Background Previous studies have focused on the respiratory system and skin damage caused by refractory ceramic fibers (RCFs). However, investigations into cardiovascular health of workers exposed to RCFs are insufficient. There is limited research on the association between occupational RCFs exposure and abnormal blood pressure, as well as the potential underlying mechanisms. Objective To explore the association between occupational exposure to RCFs and abnormal blood pressure, and to analyze the role of serum 8-hydroxy-2’-deoxyguanosine (8-OHdG) in this relationship, providing a reference for comprehensive health protection strategies for RCFs-exposed workers. Methods Using a cluster sampling method, 311 workers engaged in the production and processing of RCFs at a large RCFs enterprise were selected as the study population. A questionnaire survey was conducted to collect demographic information and other relevant data. The workers’ total dust, respirable fiber, and noise exposure levels were measured. Blood pressure was measured during occupational health examinations, and blood samples were collected. Based on blood pressure levels, the participants were divided into three groups: normotension, prehypertension, and hypertension. Serum 8-OHdG concentrations were determined by enzyme-linked immunosorbent assay (ELISA). Ordinal logistic regression and multiple linear regression models were applied to evaluate the associations of exposures to noise and RCFs with abnormal blood pressure and serum 8-OHdG levels. The mediating effect of serum 8-OHdG on the relationship between occupational RCFs exposure and abnormal blood pressure was analyzed using the PROCESS 4.1 macro. Results All 311 RCFs workers had varying levels of occupational exposure to RCFs, among whom 113 were also exposed to noise. The overall prevalences of prehypertension and hypertension among the participants were 49.84% and 11.25%, respectively. In the noise-exposed group, the prevalences of normotension, prehypertension, and hypertension were 44.2%, 43.4%, and 12.4%, respectively, which showed no statistically significant difference compared to the non-noise-exposed group (35.9%, 53.5%, and 10.6%, respectively; P=0.652). Significant differences were observed in the prevalences of normotension, prehypertension, and hypertension among workers with different levels of total dust exposure (P=0.033) and respirable fiber exposure (P=0.034). The differences in serum 8-OHdG concentrations across these groups were also statistically significant (P<0.05). Multiple regression analyses showed that both total dust exposure level (OR=1.83, 95%CI: 1.34, 2.51) and respirable fiber exposure level (OR=1.85, 95%CI: 1.31, 2.62) were positively associated with the detection of abnormal blood pressure. Furthermore, total dust exposure level (β=5.85, 95%CI: 0.53, 11.17) and respirable fiber exposure level (β=6.04, 95%CI: 0.14, 11.94) were positively associated with serum 8-OHdG concentrations. Further analysis indicated that the severity of abnormal blood pressure was positively associated with serum 8-OHdG concentrations (β=10.54, 95%CI: 3.62, 17.46). Mediation analysis demonstrated that serum 8-OHdG mediated the relationship between RCFs total dust exposure levels and the risk of abnormal blood pressure (P<0.05), accounting for 8.63% of the total effect. However, no mediating effect of serum 8-OHdG was observed in the association between RCFs respirable fiber exposure levels and the risk of abnormal blood pressure (P>0.05). Conclusion Occupational exposure to RCFs is closely associated with an increased risk of abnormal blood pressure and elevated serum 8-OHdG levels. Oxidative stress may play a mediating role in the relationship between RCF exposure and abnormal blood pressure.

Objective: To analyze the trajectories of cognitive function changes and their influencing factors among the elderly, so as to provide evidence for the prevention and intervention of cognitive impairment in this population. Methods: Data were obtained from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which was conducted in 2011, 2014, and 2018. Information on demographic characteristics and lifestyle behaviors of elderly individuals aged ≥65 years was collected. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Group-based trajectory modeling was conducted using MMSE scores from 2011, 2014, and 2018 to identify trajectories of cognitive function change. The optimal trajectory model was determined using the Bayesian information criterion, Akaike information criterion, and average posterior probability. Factors affecting cognitive function trajectories among the elderly were analyzed using a Multinomial logistic regression model. Results: Data were collected from 2 614 individuals, with the mean age of (78.20±8.93) years. There were 1 251 males (47.86%) and 1 363 females (52.14%). The group-based trajectory model identified three distinct cognitive function trajectories, defined as the stable group, slow decline group, and rapid decline group, consisting of 2 187 (83.66%), 170 (6.50%), and 257 (9.83%) individuals, respectively. Multinomial logistic regression analysis showed that compared with the stable group, each 1-year increase in age was associated with a 315.7% higher risk of being classified into the slowly declining group (OR=4.157, 95%CI: 2.922-5.914) and a 214.6% higher risk of being classified into the rapidly declining group (OR=3.146, 95%CI: 2.428-4.076). Compared with elderly individuals with no formal education, those with primary/junior high school education had a 67.5% lower risk of being classified into the slowly declining group (OR=0.325, 95%CI: 0.207-0.511) and a 30.2% lower risk of being classified into the rapidly declining group (OR=0.698, 95%CI: 0.505-0.964). Compared with unmarried/divorced/widowed elderly individuals, those who were married had a 31.0% lower risk of being classified into the rapid decline group (OR=0.690, 95%CI: 0.509-0.935). Conclusions Based on the CLHLS data, cognitive function trajectories among individuals aged ≥65 years were classified into three patterns: stable, slow decline, and rapid decline. Increased age was associated with a higher risk of cognitive decline, while higher educational level and being married demonstrated protective effects against cognitive deterioration.

