What Are the Effects of Meteorological Factors on Exacerbations of Chronic Obstructive Pulmonary Disease?

Heat and Cold Wave-Related Mortality Risk among United States Veterans with Chronic Obstructive Pulmonary Disease: A Case-Crossover Study

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a heterogeneous pulmonary disease affecting 16 million Americans. Individuals with COPD are susceptible to environmental disturbances including heat and cold waves that can exacerbate disease symptoms.

OBJECTIVE

Our objective was to estimate heat and cold wave-associated mortality risks within a population diagnosed with a chronic respiratory disease.

METHODS

We collected individual level data with geocoded residential addresses from the Veterans Health Administration on 377,545 deceased patients with COPD (2016 to 2021). A time stratified case-crossover study was designed to estimate the incidence rate ratios (IRR) of heat and cold wave mortality risks using conditional logistic regression models examining lagged effects up to 7 d. Attributable risks (AR) were calculated for the lag day with the strongest association for heat and cold waves, respectively. Effect modification by age, gender, race, and ethnicity was also explored.

RESULTS

Heat waves had the strongest effect on all-cause mortality at lag day 0 [IRR: 1.04; 95% confidence interval (CI): 1.02, 1.06] with attenuated effects by lag day 1. The AR at lag day 0 was 651 (95% CI: 326, 975) per 100,000 veterans. The effect of cold waves steadily increased from lag day 2 and plateaued at lag day 4 (IRR: 1.04; 95% CI: 1.02, 1.07) with declining but still elevated effects over the remaining 7-d lag period. The AR at lag day 4 was 687 (95% CI: 344, 1,200) per 100,000 veterans. Differences in risk were also detected upon stratification by gender and race.

DISCUSSION

Our study demonstrated harmful associations between heat and cold waves among a high-risk population of veterans with COPD using individual level health data. Future research should emphasize using individual level data to better estimate the associations between extreme weather events and health outcomes for high-risk populations with chronic medical conditions. https://doi.org/10.1289/EHP13176.

Epidemiological Characteristics of 101,471 Patients Hospitalized with Chronic Obstructive Pulmonary Disease (COPD) in Poland in 2019: Multimorbidity, Duration of Hospitalization, In-Hospital Mortality

Chronic obstructive pulmonary disease (COPD) is a common lung disease. There is a limited amount of nationwide data on COPD patients in Poland. This study aimed to characterize patients hospitalized with COPD in Poland in 2019 as well as to identify factors associated with the risk of in-hospital death and prolonged hospitalization among patients with COPD. This study is a retrospective database analysis. Data on patients hospitalized with COPD in Poland were obtained from the Nationwide General Hospital Morbidity Dataset. Data on all adults aged ≥40 years with a diagnosis of COPD from a physician (J44 code) were included in the analysis. Data were analyzed separately for patients hospitalized due to COPD (primary diagnosis) and patients with COPD as a comorbidity (secondary diagnosis). Completed medical records were available for 101,471 patients hospitalized with COPD (36.9% were females). Of those, 32% were hospitalized due to COPD. The mean age was 71.4 ± 9.7 years. The mean duration of hospitalization was 9.4 ± 11.4 days (median 7 days). Most of the COPD patients (89.3%) had at least one comorbidity. The in-hospital mortality rate was 6.8%. Older age, presence of cardiovascular diseases, and diseases of the genitourinary system (p < 0.05) were the most important factors associated with the risk of in-hospital death among patients hospitalized due to COPD.

Application of machine learning to predict hospital visits for respiratory diseases using meteorological and air pollution factors in Linyi, China

Urbanization and industrial development have resulted in increased air pollution, which is concerning for public health. This study evaluates the effect of meteorological factors and air pollution on hospital visits for respiratory diseases (pneumonia, acute upper respiratory infections, and chronic lower respiratory diseases). The test dataset comprises meteorological parameters, air pollutant concentrations, and outpatient hospital visits for respiratory diseases in Linyi, China, from January 1, 2016 to August 20, 2022. We use support vector regression (SVR) to build models that enable analysis of the effect of meteorological factors and air pollutants on the number of outpatient visits for respiratory diseases. Spearman correlation analysis and SVR model results indicate that NO2, PM2.5, and PM10 are correlated with the occurrence of respiratory diseases, with the strongest correlation relating to pneumonia. An increase in the daily average temperature and daily relative humidity decreases the number of patients with pneumonia and chronic lower respiratory diseases but increases the number of patients with acute upper respiratory infections. The SVR modeling has the potential to predict the number of respiratory-related hospital visits. This work demonstrates that machine learning can be combined with meteorological and air pollution data for disease prediction, providing a useful tool whereby policymakers can take preventive measures.

