Prevalence of ultra-processed food, alcohol and tobacco consumption and chronic non-communicable diseases in Rio Branco, capital city of the state of Acre, Brazil, 2019: comparative analysis of two epidemiological surveys

Lima, Yara de Moura Magalhães; Martins, Fernanda Andrade; Ramalho, Alanderson Alves

doi:10.1590/s1679-49742022000100023

Abstract

Objective

To describe, in a comparative manner, the prevalence of chronic non-communicable diseases and ultra-processed food, alcohol and tobacco consumption, estimated by the Chronic Disease Risk and Protective Factors Surveillance Telephone Survey (Vigitel) and National Health Survey (PNS), in Rio Branco, capital city of the state of Acre, Brazil.

Methods

This was a cross-sectional study on sociodemographic, health and lifestyle data from surveys conducted in 2019. Prevalence and 95% confidence intervals (95%CI) were described, and percentage difference was calculated.

Results

Of the 3,037 individuals assessed, similar prevalence, with difference between Vigitel (60.3%; 95%CI 56.2;64.3) and PNS (70.8%; 95%CI 67.4;73.9) regarding people of Brown race/skin color was found. In the stratification by sex, it could be seen percentage difference between the surveys, regarding obesity (male= 6.5%; female= 0.4%), smoking (male= 4.0%; female= -1.5%) and alcohol abuse (male= 6.9%; female= -2.5%), although with overlapping 95%CI.

Conclusion

The estimates assessed in both surveys were similar.

Keywords:
Population Surveys; Cross-sectional Studies; Epidemiological Monitoring; Chronic Disease; Prevalence

Research contributionMain results

Similar prevalence of ultra-processed food, alcohol and tobacco consumption and non-communicable chronic diseases was identified when comparing Vigitel and the National Health Survey in Rio Branco, state of Acre.

Implications for services

Due to absence of face-to-face surveys in remote regions with low landline coverage, such as Rio Branco, telephone surveys can be useful for monitoring actions and improving case and service management.

Perspectives

Conducting new research, which compares regions with low landline coverage with those with wide coverage, can help elucidate the validity of chronic disease monitoring measures by means of telephone survey.

Introduction

Chronic non-communicable diseases (NCDs) are an important public health problem worldwide. In Brazil, in addition to compromising the quality of life of a significant portion of the population and contributing to health service overload, NCDs accounted for approximately 70% of deaths in 2016. Population surveys, such as the Chronic Disease Risk and Protective Factors Surveillance Telephone Survey (Vigitel) and the National Health Survey (PNS), help in the monitoring of NCDs in Brazilian municipalities, although they present relevant methodological differences.¹1. Malta DC, Andrade SSCA, Oliveira TP, Moura L, Prado RR, Souza MFM. Probabilidade de morte prematura por doenças crônicas não transmissíveis, Brasil e regiões, projeções para 2025. Rev Bras Epidemiol. 2019;22: e190030. doi: 10.1590/1980-549720190030
https://doi.org/10.1590/1980-54972019003...

2. Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional de saúde: 2019: percepção do estado de saúde, estilos de vida, doenças crônicas e saúde bucal: Brasil e grandes regiões. 2. ed. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. 89 p. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101748.pdf
https://biblioteca.ibge.gov.br/visualiza... ^-³3. Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Departamento de Análise em Saúde e Vigilância de Doenças Não Transmissíveis. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2019. Brasília: Ministério da Saúde; 2020 [citado 26 mai 2021]. 137 p. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2019_vigilancia_fatores_risco.pdf
https://bvsms.saude.gov.br/bvs/publicaco...

The PNS was a population-based survey, using face-to-face data collection, while Vigitel was conducted by telephone and, therefore, implied lower cost and operational complexity.

In the municipality of Rio Branco, capital city of the state of Acre - one of the Brazilian capitals with the lowest landline coverage - there are concerns about the representativeness of Vigitel data and possible bias resulting from this limitation. However, the comparative assessment of the databases of both surveys can contribute to a better understanding of the methodological problems in these studies in the municipal context.⁴4. Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional por amostra de domicílios contínua [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2019 [citado 25 mai 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/ac/pesquisa/10070/62888?localidade2=120040
https://cidades.ibge.gov.br/brasil/ac/pe...

The objective of this study was to compare the prevalence of NCDs and ultra-processed foods, alcohol and tobacco consumption, estimated by Vigitel and PNS in Rio Branco, state of Acre, Brazil.

Methods

This was a cross-sectional study with secondary data retrieved from Vigitel and PNS in 2019, made available by the Ministry of Health, with open access, in their respective websites.⁵5. Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Departamento de Informação e Análise Epidemiológica. Vigitel [Internet]. Brasília: Ministério da Saúde; 2020 [citado 27 mai 2021]. Disponível em: http://svs.aids.gov.br/download/Vigitel/
http://svs.aids.gov.br/download/Vigitel... ^,⁶6. Instituto Brasileiro de Geografia e Estatística. Estatísticas [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 25 mai 2021]. Disponível em: https://www.ibge.gov.br/estatisticas/downloads-estatisticas.html
https://www.ibge.gov.br/estatisticas/dow... Both databases were accessed on May 4, 2021.

