Emergency room visits (ERVs) among occupational groups associated with ambient conditions in Taiwan.

OBJECTIVE: This population-based study explored emergency room visits (ERVs) from all-causes, circulatory and respiratory diseases among different occupational groups in Taiwan associated with ambient average temperature. METHOD: Daily area-age-sex specific ERVs records were obtained from the Taiwan's Ministry of Health and Welfare from 2009 to 2018. Distributed lag-nonlinear model (DLNM) was used to estimate the exposure-response relationships between daily average temperature and ERVs for all-causes, circulatory and respiratory diseases by occupational groups. Random-effects meta-analysis was used to pool the overall cumulative relative risk (RR) and 95% confidence interval (CI). RESULTS: The exposure-response curves showed ERVs of all-cause and respiratory diseases increased with rising temperature across all occupational groups. These effects were consistently stronger among younger (20-64 years old) and outdoor workers. In contrast, ERVs risk from circulatory diseases increased significantly during cold snaps, with a substantially higher risk for female workers. Interestingly, female workers, regardless of indoor or outdoor work, consistently showed a higher risk of respiratory ERVs during hot weather compared to males. Younger workers (20-64 years old) exhibited a higher risk of ERVs, likely due to job profiles with greater exposure to extreme temperatures. Notably, the highest risk of all-causes ERVs was observed in outdoor male laborers (union members), followed by farmers and private employees, with the lowest risk among indoor workers. Conversely, female indoor workers and female farmers faced the highest risk of respiratory ERVs. Again, female farmers with consistent outdoor exposure had the highest risk of circulatory ERVs during cold conditions. CONCLUSION: Our findings highlighted the complexity of temperature-related health risks associated with different occupational contexts. The population-level insights into vulnerable occupational groups could provide valuable comprehension for policymakers and healthcare practitioners.

The impact of apparent temperature on the emergency visits for traumatic fractures in Hangzhou, China.

BACKGROUND: Traumatic fractures occur frequently worldwide. However, research remains limited on the association between short-term exposure to temperature and traumatic fractures. This study aims to explore the impact of apparent temperature (AT) on emergency visits (EVs) due to traumatic fractures. METHODS: Based on EVs data for traumatic fractures and the contemporary meteorological data, a generalized Poisson regression model along with a distributed lag nonlinear model (DLNM) were undertaken to determine the impact of AT on traumatic fracture EVs. Subgroup analysis by gender and age and sensitivity analysis were also performed. RESULTS: A total of 25,094 EVs for traumatic fractures were included in the study. We observed a wide "J"-shaped relationship between AT and risk of traumatic fractures, with AT above 9.5 °C positively associated with EVs due to traumatic fractures. The heat effects became significant at cumulative lag 0-11 days, and the relative risk (RR) for moderate heat (95th percentile, 35.7 °C) and extreme heat (99.5th percentile, 38.8 °C) effect was 1.311 (95% CI: 1.132-1.518) and 1.418 (95% CI: 1.191-1.688) at cumulative lag 0-14 days, respectively. The cold effects were consistently non-significant on single or cumulative lag days across 0-14 days. The heat effects were higher among male and those aged 18-65 years old. The sensitivity analysis results remained robust. CONCLUSION: Higher AT is associated with cumulative and delayed higher traumatic fracture EVs. The male and those aged 18-65 years are more susceptible to higher AT.

Associations between PM2.5 Components and Mortality of Ischemic Stroke, Chronic Obstructive Pulmonary Disease and Diabetes in Beijing, China.

