Services on Demand
- Cited by SciELO
- Access statistics
On-line version ISSN 1518-8787
Print version ISSN 0034-8910
Rev. Saúde Pública vol.43 suppl.1 São Paulo Aug. 2009
Prevalencia, factores de riesgo y genotipos de la hepatitis C entre usuarios de drogas
Carmen L R LopesI, II; Sheila A TelesII; Márcia P Espírito-SantoIII; Elisabete LampeIII; Fabiana P RodriguesIV; Ana Rita C Motta-CastroV; Thaís A MarinhoI; Nádia R ReisI; Ágabo M C SilvaI; Regina M B MartinsI
de Patologia Tropical e Saúde Pública. Universidade Federal de
Goiás (UFG). Goiânia, GO, Brasil
IIFaculdade de Enfermagem. UFG. Goiânia, GO, Brasil
IIIInstituto Oswaldo Cruz. Fundação Oswaldo Cruz. Rio de Janeiro, RJ, Brasil
IVFaculdade de Enfermagem. Universidade Estadual de Mato Grosso do Sul. Dourados, MS, Brasil
VDepartamento de Farmácia-Bioquímica. Universidade Federal de Mato Grosso do Sul. Campo Grande, MS, Brasil
To estimate prevalence of hepatitis C virus (HCV) infection and identify risk
factors associated and circulating HCV genotypes and subtypes.
METHODS: Study conducted including 691 drug users attending 26 charitable, private and public drug treatment centers in Goiânia and Campo Grande, central-western Brazil, between 2005 and 2006. Sociodemographic characteristics and risk factors for HCV infection were collected during interviews. Blood samples were tested for HCV antibodies (anti-HCV). Positive samples were submitted to HCV RNA detection by PCR with primers complementary to 5' NC and NS5B regions of viral genome and genotyped by line probe assay (LiPA) and direct nucleotide sequencing followed by phylogenetic analysis. The prevalence and odds ratio were calculated with 95% confidence intervals. Risk factors were first estimated in the univariate analysis (p<0.10) and then analyzed by hierarchical logistic regression. Statistical significance was assessed at a 5% significance level.
RESULTS: The prevalence of anti-HCV was 6.9% (95% CI: 5.2-9.2). The multivariate analysis of risk factors revealed that age over 30 years and injecting drug use were associated with HCV infection. HCV RNA was detected in 85.4% (41/48) of anti-HCV-positive samples. Thirty-three samples were genotyped as genotype 1 by LiPA, subtypes 1a (63.4%) and 1b (17.1%), and 8 samples (19.5%) were genotype 3, subtype 3a. The phylogenetic analysis of the NS5B region showed that 17 (68%), 5 (20%), and 3 (12%) samples were subtypes 1a, 3a, and 1b, respectively.
CONCLUSIONS: The results show a high prevalence of HCV infection and predominance of subtype 1a among drug users in Brazil. In addition, injecting drug use was a major risk factor associated with HCV infection.
Descriptors: Hepatitis C. Hepatitis C Antibodies, diagnostic use. Hepacivirus, genetics. Substance Abuse, Intravenous. Needle Sharing. Risk Factors. Seroepidemiologic Studies.
Estimar la prevalencia y factores asociados a la infección por el virus
de la hepatitis C en usuarios de drogas e identificar los genotipos y subtipos
MÉTODOS: Estudio realizado con 691 usuarios de drogas de 26 centros de tratamiento de uso de drogas filantrópicos, particulares y públicos de Goiania y Campo Grande (Centro-Oeste), entre 2005 y 2006. Datos sociodemográficos y factores de riesgo para infección por el HCV fueron obtenidos por medio de entrevistas. Muestras sanguíneas fueron evaluadas para la detección de anticuerpos para el HCV. Las muestras positivas fueron sometidas a la detección de RNA-HCV por la reacción en cadena de polimerasa con iniciadores complementarios a las regiones 5' NC y NS5B del genoma viral y genotipadas por el line probe assay (LiPA) y por secuenciación directa, seguido del análisis filogenético. Prevalencia y odds ratio fueron calculados con intervalo de 95% de confianza. Los factores de riesgo con p<0,10 por el análisis univariado fueron analizados por regresión logística jerárquica. Valores de p<0,05 fueron considerados estadísticamente significativos.