Rio Branco is located in the Northern region of Brazil and it is the leading financial, corporate, political and cultural center in the state of Acre, with a high human development index (HDI= 0.727), according to the last Atlas of Human Development in Brazil, in 2010.⁷7. Instituto Brasileiro de Geografia e Estatística. Cidades e Estados: Rio Branco [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/ac/rio-branco/panorama
https://cidades.ibge.gov.br/brasil/ac/ri... ^,⁸8. Programa das Nações Unidas para o Desenvolvimento Brasil. Instituto de Pesquisa Econômica Aplicada. Fundação João Pinheiro. Atlas do Desenvolvimento Humano no Brasil [Internet]. Brasília: Programa das Nações Unidas para o Desenvolvimento Brasil; 2020 [citado 27 mai 2021]. Disponível em: http://www.atlasbrasil.org.br/ranking
http://www.atlasbrasil.org.br/ranking... In 2020, Rio Branco had a population of 413,418 inhabitants,²2. Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional de saúde: 2019: percepção do estado de saúde, estilos de vida, doenças crônicas e saúde bucal: Brasil e grandes regiões. 2. ed. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. 89 p. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101748.pdf
https://biblioteca.ibge.gov.br/visualiza... 46.2% of the total population of the state in the period, and occupied a territory of 8,835,154 km². In 2019, 91.8% of the municipality's population lived in the urban area and, according to the 2010 Demographic Census, the schooling rate in the age group 6 to 14 was 95.1%.⁷7. Instituto Brasileiro de Geografia e Estatística. Cidades e Estados: Rio Branco [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/ac/rio-branco/panorama
https://cidades.ibge.gov.br/brasil/ac/ri... ^,⁹9. Secretaria de Estado de Saúde (Acre). Plano estadual de saúde, 2020-2023. Rio Branco: Secretaria de Estado de Saúde; 2020. Regarding health indicators, the infant mortality rate was 11.1 deaths per 1,000 live births in 2019. In 2020, Rio Branco had 837 health facilities and of these, 232 were within the Brazilian National Health System (SUS).⁷7. Instituto Brasileiro de Geografia e Estatística. Cidades e Estados: Rio Branco [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/ac/rio-branco/panorama
https://cidades.ibge.gov.br/brasil/ac/ri... ^,¹⁰10. Ministério da Saúde (BR). Cadastro Nacional de Estabelecimentos de Saúde [Internet]. Brasília: Ministério da Saúde; 2020 [citado 26 mai 2021]. Disponível em: http://cnes.datasus.gov.br/
http://cnes.datasus.gov.br...

Vigitel is a telephone survey, conducted in two stages: first, (i) a systematic draw of local landline telephone, and then, (ii) the identification of the lines that were drawn, regarding their eligibility. Business and inactive phone lines or those that did not answer the phone call, were not eligible. Thus, a probabilistic sample of the adult population (≥18 years) residing in Brazilian capitals was obtained. With regard to the PNS, it is a household survey, conducted in three stages: (i) a draw of census tracts [primary sampling units (PSU)], (ii) households (secondary units) and (iii) a resident aged 15 years or older (tertiary units). Further information about the PNS method is available in another publication.²2. Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional de saúde: 2019: percepção do estado de saúde, estilos de vida, doenças crônicas e saúde bucal: Brasil e grandes regiões. 2. ed. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. 89 p. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101748.pdf
https://biblioteca.ibge.gov.br/visualiza...

Respondents aged 18 years or older were eligible for this study. Those under 18 years of age, pregnant women and women who did not know if they were pregnant were excluded. In addition, the individuals who were taking part in both surveys (Vigitel and PNS) but did not have complete records, were excluded.

The sociodemographic variables analyzed were sex (female; male), age group (in years: 18 to 24; 25 to 39; 40 to 59; 60 or older), race/skin color (White; Black; Asian; Brown; Indigenous) and schooling (in years of study: 0 to 8; 9 to 11; 12 and more). The variables related to health status were self-reported, based on a previous diagnosis of diabetes mellitus (no; yes), hypertension (no; yes), overweight (no; yes) and obesity (no; yes), with a physician confirmation. The lifestyle variables were smoking (no; yes), alcohol abuse (no; yes), ultra-processed foods (no; yes) and soft drink (no; yes) (Box 1) consumption.

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Box 1
The National Health Survey and Chronic Disease Risk and Protective Factors Surveillance Telephone Survey variables, 2019

