A Model of Loneliness in Older Adults

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Journal of Gerontology: PSYCHOLOGICAL SCIENCES

1999, Vol. 54B, N o. 4, P231-P239

Copyright 1999 by The Gerontological Society of America

A Model of Loneliness in Older Adults

Bronwyn S. Fees,

1

Peter Martin,

23

and Leonard W. Poon

4

'School of Family and Human Services, Kansas State University, Manhattan.

2

Department of Human Development and Family Studies, Iowa State University, Ames.

3

German C enter for Aging Research, University of Heidelberg, Germany.

4

Gerontology C enter, University of Georgia, Athens.

Loneliness and physical health status in older adults have been correlated strongly but the predictive direction is unclear. This

study examined the relationship between personality, cognition, social

network

and ag e modeled as predictors of loneliness

in older Americans. Self-assessed health mediated the relationship. The sample consisted of 208 independently living

individ-

uals 60 to 106 years of age from the southern region of the United States. Model comparison revealed health did not mediate

the

relationship significantly

but that

self-reported loneliness

itself mediated between personal

characteristics

and perceived

health. Results indicate anxiety, frequency of telephone contact and age, but not requency of face-to-face contact with

others or cognitive functioning, affect perceived loneliness. Perceived loneliness mediates the effects of anxiety, frequency of

telephone contact

and age on self-assessed health.

Feelings

o f

loneliness decrease

one s

evaluation

of physical

well-being.

ONELINESS is a pervasive issue among elderly adults, who

-/ often face a loss of comm itted intimate relationships and

communication with others, which are valued by the Western

culture (de Jong-G ierveld, 1987), a decline in health, and a de-

cline in personal resources. Developing a theoretical model of

loneliness that represents the experiences of elderly persons in

everyday life has been a focus of research by gerontolog ists for

several decades. Loneliness is a concept that relies on compar-

isons. It

is

defined as a sentiment that is experienced when one 's

lifestyle (state) is deprived of

the

relationships desired and cur-

rent relationships are seen as inadequate in comparison to those

of the past, to those anticipated in the future, o r to those pos-

sessed by other people (Lopata, 1995; Weiss, 1973). The pur-

pose of this study was to examine predictors of loneliness and

its relationship with self-assessed physical w ell-being.

Forty percent of the elderly population has experienced some

form of loneliness according to data from Europe and the

United States (Weeks, 1994). Weeks (1994) further suggested

that although this percentage has been relatively stable over the

last

25

years, it may be worse than it appears. This rate has been

cause for concern given that suicide, physical ailments, and de-

pression have been outcomes associated with the presence of

loneliness in the elderly pop ulation (Creecy, Berg, & W right,

1985). Elderly persons have been regarded as particularly v ul-

nerable because they are considered at high risk for experience

of change and loss (Lopata,

1995,

p.

572).

Predictors of loneliness vary not only with transitional life

events but also with increasing maturity (Dugan & Kivett,

1994; Russell, 1996; Russell, Peplau, & Ferguson, 1978;

Weeks, 1994). Several different theoretical models of loneliness

including older adult samples have been proposed. De Jon g-

Gierveld (1987) hypothesized that demographic characteristics,

living arrangem ents, and personality ch aracteristics p redicted

loneliness. Creecy and colleagues (1985) included dem ographic

characteristics, self-assessed health status, and incom e as pre-

dictors. Both authors used indicators of social involvement

(e.g., social network, social activity) as mediating variables.

Mullins, Elston, and Gutkowski (1996) proposed perceived

health status and self-rated economic condition as mediators of

the influence of demographic characteristics on loneliness.

The mod el we propose shares predictors with each of these

mo dels; however, we believe the literature suppo rts the inclu-

sion of personal traits as w ell as interpersonal relationships as

determinants of loneliness. Our m odel was based on a larger

conceptual framework that assesses successful adaptation in old

age (Poon et al., 1992). We proposed that mental health prob-

lems in later life a re, in part, dependent on individual character-

istics including personality, level of cognitive functioning, level

of social support (e.g., social network), and physical health (see

Figure 1). Physical well-being served as a mediator between

constructs because decline in health remains a dominant issue

among older adults, compared to the younger population, po-

tentially limiting interaction in stimulating relationships, espe-

cially among the oldest.

Martin, Hagberg, and Poon (1997) tested this conceptual

model across cultures by analyzing data from Am erican and

Swedish centenarians. Personality (conceptualized as anxiety),

physical health, and social support were strong predictors of

loneliness in Americans, whereas social support and cog nition

predicted loneliness for Swedish centenarians. Data were ana-

lyzed using Partial Least Squares Estimation (LVPLS) Soft

Modeling (Falk & Miller, 1992).

