Istituto per la Ricerca e l'Innovazione Biomedica, National Research Council (CNR-IRIB), Via Ugo La Malfa 153, 90146, Palermo, Italy.
Institute for Marine Sciences, National Research Council (CNR-ISMAR), Calata Porta di Massa, 80133, Napoli, Italy.
Sci Rep. 2019 Aug 12;9(1):11683. doi: 10.1038/s41598-019-48178-1.
An association between climatic conditions and asthma mortality has been widely assumed. However, it is unclear whether climatic variations have a fingerprint on asthma dynamics over long time intervals. The aim of this study is to detect a possible correlation between climatic indices, namely the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation, and asthma mortality rates over the period from 1950 to 2015 in the contiguous US. To this aim, an analysis of non-stationary and non-linear signals was performed on time series of US annual asthma mortality rates, AMO and PDO indices to search for characteristic periodicities. Results revealed that asthma death rates evaluated for four different age groups (5-14 yr; 15-24 yr; 25-34 yr; 35-44 yr) share the same pattern of fluctuation throughout the 1950-2015 time interval, but different trends, i.e. a positive (negative) trend for the two youngest (oldest) categories. Annual asthma death rates turned out to be correlated with the dynamics of the AMO, and also modulated by the PDO, sharing the same averaged ∼44 year-periodicity. The results of the current study suggest that, since climate patterns have proved to influence asthma mortality rates, they could be advisable in future studies aimed at elucidating the complex relationships between climate and asthma mortality.
人们普遍认为气候条件与哮喘死亡率之间存在关联。然而,目前尚不清楚气候的变化是否会对长时间内的哮喘动态产生影响。本研究的目的是检测在 1950 年至 2015 年期间,美国大陆的气候指数(即大西洋多年代际振荡和太平洋年代际振荡)与哮喘死亡率之间是否存在可能的相关性。为此,对美国每年的哮喘死亡率、AMO 和 PDO 指数的时间序列进行了非平稳和非线性信号分析,以寻找特征周期性。结果表明,评估的四个不同年龄组(5-14 岁;15-24 岁;25-34 岁;35-44 岁)的哮喘死亡率在 1950-2015 年期间波动模式相同,但趋势不同,即两个最年轻(最年长)的组别呈正(负)趋势。年度哮喘死亡率与 AMO 的动态相关,也受 PDO 的调制,具有相同的平均约 44 年周期性。本研究的结果表明,由于气候模式已被证明会影响哮喘死亡率,因此在未来研究中阐明气候与哮喘死亡率之间的复杂关系时,这些模式可能是明智的。