Health & Place

Urban mobility may provide insight into population health by capturing how residents connect to services, resources, and urban systems. This is relevant for communities facing higher disease burden and limited resources, where reduced connectivity may signal barriers to care, healthy environments, and participation. Mobility patterns are furthermore shaped by socioeconomic position, housing, environmental quality, facilities access, lifestyle patterns, and population composition. Mobility-health associations may therefore reflect underlying social and environmental disadvantage rather than mobility itself, risking misdirected public-health policy responses. This ecological cross-sectional study examined associations between aggregated mobile phone-based mobility and health outcomes in The Hague, Netherlands, from January-July 2019. Mobile phone mobility was measured as mean outgoing mobility distance across eight regions. Contextual and health indicators were available at neighbourhood-level and were aggregated or linked to regions where required. Health outcomes were operationalised as indicators of disease burden, including cardiometabolic medication prescriptions, polypharmacy, and a syndemic-based measure of interacting health conditions. Contextual domains were selected using spatial clustering and ordinary least squares models, after which residual mobility-health associations were assessed. Outgoing mobility varied across regions and was strongly patterned by contextual factors. Lifestyle, housing, physical environment, and income accounted for 73.2% of variance in outgoing mobility. After adjustment, residual mobility showed weak, non-significant associations with cardiometabolic medication prescription, polypharmacy, and the syndemic-based measure. Sensitivity analyses supported these findings. Aggregated mobility should not be interpreted as a straightforward independent determinant of health. Instead, it appears to function as an integrative marker of urban context, spatial structure, and population composition.

Summary Background: Spatial variation in heat-related mortality remains poorly understood, particularly at fine geographical scales. We conducted a nationwide small-area study to examine the association between spatial variation in heat-related mortality and environmental, demographic, health, and socio-economic factors. Methods: We obtained daily all-cause mortality data for people aged [≥] 65 years during the summers of 2011-2023 and linked them with municipality-level daily temperature estimates from the ERA5-Land reanalysis dataset. We applied a two-stage Bayesian hierarchical model to estimate small-area heat-related mortality and assess the contribution of community characteristics to spatial variability. Findings: Heat-related mortality showed marked geographical differences, with the highest rates in southern and southeastern Italy. Across municipalities, the relative risk at the 90th temperature percentile, relative to the minimum mortality temperature, ranged from 1.06 to 1.33. The heat-attributable fraction exceeded 6% in several southern municipalities, while excess mortality surpassed 8 deaths per 1,000 inhabitants in parts of the Po Valley, Tuscany, Apulia, and Sicily. National heat-attributable mortality peaked in 2022, with an estimated 17,828 deaths (95% credible intervals: 17,339, 18,285) among older adults. Municipalities with higher average temperatures, less green space, higher obesity prevalence, and more residents aged [≥] 85 years had higher heat-related mortality. Educational attainment and employment were among the strongest modifiers of spatial variation. Interpretation: Our findings highlight substantial small-area differences in heat-related mortality across Italy and identify socio-economic deprivation as a key determinant of vulnerability. Heat is likely to disproportionately affect disadvantaged communities, reinforcing the need for adaptation strategies addressing social inequality. Funding: Imperial College Research Fellowship; Italian Ministry of Health PNC (CUP J55I22004450001); NIHR Imperial Biomedical Research Center (BRC NIHR203323).

