IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i17p10551-d896438.html
   My bibliography  Save this article

School Feeding as a Protective Factor against Insulin Resistance: The Study of Cardiovascular Risks in Adolescents (ERICA)

Author

Listed:
  • Aline Bassetto Okamura

    (Graduate Program in Public Health, Faculty of Health Sciences, University of Brasília, Campus Universitário Darcy Ribeiro S/N, Asa Norte, Brasília 70910-900, Brazil)

  • Vivian Siqueira Santos Gonçalves

    (Graduate Program in Public Health, Faculty of Health Sciences, University of Brasília, Campus Universitário Darcy Ribeiro S/N, Asa Norte, Brasília 70910-900, Brazil)

  • Kênia Mara Baiocchi de Carvalho

    (Graduate Program in Public Health, Faculty of Health Sciences, University of Brasília, Campus Universitário Darcy Ribeiro S/N, Asa Norte, Brasília 70910-900, Brazil)

Abstract

The objective of this study was to use ERICA data from adolescents from Brazilian public schools to investigate the role of school feeding in insulin resistance markers. Public school students (12–17 years old) with available biochemical examinations were selected. Adolescents answered a self-administered questionnaire, and contextual characteristics were obtained through interviews with principals. A multilevel mixed-effects generalized linear model was performed at the contextual and individual levels with each insulin resistance marker (fasting insulin, HOMA-IR, and blood glucose levels). A total of 27,990 adolescents were evaluated (50.2% female). The prevalence of (1) altered insulin was 12.2% (95% CI; 11.1, 13.5), (2) high HOMA-IR was 24.7% (95% CI; 22.8, 26.7), and (3) high blood glucose was 4.6% (95% CI; 3.8, 5.4). School feeding was positively associated with an insulin resistance marker, decreasing by 0.135 units of HOMA-IR (95% CI; −0.19, −0.08), 0.469 μU/L of insulin levels (95% CI; −0.66, −0.28), and 0.634 mg/dL of blood glucose (95% CI; −0.87, −0.39). In turn, buying food increased blood glucose by 0.455 mg/dL (95% CI; 0.16, 0.75). School feeding was positively associated with insulin resistance variables, demonstrating the potential of planned meals in the school environment to serve as a health promoter for the adolescent population.

Suggested Citation

  • Aline Bassetto Okamura & Vivian Siqueira Santos Gonçalves & Kênia Mara Baiocchi de Carvalho, 2022. "School Feeding as a Protective Factor against Insulin Resistance: The Study of Cardiovascular Risks in Adolescents (ERICA)," IJERPH, MDPI, vol. 19(17), pages 1-10, August.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:10551-:d:896438
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/17/10551/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/17/10551/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sophia Rabe‐Hesketh & Anders Skrondal, 2006. "Multilevel modelling of complex survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 805-827, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2020. "Wage response to global production links: evidence for workers from 28 European countries (2005–2014)," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(4), pages 769-801, November.
    2. Per Strömblad & Gunnar Myrberg, 2013. "Urban Inequality and Political Recruitment," Urban Studies, Urban Studies Journal Limited, vol. 50(5), pages 1049-1065, April.
    3. Li Yu & Peter F. Orazem, 2014. "O-Ring production on U.S. hog farms: joint choices of farm size, technology, and compensation," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 431-442, July.
    4. Yang, Tingzhong & Barnett, Ross & Jiang, Shuhan & Yu, Lingwei & Xian, Hong & Ying, Jun & Zheng, Weijun, 2016. "Gender balance and its impact on male and female smoking rates in Chinese cities," Social Science & Medicine, Elsevier, vol. 154(C), pages 9-17.
    5. Marion Borderon & Patrick Sakdapolrak & Raya Muttarak & Endale Kebede & Raffaella Pagogna & Eva Sporer, 2019. "Migration influenced by environmental change in Africa: A systematic review of empirical evidence," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(18), pages 491-544.
    6. Daria Denti, 2022. "Looking ahead in anger: The effects of foreign migration on youth resentment in England," Journal of Regional Science, Wiley Blackwell, vol. 62(2), pages 578-603, March.
    7. José Ernesto Amorós & Carlos Poblete & Vesna Mandakovic, 2019. "R&D transfer, policy and innovative ambitious entrepreneurship: evidence from Latin American countries," The Journal of Technology Transfer, Springer, vol. 44(5), pages 1396-1415, October.
    8. Woojin Chung & Roeul Kim, 2020. "A Reversal of the Association between Education Level and Obesity Risk during Ageing: A Gender-Specific Longitudinal Study in South Korea," IJERPH, MDPI, vol. 17(18), pages 1-19, September.
    9. Herzfeld, Thomas & Huffman, Sonya & Rizov, Marian, 2014. "The dynamics of food, alcohol and cigarette consumption in Russia during transition," Economics & Human Biology, Elsevier, vol. 13(C), pages 128-143.
    10. Pedro Luis do N. Silva & Fernando Antônio da S. Moura, 2022. "Fitting multivariate multilevel models under informative sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1663-1678, October.
    11. Kathryn M. Yount & AliceAnn Crandall & Yuk Fai Cheong & Theresa L. Osypuk & Lisa M. Bates & Ruchira T. Naved & Sidney Ruth Schuler, 2016. "Child Marriage and Intimate Partner Violence in Rural Bangladesh: A Longitudinal Multilevel Analysis," Demography, Springer;Population Association of America (PAA), vol. 53(6), pages 1821-1852, December.
    12. Amini, Chiara & Commander, Simon, 2012. "Educational scores: How does Russia fare?," Journal of Comparative Economics, Elsevier, vol. 40(3), pages 508-527.
    13. Jean-Paul Lucas & V�ronique S�bille & Alain Le Tertre & Yann Le Strat & Lise Bellanger, 2014. "Multilevel modelling of survey data: impact of the two-level weights used in the pseudolikelihood," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(4), pages 716-732, April.
    14. Patricia Dörr & Jan Pablo Burgard, 2019. "Data-driven transformations and survey-weighting for linear mixed models," Research Papers in Economics 2019-16, University of Trier, Department of Economics.
    15. K. C. Culver & Nathaniel Bray & John Braxton, 2024. "On My Honor: A Quasi-Experimental Analysis of Honors Students’ Perceptions of Workload and Cognitive Challenge," Research in Higher Education, Springer;Association for Institutional Research, vol. 65(4), pages 679-704, June.
    16. Arrieta-Paredes, Mary-Paz & Hallsworth, Alan G. & Coca-Stefaniak, J. Andres, 2020. "Small shop survival – The financial response to a global financial crisis," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    17. Vicente, Iván & Pastor, José M. & Soler, Ángel, 2021. "Improving educational resilience in the OECD countries: Two convergent paths," Journal of Policy Modeling, Elsevier, vol. 43(6), pages 1149-1166.
    18. Laura M. Stapleton & Ji Seung Yang & Gregory R. Hancock, 2016. "Construct Meaning in Multilevel Settings," Journal of Educational and Behavioral Statistics, , vol. 41(5), pages 481-520, October.
    19. Simon COMMANDER & Natalia ISACHENKOVA & Yulia RODIONOVA, 2013. "Informal employment dynamics in Ukraine: An analytical model of informality in transition economies," International Labour Review, International Labour Organization, vol. 152(3-4), pages 445-467, December.
    20. Joanna Taylor & Liz Twigg & John Mohan, 2015. "Understanding neighbourhood perceptions of alcohol-related anti-social behaviour," Urban Studies, Urban Studies Journal Limited, vol. 52(12), pages 2186-2202, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:10551-:d:896438. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.