Data were analyzed using a statistical software for analyzing complex samples, the Statistical Package for the Social Sciences (SPSS), version 26.0. The overall prevalence of sociodemographic, health and lifestyle characteristics, stratified by sex, and 95% confidence intervals (95%CI), were estimated. The prevalence of Vigitel was weighted (rake method) using estimates of sex, age and education of the population, for the municipality of Rio Branco in 2019, aiming to standardize the distribution of the interviewed population with that estimated by the Demographic Census.³3. Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Departamento de Análise em Saúde e Vigilância de Doenças Não Transmissíveis. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2019. Brasília: Ministério da Saúde; 2020 [citado 26 mai 2021]. 137 p. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2019_vigilancia_fatores_risco.pdf
https://bvsms.saude.gov.br/bvs/publicaco... The PNS estimates were weighted by means of household weight, adjustment for non-response, sex and distribution of the total population by sex and age. The differences were calculated in percentage points, considering the proportion of each sample, Vigitel and PNS, and this difference was observed when there was no overlapping 95%CI.¹1. Malta DC, Andrade SSCA, Oliveira TP, Moura L, Prado RR, Souza MFM. Probabilidade de morte prematura por doenças crônicas não transmissíveis, Brasil e regiões, projeções para 2025. Rev Bras Epidemiol. 2019;22: e190030. doi: 10.1590/1980-549720190030
https://doi.org/10.1590/1980-54972019003... ^,¹¹11. Mendes GFF, Häfele V, Blumenberg C, Werneck AO, Radicchi MR, Coll CVN, et al. Comparação das estimativas de atividade física e comportamento sedentário em adultos brasileiros no Vigitel e PNS, Brasil, 2013. Rev Bras Ativ Fis Saúde. 2018; 23:e0062. doi: 10.12820/rbafs.23e0062
https://doi.org/10.12820/rbafs.23e0062... ^,¹²12. Malta DC, Iser BPM, Santos MAS, Andrade SSA, Stopa SR, Bernal RTI, et al. Estilos de vida nas capitais brasileiras segundo a Pesquisa Nacional de Saúde e o Sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas Não Transmissíveis por Inquérito Telefônico (Vigitel), 2013. Rev Bras Epidemiol. 2015;18 (Supl 2):68-82. doi: 10.1590/1980-5497201500060007
https://doi.org/10.1590/1980-54972015000...

The secondary data used in this article are in the public domain, made available by the Ministry of Health in an unrestricted manner and without personal identification, therefore it was not necessary to submit the research project to a Research Ethics Committee.

RESULTS

A total of 4,262 individuals (2,829 from Vigitel and 1,433 from PNS) were considered eligible. Of these, 3,037 individuals aged 18 years or older who had completed the interview (1,812 from Vigitel and 1,225 from PNS) were included in this study. 52.4% (95%CI 48.3;56.5) in Vigitel and 53.3% (95%CI 48.9;57.7) in PNS were female, and it could be seen a difference in the prevalence of -0.9%, with overlapping 95%CI (Table 1).

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Table 1
Prevalence of chronic non-communicable diseases and ultra-processed food, alcohol and tobacco consumption among the adult population (n=3,037), according to the National Health Survey and the Chronic Disease Risk and Protective Factors Surveillance Telephone Survey, Rio Branco, state of Acre, Brazil, 2019

There was a difference between the surveys regarding the prevalence of race/skin color. The prevalence of people of mixed race/skin color was lower in Vigitel (60.3%; 95%CI 56.2;64.3), compared to that found in PNS (70.8%; 95%CI 67.4;73.9). There was no difference between the prevalence estimated by the surveys regarding the other sociodemographic variables such as health and lifestyle, and there was no overlapping of 95%CI values.

When the variables were stratified by sex, no differences in prevalence between Vigitel and PNS were observed in any of the variables investigated (Table 2). Although there was overlapping 95%CI, the difference in the prevalence of obesity between the two surveys was 3.2%, and it could be seen prevalence of 6.5% among males and 0.4% among females.

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Table 2
Prevalence of chronic non-communicable diseases and ultra-processed food, alcohol and tobacco consumption stratified by sex among the adult population (n=3,037), according to the National Health Survey and the Chronic Disease Risk and Protective Factors Surveillance Telephone Survey, Rio Branco, state of Acre, Brazil, 2019

The differences in the prevalence of smoking and alcohol abuse, between Vigitel and PNS surveys, were 4.0% and 6.9%, in males, and -1.5% and -2.5% in females, respectively.

DISCUSSION

The analysis of 2019 Vigitel and PNS data showed that the prevalence related to NCDs, ultra-processed food consumption, alcohol abuse and smoking were similar, with overlapping 95%CI for the variables analyzed. Only the comparison of the prevalence of the race/skin color indicator showed a difference between the two surveys in relation to participants of Brown race/skin color, possibly related to difficulties regarding self-perception and self-declaration of this characteristic.¹³13. Piza E, Rosemberg F. Cor nos censos brasileiros. Rev USP. 1999;40:122-37. doi: 10.11606/issn.2316-9036.v0i40p122-137
https://doi.org/10.11606/issn.2316-9036....

Overlapping confidence interval for the prevalence of overweight and obesity suggests that there are no differences in the comparison between the two surveys, and corroborates studies that suggest self-reported weight and height as valid measures to determine nutritional status.¹⁴14. Moreira NF, Luz VG, Moreira CC, Pereira RA, Sichieri R, Ferreira MG, et al. Peso e altura autorreferidos são medidas válidas para determinar o estado de peso: resultados da Pesquisa Nacional de Saúde (PNS 2013). Cad Saude Publica. 2018;34(5): e00063917. doi: 10.1590/0102-311X00063917
https://doi.org/10.1590/0102-311X0006391... ^,¹⁵15. Hodge JM, Shah R, McCullough ML, Gapstur SM, Patel AV. Validation of self-reported height and weight in a large, nationwide cohort of U.S. adults. PLos ONE. 2020;15(4):1-11. doi: 10.1371/journal.pone.0231229
https://doi.org/10.1371/journal.pone.023...

