SciELO - Scientific Electronic Library Online

 
vol.21 número4Reprodutibilidade e validade do construto de três instrumentos não invasivos para a avaliação da amplitude de movimento da coluna em pacientes com dor lombarFactores asociados a la capacidad funcional de ancianos registrados en la Estrategia Salud de la Familia índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

Compartilhar


Fisioterapia e Pesquisa

versão impressa ISSN 1809-2950

Fisioter. Pesqui. vol.21 no.4 São Paulo out./dez. 2014

http://dx.doi.org/10.590/1809-2950/13166621042014 

Original Research

Impact of clinical and functional conditions on quality of life in old women with obesity

Impacto de las condiciones clínicas y funcionales en la cualidad de vida de ancianas con obesidad

Marília Caixeta De Araujo 1  

João Marcos Domingues Dias 2  

Karina Simone de Souza Vasconcelos 3  

Adriana Pedrita Pessoa Medeiros 1  

Carla Moura Santos 1  

Rosângela Correa Dias 2  

1School of Physical Education, Physical Therapy and Occupational Therapy, Universidade Federal de Minas Gerais (UFMG) - Belo Horizonte (MG), Brazil

2Physical Therapy Departament, UFMG - Belo Horizonte (MG), Brazil

3Graduate Program in Reabilitation, UFMG - Belo Horizonte (MG), Brazil

ABSTRACT

Obesity is associated with functional disabilities and impairments of quality of life, and many factors affect this relationship. This study aimed at characterizing and identifying the impact of clinical and functional conditions on health-related quality of life (HRQoL) in obese old women. The HRQoL was assessed by the questionnaires "Outcomes Study Short Form-36 Health Survey" (SF-36) and "Impact of Weight on Quality of Life - Lite" (IWQOL - Lite), which were applied to 63 women with body mass index ≥30 kg/m2. Regression models were developed for general (SF-36) and specific (IWQOL-Lite) HRQoL. The associated factors investigated were: age, number of medicines, number of diseases, depressive symptoms, body mass index, grip strength, level of physical activity, and functional performance. The old women had a low level of strength and physical activity. Their functional performance was good to moderate, but a third of the sample presented deficit of mobility. The level of physical activity and functional performance had a positive impact on the general HRQoL and number of drugs had a negative one (R2=0.44). Depressive symptoms and body mass index negatively affected the specific HRQoL (R2=0.57). The study concluded that obese old women with depressive symptoms, low levels of physical activity, and functional performance, making use of a great number of drugs, are more vulnerable to experiencing poor HRQoL. All the factors associated with the HRQoL in this study are potentially modifiable with interventions of health prevention and promotion.

Key words: Obesity; Aging; Quality of Life

RESUMEN

La obesidad está asociada a incapacidades funcionales y prejuicios a la cualidad de vida, y muchos factores interfieren en esa asociación. Eso estudio tuvo por objetivo caracterizar e identificar el impacto de las condiciones clínicas y funcionales en la cualidad de vida relacionada a la salud (CVRS) en ancianas obesas. La CVRS fue evaluada por los cuestionarios "Outcomes Study Short Form-36 Health Survey" (SF-36) e "Impact of Weight on Quality of Life - Lite" (IWQOL-Lite), aplicados a 63 mujeres con índice de masa corporal ≥30 kg/m2. Fueron desarrollados modelos de regresión para la CVRS general (SF-36) y específica (IWQOL-Lite). Los factores asociados investigados fueron: edad, número de medicamentos, número de enfermedades, síntomas depresivos, índice de masa corporal, fuerza de preensión, nivel de actividad física y desempeño funcional. Las ancianas presentaron un bajo nivel de fuerza y actividad física. El desempeño funcional varió del bueno al moderado, pero un tercio de la muestra presentó déficit de movilidad. Lo nivel de actividad física y desempeño funcional tuvieron un impacto positivo en la CVRS general y el número de medicamentos, negativo (R2=0,44). Síntomas depresivos e índice de masa corporal impactaron negativamente en la CVRS específica (R2=0,57). El estudio concluso que ancianas obesas con síntomas depresivos, bajos niveles de actividad física y desempeño funcional, utilizando una gran cuantía de medicamentos, son más vulnerables a presentaren baja CVRS. Todos los factores asociados a la CVRS son potencialmente modificables con medidas de prevención y promoción a la salud.

