Childhood overweight: a contextual model and recommendations for future research
Article first published online: 21 DEC 2001
Volume 2, Issue 3, pages 159–171, August 2001
How to Cite
Davison, K. K. and Birch, L. L. (2001), Childhood overweight: a contextual model and recommendations for future research. Obesity Reviews, 2: 159–171. doi: 10.1046/j.1467-789x.2001.00036.x
- Issue published online: 21 DEC 2001
- Article first published online: 21 DEC 2001
The prevalence of overweight among children has doubled within the past two decades. Increases in the rate of childhood overweight are of particular concern due to the negative health and psychological effects noted among overweight children. As shown by previous research, the development of childhood overweight involves a complex set of factors from multiple contexts that interact with each other to place a child at risk of overweight. This multifaceted system can be conceptualized using Ecological Systems Theory (EST). EST highlights the importance of considering the context(s), or ecological niche, in which a person is located in order to understand the emergence of a particular characteristic. In the case of a child, the ecological niche includes the family and the school, which are in turn embedded in larger social contexts including the community and society at large. In this review, EST is used as a framework with which to summarize research assessing predictors of childhood overweight. Specifically, child characteristics that place children at risk of the development of overweight (including dietary intake, physical activity, and sedentary behaviour) will be reviewed while taking into consideration the influence of the familial environment, the school environment, and the community and larger social environments. It is concluded that future research needs to adopt a broader contextual approach in order to understand and intervene against the processes leading to the development of overweight among children and that the use of theories or paradigms such as EST will facilitate developing and testing models of causal processes.