INTERNET ADDICTION AMONG ADOLESCENTS IN A WESTERN BRAZILIAN AMAZONIAN CITY

Tatiane Dalamaria Wagner de Jesus Pinto Edson dos Santos Farias Orivaldo Florencio de Souza About the authors

ABSTRACT

Objective:

Analyze the prevalence and factors associated with internet addiction in a sample of high school adolescents in Acre, a state in northern Brazil.

Methods:

A population-based cross-sectional study was conducted with 1,387 adolescents between 14 and 18 years old enrolled in high schools in the city of Rio Branco, Acre. A structured questionnaire with questions about demographics, family and behavioral patterns was applied. Internet addiction was verified using the Internet Addiction Test (IAT), with a cutoff equal to or greater than 70 points. The associated factors were identified by multiple logistic regression analyses.

Results:

The overall prevalence of Internet addiction was 10.6%. Higher dependence was observed in females. The factors associated with Internet addiction were being female, using the computer for more than two hours a day during weekdays and on the weekend, not practicing physical activities and going out to dance at nightclubs and concerts at least once a month. A protective association of reading habits in relation to Internet dependence was observed.

Conclusions:

The present study showed a high prevalence of Internet dependence, with female adolescents being more susceptible. Behavioral aspects were associated with internet dependence in a sample of adolescents from Rio Branco, Acre.

Keywords:
Addictive behavior; Leisure activities; Internet; Adolescents

RESUMO

Objetivo:

Analisar a prevalência e os fatores associados à dependência de internet em uma amostra de adolescentes do ensino médio no Acre.

Métodos:

Estudo transversal de base populacional realizado com 1.387 adolescentes entre 14 e 18 anos regularmente matriculados em instituições de ensino médio no município de Rio Branco, Acre. Questionário estruturado com questões sobre aspectos demográficos, sociais, familiares e comportamentais foi aplicado. A dependência de internet foi verificada pelo internet addiction test (IAT), com ponto de corte igual ou superior a 70. Os fatores associados foram identificados mediante regressão logística múltipla.

Resultados:

A prevalência geral para dependência de internet foi de 10,6%. Maior dependência foi evidenciada no sexo feminino. Os fatores associados à dependência de internet foram ser do sexo feminino, utilizar o computador por mais de duas horas diárias durante o meio de semana e no fim de semana, não praticar atividade física e sair por pelo menos uma vez ao mês para dançar em boates e shows. Observou-se associação protetora do hábito de leitura em relação à dependência de internet.

Conclusões:

O presente estudo evidenciou alta prevalência para dependência de internet, sendo as adolescentes do sexo feminino mais suscetíveis. Aspectos comportamentais estiveram associados à dependência de internet em uma amostra de adolescentes de Rio Branco.

Palavras-chave:
Comportamento aditivo; Atividades de lazer; Internet; Adolescente

INTRODUCTION

Nowadays, the internet is an essential part of everyday life, as it enables the fluidity necessary for the circulation of information and global communication.11. Mihajlov M, Vejmelka L. Internet Addiction: a review of the first twenty years. Psychiatr Danub. 2017;29:260-72. https://doi.org/10.24869/psyd.2017.260
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,22. Conti MA, Jardim AP, Hearst N, Cordás TA, Tavares H, Abreu CN. Avaliação da equivalência semântica e consistência interna de uma versão em português do Internet Addiction Test (IAT). Rev Psiq Clín. 2012;39:106-10. http://dx.doi.org/10.1590/S0101-60832012000300007
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Although there are benefits to this, a new pathology called internet addiction has occurred.11. Mihajlov M, Vejmelka L. Internet Addiction: a review of the first twenty years. Psychiatr Danub. 2017;29:260-72. https://doi.org/10.24869/psyd.2017.260
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,33. Kuss DJ, Griffiths MD, Karila L, Billieux J. Internet addiction: a systematic review of epidemiological research for the last decade. Curr Pharm Des. 2014;20:4026-52. https://doi.org/10.2174/13816128113199990617
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,44. Young KS. The evolution of internet addiction. Addict Behav. 2017;64:229-30. https://doi.org/10.1016/j.addbeh.2015.05.016
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As such, a fine line separates essential access to work, the teaching-learning process, social communication, and information searching with the compulsive and pathological use of the internet. Therefore, internet dependency is a new and growing problem in public health, requiring greater understanding by the scientific community in order to propose community interventions.

