Obesity Research & Clinical Practice (2014) 8, e291—e297
SHORT REPORT
Bioimpedance analysis of body composition in an international twin cohort Adam D. Tarnoki a,∗, David L. Tarnoki a,1, Emanuela Medda b,1, Rodolfo Cotichini b, Maria A. Stazi b, Corrado Fagnani b, Lorenza Nisticò b, Pierleone Lucatelli c, Emanuele Boatta c, Chiara Zini c, Fabrizio Fanelli c, Claudio Baracchini d, Giorgio Meneghetti d, Giuseppe Schillaci e, Janos Osztovits f, Gyorgy Jermendy f, Róbert G. Kiss g,h, István Préda g,h, Kinga Karlinger a, Agnes Lannert i, Julia Metneki j, Andrea A. Molnar g,h, Zsolt Garami k, Viktor Berczi a, Ildiko Halasz l, Gyorgy Baffy l a
Department of Radiology and Oncotherapy, Semmelweis University, 78/a Ulloi Street, Budapest 1082, Hungary b Genetic Epidemiology Unit, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy c Vascular and Interventional Radiology Unit, Department of Radiological Sciences, Sapienza University of Rome, viale Regina Elena 324,00162 Rome d Department of Neurosciences, University of Padua School of Medicine, via Giustiniani 5, 35128 Padova, Italy e Università degli Studi di Perugia, Unità di Medicina Interna, Ospedale ‘‘S. Maria’’, viale Tristano di Joannuccio 1, 05100 Terni, Italy f Bajcsy Zsilinszky Hospital, III Department of Internal Medicine, 89-91 Maglodi Street, Budapest 1106, Hungary g Research Group for Inflammation Biology and Immunogenomics of Hungarian Academy of Sciences and Semmelweis University, 44 Róbert Károly krt, Budapest 1134, Hungary h Department of Cardiology, Military Hospital — State Health Centre, 44 Róbert Károly krt, Budapest 1134, Hungary i Semmelweis University, School of Pharmacy, 26 Ulloi Street, Budapest 1085, Hungary j National Institute for Health Development, 2 Nagyvárad tér, Budapest, 1096, Hungary k The Methodist Hospital, DeBakey Heart and Vascular Center, 6565 Fannin Street, Houston, TX 77030, USA l Department of Medicine, VA Boston Healthcare System, Harvard Medical School, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130, USA Received 17 July 2012 ; received in revised form 25 August 2012; accepted 3 September 2012 ∗ Corresponding author at: Department of Radiology and Oncotherapy, Semmelweis University, 78/A Ulloi u., Budapest H-1082, Hungary. Tel.: +36 30 640 1183; fax: +36 1 2780367. E-mail address: [email protected] (A.D. Tarnoki). 1 These authors contributed equally to this work.
1871-403X/$ — see front matter © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.orcp.2012.09.001
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KEYWORDS Genetics; Body composition parameters; Bioelectrical impedance analysis; Twin study
A.D. Tarnoki et al. Summary Objective: Multiple twin studies have demonstrated the heritability of anthropometric and metabolic traits. However, assessment of body composition parameters by bioimpedance analysis (BIA) has not been routinely performed in this setting. Design: A cross-sectional study. Setting: Study subjects were recruited and assessed at twin festivals or at major university hospitals in Italy, Hungary, and the United States to estimate the influence of genetic and environmental components on body composition parameters in a large, wide age range, international twin cohort by using bioelectrical impedance analysis. Subjects: 380 adult twin pairs (230 monozygotic and 150 dizygotic pairs; male:female ratio, 68:32; age years 49.1 ± 15.4; mean ± standard deviation; age range 18—82) were included in the analysis. Results: Heritability was calculated for weight (82%; 95% confidence interval [CI]: 78—85), waist and hip circumferences (74%; 95%CI: 68—79), body fat percentage (74%; 95%CI: 69—79), fat-free mass (74%; 95%CI: 69—79) and body mass index (79%; 95%CI: 74—83). The completely environmental model showed no impact of shared environmental effects on the variance, while unshared environmental effects were estimated as between 18% and 26%. Conclusions: BIA findings provide additional evidence to the heritability of anthropometric attributes related to obesity and indicate the practical value of this simple method in supporting efforts to prevent obesity-related adverse health events. © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Obesity is a complex condition of excessive fat accumulation linked to major adverse health effects such as type 2 diabetes, cardiovascular disease, and certain forms of cancer [1,2]. Underlying mechanisms of the rising obesity epidemic are still unclear. Impact of the environment on the body’s energy balance by modifying caloric intake and physical activity is undeniable, but there is considerable variation in individual responsiveness to obesogenic factors [3—5]. Large epidemiological studies based on family, adoption, and twin relations underscore the importance of genetic factors and gene—environment interactions in the development of obesity [6,7]. Body mass index (BMI) is a simple anthropometric measure of obesity with heritability estimates between 50% and 90% accounting for its variance [8,9]. However, the relationship between BMI and body fat varies by age, gender, ethnicity, and level of fitness [10,11]. Moreover, the definition of obesity based on BMI alone varies by geographical areas [12]. Variables of body composition like total body fat mass, lean mass, and measures of fat distribution may indicate obesity more reliably than BMI alone, although heritability of these parameters remains less obvious [13,14]. There are several imaging methods to estimate body composition and fat distribution including CT and MRI. Dual energy X-ray absorptiometry (DXA) is a less expensive technique associated with
