Health Sociology and Economics, Catholic University of Louvain, Brussels, Belgium and Department of Public Health, Erasmus Medical Centre, Rotterdam, The Netherlands
Department of Public Health, Erasmus Medical Centre, Rotterdam, The Netherlands
Department of Public Health and Microbiology, Turin, Italy
Department of Public Health, Erasmus Medical Centre, Rotterdam, The Netherlands
EU Working Group on Socio-Economic Inequalities in Health
Correspondence: Vincent Lorant, Health Sociology and Economics, Catholic University of Louvain, Clos chapelle aux champs 30.41, 1200 Bruxelles, Belgium. Tel: +32 2 764 3263; fax: +32 2 764 3031; e-mail: lorant{at}sesa.ucl.ac.be
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ABSTRACT |
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Aims To present a first European overview of socio-economic inequalities in suicide mortality among men and women.
Method We used a prospective follow-up of censuses matched with vital statistics in ten European populations. Directly standardised rates of suicide were computed for each country.
Results In men, a low level of educational attainment was a risk factor for suicide in eight out of ten countries. Suicide inequalities were smaller and less consistent in women. In most countries, the greater the socio-economic disadvantage, the higher is the risk of suicide. The population of Turin evidenced no socio-economic inequalities.
Conclusions Socio-economic inequalities in suicide are a generalised phenomenon in western Europe, but the pattern and magnitude of these inequalities vary between countries. These inequalities call for improved access to psychiatric care for lower socio-economic groups.
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INTRODUCTION |
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The aim of this study is to present a European overview of socio-economic inequalities in suicide mortality among men and women. Using a common method and data source, our purposes were first, to assess whether socio-economic inequalities in suicide are a generalised phenomenon in Europe, and second, to compare the extent of educational and housing socio-economic inequalities in suicide in different European populations, among men and women.
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METHOD |
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Variables
The codes used to identify death by suicide in the ICD-8, ICD-9 or ICD-10
classifications (World Health Organization,
1974,
1978,
1992) were E950-E959 (ICD-8
and ICD-9) and X60-X84 (ICD-10).
Educational status and housing tenure were registered. The level of education was first classified according to the national categories of education in each country. The number of educational categories ranged from four (in most countries) to 13 in Belgium. On the basis of the description given by each representative of the data collected in each country, the national categories were converted into International Standard Classification of Education (ISCED) categories (UNESCO, 1997). As several countries provided no information on the group with primary education only (ISCED 1), the ISCED levels 1 and 2 (lower secondary school) were grouped together in the analysis. Education data were not available for Danish people older than 70 years. Education is mostly achieved by early adulthood and is not necessarily consistent with later economic achievement and wealth accumulation over the life cycle. Housing tenure was included to cover such wealth effects and was grouped in two categories: owner and tenant. This variable, however, was available for only six populations, namely those of Norway, Finland, Denmark, England and Wales, Belgium and Turin.
Analysis
Age-standardised mortality rates by educational level and housing tenure
were computed for each gender and country. Direct standardisation was applied,
using the population of the European Union and Norway of 1995. On the basis of
these standardised rates, we computed rate ratios comparing those with a low
educational level (ISCED 1 and 2) with those more highly educated (ISCED 3 and
above), and tenants with house owners. The formula for the standard error of a
relative risk was used to compute standard error
(Dawson & Trapp, 2001).
Because differences in suicide inequalities between countries could arise from
methodological or sample variations, we tested the homogeneity of inequalities
using Cochran's Q statistic, which has a w2 distribution
with a degree of freedom equal to the number of studies minus 1
(Petitti, 1994).
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RESULTS |
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The pattern of educational inequalities was very different in women. A lower educational attainment level was shown to be a significant, positive but weak risk factor for suicide only in Belgium and Finland. A lower educational level proved to be a protective risk factor for women from Norway, Denmark and Switzerland.
In four out of five countries, the risk of suicide was greater in tenants than in house owners (Table 3), for both men and women. Once again, Turin evidenced small and non-significant inequalities in suicide. The overall risk associated with ownership was slightly greater than the risk associated with education, particularly for women.
