Family Medicine, Karolinska Institutet, Stockholm, Sweden
Correspondence: Dr Kristina Sundquist, Family Medicine Stockholm, Karolinska Institutet, Alfred Nobels allé 12, SE-141 83 Huddinge, Sweden.Tel: +46 8 524 887 08; fax: +46 8 524 887 06; e-mail: Kristina.Sundquist{at}klinvet.ki.se
Declaration of interest None. Funding detailed in Acknowledgements.
See editorial, pp.
287288, this
issue.
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ABSTRACT |
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Aims To examine whether a high level of urbanisation is associated with increased incidence rates of psychosis and depression, after adjustment for age, marital status, education and immigrant status.
Method Follow-up study of the total Swedish population aged 2564 years with respect to first hospital admission for psychosis or depression. Level of urbanisation was defined by population density and divided into quintiles.
Results With increasing levels of urbanisation the incidence rates of psychosis and depression rose. In the full models, those living in the most densely populated areas (quintile 5) had 6877% more risk of developing psychosis and1220% more risk of developing depression than the reference group (quintile 1).
Conclusions A high level of urbanisation is associated with increased risk of psychosis and depression for both women and men.
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INTRODUCTION |
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METHOD |
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Outcome variable
Psychiatric morbidity was defined as the first admission to hospital for
treatment of psychosis or depression defined according to ICD9 and
ICD10 (World Health Organization,
1978,
1992). There were two
diagnostic groups: psychosis (ICD9 codes 295, 297, 298C, 298E, 298W,
298X; and ICD10 codes F2025, F28, F29) and depression
(ICD9 codes 296, 298A, 298B, 300E, 301B, 311; ICD10 codes
F3034, F38, F39). The DSMIV
(American Psychiatric Association,
1994) was also used as an instrument in the process of
diagnosis.
Explanatory variables
The study population was categorised by gender, and by age into the
following groups: 2534 years, 3544 years, 4554 years, and
5564 years of age at the start of study. Level of urbanisation was
classified into quintiles by dividing all 4.4 million individuals into five
groups according to the population density in the SAMS area where they lived.
The population density was calculated as the number of people living in the
SAMS area divided by the area in km2. The quintiles were classified
as follows: quintile 1, 19; quintile 2, 20273; quintile 3,
274818; quintile 4, 8192278; quintile 5,
2279 (all values in
persons per km2).
Marital status was classified in two categories: living alone, and married/cohabiting. Only individuals with children in common registered at the same property were counted as being cohabiting. Cohabiting without children in common is registered in the national database as single, and therefore in this study was counted as living alone.
Attained level of education was used as a measure of socio-economic status and classified into three categories: low (compulsory school), middle (at most 2 years of university study) and high (at least 3 years of university study).
Immigrant status was classified into three groups. The first group consisted of people born in countries with mainly labour-related immigration to Sweden (southern European countries and member states of the Organisation for Economic Co-operation and Development); the second group consisted of people born in countries often referred to as refugee countries (Eastern European countries, Bosnia, and all other non-European countries); and the third group consisted of Swedish-born people.
We performed separate analyses for women and men because of the gender differences in psychiatric disease established in previous research. Moreover, many psychiatric disorders decline with increasing age and socio-economic status, which is why we included age and attained level of education in the analysis (Kessler et al, 1994). Marital status was included in the analysis because of its relationship with, for example, depression (Carroll et al, 2003). Finally, the importance of immigrant status for mental health was recently confirmed by the Swedish National Institute of Public Health (Sundquist & Johansson, 2002) and by a longitudinal study of different migrant groups in Sweden (Westman et al, 2003).
During the follow-up 30% of the population had moved from one SAMS area to another. Therefore, we added the variable moved/not moved in an additional analysis (data not shown).