In light of recent research suggesting stressors in life may

have an adverse physiological affect on im mun e system func-

tioning (see review by Kiecolt-Glaser & Glaser, 1992), we ex-

amined a second hypothesis in w hich loneliness served simul-

taneously as a predictor for physical well-being and a mediator

for the remaining constructs (see Figure 2).

The focus of

the

present analyses was to determine whether

the model employed by Martin and colleagues (1997) was pre-

dictive for a more inclusive age range of older Americans using

structural equation modeling with simultaneous solutions and

to further examine the relationship between physical well-being

and loneliness. Chronological ag e was added as a predictor to

the model to examine its effect. Each construct will be reviewed

separately in the following paragraphs.

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Figure

1.

Conceptual M odel of Loneliness in Older Adults.

Figure 2. Conceptual M odel of Physical Weil-Being in Older Adults.

Personality

Research has established a strong relationship between feel-

ings of loneliness and persona lity characteristics, particularly

anxiety. Anxiety has been characterized by emotional instabil-

ity, threat sensitivity, suspiciousness, gu ilt, low integration, and

tension (Cattell, Eber, & Tatsuoka, 1970). Although anxiety

often manifests itself in reduced physical health, men and

women who reported being lonely also reported being anxious

(often being treated for nervousness) and feeling depressed

(Berg, Mellstrom, Persson, & Svanborg,

1981;

Russell, Peplau,

& Cu trona, 1980; Russell et al., 1978). An individual with a

low self-concept (correlated w ith anxiety) may not have satis-

factory relationships with others and may n ot seek out new re-

lationships that indirectly affect loneliness (de Jong-Gierveld,

1987). Social phobia, apprehension, and fear of embarrassment

in public have been related to a decrease in interaction leading

to loneliness as w ell (Weeks, 1994).

Cognitive Functioning

Decreased efficiency in mental processing has been observed

in elderly adults, yet few studies include cognitive functioning

directly as a predictor of loneliness. De Jong-Gierveld (1987)

took a cognitive processes approach by examining respon-

dents' subjective evaluations and interpretations of their per-

sonal experiences rather than using objective m easures of par-

ticipants' intellectual functioning. S ubjective evaluations of

relationships strongly predicted loneliness. Berg and colleagues

(1981) found no differences in an objective measure of intellec-

tual functioning, verbal ability, between lonely and not lonely

participants. Neither of these studies exam ined the effect of

fluid intelligence, the ability to think logically and to reason ab-

stractly, on loneliness.

Level of cognitive functioning may affect loneliness in sev-

eral ways. It may serve as a buffer against feelings of loneli-

ness; that is, as physical strength and coordination decline and

limit activity, one can remain cognitively inquisitive and alert,

thinking and imagining situations beyond one's own situation.

Conversely, a high level of cognition may be a source of frus-

tration in that one is able to think of activities to do, but is un-

able to pursue those goals. No relationship between cognition

and loneliness was found in the American centenarians; how-

ever, cognitive functioning was negatively related in Sw edish

centenarians (Martin et

al.,

1997).

Social Network

A num ber of research studies have suggested that a decline

in or absence of social support is predictive of loneliness.

Russell (1996) found that frequency of contact and number of

family members were not strongly predictive of loneliness;

however, the perceived quality of recent relationships was. Type

of living arrangement has also been determined to affect loneli-

ness (de Jong-Gierveld, 1987). In a model of loneliness based

upon persons 25 -75 years of

age,

living with a partner signifi-

cantly and negatively predicted loneliness whereas being single

significantly and positively predicted loneliness.

Frequency of contact does appear to be predictive when the

type of relationship is considered. Mullins and Dugan 's (1990)

survey of residents in urban co ngregate housing determined

that frequency of contact with neighbo rs and friends, but not

with family, w as important to reducing the feelings of loneli-

ness,

as was the quality of the relationships with friends. In a

separate study, Dugan and Kivett's (1994) survey of rural inde-

pendently living elderly persons revealed that infrequent visits

with family members (siblings) predicted loneliness as did the

loss of a spouse. Lack of friends was an important predictor of

loneliness in Swedish 70-year-olds (Berg et al., 1981).

Because loneliness may be realized by a lack of communica-

tion with others (de Jong-Gierveld, 1987), we chose to measure

social networks by the frequency of contact individuals had

with others, either through visits or over the telephone. Each

contact represented an opportunity for comm unication and rela-

tionship building.


