Strangeways Research Laboratory and Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, UK
Correspondence: Dr Nicholas Wainwright, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK. Tel: +44 (0)1223 740171; fax: +44 (0)1223 740147; e-mail: nick.wainwright{at}srl.cam.ac.uk
Declaration of interest None. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To investigate the relative strength of association between individual and area-level demographic and socio-economic factors and mood disorder prevalence in the UK.
Method Cross-sectional data from 19 687 participants from the European Prospective Investigation into Cancer and Nutrition in Norfolk.
Results Area deprivation was associated with current (12-month) mood disorders after adjusting for individual-level socio-economic status (OR for top v. bottom quartile of deprivation scores 1.29, 95% CI 1.11.5, P<0.001). However, this association was small relative to those observed for individual marital and employment status. Significant residual area-level variation in current mood disorders (representing 3.6% of total variation, P=0.04) was largely accounted for by individual-level factors.
Conclusions The magnitude of the association between socio-economic status and mood disorders is greater at the individual level than at the area level.
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INTRODUCTION |
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METHOD |
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Dependent variables
The HLEQ instrument included a structured self-assessment approach to
psychiatric symptoms representative of selected DSMIV criteria for
major depressive disorder and generalised anxiety disorder
(American Psychiatric Association,
1994). The approach was designed to provide measures of emotional
state for inclusion in a large-scale chronic disease epidemiology project (see
Surtees et al, 2000,
2003 for further details) and
to identify those EPICNorfolk participants thought likely to have met
diagnostic criteria at any time in their lives. Where any psychiatric episode
was reported, respondents were asked also to estimate its onset and (if
appropriate) offset timings and to provide an outline of the history of the
problem, including age at first onset and subsequent episode recurrence. The
primary outcome measure investigated was the prevalence of current mood
disorders, defined as an episode of either major depressive or generalised
anxiety disorder, reported as ongoing or having offset within 12 months of the
HLEQ assessment. In addition (and to provide some insight into contextual
relationships with both recency and severity), some analyses are repeated for
lifetime prevalence of either of these disorders and for the lifetime presence
of key depressive symptoms, defined as a positive response to either of the
following questions:
Individual-level measures
Age, gender, social class, marital status, employment status and
educational level were included as individual-level indicators of demographic
and socio-economic status. Social class was allocated according to the
Computer-Assisted Standard Occupational Coding
(Elias et al, 1993)
as I (professionals), II (managerial and technical occupations), III
non-manual and III manual (skilled workers), IV (partly skilled workers) and V
(unskilled manual workers). For both men and women, social class was coded
based on the male partners current or prior occupation (or the female
partners occupation where information for the male partner was
unavailable); if data were not available for either partner, social class
could not be allocated. Marital status was coded in four categories
(married/living as married, never married, widowed and divorced/separated).
Current employment status was coded as those working (full or part-time) and
not working (either unemployed or economically inactive), as previously
defined by the Office for National Statistics
(Meltzer et al,
1995). Educational attainment was coded in four categories: those
with no formal qualifications; those with formal qualifications usually
associated with a school age of 16 years; those with formal qualifications (or
vocational equivalent) usually associated with a school age of around 18
years; and those with degree-level qualifications.
Area-level measures
Participants in the EPICNorfolk study were recruited from a defined
geographical area within East Anglia, centred on the city of Norwich and the
surrounding small towns and rural areas, that has little outward migration in
the study age group (Day et al,
1999). Area of residence was defined according to the UK electoral
register (electoral wards). In 2000, an overall index of multiple deprivation
commissioned by the (then) Department of the Environment, Transport and the
Regions (2000) was created for
the 8414 electoral wards in England, derived from 32 variables in six domains:
income; employment; health deprivation and disability; education, skills and
training; housing; and geographical access to services. The index combined
information from across the six domain scores, a higher score representing a
more deprived area. These data were linked at the electoral ward level to
individual-level data gathered through the EPICNorfolk HLEQ
instrument.