Palabras-clave: Obesidad; Envejecimiento; Calidad de Vida

INTRODUCTION

Obesity is a global epidemic, affecting mainly women1. Changes in metabolism and body composition that occur with aging predispose such condition2.

Among the elderly, this condition is associated with morbidities, functional disability and impairment of quality of life related to health (HRQoL)2 , 3. Obese elderly have worse HRQoL compared to obese adults4 , 5, and women have the lowest scores4 - 7.

In general, obesity is more associated with higher losses in the physical components of HRQoL than in mental and emotional components6 , 8 - 10. However, obese individuals who have comorbidities can demonstrate losses in the three components11 , 12. It is possible that the presence of physical or functional limitations also interfere with this relationship. However, most studies on obesity and HRQoL do not control the associated effects of clinical and functional conditions.

Considering the importance of HRQoL as a target of health interventions, it is essential to identify the aggravating or mitigating factors of the relation between obesity and HRQoL. Thus, the objectives of this study were to characterize and analyze the relation between the clinical and functional conditions and the HRQoL in obese elderly.

METHODOLOGY

Study design

Observational cross-sectional study, approved by the Research Ethics Committee of the Universidade Federal de Minas Gerais (UFMG), ETIC0172.0.203.000-11. The participants signed a free and informed consent and received guidance about their participation.

Sample

The sample size was calculated by the G* Power313. For a linear regression model with eight predictors, significance level (α) was considered equal to 0.05, power (β) of 0.80 and effect size of 0.30. Thus, the sample size calculation was 60 elderly women, with a 5% increase for possible losses.

The sample consisted of women aged ≥65 years, able to walk without aid for marching and body mass index (BMI) ≥30 kg/m2. Participants were excluded with cognitive impairment (score ≤17 points in the Mini Mental State Examination)14; with physical or sensory disabilities that prevent them from conducting the tests; fractures and/or surgical interventions in the lower limbs in the last year and disease in acute or decompensated stage.

Procedures

The clinical conditions were obtained by interview and physical examination. The number of diseases was obtained from self-reported medical conditions by the seniors. For the number of drugs were considered those of regular and systematic use. BMI was calculated as kg/m2, measuring weight and height in a scale with altimeter (Fillizola, São Paulo, Brazil). The presence of depression symptoms was assessed by reduced Geriatric Depression Scale (GDS-10)15.

Functional conditions were obtained by three instruments. The hand grip strength (HGS) was recorded as the average of three attempts of six seconds in the dominant hand, with manual Jamar(r) type dynamometer (Sammons Preston, Illinois). Below 21 kgf values were considered as indicative of sarcopenia16. The level of physical activity was assessed by human activity profile (HAP), classifying the elderly as inactive, moderately active and active. This classification is obtained from the adjusted score of activity (ASA), which is calculated by subtracting the items answered as "stopped doing" of the value of maximum score of activity, being inactive the ones with ASA<53, moderately active from 53 to 74 and active>7417. Functional performance was achieved through the "Short Physical Performance Battery" (SPPB)18. Values below 1.0 m/s for march velocity (MV) were considered as a mobility deficit19.

HRQoL was measured by two questionnaires translated and validated for the Brazilian population, applied by a single trained examiner. The overall HRQoL was analyzed using the "Outcomes Study Short Form-36 Health Survey" (SF-36)20, with scores from 0 (worst) to 100 (best) in each domain. The specific HRQoL was evaluated by the "Impact of Weight on Quality of Life - Lite" (IWQOL-Lite)21, with scores processed from 0 (best) to 100 (worst) for each domain.

Statistical analysis

To characterize the sample, measures of central tendency and dispersion were used for the continuous variables and frequency distributions for the categorical.

Two multivariate linear regression models were built to analyze the relation of clinical and functional conditions and HRQoL. In the first, the dependent variable was the final score of the functional capacity domain of the SF-36 (general HRQoL) and in the second, the physical health domain of IWQOL-Lite (specific HRQoL). For each, were determined eight predictors as independent variables: age, number of diseases, number of drugs, depression symptoms, BMI, HGS, activity level and functional performance.

