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The prevalence of mental disorders among income support recipients: An important issue for welfare reform

The prevalence of mental disorders among income support recipients: An important issue for... Peter Butterworth Centre for Mental Health Research, Australian National University , Australian Capital Territory Abstract Objective: To estimate the prevalence of mental disorders and psychological distress among Australian income support recipients. Methods: Data from the 1997 National Survey of Mental Health and Wellbeing were used to examine measures of mental health, disability and use of mental health services, comparing working-age people in receipt of government payments to those with other main sources of income. he Australian social security system provides income support payments as a safety net to protect those without adequate income. Unlike most other developed countries, benef its are paid from general government revenue and are not based on previous earnings or individual contributions. Eligibility for income suppor t is subject to income and assets tests (of both the individual and their larger f amily unit) to ensure that payments are targeted to those in need. There are different categories of income support payments, with eligibility based on recipients’ personal circumstances. For example, payments are available to people of workforce age on the basis of their: disability and inability to work; caring responsibilities for people with disabilities; temporary unemployment; older age, longterm unemployment and lack of recent workforce experience making re-employment unlikely; older age and having a partner who is recei ving income suppor t payments; lone parenthood; and parenting responsibilities while having a partner with low income. For a review of the Australian social security system see Whiteford and Angenent.1 A recent social policy focus of the Commonwealth Gover nment has been welf are reform. The term welfare reform can be applied to a broad range of policy changes that emphasise active participation by payment recipients (including increased job search, mutual oblig ations, work-for-the-dole and other requirements to promote participation in work or work-type activities) rather than a passive system of income support.2,3 These changes reflect, in part, concer n that passive welfare promotes a culture of dependency, a loss of personal master y, a decrease in recipient motivation, and the development of attitudes and values inconsistent with work.4,5 Welfare reform is an international phenomenon. Experience and e vidence from the United States (US) and United Kingdom (UK) has been the basis of much policy consideration in Australia6 and, as such, is the focus of this review. Within Australia, the mo vement towards active labour market policy has steadily increased since the 1980s (with the introduction of the activity test), through the extensive labour market programs implemented under Working Nation in the mid 1990s to the present welfare reform process.1,3 In 2000, a reference group provided recommendations to the Gover nment on the direction of welfare reform in Australia.6 The Government has introduced or is considering a range of policy responses.7 There is a growing body inter national research exploring the mental health of welfare recipients. This research has demonstrated that the prevalence of mental disorders and mental health prob lems among welfare recipients is much greater than in the broader community.8-17 Research from the US suggests that the success of welfare refor m has been selective and that those recipients with more substantial bar riers, including mental health problems, have not Results: One-quarter of all income suppor t recipients had exper ienced substantial levels of psychological distress during the previous four w eeks and almost one in three had exper ienced a diagnosable mental disorder during the previous 12 months. Around 45% of unpar tnered women with children in receipt of income support payments were identified with a mental disorder. In contrast, around 10% of people not receiving welfare reported substantial psychological distress and 19% had a diagnosable mental disorder. The prevalence of physical and mental disability was also greater among income support recipients. There was no difference in service use between recipients and nonrecipients. Conclusions: Mental illness is a significant issue among income support recipients. The presence of a mental disorder is a substantial barrier to work and other forms of social participation. Mental health is an issue with relevance beyond the health portfolio, with implications for many domains of social policy and service delivery. Understanding and better assisting income support recipients with mental health problems will be impor tant in welfare reform and in the introduction of a more active welfare system. ( Aust N Z J Public Health 2003; 27: 441-8) Correspondence to: Dr Peter Butterworth, Centre for Mental Health Research, Australian National University, Canberra, ACT 0200. E-mail: Peter.Butterw orth@anu.edu.au Submitted: November 2002 Revision requested: May 2003 Accepted: June 2003 2003 VOL. 27 NO . 4 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH Butterworth Article benefited from the introduction of more work-focused welfare.18-20 Given these findings, applied research in the US has sought to better understand the ways in which mental health problems present a barrier to increased par ticipation and employment and to develop options and approaches to increase the effectiveness of policy and ser vice delivery. 8,12 Poor mental health is associated with factors such as unemployment, pover ty, lower socio-economic status and sole parenthood.21-24 For example, there is convincing evidence, particularly from longitudinal data, that mental health declines as a consequence of unemployment.25 There is clearly overlap between these factors and welfare receipt and, as such, it is expected that the prevalence of mental disorders will be higher among welfare recipients than those not receiving welfare. The purpose of this study is to quantify and explore this potentially impor tant characteristic of Australian income suppor t recipients. The aim is not to examine the causal pathways leading to poorer mental health. If income support recipients are more likely to experience a mental disorder then, regardless of the cause, this needs to be reflected in policy design and service delivery. Australian social policy has reco gnised that low-prevalence mental illnesses, such as psychosis, can significantly limit a person’s capacity to participate in society. The clinical and epidemiological study of low-prevalence disorders conducted as one aspect of the National Survey of Mental Health and Wellbeing26 found that 85% of people with psychotic disorders received a Gover nment pension or payment (primarily disability support pension). However, these types of mental disorders are rare, with Australian estimates of the 12-month prevalence of psychosis less than 1%.26 The issue examined in this paper is the extent to which income support recipients experience common mental disorders (anxiety, depressive and substance use disorders). These common mental disorders affect around 18% of the overall Australian population during a given year. This project represents the first attempt to quantify the extent that Australian income suppor t recipients experience common mental disorders. This study will also examine the level of disability, or impact on functional ability, that common mental disorders have and the e xtent to which income support recipients use mental health services. based on State, part-of-State, age, gender and probability of selection to match the overall Australian population. Measures The primary diagnostic component of the sur vey was based on a computerised version of the Composite Inter national Diagnostic Interview (CIDI) Version 2.1. 