taken from the
General Social Surveys (GSS), conducted by the National
Opinion Research Center (NORC) at the University of
Chicago (Davis and Smith, 1989b). The General Social
Surveys are based on a full probability sample design.
They utilize a multi-stage full probability sample to the
block or segment level. Quota sampling is used at the
block level with quotas based on sex, age, and employment
status. The Primary Sampling Units implemented are
Standard Metropolitan Statistical Areas (SMSAs) or non
metropolitan counties selected in NORC's Master Sample.
28
29
Before selection, the SMSAs and counties were stratified
by region, age, and race (for more details, see Davis and
Smith, 1989a). The universe sampled includes the total
non-institutionalized, English-speaking population of the
continental United States, 18 years of age and older.
This analysis is limited to persons residing in the
central cities of the 100 largest SMSAs and the most
rural areas in the United states. In order to control
for the effects of race, only whites are included in the
present analysis. In addition, only those respondents
who were asked the sociability items and the items
included in the Subjective Well-Being index were
included. Due to the rotation of questions across years,
the 1978, 1983, 1986, 1988, and 1989 surveys are used.
These are the years in which all of the necessary items
to build the Subjective Well-Being and Social stability
measures were included. After eliminating blacks,
respondents who do not reside in the central cities or
most rural areas, and respondents who were not asked the
necessary questions, a total of 1419 respondents
remained.
Operationalization of Variables
The Dependent Variable
The measure of Subjective Well-Being is a factor
score index in which a series of satisfaction questions
and a general happiness question are combined. General
happiness is weighted on a three-point scale.
30
Respondents were asked the question, "Taken all together,
how would you say things are these days -- would you say
that you are very happy, pretty happy, or not too happy?"
Responses ranged from (3) very happy, (2) pretty happy,
to (1) not too happy. For the satisfaction questions,
respondents were asked to indicate the amount of
satisfaction they are getting from each of the following
four areas of life: (1) "your non-working activities
hobbies and so on;" (2) "your family life;" (3) "your
friendships;" and (4) "your health and physical
condition." The item concerning satisfaction with place
of residence that is used in Lowe's measure of mental
well-being was dropped from this measure. Previous
findings (Carpenter, 1977; Fuguitt and Zuiches, 1975)
have shown that, while rural residents are satisfied with
the place in which they live, urban residents show great
desire to live elsewhere. If satisfaction with size of
place was used in this measure, it would then be biased
in favor of rural residents.
31
Responses to the satisfaction items ranged from "a
very great deal" (scored seven) to "none" (scored one).
Subjective Well-Being is the standardized factor score
based on the unrotated first principal component (see
Armor and Couch, 1972, for details). The first principal
component (Table 1) accounted for 45% of the variance in
items.
The Independent Variable
In order to adequately measure the differences
between the crowding of the city and the isolation of the
city, Urbanism utilized both the NORC size of place and
Survey Research Center, University of Michigan (SRC) New
Belt code measures. It was divided into two categories,
rural and center city. Urban was coded 2 and included
the central cities of the 100 largest SMSAs. Rural was
coded 1 and included areas of open country within larger
civil divisions (e.g., township, division) as defined by
NORC which were outside of the suburbs of the 100 largest
SMSAs as defined by SRC (see Davis and Smith, 1989a, for
description).
Control Variables
The rest of the variables used in the study will be
defined as follows. For the variable Sex, males were
32
coded as 1 and females as 2. Age was coded as to actual
age of respondent in years.
Socioeconomic status was measured by four questions.
To measure occupational prestige of the head of the
household, the occupation of the respondent was used if
it was a male or a single female; for married females,
the occupation of the spouse was used. The GSS
occupational prestige scores were used (see Davis and
Smith, 1989a, for details). For subjective social class,
respondents were asked, "If you were asked to use one of
the four names for your social class, which would you say
you belong in: the lower class, the working class, the
middle class, or the upper class?" Lower class was coded
1, working class--2, middle class--3, upper class--4.