In univariate analysis, were used Spearman correlation tests and comparison of means (Student's t-test and analysis of variance - ANOVA). Were included in the regression models the independent variables that presented significant correlation with the dependent (p≤0,20). For the multivariate models, it was taken into account the significance level of α≤0,05. It was used the Statistical Package for Social Sciences - SPSS Program (SPSS Inc., Chicago, DE, USA), version 15.0 for Windows.

RESULTS

Table 1 shows the clinical and functional conditions of the sample. Of the 63 volunteers, 23 (36.5%) showed depression symptoms. The number of diseases was 4.9, being hypertension, knee osteoarthritis, hypercholesterolemia and diabetes mellitus the most frequent. These participants had low levels of HGS, and 71% had sarcopenia. The average level of physical activity was moderate, being 33% inactive, 64% moderately active and 3% active. In the SPPB, 30% showed good performance (10 to 12 points) and 70%, moderate (between nine and seven points). Despite the appropriate average, 18 elderly (29%) had MV<1.0 m/s.

Table 1. Clinical and functional conditions of obesity with elderly (n=63) 

Characteristic Minimum Maximum Mean (SD)
Age (years) 65 83 71.88 (4.28)
Weight (kg) 62.00 110.00 78.87 (9.90)
Height (m) 1.40 1.66 1.52 (0.06)
Body mass index (kg/m2) 30.08 48.11 33.87 (3.32)
Disease 2 11 4.90 (2.02)
Drugs 0 12 4.37 (2.31)
Grip strength (kgf) 12.00 28.67 19.41 (3.82)
Activity level 21 83 54.73 (13.16)
Functional performance 7 12 10.08 (1.39)
Marching velocity (m/s) 0.62 1.57 1.08 (0.18)

SD: standard deviation; kgf: kilogram-force

Table 2 shows that the limitation domains by social aspects and limitation by physical aspects had the worst scores in the general HRQoL and functional capacity and limitation by emotional aspects, the best. Physical function was the domain of worst score in specific HRQoL. The areas of general and specific HRQoL had negative and moderate correlations with each other.

Table 2. Scores of quality of life related to health and correlations among the domains of each instrument 

 General HRQoL (SF-36) Specific HRQoL (IWQOL-Lite)
Mean (SD) Physical function
22.29 (9.87)
Self-esteem
11.57 (7.03)
Embarrassment
6.08 (2.68)
Correlations
General state of health 68.27 (19.23) -0.37* -0.08 -0.20
Functional capacity 72.46 (22.52) -0.33* 0.03 -0.12
Physical aspects 60.71 (39.07) -0.19 -0.14 -0.03
Emotionals aspects 73.41 (30.74) -0.21 -0.24 -0.11
Socials aspects 55.98 (25.93) -0.29* -0.03 -0.19
Pain 69.31 (40.29) -0.30* -0.13 -0.36*
Vitality 63.17 (25.25) -0.32* -0.22 -0.14
Mental health 67.81 (23.49) -0.35* -0.25* -0.17

SD: standard deviation; SF-36: Outcomes Study Short Form-36 Health Survey; IWQOL-Lite: Impact of Weight on Quality of Life - Lite;

*p=0.05; HRQoL: health-related quality of life

The clinical conditions had an impact on the two models of HRQoL, as the functional impact only in the general HRQoL (Table 3). The equations for each model were:

Table 3. Regression models for quality of life related to health 

General HRQoL (functional capacity SF-36). R2=44%
Independent variables B (95%CI) B standard error β Significance
Constant -6.44 (-122.68–109.78) 57.89 0.91
Age 0.85 (-0.40–2.11) 0.63 0.16 0.18
Disease 0.18 (-2.51–2.88) 1.35 0.02 0.89
Drugs -2.42 (-4.66–-0.17) 1.11 -0.25* 0.03
Depression symptoms -8.53 (-19.52–2.45) 5.47 -0.18 0.12
BMI -0.49 (-0.40–2.11) 0.75 -0.07 0.52
Activity level 14.38 (4.94–23.82) 1.81 0.23* 0.01
Functional performance 3.75 (0.11–7.38) 4.70 0.35* 0.04
Specific HRQOL (physical function IWQOL). R2=57%
Independent variables B (95%CI) B standard error β Significance
Constant -96.88 (-187.77–-6.01) 45.39 0.04
Age -0.34 (-1.33–0.66) 0.49 -0.06 0.50
Disease 1.28 (-0.83–3.40) 0.11 0.12 0.23
Depression symptoms 12.75 (3.93–21.56) 4.41 0.27* 0.01
BMI 4.01 (2.76–5.26) 0.62 0.60* 0.01

