Another method to be employed in this study is bioelectrical impedance analysis (BIA). This entails a small, safe, electrical current being passed through the body to measure its electrical resistance (Kyle et al., 2004). This system is based on the fact that fat and lean tissues have differing degrees of electrical conductivity, the current facing more resistance when passing through fat than it does passing through lean body mass and water. This technique is a predictive measure estimating body fat percentage in relation to muscle mass (Kushner and Roxe, 2002). Formerly, it could be performed only in clinical or research laboratories using specialized equipment, but today portable, inexpensive machines are readily available and require minimal training. In spite of the enhanced easiness of this process over the years, however, there are a number of factors which can affect the results, including hydration and body temperature, so it still requires some care when taking the test to ensure that the results are precise (Hu, 2008: Al Sindi, 2000). The advantages of using this equipment are that it is convenient, safe, relatively inexpensive, portable, quick and easy. The limitations are that the machines can be difficult to calibrate, accuracy can be compromised by the ratio of body water to fat being changed during illness, dehydration or weight loss, and with prolonged use the machines may decrease in accuracy.
Kyle et al. (2004) conducted a meta-analysis of the 1600 or more research papers (up to that time) which had reported the use of BIA. They reported that, overall, results showed very strong support for this method with correlations coefficients between r2 = 0.93 and 0.55
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when BIA was compared with DEXA or denistometry. Citing many of the prior studies they concluded that BIA works well in healthy subjects with stable water and electrolyte balance, though it was clear that the data had to be adjusted and validated with a BIA equation that is appropriate to the age and sex of the participants. They note, also, that the use of BIA in adult subjects at extremes of BMI ranges (that is, with a BMI less than 16 or greater than 34) or with abnormal hydration cannot be recommended for routine assessment until additional validation has been proven for BIA algorithm to be precise in such conditions. The authors define a number of procedural conditions, which must be met if this method is to be reliable (Kyle et al., 2004). That is, standardised conditions must be used for all participants: they should be standing, and if possible they should have fasted for about 8-10 hours because food can impede electrical flow and hence skew the readings. Also, if possible, measurements should be taken under the same conditions on two consecutive days.
Another approach to the measurement of body fat was developed by the Tanita Corporation (www.tanita.com). Like other bioelectrical impedance devices its body-fat analyser uses a variety of small electrical currents to determine body composition, but unlike others (which usually only identify only two aspects of body composition – fat and non-fat components) this machine converting the readings into four measurements of fat, muscle, body water, and overall body density. The machine has the advantage of ease-of-use and is well-suited to large scale studies; it is also being marketed for domestic use. Unlike other bioelectrical devices which use a hand-to-foot current pathway, the Tanita device measures the voltage drop as the current passes from one foot to the other from metal foot plates. Jebb et al. (2000) assessed this machine and compared it with other devices and with such methods as skinfold thickness and with BMI measurements. The testing team also developed a predictive algorithm for use when interpreting the information in this device, concluding that
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while it has particular advantages and proved to be more accurate than established height/weight formulas, it was not more accurate or reliable than other impedance equipment. However, a shortcoming which made this device unsuitable for this project was that it had not been calibrated for use with children, and neither has child-specific reference charts been developed.
The report by Jebb et al. (2000) was reinforced by a later meta-analysis by Dehghan and Merchant (2008) who examined many bioelectrical impedance devices and many studies which had made use of such devices. They reviewed the use of these machines for large epidemiological surveys, taking account of such factors as ethnicity, environment, and medical conditions of participants. For example, they point out that factors that may affect machine readings include recent food consumption and physical exercise of participants, medical conditions that affect fluid and electrolyte balance, individual characteristics, and ethnicity and associated variations in limb length. They noted that bioelectrical impedance can accurately measure body fat in populations where the machines have been validated for specific ethnic groups and conditions, but they are unreliable for large studies with diverse populations. Moreover, BIA was used on 1958 Caucasian children aged 5 -18 to measure their fat percentage in order to publish new charts for Child Growth Foundation in Southern England (McCarthy et al., 2006).
While many studies consider excess body fat in the context of overall body composition, some studies have focussed on specific aspects of fat distribution. One recent investigation considered skeletal muscle mass because the muscle-to-fat ratio has the potential as an enhanced measure of metabolic risk (McCarthy et al., 2014). Since skeletal muscle is key to motor development and represents a major metabolic influence that helps glycaemic regulation, it is important when considering the development of diabetes. That is, low
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muscle mass and fitness are linked with metabolic risk, while muscular strength is positively associated to higher insulin sensitivity in children and adolescents. Focusing not on waistline measurements or adipose distribution, but on the muscle-to-fat ratio, McCarthy et al. (2014) surveyed 1985 Caucasian children aged 5–18 years. Using a bioelectrical impedance device the researchers obtained skeletal muscle mass data from the four limbs, the data being employed to derive smoothed centile curves and the muscle-to-fat ratio.
The results of the study were that there was a very wide range of muscle-to-fat ratios for both boys and girls, but more importantly, the writers asserted that this approach to measuring body composition offers a more reliable indicator for predicting diabetes. Given that excess fat and muscle usually have opposite influences on glucose sensitivity they argue that the ratio of muscle-to-fat would be a better predictor of metabolic health than BMI; they cite as an example a child with a muscle-to-fat ratio of just 0.75 would have greater difficulty in sustaining glucose homeostasis than a child with a ratio of 3.0. Furthermore, they suggest that if this approach is confirmed as a good index of metabolic health it could lead to more precise classification of overweight and obese children into ‘high-’ and ‘low-risk’ based on their muscle-to-fat ratio.
The methods to be used in this research are all indirect insofar as they measure physical parameters (weight, height etc) in order to identify the condition of the individual. While they will not be used in this enquiry it is relevant briefly to note some of the other methods which can be used to measure overweight and obesity. There are a number of direct measures of body composition in which fat mass and various components of fat-free mass can be estimated. The direct techniques (chapter 2) can measure specific fat depots but are not usually employed to assess total body fat. These direct measures can identify with great accuracy the location and distribution of fat tissue but because of cost, time, and location
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they cannot be used in large-scale population surveys such as proposed here. Therefore, in this study the three measurements, BMI, waist circumference and bioelectrical impedance, will be tested to examine their acceptability in this age group.