The usability of bioelectrical impedance analysis in overweight and obese children

INTRODUCTION

OBESITY

Obesity is a chronic recurrent disease related to exces­sive fat tissue accumulation, presenting a risk to health status of an obese individual [1]. Beyond the numerous comorbidities affecting individuals, obesity remains a public health concern, and is one of the most pressing challenges to be addressed in the coming years.
The diagnosis of obesity in children and adolescents depends on anthropometric measurements, such as weight, height, and their calculated derivatives, i.e., body mass index (BMI) assessed via child growth standards for age and sex, specific to a population.
The purpose of this paper was to evaluate whether bioelectrical impedance analysis (BIA) is a sufficiently reli­able method for assessing body composition (BC) in the po­pulation of obese children for daily use in clinical practice.
Sarcopenic obesity (SO) is defined as sarcopenia (i.e., loss of muscle mass, function, and strength) and obesity occurring together [2]. Sarcopenia causes reduced energy expenditure; it exacerbates obesity and increases the risk of obesity-related disorders [3]. As SO refers to patients with low muscle mass and high fat mass, they are not neces­sarily ‘obese’ or ‘overweight’ when classified by a BMI Z-score. That is why besides the handgrip strength measurement (HGS), muscle-to-fat ratio (MFR) is employed to assess SO [4]. Initially, sarcopenia has been associated with elderly; therefore, diagnostic criteria have been designed for the adult population. For pediatrics, researchers rely on criteria available to the general population [3].
Metabolic-associated fatty liver disease (MAFLD), previously known as nonalcoholic fatty liver disease (NAFLD), is a spectrum of liver diseases associated with obesity. New nomenclature was proposed in 2020 because previous terminology no longer reflected current knowledge. Meta­bolic fatty disease is now understood as a phenotype with heterogenous pathogenesis, manifesting across a wide range of severity and variability [5]. In this article, the current terminology was used, though certain cited references employed former nomenclature. MAFLD can be diagnosed using the gold standard, biopsy. More acces­sible methods are indirect, but sufficient for screening, one of which is BIA.

BODY COMPOSITION ANALYSIS

BC can be assessed by a variety of field and laboratory methods, which consists of anthropometric measurements (i.e., calculation formulas derived from weight, height, body circumferences, or skinfolds), BIA, ultrasound, magnetic resonance imaging (MRI), air-displacement plethys­mography (ADP), dual-energy X-ray absorptiome­try (DEXA), and microcompartment models.
BC parameters, such as percent body fat (PBF), fat mass (FM), or fat-free mass (FFM), provide a lot of information on patients’ health, serving as a screening test for obesity or a tool for measuring the effectiveness of weight loss programs [6].

Reference methods

Up to date, DEXA remains a reference method for BC assessment. It utilizes X-rays, measuring the attenua­tion of its beam’s energy, which passes through particular body tissue (specific attenuation for any tissue). This method converts BC into FM, lean body mass (LBM), and bone mineral content (BMC). It can be utilized to assess whole body or specific body regions. The estimated margin of error for DEXA is around 3%, which makes it the golden standard [7]. DEXA uses an X-ray generating source, X-ray detector, and a computer with specific software for imaging. The exposure to radiation in the procedure is minimal, and equals to a fraction of typical chest X-ray [8].
ADP is a method assessing mass and volume of a human body, and therefore can estimate body density, which can be further calculated into FM and FFM. This method has a high level of agreement with DEXA, but requires expensive equipment [6].
Another reference method is the 4-compartment model, which integrates data from DEXA, ADP, and bioimpedance spectroscopy (BIS) or hydrometry (isotope dilution). In this model, the human body is divided into four categories, such as fat, protein, mineral, and water. The degree of complication and variety of techniques used guarantees both best results and low accessibility in field research [9].