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A MODEL OFLONEUNESS

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Age

Although a decline in physical health is common w ith age, re-

search literature has been inconclusive regarding the role of age

in predicting loneliness among older adults. College students

have been found to report higher levels of loneliness than older

adults (Russell, 1996). However, among rural adults 65 years of

age and older, Dugan and Kivett (1994) found that over half

(68%) of the sample reported social loneliness som etimes or

quite often. The authors concluded this rate was similar to that

of the general population of persons aged 65 years and older.

Creecy and colleagues (1985) concluded that age had an in-

direct effect on loneliness that was mediated by social activity

and social fulfillment, explaining less than 1% of the variance

in loneliness. Similar results were reported by de Jong-Gierveld

(1987), who found that age did not have a significant direct ef-

fect on loneliness in persons 2 5-75 years old. However, others

suggest a positive relationship between age and loneliness

(Fischer & Phillips, 1982). Exam ination of single cohort sam-

ples does suggest that loneliness and age are related. Berg and

colleagues (1981) found that 19% of their Swedish sample of

septuagenarians reported som e or frequent loneliness.

Approximately one third of a sample of centenarians in the

United States reported loneliness som etim es or often, as

did 44% of Swedish centenarians (Martin et al.,

1997).

A na-

tional Swedish study in which the proportion of persons report-

ing loneliness increased from 20% in sexagen arians to over

40% in octogenarians was cited by Berg and colleagues (1981).

Our intent was to further examine the direct effect of age on

physical health and loneliness and the effect on each construct

when mediated by the other.

Self-Assessed Physical Health

Both domestic and international studies have found that poor

self-assessed phy sical health (Mullins et al., 1996; Mullins,

Johnston, & Anderson, 1988; Mullins & Mushel, 1992;

Wenger, Davies, Shahtahmasebi, & Scott, 1996) and number of

chronic illnesses (Russell, 1996) correlated positively and

strongly w ith loneliness in elderly ad ults. Lonely elderly men

and women had more negative assessments of health and feel-

ings of fatigue than did elderly men and wom en who were not

lonely. Lonely participants also complained of backaches,

headaches, and nonspecific nausea (Berg et al.,

1981).

A pro-

gressive decrease in hearing has also been associated with feel-

ings of loneliness in elderly persons (Dugan & Kivett, 1994).

Whether poor health predicts lonely feelings or loneliness pre-

dicts self-assessed poor health is not

clear.

Self-assessed physical

health was found to mediate the effects of disability and educa-

tion on loneliness (Mullins et

al.,

1996). Physical health mediated

the effect of anxiety on loneliness in American centenarians

(Martin et al.,

1997).

Researchers have also concluded that lone-

liness may be predictive of mental health. Bazargan and Barbre

(1992) found loneliness explained variance in self-evaluations of

memory loss in older Black adults. These conclusions p rovide

support for analysis of both models as proposed.

METHODS

Participants and Procedure

The sample for

this

analysis (n = 208) was drawn from Phase

1 of the Georgia Centenarian Study (Poon et al., 1992) con-

ducted at the University of Georgia (N

=

262). The multidisci-

plinary study collected data on three cohorts of cognitively in-

tact, independently living individuals: sexagenarians, octoge-

narians, and centenarians. Participant inclusion criteria included

a minimum score of 20 on the Mini-Mental Status Exam

(Folstein, Folstein, & McH ugh, 1975) given at the beginning of

the interview/testing session and a Stage 2 or higher level on

the Global Deterioration S cale (Reisberg, Ferris, De Leon, &

Crook, 1982). Data from each of the three cohorts were aggre-

gated in the following analyses.

Participants were recruited primarily from the state of

Georgia by the U niversity of Georgia at Athens (UGA ) Survey

Research Center. Interviews and testing of centenarians were

conducted at the participant's place of residence. G roups of

6-1 0 sexagenarians and octogenarians met in a common p lace

to be interviewed and tested. Two thirds of the sample were fe-

male and approximately 72% w ere Wh ite. Between cohorts,

the level of formal education decreased with an increase in age.

Widowhood increased with age. The majority of

the

sample re-

ported good or excellent health (see Table 1).

A cross-tabular analysis of the sociodemographic character-

istics of cases w ith missing data ( n = 54) revealed that these

cases differed from the included cases on age and m arital sta-

tus.

