A multi-level analysis of the relationship between spatial clusters of outpatient-treated depression, risk factors and mental health service planning in Catalonia (Spain).

BACKGROUND Previous research identified high/low clusters of prevalence of outpatient-treated depression at municipal level in Catalonia (Spain). This study aims to analyse potential risk factors, both socioeconomic and related to the mental health service planning, which could influence the occurrence of hot/cold spots of depressed outpatients at two geographical levels: municipalities and service catchment areas. METHOD Hot/cold spots were examined in relation to socioeconomic indicators at municipal level, such as population density, unemployment, university education, personal income, and also those related to service planning at catchment area level, such as adequacy of healthcare, urbanicity, accessibility and the availability of mental health community centres. The analysis has been carried out through multilevel logistic regression models in order to consider the two different scales. RESULTS Hot spots are related to high population density, unemployment, urbanicity, the adequacy of provision of mental health services, and accessibility to mental health community centres at both study levels. On the other hand, the multilevel model weakly explains cold spots, associating them with high personal incomes. LIMITATIONS The dependent variables of the multi-level models are binary. This limits the interpretation of the results, since they cannot provide information about the variance of the dependent variables explained by the models. CONCLUSIONS The results described diverse risk factors at two levels which are related to a high likelihood of hot and cold spots of depression. The findings show the relevance of health planning in the distribution of diseases and the utilisation of healthcare services.

[1]  R. Mitchell,et al.  Do attitude and area influence health? A multilevel approach to health inequalities. , 2000, Health & place.

[2]  Jian Li Wang.  Rural–urban differences in the prevalence of major depression and associated impairment , 2004, Social psychiatry and psychiatric epidemiology.

[3]  A. Beekman,et al.  Religion as a cross-cultural determinant of depression in elderly Europeans: results from the EURODEP collaboration , 2001, Psychological Medicine.

[4]  J Fortney,et al.  The impact of geographic accessibility on the intensity and quality of depression treatment. , 1999, Medical care.

[5]  J. Clapp,et al.  Development as freedom , 1999 .

[6]  K. Morrissey,et al.  Spatial Access to Health Services , 2013 .

[7]  J. Os,et al.  The size and burden of mental disorders and other disorders of the brain in Europe 2010 , 2011, European Neuropsychopharmacology.

[8]  Josep Maria Haro,et al.  Meso-level comparison of mental health service availability and use in Chile and Spain. , 2008, Psychiatric services.

[9]  L. Krabbendam,et al.  Social disadvantage and schizophrenia , 2006, Social Psychiatry and Psychiatric Epidemiology.

[10]  Andrew D Oxman,et al.  SUPPORT Tools for evidence-informed Policymaking in health 11: Finding and using evidence about local conditions , 2009, Health research policy and systems.

[11]  M. Brezzi,et al.  OECD Extended Regional Typology: The Economic Performance of Remote Rural Regions , 2011 .

[12]  Clare Bambra,et al.  Welfare state regimes and differences in self-perceived health in Europe: a multilevel analysis. , 2008, Social science & medicine.

[13]  P. Townsend,et al.  Health and Deprivation: Inequality and the North , 1987 .

[14]  Benjamin J Cowling,et al.  A multilevel analysis of the effects of neighbourhood income inequality on individual self-rated health in Hong Kong. , 2009, Social science & medicine.

[15]  F. Mazzi,et al.  Prevalence of mental disorders in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project , 2004, Acta psychiatrica Scandinavica. Supplementum.

[16]  David McDaid,et al.  Evaluation of an integrated system for classification, assessment and comparison of services for long-term care in Europe: the eDESDE-LTC study , 2013, BMC Health Services Research.

[17]  I Diamond,et al.  A multilevel analysis of the effects of rurality and social deprivation on premature limiting long term illness , 2001, Journal of epidemiology and community health.

[18]  M. Fleury,et al.  A multi-level study of the determinants of mental health service utilization. , 2012, Revue d'epidemiologie et de sante publique.

[19]  I. Nazareth,et al.  Associations between unemployment and major depressive disorder: evidence from an international, prospective study (the predict cohort). , 2011, Social science & medicine.