Bioelectrical impedance analysis

BIA is another BC analysis method. The principle of bioimpedance is to estimate BC parameters, including FFM (consisting of BMC), extracellular water (ECW), intracellular water (ICW), visceral protein, FM, and total body water (TBW), by measuring electrical resistance (R) and reactance (Xc) of different body segments. In this method, low level electrical current is used at a particular frequency (or frequencies) flowing through patient’s body. The time in which the current passes a particular segment differs based on the tissue’s electrical properties. The higher the tissue’s hydration, the smaller resistance, as body water with diluted electrolytes has low resistance and conducts electrical current rapidly in comparison with adipose tissue, which has a much higher resistance [8].
BIA units can use a single-frequency current, typically 50 kHz, or multiple frequencies, such as 1, 5, 50, 250, 500, and 1,000 kHz, and consist of different amounts of electrodes, up to eight (2 for each foot and hand). The most accurate results are obtained by multifrequency octopolar devices [6, 10–12].
TBW parameter is calculated from R and body anthro­pometrics, including height and limb length, with several assumptions regarding body shape, limbs, and trunk considered as cylinders, water displacement, and intracellular fluid composition. Raw electrical data are converted into BC components, with manufacturer-dependent regression equations, and involve height, weight, age, sex, assessment of athletic body type, and health status [12]. Certain clinical conditions, such as patient’s ethnicity and age, can influence the outcome of estimation, resulting in overestimation or underestimation of BIA parameters, so the better the regression equation supplied by the manufacturer, the more accurate the result [13].
Apart from calculated BIA parameters, prone to over- or underestimation, some raw BIA-derived data can be interpreted without further equations. Bioelectrical impedance vector analysis (BIVA) is the first example. Through BIVA, patient’s hydration status and body cell mass (BCM) can be evaluated using R (resistance) and Xc (reactance) normalized by height (R/H and Xc/H) in the form of a graph R/Xc [13]. A longer vector in the graph indicates a greater resistance, hence dehydration and vice versa. BIVA, as a predictor of BCM and hydration, is employed as a prognosis in certain clinical conditions, such as chronic kidney disease, heart failure, various cancer types, or anorexia nervosa [13].
Another example of a directly measured BIA variable is phase angle (PhA), which is calculated from resistance and reactance from BIA reading. PhA is considered an index of hydration (ECW : ICW ratio), BCM, and cellular integrity, and is related to FFM. Moreover, it is associated with muscle strength and overall health. A lower PhA is correlated with a cell’s low ability to store energy, indicating breakdown of cellular membranes. A higher PhA indicates a high amount of intact cell membranes and BCM [14]. Furthermore, PhA value is related to sex and age; it increases with the presence of obesity, but also with physical fitness (measured by HGS); however, these correlations need further verification [14].

Body mass index

BMI is an anthropometric index calculated from patients’ weight (in kilograms) divided by their height (in meters) squared. Currently, the diagnosis of obesity in pediatric patients is based on BMI, standardized by growth charts for age and sex. Overweight is diagnosed as BMI over 85th percentile (> 1 SD), and obesity as BMI over 97th percentile (> 2 SD) [1].

MATERIAL AND METHODS

For this systematic review, on February 2, 2024, a search was conducted in the PubMed database for articles on combined bioelectrical impedance or BC, children or adolescents or pediatrics, and obesity or adiposity. Only English-written articles issued in the past 5 years were considered, providing 490 records. One author (A.K.) investigated manually all abstracts and relevant full-text papers, and excluded articles combining both adults and pediatric population, and those not focusing on obesity. The final search resulted in 31 full-text articles, which were included in the review (Figure 1).

RESULTS

The comparison between BIA and other BC analysis methods are presented in Table 1 [6, 7, 9–13, 15–20]. The results of studies on BIA used for various purposes in the obese children population are summarized in Table 2 [2–4, 15, 18, 19, 20–32].