RESULTADOS: La prevalencia para anti-HCV fue 6,9% (IC 95%:5,2;9,2). El análisis multivariado de factores de riesgo indicó que edades superiores a 30 años y uso inyectable de drogas se mostraron asociados a la infección por el HCV. El RNA-HCV fue dectado en 85,4% (41/48) de las muestras anti-HCV positivas. Treinta y tres muestras fueron del genotipo 1 por el LiPA, subtipos 1a (63,4%) y 1b (17,1%), y 8 (19,5%) del genotipo 3, subtipo 3a. El análisis filogenético de la región NS5B mostró que 17 (68%), 5 (20%) y 3 (12%) muestras fueron de los subtipos 1a, 3a y 1b, respectivamente.
CONCLUSIONES: Los resultados muestran una prevalencia elevada de la infección y del subtipo 1a del HCV en usuarios de drogas, siendo el uso inyectable de drogas el principal factor de riesgo para esa infección.
Descriptores: Hepatitis C. Anticuerpos contra la Hepatitis C, uso diagnóstico. Hepacivirus, genética. Abuso de Sustancias por Vía Intravenosa. Compartimiento de Agujas. Factores de Riesgo. Estudios Seroepidemiológicos.
Hepatitis C virus (HCV) infection is a major public health concern. It is estimated that 2.2% of the world's population, around 130 million people, are infected with HCV.1 Acute hepatitis C is often asymptomatic but it is a major cause of morbidity and mortality as most cases progress to chronic disease and can lead to liver cirrhosis and hepatocellular carcinoma.3
HCV genoma is characterized by high genetic variability. Six genotypes and multiple subtypes have been identified and they show different response to antiviral therapy as well as diverse geographical distribution. Genotypes 1, 2 and 3 are disseminated worldwide. Genotype 4 is more prevalent in North Africa and Middle East. HCV infections with genotypes 5 and 6 are commonly seen in South Africa and Asia, respectively.24 In Brazil, studies have demonstrated that genotype 1 is the most prevalent, followed by genotype 3.5,18
Hepatitis C transmission most effectively occurs through the parenteral route, transfusion and/or exposure to blood and blood products, but can also be less effectively transmitted through sexual contact and from mother to child.1 Drug users (DU) have an increased risk of HCV infection due to sharing of injecting materials and unsafe sex practices.12,13,16,23
There are few Brazilian studies investigating HCV infection in DU including both injecting and non-injecting drug users. Their HCV prevalence rates range from 5.8% to 36.2%.2,7,10,19,23
The present study is the first to investigate HCV infection in illicit DU with the objective of estimating the prevalence of and factors associated with HCV infection and identifying circulating HCV genotypes and subtypes.
A cross-sectional study was conducted in a convenience sample drawn from patients attending all charitable, private and public drug treatment centers in the municipalities of Goiânia and Campo Grande, central-western Brazil, between August 2005 and July 2006. There were selected 851 users, 542 from 18 centers (ten to 70 patients per center) in Goiânia and 309 from eight centers (ten to 76 patients per center) in Campo Grande. All subjects were informed on the study objectives and procedures and invited to participate. The following inclusion criteria were applied: 18 years of age or more; injecting and/or non-injecting drug use; and enrollment in a drug treatment center. All patients agreed to participate in the study. Injecting drug users (IDU) were defined as those patients reporting intravenous drug use; and non-injecting drug users (NIDU) were defined as those patients who reported never using intravenous drugs and reported lifetime use of marijuana, cocaine (powder, crack, and "merla"), heroin, LSD, and ecstasy through other routes (sniffing, smoking, and ingestion). Of 851 users, 691 (81.2%) were eligible to participate in the study, of which were 102 IDU and 589 NIDU.
A standardized questionnaire based on the World Health Organization (WHO) recommendations8 was applied to all subjects and data was collected on sociodemographic characteristics (age, sex, marital status, skin color, schooling, and family income) and potential risk factors for HCV infection (route of administration and length of time of drug use, prior blood transfusion/year of first transfusion and surgery, tattoos/piercing, acupuncture, condom use, number of sexual partners, IDU partner, history of sexually transmitted disease [STD] and prior imprisonment). Then 10 ml blood was drawn from each subject and sera were stored at -20°C.
