Adding socioeconomic status to Framingham scoring to reduce disparities in coronary risk assessment
Adding socioeconomic status to Framingham scoring to reduce disparities in coronary risk assessment
Background The purpose of the study was to examine the potential of adding socioeconomic status (SES) to Framingham Risk Scoring (FRS) to improve coronary heart disease (CHD) prediction by SES.
Methods We assessed the effect of measures of SES (<12 years of education or low income) on model discrimination and calibration when added to FRS in a prospective cohort, Atherosclerosis Risk in Communities. We validated use of this model in a second cohort, the National Health and Nutritional Examination Survey linked to the National Death Index.
Results Based on FRS alone, persons of higher and lower SES had a predicted CHD risk of 3.7% and 3.9%, respectively, compared with observed risks of 3.2% and 5.6%. Adding SES to a model with FRS improved calibration with predicted risk estimates of 3.1% and 5.2% for those with higher and lower SES, mitigating the discrepancy between predicted and observed CHD events for low-SES persons. Model discrimination (area under the receiver operator curve) was not significantly affected, and consistent findings were observed in the validation sample. Inclusion of SES in the model resulted in upgrading of risk classification for 15.1% of low-SES participants (95% CI 13.9–29.4%).
Conclusions Standard FRS underestimates CHD risk for those at low SES; treatment decisions ignoring SES may exacerbate SES disparities. Adding SES to CHD risk assessment reduces this bias.
Along with age and sex, socioeconomic status (SES) is a powerful determinant of health. Low SES is associated with risk for coronary heart disease (CHD) independent of traditional CHD risk factors. Yet, SES is not included in current CHD risk assessments such as Framingham Risk Scoring (FRS). Framingham Risk Scoring is based on patient age, sex, smoking, blood pressure, and total and high-density cholesterol; and it has been validated in diverse samples. It provides an estimate of the 10-year risk for CHD and is incorporated into current cholesterol treatment guidelines.
Omission of SES consideration could bias CHD risk assessment of persons with lower SES. A Scottish study showed that FRS systematically underestimated cardiovascular risk for persons living in lower-SES communities relative to those residing in more affluent communities. To our knowledge, the effects of adding SES to CHD risk assessment have not been assessed in the United States.
We evaluated (1) whether FRS systematically underestimates CHD risk for low-SES persons and (2) whether adding SES to FRS mitigates this bias. We examined model discrimination and calibration using data from the Atherosclerosis Risk in the Community (ARIC) Study and validated the model and findings using CHD mortality outcome data for persons in the nationally representative Third National Health and Nutritional Examination Survey (NHANES III).
Abstract and Introduction
Abstract
Background The purpose of the study was to examine the potential of adding socioeconomic status (SES) to Framingham Risk Scoring (FRS) to improve coronary heart disease (CHD) prediction by SES.
Methods We assessed the effect of measures of SES (<12 years of education or low income) on model discrimination and calibration when added to FRS in a prospective cohort, Atherosclerosis Risk in Communities. We validated use of this model in a second cohort, the National Health and Nutritional Examination Survey linked to the National Death Index.
Results Based on FRS alone, persons of higher and lower SES had a predicted CHD risk of 3.7% and 3.9%, respectively, compared with observed risks of 3.2% and 5.6%. Adding SES to a model with FRS improved calibration with predicted risk estimates of 3.1% and 5.2% for those with higher and lower SES, mitigating the discrepancy between predicted and observed CHD events for low-SES persons. Model discrimination (area under the receiver operator curve) was not significantly affected, and consistent findings were observed in the validation sample. Inclusion of SES in the model resulted in upgrading of risk classification for 15.1% of low-SES participants (95% CI 13.9–29.4%).
Conclusions Standard FRS underestimates CHD risk for those at low SES; treatment decisions ignoring SES may exacerbate SES disparities. Adding SES to CHD risk assessment reduces this bias.
Introduction
Along with age and sex, socioeconomic status (SES) is a powerful determinant of health. Low SES is associated with risk for coronary heart disease (CHD) independent of traditional CHD risk factors. Yet, SES is not included in current CHD risk assessments such as Framingham Risk Scoring (FRS). Framingham Risk Scoring is based on patient age, sex, smoking, blood pressure, and total and high-density cholesterol; and it has been validated in diverse samples. It provides an estimate of the 10-year risk for CHD and is incorporated into current cholesterol treatment guidelines.
Omission of SES consideration could bias CHD risk assessment of persons with lower SES. A Scottish study showed that FRS systematically underestimated cardiovascular risk for persons living in lower-SES communities relative to those residing in more affluent communities. To our knowledge, the effects of adding SES to CHD risk assessment have not been assessed in the United States.
We evaluated (1) whether FRS systematically underestimates CHD risk for low-SES persons and (2) whether adding SES to FRS mitigates this bias. We examined model discrimination and calibration using data from the Atherosclerosis Risk in the Community (ARIC) Study and validated the model and findings using CHD mortality outcome data for persons in the nationally representative Third National Health and Nutritional Examination Survey (NHANES III).
