Oral health is a matter of public health concern because it affects a large proportion of the population and is linked with general health status. Early intervention strategies to address oral health problems can prevent illness, diagnose serious conditions early, and maintain optimum overall health. The landmark publication, Oral Health in America: A Report of the Surgeon General, highlighted a lack of awareness of the importance of oral health among the general public, and found a significant disparity between racial and socioeconomic groups with regard to oral health and ensuing overall health issues. Developing interventions to improve oral health for older adults is a particular challenge, given the complex set of causal pathways and delays over the life course that are involved. System dynamics (SD) is an approach and a set of conceptual tools that enables understanding of the structure and dynamics of complex systems. SD simulation models help policymakers assess the impact of different interventions to find those that may yield the greatest leverage in the short term and in the longer term. We hypothesize that: (1) oral health in older adults is due to the lifelong accumulation of advantageous and disadvantageous experiences at multiple scales, from the micro-scale of the mouth to the societal scale that involves US federal policy, including lack of routine dental care coverage under Medicare;and (2) factors at the neighborhood scale (e.g., community access), interpersonal scale (e.g., oral health promotion), and individual scale (e.g., nutrition and chronic illness) may be particularly important in influencing dental health outcomes such as tooth retention, dental caries, and periodontal disease. It is critical to consider the complex relationships across all scales as is possible using SD conceptual tools to develop and implement interventions for older adults that cannot be gained by studying component parts in isolation. To address these hypotheses and leverage opportunities to improve dental health in older adults in Harlem and Washington Heights/Inwood, New York City, our specific aims are to:
Aim 1 : Build an SD model of factors affecting tooth retention in older adults using a group modeling process. (A) Refine our causal map through input from practitioners and policy scholars in oral health and aging. (B) Calibrate our SD model based upon the local population and local conditions in northern Manhattan.
Aim 2 : Evaluate the performance of our SD model to project the potential impacts of proposed interventions. (A) Produce a status quo simulation that assumes continuation of existing programs at current levels. (B) Examine the effects of alternative interventions involving, e.g., treatment and oral hygiene activity, on the prevalence and burden of tooth loss and other oral diseases using simulations from our SD model. (C) Compare the predictive performance of our SD model with regression models of dental health. Successful completion of these aims will aid in identifying interventions that are more effective and cost-saving than others, to provide policymakers with an indication of where scarce resources ought to be focused to improve oral health in older adults at the local level and at broader levels.
Developing interventions to improve dental health for older adults is a challenge, given the complex set of causal pathways and delays that are involved. System dynamics (SD) is an approach that enables increased understanding of the structure and dynamics of complex systems. SD simulation models generate results to cogently inform dental health practitioners and policymakers of where scarce resources ought to be focused.
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