R2: coefficient of determination; B: not standardized coefficient; IC: confidence interval; ß: standardized coefficient; BMI: body mass index; SF-36: Outcomes Study Short Form-36 Health Survey; IWQOL: Impact of Weight on Quality of Life; HRQOL: health-related quality of life;

*p=0.05

  • general HRQoL = -6.44 -2.42 (number of drugs) + 14.38 (activity level) + 3.75 (functional performance);

  • specific HRQoL = -96.88 + 12.75 (depression symptoms) + 4.01 (BMI).

DISCUSSION

Obesity can negatively affect the functional capacity of the elderly, especially for locomotion22. In this study, although no elderly have shown low functional performance in SPPB, one third of the sample showed insufficient levels of MV. Slow march is a predictor factor of adverse events among the elderly, such as falls, institutionalization and mortality19.

It was expected to observe lower values in the physical domains of HRQoL, which was not observed in the general HRQoL. In this study, obese women showed higher losses in the restriction by social and physical apects, with low values also for vitality and mental health. On the other hand, the specific HRQoL for obesity showed greater impact on physical function domain, which had significant correlations with various domains of the SF-36. This association probably reflects the functional limitations of this population.

It is known that active individuals tend to have higher levels of HRQoL23 , 24 and longitudinal studies have shown that obesity and a sedentary lifestyle can have long-term negative effects on HRQoL25 , 26. Physical inactivity also explains part of the association between chronic diseases and low HRQoL in elderly27. In this study, functional performance and activity level had a positive association with functional capacity domain of the SF-36. This implies that elderly women more active and better functional performance have better overall HRQoL.

BMI showed a negative impact on HRQoL, as demonstrated with the IWQOL-Lite28 and the SF-366. The association remained significant only in specific HRQoL model, probably by the interaction of other factors in the general HRQoL. In addition, the IWQOL-Lite is more sensitive to measure the impact of BMI on HRQoL than the SF-36, due to the use of the phrase "because of my weight" in the instrument29.

Banegas et al.11 observed that the association of hypertension and diabetes mellitus enhances the negative effects of obesity on HRQoL among the elderly, especially among women. However, some authors concluded that gender differences in the impact of obesity on HRQoL are independent of the number of diseases7 , 10. Mond and Baune7 pointed to the likely influence of psychological and emotional factors that may mediate the relation between obesity and HRQoL. Our findings support this hypothesis, since the presence of depression symptoms had a negative impact on specific HRQoL. Other authors observed the negative effect of psychological disorders on HRQoL, especially depression6 , 23 , 24. All this evidence confirms the importance of evaluating the psychological aspects of elderly patients with obesity and the need to implement therapeutic measures for depression in this population.

In this study, the number of diseases did not showed association with HRQoL in mutivariated models. However, the number of drugs remained negatively associated with overall HRQoL. This could be due to two variables being related to each other, reflecting the health status of the elderly. Thompson et al.30 used a wider measure of health status than the number of illnesses or medications in the elderly, showing a negative association between the medical care costs and HRQoL30.

Muscle weakness was common among the elderly women, which characterizes Sarcopenic obesity. This condition is more strongly associated with functional impairment and quality of life than obesity alone or sarcopenia, and may maximize the effects of physical inactivity and generate morbidities31. Silva Neto et al. showed that HGS may have a positive association with all domains of the SF-36, except for the vitality and mental health32. However, the same was not observed in this study. A possible explanation may be the homogeneity of the sample for this variable. Moreover, Silva Neto et al. used the ratio between fat and lean mass to define obesity, but not the BMI32.

Age did not influence the HRQoL in the final models. Probably part of its effect is due to other confounding factors, such as clinical and functional conditions. Longitudinal studies could explore whether there is an independent effect of aging on HRQoL.

