The health hazards caused by air pollution vary significantly depending on factors such as the composition of pollutants in the region, climate, and the susceptibility of the population. Although numerous studies have explored the relationship between air quality and pneumonia, specific research evidence from a particular inland energy city like Qingyang in China is still scarce. This study aims to quantify the short-term impact of air pollution in this under-researched region on pneumonia hospitalizations. We collected the medical records of patients with pneumonia from January 1, 2015, to December 31, 2019, and also obtained data on 6 types of common air pollutants and meteorological conditions. We performed a time series analysis using a generalized additive model and a distributed nonlinear lag model. All measured data exhibited pronounced seasonality: particulate matter less than 2.5 μm in diameter, particulate matter less than 10 μm in diameter, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) concentrations and pneumonia admissions were higher in the cold season and lower in the warm season, a pattern conversely mirrored by ozone (O3) concentrations, average temperature, and relative humidity. In the single pollutant model, for every 10 μg/m3 increase in exposure levels of particulate matter less than 2.5 μm in diameter, particulate matter less than 10 μm in diameter, SO2, NO2, and O3 8 hours and for every 1 mg/m3 increase in CO exposure level, the risk of pneumonia admission was 1.004 (0.991, 1.017), 1.004 (0.999, 1.010), 1.035 (1.022, 1.048), 1.221 (1.174, 1.271), 0.999 (0.981, 1.017), and 1.382 (1.230, 1.552), respectively. The strongest effects occur in lag 1, lag 7, lag 07, lag 07, lag 3, and lag 05, respectively. Our study identifies significant gender- and age-specific susceptibilities to air pollution in Qingyang. Men were more vulnerable to SO2, whereas women were more affected by CO. Children aged ≤14 years constituted a high-risk group. Furthermore, we observed a distinct seasonal pattern: SO2, NO2, and CO were key drivers of pneumonia admissions with stronger effects in the cold season, in contrast to O3, which exhibited adverse effects only during the warm season.

To explore the exposure-lag-response relationships and the interaction effects of meteorological and air pollutants on cerebrovascular disease admissions (CDA), this study used a distributed lag nonlinear model of time series. Univariate analysis showed a "U" shaped between relative humidity (RH) and CDA, daily mean temperature (DMT) and CDA showed fluctuating variations. Except O3, the relative risk (RR) between air pollutants and CDA showed a monotonically increasing trend. The RR values were maximum at the highest air pollutant concentration, which were RR(NO2) =2.86(95 %CI:1.79-2.58), RR(PM2.5) = 1.82 (95 %CI:1.13-2.94), RR(PM10) = 2.94(95 %CI:1.33-6.52), RR(SO2) = 2.16(95 %CI:1.24-3.75), RR(CO) = 1.91(95 %CI: 1.19-3.06). The interaction results showed statistically significant relative excess risk of interactions (RERI) except DMT with CO and O3, and RH with PM2.5 and NO2. The RERI of DMT with PM2.5, PM10, and NO2 on CDA were all greater than 0, with RERI of 0.99 (95 % CI:0.08-1.90), 0.25 (95 %CI:0.03-0.47), and 1.51 (95 %CI:0.49-2.55), respectively, whereas the RERI of DMT with SO2 on CDA were less than 0. The RERI of RH with PM10 and O3 on CDA were greater than 0 and were 1.08 (95 %CI:0.03-1.97), 2.32 (95 %CI:0.19-5.51), respectively. All factors except O3 had cumulative risks on the CDA and there was an interaction between meteorological factors and air pollutants on CDA.

It is well known that psoriasis is caused by a combination of genetic and environmental factors. Among the many environmental factors, emerging evidence suggests air pollution plays a crucial role in the exacerbation of psoriasis symptoms, and the association of air pollutants with psoriasis remains elusive. To address that, daily outpatient visit data for psoriasis from 1 January 2017 to 31 December 2022 was obtained from the Dermatology Hospital of Jiangxi Province (Nanchang, Jiangxi, China). Daily meteorological factors (temperature and relative humidity) and 24-h mean concentrations of four common air pollutants, including particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) and 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), O3 8-h maximum values (O38h) and carbon monoxide (CO), were consecutively recorded. Quasi-Poisson generalized additive model (GAM), in conjunction with a distributed lag nonlinear model (DLNM) was used to examine the associations between air pollutants and hospital outpatient visits for psoriasis. Stratified analyses by gender, age and season were further conducted. Specifically, for every 10 µg/m3 increase (1 mg/m3 in CO) of PM2.5 (lag 07), PM10 (lag 07), SO2 (lag 03), NO2 (lag 07), O38h (lag 02), and CO (lag 07), the relative risk (RR) values were 1.051 (95

