Study type

Study type

Non-interventional study

Scope of the study

Disease epidemiology
Non-interventional study

Non-interventional study design

Cohort
Study drug and medical condition

Medical condition to be studied

Asthma
Population studied

Age groups

Adults (18 to < 46 years)
Adults (46 to < 65 years)
Adults (65 to < 75 years)
Adults (75 to < 85 years)
Adults (85 years and over)

Estimated number of subjects

100000
Study design details

Main study objective

• Explore differences in asthma severity, control and phenotype by ethnic and socioeconomic groups• Explore patterns of medication usage and healthcare utilisation in different ethnic and socioeconomic groups• Identify determinants of asthma severity in different ethnic and socioeconomic groups• Identify disparities in referrals for patients from different ethnic and socioeconomic groups

Outcomes

Asthma severity will be ascertained using medication prescription data. Patients will be categorised according to the treatment steps described by GINA, Lung function measurementsBlood eosinophil countsHospital admissions A&E attendancesGP consultationsAsthma exacerbationsMaintenance medication adherence Time to treatment escalationTime to specialist referral

Data analysis plan

Descriptive statistics: Descriptive statistics will be calculated for the entire cohort and separately for each ethnic and socioeconomic groupSeverity prevalence: appropriate 95% confidence intervals calculated using the multinomial distribution. Multivariable analysis will be conducted using ordinal logistic regression.Care pathways: The number of hospital admissions, A&E attendances, GP consultations and asthma exacerbations will be analysed using Poisson regression. Lung function measurements, blood eosinophil counts and the prescription possession ratio will be analysed using linear regression. Patients who have their treatment escalated following a loss of control will be investigated using logistic regression. The time between eligibility for specialist referral and attendance will be analysed using Cox regression.Unadjusted analyses and adjusted analysis (accounting for difference in demographics, lifestyle factors etc.) will be presented