Evolution of obesity and noncommunicable diseases in populations in the capitals of Brazil between 2006 and 2018

Authors

DOI:

https://doi.org/10.11606/issn.2176-7262.rmrp.2021.171413

Keywords:

Obesity, Noncommunicable diseases, Diabetes, Cardiovascular diseases, Public health

Abstract

Study design: Cross-sectional descriptive study. Objective: This study aimed to analyze the evolution of the prevalence of overweight, obesity, and noncommunicable diseases (NCD), and their relationship with age and studying years, in Brazilian capitals. Method: Data from the VIGITEL Surveys, primarily for 2006 and 2018, were analyzed for 12 variables, using descriptive statistical procedures, frequency analysis, and dispersion diagrams with insertion of trend curves and determination coefficients. Results: The results show a significant increase in the average BMI and the prevalence of NCD in the populations of the capitals in Brazil, although the self-perception of the general state of health presents an inexpressive change. The average BMI of the population is higher in the age group between 45 and 65 years old, and the prevalence of diabetes, high blood pressure, and dyslipidemia has increased sharply since the age of 40, reaching its peak in the age group between 70 and 80 years. The more years of studies the population has, the lower the prevalence of obesity and NCD. Conclusions: Initiatives, both public and private, to reduce the risk factors that enhance the increase in obesity and NCD are necessary. Furthermore, the increase in the educational level of a population has the potential to promote significant improvement in the public health situation, reducing health expenditures and improving the quality of life of the population.

 

Downloads

Download data is not yet available.

References

Abbade EB, Dewes H. Behavioral and societal drivers of an obesogenic environment worldwide. Nutr Food Sci 2015; 45: 229–241.

Dias PC, Henriques P, Anjos LA dos, et al. Obesidade e políticas públicas: concepções e estratégias adotadas pelo governo brasileiro. Cad Saúde Pública 2017; 33: e00006016.

Giskes K, van Lenthe F, Avendano-Pabon M, et al. A systematic review of environmental factors and obesogenic dietary intakes among adults: Are we getting closer to understanding obesogenic environments? Obes Rev 2011; 12: e95–e106.

Rech DC, Borfe L, Emmanouilidis A, et al. As políticas públicas e o enfrentamento da obesidade no Brasil: uma revisão reflexiva. Rev Epidemiol E Controle Infecção 2016; 1: 192–202.

OMS [Organização Mundial da Saúde]. Global Health Observatory (GHO), http://www.who.int/gho/database/en/ (2018, accessed 5 August 2018).

MS [Ministério da Saúde]. Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico, Vigitel 2017. Ministério da Saúde Brasília, http://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2017_vigilancia_fatores_riscos.pdf (2017).

McTigue K, Larson JC, Valoski A, et al. Mortality and cardiac and vascular outcomes in extremely obese women. J Am Med Assoc 2006; 296: 79–86.

Misra A, Khurana L. Obesity and the metabolic syndrome in developing countries. J Clin Endocrinol Metab 2008; 93: s9–s30.

Moghaddam AA, Woodward M, Huxley R. Obesity and risk of colorectal cancer: A meta-analysis of 31 studies with 70,000 events. Cancer Epidemiol Biomarkers Prev 2007; 16: 2533–2547.

Abbade EB. The relationships between obesity-increasing risk factors for public health, environmental impacts, and health expenditures worldwide. Manag Environ Qual Int J 2018; 29: 131–147.

Buchmueller TC, Johar M. Obesity and health expenditures: Evidence from Australia. Econ Hum Biol 2015; 17: 42–58.

Specchia ML, Veneziano MA, Cadeddu C, et al. Economic impact of adult obesity on health systems: A systematic review. Eur J Public Health 2015; 25: 255–262.

Spieker EA, Pyzocha N. Economic Impact of Obesity. Prim Care - Clin Off Pract 2016; 43: 83–95.

Abbade EB. Análise das internações hospitalares para procedimentos de cirurgias bariátricas financiadas pelo SUS em âmbito nacional. Med Ribeirao Preto Online 2019; 52: 201–211.

WHO. The top 10 causes of death, https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death (2018, accessed 10 August 2020).

WHO. Noncommunicable diseases country profiles 2018, https://apps.who.int/iris/handle/10665/274512 (2018, accessed 4 September 2020).