Although studies have demonstrated the influence of meteorological factors on morbidity and mortality in type 2 diabetes mellitus (T2DM), research focusing specifically on their impact on hospitalization for T2DM with complications remains Limited.This study aimed to investigate the impact of meteorological factors on hospitalization for type 2 diabetes mellitus (T2DM) with complications. The distributed lag nonlinear modelling (DLNM) was used to investigate this effect of temperature and relative humidity (RH) on hospitalization for T2DM with complications. A total of 50,108 T2DM hospitalizations with complications were performed from 2014 to 2019 in Lanzhou, China. Compared to the reference temperature of 12.7 °C, low temperature (-4.1 °C) had harmful effects, with the maximum impact at lag0-1 (cumulative RR = 1.0265, 95

Ambient air pollution increases the risk of respiratory morbidity, but evidence concerning the effects of traffic-related air pollutants (TRAPs) on bronchitis admissions is scarce, and multi-city scale studies are needed. This study aimed to evaluate the associations of a set of TRAPs with bronchitis admission and to explore potential modifiers of the associations. Data on hospital admissions for bronchitis, air pollution, and meteorological factors from 1 January 2015 to 31 December 2021 were collected in 8 cities across Gansu Province, China. A generalized additive model (GAM) based on the Quasi-Poisson distribution, in combination with a distributed lag nonlinear model (DLNM), was used to evaluate the association between air pollutants and bronchitis admissions, controlling for calendar time (to control seasonality and long-term trend), meteorological factors (i.e., air temperature, relative humidity), and other possible confounders. We also performed a stratified analysis by gender, age, and season to assess potential effect modification within the study. Totally, 155,133 bronchitis patients were identified during the study period, including 2557 days. The daily number of hospital admissions for bronchitis ranged from 0 to 52. The results showed that exposure to PM2.5, PM10, NO2, and CO was positively correlated with an increased risk of hospital admission for bronchitis. Each 10 µg/m3 increase in PM2.5, PM10, NO2 was associated with a 3.2