[20]  S. Raudenbush,et al.  Maximum Likelihood for Generalized Linear Models with Nested Random Effects via High-Order, Multivariate Laplace Approximation , 2000 .

[21]  R. Ocaña-Riola.  Common errors in disease mapping. , 2010, Geospatial health.

[22]  H. Goldstein.  Multilevel Statistical Models , 2006 .

[23]  J. Haro,et al.  Epidemiology of major depressive episode in a southern European country: results from the ESEMeD-Spain project. , 2010, Journal of affective disorders.

[24]  P. Delespaul,et al.  Neighbourhood variation in incidence of schizophrenia , 2000, British Journal of Psychiatry.

[25]  K. Carey,et al.  A multilevel modelling approach to analysis of patient costs under managed care. , 2000, Health economics.

[26]  Karina Gibert,et al.  Incorporating local information and prior expert knowledge to evidence-informed mental health system research , 2013 .

[27]  Paul Clarke,et al.  Who you live with and where you live: setting the context for health using multiple membership multilevel models , 2005, Journal of Epidemiology and Community Health.

[28]  M. King,et al.  Quality of life three months and one year after first treatment for early stage breast cancer: Influence of treatment and patient characteristics , 2004, Quality of Life Research.

[29]  A. Vanasse,et al.  Assessing spatial accessibility to mental health facilities in an urban environment. , 2012, Spatial and spatio-temporal epidemiology.

[30]  Miquel Olivet,et al.  Oferta de servicios de salud y accesibilidad geográfica , 2008 .

[31]  L. Salvador-Carulla,et al.  The local burden of emotional disorders. An analysis based on a large health survey in Catalonia (Spain). , 2012, Gaceta sanitaria.

[32]  R. Jacobs,et al.  Health, policy and geography: Insights from a multi-level modelling approach☆ , 2013, Social science & medicine.

[33]  D. Deeg,et al.  Religious climate and geographical distribution of depressive symptoms in older Dutch citizens. , 1999, Journal of affective disorders.

[34]  R. Murray,et al.  Incidence of schizophrenia in ethnic minorities in London: ecological study into interactions with environment , 2001, BMJ : British Medical Journal.

[35]  C. García-Alonso,et al.  Development of a new spatial analysis tool in mental health: Identification of highly autocorrelated areas (hot-spots) of schizophrenia using a Multiobjective Evolutionary Algorithm model (MOEA/HS) , 2010, Epidemiology and Psychiatric Sciences.

[36]  J. van os,et al.  Shared social environment and psychiatric disorder: a multilevel analysis of individual and ecological effects , 1998, Social Psychiatry and Psychiatric Epidemiology.

[37]  W. Jones,et al.  Small Area Variation in the Utilization of Mental Health Services: Implications for Health Planning and Allocation of Resources , 1995, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[38]  Graham Dunn,et al.  Geographical epidemiology, spatial analysis and geographical information systems: a multidisciplinary glossary , 2007, Journal of Epidemiology and Community Health.

[39]  A. Serrano-Blanco,et al.  Use of an integrated Atlas of Mental Health Care for evidence informed policy in Catalonia (Spain) , 2014, Epidemiology and Psychiatric Sciences.

[40]  A. Gafni,et al.  Using small-area variations to inform health care service planning: what do we 'need' to know? , 2013, Journal of evaluation in clinical practice.

[41]  G. Rushton,et al.  Community-Level Risk Factors for Depression Hospitalizations , 2007, Administration and Policy in Mental Health and Mental Health Services Research.

[42]  Ashton M. Shortridge,et al.  Do More Hospital Beds Lead to Higher Hospitalization Rates? A Spatial Examination of Roemer’s Law , 2013, PloS one.

[43]  Timothy J. Robinson,et al.  Multilevel Analysis: Techniques and Applications , 2002 .

[44]  Shekhar Saxena,et al.  WHO's Assessment Instrument for Mental Health Systems: collecting essential information for policy and service delivery. , 2007, Psychiatric services.

[45]  C. García-Alonso,et al.  Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain) , 2012, International Journal of Health Geographics.

[46]  Anthony S. Bryk,et al.  Hierarchical Linear Models: Applications and Data Analysis Methods , 1992 .

[47]  P. McCullagh,et al.  Generalized Linear Models , 1984 .