Climate change poses a significant threat to public health. Existing studies on the health impacts of climate change focus primarily on chronic and infectious diseases, with limited research on injury. To address this gap, this issue launched a special column titled "Climate change and injuries". Through interdisciplinary integration of atmospheric science and public health, we explored the impact of climate change on injury risk and burden from diverse perspectives. This initiative aims to deepen a comprehensive understanding of the impact of climate change on human health, enhance China's capacity to address climate-related health risks, reduce associated disease burden, and provide scientific evidence for targeted adaptation measures.

Background Previous studies found that high temperature and heatwave increase the risk of traffic injuries. The complex road conditions in Yunnan Province result in frequent traffic accidents. However, there is limited evidence on the correlation between heatwave and traffic injuries in Yunnan Province. Objective To assess the association between heatwave events and traffic injuries, to estimate its disease burden, and to identify relevant sensitive groups. Methods We collected data on traffic injury cases and concurrent meteorological information from four surveillance sites in Yunnan Province, China: Dali, Lufeng, Zhaoyang, and Qilin from May to September each year from 2015 to 2023. Traffic injury cases refer to patients who visited the outpatient or emergency departments of local surveillance hospitals for the first time due to traffic injuries. Meteorological data were derived from the fifth generation atmosphericreanalysis dataset of the global climate provided by the European Centre for Medium-Range Weather Forecasts. A time-stratified case-crossover design combined with distributed lag non-linear model was used to analyze the association between short-term exposure to heatwave and traffic injuries. We also conducted subgroup analyses by sex, age, occupation, injury cause, activity at the time of injury occurrence, and severity of injury. Results A total of 34764 traffic injury surveillance cases were included in the analysis. The risk of traffic injuries occurred during heatwave was 1.13 times (95%CI: 1.07, 1.20) greater than those occurred during non-heatwave, and 2.64% (95%CI: 1.49%, 3.73%) of traffic injuries were attributed to heatwave exposure throughout the study period. The results of stratified analysis showed greater impacts of heatwave on the risk of traffic injuries in female [odds ratio (OR)=1.17, attributable fraction (AF)=3.23%], people aged 15-64 years (OR=1.13, AF=2.68%), farmers/workers (OR=1.22, AF=4.07%), people with non-motor vehicle traffic injuries (OR=1.17, AF=3.24%), people who were driving or riding when injuries occurred (OR=1.12, AF=2.43%), and people with minor injuries (OR=1.18, AF=3.49%) ( P<0.05). Longer duration [excess risk (ER)=0.99%] and greater intensity (ER=4.12%) of heatwave had greater impacts on the risk of traffic injuries (P<0.05). Conclusion Heatwave events are associated with an increased risk of traffic injuries. Female, people aged 15-64, farmers/workers, people with non-motor vehicle traffic injuries, those injured while driving/riding a vehicle, and people with minor injuries are particularly vulnerable. The findings suggest that targeted mitigation and adaptation measures should be taken to address the risk of traffic injuries associated with extreme climate events.

