Energy, energy balance, complexity theory and human health with an emphasis on obesity

Abstract

This thesis tests the proposition that much of the escalating human health problem of adult obesity and related conditions is caused by difficulties in managing energy in the human body. Obesity can be examined as a complex system that has two parts: an internal energy balance system and a system comprising external obesogenic drivers. This complexity is important because a complex system is characterized by unpredictability, nonlinearity, emergent properties and self-organization which may be central to the apparent intractability of obesity. Consistently, the research carries out an analysis to gain insight by applying complex system theory. The research question posed is: Would a model intervention applying Bayesian networks making intelligent inferences, in the context of the apparent complex systems associated with human energy balance and obesogenic factors in the built and natural environments, assist in managing adult obesity by improving the cooperation between practitioner and patient and improving the efficiency of treatment? The research is driven by the relationship of energy and energy balance to obesity and related health conditions including certain cancers and diabetes. The community costs of these conditions are projected by the Milken Institute to reach $4.2 trillion by 2023 in the United States alone. In direct human effect, the Australian Institute of Health and Welfare advise that 63% of adults in the Australian population are overweight or obese. The methodology adopted for the research employs analysis involving representative obesogenic variables identified in domains of biology, society, the food industry and governance. Variables are considered from the view of human ecology, medical science, statistics and complexity theory. The broad range of representative variables is intersected with the internal energy balance system to show their impact on obesity in the body. This intersection may permit the complexity of the energy-obesity system to be understood to the point where interventions can be devised. Based on this analysis, a model intervention using multiple Bayesian networks is developed that may serve as a useful approach to the management of obesity. The research reveals that: - There are many external variables that influence obesity. - Energy balance in the human body appears to be complex in terms of complexity theory with many health effects. - The complex energy-obesity system may be partly understood by intersecting external obesogenic variables with variables in the internal energy balance system. - A model intervention can be demonstrated that may have an impact on the obesity problem. The findings are significant because: - The energy-obesity complex system reveals insights into causes of obesity and related health conditions. - The model intervention may be developed to provide a possible useful degree of management of the obesity problem. - The design of the model intervention recognizes that obesity is dynamic and changes over time. The degree of complexity involved in the obesity problem introduces considerable uncertainty. Accordingly, the model makes intelligent inferences that reflect this uncertainty. It also supports the sharing of knowledge between patient and practitioner to achieve potentially better outcomes. The model is developed to a working model stage that could possibly be further developed to become a practical intervention to assist in managing obesity. Show more