The European Journal of Public Health Advance Access published online on May 7, 2007
The European Journal of Public Health, doi:10.1093/eurpub/ckm041
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Socioeconomic disadvantage, social participation and networks and the self-rated health of English men and women with mild and moderate intellectual disabilities: cross sectional survey
Eric Emerson and Chris Hatton** Institute for Health Research, Lancaster University, UK
Eric Emerson, Institute for Health Research, Lancaster University, Lancaster LA 4YT, UK, tel: 01524 592260, fax: 01524 592401, e-mail: eric.emerson{at}lancaster.ac.uk
Received July 31, 2006, accepted April 2, 2007
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Abstract |
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Background: Extremely high rates of mortality and morbidity have been reported among people with intellectual disabilities. Virtually no research has addressed the potential social determinants of health status within this very vulnerable population. Method: Cross-sectional survey of self-reported health status and indicators of socioeconomic disadvantage and social connectedness in 1273 English adults with mild or moderate intellectual disabilities. Results: Indicators of socioeconomic disadvantage accounted for a statistically significant proportion of variation in health status, over and above any variation attributable to the personal characteristics and living circumstances of participants. Indicators of social participation and networks did not add to the explanatory power of the model. Among the indicators of socioeconomic disadvantage, hardship was more strongly associated with variation in health status than either employment status or area-level deprivation. Conclusion: As in the general population, self-reported health was associated with indicators of socioeconomic disadvantage, especially hardship. In contrast, there was no evidence of any association between health status and social participation and networks.
Keywords: health inequalities, intellectual disabilities, networks, self-reported health, social participation, socioeconomic disadvantage
Approximately 2% of adults have intellectual disabilities (mental retardation).1,2 That is, they have since childhood had a marked general cognitive impairment that has impeded their ability to adapt to social demands and expectations. A multiplicity of genetic and environmental factors can cause intellectual disability.3 The most common genetic factors are X-linked chromosomal disorders and Down's syndrome.4 Environmental factors include: transplacental infections; pre-natal exposure to toxins and teratogens; birth injury, hypoxia and rhesus incompatibility; childhood infections; childhood exposure to environmental toxins; head injury; severe dehydration and undernutrition; socioeconomic disadvantage.1,3,5
Extremely high rates of mortality and morbidity have been reported among people with intellectual disabilities.6–13 Research has drawn attention to the importance of a range of factors that may contribute to these health inequalities including: genetic syndromes associated with intellectual disabilities; behavioural or lifestyle factors; and barriers to accessing health care.4,7,8,12–14 This evidence has stimulated policy initiatives to reduce health inequalities faced by people with intellectual disabilities and their non-disabled peers.15–19
What is notable, however, is the almost complete disconnection between research and policy pertaining to health inequalities faced by people with intellectual disabilities and research and policy related to the social determinants of health inequalities in the general population.7,20–23 This is somewhat puzzling given the extensive evidence that: (i) exposure over the life course (but especially in childhood) to socio-economic disadvantage and social exclusion leads to increased mortality and morbidity;24–31 and (ii) people with intellectual disabilities are significantly more likely to experience socioeconomic disadvantage and social exclusion as children and adults.1,2,32–38 It is also the case that issues pertaining to disability are rarely addressed in the wider literature on health inequalities. Indeed, a recent government report on addressing health inequalities in England concluded that ‘Evidence on ethnicity, gender, disability and age is sparse. Consequently, the relationships between these factors and health inequalities are poorly understood. This is crucial since targeting sectors of the population is a key characteristic of most effective interventions.’ p. 61 (italics added).39 Two very recent studies have begun to address this gap in knowledge. They suggest that 24–31% of the increased risk for poor health among children and adolescents with intellectual disabilities may be attributable to their relative socio-economic disadvantage.40,41
The aim of the present article is to explore the association between indictors of socio-economic disadvantage, social participation and networks and self-rated health status within a sample of adults with mild or moderate intellectual disabilities. As such, the article seeks to determine the extent to which factors associated with variation in health status within the general population also apply to the highly disadvantaged and vulnerable population of people with intellectual disabilities.