HighlightsO_LIHealth inequalities have widened over 15 years, favouring high-income groups C_LIO_LIInequality in physical activity & mental health widened the most pre-intervention C_LIO_LIPost-intervention, inequalities persisted but stayed relatively unchanged. C_LIO_LILong-term illness and unemployment were key drivers of inequality C_LIO_LIThe greenway may have slowed down the inequality widening but the impact is limited C_LI BackgroundEvidence concerning health inequalities following urban green and blue space UGBS) interventions is limited. This study examined the changes in health inequalities after a major urban regeneration project, the Connswater Community Greenway (CCG), in Belfast, UK. MethodCross-sectional household surveys were conducted in 2010/11 (baseline), 2017/18 (immediately after completion), and 2023/24 (long-term follow-up) with a sample of approximately 1,000 adults each wave. Using concentration indices (CI), income-related health inequalities for three outcomes (physical activity, mental wellbeing and quality of life) were measured. A regression-based decomposition of concentration index examined the contribution of sociodemographic factors to the observed inequalities underpinning each outcome over time. ResultsAcross three waves, there was widening of inequalities over the 15-year period across all three health outcomes, with those from high-income groups reported higher levels of physical activity (CI=0.33, SE=0.026), better mental wellbeing (CI=0.03, SE=0.003), and better quality of life (CI=0.09, SE=0.008). The widening inequalities mainly occurred during the construction phase of CCG (2010-2017) and remained stable post-intervention (2017-2023). Decomposition analysis revealed that the pro-poor concentration of long-term illness and unemployment was the key driver that together explained approximately 51%-76% of the inequalities. ConclusionThe CCG was limited in reducing health inequalities which were mainly driven by long-term illness and unemployment - factors beyond the direct scope of the UGBS intervention - resulting in low-income groups likely to fall further behind the wealthier groups. The widening of inequality is consistent with findings from other public interventions that did not have a primary equity focus.

ObjectiveTo determine the extent of inequitable distributions in green space qualities in urban areas of Australia. MethodExisting data from the cities of Sydney, Newcastle, and Wollongong in Australia was used to define green space qualities relating to accessibility, amenities/activities, beaches/coastline, biodiversity, incivilities, landcover and land use. Green space qualities were measured within multiple-scale network distance buffers for residential mesh blocks and linked with the Australian Bureau of Statistics Index of Relative Socio-economic Disadvantage (IRSD). Correlations were analysed using Spearmans rank correlation coefficient between IRSD score (reversed; higher scores are more disadvantaged) and green space qualities aggregated over mesh blocks. Influence of IRSD, population density and random effects of population structures were examined using single-level and multilevel models. Spatial patterns and clusters were identified through choropleth maps and hot spot analyses. ResultsAt the 1600m scale, more disadvantaged areas tended to have green spaces with lower percentages of nearby street trees to roads (Rho=-0.52, p[≤]0.001), lower percentages of slope >6{degrees} (Rho=-0.49), lower likelihood of threatened mammal species/habitat occurrences (Rho=-0.47), and lower percentages of tree canopy (Rho=-0.46). More disadvantaged areas tended to have green spaces with higher percentages of open grass (Rho=0.38, p[≤]0.001) and bare earth (Rho=0.33, p[≤]0.001) and higher densities of robberies (Rho=0.34, p[≤]0.001). For selected qualities, multilevel models tended to support the relationships that were found using Spearmans rank correlation. DiscussionSocioeconomic inequities in tree canopy, biodiversity and incivilities are present for green spaces in large and mid-sized Australian cities.

IntroductionObesity and related health conditions are unevenly distributed across neighborhoods, often co-occuring with multiple health challenges and socioeconomic disadvantages. Using an ecosyndemic framework, which integrates ecological and social dimensions that contribute to the clustering of health problems, this study examines how adverse obesity-related health outcomes spatially cluster in relation to obesogenic environments and socioeconomic position (SEP) across Dutch neighborhoods. MethodsNationwide neighborhood-level data on health outcomes, obesogenic environmental exposures (food environment, walkability, drivability, bikeability, sports facilities), and SEP were combined for all inhabited Dutch administrative neighborhoods in 2016 (N=12,420). Cluster analysis was used to identify distinct neighborhood profiles and descriptive statistics to characterize each cluster, with spatial patterns visualized using an interactive heatmap and principal component plots. ResultsFive neighborhood clusters were identified. The Ecosyndemic cluster (N=1,070 neighborhoods) exhibited the highest burden of obesity (17% [IQR 16;19), chronic diseases (36% [IQR 33;38%) and risk of anxiety/depression (55% [IQR 51;58]), unhealthy food environments and low SEP. In contrast, the Privileged cluster (N=6,425) had more favorable health outcomes and living conditions, including lower obesity prevalence (12% [IQR 11;14]). The Psychosocial Vulnerability cluster (N=991) was notable for elevated risk of anxiety/depression (47% [IQR 43;51]) combined with relatively low obesity (11% [IQR 8;12]). The Syndemic cluster (N=1,836; obesity 15% [IQR 14;17]) and Towards Privileged cluster (N=2,098; obesity 12% [IQR 10;13]) represented intermediate profiles. ConclusionObesity and related health issues frequently cluster with unfavorable environment and SEP at the neighborhood level. The ecosyndemic framework offers a novel approach for identifying high-risk areas and supports targeted, social and place-based interventions.

