Phase angle (PhA) in overweight and obesity: evidence of applicability from diagnosis to weight changes in obesity treatment

Assessment of phase angle as a novel indicator for sarcopenic obesity according to the ESPEN/EASO criteria in older adults with diabetes mellitus

BACKGROUND

Sarcopenic obesity (SO) is a clinical condition in which sarcopenia and obesity occur together, and is associated with more poor clinical outcomes, increased mortality, and morbidity than sarcopenia. Phase angle (PhA), a parameter derived from bioimpedance analysis (BIA), provides data on cellular health, membrane integrity, and cellular function. This study aimed to evaluate the relationship between SO and PhA among older adults with type 2 diabetes mellitus (DM).

METHODS

We performed a cross-sectional study in a tertiary hospital, and all participants underwent a comprehensive geriatric assessment, the hand-grip strength test (HGST), the chair stand test (CST) for muscle strength evaluation, the 4-meter walking test, and the timed up-and-go (TUG) test for physical performance assessment. The diagnosis of SO was made according to the ESPEN/EASO criteria. The PhA was determined automatically by the BIA using resistance and reactance at 50 kHz for each participant.

RESULTS

A total of 322 participants were included in the study. The mean age of the participants was 72.5 ±5.8, and 203 (63%) of them were female; 63 (19.6%) of them were sarcopenic obese. In multivariable logistic regression analyses, a significant relationship was found when the model was adjusted for age, female gender, MNA-sf scores, HbA1c level, and CCI scores (OR: 0.53, 95%CI: 0.29-0.98, P = 0.04). In ROC analyses, for PhA in predicting SO diagnosis, the AUC was 0.586 (95%CI: 0.505-0.678, P = 0.033). At the cut-off score 4.4, sensitivity was 57.1% and specificity was 61.4%; positive predictive value (PPV) was 26.5%; negative predictive value (NPV) was 85.5%.

CONCLUSIONS

The study identified a significant relationship between SO and PhA among older adults with type 2 DM. However, larger prospective studies are needed to confirm the potential utility of PhA as a biomarker for SO.

Revisiting the beyond BMI paradigm in excess weight diagnosis and management: A call to action

Adolphe Quételet, a 19th-century Belgian sociologist and statistician, pioneered the incorporation of statistics into social sciences. He initiated the development of anthropometry since he was interested in identifying the proportions of the 'ideal man'. He devised a ratio between weight and height, originally termed the Quételet Index, and today widely known and used as the body mass index or BMI. In 1835, he demonstrated that a normal curve accommodates the distribution of human traits articulating his reasoning on human variance around the average. Quételet's long-lasting legacy of the establishment of a simple measure to classify people's weight relative to an ideal for their height endures today with minor variations having dramatically influenced public health agendas. While being very useful, the limitations of the BMI are well known. Thus, revisiting the beyond BMI paradigm is a necessity in the era of precision medicine with morphofunctional assessment representing the way forward via incorporation of body composition and functionality appraisal. While healthcare systems were originally designed to address acute illnesses, today's demands require a radical rethinking together with an original reappraisal of our diagnosis and treatment approaches from a multidimensional perspective. Embracing new methodologies is the way forward to advance the field, gain a closer look at the underlying pathophysiology of excess weight, keep the spotlight on improving diagnostic performance and demonstrate its clinical validity. In order to provide every patient with the most accurate diagnosis together with the most appropriate management, a high degree of standardization and personalization is needed.

Is phase angle associated with visceral adiposity and cardiometabolic risk in cardiology outpatients?

BACKGROUND/OBJECTIVES

Phase angle (PhA) serves as a prognostic marker in various clinical scenarios, reflecting oxidative stress and cellular damage. Despite its clinical relevance, its connection with adiposity and cardiovascular risk markers remains underexplored. Hence, our study sought to investigate the relationship between PhA and metabolic, adiposity, and cardiovascular risk parameters among outpatients with cardiology diagnosis.

SUBJECTS/METHODS

Adults aged between 26 and 59 years, under the care of a cardiology unit, were included. Ultrasound imaging was used to assess visceral adipose tissue (VAT). Single-frequency bioelectrical impedance analysis (BIA) [50 kHz] was employed to calculate PhA, from BIA's resistance and reactance measurements. Muscle strength, body mass index, waist circumference, and waist-to-height ratio were also evaluated. Framingham's risk score was calculated to estimate the cardiovascular risk events. Metabolic blood samples' results were obtained from medical records.