All samples were tested for HCV antibodies (anti-HCV, Hepanostika Ultra, Biomedical, China) using enzyme-linked immunosorbent assay (ELISA). Positive samples for the marker anti-HCV were confirmed by immunoblot (Bioblot HCV, Biokit, Spain).
Anti-HCV positive samples were submitted to RNA extraction, reverse transcription, and polymerase chain reaction (PCR), with primers complementary to noncoding (NC) regions of the virus genoma, as described by Ginabreda et al11 (1997). RNA HCV-positive samples were genotyped by line probe assay (LiPA - Versant HCV Genotype Assay, Innogenetics, Belgium).
The phylogenetic analysis of the NS5B region of the virus genoma was performed by confirming HCV genotypes and subtypes. cDNA samples obtained by reverse transcription were amplified by PCR with primers under the same conditions as described by Sandres-Sauné et al22 (2003). PCR products were then purified using the QIAquick Gel Extraction kit (Qiagen, GmbH, Hilden, Germany) and submitted to direct nucleotide sequencing in both directions using the BigDye Terminator kit (version 3.1, Applied Biosystems, Foster City CA, USA) and analyzed in an ABI-3730 sequencer (Applied Biosystems). The sequences obtained containing 340 nucleotides (from position 8279 to 8619 of the virus genoma) were aligned using ClustalX program.25 A phylogenetic tree was constructed with a neighbor-joining method using software Mega 2.1,14 and the Kimura 2-parameter model. Reliability of clusters of the phylogenetic tree was assessed using the bootstrap test based on 1,000 pseudoreplicates. Genotypes and subtypes of HCV samples were identified by adding in the phylogenetic analysis reference sequences representative of the main HCV genotypes/subtypes available in Genbank (referred in the phylogenetic tree by subtype, followed by the number of access to Genbank).
Data analysis was carried out using Epi Info program version 2000. Prevalences and odds ratios (OR) were calculated with 95% confidence intervals (95% CI). Risk factors with p< 0.10 in the univariate analysis were then analyzed by hierarchical logistic regression using SPSS program version 11.0 to identify potential confounders. χ2 test for association, χ2 test for tendency and Fisher's exact test were also performed. A 5% significance level was set.
The study was approved by the Research Ethics Committee of Hospital Materno Infantil (Mother-Child Hospital) (Protocol No. 004/05) in Goiânia. All subjects signed a free informed consent.
Mean age of the sample studied was 28.3 years (SD= 9.0), 88.3% were males, 64.3% single, 59.5% white, 70.2% reported up to eight years of schooling and 46.5% reported family income between two and five monthly minimum wages. Most used two or more non-injecting drugs. The main drug consumed were marijuana (82.9%), powder cocaine (59.6%), "merla" cocaine (52.8%), and crack (37.9%).
Of 691 drug users studied, anti-HCV marker was detected in 49 (7.1%) blood samples. Of these, 48 were positive by immunoblot, showing a 6.9% prevalence of anti-HCV (95% CI: 5.2;9.2) (Table 1).
RNA virus was detected in 85.4% (41/48) of anti-HCV samples reactive by PCR with primers complementary to the 5' NC region. All were genotyped by LiPA. Thirty-three samples were genotype 1, 63.4% subtype 1a, and 17.1% subtype 1b. The remaining samples (19.5%) were genotype 3, and subtype 3a (Table 1). Of 41 RNA HCV-positive samples for the 5' NC region, 25 (60.1%) were amplified and genotyped in the NS5B region. Seventeen (68%) were identified as subtype 1a, five (20%) as subtype 3a, and three (12%) as subtype 1b (Figure).
The univariate analysis showed that HCV infection was significantly associated to age, marital status, family income, route of administration and length of time of drug use, prior blood transfusion and surgery, IDU partner, and history of STD (Table 2). The multiple logistic regression analysis revealed that age over 30 years (OR= 16.0; 95% CI: 3.9;66.0) and injecting drug use (OR= 18.0; 95% CI: 6.9;47.1) were independently associated to HCV infection (Table 3).
The present study has limitations that should be considered in the interpretation of results. The number of DU and their general characteristics in the cities of Goiânia and Campo Grande are not actually known since drug use is an illicit activity. For that reason, HCV infection was only investigated among those IDU and NIDU enrolled in charitable, private, and public drug treatment centers during the study period. On the other hand, given the scarcity of epidemiological data about HCV infection among DU in the cities studied, our results provide background information for formulating policies and strategies for reducing risk and damage associated to the use of illicit drugs.