27 The data repor ted in this paper use the International Classif ication of Diseases – 10th revision (ICD-10) and examine the presence of an y anxiety disorder, any affective (primarily depressive) disorder, and har mful alcohol or drug use or dependence, as well as a summar y measure of the presence of any mental disorder. The Short Form 12 Health Survey (SF-12)28 provided physical and mental health summary scores that reflect limitations across different domains of daily activities and functioning. After Sanderson and Andrews,29 SF-12 scale scores were categorised into four levels of disability based on the standardised scale mean and standard deviation: scores of 50 or higher were classif ied as no disability; scores of 40 to 49 were classified as mild disability; scores of 30 to 39 as moderate disability; and scores below 30 were classif ied as severe disability. The sur vey included the K10, a scale of psychological distress, to enable the measurement of psychological morbidity (including subclinical distress) within the population.30 The scale produces scores within the range of 10 to 50, with a higher score indicating greater distress. In addition to the scale score, the cur rent analysis categorised those respondents with a substantial level of psychological distress, identifying those with a score of 20 or g reater.31 The NSMHWB also collected data on individuals’ use of mental health services. This included infor mation on admission to a general or psychiatric hospital, admission to a drug or alcohol unit, or consultation with general practitioners, psychiatrists, psychologists, social workers, counsellors or other specialists or mental health professionals for mental health reasons. Finally, this analysis assessed a range of socio-demographic information that was collected through the sur vey, including age, gender, marital status, labour force status, main source of income, household structure, housing tenure and educational attainment. Analysis This analysis focused on the subset of survey respondents of workforce age, that is, males aged under 65 and females aged under 60. It estimated the population of income support recipients, identifying those who reported that Government pensions or payments were their main source of income. The analysis also examined different income support client segments. Five client groups were derived based on gender, partner status, full-time study having had children, the presence of children in the house, hold and labour force status. The client segments, which were devised to cor respond to the main income support payments, were: unemployed; students; par tnered women with children; unpartnered women with children; and not in the labour force (NILF; payments that do not require active job search such as disability support pension). The estimates of parenting payment VOL. Methods Sample This analysis used the conf identialised unit record file of the National Survey of Mental Health and Wellbeing (NSMHWB). The survey was conducted by the Australian Bureau of Statistics in 1997. The NSMHWB used a representative sample of persons living in private dwellings from all States and Ter ritories. The survey w as designed to provide data on the prevalence of major mental disorders and the associated levels of disability and health service usage in Australia. About 13,600 households were approached, with one person aged 18 or over from each house randomly selected for inter view. Overall, 10,641 individuals completed the survey (a 78% response rate). The sample was weighted AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH 27 NO. 4 Methods and Concepts Mental disorders among income support recipients recipients focused exclusively on women, even though the payments are available for men with child care responsibilities, as administrative data shows that 97% of parenting payment (partnered) recipients and 93% of parenting payment (single) recipients are women.32 Another pub lication provides detailed information on the characteristics of the client se gments and of analysis under taken to validate these estimates ag ainst administrative and other data sources.33 The preliminary analysis examined the association between sociodemographic characteristics and income suppor t status using chisquare tests. Data on the differences between the g roups in their experience of psychological distress (as measured by the K10 scale) was assessed using negative binomial regression models (due to severe positive skew). For all of the categorical outcome measures, a consistent set of analyses was used. The first contrasted income support recipients with non-recipients. The second contrasted each income support client segment with the non-recipients. Then, these simple analyses were replicated controlling for potential confounders, including age, gender, partner status, housing tenure, presence of children in the home and education. A series of logistic regression models examined the association between income support status and substantial psychological distress and the presence of CIDI diagnosed depression, anxiety, and substance-use disorders, as well presence of any CIDI disorder. A similar approach was used to examine the predictors of mental and physical disability. Finally, logistic regression models examined use of formal mental health services for those individuals with a CIDI-diagnosed mental disorder or substantial psychological distress. For this analysis, a third model adjusted for physical disability was also included. Statistical analyses were conducted using SPSS-11 and STATA. For the means and chi-squared analyses, the weights used represented the reciprocal of the probability of selection and were rescaled by dividing by the mean weight of the total sample (n/N). Thus, the measure of variability represents that expected from the total sample size, not from the total population. For the logistic regression and negative binomial models, the jackknife replicate weights were used to derive standard errors and conf idence inter vals. Results Demographic characteristics Table 1 presents data on the demographic characteristics of those not receiving income support payments and the f ive income support client segments. Chi-square analyses of the association between g roup membership and each of the characteristics were all Table 1: Characteristics of the income suppor t recipient and non-recipient client segments. Not receiving income support Sample (n) Unweighted Gender (%) Male Female Age (%) 18-29 30-39 40-49 50+ Marital status (%) Marr ied/de facto Divorced/separated Widowed Never married Housing tenure (%) Own Purchasing Renting Other Country of birth (%) Australia Education (%) Not completed school Completed school Trade Tertiar y studies 26.7 18.2 23.7 31.2 51.5 14.0 22.0 12.5 16.4 50.3 11.9 21.4 50.0 18.0 19.7 12.3 59.6 13.5 19.7 7.3 52.1 13.8 25.2 8.9 75.1 74.3 75.3 75.6 81.5 70.6 28.7 26.2 25.5 19.6 68.9 6.7 0.5 23.9 23.5 40.1 24.6 11.8 46.4 19.8 15.4 18.5 39.0 13.0 1.2 46.8 15.6 15.6 48.4 20.3 81.0 10.8 7.6 0.6 16.9 7.5 0.6 75.0 3.1 6.3 47.5 43.1 28.4 51.0 18.9 1.7 100 – – – 16.0 51.0 30.1 2.9 30.3 39.9 22.5 7.3 – 64.6 3.4 32.0 7.9 10.7 73.0 8.4 11.3 10.3 15.8 62.6 62.2 14.6 4.0 19.2 41.9 16.0 33.0 9.1 6,771 54.2 45.8 Unemployed Income support client segments Student Par tnered Unpartnered woman with child woman with child 137 46.5 53.5 368 – 100 310 – 100 Not in labour force 2003 VOL. 27 NO . 4 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH Butterworth Article significant at p<0.001. All income support recipient g roups, apart from students, reported lower levels of education than nonrecipients. Those in the unemployed and student g roups were generally younger than those in the other groups. Their younger age is likely to be an explanation for the greater propor tion of never mar ried clients, and the greater pre valence of rental or ‘other’ housing arrangements (likely living with parents or shared housing). In contrast, those in the NILF group were older than the non-recipients and the other client groups. This may account for their greater le vel of home ownership. The unpar tnered women with children were more likely to reside in rental accommodation than any other group. Psychological distress and mental disorders Income support recipients had signif icantly poorer mental health than people not receiving income suppor t payments (see Table 2). The mean K10 measure of current distress was g reater for income support recipients than for those not receiving income support payments (Incidence Rate Ratio (IRR, ec)=1.19; 95% confidence interval (CI) 1.16-1.22). The average K10 scores were greater for all groups of income suppor t recipients (IRRs from 1.10 for partnered women with children to 1.27 for unpartnered women with children). The second column of Table 2 shows the percentage of respondents within each group with a psychological distress score of 20 or g reater. Overall, a significantly g reater proportion of income support recipients experienced substantial psychological distress (24.2%) than non-recipients (10.3%; odds ratio (OR)=2.77, 95% CI 2.38-3.24). Simple logistic regression (see Table 3) showed that the prevalence of substantial psychological distress was greater among all income suppor t client groups than non-recipients though, because of smaller sample size and wider CI, the difference for the student group was not significant. The lack of significance for the student group w as repeated in most analyses. The