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Social Activity and Ethnicity in the UK1

Lucinda Platt, ISER, University of Essex

Paper prepared for presentation at the RC28 Montréal meeting, August 2007. Introduction

This paper explores the extent to which social activity in England and Wales

varies by ethnic group and whether social deprivation is more marked for

some groups than others. In doing this it sets out to enhance our

understanding of one particular dimension of poverty and its variation by

ethnicity, as well as empirically informing discussions of social capital

formation, in relation to informal measures of participation, and of ethnic

capital.

Lack of social participation has been a widely accepted element of the

definition of poverty since at least Townsend’s seminal (1979) study of

poverty. Opportunities for ‘normal’ social interaction and the enjoyment of

communal or community activity, including such things as celebrations of

significant religious events and being able to extend hospitality to children’s

friends (and their parents), neighbours and family are seen as core to living a

full and non-deprived lifestyle. Consequently, measures of multiple

deprivation, or of poverty conceived multi-dimensionally rather than purely in

income terms, tend to incorporate participative measures, albeit such

measures are often very limited due to the constraints of the data (Mack and

Lansley 1985; Gordon and Pantazis 1997; Nolan and Whelan 1996; Gordon

et al. 2000; Berthoud et al. 2004). And social inclusion is defined as including

‘integration with family, friends and community’ (Burchardt, 2002).

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Participation, as a specific dimension of poverty or social inclusion has,

nevertheless, received little sustained attention in its own right independent of

it inclusion in summed multiple deprivation scores. There are clearly

arguments in favour of treating the different dimensions of poverty discretely

and empirically ascertaining their relationship with one another – and with the

default measure of poverty in income terms (Capellari and Jenkins 2007).

Lack of ‘normal’ social participation is an aspect of deprivation that is arguably

best served by being considered separately from more material forms of

deprivation, and this paper specifically examines four different aspects of

social engagement or ‘sociability’. Using the British Home Office Citizenship

Survey 2001 for England and Wales, it also explores whether the results

support the idea of some underlying propensity to lack of sociability for which

all four measures act as indicators. The four measures selected were: having

friends and neighbours round, visiting friends and neighbours, involvement in

some form of organised activity or ‘club’, and going out for a social reason.

These represent potentially distinct aspects of sociability, though in the final

analysis the chances of lacking all four forms of social engagement, or none,

are examined.

Specifically this investigation examines whether patterns of sociability are

shaped by the ethnic group of the respondent, and whether lack of social

engagement can be associated with any group more than another. There are

a number of reasons why it is particularly pertinent to examine ethnic group

variations in lack of social participation. First, income poverty rates vary

dramatically across the UK’s ethnic groups, with particularly high rates for

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Pakistanis and Bangladeshis, but with above average rates for all minority

groups (Platt 2007). Measures of material deprivation tend to echo the

patterns of income poverty to the extent that relevant analysis exists, but lack

of suitable data have inhibited comparisons of multiple deprivation across

ethnic groups and there are no extant studies of variation in social deprivation

according to ethnicity. Given the extensive interest in ethnic differences in

poverty, there is clearly a contribution to be made by understanding the extent

to which participation echoes or diverges from other forms of deprivation. We

might expect that, as with forms of material deprivation, the poorest groups

are also those most at risk of lacking social participation. However, the

relative geographical clustering of the most disadvantaged groups may help to

reduce isolation – and indeed – the reason for the clustering may itself be to

provide some form of ‘buffer’ against negative experiences through social

contact. The analysis presented here can also help us to understand the

extent to which ethnic differences in social engagement appear to derive from

income differences between groups, by examining the association between

lack of social engagement and ethnic group both with and without taking

account of income.

Moreover, simply having some grasp of patterns of participation and

association as they vary across ethnic groups, goes some way to helping us

understand the extent to which the ethnic group categories into which

individuals are allocated are meaningful in a more general sense. It has been

argued that the crude – and much criticised – ethnic group categories

available to quantitative analysts serve their purpose at the point at which they

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reveal substantial inequalities between groups (Platt 2002).2 It has also been

proposed that we should be looking to refine our allocation of individuals to

groups beyond the simply ticking of subjective categories by looking at actual

measures of group belonging, such as patterns of association (Fenton

forthcoming). While the data employed in this paper do not allow us to identify

who respondents are associating with,3 ascertaining whether or not there

appear to be distinctive patterns of association for the different categories is a

first step towards building up a more sensitive understanding of ‘groupness’. A

number of qualitative studies have investigated the ways in which particular

groups interact with others, and the extent to which these interactions are

group-based in some sense, as well as the meanings of those interactions,

but of necessity such research, though illuminating, cannot answer empirical

questions relating to the extent and patterns of participation (Hudson et al.

2007; Salway et al. 2007).

The empirical analysis of lack of social participation is also of particular

interest given the increasing attention in both UK policy and academy paid to

the concept of social capital (Aldridge and Halpern 2002; ONS 2001; Li et al.

2003; Edwards et al. 2006); and tangible measures of such social capital have

been identified across British social surveys (see

http://www.statistics.gov.uk/socialcapital/).4 Social capital is largely construed

instrumentally, as potentially having pay-offs for both individual and

community (Bourdieu 1997; Coleman; Putnam 1995, 2000), compared to a

focus on participation in the context of deprivation, which treats it as an end in

itself: an experience that is crucial to the current well-being of the individual.

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Nevertheless, even though the primary concern of this paper is to understand

the extent to which individuals are deprived of social engagement, there are

clearly ways in which this analysis of social participation can inform debates

on social capital. Much of the British literature on the measurement of social

capital has focused on measures of ‘civic participation’ or associational

membership and trust (Duffy 2004; Li et al. 2002; Li et al. 2003; Warde et al.

2003; Pennant 2005). The sorts of activity that we examine here – reciprocal

visiting, participation in more organised activities such as clubs or

volunteering, as well as simply going out – can be linked to the kinds of

informal associative activity emphasised by Coleman (1988), who saw social

capital formation primarily as a consequence of activities pursued for other

purposes. These measures also, however, overlap with measures of civic

participation as more formally conceived in the existing literature and as

emphasised in Putnam’s work. In fact, Putnam’s (2000) index of social capital

includes among its 14 components two measures of informal sociability. By

providing an empirical understanding of the patterning of social participation

and of the extent to which different forms predominate across different groups

the paper examines a neglected aspect of social capital and provides a basis

for exploring more systematically current claims about community, cohesion

and isolation.

Once again, the ethnic group dimension to the analysis has particular

applicability when we consider the links with social capital formation.

Community cohesion is often taken to have a specific application to the extent

to which different ethnic groups participate across a range of different

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dimensions of participation (Commission on Integration and Cohesion 2007).

And the search for resources within communities is pursued energetically in

policy-related research (Furbey 2006). However, participation in this

framework is conceived of individualistically and, as in much of the policy level

discussions of social capital, the potential negatives are not discussed, either

for the individual enmeshed in tight social bonds that restrict their upward

mobility or via the use of networks to promote the exclusion of others (Portes

1998; Lin 2001).