low-dose radiation that allows to study the role of genetic components in total and regional body fat measures [14,15]. As an alternative to anthropometric assessment for obesity by imaging that requires an office visit, bioelectrical impedance analysis (BIA) by using a portable device has recently proved to be an informative, low-cost approach to assess body composition in a variety of health care settings [13,16,17]. Heritability studies using twin design are based upon the assumption that twins are representative of the general population for the outcomes being studied. Several groups have investigated the gene—environment interplay in obesity by studying twin cohorts and provided evidence that genetic factors play a considerable role in body weight regulation [18—21]. Interestingly, little has been reported on this contribution as determined by BIA except for a small study consisting of 30 twins in Germany, in which genetic factors amounted to a variance of 65—82% [22]. In this study, we assessed components of body composition by using BIA to determine the heritability of key anthropometric attributes in a large twin cohort from different geographical areas. Our goal was to demonstrate the ease with which this simple method may confirm the role of genetic factors in body composition attributes and prove practical in identifying individuals who would primarily benefit from lifestyle changes to prevent
Bioimpedance analysis of body composition in an international twin cohort obesity-related adverse health events. This work has been part of an international collaboration aimed at assessing the influence of genetic as well as shared and unshared environmental components on certain components of body composition in a large, wide age range, international twin cohort. We tested 380 twin pairs (157 Hungarian, 174 Italian and 49 American; 230 monozygotic and 150 dizygotic pairs; age years 49.1 ± 15.4; mean ± SD) above age of 18 in this cross-sectional twin study (Table 1). In Italy, zygosity was determined by using a validated self-report questionnaire [23], which included questions on the similarities of twins during their childhood. Exclusion criteria were race other than white (to exclude the influence of ethnicity), pregnancy, medical conditions possibly interfering with compliance during test procedures, morbid obesity, and anorexia. In the absence of genotyping data, we used a multiple self-reported question approach to assess zygosity in Hungary and the USA [24]. The study was conducted according to the guidelines in the Declaration of Helsinki and all procedures involving human subjects were approved by local university IRB committees. Written informed consent was obtained from all subjects. Body composition measurements from Hungarian subjects were taken during local twin festivals (at locations in Agfalva and Szigethalom) and in 2 large hospitals in Budapest. Italian twins were tested in hospitals in Rome, Padua and Perugia. Some data of these Italian twins have already been reported through the Italian Twin Registry [25]. American twins were tested at the Twins Day Festival in Twinsburg, OH. Body composition measurements were facilitated by the two first authors (ADT and DLT) at all research sites in order to reduce interobserver variations. To assess past medical history and personal habits (diet, smoking, alcohol consumption, and history of physical activity), all study subjects were requested to complete an on-site questionnaire. Body composition was determined by BIA using a clinically validated, portable body consistency monitor (OMRON BF500, Omron Healthcare Ltd., Kyoto, Japan) [26]. Body fat percentage was calculated as [body fat mass (kg)/body weight (kg)] × 100. Fat-free mass was interpreted as [100% − body fat percentage (%)]. Waist and hip circumferences were measured by standard criteria. Intraclass correlation with 95% confidence intervals was calculated for monozygotic and dizygotic twin pairs. Structural equation modeling was used to estimate heritability. Model fitting was done with the statistical software Mx [27]. STATA software was used to perform descriptive analyses and to determine statistical significance.