Ischemic stroke (IS), chronic obstructive pulmonary disease (COPD) and diabetes mellitus (DM) account for a large burden of premature deaths. However, few studies have investigated the associations between fine particular matter (PM2.5) components and mortality of IS, COPD and DM. We aimed to examine these associations in Beijing, China. Data on daily mortality, air pollutants and meteorological factors from 2008 to 2011 in Beijing were collected. Daily concentrations of five PM2.5 components, namely, sulfate ion (SO42-), ammonium ion (NH4+), nitrate ion (NO3-), organic matter (OM) and black carbon (BC), were obtained from the Tracking Air Pollution (TAP) database in China. The association between PM2.5 components and daily deaths was explored using a quasi-Poisson regression with the distributed lag nonlinear model (DLNM). The average daily concentrations of SO42-, NH4+, NO3-, OM and BC were 11.24, 8.37, 12.00, 17.34 and 3.32 µg/m3, respectively. After adjusting for temperature, relative humidity, pressure, particulate matter less than 10 µm in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2), an IQR increase in OM at lag day 2 and lag day 6 was associated with an increased DM mortality risk (RR 1.038; 95% CI: 1.005-1.071) and COPD mortality risk (RR 1.013; 95% CI: 1.001-1.026). An IQR increase in BC at lag day 0 and lag day 6 was associated with increased COPD mortality risk (RR 1.228; 95% CI: 1.017-1.48, RR 1.059; 95% CI: 1.001-1.121). Cumulative exposure to SO42- and NH4+ was associated with an increased mortality risk for IS, with the highest effect found for lag of 0-7 days (RR 1.085; 95% CI: 1.010-1.167, RR 1.083; 95% CI: 1.003-1.169). These effects varied by sex and age group. This study demonstrated associations of short-term exposure to PM2.5 components with increased risk of IS, COPD and DM mortality in the general population. Our study also highlighted susceptible subgroups.

Scaling features in high-concentrations PM2.5 evolution: the Ignored factor affecting scarlet fever incidence.

As an acute respiratory disease, scarlet fever has great harm to public health. Some evidence indicates that the time distribution pattern of heavy PM2.5 pollution occurrence may have an impact on health risks. This study aims to reveal the relation between scaling features in high-concentrations PM2.5 (HC-PM2.5) evolution and scarlet fever incidence (SFI). Based on the data of Hong Kong from 2012 to 2019, fractal box-counting dimension (D) is introduced to capture the scaling features of HC-PM2.5. It has been found that index D can quantify the time distribution of HC-PM2.5, and lower D values indicate more cluster distribution of HC-PM2.5. Moreover, scale-invariance in HC-PM2.5 at different time scales has been discovered, which indicates that HC-PM2.5 occurrence is not random but follows a typical power-law distribution. Next, the exposure-response relationship between SFI and scale-invariance in HC-PM2.5 is explored by Distributed lag non-linear model, in conjunction with meteorological factors. It has been discovered that scale-invariance in HC-PM2.5 has a nonlinear effect on SFI. Low and moderate D values of HC-PM2.5 are identified as risk factors for SFI at small time-scale. Moreover, relative risk shows a decreasing trend with the increase of exposure time. These results suggest that exposure to short-term clustered HC-PM2.5 makes individual more prone to SFI than exposure to long-term uniform HC-PM2.5. This means that individuals in slightly-polluted regions may face a greater risk of SFI, once the PM2.5 concentration keeps rising. In the future, it is expected that the relative risk of scarlet fever for a specific region can be estimated based on the quantitative analysis of scaling features in high-concentrations PM2.5 evolution.

Seasonal impact of diurnal temperature range on intracerebral hemorrhage in middle-aged and elderly people in central China.

Objectives: This study investigated the seasonal impact of diurnal temperature range (DTR) on hospitalization rates for intracerebral hemorrhage (ICH) in middle-aged and elderly adults. Methods: We collected data on the DTR and hospitalization records of ≥45-year-old patients with ICH in 2019 in Hunan Province, central China. Time-series analyses were performed using a distributed lag nonlinear model. Results: Overall, 54,690 hospitalizations for ICH were recorded. DTR showed a nonlinear relationship with ICH hospitalization in both middle-aged and elderly populations (45-59 and ≥60 years, respectively). During spring, a low DTR coupled with persistently low temperatures increased ICH risk in both age groups, while a high DTR was associated with an increased risk in the middle-aged group only (relative risk [RR], 1.24; 95% confidence interval [CI], 1.21 to 1.27). In the summer, a low DTR combined with persistently high temperatures was linked to a higher risk exclusively in the middle-aged group. A high DTR in the autumn was correlated with increased risk in both age groups. In winter, either a low DTR with a continuously low temperature or a high DTR elevated the risk solely in the elderly population (RR, 1.37; 95% CI, 1.00 to 1.69). In the elderly group, the impact of DTR on hospitalization risk manifested within a 5-day period. Conclusion: The impact of DTR on ICH hospitalization risk differed significantly across seasons and between age groups. Elderly individuals demonstrated greater sensitivity to the impact of DTR. Weather forecasting services should emphasize DTR values, and interventions targeting sensitive populations are needed.