On the other hand the increasing anxiety about ‘segregation’ and the relative

concentration of certain minority groups treats co-residence as a potentially

problematic phenomenon (Community Cohesion Review Team 2001), without

consideration either of the extent to which it may foster a protective

environment for the most disadvantaged and marginalised groups (Heath and

Cheung 2006; Bajekal et al. 2004) or of the ways in which it might foster

social capital of the bridging (within group) as well as the assumed bonding

variety (Schuller, Baron and Field 2000; see also Granovetter 1973; Lin

2001). There is also an implication that geographical dispersal will also be

accompanied by both economic and social integration. There has been some

challenge to this view (Peach 2005), but the extent to which geographical and

economic integration may in fact be at odds with social integration is made

evident in the results from this paper.

By contrast work on ethnic capital has illustrated the extent to which co-

residence and tight social networks may act as a resource (Zhou 2005). Both

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the meaning of ‘ethnic capital’ – as human or social capital, or both – and its

potential role in both aiding or inhibiting upward mobility or integration within

society have been debated (Borjas 1992; Esser 2005). Underlying much of

the discussion has been an assumption of relatively close ties within groups –

yet the extent to which this is reflected in patterns of social activity remains

open to empirical investigation. Existing investigation into ethnic ‘enclaves’ in

the UK does not suggest much evidence of positive effects (Clark and

Drinkwater 2002), but the contribution of social networks to either fostering or

inhibiting advancement is not well understood, particularly in relation to the

kinds of informal social contact treated here. This paper, then, aims to provide

a contribution to understanding how social contact does, indeed, play out for

different groups, which may itself help us to develop our understanding of

ethnicity as a resource further in future.

Finally, as well as considering differences in social participation according to

ethnic group, this paper pays substantial attention to health status. This stems

from the perspective that excluding the limitations that may derive from the

constraints of ill-health or caring may produce a misleading picture of group

differences. We know that rates of ill-health, disability and caring vary widely

across ethnic groups (Nazroo 1997; Erens et al. 2001). On one level this is

unsurprising given that poverty both stems from and contributes to ill-health

(Jenkins and Rigg 2004; Burchardt 2000); and rates of poverty vary greatly

across minority ethnic groups (Platt 2007). And there is an extensive literature

charting how ill-health, disability and caring may impinge on social

participation in a variety of ways (Howard 2001; Locker 1983; Parker 1993).

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While one might posit that it is ill-health that reduces participation, the positive

aspects of social contact may also have a beneficial impact on the health of

those already suffering from a chronic condition (or their absence a negative

one). A number of studies have suggested that social participation and

engagement may have a beneficial impact on health, and that social isolation

may have a negative one (Berkman 1984; Berkman et al. 2000; Veenstra

2000); and Whelan (1993) has argued that social support protects against

chronic stress consequent on material deprivation. Thus, ethnic group

patterns of participation may both need to be understood in the context of

differential health status, and potentially be able to contribute to

understanding those differences. Current explorations of the role of social

support in relation to ethnic group health outcomes are ambiguous in their

results (Stopes-Roe and Cochrane 1990; Pollard et al. 2003) It is also

important to understand how these are mediated by income, given that those

with poor health tend to be worse off than those in good health.

In the next section I describe the data and the variables and approach in more

detail. Subsequent sections discuss the results of the analyses, examining

men and women separately. The final section draws some conclusions.

Data and methods

Data

Social engagement and its lack was analysed using the Home Office

Citizenship Survey (Home Office 2003). This is a biennial survey which is

explicitly designed to capture information about the involvement of individuals

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in a range of community and civic activities, their child-rearing practices and

sources of information and support, and their experience of their

neighbourhood and attachment to it. This paper uses the survey for 2001

since it was the only one to include the participation variables which form the

basis of this analysis. The sampling unit was the individual (rather than the

households) and most of the questions related to the respondent’s own

experience, views and perceptions. The survey was specifically intended to

capture ethnic group differences in ‘citizenship’ and community experiences

and therefore, on top of its c. 10 000 person main sample, the design

incorporated a booster sample of c. 5 000 members of minority ethnic groups.

Survey weights that adjusted for survey design and for response probabilities

have been employed throughout the following analysis.

The focus of this paper is on adult respondents of working age (18-59/64).5

The outcomes for men and women are examined separately throughout the

paper, given the wide variation in both health status, caring, and social activity

according to sex.

Variables

To measure lack of social engagement four questions were selected to

summarise different aspects of sociability. From the grouped response

options, I constructed binary variables from the chosen questions to represent

deprivation on the measure, i.e. lack of that particular form of social

participation. The measures do not necessarily capture all forms of social

engagement. However, between them they allow for variation in types of

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social engagement by group or circumstances and, I argue, together they

effectively cover most potential forms of social activity. The four measures

are:

� Lack of visiting: goes round to friends or neighbours less often than once a

fortnight;

� Lack of being visited: has friends or neighbours over less often than once

a fortnight;

� Lack of going out: goes out with friends or neighbours less often than once

a fortnight; and

� Lack of organised activities: is involved in ‘clubs’ less often than once a

month or not at all. ‘Clubs’ is here an inclusive term which includes

voluntary activities, activities based round a religious centre or focus, as

well as organised interest groups. It thus summarises any more organised

forms of social activity.

Health status was measured by a question on whether the respondent

suffered from a limiting long-term health problem. Caring was measured by

the response to whether the respondent cared for someone within or outside

the household with such a limiting long-term health problem. In the 2001

survey the caring question did not distinguish between whether the person

cared for lived in or outside the household.

Overall 24 per cent of the working age population in this survey had a long-

term illness and nine per cent were carers. Nearly a quarter of the carers had

a long-term illness themselves, which means that two per cent of the sample

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were both ill and caring. Rates of illness were fairly equal across the sexes

though slightly lower for women; but women had higher rates of caring. As we

would expect, illness and caring responsibilities both became more likely with

age.

For ethnic group, a 17-level ethnic group variable was reduced to eight

groups. The eight categories were white British, Indian, Pakistani,

Bangladeshi, Black African, Black Caribbean, Chinese, and Other and Mixed.

However, the results for the Chinese are not extensively discussed in what

follows given the small counts on which they are based. The combination of

the various, numerically small, ‘mixed’ groups with ‘other’ groups results in a

residual category that is not inherently meaningful. The seven main

categories are not uncontested; nor are they assumed to be homogenous.

However, they are regularly employed in analysis as representing

aggregations with distinctive histories and displaying diverse outcomes both in

absolute terms and which often persist when a range of relevant

characteristics are held constant (see Modood et al. 1997; Platt 2007).

Whether such diversity extends also to social participation is an empirical

question that is investigated here.