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Univariate quantitative genetic model was performed to decompose phenotypic variance of the considered parameters into additive (A), nonadditive (D), common environmental (C) and unique environmental (E) effects as described before [28]. Nested models were compared using likelihoodratio 2 tests and Akaike information criteria model selection was performed according to the principle of parsimony. All the analyses were adjusted by age and gender. Due to the low number of American dizygotic twins, country-specific heritability estimates were not calculated. Table 1 presents the clinical characteristics of study subjects by countries. Females comprised 68% of the combined study population. Italian twin pairs were older than those from other countries (p < 0.01). No significant country-specific difference was observed in weight and waist circumference. All anthropometric parameters showed normal distribution. Hip circumference was significantly higher in the USA compared to Hungary and Italy (p < 0.01 in both cases). Body fat percentage was significantly higher and the fat-free mass was significantly lower in the USA compared to Hungary (p < 0.01 in both cases). Significant gender-specific differences were found in all investigated parameters of body composition except hip circumference and physical activity. Intraclass correlation coefficients of all investigated body composition parameters were higher in monozygotic than in dizygotic pairs, suggesting that genetic factors may be important contributors to these traits. Results combined from all twin data on genetic and environmental variance estimates with 95% confidence intervals are presented in Table 2. A large proportion of the total variance for all parameters is attributable to genetic factors between 74% and 82%. No role of non-additive genetic variance was found. Furthermore, a lower Akaike information criteria value was shown in the AE model than in the ACE model, proving that the AE model is the best model. Therefore, common environmental effects had no impact on total variance of all the parameters considered; unique environmental effects instead were estimated as between 19% and 26% with regard to each parameter. Our study indicates that genetic effects primarily account for high concordance of the anthropometric parameters as measured by BIA consistent with increased risk for obesity. Specifically, our heritability estimates range between 74% and 81% for the investigated body composition variables. Importantly, we found that only environmental influences unique to the individual and not those shared by family members affect the phenotype of body composition, contributing 19—26% of the
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Table 1
Baseline characteristics of study subjects by countries of origin. Hungary n
Zygosity 204 MZ 110 DZ Gender 90 Male Female 224 Age, year ± SD 314 Weight, kg ± SD 312 312 Height, m ± SD 308 Waist circumference, cm ± SD Hip 308 circumference, cm ± SD Body fat, % ± SD 309 309 Fat-free mass, % ± SD BMI, kg/m2 ± SD 312 Physical activity (sport) Yes 208 No 86
Italy
USA
Value
SD
64.97% — 35.03% 28.66 71.34 43.6 71.4 166.8 88.2
98.8
— 15.9* 15.4 9.8a 14.1
n
Value
93.88% — 6.12%
92 6 16 82 98 98 98 98
11.8c,d 98
SD
16.33 83.67 46.9 73.7 163.9 89.7
105.2
—
n 164 184
Total
Sex Value 47.13% 52.87%
SD
Males
—
134 107
—
—
16.8e 17.1 9.4a 15.2
135 213 348 347 348 347
38.79 61.21 54.6 70.8 165.9 87.0
11.6c,e
347
95.8
10.7b 10.7b
346 346
32.6 67.4
9.1 9.1
12.4*,e 12.7 9.8 11.8
55.60% 44.40%
326 193
62.81% 37.19%
460 300
—
31.71 68.29 49.1 71.5 166.0 87.8
15.4 14.5 9.8 13.2
Value 60.53% 39.47%
SD —
49.0 81.6 174.0 94.1
15.7 11.5f 8.1f 11.3f
519 517 517 513
49.1 66.8 160.7 84.9
15.3 13.3f 7.8f 13.1f
99.0
8.5
513
97.9
12.5
753
98.2
11.4
238 238
24.4 75.6
6.4f 6.4f
515 515
36.3 63.7
8.4f 8.4f
753 753
32.5 67.5
9.6 9.6
3.8*** 519
26.0
5.3*** 757
25.9
4.8
61.1% 38.9%
—
10.1c,e 240
—
31.7 68.3
9.5b 9.5b
98 98
34.7 65.3
25.7
5.1**
98
27.5
6.2**,e
347
25.7
3.8e
241
26.7
70.7% 29.3%
—
63 28
69.2% 30.8%
—
146 152
49.0% 51.0%
—
152 73
67.6%**** 32.4%
254 188
57.5%**** 42.5%
417 266
—
A.D. Tarnoki et al.
