Li Qi1, Yuan Gao2, Jun Yang3, Xian-Bin Ding4, Yu Xiong4, Kun Su4, Tian Liu5, Qin Li4, Wen-Ge Tang4, Qi-Yong Liu6. 1. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; Chongqing Municipal Center for Disease Control and Prevention, Chongqing 400042, China. 2. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China. 3. Institute for Environmental and Climate Research, Jinan University, Guangzhou 510515, China. 4. Chongqing Municipal Center for Disease Control and Prevention, Chongqing 400042, China. 5. Jingzhou Center for Disease Control and Prevention, Hubei 434000, China. 6. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China. Electronic address: liuqiyong@icdc.cn.
Abstract
OBJECTIVE: To examine the association between absolute humidity (AH) and influenza and pneumonia (P&I) mortality, and to quantify P&I mortality burden attributable to non-optimum AHs among elderly people aged ≥65 years in Chongqing, the largest municipality of China. METHODS: Daily data of P&I mortality from 2012 to 2018, and the contemporaneous meteorological data in the study area were collected. Distributed lag non-linear model (DLNM) was applied to estimate the non-linear and delayed effects of absolute humidity (AH) on P&I mortality. Then, attributable deaths were calculated for the dry and moist AH, defined as AH below and above the minimum mortality AH (MMAH), respectively. Moderate and extreme AHs were defined using cutoffs at the 2.5th and 97.5th percentiles of AH. RESULTS: The relationship between AH and P&I mortality was a U-shaped curve. The MMAH was 11.5 g/m3 (46.4th percentile). In total, 25.7% (95% confidence interval: 10.0-38.2) of P&I mortality (4673 deaths) was attributed to non-optimum AHs. Low AHs were responsible for 12.7% of the P&I death burden (95%CI: 0.2-20.1), while high AHs for 13.0% (95%CI: -9.4-25.7). Extreme low and high AHs accounted for 3.7% (95%CI: 0.1-6.8) and 3.0% (95%CI: 0-5.4) of P&I mortality. CONCLUSIONS: Our study showed that both low AHs and high AHs are responsible for considerable AH-related P&I mortality burden among elderly people. Our results may have important public health implications for the development of relevant intervention policies to reduce P&I deaths among the elderly.
OBJECTIVE: To examine the association between absolute humidity (AH) and influenza and pneumonia (P&I) mortality, and to quantify P&Imortality burden attributable to non-optimum AHs among elderly people aged ≥65 years in Chongqing, the largest municipality of China. METHODS: Daily data of P&Imortality from 2012 to 2018, and the contemporaneous meteorological data in the study area were collected. Distributed lag non-linear model (DLNM) was applied to estimate the non-linear and delayed effects of absolute humidity (AH) on P&Imortality. Then, attributable deaths were calculated for the dry and moist AH, defined as AH below and above the minimum mortalityAH (MMAH), respectively. Moderate and extreme AHs were defined using cutoffs at the 2.5th and 97.5th percentiles of AH. RESULTS: The relationship between AH and P&Imortality was a U-shaped curve. The MMAH was 11.5 g/m3 (46.4th percentile). In total, 25.7% (95% confidence interval: 10.0-38.2) of P&Imortality (4673 deaths) was attributed to non-optimum AHs. Low AHs were responsible for 12.7% of the P&Ideath burden (95%CI: 0.2-20.1), while high AHs for 13.0% (95%CI: -9.4-25.7). Extreme low and high AHs accounted for 3.7% (95%CI: 0.1-6.8) and 3.0% (95%CI: 0-5.4) of P&Imortality. CONCLUSIONS: Our study showed that both low AHs and high AHs are responsible for considerable AH-related P&Imortality burden among elderly people. Our results may have important public health implications for the development of relevant intervention policies to reduce P&Ideaths among the elderly.