Characteristics considered relevant to understanding differences across these

main variables were held constant in the multivariate analyses to allow the

comparison of differences between those with otherwise comparable

characteristics. These ‘control variables’ were identified and measured in the

following way:

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� age: a binary variable was constructed from a banded variable to

distinguish between those aged 18-39 and those aged 40-59/64, since

rates of illness and caring are much higher at the older age ranges, and

patterns of participation might also be expected to change over the life

course.

� the presence of a child aged under 5 years, which could be expected both

to limit opportunities for social activity as well as creating opportunities for

certain, child-based activity. The presence of pre-school children has

often been found to be the crucial indicator for various forms of (non-)

participation, including labour market participation. It should be noted that

this variable is strongly associated with age and thus it predominantly

serves to distinguish the probability of lack of social participation within the

younger age group.

� presence of a partner, since being in a relationship could substitute for

forms of social participation, as well as potentially enabling access to

alternative, additional networks. Partnership covers both cohabitation and

marriage.

� work history: whether currently working; whether worked in the past but

currently not in employment; and whether never worked. Some of the

justification for the reform of incapacity benefits revolves around the notion

that being on sickness benefits is bad for the health and for social relations

(as well as for the economy) (DWP 2006). Work can also be regarded as

a form of participation in itself: it could be argued that either those in work

are more likely to have social contacts (Petersen et al. 2000), resulting in

positive effects on measures of social participation, or that work itself

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constitutes such a form of social contact, which might result in negative

effects on other forms of social participation. It was important to

distinguish within the non-working between those who had worked at

some time – and might well return – and those who had never worked.

Those who had worked in the past might have existing work-based

networks to call upon. On the other hand the negative impacts of

unemployment on social engagement are well known. By contrast, those

who have never worked may have developed alternative sources of social

support and contact – or conversely may be among the most isolated. This

distinction was felt to be particularly important given that the proportions of

those who have never worked varies by ethnic group (for men as well as

women).

� income. Because illness and income are so closely related and because

some ethnic groups have lower average income, the analysis also controls

for income level, to check whether any observed effect of illness or of

ethnicity can in fact be attributed to the consequences of low income. In

deprivation analysis, the measure of deprivation tends to be validated in

relation to income. That is, the lack is only considered to constitute

deprivation if it occurs where income levels are also low. Here, however,

we examine the role of income in mitigating or accounting for social forms

of deprivation. A measure of household size adjusted the income bands

for households of equal size.

Methods

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Multivariate probit models were estimated to model outcomes for all four

dependent variables simultaneously. This approach allows for greater

flexibility in associations between the independent and each of the dependent

variables: the coefficients on the regressors can vary with each outcome

variable. At the same time, it enables us to explore whether there are

correlations between the unobservable characteristics associated with each

outcome. If all the off-diagonal correlations are equal to zero then the

multivariate probit reduces to a series of univariate probits. If however there

are correlations across the equations, it suggests that they are best modelled

together. Such correlations across each pair of equations could be argued to

imply an underlying propensity to lack of sociability for which the four

measures acted as indicators.6

Separate multivariate probits were estimated for men and women including

the independent variables identified above and with two versions: one without

income and one including it.7 This was for two reasons: one practical and one

theoretical. Around 29 per cent of adult respondents did not respond to the

income question (27 per cent of men and 30 per cent of women). The non-

response also varied by ethnic group, with as many as 39 per cent of

Pakistani men and 50 per cent of Pakistani women not providing a response.

Thus, including income substantially reduced sample sizes. By examining

models with and without income, therefore, it was possible to identify

comparable coefficients across the two, which were insignificant in the income

models but where the larger sample sizes from non-income model rendered

them statistically significant. At the theoretical level, the interest was in

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observing the extent to which forms of social engagement – or, rather, its

absence – were coterminous with lower incomes. That is, could lower levels

of social engagement be explained in terms of financial constraints?

Predictions were estimated for outcomes on the different measures of lack of

sociability and for the probability of experiencing all or none of them with

characteristics held constant and varying only on the focus of interest

(ethnicity, or caring and health status). These predicted probabilities illustrate

the very different chances and patterns of social contact that men and women

from different ethnic groups and with or without ill-health and caring

responsibilities can expect to experience.

Overview

Tables 1 and 2 (for men and women respectively) show how the four

measures of lack of social engagement varied by ethnic group and health and

caring status. Caribbeans and Black Africans were more likely to face

infrequent visiting and receiving of visits from friends or neighbours than

Pakistanis and Bangladeshis, with white British, Indian and Mixed and other

falling in between. On the other hand, Bangladeshi and Pakistani men as well

as women were less likely to go out or participate in organised activities than

those of white British, mixed and other and Indian ethnicity. These patterns

would suggest that there was some substitution between the measures, with

different groups favouring different routes for sociability. However, the

Caribbeans appeared to lose out in terms of social engagement overall. Both

male and female Caribbeans appeared more deprived of social engagement

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than the white British on all four measures. This may have implications for

their wellbeing and their opportunities. On the other hand, Black Africans,

whose overall profile makes them look similar to the Black Caribbeans in

terms of sociability, had the lowest rates of deprivation on the measure of

organised activity (participation in ‘clubs’). The central role of the Church for

many Black African communities may help to explain this finding (Hudson et

al. 2007; Salway et al. 2007). Again, then, we may be seeing some

substitution in relation to available or preferred forms of activity.

Both illness and caring appeared to increase the chances of lacking social

engagement across measures. However, overall it seemed that it was caring

that put more constraints on sociability than illness, particularly for men.

[TABLES 1 AND 2 ABOUT HERE]

The question then becomes whether these distinctive patterns of social

engagement by ethnic group and health / caring status remain when other

relevant characteristics are held constant. And to what extent do these

measures, crude as they may appear, function as markers of an underlying

propensity to lack of social engagement – or self-sufficiency? These

questions are covered in the next sections.

Multivariate analysis

Tables 3 and 4 show the estimates of the multivariate probit regression

models for men and women respectively. All the variables discussed in the

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Data section, except household income and household size, were included in

the models. In the tables, positive coefficients indicate that the characteristic

is associated with greater deprivation – or a lower chance of engaging in the

activity – while negatively signed coefficients indicate that the chances of

lacking this form of social engagement are reduced (or social engagement is

increased).

Men

Table 3 shows that older men were less likely to visit, be visited or go out. But

their involvement in organised activities was not significantly different from

younger respondents. Partnership may represent an alternative form of social

contact for respondents, as those with a partner were more likely to be

infrequent visitors of their friends and neighbours and to go out less

frequently. Having a young child seemed to constrain the types of activity

engaged in: fathers of young children were more likely to miss out on going

out and participating in organised activities relative to their peers with older or

no children. But patterns of visiting and being visited were not significantly

affected.