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The homogeneity of educational and housing risk factors of suicide was rejected for both men and women (for men, Cochran Q>73, P>0.001; for women, Cochran Q>38, P<0.001). A rejection of the homogeneity assumption implies that there are country-specific effects in inequalities, which could not be explained by random variation. Inequalities in suicide according to housing tenure were slightly less heterogeneous (standard deviation of relative risk 0.38) than inequalities according to education (standard deviation of RR=0.54).
The risk of suicide for men in all the populations, except for Danish men, was shown to decrease unimodally with increasing socio-economic advantage (Fig. 1). The intermediate socio-economic groups (high level of education and tenant; low level of education and house owner) were at less risk of suicide than the lowest group. These intermediate groups were, however, at more risk than the upper group. In all countries, house owners with a low educational level had a smaller risk than highly educated tenants. For Finland, England/Wales and Belgium, the risk of suicide decreased linearly with socio-economic status, whereas in Denmark and Norway a less regular trend was observed.
In women, the risk of suicide did not decrease unimodally with increasing socio-economic status (Fig. 2). The highest risk was found in the intermediate group of women with higher levels of educational attainment who were tenants. As among men, a lower educational status and house ownership led to a smaller risk than a higher educational level and being a tenant. In most countries, the lowest risk was found in the low-educated house owners. In Turin, socio-economic status was associated only slightly with suicide risk.
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DISCUSSION |
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Limitations
The study has a few limitations which could affect the reliability and
comparability of estimates of suicide inequalities. Misclassification could
affect the suicide registration. Indeed, there is some evidence that official
suicide rates are underestimated (Joseph
et al, 2003) because of suicide misclassification. Such
misclassification could affect our estimates if countries apply different
coding procedures (Jougla et al,
1998) and, hence, have different reliability
(Rockett & Thomas, 1999).
We assessed such risk by combining suicide and injuries of undetermined intent
(E980-E989, Y10-Y23). The results were relatively robust. When injuries and
suicide were added up, the risk of suicide among men of low education compared
with men of high education increased from 1.4 to 1.48. This change was more
dramatic for the male populations in England and Wales (from 2.67 to 4.10) and
in Belgium (from 1.61 to 2.2). The country rankings in educational
inequalities among men changed very little, except for Barcelona, which was
pushed from eighth position into fourth.
A second group of limitations arises from the differences in the educational system in the countries compared. We devoted considerable effort to obtaining internationally comparable educational categories using the ISCED system. However, the ISCED distribution is not homogeneous and some countries have a low percentage of individuals in the lower secondary educational attainment category (such as Switzerland) or in the categories with upper secondary education and above (England/ Wales and Turin). Sensitivity analysis was performed to assess the impact of the heterogeneity in education distribution. The cross-country analysis was carried out by computing a relative index of inequality on the relative rank of educational status (Mackenbach & Kunst, 1997), which takes into account each educational level individually, with a distinction of about four educational levels in most countries. Inequalities increased and became significant in all male populations but that of Turin. On average, the ranking of countries changed by 1 point. Barcelona became a high-inequality population. The highest inequality level was still seen in Madrid. Turin and Denmark had the smallest inequalities.
The inequalities in England and Wales were higher than those found in a study based on the 1981 population census (Lewis & Sloggett, 1998). They are also higher than the figures reported in a psychiatric epidemiological survey (Lewis et al, 1998). Discrepancies in source (we used the 1991 population census), in statistical power (we counted 130 suicides for England and Wales v. 581 in the study of Lewis & Sloggett) and follow-up (5 years v. 10 years) may explain such differences in the observed size of inequalities.
Previous studies and interpretation
On three aspects our results are consistent with a previous worldwide
meta-analysis of socio-economic risk factors for common mental disorders, a
main risk factor for suicide (Lorant
et al, 2003). First, in that study low socio-economic
status was found to be a significant and positive risk factor of depression in
35 out of 56 studies. Second, as in our study, the association with
socio-economic status was unimodal and stronger for economic variable than for
educational status. Finally, it was also geographically heterogeneous: greater
in the USA than in Europe.
The greater inequality between educational groups found in men as compared with women is consistent with previous individual-level studies (Kposowa, 2000; Blakely et al, 2003). It can be explained by gender differences in health-related and life-threatening behaviours, such as alcohol or drug misuse, which are known risk factors of suicide and are more prevalent among men and among lower socio-economic groups (Kessler et al, 1994; Cavelaars et al, 1997; McDonough et al, 1999), although alcohol was not particularly related to socio-economic status in the British survey of psychiatric morbidity. On the other hand, suicide inequalities in women resemble those in men more closely where house ownership is concerned than education: this may be because house ownership is mostly an attribute of the household and thus shared by both spouses, whereas education is an individual attribute, hence more sensitive to gender differences. It could be also that low wealth or income tends to have a similar association with men's and women's overall mortality risk (Duncan et al, 2002).
