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Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making
FIGURE 1-4 Percent of children and youth aged 2-19.9 who are obese (defined as BMI ≥ 95th percentile based on CDC growth charts), by family poverty−income ratio.
NOTES: The poverty−income ratio is the ratio of the income of the family to family income at the poverty level. Families with an income ratio of < 1 are below the poverty threshold.
SOURCE: Freedman et al., 2007.
While obesity is a priority from an epidemiologic and health status perspective, it gains further precedence because of the way it influences other aspects of American society. Obesity carries substantial direct and indirect costs for the nation’s economy, such as discrimination, economic disenfranchisement, lost productivity, and disability. As a result, states and communities end up diverting resources to prevention and treatment, and the nation’s health care system is burdened with the comorbidities of obesity, such as type 2 diabetes, hypertension, cardiovascular disease, osteoarthritis, and cancer (IOM, 2005). According to a recent analysis (Finkelstein et al., 2009), the annual medical burden of obesity is nearly 10 percent of all medical spending and may have risen to $147 billion per year by 2008. Further, obesity places at risk the long-term welfare and readiness of the U.S. military services by reducing the pool of individuals eligible for recruitment and decreasing the retention of new recruits (IOM, 2005). In addition to these societal costs, obesity imposes a broad range of costs on individuals. Tables 1-1 and 1-2, respectively, highlight the myriad effects of adult and child obesity on physical and mental health and quality of life.
DECISION MAKING, OBESITY PREVENTION, AND EVIDENCE NEEDS
In an ideal world, perhaps, policy decisions would be made primarily as a result of review and analysis of a carefully selected body of evidence that provided certainty and specificity as to the best approach or approaches, the outcomes that would result, and the cost of achieving those outcomes. However, real-life experience demonstrates that policy or programmatic decision making is not always such a linear process and that initiatives grounded in an idea generated by a research study may be the exception. Formal evidence may be used in highly variable ways, at different stages of a