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Background: With global climate change, the health threats of ambient high temperature have received widespread attention. However, latest spatio-temporal patterns of the non-communicable diseases (NCDs) burden attributable to high temperature have not been systematically reported. We aimed to analyze vulnerable areas and populations based on a detailed profile for the NCDs burden attributable to high temperature globally., Methods: We obtained data from the Global Burden of Diseases (GBD) Study (2019) to describe the temporal and spatial patterns of NCDs burden attributable to high temperature globally from 1990-2019. Then we analyzed the differences by region, sex, and socio-demographic index (SDI). Finally, the age‑period‑cohort (APC) model was utilized to explore the age, period, and cohort effects of NCDs mortality caused by high temperature., Results: In 2019, the number of deaths and Disability-adjusted life years (DALYs) from high-temperature-related NCDs was about 150,000 and 3.4 million globally, of which about 70% were in South Asia and North Africa and Middle East, and the burden was higher in men. Among 204 countries and territories, the highest age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) were observed in Oman and United Arab Emirates, respectively. The global burden showed an upward trend from 1990 to 2019, with an EAPC of 3.66 (95%CI: 3.14-4.18) for ASMR and 3.68 (95%CI: 3.16-4.21) for ASDR. Cardiovascular diseases were the main contributors to the global burden of high-temperature-related NCDs in 2019. The age and period effect in APC model showed an increasing trend globally. There was a significant negative correlation between SDI and both ASMR (r = -0.17) and ASDR (r = -0.20) from 1990 to 2019., Conclusion: There was an increasing trend of the global burden of high-temperature-related NCDs. The burden was likely to be higher in males and the elderly, as well as in countries and regions with less economically and socially developed and in tropical climates. Surveillance and prevention measures should be implemented with a focus on these vulnerable areas and susceptible populations., (© 2024. The Author(s).)

Background: The digital economy based on the internet and IT is developing rapidly in China, which makes a profound impact on urban environmental quality and residents' health activities. Thus, this study introduces environmental pollution as a mediating variable based on Grossman's health production function to explore the impact of digital economic development on the health of the population and its influence path., Methods: Based on the panel data of 279 prefecture-level cities in China from 2011 to 2017, this paper investigates the acting mechanism of digital economic development on residents' health by employing a combination of mediating effects model and spatial Durbin model., Results: The development of digital economy makes direct improvement on residents' health condition, which is also obtained indirectly by means of environmental pollution mitigation. Besides, from the perspective of spatial spillover effect, the development of digital economy also has a significant promoting effect on the health of adjacent urban residents, and further analysis reveals that the promoting effect in the central and western regions of China is more pronounced than that in the eastern region., Conclusions: Digital economy can have a direct promoting effect on the health of residents, and environmental pollution has an intermediary effect between digital economy and residents' health; At the same time, there is also a regional heterogeneity among the three relationships. Therefore, this paper believes that the government should continue to formulate and implement scientific digital economy development policies at the macro and micro levels to narrow the regional digital divide, improve environmental quality and enhance the health level of residents., (© 2023. The Author(s).)

Background: With the accelerated global integration and the impact of climatic, ecological and social environmental changes, China will continue to face the challenge of the outbreak and spread of emerging infectious diseases and traditional ones. This study aims to explore the spatial and temporal evolutionary characteristics of the incidence of Class B notifiable infectious diseases in China from 2007 to 2020, and to forecast the trend of it as well. Hopefully, it will provide a reference for the formulation of infectious disease prevention and control strategies., Methods: Data on the incidence rates of Class B notifiable infectious diseases in 31 provinces, municipalities and autonomous regions of China from 2007 to 2020 were collected for the prediction of the spatio-temporal evolution and spatial correlation as well as the incidence of Class B notifiable infectious diseases in China based on global spatial autocorrelation and Autoregressive Integrated Moving Average (ARIMA)., Results: From 2007 to 2020, the national incidence rate of Class B notifiable infectious diseases (from 272.37 per 100,000 in 2007 to 190.35 per 100,000 in 2020) decreases year by year, and the spatial distribution shows an "east-central-west" stepwise increase. From 2007 to 2020, the spatial clustering of the incidence of Class B notifiable infectious diseases is significant and increasing year by year (Moran's I index values range from 0.189 to 0.332, p < 0.05). The forecasted incidence rates of Class B notifiable infectious diseases nationwide from 2021 to 2024 (205.26/100,000, 199.95/100,000, 194.74/100,000 and 189.62/100,000) as well as the forecasted values for most regions show a downward trend, with only some regions (Guangdong, Hunan, Hainan, Tibet, Guangxi and Guizhou) showing an increasing trend year by year., Conclusions: The current study found that since there were significant regional disparities in the prevention and control of infectious diseases in China between 2007 and 2020, the reduction of the incidence of Class B notifiable infectious diseases requires the joint efforts of the surrounding provinces. Besides, special attention should be paid to provinces with an increasing trend in the incidence of Class B notifiable infectious diseases to prevent the re-emergence of certain traditional infectious diseases in a particular province or even the whole country, as well as the outbreak and spread of emerging infectious diseases., (© 2022. The Author(s).)

Background: In this research, the factors that influence the self-precautionary behavior during the pandemic are explored with the combination of social support and a risk perception attitude framework., Methods: An online survey was conducted among 429 members to collect information on demographic data, social support, perceptions of outbreak risk, health self-efficacy, and self-precautionary behaviors with the guide of the Social Support Scale, the COVID-19 Risk Perception Scale, the Health Self-Efficacy Scale and the Self-precautionary Behavior Scale., Results: The research shows that among the three dimensions of social support, both objective support and support utilization negatively predict risk perception, while subjective support positively predicts health self-efficacy; health self-efficacy and risk perception significantly predict self-precautionary behavior; the relationship between risk perception and self-precautionary behavior is significantly moderated by health self-efficacy., Conclusions: The combined influence of social capital and risk perception attitudinal frameworks on self-precautionary behavior is highlighted in this study, with the relationship between the public's risk perception, health self-efficacy, and self-precautionary behavior intentions examined against the background of coronavirus disease 2019 (COVID-19). These findings contribute to understanding the impact of social capital factors on risk perception and health self-efficacy, which provides insight into the current status and influencing factors of the public's precautionary behavior and facilitates early intervention during a pandemic., (© 2021. The Author(s).)