Suicide was more strongly associated with home ownership than with education. This is consistent with previous studies using housing tenure, wealth or car ownership (Lewis & Sloggett, 1998; Qin et al, 2000; Blakely et al, 2003). Several elements may explain such a difference. Housing tenure is an indicator of wealth accumulation and has shown to yield stronger inequality than education (Lorant et al, 2003), presumably because the material pathway (captured by housing tenure) has the edge over the behavioural pathway (captured by educational status). Moreover, psychiatric illness is more likely to affect house ownership than education, because reverse causation is less likely in the latter case. The fact that housing inequalities are greater than educational inequalities indicates that selection factors must not be overlooked and that the roots of inequalities are grasped in the whole life cycle (Power et al, 1998). Finally, housing tenure may also be associated with marital status, which has a clear protective effect on suicide (Kposowa, 2000).
Why is there no suicide inequality in Turin, while the largest inequalities were found in Madrid? We can speculate that the outstanding Italian mental care system might play some part. Mental illness is a major risk factor for suicide (Qin et al, 2003) and is more prevalent among lower socio-economic groups (Lorant et al, 2003). Individuals of lower socio-economic status favour primary mental care over psychiatric specialty care (Alegria et al, 2000). Italy has pioneered an integrated and community-based mental health system, introduced after the reforms of 1978 and the 1994 National Mental Health Plan (Burti, 2001; Becker & Vázquez-Barquero, 2001). As a consequence, Italy might well be able to tackle suicide inequalities more effectively. A recent assessment of time trends of suicide inequalities in Turin showed that the suicide risk was reduced most in the less educated population groups between the 1970s and the 1990s (Costa et al, personal communication). The link with the reform undergone by the Italian psychiatric system requires further study, however.
The large educational inequalities observed in Madrid (and in some analyses also in Barcelona) might be due to the higher prevalence of drug misuse in these Spanish cities compared with other countries of the European Union (Kraus et al, 2003). Suicide is a frequent cause of death among drug users in southern Europe (Orti et al, 1996), and there is a strong relationship between parenteral drug use and educational level. The small inequalities in women from Madrid are consistent with the lower prevalence of injecting drug use in women compared with men. Societal inequalities, including inequalities in income, may provide another explanation for the greater inequalities in suicide in Madrid. Spain ranks among the countries with the highest income inquality in Europe. Moreover, large inequalities among Madrid men may also be explained by the low level of suicide prevalence, as rare events tend to concentrate among lower socio-economic groups.
Clinical implications
The pervasive association between socio-economic status and suicide calls
for an improvement of access to psychiatric care for lower socio-economic
groups. This is relevant because psychiatric disorders seem to be an important
pathway in the relationship between socio-economic status and suicide
(Qin et al, 2003) and
because of the under-utilisation of speciality mental care among lower
socio-economic groups (Alegria et
al, 2000). Individuals of lower socio-economic status with a
DSM-IV disorder (American Psychiatric
Association, 1994) are more likely to receive that care in
countries (such as The Netherlands) that have succeeded in integrating mental
health within the primary and community care sectors
(Alegria et al, 2000). The shift to primary care and community care may thus contribute to reducing
socio-economic inequalities in suicide.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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REFERENCES |
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American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders (4th edn) (DSM-IV). Washington, DC: APA.
Becker, L. & Vázquez-Barquero, J. L. (2001) The European perspective of psychiatric reform. Acta Psychiatrica Scandinavica Supplement, 410,, 8-14.
Blakely, T. A., Collings, S. C. D. & Atkinson, J.
(2003) Unemployment and suicide. Evidence for a causal
association? Journal of Epidemiology and Community
Health, 57, 594
-600.
Burti, L. (2001) Italian psychiatric reform 20 plus years after. Acta Psychiatrica Scandinavica Supplement, 410, 41 -46
Cavelaars, A. E., Kunst, A. E. & Mackenbach, J. P. (1997) Socio-economic differences in risk factors for morbidity and mortality in the European Community: an international comparison. Journal of Health and Psychology, 24, 253 -372.
