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Determinants of socialengagement in older menR. H. Harwood , P. Pound & S. EbrahimPublished online: 19 Aug 2010.

To cite this article: R. H. Harwood , P. Pound & S. Ebrahim (2000) Determinants ofsocial engagement in older men, Psychology, Health & Medicine, 5:1, 75-85, DOI:10.1080/135485000106025

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PSYCHOLOGY, HEALTH & M EDICINE, VOL. 5, NO. 1, 2000

Determinants of social engagement in older

men

R. H. HARWOOD, P. POUND & S. EBRAHIM

University Department of Primary Care and Population Sciences, Royal Free Hospital School of

Medicine, London, UK

Abstract The objective of this study was to investigate associations between social engagement and

health and social variables. Cross-sectional analysis of questionnaire data from a national cohort

study was carried one. Participants were 5,905 men aged 51± 70 years, from 24 general practices

from 24 British towns. A nine-item social engagement scale was used as the outcome measurement.

Greater social engagement was associated with younger age, higher social class, house and car

ownership, being married, having fewer medical diagnoses, no disability and better self-perceived

health. Men who had suffered a stroke or heart attack had less engagement than men who had not.

Confound ing by age and socio-economic factors explained the relationship between social engagement

and heart attack. Confounding did not explain the poorer social engagement experienced by men who

had had a stroke, which appeared to be mediated by poorer self-perceived health. We have found age,

social class, marital status, home and car ownership and physical health to be associated with social

engagement. A diagnosis of stroke was associated with poorer social engagement, independently of

social and economic factors.

Introduction

The importance of considering quality of life in health research is now well established.

Global quality of life is hard to de® ne (Ebrahim, 1995), and is therefore hard to measure.

Another approach is to concentrate on more limited but measurable elements of quality of life

(Lawton et al., 1999). The World Health Organization have recently rede® ned the conse-

quences of disease in terms of body function, activity and participation, replacing the

concepts of impairment, disability and handicap from the International classi ® cation of impair-

ments, disabilities and handicaps (World Health Organization, 1980). These positive concepts

of activity Ð the nature and extent of activities associated with everyday life Ð and partici-

pation Ð the nature and extent of a person’ s involvement in life situations Ð are of particular

relevance in de® ning successful aging.

Study of `social engagement’ has its roots in social gerontology. It is de® ned as `the

degree of participation in the social milieu’ (Morgan et al., 1987), almost identical to the new

W HO de® nition of `participation’ . Social disengagement was originally hypothesized as a

normal, adaptive reaction to old age (Cumming & Henry, 1961). This view is generally

Address for correspondence: Dr Rowan Harwood, Consultant Geriatrician, Department of Health Care of the

Elderly, A Floor East Block, Queen’ s Medical Centre, Nottingham NG7 2UH, UK. Tel: 1 44 0115 924 9924 ext 42809;

Fax: 1 44 0115 970 9947; E-mail: rowan.jane.harwood@cwcom.net

ISSN 1354-8506 print /ISSN 1465-3966 online/00/010075-11 Ó Taylor & Francis Ltd

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76 R. H . HARW OOD ET AL.

rejected now (Gordon, 1975), but it is likely that some people `disengage’ from the life of

their community for alternative reasons (Lahniers, 1975; Spence, 1975), such as ill health.

Chronic illness is known to diminish roles, activities, social networks and relationships

(Anderson & Bury, 1988; Locker, 1983; Williams & Bury, 1989). The extent to which this

depends upon the type of condition or associated confounding factors is not known.

A social engagement scale was developed for the Nottingham Activity and Ageing Study

(Dallosso et al., 1986; 1988). The scale asks about nine activities that involve contact with

people outside the immediate household (telephoning, letter writing, attending religious

services, going on holiday this year or next, and membership of a club or society), or

indicating interest in the wider community (taking a magazine or journal, voting in elections,

using a public library). Previous validation work showed that the scale was capable of

discriminating between active elderly people attending a swimming group, elderly people

drawn from a general practice register, and frail elderly people attending a day hospital

(Morgan et al., 1985). In a population survey of older people (Morgan et al., 1987), the social

engagement scale was strongly correlated with Neugarten’ s Life Satisfaction Index (Neu-

garten et al., 1961), but not with a scale measuring aspects of personality (Bedford et al.,

1976), and gave higher scores in younger people and in those who were more physically

active.