Statistical analysis
The SAS software package (version 6) was used in the statistical analyses
(SAS, 1989). Age-standardised
incidence rates (per 100 000 persons per year) of psychosis and depression
were calculated by indirect age standardisation, with Sweden as the standard
population (Breslow & Day,
1987). A Cox regression model
(Kleinbaum, 1995) was used to
estimate the hazard ratios of psychosis and depression in the different
background variables. The results are shown as hazard ratios (HR) with 95%
confidence intervals. Risk time was calculated from the start of study until
the first admission to hospital because of psychosis or depression, death from
all causes, emigration from Sweden, or end of the study. The proportional
hazards assumption was tested for parallelism by studying log(log(.))
of survival curves. All variables met the assumption; no interaction between
the explanatory variables and time was found.
The study was approved by the ethics committee at the Karolinska Institute, Stockholm.
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RESULTS |
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Table 3 shows the age-adjusted and full models for men. The results show patterns similar to those for women, with a clear gradient between level of urbanisation and risk of developing psychosis or depression. For example, for men living in the most urbanised areas, the risks of developing psychosis or depression were 125% and 27% higher than for those in the least urbanised areas. These increased risks decreased slightly but remained significant after adjustment for marital status, attained level of education and immigrant status. In the full model, men living in the most urbanised areas (quintile 5), had 68% and 12% higher risks of developing psychosis and depression, respectively, than men in the least urbanised areas. When we added the variable moved/not moved, the hazard ratios remained almost unaltered: for example, in the full models the hazard ratios for psychosis in quintile 5 were 1.76 (95% CI 1.55198) for women and 1.67 (95% CI 1.491.88) for men (data not shown).
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There was also a clear association between the covariates marital status, attained level of education and immigrant status, and our outcome variables. For example, in the full model the hazard ratio for psychosis in quintile 5 for people living alone was 6.02 (95% CI 6.456.64) for men and 3.23 (95% CI 2.983.49) for women. A similar pattern was observed for low educational attainment. Individuals categorised as labour migrants or refugees exhibited increased risks of developing psychosis and depression.
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DISCUSSION |
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Other studies
Our findings of an association between urbanisation and depression were in
agreement with some studies from the USA
(Blazer et al, 1987;
Neff & Husaini, 1987). A
few studies from the Netherlands revealed higher urban than rural rates of
psychosis (Marcelis et al,
1998; van Os et al,
2001,
2002). One of these studies
confirmed that a high level of urbanisation was associated with psychotic
disorders, after adjustment for individual demographic and socio-economic
characteristics, findings in agreement with our study
(van Os et al, 2002).
However, a study from the UK showed strong urbanrural differences in
mental health that did not remain after adjustment for individual
socioeconomic characteristics (Paykel
et al, 2000). Other studies from the USA and the UK did
not agree with our study, finding no urbanrural difference in mental
health (Romans-Clarkson et al,
1990; Robins & Regier,
1991; Kessler et al,
1994; Parikh et al,
1996). In Canada, no difference was found for depression rates in
urban and rural Ontario (Parikh et
al, 1996).
In summary, previous studies of possible urbanrural differences in mental health are inconsistent. However, our findings of a significant relationship between the level of urbanisation and psychiatric morbidity shed new light on this inconsistency, because our study population consisted of the entire adult population in Sweden, and we used incidence rates, rather than prevalence rates, as our outcome.
Possible pathways
The pathways linking urbanisation and mental health have not yet been
clarified. For example, a British study based on data from 9777 individuals
showed urbanrural differences in psychiatric morbidity and substance
misuse, which were largely attributable to more adverse living circumstances
among individuals in urban social environments. These adverse circumstances
included stressful life events and low levels of social support
(Paykel et al, 2000). Social networks have been shown to be better in rural areas than in urban
areas for women (Romans-Clarkson et
al, 1990). In addition, several previous studies have shown a
relationship between mood disorders, suicide attempts and poor social networks
(Amann, 1991;
Johnsson Fridell et al,
1996; Cheng et al,
2000; Hirschfeld et
al, 2000); thus, poor social networks might be a mediator
between urbanisation and mental health. Another possible pathway linking
urbanisation and psychiatric disease is that an urban environment might
influence mental health in early life and increase general vulnerability to
schizophrenia later in life (Marcelis
et al, 1999; Pedersen
& Mortensen, 2001). Some early risk factors associated with
schizophrenia are prenatal exposure to viral infections
(Takei et al, 1995)
and poor nutrition (Brown et al,
1995). Other possible pathways between urbanisation and
schizophrenia have also been discussed, such as daily life stress
(van Os & McGuffin, 2003) and chronic difficulties in urban areas
(Brown & Prudo, 1981).
