Cold spells have been associated with mortality from a few broad categories of diseases or specific diseases. However, there is a lack of data about the health effects of cold spells on mortality from a wide spectrum of plausible diseases which can reveal a more comprehensive contour of the mortality burden of cold spells. We collected daily mortality data in Guangzhou during 2010–2018 from the Guangzhou Center for Disease Control and Prevention. The quasi-Poisson generalized linear regression model mixed with the distributed lag non-linear model (DLNM) was conducted to examine the health impacts of cold spells for 11 broad causes of death groupings and from 35 subcategories in Guangzhou. Then, we examined the effect modification by age group (0–64 and 65+ years) and sex. Effects of cold spells on mortality generally delayed for 3–5 d and persisted up to 27 d. Cold spells were significantly responsible for increased mortality risk for most categories of deaths, with cumulative relative risk (RR) over 0–27 lagged days of 1.57 [95% confidence interval (CI): 1.48–1.67], 1.95 (1.49–2.55), 1.58 (1.39–1.79), 1.54 (1.26–1.88), 1.92 (1.15–3.22), 1.75, (1.14–2.68), 2.02 (0.78–5.22), 1.92 (1.49–2.48), 1.48 (1.18–1.85), and 1.18 (1.06–1.30) for non-accidental causes, cardiovascular diseases, respiratory diseases, digestive diseases, nervous system diseases, genitourinary diseases, mental diseases, endocrine diseases, external cause and neoplasms, respectively. The magnitudes of the effects of cold spells on mortality varied remarkably among the 35 subcategories, with the largest cumulative RR of 2.87 (1.72–4.79) estimated for pulmonary heart diseases. The elderly and females were at a higher risk of mortality for most diseases after being exposed to cold spells. Increased mortality from a wide range of diseases was significantly linked with cold spells. Our findings may have important implications for formulating effective preventive strategies and early warning response plans that mitigate the health burden of cold spells.

寒假与几种疾病或特定疾病的死亡率有关。但是，缺乏关于冷拼对健康的健康影响的数据，这些数据可能来自多种可能的疾病，这些疾病可能揭示出冷拼的死亡率负担的更全面轮廓。我们从广州市疾病预防控制中心收集了2010-2018年广州的每日死亡率数据。运用拟泊松广义线性回归模型与分布式滞后非线性模型（DLNM）进行了混合，以研究感冒对健康的健康影响，这些疾病对广州市35个子类别的11个主要死亡原因产生了影响。然后，我们研究了年龄段（0-64岁和65岁以上）和性别对效果的影响。寒冷对死亡率的影响通常会延迟3-5天，并持续到27天。在大多数类别的死亡中，冷拼是导致死亡风险增加的重要原因，在0-27个滞后天的累积相对风险（RR）为1.57 [95％置信区间（CI）：1.48-1.67]，1.95（1.49-2.55） ，1.58（1.39–1.79），1.54（1.26–1.88），1.92（1.15-3.22），1.75，（1.14-2.68），2.02（0.78–5.22），1.92（1.49–2.48），1.48（1.18–1.85） ，以及非偶然原因，心血管疾病，呼吸系统疾病，消化系统疾病，神经系统疾病，泌尿生殖系统疾病，精神疾病，内分泌疾病，外因和肿瘤的发生率分别为1.18（1.06-1.30）。在35个子类别中，冷风对死亡率的影响幅度显着不同，最大的累积RR为2.87（1.72-4）。79）估计有肺心病。老年人和女性在暴露于寒潮之后，大多数疾病的死亡风险更高。多种疾病导致的死亡率增加与感冒明显相关。我们的发现可能对制定减轻感冒的健康负担的有效预防策略和预警反应计划具有重要意义。