IntroductionAccess to adequate energy in the home is necessary for a healthy and well life, however current energy use, particularly in high-income countries, is unsustainable. Decarbonisation of home energy can benefit climate mitigation and health but there is the potential to create new, or compound existing, inequalities in health if not implemented equitably. Mapping the theoretical causal pathways between home decarbonisation and health will contribute to further understanding of these mechanisms. AimsFirstly, to identify theoretical pathways between decarbonisation of home energy and health and health inequalities in high-income countries, and secondly, to synthesise these into a putative causal evidence map. Inclusion criteriaAll populations in high-income countries are included, as defined by the World Bank in 2023/24. Included concepts are decarbonisation of home energy, and health and health inequalities. Context for this review comprises of the inclusion of a clear theory linking the concepts. All study designs are included. MethodsThis protocol is for a review of theories rather than of intervention effectiveness. Medline/OVID, Scopus, and EconLit will be searched, with no limitation on date. Relevant international policy websites will also be searched. The search is limited to papers in English. Citation tracing may identify further relevant papers. Abstracts and full texts will be screened using Rayyan. At least 10% will be double-screened, and the rest screened by one author, and included full texts will be screened until data saturation is reached. Study inclusion is based on consistency with the inclusion criteria, with some flexibility allowed due to the theoretical nature of this review. Data extracted from papers will be used to develop a diagrammatic map of pathways.

The relationship between access to nature and public health outcomes has been well-studied and established in the literature. However, most studies use simple greenness indices as a proxy for access to nature, which ignores the "quality" of the nature since greenness indices are not able to predict biodiversity. My objective was to investigate the relationship between citizen scientist collected biodiversity data from the eBird platform, urban greenness and four human health outcomes (asthma, coronary heart disease, and self-assessed mental and physical health). I mapped and tested for correlations among eBird record species richness, greenness as NDVI and PLACES human health data in urban census tracts located in three metro areas/ecological zones (Albany, NY: eastern deciduous forest, Kansas City, MO: tallgrass prairie, and Phoenix, AZ: Sonoran Desert). eBird species richness was related to greenness, measures of urbanization and several human health factors; however, the correlations varied by metro area and in strength. Provided confounders are controlled for, eBird data could help to refine models surrounding relationships between public health and nature access.

Environmental noise is a significant public health concern, ranking among the top environmental risks to citizens health and quality of life. Despite various studies exploring the effects of atmospheric pollution on mental health, spatial investigations into the effects of noise pollution have been notably absent. This study addresses this gap by investigating the association between noise pollution (from road and rail networks) and depression for the first time in England and first explores localised patterns based on area deprivation. Depression prevalence, defined as the percentage of patients with a recorded depression diagnosis was calculated in small areas within Cheshire and Merseyside ICS using the Quality and Outcomes Framework Indicators dataset for 2019. Strategic noise mapping for rail and road noise (LDEN) was employed to quantify noise pollution, indicating a 24-hour annual average noise level with distinct weightings for evening and night periods. The English Index of Multiple Deprivation (IMD) was utilised to represent neighbourhood deprivation. Geographical Weighted Regression and Generalised Structural Equation Spatial Modelling (GSESM) were applied to estimate relationships between transportation noise, depression prevalence, and IMD at the Lower Super Output Area (LSOA) level. While transportation noise showed a low direct effect on depression levels in Cheshire and Merseyside ICS, it significantly mediated other factors linked to depression prevalence. Notably, GSESM revealed that health deprivation and disability was strongly associated (0.62) with depression through the indirect effect of environmental noise, particularly where transportation noise exceeds 55 dB on a 24-hour basis. Comprehending variations in noise exposure across different areas is paramount. This research not only provides valuable insights for informed decision-making but also lays the groundwork for implementing noise mitigation measures. These measures are aimed at addressing mental health inequalities, enhancing the quality of life for the exposed population and supporting a healthier ageing process in urban environments. The findings also carry crucial implications for public health, specifically in tailoring targeted interventions to mitigate noise-related health risks in areas where noise burdens exceed 55 dB, and residents may experience health deprivation and disability.