Background Injury poses a serious threat to human health. As global warming continues to intensify, there is an urgent need to explore the impact of temperature changes on injury deaths. However limited research has focused on this issue. Objective To investigate the relationship between daily mean temperature change (Tm) and injury death, as well as to estimate the associated future death burden in Hunan Province. Methods We employed an individual-level, time-stratified case-crossing design to establish a conditional logistic regression model to analyze the exposure-response relationship between daily mean temperature change and injury death in Hunan Province from 2013 to 2018. Consequently, we conducted subgroup analysis of gender, age group, and injury type. Finally, we estimated the excess burden of injury death attributable to temperature changes under a sustainable development path [low emission scenario (SSP1-2.6)], regional competition path [high emission scenario (SSP3-7.0)], or fossil fuel development path [very high emission scenario (SSP5-8.5)]. Results The study collected 155577 injury deaths in Hunan Province. The results indicated that for each 1 ℃ increment in daily mean temperature, the cumulative excess risk (CER) of injury mortality among Hunan residents increased by 0.71% (95%CI: 0.53%, 0.90%). Notably, the CER for intentional injuries (1.06%, 95%CI: 0.51%, 1.61%) was higher than that for unintentional injuries (0.66%, 95%CI: 0.46%, 0.87%). Warmer temperatures were positively associated with CER of mortality due to drowning, falls, transport injuries, assaults, and suicides, while they were negatively associated with mortality due to poisoning. Compared with 2010–2019, for 2090–2099, the excess mortality rate (EMR) due to ambient temperature increase in Hunan Province under the SSP5-8.5 scenario (14.62/100000, 95%CI: 10.81/100000, 18.40/100000) would be higher than that of the SSP3-7.0 scenario (10.28/100000, 95%CI: 7.58/100000, 12.97/100000) and the SSP1-2.6 scenario (3.35/100000, 95%CI: 2.46/100000, 4.23/100000); the EMR would be around 2.5 times among men (20.64/100000, 95%CI: 14.44/100000, 26.8/100000) than that among women (8.33/100000, 95%CI: 3.98/100000, 12.6/100000). Among unintentional injuries, the leading contributors to EMR would be drowning (4.46/100000), falls (3.96/100000), and transport injuries (2.96/100000). And among intentional injuries, the EMR for suicide (2.08/100000) would be higher than that for assault (0.47/100000). Conclusion Climate warming will increase the total burden of injury-related deaths among residents in Hunan Province, especially in the absence of effective mitigation strategies and measures. It is necessary to strengthen the prevention and control of severe injuries closely related to temperature changes, such as drowning, falls, traffic, and suicides injuries, in order to reduce injury deaths associated with climate change.

Background Under the background of global warming, research on association between ambient temperature and risk of injury is needed. Objective To examine the effect of temperature on injury in Bao'an district, Shenzhen and identify the sensitive population, thereby providing a scientific basis for formulating prevention and control strategies and measures of injury. Methods The injury reports from the Injury Surveillance System and the meteorological data of Bao'an District between 2018 to 2022 were collected. The meteorological data were sourced from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) land reanalysis data. Based on time-stratified case-crossover design, conditional logistic regression combined with distributed lag nonlinear model was used to evaluate the exposure-response association between ambient temperature and injury. The stratified analyses were further conducted by gender, age, and causes of injury. Results A total of 156205 injury cases were collected from the injury surveillance sentinel hospitals in Bao'an District of Shenzhen from 2018 to 2022, and the median of daily average temperature during the same period was 20.0 ℃. The exposure-response curve showed that the risk of injury was positively correlated with temperature. The linearized analysis revealed that each 1°C increase in temperature was associated with a 1.05% (95%CI: 0.68%, 1.42%) rise in injury risk (ER). Notably, the effect was greater in females (ER=1.31%, 95%CI: 0.67%, 1.94%) than males (ER=0.92%, 95%CI: 0.47%, 1.37%). Among age groups, adults ＞60 years faced the highest risk (ER=1.91%, 95%CI: −0.36%, 4.24%). The top three temperature-associated injury risks were sharp instrument injuries (ER=2.19%, 95%CI: 1.16%, 3.22%), animal injuries (ER=1.71%, 95%CI: 0.86%, 2.56%), and blunt injuries (ER=071%, 95%CI: −0.08%, 1.51%). The impact of temperature on unintentional injuries (ER=1.11%, 95%CI: 0.72%, 1.49%) was higher than that on intentional injuries (ER=0.43%, 95%CI: −0.85%, 1.72%). Severe injuries (ER=2.20%, 95%CI: −3.09%, 7.77%) were more affected by temperature than mild injuries (ER=1.00%, 95%CI: 0.58%, 1.43%) and moderate injuries (ER=1.15%, 95%CI: 0.42%, 1.89%). Conclusion The increase in ambient temperature associates with injury occurrence, and the impact of temperature exhibits obvious heterogeneity among different populations, indicating that targeted intervention measures should be taken for different populations and types of injuries.