Qualifications reduced chances of lacking social engagement across the

board, as would be expected; and not being employed appeared to allow

greater time for visiting and being visited but restricted opportunities for going

out. This could a disguised income effect: those not in work having fewer

resources to spend on going out, with substitution between more expensive

and cheaper activities taking place. The model with income included

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(discussed below) indicated that this was indeed the case. However, for

those who had never worked, income did not seem to make much difference

and thus lack of networks to go out might be inferred as being more important.

Among men, illness was scarcely significantly associated with any of the

measures of sociability. That is, people with a long-term health condition

were no more or less likely than those without to lack social opportunities. It

has been suggested that isolation may exacerbate or produce ill-health, but

the lack of association between sociability and long-term illness here gives

little support to that argument – at least for those of working age. The story for

caring was somewhat different. Caring rendered lack of social engagement

significantly more likely for men in relation to three out of the four measures.

Interestingly, it was involvement in organised activities that was not

significantly affected, even though it might be expected that more organised

social contact would be the hardest to combine with the demands of caring.

Looking at ethnic variations in lack of social participation, Bangladeshis were

much less likely to lack reciprocal visiting than their otherwise comparable

white British counterparts, and Pakistanis were less likely to lack opportunities

for visiting. On the other hand Pakistanis and Bangladeshis, alongside Black

Caribbeans and Black Africans, were much more likely to miss out on going

out. For Black Africans this was accompanied by higher chances of being

deprived on the visiting / visited measures, and, for Black Caribbeans on the

organised activity and (marginally) on the visiting measure. Thus, these two

Black groups appeared to face limited social opportunities compared to both

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their white peers and those from other minority ethnic groups. Again, the

amount that can be explained by differentials in income will be illustrated from

the results of the next model.

Finally, Table 3 showed substantial variations in the cross-equation

correlations (the rhos). The correlations between lack of involvement in

organised activity and the other three outcome variables were between 0.16

and 0.28. The correlation between not visiting and not being visited was,

however, over 0.88, which shows a high level of reciprocity between these

activities (people don’t ask you round if you don’t ask them). Correlations

between these measures of visiting and not going out were above 0.5. All the

correlations were, nevertheless, statistically significant and the likelihood ratio

test clearly rejects the independence of the equations. As discussed above, if

there are correlations across the equations, it indicates that they are best

modelled together. The results suggest an underlying propensity to lack of

social engagement. That is, that these four measures act between them as

indicators of a tendency not to participate socially, call it asociability or, more

positively, self-sufficiency, that cannot itself be measured directly and that is

independent of the characteristics already controlled.

[TABLE 3 ABOUT HERE]

Women

Table 4 shows that the same pattern for the cross equation correlations were

observed for women, suggesting that these measures work as indicators of

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such a latent propensity across the sexes. The individual correlations were

also of a similar size.

In relation to the coefficients for the independent variables, age, qualifications

and work history variables showed the same overall pattern of effects for

women as for men. Partnership also seemed to act as a substitute for social

activity for women. Those with young children were less likely to lack visitors

than those with older or no children – and this was controlling for work status.

But for women, unlike for men, having a young child was not associated with

lower participation in organised activities.

Illness had a statistically significant association with infrequently going out

among women, as well as a marginally significant effect on low levels of visits

to friends and neighbours. Women carers were, however, not especially at

risk of receiving infrequent visits; and they were more likely than non-carers to

be involved in organised activities. Nevertheless, caring increased risks of

infrequent visiting and infrequently going out, suggesting that their

responsibilities kept them predominantly at home.

Black African women showed high risks (relative to comparable white British

women) of being deprived across the first three measures, though the

coefficient was negative – albeit not statistically significant – for involvement in

organised activities. And Black Caribbean women replicated this pattern of

reduced participation on the first three measures, and much more strongly

than their male counterparts. That is, they appeared to differ more from white

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British women than Black Caribbean men differed from white British men in

terms of social participation. Pakistani and Bangladeshi men lost out on going

out compared to their white British counterparts; but they showed no

significant differences in relation to organised activities. However, Pakistani

and Bangladeshi women were significantly more likely to lack involvement in

organised activities than white British women as well as going out less.

Similarly, where Pakistani and Bangladeshi men engaged in reciprocal visiting

more than white British men this was not evident for Pakistani and

Bangladeshi women compared to white British women. Finally, where Indian

men were insignificantly different from their white counterparts in relation to

their patterns of social participation, Indian women were significantly more

likely to lack social engagement, relative to white women, on at least two of

the measures. This is not a ‘South Asian’ effect, however, since Caribbean

women and Black African women also showed much higher risks of being

deprived on these measures than their white British counterparts. Nor is it a

simple gender effect since, clearly, these contrasts are with white British

women – who might be expected to face many of the same gender

constraints as other women, particularly when employment and family status

are controlled.


There are clearly preferences or constraints operating to shape patterns of

social participation in ways that are distinctive across ethnicities. One such

constraint that might potentially be playing an important role is, of course,

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levels of resources. There is only a measure of annual household income

(from all sources), so we do not know about the respondent’s individual

access to resources, and this issue of control over resources might be

particularly relevant for women’s participation – or lack of it. However,

controlling for the income level in the household should still provide some

grasp of whether financial limitations were affecting patterns of participation

and opportunities for social contact.

The effect of income

We now turn therefore to one of the original motivating issues for the analysis.

To what extent are differences in participation and in lack of social

engagement – co-terminous with income differences? The multivariate probit

models were therefore re-estimated controlling additionally for banded income

and household size (to adjust income to needs). Table 5 reports the

coefficients for illness, caring and ethnic group from this model. The full tables

can be found in Tables A1 and A2 in the Appendix. Income itself had a

statistically significant and negative effect across all four equations for both

men and women. That is (as would be expected), social participation

increased with income level, across all measures. The cross-equation

correlations (the rhos) remained very similar for the two models for both men

and women, so the argument that there is an underlying propensity to lack of

social engagement holds for these models. Given the non-response on

income, the models with and without income are based on different samples

and so cannot be directly compared. Nevertheless, if we find sizeable and

statistically significant results for ethnic group or health status following the

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inclusion of income in the model, it suggests that that these effects are

insensitive to income. That is, it is not the differences in poverty between

groups that account for the differences in patterns of participation.

Conversely, if income differences are playing a significant part in the patterns

of social participation that we observe, then we would expect to find negligible

and statistically insignificant coefficients on ethnic group and health status,

indicating that the observed differences between groups can be attributed to

their very different experiences and characteristics, including in terms of

household resources.

For men, coefficients reduced substantially in size and became statistically

insignificant in relation to going out for carers and for Pakistani, Bangladeshi

and Black Caribbean men. This suggests that variations in patterns of going

out for these groups are heavily dependent on access to resources, as might

be expected. However, Black African men remained significantly more likely

to miss out on going out than their white British counterparts of the same

income level, as well as to lack visiting. And, male carers and Black

Caribbean and Chinese men were significantly more likely to lack reciprocal

visiting than their non-caring / white British counterparts. Access to resources

is thus important for enabling some forms of social participation, especially

going out, for men from some marginalised groups, refuting the argument that

forms of social contact are culturally rather than economically driven. On the

other hand, different patterns of neighbourly visiting appear relatively

independent of income, suggesting different access to forms of ‘ethnic capital’

and potentially the protective use of community resources.

