Advancing precision public health for obesity in children

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.

Automated summary

Globally, the number of children and adolescents suffering from obesity is alarmingly high, with rates continuing to rise despite efforts of public health initiatives. This review examines the potential of precision public health in preventing childhood obesity and discusses its advancements in the field. Although the concept of precision public health is still evolving and lacks sufficient literature, recent studies in surveillance, risk factor identification, intervention, evaluation, and implementation have shown promising use of big data to address obesity in children. Challenges in data access, integration, inclusivity, ethics, and policy translation need to be addressed for precision public health to contribute to effective obesity prevention in children.