Several factors are associated with internet addiction, such as sociodemographic aspects related to internet use and psychosocial habits55. Jorgenson AG, Hsiao RC, Yen CF. Internet addiction and other behavioral addictions. Child Adolesc Psychiatr Clin N Am. 2016;25:509-20. https://doi.org/10.1016/j.chc.2016.03.004
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,66. Nakayama H, Mihara S, Higuchi S. Treatment and risk factors of Internet use disorders. Psychiatry Clin Neurosci. 2017;71:492-505. https://doi.org/10.1111/pcn.12493
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,77. Cerniglia L, Zoratto F, Cimino S, Laviola G, Ammaniti M, Adriani W. Internet addiction in adolescence: Neurobiological, psychosocial and clinical issues. Neurosci Biobehav Rev. 2017;76:174-84. https://doi.org/10.1016/j.neubiorev.2016.12.024
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. Some studies have reported that types of leisure activities done in one’s free time, in addition to the multiple activities performed online, are predisposing factors for internet dependence.88. Wang H, Zhou X, Lu C, Wu J, Deng X, Hong L. Problematic internet use in high school students in Guangdong Province, China. PLoS ONE. 2011;6:e19660. https://doi.org/10.1371/journal.pone.0019660
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,99. Zhou R, Fong PS, Tan P. Internet use and its impact on engagement in leisure activities in China. PloS ONE. 2014;9:e89598. https://doi.org/10.1371/journal.pone.0089598
https://doi.org/https://doi.org/10.1371/...
Specifically, systematic reviews have indicated several adverse effects of internet addiction on mental health, such as attention deficit hyperactivity disorder, depression, hostility and low self-esteem.11. Mihajlov M, Vejmelka L. Internet Addiction: a review of the first twenty years. Psychiatr Danub. 2017;29:260-72. https://doi.org/10.24869/psyd.2017.260
https://doi.org/https://doi.org/10.24869...
,55. Jorgenson AG, Hsiao RC, Yen CF. Internet addiction and other behavioral addictions. Child Adolesc Psychiatr Clin N Am. 2016;25:509-20. https://doi.org/10.1016/j.chc.2016.03.004
https://doi.org/https://doi.org/10.1016/...
,66. Nakayama H, Mihara S, Higuchi S. Treatment and risk factors of Internet use disorders. Psychiatry Clin Neurosci. 2017;71:492-505. https://doi.org/10.1111/pcn.12493
https://doi.org/https://doi.org/10.1111/...
.77. Cerniglia L, Zoratto F, Cimino S, Laviola G, Ammaniti M, Adriani W. Internet addiction in adolescence: Neurobiological, psychosocial and clinical issues. Neurosci Biobehav Rev. 2017;76:174-84. https://doi.org/10.1016/j.neubiorev.2016.12.024
https://doi.org/https://doi.org/10.1016/...

Data from the Brazilian National Household Sample Survey indicate that, in Brazil, 49.4% of people are connected to the internet, and this is mostly concentrated in the 15-17-year-old age group.1010. Brazil - Ministério do Planejamento, Desenvolvimento e Gestão. Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional por amostra de domicílio: acesso à internet e a televisão e posse de telefone móvel celular para uso pessoal 2013. Rio de Janeiro: IBGE; 2015. Thus, the aim of this study was to investigate the prevalence of internet addiction and associated factors in high school students in the municipality of Rio Branco, in the Brazilian state of Acre.