MZ, monozygotic; DZ, dizygotic; SD, standard deviation. a Hungarian vs American, p < 0.05. b Hungarian vs American, p < 0.01. c Hungarian vs American, p < 0.001. d Hungarian vs Italian, p < 0.005. e American vs Italian p < 0.001. f Males vs females p < 0.001. * Hungarian vs Italian p < 0.001. ** Hungarian vs American, p < 0.005. *** Males vs Females p < 0.01. **** Males vs Females p < 0.05.
n
241 519 760 757 758 753
241 240 240 240
—
Females
n
Intraclass correlation and ACE/ADE model of body composition variables. Zygosity
BMI 229 MZ 150 DZ Waist circumference 227 MZ 149 DZ Hip circumference 227 MZ DZ 149 Body fat 228 MZ 148 DZ Fat-free mass 228 MZ 148 DZ
Intraclass correlation
Best model analysis
Value
95%CI
A
95%CI of A
E
95%CI of E
2*
df
P
AIC
0.81 0.44
0.77—0.85 0.29—0.55
0.81
0.77—0.85
0.19
0.15—0.23
0.19
1
0.66
−1.81
0.74 0.41
0.68—0.79 0.27—0.53
0.74
0.68—0.79
0.26
0.21—0.31
0.37
1
0.54
−1.63
0.74 0.49
0.68—0.79 0.35—0.59
0.74
0.69—0.79
0.26
0.21—0.31
3.09
1
0.08
1.09
0.76 0.39
0.71—0.81 0.24—0.52
0.76
0.71—0.81
0.24
0.19—0.29
0.02
1
0.89
−1.98
0.76 0.39
0.71—0.81 0.24—0.52
0.76
0.71—0.81
0.24
0.19—0.29
0.02
1
0.89
−1.98
Bioimpedance analysis of body composition in an international twin cohort
Table 2
MZ, monozygotic; DZ, dizygotic; A, additive genetic effects; E, unique environmental effects; 2 , chi-square (2 = [−2 log-likelihood submodel] − [−2 log-likelihood full model]); df, df submodel − df full model; P, probability; AIC, Akaike Information Criteria, 2 − 2df.
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e296 variance, while shared environmental effects have no effect on the variance in line with earlier reports [13,21,29,30]. For example, BMI variations in the large GenomEUtwin study were mostly influenced by additive genetic and unique (unshared) environmental factors, with the genetic contribution of BMI varying between 45% and 85% according to different countries [31]. A major limitation of our study is that BIA cannot measure fat distribution and provides no heritability estimate on visceral obesity, an important predictor of cardiovascular morbidity and mortality. Several studies have reported strong genetic association with body fat distribution and the relative proportion of subcutaneous and visceral fat depots [14,32,33]. Another limitation of the study is that our modeling of heritability assumes equal common environmental influences on both monozygotic and dizygotic pairs. As true for all twin studies, if this assumption does not hold, then our estimate of heritability may be biased upwards. While the accuracy of BIA has been called into question [34], clinical data from a recent large study support the value of BIA in assessing total body and segmental body composition in the general middle-aged population, particularly for estimating body lean mass [35]. Several authors observed that BIA systems provide good agreement with reference methods at a population level although BIA may be less accurate at the individual level [17,36]. The strength of the study is that all tests were performed by the same protocol, same personnel, and same device at all international locations, involving a relatively large number of twins with a wide age range from different geographical areas. Our findings support routine use of a widely available, portable device to perform BIA as a convenient, noninvasive way to routine assessment of key anthropometric parameters. At the very least, individuals with a positive family history of obesity may need to be monitored during their young adulthood to detect body composition attributes that indicate the development of obesity and the need for life-style changes to reduce the impact of environmental challenges and prevent obesityassociated co-morbidities.
Support This work was supported by Medexpert Ltd, the Twins Days Festival Committee, the Balassi Institute Hungarian Scholarship Board Office, and the Ministry for Foreign Affairs of the Republic of Italy.
A.D. Tarnoki et al. Authors will confer the manuscript copyright to Obesity Research & Clinical Practice in case of acceptance.
Conflicts of interest The authors declare no conflicts of interest.
Acknowledgments Medexpert Ltd. has provided financial support for the development and maintenance of this study. Italian part of the research was supported by the Balassi Institute — Hungarian Scholarship Board Office. We would like to acknowledge the support of Twins Days Festival committee and Istvan Luczek, MD for the American part of the study. Studies were approved by local ethical committees (IRB committee names and project approval numbers: Semmelweis University Regional and Institutional Committee of Science and Research Ethics, 29/2009; Twins Days Festival Ethical Board, 1/2009; Ethical Committee of Istituto Superiore di Sanità).
