Spatiotemporal Distribution and Epidemiological Characteristics of Hospital Admissions for Carbon Monoxide Poisoning in Guangdong, China, 2013–2020

• Published in: Biomedical and environmental sciences Vol. 35; no. 10; pp. 943 - 953
• Main Authors: XIAO, Bin, ZHANG, You Miao, ZHOU, Jing, XU, Cheng Dong, HU, Wei, WEN, Wei, CHEN, Jia Bin, SUN, Cheng Ye
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2022; Guangdong Province Hospital for Occupational Disease Prevention andTreatment%Guangdong Provincial Key Laboratory of Occupational Disease Prevention and Treatment,Guangzhou510300,Guangdong,China%National Institute for Occupational Health and Poison Control,Chinese Center for Disease Control andPrevention,Beijing 100050,China%School of Public Health,Sun Yat-sen University,Guangzhou 510030,Guangdong,China; National Institute for Occupational Health and Poison Control,Chinese Center for Disease Control andPrevention,Beijing 100050,China; State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Scienceand Natural Resource Research,Chinese Academy of Sciences,Beijing 100101,China%University of ChineseAcademy of Sciences,Beijing 100101,China%Guangdong Province Hospital for Occupational Disease Prevention andTreatment
• Subjects: Carbon monoxide poisoning; Distributed lag nonlinear model; Hospitalization; Spatial-temporal model; Distributed lag nonlinear model; Carbon monoxide poisoning; Hospitalization; Spatial-temporal model
• ISSN: 0895-3988; 2214-0190
• DOI: 10.3967/bes2022.053

This study aimed to determine the spatiotemporal distribution and epidemiological characteristics of hospital admissions for carbon monoxide poisoning (COP) in Guangdong, China, from 2013 to 2020. Data on age- and sex- specific numbers of hospital admissions due to COP in Guangdong (2013–2020) were collected. Daily temperatures were downloaded through the China Meteorological Data Sharing Service System. We analyzed temporal trends through time series decomposition and used spatial autocorrelation analysis to detect spatial clustering. The distributed lag nonlinear model was used to quantify the effects of temperature. There were 48,854 COP admissions over the study period. The sex ratio (male to female) was 1:1.74. The concentration ratios (M) ranged from 0.73–0.82. The highest risk occurred in January (season index = 3.59). Most cases were concentrated in the northern mountainous areas of Guangdong with high-high clustering. COP in the study region showed significant spatial autocorrelation, and the global Moran's I value of average annual hospital admission rates for COP was 0.447 (P < 0.05). Low temperatures were associated with high hospital admission rates for COP, with a lag lasting 7 days. With a lag of 0 days, the effects of low temperatures [5th (12 °C)] on COP were 2.24–3.81, as compared with the reference temperature [median (24 °C)]. COP in Guangdong province showed significant temporal and spatial heterogeneity. Low temperature was associated with a high risk of COP, and the influence had a lag lasting 7 days.