Environmental components of childhood obesity prevention interventions: an overview of systematic reviews.

Childhood obesity has a complex multi-factorial aetiology grounded in environmental and individual level factors that affect behaviour and outcomes. An ecological, systems-based approach to addressing childhood obesity is increasingly being advocated. The primary aim of this review is to summarize the evidence reported in systematic reviews on the effectiveness of population-level childhood obesity prevention interventions that have an environmental component. We conducted a systematic review of reviews published since 1995, employing a standardized search strategy in nine databases. Inclusion criteria required that reviews be systematic and evaluated at least one population-level, environmental intervention in any setting aimed at preventing or reducing obesity in children (5-18 years). Sixty-three reviews were included, ten of which were of high quality. Results show modest impact of a broad range of environmental strategies on anthropometric outcomes. Systematic reviews vary in methodological quality, and not all relevant primary studies may be included in each review. To ensure relevance of our findings to practice, we also report on relevant underlying primary studies, providing policy-relevant recommendations based on the evidence reviewed. Greater standardization of review methods and reporting structures will benefit policymakers and public health professionals seeking informed decision-making

[Accepted Manuscript] Towards a new model of evidence for public health

BackgroundWe are faced with a growing crisis of non-communicable diseases driven by factors such as unhealthy diets, physical inactivity, tobacco use, and alcohol consumption, compounded by major inequalities in health. Over recent decades, biomedical research methods have helped to answer many important questions about treatment and prevention, but the kinds of tools that can tell us which intervention to choose over another are not invariably the most appropriate to address complex challenges such as designing healthier cities, or creating healthier, more sustainable food systems. The aim of this project was to identify the main obstacles to obtaining valid and appropriate evidence to guide public health decision making, and propose a set of solutions to address these problems

The HADES Tracking System

The tracking system of the dielectron spectrometer HADES at GSI Darmstadt is formed out of 24 low-mass, trapezoidal multi-layer drift chambers providing in total about 30 square meter of active area. Low multiple scattering in the in total four planes of drift chambers before and after the magnetic field is ensured by using helium-based gas mixtures and aluminum cathode and field wires. First in-beam performance results are contrasted with expectations from simulations. Emphasis is placed on the energy loss information, exploring its relevance regarding track recognition.Comment: 6 pages, 4 figures, presented at the 10th Vienna Conference on Instrumentation, Vienna, February 2004, to be published in NIM A (special issue

Neighbourhood social capital: measurement issues and associations with health outcomes.

We compared ecometric neighbourhood scores of social capital (contextual variation) to mean neighbourhood scores (individual and contextual variation), using several health-related outcomes (i.e. self-rated health, weight status and obesity-related behaviours). Data were analysed from 5,900 participants in the European SPOTLIGHT survey. Factor analysis of the 13-item social capital scale revealed two social capital constructs: social networks and social cohesion. The associations of ecometric and mean neighbourhood-level scores of these constructs with self-rated health, weight status and obesity-related behaviours were analysed using multilevel regression analyses, adjusted for key covariates. Analyses using ecometric and mean neighbourhood scores, but not mean neighbourhood scores adjusted for individual scores, yielded similar regression coefficients. Higher levels of social network and social cohesion were not only associated with better self-rated health, lower odds of obesity and higher fruit consumption, but also with prolonged sitting and less transport-related physical activity. Only associations with transport-related physical activity and sedentary behaviours were associated with mean neighbourhood scores adjusted for individual scores. As analyses using ecometric scores generated the same results as using mean neighbourhood scores, but different results when using mean neighbourhood scores adjusted for individual scores, this suggests that the theoretical advantage of the ecometric approach (i.e. teasing out individual and contextual variation) may not be achieved in practice. The different operationalisations of social network and social cohesion were associated with several health outcomes, but the constructs that appeared to represent the contextual variation best were only associated with two of the outcomes

Exploring why residents of socioeconomically deprived neighbourhoods have less favourable perceptions of their neighbourhood environment than residents of wealthy neighbourhoods.