Epidemic Characteristics and Meteorological Risk Factors of Hemorrhagic Fever With Renal Syndrome in 151 Cities in China From 2015 to 2021: Retrospective Analysis.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant public health threat to the population in China. Previous epidemiological evidence indicates that HFRS is climate sensitive and influenced by meteorological factors. However, past studies either focused on too-narrow geographical regions or investigated time periods that were too early. There is an urgent need for a comprehensive analysis to interpret the epidemiological patterns of meteorological factors affecting the incidence of HFRS across diverse climate zones. OBJECTIVE: In this study, we aimed to describe the overall epidemic characteristics of HFRS and explore the linkage between monthly HFRS cases and meteorological factors at different climate levels in China. METHODS: The reported HFRS cases and meteorological data were collected from 151 cities in China during the period from 2015 to 2021. We conducted a 3-stage analysis, adopting a distributed lag nonlinear model and a generalized additive model to estimate the interactions and marginal effects of meteorological factors on HFRS. RESULTS: This study included a total of 63,180 cases of HFRS; the epidemic trends showed seasonal fluctuations, with patterns varying across different climate zones. Temperature had the greatest impact on the incidence of HFRS, with the maximum hysteresis effects being at 1 month (-19 ºC; relative risk [RR] 1.64, 95% CI 1.24-2.15) in the midtemperate zone, 0 months (28 ºC; RR 3.15, 95% CI 2.13-4.65) in the warm-temperate zone, and 0 months (4 ºC; RR 1.72, 95% CI 1.31-2.25) in the subtropical zone. Interactions were discovered between the average temperature, relative humidity, and precipitation in different temperature zones. Moreover, the influence of precipitation and relative humidity on the incidence of HFRS had different characteristics under different temperature layers. The hysteresis effect of meteorological factors did not end after an epidemic season, but gradually weakened in the following 1 or 2 seasons. CONCLUSIONS: Weather variability, especially low temperature, plays an important role in epidemics of HFRS in China. A long hysteresis effect indicates the necessity of continuous intervention following an HFRS epidemic. This finding can help public health departments guide the prevention and control of HFRS and develop strategies to cope with the impacts of climate change in specific regions.

Delayed effects of air pollution on public bike-sharing system use in Seoul, South Korea: A time series analysis.

BACKGROUND: As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution. METHOD: To assess the short-term impact of daily exposure to multiple air pollutants (PM2.5, PM10, NO2, and O3) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018-2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19. RESULTS: We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM2.5, 0.89% (0.85% to 0.94%) for PM10, 0.87% (0.82% to 0.91%) for O3, and 0.92% (0.87% to 0.98%) for NO2, reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants. CONCLUSIONS: Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured.

The effects of ambient temperature on road traffic injuries in Jinan city: a time-stratified case-crossover study based on distributed lag nonlinear model.

Objectives: The impact of climate change, especially extreme temperatures, on health outcomes has become a global public health concern. Most previous studies focused on the impact of disease incidence or mortality, whereas much less has been done on road traffic injuries (RTIs). This study aimed to explore the effects of ambient temperature, particularly extreme temperature, on road traffic deaths in Jinan city. Methods: Daily data on road traffic deaths and meteorological factors were collected among all residents in Jinan city during 2011-2020. We used a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the association between daily mean temperature, especially extreme temperature and road traffic deaths, and its variation in different subgroups of transportation mode, adjusting for meteorological confounders. Results: A total of 9,794 road traffic deaths were collected in our study. The results showed that extreme temperatures were associated with increased risks of deaths from road traffic injuries and four main subtypes of transportation mode, including walking, Bicycle, Motorcycle and Motor vehicle (except motorcycles), with obviously lag effects. Meanwhile, the negative effects of extreme high temperatures were significantly higher than those of extreme low temperatures. Under low-temperature exposure, the highest cumulative lag effect of 1.355 (95% CI, 1.054, 1.742) for pedal cyclists when cumulated over lag 0 to 6 day, and those for pedestrians, motorcycles and motor vehicle occupants all persisted until 14 days, with ORs of 1.227 (95% CI, 1.102, 1.367), 1.453 (95% CI, 1.214, 1.740) and 1.202 (95% CI, 1.005, 1.438), respectively. Under high-temperature exposure, the highest cumulative lag effect of 3.106 (95% CI, 1.646, 5.861) for motorcycle occupants when cumulated over lag 0 to 12 day, and those for pedestrian, pedal cyclists, and motor vehicle accidents all peaked when persisted until 14 days, with OR values of 1.638 (95% CI, 1.281, 2.094), 2.603 (95% CI, 1.695, 3.997) and 1.603 (95% CI, 1.066, 2.411), respectively. Conclusion: This study provides evidence that ambient temperature is significantly associated with the risk of road traffic injuries accompanied by obvious lag effect, and the associations differ by the mode of transportation. Our findings help to promote a more comprehensive understanding of the relationship between temperature and road traffic injuries, which can be used to establish appropriate public health policies and targeted interventions.

