Natural environments and suicide mortality in the Netherlands: a cross-sectional, ecological study

Background: Natural outdoor environments, such as green spaces (ie, grass, forests, or parks), blue spaces (ie, visible bodies of fresh or salt water), and coastal proximity, have been increasingly shown to promote mental health. However, little is known about how and the extent to which these natural environments are associated with suicide mortality. Our aim was to investigate whether the availability of green space and blue space within people's living environments and living next to the coast are protective against suicide mortality. Methods: In this cross-sectional, ecological study, we analysed officially confirmed deaths by suicide between 2005 and 2014 per municipality in the Netherlands. We calculated indexes to measure the proportion of green space and blue space per municipality and the coastal proximity of each municipality using a geographical information system. We fitted Bayesian hierarchical Poisson regressions to assess associations between suicide risk, green space, blue space, and coastal proximity, adjusted for risk and protective factors. Findings: Municipalities with a large proportion of green space (relative risk 0·879, 95% credibility interval 0·779–0·991) or a moderate proportion of green space (0·919, 0·846–0·998) showed a reduced suicide risk compared with municipalities with less green space. Green space did not differ according to urbanicity in relation to suicide. Neither blue space nor coastal proximity was associated with suicide risk. The geographical variation in the residual relative suicide risk was substantial and the south of the Netherlands was at high risk. Interpretation: Our findings support the notion that exposure to natural environments, particularly to greenery, might have a role in reducing suicide mortality. If confirmed by future studies on an individual level, the consideration of environmental exposures might enrich suicide prevention programmes

Multilevel Modelling for Public Health and Health Services Research

This open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) – a statistical technique being increasingly used in public health and health services research. The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the growing body of research that uses it, but also to recognise the limitations of research that did not use it. The volume also guides the analysis of real-life data sets by introducing and discussing the use of the multilevel modelling software MLwiN, the statistical package that is used with the example data sets. Importantly, the book also makes the training material accessible for download – not only the datasets analysed within the book, but also a freeware version of MLwiN to allow readers to work with these datasets. The book’s practical review of MLA comprises: Theoretical, conceptual, and methodological background Statistical background The modelling process and presentation of research Tutorials with example datasets Multilevel Modelling for Public Health and Health Services Research: Health in Context is a practical and timely resource for public health and health services researchers, statisticians interested in the relationships between contexts and behaviour, graduate students across these disciplines, and anyone interested in utilising multilevel modelling or multilevel analysis. “Leyland and Groenewegen’s wealth of teaching experience makes this book and its accompanying tutorials especially useful for a practical introduction to multilevel analysis.” ̶ Juan Merlo, Professor of Social Epidemiology, Lund University “Comprehensive and insightful. A must for anyone interested in the applications of multilevel modelling to population health”. ̶ S. (Subu) V. Subramanian, Professor of Population Health and Geography, Harvard University ; For researchers and students with a basic mastery of ordinary least squares and logistic regression Discusses multilevel analysis in context of public health, health services research, and epidemiology Includes an online component where users can download the datasets analyzed in the book, and also a freeware version of the multilevel modelling software MLwiN ​​​​​​​Can be used as part of a course on multilevel modelling, or as a self-training tex

Exploring the black box of quality improvement collaboratives: modelling relations between conditions, applied changes and outcomes

<p>Abstract</p> <p>Introduction</p> <p>Despite the popularity of quality improvement collaboratives (QICs) in different healthcare settings, relatively little is known about the implementation process. The objective of the current study is to learn more about relations between relevant conditions for successful implementation of QICs, applied changes, perceived successes, and actual outcomes.</p> <p>Methods</p> <p>Twenty-four Dutch hospitals participated in a dissemination programme based on QICs. A questionnaire was sent to 237 leaders of teams who joined 18 different QICs to measure changes in working methods and activities, overall perceived success, team organisation, and supportive conditions. Actual outcomes were extracted from a database with team performance indicator data. Multi-level analyses were conducted to test a number of hypothesised relations within the cross-classified hierarchical structure in which teams are nested within QICs and hospitals.</p> <p>Results</p> <p>Organisational and external change agent support is related positively to the number of changed working methods and activities that, if increased, lead to higher perceived success and indicator outcomes scores. Direct and indirect positive relations between conditions and perceived success could be confirmed. Relations between conditions and actual outcomes are weak. Multi-level analyses reveal significant differences in organisational support between hospitals. The relation between perceived successes and actual outcomes is present at QIC level but not at team level.</p> <p>Discussion</p> <p>Several of the expected relations between conditions, applied changes and outcomes, and perceived successes could be verified. However, because QICs vary in topic, approach, complexity, and promised advantages, further research is required: first, to understand why some QIC innovations fit better within the context of the units where they are implemented; second, to assess the influence of perceived success and actual outcomes on the further dissemination of projects over new patient groups.</p

Changes in health and primary health care use of Moroccan and Turkish migrants between 2001 and 2005: a longitudinal study

Background: Social environment and health status are related, and changes affecting social relations may also affect the general health state of a group. During the past few years, several events have affected the relationships between Muslim immigrants and the non-immigrant population in many countries. This study investigates whether the health status of the Moroccan and Turkish immigrants in the Netherlands has changed in four years, whether changes in health status have had any influence on primary health care use, and which socio-demographic factors might explain this relationship. Methods: A cohort of 108 Turkish and 102 Moroccan respondents were interviewed in 2001 and in 2005. The questionnaire included the SF-36 and the GP contact frequency (in the past two months). Interviews were conducted in the language preferred by the respondents. Data were analysed using multivariate linear regression. Results: The mental health of the Moroccan group improved between 2001 and 2005. Physical health remained unchanged for both groups. The number of GP contacts decreased with half a contact/2 months among the Turkish group. Significant predictors of physical health change were: age, educational level. For mental health change, these were: ethnicity, age, civil status, work situation in 2001, change in work situation. For change in GP contacts: ethnicity, age and change in mental and physical health. Conclusion: Changes in health status concerned the mental health component. Changes in health status were paired with changes in health care utilization. Among the Turkish group, an unexpected decrease in GP contacts was noticed, whilst showing a generally unchanged health status. Further research taking perceived quality of care into account might help shedding some light on this outcome.