Search

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.

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688–141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in 5-km buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to e300,000. The directions of associations were less consistent for walkability

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.

Objectives: The study aimed to assess whether psychological distress mediates the association between financial strain and oral health and dental attendance in the Dutch adult population.Methods: The study followed a cross-sectional design based on 2812 participants from the 2014 wave of the Dutch population-based GLOBE study. Financial strain was considered the exposure, while psychological distress measured with the Mental Health Inventory-5 (MHI-5) was the mediator. The outcomes included self-reported number of teeth, self-rated oral health, and self-reported dental attendance. Generalized regression analyses were used for the mediation analysis adjusted for several covariables. Results: Greater financial strain was significantly associated with poorer self-rated oral health (total effect: 0.09, 95%CI: 0.05; 0.14) and restorative or no dental attendance (i.e. participants never visiting a dentist or only visiting a dentist for regular treatments or when they have complaints with their mouth, teeth, or prosthesis) (total effect: 0.05, 95%CI: 0.02; 0.09). Greater financial strain was not significantly associated with self-reported number of teeth (total effect: −0.14, 95%CI: −0.91; 0.64). Psychological distress significantly mediated the association of financial strain with self-rated oral health (average causal mediation effect [ACME]: 0.02, 95%CI: 0.01; 0.03) and self-reported dental attendance (ACME: 0.01, 95%CI: 0.00; 0.02), respectively. However, it did not significantly mediate the association of financial strain with self-reported number of teeth (ACME: −0.11, 95%CI: −0.25; 0.02). The estimated proportion of the total effect of financial strain on self-rated oral health and self-reported dental attendance that could be explained by psychological distress was respectively 24% (95%CI: 14%; 48%) and 19% (95%CI: 6%; 62%). Conclusions: Psychological distress partly explains the associ

Introduction: In recent decades, there has been a rise in mental illnesses. Community infrastructures are increasingly acknowledged as important for sustaining good mental health. Moreover, green spaces are anticipated to offer advantages for both mental health and social cohesion. However, the mediating pathway between green space, social cohesion and mental health and especially the proximity and characteristics of green spaces that trigger these potential effects remain of interest. Methods: We gathered data from 1365 individuals on self-reported social cohesion and mental health across four satellite districts in European cities: Nantes (France), Porto (Portugal), Sofia (Bulgaria), and Høje-Taastrup (Denmark). Green space data from OpenStreetMap was manually adjusted using the PRIGSHARE guidelines. We used the AID-PRIGSHARE tool to generate 7 indicators about green space characteristics measured in distances from 100–1500 m, every 100 m. This resulted in 105 different green space variables that we tested in a single mediation model with structural equation modelling. Results: Accessible greenness (900–1400 m), accessible green spaces (900–1500 m), accessible green space corridors (300–800 m), accessible total green space (300−800), and mix of green space uses (700–1100 m) were significantly associated with social cohesion and indirectly with mental health. Green corridors also showed negative indirect and direct associations with mental health in larger distances. Surrounding greenness and the quantity of green space uses were not associated with social cohesion nor indirectly with mental health. We also observed no positive direct associations between any green space variable in any distance to mental health. Conclusions: Our results suggest that accessibility, connectivity, mix of use and proximity are key characteristics that drive the relationship between green spaces, social cohesion and mental health. This gives further guidance to urban planners and de, Heritage & Architecture, Environmental Technology and Design

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 c, Heritage & Architecture, Environmental Technology and Design

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 c

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.

Introduction: In recent decades, there has been a rise in mental illnesses. Community infrastructures are increasingly acknowledged as important for sustaining good mental health. Moreover, green spaces are anticipated to offer advantages for both mental health and social cohesion. However, the mediating pathway between green space, social cohesion and mental health and especially the proximity and characteristics of green spaces that trigger these potential effects remain of interest. Methods: We gathered data from 1365 individuals on self-reported social cohesion and mental health across four satellite districts in European cities: Nantes (France), Porto (Portugal), Sofia (Bulgaria), and Høje-Taastrup (Denmark). Green space data from OpenStreetMap was manually adjusted using the PRIGSHARE guidelines. We used the AID-PRIGSHARE tool to generate 7 indicators about green space characteristics measured in distances from 100–1500 m, every 100 m. This resulted in 105 different green space variables that we tested in a single mediation model with structural equation modelling. Results: Accessible greenness (900–1400 m), accessible green spaces (900–1500 m), accessible green space corridors (300–800 m), accessible total green space (300−800), and mix of green space uses (700–1100 m) were significantly associated with social cohesion and indirectly with mental health. Green corridors also showed negative indirect and direct associations with mental health in larger distances. Surrounding greenness and the quantity of green space uses were not associated with social cohesion nor indirectly with mental health. We also observed no positive direct associations between any green space variable in any distance to mental health. Conclusions: Our results suggest that accessibility, connectivity, mix of use and proximity are key characteristics that drive the relationship between green spaces, social cohesion and mental health. This gives further guidance to urban planners and de

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.

