Body mass index prediction rule for mid-upper arm circumference: the atherosclerosis risk in communities study. Issue 1 (15th September 2021)

• Record Type: Journal Article
• Authors: Northuis, Carin A.; Murray, Thomas A.; Lutsey, Pamela L.; Butler, Kenneth R.; Nguyen, Steve; Palta, Priya; Lakshminarayan, Kamakshi
• Is Part Of: Blood pressure monitoring. Volume 27:Issue 1(2022)
• Page Start: 50
• Page End: 54
• Publication Date: 2021-09-15
• Subjects: Atherosclerosis Risk in Communities -- blood pressure cuff sizes -- mid-arm circumference -- hypertension; Blood pressure -- Measurement -- Periodicals; Blood Pressure Determination -- Periodicals; Blood Pressure Monitoring, Ambulatory -- Periodicals; Blood Pressure Monitors -- Periodicals; Hypertension -- Periodicals; 612.140287
• DOI: 10.1097/MBP.0000000000000567
• Languages: English
• ISSNs: 1359-5237

Abstract

Abstract : Supplemental Digital Content is available in the text. Abstract : Objectives: Electronic health records (EHR) are a convenient data source for clinical trial recruitment and allow for inexpensive participant screening. However, EHR may lack pertinent screening variables. One strategy is to identify surrogate EHR variables which can predict the screening variable of interest. In this article, we use BMI to develop a prediction rule for arm circumference using data from the Atherosclerosis Risk in Communities (ARIC) Study. This work applies to EHR patient screening for clinical trials of hypertension. Methods: We included 11 585 participants aged 52–75 years with BMI and arm circumference measured at ARIC follow-up visit 4 (1996–1998). We selected the following arm circumference cutpoints based on the American Heart Association recommendations for blood pressure (BP) cuffs: small adult (≤26 cm), adult (≤34 cm) and large adult (≤44 cm). We calculated the sensitivity and specificity of BMI values for predicting arm circumference using receiver operating characteristic curves. We report the BMI threshold that maximized Youden's Index for each arm circumference upper limit of a BP cuff. Results: Participants' mean BMI and arm circumference were 28.8 ± 5.6 kg/m 2 and 33.4 ± 4.3 cm, respectively. The BMI-arm circumference Pearson's correlation coefficient was 0.86. The BMI threshold for arm circumference≤26 cm was 23.0 kg/m 2, arm circumference≤34 cm was 29.2 kg/m 2 and arm circumference≤44 cm was 37.4 kg/m 2 . Only the BMI threshold for arm circumference≤34 cm varied significantly by sex. Conclusions: BMI predicts arm circumference with high sensitivity and specificity and can be an accurate surrogate variable for arm circumference. These findings are useful for participant screening for hypertension trials. Providers can use this information to counsel patients on appropriate cuff size for BP self-monitoring.