BackgroundA limited ability to identify social vulnerability and community resilience at local scales has been recognised as a critical barrier to both climate adaptation and health risk assessment and planning. This study aims to assess multidimensional social vulnerability to the health impacts of climate change across communities in Australia, quantify its contribution to health inequalities, and identify key drivers of health vulnerability. MethodsInformed by a scoping review and the WHO Social Determinants of Health Equity framework, we compiled area-level data from multiple sources on 61 social vulnerability indicators, subsumed under 27 subdomains and 8 domains (demographic profile, economic security, residential environment, infrastructure and services, social stability and community support, population health, governance and policies, climate knowledge and awareness). These indicators were used to construct a Social Vulnerability Index for the Health Impact of Climate Change (SVI-HICC) and scores in each domain. We used dominance analyses to identify the strongest predictors of vulnerability, examined inequalities in mental, physical, and social health associated with extreme weather and climate events across the vulnerability distribution, and tested the capacity of SVI-HICC to predict adverse health outcomes following climate-related extreme events in comparison to alternative social indices. FindingsSpatial mapping showed that high vulnerability was clustered in regional and remote areas, with pockets of moderate vulnerability in urban areas. People living in high vulnerability areas experienced significant health losses from weather and climate disaster, this was not seen for people in low vulnerability areas. Infrastructure and services, economic security, and residential environment were identified as the most influential domains contributing to social vulnerability, primarily driven by access to healthcare services, area disadvantage, dwelling condition, and housing precarity. InterpretationAn area-level assessment of multi-dimensional social vulnerability makes visible how social and structural determinants contribute to health inequalities in climate change. Such insights can inform climate adaptation policies that are equity-oriented and context-sensitive.

BackgroundDrowning remains a major global public health challenge. This study examined whether the timing and trajectories of urbanisation--beyond the current built environment--are associated with subnational drowning mortality. MethodsWe linked satellite-derived measures of built-environment change (GHSL), population crowding (WorldPop), surface water exposure (JRC Global Surface Water), and infrastructure proxies (VIIRS/DMSP nighttime lights) to GBD 2021 drowning mortality estimates across 203 ADM1 regions in 12 countries (2006-2021; 3,248 region-year observations). Temporal predictors captured recent expansion, development "newness" ([≤]10-year built share), acceleration/volatility, and a crowdingxgrowth interaction. We screened predictors using LASSO (10-fold cross-validation) and fitted mixed-effects models with region random intercepts. Distributed-lag models tested temporal precedence and development age, and income-stratified models assessed heterogeneity. ResultsAdding temporal predictors improved fit beyond contemporaneous built-environment measures ({Delta}AIC=177; {Delta}BIC=147). In adjusted models, crowdingxgrowth was strongly positively associated with drowning mortality, and a higher share of recent development was associated with higher mortality. Lag models showed a development age gradient: older built environment was most protective. Associations differed by income group, with several key coefficients reversing sign across strata. DiscussionDrowning mortality appears shaped by development histories as well as present-day conditions, with risk concentrated in rapidly changing, dense settings and the newest built environments. Cross-context heterogeneity suggests mechanisms and prevention priorities are unlikely to be uniform. ConclusionsDevelopment timing and trajectories help explain subnational drowning mortality beyond current built form alone. Prevention and planning should prioritise transition-period safety strategies in newly developing and rapidly densifying areas.