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SHORT REPORT
Bioimpedance analysis of body composition in an international twin cohort Adam D. Tarnoki a,∗, David L. Tarnoki a,1, Emanuela Medda b,1, Rodolfo Cotichini b, Maria A. Stazi b, Corrado Fagnani b, Lorenza Nisticò b, Pierleone Lucatelli c, Emanuele Boatta c, Chiara Zini c, Fabrizio Fanelli c, Claudio Baracchini d, Giorgio Meneghetti d, Giuseppe Schillaci e, Janos Osztovits f, Gyorgy Jermendy f, Róbert G. Kiss g,h, István Préda g,h, Kinga Karlinger a, Agnes Lannert i, Julia Metneki j, Andrea A. Molnar g,h, Zsolt Garami k, Viktor Berczi a, Ildiko Halasz l, Gyorgy Baffy l a
Department of Radiology and Oncotherapy, Semmelweis University, 78/a Ulloi Street, Budapest 1082, Hungary b Genetic Epidemiology Unit, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy c Vascular and Interventional Radiology Unit, Department of Radiological Sciences, Sapienza University of Rome, viale Regina Elena 324,00162 Rome d Department of Neurosciences, University of Padua School of Medicine, via Giustiniani 5, 35128 Padova, Italy e Università degli Studi di Perugia, Unità di Medicina Interna, Ospedale ‘‘S. Maria’’, viale Tristano di Joannuccio 1, 05100 Terni, Italy f Bajcsy Zsilinszky Hospital, III Department of Internal Medicine, 89-91 Maglodi Street, Budapest 1106, Hungary g Research Group for Inflammation Biology and Immunogenomics of Hungarian Academy of Sciences and Semmelweis University, 44 Róbert Károly krt, Budapest 1134, Hungary h Department of Cardiology, Military Hospital — State Health Centre, 44 Róbert Károly krt, Budapest 1134, Hungary i Semmelweis University, School of Pharmacy, 26 Ulloi Street, Budapest 1085, Hungary j National Institute for Health Development, 2 Nagyvárad tér, Budapest, 1096, Hungary k The Methodist Hospital, DeBakey Heart and Vascular Center, 6565 Fannin Street, Houston, TX 77030, USA l Department of Medicine, VA Boston Healthcare System, Harvard Medical School, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130, USA Received 17 July 2012 ; received in revised form 25 August 2012; accepted 3 September 2012 ∗ Corresponding author at: Department of Radiology and Oncotherapy, Semmelweis University, 78/A Ulloi u., Budapest H-1082, Hungary. Tel.: +36 30 640 1183; fax: +36 1 2780367. E-mail address: [email protected] (A.D. Tarnoki). 1 These authors contributed equally to this work.
1871-403X/$ — see front matter © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.orcp.2012.09.001
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KEYWORDS Genetics; Body composition parameters; Bioelectrical impedance analysis; Twin study
A.D. Tarnoki et al. Summary Objective: Multiple twin studies have demonstrated the heritability of anthropometric and metabolic traits. However, assessment of body composition parameters by bioimpedance analysis (BIA) has not been routinely performed in this setting. Design: A cross-sectional study. Setting: Study subjects were recruited and assessed at twin festivals or at major university hospitals in Italy, Hungary, and the United States to estimate the influence of genetic and environmental components on body composition parameters in a large, wide age range, international twin cohort by using bioelectrical impedance analysis. Subjects: 380 adult twin pairs (230 monozygotic and 150 dizygotic pairs; male:female ratio, 68:32; age years 49.1 ± 15.4; mean ± standard deviation; age range 18—82) were included in the analysis. Results: Heritability was calculated for weight (82%; 95% confidence interval [CI]: 78—85), waist and hip circumferences (74%; 95%CI: 68—79), body fat percentage (74%; 95%CI: 69—79), fat-free mass (74%; 95%CI: 69—79) and body mass index (79%; 95%CI: 74—83). The completely environmental model showed no impact of shared environmental effects on the variance, while unshared environmental effects were estimated as between 18% and 26%. Conclusions: BIA findings provide additional evidence to the heritability of anthropometric attributes related to obesity and indicate the practical value of this simple method in supporting efforts to prevent obesity-related adverse health events. © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Obesity is a complex condition of excessive fat accumulation linked to major adverse health effects such as type 2 diabetes, cardiovascular disease, and certain forms of cancer [1,2]. Underlying mechanisms of the rising obesity epidemic are still unclear. Impact of the environment on the body’s energy balance by modifying caloric intake and physical activity is undeniable, but there is considerable variation in individual responsiveness to obesogenic factors [3—5]. Large epidemiological studies based on family, adoption, and twin relations underscore the importance of genetic factors and gene—environment interactions in the development of obesity [6,7]. Body mass index (BMI) is a simple anthropometric measure of obesity with heritability estimates between 50% and 90% accounting for its variance [8,9]. However, the relationship between BMI and body fat varies by age, gender, ethnicity, and level of fitness [10,11]. Moreover, the definition of obesity based on BMI alone varies by geographical areas [12]. Variables of body composition like total body fat mass, lean mass, and measures of fat distribution may indicate obesity more reliably than BMI alone, although heritability of these parameters remains less obvious [13,14]. There are several imaging methods to estimate body composition and fat distribution including CT and MRI. Dual energy X-ray absorptiometry (DXA) is a less expensive technique associated with