Dawson, B. & Trapp, R. (2001) Basic and Clinical Biostatistics. New York: McGraw-Hill.
Duncan, G. J., Daly, M. C., McDonough, P., et al
(2002) Optimal indicators of socioeconomic status for health
research. American Journal of Public Health,
92, 1151
-1157.
Joseph, A., Abraham, S., Muliyil, J. P., et al
(2003) Evaluation of suicide rates in rural India using
verbal autopsies, 1994-9. BMJ,
326, 1121.
Jougla, E., Pavillon, G., Rossollin, F., et al (1998) Improvement of the quality and comparability of causes-of-death statistics inside the European Community. Revue d'Épidémiologie et Santé Publiques, 46, 447 -456.
Kessler, R. C., McGonagle, K. A., Zhao, S. Y., et al (1994) Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Archives of General Psychiatry, 51, 8-19.[Abstract]
Kposowa, A. J. (2000) Marital status and
suicide in the National Longitudinal Mortality Study. Journal of
Epidemiology and Community Health,
54, 254
-261.
Kposowa, A. J. (2001) Unemployment and suicide: a cohort analysis of social factors predicting suicide in the US National Longitudinal Mortality Study. Psychological Medicine, 31, 127 -138.[CrossRef][Medline]
Kraus, L., Augustin, R., Frischer, M., et al (2003) Estimating prevalence of problem drug use at national level in countries of the European Union and Norway. Addiction, 98, 471 -485.[CrossRef][Medline]
Lewis, G. & Sloggett, A. (1998) Suicide,
deprivation, and unemployment: record linkage study.
BMJ, 317, 1283
-1286.
Lewis, G., Bebbington, P., Brugha, T., et al (1998) Socioeconomic status, standard of living, and neurotic disorder. Lancet, 352, 605 -609.[CrossRef][Medline]
Lorant, V., Deliege, D., Eaton, W., et al
(2003) Socioeconomic inequalities in depression: a
meta-analysis. American Journal of Epidemiology,
157, 98
-112.
Mackenbach, J. P. & Kunst, A. E. (1997) Measuring the magnitude of socio-economic inequalities in health: an overview of available measures. Social Science and Medicine, 44, 757 -771.[CrossRef][Medline]
McDonough, P., Williams, D. R., House, J. S., et al (19 (1999) 99) Gender and the socioeconomic gradient in mortality. Journal of Health and Social Behavior, 40, 17-31.[Medline]
Orti, R. M., Domingo-Salvany, A., Muñoz, A., et al (1996) Mortality trends in a cohort of opiate addicts, Catalonia, Spain. International Journal of Epidemiology, 25, 545 -553.[Abstract]
Petitti, D. B. (1994) Meta-analysis, Decision Analysis, and Cost-effectiveness Analysis. Methods for Quantitative Synthesis in Medicine . New York: Oxford University Press.
Power, C., Matthews, S. & Manor, O. (1998) Inequalities in self-rated health: explanations from different stages of life. Lancet, 351, 1009 -1014.[CrossRef][Medline]
Qin, P., Mortensen, P., Agerbo, E., et al
(2000) Gender differences in risk factors for suicide in
Denmark. British Journal of Psychiatry,
177, 546
-550.
Qin, P., Agerbo, E. & Mortensen, P. B.
(2003) Suicide risk in relation to socioeconomic,
demographic, psychiatric, and familial factors: a national register-based
study of all suicides in Denmark, 1981-1997. American Journal of
Psychiatry, 160, 765
.
Rockett, I. R. & Thomas, B. M. (1999) Reliability and sensitivity of suicide certification in higher-income countries. Suicide and Life-Threatening Behavior, 29, 141 -149.[Medline]
UNESCO (1997) International Standard Classification of Education: ISCED 1997. Paris:UNESCO.
World World Health Organization (1974) International Statistical Classification of Diseases and Related Health Problems (ICD-8). Geneva: WHO.
World Health Organization (1978) International Statistical Classification of Diseases and Related Health Problems (ICD-9). Geneva: WHO.
World World Health Organization (1992) International Statistical Classification of Diseases and Related Health Problems (ICD-10). Geneva: WHO.
Received for publication November 24, 2003. Accepted for publication June 22, 2004.
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