A census-based socio-economic status (SES) index as a tool to examine the relationship between mental health services use and deprivation

Identifying Social Determinants and Measuring Socioeconomic Inequalities in the Use of Four Different Mental Health Services by Australian Adolescents Aged 13-17 Years: Results from a Nationwide Study

AIM

In this study, we aimed to identify the determinants of four different forms of mental health service usage (general health services, school counselling, telephone, and online services), and the number of mental health services accessed (single and multiple) by Australian adolescents aged 13-17 years. We also measured socioeconomic inequality in mental health services' usage following the concentration index approach within the same sample.

SUBJECT AND METHODS

The data came from the nationwide cross-sectional survey, Young Minds Matter (YMM): the second Australian Child and Adolescent Survey of Mental Health and Wellbeing. Random effect models were used to identify the factors associated with four different mental health services and the number of services accessed. Further, the Erreygers' corrected concentration indices for binary variables were used to quantify the socioeconomic inequality in each mental health service. The four services were the general health service (GP, specialist, psychiatrist, psychologist, hospital including emergency), school services, telephone counselling and online services.

RESULTS

Overall, 31.9% of the total analytical sample (n = 2268) aged 13-17 years old visited at least one service, with 21.9% accessing a single service and 10% accessing multiple services. The highest percentage of adolescents used online services (20.1%), followed by general mental health services (18.3%), while school services (2.4%) were the least used service. Age, gender, family type and family cohesion statistically significantly increased the use of general health and multiple mental health service usage (p < 0.05). Area of residence was also found to be a significant factor for online service use. The concentration indices (CIs) were -0.073 (p < 0.001) and -0.032 (p < 0.001) for health and telephone services, respectively, which implies pro-rich socio-economic inequality.

CONCLUSION

Adolescents from low-income families frequently used general mental health services and telephone services compared to those who belonged to high-income families. The study concluded that if we want to increase adolescents' usage of mental health services, we need to tailor our approaches to their socioeconomic backgrounds. In addition, from a policy standpoint, a multi-sectoral strategy is needed to address the factors related to mental health services to reduce inequity in service utilisation.

Construction and Validation of an Individual Deprivation Index: a Study Based on a Representative Cohort of the Paris Metropolitan Area

The association between health status and deprivation is well established. However, it is difficult to measure deprivation at an individual level and already-existing indices in France are not validated or do not meet the needs of health practitioners. The aim of this work was to establish a validated, easy-to-use, multidimensional, relevant index that was representative of the population in the Paris metropolitan area. From the SIRS 2010 cohort study, 14 socio-economic characteristics were selected: health insurance, educational background, socio-professional category, professional status, feelings of loneliness, emotional situation, household type, income, perceived financial situation, social support (support in daily life, financial and emotional), housing situation, and migration origin. In addition, a total of 12 health status, healthcare use, and nutrition-related variables were also selected. Content validity and internal validity of the index were explored. The 14 socio-economic indicators were associated to varying degrees with poorer health status, less use of healthcare, and poorer nutrition and were distributed across the 14 multiple-choice questions of the index. Each answer was rated from 0 to 2. The index value of 10 that isolates 20% of the most deprived individuals was used as threshold. "Being deprived," as defined with this value, was significantly associated with 9 of the 12 studied health variables. This index could be a relevant instrument in the assessment of deprivation and social inequalities of health.

Investigating geographical variation in the use of mental health services by area of England: a cross-sectional ecological study

BACKGROUND

There is evidence of geographical variation in the use of mental health services in the UK and in international settings. It is important to understand whether this variation reflects differences in the prevalence of mental disorders, or if there is evidence of variation related to other factors, such as population socioeconomic status and access to primary care services.

METHODS

This is a cross-sectional ecological study using Public Health England data. The unit of analysis was the population served by clinical commissioning groups (CCGs), National Health Service (NHS) catchment areas. The analysis explored associations between area characteristics and the number of people in contact with mental health services using regression modelling. Explanatory variables included age, gender, prevalence of severe mental illness (SMI), prevalence of common mental disorder (CMD), index of multiple deprivation (IMD), unemployment, proportion of the population who are Black and Minority Ethnic (BAME), population density, access to and recovery in primary care psychological therapies. Unadjusted results are reported, as well as estimates adjusted for age, prevalence of CMD and prevalence of SMI.

