1. Isolation and ethnicity: long-term illness and patterns of participation
Lucinda Platt
University of Essex,
Kaveri Harriss
London School of Hygiene and Tropical Medicine

2. The project (1)
The research presented here is part of a project (joint with colleagues at the University of Sheffield and the London School of Hygiene and Social Action for Health) on long-term illness and poverty and how the relationship between the two -- and the strategies in dealing with them -- vary by ethnic group.
This project engages in a complex area that is receiving increasing research and policy attention in relation to such issues as caring, extra costs of disability, the relationship between sickness and work, the role of social security benefits and the interface between work and benefits, and the impact of long-term illness on other household members.
However, many gaps still remain, and some current research could benefit from further development and this project hopes to explore a number of the gaps and contribute to evidence base and understanding of patterning of illness across households, specifically contributing to our understanding of how it varies by ethnic group.

3. The project (2): details
Details of the research project:
Limiting illness and poverty: breaking the vicious cycle, January 2005-June 2006
Funded by the Joseph Rowntree Foundation
Research team
Sarah Salway, University of Sheffield (project leader)
Punita Chowbey, University of Sheffield
Kaveri Harriss, London School of Hygiene and Tropical Medicine
Lucinda Platt, University of Essex
Elizabeth Bayliss, Social Action for Health

4. The project (3): contribution
Specific contribution of the project:
Exploring ethnic group differences in rates of illness, coping with illness and in the relationship between illness and various indicators of poverty (including worklessness)
Looking at and within households, considering the whole unit and the interplay between different household members.
Focusing on social relationships and social participation among those with long-term illness and those with caring responsibilities and other members of their households
Looking at use of benefits by those with long-term illnesses
Using the livelihoods approach to examine coping strategies, and how people use their strengths

5. The project (4): framework
Approach:
Predominantly qualitative project (focused on ethnographic work in the East End of London) supplemented by quantitative exploration of some of the issues (including what is being presented in this paper), but integrated approach.
Focusing on four main groups: Ghanaians, Punjabi Pakistanis, Bangladeshis and White English.

6. Issues In this part of the project, we wanted to explore:
whether it makes sense to consider lack of social participation as poverty
What the relationship is between long-term illness or caring and social participation
What the relationship is between ethnic group and social participation – and whether this varies by whether the individual is long-term ill or a carer

7. Background (1)
Since Townsend’s 1979 work on Poverty in the United Kingdom (and arguably before) it has become standard to think about poverty in terms of either (definitionally) or (causally – resulting in) lack of participation in ‘normal’ life including social life. However, measures of social participation have only tended to be accepted if ‘validated’ by low income.

8. Background (2)
Long-term illness is associated with higher rates of income poverty. This is partly but not wholly a consequence of the characteristics of those who are more likely to be long-term ill, which make them more vulnerable to poverty (e.g. lower average qualifications levels). Given the potential protective aspects of social interaction / social support on recovery from illness, it may be important to consider how social participation and illness relate and the role of income in this.

9. Background (3)
We know that minority ethnic groups have higher rates of morbidity, and particular types of morbidity, than the population as a whole. In particular, older Bangladeshi and Pakistani men have particularly high rates of long-term illness. It has not, to our knowledge, been explored in any detail how different rates of within-group illness affect the impact of that illness or its relationship with other factors (work, participation, benefit receipt etc).

10. Ethnicity and health: poor reported health
Source: Health Survey for England, 1999, Department of Health, in Focus on Ethnicity:

11. Background (4)
Minority ethnic groups have higher rates of income poverty than the population as a whole. Those groups that have the highest rates of income poverty are those that also have the highest rates of long-term illness (Pakistanis and Bangladeshis). However, Black Africans also have high rates of income poverty but they have low rates of long-term illness. How do we understand the intersection between ethnicity, poverty and long-term illness?

12. Low income and ethnicity
Notes:1. Low income household is defined as having less than 60 per cent of the median disposable income.
Source: Households Below Average Income, Family Resources Survey, 2000/01, Department for Work and Pensions, in Focus on Ethnicity:

13. Contribution of this paper (1)
Explores a range of measures of social participation – separately and together
Explores relationship between ethnic group and social participation controlling for long-term illness / caring (and vice versa)
Explores whether interactions between ethnic group and illness/caring can be identified, i.e. if the impact of illness / caring on social participation varies by ethnic group

14. Contribution of this paper (2)
Explores whether income explains most / all of ethnic group and illness effects: i.e. attempts to decouple lack of participation from income poverty
Explores if analysis supports the existence of a latent isolation propensity on the basis of the multiple measures selected.

