Impact of residential greenness on myocardial infarction in the population with diabetes: A sex-dependent association?

Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada

BACKGROUND

Psoriasis is a major global health burden affecting ~ 60 million people worldwide. Existing studies on psoriasis focused on individual-level health behaviors (e.g. diet, alcohol consumption, smoking, exercise) and characteristics as drivers of psoriasis risk. However, it is increasingly recognized that health behavior arises in the context of larger social, cultural, economic and environmental determinants of health. We aimed to identify the top risk factors that significantly impact the incidence of psoriasis at the neighborhood level using populational data from the province of Quebec (Canada) and advanced tree-based machine learning (ML) techniques.

METHODS

Adult psoriasis patients were identified using International Classification of Disease (ICD)-9/10 codes from Quebec (Canada) populational databases for years 1997-2015. Data on environmental and socioeconomic factors 1 year prior to psoriasis onset were obtained from the Canadian Urban Environment Health Consortium (CANUE) and Statistics Canada (StatCan) and were input as predictors into the gradient boosting ML. Model performance was evaluated using the area under the curve (AUC). Parsimonious models and partial dependence plots were determined to assess directionality of the relationship.

RESULTS

The incidence of psoriasis varied geographically from 1.6 to 325.6/100,000 person-years in Quebec. The parsimonious model (top 9 predictors) had an AUC of 0.77 to predict high psoriasis incidence. Amongst top predictors, ultraviolet (UV) radiation, maximum daily temperature, proportion of females, soil moisture, urbanization, and distance to expressways had a negative association with psoriasis incidence. Nighttime light brightness had a positive association, whereas social and material deprivation indices suggested a higher psoriasis incidence in the middle socioeconomic class neighborhoods.

CONCLUSION

This is the first study to highlight highly variable psoriasis incidence rates on a jurisdictional level and suggests that living environment, notably climate, vegetation, urbanization and neighborhood socioeconomic characteristics may have an association with psoriasis incidence.

Co-exposure to multiple air pollutants, genetic susceptibility, and the risk of myocardial infarction onset: a cohort analysis of the UK Biobank participants

AIMS

The relationship between the long-term joint exposure to ambient air pollution and incidence of myocardial infarction (MI) and modification by genetic susceptibility remain inconclusive.

METHODS AND RESULTS

We analysed 329 189 UK Biobank participants without MI at baseline. Exposure concentrations to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were obtained. Air pollution score assessing the joint exposure was calculated, and its association with MI was evaluated via Cox model under the P value aggregation framework. Genetic susceptibility to MI was evaluated by incorporating polygenic risk score (PRS) into models. Risk prediction models were also established. During a median follow-up of 13.4 years, 9993 participants developed MI. Per interquartile range increase of PM2.5, PM10, NO2, and NOx resulted in 74% [95% confidence intervals (CIs) 69%-79%], 67% (63%-72%), 46% (42%-49%), and 38% (35%-41%) higher risk of MI. Compared with the lowest quartile (Q1) of air pollution score, the multivariable adjusted hazard ratio (HR) (95%CIs) of Q4 (the highest cumulative air pollution) was 3.50 (3.29-3.72) for MI. Participants with the highest PRS and air pollution score possessed the highest risk of incident MI (HR = 4.88, 95%CIs 4.35-5.47). Integrating PRS, air pollution exposure, and traditional factors substantially improved risk prediction of MI.

CONCLUSION

Long-term joint exposure to air pollutants including PM2.5, PM10, NO2, and NOx is substantially associated with increased risk of MI. Genetic susceptibility to MI strengthens such adverse joint association. Air pollutions together with genetic and traditional factors enhance the accuracy of MI risk prediction.

Association of greenspaces exposure with cardiometabolic risk factors: a systematic review and meta-analysis

BACKGROUND

Cardiometabolic conditions are major contributors to the global burden of disease. An emerging body of evidence has associated access to and surrounding public open spaces (POS) and greenspace with cardiometabolic risk factors, including obesity, body mass index (BMI), hypertension (HTN), blood glucose (BG), and lipid profiles. This systematic review aimed to synthesize this evidence.

