Figures
Abstract
Objective
To analyze bone mineral density (BMD) values in adolescents and to assess obesity impact, measured through body fat #x2013;on this variable through the assessment by DEXA.
Methodology
A total of 318 males adolescents (12–17 years) were evaluated considering weight, height, body mass index (BMI), bone mineral density (BMD), fat and lean mass. BMD was assessed for the arms, legs, hips, and lumbar regions, as well as for total amount. Stratification of the nutritional status was determined by body fat (%BF) percentage; comparison of groups was scrutinized by analysis of variance; and the association of variables was performed using Pearson's test.
Results
There was a progressive increase in weight, height, and BMD for all evaluated age groups following the advance of chronological age. A negative correlation was found between the %BF with BMD in all evaluated segments. Significant differences were found between the eutrophic group compared to the overweight group and the obesity group in the evaluated segments (P <0.01) noting a reduction of up to 12.92% for the lumbar region between eutrophic and obese.
Citation: Ripka WL, Modesto JD, Ulbricht L, Gewehr PM (2016) Obesity Impact Evaluated from Fat Percentage in Bone Mineral Density of Male Adolescents. PLoS ONE 11(9): e0163470. https://doi.org/10.1371/journal.pone.0163470
Editor: Jin-Ran Chen, University of Arkansas for Medical Sciences College of Pharmacy, UNITED STATES
Received: May 18, 2016; Accepted: September 9, 2016; Published: September 29, 2016
Copyright: © 2016 Ripka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This project received funding from Programa de Pesquisa para o Sistema Único de Saúde: Gestão Compartilhada em Saúde PPSUS - edition 04/2012, Project number: 41614 – FA, agreement 982/2013 with Federal University of Technology- Paraná. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript, and none of the authors received a salary. The resources were used to fund adolescents’ DXA evaluation.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Adolescence represents a critical period for bone mineralization in both genders [1] and approximately 60% risk of developing osteoporosis in adulthood is related to bone mass acquisition in this stage of life [2,3]. However, there are several factors associated with changes in this tissue, including age [1], nutritional and, hormonal status [4,5], physical exercise [6], genetics and dietary habits [7,8].
In regard to nutritional status, the excess of fat during adolescence, in addition to effects on bone tissue [4,9], is largely related to the onset of clinical manifestations of coronary heart disease [10], respiratory problems [11] and type 2 diabetes [12]. These risk factors associated with obesity and its alarming growth in recent decades has put the control of this disorder as a new health policy challenge worldwide, even in developing countries [13].
Among the ways to evaluate bone tissue and fat tissues there is the technology of dual energy X-ray absorptiometry (DEXA). This method, developed in the 80s, has its operation based on the measurement of photons attenuation generated by X-ray sources, in both low and high density tissues, allowing the assessment of bone tissue characteristics such as mineral density (BMD) (g/cm2) and mineral content (g). As for the body mass, the equipment allows fat mass section, lean mass section and body fat percentage, and it is considered one of the main evaluation methods [14,15].
Previous studies [4,16–18] which evaluated the relationship between BMD and nutritional status used body mass index (BMI) as a ranking factor, but it is believed that this method tends to generate a different interpretation of that proposed by the analysis of body fat specifically.
Thus, the objective of this study was to analyze BMD values in male adolescents (12–17) and to verify the impact of obesity as measured by body fat on the BMD variable through measurements by DEXA.
Materials and Methods
Study population
Data for this study were obtained for approximately two years (2015–2016) among caucasian adolescents enrolled in the school system, aged 12 to 17 whose parents gave them permission to participate in the research by signing an informed consent form. This study was approved by the Ethics Committee through the Brazil Platform under number 11583113.7.0000.5547.
A sampling error of 4% under confidence level of 95% for a population of 82,414 individuals was specified for the sample size [19]. All adolescents whose: a) parents did not allow participation; b) made use of medicines containing calcium; c) went through radiography in the seven days before the evaluation, were excluded from the research.
Anthropometric assessment
Body mass was collected with the use of a mechanical scale and height with the use of a stadiometer coupled to the scale (Filizola, São Paulo, SP, Brazil).
The DEXA evaluation was performed using a Hologic Discovery A fan-beam scan type (Hologic, Inc., Bedford, MA, USA). Individuals were placed in supine position on the scanner table. It was not allowed the presence of metal artifacts such as earrings, chains or rings, as well as clothing possessing any kind of metal. The total fat percentage (%BF) was obtained automatically by the machine software. For BMD values, five evaluation points were considered: arms, legs, pelvis, lumbar and whole body.
