Cold waves and fine particulate matter in high-altitude Chinese cities: assessing their interactive impact on outpatient visits for respiratory disease.

BACKGROUND: Extreme weather events like heatwaves and fine particulate matter (PM2.5) have a synergistic effect on mortality, but research on the synergistic effect of cold waves and PM2.5 on outpatient visits for respiratory disease, especially at high altitudes in climate change-sensitive areas, is lacking. METHODS: we collected time-series data on meteorological, air pollution, and outpatient visits for respiratory disease in Xining. We examined the associations between cold waves, PM2.5, and outpatient visits for respiratory disease using a time-stratified case-crossover approach and distributional lag nonlinear modeling. Our analysis also calculated the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S). We additionally analyzed cold waves over time to verify climate change. RESULTS: Under different definitions of cold waves, the odds ratio for the correlation between cold waves and outpatient visits for respiratory disease ranged from 0.95 (95% CI: 0.86, 1.05) to 1.58 (1.47, 1.70). Exposure to PM2.5 was significantly associated with an increase in outpatient visits for respiratory disease. We found that cold waves can synergize with PM2.5 to increase outpatient visits for respiratory disease (REOI > 0, AP > 0, S > 1), decreasing with stricter definitions of cold waves and longer durations. Cold waves' independent effect decreased over time, but their interaction effect persisted. From 8.1 to 21.8% of outpatient visits were due to cold waves and high-level PM2.5. People aged 0-14 and ≥ 65 were more susceptible to cold waves and PM2.5, with a significant interaction for those aged 15-64 and ≥ 65. CONCLUSION: Our study fills the gap on how extreme weather and PM2.5 synergistically affect respiratory disease outpatient visits in high-altitude regions. The synergy of cold waves and PM2.5 increases outpatient visits for respiratory disease, especially in the elderly. Cold wave warnings and PM2.5 reduction have major public health benefits.

Effects of combined exposure to fine particulate matter and cold waves and on IHD hospitalizations at low and high altitudes.

Climate change and air pollution are major challenges facing the world today. Cold waves and air pollution significantly impact ischemic heart disease (IHD), but the extent of these effects at different altitudes remains unclear, especially their interactions. We collected daily meteorological, pollutant, and IHD hospitalization data from Xining and Xinxiang from 2016 to 2021. Using a time-stratified case-crossover approach, we fitted conditional Poisson regression models to assess the association between cold waves, PM2.5, and IHD hospitalizations and quantified their interactions. Additionally, we calculated the attributable fraction (AF) and attributable number (AN) of hospitalizations due to exposure to cold waves and medium to high-level PM2.5. We also performed stratified analyses by altitude, gender, and age. Both cold waves and PM2.5 were positively associated with IHD hospitalization rates in Xining and Xinxiang, but the differences between the two regions were not significant. The relative risk of cold waves was 1.15 (1.07, 1.24) in Xining and 1.16 (1.11, 1.21) in Xinxiang. In Xining, there was an interaction between cold waves and different levels of PM2.5. We estimated the attributable fraction due to the joint exposure of cold waves and PM2.5 to be 0.14-0.49 in Xining and 0.26-0.36 in Xinxiang. Older adults and males faced higher risks. This study highlights the importance of reducing PM2.5 exposure and optimizing extreme weather warning systems and suggests further exploration of the impacts of individual behaviors and regional characteristics on IHD.

Extreme cold weather and circulatory diseases of older adults: A time-stratified case-crossover study in jinan, China.

OBJECTIVES: We aimed to investigate the acute effect of extreme cold weather on circulatory disease mortality of older adults in Jinan, with individual and regional-scale characteristics as subgroup analyses to further identify vulnerable populations. METHODS: This study contained the death data of Jinan from 2011 to 2020 (Nov-Mar). A time-stratified case-crossover method was used to estimate the effects of extreme cold weather and lags 0-8 days, controlling for holiday and relative humidity. To evaluate the impact of different durations and thresholds of extreme cold weather, we considered 4 cold day and 12 cold wave definitions RESULTS: Our results showed an increase in circulatory disease deaths under several definitions. The number of older adults died of circulatory diseases totaled 92,119 during the study period. In the definitions of cold day, the maximum significant effect ranging from 1.08 (95% CI: 1.03,1.14) to 1.13 (95% CI: 1.04,1.24) and appeared on Lag5 or Lag6. In the definitions of cold wave, the maximum significant effect ranging from 1.07 (95% CI: 1.02, 1.12) to 1.14 (95% CI: 1.03, 1.25). The cold effect is mainly attributable to cold day rather than an added effect related to the duration. Our research confirmed that extreme cold weather had a stronger impact on women [maximum effects with an OR of 1.21 (95% CI: 1.08, 1.36) in P1, 1.19 (95% CI: 1.05, 1.36) in M12)], and the effect gradient increased with age. CONCLUSIONS: Our findings support the evidence on the impact of extreme cold weather on circulatory disease mortality and provide a basis for policymakers to select target groups to develop policies and reduce the public health burden.

The effect of cold and heat waves on mortality in Urmia a cold region in the North West of Iran.

