Effects of Regional Meteorological and Air Conditions on Community-Acquired Pneumonia Patients with Pre-Existing COPD and Asthma

Abstract

Climate change will further increase extreme weather conditions’ frequencies and intensities. Extreme meteorological and air conditions can adversely affect people’s health (Sohn, 2019). Community-acquired pneumonia, in the following simply called pneumonia, is one of the most common causes of death worldwide (Aliberti et al., 2021). Since clear linkages between this disease and both meteorological and air conditions exist (Wang et al., 2021), it is crucial to understand the effect of these conditions on pneumonia cases more profoundly but also, more specifically, how these effects interact and depend on the personal characteristics and medical backgrounds of patients. It is well-studied that especially extreme weather and air conditions, the latter including air quality and wind conditions, impact the number of people hospitalized for pneumonia (Y. Liu et al., 2014; Onozuka et al., 2009). However, many studies analyze the effects of meteorological and air conditions separately with mortality data as an endpoint while predominantly covering the Asian continent and, specifically larger cities (Basu & Samet, 2002; Chung et al., 2009; Ge et al., 2013). Therefore, data on other geographical regions and combinations of rural and urban areas are required. Additionally, little is known about how personal characteristics (age, sex) and health background (diseases, overweight, etc.) affect the sensitivity of pneumonia cases regarding meteorological and air conditions. We close this research gap by analyzing a prospective multicenter cohort that was treated in an in- or outpatient setting for pneumonia with pre-existing COPD and asthma background in 22 German hospitals or outpatient clinics. The dataset contains personal and health information for more than 10,000 patients. We match this data with daily regional meteorological and air condition data while not only considering the conditions on the day of hospitalization but also up to four days before. By using this time lag, we can explain hospitalization events more adequately. Logistic regressions are used to examine the impact of meteorological and air conditions on pneumonia cases considering a short-term and long-term perspective and the modification effects of various personal characteristics on these relationships. This research is valuable since it aims not only to determine but also to predict when people with COPD and pneumonia are at increased risk of pneumonia. This can support healthcare providers during weather conditions favoring pneumonia in better-preparing resources such as staff and treatments and guiding prophylaxis such as limiting outdoor activities.