The results of this study are limited to older women and feature cross associations. Factors associated with psychological and social domains of HRQoL were not explored in this analysis. However, this research is one of the few who studied the relation between obesity and HRQoL in the elderly, considering physical, functional and psychological aspects.

CONCLUSION

Senior obese women using a large number of drugs and showing high levels of BMI, depression symptoms and low levels of physical activity and functional performance are more vulnerable to present low HRQOL. All these factors are modifiable with approaches to prevention and health promotion. Oriented physical activity, in particular, can bring several benefits to this population and directly impact on HRQoL.

REFERENCES

1. World Health Organization. Obesity: preventing and managing the global epidemic. Report Series 894; 2000. [ Links ]

2. Han TS, Tajar A, Lean ME. Obesity and weight management in the elderly. Br Med Bull. 2011;97:169-96. [ Links ]

3. Villareal D, Apovian C, Kushner R, Klein S. Obesity in older adults:technical review and position statement of the American Society for Nutrition and NAASO, The Obesity Society. Am J Clin Nutr. 2005;82:923-34. [ Links ]

4. Zabelina DL, Erickson AL, Kolotkin RL, Crosby RD. The effect of age on weight-related quality of life in overweight and obese individuals. Obesity (Silver Spring). 2009;17(7):1410-3. [ Links ]

5. Sirtori A, Brunani A, Villa V, Berselli ME, Croci M, Leonardi M, et al. Obesity is a marker of reduction in QoL and disability. Scientific World J. 2012;2012:167520. [ Links ]

6. Mannucci E, Petroni ML, Villanova N, Rotella CM, Apolone G, Marchesini G; QUOVADIS Study Group. Clinical and psychological correlates of health-related quality of life in obese patients. Health Qual Life Outcomes. 2010;8:90. [ Links ]

7. Mond JM, Baune BT. Overweight, medical comorbidity and health-related quality of life in a community sample of women and men. Obesity (Silver Spring). 2009;17(8):1627-34. [ Links ]

8. Bentley TG, Palta M, Paulsen AJ, Cherepanov D, Dunham NC, Feeny D, et al. Race and gender associations between obesity and nine health-related quality-of-life measures. Qual Life Res. 2011;20(5):665-74. [ Links ]

9. Buckley J, Tucker G, Hugo G, Wittert G, Adams RJ, Wilson DH. The Australian Baby Boomer Population--Factors Influencing Changes to Health-Related Quality of Life Over Time. J Aging Health. 2013;25(1):29-55. [ Links ]

10. Yan LL, Daviglus ML, Liu K, Pirzada A, Garside DB, Schiffer L, et al. BMI and health-related quality of life in adults 65 years and older. Obes Res. 2004;12(1):69-76. [ Links ]

11. Banegas JR, Lopez-Garcia E, Graciani A, Guallar-Castillon P, Gutierrez-Fisac JL, Alonso J, et al. Relationship between obesity, hypertension and diabetes, and health-related quality of life among the elderly. Eur J Cardiovasc Prev Rehabil. 2007;14(3):456-62. [ Links ]

12. Doll HA, Petersen SE, Stewart-Brown SL. Obesity and physical and emotional well-being: associations between body mass index, chronic illness, and the physical and mental components of the SF-36 questionnaire. Obes Res. 2000;8(2):160-70. [ Links ]

13. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175-91. [ Links ]

14. Bertolucci P, Brucki S, Campacci S, Juliano Y. Impacto do Mini-exame do estado mental em uma população geral. Impacto da escolaridade. Arq Neuropsiquiatr. 1994;52(1):1-7. [ Links ]

15. Almeida OP, Almeida SA. Short versions of the geriatric depression scale: a study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV. Int J Geriatr Psychiatry. 1999;14(10):858-65. [ Links ]

16. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol. 2001;56A(3):M146-56. [ Links ]

17. Souza A, Magalhães L, Teixeira-Salmela L. Adaptação transcultural e análise das propriedades psicométricas da versão brasileira do perfil de atividade humana. Cad Saúde Pública. 2006;22:2623-36. [ Links ]