DISCUSSION

The results presented in Table 1 demonstrate that, although BIA is not a flawless method for assessing BC, it seems to be sufficient in daily pediatric practice.
Firstly, BIA is a better tool than BMI for diagnosing obesity. Anthropometric indices have many advantages, such as simplicity, low cost, repeatability, and accessibility, which is why they are still the most commonly used tools in Poland. On the other hand, they may be misleading in certain conditions, such as exceeding muscle tissue in athletes and obesity, providing the same result on BMI percentile charts, though the discrepancy of these two conditions is evident. Moreover, a higher BMI position on percentile charts gives no information regarding the amount of fat tissue or its distribution, which affects obesity health hazard [1]. BMI as a tool for weight loss monitoring is incapable of determining whether it is due to reduction of FM, FFM, or TBW. In summary, various disadvantages of BMI, including low specificity to adiposity or sarcopenia and insufficient correlation to obesity complications, suggest the necessity for a more specific tool.
DEXA, the gold standard for BC assessment, still has advantages over bioimpedance techniques. Further studies confirm a well-known bias, i.e., BIA-derived FM and PBF are overestimated and FFM is underestimated in comparison with DEXA [11]. However, bias is less significant using higher-quality BIA units, with multifrequency octopolar models suggesting to have negligible bias. In gene­ral, most of the cited researchers agree that BIA can be successfully used as an alternative to DEXA [9, 12, 20, 21]. Orsso et al. [6] in their review of BC assessment techniques in obese children were less optimistic regarding BIAs rele­vance in comparison with DEXA. BIA, as a technique, showed a statistically high bias in comparison with the 4-compartment model or DEXA, but the reviewed articles results were inconsistent [6].
Although DEXA has a clear advantage over BIA in terms of measurement accuracy, it has several limitations, including cost of equipment, requirement of quali­fied staff, possible contradictions, low accessibility, long scanning time, and for obese patients, limited acceptable size of a body possible to scan. Another limitation is unavailability to use DEXA as a field technique, as the size of the machine excludes its portability [7, 33].
Other methods, such as MRI or ADP, have rarely been directly compared with BIA. Based on the available lite­rature, it can be concluded that the agreement between these methods is sufficient [10, 20]. The same applies when comparing these methods with DEXA. MRI compared with DEXA shows a good level of agreement. Also, ADP has a good level of agreement with DEXA, but requires expensive equipment [6].
Table 2 summarizes the results of the available literature regarding different applications of BIA in the obese pediatric population, showing evidently that BIA has already been used in various studies.
Positive correlations between BIA-derived parameters, such as PBF, FM, and FFM, and obesity-related laboratory and clinical parameters, have been observed by numerous researchers. These correlations highlight the potential role of BIA-derived measurements in diagnosing and monitoring obesity and its comorbidities.
Another important condition in which BIA is utilized is SO. As mentioned, SO refers to patients with low muscle mass and high fat mass, so they are not necessarily “obese” or “overweight” when classified by BMI Z-score; thus, measuring BC is the most effective way to diagnose this condition. Diagnostic criteria were designed for the adult population only, while for pediatrics, researchers rely on criteria available to the general population, which needs further research in this area.
Dehydration is a significant concern in obese children. Studies showed that it can affect up to half of this population. Dehydration can have a negative impact on metabolic functions and impair physical performance. In addition, pharmacokinetics of drugs in the obese pediatric population remains an underexplored area due to altered BC.
The recent field of research on the obese children po­pulation where BIA has been utilized, involves monitoring weight loss and assessing fitness levels. The cited studies demonstrate that BIA can be successfully used in childhood obesity treatment programs.
The strength of this review is the broad investigation, which eventually resulted in detecting a whole spectrum of obesity-related comorbidities, linked to various BIA parameters. Another strength is comparing various BC measurement methods regarded as the gold standards with BIA, and establishing the role of the bioimpedance method among other BC measuring techniques.
The limitation of our review is its timing. Conducting another review in the future, investigating the relation between BIA parameters in obese pediatric children using pharmaceutical therapy would enrich the results. Another possible limitation is choosing only one database, and including only English-written articles.
Despite the considerable amount of new literature, many aspects of BIA’s usability in overweight and obese children remain to be explored. For example, the subject of puberty and its impact on BIA-derived parameters, appears challenging to study and standardize.

CONCLUSIONS

Obesity, understood as a disease related to excessive fat tissue accumulation, requires a better diagnostic method than the currently widely used BMI. BIA, despite possible inaccuracies compared with reference methods, is presently the most easily accessible and sufficiently accurate method for measuring BC. It is useful in diagnosing and monitoring obesity and its associated comor­bi­dities.

DISCLOSURE

1. Institutional review board statement: Not applicable.
2. Assistance with the article: None.
3. Financial support and sponsorship: None.
4. Conflicts of interest: None.

REFERENCES