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Association of individual green space exposure with the incidence of asthma and allergic rhinitis: a systematic review and meta-analysis
Authors:Wu  Birong  Guo  Xianwei  Liang  Mingming  Sun  Chenyu  Gao  Juan  Xie  Peng  Feng  Linya  Xia  Weihang  Liu  Haixia  Ma  Shaodi  Zhao  Dongdong  Qu  Guangbo  Sun  Yehuan
Institution:1.Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
;2.AMITA Health Saint Joseph Hospital Chicago, 2900 N. Lake Shore Drive, Chicago, IL, 60657, USA
;3.Chaohu Hospital, Anhui Medical University, Hefei, 238006, Anhui, China
;4.Center for Evidence-Based Practice, Anhui Medical University, Hefei, 230032, Anhui, China
;
Abstract:

The association between allergic respiratory diseases, such as asthma and allergic rhinitis (AR), and green space (GS) remains controversial. Our study aimed to summarize and synthesize the association between individual GS exposure and the incidence of asthma/AR. We systematically summarized the qualitative relationship between GS exposure and asthma and AR. The pooled odds ratio (OR) with 95% confidence intervals (CIs) was used to estimate the effect of the Normalized Difference Vegetation Index (NDVI) on asthma and AR. A total of 21 studies were included for systematic review, and 8 of them underwent meta-analysis. In the meta-analysis of current asthma, the 0?<?radius?≤?100 m group, 100?<?radius?≤?300 m group, and 500?<?radius?≤?1000 m group presented weak negative associations between the NDVI and current asthma. For ever asthma, slight positive associations existed in the 0?<?radius?≤?100 m group and 300?<?radius?≤?500 m group. In addition, the NDVI might slightly reduce the risk of AR in radius of 100 m and 500 m. Our findings suggest that the effects of GS exposure on asthma and AR were not significant. Differences in GS measurements, disease diagnoses and adjusted confounders across studies may have an impact on the results. Subsequent studies should consider potential confounding factors and use more accurate GS exposure measurements to better understand the impact of GS exposure on respiratory disease in the population.

Keywords:
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