15. Data
The Home Office Citizenship Survey (or People, Families and Community Survey), 2001
A biennial survey, first carried out in 2001, with focus on people’s local networks, their participation in civic and social activities, including volunteering, their approach to child-rearing and use of advice and support, their experience of and attitudes to racisms and their views about their local environment.
The 2003 data were released in 2005, but inexplicable results for the Bangladeshis raised doubts about the quality of these data so using the 2001 data

16. Data (cont.)
Design: a nationally representative sample of c. 10,000 individuals accompanied by a booster sample of 5,000 minority ethnic group members. This facilitates analysis by ethnic group, though for sub-groups of smaller minority groups (e.g Black Africans), numbers remain small.
Acknowledgement:
I am grateful to the Home Office for use of the data and to the UK Data Archive for making them available. Neither the Home Office or the UK Data Archive, however, bear and responsibility for the analysis or interpretation offered here.
Crown copyright material is reproduced with the permission of the Controller of HMSO and the Queen's Printer for Scotland

17. Measures of (lack of) social participation
Infrequent (< once a fortnight) visits to friends /neighbours (lonbvis)
Infrequent (< once a fortnight) receipt of visits from friends / neighbours (lovisit)
Infrequent (< once a fortnight) going out socially with friends (logoout)
Infrequent (< once a month) attendance at / involvement with clubs (irregclb)

18. Results Overview of rates of long-term illness and caring
Rates of lack of social participation
Ordered logits on probability of isolation controlling for other factors
MV probit on probability of different components of isolation controlling for other factors

19. Rates of long-term illness and caring by age band, 2001
Source: Home Office Citizenship Survey 2001, authors’ analysis

20. Long term illness and caring by age band and sex, 2001
Source: Home Office Citizenship Survey 2001, authors’ analysis

21. Long term illness and caring by ethnic group, 2001
Source: Home Office Citizenship Survey 2001, authors’ analysis

22. Long-term illness among men and women by age band and ethnic group, 2001
Source: Home Office Citizenship Survey 2001, authors’ analysis

23. % with limited social participation, by ethnic group
Infrequent visits
Infrequent visiting
Infrequent going out
Low contact with clubs
White British 36 39 32 46
Pakistani 30 49 55
Bangladeshi 26 58
Black African 42 52 50 41
Source: Home Office Citizenship Survey 2001, authors’ analysis

24. Lack of social participation by illness / caring and age band 2001
Source: Home Office Citizenship Survey 2001, authors’ analysis

25. Lack of participation by ethnic group, 2001
Source: Home Office Citizenship Survey 2001, authors’ analysis

26. Isolation (lack of social participation)
No isolation
28.1
Isolated on 1 element
25.9
Isolated on 2 elements
19.3
Isolated on 3 elements
16.8
Isolated on all 4 elements
8.9
Source: Home Office Citizenship Survey 2001, authors’ analysis

27. Isolation by ethnic group
Source: Home Office Citizenship Survey 2001, authors’ analysis

28. Modelling isolation Ordered logits controlling for
Model 1: Age group (18-44/ 45-59/64); sex; presence of a child under 5; and illness or caring and ethnic group
Model 2: As above but with work history (in work, not in work but worked in past, never worked) included
Model 3: As above with income bands and household size included
Also models were rerun controlling for qualifications and type of area additionally

29. Results for illness and ethnic group

30. Results for caring and ethnic group
Model 1
Model 2
Model 3
Caring
.269 (.083)***
.258 (.084)**
.265 (.094)**
Ethnic group (base is white British)
Indian
.116 (.076)
.091 (.078)
.041 (.104)
Pakistani
.361 (.082)***
.359 (.091)***
.029 (.121)
Bangladeshi
.331 (.111)**
.321 (.120)**
.007 (.158)
Black Caribbean
.500 (.087)***
.514 (.089)***
.419 (.110)***
Black African
.592 (.010)***
.576 (.105)***
.376 (.113)***
Chinese
.588 (.168)***
.617 (.174)***
.363 (.220)
Mixed and other groups
.088 (.098)
.081 (.099)
.091 (.112)

31. The effect of income (1)
Including income bands (even though a rather crude measure resulted in illness ceasing to have a significant association with isolation but did not make a difference to the size or significance of the coefficient for caring. Thus while the isolation associated with illness can be attributed to reduced resources, that for caring cannot. Interestingly, work history was only significantly related to isolation once income was included.