We did not observe any differences between the prevalence of smoking and alcohol abuse, in this study. However, other investigations suggest that, because it is a survey, in which there is no eye contact, respondents may feel more comfortable answering sensitive questions such as those related to the consumption of licit drugs.¹⁶16. Barros MBA. Perfil do consumo de bebidas alcoólicas: diferenças sociais e demográficas no município de Campinas, Estado de São Paulo, Brasil, 2003. Epidemiol Serv Saude. 2008; 17(4):259-70. doi: 10.5123/S1679-49742008000400003
https://doi.org/10.5123/S1679-4974200800... ^,¹⁷17. Malta DC, Iser BPM, Sá NNB, Yokota RTC, Moura L, Claro RM, et al. Tendências temporais no consumo de tabaco nas capitais brasileiras, segundo dados do VIGITEL, 2006 a 2011. Cad Saude Publica. 2013;29(4):812-22. doi: 10.1590/S0102-311X2013000400018
https://doi.org/10.1590/S0102-311X201300...

The similarities identified in the prevalence of ultra-processed food and soft drink consumption, between both surveys, and in the prevalence of most of the variables evaluated in this study, are similar to those of another study that analyzed data from 2013 Vigitel and PNS surveys,¹²12. Malta DC, Iser BPM, Santos MAS, Andrade SSA, Stopa SR, Bernal RTI, et al. Estilos de vida nas capitais brasileiras segundo a Pesquisa Nacional de Saúde e o Sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas Não Transmissíveis por Inquérito Telefônico (Vigitel), 2013. Rev Bras Epidemiol. 2015;18 (Supl 2):68-82. doi: 10.1590/1980-5497201500060007
https://doi.org/10.1590/1980-54972015000... when the variables related to health and lifestyle in Brazilian capitals were compared.

This study has some limitations with regard to the method adopted by each of the surveys, this is the reason why the comparisons made are subject to possible biases of information and selection. There may be selection bias regarding Vigitel data, considering the need for landline coverage. Furthermore, it is worth highlighting the possibility of information bias due to the way Vigitel data was collected, by means of telephone interview, compared to PNS data collection. However, weighting methods were used and the differences in the information between the surveys showed overlapping 95%CI, and it can be inferred that telephone survey results were similar to those of the face-to-face survey. These findings corroborate evidence from other studies, which did not observe statistical differences in the comparison of parameter estimation, based on telephone and face-to-face surveys, of chronic diseases such as hypertension and diabetes mellitus, and sociodemographic variables such as sex, age (in years) and schooling.¹⁸18. Francisco PMSB, Barros MBA, Segri NJ, Alves MCGP, Cesar CLG, Malta DC. Comparação de estimativas para o auto-relato de condições crônicas entre inquérito domiciliar e telefônico - Campinas (SP), Brasil. Rev Bras Epidemiol. 2011;14(Supl 1):5-15. doi: 10.1590/S1415-790X2011000500002
https://doi.org/10.1590/S1415-790X201100... ^,¹⁹19. Bernal RTI, Malta DC, Morais Neto OL, Claro RM, Mendoça BCA, Oliveira ACC, et al. Vigitel-Aracaju, Sergipe, 2008: efeitos da pós-estratificação na correção de vícios decorrentes da baixa cobertura de domicílios com telefone fixo. Rev Bras Epidemiol. 2014;17(1):163-74. doi: 10.1590/1415-790X201400010013ENG
https://doi.org/10.1590/1415-790X2014000...

Estimates of the prevalence of NCDs, ultra-processed food consumption, alcohol abuse and smoking in Rio Branco, state of Acre, in 2019, overlapped in both the Vigitel and PNS suggesting that even for the most distant regions from large centers and with low landline coverage such as the municipality of Rio Branco, telephone surveys may be a more cost-effective option when compared to face-to-face surveys.

