BACKGROUND: Hemorrhagic stroke (HS) is associated with significant disability and mortality. However, the relationship between meteorological factors and hemorrhagic stroke, as well as the potential moderating role of these factors, remains unclear. METHODS: Daily data on HS, air pollution, and meteorological conditions were collected from January 2015 to December 2021 in Ganzhou to analyze the relationship between meteorological factors and HS admissions. This analysis employed a time-stratified case-crossover design in conjunction with a distributional lag nonlinear model. Additionally, a bivariate response surface modelling was utilized to further investigate the interaction between meteorological factors and particulate matter. The study also stratified the analyses by gender and age. To investigate the potential impact of extreme weather conditions on HS, this study defined the 97.5th percentile as representing extremely high weather conditions, while the 2.5th percentile was classified as extremely low. RESULTS: In single-day lags, the risk of admissions for HS was significantly associated with extremely low temperature (lag 1-2 and lag 13-14), extremely low humidity (lag 1 and lag 9-12), and extremely high precipitation (lag 2-7). Females exhibited greater susceptibility to extremely low temperature than males within the single-day lag pattern in the subcomponent layer, with a maximum relative risk (RR) that was 7% higher. In the cumulative lag analysis, the risk of HS admissions was significantly associated with extremely high temperature (lag 0-8∼lag 0-14), extremely low humidity (lag 0-2∼lag 0-14), and extremely high precipitation (lag 0-4∼lag 0-14). Within the cumulative lag day structure of the subcomponent layer, both extremely low and extremely high temperature had a more pronounced effect on females and aged ≥65 years. The risk of HS admissions was positively associated with extremely high barometric pressure in the female subgroups (lag 0-1 and lag 0-2). The highest number of HS admissions occurred when high PM_2.5 concentrations coexisted with low precipitation. CONCLUSIONS Meteorological factors were significantly associated with the risk of hospital admissions for HS. Individuals who were female and aged ≥65 years were found to be more susceptible to these meteorological influences. Additionally, an interaction was observed between airborne particulate matter and meteorological factors. These findings contributed new evidence to the association between meteorological factors and HS.
China/epidemiology* ; Humans ; Female ; Male ; Aged ; Middle Aged ; Cross-Over Studies ; Hospitalization/statistics & numerical data* ; Adult ; Hemorrhagic Stroke/etiology* ; Meteorological Concepts ; Weather ; Particulate Matter/analysis* ; Air Pollution/adverse effects* ; Environmental Exposure/adverse effects* ; Aged, 80 and over ; Young Adult

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

Objective: To understand the influence of meteorological factors on the morbidity of influenza in northern cities of China and explore the differences in the influence of meteorological factors on the morbidity of influenza in 15 cities. Methods: The monthly reported morbidity of influenza and monthly meteorological data from 2008 to 2020 were collected in 15 provincial capital cities, including Xi 'an, Lanzhou, Xining, Yinchuan and Urumqi (5 northwestern cities), Beijing, Tianjin, Shijiazhuang, Taiyuan, Hohhot, Ji'nan, Zhengzhou (7 northern cities), Shenyang, Changchun and Harbin (3 northeastern cities). The panel data regression model was applied to conduct quantitative analyze on the influence of meteorological factors on influenza morbidity. Results: The univariate and multivariate panel regression analysis showed that after controlling the population density and other meteorological factors, for each 5 ℃ drop of monthly average temperature, the morbidity change percentage (MCP) of influenza was 11.35%, 34.04% and 25.04% in the 3 northeastern cities, 7 northern cities and 5 northwestern cities, respectively, and the best lag period months was 1, 0 and 1 month; When the monthly average relative humidity decreased by 10%, the MCP was 15.84% in 3 cities in northeastern China and 14.80% in 7 cities in northern China respectively, and the best lag period months was 2 and 1 months respectively; The MCP of 5 cities in northwestern China was 4.50% for each 10 mm reduction of monthly accumulated precipitation, and the best lag period months was 1 month; The MCPs of 3 cities in northeastern China and 5 cities in northwestern China were 4.19% and 5.97% respectively when the accumulated sunshine duration of each month decreased by 10 hours, the best lag period months was 1 month. Conclusions: In northern cities of China from 2008 to 2020, the temperature, relative humidity, precipitation and sunshine duration all had negatively impact on the morbidity of influenza, and temperature and relative humidity were the main sensitive meteorological factors. Temperature had a strong direct impact on the morbidity of influenza in 7 cities in northern China, and relative humidity had a strong lag effect on the morbidity of influenza in 3 cities in northeastern China. The duration of sunshine in 5 cities in northwestern China had a greater impact on the morbidity of influenza compared with 3 cities in northeastern China.
Humans ; Cities ; Influenza, Human ; China ; Beijing ; Meteorological Concepts