Effects of ambient temperature and humidity on COPD mortality in Ganzhou city, China.

This study used the time series data of Ganzhou city to explore the individual and interaction effects of temperature and humidity on COPD death, and identify vulnerable subgroups of the population. We collected daily COPD mortality and meteorological data in Ganzhou from 2016 to 2019. The nonlinear distribution lag model was used to examine the associations and interaction between daily mean temperature and humidity and COPD mortality. For the total population, male and 65 years old or above, the relative risk (RR) for COPD mortality could be significant at extremely low temperature (3.3 ℃), reaching 1.799 (95% confidence interval [CI]: 1.216, 2.662), 1.894 (95% CI: 1.164, 3.084) and 1.779 (95% CI:1.185, 2.670). Also, at extremely low humidity (47.8%), the risk reached 1.888 (95% CI: 1.217, 2.930), 1.837 (95% CI: 1.066, 3.165) and 2.166 (95% CI: 1.375, 3.414). The cumulative COPD death risk for females was 3.524 (95% CI: 1.340, 9.267) at high temperature (30.7 ℃), 1.953(95% CI: 1.036, 3.683) at low humidity (47.8%) and 1.726 (95% CI: 1.048, 2.845) at high humidity (96.7%). For the total COPD deaths and subgroups, the interaction effects between daily temperature and humidity were not significant (p > 0.05). Both extremely low temperature and low humidity increased the risk of COPD death in Ganzhou city, especially for males and people over 65 years old. Females were more sensitive to extremely high temperature and humidity. Patients with COPD should pay attention to self-protection under extreme temperature and humidity weather conditions.

Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014-2021.

BACKGROUND: Tuberculosis (TB) remains a pressing public health issue, posing a significant threat to individuals' well-being and lives. This study delves into the TB incidence in Chinese mainland during 2014-2021, aiming to gain deeper insights into their epidemiological characteristics and explore macro-level factors to enhance control and prevention. METHODS: TB incidence data in Chinese mainland from 2014 to 2021 were sourced from the National Notifiable Disease Reporting System (NNDRS). A two-stage distributed lag nonlinear model (DLNM) was constructed to evaluate the lag and non-linearity of daily average temperature (℃, Atemp), average relative humidity (%, ARH), average wind speed (m/s, AWS), sunshine duration (h, SD) and precipitation (mm, PRE) on the TB incidence. A spatial panel data model was used to assess the impact of demographic, medical and health resource, and economic factors on TB incidence. RESULTS: A total of 6,587,439 TB cases were reported in Chinese mainland during 2014-2021, with an average annual incidence rate of 59.17/100,000. The TB incidence decreased from 67.05/100,000 in 2014 to 46.40/100,000 in 2021, notably declining from 2018 to 2021 (APC = -8.87%, 95% CI: -11.97, -6.85%). TB incidence rates were higher among males, farmers, and individuals aged 65 years and older. Spatiotemporal analysis revealed a significant cluster in Xinjiang, Qinghai, and Xizang from March 2017 to June 2019 (RR = 3.94, P < 0.001). From 2014 to 2021, the proportion of etiologically confirmed cases increased from 31.31% to 56.98%, and the time interval from TB onset to diagnosis shortened from 26 days (IQR: 10-56 days) to 19 days (IQR: 7-44 days). Specific meteorological conditions, including low temperature (< 16.69℃), high relative humidity (> 71.73%), low sunshine duration (< 6.18 h) increased the risk of TB incidence, while extreme low wind speed (< 2.79 m/s) decreased the risk. The spatial Durbin model showed positive associations between TB incidence rates and sex ratio (ß = 1.98), number of beds in medical and health institutions per 10,000 population (ß = 0.90), and total health expenses (ß = 0.55). There were negative associations between TB incidence rates and population (ß = -1.14), population density (ß = -0.19), urbanization rate (ß = -0.62), number of medical and health institutions (ß = -0.23), and number of health technicians per 10,000 population (ß = -0.70). CONCLUSIONS: Significant progress has been made in TB control and prevention in China, but challenges persist among some populations and areas. Varied relationships were observed between TB incidence and factors from meteorological, demographic, medical and health resource, and economic aspects. These findings underscore the importance of ongoing efforts to strengthen TB control and implement digital/intelligent surveillance for early risk detection and comprehensive interventions.