How Vulnerable Are Patients with COPD to Weather Extremities?—A Pilot Study from Hungary

Chronic obstructive pulmonary disease (COPD) is one of the most common causes of death globally, with increasing prevalence and years lived with disability (YLD). We aimed to investigate how extreme weather conditions were associated with the number of daily COPD-related emergency visits. We collected data regarding the number of daily emergency department (ED) visits made by patients with COPD in 2017, along with all relevant daily meteorological data for the same year. An analysis of the relationship between the number of COPD-related ED visits and extreme meteorological events was carried out. Extremely low temperatures (OR = 1.767) and dew points (OR = 1.795), extremely high atmospheric pressure (OR = 1.626), a high amount of precipitation (OR = 1.270), and light wind speed (OR = 1.560) were identified as possible risk factors for a higher number of COPD-related ED visits. In contrast, extremely high temperatures (OR = 0.572) and dew points (OR = 0.606) were found to be possible protective factors for COPD-related ED visits. By determining the meteorological risk factors for a high number of COPD-related ED visits, our study may help provide invaluable data for identifying vulnerable patient groups based on weather events, thus making more optimal capacity planning at the ED possible.

Climate-mediated air pollution associated with COPD severity

Air pollution has been reported to be associated with chronic obstructive pulmonary disease (COPD). Our study aim was to examine the mediating effects of air pollution on climate-associated health outcomes of COPD patients. A cross-sectional study of 117 COPD patients was conducted in a hospital in Taiwan. We measured the lung function, 6-min walking distance, oxygen desaturation, white blood cell count, and percent emphysema (low attenuation area, LAA) and linked these to 0-1-, 0-3-, and 0-5-year lags of individual-level exposure to relative humidity (RH), temperature, and air pollution. Linear regression models were conducted to examine associations of temperature, RH, and air pollution with severity of health outcomes. A mediation analysis was conducted to examine the mediating effects of air pollution on the associations of RH and temperature with health outcomes. We observed that a 1 % increase in the RH was associated with increases in forced expiratory volume in 1 s (FEV₁), eosinophils, and lymphocytes, and a decrease in the total-lobe LAA. A 1 °C increase in temperature was associated with decreases in oxygen desaturation, and right-, left-, and upper-lobe LAA values. Also, a 1 μg/m³ increase in PM_2.5 was associated with a decrease in the FEV₁ and an increase in oxygen desaturation. A 1 μg/m³ increases in PM₁₀ and PM_2.5 was associated with increases in the total-, right-, left, upper-, and lower-lobe (PM_2.5 only) LAA. A one part per billion increase in NO₂ was associated with a decrease in the FEV₁ and an increase in the upper-lobe LAA. Next, we found that NO₂ fully mediated the association between RH and FEV₁. We found PM_2.5 fully mediated associations of temperature with oxygen saturation and total-, right-, left-, and upper-lobe LAA. In conclusion, climate-mediated air pollution increased the risk of decreasing FEV₁ and oxygen saturation and increasing emphysema severity among COPD patients. Climate change-related air pollution is an important public health issue, especially with regards to respiratory disease.

Effect of high-level fine particulate matter and its interaction with meteorological factors on AECOPD in Shijiazhuang, China

Epidemiological evidence of the effect of high-level air pollution and its interaction with meteorological factors on the risk of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is limited. Daily data on AECOPD cases, air pollutants and meteorological factors were collected from 2015 to 2018 in Shijiazhuang. A distributed lag non-linear model (DLNM) was used to explore the lag and cumulative effect of PM_2.5 on the risk of AECOPD. The effect of the interaction between PM_2.5 and meteorological factors on AECOPD was estimated by a generalized additive model (GAM) and a stratification model. A total of 4766 patients with AECOPD were enrolled. After controlling for confounders, each 10 μg/m³ increase in PM_2.5 led to a 5.8% increase in the risk of AECOPD on day lag 0. The cumulative effect of PM_2.5 on AECOPD risk showed an increasing trend after 3 days. Similar results were observed in both smoking and non-smoking patients. There was an interaction between PM_2.5 and meteorological factors, and the risk of AECOPD was higher in cold and lower humidity conditions than in other conditions. High-level PM_2.5 exposure is positively associated with the risk of AECOPD onset, and the effect of PM_2.5 can be modified by the temperature and relative humidity. Public health guidelines should pay close attention to AECOPD risk under the condition of high-level PM_2.5 with low temperature or low humidity.