RESULTS

One hundred and five participants were included in our study. Low PhA was observed in 29.5% of our sample. Higher PhA values were independently and inversely associated with both higher VAT and cardiovascular risk (adjusted OR: 0.79 [95% CI 0.69;0.91], OR: 0.74 [95% CI 0.60;0.89], respectively). Lower PhA values (≤5.59) were goodly associated with high VAT (AUC: 0.82 p < 0.001). Lower PhA values (≤5.06) were fairly associated with higher cardiovascular risk (AUC: 0.70 p = 0.003).

CONCLUSION

Our study provides evidence that PhA is independently and inversely associated with elevated VAT and cardiovascular risk. These findings underscore the potential of PhA as a valuable complementary marker in assessing cardiometabolic health.

Phase angle as an indicator of body composition and physical performance in handball players

BACKGROUND

Phase angle (PhA), obtained from the bioimpedance analysis, is widely used in clinical situations and in sports. This study evaluated the association between PhA with body composition and physical performance of handball athletes.

METHODS

43 national-level players (22.19 ± 3.86 years) of both sexes were evaluated regarding anthropometry, body composition, squat (SJ) and countermovement (CMJ) jumps, handgrip strength, and cardiorespiratory fitness.

RESULTS

We verified a correlation between PhA of the whole body and fat-free mass (r = 0.511), body mass index (r = 0.307), and body fat % (r = -0.303). There was a positive correlation between PhA of the whole body and SJ (r = 0.376), CMJ (r = 0.419), and handgrip for the dominant hand (r = 0.448). Moreover, PhA of the upper limbs was more strongly correlated with handgrip for the dominant (r = 0.630) and non-dominant hand (r = 0.575) compared to PhA of the whole body considering both sexes. Similarly, segmental PhA had a stronger significant correlation with SJ (r = 0.402) and handgrip for the dominant hand (r = 0.482) in males, as well as CMJ (r = 0.602) in females, compared to PhA of the whole body.

CONCLUSION

PhA of the whole body was positively related to fat-free mass, body mass index, body fat %, and lower- and upper-limbs strength in handball athletes. Segmental PhA might be used as a tool for estimating lower and upper limbs performance considering the sex, in preference to the PhA of the whole body.

Specific bioelectrical vectors pattern in individuals with sarcopenic obesity

BACKGROUND

Sarcopenic obesity is a common condition in the elderly associated with excessive adiposity and low muscle mass and strength.

AIMS

This study aims to establish a method for detecting bioelectrical characteristics in individuals with sarcopenic obesity through specific Bioelectrical Impedance Vector Analysis (specific BIVA), while considering the characteristics of individuals with healthy, sarcopenic, and obese conditions.

METHODS

The sample was composed by 915 Italian adults over 50 years of age (men: 74.6 ± 8.8 y; women:76.3 ± 8.8 y) living in Sardinia (Italy). A dataset of 1590 US adults aged 21 - 49 years retrieved from the 2003 - 2004 National Health and Nutrition Examination Survey was also considered in a final step of the study. Anthropometric (stature, weight, waist, arm, and calf circumferences) and whole-body bioelectrical variables were taken. In the Italian sample, bioelectrical impedance was applied to estimate the relative content of fat mass and skeletal muscle mass. Groups with healthy body composition (NS-NO), or consistent with sarcopenia (S), sarcopenic obesity (S-O), and obesity (O) were defined based on the cut-offs suggested by European expert guidelines (EWGSOP2 and ESPEN-EASO). Specific BIVA was applied to compare groups and to identify the area for sarcopenic obesity within young-adults tolerance ellipses. The position of the specific vector of US individuals with S-O, selected on the basis of DXA measurements, was also considered.

RESULTS

In both sexes of the Italian sample, the bioelectrical characteristics of the four groups were different (p < 0.001). The differences were mainly related to vector length, indicative of higher fat mass, which was longer in the O and S-O groups, and phase angle, a proxy of intracellular/extracellular water and muscle mass, lower in the sarcopenic groups. Bioelectrical vectors of the S-O group fell in the right quadrant, outside of the 95 % tolerance ellipses of young adults. The mean vector of the US sample with S-O fell in the same area. Within the S-O area, women had similar bioelectrical values, while men showed phase angle variability, which was related to the severity of the condition.

CONCLUSIONS

Specific BIVA detects body composition peculiarities of individuals with sarcopenic obesity, thus allowing their diagnosis when associated with low handgrip strength values.