Statistical analysis
Contextual analysis (standard logistic regression including covariates to
represent both individual and area-level measures) was used to investigate the
association between individual-level demographic and socio-economic factors,
multiple deprivation (included as a categorical variable in quartiles) and
current mood disorders. Results are presented as odds ratios, adjusted first
for age (in 5-year bands) and gender, and second for age, gender, social
class, marital status, employment status, educational attainment and multiple
deprivation. As it was not possible to define social class for a sizeable
subgroup of participants, this subgroup was included in adjusted analyses as
an extra category (data not shown). Subsequently, multilevel models were used,
with individuals at level 1 and electoral wards at level 2, to quantify the
extent of residual area-level variation in sustained depressive symptoms and
in life-time and current mood disorders. Residual variation at the individual
and area levels is presented along with the percentage of variation at the
area level, first unadjusted and then adjusted for age and gender. The models
used were random intercept logistic multilevel models
(Goldstein, 1995) with no
overdispersion. For these models, individual-level variation equals unity, and
the proportion of variation at the area level is equivalent to the intraclass
correlation coefficient and represents the degree of correlation between the
health of individuals within the same electoral ward
(Subramanian et al,
2003). Analysis was performed in SPlus
(Chambers & Hastie, 1992)
and MLwiN (Rasbash et al,
2000). For the multilevel models, estimation was by second-order
penalised quasilikelihood and Wald chi-squared tests were used as approximate
tests of the significance of area-level variation
(Rasbash et al,
2000).
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RESULTS |
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Study participants were resident in 162 different electoral wards with a mean of 121 participants per ward (median 81, range 1850). Multiple deprivation scores in the range 5.258.8 place these 162 wards as ranked between the 7991st and 288th most deprived of the 8414 wards in England, a coverage of 91.5% of the population distribution of deprivation scores. Of the study participants, 90% were resident in wards with multiple deprivation scores in the range 7.437.2, corresponding to ward-level ranks of 7307 and 1321 (and a coverage of 71.1% of the population distribution). Table 1 shows that the 12-month prevalence of either major depressive disorder or generalised anxiety disorder was highest for participants living in the most deprived wards (highest quartile of deprivation scores). The proportion of participants in the non-manual social classes was higher (79.1% v. 63.3%) for those who were resident in the least deprived as compared with the most deprived wards, respectively (bottom and top quartiles, data not displayed).
Table 2 shows the results of the contextual analysis of the association between individual-level demographic and socio-economic factors, multiple deprivation and current mood disorders. After adjustments for age and gender, an association was observed for multiple deprivation (P<0.001) such that participants resident in the most deprived wards (top quartile of deprivation scores) were approximately 1.4 times more likely to have reported current mood disorders than those resident in the least deprived wards (bottom quartile of deprivation scores). This association remained with further adjustment for individual social class, marital status, employment status and educational attainment (OR=1.3, P<0.001). In this model, marital status and employment status were strongly associated with prevalent mood disorders, and the magnitude of these associations was substantially greater than that for deprivation. Prevalence of mood disorders was 2.6 times higher in participants who were divorced or separated (compared with those who were married or living as married) and 2.1 times higher in those who were not working (compared with those who were working) at the time of HLEQ assessment. No association was observed for individual social class and educational attainment.
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Table 3 shows the results of the multilevel analysis of residual individual and area-level variation in depressive symptoms (depressed mood or loss of interest) and lifetime and current prevalence of mood disorders. Unadjusted for any covariates, significant residual variation at the area level was observed for all three outcomes, with the amount of variation at the area level lowest for depressive symptoms (0.9% of total variation, P=0.03), greater for lifetime prevalence (2.0%, P=0.01) and greater still for current prevalence (3.6%, P=0.04). After adjustment for age and gender, the percentage variation at the area level was reduced and was significant only for lifetime prevalence (1.8%, P=0.03), although it remained higher for current prevalence (2.9%, P=0.07). No significant variation was observed at the area level with further adjustment for marital and employment status, and the amount of variation remaining at the area level was modest: 0.4%, 1.0% and 0.9% for symptoms, lifetime and current prevalence, respectively.
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DISCUSSION |
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Multilevel models are recommended for the joint analysis of area (contextual) and individual factors (composition), in particular allowing residual variation to be taken into account and quantified at both the individual and area levels (Duncan et al, 1998; Diez Roux, 2000; Pickett & Pearl, 2001). However, standard regression methods with covariates constructed to represent both individual and area-level characteristics (contextual analysis) (Diez Roux, 2003) are adequate when there is no interest in quantifying this variation and when the assumptions of independence are not violated (i.e. there is little or no residual area-level variation) (Diez-Roux, 2000, 2003). In this paper we have presented both a contextual analysis to investigate the impact of area deprivation on prevalent mood disorders and a multilevel analysis to quantify the extent of residual variation at the individual and area levels.
Study limitations
The study has a number of important limitations that warrant further
comment.
First, participation in EPICNorfolk involved extensive follow-up and included a request for detailed biological and dietary data. As a result, only around 45% of eligible participants were recruited into the study and the cohort, therefore, did not represent a truly random sample of the population. The response rate, along with the age range (4180 years), social class distribution (predominantly non-manual) and type of geographical area (predominantly rural), may limit the generalisability of results. However, the EPICNorfolk cohort is representative of the general resident population of England in terms of anthropometric variables, blood pressure and serum lipid levels, although it has fewer current smokers (Day et al, 1999), and is comparable (agegender standardised) with UK population norms in terms of physical and mental functional health (Surtees et al, 2004). In addition, the deprivation scores from the 162 electoral wards in this study covered 90% of the range of deprivation scores for all 8414 electoral wards in England, although it remains possible that results will not be generalisable to residents of areas that are either extremely deprived or extremely affluent.