The prevalence of HCV infection found (6.9%, 95% CI: 5.2;9.2) was higher than that reported in non-drug user blood donors (1.4%, Martins et al,17 1994) in this Brazilian region. Based on other studies investigating illicit drug users in Brazil, the prevalence here estimated was similar to that reported by Bastos et al2 (2000) in the city of Rio de Janeiro (5.8%, 95% CI: 1.7;7.1) and by Carvalho et al7 (2003) in the city of São Paulo (6%, 95% CI: 2.2;14.1). But it was lower that those found in the cities of Porto Alegre (25%; 95% CI: 15.1;38.1), Belém (16%, 95% CI: 11.3;2.0) and Santos (36.2%, 95% CI: 31.9;40.4).10,19,23 This inconsistency can be explained by the greater proportion of IDU in the samples of the latter studies compared to the former ones (22%-27% versus 10%-15%).
The investigation of HCV RNA reveals those individuals who are HCV carriers, especially in high-risk groups such as drug users. In the present study, of 48 subjects with anti-HCV positive, 41 were HCV RNA-positive, showing a high rate of viremia (85.4%). This finding shows that drug users are thus major HCV carriers and potential transmitters, which is corroborated by other studies.10,13
All 41 samples HCV-RNA positive were genotyped by LiPA, and genotype 1 was found to be the most prevalent, followed by genotype 3. Similar results were demonstrated in IDU in the city of Rio de Janeiro,20 and these same genotypes are the most prevalent in Brazil,5 as well in central-western region.18 Subtypes 1a (63.4%), followed by 3a (19.5%) and 1b (17.1%) were the most predominant. The 5' NC region, as it is the most preserved in the virus genoma, could be amplified by PCR in a large number of samples genotyped. That is why the 5' NC region is often investigated for HCV detection and genotyping, especially for the clinical purpose of choosing the best therapeutic regimen for viral hepatitis C.9
A similar distribution was seen for subtypes 1a, 3a, and 1b in the phylogenetic analysis of the NS5B region (68%, 20%, and 12%, respectively). There is no inconsistency between genotypes and subtypes of 25 samples tested by both methods. Although both methods are as effective for genotyping, inconsistent results between HCV subtypes have been reported in other studies. Some authors9,15,22 believe that the NS5B region is more adequate for subtyping that the 5' NC region, which is too preserved and cannot differentiate some subtypes, especially 1a and 1b. Hence, the phylogenetic analysis of the NS5B region is more adequate to identify HCV in epidemiological studies and was used to confirm HCV genotypes and subtypes in the sample studied.
In the present study, age over 30 years was associated to HCV infection (OR=16.0; 95% CI: 3.9;66.0), which is consistent with other studies investigating illicit drug users.12,16,21 This association can be explained by higher risk of virus exposure during their lifetime.
IDU subjects were more likely to have HCV infection (OR= 18.0, 95% CI: 6.9;47.1) compared to NIDU. In addition, HCV prevalence was nearly 12-fold greater in IDU than NIDU (31.4% versus 2.7%, Table 2). Higher risk for hepatitis C infection in IDU compared to NIDU also was reported by several authors,2,7,10,13,23 which corroborates the finding of efficient HCV transmission through parenteral route.
There was seen a tendency for the association between prior blood transfusion and HCV infection. This association has been reported especially in blood transfusions before the implementation in Brazil of anti-HCV screening in blood banks in November 1993.4,6 In fact, in the present study, among 14 anti-HCV positive subjects who had prior blood transfusion, most of them took place prior to this date (data not shown), stressing the importance of anti-HCV screening in blood banks in Brazil.
It was also observed an association between HCV infection and anti-HBc (χ2= 20.2; p<0.05; data not shown), a marker of HBV exposure. This finding with potential clinical and epidemiological relevance corroborates the findings of other authors investigating drug users,21,23 and suggests common transmission forms of HBV and HCV in DU.
In conclusion, the present study evidenced high prevalence of HCV infection and subtype 1a among illicit drug users. It was also found that injecting drug use is a major risk factor for HCV infection. This data, associated to the progress to chronic infection, low response of genotype 1 to antiviral therapy and unavailability of a hepatitis C vaccine, reinforces the need for effective programs for prevention and control of hepatitis C among illicit drug users.
