We conducted a population-based retrospective open cohort study between the 31 January 2020 and 28 February 2021 using ‘The Health Improvement Network’ (THIN) database.
THIN database, hosted by Cegedim Health Data, consists of a sample of UK electronic medical records taken from 867 general practices (covering approximately 6% of the population) which have commissioned the use of the Vision software system [11, 12]. General practitioners (GPs), within the UK, have the option to subscribe to any of the NHS registered system suppliers and only those who have selected the Vision system will contribute data to THIN research database [13].
Following inception, THIN has been shown to be representative of the UK population in terms of demographic structure and prevalence of key comorbidities [14]. Symptoms, examinations, and diagnoses in THIN are recorded using a hierarchical clinical coding system called Read codes [15]. Of note, the database has been used extensively to examine outcomes of women exposed to DVA [7, 16,17,18,19]. General practices were included 1 year following their (1) instalment of electronic practice records and (2) acceptable mortality recording date to meet quality standards [20]. During the study period, 344 general practices (7,026,841 patients) met this inclusion criteria. Of those eligible general practices, only patients aged over 16 years, coded as female and registered with their general practice for at least 12 months prior to study start date (to ensure adequate time for baseline data recording to take place), were included. This led to a total of 2,512,769 remaining eligible patients for inclusion in the study.
Women (aged 16+ years) in the exposed group were defined as those with clinically coded exposure to DVA (Additional file 1: Table S1) who were then age- and sex-matched to those without such a recorded code (unexposed group). The Read code selection process has been previously described in the literature [21]. Ascertainment of exposure to DVA included the presence of broad codes such as ‘14X8.00: Victim of domestic violence’ as well as more specific exposures to sub-types of DVA such as ‘14XD200: H/O domestic sexual abuse’.
The index date in the exposed group was the date of the first code relating to DVA exposure or when they became eligible to enter the study. To mitigate immortality time bias, the same index date was assigned to the corresponding unexposed patient. The follow-up period for each patient was from the index date until the exit date, defined as the earliest of either of the following: study end date, last date of data collection from a given general practice, date patient transferred from general practice, date of death or date the outcome of interest occurred. The outcome of interest was the presence of a GP recorded diagnosis of suspected or confirmed COVID-19. Covariates (sociodemographic, lifestyle risk factors and comorbidities) relating to known risk factors for the development of COVID-19 complications were also recorded at each patient’s study entry [8].
Crude incidence rates per 1000 person-years were estimated for the exposed and the unexposed groups. A Cox proportional hazards regression model was then undertaken to determine crude and adjusted hazard ratios (HR) with 95% confidence intervals (CI) describing the COVID-19 risk in the exposed compared to the unexposed group. Where there were missing data in our covariates, they were treated as a separate missing category and included in the final analysis.
To examine the impact of recent DVA exposure and risk of outcome development, we have also undertaken a sensitivity analysis including only those with a code for DVA exposure in the 1 year prior to the study start date or during the study period.