Measurement of Body Fat Mass, Fat-Free Mass, and Muscle Mass Measured using Bioelectric Impedance and Dual-Energy X-Ray Absorptiometry

In this research, we discussed the bone density by measuring the total bone mineral density, fat mass and lean mass in a sample of Mosul people, as soon as to compare the accuracy of the BIA approach to DXA in assessing total body compartments and segmental tissue mass. A cross sectional study conducted at DXA laboratory, Physiology Department, College of Medicine, Nineveh University, Mosul-Iraq. A total of 136 persons, 44 males and 92 women, recruited from reviewing of college Medical College Academic Centre and took part in the current study. A highly statistically significant association between BIA and DXA measures for TFM, TLM, and FFM was also found. BIA underestimates total fat mass by 7.24 kg than DXA. BIA approach overestimated muscle mass by 10.1 kg when compared to the DXA. BIA underestimates fatfree mass by 20.67 kg compared to DXA.


INTRODUCTION
It is commonly recognized that physical form has a distinct impact on happiness. As a result, body composition analysis is frequently used in clinical practice to assess and control dietary intake, such as in obesity and malnutrition research (Tylavsky et al., 2003). For the treatment of excess fat mass, determining the size of body fat is also necessary. Several studies have been conducted, ranging from analyzing an individual's nutritional state to determining the nature of his or her response to a variety of diseases and metabolic disorders (Kalkwarf et al., 2003). Because it is so closely linked to human physiology and disease, the body structure has a wide range of applications in diet, exercise physiology, medicine, geriatrics, and health. The most prevalent methods for assessing body composition are hydro densitometry, air displacement plethysmography, skinfold measurements, bioelectrical impedance analysis (BIA), and dual-energy X-ray absorptiometry (DXA). (Rodrigues Filho et al., 2016), (Sampriti et al., 2018), (Tomlinson et al., 2019). In recent years, BIA has grown in popularity in clinical practice, epidemiological research, and among individuals on a personal level due to its non-invasive, easy-to-use, and handy nature (Rodrigues Filho et al., 2016). BIA measures the water compartment's electrical impedance to the flow of single or multi-frequency currents. Najate Achamrah (Achamrah et al., 2018(. However, because the human body is not a homogenous cylinder, predicting body composition from impedance requires a number of assumptions as well as a sophisticated regression equation for the target population. (Rodrigues Filho et al., 2016(. Clinical medical evaluations revealed that all of the participants were in good health. People who had chronic medical illnesses, were taking medications that affected bone metabolism, or had a family history of osteoporosis, as well as smokers, were excluded from the study.
The aim of the study is to evaluate total fat mass, total muscle mass, and total fat-free mass in a sample of Mosul people, as well as to compare the accuracy of the BIA approach to DXA in assessing total body compartments and segmental tissue mass. The total body compartments prediction equations based on segmental portions of the body and BMD distribution were also researched and discussed.

MATERIAL AND METHODS
From July 1, 2020, to April 30, 2021, the study was done at the Medical Physics Unit / DXA laboratory at the Department of Physiology, College of Medicine, Nineveh University, Mosul, Iraq. A group of healthy adults who volunteered to take part in the study. The ethics committee at Nineveh University's College of Medicine approved the study's ethical approval (Mosul, Iraq). Written informed consent forms were given to all participants in this investigation. A total of 136 persons, 44 males and 92 females, took part in the current study. In a supine position, DXA measures of soft tissue composition were taken. It takes 12 to 15 minutes to scan the entire body. The scanner is a prospective X-ray generator that uses the DXA type Stratos Bone Densitometer scanner to produce two energy levels of (40-70) keV. (Stratos from DMS group, France). Aggarwal, 2016). During scanning, patients were required to wear hospital gowns and remove all metal jewelry (Aggarwal and Ranganathan, 2016). In kilos, the scanner delivers. scanner delivers direct whole and segmental body fat mass. Also calculated the total and segmental fat mass, fat-free mass, and predicted muscle mass. The soft tissue composition was measured using BIA in a standing position with abducted arms and legs, which took about a minute. Bioelectrical impedance is recorded utilizing an eight-contact electrode system Model BC-418 analyzers to estimate wholebody and segmental fat mass (Tanita Corp., Tokyo, Japan). At 50 kHz, measurements are authorized. The apparatus provides a direct estimation of entire fat mass and body composition in the human body (kg).