other income support recipient g roups continued to demonstrate significantly greater psychological distress than nonrecipients after adjustment for potentially confounding variables. Those receiving income suppor t payments were also more likely to have experienced a CIDI-diagnosed af fective, anxiety or substance-use disorder in the previous 12 months than those not receiving income support payments. The ORs were 1.99 (95% CI 1.66-2.38), 2.33 (95% CI 1.92-2.85) and 1.60 (95% CI 1.34-1.92), respectively. Further, those receiving income support payments had higher levels of mental disorders overall than the no income support group (OR=1.92, 95% CI 1.64-2.26). Around 19% of non-income support recipients of workforce age experienced a mental disorder, compared with more than 30% of income support recipients. The data in Table 2 demonstrate a pattern that differs as a function of client group and type of disorder. All income support client groups demonstrated greater prevalence of depressive disorders than non-recipients, although the increased prevalence of the partnered women with children and student groups was not signif icantly different. Anxiety disorders were signif icantly more prevalent in all income support recipient groups, and (again) markedly g reater in the unpartnered mother group. The le vel of substance-use disorders was most pronounced in the unemployed group, with students and unpartnered women with children also showing considerably g reater levels of substance-use disorders than non-recipients. The partnered women with children group experienced only half the level of substanceuse disorders as the comparison group. However, after adjustment, only the unemployed and the NILF groups demonstrated substance-use disorders at a level signif icantly different to nonrecipients. Levels of disability Figure 1 presents SF-12 data on disability due to mental and physical causes. For almost all client groups, there was a gradient Table 2: Mental health characteristics of income support recipients (overall and each client segment) and nonrecipients, with 95% confidence intervals. Kessler K10 Mean CI %>20 Affective disorders (% & CI) 7.1 6.51-7.70 13.2 11.52-14.84 12.7 9.47-15.95 10.7 5.83-15.52 9.6 6.51-12.73 20.3 14.38-26.31 14.3 11.22-17.34 CIDI diagnoses (ICD-10) Anxiety Substance disorders use disorders (% & CI) (% & CI) 8.7 8.04-9.35 18.2 16.32-20.11 16.6 13.01-20.25 17.2 11.26-23.11 14.7 10.92-18.38 30.4 23.58-37.21 18.0 14.63-21.35 8.3 7.65-8.93 12.6 11.01-14.27 21.5 17.53-25.53 14.9 9.34-20.53 4.2 2.11-6.35 13.6 8.55-18.72 10.5 7.84-13.21 Total mental disorder s (% & CI) 18.7 17.77-19.58 30.6 28.38-32.90 33.7 29.14-38.34 30.2 23.01-37.42 20.9 16.62-25.20 45.2 37.87-52.62 29.8 25.84-33.84 No income suppor t Receiving income support – total Unemployed Studying Partnered women with children 13.9 13.80-14.02 16.5 16.18-16.85 15.8 15.22-16.41 16.4 15.57-17.27 15.30 14.72-15.89 10.3 9.61-11.02 24.2 22.11-26.31 21.5 17.53-25.53 24.6 17.82-31.34 18.6 14.52-22.73 30.4 23.60-37.24 27.9 24.00-31.84 Unpartnered women with children 17.63 16.58-18.69 Not in labour force/disability 17.55 16.85-18.26 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH VOL. 27 NO. 4 Methods and Concepts Mental disorders among income support recipients of disability, with mild disability more common than moderate which in turn was more common than severe disability. Only the NILF group differed from this pattern, reporting greater prevalence of severe and moderate physical disabilities. Physical disabilities were more common among income support recipients than non-recipients (OR= 2.24; 95% CI 1.81-2.79). Compared with those not in receipt of income support, physical disability was more prevalent among the partnered women with children (OR=1.50, 95% CI 1.22- 1.85), unpartnered women with children (OR=1.95, 95% CI 1.44-2.65) and NILF g roup (OR=6.25, 95% CI 4.66-8.40). Disability because of poor mental health was also more prevalent for income support recipients than non-recipients (OR=2.17, 95% CI 1.91-2.46). All client segments showed higher levels of mental disability than the non-recipients (unemployed: OR=1.94, 95% CI 1.58-2.38; students: OR=1.93, 95% CI 0.97-3.81; partnered women with children: OR=1.94, 95% CI 1.50-2.50; unpartnered women with children: OR=3.01, 95% CI 2.36-3.85; NILF: OR=2.36, 95% CI 1.82-3.06). After adjustment, the partnered women with children, unpartnered women with children and the NILF groups continued to demonstrate significantly higher levels of disability (both physical and mental) than non-recipients, while the unemployed group had a higher level of mental disability. Use of services Table 4 sho ws the extent to which people with a CIDIdiagnosed mental disorder or a K10 score of 20 or greater used mental health services. The data indicate that around 32% of those with a mental disorder and not receiving income support payments used mental health services compared with 39% of those Table 3: Simple and adjusted odds ratios and 95% confidence intervals for the associations between income support status and measures of mental disorders and psychological distress. Simple OR 95% CI Depressive disorders No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Anxiety disorders No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Substance use disorders No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Total – any disorder No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Adjusted a OR 95% CI 1.31-2.76 0.60-4.08 0.90-2.16 2.45-4.55 1.65-2.87 1.12-2.44 0.48-3.42 0.69-1.60 0.99-2.05 1.54-2.84 Figure 1: SF-12 data on disability due to mental and physical causes (% of recipients in each category with disability). SF-12mental disability Mild No income support Income support Moderate 27.3 44.9 Severe 1.29-3.40 1.35-3.52 1.31-2.48 2.99-7.03 1.75-3.02 1.10-3.25 1.06-3.24 0.98-2.06 1.27-3.74 1.70-2.93 2.05-4.26 0.89-4.24 0.31-0.77 1.13-2.69 0.91-1.87 1.31-3.01 0.44-3.07 0.58-1.63 0.93-2.57 1.01-2.34 unemployed students partnered women with chd unpartnered women with chd not in labourforce 0 20 40 1.68-2.93 0.92-3.86 0.87-1.52 2.68-4.84 1.35-2.54 1.31-2.34 0.61-2.83 0.80-1.52 1.28-2.96 1.51-2.65 SF-12Physical disab ility Mild No income support Income support Moderate 29.7 48.7 Severe unemployed students partnered women with chd unpartnered women with chd not in labour force 0 20 40 Psychological distress > 20 No income suppor t (ref) Unemployed 2.39 Students 2.83 Partnered women 1.99 with children Unpartnered women 3.80 with children Not in labour force 3.37 1.48-3.83 0.92-8.73 1.51-2.62 2.86-5.06 2.61-4.35 1.23-3.21 0.87-6.00 1.26-2.60 1.14-3.37 2.34-4.07 Note: (a) Adjusted for age, housing tenure, partner status , presence of children at home and educational attainment. 2003 VOL. 27 NO . 4 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH Butterworth Article with a mental disorder who did receive income support payments (OR=1.37, 95% CI 1.01-1.83). Consideration of the separate client segments showed that only the unpartnered women with children and the NILF groups used mental health services more than non-recipients. However, the unpartnered women with children did not differ from non-recipients after adjusting for sociodemographic variables and the NILF group did not differ after adjusting for socio-demographic variables and level of physical disability (SF-12 physical score). Discussion This study estimated the prevalence of mental disorders and psychological distress among Australian income support recipients. The analysis showed that one-quarter of all income support recipients had experienced substantial levels of psychological distress in the previous four weeks and that almost one in three had experienced a diagnosable mental disorder during the previous 12 months. Mental disorders (primarily depression) are the third-leading cause of overall disease b urden in Australia.34 Given the relatively low levels of mor tality associated with mental illness, this disease burden mainly represents functional limitations and restricted participation in activities, such as work. As such, it was expected that there would be a strong association between receipt of income support and mental illness. This study is important as it presents quantitative national data on the topic. This study also examined the circumstances of different subgroups within the population of income support recipients. It differentiated clients on the basis of characteristics that cor respond to the payment str ucture. While most client segments demonstrated elevated levels of all disorders, the anal ysis showed that different groups experienced different types and different rates of mental disorders. This knowledge is important to ensure an appropriate and