Urban green spaces, self-rated air pollution and health:A sensitivity analysis of green space characteristics and proximity in four European cities

Exploring the influence of green space characteristics and proximity on health via air pollution mitigation, our study analysed data from 1,365 participants across Porto, Nantes, Sofia, and Høje-Taastrup. Utilizing OpenStreetMap and the AID-PRIGSHARE tool, we generated nine green space indicators around residential addresses at 15 distances, ranging from 100m to 1500m. We performed a mediation analysis for these 135 green space variables and revealed significant associations between self-rated air pollution and self-rated health for specific green space characteristics. In our study, indirect positive effects on health via air pollution were mainly associated with green corridors in intermediate Euclidean distances (800-1,000m) and the amount of accessible green spaces in larger network distances (1,400–1,500m). Our results suggest that the amount of connected green spaces measured in intermediate surroundings seems to be a prime green space characteristic that could drive the air pollution mitigation pathway to health.</p

The relation between proximity to and characteristics of green spaces to physical activity and health:A multi-dimensional sensitivity analysis in four European cities

Introduction: Non-communicable diseases are the global disease burden of our time, with physical inactivity identified as one major risk factor. Green spaces are associated with increased physical activity of nearby residents. But there are still gaps in understanding which proximity and what characteristics of green spaces can trigger physical activity. This study aims to unveil these differences with a rigorous sensitivity analysis. Methods: We gathered data on self-reported health and physical activity from 1365 participants in selected neighbourhoods in Porto, Nantes, Sofia, and Høje-Taastrup. Spatial data were retrieved from OpenStreetMap. We followed the PRIGSHARE guidelines to control for bias. Around the residential addresses, we generated seven different green space indicators for 15 distances (100–1500 m) using the AID-PRIGSHARE tool. We then analysed each of these 105 green space indicators together with physical activity and health in 105 adjusted structural equation models. Results: Green space accessibility and green space uses indicators showed a pattern of significant positive associations to physical activity and indirect to health at distances of 1100 m or less, with a peak at 600 m for most indicators. Greenness in close proximity (100 m) had significant positive effects on physical activity and indirect effects on health. Surrounding greenness showed positive direct effects on health at 500–1100 m and so do green corridors in 800 m network distance. In contrast, a high quantity of green space uses, and surrounding greenness measured in a larger radius (1100–1500 m) showed a negative relationship with physical activity and indirect health effects. Conclusions: Our results provide insight into how green space characteristics can influence health at different scales, with important implications for urban planners on how to integrate accessible green spaces into urban structures and public health decision-makers on the ability of green spaces to combat physical inactivity.</p

Sports participation, perceived neighborhood safety, and individual cognitions: how do they interact?

After publication of this work [Beenackers et al: Int J Behav Nutr Phys Act 2011, 8:76] it was realized that formula 3 and formula 4 in the Statistical Analysis section of the Methods were incorrectly listed. Since the formulas were correctly used in the analysis, this correction does not affect the results or conclusions of the paper

Longitudinal study of changes in greenness exposure, physical activity and sedentary behavior in the ORISCAV-LUX cohort study

Background: Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007–2017, n = 628). Methods: The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants’ exact residential address. Results: Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = − 2.60, 95% CI − 4.75; − 0.44), and negative between-individual associations of GLUM and PA (β = − 2.02, 95% CI − 3.73; − 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer. Discussion: Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its’ different associations with PA and SB.</p

Longitudinal study of changes in greenness exposure, physical activity and sedentary behavior in the ORISCAV-LUX cohort study

Background: Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007–2017, n = 628). Methods: The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants’ exact residential address. Results: Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = − 2.60, 95% CI − 4.75; − 0.44), and negative between-individual associations of GLUM and PA (β = − 2.02, 95% CI − 3.73; − 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer. Discussion: Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its’ different associations with PA and SB.</p

Urban densification in the Netherlands and its impact on mental health:An expert-based causal loop diagram

Urban densification is a key strategy to accommodate rapid urban population growth, but emerging evidence suggests serious risks of urban densification for individuals’ mental health. To better understand the complex pathways from urban densification to mental health, we integrated interdisciplinary expert knowledge in a causal loop diagram via group model building techniques. Six subsystems were identified: five subsystems describing mechanisms on how changes in the urban system caused by urban densification may impact mental health, and one showing how changes in mental health may alter urban densification. The new insights can help to develop resilient, healthier cities for all.</p

Urban densification in the Netherlands and its impact on mental health:An expert-based causal loop diagram

Urban densification is a key strategy to accommodate rapid urban population growth, but emerging evidence suggests serious risks of urban densification for individuals’ mental health. To better understand the complex pathways from urban densification to mental health, we integrated interdisciplinary expert knowledge in a causal loop diagram via group model building techniques. Six subsystems were identified: five subsystems describing mechanisms on how changes in the urban system caused by urban densification may impact mental health, and one showing how changes in mental health may alter urban densification. The new insights can help to develop resilient, healthier cities for all.</p

Overview of retrospective data harmonisation in the MINDMAP project : process and results

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Urban densification in the Netherlands and its impact on mental health: An expert-based causal loop diagram

Urban densification is a key strategy to accommodate rapid urban population growth, but emerging evidence suggests serious risks of urban densification for individuals’ mental health. To better understand the complex pathways from urban densification to mental health, we integrated interdisciplinary expert knowledge in a causal loop diagram via group model building techniques. Six subsystems were identified: five subsystems describing mechanisms on how changes in the urban system caused by urban densification may impact mental health, and one showing how changes in mental health may alter urban densification. The new insights can help to develop resilient, healthier cities for all

Do financial constraint and perceived stress modify the effects of food tax schemes on food purchases: moderation analyses in a virtual supermarket experiment

Objective: To investigate whether financial constraint and perceived stress modify the effects of food-related taxes on the healthiness of food purchases. Design: Moderation analyses were conducted with data from a trial where participants were randomly exposed to: a control condition with regular food prices, an sugar-sweetened beverage (SSB) tax condition with a two-tiered levy on the sugar content in SSB (5-8 g/100 ml: €0·21 per l and ≥8 g/100 ml: €0·28 per l) or a nutrient profiling tax condition where products with Nutri-Score D or E were taxed at a 20 percent level. Outcome measures were overall healthiness of food purchases (%), energy content (kcal) and SSB purchases (litres). Effect modification was analysed by adding interaction terms between conditions and self-reported financial constraint or perceived stress in regression models. Outcomes for each combination of condition and level of effect modifier were visualised. Setting: Virtual supermarket. Participants: Dutch adults (n 386). Results: Financial constraint or perceived stress did not significantly modify the effects of food-related taxes on the outcomes. Descriptive analyses suggest that in the control condition, the overall healthiness of food purchases was lowest, and SSB purchases were highest among those with moderate/high levels of financial constraint. Compared with the control condition, in a nutrient profiling tax condition, the overall healthiness of food purchases was higher and SSB purchases were lower, especially among those with moderate/high levels of financial constraint. Such patterns were not observed for perceived stress. Conclusion: Further studies with larger samples are recommended to assess whether food-related taxes differentially affect food purchases of subgroups