24

For women carers, restrictions on social participation appeared relatively

insensitive to income. Among those with long-term illness, however, patterns

of going out and visiting were statistically insignificant from their healthy

counterparts at the same income level. Interestingly Pakistani and

Bangladeshi women’s participation was insignificantly different from

comparable white British women’s with the exception of participation in

organised activities. On the other hand, Indian, Black Caribbean and Black

African women were significantly less likely to participate on three out of the

four measures than their white British peers. For the Bangladeshi and

Pakistani women it could be argued that the observed differentials in Table 2

were in large part caused by the lack of resources wherewith to engage in

social participatory activities, despite the fact that it is for these groups that

cultural constraints on participation are most frequently invoked (Tackey et al.

2006; and cf. Dale 2002).

By contrast, among those Black women who do not tend to be considered so

culturally constrained, we find that their patterns of participation are

insensitive to income and, in some cases, the size of the coefficient even

seemed to increase, once income was controlled. In these instances, it is

those who are not necessarily the worst off who nevertheless experience

lower participation. If we take seriously the notion of lack of participation as a

form of poverty we should consider as deprived those who lack opportunities

for participation despite their income level. And we can see that this lack of

25

social participation could not be simply fixed by higher incomes or

participation in employment.


Adding up social engagement

This final section treats the question of what these different patterns of social

participation all add up to. In the preceding sections the focus has been on

the distributions of the individual measures of sociability across potentially

vulnerable groups. On the other hand, early on the question was raised of

whether there were some substitution effects, which might indicate that it was

preferences for particular types of sociability rather than constraints that

determined the patterns of social engagement. Here, predicted probabilities

for being deprived on all four measures or on none are estimated. Do the

differential risks on individual measure add up to mean that the chances of

overall social engagement or lack of social engagement are highly unevenly

distributed? To examine the marginal impact of ethnic group and of illness

and caring, other characteristics were held constant across groups for these

predictions;8 and the predicted probabilities from the models for men and

women were compared. Figures 1 and 2 show the predicted probabilities of

having ‘zeros’ on all four measures (full social engagement), or having ‘ones’

on all four measures (lacking social engagement on all counts).

Figure 1 shows the patterns contrasting those who were not ill and not caring

with those who were. This comparison is made purely for white British men

26

and women. While empirically there were few in the sample who were both ill

and caring and who fitted the baseline characteristics selected, the point is

heuristic. It shows the extreme case of being both long-term ill and caring and

the effect that has on extreme positions of sociability. For both men and

women, the combined effects of being ill and caring caused an approximately

four percentage point reduction in the chances of not being deprived on any of

the four measures. For risks of being deprived on all four measures,

however, the impact was greater for women than for men. Men who were

caring and long-term ill were only one percentage point more likely to not be

participating on any of the four measures than their well, non-caring

counterparts. For women, by contrast, the increase in risk was of the nature

of three percentage points. These effects are relatively small. The risks of

extreme social isolation are not as great as we might have anticipated for

those experiencing both ill-health and caring responsibilities. There would

appear to be some balancing between different forms of social engagement

that means that still relatively few are constrained in relation to all four

measures of sociability.

[FIGURE 1 ABOUT HERE]

On the other hand, the picture was much starker for those from certain

minority ethnic groups. Figure 2 illustrates the predicted probabilities for men

and women from six ethnic groups. (Chinese are excluded because the small

sample sizes make some of the coefficients unreliable, and Mixed and other is

27

both a residual category and differed little from the white British in all models.)

The health and caring status for Figure 2 was set as not ill and not caring.

Figure 2 shows that, for women, all the minority groups had substantially

lower probabilities than their white counterparts of not being deprived on any

measure, with the Bangladeshis, Black Caribbeans and Black Africans

clustering together at around 19 percent. They also had lower probabilities

than their male counterparts across all groups. Women from minority groups

also had higher probabilities of being deprived on all four measures than their

white British counterparts, with the position of Black Caribbean and Black

African women standing out here. Black African and Black Caribbean men

also fared badly in relation to participation by comparison with men from other

groups (though not by comparison with women from the same group). And

the situation of Pakistani and Bangladeshi men indicates the centrality of

sociability for them – other things being equal.

Comparing Figure 2 with Figure 1, we can see that the predicted probability of

limited sociability on all four measures for white women who were ill and

caring was still well below the predictions for Black Caribbean and Black

African women, which were estimated at 12 and 13 per cent respectively.

This emphasises once again the particularly deprived position of Black

Africans and Black Caribbeans, and especially women from these groups, in

relation to their constrained patterns of social engagement. If social support

and social contact is an important element of current well-being, as well as of

28

the welfare of future generations, then this result should give us cause for

concern.

[FIGURE 2 ABOUT HERE]

Conclusions

Results showed that there was indeed variation in patterns of social

participation by both illness/caring and ethnic group. However, the impact of

illness on opportunities for social participation was not substantial once

relevant factors were held constant. That does not mean that, in absolute

terms, those with a long-term illness are not more isolated than those without,

but this would appear to have less to do with the illness than with other

associated characteristics (such as age, income and qualifications). For

carers, particularly male carers, their responsibilities did seem to create more

constraints on their social activity. And only some of this can be attributed to

income: caring responsibilities in their own right appeared to divorce people

from opportunities for extensive social engagement. However, there seemed

to be some substitution between different forms of social engagement, and

carers, even ill carers, were not much more likely to be deprived on all four

measures than non-carers.

Turning to or main focus on ethnic group, there was clear variation in patterns

of social engagement by ethnic group. In particular there were distinctively

high levels of reciprocal visiting among Bangladeshis and Pakistanis – and

particularly men from these groups. Conversely, Black Africans were more

29

likely to engage in more organised activities and less in the more informal

social activities. Black Caribbeans showed more differences from the white

majority in their patterns of social participation given that they are the minority

group which shows the highest overall levels of geographical and economic

integration and analysis frequently reveals their comparability with the white

majority. Given that these differences tended to be in terms of deficits – that is

lower levels of social engagement, they in a sense echo the analysis of the

economic and labour market experience of Caribbeans which shows overall

compability but with some clear deficits and disadvantages – particularly in

unemployment rates, that suggest on-going processes of racialised exclusion.

These distinctive patterns of social participation do give some support to

notions of groupness associated with the ethnic group categories, as

discussed in the introduction – and this notion of groupness is further

supported by the fact that patterns of participation tended to be more similar

between the sexes within a group than within the sexes. Patterns of

participation on their own did not closely match the wel-attested ranking of

income or material deprivation across the groups, suggesting that this form of

deprivation – of social engagement – is best considered in its own right.