The effects of meteorological factors and air pollutants on upper respiratory tract infection (URTI) varied across different regions depending on climate zones. Previous studies have identified potential interactions between air pollutants and meteorological factors (temperature and relative humidity, i.e., RH) on URTI morbidity. However, research in the inland provinces of Northwest China remains limited. Variations in air pollution levels, pollutant composition, climatic conditions, and population susceptibility across regions contribute to substantial heterogeneity in findings, rendering existing evidence inapplicable to Northwest inland provinces. Therefore, it is necessary to conduct region-specific investigations in representative cities within this area. In this study, we selected cities from different climatic zones in Gansu Province for analysis (temperate continental climate: Jiuquan; temperate semi-arid continental climate: Dingxi; temperate subhumid climate: Tianshui). This study explored several major meteorological factors, including air pollution, temperature and RH, to identify potential modifiable risk factors and their interactive effects on URTI in the three cities in different climate zones. Data from 2017 to 2019 on URTI outpatient visits, air pollutants, and weather in three cities with varying climates were analyzed using generalized additive models and distribution lag nonlinear model (DLNM) to assess the delayed impact of meteorological factors on URTI. Further, bivariate and stratified models explored the interaction between pollutants and meteorological factors on URTI outpatient visits. Our results indicated that PM2.5, PM10, NO2, and CO were significantly associated with increased hospital outpatient visits for URTI, with lagged effects observed. The maximum relative risks (RRs) of PM2.5 were 1.134 (95% CI: 1.057, 1.218) in Jiuquan (lag014), 1.118 (95% CI: 1.069, 1.168) in Dingxi (lag014), and 1.035 (95% CI: 1.013, 1.057) in Tianshui (lag03). For PM10, the maximum RRs were 1.045 (95% CI: 1.026, 1.064) in Jiuquan (lag014) and 1.020 (95% CI: 1.005, 1.035) in Tianshui (lag010), while PM10 has no significant association in Dingxi. For NO2, the maximum RRs were 1.118 (95% CI: 1.022, 1.224) in Jiuquan (lag011) and 1.158 (95% CI: 1.104, 1.215) in Tianshui (lag011), while NO2 has no significant association in Dingxi. For CO, the maximum RRs were 5.433 (95% CI: 2.818, 10.475) in Jiuquan (lag014), 2.289 (95% CI: 1.659, 3.156) in Dingxi (lag014), and 1.835 (95% CI: 1.509, 2.231) in Tianshui (lag012). Stratified analyses indicated that the associations were stronger in males and children (0-14 years). Furthermore, the associations were stronger in cold season than in warm season. Our results also revealed that both low and high temperatures could elevate the risk of outpatient visits for URTI. Compared with the median temperature of each city, the maximum RRs of low temperatures were 1.455 (95% CI: 1.365, 1.550) at lag08, 1.073 (95% CI: 1.027, 1.121) at lag014, and 1.127 (95% CI: 1.067, 1.190) at lag014 for Jiuquan, Dingxi, and Tianshui, respectively. For the high temperature exposure, we only observed significant associations in Jiuquan and Tianshui [RR = 1.143 (95% CI: 1.090, 1.200) at lag05 in Jiuquan, RR = 1.023 (95% CI: 1.008, 1.038) at lag14 in Tianshui], while no significant associations with high temperatures were detected in Dingxi. Stratified analyses by gender and age revealed that extremely low temperatures had a more pronounced effect on males and children aged 0-14 years across the three cities, whereas extremely high temperatures exhibited adverse effects only among males and individuals aged 15-64 years in Jiuquan. Similarly, both low and high RH were associated with increased risk of URTI outpatient visits in the three cities, though the impact of extreme RH varied among them. The effect of extremely low RH on URTI outpatient visits was strongest at lag07 for Jiuquan (RR = 1.296, 95% CI: 1.264, 1.329), lag06 for Dingxi (RR = 1.091, 95% CI: 1.031, 1.155), and lag07 for Tianshui (RR = 1.279, 95% CI: 1.176, 1.390). Adverse effects of extremely high RH were observed exclusively in Dingxi and Tianshui, with the strongest associations at lag7 and lag07, respectively. The relative risk (RR) for Dingxi was 1.043 (95% CI: 1.019, 1.069) and for Tianshui it was 1.069 (95% CI: 1.002, 1.140). Stratified analyses by gender and age indicated that extremely low RH had a more pronounced impact on males and children aged 0-14 years across all three cities, while extremely high RH exerted a greater effect on males and children aged 0-14 years in Dingxi and Tianshui. Meteorological factors and air pollutants have an interactive effect on URTI. The response surface analysis indicated that the adverse effects of the four air pollutants on URTI incidence were most pronounced under low temperature and high concentration conditions across the three cities. Stratified analysis demonstrated that, under low temperature, each 10 μg m-3 increase in pollutant concentration (CO: 1 mg m-3) was associated with elevated outpatient risk of URTI in Jiuquan, with RRs as follows: PM2.5 (RR = 1.112, 95% CI: 1.023, 1.203), PM10 (RR = 1.041, 95% CI: 1.021, 1.065), NO2 (RR = 1.341, 95% CI: 1.230, 1.462), and CO (RR = 2.603, 95% CI: 1.433, 4.728). In Dingxi, the corresponding RRs were: PM2.5 (RR = 1.148, 95% CI: 1.062, 1.241), PM10 (RR = 1.052, 95% CI: 1.018, 1.087), NO2 (RR = 1.128, 95% CI: 1.055, 1.206), and CO (RR = 2.294, 95% CI: 1.842, 2.857). In Tianshui, the RRs were: PM2.5 (RR = 1.150, 95% CI: 1.095, 1.208), PM10 (RR = 1.038, 95% CI: 1.022, 1.054), NO2 (RR = 1.305, 95% CI: 1.162, 1.466), and CO (RR = 1.682, 95% CI: 1.462, 1.935). Similarly, the response surface plots indicate that the adverse effects of the four air pollutants on URTI incidence in the three cities are most pronounced under low RH and high concentration conditions. Stratified analyses reveal that, under low RH, each 10 μg m-3 increase in pollutant concentration (CO: 1 mg m-3) is associated with the following RRs for URTI outpatient visits in Jiuquan: PM2.5 (RR = 1.101, 95% CI: 1.032, 1.176), PM10 (RR = 1.042, 95% CI: 1.015, 1.069), NO2 (RR = 1.236, 95% CI: 1.056, 1.446), and CO (RR = 2.569, 95% CI: 1.625, 4.060). In Dingxi, the corresponding RRs are: PM2.5 (RR = 1.171, 95% CI: 1.129, 1.214), PM10 (RR = 1.063, 95% CI: 1.037, 1.090), NO2 (RR = 1.141, 95% CI: 1.042, 1.249), and CO (RR = 2.071, 95% CI: 1.645, 2.607). In Tianshui, the RRs are: PM2.5 (RR = 1.090, 95% CI: 1.058, 1.124), PM10 (RR = 1.043, 95% CI: 1.024, 1.062), NO2 (RR = 1.180, 95% CI: 1.115, 1.248), and CO (RR = 1.894, 95% CI: 1.631, 2.210). In conclusion, both air pollutants and meteorological factors had an influence on URTI outpatient visits, and the influence on URTI outpatient visits may have an interaction.