METHOD

This is a population-based, cross-sectional study with high school students in the municipality of Rio Branco, conducted in the months of May and June 2015. The study population consisted of 20,476 students enrolled in 37 high schools in the urban area of Rio Branco. To determine sample size, an expected prevalence for internet dependency of 12% was considered, as observed in high school students in China.88. Wang H, Zhou X, Lu C, Wu J, Deng X, Hong L. Problematic internet use in high school students in Guangdong Province, China. PLoS ONE. 2011;6:e19660. https://doi.org/10.1371/journal.pone.0019660
https://doi.org/https://doi.org/10.1371/...
Precision was set for a sampling error of 0.03 and a level of confidence of 95% was set. With these criteria, the study required a sample of 1,182 students. To protect the investigation from the effects of non-response, 18% was added to the sample size, taking into account operational restrictions, such as the number of researchers and the time available for data collection. The final sample size was estimated at 1,391 students.

The selection of students took place in three stages. First, five schools were selected by simple random sampling. Three schools were public and two were private. This number of schools was based on operational restrictions for data collection. In the second stage, classrooms from each school were chosen by allocation proportional to size, and students were chosen by classroom in the third stage. As inclusion criteria, students aged between 14 and 18 years and 11 months, who were regularly enrolled in a high school institution in the city of Rio Branco were considered. The exclusion criteria were pathologies that would make it impossible for students to participate in data collection without assistance, given the importance of privacy in answering the questions. The study was approved by the Research Ethics Committee of the Universidade Federal do Acre under protocol number 39594914.8.0000.5010. Before beginning data collection, the parents and adolescents signed a free and informed consent form.

A structured and self-answered questionnaire was applied to students with questions regarding demographic (gender and age), social and family (marital status, being an only child, number of true friends and number of teenagers at home), leisure activities (physical activity; going to the movies and theater, going out to dance at nightclubs and shows; and reading newspapers, magazines or books), parental control and computer usage time.

To obtain information on physical activity, the self-administered physical activity checklist was applied, and then validated by Farias Junior et al.1111. Farias Junior JC, Lopes AS, Mota J, Santos MP, Ribeiro JC, Hallal PC. Validity and reproducibility of a physical activity questionnaire for adolescents: adapting the Self-Administered Physical Activity Checklist. Rev Bras Epidemiol. 2012;15:198-210. https://doi.org/10.1590/s1415-790x2012000100018
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Using this instrument, the types of physical activity and the number of minutes engaging in physical activity per week were verified. This variable was categorized into: equal to or greater than 300 minutes, between 150 and 299 minutes, from 1 and 149 minutes, and does not practice physical activity.

According to the protocol suggested by Petroski,1212. Petroski EL. Antropometria: técnicas e padronizações. 5th ed. Jundiaí: Fontoura; 2011. body weight was measured using a digital portable scale with a maximum capacity of 150 kg and a sensitivity of 50 g, while height was measured using a portable stadiometer with a maximum extension of 2 subdivided into 0.1 cm. The variable body mass index (BMI) was used as recommended by the World Health Organization,1313. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85:660-7. https://doi.org/10.2471/blt.07.043497
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with excess weight (sum of overweight and obese individuals) determined using BMI values for age equal to or greater than 1 Z score.

The test for internet addiction was verified by the internet addiction test (IAT),1414. Young KS. Internet addiction: the emergence of a new clinical disorder. Cyber Psychol Behav. 1998;1:237-44. https://doi.org/10.1089/cpb.1998.1.237
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which was validated and adapted into the Portuguese language.22. Conti MA, Jardim AP, Hearst N, Cordás TA, Tavares H, Abreu CN. Avaliação da equivalência semântica e consistência interna de uma versão em português do Internet Addiction Test (IAT). Rev Psiq Clín. 2012;39:106-10. http://dx.doi.org/10.1590/S0101-60832012000300007
https://doi.org/http://dx.doi.org/10.159...
,1515. Pontes HM, Patrão IM, Griffiths MD. Portuguese validation of the internet addiction test: an empirical study. J Behav Addict. 2014;3:107-14. https://doi.org/10.1556/JBA.3.2014.2.4
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The test consists of 20 questions on a Likert scale ranging from 1 (rarely) to 5 (always), for the individuals to fill out themselves. Individuals with a score equal to or greater than 70 points were considered to be internet dependent.