targeted policy response. Those classif ied as unemployed were far more likely to experience a disorder associated with harmful substance use or dependence than other segments and non-recipients. The NILF group demonstrated consistently higher levels of all disorders while showing markedly greater psychological distress. This group reported higher levels of physical disability (over 70%). Their psychological distress may have been associated with these physical disorders. Unpartnered women with children demonstrated levels of depression and anxiety disorders over three times that of non-recipients, with around 45% estimated to have some type of mental disorder in the previous 12 months. While alarming, this result is consistent with international evidence of the level of mental illness among sole parents receiving welfare.9,10,16 Income support recipients in most client segments experienced higher levels of disability associated with poor mental health than non-recipients. That is, their ability to undertake daily activities including working, looking for a job or caring for children was more likely to be compromised by mental illness. This is consistent with the data on burden of disease34 and research showing mental illness presents a significant bar rier to economic participation.11,35,36 This research shows that mental health is an issue with implications and relevance beyond health policy. Recently there has been greater recognition in Australia of the relevance of client mental health to the achievement of social policy goals and objectives in the areas of employment and income support.37,38 Mental illness does not only limit the well-being and par ticipation of individuals, but maternal depression and mater nal mental illness have negative consequences for children.39 The current findings, therefore, have implications for many domains of social policy and service delivery including employment, income support, family services, targeting early inter vention and prevention strategies and disability services. These results need not be viewed pessimistically. Recent advances in prevention, diagnosis and treatment (including improved efficacy and cost effectiveness) of mental health problems means that most people with mental disorders can be helped.40 Having identified the magnitude of mental health barriers among income support recipients, Commonwealth social policy agencies will be better placed to understand and address Table 4: Use (%) of mental health services of those with mental disorders or significant psychological distress by income support status with simple and adjusted odds ratios and 95% confidence inter vals. n (with mental health problems) No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force 1,629 164 63 101 94 204 Access mental health services % Simple Adjusted Socio-demographica Adjusted Socio-demographica and physical disability OR OR 95% CI 0.60-1.82 0.54-3.65 0.61-1.77 1.10-2.45 1.11-2.70 OR 95% CI 0.65-2.15 0.60-4.62 0.46-1.67 0.52-1.73 1.12-3.39 95% CI 0.66-2.08 0.59-4.78 0.45-1.66 0.52-1.59 0.92-3.26 Notes: (a) Adjusted for age, housing tenure, partner status, presence of children at home and educational attainment. AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH VOL. 27 NO. 4 Methods and Concepts Mental disorders among income support recipients the consequences of these disorders. This could increase the positive outcomes achieved by participants. The types of policy responses could include: the introduction of screening and assessment processes that target mental health; improving the mental health literacy41 of polic ymakers and service delivery staff (the knowledge and awareness of mental health and mental disorders); the provision of specialist programs for those with signif icant mental health problems (such as the recently introduced personal support program); the inclusion of mental health practices within employment programs, such as cognitive behaviour therapy techniques;42-45 and promoting linkages with existing mental health services. The NSMHWB data show that less than one-third of those with mental disorders seek assistance.46 This study found that income support recipients were somewhat more likely to use ser vices. This increased service use was accounted for by demographic characteristics and level of physical disability. This was consistent with Parslow and Jorm,47 who found that three sociodemographic variables (being female, being separated and ha ving a higher education) were associated with increased use of mental health services. These features account for the increased use of mental health services by sole parents on income suppor t (see also Cairney and Wade17). The NILF group had greater physical disabilities and, therefore, may have had g reater contact with medical professionals. Their increased use of mental health ser vices may have been a consequence of their general greater use of services. It is important to recognise that this Australian data does not show lesser use of mental health services by those on income support, as is found in studies of welfare recipients in the US.10 The study did not examine causality and, thus, cannot disentangle the direction of the relationship between welfare receipt and mental illness. While it is likely that the relationship is bidirectional, it is also likely that both factors reflect and interact with other underlying characteristics (e.g. early abuse/trauma, lack of education and work skills, unemployment, levels of social and community support, divorce/separation, poverty, coping skills and resilience). The differing pattern of mental health problems across the client segments shows there is not a simple association between welfare receipt and poor mental health outcomes. The categorical nature of the income support system means that recipients of different payments have v ery different characteristics and are in different circumstances. The striking difference in the mental health of partnered and unpartnered women with children illustrates this diversity. Future research will need to consider different client groups separately in order to better understand the specific circumstances and risk factors that are associated with elevated mental distress among different groups of income support recipients. The main limitation of this study is that it estimated the income support client se gments using demographic characteristics. This is, however, unique research in the Australian context. No data source contains both the richness of mental health information and detailed data on income support receipt. Further, the estimates of the client groups have been shown to match the 2003 VOL. 27 NO . 4 administrative data.33 Another limitation is that the various measures examined in this analysis reference different time periods (e.g. psychological distress and disability refer to the last four weeks, mental disorders and service use refer to the last 12 months, while income support receipt is based on cur rent circumstances). Thus, the cur rent analysis may underestimate the association between income support receipt and mental health problems. In conclusion, this study has shown that mental illness is a significant issue among income suppor t recipients. Mental illness is associated with disability/impairment in a substantial number of income support recipients across all types of payments, not just disability payments. This is likely to present a substantial barrier to work and other for ms of social and economic participation. Mental health is, therefore, an impor tant issue in the context of welfare reform and the introduction of a more active welfare system aiming to increase participation. Traditionally, social policy researchers have focused on str uctural (financial incentives, child care, transport), human capital (education, employment experience, job skills) or demographic characteristics (age, marital status, housing tenure) when analysing labour market circumstances and income support receipt. The findings from this study indicate that an approach that does not consider mental illness overlooks an impor tant characteristic associated with receipt of income support. Fur ther, contrary to general perceptions, mental disorders are readily treated and prevented40 and may be more easy and inexpensive to address than many of these human capital characteristics. Acknowledgements I wish to thank Tony Jor m and Kaarin Anstey for comments on an earlier draft of this manuscript and Ruth Parslow for statistical advice. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australian and New Zealand Journal of Public Health Wiley

The prevalence of mental disorders among income support recipients: An important issue for welfare reform

