Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia, United States of America.
PLoS One. 2024 Sep 20;19(9):e0310545. doi: 10.1371/journal.pone.0310545. eCollection 2024.
The objective of this study is to determine the relationship between short-term temperature variability on neighboring days and mortality. The change in maximum temperature in Northern Virginia, Richmond, Roanoke, and Norfolk, Virginia, on neighboring days was calculated from airport observations and associated with total mortality over a multi-county area surrounding each weather station. The association between day-to-day temperature change and mortality, lagged over a 28-day period, was analyzed using distributed lag non-linear models that controlled for air quality, temporal trends, and other factors. Days following large temperature declines were associated with an increased risk of mortality in three of the four locations, and temperature increases were linked to higher mortality risk in two cities. For example, the relative risk of mortality for a 12°C daily temperature decline (1st percentile) was 1.74 [0.92, 3.27] in Roanoke and 1.16 [0.70, 1.92] in Richmond. The net effect of short-term temperature increases was smaller, with the largest relative risk of 1.03 [0.58, 1.83] for a 12°C increase (99th percentile) in maximum temperature in Norfolk. In Richmond and Roanoke, there was an observed lagged effect of increased mortality (maximum relative risks varying from 1.08 to 1.10) that extended from 5 to 25 days associated with large temperature declines of 15°C or more. In contrast, there was a strong and immediate (lag 0-3 day) increase in the risk of mortality (1.10 to 1.15) in northern Virginia and Norfolk when the temperature increase exceeded 10°C (short-term warming). In general, consecutive day warming had a more immediate mortality impact than short-term cooling, when the peak mortality is lagged by one week or more. However, cooling of at least 10°C after a hot (summer) day reduced mortality relative to comparable cooling following a cold (winter) day, which is associated with high mortality. This differential mortality response as a function of temperature suggests that there is some relationship between average temperature, temperature variability, and season. The findings of this study may be useful to public health officials in developing mitigation strategies to reduce the adverse health risks associated with short-term temperature variability.
本研究旨在探讨相邻日短期温度变化与死亡率之间的关系。通过机场观测计算了弗吉尼亚州北部、里士满、罗阿诺克和诺福克相邻日最高温度的变化，并将其与每个气象站周围多县地区的总死亡率相关联。使用分布式滞后非线性模型分析了 28 天滞后期内每日温度变化与死亡率之间的关联，该模型控制了空气质量、时间趋势和其他因素。在四个地点中的三个地点，紧随大的温度下降之后的日子与死亡率升高有关，而在两个城市中，温度升高与更高的死亡率风险有关。例如，在罗阿诺克，12°C 日温度下降（第 1 百分位数）的死亡率相对风险为 1.74[0.92,3.27]，在里士满为 1.16[0.70,1.92]。短期温度升高的净效应较小，最大相对风险为 1.03[0.58,1.83]，即诺福克最高温度升高 12°C（99 百分位数）。在里士满和罗阿诺克，观察到与 15°C 或更高的大温度下降相关的死亡率滞后增加效应（最大相对风险从 1.08 到 1.10），持续 5 至 25 天。相比之下，在弗吉尼亚州北部和诺福克，当温度升高超过 10°C（短期变暖）时，死亡率（1.10 到 1.15）会立即（滞后 0-3 天）增加。一般来说，连续日升温比短期降温对死亡率的影响更为直接，当高峰期死亡率滞后一周或更长时间时更是如此。然而，与类似的低温（冬季）降温相比，炎热（夏季）日之后至少 10°C 的降温会降低死亡率，这与高死亡率有关。这种作为温度函数的死亡率差异反应表明，平均温度、温度变异性和季节之间存在一定的关系。本研究的结果可能对公共卫生官员制定缓解策略以降低短期温度变异性相关的不良健康风险有用。
