Asthma is a common lung condition that occasionally makes it difficult for people to breathe, causing symptoms like coughing and wheezing. Pollution and temperature changes can harm people's health, especially those with asthma. Scientists study how the environment affects health, but comparing different timescales, like hourly pollution and daily health data, was not possible previously. We created a way to combine detailed weather and pollution data with health data, even if they're on different timescales. We want to see how hourly high temperatures and high air pollution levels may affect patients with asthma. Therefore, we aim to study how rapid changes in pollution and temperature affect people with asthma. Unlike typical studies that focus on daily values, we are interested in shorter time-periods, as high levels of pollution or high temperature usually last for only a few hours a day. This research could help people with asthma avoid getting sick when the environment is poor.
Extreme temperatures and air pollution, particularly high and low temperatures, as well as elevated concentrations of fine particles measuring 2.5 microns or less in diameter (PM2.5), are risk factors linked to exacerbations of asthma symptoms. In exposure-response modeling, environmental epidemiologists often need to aggregate their exposure data, for instance, from hourly to daily, to match the resolution of health data. The aggregation of exposure data results in the loss of available exposure information, which could lead to an underestimation of the impact of extreme environmental exposure on human health. Therefore, we have developed a method called mixed-frequency distributed lag nonlinear models (mfDLNM).
This study aims to estimate the risk of hospitalization among asthma patients for respiratory diseases due to temperature and air pollution at a one-hour temporal resolution, which is rare in the epidemiological literature. Asthma affects over 262 million people globally, and the UK experiences a high burden of morbidity and mortality associated with the condition, with three deaths per day and 60,000 emergency hospital admissions annually [1-3].
We intend to employ mfDLNM, a mixed frequency time series model, to characterise the relationship between daily hospitalization rates for asthma patients and hourly environmental exposures. The daily rate of hospitalization for respiratory diseases among asthma patients in England will be obtained from Hospital Episode Statistics (HES) records linked to CPRD. The exposure information will include hourly PM2.5 and temperature from the UK Automatic Urban and Rural Network (AURN) and modelled data from the Copernicus programme. The study, covering 2010 to 2022, focuses on the time-dependent response to environmental exposures.
This will enable us to identify the hourly risk of hospitalization among asthma patients due to hourly exposure to these variables in England, which will aid in future preventive decision-making during extreme environmental events.
Daily hospitalization counts due to respiratory disease (International Classification of Diseases (ICD)-10 J00-J99) amongst asthma patients.
Tim Lucas - Chief Investigator - University of Leicester
Nidhi Shukla - Corresponding Applicant - University of Leicester
Anna Hansell - Collaborator - University of Leicester
Suzanne Bartington - Collaborator - University of Birmingham
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;CPRD Aurum Ethnicity Record;CPRD GOLD Ethnicity Record;Practice Level Rural-Urban Classification