Search

Dental caries among long-term care (LTC) residents is a persistent and complex problem driven by social and structural factors. Systems thinking may be useful in considering novel approaches to reducing disease. This study aimed to develop a system dynamics model to simulate the progression of dentate older adults in LTC through caries severity states and estimate the effects of 3 intervention scenarios on the progression of caries: preventive topical fluoride (TF), arrest of caries with silver diamine fluoride (SDF), and a combination of TF and SDF. Dentate older adults in LTC were categorized into 4 caries severity states by their number of untreated carious lesions. The model assumed that changes in severity states were consistent with incidence rates reported in the literature and available billing data for dental care and that individuals move in and out of the system by entering and exiting the facility or experiencing edentulism. For all scenarios, the proportion of dentate older adults in LTC with 1 or more untreated lesions stays stable, the distribution of disease shifts from a high severity state, and the system approaches equilibrium after 4 y. The TF intervention predicts minimal impacts on decreasing the proportion of dentate older adults with 1 or more untreated lesions (2.5% decrease), while the SDF intervention and the combination interventions were most disruptive. There was a 29.6% and 33.6% decrease, respectively. Given the specific population dynamics in LTC, these findings suggest that long-term (greater than 4 y) interventions should be designed to address both the management of existing lesions and their incidence. This system dynamics model allows researchers to render institution-specific data points from LTCs to estimate the effects of proposed interventions at the respective site. [ABSTRACT FROM AUTHOR]

This longitudinal cohort study examines if 1) cognitive decline varies by birth cohort, adjusting for covariates, and 2) edentulism and nonuse of dental care predict 10-y cognitive decline (2008–2018). The Health and Retirement Study (HRS) features a representative sample of US adults over age 50. Eligibility criteria included having cognitive interview data available and responding to the question, "Have you lost all of your upper and lower natural permanent teeth?" at 2+ time points between 2006 and 2018. Use of dental care in the past 2 y was assessed. Linear mixed models for repeated measures estimated the trajectories of mean cognition over time for the birth cohorts, adjusted for baseline cognition, dentition status, dental care use, and covariates (demographic characteristics, health behaviors, and medical conditions). Cohort-by-time interaction terms were included to assess if cognitive decline varied by birth cohort. Ten-year change in cognition status (measured by HRS Cogtot27)—categorized as dementia (<7); cognitive impairment, not demented (7-11) 7≤Cogtot27<12; and normal (≥12)—was also investigated according to birth cohort, dentition status, and dental care use. Mean (SD) baseline age was 63.4 (10.1) y (n = 22,728). Older birth cohorts had greater cognitive decline than younger cohorts. Linear mixed-model estimates and 95% confidence intervals for protective factors for cognitive decline included higher baseline cognition (HRS Cogtot27) (0.49; 0.48–0.50), use of dental care in the past 2 y (0.17; 0.10–0.23), and covariates such as greater household wealth and being married. Risk increased with being edentulous (−0.42; −0.56 to −0.28), history of stroke or diabetes, less education, Medicaid recipient, current smoker, loneliness, and poor/fair self-rated health. Edentulism and irregular dental care are among important predictors of cognitive decline. Tooth retention and regular dental care throughout life appear to be important for maintaining oral and cognitive health. [ABSTRACT FROM AUTHOR]