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Original research
Greenness may improve lung health in low–moderate but not high air pollution areas: Seven Northeastern Cities’ study

Abstract

Introduction There is growing interest in the impact of greenness exposure on airway diseases, but the impact of greenness on lung function in children is limited. We aimed to investigate the associations between greenness surrounding schools and lung function in children and whether these associations are modified by air pollution exposure.

Methods Between 2012 and 2013, a cross-sectional survey and spirometry were performed among 6740 school children. Lung function patterns were determined as obstructive forced expiratory volume 1 s/forced vital capacity (FEV1/FVC <0.8) or restrictive (FEV1/FVC ≥0.8 but FVC <80% of predicted). School greenness was defined by Normalized difference vegetation index (NDVI) and soil-adjusted vegetation index. Nitrogen dioxide, sulphur dioxide and particular matter concentrations were assessed using a spatiotemporal model and national monitoring data. Two-level generalised linear models were used to investigate associations and interactions.

Results Overall, an IQR in NDVI within 500 m was associated with higher FEV1 (+57 mL 95% CI 44 to 70) and FVC (+58 mL 95% CI 43 to 73). NDVI was similarly associated with 25% reduced odds of spirometric restriction (OR: 0.75, 95% CI 0.65 to 0.86). However, among children exposed to the highest compared with the lowest quartile of particulate matter, increasing NDVI was paradoxically associated with lower −40 mL FVC (95% CI −47 to –33, p interaction <0.05).

Discussion Our findings suggest that, in this study population, greening urban areas may promote lung health in low–moderate pollution areas but not in high air pollution areas. If the findings are replicated in other moderate-to-high pollution settings, this highlights a need to have a flexible green policy.

  • respiratory measurement
  • paediatric lung disaese

Data availability statement

Data are available upon reasonable request. See author contributions for specific data sets.

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