In this study we measured associations between social engagement in men and a variety

of social, economic and health factors. In particular we considered the effects of heart attack

and stroke, both of which are acute in onset, life threatening and may recur. They have

profound consequences for patients and their families (Anderson, 1992; Schott & Badura,

1988; Speedling, 1982) in terms of disruption of lifestyle, roles and social relationships. For

people who survive a stroke the consequences are likely to be more diverse, visible and

long-lasting than for those who survive a heart attack. We have previously demonstrated high

levels of handicap in stroke survivors (Harwood et al., 1994). Among the possible conse-

quences of stroke are speech impairment, cognitive impairment, abnormal gait, incontinence,

hemiparesis, depression and emotionalism, while after heart attack, there may be disability

from angina or heart failure, apprehension towards strenuous activities or fear of recurrence.

W e hypothesized that stroke survivors would be disproportionately likely to withdraw from

social activities, even after their levels of disability are taken into account.

Methods

The British Regional Heart Study

The British Regional Heart Study is a national prospective investigation into the fundamental

causes of cardiovascular disease (Shaper et al., 1981). In 1978± 80, 7,735 men aged 40± 59

were drawn at random from one general practice in each of 24 towns in England, Wales and

Scotland and had a detailed examination including a questionnaire on personal and family

factors, an electrocardiogram, lung function tests and a blood sample for 24 biochemical and

haematological measurements. Men have been followed for all-cause mortality and for fatal

and non-fatal cardiovascular events, with contact being maintained with 99% of surviving

men.

In 1992, the men were sent a questionnaire by post which included questions on

self-rated health, medical diagnoses, occupation, marital status, housing tenure, car owner-

ship, physical disability and social engagement. Self-rated health was classi® ed as excellent,

good, fair or poor (Wannamethee & Shaper, 1991). Subjects were asked if they had ever been

told by a doctor that they had any of the following medical diagnoses: heart attack, stroke,

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SOCIAL ENGAG EMENT IN OLDER M EN 77

angina, other heart trouble, high blood pressure, aortic aneurysm, diabetes, peptic ulcer,

gout, gall bladder disease, thyroid disease, arthritis, bronchitis, asthma or cancer. Disability

items comprised bending and straightening, keeping balance, climbing stairs, getting out of

the house and walking 400 yards (365 metres).

Statistical analyses

W e examined the effect of heart attack and stroke on social engagement, and conducted

analyses to investigate the origins of any differences seen. Mean social engagement scores

(SES) were calculated for people who had and had not reported heart attack and stroke, and

for possible confounding and explanatory factors. Men were categorized according to

® ve-year age bands, social class (Registrar General’ s classi® cation), whether or not any of the

six disability items could not be performed, and whether none, one, two or three or more

co-morbid conditions were reported. Disability was dichotomized as the distribution was

heavily skewed, with the majority of subjects recording no disability. The signi® cance of

differences were tested using t-tests, chi-square tests or tests of linear trend in means as

appropriate.

Multiple regression analysis (SAS procedure GLM) was used to investigate the relation-

ship between social engagement score (the dependent variable) and diagnosis (heart attack,

stroke, both or neither), once the effects of other variables had been taken into account. The

® rst model included only the diagnosis. The second model added age and socio-economic

variables. Thirdly, the co-morbidity variable was included. Finally, all the measured variables

were entered, including current health status measured according to self-rated health and

disability status. It is possible that these last two variables lie on the causal pathway between

diagnosis and social engagement score, and so are not true confounders. They were included

to investigate whether the diagnosis of stroke or heart attack per se led to social disengagement

or whether this was mediated via poor physical health.

For each model the statistical signi® cance of including the diagnosis variable was tested,

the R-squared statistic examined for the ® t of the model and least squares adjusted mean

estimates for social engagement score calculated for the different diagnostic groups. These

adjusted means are comparable within models but not between different models. Con ® dence

intervals were calculated for differences in adjusted SES according to diagnosis.