More centenarians and widowed adults were excluded than

expected and fewer sexagenarians and married adults were ex-

cluded than expected. N o group differences were found for sex,

education, race, or income.

Variables and Instruments

Three subscales of anxiety were used from the Sixteen

Personality Factor questionnaire (16PF; Cattell et al., 1970).

The three first-order factors were measured on a normed scale

from

1

(low) to 10 (high) and included (1) emotional stability,

(2) apprehension, and (3) tension. High scores reflected high

anxiety. Reported test-retest reliability (1 to 7 days) for each of

the scales, respectively, were .79 to .82, .72 to .83, and .81 to

.90 (Cattell et al., 1970).

Cognition was measured with three subtests from the

Wechsler Adult Intelligence Scale-Revised (Wechsler, 1987):

picture arrangement, block design, and arithmetic. Each mea-

sure was continuous; high scores reflected high cognitive abil-

ity. The average reported split-half reliability coefficient for pic-

ture arrangement was .74; block design and arithmetic

exceeded .80 (Kaufman, 1985).

Social Network was measured with two questions taken

from the Older Americans Resources and S ervices Procedures

(OARS; Fillenbaum, 1988) Interaction scale: About how many

times did you talk to someone— friends, relatives, or others—

on the telephone in the past week and How many times dur-

ing the past week did you spend some time with som eone who

does not live with you; that is, you went to see them o r they

came to visit you, or you went out to do things together. Both

measures were scored from 3 (once a day) to 0 (not at all).

Reported reliability coefficient for the scale was .56

(Fillenbaum, 1988).

Although w e intended to measure the extent of involvement in

social relationships, preliminary confirmatory factor analyses in-

dicated that w e were, in fact, measuring two unique constructs.

The first was telephone interaction, which may be a dominant

means of commun ication am ong those who are not indepen-


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Table

1.

Participant Characteristics

Characteristics

Age Range (years)

Mean (SD)

Gender (n)

Male

Female

Race(«)

White

African American

Education (n)

0-4 years

5-8 years

Some high school

Completed secondary

Business/trade school

1-3 years of college

Completed college

Graduate school

Marital Status (n)

Single

Married

Widowed

Divorced

Separated

Missing

Subjective Health (n)

Poor

Fair

Good

Excellent

Sexagenarians

(n = 82)

60-^9

64.96(2.80)

33

49

57

25

4

6

11

15

5

10

13

18

2

50

19

9

2

0

5

10

45

22

Octogenarians

(n = 79)

79-89

82.59 (2.45)

26

53

61

18

3

14

15

7

8

10

5

17

0

29

46

4

0

0

1

21

40

17

Centenarians

(n = 47)

99-106

100.79 (1.52)

11

36

31

16

8

9

6

5

4

6

5

4

4

1

39

2

0

1

4

14

27

2

Total Group

n = 208)

60-106

79.75 (14.00)

70

138

149

59

15

29

32

27

17

26

23

39

6

80

104

15

2

1

10

45

112

41

dently mobile or are separated from family and friends by great

distances. Visiting suggested some level of independent mo bil-

ity, in which case there may be less reliance on the telephone

than for less able-bodied persons or for those who live farther

from family and friends. Additionally, deterioration in hearing

may actually discourage telephone communication and increase

reliance on visiting, if possible. Each question, therefore, be-

came a sing le-item indicator reflective of separate constructs;

high scores reflected frequent interaction. Age, in years, was

self-reported.

Two indicators from the O ARS (Fillenbaum, 1988) served as

indicators for the latent con struct Physical Illness. The first

measure assessed current perceived overall health, How would

you rate your overall health at the present time, from 3 (excel-

lent) to 0 (poor). The second indicator was a comparative indi-

cator of health, Is your health now better, about the same, or

worse than it was five years ago, from 2 (better) to 0 (worse).

Measures were recoded so that high scores reflected illness.

Reported reliability for the items was .74 (Fillenbaum, 1988).

Loneliness was measured with three indicators. The first,

Do you find yourself feeling lonely quite often, sometimes, or

almost never (OAR S; Fillenbaum , 1988), was coded as 0

(often), 1 (sometimes), and 2 (seldom ). The item was a part of

the Affective dim ension of social support, with a reported relia-

bility of .71. The second m easure was taken from the Bradburn

Affect Balance Scale (BABS; Bradburn, 1969): During the

past few weeks did you ever feel very lonely or remote from

other people, with four values ranging from 1 (not at all) to 4

(often). This item w as part of

the

negative affect balance scale

with a reported test-retest reliability of

.81

(Bradburn, 1969).