References

¹
Malta DC, Andrade SSCA, Oliveira TP, Moura L, Prado RR, Souza MFM. Probabilidade de morte prematura por doenças crônicas não transmissíveis, Brasil e regiões, projeções para 2025. Rev Bras Epidemiol. 2019;22: e190030. doi: 10.1590/1980-549720190030
» https://doi.org/10.1590/1980-549720190030
²
Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional de saúde: 2019: percepção do estado de saúde, estilos de vida, doenças crônicas e saúde bucal: Brasil e grandes regiões. 2. ed. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. 89 p. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101748.pdf
» https://biblioteca.ibge.gov.br/visualizacao/livros/liv101748.pdf
³
Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Departamento de Análise em Saúde e Vigilância de Doenças Não Transmissíveis. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2019. Brasília: Ministério da Saúde; 2020 [citado 26 mai 2021]. 137 p. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2019_vigilancia_fatores_risco.pdf
» https://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2019_vigilancia_fatores_risco.pdf
⁴
Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional por amostra de domicílios contínua [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2019 [citado 25 mai 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/ac/pesquisa/10070/62888?localidade2=120040
» https://cidades.ibge.gov.br/brasil/ac/pesquisa/10070/62888?localidade2=120040
⁵
Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Departamento de Informação e Análise Epidemiológica. Vigitel [Internet]. Brasília: Ministério da Saúde; 2020 [citado 27 mai 2021]. Disponível em: http://svs.aids.gov.br/download/Vigitel/
» http://svs.aids.gov.br/download/Vigitel
⁶
Instituto Brasileiro de Geografia e Estatística. Estatísticas [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 25 mai 2021]. Disponível em: https://www.ibge.gov.br/estatisticas/downloads-estatisticas.html
» https://www.ibge.gov.br/estatisticas/downloads-estatisticas.html
⁷
Instituto Brasileiro de Geografia e Estatística. Cidades e Estados: Rio Branco [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020 [citado 26 mai 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/ac/rio-branco/panorama
» https://cidades.ibge.gov.br/brasil/ac/rio-branco/panorama
⁸
Programa das Nações Unidas para o Desenvolvimento Brasil. Instituto de Pesquisa Econômica Aplicada. Fundação João Pinheiro. Atlas do Desenvolvimento Humano no Brasil [Internet]. Brasília: Programa das Nações Unidas para o Desenvolvimento Brasil; 2020 [citado 27 mai 2021]. Disponível em: http://www.atlasbrasil.org.br/ranking
» http://www.atlasbrasil.org.br/ranking
⁹
Secretaria de Estado de Saúde (Acre). Plano estadual de saúde, 2020-2023. Rio Branco: Secretaria de Estado de Saúde; 2020.
¹⁰
Ministério da Saúde (BR). Cadastro Nacional de Estabelecimentos de Saúde [Internet]. Brasília: Ministério da Saúde; 2020 [citado 26 mai 2021]. Disponível em: http://cnes.datasus.gov.br/
» http://cnes.datasus.gov.br
¹¹
Mendes GFF, Häfele V, Blumenberg C, Werneck AO, Radicchi MR, Coll CVN, et al. Comparação das estimativas de atividade física e comportamento sedentário em adultos brasileiros no Vigitel e PNS, Brasil, 2013. Rev Bras Ativ Fis Saúde. 2018; 23:e0062. doi: 10.12820/rbafs.23e0062
» https://doi.org/10.12820/rbafs.23e0062
¹²
Malta DC, Iser BPM, Santos MAS, Andrade SSA, Stopa SR, Bernal RTI, et al. Estilos de vida nas capitais brasileiras segundo a Pesquisa Nacional de Saúde e o Sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas Não Transmissíveis por Inquérito Telefônico (Vigitel), 2013. Rev Bras Epidemiol. 2015;18 (Supl 2):68-82. doi: 10.1590/1980-5497201500060007
» https://doi.org/10.1590/1980-5497201500060007
¹³
Piza E, Rosemberg F. Cor nos censos brasileiros. Rev USP. 1999;40:122-37. doi: 10.11606/issn.2316-9036.v0i40p122-137
» https://doi.org/10.11606/issn.2316-9036.v0i40p122-137
¹⁴
Moreira NF, Luz VG, Moreira CC, Pereira RA, Sichieri R, Ferreira MG, et al. Peso e altura autorreferidos são medidas válidas para determinar o estado de peso: resultados da Pesquisa Nacional de Saúde (PNS 2013). Cad Saude Publica. 2018;34(5): e00063917. doi: 10.1590/0102-311X00063917
» https://doi.org/10.1590/0102-311X00063917
¹⁵
Hodge JM, Shah R, McCullough ML, Gapstur SM, Patel AV. Validation of self-reported height and weight in a large, nationwide cohort of U.S. adults. PLos ONE. 2020;15(4):1-11. doi: 10.1371/journal.pone.0231229
» https://doi.org/10.1371/journal.pone.0231229
¹⁶
Barros MBA. Perfil do consumo de bebidas alcoólicas: diferenças sociais e demográficas no município de Campinas, Estado de São Paulo, Brasil, 2003. Epidemiol Serv Saude. 2008; 17(4):259-70. doi: 10.5123/S1679-49742008000400003
» https://doi.org/10.5123/S1679-49742008000400003
¹⁷
Malta DC, Iser BPM, Sá NNB, Yokota RTC, Moura L, Claro RM, et al. Tendências temporais no consumo de tabaco nas capitais brasileiras, segundo dados do VIGITEL, 2006 a 2011. Cad Saude Publica. 2013;29(4):812-22. doi: 10.1590/S0102-311X2013000400018
» https://doi.org/10.1590/S0102-311X2013000400018
¹⁸
Francisco PMSB, Barros MBA, Segri NJ, Alves MCGP, Cesar CLG, Malta DC. Comparação de estimativas para o auto-relato de condições crônicas entre inquérito domiciliar e telefônico - Campinas (SP), Brasil. Rev Bras Epidemiol. 2011;14(Supl 1):5-15. doi: 10.1590/S1415-790X2011000500002
» https://doi.org/10.1590/S1415-790X2011000500002
¹⁹
Bernal RTI, Malta DC, Morais Neto OL, Claro RM, Mendoça BCA, Oliveira ACC, et al. Vigitel-Aracaju, Sergipe, 2008: efeitos da pós-estratificação na correção de vícios decorrentes da baixa cobertura de domicílios com telefone fixo. Rev Bras Epidemiol. 2014;17(1):163-74. doi: 10.1590/1415-790X201400010013ENG
» https://doi.org/10.1590/1415-790X201400010013ENG

Publication Dates

Publication in this collection
15 Apr 2022
Date of issue
2022

History

Received
21 July 2021
Accepted
07 Jan 2022

Este é um artigo publicado em acesso aberto sob uma licença Creative Commons

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» https://doi.org/10.12820/rbafs.23e0062