BACKGROUND: Weather conditions are a possible contributing factor to age-related macular degeneration (AMD), a leading cause of irreversible loss of vision. The present study evaluated the joint effects of meteorological factors and fine particulate matter (PM_2.5) on AMD. METHODS: Data was extracted from a national cross-sectional survey conducted across 10 provinces in rural China. A total of 36,081 participants aged 40 and older were recruited. AMD was diagnosed clinically by slit-lamp ophthalmoscopy, fundus photography, and spectral domain optical coherence tomography (OCT). Meteorological data were calculated by European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and were matched to participants' home addresses by latitude and longitude. Participants' individual PM_2.5 exposure concentrations were calculated by a satellite-based model at a 1-km resolution level. Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the joint effects of meteorological factors and PM_2.5 on AMD. RESULTS: The prevalence of AMD in the study population was 2.6% (95% CI 2.42-2.76%). The average annual PM_2.5 level during the study period was 63.1 ± 15.3 µg/m³. A significant positive association was detected between AMD and PM_2.5 level, temperature (T), and relative humidity (RH), in both the independent and the combined effect models. For PM_2.5, compared with the lowest quartile, the odds ratios (ORs) with 95% confidence intervals (CIs) across increasing quartiles were 0.828 (0.674,1.018), 1.105 (0.799,1.528), and 2.602 (1.516,4.468). Positive associations were observed between AMD and temperature, with ORs (95% CI) of 1.625 (1.059,2.494), 1.619 (1.026,2.553), and 3.276 (1.841,5.830), across increasing quartiles. In the interaction analysis, the estimated relative excess risk due to interaction (RERI) and the attributable proportion (AP) for combined atmospheric pressure and PM_2.5 was 0.864 (0.586,1.141) and 1.180 (0.768,1.592), respectively, indicating a synergistic effect between PM_2.5 and atmospheric pressure. CONCLUSIONS This study is among the first to characterize the coordinated effects of meteorological factors and PM_2.5 on AMD. The findings warrant further investigation to elucidate the relationship between ambient environment and AMD.
Humans ; Adult ; Middle Aged ; Cross-Sectional Studies ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; China/epidemiology* ; Macular Degeneration/etiology* ; Meteorological Concepts

SARS-CoV-2 has infected more than 600 million people worldwide and caused more than 6 million deaths. The emerging novel variants have made the epidemic rebound in many places. Meteorological factors can affect the epidemic spread by changing virus activity, transmission dynamic parameters and host susceptibility. This paper systematically analyzed the currently available laboratory and epidemiological studies on the association between the meteorological factors and COVID-19 incidence, in order to provide scientific evidence for future epidemic control and prevention, as well as developing early warning system.
Humans ; SARS-CoV-2 ; COVID-19 ; Meteorological Concepts ; Laboratories ; Epidemiologic Studies

Humans ; Mississippi/epidemiology* ; Influenza, Human/epidemiology* ; Meteorological Concepts ; Virus Diseases

Objective: Previous studies have shown that meteorological factors may increase COVID-19 mortality, likely due to the increased transmission of the virus. However, this could also be related to an increased infection fatality rate (IFR). We investigated the association between meteorological factors (temperature, humidity, solar irradiance, pressure, wind, precipitation, cloud coverage) and IFR across Spanish provinces ( Methods: We estimated IFR as excess deaths (the gap between observed and expected deaths, considering COVID-19-unrelated deaths prevented by lockdown measures) divided by the number of infections (SARS-CoV-2 seropositive individuals plus excess deaths) and conducted Spearman correlations between meteorological factors and IFR across the provinces. Results: We estimated 2,418,250 infections and 43,237 deaths. The IFR was 0.03% in < 50-year-old, 0.22% in 50-59-year-old, 0.9% in 60-69-year-old, 3.3% in 70-79-year-old, 12.6% in 80-89-year-old, and 26.5% in ≥ 90-year-old. We did not find statistically significant relationships between meteorological factors and adjusted IFR. However, we found strong relationships between low temperature and unadjusted IFR, likely due to Spain's colder provinces' aging population. Conclusion The association between meteorological factors and adjusted COVID-19 IFR is unclear. Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.
Adult ; Aged ; Aged, 80 and over ; COVID-19/virology* ; Humans ; Meteorological Concepts ; Middle Aged ; Pandemics/statistics & numerical data* ; SARS-CoV-2/physiology* ; Spain/epidemiology* ; Weather ; Young Adult

China/epidemiology* ; Environmental Monitoring ; Gastrointestinal Hemorrhage/etiology* ; Humans ; Meteorological Concepts ; Particulate Matter ; Seasons

Air Pollution ; China ; Humans ; Meteorological Concepts ; Outpatients ; Particulate Matter/analysis* ; Skin Diseases/epidemiology*

BACKGROUND: This study investigated the effect of fine dust concentrations in the air on the incidence of viral respiratory infections in the Republic of Korea.METHODS: A time series analysis using R statistics was performed to determine the relationship between weekly concentrations of fine dust in the air and the incidences of acute respiratory tract infections caused by the respiratory syncytial virus (RSV), adenovirus (HAdV), rhinovirus (HRV), human metapneumovirus (HMPV), human coronavirus (HCoV), human bocavirus (HBoV), human parainfluenza virus (HPIV), and influenza virus (IFV), from the beginning of 2016 to the end of 2017. Correlations between various meteorological factors and the amount of fine dust were analyzed using the Spearman's rank correlation coefficient. To analyze the relationship between viral infections and fine dust, a quasi-poisson analysis was performed.RESULTS: The incidence of the HAdV was proportional to fine dust and air temperature. The IFV was proportional to fine dust and relative humidity and was inversely proportional to temperature. The HMPV was proportional to fine dust, wind speed, and inversely proportional to relative humidity. The HCoV was proportional to micro dust, relative humidity, and inversely proportional to temperature. Both the HBoV and HPIV were directly proportional to fine dust, temperature, wind speed, and inversely proportional to relative humidity. The RSV was inversely proportional to fine dust, temperature, wind speed. A lag effect was observed for the influenza virus, in that its incidence increased 2–3 weeks later on the cumulative lag model.CONCLUSION: As the weekly average concentration of fine dust increases, the incidence of HAdV, HMPV, HCoV, HBoV, HPIV, and influenza increase.
Adenoviridae ; Air Pollution ; Coronavirus ; Dust ; Human bocavirus ; Humans ; Humidity ; Incidence ; Influenza, Human ; Metapneumovirus ; Meteorological Concepts ; Orthomyxoviridae ; Paramyxoviridae Infections ; Particulate Matter ; Republic of Korea ; Respiration Disorders ; Respiratory Syncytial Viruses ; Respiratory Tract Infections ; Rhinovirus ; Wind