Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach

Detalhes bibliográficos
Autor(a) principal: Bôto, Joana Margarida
Data de Publicação: 2021
Outros Autores: Marreiros, Ana, Diogo, Patricia, Pinto, Ezequiel, Mateus, Maria Palma
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.1/19230
Resumo: Objective: This study aimed to identify health behaviours that determine adolescent's adherence to the Mediterranean diet (MD) through a decision tree statistical approach. Design: Cross-sectional study, with data collected through a self-fulfilment questionnaire with five sections: (1) eating habits; (2) adherence to the MD (KIDMED index); (3) physical activity; (4) health habits and (5) socio-demographic characteristics. Anthropometric and blood pressure data were collected by a trained research team. The Automatic Chi-square Interaction Detection (CHAID) method was used to identify health behaviours that contribute to a better adherence to the MD. Setting: Eight public secondary schools, in Algarve, Portugal. Participants: Adolescents with ages between 15 and 19 years (n 325). Results: According to the KIDMED index, we found a low adherence to MD in 9 center dot 0 % of the participants, an intermediate adherence in 45 center dot 5 % and a high adherence in 45 center dot 5 %. Participants that regularly have breakfast, eat vegetable soup, have a second piece of fruit/d, eat fresh or cooked vegetables 1 or more times a day, eat oleaginous fruits at least 2 to 3 times a week, and practice sports and leisure physical activities outside school show higher adherence to the MD (P < 0 center dot 001). Conclusions: The daily intake of two pieces of fruit and vegetables proved to be a determinant health behaviour for high adherence to MD. Strategies to promote the intake of these foods among adolescents must be developed and implemented.
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spelling Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approachMediterranean DietAdolescenceHealth behavioursDietary habitsDecision treesMachine learningObjective: This study aimed to identify health behaviours that determine adolescent's adherence to the Mediterranean diet (MD) through a decision tree statistical approach. Design: Cross-sectional study, with data collected through a self-fulfilment questionnaire with five sections: (1) eating habits; (2) adherence to the MD (KIDMED index); (3) physical activity; (4) health habits and (5) socio-demographic characteristics. Anthropometric and blood pressure data were collected by a trained research team. The Automatic Chi-square Interaction Detection (CHAID) method was used to identify health behaviours that contribute to a better adherence to the MD. Setting: Eight public secondary schools, in Algarve, Portugal. Participants: Adolescents with ages between 15 and 19 years (n 325). Results: According to the KIDMED index, we found a low adherence to MD in 9 center dot 0 % of the participants, an intermediate adherence in 45 center dot 5 % and a high adherence in 45 center dot 5 %. Participants that regularly have breakfast, eat vegetable soup, have a second piece of fruit/d, eat fresh or cooked vegetables 1 or more times a day, eat oleaginous fruits at least 2 to 3 times a week, and practice sports and leisure physical activities outside school show higher adherence to the MD (P < 0 center dot 001). Conclusions: The daily intake of two pieces of fruit and vegetables proved to be a determinant health behaviour for high adherence to MD. Strategies to promote the intake of these foods among adolescents must be developed and implemented.European RegionalDevelopment Fund (ERDF) through the Operational Program (POCTEP) 0290_MEDITA_5_PCambridge University PressSapientiaBôto, Joana MargaridaMarreiros, AnaDiogo, PatriciaPinto, EzequielMateus, Maria Palma2023-03-13T11:13:44Z2021-072021-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/19230eng10.1017/S13689800210032931475-2727info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-24T10:31:39Zoai:sapientia.ualg.pt:10400.1/19230Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:08:51.689084Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
title Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
spellingShingle Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
Bôto, Joana Margarida
Mediterranean Diet
Adolescence
Health behaviours
Dietary habits
Decision trees
Machine learning
title_short Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
title_full Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
title_fullStr Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
title_full_unstemmed Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
title_sort Health behaviours as predictors of the Mediterranean diet adherence: a decision tree approach
author Bôto, Joana Margarida
author_facet Bôto, Joana Margarida
Marreiros, Ana
Diogo, Patricia
Pinto, Ezequiel
Mateus, Maria Palma
author_role author
author2 Marreiros, Ana
Diogo, Patricia
Pinto, Ezequiel
Mateus, Maria Palma
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Sapientia
dc.contributor.author.fl_str_mv Bôto, Joana Margarida
Marreiros, Ana
Diogo, Patricia
Pinto, Ezequiel
Mateus, Maria Palma
dc.subject.por.fl_str_mv Mediterranean Diet
Adolescence
Health behaviours
Dietary habits
Decision trees
Machine learning
topic Mediterranean Diet
Adolescence
Health behaviours
Dietary habits
Decision trees
Machine learning
description Objective: This study aimed to identify health behaviours that determine adolescent's adherence to the Mediterranean diet (MD) through a decision tree statistical approach. Design: Cross-sectional study, with data collected through a self-fulfilment questionnaire with five sections: (1) eating habits; (2) adherence to the MD (KIDMED index); (3) physical activity; (4) health habits and (5) socio-demographic characteristics. Anthropometric and blood pressure data were collected by a trained research team. The Automatic Chi-square Interaction Detection (CHAID) method was used to identify health behaviours that contribute to a better adherence to the MD. Setting: Eight public secondary schools, in Algarve, Portugal. Participants: Adolescents with ages between 15 and 19 years (n 325). Results: According to the KIDMED index, we found a low adherence to MD in 9 center dot 0 % of the participants, an intermediate adherence in 45 center dot 5 % and a high adherence in 45 center dot 5 %. Participants that regularly have breakfast, eat vegetable soup, have a second piece of fruit/d, eat fresh or cooked vegetables 1 or more times a day, eat oleaginous fruits at least 2 to 3 times a week, and practice sports and leisure physical activities outside school show higher adherence to the MD (P < 0 center dot 001). Conclusions: The daily intake of two pieces of fruit and vegetables proved to be a determinant health behaviour for high adherence to MD. Strategies to promote the intake of these foods among adolescents must be developed and implemented.
publishDate 2021
dc.date.none.fl_str_mv 2021-07
2021-07-01T00:00:00Z
2023-03-13T11:13:44Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.1/19230
url http://hdl.handle.net/10400.1/19230
dc.language.iso.fl_str_mv eng
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1475-2727
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dc.publisher.none.fl_str_mv Cambridge University Press
publisher.none.fl_str_mv Cambridge University Press
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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