Multivariate analysis enabled consideration of the extent to which the absolute

differences could be attributed to differences in characteristics and

circumstances. Among Bangladeshi men and Pakistani women, the contrast

between visiting and going out was clear even when most characteristics

were controlled – but the lower tendency to go out did seem to be associated

with income constraints. In the final analysis, Bangladeshi and Pakistani men

30

appeared to have a greater propensity towards (or opportunities for) social

engagement and were less at risk of social isolation than other groups. This

may suggest the important role of social contact in ameliorating otherwise

very disadvantaged circumstances – and indicate the potentially positive role

of co-residence in local communities in facilitating that. The results indicate

that a focus on improving material circumstances of these groups would have

pay-offs in extending their range of social contacts through different forms of

activity. Indian men appeared little different from comparable white British

men; however Indian women were much more likely to experience low

participation across activities than comparable white women from the same

income bracket, suggesting that rather different opportunities across the

sexes within this group and possibly access to household resources. Indian

women have not experienced the policy attention paid to Bangladeshi and

Pakistani women, whose low levels of labour market participation (often,

thought not necessarily accurately or informatively attributed to ‘cultural

barriers’) are often regarded as the key to improving the welfare of the groups

overall. But these findings suggest that in terms of social contact, there are

constraints facing Indian women that go beyond the material circumstances of

the household.

However, it is when turning to the experience of the Black African and Black

Caribbean groups that the most distinctive finding emerges. The Black

Caribbean group is the longest-standing of Britain’s post-war minority groups

and, as noted, is the most ‘integrated’ according to conventional measures of

labour market participation, geographical distribution, inter-ethnic unions and

so on. In particular Caribbean women’s high labour market participation rates

31

and the greater tendency than among the white majority for Caribbean lone

parents to combine work and childcare are noted alongside the high levels of

qualifications among women from these groups. While young Caribbean

men’s unemployment rates are a cause for substantial concern, the group as

a whole is experiencing upward mobility and increasingly its profile is

becoming comparable to that of the population as a whole (Platt 2005). Black

Africans tend to be more recently arrived and more highly concentrated in

London, but also often bring high levels of skills and qualifications, which

might be expected to increase opportunities for participation. But these results

show how that both these groups experience distinctively higher risks of not

engaging in opportunities for social participation, and that these are not

associated with characteristics or family or employment status (which can

place extensive demands on women in particular (Reynolds 2005). In

particular we observe that the highest probabilities of not participating in any

of the four forms of activity are reserved for Black African and Black

Caribbean women. As mentioned, much has been made of the potential

cultural and religious constraints on the activity of women from South Asian

groups. And it is important to remember the large absolute differences for

South Asian women. However, if we are concerned about the well-being

offered by social contact and the deprivation suffered by its lack more

attention should be paid to supporting the networks and combating the

exclusionary processes faced by Black women; and how to build social capital

within groups which are often considered well-integrated into labour markets

and subject to relatively little policy attention. These women may have

alternative forms of informal social contact not measured here, but it is hard to

32

imagine what they would look like, and the finding invites further investigation.

Meanwhile, it serves as an important caveat about the potential costs of

‘integration’ in a stratified and racialised society.

Notes

1 Acknowledgments: I would like to thank the Home Office /Communities and Local Government for the use of these data and the Data Archive at the University of Essex for making them available to me. I am, of course, solely responsible for the analysis and for the interpretation made of them. I would also like to thank CASE at the LSE for hosting me while I worked on the first version of this paper, and Howard Glennerster for his positive feedback on the working paper version. The University of Essex allowed me leave during which I worked on this paper (among other projects). Thanks go to the British Academy, which funded my presence at the RC28 Montreal meeting where I presented the current version of the paper. I have received helpful comments from participants at seminars at Loughborough University, Institute of Education, University of London, University of Essex, Stratification Seminar Cardiff meeting, comments which I have aimed to work through in what is presented here. I am grateful to colleagues on the Joseph Rowntree Foundation funded project on Long-term ill health, poverty and ethnicity, a project which prompted my work on this paper, and to Sarah Salway for her detailed comments on an early version of the paper. 2 The categories typically employed in secondary analysis (and available to analysts) are now the ONS 2001 Census categories. There are typically 15 such categories in data covering England and Wales. In this paper these have been reduced to 8 since the ‘other’ categories are not considered independently meaningful and the ‘mixed’ categories are not considered meaningful in aggregate and are too small individually to allow separate analysis. 3 In 2003 and 2005 versions of the survey questions on ethnic group of friendship networks was asked. However, it was not asked in 2001, and in the later surveys, the questions on social practices were absent. 4 ONS have defined five dimensions of social capital: views about the local area; civic participation; social networks and support; social participation; reciprocity and trust. The approach adopted here does not fit clearly into one of these dimensions, but it links social networks and support and social participation. 5 The lower age of 18 rather than 16 was chosen as few 16 and 17 year olds are in fact in employment or can be considered fully independent. While 16 is the minimum school leaving age, 18 is the age of majority. 6 It could be argued that such correlations are picking up characteristics that are potentially measurable that we have failed to include in the equation rather than ‘unobservables’, i.e. an unmeasurable latent propensity for sociability or, conversely, self-sufficiency. However, we include a wide range of independent variables and have tested for a number of others, which were found not to contribute to the explanatory power of the model and were therefore excluded. 7 The multivariate probit model was estimated using the –mvprobit– program for Stata software (Capellari and Jenkins, 2003). Each model was run with 30 draws and using antithetic acceleration in the interests of robustness of results. Predicted probabilities were derived using the companion post-estimation program –mvpred–. I am grateful to Stephen Jenkins for his advice on the use of mvprobit. 8 Characteristics were set to: younger, partnered, no child under five, in employment, with level three qualifications and with annual household income of between £30 000 and £34 999

33

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Figures and Tables Figure 1: Predicted probabilities for proportions experiencing no lack of social engagement on any of four measures and those experiencing lack of social engagement on all four measures, by sex and caring/health status

Source: Home Office Citizenship Survey 2001, author’s analysis Notes: weights are used to estimate these proportions. Unweighted Ns: men=5 406; women=6 310. Horizontal axis represents the probability.

41

Figure 2: Predicted probabilities for proportions of those experiencing no lack of social engagement on any of four measures and of those experiencing lack of social engagement on all four measures, by sex and ethnic group, 2001

Notes as for Figure 1

42

Table 1: Percentage with limited forms of social engagement according to four measures, by ethnic group: men aged 16-64

Ethnic group (N -unweighted)

Infrequent visits

Infrequent visiting

Infrequent going out

Low contact

with clubs

Not socially

deprived on any of

the 4

Socially deprived

on all 4

White British (2842)

37 41 29 46 30 10

Indian (535)

34 38 31 44 32 11

Pakistani (401)

32 34 45 48 24 10

Bangladeshi (255)

23 31 43 49 28 11

Caribbean (322)

40 42 36 57 22 12

Black African (260)

39 50 44 42 20 14

Chinese (58)

54 57 24 56 18 19

Mixed and other (730)

35 39 34 45 28 10

Long-term ill (910)

41 50 40 49 20 11

Caring (423)

48 60 43 45 21 14

ALL men (5403)

37 41 30 46 29 10

Source: Home Office Citizenship Survey 2001, author’s analysis Notes: percentages are based on weighted counts and have been rounded up.

