MODELING THE EFFECT OF TEMPERATURE ON OZONE-RELATED MORTALITY

被引:26
|
作者
Wilson, Ander [1 ]
Rappold, Ana G. [2 ]
Neas, Lucas M. [2 ]
Reich, Brian J. [1 ]
机构
[1] N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA
[2] US EPA, Environm Publ Hlth Div, Chapel Hill, NC 27599 USA
来源
ANNALS OF APPLIED STATISTICS | 2014年 / 8卷 / 03期
关键词
Air pollution; monotone regression; mortality; ozone-temperature interaction; semi-parametric regression; spatial modeling; DISTRIBUTED LAG MODELS; SHORT-TERM MORTALITY; AIR-POLLUTION; EXPOSURE; COMMUNITIES; SENSITIVITY; REGRESSION; MORBIDITY; CURVE;
D O I
10.1214/14-AOAS754
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Climate change is expected to alter the distribution of ambient ozone levels and temperatures which, in turn, may impact public health. Much research has focused on the effect of short-term ozone exposures on mortality and morbidity while controlling for temperature as a confounder, but less is known about the joint effects of ozone and temperature. The extent of the health effects of changing ozone levels and temperatures will depend on whether these effects are additive or synergistic. In this paper we propose a spatial, semi-parametric model to estimate the joint ozone-temperature risk surfaces in 95 US urban areas. Our methodology restricts the ozone-temperature risk surfaces to be monotone in ozone and allows for both nonadditive and nonlinear effects of ozone and temperature. We use data from the National Mortality and Morbidity Air Pollution Study (NMMAPS) and show that the proposed model fits the data better than additive linear and nonlinear models. We then examine the synergistic effect of ozone and temperature both nationally and locally and find evidence of a nonlinear ozone effect and an ozone-temperature interaction at higher temperatures and ozone concentrations.
引用
收藏
页码:1728 / 1749
页数:22
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