MS [Ministério da Saúde]. Vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: VIGITEL 2011. Brasília: Ministério da Saúde, 2012.

World Health Organization. Physical status: The use of and interpretation of anthropometry, Report of a WHO Expert Committee. Geneva: World Health Organization, https://apps.who.int/iris/bitstream/handle/10665/37003/WHO_TRS_854.pdf (1995, accessed 5 May 2020).

Canella DS, Levy RB, Martins APB, et al. Ultra-Processed Food Products and Obesity in Brazilian Households (2008–2009). PLOS ONE 2014; 9: e92752.

Cunha DB, Costa THM da, Veiga GV da, et al. Ultra-processed food consumption and adiposity trajectories in a Brazilian cohort of adolescents: ELANA study. Nutr Diabetes 2018; 8: 1–9.

Castronuovo L, Allemandi L, Tiscornia V, et al. Analysis of a voluntary initiative to reduce sodium in processed and ultra-processed food products in Argentina: the views of public and private sector representatives. Cad Saude Publica 2017; 33: e00014316.

Kanter R, Reyes M, Swinburn B, et al. The food supply prior to the implementation of the Chilean Law of Food Labeling and Advertising. Nutrients 2019; 11: 52.

Nilson EA, Spaniol AM, Gonçalves VS, et al. Sodium reduction in processed foods in Brazil: analysis of food categories and voluntary targets from 2011 to 2017. Nutrients 2017; 9: 742.

Dee A, Kearns K, O’Neill C, et al. The direct and indirect costs of both overweight and obesity: a systematic review. BMC Res Notes 2014; 7: 242.

Malta DC, Andrade SC, Claro RM, et al. Trends in prevalence of overweight and obesity in adults in 26 Brazilian state capitals and the Federal District from 2006 to 2012. Rev Bras Epidemiol 2014; 17: 267–276.

Nilson EAF, Andrade R da CS, Brito DA de, et al. Custos atribuíveis a obesidade, hipertensão e diabetes no Sistema Único de Saúde, Brasil, 2018. Rev Panam Salud Pública 2020; 44: e32.

Rudman D, Feller AG, Nagraj HS, et al. Effects of human growth hormone in men over 60 years old. N Engl J Med 1990; 323: 1–6.

WHO. Obesity: preventing and managing the global epidemic. World Health Organization, 2000.

WHO. Diet, nutrition, and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. World Health Organization, 2003.

Vergnaud A-C, Bertrais S, Oppert J-M, et al. Weight fluctuations and risk for metabolic syndrome in an adult cohort. Int J Obes 2008; 32: 315–321.

Coelho MSPH, Assis MAA de, Moura EC. Body mass index increase after the age of 20 and associations with risk or protection factors for chronic non-communicable diseases. Arq Bras Endocrinol Amp Metabol 2009; 53: 1146–1156.

Van Lenthe FJ, Droomers M, Schrijvers CTM, et al. Socio-demographic variables and 6 year change in body mass index: longitudinal results from the GLOBE study. Int J Obes 2000; 24: 1077–1084.

Pavão ALB, Werneck GL, Campos MR. Autoavaliação do estado de saúde e a associação com fatores sociodemográficos, hábitos de vida e morbidade na população: um inquérito nacional. Cad Saúde Pública 2013; 29: 723–734.

Nardocci M, Leclerc B-S, Louzada M-L, et al. Consumption of ultra-processed foods and obesity in Canada. Can J Public Health 2019; 110: 4–14.

Lwin MO, Shin W, Yee AZH, et al. A Parental Health Education Model of Children’s Food Consumption: Influence on Children’s Attitudes, Intention, and Consumption of Healthy and Unhealthy Foods. J Health Commun 2017; 22: 403–412.

Published

2021-07-02 — Updated on 2021-08-02

Issue

Section

Original Articles

How to Cite

1.
Abbade EB. Evolution of obesity and noncommunicable diseases in populations in the capitals of Brazil between 2006 and 2018. Medicina (Ribeirão Preto) [Internet]. 2021 Aug. 2 [cited 2024 Dec. 21];54(1):e171413. Available from: https://revistas.usp.br/rmrp/article/view/171413

Funding data