RESULTS

The populations of 194 CCGs were included, clustered within 62 trusts (NHS providers of mental health services). The number of people in contact with mental health services showed wide variation by area (range from 1131 to 5205 per 100,000 population). Unemployment (adjusted IRR 1.11; 95% CI 1.05 to 1.17; p < 0.001) and deprivation (adjusted IRR 1.02 95% CI 1.01 to 1.04; p < 0.001) were associated with more people being in contact with mental health services. Areas with a higher proportion of the population who are BAME (IRR 0.95 95% CI 0.92 to 0.99 p = 0.007) had lower service use per 100,000 population. There was no evidence for association with access to primary care psychological therapies.

CONCLUSIONS

There is substantial variation in the use of mental health services by area of England. Social factors including deprivation, unemployment and population ethnicity continued to be associated with the outcome after controlling for the prevalence of mental illness. This suggests that there are factors that influence the local population use of mental health services in addition to the prevalence of mental disorder.

Social inequalities in mobility during and following the COVID-19 associated lockdown of the Madrid metropolitan area in Spain

Spain has been one of the most affected regions by the COVID-19 worldwide, and Madrid its most affected city. In response to this, the Spanish government enacted a strict lockdown in late March 2020, that was gradually eased until June 2020. We explored differentials in mobility by area-level deprivation in the functional area of Madrid, before, during, and after the COVID-19 lockdown. We used cell phone-derived mobility indicators (% of the population leaving their area) from the National Institute of Statistics (INE), and a composite measure of deprivation from the Spanish Society of Epidemiology (SEE). We computed changes in mobility with respect to pre-pandemic levels, and explored spatial patterns and associations with deprivation. We found that levels of mobility before COVID-19 were slightly higher in areas with lower deprivation. The economic hibernation period resulted in very strong declines in mobility, most acutely in low deprivation areas. These differences weakened during the re-opening, and levels of mobility were similar by deprivation once the lockdown was completely lifted. Given the existence of important socioeconomic differentials in COVID-19 exposure, it is key to ensure that these interventions do not widen existing social inequalities.

Small-area socioeconomic deprivation indices in Cyprus: development and association with premature mortality

BACKGROUND

Area-level measures of socioeconomic deprivation are important for understanding and describing health inequalities. The aim of this study was the development and validation of a small-area index of socioeconomic deprivation for Cypriot communities and the investigation of its association with the spatial distribution of all-cause premature adult mortality.

METHODS

Six area-level socioeconomic indicators were used from the 2011 national population census (low educational attainment, unemployment, not owner occupied household, single-person household, divorced or widowed and single-parent households). After normalization and standardization of the geographically smoothed indicators, Principal Component Analysis (PCA) was used to construct indicator weights. The association between deprivation indices and the spatial distribution of all-cause premature adult mortality was estimated in Poisson log-linear spatial models.

RESULTS

PCA resulted in two principal components explaining the 65.7% of the total variance. The first principal component included four indicators (low educational attainment, single-person households, divorced or widowed and single-parent households, the latter however with a negative loading) and it thought more likely to capture rural-related aspects of deprivation. The second principal component included the other two indicators (unemployment and not owner occupied households) and it is more likely to capture urban-related aspects of material deprivation. Restricting the analysis in the metropolitan areas of the island resulted in a different set of indicators for the urban-specific deprivation index. All developed indices were linearly associated with all-cause premature adult mortality. The all-cause premature adult mortality increased by 17% per 1 standard deviation (SD) increase in rural-related socioeconomic deprivation (95% CrI: 8-27%) and 8% per 1 SD increase in urban-related aspects of material deprivation (95% CrI: 3-15%) in the nationwide analysis and 9% per 1 SD increase in urban-specific socioeconomic deprivation (95% CrI: 4-15%) across metropolitan areas.