Climate change is a significant environmental concern in the 21^st century. It can directly and indirectly affect public health, making it a major public health problem. This review focused on the relationship between meteorological factors and health-related behaviors such as physical activity, sleep, dietary behavior, and social contact behavior. The results indicated that meteorological factors such as temperature, relative humidity, wind speed, atmospheric pressure, and rainfall are associated with the four health behaviors. Physical activity levels are negatively associated with temperature, relative humidity, and rainfall. Sleep quality tends to decrease under extreme temperatures and extreme weather events. Dietary behavior is influenced by high and low temperatures, low pressure, and daylight duration, which in turn affects appetite and food intake. Social contact frequency decreases in response to extreme temperatures, increased rainfall, and extreme weather events. However, there are differences in the strength and direction of the associations between meteorological factors and health-related behaviors in various studies. Research on the combined effects of multiple meteorological factors exposure on health-related behaviors is rare, and the mechanisms underlying the associations are unclear. Therefore, there is a need for more multi-center, large-scale studies to explore the biological and behavioral mechanisms behind these associations, which will help clarify the complex effects of meteorological factors on human health behaviors and provide scientific evidence for policy-making, thereby mitigating the negative impact of climate change on public health.

Falls are one of the most common injuries, with a high prevalence and risk of disability, which poses the greatest threat to the health of the elderly. Falls are influenced by a variety of factors, including environmental factors such as slippery pavements, poor meteorological conditions, and inadequate lighting. The Sixth Assessment Report of the United Nations Intergovernmental Panel on Climate Change (IPCC) stated that climate change has become more frequent and stronger in recent years, which may threat people's health and lives. This review summarized the progress of epidemiological studies on the association between meteorological factors (e.g. temperature, precipitation, frost, and snowfall) and falls, and found that most of the studies focused on the association between temperature and falls, and the results of different studies varied greatly. While the studies on the association between other meteorological factors and falls were relatively few. Moreover, the mechanisms behind the associations were unclear. Therefore, we point out that it is necessary to further conduct large-sample and multi-centre studies to evaluate the effects of exposure to multiple meteorological factors, and further to explore the mechanisms of the associations, which may provide scientific evidence for better response to climate change.

Stroke is a critical health issue in China, and carotid artery stenosis and plaque play key roles in its prevalence. Despite the acknowledged significance of this condition, detailed information regarding the prevalence of carotid artery stenosis and plaque across the Chinese population has been scarce. This study analyzed data from the China Stroke High-risk Population Screening and Intervention Program for 2020-2021, focusing on 194 878 Chinese adults aged 40 years and above. It assessed the prevalence of carotid artery stenosis and plaque and identified their associated risk factors. Results revealed a standardized prevalence of 0.40% for carotid artery stenosis and 36.27% for carotid plaque. Notably, the highest rates of stenosis were observed in north and south China at 0.61%, while southwestern China exhibited the highest plaque prevalence at 43.17%. Key risk factors included older age, male gender, hypertension, diabetes, stroke, smoking, and atrial fibrillation. This study highlights significant geographical and demographic disparities in the prevalence of these conditions, underlining the urgent need for targeted interventions and policy reforms. These measures are essential for reducing the incidence of stroke and improving patient outcomes, addressing this significant health challenge in China.
Humans ; China/epidemiology* ; Male ; Female ; Prevalence ; Middle Aged ; Carotid Stenosis/epidemiology* ; Risk Factors ; Aged ; Adult ; Plaque, Atherosclerotic/epidemiology* ; Stroke/epidemiology* ; Aged, 80 and over

The rapid development of artificial intelligence （AI） technology provides new opportunities for the modernisation of traditional Chinese medicine （TCM） diagnosis. By analysing the foundation， research progress and difficulties of the combination of AI and TCM diagnosis， it is concluded that AI has made remarkable development in intelligence-driven modernization of TCM tongue diagnosis， pulse diagnosis， listening and smelling diagnosis and text processing， and there are useful explorations in the field of constructing data-driven TCM diagnostic model and multidisciplinary integration of TCM diagnostic models. However， the current integration of AI technology in TCM diagnosis still faces many challenges， such as the scarcity and uneven quality of clinical data， the limited ability of AI algorithms to express TCM thinking model of syndrome differentiation and empirical knowledge， and the possible existence of ethical and privacy issues. By systematically sorting out the current research status and development direction of AI-empowered TCM diagnostics， it is proposed to promote the application of AI technology in TCM diagnostics in four aspects， namely， strengthening the construction of TCM big data and talent cultivation， encouraging cross-disciplinary cooperation， improving the legal and ethical framework， and promoting the popularity of the technology in primary care， so as to enhance the modernisation of TCM diagnostics.