Residents of socioeconomically deprived areas perceive their neighbourhood as less conducive to healthy behaviours than residents of more affluent areas. Whether these unfavourable perceptions are based on objective neighbourhood features or other factors is poorly understood. We examined individual and contextual correlates of socioeconomic inequalities in neighbourhood perceptions across five urban regions in Europe. Data were analysed from 5205 participants of the SPOTLIGHT survey. Participants reported perceptions of their neighbourhood environment with regard to aesthetics, safety, the presence of destinations and functionality of the neighbourhood, which were summed into an overall neighbourhood perceptions score. Multivariable multilevel regression analyses were conducted to investigate whether the following factors were associated with socioeconomic inequalities in neighbourhood perceptions: objectively observed neighbourhood features, neighbourhood social capital, exposure to the neighbourhood, self-rated health and lifestyle behaviours. Objectively observed traffic safety, aesthetics and the presence of destinations in the neighbourhood explained around 15% of differences in neighbourhood perceptions between residents of high and low neighbourhoods; levels of neighbourhood social cohesion explained around 52%. Exposure to the neighbourhood, self-rated health and lifestyle behaviours were significant correlates of neighbourhood perceptions but did not contribute to socioeconomic differences. This cross-European study provided evidence that socioeconomic differences in neighbourhood perceptions are not only associated with objective neighbourhood features but also with social cohesion. Levels of physical activity, sleep duration, self-rated health, happiness and neighbourhood preference were also associated with neighbourhood perceptions

A systematic review on health resilience to economic crises

Background The health effects of recent economic crises differ markedly by population group. The objective of this systematic review is to examine evidence from longitudinal studies on factors influencing resilience for any health outcome or health behaviour among the general population living in countries exposed to financial crises. Methods We systematically reviewed studies from six electronic databases (EMBASE, Global Health, MEDLINE, PsycINFO, Scopus, Web of Science) which used quantitative longitudinal study designs and included: (i) exposure to an economic crisis; (ii) changes in health outcomes/behaviours over time; (iii) statistical tests of associations of health risk and/or protective factors with health outcomes/behaviours. The quality of the selected studies was appraised using the Quality Assessment Tool for Quantitative Studies. PRISMA reporting guidelines were followed. Results From 14,584 retrieved records, 22 studies met the eligibility criteria. These studies were conducted across 10 countries in Asia, Europe and North America over the past two decades. Ten socio-demographic factors that increased or protected against health risk were identified: gender, age, education, marital status, household size, employment/occupation, income/ financial constraints, personal beliefs, health status, area of residence, and social relations. These studies addressed physical health, mortality, suicide and suicide attempts, mental health, and health behaviours. Women’s mental health appeared more susceptible to crises than men’s. Lower income levels were associated with greater increases in cardiovascular disease, mortality and worse mental health. Employment status was associated with changes in mental health. Associations with age, marital status, and education were less consistent, although higher education was associated with healthier behaviours. Conclusions Despite widespread rhetoric about the importance of resilience, there was a dearth of studies which operationalised resilience factors. Future conceptual and empirical research is needed to develop the epidemiology of resilience

Neighbourhood typology based on virtual audit of environmental obesogenic characteristics.

Virtual audit (using tools such as Google Street View) can help assess multiple characteristics of the physical environment. This exposure assessment can then be associated with health outcomes such as obesity. Strengths of virtual audit include collection of large amount of data, from various geographical contexts, following standard protocols. Using data from a virtual audit of obesity-related features carried out in five urban European regions, the current study aimed to (i) describe this international virtual audit dataset and (ii) identify neighbourhood patterns that can synthesize the complexity of such data and compare patterns across regions. Data were obtained from 4,486 street segments across urban regions in Belgium, France, Hungary, the Netherlands and the UK. We used multiple factor analysis and hierarchical clustering on principal components to build a typology of neighbourhoods and to identify similar/dissimilar neighbourhoods, regardless of region. Four neighbourhood clusters emerged, which differed in terms of food environment, recreational facilities and active mobility features, i.e. the three indicators derived from factor analysis. Clusters were unequally distributed across urban regions. Neighbourhoods mostly characterized by a high level of outdoor recreational facilities were predominantly located in Greater London, whereas neighbourhoods characterized by high urban density and large amounts of food outlets were mostly located in Paris. Neighbourhoods in the Randstad conurbation, Ghent and Budapest appeared to be very similar, characterized by relatively lower residential densities, greener areas and a very low percentage of streets offering food and recreational facility items. These results provide multidimensional constructs of obesogenic characteristics that may help target at-risk neighbourhoods more effectively than isolated features