The nutritional classification for %BF was made based on the criteria established by Lohman et al. [20]. Boys with values up to 20% were considered eutrophic; >20% and ≤25% overweight and >25% obese. With regard to the BMI classification, it was made from the index calculation (kg/m2) using the recommendation of the World Health Organization (WHO) which classifies as eutrophic adolescents those between the 5th and the 85th percentiles, as overweight those classified between the 85th and the 95th percentiles, and as obese those above [21].
Statistical analysis
Statistical analysis was made by descriptive presentation of the mean ± standard deviation values. To quantify the intensity and direction of variables association the Bravis-Pearson bivariate correlation test was performed. To test for the equality of mean BMD measurements between nutritional groups (eutrophic, overweight, obese) we used a one-way analysis of variance (ANOVA). When H0 was rejected and the existence of a difference was found between sample groups, the post-Hoc Tukey test was applied for multiple comparisons. The assumption of normal distribution of variables was tested using Kolmogorov-Smirnov.
For the analysis, the statistical significance value p < 0.05 was adopted and the statistical packages –Statistical Package for Social Sciences (SPSS)–version 17.0 (SPSS Inc. Chicago, IL) were used.
Results
Three hundred and eighteen adolescents were evaluated with an average age of 14.87±1.52. For normal distribution analysis, p > 0.05 was obtained in all variables. Descriptive values for anthropometric variables and bone mineral density are shown in Table 1. It is observed a progressive increase in weight (kg), height (m) and BMD (g/cm2) following chronological age advance. The characteristics were presented in mean±standard deviation form.
In a second instance, we tested the correlation of BMI and %BF with BMD. Our findings were that in all analysis %BF presented negative correlation with BMD (Figs 1A, 2A, 3A, 4A and 5A). As opposed to that, BMI presented positive association as shown in Figs 1B, 2B, 3B, 4B and 5B.
(A) Stratification from %BF. (B) Stratification from BMI.
(A) Stratification from %BF. (B) Stratification from BMI.
(A) Stratification from %BF. (B) Stratification from BMI.
(A) Stratification from %BF. (B) Stratification from BMI.
(A) Stratification from %BF. (B) Stratification from BMI.
Using the ANOVA, with Tukey post-Hoc, to test the impact of %BF on BMD variables, we have noted a significant decrease between overweight and obesity groups in comparison with the eutrophic group in all evaluated segments. There was a reduction of up to 12.92% for the lumbar region between eutrophic and obese groups. The impact of increased %BF in BMD was also observed between overweight and obesity groups for arms and lumbar regions (Table 2 and S1 Table).
After the group's nutritional status was categorized from the BMI, we noted a significant increase in BMD for the overweight group in comparison to the eutrophic group for the variables pelvis and arms. When comparing the groups Overweight and Obesity, the arms and lumbar regions showed lower significant values for the obese group (Table 3 and S2 Table).
Discussion
This study verified the impact of %BF in BMD in male adolescents. The results showed that group stratification according to the %BF highlights the significant loss of BMD for overweight and obesity groups as compared to the eutrophic group in all evaluated segments, with a loss of 9.91% (whole body) and 12.92% (lumbar). The findings recorded from the use of BMI as classification criteria, in turn,demonstrateda different association between nutritional status change and BMD loss.
Although the mechanism involving the relationship between adipose and skeletaltissue to be uncertain [4]. Amongst the explanations for that one can note the relation between the increase in adipogenesis and the decrease of osteoblastogenesis caused by obesity [22] in addition to diets with excess of fatty foods which interfere in calcium absorption [17,22].
Fat excess in adolescents is highlighted with concern by the World Health Organization publications, since it generates an early increase of medical expenses [21,23]. The inverse relationship between %BF and BMD pointed in this study suggests the need for a new approach to the health of adolescents. Therefore, the increase of %BF and the decrease in BMD may reflect bone metabolic disorder and, subsequently, osteoporosis. In Brazil, where ~75% of the population uses the free health care system, the creation of public policies associated with the impact of the relationship of %BF in BMD may prevent a collapse in public spending.
Recent research which compared bone measurements in adolescents according to the nutritional status from BMI diverged from the findings of this study. Mosca et al. [4] evaluated 170 boys (10–19) from São Paulo (Brazil) and showed that eutrophic individuals had lower BMD values for the lumbar, femur, and total body compared to adolescents with overweight, obesity and extreme obesity. Similar results to the previous study were found by Jeddi et al. [17] after assessing 237 Jordanian adolescents (9–18) where eutrophic, overweight and obese individuals showed mean BMD values for whole body equal to 0.88±0.11g/cm2, 0.93±0.11g/cm2, 0.93±0.12g/cm2, respectively. Another study evaluated 235 adolescents among which 103 were obese (4–20), and again it was found that individuals with obesity, ranked from BMI, were those with higher BMD values [24].