43

Table 2: Percentage with limited forms of social engagement according to four measures, by ethnic group: women aged 16-59

Ethnic group (N -unweighted)

Infrequent visits from friends or

neighbours

Infrequent visiting to friends or

neighbours

Infrequent going out

Low contact

with clubs

Not socially

deprived on any

measure

Socially deprived

on all four measures

White British (3271)

34 36 36 47 27 10

Indian (590)

36 39 45 54 23 16

Pakistani (414)

28 38 55 64 16 17

Bangladeshi (289)

29 30 56 68 11 11

Caribbean (456)

48 52 49 47 15 13

Black African (393)

45 54 56 40 19 15

Chinese (80)

45 54 32 46 26 8

Mixed and other (844)

36 37 35 49 30 11

Long-term ill (986)

37 42 48 54 20 12

Caring (683)

39 45 48 46 22 15

ALL women (6307)

35 37 36 48 27 10

Notes: as for Table 1

44

Table 3: Multivariate probit regression estimates of the effects of various characteristics on measures of lack of social engagement, 2001: Men [1]

Infrequent visits from friends or neighbours

[2] Infrequent visits to friends or neighbours

[3] Infrequent going out

[4] Irregular/ no involvement in organised activities

Older age group .593 (.055)*

.607 (.054)*

.543 (.057)* .052 (.055)

Partnered .071 (.058) .349 (.059)*

.571 (.061)* -.103 (.078)†

With child under 5 -.088 (.080)

.095 (.077) .378 (.077)* .201 (.077)*

Long-term ill -.042 (.070)

.130 (.075) .108 (.070) -.014 (.076)

Caring for someone .217 (.090)*

.389 (.093)*

.193 (.092)* -.052 (.092)

Ethnic Group Indian -.011

(.080) -.048

(.084) .073 (.075) -.010 (.075)

Pakistani -.075 (.094)

-.201 (.093)*

.348 (.087)* -.043 (.091)

Bangladeshi -.355 (.140)*

-.282 (.126)*

.329 (.125)* -.113 (.124)

Black Caribbean .154 (.103 .180 (.106)†

.318 (.101)* .216 (.101)*

Black African .288 (.106)*

.508 (.114)*

.630 (.109)* .006 (.110)

Chinese .688 (.192)*

.699 (.199)*

-.029 (.223) .337 (.201)

Other and mixed .052 (.097) .052 (.101) .191 (.094)* .036 (.098) Qualifications level 1 -.130

(.121) -.263

(.121)* .006 (.127) -.235 (.120)*

level 2 -.291 (.086)*

-.323 (.086)*

-.155 (.087)† -.419 (.085)*

level 3 + apprenticeships

-.285 (.074)*

-.287 (.074)*

-.237 (.075)* -.441 (.075)*

higher / higher diplomas

-.407 (.075)*

-.413 (.074)*

-.277 (.074)* -.662 (.075)*

other -.216 (.179)

.053 (.171) -.177 (.174) -.090 (.178)

Work history Not currently in employment

-.173 (.073)*

-.145 (.070)*

.271 (.070)* -.005 (.073)

Never worked -.501 (.149)*

-.293(.153)

†

.151 (.166) -.366 (.203)†

Constant -.395 (.081)*

-.558 (.080)*

-1.219 (.085)*

.343 (.081)*

45

Rho eq. 2-4 .205 (.031)* Rho eq. 1-4 .158 (.030)* Rho eq. 3-4 .283 (.029)* Rho eq. 1-2 .882 (.011)* Rho eq. 2-3 .550 (.025)* Rho eq. 1-3 .527 (.027)* Likelihood ratio test of rho14=rho24=rho34=rho13=rho23=rho12=0

Chi2 (6)=359.448*

Source: Home Office Citizenship Survey 2001, author’s analysis Notes: reference categories for the categorical variables are younger (aged 18-39); single; no child under 5; not long-term ill; no caring responsibilities; white British; no qualifications; in employment. Standard errors are given in brackets. *= statistically significant at at least the 5% level; †= statistically significant at the 10% level. Survey weights are used. Unweighted number of observations=5300.

46

Table 4: Estimates from a multivariate probit indicating the effects of various characteristics on measures of lack of social engagement, 2001: Women [1]




[4] Irregular/ no in-volvement in organised activities

Older age group .400 (.053)* .507 (.052)*

.448 (.053)*

-.041 (.052)

Partnered .249 (.051)* .278 (.050)*

.289 (.049)*

.070 (.050)

With child under 5 -.155 (.067)* -.039 (.070)

.469 (.065)*

-.030 (.064)

Long-term ill .067 (.067) .118 (.069)†

.164 (.066)*

.097 (.067)

Caring for someone .066 (.074) .149 (.074)*

.182 (.075)*

-.135 (.064)†

Ethnic Group Indian .100 (.076) .151

(.076)* .246 (.074)*

.123 (.076)

Pakistani -.040 (.106) .205 (.109)†

.313 (.107)*

.413 (.104)*

Bangladeshi .066 (.166) .081 (.147) .264 (.138)†

.424 (.138)*

Black Caribbean .483 (.084)* .528 (.085)*

.446 (.084)*

.073 (.085)

Black African .513 (.098)* .728 (.096)*

.616 (.097)*

-.111 (.096)

Chinese .439 (.154)* .675 (.179)*

.084 (.164) .088 (.180)

Other and mixed .138 (.098) .139 (.095) .045 (.088) .134 (.090) Qualifications level 1 -.145 (.094) -.114

(.095) -.225 (.092)*

-.363 (.091)*

level 2 -.114 (.073) -.113 (.071)

-.314 (.072)*

-.495 (.072)*


-.212 (.080)* -.218 (.083)*

-.414 (.079)*

-.704 (.080)*


-.228 (.071)* -.256 (.071)*

-.571 (.069)*

-.926 (.070)*

other -.459 (.236)† -.366 (.233)

-.207 (.232)

-.679 (.230)*


-.257 (.057)* -.217 (.060)*

.200 (.055)*

-.027 (.057)

Never worked -.170 (.131) -.245 (.128)

.400 (.120)*

-.037 (.121)

Constant -.552 (.077)* -.609 -.658 .454

47

(.075)* (.076)* (.076)* Rho eq. 2-4 .212 (.029)* Rho eq. 1-4 .167 (.029)* Rho eq. 3-4 .203 (.028)* Rho eq. 1-2 .863 (.011)* Rho eq. 2-3 .466 (.025)* Rho eq. 1-3 .477 (.026)* Likelihood ratio test of rho14=rho24=rho34=rho13=rho23=rho12=0

chi2(6) = 679.47*

Notes: as for Table 3. Unweighted number of observations=6167.