Statistical analysis of the data was performed using the Stata program, version 10 (Stata Corp. College Station, TX, United States). The associated factors were identified in two stages. First, the independent variables that showed associations with internet dependence with p≤0.20 by the Wald test in simple logistic regression were selected to compose the final multiple model. Subsequently, using multiple logistic regression, using the step-by-step procedure with retrograde elimination, variables with p≤0.05 were selected to compose the final multiple model. The variables with a -value between 0.05 and 0.10 remained in the model as adjustment variables.

RESULTS

Of the 1,391 adolescents contacted, there were four losses due to refusal to participate in the study. Thus, 1,387 adolescents were considered in the analysis, of which 76.8% were from public schools and 23.2% were from private schools. Of these, 53.1% were female, 44.5% were between 14 and 15 years old, and 55.5% were between 16 and 18 years old.

The overall prevalence of internet addiction was 10.6%. Male students showed a lower prevalence (6.9%) of internet dependence in contrast to female students (13.9%). However, no statistical difference was identified between the ages for internet dependence.

The variables sex, true friends, use of a computer in the bedroom, times using a computer in the middle of the week and on the weekend, going to the movies or theater, going out to dance in nightclubs or shows, reading the newspaper, magazines or books, and practicing physical activity were candidates for the final multiple model (Tables 1 and 2).

Table 1
Prevalence (%) and Odds Ratio of internet dependence according to demographic, social and family variables and body mass index in high school adolescents, Rio Branco, Acre, Brazil.
Table 2
Prevalence (%) and Odds Ratio of internet dependence according to variables of leisure activities, parental control and time spent using computers in high school adolescents, Rio Branco, Acre, Brazil.

In the analysis of factors associated with internet dependence (Table 3), girls were 1.84 times more likely to be dependent on the internet than boys. Adolescents who spent more than two hours on the computer on weekdays and on the weekend showed associations of 2.39 and 2.08, respectively, with regard to internet dependence. Adolescents who did not practice physical activity were 2.27 times more likely to be dependent on the internet when compared to those who practiced more than 300 minutes per week, while adolescents who went out weekly to dance at nightclubs or shows were 3.32 times more likely to be dependent on the Internet than those who rarely or never frequented such places. The habit of reading weekly was presented as an adjustment variable in the final model of internet dependence.

Table 3
Multiple model of internet addiction in high school adolescents, Rio Branco, Acre, Brazil, described in Odds Ratio and 95% confidence interval.

DISCUSSION

In this cross-sectional population-based study in the Brazilian Amazon region with high school teenagers, a prevalence of 10.6% internet dependence was identified. Girls showed a higher prevalence of dependence in contrast to boys. The factors associated with internet dependency were use of a computer in free time for more than two hours a day, physical inactivity, and going out to dance in nightclubs and shows.

The high prevalence of internet addiction observed here may have been stimulated by the digital inclusion policy, which made free internet access available in various public places in the city of Rio Branco, including schools. Kuss et al.1616. Kuss DJ, van Rooij AJ, Shorter GW, Griffiths MD, van de Mheen D. Internet addiction in adolescents: prevalence and risk factors. Comput Hum Behav. 2013;29:1987-96. http://dx.doi.org/10.1016/j.chb.2013.04.002
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suggest that unrestricted accessibility to the internet may contribute to internet dependence.