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Wiley
Copyright
Copyright © 2003 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1326-0200
eISSN
1753-6405
DOI
10.1111/j.1467-842X.2003.tb00424.x
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Abstract

Peter Butterworth Centre for Mental Health Research, Australian National University , Australian Capital Territory Abstract Objective: To estimate the prevalence of mental disorders and psychological distress among Australian income support recipients. Methods: Data from the 1997 National Survey of Mental Health and Wellbeing were used to examine measures of mental health, disability and use of mental health services, comparing working-age people in receipt of government payments to those with other main sources of income. he Australian social security system provides income support payments as a safety net to protect those without adequate income. Unlike most other developed countries, benef its are paid from general government revenue and are not based on previous earnings or individual contributions. Eligibility for income suppor t is subject to income and assets tests (of both the individual and their larger f amily unit) to ensure that payments are targeted to those in need. There are different categories of income support payments, with eligibility based on recipients’ personal circumstances. For example, payments are available to people of workforce age on the basis of their: disability and inability to work; caring responsibilities for people with disabilities; temporary unemployment; older age, longterm unemployment and lack of recent workforce experience making re-employment unlikely; older age and having a partner who is recei ving income suppor t payments; lone parenthood; and parenting responsibilities while having a partner with low income. For a review of the Australian social security system see Whiteford and Angenent.1 A recent social policy focus of the Commonwealth Gover nment has been welf are reform. The term welfare reform can be applied to a broad range of policy changes that emphasise active participation by payment recipients (including increased job search, mutual oblig ations, work-for-the-dole and other requirements to promote participation in work or work-type activities) rather than a passive system of income support.2,3 These changes reflect, in part, concer n that passive welfare promotes a culture of dependency, a loss of personal master y, a decrease in recipient motivation, and the development of attitudes and values inconsistent with work.4,5 Welfare reform is an international phenomenon. Experience and e vidence from the United States (US) and United Kingdom (UK) has been the basis of much policy consideration in Australia6 and, as such, is the focus of this review. Within Australia, the mo vement towards active labour market policy has steadily increased since the 1980s (with the introduction of the activity test), through the extensive labour market programs implemented under Working Nation in the mid 1990s to the present welfare reform process.1,3 In 2000, a reference group provided recommendations to the Gover nment on the direction of welfare reform in Australia.6 The Government has introduced or is considering a range of policy responses.7 There is a growing body inter national research exploring the mental health of welfare recipients. This research has demonstrated that the prevalence of mental disorders and mental health prob lems among welfare recipients is much greater than in the broader community.8-17 Research from the US suggests that the success of welfare refor m has been selective and that those recipients with more substantial bar riers, including mental health problems, have not Results: One-quarter of all income suppor t recipients had exper ienced substantial levels of psychological distress during the previous four w eeks and almost one in three had exper ienced a diagnosable mental disorder during the previous 12 months. Around 45% of unpar tnered women with children in receipt of income support payments were identified with a mental disorder. In contrast, around 10% of people not receiving welfare reported substantial psychological distress and 19% had a diagnosable mental disorder. The prevalence of physical and mental disability was also greater among income support recipients. There was no difference in service use between recipients and nonrecipients. Conclusions: Mental illness is a significant issue among income support recipients. The presence of a mental disorder is a substantial barrier to work and other forms of social participation. Mental health is an issue with relevance beyond the health portfolio, with implications for many domains of social policy and service delivery. Understanding and better assisting income support recipients with mental health problems will be impor tant in welfare reform and in the introduction of a more active welfare system. ( Aust N Z J Public Health 2003; 27: 441-8) Correspondence to: Dr Peter Butterworth, Centre for Mental Health Research, Australian National University, Canberra, ACT 0200. E-mail: Peter.Butterw orth@anu.edu.au Submitted: November 2002 Revision requested: May 2003 Accepted: June 2003 2003 VOL. 27 NO . 4 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH Butterworth Article benefited from the introduction of more work-focused welfare.18-20 Given these findings, applied research in the US has sought to better understand the ways in which mental health problems present a barrier to increased par ticipation and employment and to develop options and approaches to increase the effectiveness of policy and ser vice delivery. 8,12 Poor mental health is associated with factors such as unemployment, pover ty, lower socio-economic status and sole parenthood.21-24 For example, there is convincing evidence, particularly from longitudinal data, that mental health declines as a consequence of unemployment.25 There is clearly overlap between these factors and welfare receipt and, as such, it is expected that the prevalence of mental disorders will be higher among welfare recipients than those not receiving welfare. The purpose of this study is to quantify and explore this potentially impor tant characteristic of Australian income suppor t recipients. The aim is not to examine the causal pathways leading to poorer mental health. If income support recipients are more likely to experience a mental disorder then, regardless of the cause, this needs to be reflected in policy design and service delivery. Australian social policy has reco gnised that low-prevalence mental illnesses, such as psychosis, can significantly limit a person’s capacity to participate in society. The clinical and epidemiological study of low-prevalence disorders conducted as one aspect of the National Survey of Mental Health and Wellbeing26 found that 85% of people with psychotic disorders received a Gover nment pension or payment (primarily disability support pension). However, these types of mental disorders are rare, with Australian estimates of the 12-month prevalence of psychosis less than 1%.26 The issue examined in this paper is the extent to which income support recipients experience common mental disorders (anxiety, depressive and substance use disorders). These common mental disorders affect around 18% of the overall Australian population during a given year. This project represents the first attempt to quantify the extent that Australian income suppor t recipients experience common mental disorders. This study will also examine the level of disability, or impact on functional ability, that common mental disorders have and the e xtent to which income support recipients use mental health services. based on State, part-of-State, age, gender and probability of selection to match the overall Australian population. Measures The primary diagnostic component of the sur vey was based on a computerised version of the Composite Inter national Diagnostic Interview (CIDI) Version 2.1. 