The respondent's education was coded from zero to twenty,
reflecting the number of years of formal education
obtained. Family income was first converted into dollar
amounts, using the midpoint of each of the original
categories. In the 1977-1980 surveys, there were 16
categories for family income. The lowest category was
for family incomes under $1,000 and was coded 500. The
highest category was for family incomes $50,000 or over
and was coded 55,000. The 1982-1985 surveys included 17
categories for family income. The lowest category was
for family incomes under $1,000 and was coded 500. The
33
highest category was for family incomes $50,000 or over
and was coded 55,000. There were 20 categories included
for family income in the 1986-1989 surveys. The lowest
category was for family incomes under $1,000 and was
coded 500. The highest was for family incomes $60,000 or
over and was coded 65,000. The dollar amounts were then
standardized by using a z-transformation within each
year. Thus, all respondents' incomes were standardized
for their respective years. The final measure of SES was
a standardized factor score based on the unrotated first
principal component (see Armor and Couch, 1972, for
details). The first principal component accounted for
51.2% of the variance in items (Table 2).
The index of Social Stability used is a modification
of an earlier index developed by Lowe (1971). Both
conjugal and extended family are potential sources of
support. Sources of conjugal support are measured by
asking the respondent if sjhe is married and currently
living with the spouse. Another indication of whether
the respondent may receive support from relatives or
adults is obtained by asking whether sjhe lives with a
relative, an adult, or anyone. Further, the respondent
was asked whether social evenings spent were ever spent
with relatives, parents, siblings, friends, and
neighbors.
34
The respondent was asked questions about religious
identification and frequency of church attendance in
order to measure religious ties and the strength of those
ties.
Employment is an important means of support for an
individual. The respondent's and spouse's current
employment status were included, along with union
membership. Additionally, the respondent was questioned
about memberships in voluntary associations and the
number of such associations in which sjhe was a member.
The items included in the social stability measure are as
follows.
(1) Is the respondent married and living with hisjher spouse?
(2) Does the respondent live with any relative?
( 3) Does the respondent live with any adult?
(4) Does the respondent live with anyone?
(5) Is the respondent employed?
(6) Is the respondent's spouse employed?
(7) Is the respondent or spouse employed?
(8) Does the respondent ever spend a social evening with relatives?
(9) Does the respondent ever spend a social evening with parents?
(10) Does the respondent ever spend a social evening with siblings?
35
(11) Does the respondent ever spend a social evening with friends?
(12) Does the respondent ever spend a social evening with neighbors?
(13) Does the respondent have some religious identification?
(14) Does the respondent attend church greater than once a year?
(15) Does the respondent attend church more than once a month?
(16) Is the respondent a union member?
(17) Does the respondent claim membership in any voluntary association?
(18) Is the respondent a member of three or more voluntary association?
Each of the previous items concerning the respondent was
coded as 1 if the question was answered affirmatively,
and 0, if not. The level of social stability is the sum
of all of the items. The possible range for the social
stability variable is 0 to 18. The actual range for
respondents on this variable is also 0 to 18 with a mean
of 11.43 and standard deviation of 3.40.
TABLE 1
Principal Component Factor Analysis of Subjective Well-Being Items
36
=========================================================
Item Description Loadings
Principal Component Factor
Happiness Satisfaction from hobbies Satisfaction from family life Satisfaction from friendships Satisfaction from health Eigenvalue
.631
.654
.683
.717
.667 2.252
TABLE 2
Principal Component Factor Analysis of Socioeconomic Status Items
37
=========================================================
Item Description Loadings
Principal Component Factor
Standardized Income Prestige of Head of Household Subjective Social Class Respondent Education Eigenvalue
.691
.740
.653
.773 2.049
CHAPTER III
FINDINGS
As a preliminary step, the zero-order correlations
between subjective well-being and the independent and
control variables are examined (Table 3). These are all
correlated with subjective well-being approximately as
expected. People in rural areas have better subjective
well-being than those in urban areas (r = -.084). Age is
shown to be negatively related to subjective well-being
(r = -.074). Gender is related (r = .039) to subjective
well-being with females being slightly higher than males,
while socioeconomic status (r = .275) and social
stability (r = .321) produce positive correlations which
are by far the strongest associations with the dependent
variable. Urbanism and age are significant at the .01
level, while socioeconomic status and social stability
are significant at the .001 level.
