Can change in phase angle predict the risk of morbidity and mortality during an 18-year follow-up period? A cohort study among adults - Langer, Raquel D.; Ward, Leigh C.; Larsen, Sofus C.; Heitmann, Berit L. (Frontiers in Nutrition, 2023)
Introduction: Phase angle (PhA, degrees) measured via bioimpedance (BIA, 50 kHz) is an index that has been used as an indicator of nutritional status and mortality in several clinical situations. To determine the relationship between six-year changes in PhA and total mortality as well as the risk of incident morbidity and mortality from cardiovascular disease (CVD) and coronary heart disease (CHD) during 18 years of follow-up among otherwise healthy adults. Methods: A random subset (n=1987) of 35-65 years old men and women were examined at baseline in 1987/88 and 6 years later in 1993/94. Measures included weight, height, and whole-body BIA, from which PhA was calculated. Information on lifestyle was obtained by questionnaire. The associations between 6-year PhA changes (ΔPhA) and incident CVD and CHD were assessed by Cox proportional hazard models. The median value of ΔPhA was used as the reference value. The hazard ratio (HRs) model and confidence intervals (CIs) of incident CVD and CHD were used according to the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ΔPhA. Results: During 18 years of follow-up, 205 women and 289 men died. A higher risk of both total mortality and incident CVD was present below the 50th percentile (Δ=-0.85º). The highest risk was observed below the 5th percentile (ΔPhA=-2.60º) in relation to total mortality (HR: 1.55; 95%CI: 1.10–2.19) and incident CVD (HR: 1.52; 95%CI: 1.16–2.00). Discussion: The larger the decrease in PhA the higher risk of early mortality and incident CVD over the subsequent 18 years. PhA is a reliable and easy measure that may help identify those apparently healthy individuals who may be at increased risk of future CVD or of dying prematurely. More studies are needed to confirm our results before it can be definitively concluded that PhA changes can improve clinical risk prediction.