Results

Of the original 7,735 men, 6,528 were known to be alive in 1992. Of these, 5,905 responded

(90.4% of survivors); 5,681 (96%) had complete data for the social engagement questions,

and 4,772 men had data complete for all variables, these forming the subjects for the

multivariate analyses. Internal consistency for the scale was reasonable (Cronbach’ s al-

pha 5 0.61).

Distribution of scores

The distribution of social engagement scores (SES) in this population is shown in Figure 1.

Mean SES was 5.1 out of nine, standard deviation was 2.0. Social engagement scores were

lower in men who had had a heart attack (M 5 4.9, SD 5 1.9) or stroke (M 5 4.3, SD 5 2.1)

compared with those who had neither (M 5 5.2, SD 5 1.9). The difference in SES between

heart attack and stroke was statistically signi® cant (p 5 0.0001).

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78 R. H . HARW OOD ET AL.

Table 1. Association between social engagemen t scores and explanator y values

Mean social engagement Difference from baseline in

Variable Number score mean SES (95% CI)

Heart attack

Yes 579 4.92 0

No 4761 5.18 1 0.26 (0.09,0.43)

Stroke

Yes 214 4.27 0

No 4984 5.18 1 0.91(0.63,1.19)

Age group

51± 55 years 1536 5.16 0

56± 60 years 1528 5.10 2 0.06 ( 2 0.19, 1 0.07)

61± 65 years 1496 5.09 2 0.07 ( 2 0.21, 1 0.07)

66± 70 years 1310 5.00 2 0.16 ( 2 0.02, 2 0.30)

Occupational

social class

I 494 6.57 0

II 1451 6.00 2 0.57 ( 2 0.40, 2 0.64)

III non manual 571 5.50 2 1.07 ( 2 0.86, 2 1.28)

III manual 2406 4.51 2 2.06 ( 2 1.90, 2 2.22)

IV 564 4.06 2 2.51 ( 2 2.30, 2 2.72)

V 205 3.70 2 2.87 ( 2 2.60, 2 3.14)

House

ownership

Yes 4787 5.34 0

No 1037 3.99 2 1.35 ( 2 1.42, 2 1.48)

Marital status

Married 5001 5.21 0

Not married 855 4.39 2 0.82 ( 2 0.67, 2 0.97)

Car ownership

Yes 4768 5.36 0

No 1048 3.91 2 1.45 ( 2 1.32, 2 1.58)

Co-morbidity

None 1877 5.22 0

1 condition 1933 5.17 2 0.05 ( 2 0.18, 1 0.08)

2 conditions 1232 4.96 2 0.26 ( 2 0.12, 2 0.50)

3 1 conditions 807 4.84 2 0.38 ( 2 0.21, 2 0.55)

Self-rated

health

Excellent 946 5.83 0

Good 3173 5.31 2 0.52 ( 2 0.39, 2 0.65)

Fair 1409 4.37 2 1.46 ( 2 1.31, 2 1.61)

Poor 255 3.53 2 2.30 ( 2 0.04, 2 2.56)

Disabled

Yes 4313 4.50 0

No 1441 5.32 1 0.82 (0.70,0.92)

Associations with social engagement score

Social engagement was higher in married than non-m arried men, non-disabled compared

with disabled men, and in both house and car owners compared with non-owners (Table 1).

These differences were all highly statistically signi® cant (t-test, p , 0.00005). There were

strong trends of lower mean SES with worse self-rated health (test for linear trend,

p 5 0.0001), lower social class (p 5 0.0001) and with increasing co-morbidity (p 5 0.0003).