27 The data repor ted in this paper use the International Classif ication of Diseases – 10th revision (ICD-10) and examine the presence of an y anxiety disorder, any affective (primarily depressive) disorder, and har mful alcohol or drug use or dependence, as well as a summar y measure of the presence of any mental disorder. The Short Form 12 Health Survey (SF-12)28 provided physical and mental health summary scores that reflect limitations across different domains of daily activities and functioning. After Sanderson and Andrews,29 SF-12 scale scores were categorised into four levels of disability based on the standardised scale mean and standard deviation: scores of 50 or higher were classif ied as no disability; scores of 40 to 49 were classified as mild disability; scores of 30 to 39 as moderate disability; and scores below 30 were classif ied as severe disability. The sur vey included the K10, a scale of psychological distress, to enable the measurement of psychological morbidity (including subclinical distress) within the population.30 The scale produces scores within the range of 10 to 50, with a higher score indicating greater distress. In addition to the scale score, the cur rent analysis categorised those respondents with a substantial level of psychological distress, identifying those with a score of 20 or g reater.31 The NSMHWB also collected data on individuals’ use of mental health services. This included infor mation on admission to a general or psychiatric hospital, admission to a drug or alcohol unit, or consultation with general practitioners, psychiatrists, psychologists, social workers, counsellors or other specialists or mental health professionals for mental health reasons. Finally, this analysis assessed a range of socio-demographic information that was collected through the sur vey, including age, gender, marital status, labour force status, main source of income, household structure, housing tenure and educational attainment. Analysis This analysis focused on the subset of survey respondents of workforce age, that is, males aged under 65 and females aged under 60. It estimated the population of income support recipients, identifying those who reported that Government pensions or payments were their main source of income. The analysis also examined different income support client segments. Five client groups were derived based on gender, partner status, full-time study having had children, the presence of children in the house, hold and labour force status. The client segments, which were devised to cor respond to the main income support payments, were: unemployed; students; par tnered women with children; unpartnered women with children; and not in the labour force (NILF; payments that do not require active job search such as disability support pension). The estimates of parenting payment VOL. Methods Sample This analysis used the conf identialised unit record file of the National Survey of Mental Health and Wellbeing (NSMHWB). The survey was conducted by the Australian Bureau of Statistics in 1997. The NSMHWB used a representative sample of persons living in private dwellings from all States and Ter ritories. The survey w as designed to provide data on the prevalence of major mental disorders and the associated levels of disability and health service usage in Australia. About 13,600 households were approached, with one person aged 18 or over from each house randomly selected for inter view. Overall, 10,641 individuals completed the survey (a 78% response rate). The sample was weighted AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH 27 NO. 4 Methods and Concepts Mental disorders among income support recipients recipients focused exclusively on women, even though the payments are available for men with child care responsibilities, as administrative data shows that 97% of parenting payment (partnered) recipients and 93% of parenting payment (single) recipients are women.32 Another pub lication provides detailed information on the characteristics of the client se gments and of analysis under taken to validate these estimates ag ainst administrative and other data sources.33 The preliminary analysis examined the association between sociodemographic characteristics and income suppor t status using chisquare tests. Data on the differences between the g roups in their experience of psychological distress (as measured by the K10 scale) was assessed using negative binomial regression models (due to severe positive skew). For all of the categorical outcome measures, a consistent set of analyses was used. The first contrasted income support recipients with non-recipients. The second contrasted each income support client segment with the non-recipients. Then, these simple analyses were replicated controlling for potential confounders, including age, gender, partner status, housing tenure, presence of children in the home and education. A series of logistic regression models examined the association between income support status and substantial psychological distress and the presence of CIDI diagnosed depression, anxiety, and substance-use disorders, as well presence of any CIDI disorder. A similar approach was used to examine the predictors of mental and physical disability. Finally, logistic regression models examined use of formal mental health services for those individuals with a CIDI-diagnosed mental disorder or substantial psychological distress. For this analysis, a third model adjusted for physical disability was also included. Statistical analyses were conducted using SPSS-11 and STATA. For the means and chi-squared analyses, the weights used represented the reciprocal of the probability of selection and were rescaled by dividing by the mean weight of the total sample (n/N). Thus, the measure of variability represents that expected from the total sample size, not from the total population. For the logistic regression and negative binomial models, the jackknife replicate weights were used to derive standard errors and conf idence inter vals. Results Demographic characteristics Table 1 presents data on the demographic characteristics of those not receiving income support payments and the f ive income support client segments. Chi-square analyses of the association between g roup membership and each of the characteristics were all Table 1: Characteristics of the income suppor t recipient and non-recipient client segments. Not receiving income support Sample (n) Unweighted Gender (%) Male Female Age (%) 18-29 30-39 40-49 50+ Marital status (%) Marr ied/de facto Divorced/separated Widowed Never married Housing tenure (%) Own Purchasing Renting Other Country of birth (%) Australia Education (%) Not completed school Completed school Trade Tertiar y studies 26.7 18.2 23.7 31.2 51.5 14.0 22.0 12.5 16.4 50.3 11.9 21.4 50.0 18.0 19.7 12.3 59.6 13.5 19.7 7.3 52.1 13.8 25.2 8.9 75.1 74.3 75.3 75.6 81.5 70.6 28.7 26.2 25.5 19.6 68.9 6.7 0.5 23.9 23.5 40.1 24.6 11.8 46.4 19.8 15.4 18.5 39.0 13.0 1.2 46.8 15.6 15.6 48.4 20.3 81.0 10.8 7.6 0.6 16.9 7.5 0.6 75.0 3.1 6.3 47.5 43.1 28.4 51.0 18.9 1.7 100 – – – 16.0 51.0 30.1 2.9 30.3 39.9 22.5 7.3 – 64.6 3.4 32.0 7.9 10.7 73.0 8.4 11.3 10.3 15.8 62.6 62.2 14.6 4.0 19.2 41.9 16.0 33.0 9.1 6,771 54.2 45.8 Unemployed Income support client segments Student Par tnered Unpartnered woman with child woman with child 137 46.5 53.5 368 – 100 310 – 100 Not in labour force 2003 VOL. 27 NO . 4 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH Butterworth Article significant at p<0.001. All income support recipient g roups, apart from students, reported lower levels of education than nonrecipients. Those in the unemployed and student g roups were generally younger than those in the other groups. Their younger age is likely to be an explanation for the greater propor tion of never mar ried clients, and the greater pre valence of rental or ‘other’ housing arrangements (likely living with parents or shared housing). In contrast, those in the NILF group were older than the non-recipients and the other client groups. This may account for their greater le vel of home ownership. The unpar tnered women with children were more likely to reside in rental accommodation than any other group. Psychological distress and mental disorders Income support recipients had signif icantly poorer mental health than people not receiving income suppor t payments (see Table 2). The mean K10 measure of current distress was g reater for income support recipients than for those not receiving income support payments (Incidence Rate Ratio (IRR, ec)=1.19; 95% confidence interval (CI) 1.16-1.22). The average K10 scores were greater for all groups of income suppor t recipients (IRRs from 1.10 for partnered women with children to 1.27 for unpartnered women with children). The second column of Table 2 shows the percentage of respondents within each group with a psychological distress score of 20 or g reater. Overall, a significantly g reater proportion of income support recipients experienced substantial psychological distress (24.2%) than non-recipients (10.3%; odds ratio (OR)=2.77, 95% CI 2.38-3.24). Simple logistic regression (see Table 3) showed that the prevalence of substantial psychological distress was greater among all income suppor t client groups than non-recipients though, because of smaller sample size and wider CI, the difference for the student group was not significant. The lack of significance for the student group w as repeated in most