Bureau of Environmental Surveillance and Policy, New York City Department of Health and Mental Hygiene, New York, New York 10007, USA.
Environ Health Perspect. 2010 Jan;118(1):80-6. doi: 10.1289/ehp.0900906.
To assess the public health risk of heat waves and to set criteria for alerts for -excessive heat, various meteorologic metrics and models are used in different jurisdictions, generally without systematic comparisons of alternatives. We report such an analysis for New York City that compared maximum heat index with alternative metrics in models to predict daily variation in warm-season natural-cause mortality from 1997 through 2006.
We used Poisson time-series generalized linear models and generalized additive models to estimate weather-mortality relationships using various metrics, lag and averaging times, and functional forms and compared model fit.
A model that included cubic functions of maximum heat index on the same and each of the previous 3 days provided the best fit, better than models using maximum, minimum, or average temperature, or spatial synoptic classification (SSC) of weather type. We found that goodness of fit and maximum heat index-mortality functions were similar using parametric and nonparametric models. Same-day maximum heat index was linearly related to mortality risk across its range. The slopes at lags of 1, 2, and 3 days were flat across moderate values but increased sharply between maximum heat index of 95 degrees F and 100 degrees F (35-38 degrees C). SSC or other meteorologic variables added to the maximum heat index model moderately improved goodness of fit, with slightly attenuated maximum heat index-mortality functions.
In New York City, maximum heat index performed similarly to alternative and more complex metrics in estimating mortality risk during hot weather. The linear relationship supports issuing heat alerts in New York City when the heat index is forecast to exceed approximately 95-100 degrees F. Periodic city-specific analyses using recent data are recommended to evaluate public health risks from extreme heat.
为了评估热浪对公共健康的风险，并为高温预警设定标准，不同司法管辖区使用了各种气象指标和模型，但通常没有对替代方案进行系统比较。我们报告了对纽约市的此类分析，该分析比较了 1997 年至 2006 年期间，预测暖季自然原因死亡率的模型中最高热指数与替代指标的差异。
我们使用泊松时间序列广义线性模型和广义加性模型，使用各种指标、滞后和平均时间以及函数形式来估计天气与死亡率之间的关系，并比较模型拟合度。
一个包含前 3 天最高热指数三次函数的模型提供了最佳拟合，优于使用最高、最低或平均温度或天气类型空间同步分类（SSC）的模型。我们发现，使用参数和非参数模型，拟合优度和最高热指数与死亡率的函数相似。同一天的最高热指数与死亡率风险呈线性关系，在其范围内。在 1、2 和 3 天的滞后处，斜率在中等值范围内较为平坦，但在 95 华氏度至 100 华氏度（35-38 摄氏度）之间急剧增加。SSC 或其他气象变量添加到最高热指数模型中，适度提高了拟合优度，而最高热指数与死亡率的函数略有减弱。
在纽约市，最高热指数在估计炎热天气下的死亡率风险方面与替代指标和更复杂的指标表现相似。线性关系支持在纽约市发布高温警报，当预测热指数超过约 95-100 华氏度时。建议使用最近的数据定期进行特定于城市的分析，以评估极端高温对公共健康的风险。
