Data from: Clarifying life lost due to cold and heat: a new approach using annual time series.

Objective: To clarify whether deaths associated with hot and cold days are among the frail who would have died anyway in the next few weeks or months. Design: Time series regression analysis of annual deaths in relation to annual summaries of cold and heat. Setting: London, UK. Participants: 3 530 280 deaths from all natural causes among London residents between October 1949 and September 2006. Main outcome measures: Change in annual risk of death (all natural cause, cardiovascular and respiratory) associated with each additional 1°C of average cold (or heat) below (above) the threshold (18°C) across each year. Results: Cold years were associated with increased deaths from all causes. For each additional 1° of cold across the year, all-cause mortality increased by 2.3% (95% CI 0.7% to 3.8%), after adjustment for influenza and secular trends. The estimated association between hot years and all-cause mortality was very imprecise and thus inconclusive (effect estimate 1.7%, −2.9% to 6.5%). These estimates were broadly robust to changes in the way temperature and trend were modelled. Estimated risk increments using weekly data but otherwise comparable were cold: 2.0% (2.0% to 2.1%) and heat: 3.9% (3.4% to 3.8%). Conclusions: In this London annual series, we saw an association of cold with mortality which was broadly similar in magnitude to that found in published daily studies and our own weekly analysis, suggesting that most deaths due to cold were among individuals who would not have died in the next 6 months. The estimated association with heat was imprecise, with the CI including magnitudes found in daily studies but also including zero.研究目标：明确与冷热极端天气相关的死亡案例，是否属于那些在后续数周或数月内本就会离世的体弱人群。研究设计：针对年度死亡数据与冷热天气年度汇总指标开展时间序列回归分析。研究场景：英国伦敦。研究对象：1949年10月至2006年9月期间，伦敦居民中所有自然原因死亡病例共计3530280例。主要结局指标：以18℃为阈值，将年度平均气温低于（高于）该阈值的寒冷（炎热）程度每增加1℃时，各类全因死亡、心血管疾病及呼吸系统疾病的年度死亡风险变化情况。研究结果：寒冷年份与全因死亡人数增加相关。在校正流感流行与长期时间趋势后，年度每额外增加1℃的寒冷程度，全因死亡率上升2.3%（95%置信区间：0.7%~3.8%）。而炎热年份与全因死亡率的关联估计精度极低，因此尚无定论（效应估计值为1.7%，95%置信区间：-2.9%~6.5%）。上述估计结果在温度与趋势的建模方式调整后仍保持大体稳健。若采用周度数据开展可比分析，得到的风险增量分别为：寒冷相关2.0%（2.0%~2.1%），炎热相关3.9%（3.4%~3.8%）。研究结论：在本次伦敦年度数据序列中，我们观察到寒冷与死亡率存在关联，其关联强度与已发表的每日尺度研究及本次周度分析结果大体相近，提示大多数寒冷相关死亡者属于那些无法在后续6个月内存活的人群。本次估计的炎热相关关联精度不足，其置信区间既包含了每日尺度研究中观测到的关联强度，也包含了零效应。