low-dose radiation that allows to study the role of genetic components in total and regional body fat measures [14,15]. As an alternative to anthropometric assessment for obesity by imaging that requires an office visit, bioelectrical impedance analysis (BIA) by using a portable device has recently proved to be an informative, low-cost approach to assess body composition in a variety of health care settings [13,16,17]. Heritability studies using twin design are based upon the assumption that twins are representative of the general population for the outcomes being studied. Several groups have investigated the gene—environment interplay in obesity by studying twin cohorts and provided evidence that genetic factors play a considerable role in body weight regulation [18—21]. Interestingly, little has been reported on this contribution as determined by BIA except for a small study consisting of 30 twins in Germany, in which genetic factors amounted to a variance of 65—82% [22]. In this study, we assessed components of body composition by using BIA to determine the heritability of key anthropometric attributes in a large twin cohort from different geographical areas. Our goal was to demonstrate the ease with which this simple method may confirm the role of genetic factors in body composition attributes and prove practical in identifying individuals who would primarily benefit from lifestyle changes to prevent
Bioimpedance analysis of body composition in an international twin cohort obesity-related adverse health events. This work has been part of an international collaboration aimed at assessing the influence of genetic as well as shared and unshared environmental components on certain components of body composition in a large, wide age range, international twin cohort. We tested 380 twin pairs (157 Hungarian, 174 Italian and 49 American; 230 monozygotic and 150 dizygotic pairs; age years 49.1 ± 15.4; mean ± SD) above age of 18 in this cross-sectional twin study (Table 1). In Italy, zygosity was determined by using a validated self-report questionnaire [23], which included questions on the similarities of twins during their childhood. Exclusion criteria were race other than white (to exclude the influence of ethnicity), pregnancy, medical conditions possibly interfering with compliance during test procedures, morbid obesity, and anorexia. In the absence of genotyping data, we used a multiple self-reported question approach to assess zygosity in Hungary and the USA [24]. The study was conducted according to the guidelines in the Declaration of Helsinki and all procedures involving human subjects were approved by local university IRB committees. Written informed consent was obtained from all subjects. Body composition measurements from Hungarian subjects were taken during local twin festivals (at locations in Agfalva and Szigethalom) and in 2 large hospitals in Budapest. Italian twins were tested in hospitals in Rome, Padua and Perugia. Some data of these Italian twins have already been reported through the Italian Twin Registry [25]. American twins were tested at the Twins Day Festival in Twinsburg, OH. Body composition measurements were facilitated by the two first authors (ADT and DLT) at all research sites in order to reduce interobserver variations. To assess past medical history and personal habits (diet, smoking, alcohol consumption, and history of physical activity), all study subjects were requested to complete an on-site questionnaire. Body composition was determined by BIA using a clinically validated, portable body consistency monitor (OMRON BF500, Omron Healthcare Ltd., Kyoto, Japan) [26]. Body fat percentage was calculated as [body fat mass (kg)/body weight (kg)] × 100. Fat-free mass was interpreted as [100% − body fat percentage (%)]. Waist and hip circumferences were measured by standard criteria. Intraclass correlation with 95% confidence intervals was calculated for monozygotic and dizygotic twin pairs. Structural equation modeling was used to estimate heritability. Model fitting was done with the statistical software Mx [27]. STATA software was used to perform descriptive analyses and to determine statistical significance.
