Objective To investigate the modification effect of atmospheric temperature on outpatient visits caused by O₃ in Linzhi City. Methods The daily outpatient data, the daily O₃ concentration and daily meteorological data (including daily average temperature, average relative humidity, etc.) in Linzhi City from 2018 to 2019 were collected. The distributed lag non-liner-model (DLNM) was used to quantitatively evaluate the impact of O₃ in different temperature layers on the risk of outpatient visits. Results At low temperature layers, the cumulative relative risk (CRR) of total outpatient visits and non-injury outpatient visits increased by 53.8%（4.2% -126.9%) and 59.1%（5.8% -139.2%）for every 10 μg/m³ increase of O₃ concentration, respectively. The subgroup analysis showed that for every 10 μg/m³ increase of O₃ concentration at low temperature, the CRR of patients with circulatory diseases, men, women, and people being <14 years old and 14-65 years old increased by 152.1% (15.1% - 451.9%), 58.3% (2.1%-145.5%), 49.2% (3.0% -116.1%), 39.6% (2.5% - 90.3%), and 61% (0.8%-157.1%), respectively. Conclusion The average temperature may have a modifying effect on the outpatient visits caused by O₃ in Linzhi City. In general, the cumulative risk increases as the temperature decreases.

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.