Phase angle is associated with sarcopenic obesity in post-stroke patients

BACKGROUND & AIMS

Evidence is limited concerning the association between bioimpedance analysis-derived phase angle and sarcopenic obesity. This study examined this association in patients who underwent convalescent rehabilitation after stroke.

METHODS

This cross-sectional study included hospitalized patients with post-acute stroke. The phase angle was measured using a multifrequency bioimpedance analysis. Sarcopenic obesity was diagnosed according to the European Society of Clinical Nutrition and Metabolism/European Association for the Study of Obesity criteria. A multiple linear regression analysis was used to examine the association between the phase angle and sarcopenic obesity after adjusting for confounding factors. A receiver operating characteristic curve was used to calculate the optimal phase angle cutoff value for predicting sarcopenic obesity.

RESULTS

A total of 760 patients (median age 71 years; 352 women) were analyzed. The median (interquartile range, 25th and 75th percentiles) phase angle was 4.45° (4.10°, 4.88°). Sarcopenic obesity was diagnosed in 16 (3.9%) men, 18 (5.1%) women, and 34 (4.5%) patients overall. The multiple linear regression analysis showed that sarcopenic obesity (β = -0.185, p = 0.017) and sarcopenia (β = -0.121, p = 0.012) were significantly and negatively associated with the phase angle. Obesity was not significantly associated with the phase angle (β = -0.078, p = 0.094). The optimal cutoff value of the phase angle for diagnosing sarcopenic obesity was 4.29° (sensitivity 0.65, specificity 0.80, area under the curve [AUC] 0.79, 95% CI 0.77-0.87, p < 0.001) in men and 3.84° (sensitivity 0.67, specificity 0.84, AUC 0.81, 95% CI 0.79-0.86, p < 0.001) in women.

CONCLUSION

The phase angle was associated with sarcopenic obesity, and the cutoff values of the phase angle that could predict sarcopenic obesity were 4.29° for men and 3.84° for women. This simple and practical phase angle-based prediction of sarcopenic obesity can be useful in clinical practice.

Association between phase angle and the nutritional status in pediatric populations: a systematic review

Background and aims

Malnutrition is prevalent in pediatric populations with any disease, and it is also related to changes in body composition. In addition, recent studies have documented relationships between these changes and phase angle (PhA), an important parameter of functional nutritional assessment. PhA could be a new marker of nutritional status. Many studies have generated information about the association between PhA and malnutrition in various pathologies, although the vast majority of this information is from adult populations. In this systematic review, we answered the following question: What is the association between PhA and the nutritional status in pediatric populations?

Methods

We performed a systematic search of the Medline/PubMed and Latin American and Caribbean Health Sciences Literature databases (LILACS) databases for studies published up to October 2022. The inclusion criteria were pediatric subjects, which reported the relationship between PhA and the nutritional status with any objective nutritional indicator, and PhA was measured by electric impedance and reported at 50 kHz. We synthesized data from the studies that reported cutoff analysis of PhA with receiver operating characteristic (ROC) curves, mean PhA values presented by nutritional status strata, and correlations between PhA and nutritional status indicators. We assessed the risk of bias by using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies and the Quality Assessment for Diagnostic Accuracy Studies.

Results

Of the 126 studies we identified, 15 met the inclusion criteria. The included studies reported the association between PhA and objective indicators of nutritional status, including weight-for-age z-score (WAZ) <-1 standard deviation (SD) for malnutrition, height-for-age z-score (HAZ) for malnutrition-stunting, body mass index (BMI) for the starvation state, body mass index z-score (BMIz) and BMI for malnutrition, mid-upper arm circumference (MUAC) <11 cm for severe acute malnutrition (SAM), and fat-free mass index z-score (FFMIz) <-2 z-score for moderate malnutrition, among others. The report of these associations between PhA and nutritional status was based on cutoff points generated with ROC curve analysis or comparison of mean PhA values, which were reported stratified by the presence or absence of malnutrition, and correlations between PhA and anthropometric indicators for the evaluation of the nutritional status in the pediatric population. It was difficult to compare the studies due to the heterogeneity of the bioelectrical impedance analysis models used, how PhA was reported (standardized, percentiles, or degrees), and the anthropometric indicators used to diagnose malnutrition.

Conclusion

The early identification of malnutrition is relevant to establish the correct nutritional treatment; PhA appears to be a sensitive indicator of nutritional status and is easy to obtain. Although the results of this review are inadequate to establish PhA cutoff points associated with malnutrition in pediatric populations, in most of the studies, there was an association between PhA and objective indicators of nutritional status.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022362413, identifier: PROSPERO 2022 CRD42022362413.