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Maternal and pediatric nutrition

Use of a hybrid method to derive dietary patterns in 7 years olds with explanatory ability of body mass index at age 10

European Journal of Clinical Nutrition volume 75, pages 1598–1606 (2021)Cite this article

Subjects

Abstract

Background/Objectives

The usual definition of dietary patterns only accounts for the explanation of dietary choices and not a specific health outcome. This could partially explain the lack of consistent associations between diet and related diseases. This study aims to identify dietary patterns in 7 years olds explaining body mass index (BMI) at age 10 and to assess their association with early-life factors (sociodemographic, birth, and infancy characteristics).

Methods

Children from the birth cohort Generation XXI at ages 7 and 10 were included (n = 4698). Diet was assessed by a validated food-frequency questionnaire. Measured BMI z-scores (zBMI) were calculated. Principal component analysis (PCA) and partial least squares (PLS) were run to derive dietary patterns.

Results

The component scores of PCA was able to explain 13.0% of food groups and only 0.2% of zBMI, while the PLS scores explained the variance of both food groups (10.1%) and zBMI at age 10 (4.2%). By using PLS, two dietary patterns were derived, but only one, higher in processed meats and energy-dense foods and lower in vegetable soup consumption, was significantly associated with an increased zBMI in 10 years olds (adjusted β̂ 0.032; 95% CI:0.017; 0.047). It was more likely followed by children from younger and less educated mothers and who were born heavier.

Conclusions

A dietary pattern higher in processed and energy-dense foods and with lower vegetable soup intake in 7 years olds significantly explained zBMI of 10 years olds, and was predicted by early-life characteristics. The other dietary patterns were not significantly associated with zBMI at age 10.

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Fig. 1: Flowchart of participants.
Fig. 2: Discriminatory power of methods to classify obesity by using the area under the curve (AUC) of receiver operating characteristic (ROC) curves.

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Acknowledgements

The authors are indebted to all participants for providing the data used in the Generation XXI birth cohort, as well to all members of the research team and its coordinators. The authors acknowledge the support from the Epidemiology Research Unit (EPI-Unit: UID-DTP/04750/2013; POCI-01-0145-FEDER-006862).

Funding

Generation XXI was funded by the Health Operational Programme—Saúde XXI, Community Support Framework III, and the Regional Department of Ministry of Health. This study was supported through FEDER from the Operational Programme Factors of Competitiveness—COMPETE and through national funding from the Foundation for Science and Technology—FCT (Portuguese Ministry of Education and Science) under the projects “Appetite and adiposity—evidence for gene-environment interplay in children” (IF/01350/2015) and “Appetite regulation and obesity in childhood: a comprehensive approach towards understanding genetic and behavioral influences” (POCI-01-0145-FEDER-030334; PTDC/SAU-EPI/30334/2017) and through the Investigator Contract (IF/01350/2015—AO). This study was also supported by the Calouste Gulbenkian Foundation.

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Authors and Affiliations

  1. Institute of Public Health of the University of Portoa, Porto, Portugal

    Andreia Pinto, Milton Severo & Andreia Oliveira

  2. Department of Public Health and Forensic Sciences, and Medical Education, Faculty of Medicine, University of Porto, Porto, Portugal

    Milton Severo & Andreia Oliveira

Authors
  1. Andreia Pinto
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  2. Milton Severo
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Contributions

AP performed statistical analyses and data interpretation and wrote the paper. MS performed statistical analyses and data interpretation. AO designed and conducted research and had primary responsibility for final content. All authors read and approved the final manuscript.

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Correspondence to Andreia Oliveira.

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Pinto, A., Severo, M. & Oliveira, A. Use of a hybrid method to derive dietary patterns in 7 years olds with explanatory ability of body mass index at age 10. Eur J Clin Nutr 75, 1598–1606 (2021). https://doi.org/10.1038/s41430-021-00883-9

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