analyses. The other income support recipient g roups continued to demonstrate significantly greater psychological distress than nonrecipients after adjustment for potentially confounding variables. Those receiving income suppor t payments were also more likely to have experienced a CIDI-diagnosed af fective, anxiety or substance-use disorder in the previous 12 months than those not receiving income support payments. The ORs were 1.99 (95% CI 1.66-2.38), 2.33 (95% CI 1.92-2.85) and 1.60 (95% CI 1.34-1.92), respectively. Further, those receiving income support payments had higher levels of mental disorders overall than the no income support group (OR=1.92, 95% CI 1.64-2.26). Around 19% of non-income support recipients of workforce age experienced a mental disorder, compared with more than 30% of income support recipients. The data in Table 2 demonstrate a pattern that differs as a function of client group and type of disorder. All income support client groups demonstrated greater prevalence of depressive disorders than non-recipients, although the increased prevalence of the partnered women with children and student groups was not signif icantly different. Anxiety disorders were signif icantly more prevalent in all income support recipient groups, and (again) markedly g reater in the unpartnered mother group. The le vel of substance-use disorders was most pronounced in the unemployed group, with students and unpartnered women with children also showing considerably g reater levels of substance-use disorders than non-recipients. The partnered women with children group experienced only half the level of substanceuse disorders as the comparison group. However, after adjustment, only the unemployed and the NILF groups demonstrated substance-use disorders at a level signif icantly different to nonrecipients. Levels of disability Figure 1 presents SF-12 data on disability due to mental and physical causes. For almost all client groups, there was a gradient Table 2: Mental health characteristics of income support recipients (overall and each client segment) and nonrecipients, with 95% confidence intervals. Kessler K10 Mean CI %>20 Affective disorders (% & CI) 7.1 6.51-7.70 13.2 11.52-14.84 12.7 9.47-15.95 10.7 5.83-15.52 9.6 6.51-12.73 20.3 14.38-26.31 14.3 11.22-17.34 CIDI diagnoses (ICD-10) Anxiety Substance disorders use disorders (% & CI) (% & CI) 8.7 8.04-9.35 18.2 16.32-20.11 16.6 13.01-20.25 17.2 11.26-23.11 14.7 10.92-18.38 30.4 23.58-37.21 18.0 14.63-21.35 8.3 7.65-8.93 12.6 11.01-14.27 21.5 17.53-25.53 14.9 9.34-20.53 4.2 2.11-6.35 13.6 8.55-18.72 10.5 7.84-13.21 Total mental disorder s (% & CI) 18.7 17.77-19.58 30.6 28.38-32.90 33.7 29.14-38.34 30.2 23.01-37.42 20.9 16.62-25.20 45.2 37.87-52.62 29.8 25.84-33.84 No income suppor t Receiving income support – total Unemployed Studying Partnered women with children 13.9 13.80-14.02 16.5 16.18-16.85 15.8 15.22-16.41 16.4 15.57-17.27 15.30 14.72-15.89 10.3 9.61-11.02 24.2 22.11-26.31 21.5 17.53-25.53 24.6 17.82-31.34 18.6 14.52-22.73 30.4 23.60-37.24 27.9 24.00-31.84 Unpartnered women with children 17.63 16.58-18.69 Not in labour force/disability 17.55 16.85-18.26 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH VOL. 27 NO. 4 Methods and Concepts Mental disorders among income support recipients of disability, with mild disability more common than moderate which in turn was more common than severe disability. Only the NILF group differed from this pattern, reporting greater prevalence of severe and moderate physical disabilities. Physical disabilities were more common among income support recipients than non-recipients (OR= 2.24; 95% CI 1.81-2.79). Compared with those not in receipt of income support, physical disability was more prevalent among the partnered women with children (OR=1.50, 95% CI 1.22- 1.85), unpartnered women with children (OR=1.95, 95% CI 1.44-2.65) and NILF g roup (OR=6.25, 95% CI 4.66-8.40). Disability because of poor mental health was also more prevalent for income support recipients than non-recipients (OR=2.17, 95% CI 1.91-2.46). All client segments showed higher levels of mental disability than the non-recipients (unemployed: OR=1.94, 95% CI 1.58-2.38; students: OR=1.93, 95% CI 0.97-3.81; partnered women with children: OR=1.94, 95% CI 1.50-2.50; unpartnered women with children: OR=3.01, 95% CI 2.36-3.85; NILF: OR=2.36, 95% CI 1.82-3.06). After adjustment, the partnered women with children, unpartnered women with children and the NILF groups continued to demonstrate significantly higher levels of disability (both physical and mental) than non-recipients, while the unemployed group had a higher level of mental disability. Use of services Table 4 sho ws the extent to which people with a CIDIdiagnosed mental disorder or a K10 score of 20 or greater used mental health services. The data indicate that around 32% of those with a mental disorder and not receiving income support payments used mental health services compared with 39% of those Table 3: Simple and adjusted odds ratios and 95% confidence intervals for the associations between income support status and measures of mental disorders and psychological distress. Simple OR 95% CI Depressive disorders No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Anxiety disorders No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Substance use disorders No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Total – any disorder No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force Adjusted a OR 95% CI 1.31-2.76 0.60-4.08 0.90-2.16 2.45-4.55 1.65-2.87 1.12-2.44 0.48-3.42 0.69-1.60 0.99-2.05 1.54-2.84 Figure 1: SF-12 data on disability due to mental and physical causes (% of recipients in each category with disability). SF-12mental disability Mild No income support Income support Moderate 27.3 44.9 Severe 1.29-3.40 1.35-3.52 1.31-2.48 2.99-7.03 1.75-3.02 1.10-3.25 1.06-3.24 0.98-2.06 1.27-3.74 1.70-2.93 2.05-4.26 0.89-4.24 0.31-0.77 1.13-2.69 0.91-1.87 1.31-3.01 0.44-3.07 0.58-1.63 0.93-2.57 1.01-2.34 unemployed students partnered women with chd unpartnered women with chd not in labourforce 0 20 40 1.68-2.93 0.92-3.86 0.87-1.52 2.68-4.84 1.35-2.54 1.31-2.34 0.61-2.83 0.80-1.52 1.28-2.96 1.51-2.65 SF-12Physical disab ility Mild No income support Income support Moderate 29.7 48.7 Severe unemployed students partnered women with chd unpartnered women with chd not in labour force 0 20 40 Psychological distress > 20 No income suppor t (ref) Unemployed 2.39 Students 2.83 Partnered women 1.99 with children Unpartnered women 3.80 with children Not in labour force 3.37 1.48-3.83 0.92-8.73 1.51-2.62 2.86-5.06 2.61-4.35 1.23-3.21 0.87-6.00 1.26-2.60 1.14-3.37 2.34-4.07 Note: (a) Adjusted for age, housing tenure, partner status , presence of children at home and educational attainment. 2003 VOL. 27 NO . 4 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH Butterworth Article with a mental disorder who did receive income support payments (OR=1.37, 95% CI 1.01-1.83). Consideration of the separate client segments showed that only the unpartnered women with children and the NILF groups used mental health services more than non-recipients. However, the unpartnered women with children did not differ from non-recipients after adjusting for sociodemographic variables and the NILF group did not differ after adjusting for socio-demographic variables and level of physical disability (SF-12 physical score). Discussion This study estimated the prevalence of mental disorders and psychological distress among Australian income support recipients. The analysis showed that one-quarter of all income support recipients had experienced substantial levels of psychological distress in the previous four weeks and that almost one in three had experienced a diagnosable mental disorder during the previous 12 months. Mental disorders (primarily depression) are the third-leading cause of overall disease b urden in Australia.34 Given the relatively low levels of mor tality associated with mental illness, this disease burden mainly represents functional limitations and restricted participation in activities, such as work. As such, it was expected that there would be a strong association between receipt of income support and mental illness. This study is important as it presents quantitative national data on the topic. This study also examined the circumstances of different subgroups within the population of income support recipients. It differentiated clients on the basis of characteristics that cor respond to the payment str ucture. While most client segments demonstrated elevated levels of all disorders, the anal ysis showed that different groups experienced different types and different rates of mental disorders. This knowledge is important to ensure an