Abstract
Given the high prevalence of anxiety and depressive disorders in the community, interest in predisposing factors to these problems has grown [1, 2]. Unemployment has been identified as one of the most important factors for poor health status, including mental health [3–8]. However, the causal links are complex [9]. Few longitudinal studies have investigated the impact of unemployment on mental health.
Higher rates of health service use including doctor visits have been documented among unemployed people [2, 10, 11]. Previous work, undertaken by our group, indicated that general practitioners (GPs) who reported treating patients for anxiety and/or affective disorders were significantly more likely to prescribe medications for unemployed compared to employed patients, but were no more likely to refer unemployed patients to other health services [12]. These results imply that GPs’ treatment of unemployed patients with mental health disorders may be either biased towards over-prescription of medication or under-referral to specialists.
The1997 National Survey of Mental Health and Wellbeing of Adults (SMHWB) was the first national survey of the prevalence of common mental disorders in the Australian population. Using data from the SMHWB survey, the aim of this study was to compare the prevalence of anxiety and/or affective disorders between employed and unemployed patients and to examine information on treatment received between the two groups.
Method
The 1997 National Survey of Mental Health and Wellbeing of Adults [13] surveyed Australian adults’ mental health between May and August 1997 under the authority of the Census and Statistics Act 1905. The survey provided information about the prevalence of selected mental disorders, the level of disability associated with these disorders, health services used and help needed as a consequence of a mental health problem for Australians aged 18 years or more.
Stratified multistage probability sampling techniques were used to provide a representative sample of 13 600 private dwellings from all states and territories. One person aged 18 years or over was randomly selected from each dwelling. Interviews were completed with 10 641 people reflecting a response rate of 78%.
Mental disorders were assessed by a modified version of the Composite International Diagnostic Interview (CIDI) [14]. This comprehensive interviewing tool is designed to assess current and lifetime prevalence of mental disorders through the measurement of symptoms and their impact on day-to-day activities. This instrument enabled mental disorders to be defined in terms of ICD-10 and DSM-IV diagnostic criteria.
Information about affective disorders (depression, dysthymia, mania, hypomania and bipolar affective disorder) and anxiety disorders (panic disorder, agoraphobia, social phobia, generalized anxiety disorder, obsessive–compulsive disorder and posttraumatic stress disorder) was assessed for the purposes of this study [15]. Results for anxiety, affective and anxiety and/or affective disorders are presented in this analysis.
Demographic information used in the analysis included age (grouped), sex, country of birth (English/non-English speaking country of birth) and language spoken at home (English/non-English speaking). Employment status was classified according to Australian Bureau of Statistics criteria as ‘employed’ (full or part-time), ‘not in the labour force’ and ‘unemployed’ (defined as seeking work during the previous four weeks) [15]. Physical illness and substance abuse were examined as potential confounders of the relationship between anxiety/affective disorders and unemployment and were investigated in the analysis. Study participants were regarded as positive to physical illness if they reported one or more of 12 listed conditions: asthma, bronchitis, anaemia, high blood pressure, heart trouble, arthritis, kidney disease, diabetes, cancer, stomach/duodenal ulcer, liver/gallbladder trouble, or hernia/ rupture, and to substance abuse if they reported dependence or harmful use of alcohol, opioid products, cannabis, sedatives, or amphetamine. Information on consultation with health professionals was sought, and on treatment received, by either medication or psychological help. These were classified as GP services and as other relevant health professionals (including psychiatrist, psychologist, drug or other counsellor, mental health team, and social worker). Information on the type of treatment received was based on subject self-report.
Statistical analysis
Analyses were conducted using SAS V6.12 (SAS Institute, Cary NC, USA). The data were summarized using cross-tabulations and differences between groups were tested using the χ 2 statistic. Logistic regression models were employed to investigate the association of mental ill health (anxiety, affective or anxiety and/or affective disorders) and socioeconomic status (employment status) controlling for potential confounders: age, gender, non-English speaking country of birth, physical illness and substance abuse.
A poststratification Jackknife method of replicated weighting was adopted for the SMHWB complex sample design. The full sample regression estimates were weighted by the full post stratification weight. The variance for the sample estimates was calculated from the ‘Jackknife’ method from 30 regression estimates weighted using 30 replicate weights. The Jackknife variance estimate is calculated from the following formula: where g is the number of replicate groups, 30 in this case θ is the estimate of the variable of interest from the full sample θ (k) is the estimate of the variable of interest after the k th replicate group has been dropped
Results
The demographic characteristics of survey participants are summarized in Table 1. The proportion of the sample that was unemployed was 4.2% (n = 444); 32.5% (n = 3457) were not in the workforce and the remaining 63.3% (n = 6740) worked part- or full-time. Comparing the groups, participants who were ‘not in the workforce’ were more likely to be female; there were only small, but statistically significant, differences in ethnicity and language; but unemployed participants were twice as likely as employed participants to be aged less than 25. Physical illness and substance abuse were significantly more likely to be reported by unemployed participants.