RESULTS AND DISCUSSIONS
In the study, which included participants from the Mosul city population in Iraq, we evaluated our evaluated our findings utilizing both DXA and BIA techniques for measuring and assessing body composition. A total of 136 men and women, 44 men and 92 women, took part in the current study. (Table 1) shows descriptive information for the subjects based on their anthropometric measures.  The amount of bone mineral density among the participants according to the body mass index (BMI) of the three groups (health, overweight, and obesity). According to gender is depicted graphically in Fig. (1). For all BMI category groups, the amount of BMD in females is smaller than in males, as seen in the graph. Through male and female, it is equal to 0.95 g/cm 2 , 0.75 g/cm 2 for healthy subgroup, 0.95 g/cm 2 , 0.78 g/cm 2 for overweight subgroup, and 0.96 g/cm 2 , 0.83 g/cm 2 for obese subgroup. The obese subgroup had a greater one, according to the findings.
The T-score distribution among the participants according to the body mass index (BMI) of the three cases (health, overweight, and obesity) is shown in (Table 3).
The results showed that the overweight subgroup had the lowest T-score, as shown in the graph above.

Table 3: T-score evaluation for all subgroups
For all study groups, the findings of the T-score for the entire body from the class of osteopenia for both males and females. Fig. (2) shows scattered figures utilizing DXA scan that revealed a good correlation between the T-score of the total body and the Z-score distribution among all individuals, with R 2 =0.66.

Soft Tissues Calculations
The correlation between total lean mass and segmental lean compartments of the body are shown in Fig. (