Few studies have investigated the different extreme temperature effects (heat-cold) of one geographical location at the same time in Iran. This study was conducted to assess the impact of heat and cold waves on mortality in Urmia city, which has a cold and mountainous climate. Distributed Lag Non-linear Models combined with a quasi-Poisson regression were used to assess the impact of heat (HW) and cold waves (CW) on mortality in subgroups, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. The heat/cold effect was divided into two general categories A-main effect (the effect caused by temperature), B-added effect (the effect caused by persistence of extreme temperature). Results show that there was no relation between HW and respiratory and cardiovascular death, but in main effects, HW(H1) significantly increased, the risk of Non-Accidental Death (NAD) in lag 0 (Cumulative Excess Risk (CER) NAD = 31(CI; 4-65)). Also in added effects, HW had a significant effect on NAD (CER H1; NAD; lag;0-2 = 31(CI; 5, 51), CER H2; NAD; lag;0-2 = 26(CI; 6, 48)). There was no relation between CW and respiratory death and cardiovascular death, but in added effects, CW(C1) significantly decreased, the risk of non-accidental death in initial lags (CER C1; NAD; lag;0-2 = -19 (CI; -35, -2)). It seems that high temperatures and heat waves increase the risk of non-accidental mortality in northwest of Iran.

Impacts of cold weather on emergency hospital admission in Texas, 2004-2013.

Cold weather has been identified as a major cause of weather-related deaths in the U.S. Although the effects of cold weather on mortality has been investigated extensively, studies on how cold weather affects hospital admissions are limited particularly in the Southern United States. This study aimed to examine impacts of cold weather on emergency hospital admissions (EHA) in 12 major Texas metropolitan statistical areas (MSAs) for the 10-year period, 2004-2013. A two-stage approach was employed to examine the associations between cold weather and EHA. First, the cold effects on each MSA were estimated using distributed lag non-linear models (DLNM). Then a random effects meta-analysis was applied to estimate pooled effects across all 12 MSAs. Percent increase in risk and corresponding 95% confidence intervals (CIs) were estimated as with a 1 °C (°C) decrease in temperature below a MSA-specific threshold for cold effects. Age-stratified and cause-specific EHA were modeled separately. The majority of the 12 Texas MSAs were associated with an increased risk in EHA ranging from 0.1% to 3.8% with a 1 °C decrease below cold thresholds. The pooled effect estimate was 1.6% (95% CI: 0.9%, 2.2%) increase in all-cause EHA risk with 1 °C decrease in temperature. Cold wave effects were also observed in most eastern and southern Texas MSAs. Effects of cold on all-cause EHA were highest in the very elderly (2.4%, 95% CI: 1.2%, 3.6%). Pooled estimates for cause-specific EHA association were strongest in pneumonia (3.3%, 95% CI: 2.8%, 3.9%), followed by chronic obstructive pulmonary disease (3.3%, 95% CI: 2.1%, 4.5%) and respiratory diseases (2.8%, 95% CI: 1.9%, 3.7%). Cold weather generally increases EHA risk significantly in Texas, especially in respiratory diseases, and cold effects estimates increased by elderly population (aged over 75 years). Our findings provide insight into better intervention strategy to reduce adverse health effects of cold weather among targeted vulnerable populations.

Impact of heat and cold waves on female cattle mortality beyond the effect of extreme temperatures.

Although heat and cold temperatures are known to have an impact on cattle mortality, no study has evidenced and quantified the influence of the prolonged exposure to extreme temperatures beyond the single effect of daily temperatures. We defined a heat (or cold) wave by a continuous variable indicating the number of successive days with temperatures above (or below) a given threshold. For heat wave, the threshold was set to the 95th or 99th percentile of the mean daily temperature distribution and for cold wave to the 1st or 5th percentile. We collected female cattle mortality data by type of production and age classes between 2001 and 2015 for 100 iso-hygro-thermal areas in France. We used time-series analyses to estimate the area-specific heat wave- and cold wave-mortality relationships. Then, we applied meta-analyses to pool area-specific effects at the country level for each definition of heat and cold wave. For each type of production and age classes, our models predicted symmetrical relationships between temperature and mortality, with a temperature range of minimum mortality located approximately between 15 and 20 °CTHI in most categories. Outside that range, relative risks between 1.3 and 2.5 were estimated for extreme cold temperatures and relative risks between 1.1 and 1.5 were estimated for extreme hot temperatures depending on age categories and production type. Our results indicated that a prolonged exposure to high (or low) temperatures caused a significant increase on mortality (up to 40% during heat waves and 23% for cold waves, depending on type of production and age classes), in addition to the effect of extreme temperature alone. This additional mortality risk increased along with the duration and intensity of the exposure. Our results suggest that not discriminating the effect of the prolonged exposure to extreme temperature, may overestimate the effect of temperature alone on mortality.

Extreme climatic conditions and health service utilisation across rural and metropolitan New South Wales.