CONCLUSIONS

The results of this study demonstrate that a set of small-area indices of socioeconomic deprivation across Cypriot communities have good construct and predictive validity. However, the study indicates that different aspects of socioeconomic deprivation may be important in rural and urban areas in Cyprus. The developed socioeconomic deprivation indices could offer a valid new tool for Cypriot public health research and policy in terms of identifying areas in greatest need, guiding resource allocation and developing area-targeted public health programmes and policies.

Standard comparison of local mental health care systems in eight European countries

AIMS

There is a need of more quantitative standardised data to compare local Mental Health Systems (MHSs) across international jurisdictions. Problems related to terminological variability and commensurability in the evaluation of services hamper like-with-like comparisons and hinder the development of work in this area. This study was aimed to provide standard assessment and comparison of MHS in selected local areas in Europe, contributing to a better understanding of MHS and related allocation of resources at local level and to lessen the scarcity in standard service comparison in Europe. This study is part of the Seventh Framework programme REFINEMENT (Research on Financing Systems' Effect on the Quality of Mental Health Care in Europe) project.

METHODS

A total of eight study areas from European countries with different systems of care (Austria, England, Finland, France, Italy, Norway, Romania, Spain) were analysed using a standard open-access classification system (Description and Evaluation of Services for Long Term Care in Europe, DESDE-LTC). All publicly funded services universally accessible to adults (≥18 years) with a psychiatric disorder were coded. Care availability, diversity and capacity were compared across these eight local MHS.

RESULTS

The comparison of MHS revealed more community-oriented delivery systems in the areas of England (Hampshire) and Southern European countries (Verona - Italy and Girona - Spain). Community-oriented systems with a higher proportion of hospital care were identified in Austria (Industrieviertel) and Scandinavian countries (Sør-Trøndelag in Norway and Helsinki-Uusimaa in Finland), while Loiret (France) was considered as a predominantly hospital-based system. The MHS in Suceava (Romania) was still in transition to community care.

CONCLUSIONS

There is a significant variation in care availability and capacity across MHS of local areas in Europe. This information is relevant for understanding the process of implementation of community-oriented mental health care in local areas. Standard comparison of care provision in local areas is important for context analysis and policy planning.

Identifying Local and Centralized Mental Health Services-The Development of a New Categorizing Variable

The challenges of mental health and substance abuse services (MHS) require shifting of the balance of resources from institutional care to community care. In order to track progress, an instrument that can describe these attributes of MHS is needed. We created a coding variable in the European Service Mapping Schedule-Revised (ESMS-R) mapping tool using a modified Delphi panel that classified MHS into centralized, local services with gatekeeping and local services without gatekeeping. For feasibility and validity, we tested the variable on a dataset comprising MHS in Southern Finland, covering a population of 2.3 million people. There were differences in the characteristics of services between our study regions. In our data, 41% were classified as centralized, 37% as local without gatekeeping and 22% as local services with gatekeeping. The proportion of resources allocated to local services varied from 20% to 43%. Reclassifying ESMS-R is an easy way to compare the important local vs. centralized balance of MHS systems globally, where such data exists. Further international studies comparing systems and validating this approach are needed.

Comparison of small-area deprivation measures as predictors of chronic disease burden in a low-income population

Background

Measures of small-area deprivation may be valuable in geographically targeting limited resources to prevent, diagnose, and effectively manage chronic conditions in vulnerable populations. We developed a census-based small-area socioeconomic deprivation index specifically to predict chronic disease burden among publically insured Medicaid recipients in South Carolina, a relatively poor state in the southern United States. We compared the predictive ability of the new index with that of four other small-area deprivation indicators.

Methods

To derive the ZIP Code Tabulation Area-Level Palmetto Small-Area Deprivation Index (Palmetto SADI), we evaluated ten census variables across five socioeconomic deprivation domains, identifying the combination of census indicators most highly correlated with a set of five chronic disease conditions among South Carolina Medicaid enrollees. In separate validation studies, we used both logistic and spatial regression methods to assess the ability of Palmetto SADI to predict chronic disease burden among state Medicaid recipients relative to four alternative small-area socioeconomic deprivation measures: the Townsend index of material deprivation; a single-variable poverty indicator; and two small-area designations of health care resource deprivation, Primary Care Health Professional Shortage Area and Medically Underserved Area/Medically Underserved Population.