The next step in the analysis is to examine the
relationship between urbanism and subjective well-being
before any of the controls are considered. This is the
equivalent of the zero order correlation coefficient.
The analysis of variance employed indicates that the
difference between rural residents (mean = 0.025) and
38
39
urban residents (mean = -0.148) is statistically
significant at the .01 level (see Table 4). The reader
is reminded that the subjective well-being scores are
standardized on the total white population and has mean
zero and standard deviation of one. Rural residents,
then, have above average subjective well-being and urban
residents, with a mean below zero, are below average.
This is significant at the .002 level.
The second step is to consider the influence of two
variables that influence subjective well-being, but which
do not necessarily vary between rural and urban samples-
age and gender. When the means were adjusted for the
influence of these two factors, the difference between
rural and urban residents increased slightly (Table 5).
The adjusted mean of rural residents changed to 0.031 and
urban residents changed to -0.154. This shows that, when
controlling for these two variables, the difference
between rural and urban gets even larger with rural
residents still having better well-being and is
significant at the .001 level.
The third step is to consider the influence of
socioeconomic status. Social class is strongly and
positively related to subjective well-being. Persons in
urban areas have higher socioeconomic status, on average,
than do rural residents. Further, the influence of
40
social class, whether it be the increased stress
associated with lower class life or the cushioning effect
of the higher resources associated with high
socioeconomic status, should have a suppressor effect on
the relationship between urbanism and subjective well
being. Adding socioeconomic status as a covariate showed
this to be the case (Table 6). After adjustment for
socioeconomic status in addition to age and gender, rural
residents show a mean subjective well-being score of
0.080 while urban residents dropped to -0.203.
We are now ready to consider the influence of social
stability on the relationship (Table 7). The addition of
this covariate raised the mean for urban residents to
-0.137 and lowered that of rural residents to 0.014, only
slightly above the national average for whites. Clearly,
a major factor contributing to the more favorable
subjective well-being of rural residents is their higher
level of social stability. However, just as clearly, the
stresses associated with urbanism have a significant
influence on mental health.
In the analysis of variance, urbanism was treated as
a factor of classification which, in the model utilized,
did not allow it to compete equally in the explanation of
variance. The tests are now repeated using stepwise
multiple regression.
41
As can be seen in Table 8, multiple regression shows
the same effects in a slightly different form. In the
first step, the standardized partial regression
coefficient showed urbanism to be negatively correlated
(Beta = -.084) with subjective well-being. This was
significant at a level of .002. In the second step,
gender was added to the equation. When gender was added,
the effect of urbanism remained relatively the same with
a standardized regression coefficient of -0.086 and was
significant at the .002 level. Age was added to the
equation in the third step. Here, the standardized
coefficient for urbanism rose to -0.090 with a
significance level of .001. When socioeconomic status
was added to the equation in the fourth step, the
standardized coefficient for urbanism rose to -0.137 with
a significance level of .001. In this equation, urbanism
added 1.8 percent to the variance explained by the other
variables.
In the final step (Table 9), social stability was
added to the equation, and we see that urbanism retains
statistical significance in the company of these other
powerful influences on mental health. While the
standardized partial regression coefficient for urbanism
dropped to -0.073 in this equation, it is still related
to subjective well-being at the .005 level. All of the
42
other variables other than age were significant at the
.001 level. By far, the most influential variable in the
equation was social stability, which added 4.9% to the
variance in subjective well-being explained by the other
four variables. For complete results of all five steps,
see Tables 10-14 in the Appendix.