Periods of successive extreme heat and cold temperature have major effects on human health and increase rates of health service utilisation. The severity of these events varies between geographic locations and populations. This study aimed to estimate the effects of heat waves and cold waves on health service utilisation across urban, regional and remote areas in New South Wales (NSW), Australia, during the 10-year study period 2005-2015. We divided the state into three regions and used 24 over-dispersed or zero-inflated Poisson time-series regression models to estimate the effect of heat waves and cold waves, of three levels of severity, on the rates of ambulance call-outs, emergency department (ED) presentations and mortality. We defined heat waves and cold waves using excess heat factor (EHF) and excess cold factor (ECF) metrics, respectively. Heat waves generally resulted in increased rates of ambulance call-outs, ED presentations and mortality across the three regions and the entire state. For all of NSW, very intense heat waves resulted in an increase of 10.8% (95% confidence interval (CI) 4.5, 17.4%) in mortality, 3.4% (95% CI 0.8, 7.8%) in ED presentations and 10.9% (95% CI 7.7, 14.2%) in ambulance call-outs. Cold waves were shown to have significant effects on ED presentations (9.3% increase for intense events, 95% CI 8.0-10.6%) and mortality (8.8% increase for intense events, 95% CI 2.1-15.9%) in outer regional and remote areas. There was little evidence for an effect from cold waves on health service utilisation in major cities and inner regional areas. Heat waves have a large impact on health service utilisation in NSW in both urban and rural settings. Cold waves also have significant effects in outer regional and remote areas. EHF is a good predictor of health service utilisation for heat waves, although service needs may differ between urban and rural areas.

Influence of Cold Wave Diversities on Thermal Stress and Thermal Fatigue Life of Asphalt Mixture.

Apart from low-temperature cracking, asphalt pavement may also suffer from thermal fatigue cracking. To clarify the impact of cold waves on the thermal fatigue performance of asphalt mixtures, the typical atmospheric temperature characteristics of different regions in China from 2012 to 2019 were analyzed, and the frequency of cold waves in these regions was determined. The viscoelastic parameters of an asphalt mixture are determined through an indirect tensile relaxation test. The thermal stress of the asphalt mixture is simulated and analyzed by using the finite element method. The effect of cold waves on the thermal fatigue life of the asphalt mixture was evaluated. The results show that the frequency of cold waves is different from region to region in China, and the cold waves mainly occurred from October of one year to February of the next year. Northeast China has the most frequency and the largest temperature drop amplitude, followed by North China. The maximum thermal stress increases with the decrease in temperature drop and initial temperature and is unrelated to the duration of cold waves. The thermal stress calculated based on the atmospheric thermal boundary is higher than the value using the road surface temperature. The thermal fatigue lives of asphalt mixtures in North China and Northeast China are very short, while the thermal fatigue life of the mixture in Central China is the longest. To meet the requirement of thermal fatigue damage caused by cold waves during the designed service stage, the recommended threshold for thermal stress is 0.39-0.77 MPa.

Acute Effects of Low Temperatures and Cold Waves on Elderly Infectious Pneumonia Mortality - Jinan City, Shandong Province, China, 2014-2022.

What is already known about this topic?: The mortality rate due to pneumonia varies depending on the infectious agents present in a low- temperature environment. What is added by this report?: This study aimed to examine the relationship between low temperatures and cold waves and the risk of mortality from infectious pneumonia in the elderly. The findings indicate a significant increase in the risk of infectious pneumonia, specifically bacterial pneumonia, during periods of low temperatures and cold waves. What are the implications for public health practice?: This study presents compelling evidence that highlights the importance of proactive public responses to infectious pneumonia among the elderly population during periods of cold waves.

Role of meteorology and air pollution on fog conditions over Delhi during the peak winter 2024.

Severe air pollution and foggy conditions during winter are persistent challenges, pose significant health hazards, and disrupt daily routines worldwide. In this study, we have investigated the conditions favoring the prolonged fog events in Delhi during January 2024 using observations, back trajectories, and reanalysis datasets. Analysis of visibility observations reveals that foggy (54, 121, 139, and 372 half-hours of very dense, dense, moderate, and shallow fog, respectively) conditions persisted in Delhi for 46 % of the time during the study period. The existence of 3-4 days of cold wave to severe cold wave conditions and the lack of passage of strong western disturbances across north and northwest India have also favored the prolonged fog formation. In addition, high relative humidity (>80 %), shallow boundary layer (216 m), stable weather conditions such as the absence of significant surface winds, the existence of cold wave to severe cold wave, temperature inversion (up to 4 °C), poor ventilation, and presence of high particulate matter (PM10: 298 µg/m3 and PM2.5: 182 µg/m3) facilitated the fog formation. Further, analyses reveal a spurt in daily particulate matter (PM10: 603 µg/m3 and PM2.5: 420 µg/m3; 13.4 and 28 times, respectively, exceeded the WHO air quality guideline levels) along with 4.5 h of zero visibility on 14th January. The analysis of particulate matter reveals the dominance of fine particles from nearby regions, which could have originated from the large-scale anthropogenic open biomass burning used for heating activities. The results derived from this study indicate the need for an accurate representation of the local anthropogenic emissions in the atmospheric models to improve the predictability of air quality and fog and provide insights into the need for their control, particularly during such extreme events.