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SOCIAL ENGAG EMENT IN OLDER M EN 79

Table 2. Association between heart attack, stroke and explanator y variable s

% heart

Variable attack n % stroke n

Age group

51± 55 years 6.1 (87) 1.7 (24)

56± 60 years 9.3 (130) 3.5 (48)

61± 65 years 14.4 (195) 4.7 (62)

66± 70 years 14.1 (163) 6.8 (77)

Occupational

social class

I 7.9 (37) 1.3 (6)

II 10.3 (141) 4.0 (53)

IIIN 9.7 (50) 4.7 (24)

IIIM 11.7 (251) 4.2 (88)

IV 11.1 (55) 5.4 (26)

V 14.4 (26) 4.1 (7)

House

ownership

Yes 10.0 (439) 3.6 (155)

No 15.3 (137) 6.4 (55)

Marital status

Married 10.8 (492) 4.09 (182)

Not married 11.3 (85) 4.08 (30)

Car ownership

Yes 10.6 (467) 3.5 (149)

No 12.1 (107) 6.9 (59)

Co-morbidity

None 3.6 (67) 1.6 (30)

1 condition 7.9 (137) 3.7 (63)

2 conditions 17.1 (180) 6.2 (62)

3 1 conditions 28.3 (195) 9.3 (59)

Self-rated

health

Excellent 3.6 (33) 0.7 (6)

Good 6.4 (190) 2.2 (65)

Fair 23.5 (275) 8.6 (94)

Poor 36.1 (73) 24.2 (45)

Disabled

Yes 22.5 (272) 2.1 (84)

No 7.3 (294) 10.3 (117)

There was a weak but statistically signi® cant trend of lower mean social engagement with

advancing age (p 5 0.05).

Associations with heart attack and stroke

Age, not owning a house, disability, worse self-rated health and greater co-morbidity were all

strongly associated with increased risk of having had a heart attack or stroke (test for linear

trend or chi-squared test, p , 0.0005 for each association) (Table 2). In addition non-car

ownership was associated with risk of stroke (p , 0.0005) and lower social class was

associated with risk of heart attack (p 5 0.02). Marital status was not associated with risk of

heart attack or stroke.

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80 R. H . HARW OOD ET AL.

Table 3. Association between heart attack, stroke and social engagemen t score after adjusting for potential confounding variable s

Adjusted mean SES for diagnosis and difference from baseline

(95% CI) in italics Significance

of diagnosis

Model Neither Heart attack Stroke Both R2 variable

Diagnosis only 5.18 5.03 4.40 3.87 0.01 F 5 16,

p 5 0.0001

0 2 0.15 2 0.78 2 1.31

( 1 0.03, 2 0.33) ( 2 0.46, 2 1.10) ( 2 0.77, 2 1.85)

Diagnoses, age and 4.63 4.58 4.19 3.57 0.24 F 5 9.1

socio-economic1

p 5 0.0001

variables 0 2 0.05 2 0.44 2 1.06

( 1 0.11, 2 0.21) ( 2 0.14, 2 0.74) ( 2 0.58, 2 1.54)

Diagnosis, age, 4.62 4.58 4.19 3.58 0.24 F 5 8.8

socio-economic and p 5 0.0001

co-morbidity 0 2 0.04 2 0.43 2 1.04

variables ( 1 0.12, 2 0.20) ( 2 0.13, 2 0.73) ( 2 0.56, 2 1.52)

Diagnoses, age, 4.46 4.63 4.28 3.79 0.26 F 5 4.6,

socio-economic, co- p 5 0.003

morbidity and 0 1 0.17 2 0.17 2 0.67

current health2( 1 0.01, 1 0.33) ( 1 0.13, 2 0.47) ( 2 0.17, 2 1.17)

variables

1Social class, house ownership, marital status and car ownership .

2Self-rated health and disability.

Multiple regression analyses

The multiple regression models were based on the slightly smaller sub-set of the population

with complete data for all variables (Table 3). Diagnosis remained an independent predictor

of social engagement after taking account of age and socio-economic variables. The adjusted

estimate of SES in stroke patients was 0.44 lower than in men who had neither heart attack

nor stroke, a difference that was statistically signi® cant (t 5 3.0, p 5 0.003). However, after

adjustment, the SES in men who had had a heart attack was not signi® cantly different from

that in those who had had neither heart attack nor stroke (p 5 0.64). Further adjustment for

co-morbid diagnoses did not alter these estimates.