Results

Palmetto SADI was the best predictor of chronic disease burden (presence of at least one condition and presence of two or more conditions) among state Medicaid recipients compared to all alternative deprivation measures tested.

Conclusions

A low-cost, regionally optimized socioeconomic deprivation index, Palmetto SADI can be used to identify areas in South Carolina at high risk for chronic disease burden among Medicaid recipients and other low-income Medicaid-eligible populations for targeted prevention, screening, diagnosis, disease self-management, and care coordination activities.

Regional Deprivation Index and Socioeconomic Inequalities Related to Infant Deaths in Korea

Deprivation indices have been widely used to evaluate neighborhood socioeconomic status and therefore examine individuals within their regional context. Although some studies on the development of deprivation indices were conducted in Korea, additional research is needed to construct a more valid and reliable deprivation index. Therefore, a new deprivation index, named the K index, was constructed using principal component analysis. This index was compared with the Carstairs, Townsend and Choi indices. A possible association between infant death and deprivation was explored using the K index. The K index had a higher correlation with the infant mortality rate than did the other three indices. The regional deprivation quintiles were unequally distributed throughout the country. Despite the overall trend of gradually decreasing infant mortality rates, inequalities in infant deaths according to the deprivation quintiles persisted and widened. Despite its significance, the regional deprivation variable had a smaller effect on infant deaths than did individual variables. The K index functions as a deprivation index, and we may use this index to estimate the regional socioeconomic status in Korea. We found that inequalities in infant deaths according to the time trend persisted. To reduce the health inequalities among infants in Korea, regional deprivation should be considered.

Characterizing social environment's association with neurocognition using census and crime data linked to the Philadelphia Neurodevelopmental Cohort

BACKGROUND

The contribution of 'environment' has been investigated across diverse and multiple domains related to health. However, in the context of large-scale genomic studies the focus has been on obtaining individual-level endophenotypes with environment left for future decomposition. Geo-social research has indicated that environment-level variables can be reduced, and these composites can then be used with other variables as intuitive, precise representations of environment in research.

METHOD

Using a large community sample (N = 9498) from the Philadelphia area, participant addresses were linked to 2010 census and crime data. These were then factor analyzed (exploratory factor analysis; EFA) to arrive at social and criminal dimensions of participants' environments. These were used to calculate environment-level scores, which were merged with individual-level variables. We estimated an exploratory multilevel structural equation model (MSEM) exploring associations among environment- and individual-level variables in diverse communities.

RESULTS

The EFAs revealed that census data was best represented by two factors, one socioeconomic status and one household/language. Crime data was best represented by a single crime factor. The MSEM variables had good fit (e.g. comparative fit index = 0.98), and revealed that environment had the largest association with neurocognitive performance (β = 0.41, p < 0.0005), followed by parent education (β = 0.23, p < 0.0005).

CONCLUSIONS

Environment-level variables can be combined to create factor scores or composites for use in larger statistical models. Our results are consistent with literature indicating that individual-level socio-demographic characteristics (e.g. race and gender) and aspects of familial social capital (e.g. parental education) have statistical relationships with neurocognitive performance.

Developing a tool for mapping adult mental health care provision in Europe: the REMAST research protocol and its contribution to better integrated care

INTRODUCTION

Mental health care is a critical area to better understand integrated care and to pilot the different components of the integrated care model. However, there is an urgent need for better tools to compare and understand the context of integrated mental health care in Europe.

METHOD

The REMAST tool (REFINEMENT MApping Services Tool) combines a series of standardised health service research instruments and geographical information systems (GIS) to develop local atlases of mental health care from the perspective of horizontal and vertical integrated care. It contains five main sections: (a) Population Data; (b) the Verona Socio-economic Status (SES) Index; (c) the Mental Health System Checklist; (d) the Mental Health Services Inventory using the DESDE-LTC instrument; and (e) Geographical Data.