Prevalence (%) of population characteristics stratified by employment status
The overall prevalence of anxiety disorders was 5.68% (n = 604), of affective disorders was 6.73% (n = 716) and anxiety and/or affective disorders was 9.79% (n = 1042). The prevalence of these disorders was significantly higher for females and for young adults but did not vary by ethnicity or language spoken at home (Table 2). Unemployed participants had significantly higher rates of anxiety and/or affective disorders compared to employed participants (Table 2). When adjusted for population characteristics unemployed participants were three times (OR = 3.13, 95% CI = 2.82–3.47) as likely to be identified as having anxiety disorders, twice (OR = 2.13. 95% CI = 1.97–2.30) as likely to have affective disorders and were (OR = 2.52, 95% CI = 2.37–2.69) more likely to have anxiety and/or affective disorders (Table 3). Participants who were ‘not in the workforce’ were also at increased risk of these disorders although the difference was less marked. While controlling for the impact of physical illness and substance abuse reduced the size of the estimates, unemployed participants were twice as likely to report anxiety and/or affective disorders.
Prevalence of anxiety and affective mental illness stratified by population characteristics
Odds ratio for anxiety and/or affective disorders, stratified by employment status and adjusted for population characteristics
Use of health services
Unemployed participants with anxiety and/or affective disorders (71.2%; OR = 0.33 (95% CI = 0.29–0.38)) were significantly less likely to report seeing a GP during the previous 12 months than were participants who worked full- or part-time (88.1%), while those with anxiety and/or affective disorders who were not in the workforce (90.9%, OR = 1.35 (95% CI = 1.19–1.54)) were significantly more likely to report seeing a GP (Table 4). However, of those participants who attended with symptoms, the frequency of consultation with GPs did not differ significantly according to employment status. Unemployed people with anxiety and/or affective disorders were no less likely to report seeing other health professionals for counselling than those employed with similar symptoms (employed: 32.9%, not in the workforce: 33.1%, unemployed: 31.8%). Importantly, 21.5% of unemployed participants with these disorders had not sought any health care compared with 8.6% of employed participants and 7.8% who were not in the workforce.
Odds ratio for seeing a GP (all) during the last 12 months by participants reporting anxiety and/or affective disorders adjusted for population characteristics
Next, information about the type of help that participants received for either anxiety and/or affective disorders was examined. Unemployed participants with either disorder who had seen a GP (35.0%) were no more likely than employed participants (36.8%) to report receiving medication but were only slightly more likely to receive psychological help (44.4% and 39.4%, respectively, p < 0.01). Participants who were not in the workforce were more likely to receive medication (48.9% compared with 36.8%, p < 0.01) but not psychological help (38.0% compared with 39.4%, NS).
Discussion
Analysis of data from the NMHWB survey enabled us to investigate how GPs manage symptoms of anxiety and/or affective disorders among unemployed adults drawn from the community rather than from general practice patient populations and compare this with information for adults who were employed or not in the workforce. We observed an increase in the prevalence of anxiety and/or affective disorders among unemployed participants that remained significant after controlling for potential confounding factors, notably physical health problems and substance abuse. These results confirm the result of our previous research findings in regard to the prevalence of these disorders among unemployed people but not in terms of reported management [12].
While the results show a trend in the prevalence of these disorders by employment status that has been previously reported, this new information suggests that unemployed adults with anxiety and/or affective disorders were significantly less likely to have sought medical help for these problems. However, if they did seek help they were just as likely as employed adults to receive comparable medical care. This result contrasted with our previous study based on a GP report, that suggested GPs were more likely to prescribe medication but were no more likely to refer patients with anxiety and/or affective disorders for specialist care, suggesting a different approach to care for unemployed patients [12]. This difference may be explained by the selective nature of the previous study (general practice patients) and the fact that the disorders and interventions were recorded by the GP as they saw the patient. This study relied on patient's recall of the reason for encounter and treatment received for anxiety and/or affective disorders. They may for example have presented with comorbidity or psychosomatic symptoms where the GP made a diagnosis of anxiety and/or affective disorder but the patient did not identify this [16].
A more fundamental explanation challenges the assumptions of the representativeness of the SMHWB survey and identifies differences in the demographic characteristics of each data set from those of the communities at that time. The SMHWB sample had an unemployment rate of 6.2% (444/7184; excluding those who were not in the labour force), which was less than the unemployment rate at that time of 8.7% (calculated as the proportion of those who were unemployed and looking for work expressed as a per cent of this group plus those who were employed either full or part time; those who are not in the workforce are excluded from this estimate) [17] while the proportion of young unemployed and people from a non-English speaking background were over-represented. Our previous work over-represented immigrant adults but was more similar to Australian Bureau of Stastics data on other estimates [12].
The strength of this study was that it used an internationally recognized diagnostic tool (the CIDI) to identify cases according to standard classifications in a community-based sample with a known probability of selection. The instrument was adapted for the purposes of data collection in this survey. Studies have shown that self-reported data from patients with mental disorders is generally reliable [18].
The results suggest a need for strategies to encourage unemployed people to recognize their symptoms and seek health service assistance. In particular, strategies should be tailored to the needs of young adults, who may have less well-established coping strategies and for whom early detection and intervention to manage risks for these disorders, including psychological education, are indicated. The second National Mental Health Strategy's emphasis on targeted population approaches to enhance mental health literacy [19], and its focus on the young and promotion of help-seeking, including primary care, appears appropriate. The extent to which this particular population, at risk of developing mental illness, use GP services and can be encouraged to do so for psychological problems remains a question.
In conclusion, adults who were unemployed had a higher prevalence of symptoms of anxiety and/or affective disorder, were less likely to seek medical treatment, but received similar treatment in general practice when they did seek help. The difference from previous research about inequalities in treatment by GPs warrants further investigation.