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新西兰奥塔哥地区每日温度与儿童住院率:病例时间序列分析。

Daily Temperatures and Child Hospital Admissions in Aotearoa New Zealand: Case Time Series Analysis.

机构信息

Section of Epidemiology and Biostatistics, University of Auckland, Auckland 1023, New Zealand.

Department of Statistics, University of Auckland, Auckland 1010, New Zealand.

出版信息

Int J Environ Res Public Health. 2024 Sep 19;21(9):1236. doi: 10.3390/ijerph21091236.

Abstract

The influence of global climate change on temperature-related health outcomes among vulnerable populations, particularly young children, is underexplored. Using a case time series design, we analysed 647,000 hospital admissions of children aged under five years old in New Zealand, born between 2000 and 2019. We explored the relationship between daily maximum temperatures and hospital admissions across 2139 statistical areas. We used quasi-Poisson distributed lag non-linear models to account for the delayed effects of temperature over a 0-21-day window. We identified broad ICD code categories associated with heat before combining these for the main analyses. We conducted stratified analyses by ethnicity, sex, and residency, and tested for interactions with long-term temperature, socioeconomic position, and housing tenure. We found J-shaped temperature-response curves with increased risks of hospital admission above 24.1 °C, with greater sensitivity among Māori, Pacific, and Asian compared to European children. Spatial-temporal analysis from 2013-2019 showed rising attributable fractions (AFs) of admissions associated with increasing temperatures, especially in eastern coastal and densely populated areas. Interactive maps were created to allow policymakers to prioritise interventions. Findings emphasize the need for child-specific and location-specific climate change adaptation policies, particularly for socioeconomically disadvantaged groups.

摘要

全球气候变化对弱势群体(尤其是幼儿)与温度相关的健康结果的影响尚未得到充分研究。本研究采用病例时间序列设计,分析了 2000 年至 2019 年间出生于新西兰、年龄在 5 岁以下的 647,000 名儿童的住院记录。我们在 2139 个统计区域内探讨了每日最高温度与住院人数之间的关系。我们使用拟泊松分布的滞后非线性模型,在 0-21 天的时间窗口内考虑温度的滞后效应。我们在进行主要分析之前,先确定与热相关的广泛 ICD 代码类别,并将这些类别结合起来。我们按族裔、性别和居住地点进行分层分析,并检验了与长期温度、社会经济地位和住房所有权之间的相互作用。我们发现,在 24.1°C 以上的温度范围内,住院风险呈 J 形曲线上升,毛利人、太平洋岛民和亚裔儿童的敏感性高于欧洲儿童。2013-2019 年的时空分析显示,与温度升高相关的住院归因分数(AF)不断上升,尤其是在东部沿海和人口密集地区。我们创建了交互式地图,以便决策者能够优先考虑干预措施。研究结果强调了需要制定针对儿童和特定地点的气候变化适应政策,特别是针对社会经济弱势群体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f481/11432253/29a6862f1a34/ijerph-21-01236-g001.jpg

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