EXPECTED RESULTS

The REMAST tool facilitates context analysis in mental health by providing the comparative rates of mental health service provision according to the availability of main types of care; care placement capacity; workforce capacity; and geographical accessibility to services in the local areas in eight study areas in Austria, England, Finland, France, Italy, Norway, Romania and Spain.

DISCUSSION

The outcomes of this project will facilitate cooperative work and knowledge transfer on mental health care to the different agencies involved in mental health planning and provision. This project would improve the information to users and society on the available resources for mental health care and system thinking at the local level by the different stakeholders. The techniques used in this project and the knowledge generated could eventually be transferred to the mapping of other fields of integrated care.

Development of a Canadian socioeconomic status index for the study of health outcomes related to environmental pollution

Background

Socioeconomic status (SES) is an important determinant of health and potential modifier of the effects of environmental contaminants. There has been a lack of comprehensive indices for measuring overall SES in Canada. Here, a more comprehensive SES index is developed aiming to support future studies exploring health outcomes related to environmental pollution in Canada.

Methods

SES variables (n = 22, Census Canada 2006) were selected based on: cultural identities, housing characteristics, variables identified in Canadian environmental injustice studies and a previous deprivation index (Pampalon index). Principal component analysis with a single varimax rotation (factor loadings ≥ │60│) was performed on SES variables for 52974 census dissemination areas (DA). The final index was created by averaging the factor scores per DA according to the three components retained. The index was validated by examining its association with preterm birth (gestational age < 37 weeks), term low birth weight (LBW, <2500 g), small for gestational age (SGA, <10 percentile of birth weight for gestational age) and PM_2.5 (particulate matter ≤ 2.5 μm) exposures in Edmonton, Alberta (1999–2008).

Results

Index values exhibited a relatively normal distribution (median = 0.11, mean = 0.0, SD = 0.58) across Canada. Values in Alberta tended to be higher than in Newfoundland and Labrador, Northwest Territories and Nunavut (Pearson chi-square p < 0.001 across provinces). Lower quintiles of our index and the Pampalon’s index confirmed know associations with a higher prevalence of LBW, SGA, preterm birth and PM_2.5 exposure. Results with our index exhibited greater statistical significance and a more consistent gradient of PM_2.5 levels and prevalence of pregnancy outcomes.

Conclusions

Our index reflects more dimensions of SES than an earlier index and it performed superiorly in capturing gradients in prevalence of pregnancy outcomes. It can be used for future research involving environmental pollution and health in Canada.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-015-1992-y) contains supplementary material, which is available to authorized users.

Socioeconomic differentials in the immediate mortality effects of the national Irish smoking ban

BACKGROUND

Consistent evidence has demonstrated that smoking ban policies save lives, but impacts on health inequalities are uncertain as few studies have assessed post-ban effects by socioeconomic status (SES) and findings have been inconsistent. The aim of this study was to assess the effects of the national Irish smoking ban on ischemic heart disease (IHD), stroke, and chronic obstructive pulmonary disease (COPD) mortality by discrete and composite SES indicators to determine impacts on inequalities.

METHODS

Census data were used to assign frequencies of structural and material SES indicators to 34 local authorities across Ireland with a 2000-2010 study period. Discrete indicators were jointly analysed through principal component analysis to generate a composite index, with sensitivity analyses conducted by varying the included indicators. Poisson regression with interrupted time-series analysis was conducted to examine monthly age and gender-standardised mortality rates in the Irish population, ages ≥35 years, stratified by tertiles of SES indicators. All models were adjusted for time trend, season, influenza, and smoking prevalence.

RESULTS

Post-ban mortality reductions by structural SES indicators were concentrated in the most deprived tertile for all causes of death, while reductions by material SES indicators were more equitable across SES tertiles. The composite indices mirrored the results of the discrete indicators, demonstrating that post-ban mortality decreases were either greater or similar in the most deprived when compared to the least deprived for all causes of death.

CONCLUSIONS

Overall findings indicated that the national Irish smoking ban reduced inequalities in smoking-related mortality. Due to the higher rates of smoking-related mortality in the most deprived group, even equitable reductions across SES tertiles resulted in decreases in inequalities. The choice of SES indicator was influential in the measurement of effects, underscoring that a differentiated analytical approach aided in understanding the complexities in which structural and material factors influence mortality.