In the ® nal model, which also included current health status variables, adjusted SES was

higher for heart attack patients (t 5 2.1, p 5 0.04), and non-signi® cantly lower for stroke

patients (p 5 0.24), compared with men who had had neither. Men who had had both heart

attack and stroke remained signi® cantly less engaged (t 5 2.7, p 5 0.008). In this model,

self-rated health, house ownership, car ownership, social class, disability and co-morbidity,

but not age, were also signi® cantly and independently associated with social engagement

(Table 4).

The models explained up to 26% of the variance in the data (R2). Most of this was due

to the addition of the socio-economic variables. Indeed, 10% of the variance in SES was

explained by social class alone. Diagnosis explained slightly less than 1% of the variance, and

current health status 2% of the variance.

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SOCIAL ENGAG EMENT IN OLDER M EN 81

Table 4. Association between explanatory variable s and social engagement scores in ® nal multivaria te model

95% CI

for Statistical

Adjusted difference from significance of term

Variable mean SES baseline in model

Age group

51± 55 years 4.23 0.00, 2 0.28 F 5 2.0, p 5 0.12

56± 60 years 4.23 0.00, 2 0.28

61± 65 years 4.33 0.10, 2 0.18

66± 70 years 4.37 ±

Social class

I 5.46 1.76,2.38 F 5 142, p 5 0.0001

II 4.98 1.31,1.87

IIIN 4.61 0.92,1.52

IIIM 3.79 0.12,0.68

IV 3.51 2 0.18,0.42

V 3.39 ±

House ownership

Yes 4.50 0.29,0.57 F 5 37, p 5 0.0001

No 4.08 ±

Marital status

Married 4.47 0.21,0.56 F 5 25, p 5 0.0001

Not married 4.12

Car ownership

Yes 4.59 0.45,0.73 F 5 70, p 5 0.0001

No 4.00 ±

Disabled

No 4.36 0.00,0.26 F 5 3.8, p 5 0.05

Yes 4.23 ±

Co-morbidity

None 4.45 0.17,0.53 F 5 6.7, p 5 0.0002

1 4.34 0.04,0.36

2 4.26 2 0.06,0.30

3 1 4.11 ±

Self-rated health

Excellent 4.95 1.17,1.77 F 5 45, p 5 0.0001

Good 4.63 0.87,1.43

Fair 4.10 0.36,0.88

Poor 3.48 ±

Discussion

This study has used a measure of social engagement in a large national study to investigate

variation in participation, an important aspect of quality of life in the new W HO classi® cation

of the consequences of ill health.

Both socio-economic factors and health status are likely to have an in¯ uence on social

engagement. Clearly wealth (re¯ ected in house and car ownership), and perhaps social class,

will have a bearing on the opportunities for and the range of socially engaging activities.

Health variables, including diagnoses, disability and self-rated health are also important. The

strong socio-economic predisposition to ill health, illustrated by the risk of heart attack or

stroke, however, might confound the relationship between health and social engagement.

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00

Fre

que

ncy

Social engagement score1 2 3 4 5 6 7 8 9

200

400

600

800

1000

1200

82 R. H . HARW OOD ET AL.

FIG . 1. Distribution of social engagement scores in 5,870 men.

We have demonstrated that both heart attack and stroke (and other, co-morbid,

diagnoses) were associated with lower social engagement scores, and that the effect was

quantitatively greater for stroke. The multivariate analyses demonstrate that limitation in

social engagement in stroke patients went beyond that expected due to the effect of

confounding factors. Most of this limitation could be explained by the effect of poorer

self-perceived health in men who had had a stroke. Poor self-perceived health status was

strongly associated with low social engagement, in a graded `dose± response’ manner, and

independently of potential confounding by age and socio-economic factors. This is consistent

with the relationship being causal (although it is also possible that low levels of social

engagement lead to poor self-perceived health).

The fact that the size of the differences in adjusted mean SES between stroke and heart

attack patients and those who had neither decreased as potential confounding and explana-

tory factors were entered into the model indicates that residual confounding is a possible

explanation of at least some of the remaining differences (Davey Smith & Phillips, 1992).

