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Characteristics of the school food environment associated with hypertension and obesity in Brazilian adolescents: a multilevel analysis of the Study of Cardiovascular Risks in Adolescents (ERICA)

  • Vivian SS Gonçalves (a1), Elisabeth C Duarte (a2), Eliane S Dutra (a1), Laura A Barufaldi (a3) and Kênia MB Carvalho (a1)...



To characterize the food environment in schools that participated in the Study of Cardiovascular Risks in Adolescents (ERICA) and to identify individual and contextual factors associated with hypertension and obesity.


National school-based survey.


Blood pressure, weight and height were measured, and characteristics of the schools were obtained in interviews with the principals. For each outcome, multilevel models of mixed effects were applied by logistic regression.


School-going adolescents aged 12–17 years.


A total of 73 399 adolescents were evaluated. The prevalence of hypertension was 9·6 (95 % CI 9·0, 10·3) % and that of obesity was 8·4 (95 % CI 7·9, 8·9) %. Approximately 50 % of the adolescents were able to purchase food at school and in its immediate vicinity and 82 % had access to no-charge meals through Brazil’s National School Feeding Program. In the adjusted analysis, hypertension was associated (OR; 95 % CI) with the consumption of meals prepared on the school premises (0·79; 0·69, 0·92), the sale of food in the school’s immediate vicinity (0·67; 0·48, 0·95) and the purchase of food in the school cafeteria (1·29; 1·11, 1·49). It was observed that there were lower odds of obesity among students who were offered meals prepared on the school premises (0·68; 0·54, 0·87).


High frequency of sales of ultra-processed foods in schools was identified. Contextual and individual characteristics in the school food environment were associated with hypertension and obesity, pointing to the need for regulation and supervision of these spaces.