18. Freire AN, Guerra RO, Alvarado B, Guralnik JM, Zunzunegui MV. Validity and Reliability of the short physical performance battery in two diverse older adult populations in Quebec and Brazil. J Aging Health. 2012;24(2):1-16. [ Links ]

19. Abellan van KG, Rolland Y, Andrieu S, Bauer J, Beauchet O, Bonnefoy M, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging. 2009;13(10):881-9. [ Links ]

20. Ciconelli RM. Tradução para o português e validação do questionário genérico da avaliação de qualidade de vida "Medical outcomes study 36-item short-form health survey (SF-36)" [tese]. São Paulo: Escola Paulista de Medicina, Universidade Federal de São Paulo; 1997. [ Links ]

21. de A Mariano MH, Kolotkin RL, Petribú K, de N L Ferreira M, Dutra RF, Barros MV, et al. Psychometric evaluation of a Brazilian version of the impact of weight on quality of life (IWQOL-Lite) instrument. Eur Eat Disord Rev. 2010;18(1):58-66. [ Links ]

22. Alley D, Chang V. The Changing relationship of obesity and disability, 1988-2004. JAMA. 2007;298(17):2020-7. [ Links ]

23. Alexandre TS, Cordeiro RC, Ramos LR. Factors associated to quality of life in active elderly. Rev Saúde Pública. 2009;43(4):613-21. [ Links ]

24. Pimenta F, Simil F, Torres H, Amaral C, Rezende C, Coelho T, et al. Avaliação da qualidade de vida de aposentados com a utilização do questionário SF-36. Rev Assoc Med Bras. 2008;54(1):55-60. [ Links ]

25. Buckley J, Tucker G, Hugo G, Wittert G, Adams RJ, Wilson DH. The Australian Baby boomer population--factors influencing changes to health-related quality of life over time. J Aging Health. 2013;25(1):29-55. [ Links ]

26. Jia H, Lubetkin EI. Obesity-related quality-adjusted life years lost in the U.S. from 1993 to 2008. Am J Prev Med. 2010;39(3):220-7. [ Links ]

27. Sawatzky R, Liu-Ambrose T, Miller WC, Marra CA. Physical activity as a mediator of the impact of chronic conditions on quality of life in older adults. Health Qual Life Outcomes. 2007;5:68. [ Links ]

28. Sirtori A, Brunani A, Villa V, Berselli ME, Croci M, Leonardi M, et al. Obesity is a marker of reduction in QoL and disability. Scientific World J. 2012;2012:167520. [ Links ]

29. Kolotkin RL, Crosby RD. Psychometric evaluation of the impact of weight on quality of life-lite questionnaire (IWQOL-lite) in a community sample. Qual Life Res. 2002;11(2):157-71. [ Links ]

30. Thompson WW, Zack MM, Krahn GL, Andresen EM, Barile JP. Health-related quality of life among older adults with and without functional limitations. Am J Public Health. 2012;102(3):496-502. [ Links ]

31. Zamboni M, Mazzali G, Fantin F, Rossi A, Di Francesco V. Sarcopenic obesity: a new category of obesity among the elderly. Nutr Metab Cardiovasc Dis. 2008;18(5):388-95. [ Links ]

32. Silva Neto L, Karnikowiski M, Tavares A, Lima R. Associação entre sarcopenia, obesidade sarcopênica e força muscular com variáveis relacionadas de qualidade de vida em idosas. Rev Bras Fisioterap. 2012;16(5):360-7. [ Links ]

Study conducted at the Function Human and Motor Performance Laboratory, Department of Physical Therapy, School of Physical Education, Physical and Occupational Therapy, , Universidade Federal de Minas Gerais (UFMG) - Belo Horizonte (MG), Brazil.

Financing source: none

Approval of the Research Ethics Committee nº ETIC0172.0.203.000-11.

Received: March 2014; Accepted: September 2014

Correspondence to: João Marcos Domingues Dias - Escola de Educação Física, Fisioterapia e Terapia Ocupacional - Departamento de Fisioterapia, UFMG - Avenida Presidente Antônio Carlos, 6.627 - campus Pampulha - CEP: 31270-901 - Belo Horizonte (MG), Brazil - E-mail: jmdd@ufmg.br

Conflict of interests: nothing to declare

Creative Commons License This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.