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Epidemiological analysis of association between lagged meteorological variables and pneumonia in wet-dry tropical North Australia, 2006-2016.
Journal of Exposure Science and Environmental Epidemiology ( IF 4.5 ) Pub Date : 2019-10-07 , DOI: 10.1038/s41370-019-0176-8
Oyelola A Adegboye 1 , Emma S McBryde 1 , Damon P Eisen 1, 2
Affiliation  

Pneumonia accounts for 1.5% of all overnight hospital admission in Australia. We investigated the nonlinear and delay effect of weather (temperature and rainfall) on pneumonia. This study was based on a large cohort of inpatients that were hospitalized due to pneumonia between 2006 and 2016. Cases were identified using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD10-AM) codes J10.0*-J18.0*. A time-varying distributed lag nonlinear model was used to estimate the burden of the disease attributable to varying weather-lag pneumonia relationships and identify vulnerable groups. The relative risk (presented as logRR) associated with temperature was immediate and highest in late winter at the lowest temperature of 16 °C (logRR = 1.13, 95% confidence intervals (CI): 0.59, 1.66). The cumulative effect over the lag range 0-8 weeks revealed two peaks for low (12 mm, logRR = 0.73, 95% CI: 0.32, 1.13) and moderately high rainfall (51 mm) with logRR of 1.15 (95% CI: 0.10, 2.20). A substantial number, 22.50% (95% empirical CI: 1.83, 34.68), of pneumonia cases were attributable to temperature (mostly due to moderate low temperatures). Females and indigenous (Aboriginal and Torres Strait Islander) patients were particularly vulnerable to the impact of temperature-related pneumonia. In this study, we highlighted the delayed effects and magnitude of burden of pneumonia that is associated with low temperature and rainfall. The findings in this study can inform a better understanding of the health implications and burden associated with pneumonia to support discussion-making in healthcare and establish a strategy for prevention and control of the disease among vulnerable groups.

中文翻译:

2006-2016年北澳大利亚热带湿润热带地区滞后气象变量与肺炎之间关联的流行病学分析。

肺炎占澳大利亚所有过夜医院入院的1.5%。我们研究了天气(温度和降雨)对肺炎的非线性和延迟影响。本研究基于2006年至2016年因肺炎住院的大量住院患者。病例使用国际疾病和相关健康问题统计分类第十次修订本澳大利亚修订版(ICD10-AM)代码J10.0进行识别。 * -J18.0 *。使用随时间变化的分布式滞后非线性模型来估计由于天气滞后性肺炎关系的变化而引起的疾病负担,并确定易感人群。与温度相关的相对风险(以logRR表示)是立即发生的,并且在冬季后期,最低温度为16°C时最高(logRR = 1.13,95%置信区间(CI):0.59,1.66)。在0-8周的滞后范围内的累积效应显示出两个峰值,分别为低(12 mm,logRR = 0.73,95%CI:0.32,1.13)和中等高降雨(51 mm),logRR为1.15(95%CI:0.10) ,2.20)。相当多的22.50%的肺炎病例(95%的经验CI:1.83,34.68)归因于温度(主要是由于中度低温)。女性和土著(土著和托雷斯海峡岛民)患者特别容易受到温度相关性肺炎的影响。在这项研究中,我们强调了与低温和降雨有关的肺炎的延迟影响和负担的严重性。
更新日期:2019-10-07
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