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1.Blum, RW, Bastos, FIPM, Kabiru, CW et al. (2012) Adolescent health in the 21st century. Lancet 379, 15671568.
2.United Nations Population Division, Department of Economic and Social Affairs (2017) World population prospects: the 2017 revision. (accessed January 2018).
3.Bibiloni, M del, M, Pons, A & Tur, JA (2013) Prevalence of overweight and obesity in adolescents: a systematic review. ISRN Obes 2013, 392747.
4.Moraes, ACF, Lacerda, MB, Moreno, LA et al. (2014) Prevalence of high blood pressure in 122053 adolescents. Medicine (Baltimore) 93, e232.
5.Ewald, DR & Haldeman, LA (2016) Risk factors in adolescent hypertension. Glob Pediatr Health 3, 2333794X1562515.
6.Morton, KL, Atkin, AJ, Corder, K et al. (2016) The school environment and adolescent physical activity and sedentary behaviour: a mixed-studies systematic review. Obes Rev 17, 142158.
7.Azeredo, CM, Levy, RB, Araya, R et al. (2015) Individual and contextual factors associated with verbal bullying among Brazilian adolescents. BMC Pediatr 15, 49.
8.Godin, KM, Chacón, V, Barnoya, J et al. (2017) The school environment and sugar-sweetened beverage consumption among Guatemalan adolescents. Public Health Nutr 20, 29802987.
9.Azeredo, CM, de Rezende, LFM, Canella, DS et al. (2016) Food environments in schools and in the immediate vicinity are associated with unhealthy food consumption among Brazilian adolescents. Prev Med 88, 7379.
10.Fitzpatrick, C, Datta, GD, Henderson, M et al. (2017) School food environments associated with adiposity in Canadian children. Int J Obes (Lond) 41, 10051010.
11.Osei-Assibey, G, Dick, S, Macdiarmid, J et al. (2012) The influence of the food environment on overweight and obesity in young children: a systematic review. BMJ Open 2, e001538.
12.Fox, MK, Dodd, AH, Wilson, A et al. (2009) Association between school food environment and practices and body mass index of US public school children. J Am Diet Assoc 109, 2 Suppl., S108S117.
13.Brazilian Institute of Geography and Statistics (2016) National Household Sample Survey (PNAD) – Synthesis of Indicators 2015. Rio de Janeiro, RJ: IBGE.
14.von Elm, E, Altman, DG, Egger, M et al. (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370, 14531457.
15.Bloch, KV, Szklo, M, Kuschnir, MCC et al. (2015) The Study of Cardiovascular Risk in Adolescents – ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents. BMC Public Health 15, 94.
16.Vasconcellos, MTL, Silva, PLN, Szklo, M et al. (2015) Sampling design for the Study of Cardiovascular Risks in Adolescents (ERICA). Cad Saude Publica 31, 921930.
17.National Institutes of Health (2004) The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 114, 555576.
18.Stergiou, GS, Yiannes, NG & Rarra, VC (2006) Validation of the Omron 705 IT oscillometric device for home blood pressure measurement in children and adolescents: the Arsakion School Study. Blood Press Monit 11, 229234. Onis, M, Onyango, AW, Borghi, E et al. (2007) Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 85, 660667.
20.Farias Júnior, JC, Lopes, AS, Mota, J et al. (2012) Validity and reproducibility of a physical activity questionnaire for adolescents: adapting the Self-Administered Physical Activity Checklist. Rev Bras Epidemiol 15, 198210.
21.Tanner, JM (1962) Growth at Adolescence. Springfield, IL: Blackwell Science.
22.Larsen, K & Merlo, J (2005) Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression. Am J Epidemiol 161, 8188.
23.Merlo, J, Chaix, B, Ohlsson, H et al. (2006) A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J Epidemiol Community Health 60, 290297.
24.Merlo, J, Yang, M, Chaix, B et al. (2005) A brief conceptual tutorial on multilevel analysis in social epidemiology: investigating contextual phenomena in different groups of people. J Epidemiol Community Health 59, 729736.
25.Silva, TLN, Klein, CH, Moura Souza, A et al. (2016) Response rate in the Study of Cardiovascular Risks in Adolescents – ERICA. Rev Saude Publica 50, Suppl. 1, 1S13S.
26.Rezende, LFM de, Azeredo, CM, Canella, DS et al. (2016) Coronary heart disease mortality, cardiovascular disease mortality and all-cause mortality attributable to dietary intake over 20 years in Brazil. Int J Cardiol 217, 6468.
27.Datar, A & Nicosia, N (2017) The effect of state competitive food and beverage regulations on childhood overweight and obesity. J Adolesc Health 60, 520527.
28.Taber, DR, Chriqui, JF, Vuillaume, R et al. (2014) How state taxes and policies targeting soda consumption modify the association between school vending machines and student dietary behaviors: a cross-sectional analysis. PLoS One 9, e98249.
29.Callaghan, M, Molcho, M, Nic Gabhainn, S et al. (2015) Food for thought: analysing the internal and external school food environment. Health Educ 115, 152170.
30.Mâsse, LC, de Niet-Fitzgerald, J, Watts, AW et al. (2014) Associations between the school food environment, student consumption and body mass index of Canadian adolescents. Int J Behav Nutr Phys Act 11, 29.
31.Terry-McElrath, YM, O’Malley, PM & Johnston, LD (2014) Accessibility over availability: associations between the school food environment and student fruit and green vegetable consumption. Child Obes 10, 241250.
32.Cutumisu, N, Traoré, I, Paquette, MC et al. (2017) Association between junk food consumption and fast-food outlet access near school among Quebec secondary-school children: findings from the Quebec Health Survey of High School Students (QHSHSS) 2010–11. Public Health Nutr 20, 927937.
33.Park, S, Choi, BY, Wang, Y et al. (2013) School and neighborhood nutrition environment and their association with students’ nutrition behaviors and weight status in Seoul, South Korea. J Adolesc Health 53, 655662.
34.Richmond, TK, Elliott, MN, Franzini, L et al. (2014) School programs and characteristics and their influence on student BMI: findings from Healthy Passages. PLoS One 9, e83254.
35.Driessen, CE, Cameron, AJ, Thornton, LE et al. (2014) Effect of changes to the school food environment on eating behaviours and/or body weight in children: a systematic review. Obes Rev 15, 968982.
36.Brazil, Ministry of Education (2018) National School Feeding Program – PNAE. (accessed January 2018).
37.Brazil, Ministry of Education (2013) Resolution No. 26, of June 17, 2013 – Provides for the attendance of school feeding to students of basic education within the framework of the National School Feeding Program – PNAE.,-de-17-de-junho-de-2013 (accessed April 2019).
38.Paim, J, Travassos, C, Almeida, C et al. (2011) The Brazilian health system: history, advances, and challenges. Lancet 377, 17781797.
39.Schmidt, MI, Duncan, BB, Silva, E GA et al. (2011) Chronic non-communicable diseases in Brazil: burden and current challenges. Lancet 377, 19491961.
40.Longacre, MR, Drake, KM, Titus, LJ et al. (2014) School food reduces household income disparities in adolescents’ frequency of fruit and vegetable intake. Prev Med 69, 202207.
41.Williams, J, Scarborough, P, Matthews, A et al. (2014) A systematic review of the influence of the retail food environment around schools on obesity-related outcomes. Obes Rev 15, 359374.
42.Seliske, LM, Pickett, W, Boyce, WF et al. (2009) Association between the food retail environment surrounding schools and overweight in Canadian youth. Public Health Nutr 12, 13841391.
43.Laska, MN, Hearst, MO, Forsyth, A et al. (2010) Neighbourhood food environments: are they associated with adolescent dietary intake, food purchases and weight status? Public Health Nutr 13, 17571763.


Characteristics of the school food environment associated with hypertension and obesity in Brazilian adolescents: a multilevel analysis of the Study of Cardiovascular Risks in Adolescents (ERICA)

  • Vivian SS Gonçalves (a1), Elisabeth C Duarte (a2), Eliane S Dutra (a1), Laura A Barufaldi (a3) and Kênia MB Carvalho (a1)...


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