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Univariate quantitative genetic model was performed to decompose phenotypic variance of the considered parameters into additive (A), nonadditive (D), common environmental (C) and unique environmental (E) effects as described before [28]. Nested models were compared using likelihoodratio 2 tests and Akaike information criteria model selection was performed according to the principle of parsimony. All the analyses were adjusted by age and gender. Due to the low number of American dizygotic twins, country-specific heritability estimates were not calculated. Table 1 presents the clinical characteristics of study subjects by countries. Females comprised 68% of the combined study population. Italian twin pairs were older than those from other countries (p < 0.01). No significant country-specific difference was observed in weight and waist circumference. All anthropometric parameters showed normal distribution. Hip circumference was significantly higher in the USA compared to Hungary and Italy (p < 0.01 in both cases). Body fat percentage was significantly higher and the fat-free mass was significantly lower in the USA compared to Hungary (p < 0.01 in both cases). Significant gender-specific differences were found in all investigated parameters of body composition except hip circumference and physical activity. Intraclass correlation coefficients of all investigated body composition parameters were higher in monozygotic than in dizygotic pairs, suggesting that genetic factors may be important contributors to these traits. Results combined from all twin data on genetic and environmental variance estimates with 95% confidence intervals are presented in Table 2. A large proportion of the total variance for all parameters is attributable to genetic factors between 74% and 82%. No role of non-additive genetic variance was found. Furthermore, a lower Akaike information criteria value was shown in the AE model than in the ACE model, proving that the AE model is the best model. Therefore, common environmental effects had no impact on total variance of all the parameters considered; unique environmental effects instead were estimated as between 19% and 26% with regard to each parameter. Our study indicates that genetic effects primarily account for high concordance of the anthropometric parameters as measured by BIA consistent with increased risk for obesity. Specifically, our heritability estimates range between 74% and 81% for the investigated body composition variables. Importantly, we found that only environmental influences unique to the individual and not those shared by family members affect the phenotype of body composition, contributing 19—26% of the
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Table 1
Baseline characteristics of study subjects by countries of origin. Hungary n
Zygosity 204 MZ 110 DZ Gender 90 Male Female 224 Age, year ± SD 314 Weight, kg ± SD 312 312 Height, m ± SD 308 Waist circumference, cm ± SD Hip 308 circumference, cm ± SD Body fat, % ± SD 309 309 Fat-free mass, % ± SD BMI, kg/m2 ± SD 312 Physical activity (sport) Yes 208 No 86
Italy
USA
Value
SD
64.97% — 35.03% 28.66 71.34 43.6 71.4 166.8 88.2
98.8
— 15.9* 15.4 9.8a 14.1
n
Value
93.88% — 6.12%
92 6 16 82 98 98 98 98
11.8c,d 98
SD
16.33 83.67 46.9 73.7 163.9 89.7
105.2
—
n 164 184
Total
Sex Value 47.13% 52.87%
SD
Males
—
134 107
—
—
16.8e 17.1 9.4a 15.2
135 213 348 347 348 347
38.79 61.21 54.6 70.8 165.9 87.0
11.6c,e
347
95.8
10.7b 10.7b
346 346
32.6 67.4
9.1 9.1
12.4*,e 12.7 9.8 11.8
55.60% 44.40%
326 193
62.81% 37.19%
460 300
—
31.71 68.29 49.1 71.5 166.0 87.8
15.4 14.5 9.8 13.2
Value 60.53% 39.47%
SD —
49.0 81.6 174.0 94.1
15.7 11.5f 8.1f 11.3f
519 517 517 513
49.1 66.8 160.7 84.9
15.3 13.3f 7.8f 13.1f
99.0
8.5
513
97.9
12.5
753
98.2
11.4
238 238
24.4 75.6
6.4f 6.4f
515 515
36.3 63.7
8.4f 8.4f
753 753
32.5 67.5
9.6 9.6
3.8*** 519
26.0
5.3*** 757
25.9
4.8
61.1% 38.9%
—
10.1c,e 240
—
31.7 68.3
9.5b 9.5b
98 98
34.7 65.3
25.7
5.1**
98
27.5
6.2**,e
347
25.7
3.8e
241
26.7
70.7% 29.3%
—
63 28
69.2% 30.8%
—
146 152
49.0% 51.0%
—
152 73
67.6%**** 32.4%
254 188
57.5%**** 42.5%
417 266
—
A.D. Tarnoki et al.