32. The effect of income (2)
Including income rendered non-significant the ethnic group effects for Pakistanis, Bangladeshis and Chinese. This suggests that it is lack of income that affects ability to participate for these groups, but it is interesting that this is the case when illness / caring are already being controlled for. Ill Bangladeshis, Pakistanis and Chinese would thus appear to have fewer resources available for social participation than their long-term ill white comparators.

33. Adding in qualifications and area type
Living in a rural as opposed to an urban area decreased the probability of isolation, but did not have much effect on the other coefficients
Qualifications (at all levels) reduced the probability of isolation compared to having none and also when qualifications were controlled for illness had a weaker association with isolation. Qualifications retained their significant negative association with isolation even when income was controlled for, indicating that education makes a difference to ability to participate regardless of income.

34. Interactions between ethnic group and illness / caring
We failed to identify any interactions between ethnicity and long-term illness in any of our models.
However, when exploring caring interacted with ethnicity, we found that for Caribbeans and Chinese, the interaction between caring and ethnic group produced a significant negative effect that outweighed or at least equalled the positive main effects of caring and ethnicity. That is, while being Caribbean or Chinese made isolation more likely among those not caring, and caring made isolation more likely for the white group, Caribbean and Chinese carers were no more likely than white non-carers to be isolated.

35. Modelling components of isolation simultaneously
Multivariate probits were run to test simultaneously the effect of the explanatory variables on the different components of ‘isolation’ – the lack of participation variables.
Correlations between the error terms across these equations lend support to the view that there is a latent continuum of isolation (or propensity to be isolated) captured by these repeated observed measures (cf. measurement of deprivation).

36. Predicted probabilities from the multivariate probits
Predicted probabilities for different sets of characteristics were estimated on the basis of the regression results for a models with and without income. The ‘individuals’ for whom probability of single measures of isolation, all measures together and no isolation were estimated were:
1 (typical values) younger white man with no children under 5 not long-term ill and in employment
2 (contrast case) older Bangladeshi woman, long-term ill with child under 5, never worked and no qualifications
3 Younger Caribbean woman, not long-term ill, child under 5, in work, level 3 qualifications
4 Older Pakistani man, long-term ill, not currently in work, no child under 5, level 1 qualifications
5 Younger Caribbean man, no child under 5 not long-term ill, in employment, level 4 qualifications
6 Older white woman, long-term ill not currently in work, level 1 qualifications

37. Predicted probabilities: no or max isolation (without income and area)

38. Predicted probabilities: no or max isolation (with average income and in urban area)

39. Predicted probabilities: single indicators (without income and area)

40. Conclusions (1)
There are ethnic differences in levels and types of social participation
Most minority ethnic groups are more likely to be isolated than their white counterparts of the same age group sex and family status. However, for Pakistanis, Bangladeshis and Chinese this is more to do with income than ethnicity per se.
Similarly the association of long-term illness with isolation seems to be to do with economic resources rather than illness per se. But this is not the case with caring, which is isolating at each income level.
For Black Caribbeans and Black Africans, higher probabilities of isolation are not affected by income levels.

41. Conclusions (2)
There is little evidence that the relationship between illness and isolation varies by ethnic group. However, there is evidence that the relationship between caring and ethnicity does so for some ethnic groups. For Chinese and Black Caribbeans, those caring do not appear to experience the greater risks of isolation generally associated with caring or their ethnicity.
Unobservable characteristics are correlated across equations for components of isolation, suggesting a latent ‘propensity to isolation’ captured by the repeated measures (assuming that a sufficient range of observed characteristics have been incorporated in the equations)

42. Next steps
To conduct analyses separately for men and women (sample sizes permitting) rather than simply controlling for sex
To formulate the relationship between income, illness and participation more clearly
To examine whether any other measures of or refinements to measures of participation might be relevant.
To incorporate income measure into mvprobits
Other?