Highlights- Nation-wide study with data for nearly all adult Dutch inhabitants. - Ethnic minorities face higher physico-chemical exposures than Dutch-origin inhabitants. - Food & physical activity environments better for ethnic minorities than Dutch-origin. - Socio-economic characteristics less favorable for ethnic minorities than Dutch-origin. IntroductionEthnic minority populations may be disproportionally affected by unhealthy environmental exposures, increasing health inequities. This study aims to identify whether residential neighborhood exposures differ between ethnic groups in the Netherlands. MethodsThis cross-sectional study included all adult residents of the Netherlands registered in the national population register on 01/01/2022 (N=13,926,871). Exposure data (physico-chemical, food and physical environment, socio-economic characteristics, health and social well-being) were obtained from Statistics Netherlands, GECCO and the Dutch Health Monitor, and linked to individuals based on geocoded home addresses. Ethnicity was based on country of birth of individuals and their parents. Estimated marginal means were calculated and ethnic differences in exposure determined using multiple linear and logistic regression, adjusted for age and sex, stratified by socio-economic status (SES) and population density. ResultsCompared to Dutch-origin, ethnic minority populations had less favorable physico-chemical exposures (e.g. 0.87{micro}g/m3 [95%-CI: 0.86;0.88] higher PM2.5 exposure for Moroccans in "high SES-high population density"). Conversely, the food and physical activity environment was more favorable for ethnic minorities (e.g. 1.82km/ha [95%-CI 1.80;1.83] higher bike path density among Turks in the "low SES-low population" density category). Socio-economic characteristics of the environment were generally less favorable for ethnic minorities (E.g. difference between Dutch Caribbeans and Dutch-origin -4.23% [95%-CI -4.35;-4.11] in "high income-high population density". Ethnic differences in health and social well-being varied. Neighborhood-level smoking was most prevalent among ethnic minorities, while excessive drinking was most prevalent among Dutch-origin. Exposure to vandalism and (sexual)violence was lowest among Dutch-origin and highest among Dutch Caribbean, Moroccans, Turks and Surinamese. ConclusionPhysico-chemical exposure, socio-economic characteristics of the environment and safety from crime were less favorable among ethnic minority populations compared to Dutch-origin. The food and physical activity environment was more favorable for ethnic minorities. Ethnic inequalities were most pronounced among Moroccans, Turks, Surinamese and Dutch Caribbeans compared to Dutch-origin.

ObjectiveTo identify factors associated with local variation in the time course of COVID-19 case burden in England. MethodsWe analyzed laboratory-confirmed COVID-19 case data for 150 upper tier local authorities, from the period from January 30 to May 6, 2020, as reported by Public Health England. Using methods suitable for time-series data, we identified clusters of local authorities with distinct trajectories of daily cases, after adjusting for population size. We then tested for differences in sociodemographic, economic, and health disparity factors between these clusters. ResultsTwo clusters of local authorities were identified: a higher case trajectory that rose faster over time to reach higher peak infection levels, and a lower case trajectory cluster that emerged more slowly, and had a lower peak. The higher case trajectory cluster (79 local authorities) had higher population density (p<0.001), higher proportion of Black and Asian residents (p=0.03; p=0.02), higher multiple deprivation scores (p<0.001), a lower proportions of older adults (p=0.005), and higher preventable mortality rates (p=0.03). Local authorities with higher proportions of Black residents were more likely to belong to the high case trajectory cluster, even after adjusting for population density, deprivation, proportion of older adults and preventable mortality (p=0.04). ConclusionAreas belonging to the trajectory with significantly higher COVID-19 case burden were more deprived, and had higher proportions of ethnic minority residents. A higher proportion of Black residents in regions belonging to the high trajectory cluster was not fully explained by differences in population density, deprivation, and other overall health disparities between the clusters. What is already known on this subject?Emerging evidence suggests that the burden of COVID-19 infection is falling unequally across England, with provisional data suggesting higher overall infection and mortality rates for Black, Asian, and mixed race/ethnicity individuals. What does this study add?We found that regions with greater socioeconomic deprivation and poorer population health measures showed a faster rise in COVID-19 cases, and reached higher peak case levels. Areas with a higher proportion of Black residents were more likely to show this kind of time course, even after adjusting for multiple co-occurring factors, including population density. This finding merits further investigation in terms of the intersecting vulnerability factors Black and other minority ethnic individuals face in England (e.g. proportion of people working in service and caring roles, and the role of structural discrimination), and has implications for the ongoing allocation of public health resources, in order to better mitigate such inequalities.