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» https://doi.org/10.1590/1980-5497201500060007

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» https://doi.org/10.11606/issn.2316-9036.v0i40p122-137

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» https://doi.org/10.1590/0102-311X00063917

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Hodge JM, Shah R, McCullough ML, Gapstur SM, Patel AV. Validation of self-reported height and weight in a large, nationwide cohort of U.S. adults. PLos ONE. 2020;15(4):1-11. doi: 10.1371/journal.pone.0231229
» https://doi.org/10.1371/journal.pone.0231229

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Barros MBA. Perfil do consumo de bebidas alcoólicas: diferenças sociais e demográficas no município de Campinas, Estado de São Paulo, Brasil, 2003. Epidemiol Serv Saude. 2008; 17(4):259-70. doi: 10.5123/S1679-49742008000400003
» https://doi.org/10.5123/S1679-49742008000400003

[17] ¹⁷
Malta DC, Iser BPM, Sá NNB, Yokota RTC, Moura L, Claro RM, et al. Tendências temporais no consumo de tabaco nas capitais brasileiras, segundo dados do VIGITEL, 2006 a 2011. Cad Saude Publica. 2013;29(4):812-22. doi: 10.1590/S0102-311X2013000400018
» https://doi.org/10.1590/S0102-311X2013000400018

[18] ¹⁸
Francisco PMSB, Barros MBA, Segri NJ, Alves MCGP, Cesar CLG, Malta DC. Comparação de estimativas para o auto-relato de condições crônicas entre inquérito domiciliar e telefônico - Campinas (SP), Brasil. Rev Bras Epidemiol. 2011;14(Supl 1):5-15. doi: 10.1590/S1415-790X2011000500002
» https://doi.org/10.1590/S1415-790X2011000500002

[19] ¹⁹
Bernal RTI, Malta DC, Morais Neto OL, Claro RM, Mendoça BCA, Oliveira ACC, et al. Vigitel-Aracaju, Sergipe, 2008: efeitos da pós-estratificação na correção de vícios decorrentes da baixa cobertura de domicílios com telefone fixo. Rev Bras Epidemiol. 2014;17(1):163-74. doi: 10.1590/1415-790X201400010013ENG
» https://doi.org/10.1590/1415-790X201400010013ENG