Exploring why residents of socioeconomically deprived neighbourhoods have less favourable perceptions of their neighbourhood environment than residents of wealthy neighbourhoods

Residents of socioeconomically deprived areas perceive their neighbourhood as less conducive to healthy behaviours than residents of more affluent areas. Whether these unfavourable perceptions are based on objective neighbourhood features or other factors is poorly understood. We examined individual and contextual correlates of socioeconomic inequalities in neighbourhood perceptions across five urban regions in Europe. Data were analysed from 5205 participants of the SPOTLIGHT survey. Participants reported perceptions of their neighbourhood environment with regard to aesthetics, safety, the presence of destinations and functionality of the neighbourhood, which were summed into an overall neighbourhood perceptions score. Multivariable multilevel regression analyses were conducted to investigate whether the following factors were associated with socioeconomic inequalities in neighbourhood perceptions: objectively observed neighbourhood features, neighbourhood social capital, exposure to the neighbourhood, self-rated health and lifestyle behaviours. Objectively observed traffic safety, aesthetics and the presence of destinations in the neighbourhood explained around 15% of differences in neighbourhood perceptions between residents of high and low neighbourhoods; levels of neighbourhood social cohesion explained around 52%. Exposure to the neighbourhood, self-rated health and lifestyle behaviours were significant correlates of neighbourhood perceptions but did not contribute to socioeconomic differences. This cross-European study provided evidence that socioeconomic differences in neighbourhood perceptions are not only associated with objective neighbourhood features but also with social cohesion. Levels of physical activity, sleep duration, self-rated health, happiness and neighbourhood preference were also associated with neighbourhood perceptions

Mismatch between perceived and objectively measured environmental obesogenic features in European neighbourhoods.

Findings from research on the association between the built environment and obesity remain equivocal but may be partly explained by differences in approaches used to characterize the built environment. Findings obtained using subjective measures may differ substantially from those measured objectively. We investigated the agreement between perceived and objectively measured obesogenic environmental features to assess (1) the extent of agreement between individual perceptions and observable characteristics of the environment and (2) the agreement between aggregated perceptions and observable characteristics, and whether this varied by type of characteristic, region or neighbourhood. Cross-sectional data from the SPOTLIGHT project (n = 6037 participants from 60 neighbourhoods in five European urban regions) were used. Residents' perceptions were self-reported, and objectively measured environmental features were obtained by a virtual audit using Google Street View. Percent agreement and Kappa statistics were calculated. The mismatch was quantified at neighbourhood level by a distance metric derived from a factor map. The extent to which the mismatch metric varied by region and neighbourhood was examined using linear regression models. Overall, agreement was moderate (agreement < 82%, kappa < 0.3) and varied by obesogenic environmental feature, region and neighbourhood. Highest agreement was found for food outlets and outdoor recreational facilities, and lowest agreement was obtained for aesthetics. In general, a better match was observed in high-residential density neighbourhoods characterized by a high density of food outlets and recreational facilities. Future studies should combine perceived and objectively measured built environment qualities to better understand the potential impact of the built environment on health, particularly in low residential density neighbourhoods

Self-defined residential neighbourhoods: size variations and correlates across five European urban regions.

The neighbourhood is recognized as an important unit of analysis in research on the relation between obesogenic environments and development of obesity. One important challenge is to define the limits of the residential neighbourhood, as perceived by study participants themselves, in order to improve our understanding of the interaction between contextual features and patterns of obesity. An innovative tool was developed in the framework of the SPOTLIGHT project to identify the boundaries of neighbourhoods as defined by participants in five European urban regions. The aims of this study were (i) to describe self-defined neighbourhood (size and overlap with predefined residential area) according to the characteristics of the sampling administrative neighbourhoods (residential density and socioeconomic status) within the five study regions and (ii) to determine which individual or/and environmental factors are associated with variations in size of self-defined neighbourhoods. Self-defined neighbourhood size varies according to both individual factors (age, educational level, length of residence and attachment to neighbourhood) and contextual factors. These findings have consequences for how residential neighbourhoods are defined and operationalized and can inform how self-defined neighbourhoods may be used in research on associations between contextual characteristics and health outcomes such as obesity