The aim of this study was to use the distributed lag non-linear model (DLNM) to investigate the association between temperature differences (including temperature change between neighboring days (TCN) and diurnal temperature range (DTR)) and acute exacerbation of chronic obstructive pulmonary disease (AECOPD) outpatient visits. We also stratify by sex (male, female) and age (< 65 years, 65–74 years and ≥ 75 years). The results showed that the maximum relative risk (RR) of low temperature for AECOPD outpatient visits was 1.175 (95

As a common chronic disease, type 2 diabetes mellitus (T2DM) and its complications not only jeopardize the health of patients but also impose a heavy economic burden on society and patients’ families. Nevertheless, there is a scarcity of evidence regarding the effects of nitrogen dioxide (NO2) on T2DM. In our study, daily data for T2DM outpatients, air pollutants and meteorological factors from January 1, 2018, to December 31, 2020 were collected in three cities: Dingxi, Tianshui and Longnan, an inland province of northwest China. Generalized additive model (GAM) with quasi-Poisson regression combined with the Distributed Lag Non-linear Model (DLNM) were employed to assess the associations between NO2 and daily T2DM outpatients, as well as their lag effects in various cities. We also stratified by gender, age, and season. The results from DLNM revealed that NO2 was significant positively associated with the increase of the number of outpatient visits for T2DM at individual single-day and all cumulative lag days in three cities, with the largest Relative Risk (RR) at lag05, lag05 and lag07 [RR = 1.106 (95

Little is known on the potential impact of temperature on emergency room (ER) visits of total and cause-specific respiratory diseases (RD) including upper respiratory tract infection (URTI), Pneumonia, chronic obstructive pulmonary disease (COPD), Bronchitis, especially for patients in the areas of the semi-arid Northwest region. This study investigated the impact of ambient temperature on the ER risk of total and cause-specific RD in Lanzhou, China from 2013 to 2019. A quasi-Poisson generalized additive model (GAM) and a distributed lag non-linear model (DLNM) were used to examine the association between ambient temperature and daily ER visits for total and cause-specific RD. Then we conducted stratified analysis by gender and age groups. The results showed that temperature-related ER risks varied by age, sex, and disease. Extremely cold temperatures (–6.7 °C) resulted in an increase (relative risk (RR) = 1.823, 95

