Majeed Haris, Moore G W K
Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada.
Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada.
BMJ Open. 2018 Apr 13;8(4):e020822. doi: 10.1136/bmjopen-2017-020822.
It is well known that climate variability and trends have an impact on human morbidity and mortality, especially during the winter. However, there are only a handful of studies that have undertaken quantitative investigations into this impact. We evaluate the association between the UK winter asthma mortality data to a well-established feature of the climate system, the Scandinavian (SCA) pattern.
Time series analysis of monthly asthma mortality through the period of January 2001 to December 2015 was conducted, where the data were acquired from the UK's Office for National Statistics. The correlations between indices of important modes of climate variability impacting the UK such as the North Atlantic Oscillation as well as the SCA and the asthma mortality time series were computed. A grid point correlation analysis was also conducted with the asthma data with sea level pressure, surface wind and temperature data acquired from the European Centre for Medium-Range Weather Forecasts.
We find that sea level pressure and temperature fluctuations associated with the SCA explain ~20% (>95% CL) of variance in the UK asthma mortality through a period of 2001-2015. Furthermore, the highest winter peak in asthma mortality occurred in the year 2015, during which there were strong northwesterly winds over the UK that were the result of a sea level pressure pattern similar to that associated with the SCA.
Our study emphasises the importance of incorporating large-scale geospatial analyses into future research of understanding diseases and its environmental impact on human health.
众所周知，气候变率和趋势会对人类发病率和死亡率产生影响，尤其是在冬季。然而，仅有少数研究对这种影响进行了定量调查。我们评估了英国冬季哮喘死亡率数据与气候系统中一个既定特征——斯堪的纳维亚（SCA）模式之间的关联。
对2001年1月至2015年12月期间的月度哮喘死亡率进行时间序列分析，数据取自英国国家统计局。计算了影响英国的重要气候变率模式指数（如北大西洋涛动以及SCA）与哮喘死亡率时间序列之间的相关性。还对哮喘数据与从欧洲中期天气预报中心获取的海平面气压、地面风和温度数据进行了格点相关分析。
我们发现，与SCA相关的海平面气压和温度波动在2001 - 2015年期间解释了英国哮喘死亡率约20%（>95%置信区间）的方差。此外，哮喘死亡率最高的冬季峰值出现在2015年，在此期间，英国上空有强劲的西北风，这是由一种与SCA相关的海平面气压模式导致的。
我们的研究强调了在未来理解疾病及其对人类健康的环境影响的研究中纳入大规模地理空间分析的重要性。