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Methods |
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Participants
Participants were a subset of 1273 adults with mild or moderate intellectual disabilities drawn from the survey of Adults with Learning Difficulties in England 2003/3.35 The process of participant section from the wider sample is described subsequently. The wider survey involved the participation of 2898 adults with intellectual disabilities drawn from five sampling frames, and taken together, provide comprehensive coverage of adults with intellectual disabilities living in either private households (independently or with relatives) or in some form of long-term supported accommodation. Adults with intellectual disabilities who were homeless, incarcerated or living temporarily in a health related treatment facility were not included in the survey.
General household omnibus survey
Screening questions to identify adults with intellectual disabilities were placed on weekly general household omnibus surveys operated by a market research organization (BMRB) for 56 weeks between July 2003 and August 2004. These surveys use random locale sampling to contact 
1700 general households a week. This led to the identification of 2214 potential participants, 74% of whom gave permission to be re-contacted and for whom there was sufficient information for them to be included in the issued sample. Of the issued sample, 35% were deemed ineligible as they either did not have an intellectual disability or were <16 years old. Information was collected on 750 people (70% of the issued eligible sample). Of these, 58 (8%) were subsequently excluded as their academic attainments made it highly unlikely that they had an intellectual disability.
Administrative records of adults with intellectual disabilities living in private households
Twenty Councils with Social Services Responsibilities (CSSR) were selected to ensure coverage by type of Council, percentage of population from minority ethnic communities, affluence and geographical region. Each CSSR randomly selected 50 adults with intellectual disabilities who were living in private households and receiving services from the CSSR. The sample size per CSSR was determined by consideration of the likely maximum sample size with which CSSRs would comply. Information was collected on 480 people (71% of the eligible issued sample).
Administrative records of adults with intellectual disabilities living in differing forms of supported accommodation
Three non-overlapping sampling frames were employed to draw random samples of adults with intellectual disabilities living in three administratively defined systems of supported accommodation: (i) Registered Residential Care Homes (RRCH) (using a national data base provided by the National Care Standards Commission); (ii) supported accommodation funded through the national Supporting People programme (SP) (using a national data base provided by the Office of the Deputy Prime Minister); (iii) medium to long-term accommodation operated by the UK's National Health Service (NHS) (using a national data base provided by the Department of Health). From each database, a random sample of providers was selected with probability proportionate to size (number of residents or households). Each provider was requested to randomly sample 10 respondents using a one-in-n approach from an alphabetically sorted list of all residents. The sample size per provider organization was determined by consideration of: (i) the likely maximum sample size with which providers would comply, and (ii) the desirability of sampling as wide a range of provider organizations as possible. Information was collected on: 919 people living in Registered Residential Care Homes (70% of the eligible issued sample); 562 people living in Supporting People settings (68% of the eligible issued sample); 263 people living in NHS accommodation (83% of the eligible issued sample).
Self-report data and proxy respondents
Due to the severity of their intellectual disability, a significant proportion of the sample had difficulty answering interview questions. In such cases, information was solicited from a proxy respondent. To avoid problems associated with combining self-report and proxy data,42,43 we identified participants who had answered most of the questions themselves (the interviewer recorded at the end of each interview section whether answers were primarily answered by the participant with intellectual disabilities, by a proxy informant or by a mix of the two), and who provided codeable answers to key questions related to health and well-being. This subset contained 1296 adults with intellectual disabilities (45% of the total sample).
Response bias
In order to address problems of response bias and acquiescence,43,44 we examined responses to four adjacent interview items that shared a common repose format (3-point scale) and were related to the measurement of well-being. Of the four items, three related to the frequency of negative psychological states (feeling sad/worried, feeling left out or feeling helpless), one related to the frequency of a positive psychological state (feeling confident). We excluded a further 23 participants (1.6% of the sample) who gave extreme positive or negative answers to all four items (even though the direction of one item was reversed). As a result the final sample contained 1273 adults with intellectual disabilities who provided self-report data on their health status that was not deemed to be of questionable validity (45% of the total sample).