Association between ambient temperature and hospitalizations for urolithiasis in four counties of Ganzhou, China.

We collected meteorological and urolithiasis-related hospitalization data from four counties in Ganzhou City for 2018-2019 and used the DLNM method to assess the lagged and cumulative effects of temperature on urolithiasis hospitalizations and obtain the total effect after meta-combination. Based on the nonlinear association between temperature and urolithiasis hospitalizations, the relative risk of overall high temperature (30℃) was 2.10 (95% CI: 1.07-4.10). No statistically significant difference (p = 0.07) was observed between males (RR = 2.04, 95% CI: 1.42-2.94) and females (RR = 1.45, 95% CI: 1.09-1.92) for the heat effect, which was higher in the ≥ 60 years age group (RR = 3.18, 95% CI: 1.76-5.76) than in the < 60 years age group (p = 0.007). High temperatures increased the risk of hospitalization for urolithiasis in Ganzhou, China, and the risk was greatest for individuals aged 60 and above, with similar risks observed across counties and genders.

Association between ambient temperature and mammalian-related injuries in Guangzhou, China, 2014-2019.

BACKGROUND: Meteorological factors are associated with various health outcomes. However, it remains uncertain whether ambient temperature affects animal aggressive behaviors and causes mammalian-related injuries (MRI) in humans. The study aimed to examine the effect of daily mean temperature on MRI in Guangzhou, China. METHODS: Individual cases of MRI were obtained from Guangzhou Injury Surveillance System during 2014-2019. A combination of a distributed lag nonlinear model and conditional quasi-Poisson regression, implemented within a time-stratified case-crossover design, was employed to evaluate the association between temperature and MRI. Subgroup analyses were conducted by sex, age group, education level, and types of mammals. RESULT: This study included 24,206 MRI cases among which 89.7 % were caused by cats or dogs. We observed a nonlinear relationship between daily mean temperature and MRI. The impact of high temperatures was most pronounced on the current day and remained statistically significant on the next day. Compared with the reference temperature with a minimum risk of injuries (9.3 °C, approximately 2nd percentile of temperature), 75th percentile of temperature (27.4 °C) exerted the greatest relative risk (RR) of injuries (RR = 1.45, 95 % CI: 1.25-1.68) over lag 0-1 days. In subgroup analyses, the effects of high temperatures among males and females were similar. Individuals aged 15-34 years and 35-59 years were more susceptible to MRI at high temperatures compared to other age groups. The risk of injuries caused by cats or dogs consistently increased with high temperatures. We did not find significant impacts of low temperatures. CONCLUSION: Short-term heat exposure plays an important role in the occurrence of MRI. The findings highlight the importance of enhancing public awareness regarding the high temperature-associated hazards posed by mammals. There is a need for enhanced regulations and measures on the management for cats and dogs to mitigate the harm caused in hot seasons.

Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease: A time-series study in Xiangyang, China.

BACKGROUND: Data on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent. OBJECTIVE: To explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors. METHOD: A time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated. RESULTS: CVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 µm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996-1.087), PM2.5 (1.025, 1.004-1.045), nitrogen dioxide (NO2; 1.074, 1.039-1.111), and sulfur dioxide (SO2; 1.079, 1.019-1.141) at Lag 0 and ozone (O3; 1.018, 1.004-1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk. CONCLUSION: Short-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk.

Short-term exposure to extreme temperature and outpatient visits for respiratory diseases among children in the northern city of China: a time-series study.