METHODS

This systematic review was conducted based on the PRISMA guidelines. Four electronic databases including Web of Science, PubMed, Scopus, and Google Scholar were searched for eligible articles published until July 2023. All observational studies which assessed the association of greenspace and POS with cardiometabolic risk factors including obesity, BMI, HTN, BG, and lipid profiles were included and reviewed by two authors independently. Heterogeneity between studies was assessed using the I2 index and Cochrane's Q test. Random/fixed effect meta-analyses were used to combine the association between greenspace exposure with cardiometabolic risk factors.

RESULTS

Overall, 118 relevant articles were included in our review. The majority of the articles were conducted in North America or Europe. In qualitative synthesis, access or proximity to greenspaces or POS impacts BMI and blood pressure or HTN, BG, and lipid profiles via various mechanisms. According to the random effect meta-analysis, more access to greenspace was significantly associated with lower odds of HTN (odds ratio (OR): 0.81, 95% confidence intervals (CIs): 0.61-0.99), obesity (OR: 0.83, 95% CIs: 0.77-0.90), and diabetes (OR:0.79, 95% CI: 0.67,0.90).

CONCLUSIONS

Findings of this systematic review and meta-analysis suggested that greenspace accessibility is associated with some cardiometabolic risk factors. Improving greenspace accessibility could be considered as one of the main strategies to reduce cardiometabolic risk factors at population level.

Impacts of Urban Green on Cardiovascular and Cerebrovascular Diseases-A Systematic Review and Meta-Analysis

Cardiovascular diseases (CVDs) are a leading cause of mortality globally. In particular, ischemic heart diseases (IHDs) and cerebrovascular diseases (CBVDs) represent the main drivers of CVD-related deaths. Many literature examples have assessed the association between CVD risk factors and urban greenness. Urban green (UG) may positively affect physical activity, reduce air and noise pollution, and mitigate the heat island effect, which are known risk factors for CVD morbidity. This systematic review aims to assess the effects of urban green spaces on CVD morbidity and mortality. Peer-reviewed research articles with a quantitative association between urban green exposure variables and cardiovascular and cerebrovascular outcomes were included. Meta-analyses were conducted for each outcome evaluated in at least three comparable studies. Most of the included studies' results highlighted an inverse correlation between exposure to UG and CVD outcomes. Gender differences were found in four studies, with a protective effect of UG only statistically significant in men. Three meta-analyses were performed, showing an overall protective effect of UG on CVD mortality (HR (95% CI) = 0.94 (0.91, 0.97)), IHD mortality (HR (95% CI) = 0.96 (0.93, 0.99)), and CBVD mortality (HR (95% CI) = 0.96 (0.94, 0.97)). The results of this systematic review suggest that exposure to UG may represent a protective factor for CVDs.

Associations and pathways between residential greenness and metabolic syndromes in Fujian Province

Background

Greenness exposure is beneficial to human health, but its potential mechanisms through which the risk for metabolic syndrome (MetS) could be reduced have been poorly studied. We aimed to estimate the greenness-MetS association in southeast China and investigate the independent and joint mediation effects of physical activity (PA), body mass index (BMI), and air pollutants on the association.

Methods

A cross-sectional study was conducted among the 38,288 adults based on the Fujian Behavior and Disease Surveillance (FBDS), established in 2018. MetS was defined as the presence of three or more of the five components: abdominal obesity, elevated triglyceride, reduced high-density lipoprotein cholesterol (HDL-C), high blood pressure, and elevated fasting glucose. The residential greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 250, 500, and 1,000 meters (m) buffer zones around the residential address of each participant. Logistic regression models were used to estimate the greenness-MetS association. The causal mediation analysis was used to estimate the independent and joint mediation effects of PA, BMI, particulate matter with an aerodynamic diameter of 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂).