Numerous studies have identified air pollutant as a primary risk factor for chronic obstructive pulmonary disease (COPD), particularly for fine particulate matter (PM2.5). However, the daily average levels of PM2.5 may not accurately reflect the actual exposure level due to the fluctuating air pollutant levels throughout the day and different human activity patterns. Few studies have comparatively analyzed the association between different exposure metrics of PM2.5 and COPD hospitalization. We aimed to explore the association between PM2.5 and COPD admission in Tianshui city using five different exposure metrics (a) Daily mean concentration (DailyPM2.5mean), (b) Daily hourly peak concentration (DailyPM2.5max), (c) Daily morning concentration (DailyPM2.5mor), (d) Daily evening concentration (DailyPM2.5eve) and (e) Daily excessive concentration hours (PM2.5DECH). The PM2.5DECH was defined as daily total concentration hours > 25 µg/m3. We collected daily records of COPD admission and hourly data on air pollutants and meteorological factors from Tianshui, China, 2018-2019. DailyPM2.5mean, DailyPM2.5max, DailyPM2.5mor, DailyPM2.5eve and PM2.5DECH were used as the exposure variables. A generalized additive model (GAM) based Poisson-distribution combined with a distributed lag non-linear model (DLNM) was applied to quantify the association between five different exposure metrics of PM2.5 and COPD admission. Stratified analyses were conducted to examine the effect modifications of gender, age, and season. The analysis revealed significant associations between five different exposure metrics of PM2.5 and COPD admission. PM2.5-related risks of COPD admission differed by five exposure metrics. An interquartile range (IQR) increment in DailyPM2.5mean at lag06, DailyPM2.5max at lag06, DailyPM2.5mor at lag04, DailyPM2.5eve at lag06 and PM2.5DECH at lag07 was associated with a 21.64%(95%CI: 7.46%, 36.68%), 12.84%(95%CI: 1.47%, 24.58%), 16.47%(95%CI: 0.96%, 33.01%), 31.54%(95%CI: 16.49%, 47.58%), and 30.37%(95%CI: 13.91%, 46.88%) increase in Tianshui's COPD admissions, respectively. Associations of COPD admission with five different exposure metrics of PM2.5 appeared to be stronger in the cold season and among the females, while we found significantly higher effects in the population < 65 years old. The five metrics of PM2.5 exposure and COPD hospitalization show an exposure-response relationship that resembles a function curve that increases monotonically. This study added evidence for increased risk of admissions associated with exposure to the five metrics of ambient PM2.5 in Tianshui City, China, and DailyPM2.5eve or PM2.5DECH may be a significant risk factor for the increased risk of COPD admission, indicating that we should focus more on the relationship between air pollution and related diseases during the evening peak hours.

It's unclear exactly how variations in a number of meteorological factors relate to the chance of being hospitalized with COPD. The majority of earlier research was incomplete and non-systematic, describing only the association between a single climatic element and hospitalization for COPD. The results were often inconsistent. The purpose of this study is to investigate the relationship between three meteorological factors (temperature, DTR, and relative humidity) and the daily hospital admissions of COPD in Qingyang, China, as well as to examine the lag effects of each meteorological indicator on various subgroups. Based on daily COPD hospital admissions and meteorological data in Qingyang City, China, from 2015 to 2019, a generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) was used to examine the effects of three meteorological factors on COPD hospital admissions. At the same time, the 95th and 5th percentiles were utilized as the high and low effect nodes of each meteorological index to assess its relationship with COPD admission. Temperature, DTR, and relative humidity exhibited inverted J-, M-, and W-shaped exposure-response relationships with COPD admission. The negative effects of the cold effect and high DTR reached their peak at lag0-21. The RR values were 1.867 (95%CI:1.624,2.148) and 1.542 (95%CI:1.215,1.959), respectively. The highest negative effect of low humidity was in lag0-7, with RR values of 1.239 (95% CI:1.116,1.374). The three factors had a greater negative impact on those over 65 years old. Women were more susceptible to the cold, but men were more vulnerable to high DTR and low humidity. The study found significant correlations between meteorological factors and COPD hospitalizations. Lower temperatures, higher diurnal temperature variation, and lower humidity were associated with increased admission risks, with differential impacts observed across age groups and genders.

This study investigated the association between temperature and hospitalizations for respiratory diseases (RD) among suburban farmers in Zhangye, Wuwei, Dingxi, and Tianshui in Gansu province. We collected the daily hospital admission data for RD in four cities from the local public hospitals, covering the period from January 1, 2018 to December 31, 2019. The association was estimated using a quasi-Poisson generalized additive model (GAM) and distributed lag nonlinear model (DLNM) to account for lagged and non-linear effects, and the association varies geographically. Our study found that both low and high temperatures were associated with RD morbidity, and had significant lag effects in four cities, the risk of temperature on RD morbidity increased significantly in Zhangye (low temperature: RR = 2.107, 95