Prediction of community mental health service utilization by individual and ecological level socio-economic factors

Individuals with a more deprived socioeconomic status (SES) are more likely to have higher rates of psychiatric morbidity and use of psychiatric services. Such service use is also influenced by socioeconomic factors at the ecological level. The aim of this article is to investigate the influence of these variables on service utilization. All patients in contact with three Italian community psychiatric services (CPS) were included. Community and hospital contacts over 6 months were investigated. Socio-economic characteristics were described using a SES Index and two new Resources Accessibility Indexes. Low SES was found to be associated with more community service contacts. When other individual and ecological variables were controlled for, SES was negatively associated only with the number of home visits, which was about half the rate in deprived areas. An association between service utilization and the resources of the catchment area was also detected. The economic crisis in Europe is increasing inequality of access, so paying attention to SES characteristics at both the individual and the ecological levels is likely to become increasingly important in understanding patterns of psychiatric service utilization and planning care accordingly.

Lower socioeconomic status is associated with worse outcomes after both listing and transplanting children with heart failure

The relationship between SES and outcomes surrounding pediatric cardiac transplantation is complex and influenced by recipient race. Broad-based studies of SES have not been performed. A retrospective review of all 5125 primary pediatric heart transplants performed in the United States between 2000 and 2011. Patients were stratified by SES based on zip code of residence and U.S. census data (low SES: 1637; mid-SES: 2253; high SES: 1235). Survival following listing and transplantation was compared across strata. Risk-adjusted long-term mortality on the waitlist was higher among low SES patients (hazard 1.32, CI 1.07-1.63). The relationship between SES and outcomes varied by race. Early risk-adjusted post-transplant outcomes were worst among high SES patients (10.8% vs. low SES: 8.9%, p < 0.05). The incidence of non-compliance was higher among low SES patients (p < 0.0001). Long-term risk-adjusted patient survival was poorer among low (hazard 1.41, CI 1.10-1.80) and mid-SES (1.29, 1.04-1.59) groups. Low SES is associated with worse outcomes on both the waitlist and late following transplantation. Higher SES patients had more complex transplants with higher early mortality. Further research should be directed at identifying and addressing underlying causal factors for these disparities.

Regional variation in survival before and after pediatric heart transplantation--an analysis of the UNOS database

Geographic variation occurs in a variety of health outcomes. Regional influences on outcomes before and after listing for pediatric heart transplantation have not been assessed. Review of the UNOS dataset identified 5398 pediatric (≤ 18 years) patients listed for heart transplantation 2000-2011. Patients were stratified based on the region of listing. Regional-level variables were correlated with individual risk-adjusted outcomes. Mean time spent on the waitlist varied from 91.0 ± 163 days (Region 6 [R6]) to 248.1 ± 493 days (R4, p < 0.0001). Regions with more transplant centers (p < 0.0001) and fewer transplants (p = 0.0015) had higher waitlist mortality. Risk-adjusted individual waitlist mortality varied from 6.9% (R1, CI 6.2-7.8) to 19.2% (R5, CI 18.0-20.6). Waitlist mortality was higher for individuals awaiting transplant in regions with more listings per center (OR 1.04, CI 1.01-1.08) and lower in regions with more donors per center (OR 0.95, CI 0.90-0.99 per donor). Posttransplant risk-adjusted survival varied across regions (R4: 5.4%, CI 4.2-7.4; R7: 18.0%, CI 12.4-32.5), but regional variables were not correlated with outcomes. Outcomes among children undergoing heart transplantation vary by region. Factors leading to increased competition for donor allografts are associated with poorer waitlist survival. Equitable allocation of cardiac allografts requires further investigation of these findings.

A statistical procedure to create a neighborhood socioeconomic index for health inequalities analysis

Introduction

In order to study social health inequalities, contextual (or ecologic) data may constitute an appropriate alternative to individual socioeconomic characteristics. Indices can be used to summarize the multiple dimensions of the neighborhood socioeconomic status. This work proposes a statistical procedure to create a neighborhood socioeconomic index.