The final measure was a subscale score from the Philadelphia

Geriatric Center Morale Scale (PGC; Lawton, 1975) labeled as

lonely dissatisfaction. This subscale was composed of six di-

chotomously scored items from which an aggregated subscore

was derived. Items represented the extent to which an individ-

ual feels lonely and dissatisfied with life (Sauer & Warland,

1982, p. 223). Cronbach 's alpha was reported as .85 (Lawton,

1975) for the six-item scale. Measures were recoded so that a

high score reflected greater loneliness.

Reliability of the measures within the model may be esti-

mated from the factor lo adings; that is, the factor loading is a

measure of the validity of a construct. Because the square root

of reliability is its validity, validity squared is an estimate of the

reliability of the measure (Bollen, 1989). The presence of error

is calculated as part of mod el estimation. Refer to Table 2 for

estimated reliabilities within the mod el.

Data Analysis

A covariance matrix was generated using a listwise proce-

dure (see Table 2). Data were analyzed using the structural

equation mod eling procedures in LISREL VIII (Joreskog &

Sbrbom, 1994) with maximum likelihood estimation.


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A MODEL OF LONELINESS

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Table 2. Correlation Matrix, Means and Standard Deviations for Measurement Model (n = 208)

Indicator 1 10 11 12 13 14

1.

Emotional stability

2. Apprehension

3.

Tension

4.

Picture arrangement

5. Block design

6. Arithmetic

7.

Visiting friends/relatives

8. Telephone contact

9. Age

10.

Self-health rating

11. Health problems

12. Lonely

13. Feeling lonely/remote

14. Lonely dissatisfaction

Mean

Standard Deviation

1.00

-.42

-.39

.10

.16

.17

.01

.09

.01

-.26

-.07

.32

.22

.28

5.28

1.91

1.00

.46

-.11

-.14

-.23

-.02

-.00

-.04

.22

.11

-.24

-.17

-.20

5.12

1.88

1.00

.02

.03

.02

.13

.02

-.15

.17

.00

-.18

-.18

-.23

5.01

1.87

1.00

.64

.58

.13

.20

-.48

-.24

-.13

.15

.15

.08

5.56

4.54

1.00

.64

.09

.25

-.52

-.29

-.17

.14

.10

.16

15.06

10.61

1.00

.08

.18

-.43

-.30

-.14

.23

.04

.17

9.29

4.05

1.00

.31

-.04

-.09

-.05

-.01

.08

.10

2.16

.74

1.00

-.24

-.17

-.04

.12

.22

.27

2.48

.76

1.00

.22

.24

-.12

-.21

-.18

79.75

14.00

1.00

.29

-.34

-.32

-.35

1.12

.77

1.00

-.07

-.05

-.12

1.06

.64

1.00

.48

.34

1.65

.57

1.00

.50

3.53

.92

1.00

11.04

1.24

Table 3. Measurement Model: Standardized Factor Loadings Table

4.

Correlations Among Latent Variables

Latent Construct and Indicators Factor Loading Estimated Reliabili ty Latent Variable

Personality

Emotional stability

Apprehension

Tension

Cognition

Picture arrangement

Block design

Arithmetic

Visiting Friends/Relatives

Telephone Contact

Age

Physical Health

Self-health rating

Health problems

Loneliness

Feeling lonely (OARS)

Feel very lonely/remote (BABS)

Lonely dissatisfaction (PGC)

-.64

.66

.62

.76

.84

.75

1.00

1.00

1.00

.78

.37

.60

.74

.67

.41

.44

.38

.58

.71

.56

1.00

1.00

1.00

.61

.14

.36

.55

.45

Validity (factor loading) squared is an estimate of the reliability of the indi-

cator (Bollen, 1989). x

2

(60) = 88.11,/? < .05.

RESULTS

An advantage of structural equation modeling was the use of

multiple indicators of latent constructs. Multiple indicators re-

flected the specific domain of content defined by the latent vari-

able, allowed estimation of measurement error, and simultane-

ous estimation of parameters in the model. Preliminary

confirmatory factor analyses were conducted using LISREL

VIII (Joreskog & S orbom, 1994) to estimate the measurement

model w ith significant indicators of the latent constructs. The

proposed measurement model and regression model were con-

ducted concurrently (see Table 3 for factor loadings and Table 4

for correlations am ong latent variables).

To

examine the direct, indirect, and total effects of

the

latent

exogenous constructs on loneliness, nested mod els were com-

1.

2.

3.

4.

5.

6.

7.