Increasing urban vegetation coverage is associated with improved human health and well-being, reduced environmental impact of cities and enhanced urban resilience to climate change. To support evidence-based urban planning, this study quantifies the mortality benefits, equity implications and cost-benefit ratio of several scenarios of green space development in Paris by 2040, including the replacement of car-dedicated surfaces with green spaces and a best-case scenario. This quantitative health impact assessment is based on estimated changes in the Normalized Difference Vegetation Index (NDVI), obtained through the estimation of the dynamic effects over time using a Difference-in-Differences approach based on previous public greening interventions, and on an exposure-response relationship linking NDVI and all-cause mortality. It was conducted at the sub-municipal level (IRIS) and incorporates a social deprivation index to assess health equity implications. Vegetation costs are drawn from a previous French study estimating urban soil restoration prices. Replacing surplus on-street parking and 20% of street space with vegetation could reduce all-cause mortality by around 0.8%, while reaching 15% of vegetation coverage in each IRIS could prevent around 3% of deaths yearly in Paris as early as 2040. For all scenarios, these benefits were approximatively equally distributed across deprivation levels. Predicted monetised health benefits outweigh intervention costs by 2035, with further impacts representing net gain. In conclusion, greening interventions targeting car-dedicated space in Paris would equitably improve health while supporting more sustainable and resilient cities.

Drowning remains a major global public health challenge, yet how built environment characteristics shape population-level drowning risk remains poorly understood. This study linked satellite-derived built environment data to subnational drowning mortality estimates across 203 regions in 12 countries from 2006-2021. It found that built environment associations with drowning mortality are complex, non-linear, and shaped by development context. Urban extent was strongly protective, while built area near water showed protection overall but increased risk when combined with high population crowding. Almost all drowning mortality variance occurred between regions rather than within regions over time, indicating risk is predominantly determined by place-based characteristics. Income-stratified analyses revealed profound heterogeneity: crowding was protective in low-to middle-income settings but near-null in high-income regions, while waterfront development captured very different realities across contexts. These findings highlight the importance of tailoring drowning prevention strategies to local built environment configurations and development contexts.

Greenspace has been associated with a wide range of health outcomes and conditions related to functional limitation and disability. Yet less is known about how the spatial morphology of greenspace relates to disability prevalence across different stages of the life course. This study examines associations between greenspace morphology and disability prevalence among children, working-age adults, and older adults in urban census tracts across the contiguous United States. Using national land-cover data, we quantified morphological metrics at the census-tract level, including greenspace percentage, density, mean size, connectedness, shape complexity, inter-greenspace distance, and diversity. These indicators were linked with age-specific disability prevalence obtained from the American Community Survey. Spatial lag regression models were used to account for spatial dependence while adjusting for socio-demographic and contextual characteristics. Across age groups, higher greenspace percentage was consistently associated with lower disability prevalence (children: {beta} = -0.081, 95% CI: -0.096 to -0.066; adults: {beta} = -0.804, -0.858 to -0.750; older adults: {beta} = -1.132, -1.250 to -1.013). Among children, patch density ({beta} = -0.045, -0.061 to -0.029), mean patch area ({beta} = -0.029, -0.040 to -0.018), connectedness ({beta} = -0.051, -0.069 to -0.032), diversity ({beta} = -0.036, -0.051 to -0.020), and inter-greenspace distance ({beta} = 0.056, 0.039 to 0.073) were all associated with disability prevalence, whereas shape complexity was not ({beta} = 0.004, -0.010 to 0.018). Among working-age adults, associations were observed for mean area ({beta} = -0.023, -0.090 to -0.002), connectedness ({beta} = -0.127, -0.243 to -0.011), shape complexity ({beta} = -0.123, -0.174 to -0.072), diversity ({beta} = -0.146, -0.201 to -0.091), and inter-greenspace distance ({beta} = 0.151, 0.059 to 0.242), whereas patch density was not significantly associated with disability prevalence ({beta} = -0.013, -0.048 to 0.022). In older adults, all examined greenspace morphology metrics showed significant associations with disability prevalence, including patch density ({beta} = -0.445, -0.842 to -0.049), diversity ({beta} = -0.126, -0.188 to -0.065), and inter-greenspace distance ({beta} = 0.455, 0.409 to 0.501). Overall, the findings suggest that higher greenspace percentage, larger patch size, greater connectedness, greater diversity, and more spatially clustered greenspace distributions are associated with lower disability prevalence across the life course, although the strength and consistency of these associations varied across age groups. The study provides national-scale evidence for incorporating greenspace morphology into urban planning and public health strategies to support more inclusive and health-supportive urban environments.

