Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 3 appraisals
Journal of global health
Residential green space mitigates genetic susceptibility to incident irritable bowel syndrome in a prospective cohort of 376 749 individuals
BACKGROUND: Environmental exposures may influence irritable bowel syndrome (IBS) pathogenesis, but the interplay between genetic risk, residential green/blue space, and IBS incidence remains unexplored. METHODS: We aimed to study the association between green/blue space and incident IBS, and to assess effect modification by genetic susceptibility. The study included 376 749 UK Biobank participants at baseline. Residential green space was measured using the normalised difference vegetation index (NDVI), and blue space was defined by distance to the nearest water bodies. For time-to-event analyses, we used Cox proportional hazards models, polygenic risk scores (PRS), and mediation analysis to test gene-environment interactions. Results are presented as hazard ratios (HRs) with 95% confidence intervals (95% CIs). RESULTS: During a follow-up of 11.73 years, 7091 incident IBS cases were documented. Higher residential green space exposure was associated with reduced risk of incident IBS. Specifically, within a 1000 m buffer, each interquartile range (IQR) increase in NDVI corresponded to a 5% lower IBS risk (HR = 0.95; 95% CI = 0.91-0.98), with consistent effects observed at 800 m and 500 m buffers. Conversely, a greater distance to water bodies was associated with reduced IBS risk. Stratification by PRS revealed a significant interaction: increased green space (1000 m buffer) reduced IBS risk by 8% exclusively among high-genetic-risk individuals (HR = 0.92; 95% CI = 0.88-0.96), whereas no interaction was observed for blue space. Moreover, physical activity mediated the association between green space and IBS. CONCLUSIONS: Increased residential green space exposure is associated with reduced IBS incidence, particularly among individuals with high genetic susceptibility. These findings underscore the importance of urban greening as a public health strategy to mitigate IBS risk, highlighting the potential for targeted environmental interventions to offset genetic predispositions.
13 June 2026
Read appraisal →Environmental monitoring and assessment
XGBoost-based analysis of short- and long-term COVID-19 air quality impacts in Tehran, Iran.
This study examines the air quality trends associated with COVID-19 lockdowns and the subsequent recovery on air quality in Tehran, employing an established XGBoost framework for de-weathering with daily data from 22 monitoring stations from 2019 to 2025. A comprehensive analysis was conducted on six principal pollutants (PM₂.₅, PM₁₀, NO₂, O₃, SO₂, and CO) across four distinct temporal phases: Pre-pandemic, Pandemic, Post-COVID, and After Termination. While the model effectively reduced meteorological bias, exhibiting strong efficacy for particulate matter (R = 0.78-0.88; IOA = 0.68-0.88; FAC2 > 0.95), we explicitly acknowledge less consistent outcomes for reactive gases such as O₃ (R < 0.75; NMGE > 0.30). The imposition of lockdown measures coincided with significant reductions in pollutants associated with vehicular traffic: NO₂ exhibited a decline of - 30 to - 36%, PM₂.₅ decreased by - 18 to - 22%, and CO diminished by - 20%. In contrast, O₃ experienced an increase of + 20-30%, indicative of diminished NO titration. Principal Component Analysis (PCA) corroborated these trends, with PC1 (NO₂, PM₂.₅, CO) accounting for approximately 60% of the variance throughout the pandemic. In subsequent phases, partial recoveries were noted: PM₂.₅ escalated by + 15-20%, NO₂ stabilized at around -10%, SO₂ consistently decreased (-30% by 2025), whereas O₃ surged by + 20% by 2025, clustering with PM₁₀ in PC2, thereby highlighting the impacts of dust and secondary formation processes. Lockdowns yielded transient enhancements in air quality, with restricted long-term advantages. Sustainable progress necessitates the adoption of comprehensive policies targeting traffic, industrial emissions, VOCs, and dust management.
25 May 2026
Read appraisal →PloS one
Healthy living environments create healthy physical activity-related habits (ELEVATE): A protocol for a smartphone-based mixed-method study
Physical inactivity remains a key risk factor for adverse public health outcomes, disproportionately burdening lower socioeconomic groups. While individual-level interventions may temporarily increase walking-related physical activity (WPA) for some, they rarely achieve population-wide benefits. In contrast, built and natural environments are better positioned to support sustained WPA at the population level. Despite the importance of the environment to WPA, state-of-the-art research has limitations: it often relies on cross-sectional self-reports, uses coarse, simplistic environmental indicators, and focuses narrowly on residential neighborhoods, overlooking the diverse streetscapes people encounter in daily mobility. Using a transdisciplinary approach, ELEVATE addresses these gaps by 1) assessing how adults perceive and experience the built and natural streetscape environment during their WPA, 2) longitudinally assessing the relationships between streetscape environments and WPA, and 3) developing an artificial intelligence-powered system to suggest place-based environmental interventions that promote WPA. ELEVATE will employ a mixed-methods study design grounded in participatory co-creation, on-site and walk-along interviews to capture the everyday practices and experiences of WPA. We will use deep learning to extract objective environmental features and perceived streetscape qualities from street view images. A sample of approximately 200 adults residing in Amsterdam, The Netherlands, will be recruited. To examine relationships between micro-scale streetscape features and WPA, we will collect seven days of intensive longitudinal data using smartphones, including global positioning system (GPS)-based mobility and step counts. We will use spatiotemporal clustering to identify where people are most and least physically active, and mixed models to assess associations between these environmental measures and step counts. Qualitative and quantitative results will be triangulated in co-created focus groups. Finally, to support evidence-based public health and urban planning interventions, we will develop an AI-powered recommender system that generates context-sensitive (re)design guidelines framing the built and natural environment as a modifiable determinant of WPA. This study will generate evidence on how micro-scale built and natural street environments encountered during daily mobility are associated with WPA in adults. The findings are expected to inform place-based public health strategies by identifying modifiable environmental characteristics associated with physical activity and socioeconomic inequalities in urban settings.
13 May 2026
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