MZ, monozygotic; DZ, dizygotic; SD, standard deviation. a Hungarian vs American, p < 0.05. b Hungarian vs American, p < 0.01. c Hungarian vs American, p < 0.001. d Hungarian vs Italian, p < 0.005. e American vs Italian p < 0.001. f Males vs females p < 0.001. * Hungarian vs Italian p < 0.001. ** Hungarian vs American, p < 0.005. *** Males vs Females p < 0.01. **** Males vs Females p < 0.05.
n
241 519 760 757 758 753
241 240 240 240
—
Females
n
Intraclass correlation and ACE/ADE model of body composition variables. Zygosity
BMI 229 MZ 150 DZ Waist circumference 227 MZ 149 DZ Hip circumference 227 MZ DZ 149 Body fat 228 MZ 148 DZ Fat-free mass 228 MZ 148 DZ
Intraclass correlation
Best model analysis
Value
95%CI
A
95%CI of A
E
95%CI of E
2*
df
P
AIC
0.81 0.44
0.77—0.85 0.29—0.55
0.81
0.77—0.85
0.19
0.15—0.23
0.19
1
0.66
−1.81
0.74 0.41
0.68—0.79 0.27—0.53
0.74
0.68—0.79
0.26
0.21—0.31
0.37
1
0.54
−1.63
0.74 0.49
0.68—0.79 0.35—0.59
0.74
0.69—0.79
0.26
0.21—0.31
3.09
1
0.08
1.09
0.76 0.39
0.71—0.81 0.24—0.52
0.76
0.71—0.81
0.24
0.19—0.29
0.02
1
0.89
−1.98
0.76 0.39
0.71—0.81 0.24—0.52
0.76
0.71—0.81
0.24
0.19—0.29
0.02
1
0.89
−1.98
Bioimpedance analysis of body composition in an international twin cohort
Table 2
MZ, monozygotic; DZ, dizygotic; A, additive genetic effects; E, unique environmental effects; 2 , chi-square (2 = [−2 log-likelihood submodel] − [−2 log-likelihood full model]); df, df submodel − df full model; P, probability; AIC, Akaike Information Criteria, 2 − 2df.
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e296 variance, while shared environmental effects have no effect on the variance in line with earlier reports [13,21,29,30]. For example, BMI variations in the large GenomEUtwin study were mostly influenced by additive genetic and unique (unshared) environmental factors, with the genetic contribution of BMI varying between 45% and 85% according to different countries [31]. A major limitation of our study is that BIA cannot measure fat distribution and provides no heritability estimate on visceral obesity, an important predictor of cardiovascular morbidity and mortality. Several studies have reported strong genetic association with body fat distribution and the relative proportion of subcutaneous and visceral fat depots [14,32,33]. Another limitation of the study is that our modeling of heritability assumes equal common environmental influences on both monozygotic and dizygotic pairs. As true for all twin studies, if this assumption does not hold, then our estimate of heritability may be biased upwards. While the accuracy of BIA has been called into question [34], clinical data from a recent large study support the value of BIA in assessing total body and segmental body composition in the general middle-aged population, particularly for estimating body lean mass [35]. Several authors observed that BIA systems provide good agreement with reference methods at a population level although BIA may be less accurate at the individual level [17,36]. The strength of the study is that all tests were performed by the same protocol, same personnel, and same device at all international locations, involving a relatively large number of twins with a wide age range from different geographical areas. Our findings support routine use of a widely available, portable device to perform BIA as a convenient, noninvasive way to routine assessment of key anthropometric parameters. At the very least, individuals with a positive family history of obesity may need to be monitored during their young adulthood to detect body composition attributes that indicate the development of obesity and the need for life-style changes to reduce the impact of environmental challenges and prevent obesityassociated co-morbidities.
Support This work was supported by Medexpert Ltd, the Twins Days Festival Committee, the Balassi Institute Hungarian Scholarship Board Office, and the Ministry for Foreign Affairs of the Republic of Italy.
A.D. Tarnoki et al. Authors will confer the manuscript copyright to Obesity Research & Clinical Practice in case of acceptance.
Conflicts of interest The authors declare no conflicts of interest.
Acknowledgments Medexpert Ltd. has provided financial support for the development and maintenance of this study. Italian part of the research was supported by the Balassi Institute — Hungarian Scholarship Board Office. We would like to acknowledge the support of Twins Days Festival committee and Istvan Luczek, MD for the American part of the study. Studies were approved by local ethical committees (IRB committee names and project approval numbers: Semmelweis University Regional and Institutional Committee of Science and Research Ethics, 29/2009; Twins Days Festival Ethical Board, 1/2009; Ethical Committee of Istituto Superiore di Sanità).
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