Second, the assessments of major depressive disorder and generalised anxiety disorder were based on a self-report questionnaire; however, previous work with the HLEQ-derived measure of major depressive disorder showed only a small amount of episode compression (clustering of episodes in the immediate pre-assessment period), and prevalence estimates and agegender distributions were comparable with those obtained from interview-based assessment methods in UK and international studies (Surtees et al, 2000).
Third, the data used for this study were cross-sectional. Current measures of neighbourhood exposures may not be a good reflection of overall exposures, and we are unable to distinguish between social causation (area deprivation influences mental health) and residual selection (individuals mental health influences or limits their choice of area of residence) (Kawachi & Berkman, 2003).
Fourth, the specification of areas is based on administrative boundaries (driven by practical considerations), which may not capture the relevant neighbourhoods and has no explicit theoretical justification (Duncan et al, 1998). In addition, census-based area variables may not be the most appropriate area factors and may lead to underestimation of area-level effects (Kawachi & Berkman, 2003).
Fifth, the investigation of area-level residual variation in multilevel models is limited by issues of statistical power: this depends on the number of areas studied, the average number of individuals within each area and on the type of model and method of estimation (Duncan et al, 1998; Diez Roux, 2000). For binary models current methods may underestimate the random effects (Diez Roux, 2000). Although the size of the current study cohort is a major strength, the absence of significant residual variation at the area level (particularly for current mood disorders, for which end-points were rarer) may still reflect these limitations of power. However, in addition to significance, the multilevel model also provides an estimate of the proportion of variation at the area level, and this was found to be modest.
Implications of the findings
In agreement with previous work
(Burvill, 1995), our study
demonstrated strong associations between individual marital and employment
status and prevalent mood disorders. Although the evidence for a gradient in
mental health by social class and educational attainment has been less
consistently demonstrated, a number of studies have produced positive results
(Stansfeld & Marmot, 1992; Lorant et al, 2003),
whereas in our study no association was observed for these factors.
Few studies have investigated contextual effects and mental health outcomes, and even fewer have employed multilevel methods (Pickett & Pearl, 2001; Silver et al, 2002). Previous studies have demonstrated contextual effects for psychiatric disorders such as schizophrenia and substance misuse (Goldsmith et al, 1998; Van Os et al, 2000; Silver et al, 2002), whereas evidence for minor psychiatric problems and mood disorders has been mixed. Of studies based on cross-sectional measures of psychiatric symptoms, such as those using the General Health Questionnaire (Goldberg & Williams, 1988), some demonstrated contextual effects or regional variations (Lewis & Booth, 1992, 1994; Weich & Lewis, 1998; Yen & Kaplan, 1999; Ross, 2000), but others reported negative results (Duncan et al, 1995; Reijneveld & Schene, 1998; Weich et al, 2003). In studies that used assessments based on diagnostic criteria, neighbourhood factors were found to be associated with neurotic disorder (Lewis et al, 1998), non-psychotic, non-organic disorders (Driessen et al, 1998) and depression (Silver et al, 2002), although a different study found no association for affective disorders (Goldsmith et al, 1998).
Our study investigated area-level (contextual) effects for mood disorders through contextual and multilevel analysis, using an assessment designed to represent selected DSMIV diagnostic criteria for major depressive disorder and generalised anxiety disorder and including details of lifetime episodes, and of time of onset and offset for the most recent episode (Surtees et al, 2000). We found evidence for contextual effects in relation to prevalent mood disorders (episodes within 12 months of assessment), but in agreement with other multilevel investigations of minor psychiatric disorder the proportion of variation explained at the area level was found to be small once important individual-level socio-economic correlates had been taken into account (Duncan et al, 1995; Reijneveld & Schene, 1998; Ross, 2000; Weich et al, 2003).
The joint investigation of area-level measures of social context and individual-level socio-economic status can provide a more complete understanding of the determinants of disease (Diez Roux, 1998). Our study has provided evidence for a modest association between social context, represented by a measure of area deprivation, and prevalent mood disorders. Although the strength of these results is limited by issues of power and by definitions of area measures and area boundaries, our findings suggest that the magnitude of associations between measures of socio-economic status and prevalent mood disorders is greater at the individual level than at the area level.
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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 October 17, 2003. Revision received April 16, 2004. Accepted for publication April 22, 2004.