Results

Each interquartile range (IQR) increase in greenness was associated with a decrease of 13% (OR = 0.87 [95%CI: 0.83, 0.92] for NDVI_500m and OR = 0.87 [95%CI: 0.82, 0.91] for EVI_500m) in MetS risk after adjusting for covariates. This association was stronger in those aged < 60 years (e.g., OR = 0.86 [95%CI: 0.81, 0.92] for NDVI_500m), males (e.g., OR = 0.73 [95%CI: 0.67, 0.80] for NDVI_500m), having an educational level of primary school or above (OR = 0.81 [95%CI: 0.74, 0.89] for NDVI_500m), married/cohabitation (OR = 0.86 [95%CI: 0.81, 0.91] for NDVI_500m), businessman (OR = 0.82 [95%CI: 0.68, 0.99] for NDVI_500m), other laborers (OR = 0.77 [95%CI: 0.68, 0.88] for NDVI_500m), and non-smokers (OR = 0.77 [95%CI: 0.70, 0.85] for NDVI_500m). The joint effect of all six mediators mediated about 48.1% and 44.6% of the total effect of NDVI_500m and EVI_500m on the MetS risk, respectively. Among them, BMI showed the strongest independent mediation effect (25.0% for NDVI_500m), followed by NO₂ and PM₁₀.

Conclusion

Exposure to residential greenness was associated with a decreased risk for MetS. PA, BMI, and the four air pollutants jointly interpreted nearly half of the mediation effects on the greenness-MetS association.

Associations of parks, greenness, and blue space with cardiovascular and respiratory disease hospitalization in the US Medicare cohort

Natural environments have been linked to decreased risk of cardiovascular disease (CVD) and respiratory disease (RSD) mortality. However, few cohort studies have looked at associations of natural environments with CVD or RSD hospitalization. The aim of this study was to evaluate these associations in a cohort of U.S. Medicare beneficiaries (∼63 million individuals). Our open cohort included all fee-for-service Medicare beneficiaries (2000-2016), aged ≥65, living in the contiguous U.S. We assessed zip code-level park cover based on the United States Geological Survey Protected Areas Database, average greenness (Normalized Difference Vegetation Index, NDVI), and percent blue space cover based on Landsat satellite images. Cox-equivalent Poisson models were used to estimate associations of the exposures with first CVD and RSD hospitalization in the full cohort and among those living in urban zip codes (≥1000 persons/mile2). NDVI was weakly negatively correlated with percent park cover (Spearman ρ = -0.23) and not correlated with percent blue space (Spearman ρ = 0.00). After adjustment for potential confounders, percent park cover was not associated with CVD or RSD hospitalization in the full or urban population. An IQR (0.27) increase in NDVI was negatively associated with CVD (HR: 0.97, 95%CI: 0.96, 0.97), but not with RSD hospitalization (HR: 0.99, 95%CI: 0.98, 1.00). In urban zip codes, an IQR increase in NDVI was positively associated with RSD hospitalization (HR: 1.02, 95%CI: 1.00, 1.03). In stratified analyses, percent park cover was negatively associated with CVD and RSD hospitalization for Medicaid eligible individuals and individuals living in low socioeconomic status neighborhoods in the urban population. We observed no associations of percent blue space cover with CVD or RSD hospitalization. This study suggests that natural environments may benefit cardiorespiratory health; however, benefits may be limited to certain contexts and certain health outcomes.

Exploring the impacts of street-level greenspace on stroke and cardiovascular diseases in Chinese adults

In recent years, cardiovascular diseases (CVDs) have become the primary cause of death in the world. Existing studies have found that greenspace is important for the prevention of CVDs and stroke. However, since they only focus on large green infrastructure (e.g., urban parks) or the general greenspace (usually being evaluated through normalized difference vegetation index), little information exists regarding the association between street-level greenspace and CVDs (stroke). In this study, the CVDs and stroke data of participants were retrieved from the 33 Chinese Community Health Study. We measured participants' exposure to street-level greenspace exposure using street view images and machine learning technique. Multilevel logistic regressions were applied. While controlling for confounders, we found that higher level of street-level greenspace exposure was associated with lower CVDs prevalence. However, street-level greenspace exposure was associated with stroke prevalence only for females. The associations were stronger among females, younger adults, participants with educational attainment above high school, physically active participants and participants who were not overweight. None of the mediators (air pollution, physical exercise, and BMI) can explain the associations between street-level greenspace exposure and CVDs (stroke) prevalence. Our findings suggest that street-level vegetation should be increased to cope with the rapid growth of the CVDs burdens. Also, the differences between the effect of street-level trees and grasses should be noted before formulating specific urban planning policies.