appropriate and targeted policy response. Those classif ied as unemployed were far more likely to experience a disorder associated with harmful substance use or dependence than other segments and non-recipients. The NILF group demonstrated consistently higher levels of all disorders while showing markedly greater psychological distress. This group reported higher levels of physical disability (over 70%). Their psychological distress may have been associated with these physical disorders. Unpartnered women with children demonstrated levels of depression and anxiety disorders over three times that of non-recipients, with around 45% estimated to have some type of mental disorder in the previous 12 months. While alarming, this result is consistent with international evidence of the level of mental illness among sole parents receiving welfare.9,10,16 Income support recipients in most client segments experienced higher levels of disability associated with poor mental health than non-recipients. That is, their ability to undertake daily activities including working, looking for a job or caring for children was more likely to be compromised by mental illness. This is consistent with the data on burden of disease34 and research showing mental illness presents a significant bar rier to economic participation.11,35,36 This research shows that mental health is an issue with implications and relevance beyond health policy. Recently there has been greater recognition in Australia of the relevance of client mental health to the achievement of social policy goals and objectives in the areas of employment and income support.37,38 Mental illness does not only limit the well-being and par ticipation of individuals, but maternal depression and mater nal mental illness have negative consequences for children.39 The current findings, therefore, have implications for many domains of social policy and service delivery including employment, income support, family services, targeting early inter vention and prevention strategies and disability services. These results need not be viewed pessimistically. Recent advances in prevention, diagnosis and treatment (including improved efficacy and cost effectiveness) of mental health problems means that most people with mental disorders can be helped.40 Having identified the magnitude of mental health barriers among income support recipients, Commonwealth social policy agencies will be better placed to understand and address Table 4: Use (%) of mental health services of those with mental disorders or significant psychological distress by income support status with simple and adjusted odds ratios and 95% confidence inter vals. n (with mental health problems) No income suppor t (ref) Unemployed Students Partnered women with children Unpartnered women with children Not in labour force 1,629 164 63 101 94 204 Access mental health services % Simple Adjusted Socio-demographica Adjusted Socio-demographica and physical disability OR OR 95% CI 0.60-1.82 0.54-3.65 0.61-1.77 1.10-2.45 1.11-2.70 OR 95% CI 0.65-2.15 0.60-4.62 0.46-1.67 0.52-1.73 1.12-3.39 95% CI 0.66-2.08 0.59-4.78 0.45-1.66 0.52-1.59 0.92-3.26 Notes: (a) Adjusted for age, housing tenure, partner status, presence of children at home and educational attainment. AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH VOL. 27 NO. 4 Methods and Concepts Mental disorders among income support recipients the consequences of these disorders. This could increase the positive outcomes achieved by participants. The types of policy responses could include: the introduction of screening and assessment processes that target mental health; improving the mental health literacy41 of polic ymakers and service delivery staff (the knowledge and awareness of mental health and mental disorders); the provision of specialist programs for those with signif icant mental health problems (such as the recently introduced personal support program); the inclusion of mental health practices within employment programs, such as cognitive behaviour therapy techniques;42-45 and promoting linkages with existing mental health services. The NSMHWB data show that less than one-third of those with mental disorders seek assistance.46 This study found that income support recipients were somewhat more likely to use ser vices. This increased service use was accounted for by demographic characteristics and level of physical disability. This was consistent with Parslow and Jorm,47 who found that three sociodemographic variables (being female, being separated and ha ving a higher education) were associated with increased use of mental health services. These features account for the increased use of mental health services by sole parents on income suppor t (see also Cairney and Wade17). The NILF group had greater physical disabilities and, therefore, may have had g reater contact with medical professionals. Their increased use of mental health ser vices may have been a consequence of their general greater use of services. It is important to recognise that this Australian data does not show lesser use of mental health services by those on income support, as is found in studies of welfare recipients in the US.10 The study did not examine causality and, thus, cannot disentangle the direction of the relationship between welfare receipt and mental illness. While it is likely that the relationship is bidirectional, it is also likely that both factors reflect and interact with other underlying characteristics (e.g. early abuse/trauma, lack of education and work skills, unemployment, levels of social and community support, divorce/separation, poverty, coping skills and resilience). The differing pattern of mental health problems across the client segments shows there is not a simple association between welfare receipt and poor mental health outcomes. The categorical nature of the income support system means that recipients of different payments have v ery different characteristics and are in different circumstances. The striking difference in the mental health of partnered and unpartnered women with children illustrates this diversity. Future research will need to consider different client groups separately in order to better understand the specific circumstances and risk factors that are associated with elevated mental distress among different groups of income support recipients. The main limitation of this study is that it estimated the income support client se gments using demographic characteristics. This is, however, unique research in the Australian context. No data source contains both the richness of mental health information and detailed data on income support receipt. Further, the estimates of the client groups have been shown to match the 2003 VOL. 27 NO . 4 administrative data.33 Another limitation is that the various measures examined in this analysis reference different time periods (e.g. psychological distress and disability refer to the last four weeks, mental disorders and service use refer to the last 12 months, while income support receipt is based on cur rent circumstances). Thus, the cur rent analysis may underestimate the association between income support receipt and mental health problems. In conclusion, this study has shown that mental illness is a significant issue among income suppor t recipients. Mental illness is associated with disability/impairment in a substantial number of income support recipients across all types of payments, not just disability payments. This is likely to present a substantial barrier to work and other for ms of social and economic participation. Mental health is, therefore, an impor tant issue in the context of welfare reform and the introduction of a more active welfare system aiming to increase participation. Traditionally, social policy researchers have focused on str uctural (financial incentives, child care, transport), human capital (education, employment experience, job skills) or demographic characteristics (age, marital status, housing tenure) when analysing labour market circumstances and income support receipt. The findings from this study indicate that an approach that does not consider mental illness overlooks an impor tant characteristic associated with receipt of income support. Fur ther, contrary to general perceptions, mental disorders are readily treated and prevented40 and may be more easy and inexpensive to address than many of these human capital characteristics. Acknowledgements I wish to thank Tony Jor m and Kaarin Anstey for comments on an earlier draft of this manuscript and Ruth Parslow for statistical advice.

Journal

Australian and New Zealand Journal of Public HealthWiley

Published: Aug 1, 2003

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