Influence of the Spatial Resolution of the Exposure Estimate in Determining the Association between Heat Waves and Adverse Health Outcomes

Abstract

Area-level estimates of temperature might lead to exposure misclassification in studies examining associations between heat waves and health outcomes. Our study compared the association between heat waves and preterm birth (PTB) or nonaccidental death (NAD) using exposure metrics at varying levels of spatial resolution: ZIP codes, 12.5 km, and 1 km. Using geocoded residential addresses on birth (1990–2010) and death (1997–2010) records from Alabama, we implemented a time-stratified case–crossover design to examine the association between heat waves and PTB or NAD. ZIP code and 12.5-km heat wave indexes (HIs) were derived using air temperatures from Phase 2 of the North American Land Data Assimilation System (NLDAS–2). We downscaled NLDAS–2 data, using land surface temperatures from the Moderate Resolution Imaging Spectroradiometer product, to estimate fine spatial resolution HIs (1 km). The association between heat waves and PTB or NAD was significant and positive using ZIP code, 12.5-km, and 1-km exposure metrics. Moreover, results show that these three exposure metric analyses produced similar effect estimates. Urban heat islands were evident with the 1-km metric. When analyses were stratified by rurality, we found that associations in urban areas were more positive than those in rural areas. Comparing results of models with a varying spatial resolution of the exposure metric allows for examination of potential bias associated with exposure misclassification.

地区层级的温度评估，可能导致检验热浪和健康后果的关联性研究产生暴露的错误分类。我们的研究运用在各空间分辨率层级的暴露指标，比较热浪与早产（PTB）或非意外死亡（NAD）之间的关联性：邮政区号、12.5公里，以及1公里。我们运用阿拉巴马州出生（1990至2010年）与死亡（1997至2010年）的地理编码之居住地址，执行时间分层的交叉研究设计，以检视热浪和PTB或NAD之间的关联性。本研究运用北美土地数据模拟系统（NLDAS-2）第二阶段的空气温度，推导邮政编码与12.5公里的热浪指标 (HIs)。我们运用中分辨率成像光谱仪产出的地表温度，缩减NLDAS-2数据，以评估精细的空间分辨率His (1公里)。运用邮政编码、12.5公里以及1公里暴露指标时，热浪与PTB或NAD之间的关联性相当显着。此外，研究结果显示，这三大暴露指标分析生产了相似的效应评估。1公里指标中的城市热岛相当明显。我们发现，当分析以乡村性进行分层时，城市地区的关联性较乡村地区更为明显。比较不同空间分辨率的暴露指标之模型结果，得以考量检视与暴露的错误分类相关的潜在偏见。

Los cálculos del nivel-área de la temperatura podrían conducir a una mala clasificación en estudios dedicados a examinar las asociaciones entre las olas de calor y las consecuencias para la salud. Nuestro estudio comparó la asociación entre olas de calor y alumbramientos prematuros (PTB) o muerte no accidental (NAD) usando métricas de exposición a varios niveles de resolución espacial: códigos ZIP, 12.5 km, y 1 km. Usando registros de direcciones residenciales geocodificadas al nacimiento (1990–2010) y muerte (1997–2010) de Alabama, implementamos un diseño de caso cruzado estratificado en el tiempo para examinar la asociación entre olas de calor y PTB o NAD. El código ZIP y los índices de olas de calor de 12.5 km (HIs) se derivaron usando las temperaturas del aire de la Fase 2 del Sistema de Asimilación Norteamericano de Datos de la Tierra (NLDAS–2). Bajamos la escala de los datos NLDAS–2 usando temperaturas de la superficie terrestre del producto de Imagen Espectro-radiométrica a Resolución Moderada, para calcular los HIs de resolución espacial fina (1 km). La asociación entre olas de calor y PTB o NAD fue significativa y positiva usando el código ZIP, 12.5 km y métricas de exposición de 1 km. Aún más, los resultados muestran que estos análisis métricos de tres exposiciones produjeron estimativos de efectos similares. Las islas de calor urbanas fueron evidentes con la métrica de 1 km. Cuando los análisis fuero estratificados por la ruralidad, hallamos que las asociaciones en áreas urbanas eran más positivas que en áreas rurales. La comparación de los resultados de los modelos con la métrica de la exposición a variable resolución espacial permite el análisis de sesgo potencial asociado con clasificación equivocada de la exposición.

Key Words:

• case–crossover design
• heat waves
• nonaccidental death
• preterm birth
• temperature

关键词:

• 交叉案例设计
• 热浪
• 非意外死亡
• 早产
• 温度。

Palabras clave:

• alumbramiento prematuro
• diseño de caso cruzado
• muerte no accidental
• olas de calor
• temperatura

Acknowledgments

The authors are grateful to Sung Ho Kim from the Department of Computer Science at Virginia Tech for helping us to develop the code for downscaling temperature data.

Additional information

Funding

The results reported herein correspond to specific aims of grant R01 ES023029 to investigator Julia M. Gohlke from the National Institute of Environmental Health Sciences. This work was also supported in part by CNIMS Contract HDTRA1-17-0118 from the Defense Threat Reduction Agency and Grant 1R01GM109718 from the National Institutes of Health.

Notes on contributors

Connor Y. H. Wu

CONNOR Y. H. WU is currently Assistant Professor in the Department of Social Sciences and Leadership, College of Arts & Sciences, Troy University, Troy, AL 36082. E-mail: [email protected]. His research interests include environmental geographic information systems, heat waves, transportation safety, and remote sensing.

Benjamin F. Zaitchik

BENJAMIN F. ZAITCHIK is an Associate Professor in the Department of Earth and Planetary Sciences, Zanvyl Krieger School of Arts & Sciences, Johns Hopkins University, Baltimore, MD 21218. E-mail: [email protected]. His research is directed at understanding, managing, and coping with climatic and hydrologic variability.

Samarth Swarup

SAMARTH SWARUP is a Research Assistant Professor in the Network Dynamics and Simulation Science Laboratory at the Biocomplexity Institute of Virginia Tech, Blacksburg, VA, 24061. E-mail: [email protected]. His research themes focus on resilience and sustainability, computational social science, and complex networks and network dynamics.

Julia M. Gohlke

JULIA M. GOHLKE is an Associate Professor in the Department of Population Health Sciences at Virginia Tech, Blacksburg, VA 24061. E-mail: [email protected]. Her research interests include human health implications of global environmental change, bioinformatic and alternative model methods for estimating human health risk, and human health risk assessment and communication after large-scale environmental disasters.