TABLE 3
Zero-Order Correlation Coefficients for Subjective Well-Being
43
=========================================================
Variable Zero-Order Correlation Coefficient
Urbanism -0.084 ** Gender 0.039
Age -0.074 ** SES 0.275 ***
Social Stability 0.321 ***
** significance under .01
*** significance under .001
TABLE 4
Mean Level of Subjective Well-Being for Rural and Urban Residents
44
=========================================================
Mean
Effect
so
N
Rural Urban
0.025 -0.148
0.087 -0.087
0.971 1.066
639 780
Unweighted Means Analysis of Variance for Subjective Well-Being
=========================================================
Sum of Squares DF F-Test Significance
Urbanism 10.546 1 10.054 0.002
Unit 1486.366 1417 Not Tested
Total 1496.912 1418
Subjective Well-Being scores have mean zero and standard deviation one. Higher scores designate better wellbeing.
TABLE 5
Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age and Gender
45
=========================================================
Rural Urban
N 639 780
Adj. Mean 0.031 -0.154
Adj. Effect 0.092 -0.092
Unweighted Means Analysis of Variance for Subjective Well-Being Adjusted
for Age and Gender
=========================================================
ss DF F-Test Significance
Urbanism 11.972 1 11.493 0.001
Covariates 12.393 2 5.948 0.003
Unit 1473.973 1415 Not Tested
Subjective Well-Being scores have mean zero and standard deviation one. Higher scores designate better wellbeing.
TABLE 6
Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age, Gender, and
Socioeconomic Status
46
=========================================================
Rural Urban
N 639 780
Adj. Mean 0.080 -0.203
Adj. Effect 0.142 -0.142
Unweighted Means Analysis of Variance for Subjective Well-Being Adjusted for Age, Gender,and Socioeconomic Status
=========================================================
ss DF F-Test Significance
Urbanism 27.409 1 28.805 Under 0.001
Covariates 140.888 3 49.355 Under 0.001
Unit 1345.478 1414 Not Tested
Subjective Well-Being scores have mean zero and standard deviation one. Higher scores designate better wellbeing.
TABLE 7
Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted
for Age, Gender, Socioeconomic Status, and Social Stability
47
=========================================================
Rural Urban
N 639 780
Adj. Mean 0.014 -0.137
Adj. Effect 0.076 -0.076
Unweighted Means Analysis of Variance for Subjective Well-Being Adjusted for
Age, Gender, Socioeconomic Status, and Social Stability
=========================================================
ss DF F-Test Significance
Urbanism 7.238 1 8.042 0.005
Covariates 214.673 4 59.632 Under 0.001
Unit 1271.693 1413 Not Tested
Subjective Well-Being scores have mean zero and standard deviation one. Higher scores designate better wellbeing.
TABLE 8
Results by Step for Urbanism in Stepwise Multiple Regression on
Subjective Well-Being
48
=========================================================
Variable Added
Step 1
Gender
Age
SES
Stability
Standardized Coefficient for Urbanism T-Test
-0.084 -3.17
-0.086 -3.23
-0.090 -3.39
-0.137 -5.37
-0.073 -2.84
Unique Variance
Sig. for Urbanism R2
.002 .007 .007
.002 .007 .009
.001 .008 .015
<.001 .018 .101
.005 .005 .150
TABLE 9
Regression Results for Subjective Well-Being
Final Step
49
=========================================================
Standardized Variable Coefficient Significance
Urbanism -0.073 .005
Gender 0.097 <.001
Age 0.037 .169
SES 0.212 <.001
Social stability 0.264 <.001
Multiple Correlation Squared = 0.150
Unique Variance
.005
.009
.001
.037
.049
CHAPTER IV
SUMMARY
A review of the literature has shown two schools of
thought concerning differentials between the size of
place of residence and mental health. Both arguments
view stress as a major factor in influencing mental
health. Proponents of the theory that urban residents
have better mental health argue that rural life causes
stress because of factors such as crowding in the home,
isolation, and factors associated with financial
hardships which are detrimental to a person's mental
state. On the other hand is the contention that urban
life is characterized by a overcrowding, high division of
labor, and excess sensory stimulation, all of which are
potential causes of stress. Advocates of this theory
assert that rural residents have better forms of support
that they can turn to in times of stress in order to cope
with this stress.