Physical Illness

Loneliness

Anxiety

Cognition

Visiting

Telephone Contact

Age

Note: n = 208

—

-.55

.38

-.40

-.11

-.19

.27

—

-.50

.24

.09

.31

-.26

—

-.19

.04

-.03

-.10

—

.12 —

.27 .31 —

-.61 -.04 -.24 —

pared. First, a nonmediated model was tested in which the direct

path coefficient from the mediator to the outcome was fixed to

zero and all other paths were estimated (Baron & K enny, 1986).

Second, a fully recursive, mediated model w as run to assess me-

diation. Total effects were decomposed in the later model.

Model A:

Loneliness

as

Outcome

The focus of this first set of analyses was to exam ine the direct

and mediated effects of each construct on loneliness. Resu lts of

the nonmediated model indicated a reasonable fit of the model to

the data, x

2

(60) = 88.1 1,/? < .05, GFI = .95, AGFI = .90.

Regression coefficients were significant betw een Anxiety and

Physical Illness (standardized coefficients reported), 7 =

.48,

t =

4.16, as well as Anxiety and Loneliness, 7 =

.60,

t = 4.57. Higher

levels of anxiety were related to higher levels of physical illness

and higher levels of loneliness. Age significantly predicted

Physical Illness, 7 =

.23,

t

=

2.03 , and Loneliness, 7 = .36, t =

3.16, suggesting the older the individual, the higher the evaluation

of physical illness and the greater loneliness experienced.

Telephone contact negatively predicted Loneliness, 7 = - .23, t =

2.73. Cognition and Visiting were not predictive of either criterion

variable.

According to Baron and Kenny (1986), mediation is present

if the significant coefficients between the latent exogenous

(Anxiety and Age) and the latent endogenous (Loneliness) are

reduced (partially mediated ) or becom e nonsignificant (fully

mediated) when the mediating path is present and significant in


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Figure 3. Structural Model of Loneliness in Older Adults. Figure 4. Structural Model of Physical Weil-Being in Older Adults.

Table 5. Model A: Decomposition of Effects of P ersonal

Characteristics on Loneliness

Table 6. Model B: Decomposition of Effects of Personal

Characteristics on Physical Illness

Variables

Anxiety

Cognition

Visiting Others

Telephone Contact

Age

Physical Illness

R

2

Physical Illness

Direct Indirect Total

.35

-.22

-.07

-.06

.15

***

25***

— -.22

— -.07

— -.06

— .15

.28

Loneliness

Direct Indirect

.42*** .13

.22 -.08

-.02 -.03

- .21***

-.02

.28***

.05

.37*

Total

55***

.14

-.04

-.23***

.34***

.37*

.50

Variables

Anxiety

Cognition

Visiting Others

Telephone Contact

Age

Loneliness

R

2

Loneliness

Direct Indirect

55***

.14 —

-.04 —

-.23***

—

24***

Total

.55***

.14

-.04

-.23***

24***

.40

Physical Illness

Direct

.11

-.28**

-.05

.04

.00

44***

Indirect

24***

.06

-.02

-.10**

.15**

Total

35***

-.22

-.07

-.06

.15

.44***

.40

Note: n = 208. Standardized regression coefficients shown.

*p <

.05;

**p <

.01;

***p


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A MODEL OFLONEUNESS

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to .55 (t

=

4.34). The path from A ge to Illness dropped from .23

to .00 and was not significant (t = .02). Age to Loneliness (t

=

3.00) and Telephone Contact to Loneliness

( t

= 2.78) remained

virtually unchanged. Cognition emerged as a negative predictor

of Physical Illness, 7 =

- .28 ,

t = 2.41. Visiting was n ot predic-

tive. The mediated model accounted for

40%

of the variance in

Loneliness and 40% of the variance in Physical Illness.

Total effect of Anxiety on Physical Illness was significant (t =

3.45). In contrast with Model

A,

the indirect effects of Anxiety,

Telephone Contact, and Age on Physical Illness were significant

(see Table 6). Although Cog nition had a significant regression

coefficient, neither it nor Visiting had significant effects.

DISCUSSION

The models examined in these analyses were unique with re-

spect to previous mode ls in that they examined the effects of

the level of cognitive functioning and personality on loneliness

mediated by self-assessed physical health. Loneliness as a me-

diator was modeled as well, given research suggesting per-

ceived inadequate relationships affect physical w ell-being.

One of

the

most provocative findings of

these

analyses is the

relationship between loneliness and self-evaluation of health.