The divergence of results can be explained by the fact that in all cases BMI was used for nutritional classification of individuals and not the %BF. The use of this index as rating instrument has as its parameters both weight and height. Both variables have a positive correlation with the bone tissue, and BMI is limited to distinguish fat mass and muscle mass [25].
Despite this contradiction, the linear increase trend in BMD values with the advance of age and the negative association of this variable with body fat corroborates other studies conducted with adolescents [1,4,17,26]. Moreover, correlation values found between BMI and BMD (R = 0.514; P < 0.001) and between %BF and BMD (R = -0.321; P < 0.001), as well as graphical analysis, reinforce the opposition between the two classification forms [18,27].
Conclusion
In conclusion some limitations need to be highlighted. Although all participants were white, and was not possible to keep a specific control over race of the adolescents. Considering that in the region where the study was conducted there are adolescents with ethnic background from different regions in Europe (Ukrainians, Polish, Italian, German, Portuguese and Lebanese), besides the ones with Latin American ancestry. Sexual maturation of those individuals and its impact on skeleton were not controlled. Finally, it is suggested that overweight and obesity, classified from the %BF are associated with lower BMD among male adolescents. This strengthens the need for health public policies for adolescents in order to prevent and control body fat excess.
Supporting Information
S1 Table. ANOVA, with Tukey post-Hoc, to test the impact of %BodyFat on bone mineral density variables.
https://doi.org/10.1371/journal.pone.0163470.s001
(XLSX)
S2 Table. ANOVA, with Tukey post-Hoc, to test the impact of BMI on bone mineral density variables.
https://doi.org/10.1371/journal.pone.0163470.s002
(XLSX)
Author Contributions
- Conceptualization: WLR LU PMG.
- Data curation: WLR.
- Formal analysis: WLR JDM LU PMG.
- Funding acquisition: LU PMG.
- Investigation: WLR JDM.
- Methodology: WLR LU PMG.
- Project administration: WLR.
- Resources: LU JDM.
- Supervision: LU PMG.
- Validation: WLR LU.
- Visualization: WLR JDM LU PMG.
- Writing – original draft: WLR JDM LU PMG.
- Writing – review & editing: WLR LU PMG.
References
- 1. Silva CC, Goldberg TB, Teixeira AS, Dalmas JC. Mineralização óssea em adolescentes do sexo masculino: anos críticos para a aquisição da massa óssea. J Pediatr (Rio J). 2004;80(6):461–7. pmid:15622422
- 2. Bachrach LK, Hastie T, Wang M-C, Narasimhan B, Marcus R. Bone Mineral Acquisition in Healthy Asian, Hispanic, Black, and Caucasian Youth: A Longitudinal Study 1. The Journal of Clinical Endocrinology & Metabolism. 1999;84(12):4702–12.
- 3. Wren TA, Kalkwarf HJ, Zemel BS, Lappe JM, Oberfield S, Shepherd JA, et al. Longitudinal tracking of dual-energy X-ray absorptiometry bone measures over 6 years in children and adolescents: persistence of low bone mass to maturity. The Journal of pediatrics. 2014;164(6):1280–5.e2. pmid:24485819
- 4. Mosca LN, Goldberg TBL, da Silva VN, da Silva CC, Kurokawa CS, Rizzo ACB, et al. Excess body fat negatively affects bone mass in adolescents. Nutrition. 2014;30(7):847–52. pmid:24985003
- 5. Mosca LN, Da Silva VN, Goldberg TBL. Does excess weight interfere with bone mass accumulation during adolescence? Nutrients. 2013;5(6):2047–61. pmid:23743968
- 6. da Silva Filho JN, da Fonseca RC, Cruz AP, de Maio Godoi Filho JR, Saraiva B, Ferreira RA. Efeitos do exercício físico de força sobre o desenvolvimento ósseo em crianças e adolescentes: uma revisão sistemática. Revista Brasileira de Prescrição e Fisiologia do Exercício. 2015;9(51):40–7.
