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Review
. 2023 Oct;24(5):1003-1010.
doi: 10.1007/s11154-023-09802-8. Epub 2023 Apr 14.

Advancing precision public health for obesity in children

Affiliations
Review

Advancing precision public health for obesity in children

Jennifer L Baker et al. Rev Endocr Metab Disord. 2023 Oct.

Abstract

Worldwide, far too many children and adolescents are living with the disease of obesity. Despite decades of public health initiatives, rates are still rising in many countries. This raises the question of whether precision public health may be a more successful approach to preventing obesity in youth. In this review, the objective was to review the literature on precision public health in the context of childhood obesity prevention and to discuss how precision public health may advance the field of childhood obesity prevention. As precision public health is a concept that is still evolving and not fully identifiable in the literature, a lack of published studies precluded a formal review. Therefore, the approach of using a broad interpretation of precision public health was used and recent advances in childhood obesity research in the areas of surveillance and risk factor identification as well as intervention, evaluation and implementation using selected studies were summarized. Encouragingly, big data from a multitude of designed and organic sources are being used in new and innovative ways to provide more granular surveillance and risk factor identification in obesity in children. Challenges were identified in terms of data access, completeness, and integration, ensuring inclusion of all members of society, ethics, and translation to policy. As precision public health advances, it may yield novel insights that can contribute to strong policies acting in concert that ultimately lead to the prevention of obesity in children.

Keywords: Children; Obesity; Precision public health.

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Conflict of interest statement

JLB reports no potential conflicts of interest related to this manuscript and declares having received consulting fees from Novo Nordisk Denmark A/S. LGB reports no potential conflicts of interest.

Figures

Fig. 1
Fig. 1
Precision public health framework Designed data are collected for a pre-specified purpose (e.g. administrative databases, disease registries, cohorts, trials, surveys). Organic data are generated through other processes that were not specifically designed for research (e.g. electronic health records [EHRs], electronic maps, insurance claims databases, mobile health, social media)

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