白国霞, 吴君乐, 史恒, 平措卓玛, 李亚杰, 嘎玛仓决, 胡建雄, 李致兴, 刘涛, 马文军. 西藏高原地区气温对人群非意外死亡影响的病例交叉研究[J]. 环境与职业医学, 2022, 39(3): 261-267. DOI: 10.11836/JEOM21462
引用本文: 白国霞, 吴君乐, 史恒, 平措卓玛, 李亚杰, 嘎玛仓决, 胡建雄, 李致兴, 刘涛, 马文军. 西藏高原地区气温对人群非意外死亡影响的病例交叉研究[J]. 环境与职业医学, 2022, 39(3): 261-267. DOI: 10.11836/JEOM21462
BAI Guoxia, WU Junle, SHI Heng, PINGCUO Zhuoma, LI Yajie, GAMA Cangjue, HU Jianxiong, LI Zhixing, LIU Tao, MA Wenjun. Case-crossover study on association between temperature and non-accidental mortality in Tibet Plateau, China[J]. Journal of Environmental and Occupational Medicine, 2022, 39(3): 261-267. DOI: 10.11836/JEOM21462
Citation: BAI Guoxia, WU Junle, SHI Heng, PINGCUO Zhuoma, LI Yajie, GAMA Cangjue, HU Jianxiong, LI Zhixing, LIU Tao, MA Wenjun. Case-crossover study on association between temperature and non-accidental mortality in Tibet Plateau, China[J]. Journal of Environmental and Occupational Medicine, 2022, 39(3): 261-267. DOI: 10.11836/JEOM21462

西藏高原地区气温对人群非意外死亡影响的病例交叉研究

Case-crossover study on association between temperature and non-accidental mortality in Tibet Plateau, China

  • 摘要: 背景 在全球气候变化的背景下,气温将呈持续上升趋势。目前大多数气温与健康的研究是针对低海拔地区,对高原地区的研究甚少。

    目的 分析西藏高原地区气温对人群非意外总死亡的影响,识别脆弱人群,为制定有针对性的气候变化适应政策提供科学依据。

    方法 收集2013—2019年西藏自治区居民死因监测资料、气象数据和大气污染物数据,基于时间分层的病例交叉设计,利用条件logistic回归模型分析气温与死亡的暴露-反应关系,将暴露-反应关系线性化处理获取气温每变化1 ℃的超额死亡风险;计算归因分值评估由气温造成的归因死亡负担;并进一步按照性别、年龄(<65岁,≥65岁)、死因分类(心血管疾病、脑血管疾病和呼吸系统疾病)进行分层分析。通过调整模型参数与变量进行敏感性分析。

    结果 2013—2019年西藏非意外总死亡26045人,气温中位数为5.0 ℃。气温与非意外死亡的暴露-反应关系为死亡风险随着气温降低而升高。气温每降低1 ℃,非意外总死亡的超额死亡风险为2.01%(95%CI:0.94%~3.07%),男性为2.05%(95%CI:0.62%~3.47%),女性为1.96%(95%CI:0.34%~3.56%),均有统计学意义;<65岁人群为1.45%(95%CI:−0.10%~2.98%),无统计学意义,≥65岁人群为2.52%(95%CI:1.04%~3.99%),有统计学意义。心血管疾病死因人群的超额死亡风险为2.65%(95%CI:1.03%~4.24%),脑血管疾病为3.70%(95%CI:0.74%~6.57%),均有统计学意义,而呼吸系统疾病为2.18%(95%CI:−0.14%~4.44%),但无统计学意义。非意外总死亡的归因死亡数为5340(95%CI:2 719~7 528)例,归因分值为20.50%(95%CI:10.44%~28.91%)。一些特定亚组的归因分值较高,如男性(20.72%),≥65岁人群(23.33%)以及心血管疾病死因人群(26.07%)。

    结论 西藏高原地区气温与非意外死亡的暴露-反应关系呈现为死亡风险随着气温降低而升高,疾病负担较大。男性、≥65岁人群、罹患心血管疾病与呼吸系统疾病的人群可能是脆弱人群。

     

    Abstract: Background Under the background of global climate change, temperature has increased dramatically. Most studies about association between temperature and human health are conducted in low-altitude areas, but rarely focus on plateau areas.

    Objective To examine the association between temperature and non-accidental mortality risk in Tibet Plateau, China and to identify vulnerable populations for formulating targeted policies of climate change adaptation.

    Methods The mortality data, meteorological data, and pollutant data of Tibet area between 2013 to 2019 were collected. Based on time-stratified case-crossover design, conditional logistic regression models were used to analyze the exposure-response relationship between temperature and cause-specific mortality, which was linearized to obtain excess risk for 1 ℃ change; attributable fraction was calculated for assessing burden attributable to temperature; and stratified analyses were further conducted by gender, age (<65 years old, ≥65 years old), and causes of death (cardiovascular diseases, cerebrovascular diseases, and respiratory diseases). Sensitivity analyses were conducted by adjusting model parameters and variables.

    Results A total of 26 045 non-accidental deaths were collected in Tibet during 2013 and 2019, and the P50 of temperature was 5.0 ℃. The non-accidental mortality risk increased as temperature become colder. A 1 ℃ decrease in temperature was associated with a 2.01% (95%CI: 0.94%-3.07%) increase in total non-accidental mortality, while the association changed to 2.05% (95%CI: 0.62%-3.47%) for male and 1.96% (95%CI: 0.34%-3.56%) for female, both of statistial significance; 1.45% (95%CI: −0.10%-2.98%) for the people <65 years old (not of significance) and 2.52% (95% CI : 1.04%-3.99%) for the people ≥65 years old (of significance); the excess risk for cardiovascular mortality was 2.65% (95%CI: 1.03%-4.24%), for cerebrovascular mortality was 3.70% (95%CI: 0.74%-6.57%), both of statistical significance, and for respiratory mortality was 2.18% (95%CI: −0.14%-4.44%), without significance. The total attribution number of non-accidental mortality was 5340 (95%CI: 2719-7528), and the total attributable fraction was 20.50% (95%CI: 10.44%-28.91%). The attributable fractions were higher in specific subgroups like male (20.72%), people ≥65 years (23.33%), and people with cardiovascular diseases (26.07%).

    Conclusion The exposure-response relationship between temperature and non-accidental mortality in Tibet showes that the non-accidental mortality risk increase as temperature become colder. The attributable burden of disease is heavy. Residents being male, ≥65 years, with cardiovascular diseases and respiratory diseases may be vulnerable to nonoptimal temperature.

     

/

返回文章
返回