To Renata Carneiro Ferreira, doctorate student at the Instituto de Patologia Tropical e Saúde Pública at Universidade Federal de Goiás for her help with interviews and serological testing.
1. Alter MJ. Epidemiology of viral hepatitis C infection. World J Gastroenterol. 2007;13(17):2436-41. [ Links ]
2. Bastos FI, Lowndes CM, Castelo-Branco LR, Linhares-de-Carvalho MI, Oeleman W, Bernier F, et al. Sexual behaviour and infection rates for HIV, blood-borne and sexually transmitted infections among patients attending drug treatment centres in Rio de Janeiro, Brazil. Int J STD AIDS. 2000;11(6):383-92. DOI: 10.1258/0956462001916100 [ Links ]
3. Blackard JT, Shata MT, Shire NJ, Sherman KE. Acute hepatitis C virus infection: a chronic problem. Hepatology. 2008;47(1):321-31. DOI: 10.1002/hep.21902 [ Links ]
4. Botelho SM, Ferreira RC, Reis NR, Kozlowski AG, Carneiro MA, Teles SA, et al. E pidemiological aspects of hepatitis C virus infection among renal transplant recipients in Central Brazil. Mem Inst Oswaldo Cruz. 2008;103(5):472-6. DOI: 10.1590/S0074-02762008000500011 [ Links ]
5. Campiotto S, Pinho JRR, Carrilho FJ, Da Silva LC, Souto FJD, Spinelli V, et al. Geographic distribution of hepatitis C virus genotypes in Brazil. Braz J Med Biol Res. 2005;38(1):41-9. DOI: 10.1590/S0100-879X2005000100007 [ Links ]
6. Carneiro MA, Teles SA, Lampe E, Espírito-Santo MP, Gouveia-Oliveira R, Reis NR, et al. Molecular and epidemiological study on nosocomial transmission of HCV in hemodialysis patients in Brazil. J Med Virol. 2007;79(9):1325-33. DOI: 10.1002/jmv.20932 [ Links ]
7. Carvalho HB, Seibel SD, Burattini MN, Massad E, Reingold A. Vulnerabilidade às infecções pelo HIV, hepatites B e C e sífilis entre adolescentes infratores institucionalizados na cidade de São Paulo, Brasil. J Bras Doenças Sex Transm. 2003;15(3):41-5. [ Links ]
8. Des Jarlais DC, Perlis TE, Stimson GV, Poznyak V; WHO Phase II Drug Injection Collaborative Study Group. Using standardized methods for research on HIV and injecting drug use in developing/transitional countries: case study from the WHO Drug Injection Study Phase II. BMC Public Health. 2006;6:54. DOI: 10.1186/1471-2458-6-54 [ Links ]
9. Espírito-Santo MP, Carneiro MAS, Reis NRS, Kozlowski AG, Teles SA, Lampe E, et al. Genotyping hepatitis C virus from hemodialysis patients in Central Brazil by line probe assay and sequence analysis. Braz J Med Biol Res. 2007;40(4):545-50. DOI: 10.1590/S0100-879X2007000400013 [ Links ]
10. Galperim B, Cheinquer H, Stein A, Fonseca A, Lunge V, Ikuta N. Intranasal cocaine use does not appear to be an independent risk factor for HCV infection. Addiction. 2004;99(8):973-7. DOI: 10.1111/j.1360-0443.2004.00761.x [ Links ]
11. Ginabreda MGP, Yoshida CFT, Niel C. Genomic characterization of Brazilian hepatitis C virus genotypes 1a and 1b. Braz J Med Biol Res. 1997;30(3):339-45. DOI: 10.1590/S0100-879X1997000300006 [ Links ]
12. Howe CJ, Fuller CM, Ompad DC, Galea S, Klobin B, Thomas D, et al. Association of sex, hygiene and drug equipment sharing with hepatitis C virus infection among non-injecting drug users in New York City. Drug Alcohol Depend. 2005;79(3):389-95. DOI: 10.1016/j.drugalcdep.2005.03.004 [ Links ]
13. Jittiwutikarn J, Thongsawat S, Suriyanon V, Maneekarn N, Celentano D, Razak MH, et al. Hepatitis C infection among drug users in northern Thailand. Am J Trop Med Hyg. 2006;74(6):1111-6. [ Links ]