Variables	Questions
Variables	Vigitel/2019^a	PNS/2019^b	Comparison
Sociodemographic
Sex	Sex:1 ( ) Male / 2 ( ) Female	Sex:1 ( ) Male/ 2 ( ) Female	Similar questions
Age	How old are you? (you must be ≥18 years old and <150) ____ years old.	Age (calculated based on date of birth).	Similar questions
Age	The variable was re-coded according to age in years.	The variable was re-coded according to age in years.	Similar questions
Race/skin color	What is your race/skin color?	Race or skin color?	Similar questions
	1 ( ) White 2 ( ) Black	1 ( ) White 2 ( ) Black
	3 ( ) Asian 4 ( ) Brown	3 ( ) Asian 4 ( ) Brown
	5 ( ) Indigenous	5 ( ) Indigenous
Interviewee’s schooling	Schooling based on the following questions:	What is your major?	.
	Up to which grade or level did you study?	What grade level/ semester are you in?	Vigitel database includes an educational indicator, with the following categories, in years of study: 0 to 8; 9 to 11; 12 and over. For the construction of this indicator in the PNS, the aforementioned questions were used. and based on them, a variable 'years of study' was created. Thus, it was possible to categorize it for schooling, consistent with Vigitel.
	1 ( ) Primary School	What was the highest level of education/course you attended?
	2 ( ) Middle School Entrance Examination	How long did this course last?
	3 ( ) Middle School	What was the last grade level/semester you completed, and was approved, in this course?
	4 ( ) Elementary Education or Supplementary Elementary Education
	5 ( ) Standard High School or Technical High School or Scientific High School or Supplementary High School Education
	6 ( ) Higher Education
	7 ( ) Postgraduate Education (Specialization, Master’s Degree, Doctoral Degree)
	8 ( ) Never studied
	What was the highest school grade you finished?
	1^st ( ) 2^nd ( ) 3^rd ( ) 4^th ( )
	5^th ( ) 6^th ( ) 7^th ( ) 8^th or above
	Are you currently taking a course/attending school or taking someone to do a course/attend school?
	1 ( ) Yes / 2 ( ) No
Health
Diabetes mellitus	Has a doctor ever told you that you have diabetes?	Has any doctor ever given you a diagnosis of diabetes mellitus?		Similar questions
Diabetes mellitus	1 ( ) Yes / 2 ( ) No	1 ( ) Yes / 2 ( ) No		Similar questions
Arterial hypertension	Has a doctor ever told you that you have hypertension?	Has any doctor ever given you a diagnosis of Arterial hypertension?	Similar questions
Arterial hypertension	1 ( ) Yes / 2 ( ) No	1 ( ) Yes / 2 ( ) No	Similar questions
Overweight and obesity	Do you know how much you weight (even if it is an approximate value )? (only ≥30 kg and <300 kg) ____ kg are accepted	Height, first measurement: ____ cm; height, second measurement: ____ cm;	Vigitel database includes an overweight indicator, being considered as BMI >25kg/m² and obesity >30kg/m². For the construction of this indicator in the PNS, the variables 'final weight, in kg' and 'final height, in cm' were used, based on the questions presented, and based on them the 'BMI' and the overweight indicator were calculated, being considered as BMI >25kg/m² and obesity >30kg/m².
Overweight and obesity	Do you know your height? (only ≥1.20 m and <2.20 m) ____ m ____ cm are accepted	Weight, first measurement: ____ kg; weight, second measurement: ____ kg;
Lifestyle
Smoking	Do you currently smoke?	Do you currently smoke any tobacco products?	Similar questions
	1 ( ) Yes, every day	1 ( ) Yes, every day
	2 ( ) Yes, but not every day	2 ( ) Yes, but not every day
	3 ( ) No	3 ( ) Do not smoke currently
Alcohol abuse	For women: in the last 30 days, did you consume four or more doses of alcoholic drinks on a single occasion? (four doses of alcoholic drinks are equivalent to four cans of beer, four glasses of wine or four doses of cachaça, whisky or any other distilled alcoholic liquor) (only for women)	In the last 30 days, did you consume five or more doses of alcoholic drinks on a single occasion? (one dose of alcoholic drink is equivalent to one can of beer, one glass of wine or one dose of cachaça, whisky or any other distilled alcoholic liquor)	The PNS considers five or more doses for both sexes.
	1 ( ) Yes / 2 ( ) No	1 ( ) Yes / 2 ( ) No
	For men: in the last 30 days, did you consume five or more doses of alcoholic drinks on a single occasion? (five doses of alcoholic drinks are equivalent to five cans of beer, five glasses of wine or five doses of cachaça, whisky or any other distilled liquor)
	1 ( ) Yes / 2 ( ) No
Ultra-processed food consumption	Now I am going to list some industrialized foods and I would like you to tell me if you have any of them yesterday (when you woke up until you went to bed)	Now let's talk about your eating habits. I am going to ask you a few questions about industrialized foods you consumed yesterday.	Based on the questions presented, an indicator of 'consumption of five or more ultra-processed foods on the previous day' was constructed.
	a. Soft drink	Yesterday, did you drink or eat:
	1 ( ) Yes / 2 ( ) No	a. Soft drink
	b. Caton or canned juice	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	b. Carton or canned juice or powdered juice?
	c. Powdered juice	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	c. Chocolate milk or flavored yogurt?
	d. Chocolate milk	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	d. Packet snacks or savory biscuits/crackers?
	e. Flavored yogurt	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	e. Sweet or filled biscuits/crackers or packet cupcake?
	f. Packet snacks (or chips) or savory biscuit/crackers	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	f. Ice cream, chocolate, gelatin, flan or other industrialized dessert?
	g. Sweet/wafer biscuits, filled biscuits or packet cupcakes	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	g. Sausage, mortadella or ham?
	h. Chocolate, ice cream, gelatin, flan or other industrialized dessert	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	h. Sliced bread, hot dog or hamburger buns?
	i. Sausage, mortadella or ham	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	i. Margarine, mayonnaise, ketchup or other industrialized sauces?
	j. Sliced bread, hot dog or hamburger buns	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No	j. Instant noodles, packet soup, frozen lasagna or another frozen prepared food meals (takeout)?
	k. Mayonnaise, ketchup or mustard	1 ( ) Yes / 2 ( ) No
	1 ( ) Yes / 2 ( ) No
	l. Margarine
	1 ( ) Yes / 2 ( ) No
	m. Instant noodles, packet soup, frozen lasagna or another frozen prepared food meals (takeout)
	1 ( ) Yes / 2 ( ) No
Soft drink consumption	How many days a week do you usually drink soda or artificial juice?	How many days a week do you usually drink soda? ____ Days; 0. Never or less than once a week.	Vigitel took into account the consumption of soft drinks and artificial juice. The PNS took into account only the consumption of soft drinks. In both databases, an indicator was created taking into consideration how to control the consumption by five or more days a week.
	1 ( ) 1 a 2 days a week
	2 ( ) 3 a 4 days a week
	3 ( ) 5 a 6 days a week
	4 ( ) Every day (including Saturday and Sunday)
	5 ( ) Almost never
	6 ( ) Never