Green space and cardiovascular disease: A systematic review with meta-analysis

Exposure to green space has been proposed to be beneficially associated with cardiovascular morbidity and mortality. Many studies have explored this topic, but the results remain conflicting. We aimed to evaluate the epidemiological evidence on this topic by performing a systematic review with meta-analysis. We searched PubMed, Web of Science and Embase for studies on the association between green space and cardiovascular disease (CVD) that were published till January 2022. Two authors independently performed study selection, data extraction, quality assessment, and risk of bias assessment. For studies providing detailed numeric data, we also conducted quantitative meta-analyses and calculated the pooled odd ratios (ORs) for associations between the most commonly used exposure estimate (normalized difference vegetative index [NDVI]) and five CVD events: CVD mortality, ischemic heart disease (IHD) mortality, cerebrovascular disease (CBVD) mortality, and stroke incidence/prevalence. Additional analyses were conducted to explore the geographical scale effects of NDVI. Publication bias tests were also conducted. Of the 6787 records identified, 53 studies were eligible for inclusion. These studies covered 18 countries and included data from more than 100 million persons. Meta-analyses showed that a 0.1 increase in NDVI was significantly associated with 2-3% lower odds of CVD mortality (OR: 0.97, 95% CI: 0.96-0.99), IHD mortality (OR: 0.98, 95% CI: 0.96-1.00), CBVD mortality (OR: 0.98, 95% CI: 0.97-1.00), and stroke incidence/prevalence (OR: 0.98, 95% CI: 0.96-0.99). There was no significant difference between the pooled estimates for different buffer sizes. No evidence of publication bias was detected. We provide strong and robust evidence for the beneficial effects of green space exposure on cardiovascular health. More prospective studies and mechanistic studies, especially that conducted in low- and middle-income countries, are merited to strengthen our conclusions.

Green balance in urban areas as an indicator for policy support: a multi-level application

Green spaces are increasingly recognised as key elements in enhancing urban resilience as they provide several ecosystem services. Therefore, their implementation and monitoring in cities are crucial to meet sustainability targets.

In this paper, we provide a methodology to compute an indicator that assesses changes in vegetation cover within Urban Green Infrastructure (UGI). Such an indicator is adopted as one of the indicators for reporting on the key area “nature and biodiversity” in the Green City Accord (GCA).

In the first section, the key steps to derive the indicator are described and a script, which computes the trends in vegetation cover using Google Earth Engine (GEE), is provided.

The second section describes the application of the indicator in a multi-scale, policy-orientated perspective. The analysis has been carried out in 696 European Functional Urban Areas (FUAs), considering changes in vegetation cover inside UGI between 1996 and 2018. Results were analysed for the EU and the United Kingdom. The Municipality of Padua (Italy) is used as a case study to illustrate the results at the local level.

Over the last 22 years, a slight upward trend characterised the vegetation growth within UGI in European FUAs. Within core cities and densily built-upcommuting zones, the trend was stable; in non-densely built-up areas, an upward trend was recorded. Vegetation cover in UGI has been relatively stable in European cities. However, a negative balance between abrupt changes in greening and browning has been recorded, affecting most parts of European cities (75% of core cities and 77% of commuting zones in densely built-up areas). This still indicates ongoing land take with no compensation of green spaces that are lost to artificial areas.

Focusing on the FUA of Padua, a downward trend was observed in 33.3% and 12.9% of UGI in densely built-up and not-densely built-up areas, respectively. Within the FUA of Padua, most municipalities are characterised by a negative balance between abrupt greening and browning, both in non-densely built-up and densely built-up areas.

This approach complements traditional metrics, such as the extent of UGI or tree canopy cover, by providing a valuable measure of condition of urban ecosystems and an instrument to monitor the impact of land take.