Transdisciplinary Research in Energetics and Cancer (TREC) is an initiative from the National Cancer Institute (https://www.compass.fhcrc.org/trec/
) with two main foci: (1) to increase our understanding of the mechanisms underlying the associations between energy balance and carcinogenesis across the cancer continuum, from causation and prevention through survival; and (2) to develop effective innovative approaches with broad population impact at the social-environmental and policy levels for prevention of obesity, with particular emphasis on children and critical time periods during childhood where weight gain is likely. The Identifying Determinants of Eating and Activity (IDEA) project focuses on this second aim by examining predictors of youth obesity in a population-based sample.
The first research goal of the IDEA project was to develop a conceptual model to guide our research that would: (1) include multiple levels of influence; (2) focus on factors that showed evidence from previous research as being potential predictors of the development of obesity in youth; (3) focus on mutable factors that could be examined in future community-level health-promotion interventions; and (4) specify relationships between suggested predictive factors and the outcome of body mass index (BMI) and weight status in a causal pathway that could be tested in a single, comprehensive research trial.
The development of the TREC IDEA conceptual model began with a small team of investigators examining the peer-reviewed literature for factors suggested as related to the development of childhood obesity. A subset of levels of influence to be included in the conceptual model was identified, and, within each level of influence, a set of factors felt to be closest to energy balance and most likely mutable in intervention research. A theory-based framework was used to organize the levels of influence (Perry 1999
). A larger team of scientists, from a wide set of disciplines (including urban planning, exercise physiology, nutrition, epidemiology, physiologists, and psychology) were asked to review the draft model and provide input on the factors selected and the relationships suggested in the causal pathway.
shows the conceptual model developed to guide empirical research on the etiology of childhood obesity. We did not attempt to identify every possible association in the model and, while causal pathways are inferred, we believe that many, if not most, of the relationships are reciprocal and bi-directional.
Conceptual model: etiology of childhood obesity
The model posits that obesity-related risk factors in youth, including BMI percentile and body composition, are most closely and most directly affected by diet, biological and activity-related factors. In turn, biological factors are directly affected by youth weight status. Physiologically, an individual’s weight status is determined by metabolic interactions related to energy balance and the development of adiposity. In youth, pubertal status is well-recognized as influencing weight gain during critical developmental times and, conversely, weight status may affect pubertal development (Cook et al. 2003
). Less is known about how weight status may affect blood chemistry in youth. There is some evidence to suggest that glucose and lipid metabolism and inflammation and oxidative stress may be biological markers that manifest as possible risk factors for cancer, cardiovascular and metabolic disease and that these markers may be related to obesity (Dandona et al. 2005
; Lakka et al. 2002
; O’Byrne and Dalgleish 2001
; Reaven 1988
; Sinaiko et al. 2005
; Young-Hyman et al. 2001
). Examining the relationship of those biomarkers with weight status over time may provide important clues into how obesity affects risk factors for a number of chronic diseases.
Biological factors and energy balance are impacted by behavioral factors related to diet, activity and sedentary patterns, and other behaviors such as sleep, substance use and weight control behaviors. Dietary choices affect caloric intake and dietary patterns and specific eating behaviors, such as skipping breakfast, consumption of sugar-sweetened beverages. Eating a lot of fast food and not eating a lot of fruits, vegetables and whole grains have also been linked with obesity risk (Affenito et al. 2005
; Ebbeling et al. 2004
; Ludwig et al. 2001
; Newby 2007
). Behavioral choices related to the amount of physical activity and sedentary behaviors impact the energy expenditure side of the energy balance equation (Dietz and Gortmaker 1993
; Gortmaker et al. 1996
Other behaviors may impact both diet and activity levels. Recent research suggests a link between inadequate amount of sleep and obesity risk in adults (Gangwisch et al. 2005
; Hasler et al. 2004
; Singh et al. 2005
). The unusual sleep patterns of many adolescents suggest that the relationship between sleep and obesity risk, as well as unhealthy sleep patterns and diet, activity and sedentary behaviors, is worth examining in youth. Substance use, including tobacco and alcohol use, may also affect obesity risk through diet and activity-related factors (Lytle et al. 1995
; Pasch et al. 2007
; Strauss and Mir 2001
; Yeomans 2004
). A literature is also beginning to develop that suggests that behaviors related to weight control, even in youth at healthy weights, may actually predict the development of obesity in youth (Klein et al. 2008
; Neumark-Sztainer et al. 2006
Contextual factors exist at multiple levels, including the individual/psychosocial level (e.g., one’s beliefs, attitudes, values and expectations) and the socio-environmental level (e.g., interpersonal dynamics, role modeling, norms and support) that occur with families, among peers and within other community environments, specifically schools. The physical environment (e.g., the access to and support for healthy eating, recreational physical activity, and active transportation) is another important contextual factor that operates at the home, school, and neighborhood environments. The Geographical Information System (GIS) is an analysis tool for geographic data that is being used to assess the physical environment of neighborhoods (Melnick 2002
). The GIS provides for systematic mapping of neighborhood resources for healthy energy balance, including the presence of parks, playgrounds, healthful transportation options and leisure time activities, healthful food options and other spatial assets and barriers in the environment. Documentation of the physical environment may add substantially to our understanding of the neighborhood contexts influencing a healthy weight balance.
Demographics, socioeconomic factors, family history, and structure are immutable factors for community-level health-promotion efforts that influence the context wherein young peoples’ eating and activity behaviors occur, the behavioral opportunities presented to youth and many of their biological factors. Societal influences (such as media messages, portion sizes served in restaurants, cultural norms and expectations, and local, state and federal policy affecting economic conditions, food availability and the built environment) are even broader contextual factors potentially influencing obesity (IOM 2005
), but are not delineated in the present model because these factors are not easily changed in most health-promotion intervention research. In addition, by the nature of our longitudinal research, we were limited in the number of factors that we could operationalize and evaluate.
The model is designed to guide a wide range of analyses. These analyses include examining proximal and distal correlates and predictors of weight status, the potential interactive effects of the factors assessed at each level of the conceptual model, mediating and moderating effects of the contextual, behavioral, and biological factors and a variety of outcomes including behavioral, biological and weight-related endpoints. The immutable factors, including family demographics, socioeconomic factors, and family structure and history will be examined as effect modifiers. In addition, other mutable factors, such as weight status at baseline, psychosocial or family status, and school or neighborhood situation may also emerge as potential effect modifiers. Most of the constructs are measured in a youth/adult dyad, adding another layer of interactions and predictors that may be examined.