Johnson Nicholaus P, Del Favero-Campbell Alexandra, Nori-Sarma Amruta, Amezcua-Smith Audrey, Lewis Brandon, Chen Chen, Lin Chengyi, Foo Damien, Byun Garam, Choi Hayon Michelle, Kim Honghyok, Berman Jesse D, Son Ji-Young, Warren Joshua L, Chen Kai, Burrows Kate, Fong Kelvin C, Goldsmith Leo, Meadows Marie-Claire, Smith Morrison, Stewart Rory, Heo Seulkee, Lin Shuqi, Ning Xuejuan, Choi Yongsoo, Bell Michelle L, Deziel Nicole C
Yale School of Public Health, New Haven, Connecticut, 06510, USA.
Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada.
Curr Environ Health Rep. 2025 Aug 20;12(1):30. doi: 10.1007/s40572-025-00494-7.
The impacts of environmental health risk factors, including temperature, vary across urban and rural areas. Application of different metrics of rurality and urbanicity can yield different risk characterizations. We aimed to identify, describe, and quantify how urban/rural metrics are used in epidemiologic studies of ambient temperature and health across the United States (US).
Using PubMed and Scopus, we identified epidemiologic studies published between January 2010 and March 2025 that examined ambient temperature and health in the US and included a defined, quantitative metric of urbanicity/rurality. Titles, abstracts, and full texts were evaluated by two independent reviewers. Data from included studies were extracted using a predetermined tool.
Of the 11,013 studies resulting from our search, 36 were included. We identified 23 metrics drawing from 10 data sources. The most frequently used metrics were population density and size from the US Census ( = 11 studies). Other metrics reflected connectivity and proximity to surrounding areas, such as the US Census’s Urban-Rural Classification ( = 7 studies), and the US Department of Agriculture’s Rural-Urban Commuting Area Codes ( = 4 studies) and Rural-Urban Continuum Codes ( = 2 studies). Additional metrics captured features related to the natural environment, built environment, and employment. Many studies did not provide a rationale for metric selection.
Urbanicity and rurality metrics have moved beyond population size and density to include other features. Providing rationales for choice of metric or the differential vulnerability or adaptive capacity captured by the metric could bolster understanding of urban-rural differences in the impact of temperature on health.
The online version contains supplementary material available at 10.1007/s40572-025-00494-7.
包括温度在内的环境健康风险因素的影响在城乡地区存在差异。应用不同的城乡指标会产生不同的风险特征描述。我们旨在识别、描述和量化美国城乡指标在环境温度与健康的流行病学研究中的使用情况。
利用PubMed和Scopus数据库,我们检索了2010年1月至2025年3月期间发表的、研究美国环境温度与健康关系且包含明确的城乡定量指标的流行病学研究。由两名独立评审员对标题、摘要和全文进行评估。使用预先确定的工具提取纳入研究的数据。
在我们检索到的11,013项研究中,有36项被纳入。我们从10个数据源中识别出23个指标。最常用的指标是美国人口普查中的人口密度和规模(11项研究使用)。其他指标反映了与周边地区的连通性和接近程度,如美国人口普查的城乡分类(7项研究使用)、美国农业部的城乡通勤区代码(4项研究使用)和城乡连续体代码(2项研究使用)。其他指标还涵盖了与自然环境、建成环境和就业相关的特征。许多研究没有提供指标选择的理由。
城乡指标已从人口规模和密度扩展到包括其他特征。为指标选择或该指标所反映的差异脆弱性或适应能力提供理由,有助于加深对温度对健康影响的城乡差异的理解。
在线版本包含可在10.1007/s40572-025-00494-7获取的补充材料。