AIMS: Obesity and cardiovascular diseases (CVDs) often co-occur, likely increasing the intensity of healthcare resource utilization (HCRU). This retrospective, observational database study examined the joint effect of obesity and cardiovascular risk status on HCRU and compared HCRU between body mass index (BMI) categories and CVD-risk categories in the UK. METHODS: Patient demographics and data on CVD and BMI were obtained from the UK Clinical Practice Research Datalink. Cardiovascular risk status, calculated using the Framingham Risk Equation, was used to categorize people into high-risk and low-risk groups, while a CVD diagnosis was used to define the established CVD group. Patients were split into BMI categories using the standard World Health Organization classifications. For each CVD and BMI category, mean number and costs of general practitioner contacts, hospital admissions and prescriptions were estimated. RESULTS: The final study population included 1,600,709 patients. Data on CVD status were available on just over one-quarter of the sample (28.6%) and BMI data for just less than half (43.2%). The number of general practitioner contacts and prescriptions increased with increasing BMI category for each of the three CVD-risk groups. The group with established CVD had the greatest utilization of all components of healthcare resource, followed by high CVD risk then low CVD-risk groups. CONCLUSION: Increasing BMI category and CVD-risk status both affected several HCRU components. These findings highlight the importance of timely obesity management and treatment of CVD-risk factors as a means of preventing increasing HCRU. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: Obesity and cardiovascular diseases (CVDs) often co-occur, likely increasing the intensity of healthcare resource utilization (HCRU). This retrospective, observational database study examined the joint effect of obesity and cardiovascular risk status on HCRU and compared HCRU between body mass index (BMI) categories and CVD-risk categories in the UK. METHODS: Patient demographics and data on CVD and BMI were obtained from the UK Clinical Practice Research Datalink. Cardiovascular risk status, calculated using the Framingham Risk Equation, was used to categorize people into high-risk and low-risk groups, while a CVD diagnosis was used to define the established CVD group. Patients were split into BMI categories using the standard World Health Organization classifications. For each CVD and BMI category, mean number and costs of general practitioner contacts, hospital admissions and prescriptions were estimated. RESULTS: The final study population included 1,600,709 patients. Data on CVD status were available on just over one-quarter of the sample (28.6%) and BMI data for just less than half (43.2%). The number of general practitioner contacts and prescriptions increased with increasing BMI category for each of the three CVD-risk groups. The group with established CVD had the greatest utilization of all components of healthcare resource, followed by high CVD risk then low CVD-risk groups. CONCLUSION: Increasing BMI category and CVD-risk status both affected several HCRU components. These findings highlight the importance of timely obesity management and treatment of CVD-risk factors as a means of preventing increasing HCRU. Published on behalf of the European Society of Cardiology. All rights reserved.