In The Netherlands it was found that about three-quarters of individuals living in urban areas had also been born there (Marcelis et al, 1999). These findings indicate a relatively stable urbanrural exposure over time, supporting the theory that being born and/or spending ones childhood in an urban environment increases the risk of later developing a psychotic disorder. Some urban areas might also be socio-economically deprived and ethnically segregated. However, these possible pathways between urbanisation and mental health were not included in our study. Finally, it is possible that there might be a biological synergism between genetic liability and urban exposure. In a study from The Netherlands, the authors found that both the level of urbanisation and familial liability (defined as a family history of delusions and/or hallucinations necessitating psychiatric treatment) increased the risk of psychotic disorder, independently of each other. Moreover, the effect of urbanisation on the additive scale was much larger for people with evidence of familial liability than for those without familial liability (van Os et al, 2003).
Limitations and strengths
There are some limitations to this study. First, the database of the whole
Swedish adult population included only marital status as a measure of social
support. If rural areas have better social support than urban ones, it is
possible that people experiencing a first episode of psychosis or depression
are less likely to be admitted to hospital in rural areas. This might lead to
underestimates of the incidence of rural psychosis and depression owing to the
effects of community rather than institutional care. It is also possible that
the distribution of psychiatric beds across Sweden would bias our results if,
for example, the number of psychiatric beds was higher in urban areas;
however, we found that in the urbanised area of Stockholm County the number of
psychiatric beds was 0.52 per 1000 inhabitants, and in the rural northern
region it was 0.58 per 1000 inhabitants. The fact that cohabiting persons
without children in common are registered as living alone may result in
underestimates of the risks of psychiatric disease. Another limitation is that
we were not able to adjust our results for possible effects of selective
migration (e.g. from rural to urban areas), and the stress related to that
migration. However, after adjustment of our results for migration between SAMS
areas, the hazard ratios remained unaltered.
Our study also has a number of strengths. For example, the prospective nature of our data allowed us to calculate incidence rates of psychosis and depression, rather than prevalence rates. Data from the national database were nearly complete for all variables. This completeness is made possible by the Swedish registration system, which provides a personal identification number for each individual. This number is used to link data from different registers, and was used to follow each individual during the entire study period.
Our urbanisation measure, calculated as population density, is an actual measure of number of people per unit area. In another study of urbanisation the population density was calculated as number of addresses per unit area (van Os et al, 2002), which is not a precise measure of the actual number of people in that area. The level of urbanisation was estimated in one study according to the respondents own judgement, which implies a self-report bias (Paykel et al, 2000).
Our study population consisted of all Swedish women and men aged 2564 years, in total 4.4 million persons. The validity of the diagnosis from the Swedish In-Care Register has been shown to be high in an evaluation by the Swedish National Board of Health and Social Welfare (National Board of Health and Welfare, 2000).
Implications
Our findings suggest that the level of urbanisation is associated with
psychosis and depression in both women and men. For clinicians in urban areas
who are involved in both treatment and prevention of disease, it is of great
importance to consider possible pathways in the development of psychiatric
morbidity. These pathways might include lack of social support, stressful life
events and familial liability. Moreover, when planning the distribution of
health care resources, it is important to consider the level of urbanisation
in order to improve services for people who are at high risk of developing
psychiatric morbidity.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication May 8, 2003. Revision received September 12, 2003. Accepted for publication October 29, 2003.
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