Consent and ethical approval
Ethical approval was obtained from relevant agencies. The ability of each potential participant to give informed consent was assessed by the interviewer providing them with a verbal and written overview of the project and then determining whether they could recall: (i) examples of the content of the proposed interview; (ii) the aim of the project; (iii) possible adverse aspects regarding participation and (iv) that they were free to withdraw consent at any time. Of the participants, 90% were judged able to give informed consent (by giving positive responses in each of the four areas). For the remaining 10%, agreement to participate was sought and gained from a relative.
Procedure
Information was collected by face-to-face computer assisted interviews undertaken at the homes of participants or in service settings attended by participants. Participants had the opportunity of being supported during the interview by a person of their choice. For our subset of participants: 712 (56%) were interviewed alone; 269 (21%) were supported by a relative (most commonly a parent); 255 (20%) were supported by a paid support worker; 19 (1%) were supported by their partner; 11 (1%) were supported by an independent advocate and 7 (1%) were supported by a friend. Interviewers were recruited from within a pool of interviewers used by BMRB and provided with specific training related to interviewing people with intellectual disabilities. A number of strategies were adopted to maximize the active participation of the participant with intellectual disabilities. These included: (i) providing specific training for all interviewers (part of which was undertaken by trainers who had intellectual disabilities); (ii) simplifying the wording of questions; (iii) employing visual aids and (iv) encouraging interviewers to rephrase questions.35
Key measures
The survey collected wide ranging information about the life experiences of participants.35 The full questionnaire is available at http://www.ic.nhs.uk/pubs/learndiff2004. Key measures for the present analyses are described below.
Self-rated health
Participants were asked ‘In the last year would you say your health was very good, fairly good or not good’.
Personal characteristics and living situation
A number of variables related to the personal characteristics of participants and their living situation were extracted from the data set. Personal characteristics included: (i) age; (ii) gender; (iii) ethnicity; (iv) marital status and (v) level of support needs. The latter was measured through use of an 11-item scale that measured level of support required to engage in a range of personal and social activities (getting dressed in the morning, putting on a pair of shoes, having a shower or a bath, ordering something to eat or drink at a café, drinking a cup of tea, washing your clothes, making a sandwich, filling in a form (e.g. if you were applying for a job), finding out what is on the television tonight, paying money into your bank or post office, making an appointment (e.g. to see your doctor). The scale showed acceptable levels of internal consistency for participants in our analyses (alpha = 0.77). Living situation was categorized as living in: (i) a private household (PH); (ii) a Registered Residential Care Home (RRCH); (iii) supported accommodation funded through the a national Supporting People programme (SP) and (iv) medium to long-term accommodation operated by the UK's National Health Service (NHS).
Socioeconomic disadvantage
Three indicators of socioeconomic disadvantage were extracted from the data set: (i) whether the participant was in paid employment; (ii) overall neighbourhood deprivation quintile from the English Indices of Deprivation;45 (iii) a measure of hardship. The latter contained nine items derived from the Millennium Poverty and Social Exclusion Survey.46 Participants were asked ‘Sometimes, when money is tight, people have to go without things. In the last year, have you always had enough money for [item] when you wanted it/them?) The specific items included were: new clothes; new shoes; food; heating; telephoning friends or family; going out; visits to the pub or a club; a hobby or sport; a holiday. Visual cues were used to illustrate each item. The hardship scale showed acceptable levels of internal consistency for participants in our analyses (alpha = 0.89).
Social participation and networks
Five indicators of social participation and networks were extracted from the data set: (i) whether the person has participated over the preceding month in each of nine named community-based activities (e.g. going to the shops, playing a sport or swimming), this indicator showed moderate levels of internal consistency for participants included in our analyses (alpha = 0.54); (ii) whether the person was in unpaid employment (i.e. volunteering in an organization); (iii) the frequency of contact with relatives; (iv) friends who had intellectual disabilities; and (v) friends who did not have intellectual disabilities.
Approach to analysis
Weighting
Data were weighted to reflect: (i) best estimates of the proportion of adults with intellectual disabilities that live in private households and the three types of supported accommodation sampled; and (ii) size of CSSR. Full details are available at http://www.ic.nhs.uk/pubs/learndiff2004.