Attempts to measure the differentials between urban
and rural residents' mental health have yielded ambiguous
results. This is due to inconsistent and problematic
methods of measurement such as treatment rates for mental
illnesses and use of the Global Happiness Item.
50
51
Recently, the use of subjective well-being has helped to
alleviate such problems (Gove et al., 1983; Lowe and
Smith, 1987; Lowe and Witt, 1978; McLanahan and Adams,
1989).
Three hypotheses have been stated. Hypothesis I is
that higher stress from poor interpersonal relationships
and excess sensory stimulation in urban areas will result
in rural residents having better subjective well-being.
Hypothesis II follows the line of thinking that rural
residents will have more stress from overcrowding in the
home and social isolation and, therefore, states that
urban residents will have better subjective well-being.
There is the possibility that the technological growth of
society has reduced the differences between rural and
urban areas and that stress is equal in both areas.
Hypothesis III is that there is no difference between
urban and rural residents in subjective well-being.
This analysis has shown that, before controlling for
relevant variables, rural residents have significantly
better subjective well-being. When controlling for
gender, age, and socioeconomic status, the differences
get larger with the addition of each successive control
variable. When social stability is added as a control
variable, the differences become smaller, but there is
still a significant difference. Rural residents still
52
have better well-being. These results are consistent
when two different types of analysis are employed, those
being analysis of variance and stepwise multiple
regression.
An important finding in this analysis concerns the
effect of social stability on the relationship between
urbanism and subjective well-being. In the step where
gender, age, and socioeconomic status were added to the
regression equation, there was a strong relationship
between urbanism and well-being. When social stability
was added, the relationship was reduced, but remained
significant. At this point, it may be possible to
conclude that the differences in well-being are not large
enough to provide support for the hypothesis that stress
is greater in urban areas which results in better well
being for rural residents. However, since social
stability is believed to be an important factor in
dealing with stress, the addition of this variable should
compensate for the different means of coping that the two
groups (rural and urban residents) have available.
Social stability has a strong impact on the relationship
between urbanism and well-being due to the strong
negative relationship that it has with urbanism. Because
of the strong relationship between social stability and
well-being, the relationship between urbanism and well-
53
being weakens when social stability is controlled. This
relationship remains significant though, thus providing
support for Hypothesis I: Subjective Well-Being is
better among persons residing in rural areas.
It is possible, then, to conclude that urban life
has a more detrimental effect on its residents than rural
life. This is likely because urban residents are the
recipients of more stress than those residing in rural
areas. Rather than the overcrowding in the home and
social isolation in rural areas, it appears to be
crowding on the macro level, and stress associated with
the city that leads to poor mental health. There is a
large enough differential in mental well-being that it
remains significant even when the high levels of social
stability in rural areas are controlled.
A potential problem with the conclusion drawn in
this study is that of the many separate "communities"
that exist in the city. These communities may be seen in
the form of neighborhoods, particularly ones that are
inhabited mainly by people of the same ethnic background.
Gans (1962) refers to these neighborhoods as "urban
villages." People in these neighborhoods have
characteristics similar to small rural communities.
People in these areas tend to know everyone in the
neighborhood, or they at least know something about
54
everyone. In such areas, there is solidarity and
cohesiveness that is more typical of small rural
communities than of the large city. The isolation from
one's neighbors is not the same as it may be in other
parts of the city. Thus, city life may not affect these
residents in the same way as it affects others. One may
question the effect that city life has on these
inhabitants.