Gentrification is a complex and controversial process, where the influx of new, wealthier residents to previously run-down neighbourhoods brings change such as economic development, infrastructure investments and lower crime rates, but can be to the detriment of the original lower-income residents, who are either displaced, or stay but cannot take advantage of the new opportunities. Understanding how neighbourhood change affects food environments can shed light on the possible causal pathways between gentrification and urban health inequalities. This rapid evidence assessment reviewed evidence on the impact of gentrification on the healthfulness of food environments globally. Ten studies were identified through a systematic keyword search and assessed. We found limited evidence of an effect, with a small, albeit consistent, body of evidence mostly comprised of low- to medium-quality observational studies, all from high-income countries. Most studies examined effects on availability or affordability of food, finding an association between gentrification and increased availability of unhealthy foods, or reduced affordability for original low-income residents.

BackgroundEvidence on the long-term impact of urban green and blue spaces (UGBS) interventions remains limited. This study is a 15-year evaluation of an urban greenway development in Belfast (United Kingdom), assessing the potential effects of this UGBS intervention on physical activity (PA), mental wellbeing and co-benefits. MethodsUsing quasi-experimental design, a repeated cross-sectional survey was conducted in 2010 (baseline), 2017 (post-opening) and 2023 (long-term follow-up) with about 1,200 adults participated each wave. Outcomes included PA, mental wellbeing, general health, quality of life, social capital and environmental perception. Multilevel mixed-effect regressions were performed to examine within-group changes at long-term follow-up. Difference-in-differences analysis investigated the between-group changes that might be attributed to the greenway. Additional comparative analyses included distance-decay analysis and comparison with population trends in Northern Ireland. ResultsAt six years after completion, the greenway intervention appears to buffer a decline in duration of PA - mainly from moderate-intensity activity (decline lower by 118.6 min/week, 95%CI: 3.9-232.2) but with no significant impact on the proportion of the population meeting the recommended PA level. The intervention is associated with a smaller decline in self-rated health (4.98 units; 95%CI: 0.62-9.34) relative to control group. Intervention association with mental wellbeing was positive but not significant (p=0.30). The greenway also showed positive effects on social capital and environmental perceptions, with impacts most evident in improving safety and trust in the local area. ConclusionThis study provides evidence to support the public health impact of UGBS and its long-term health and social benefits.