Elevated feelings of loneliness not only predict poor subjective

health evaluations but also transform the effects of increasing

age and anxiety on health. These findings are consistent with

the psychoneuroimmunology literature which suggests that

one's psychological characteristics, including evaluations of

personal relationships, affect one's physical health and, in this

case, one's feelings about physical health. Kiecolt-Glaser,

Garner, Speicher, Perm, and Glaser's (1984) analyses of loneli-

ness in medical students found lon eliness to be negatively re-

lated to immune functioning.

Although the relationship between health status and loneliness

in Model A was in the expected direction (poor subjective health

status predicts greater feelings of loneliness), a stronger effect was

anticipated given Martin and colleagues' results (1997) for

American centenarians and the significant change in path coeffi-

cients for anxiety and age. Self-assessed health did not serve as a

strong mediator of the effects of the o ther constructs. Several pos-

sible explanations exist for

the

apparent

discrepancy.

First, it may

be a consequence of the difference in estimation procedures be -

tween LVPLS and L ISREL. Partial least squares uses component

analyses (such as principal component analyses) to estimate the

regression coefficients, whereas the maximum likelihood estima-

tion procedure uses simultaneous solutions. Second, the sample

represents a broader age range including individuals in the Third

Age (approximate age range of 60-75 years) and Fourth Age

(persons 85 and older; Baltes & B altes, 1998), which are theo-

rized to be distinctly different groups in terms of physical and psy-

chological functioning. A third potential explanation for

the

rela-

tively weak relationship between the two may be the relative

homogeneous nature of our sample on health; mat is, about two

thirds of the participants in this study were reporting good or

ex-

cellent health. Consequently, physical illness may have a greater

mediational effect for those who experience poorer health.

However, given the near significance of die coefficient from health

to loneliness, we believe the results deserve further examination

by cohort (age groups) with a more heterogeneous health sample.

Contrary to the conclusions of

de

Jong-Gierveld (1987) and

Creecy and colleagues (1985), our results indicate that age has

a significant total effect on feelings of loneliness; the older the

participants were, the more likely they were to report loneli-

ness.

Our results also suggest the effect of old age on serf-eval-

uation of health is effectively mediated by loneliness. With ad-

vancing age, feelings of loneliness affect perceptions of health

rather than self-perceived health affecting feelings of loneliness.

Health status does appear to decline with

age:

centenarians

reported proportionally more poor and fair health whereas

sexagenarians and octogenarians reported higher percentages of

g ood and excellent health. An exception to the trend, how-

ever, is that fewer octogenarians report poor physical health,

leading u s to ask what is the effect of coho rt as a moderating

variable rather than age as a predictor. Additional analyses need

to examine how well this model fits he data for each cohort.

Consistent with the literature, a predictive positive relation-

ship is present between anxiety and feelings of loneliness (e.g.,

Berg et al., 1981; de Jong-G ierveld, 1987); greater anxiety is

reflected in grea ter feelings of lonelines s. However, like age,

when loneliness w as the mediator, the effect of anxiety on phys-

ical well-being was totally indirect. High levels of anxiety in-

crease feelings of loneliness, w hich in turn decrease assessment

of well-being. The outcome of anxiety may be both poor feel-

ings about relationships and health.

Although an anxious personality may serve a positive func-

tion (e.g., motivation for action or learning), high and continu-

ous anxiety (characterized by em otional instability, apprehen-

sion and tension) heightens sensitivity to any feelings of illness

or may m anifest itself in concrete phy sical illness. Inadequate

relationships may b e the consequence of a lack of stimulating

interaction or in overly cautious, serf-conscious behavior, char-

acteristic of an anx ious personality. These results suggest that

the linkage by w hich anxiety affects interaction and perceptions

of health needs to be explored m ore fully.

The difference in effect between the two social network vari-

ables is noteworthy. Participating in frequent telephone conver-

sations not only reduced the loneliness perceived by partici-

pants but also affected perceived health indirectly and

significantly. Visiting with someone other than a spouse or

roommate had no predictive relationship with either outcome

variable. We measured frequency of contact rather than with

whom one had contact, specifically. O ur results, therefore, are

somewhat discrepant with previous research by Ru ssell (1996)

and the conclusions of Marangoni and Ickes (1989), in which

loneliness in older adults was found to be related weakly to the

number of persons in the social network and average frequency

of social contact but strongly related to perceived quality of

contact. These results suggest frequency of contact, via the tele-

phone , is important. Older adults may b e more limited in their

physical m obility or lack the means to travel independently.