There is still the possibility that a problem that
is associated with measuring mental illness by using
treatment rates is present in this analysis. Cockerham
(1989) discusses the idea that persons with poor mental
health who live in rural areas are likely to migrate to
the city in order to receive treatment. It is not
possible to measure this type of migration in the present
study due to the unavailability of data on a person's
prior place of residence. While it is not possible to
accurately measure migration, it is a factor that should
be taken into consideration. It is possible that this
could be a reason for migration, not necessarily because
of persons seeking treatment, but rather because a person
may be dissatisfied with the course that hisjher life is
taking. There may be a large number of formerly rural
residents who have moved to the city because of problems
in the country in order to resolve these difficulties.
55
Cockerham (1989) also talks about this possibility. He
says that people are likely to move in order to seek
economic, social, and cultural opportunities somewhere
else. It is possible that these people have never been
able to find what it is that they seek. Those that
remain in the country, though, are possibly the ones who
are content with their lives.
This study has shown support for the idea of
isolation and stress that is associated with the urban
lifestyle. This is consistent with Wirth's (1938) theory
of urbanism. While it has been shown that rural
residents have better subjective well-being, it should be
noted that the possibility of migration is a potential
problem. This could be resolved by the use of data that
have a measure of the individual's previous residence.
It is also relevant to question what specific stressful
factors may lead to these differences. It would be
beneficial to isolate these factors and evaluate how
people react differently to these events in the city and
in the country. This may produce more helpful
information about why rural residents have better
subjective well-being.
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APPENDIX: COMPLETE TABLES FOR STEPWISE MULTIPLE REGRESSION ON SUBJECTIVE WELL-BEING
66
TABLE 10
Results for Step 1 in Stepwise Multiple Regression on Subjective Well-Being
67
=========================================================
Variable Unstandardized Coefficient
Standardized Coefficient
Urbanism -0.1733 -0.084
R2 F p
= = =
0.007 10.05 with 1 and 1417 degrees of freedom .002
T-Test Sig.
-3.17 .002
TABLE 11
Results for Step 2 in Stepwise Multiple Regression on Subjective Well-Being
68
=========================================================
Variable
Urbanism
Gender
R2 = 0.009
Unstandardized Coefficient
-0.1766
0.0875
Standardized Coefficient
-0.086
0.042
F p
= =
6.31 with 2 and 1416 degrees of freedom .002
T-Test Sig.
-3.23 .002
1.60 .110
TABLE 12
Results for Step 3 in Stepwise Multiple Regression on Subjective Well-Being
69
=========================================================
Variable
Urbanism
Gender
Age
R2 = 0.015
Unstandardized Coefficient
-0.1850
0.0978
-0.0046
Standardized Coefficient
-0.090
0.047
-0.081
F = 7.34 with 3 and 1415 degrees of freedom p = <.001
T-Test Sig.
-3.39 .001
1.79 .074
-3.05 .003
70
TABLE 13
Results for Step 4 in Stepwise Multiple Regression on Subjective Well-Being
=========================================================
Variable
Urbanism
Gender
Age
SES
R2 = 0.101
Unstandardized Coefficient
-0.2836
0.1658
-0.0032
0.3097
Standardized Coefficient
-0.137
0.080
-0.057
0.300
T-Test Sig.
- 5.37 <.001
3.15 .002
- 2.24 .026
11.62 <.001
F = 39.78 with 4 and 1414 degrees of freedom p = <.001
TABLE 14
Results for Step 5 in Stepwise Multiple Regression on Subjective Well-Being
71
=========================================================
Unstandardized Variable Coefficient
Urbanism -0.1515
Gender 0.2004
Age 0.0021
SES 0.2190
stability 0.0800
R2 = 0.150
Standardized Coefficient
-0.073
0.097
0.037
0.212
0.264
T-Test
-2.84
3.91
1.38
7.88
9.05
F = 50.05 with 5 and 1413 degrees of freedom p = <.001
Sig.
.005
<.001
.169
<.001
<.001