- 7. Shapiro R, Heaney R. Co-dependence of calcium and phosphorus for growth and bone development under conditions of varying deficiency. Bone. 2003;32(5):532–40. pmid:12753869
- 8. Pekkinen M, Viljakainen H, Saarnio E, Lamberg-Allardt C, Mäkitie O. Vitamin D is a major determinant of bone mineral density at school age. Plos One. 2012;7(7):e40090. pmid:22768331
- 9. Pollock NK, Bernard PJ, Gutin B, Davis CL, Zhu H, Dong Y. Adolescent obesity, bone mass, and cardiometabolic risk factors. The Journal of pediatrics. 2011;158(5):727–34. pmid:21232765
- 10. Rank M, Siegrist M, Wilks DC, Langhof H, Wolfarth B, Haller B, et al. The cardio-metabolic risk of moderate and severe obesity in children and adolescents. The Journal of pediatrics. 2013;163(1):137–42. pmid:23434121
- 11. Tenório LHS, Santos AC, Oliveira AS, Lima AMJ, Brasileiro-Santos MS. Obesity and pulmonary function tests in children and adolescents: a systematic review. Revista Paulista de Pediatria. 2012;30(3):423–30.
- 12. Copeland KC, Silverstein J, Moore KR, Prazar GE, Raymer T, Shiffman RN, et al. Management of newly diagnosed type 2 diabetes mellitus (T2DM) in children and adolescents. Pediatrics. 2013;131(2):364–82. pmid:23359574
- 13. De Onis M, Blössner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. The American journal of clinical nutrition. 2010;92(5):1257–64. pmid:20861173
- 14. Silva DR, Ribeiro AS, Pavão FH, Ronque ER, Avelar A, Silva AM, et al. Validade dos métodos para avaliação da gordura corporal em crianças e adolescentes por meio de modelos multicompartimentais: uma revisão sistemática. Revista da Associação Médica Brasileira. 2013;59(5):475–86. pmid:24119380
- 15. Albanese CV, Diessel E, Genant HK. Clinical applications of body composition measurements using DXA. Journal of Clinical Densitometry. 2003;6(2):75–85. pmid:12794229
- 16. Ito IH, Mantovani AM, Agostinete RR, Costa P, Zanuto EF, Christofaro DGD, et al. Practice of martial arts and bone mineral density in adolescents of both sexes. Revista Paulista de Pediatria (English Edition). 2016; 34(2):210–5. pmid:27017002
- 17. Jeddi M, Dabbaghmanesh MH, Omrani GR, Ayatollahi SMT, Bagheri Z, Bakhshayeshkaram M. Relative Importance of Lean and Fat Mass on Bone Mineral Density in Iranian Children and Adolescents. International journal of endocrinology and metabolism. 2015;13(3): e25542. pmid:26401143
- 18. Carvalho WRGd, Gonçalves EM, Ríbeiro RR, Farias ES, Carvalho SSPd, Guerra-Júnior G. Influência da composição corporal sobre a massa óssea em crianças e adolescentes. Rev Assoc Med Bras(1992). 2011;57(6):662–7.
- 19.
Barbetta PA. Estatística aplicada às ciências sociais. 1ªed. UFSC; 2008.
- 20. Lohman TG. Advances in body composition assessment. Medicine & Science in Sports & Exercise. 1993;25(6):762.
- 21.
World Health Organization. Adolescent Health. Geneva 2014 [acess jan 15 2016] Available from: http://www.who.int/topics/adolescent_health/en/.
- 22. Cao JJ. Effects of obesity on bone metabolism. Journal of orthopaedic surgery and research. 2011;6(1):1–6. pmid:21676245
- 23.
World Health Organization. Population-based prevention strategies for childhood obesity: report of a WHO forum and technical meeting. Geneva 2010.
- 24. Leonard MB, Shults J, Wilson BA, Tershakavec AM, Babette SZ. Obesity during childhood and adolescence augments bone mass and bone dimensions. The American journal of clinical nutrition. 2004;80:514–523. pmid:15277178
- 25. Hariri AA, Oliver NS, Johnston DG, Stevenson JC, Godsland IF. Adiposity Measurements by BMI, Skinfolds and Dual Energy X-Ray Absorptiometry in relation to Risk Markers for Cardiovascular Disease and Diabetes in Adult Males. Disease Markers. 2013;35(6):753–64. pmid:24347796
- 26. Palermo A, Tuccinardi D, Defeudis G, Watanabe M, D’Onofrio L, Pantano AL, Napoli N, Pozzili P, Manfrini S. BMI and BMD: The Potential Interplay between Obesity and Bone Fragility. International journal of environmental research and public health. 2016;13:544–74. pmid:27240395
- 27. El Khayat H, Emam E, Hassan N, Kandeel W, Elagouza I, Zaki M. Impact of body fat mass on bone mineral density and content and on serum level of c-terminal telopeptide of type 1 collagen among overweight and obese children and adolescents. J of Applied Sci Res. 2013;9(1):770–80.