The telephone, then, becomes a dominant and readily accessi-

ble mechanism (used by all ages) to remain in contact with dis-

tant family members, such as children, and friends, allowing

adults to maintain an emotionally intimate relationship. Once

again, it is important to no te the characteristics of the sample.

All participants were living independently. Mo st centenarians

in this sample were w idowed, and m ore than half of the sexage-

narians were married as were about one third of the octogenari-

ans;

therefore, for many younger participants, the presence of

a

spouse may limit the reliance on the physical presence of out-

siders for interaction.


8/9

P238

FEESETAL.

A second possible explanation for the discrepancy is that re-

spondents, as a whole, w ere expressing m ore emotional loneli-

ness rather than social loneliness (Weiss, 1973). The amount of

face-to-face contact with o thers (i.e., visiting) would be less rel-

evant than having an intimate confidant, a relationship that

could be maintained over the telephone . This explanation is

consistent with the strong positive relationship between anxiety

and loneliness given that anxiety w as in part assessed by em o-

tional stability (Cattell et al., 1970).

Limitations an d Implications

We recognize several limitations in this analysis. The first is

in the manner in which loneliness was assessed. Participants

were asked, in three se parate measu res, if they felt lonely. As

such, the definition of loneliness was left to the individual; mul-

tiple interpretations of loneliness may be represented in the

analysis. The feelings of the participants appeared genuine, re-

flecting their perception of their personal status. The nature of

the question, however, does not allow us to tease out whether

the type of loneliness experienced was dom inantly social or

emotional (M arangoni & Ickes, 1989). Second, with regard to

model evaluation, our chi-square statistic was significant in the

nonmediated model. Examined alone, this would indicate a

poor fit of the model to the data (Bollen, 1989). However, given

the AGFI and GFI indices of fit (above .90) and a critical N of

200 (Hoelter, 19 83), we believe our models are not only theo-

retically but also statistically defensible.

The statement that correlation does not prove causation

(Bollen, 1989, p. 52) holds true for this model. The d ata in this

analysis represent one time period within the study, although

future analyses with the data will take a longitudinal perspec-

tive. As Bollen suggests, models can only approxim ate reality,

which is what we have attempted to do. We are attempting to

build a foundation for further model building which more accu-

rately reflects the experiences of o lder Americans living inde-

pendently. By the same token, the lack of a correlation does

not disprove causation (Bollen, 1989, p. 52). Consequently,

future data collection and analyses that are able to isolate, if

possible, variables from other agents may indeed find our initial

model to be a valid representation of reality. Obviously replica-

tion is necessary.

The generalizability of this study is limited by the character-

istics of the sample. A s noted, all participants were living inde-

pendently and lived in the southern region of the United States;

consequently, an analysis of institutionalized older adults or

adults from different regions of the country may produce re-

sults different from those presented here.

Despite these shortcomings, the im plications of this study

are clear. Loneliness does affect o ne's perceptions abou t health.

As recognized by Christian, Dluhy, and

O Neill

(1989), profes-

sionals w ho work with older adults must be attentive to this re-

lationship in their clients and keep in mind that alleviating lone-

liness may be one way of affecting overall health. Among

elderly p ersons living independently, loneliness is more preva-

lent with increasing age. Anx iety is particularly detrimental by

increasing perceived loneliness and thus perceived ill-health. It

is clear too that the telephone is a fundamental tool for older

adults living independently to maintain relationships. Increasing

sensory impairm ent, particularly hearing loss, therefore, is of

concern to effective telephone usage. As Baltes and Baltes

(1998) sugg est, we are challenged to create a cultural support

system for the Fourth

Age

that allocates more resources to com-

pensate for the increasing dysfunctionality that occurs with age.

All professionals that care for or interact with older adults must

be alert to the level of functioning and health in the individual.

Model replication relies on further analyses specifically exam-

ining the moderating effects of cohort and of residential status,

that is, dependent care versus independent living, and following

individuals over time.

ACKNOWLEDGMENTS

Funding for this research was provided by N IH Grant R01-43435.

The authors would like to thank Dan Russell, Ph D, for his review and com-

ments on this manuscript, and acknowledge a reviewer's suggestion to test the

model with loneliness as the mediating variable.

Address correspondence to Dr. Peter Martin, German Center for Research

on Aging, University of Heidelberg, Bergheimer Str. 20, 69115 Heidelberg,

Germany. E-mail: [email protected]

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Received January

5

1998

Accepted December

22,

1998

A Model of Loneliness in Older Adults

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