Variables	Vigitel^a		PNS^b		Difference in percentage points
	n=1,812		n=1,225
	%	95%CI^c	%	95%CI^c
Sex
Male	47.6	43.5;51.7	46.7	42.3;51.1
Female	52.4	48.3;56.5	53.3	48.9;57.7	-0.9^d
Age (in years)
18-24	17.9	15.3;20.9	18.1	14.8;21.8	-0.2^d
25-39	38.1	33.9;42.6	31.3	28.4;34.4	6.8^d
40-59	31.6	28.2;35.2	35.0	31.8;38.4	-3.4^d
≥60	12.4	10.9;14.0	15.6	13.2;18.2	-3.2^d
Race/skin color
White	25.9	22.5;29.6	20.5	17.8;23.6	5.4^d
Black	6.7	4.5;9.8	7.6	6.0;9.5	-0.9^d
Asian	0.3	0.2;0.8	0.3	0.1;0.9	0.0^d
Brown	60.3	56.2;64.3	70.8	67.4;73.9	-10.5
Indigenous	0.8	0.4;1.6	0.8	0.4;1.6	0.0^d
Schooling (in years of study)
0-8	31.0	26.8;35.6	28.5	23.9;33.6	2.5^d
9-11	38.2	34.5;42.0	38.8	33.3;43.0	0.6^d
≥12	30.8	27.7;34.1	33.4	29.6;37.5	-2.6^d
Diabetes mellitus
No	95.1	93.6;96.1	93.9	92.4;95.1
Yes	4.9	3.9;6.3	6.1	4.9;7.6	-1.2^d
Arterial hypertension
No	81.5	78.8;83.9	79.5	76.6;82.1
Yes	18.5	16.1;21.2	20.5	17.9;23.4	-2.0^d
Overweight
No	43.4	39.4;47.5	41.8	38.4;45.3
Yes	56.6	52.5;60.6	58.2	54.7;61.6	-1.6^d
Obesity
No	76.7	73.0;80.0	79.9	76.6;82.8
Yes	23.3	20.0;27.0	20.1	17.2;23.4	3.2^d
Smoking
No	88.1	84.0;91.2	89.3	86.6;91.5
Yes	11.9	8.8;16.0	10.7	8.5;13.4	1.2^d
Alcohol abuse
No	82.3	78.3;85.8	84.4	81.7;86.8
Yes	17.7	14.2;21.7	15.6	13.2;18.2	2.1^d
Consumption of five or more groups of ultra-processed foods on the day before the interview
No	85.3	82.4;87.8	84.4	81.7;86.8
Yes	14.7	12.2;17.6	15.6	13.2;18.2	2.1^d

Variables	Male			Female
	Vigitel^a N=631	PNS^b N=538	Difference in percentage points	Vigitel^a N=1,181	PNS^b N=687	Difference in percentage points
	% (95%CI^c)	% (95%CI^c)	Difference in percentage points	% (95%CI^c)	% (95%CI^c)	Difference in percentage points
Diabetes mellitus
No	95.9 (93.8;97.1)	93.5 (90.3;95.6)		94.3 (92.3;95.8)	94.2 (92.3;95.7)
Yes	4.1 (2.8;6.1)	6.5 (4.4;9.7)	-2.4^d	5.7 (4.2;7.7)	5.8 (4.3;7.7)	-0.1^d
Arterial hypertension
No	85.1 (80.9;88.3)	82.6 (78.8;85.8)		78.3 (74.7;81.5)	76.8 (72.7;80.4)
Yes	14.9 (11.6;19.0)	17.4 (14.2;21.2)	-2.5^d	21.7 (18.5;25.3)	23.2(19.6;27.3)	-1.5^d
Overweight
No	42.0 (35.3;49.1)	40.5 (34.6;46.7)		44.6 (40.1;49.2)	43.0 (38.6;47.4)
Yes	58.0 (50.9;64.7)	59.5 (53.3;65.4)	-1.5^d	55.4 (50.8;59.9)	57.0 (52.6;61.4)	-1.6^d
Obesity
No	76.7 (70.6;81.9)	83.2 (79.0;86.7)		76.6 (72.1;80.7)	77.0 (72.4;81.0)
Yes	23.3 (18.1;29.4)	16.8 (13.3;21.0)	6.5^d	23.4 (19.3;27.9)	23.0 (19.0;27.6)	0.4^d
Smoking
No	82.9 (74.9;88.7)	86.9 (81.3;91.1)		92.8 (90.2;94.8)	91.3 (88.8;93.3)
Yes	17.1 (11.3;25.1)	13.1 (8.9;18.7)	4.0^d	7.2 (5.2;9.8)	8.7 (6.7;11.2)	-1.5^d
Alcohol abuse
No	71.4 (64.0;77.7)	78.3 (73.8;82.3)		92.3 (89.7;94.3)	89.8 (86.7;92.2)
Yes	28.6 (22.3;36.0)	21.7 (17.7;26.2)	6.9^d	7.7 (5.7;10.3)	10.2 (7.8;13.3)	-2.5^d
Consumption of five or more groups of ultra-processed foods on the day before the interview
No	83.3 (78.2;87.4)	83.3 (78.7;87.1)		87.2 (83.8;89.9)	90.4 (87.8;92.5)
Yes	16.7 (12.6;21.8)	16.7 (12.9;21.3)	0.0^d	12.8 (10.1;16.2)	9.6 (7.5;12.2)	3.2^d
Regular consumption of soft drink five or more days a week
No	85.8 (80.0;90.1)	84.3 (79.8;87.8)		89.6 (85.8;92.4)	93.2 (90.6;95.1)
Yes	14.2 (9.9;20.0)	15.7 (12.2;20.2)	-1.5^d	10.4 (7.6;14.2)	6.8 (4.9;9.4)	3.6^d

Saúde Pública

Saúde Pública

Prevalence of ultra-processed food, alcohol and tobacco consumption and chronic non-communicable diseases in Rio Branco, capital city of the state of Acre, Brazil, 2019: comparative analysis of two epidemiological surveys

Abstract

Objective

Methods

Results

Conclusion

Introduction

Methods

RESULTS

DISCUSSION

References

Publication Dates

History