Emerging evidence indicates an increasing prevalence of allergic rhinitis (AR), potentially linked to air quality. The aim of the present study was to assess the relationship between traffic-related air pollutants (TRAPs) and outpatient visits for AR. Daily outpatient data for AR, air pollutant concentrations, and meteorological data were collected from January 2018 to December 2020 in Dingxi, Longnan, and Tianshui. Utilizing a Quasi-Poisson distribution, a generalized additive model (GAM) was employed in conjunction with distributed lag non-linear models (DLNM) to explore the association and lag effects of TRAPs on AR outpatient visits across the three cities. Stratified analyses based on gender, age, and season were conducted. A total of 11 106 outpatient visits for AR were recorded in the three cities. For an increase of 10 mu g m-3 in PM2.5, the effect estimates in Dingxi, Longnan, and Tianshui reached their maximum at lag04, lag06, and lag07, respectively, with relative risk (RR) values of 4.696 (95% CI: 1.890, 11.614), 2.842 (95% CI: 2.102, 4.922), and 1.102 (95% CI: 1.066, 1.140). For NO2, the highest associations were exhibited in Dingxi (RR = 1.262, 95% CI: 1.081, 1.473) at lag07, in Longnan (RR = 2.554, 95% CI: 2.100, 4.805) at lag06, and in Tianshui (RR = 1.158, 95% CI: 1.106, 1.213) at lag07. Meanwhile, the strongest effects observed for a 1 mg m-3 increase in CO were 2.786 (95% CI: 1.467, 5.291) for Dingxi at lag07, 1.502 (95% CI: 1.096, 2.059) for Longnan at lag05, and 1.385 (95% CI: 1.137, 1.686) for Tianshui at lag04. Adults aged 15-64 years appeared to be more susceptible to TRAPs, and the associations were stronger in the cold season. The results of the present study indicate that exposure to TRAPs was positively correlated with outpatient visits for AR. Emerging evidence indicates an increasing prevalence of allergic rhinitis (AR), potentially linked to air quality.

This study aimed to evaluate the effects of temperature on CVD hospitalizations in suburban farmers of Zhangye, Wuwei, and Longnan with different climatic zones in Gansu Province, China. We obtained daily CVD hospitalization data for the three cities from the medical records of inpatients with the New Rural Cooperative Medical Scheme from the period January 1, 2018 to December 31, 2019. Generalized additive model based on Quasi-Poisson distribution and distributed lag nonlinear model were used to evaluate the effects of temperature on CVD hospitalizations, with analyses stratified by gender and age (adults: <65 years; the elderly:>= 65 years). The effect of minimum-morbidity temperature was used as the reference value to calculate estimates. M-shaped exposure-response curves were observed between temperature and CVD hospitalizations in the three cities. There are some differences in the susceptible populations of temperature in different regions, gender and age. This study showed that both low and high temperatures could increase the relative risks for CVD hospitalizations in the three cities. High temperatures have more significant and long-lasting effects than low temperatures.

Nitrogen dioxide (NO2) represents a deleterious effect on acute myocardial infarction (AMI), but few relevant studies have been conducted in China. We aim to evaluate the acute effects of NO2 exposure on hospitalization for AMI in Lanzhou, China. In this study, we applied a distributional lag nonlinear model (DLNM) to assess the association between NO2 exposure and AMI hospitalization. We explored the sensitivity of various groups through stratified analysis by gender, age, and season. The daily average concentration of NO2 is 47.50 +/- 17.38 mu g/m3. We observed a significant exposure-response relationship between NO2 concentration and AMI hospitalization. The single pollutant model analysis shows that NO2 is positively correlated with AMI hospitalization at lag1, lag01, lag02, and lag03. The greatest lag effect estimate occurs at lag01, where a 10 mu g/m3 increase in NO2 concentrations is significantly associated with a relative risk (RR) of hospitalization due to AMI of 1.027 [95% confidence interval (CI): 1.013, 1.042]. The results of the stratified analysis by gender, age, and season indicate that males, those aged >= 65 years, and the cold season are more sensitive to the deleterious effects caused by NO2 exposure. Short-term exposure to NO2 can enhance the risk of AMI hospitalization in urban Lanzhou.Implications: Exposure to particulate matter can lead to an increased incidence of AMI. Our study once again shows that NO2 exposure increases the risk of AMI hospital admission. AMI is a common and expensive fatal condition. Reducing NO2 exposure will benefit cardiovascular health and save on healthcare costs.