Investigations on internet addiction have shown different prevalence levels in several countries. This variability in prevalence may be due to the numerous measurement instruments and cutoff points used to demarcate levels of dependence. In addition, the inequality in access to the internet in various locations, due to cultural diversity, may have contributed to this variation in the prevalence of internet dependence.1717. Vondráčková P, Gabrhelík R. Prevention of internet addiction: a systematic review. J Behav Addict. 2016;5:568-79. https://doi.org/10.1556/2006.5.2016.085
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Therefore, caution should be used when comparing the prevalence in studies with different methods. However, considering only research that used a cutoff point equal to or greater than 70 points in the IAT, the prevalence of internet dependence verified in the present study was higher in relation to that of students in South Korea (2.3%)1818. Choi K, Son H, Park M, Han J, Kim K, Lee B, et al. Internet overuse and excessive daytime sleepiness in adolescents. Psychiatry Clin Neurosci. 2009;63:455-62. https://doi.org/10.1111/j.1440-1819.2009.01925.x
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and Lebanon (4.2%).1919. Hawi NS. Internet addiction among adolescents in Lebanon. Comput Hum Behav. 2012;28:1044-53. https://doi.org/10.1016/j.chb.2012.01.007
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In modeling the associated factors, the female gender presented a greater association with internet dependence. Controversially, other studies show that boys are more dependent than girls.2020. Krishnamurthy S, Chetlapalli S. Internet addiction: Prevalence and risk factors: a cross-sectional study among college students in Bengaluru, the Silicon Valley of India. Indian J Public Health. 2015;59:115-21. https://doi.org/10.4103/0019-557X.157531
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,2121. Müller KW, Dreier M, Beutel ME, Duven E, Giralt S, Wölfling K. A hidden type of internet addiction? Intense and addictive use of social networking sites in adolescents. Comput Hum Behav. 2016;55:172-7. https://doi.org/10.1016/j.chb.2015.09.007
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,2222. Tang CS, Koh YW, Gan Y. Addiction to internet use, online gaming, and online social networking among young adults in China, Singapore, and the United States. Asia Pac J Public Health. 2017;29:673-82. https://doi.org/10.1177/1010539517739558
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However, the level of internet use among females has increased in recent years.2323. Yates TM, Gregor MA, Haviland MG. Child maltreatment, alexithymia, and problematic internet use in young adulthood. Cyberpsychology Behav Soc Netw. 2012;15:219-25. https://doi.org/10.1089/cyber.2011.0427
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In the present study, the time spent on a computer both during the week and over the weekend showed an association with internet dependence. Analogous information was verified in the city of Shanghai, with respect to the hours spent online on weekdays and weekends.88. Wang H, Zhou X, Lu C, Wu J, Deng X, Hong L. Problematic internet use in high school students in Guangdong Province, China. PLoS ONE. 2011;6:e19660. https://doi.org/10.1371/journal.pone.0019660
https://doi.org/https://doi.org/10.1371/...
According to studies in China and Turkey, adolescents who spent more than two hours a day on a computer were more likely to be dependent on the internet compared to those who spent less time.99. Zhou R, Fong PS, Tan P. Internet use and its impact on engagement in leisure activities in China. PloS ONE. 2014;9:e89598. https://doi.org/10.1371/journal.pone.0089598
https://doi.org/https://doi.org/10.1371/...
,2424. Sasmaz T, Oner S, Kurt AÖ, Yapici G, Yazici AE, Bugdayci R, et al. Prevalence and risk factors of internet addiction in high school students. Eur J Public Health. 2014;24:15-20. https://doi.org/10.1093/eurpub/ckt051
https://doi.org/https://doi.org/10.1093/...
Thus, spending more than two hours a day on a computer with Internet access is considered to be sedentary behavior and has the potential to have a negative impact on health.2525. Ferreira RW, Rombaldi AJ, Ricardo LI, Hallal PC, Azevedo MR. Prevalence of sedentary behavior and its correlates among primary and secondary school students. Rev Paul Pediatr. 2016;34:56-63. http://dx.doi.org/10.1016/j.rppede.2015.09.002
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Therefore, controlling adolescents’ time spent on computers is an effective method for preventing internet addiction.