BACKGROUND: Although studies have indicated that extreme temperature is strongly associated with respiratory diseases, there is a dearth of studies focused on children, especially in China. We aimed to explore the association between extreme temperature and children's outpatient visits for respiratory diseases and seasonal modification effects in Harbin, China. METHODS: A distributed lag nonlinear model (DLNM) was used to explore the effect of extreme temperature on daily outpatient visits for respiratory diseases among children, as well as lag effects and seasonal modification effects. RESULTS: Extremely low temperatures were defined as the 1st percentile and 2.5th percentile of temperature. Extremely high temperatures were defined as the 97.5th percentile and 99th percentile of temperature. At extremely high temperatures, both 26 °C (97.5th) and 27 °C (99th) showed adverse effects at lag 0-6 days, with relative risks (RRs) of 1.34 [95% confidence interval (CI): 1.21-1.48] and 1.38 (95% CI: 1.24-1.53), respectively. However, at extremely low temperatures, both - 26 °C (1st) and - 23 °C (2.5th) showed protective effects on children's outpatient visits for respiratory diseases at lag 0-10 days, with RRs of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.95), respectively. We also found seasonal modification effects, with the association being stronger in the warm season than in the cold season at extremely high temperatures. CONCLUSIONS: Our study indicated that extremely hot temperatures increase the risk of children's outpatient visits for respiratory diseases. Efforts to reduce the exposure of children to extremely high temperatures could potentially alleviate the burden of pediatric respiratory diseases, especially during the warm season.

Short-Term Exposure to PM2.5 Chemical Components and Depression Outpatient Visits: A Case-Crossover Analysis in Three Chinese Cities.

BACKGROUND: The association between specific chemical components of PM2.5 and depression remains largely unknown. METHODS: We conducted a time-stratified case-crossover analysis with a distributed lag nonlinear model (DLNM) to evaluate the relationship of PM2.5 and its chemical components, including black carbon (BC), organic matter (OM), sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+), with the depression incidence. Daily depression outpatients were enrolled from Huizhou, Shenzhen, and Zhaoqing. RESULTS: Among 247,281 outpatients, we found the strongest cumulative effects of PM2.5 and its chemical components with the odd ratios (ORs) of 1.607 (95% CI: 1.321, 1.956) and 1.417 (95% CI: 1.245, 1.612) at the 50th percentile of PM2.5 and OM at lag 21, respectively. Furthermore, the ORs with SO42- and NH4+ at the 75th percentile on the same lag day were 1.418 (95% CI: 1.247, 1.613) and 1.025 (95% CI: 1.009, 1.140). Relatively stronger associations were observed among females and the elderly. CONCLUSIONS: Our study suggests that PM2.5 and its chemical components might be important risk factors for depression. Reducing PM2.5 emissions, with a particular focus on the major sources of SO42- and OM, might potentially alleviate the burden of depression in South China.

Exploring the effects and interactions of meteorological factors on the incidence of scrub typhus in Ganzhou City, 2008-2021.

BACKGROUND: Scrub typhus poses a substantial risk to human life and wellbeing as it is transmitted by vectors. Although the correlation between climate and vector-borne diseases has been investigated, the impact of climate on scrub typhus remains inadequately comprehended. The objective of this study is to investigate the influence of meteorological conditions on the occurrence of scrub typhus in Ganzhou City, Jiangxi Province.  METHODS: From January 1, 2008 to December 31, 2021, we gathered weekly records of scrub typhus prevalence alongside meteorological data in Ganzhou city. In order to investigate the correlation between meteorological factors and scrub typhus incidence, we utilized distributional lag nonlinear models and generalized additive models for our analysis. RESULTS: Between 2008 and 2021, a total of 5942 cases of scrub typhus were recorded in Ganzhou City. The number of females affected exceeded that of males, with a male-to-female ratio of 1:1.86. Based on the median values of these meteorological factors, the highest relative risk for scrub typhus occurrence was observed when the weekly average temperature reached 26 °C, the weekly average relative humidity was 75%, the weekly average sunshine duration lasted for 2 h, and the weekly mean wind speed measured 2 m/s. The respective relative risks for these factors were calculated as 3.816 (95% CI: 1.395-10.438), 1.107 (95% CI: 1.008-1.217), 2.063 (95% CI: 1.022-4.165), and 1.284 (95% CI: 1.01-1.632). Interaction analyses showed that the risk of scrub typhus infection in Ganzhou city escalates with higher weekly average temperature and sunshine duration. CONCLUSION: The findings of our investigation provide evidence of a correlation between environmental factors and the occurrence of scrub typhus. As a suggestion, utilizing environmental factors as early indicators could be recommended for initiating control measures and response strategies.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China.