In the interdisciplinary field of green space health research, there is a demand to reduce the effort to assess green space, especially for non-spatial disciplines. To address this issue, we developed AID-PRIGSHARE, an open-source script that automates over 400 QGIS processes to substantially reduces the time-intensive task of generating green space indicators. AID-PRIGSHARE calculates greenness, public green space, access to green infrastructure, and green space uses within distances of 100–1500 m around geolocations. This substantially reduces the effort for sensitivity analysis and may provide support for research that aims to understand the impact of different green space features and distances on health outcomes., Heritage & Architecture, Environmental Technology and Design

In the interdisciplinary field of green space health research, there is a demand to reduce the effort to assess green space, especially for non-spatial disciplines. To address this issue, we developed AID-PRIGSHARE, an open-source script that automates over 400 QGIS processes to substantially reduces the time-intensive task of generating green space indicators. AID-PRIGSHARE calculates greenness, public green space, access to green infrastructure, and green space uses within distances of 100–1500 m around geolocations. This substantially reduces the effort for sensitivity analysis and may provide support for research that aims to understand the impact of different green space features and distances on health outcomes.

The relationship between green spaces and health is attracting more and more societal and research interest. The research field is however still suffering from its differing monodisciplinary origins. Now in a multidisciplinary environment on its way to a truly interdisciplinary field, there is a need for a common understanding, precision in green space indicators, and coherent assessment of the complexity of daily living environments. In several reviews, common protocols and open-source scripts are considered a high priority to advance the field. Realizing these issues, we developed PRIGSHARE (Preferred Reporting Items in Greenspace Health Research). It is accompanied by an open-source script that supports non-spatial disciplines in assessing greenness and green space on different scales and types. The PRIGSHARE checklist contains 21 items that have been identified as a risk of bias and are necessary for understanding and comparison of studies. The checklist is divided into the following topics: objectives (3 items), scope (3 items), spatial assessment (7 items), vegetation assessment (4 items), and context assessment (4 items). For each item, we include a pathway-specific (if relevant) rationale and explanation. The PRIGSHARE guiding principles should be helpful to support a high-quality assessment and synchronize the studies in the field while acknowledging the diversity of study designs., Heritage & Architecture, Environmental Technology and Design

In their paper, published in this journal, Dijkstra & Horstman critically reflect on a selection of social epidemiological articles and examine how low socioeconomic status populations are constructed in these articles. They identify four components which they argue represent the “dominant thought style” of this literature: 1) proliferation, 2) generalization, 3) problematization and 4) individualization. We largely agree with their first two points, but strongly disagree with the other two, and explain why in our reply. All in all, we believe that their analysis is a wake-up call for social epidemiologists, rightly pointing to the risk that the relevance and moral origins of the use and study of categories, like ‘low socioeconomic status’, can easily become less visible, and therefore should be articulated and explained every time.

This study examined whether changes in green space within the living environment were associated with changes in walking and cycling frequencies in a cohort of 3,220 Dutch adults between 2004, 2011 and 2014. Data on self-reported weekly time spent walking and cycling for active commute and leisure were linked to geographic information system (GIS) measures of total green areas within 1000 m buffer zones around each participant's home address, and distance to the nearest green space. First, cross-sectional linear regression models showed no statistically significant associations between green space measures and walking and cycling. Second, fixed effects (FE) models were used to analyze whether changes in green space were associated with changes in walking and cycling, using longitudinal data from respondents who did not relocate over time. As distance to the nearest green area increased by 100 m, individuals spent 22.76 fewer (95% CI: -39.92, -5.60) minutes walking for leisure per week and 3.21 more (95% CI: 0.46, 5.96) minutes walking for active commute. Changes in distance to green space were not significantly related to changes in cycling measures. No clear associations between changes in green areas within 1000 m buffers and changes in walking and cycling were observed. Overall, there was weak evidence of an effect of changes in green space area on changes in walking, and no evidence for cycling.