Data reduction
In order to simplify interpretation and address the non-normality of variable distributions, non-binary indicators of social connectedness and hardship were reduced to binary variables by splitting variables at the median scale point.
Alpha level
Due to the statistical power provided by the relatively large sample and the number of bivariate associations investigated, an alpha level of P < 0.01 was set for bivariate analyses.
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Bivariate associations between self-reported health status and the personal characteristics and living circumstances of participants, and indicators of socioeconomic disadvantage and social participation and networks are presented in table 1. Health status was associated with gender, age, marital status, living circumstances, all three indicators of socioeconomic disadvantage and two of five indicators of social participation and networks.
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Multivariate analyses (binary logistic regression forward stepwise conditional variable entry P-entry <0.05 P-exit >0.10) were undertaken in order to determine the unique contribution of these variables to self-reported health status (not good versus fairly good/very good health).
Independent variables were conditionally entered in two blocks: Block 1 contained indicators of personal characteristics, living situation, the interview procedure and gender by personal characteristics interaction terms; and Block 2 contained indicators of socioeconomic disadvantage and gender by socioeconomic disadvantage interaction terms and indicators of social participation and networks and gender by social participation and networks interaction terms. Due to the extremely small proportions involved, ethnicity was not entered into the analyses and people living in NHS accommodation were excluded from the analyses. These analyses were undertaken on a subset of 1203 participants for whom full data were available (95% of the sample). Results are presented in table 2.
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The introduction of indicators of personal characteristics and details of the interview procedure (Block 1) accounted for a significant proportion of the variance in health status (Nagelkerke r2 = 0.148). Specifically, older age, being married/separated or divorced, having higher support needs, living in a private household or registered residential care home and being interviewed alone were all independently associated with poor health status. There were no significant associations (either main effects or interaction terms) between gender and health status.
The introduction of indicators of socio-economic disadvantage and social participation and networks (Block 2) accounted for an additional statistically significant proportion of variation in health status, over and above any variation attributable to the personal characteristics and living circumstances (Nagelkerke r2 rising from 0.148 to 0.198; Block 
2 = 38.7, df = 2, P < 0.001). Specifically, once the effects of personal characteristics and living circumstances were taken into account, facing greater material and social hardship and being unemployed (especially for women) were independently associated with poorer health status. There were no significant associations between health status and either indicators of neighbourhood deprivation or social participation and networks. The introduction of the indicators of socio-economic disadvantage appeared to partially mediate the association between marital status and not good health (reducing the increased risk associated with marital status by 38%)
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Discussion |
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Principal findings
Indicators of socio-economic disadvantage accounted for a statistically significant proportion of variation in the health status of people with mild or moderate intellectual disabilities, over and above any variation attributable to personal characteristics and living circumstances. Indicators of social participation and networks did not add to the explanatory power of the model. Among the indicators of socio-economic disadvantage, hardship was more strongly associated with health status than either employment status or area-level deprivation. Introduction of the indicators of socioeconomic disadvantage appeared to partially mediate the association between marital status and poor health.
Strengths and weaknesses of the study
The main strengths of the study are: (i) the use of a well-constructed and reasonably sized sample of adults with mild or moderate intellectual disabilities; and (ii) the employment of a range of strategies to support the active participation of people with intellectual disabilities in the interviews. The latter point is important as, due to well-rehearsed concerns regarding the reliability of self-report data collected from people with intellectual disabilities,44 the vast majority of research undertaken on the health, well-being and life opportunities of people with intellectual disabilities has collected data from proxy respondents. The use of proxy data is, however, extremely problematic when attempting to capture subjective experience.42 The results of the present study indicates that concerns regarding response bias may have been significantly overestimated and that the use of self-report data is viable for a significant proportion of respondents with mild and moderate intellectual disability. The results do, however, indicate an association between self-rated health and the presence of a third party during the interview, with people interviewed alone being more likely to report poor health. This association may reflect either an influence on responding as a result of the presence of a third party and/or the influence of unmeasured variables (e.g. mental health status of the interviewee, degree of control exerted by others in the interviewee's living situation) on both self-rated health and the presence of a third party.