48

Table 5: Multivariate probit regression estimates of the effects of ethnic group and health status on measures of lack of social engagement controlling for income. [1]





MEN Long-term ill -.111

(.080) .052 (.084) .016 (.078) -.101 (.090)


.355 (.102)*

.136 (.104)* -.051 (.104)

Ethnic Group Indian .074 (.099) -.009

(.099) -.077. (.099) .058 (.095)

Pakistani .020 (.129) -.220 (.124)

.163 (.119) -.101 (.124)


-.256 (.160)

-.008 (.160) -.010 (.157)

Black Caribbean .234 (.121)†

.209 (.122)†

.191 (.120) .119 (.128)

Black African .169 (.120) .311 (.125)*

.487 (.130)* -.029 (.125)

Chinese .580 (.230)*

.812 (.257)*

-.425 (.301) -.125 (.289)

Other and mixed .069 (.110) .119 (.121) .210 (.107)* .120 (.114) WOMEN Long-term ill .028 (.076) .058 (.078) .079 (.077) .067 (.078) Caring for someone .215

(.085)* .164 (.085)†

.168 (.087)† -.124 (.086)

Ethnic Group Indian .186

(.101)† .153 (.010)*

.225 (.096)* .269 (.100)*

Pakistani .025 (.134) .007 (.142) .108 (.145) .409 (.144)* Bangladeshi .192 (.195) .084 (.177) -.133 (.169) .598 (.167)* Black Caribbean .519

(.097)* .474 (.097)*

.344 (.100)* .065 (.102)

Black African .552 (.109)*

.662 (.109)*

.503 (.109)* -.063 (.113)

Chinese .502 (.188)*

.529 (.210)*

-.123 (.207) .201 (.229)

Other and mixed .067 (.114) .073 (.112) -.077 (.105) .063 (.105) Notes: As for Table 3. Unweighted number of observations= 3904 (men) and 4369 (women). Full results in Appendix: Tables A1 and A2

49

Table A1: Multivariate probit regression estimates of the effects of various characteristics including income on measures of lack of social engagement, 2001: Men [1]





Older age group .589 (.063)*

.543 (.063)*

.532 (.065)* -.015 (.062)

Partnered .167 (.077)*

.371 (.079)*

.655 (.083)* -.001 (.079)

With child under 5 .011 (.093) .096 (.092) .301 (.091)* .221 (.092)* Long-term ill -.111

(.080) .052 (.084) .016 (.078) -.101 (.090)


.355 (.102)*

.136 (.104)* -.051 (.104)

Ethnic Group Indian .074 (.099) -.009

(.099) -.077. (.099) .058 (.095)

Pakistani .020 (.129) -.220 (.124)

.163 (.119) -.101 (.124)


-.256 (.160)

-.008 (.160) -.010 (.157)

Black Caribbean .234 (.121)†

.209 (.122)†

.191 (.120) .119 (.128)

Black African .169 (.120) .311 (.125)*

.487 (.130)* -.029 (.125)

Chinese .580 (.230)*

.812 (.257)*

-.425 (.301) -.125 (.289)

Other and mixed .069 (.110) .119 (.121) .210 (.107)* .120 (.114) Qualifications level 1 -.095

(.145) -.250

(.149)† .005 (.152) -.365 (.141)*

level 2 -.241 (.100)*

-.252 (.101)*

-.075 (.101) -.461 (.100)*


-.177 (.088)*

-.171 (.089)†

-.127 (.089)* -.413 (.090)*


-.324 (.092)*

-.324 (.094)*

-.049 (.092)* -.687 (.094)*

other -.172 (.204)

.005 (.202) -.172 (.221) -.010 (.214)


-.224 (.085)*

-.157 (.087)†

.042 (.083) -.077 (.089)

Never worked -.105 (.192)

.173 (.198)†

.467 (.249)† -.140 (.209)

Income band -.026 (.011)*

-.025 (.012)*

-.080 (.012)* -.026 (.011)*

Household size -.062 -.038 .043 (.028) -.067 (.030)*

50

(.028)* (.029) Constant -.169

(.113) -.299

(.120)* -.860 (.121)* .667 (.122)*


Chi2 (6)=164.004*

Notes: As for Table 3. Unweighted number of observations=3904.

51

Table A2: Estimates from a multivariate probit indicating the effects of various characteristics including income on measures of lack of social engagement, 2001: Women [1]




[4] Irregular/ no in-volvement in organised activities

Older age group .398 (.061)* .493 (.061)*

.467 (.061)*

-.025 (.061)

Partnered .346 (.076)* .399 (.067)*

.316 (.067)*

.228 (.069)*

With child under 5 -.056 (.081)* -.118 (.082)

.356 (.078)*

.017 (.077)

Long-term ill .028 (.076) .058 (.078) .079 (.077) .067 (.078) Caring for someone .215 (.085)* .164

(.085)† .168 (.087)†

-.124 (.086)

Ethnic Group Indian .186 (.101)† .153

(.010)* .225 (.096)*

.269 (.100)*

Pakistani .025 (.134) .007 (.142) .108 (.145) .409 (.144)*

Bangladeshi .192 (.195) .084 (.177) -.133 (.169)

.598 (.167)*

Black Caribbean .519 (.097)* .474 (.097)*

.344 (.100)*

.065 (.102)

Black African .552 (.109)* .662 (.109)*

.503 (.109)*

-.063 (.113)

Chinese .502 (.188)* .529 (.210)*

-.123 (.207)

.201 (.229)

Other and mixed .067 (.114) .073 (.112) -.077 (.105)

.063 (.105)

Qualifications level 1 -.234 (.111)* -.125

(.113) -.223 (.109)*

-.403 (.108)*

level 2 -.142 (.087) -.094 (.087)

-.203 (.087)*

-.426 (.087)*


-.229 (.100)* -.164 (.104)

-.317 (.098)*

-.626 (.099)*


-.270 (.093)* -.178 (.091)†

-.375 (.089)*

-.791 (.089)*

other -.553 (.243)* -.387 (.116)*

-.105 (.262)

-.653 (.239)*


-.338 (.068)* -.281 (.071)*

.132 (.067)*

-.094 (.069)

Never worked -.362 (.158)* -.294 (.149)*

.606 (.151)*

.167 (.147)

52

Income band -.005 (.012) -.032 (.012)*

-.053 (.011)*

-.037 (.011)*

Household size -.088 (.026)* .001 (.028) .096 (.026)*

-.062 (.025)*

Constant -.301 (.109)* -.437 (.108)*

-.631 (.109)*

.684 (.109)*


chi2(6) = 4753

Notes: As for Table 3. Unweighted number of observations=4369.

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