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 µg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

Modeling the lagged impacts of hourly weather and speed variation factors on the segment crash risk of rural interstate freeways: Applying a space-time-stratified case-crossover design.

In the realm of traditional roadway crash studies, cross-sectional modeling methods have been commonly employed to investigate the intricate relationship between the crash risk of roadway segments and variables including roadway geometrics, weather conditions, and speed distribution. However, these methodologies assume that the explanatory variables and target variable are only associated within the same time period. Although this assumption is well-founded for static factors like roadway geometrics, it proves inadequate when dealing with highly time-varying variables related to weather conditions and speed variation. Recent investigations have unveiled that these time-varying variables may exhibit lagged impacts on segment crash risk, necessitating the adoption of more comprehensive time-series modeling methods. This study employs two interpretable statistical methods, namely the distributed lag model (DLM) and the distributed lag nonlinear model (DLNM), to elucidate meaningful and interpretable patterns of the lagged impacts of weather and speed variation factors on segment crash risk. Empirical evidence based on crash data collected from rural interstate freeways in the state of Texas demonstrates coherent and interpretable lagged impact patterns of these variables. This study's results serve as strong support for the existence of lagged impacts on roadway segment-level crash risk, emphasizing the need for considering time-series effects in future crash modeling research. Furthermore, these findings could offer practical implications for the design of real-time crash warning systems and the effective implementation of variable speed limits to enhance road safety.

Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study.

Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54-17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02-3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.

Short-term effects of air pollutants on outpatient volume of respiratory diseases in Guiyang / 环境与职业医学

Background Affected by concentration, composition, and population tolerance of air pollutants, the relationship between air pollutants and population health has regional differences. There is still a research gap in Guiyang. Objective To explore the short-term effects of air pollutant concentrations in low-pollution areas on the outpatient volume of respiratory diseases. Methods Spearman correlation analysis was used to evaluate the correlation between air pollutants, meteorological factors, and respiratory outpatient volume from January 1, 2013 to December 31, 2020 in Guiyang City. A single pollutant distribution lag nonlinear model and a multi-pollutant interaction model were established based on Poisson distribution. A three-dimensional diagram was drawn to display the relationship between air pollutants and respiratory outpatient volume. Quantitative analysis was conducted on the attribution risk and lag effect of air pollutant concentration on outpatient volume of respiratory diseases in Guiyang City. Results The results of the single pollutant model showed that fine particulate matter (PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) elevated the outpatient volume of respiratory diseases. The maximum relative risk (RR) and 95%CI values of PM2.5, NO2,CO, and SO2 appeared on Day 2, 0, 5, and 6, respectively, which were 1.019 (1.015, 1.023), 1.146 (1.122, 1.171), 1.129 (1.116, 1.143), and 1.046(1.040, 1.052), respectively. For every quartile concentration increment of PM2.5, NO2, CO, or SO2, the outpatient volume of respiratory diseases increased by 0.943% (0.111%, 1.782%), 4.050% (3.573%, 4.529%), 0.595% (0.317%, 0.874%), or 0.667% (0.235%, 1.100%), respectively. The maximum RR (95%CI) of O3 was 1.015 (1.007, 1.023) and appeared on Day 0. The results of multi-pollutant model showed that PM2.5, NO2, CO, SO2, and O3 all elevated the outpatient volume of respiratory diseases. The maximum RR values of PM2.5, NO2, CO, SO2 and O3 appeared on Day 14, 0, 5, 7 and 0, respectively, which were 1.027 (1.021, 1.034), 1.213 (1.179, 1.248), 1.059 (1.043, 1.074), 1.016 (1.005, 1.026), and 1.024 (1.015, 1.033), respectively. Compared with the single pollutant model, the RR values of PM2.5, NO2, and O3 on the outpatient volume of respiratory diseases in the multi-pollutant model showed an upward trend, while the RR values of CO and SO2 in the multi-pollutant model showed a downward trend. Conclusion The impact of low concentrations of PM2.5, NO2, CO, and SO2 on human health cannot be ignored.