Engaging in physical activity has been recommended as an important public health strategy to improve the health of children and adolescents. Nowadays, there is a decrease in physical activity and leisure time caused by computerization.2626. Valencia-Peris A, Úbeda-Colomer J, Lizandra J, Peiró-Velert C, Devís-Devís J. Active gaming prevalence and correlates by type of day in Spanish youth. J Phys Act Health. 2019;17:1-7. https://doi.org/10.1123/jpah.2018-0448
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,2727. Simons M, de Vet E, Brug J, Seidell J, Chinapaw MJ. Active and non-active video gaming among Dutch adolescents: who plays and how much? J Sci Med Sport. 2014;17:597-601. https://doi.org/10.1016/j.jsams.2013.10.250
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In conjunction with the results demonstrated in this study, research has identified an association between the lowest levels of physical activity and internet addiction in adolescents.2828. Babey SH, Hastert TA, Wolstein J. Adolescent sedentary behaviors: correlates differ for television viewing and computer use. J Adolesc Health. 2013;52:70-6. https://doi.org/10.1016/j.jadohealth.2012.05.001
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,2929. Khan MA, Shabbir F, Rajput TA. Effect of gender and physical activity on internet addiction in medical students. Pak J Med Sci. 2017;33:191-4. https://doi.org/10.12669/pjms.331.11222
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,3030. Park S. Associations of physical activity with sleep satisfaction, perceived stress, and problematic Internet use in Korean adolescents. BMC Public Health. 2014;14:1143. https://doi.org/10.1186/1471-2458-14-1143
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Also Babey et al.2828. Babey SH, Hastert TA, Wolstein J. Adolescent sedentary behaviors: correlates differ for television viewing and computer use. J Adolesc Health. 2013;52:70-6. https://doi.org/10.1016/j.jadohealth.2012.05.001
https://doi.org/https://doi.org/10.1016/...
state that teenagers are likely to replace physical activity in their spare time with time on the computer.

The teenagers who go out to dance in nightclubs or shows showed greater dependence on the internet. This result corroborates the argument of Zhou et al.,99. Zhou R, Fong PS, Tan P. Internet use and its impact on engagement in leisure activities in China. PloS ONE. 2014;9:e89598. https://doi.org/10.1371/journal.pone.0089598
https://doi.org/https://doi.org/10.1371/...
who inferred that internet usage contributes to maintaining or increasing social commitments. Usually, teenagers attend shows and nightclubs as part of a social time. Thus, it is believed that they experience real time in connection with the virtual space of the internet, using it for their personal promotion in search of self-affirmation.

As an adjustment variable in the modeling, the weekly habit of reading a newspaper, magazine or book is an indicator of protection against internet dependence. In this sense, Sasmaz et al.2424. Sasmaz T, Oner S, Kurt AÖ, Yapici G, Yazici AE, Bugdayci R, et al. Prevalence and risk factors of internet addiction in high school students. Eur J Public Health. 2014;24:15-20. https://doi.org/10.1093/eurpub/ckt051
https://doi.org/https://doi.org/10.1093/...
affirmed that the construction of a healthy living environment through the control of computer use and internet access, and the promotion of book reading, favor the prevention and treatment of internet addiction in adolescents.

There are some limitations in this study that should be highlighted. First, the cross-sectional design used in the present study made it impossible to identify the causality of factors associated with internet dependence. Second, the data were obtained from a self-administered questionnaire by the adolescents, with no complementary information from parents or other informants.

In conclusion, the present study showed a prevalence of 10.6% for internet addiction in a sample of high school adolescents in Acre. Female adolescents were more susceptible to internet addiction when compared to male adolescents. Time spent on the computer and physical inactivity were major factors for internet dependence. From the leisure time activities, the habit of reading proved to be indicative of being protective for internet dependence. On the other hand, attending shows and nightclubs was positively associated with internet dependence.

In view of this evidence, for the prevention of internet addiction in schoolchildren, implementing strategies aimed at reducing internet time and computer use at school and in a social-family context are recommended. Concomitantly, encouraging the participation in physical activities and in reading newspapers, magazines and books is suggested.

REFERENCES

Funding

  • The research project was funded by the Research Support Foundation of the State of Acre (Fundação de Amparo à Pesquisa do Estado do Acre - FAPAC) (015/2013).

Publication Dates

  • Publication in this collection
    03 July 2020
  • Date of issue
    2021

History

  • Received
    30 July 2019
  • Accepted
    21 Oct 2019
  • Published
    26 June 2020
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