Methods

The study setting is composed of three French urban areas. Socioeconomic data at the census block scale come from the 1999 census. Successive principal components analyses are used to select variables and create the index. Both metropolitan area-specific and global indices are tested and compared. Socioeconomic categories are drawn with hierarchical clustering as a reference to determine “optimal” thresholds able to create categories along a one-dimensional index.

Results

Among the twenty variables finally selected in the index, 15 are common to the three metropolitan areas. The index explains at least 57% of the variance of these variables in each metropolitan area, with a contribution of more than 80% of the 15 common variables.

Conclusions

The proposed procedure is statistically justified and robust. It can be applied to multiple geographical areas or socioeconomic variables and provides meaningful information to public health bodies. We highlight the importance of the classification method. We propose an R package in order to use this procedure.

Is treatment adherence consistent across time, across different treatments and across diagnoses?

OBJECTIVE

The objective was to examine consistency of adherence across depression treatments and consistency of adherence between depression treatments and treatments for chronic medical illness.

METHODS

For 25,456 health plan members beginning psychotherapy for depression between 2003 and 2008, health plan records were used to examine adherence to all episodes of psychotherapy, antidepressant medication, antihypertensive medication and lipid-lowering medication.

RESULTS

Within treatments, adherence to psychotherapy in one episode predicted approximately 20% greater likelihood of subsequent psychotherapy adherence [odds ratio (OR)=2.20, 95% confidence interval (CI) 1.83-2.64]. Similarly, adherence to antidepressant medication in one episode predicted approximately 20% greater likelihood of subsequent antidepressant adherence (OR=1.99, 95% CI 1.74-2.28). Across treatments, adherence to antidepressant medication predicted approximately 10% greater likelihood of concurrent or subsequent adherence to psychotherapy (OR=1.52, 95% CI 1.42-1.63), a 4% greater likelihood of adherence to antihypertensive medication (OR=1.24, 95% CI 1.14-1.37) and a 3% greater likelihood of adherence to lipid-lowering medication (OR=1.16, 95% CI 1.03-1.32). Adherence to psychotherapy predicted a 2% greater likelihood of concurrent or subsequent adherence to antihypertensive medication (OR=1.11, 95% CI 1.04-1.19) and was not a significant predictor of adherence to lipid-lowering medication (OR=0.99, 95% CI 0.90-1.18).

CONCLUSIONS

Adherence is moderately consistent across episodes of depression treatment. Depression treatment adherence is a statistically significant, but relatively weak, predictor of adherence to antihypertensive or lipid-lowering medication.

Measuring socioeconomic inequality in the incidence of AIDS: rural-urban considerations

Low socioeconomic status (SES) influences the risk of acquiring human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and thus should be considered when analyzing HIV/AIDS surveillance data. Most surveillance systems do not collect individual level SES data but do collect residential ZIP code. We developed SES deprivation indices at the ZIP code tabulation area and assessed their predictive validity for AIDS incidence relative to individual neighborhood-level indicators in Florida using reliability analysis, factor analysis with principal component factorization, and structural equation modeling. For urban areas an index of poverty performed best, although the single factor poverty also performed well. For rural areas no index performed well, but the individual indicators of no access to a car and crowding performed well. In rural areas poverty was not associated with increased AIDS incidence. Users of HIV/AIDS surveillance data should consider urban and rural areas separately when assessing the impact of SES on AIDS incidence.

State of psychiatry in Italy 35 years after psychiatric reform. A critical appraisal of national and local data

Thirty-four years have elapsed since the passing of the Italian Law 180, the reform law that marked the transition from a hospital-based system of care to a model of community psychiatry that was designed to be an alternative to, rather than to complement, the old hospital-centred services. The main principle of Law 180 is that psychiatric patients have the right to be treated the same way as patients with other diseases and only voluntary treatments are allowed, with a few exceptions that are strictly regulated. The main features and consequences of the Italian reform are initially reviewed; national and local level experiences and epidemiological data are then analysed in order to highlight and disentangle the 'active ingredients' of the Italian experience. A public health attitude with the capacity to network good practice in service organization by giving voice to successful experiences and promoting health service research, apart from some local services, is still generally lacking. Furthermore, it is still difficult to provide an evidence-based reply to the question: can à l'Italienne community-care be exported elsewhere?