14. Kumar S, Tamura K, Jakobsen IB, Nei M. MEGA2: molecular evolutionarygenetics analysis software. Bioinformatics. 2001;17(12):1244-5. DOI: 10.1093/bioinformatics/17.12.1244 [ Links ]
15. Laperche S, Lunel F, Izopet J, Alain S, Dény P, Duverlie G, et al. Comparison of hepatitis C virus NS5b and 5' noncoding gene sequencing methods in a multicenter study. J Clin Microbiol. 2005;43(2):733-9. DOI: 10.1128/JCM.43.2.733-739.2005 [ Links ]
16. Macías J, Palacios RB, Claro E, Vargas J, Vergara S, Mira JA, et al. High prevalence of hepatitis C virus infection among noninjecting drug users: association with sharing the inhalation implements of crack. Liver Int. 2008;26:781-6. [ Links ]
17. Martins RBM, Vanderborght BOM, Rouzere CD, Santana CL, Santos CO, Mori DN, et al. Anti-HCV related to HCV PCR and risk factors analysis in a blood donor population of Central Brazil. Rev Inst Med Trop São Paulo. 1994;36(6):501-6. DOI: 10.1590/S0036-46651994000600005 [ Links ]
18. Martins RBM, Teles SA, Freitas NR, Motta-Castro ARC, Souto FJD, Mussi A, et al. Distribution of hepatitis C virus genotypes among blood donors from mid-west region of Brazil. Rev Inst Med Trop São Paulo. 2006;48(1):53-5. DOI: 10.1590/S0036-46652006000100012 [ Links ]
19. Monteiro MR, do Nascimento MM, Passos AD, Figueiredo JF. Hepatite C: prevalência e fatores de risco entre portadores do VIH/SIDA em Belém, Pará, na Amazônia brasileira. Rev Soc Bras Med Trop. 2004;37(Supl 2):40-6. [ Links ]
20. Oliveira MLA, Bastos FI, Telles PR, Hacker MA, Oliveira SAN, Miguel JC, Yoshida CFT. Epidemiological and genetic analyses of hepatitis C virus transmission among young/short- and long-term injecting drug users from Rio de Janeiro, Brazil. J Clin Virol. 2009;44(3):200-6. DOI: 10.1016/j.jcv.2008.12.008 [ Links ]
21. Quaglio G, Lugoboni F, Pajusco B, Sarti M, Talamini G, Lechi A, et al. Factors associated with hepatitis C virus infection in injection and noninjection drug users in Italy. Clin Infect Dis. 2003;37(1):33-40. DOI: 10.1086/375566 [ Links ]
22. Sandres-Sauné K, Deny P, Pasquier C, Thibaut V, Duverlie G, Izopet J. Determining hepatitis C genotype by analyzing the sequence of the NS5B region. J Virol Methods. 2003;109(2):187-93. DOI: 10.1016/S0166-0934(03)00070-3 [ Links ]
23. Segurado AC, Braga P, Etzel A, Cardoso MRA. Hepatitis C virus coinfection in a cohort of HIV-infected individuals from Santos, Brazil: Seroprevalence and associated factors. AIDS Patient Care STDS. 2004;18(3):135-43. DOI: 10.1089/108729104322994829 [ Links ]
24. Simmonds P, Bukh J, Combet C, Deléage G, Enomoto N, Feinstone S, et al. Consensus proposals for a unified system of nomenclature of hepatitis C virus genotypes. Hepatology. 2005;42(4):962-73. DOI: 10.1002/hep.20819 [ Links ]
25. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The CLUSTAL_X windows interface: Flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997;25(24):4876-82. DOI: 10.1093/nar/25.24.4876 [ Links ]
Regina Maria Bringel Martins
R. 235, S/N - Setor Universitário
Caixa Postal 131
74605-050 Goiânia, GO, Brasil
Research funded by the Ministério da Saúde (Brazilian Ministry of Health) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq Proc. nº 402783/2004-2).
This article underwent
the peer review process adopted for any other manuscript submitted to this journal,
with anonymity guaranteed for both authors and reviewers. Editors and reviewers
declare that there are no conflicts of interest that could affect their judgment
with respect to this article.
The authors declare that there are no conflicts of interest.