BackgroundFrailty is a common condition in older adults and has a major impact on patient outcomes and service use. Information on the prevalence in middle-aged adults and the patterns of progression of frailty at an individual and population level is scarce. To address this, a cohort was defined from a large primary care database in England to describe the epidemiology of frailty and understand the dynamics of frailty within individuals and across the population. This article describes the structure of the dataset, cohort characteristics and planned analyses.MethodsRetrospective cohort study using electronic health records. Participants were aged ≥50 years registered in practices contributing to the Oxford Royal College of General Practitioners Research and Surveillance Centre between 2006 to 2017. Data include GP practice details, patient sociodemographic and clinical characteristics, twice-yearly electronic Frailty Index (eFI), deaths, medication use and primary and secondary care health service use. Participants in each cohort year by age group, GP and patient characteristics at cohort entry are described.ResultsThe cohort includes 2,177,656 patients, contributing 15,552,946 person-years, registered at 419 primary care practices in England. The mean age was 61 years, 52.1% of the cohort was female, and 77.6% lived in urban environments. Frailty increased with age, affecting 10% of adults aged 50–64 and 43.7% of adults aged ≥65. The prevalence of long-term conditions and specific frailty deficits increased with age, as did the eFI and the severity of frailty categories.ConclusionA comprehensive understanding of frailty dynamics will inform predictions of current and future care needs to facilitate timely planning of appropriate interventions, service configurations and workforce requirements. Analysis of this large, nationally representative cohort including participants aged ≥50 will capture earlier transitions to frailty and enable a detailed understanding of progression and impact. These results will inform novel simulation models which predict future health and service needs of older people living with frailty.Study registrationRegistered on www.clinicaltrials.gov October 25th 2019, NCT04139278.