Background Childhood overweight and obesity represent major public health challenges, shaped by socio-economic and environmental factors. This study investigates the mediating and moderating role of urban environmental exposures in socio-economic disparities in childhood excess weight. Methods Data was drawn from a population-based sample of children (2-9 years) and adolescents (10-17 years) living in Geneva, Switzerland. Parents reported household financial situation and children's height and weight, from which excess weight (i.e. overweight or obesity) was derived. Residential exposures to air pollution (PM2.5, NO2), noise (daytime, nighttime), and neighborhood greenness (green areas, canopy coverage) were estimated based on geocoded residential addresses. The association between household financial situation and excess weight was evaluated, as well as the mediating and moderating roles of urban environmental exposures. Results The analysis included 1006 children and 1154 adolescents. Among children, an average-to-poor household financial situation was associated with higher odds of excess weight in children (adjusted odds ratio [aOR]: 1.79, 95% confidence interval [CI]: 1.13; 2.84). Higher noise exposure was associated with excess weight (daytime: aOR: 1.40, 95% CI: 1.10; 1.77, nighttime: aOR: 1.37, 95% CI: 1.08; 1.74), while the association with PM2.5 appeared stronger among socio-economically disadvantaged children, though the interaction did not reach statistical significance (financial situation x PM2.5 interaction: aOR: 1.59, 95% CI: 0.98; 2.59). No significant associations were observed among adolescents. Conclusion These findings highlight the joint influence of social and environmental inequalities on childhood excess weight and stress the need to address these interconnected determinants to design equitable, targeted public health interventions.

The association between multi-dimensional deprivation and public health is well established, and many area-based indices have been developed to measure or account for socioeconomic status in health surveillance. The Yost Index, developed in 2001, has been adopted in the US for cancer surveillance and is based on the combination of two heavily weighted (household income, poverty) and five lightly weighted (rent, home value, employment, education and working class) indicator variables. Our objectives were to 1) update indicators and find a more parsimonious version of the Yost Index by examining potential models that included indicators with more balanced weights/influence and reduced redundancy and 2) test the statistical consistency of the factor upon which the Yost Index is based. Despite the usefulness of the Yost Index, a one-factor structure including all seven Yost indicator variables is not statistically reliable and should be replaced with a three-factor model to include the true variability of all seven indicator variables. To find a one-dimensional alternative, we conducted maximum likelihood exploratory factor analysis on a subset of all possible combinations of fourteen indicator variables to find well-fitted one-dimensional factor models and completed confirmatory factor analysis on the resulting models. One indicator combination (poverty, education, employment, public assistance) emerged as the most stable unidimensional model. This model is more robust to extremes in local cost of living conditions, is comprised of ACS variables that rarely require imputation by the end-user and is a more parsimonious solution than the Yost index with a true one-factor structure.

BackgroundEmerging evidence has demonstrated that nature-based interventions (NBIs) can improve mental and physical health. Considering that the global burden of poor mental health continues to rise, such interventions could be a cost-effective means to improve mental health, as well as reconnect individuals with the natural world, and thus aid efforts. However, the effectiveness of NBIs as a prescriptive intervention is, in part, a function of access to blue and green spaces. Accordingly, this scoping review will explore how structural inequalities influence the effectiveness of nature-based interventions as treatment options for mental and physical ill health. MethodsA scoping review will be conducted to identify the barriers and facilitators associated with the utilisation of green and blue spaces. The review will follow the PRISMA-ScR guidelines, in addition to the associated Cochrane guidelines for scoping reviews. A literature search will be performed across five databases, and articles will be selected based on key inclusion/ exclusion criteria. All data will be extracted to a pre-defined charting table. The primary and secondary outcomes will be mental and physical health respectively. DiscussionThis review will better inform relevant stakeholders of the potential enablers and barriers of nature-based interventions, and thereby improve provision and implementation of NBIs as public health initiatives. Ethics and DisseminationAll data rely on secondary, publicly available data sources; therefore no ethical clearance is required. Upon completion, the results of this study will be disseminated via the Imperial College London Community and published in an open access, peer-reviewed journal. Article SummaryO_ST_ABSStrengths and Limitations of this StudyC_ST_ABSO_LIThis scoping review protocol is the first to focus on the accessibility to green and blue spaces in the context of mental and physical health. C_LIO_LIThis protocol and subsequent review benefit from increased transparency, a systematised strategy (PRISMA-ScR), and a reduction in the risk of bias, through publication in an open access journal. C_LIO_LIThis review will also capture grey literature - studies published outside peer-reviewed journals. C_LIO_LIDue to the broad nature of the review, the research may unearth more questions than solutions. C_LI Registration NumberOpen Science Framework: 10.17605/OSF.IO/8J5Q3