The main weaknesses of the study are: (i) the use of self-rated health as the sole indicator of health status; (ii) the use of a restricted range of indicators of socioeconomic disadvantage and social participation and networks; and (iii) the use of a cross-sectional design. With regard to the first point, while there is extensive evidence that self-rated health is a robust predictor of mortality,47–49 it is clearly not equivalent to health status.50 Indeed, the relationship between general self-reported health and morbidity is complex and is likely to reflect such factors as individual and group differences in: (i) interpreting the question (e.g. the time span over which health is to be evaluated, whether ‘health’ includes mental health and well as physical health); (ii) expectations regarding what would constitute ‘good’ or ‘poor’ health and (iii) the extent to which ill health impacts on meeting the demands of everyday life. Thus, for example, evidence suggests that low socio-economic position may be associated with an under-reporting of ill health, an association that would lead to measures of self-reported health underestimating social gradients in health status.51
With regard to the second point, the measurement of socioeconomic disadvantage among adults with intellectual disabilities is highly problematic due to very narrow ranges of: (i) income (determined primarily by benefit receipt); (ii) occupational status and (iii) educational attainment.21 This is the first study that has used a measure of hardship among people with intellectual disabilities. The success of this measure in predicting health status suggests that it may have considerable value as an indicator of socio-economic disadvantage among adults with intellectual disabilities. The indicator of social participation and networks employed in the study was developed from available interview items. It is possible that lack of effect noted in the analyses may reflect conceptual and psychometric weaknesses of the measure.
With regard to the final point, all analyses undertaken on cross-sectional data are correlational in nature. As such, it is not possible to ascribe any causal relations between socio-economic disadvantage and health status from the present data. However, unless we assume that people with intellectual disabilities are somehow immune from the impact of socio-economic disadvantage on health,24,28,52 it does appear plausible to suggest that the increased rates of exposure of people with intellectual disabilities to socio-economic disadvantage are likely to have an impact on their health and well-being.
Meaning of the study
The main findings of the study, that health status is associated with indicators of socio-economic disadvantage, is consistent with the wealth of evidence of such an association derived from studies of the general population.25–29,31,53,54 They add to this literature, however, by indicating that these associations are also apparent within a highly marginalized group of adults with significant long-term intellectual disabilities and very poor health outcomes. As such, the study makes a modest contribution to bridging the gap between these two worlds of enquiry.
The findings of the study add significantly to research addressing the health of people with intellectual disabilities. As we have discussed, research in this area has been dominated by medical and psychosocial approaches that have largely failed to address the potential impact of social context on the health of people with intellectual disabilities.21,32,38,40,41 In particular they draw attention to the potential importance of material and social hardship and employment52 in understanding variations in the health status of people with intellectual disabilities.
The results are notable, and stand in contrast to the wider literature, in failing to find associations between health status and either gender (beyond an interaction effect with employment status) or indicators of social participation and networks.24,28 As noted earlier, the failure to find associations with indicators of social participation and networks may be due to the selection of measures. The failure to find effects related to gender are more puzzling.55 They are, however, consistent with other results reported from this and other data sets which suggests that few associations are found between gender and the life experiences of people with intellectual disabilities.35,56,57 The systematic absence of gender effects may reflect the de-gendered social construction of intellectual disability.
Unanswered questions and future research
This is the first study to address the relationship between self-reported health status and indicators of personal characteristics, socio-economic disadvantage and social participation and networks among adults with intellectual disabilities. The results clearly require replication across other samples (including people with more severe intellectual disabilities and other indicators, particularly of health status and social participation and networks). There is also a clear need for longitudinal research to further our understanding of both the direction of effects and the extent to which the processes that mediate and moderate the association between socio-economic disadvantage and health status among people with intellectual disabilities are similar to or dissimilar from pathways and processes that operate within the wider population. Finally, there is a clear need for more ‘generic’ research into the social determinants of health to begin to address the situation of sections of the population that may be particularly vulnerable to poor health outcomes, including people with intellectual and other disabilities.
Key points
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Conflict of interest: None declared.
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