This study assessed the impact of various temperature indices, including mean temperature (MT), diurnal temperature range (DTR), and temperature changes between neighboring days (TCN) on hospitalization rates for cardiovascular system diseases among residents of Zhangye City, a typical western city in China. The Quasi-Poisson generalized additive regression model (GAM) in conjunction with a distributed lag nonlinear model (DLNM) was applied to estimate the association of temperature indices with CVD hospitalization rates in Zhangye City during the periods of 2015-2021. The exposure-response relationship and relative risk were discussed and stratified analyses by age and gender were conducted. We found that the hospitalization rates of cardiovascular disease (CVD) patients in Zhangye City was significantly related to different temperature indicators (MT, DTR, TCN). Both low and high MT, DTR, and TCN increased the risk of cardiovascular disease (CVD) among residents. Besides, different demographic populations exhibited distinct sensitivities to temperature conditions. Relevant authorities should devise corresponding preventive and control measures to protect vulnerable populations.

Diabetes is a global public health problem, and the impact of air pollutants on type 2 diabetes mellitus (T2DM) has attracted people's attention. This study aimed to assess the association of short-term exposure to six criteria air pollutants with T2DM outpatient visits in Lanzhou, China. We collected data on daily outpatient visits for T2DM, daily meteorological data and hourly concentrations of air pollutants in Lanzhou from 2013 to 2019. An over-dispersed passion generalized addictive model combined with a distributed lag non-linear model was applied to estimate the associations and stratified analyses were performed by gender, age, and season. The models were fitted with different lag structures, including single lag days from the current to the previous seven days (lag0 to lag7) and moving average concentrations over seven lag days (lag01 to lag07). A positive association between multiple air pollutants, especially PM2.5, NO2, O(3)8h and CO and hospital outpatient visits for T2DM was observed. The largest association between T2DM outpatient visits and PM2.5 was observed at lag06 (RR 1.013, 95% CI: 1.001, 1.027), NO(2 )at lag03 (RR 1.034, 95% CI: 1.018, 1.050), O38h at lag05 (RR 1.012, 95% CI: 1.001, 1.023) for an increase of 10 mu g m(-3) and CO at lag03 (RR 1.084, 95% CI: 1.029, 1.142) for an increase of 1 mg m-3 in the concentrations. In addition, people aged <65 and males are more susceptible, and air pollutants have a greater impact on the cold season. This study showed that although the air pollution in Lanzhou was improved, there was still a statistical correlation between air pollution exposure and T2DM outpatient visits. Therefore, the local government still needs to strengthen the control of air pollution and enhance the protection awareness of the diabetic population through education and publicity.

With the backdrop of global climate change, the impact of climate change on respiratory diseases like asthma is receiving increasing attention. However, the effects of temperature and diurnal temperature range (DTR) on asthma are complex, and understanding these effects across different seasons, age groups, and sex is of utmost importance. This study utilized asthma hospitalization data from Lanzhou, China, and implemented a distributed lag nonlinear model (DLNM) to investigate the relationship between temperature and DTR and asthma hospitalizations. It considered differences in the effects across various seasons and population subgroups. The study revealed that low temperatures immediately increase the risk of asthma hospitalization (RR = 1.2010, 95

The aim of this study was to determine the relationship between short-term exposure to ambient air pollution and the number of daily hospital admissions for genitourinary disorders in Lanzhou. Hospital admission data and air pollutants, including PM2.5, PM10, SO2, NO2, O38h and CO, were obtained from the period 2013 to 2020. A generalized additive model (GAM) combined with distribution lag nonlinear model (DLNM) based on quasi-Poisson distribution was used by the controlling for trends, weather, weekdays and holidays. Short-term exposure to PM2.5, NO2 and CO increased the risk of genitourinary disorder admissions with RR of 1.0096 (95

Until now, evidence for acute effects of ambient air pollution exposure on hospital admissions for chronic obstructive pulmonary disease (COPD) in the semi-arid Loess Plateau is scarce. We aimed to examine the association between short-term ambient air pollution and daily COPD admissions in Dingxi, China. Daily COPD hospital admissions data during 2018–2020 were acquired from all the tertiary and secondary hospitals in Dingxi. Air pollution and meteorological data over the same periods were also collected. A Poisson generalized additive models (GAM), combined with a distributed lag nonlinear model (DLNM), were employed to evaluate the association between ambient air pollution and hospital admission among patients with COPD. Stratified analyses by gender, age, and season were also performed. Our results showed that PM2.5, PM10, NO2, CO, and O38 h were associated with COPD-related hospitalizations, and no significant influence of SO2 was found on COPD hospital admission. When the concentration of PM2.5 (lag07), PM10 (lag07), NO2 (lag03), and CO (lag07) increased by 10 μg/m3, the daily number of COPD admissions increased by 11.55