Fig. 5: Correlation between total lean mass and segmental lean mass of the legs
The following formula was used to calculate total muscle mass (BIA) in our study (Majeed, 2019). Total muscle mass (BIA) = predicted muscle mass of right arm+ predicted muscle mass of left arm+ predicted muscle mass of right leg+ predicted muscle mass of left leg+ predicted muscle mass of the trunk as shown in the Figs. (3-5). A scattered plot and fitted regression lines between both total fat mass and segmental fat mass of the arms are depicted in Fig. (6) p<0.0001.   The main differences in total body compartment mass estimates between BIA and DXA are shown in Table 4. For both total fat mass and total fat-free mass, BIA estimates were considerably lower than DXA estimates (p-value<0.0001). The following were the average differences: total fat mass difference (7.24) kg; total fat free mass difference was (20.67). The estimations of BIA were significantly higher than those by DXA for total lean mass (p-value <0.0001). Since the difference in total lean mass (-10.1) kg. For total lean mass, DXA estimates were considerably lower than BIA estimates (p-value<0.0001). (Table 4) shows the correlation and regression analysis used to evaluate the performance of both the BIA and DXA measurements. Figs. (9) through 11 show the scattered plot and fitted regression lines to estimate total body compartments using both BIA and DXA methodologies (13). Body fat mass (regression coefficient, R 2 =0.91) was found to be the best fit line for both tests. While the fitting line of both tests was found in the estimation of total muscle mass and total fat free mass (regression coefficient, R2 were 0.87 and 0.48). Thus, 91% of BIA measurement of total fat mass is explained by DXA. In other words, 87% of BIA measurements of total muscle mass are explained by DXA. However, slightly less than half of variation in total fat free mass is explained by DXA estimation.
The mathematical models below can be used to correct DXA estimates of various body compartments to obtain corresponding BIA estimates (p-value<0.0001): Total fat mass in  …….. (1) Total Fat-free mass in BIA=18.31+0.45 (Body Fat-Free Mass in DXA) …… (2) Total muscle mass in BIA=0.26+0.55 (Body muscle Mass in DXA) ………… (3) The above mathematical models were calculated using this formula: Dependent variable = constant (B 0 ) + (B 1 ) *(independent variable "segment part") However, it is equal to; where Y represents the value of the variable being predicted, B 0 is the y-interception, B 1 is the slope of the straight line, and X is the known value of the independent variable (segment portion). This study provides new insight into the bone mineral content, bone mineral density, T-score, and Z-score of Mosul population of men and women. Quantitative ultrasonography, x-ray radiography, and invasive Quantitative computed tomography QCT-scan were utilized in previous investigations (Marra et al., 2019), (Poehlman et al., 2002) (Peltz et al., 2010). In this study, we used both modern Dual-energy X-ray Absorptiometry (DXA) technique and BIA to analyze segmental and total body composition to show the differences in the body tissue measurements according to the usage the two machines for both genders. This is the second scientific study on the Iraqi level that deals with the accuracy of body composition measures and their comparison through the use of two separate instruments (DXA and BIA). The DXA uses dual-energy X-ray absorption technology, whereas the BIA employs electrical impedance technology. However, using a DXA technology that uses a tiny dosage of X-ray to obtain extremely accurate measures of bone health of segmental and total body composition is beneficial (Silva et al., 2014).
Leg-to-leg BIA, according to Miyatani et al., can be utilized to make a routine assessment with DM type 2 and measure body composition analysis (Miyatani et al., 2012). Other studies found that using a BIA device to assess body composition in obese people and people with cardiometabolic illnesses was effective, practical, and a good approach (Ugras, 2020). The current study was the highly selective criteria used in recruiting the current study sample (normal overweight BMI class; (28.81 ± 5.77) kg/m 2 with ethnic of Middle eastern sample. Obese people had the highest bone mineral density, followed by overweight people, and healthy people had the lowest. This is totally in line with the information supplied by (Siddapur et al., 2015). The final calculation yield of the T-score for the total body from the osteopenia class revealed that the overweight class had the lowest T-score for both genders, which is consistent with (Miyatani et al., 2012) utilizing DXA technology. Previous research has attempted to compare the accuracy of skinfold thickness to DXA as gold standards in assessing total body fat in a variety of groups (Aggarwal and Ranganathan, 2016). Meanwhile, several researchers employed the DXA and BIA procedures to determine the amount of body fat (Achamrah et al., 2018). The findings revealed a discrepancy in their research findings. Some researchers concluded that the BIA overestimates fat and fat-free mass composition, whereas others concluded that the BIA underestimates fat mass composition (Bolanowski and Nilsson, 2001), (Majeed et al., 2019). A highly statistically significant correlation between BIA and DXA measures for TFM, TLM, and FFM (p-value 0.0001) was also founding. Total fat mass had the strongest correlation (r=0.95, p-value 0.0001). In a sample of 100 Swedish patients, Bolanowski et al show high agreement in body fat estimates between BIA and DXA (Bolanowski, 2001). All of the linear regressions for BIA prediction in TFM, TLM, and FFM using DXA were statistically significant, with p< 0.0001. Leahy S et al concluded that BIA overestimates fat composition (Leahy, 2012), other researchers concluded that BIA underestimates fat composition (Neovius, 2006). According to the findings of this study, BIA underestimates total fat mass by 7.24 kg. This figure is close to that reported by Bolanowski et al.,(6.5 kg) (Bolanowski, 2001). It was, however, far higher than the result reported by Volgyi et al., (Volgyi et al., 2008), which was 4.3 kg lower than DXA.
Our findings demonstrated that the BIA approach overestimated muscle mass by 10.1 kg when compared to the DXA approach. This is because the total body water contained in lean body tissue causes the quantity of lean mass measured by BIA to be greater than that identified by DXA. It was, however, 5.0kg more than the figure reported by Bolanowski et al., (Bolanowski, 2001). On the other hand, our analyses reveal that BIA underestimates fat-free mass by 20.67 kg compared to DXA. This high level of agreement result was mentioned by (Berstad et al., 2012). Since they used their study in University of Limerick Research, Leahy et al discovered that BIA was overstated by 2.0 kg in the female group (Leahy et al., 2012). Nana et colleagues also find that among a group of obese adolescents, the difference is somewhat more than 2 kg (Nana et al., 2012).

CONCLUSIONS
In this study, we used two techniques (BIA and DXA). DXA machine used to detect Bone content, bone mineral density, T-score, Z score, and the body compositions by using two energies. BIA tool used to measure total and segmental body compositions like fat mass, predicted muscle mass, and fat-free mass using the bioelectric impedance of the body. Every tool can detect body composition differently. The study aimed to evaluate the total fat mass, total muscle mass, and total fat-free mass in a sample of Mosul people using both techniques. A correlation was also found between total and segmental bone mineral density (BMD). Comparing the accuracy of the BIA approach to DXA in assessing total body compartments and segmental tissue mass. The measurements of the total body compartments based on segmental portions of the body distribution were also and discussed. The correlation between the total and segmental bone mineral density (BMD) was calculated. The relation of the total body compartments based on the segmental parts of the body and the distribution of BMD were also studied. Furthermore, the assessment of the linear regression between total fat mass, muscle mass, and fat-free mass between (BIA and DXA) technique were calculated. New mathematical models were founding and used to correct DXA estimates of various body compartments to obtain corresponding BIA estimates.
Ugras, S. (2020). Evaluating of altered hydration status on effectiveness of body composition