The difficult task of predicting the costs of community-based mental health care. A comprehensive case register study

BACKGROUND

Previous studies have attempted to forecast the costs of mental health care, using clinical and individual variables; the inclusion of ecological measures could improve the knowledge of predictors of psychiatric service utilisation and costs to support clinical and strategic decision-making.

METHODS

Using a Psychiatric Case Register (PCR), all patients with an ICD-10 psychiatric diagnosis, who had at least one contact with community-based psychiatric services in the Verona Health District, Northern Italy, were included in the study (N = 4558). For each patient, one year's total cost of care was calculated by merging service contact data with unit cost estimates and clinical and socio-demographic variables were collected. A socio-economic status (SES) index was developed, as a proxy of deprivation, using census data. Multilevel multiple regression models, considering socio-demographic and clinical characteristics of patients as well as socioeconomic local characteristics, were estimated to predict costs.

RESULTS

The mean annual cost for all patients was 2,606.11 Euros; patients with an ongoing episode of care and with psychosis presented higher mean costs. Previous psychiatric history represented the most significant predictor of cost (36.99% R2 increase) and diagnosis was also a significant predictor but explained only 4.96% of cost variance. Psychiatric costs were uniform throughout the Verona Health District and SES characteristics alone contributed towards less than 1% of the cost variance.

CONCLUSIONS

For all patients of community-based psychiatric services, a comprehensive model, including both patients' individual characteristics and socioeconomic local status, was able to predict 43% of variance in costs of care.

Information systems for mental health

The use of information systems and computer science applications in the health sector is now entrenched and widespread. In mental health services there are the typical applications of information systems concerning administrative, clinical and research issues, as well as innovative applications concerning diagnostic procedures, self-help, communication and delivery of psychotherapy.

A new multiple regression model to identify multi-family houses with a high prevalence of sick building symptoms "SBS", within the healthy sustainable house study in Stockholm (3H)

PURPOSES

The aim was to develop a new model to identify residential buildings with higher frequencies of "SBS" than expected, "risk buildings".

METHODS

In 2005, 481 multi-family buildings with 10,506 dwellings in Stockholm were studied by a new stratified random sampling. A standardised self-administered questionnaire was used to assess "SBS", atopy and personal factors. The response rate was 73%. Statistical analysis was performed by multiple logistic regressions.

RESULTS

Dwellers owning their building reported less "SBS" than those renting. There was a strong relationship between socio-economic factors and ownership. The regression model, ended up with high explanatory values for age, gender, atopy and ownership. Applying our model, 9% of all residential buildings in Stockholm were classified as "risk buildings" with the highest proportion in houses built 1961-1975 (26%) and lowest in houses built 1985-1990 (4%).

CONCLUSION

To identify "risk buildings", it is necessary to adjust for ownership and population characteristics.

[Social deprivation and mental health. Replicability and applicability in the Italian context of the resource allocation methods developed in the United Kingdom]

AIMS

Most of the available evidence on the relationship between socioeconomic indicators of social deprivation and patterns of use of mental health services has been produced in the United Kingdom, where the Ministry of Health has developed a resource allocation formula based upon the results of those studies. The main aim of the paper is to evaluate the replicability in the Italian context of such research, and of the resulting allocation strategies.

METHODS

Detailed description of the resource allocation method currently adopted in the United Kingdom, whose main purpose consists in reaching the best balance between available funding and patterns of need. Detailed description of resource allocation processes in Italy; discussion of the main methodological and statistical limitations restraining the replicability of the British formula in the Italian context.

CONCLUSIONS

There is a growing interest in Italy towards the introduction of evidence-based methods in health decision making, in order to correct the overwhelming influence of political issues. What is needed is a better understanding of the relationship between higher levels of equity in health services access, and their effects in terms of better outcomes.