The study considered only men which clearly limits generalizability, especially as women

suffer more strokes. There is an advantage, however, in that SES may be associated with

gender (as a result of the items in the scale) and restriction to men avoids confounding by sex.

The ® nding of a higher adjusted SES am ongst men with heart attack should not be over

interpreted, as multivariate models are prone to distortion (by colinearity and residual

confounding). A conservative interpretation is that the difference seen in the univariate

comparison of men with heart attack, and neither heart attack nor stroke, is abolished once

confounding by socio-economic factors and current health status is taken into account. The

most important message to emerge from the multivariate analyses is that socio-economic

factors are responsible for much more of the variation in social engagement than are health

factors.

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SOCIAL ENGAG EMENT IN OLDER M EN 83

Implications of lower social engagement

Poor social engagement is important in its own right, re¯ ecting disadvantage, exclusion and

missed opportunities, making it important that health services address its causes if possible.

Rehabilitation aims at re-ablement, re-integration and the maximizing of potential (Ebrahim,

1992). Fortunately, poor levels of social engagement are potentially reversible, by tackling

medical, psychological, environmental and social barriers to participation, even in very

disabled subjects (Schroll et al., 1997). Lawton et al. (1999) describe social engagement as

being `close to the core of overall quality of life’ , and demonstrated direct and indirect

associations between social engagement and measures of psychological wellbeing in elderly

subjects.

Diminished social engagement may also have wider implications for health. For example,

low levels of social engagement have been associated with the onset of cognitive decline

(Basuk et al., 1999). The items in the social engagement scale relate to elements of social

networks and social support. Studies investigating the impact of social networks, or network

size, on people with stroke point to the bene® ts associated with them in terms of recovery

(Vogt et al., 1992) and reduction in physical limitation (Colantonio et al., 1993). After a heart

attack social isolation has been associated with a two- to three-fold increase in mortality over

nine years compared with those most socially engaged (Kaplan, 1988). Additionally, in-

creased levels of social support have been associated with functional recovery after stroke

(Glass et al., 1993) and community social support has been found to produce a strong

protective effect on psychosocial outcomes after stroke (Friesland & McColl, 1987). The

perception am ongst stroke patients and their carers that support is lacking has been associ-

ated with depression after stroke (Morris et al., 1991).

It is possible that the lower social engagement in the stroke group might be explained

by depression, which is common and often undiagnosed after stroke (Ebrahim & Harwood,

1999; House, 1987), or by the stigmatizing consequences of stroke which are arguably

greater than those of heart attack or other conditions (by virtue of the range, nature and

visibility of the resulting problems). Either might lead men to perceive their health as worse

and to engage in fewer social activities. The experience or anticipation of stigma by subjects

might lead them to withdraw from social activities in order to avoid discrediting situations.

Support for this theory comes from the ® ndings that people with rectal cancer who felt

stigmatized were more likely to withdraw from social activities (MacDonald & Anderson,

1984).

Educating the public about disability and its causes might go some way towards

lessening any associated stigma. Rehabilitation staff have a role to play in helping to promote

self-con ® dence and self-esteem. Stroke, for example, has been described as an assault on

the `taken for granted’ self (Kaufman, 1991); people’ s sense of identity and, sometimes, their

personality may be affected (Charmaz, 1983). In this context it is easy to understand

how important it is for rehabilitation staff to help patients maintain a sense of identity

and continuity with the life they had before the onset of health problems (Bury, 1982), and

to recognize depression. This means that people should be encouraged and enabled to

continue in their customary roles, so that participation in their community and their social

networks might be maintained. However, it also goes beyond this. It has been argued that

rehabilitation staff need biographical knowledge of the people they are working with (Kauf-

man, 1988). This would facilitate understanding of the meaning of the illness to the

individual and an appreciation of its impact on them, given their lifestyle, previous roles and

interests.

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84 R. H . HARW OOD ET AL.

Acknowledgements

The BRHS was funded by the Department of Health and the British Heart Foundation. RH

was an MRC Health Services Research Training Fellow and PP was funded by the Stroke

Association. Richard Morris advised on statistical methods, and Andy Thompson ran the

computer analyses.

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