Elizabeth Krall Kaye

Objective: We examined whether taste or smell dysfunction was associated with untreated caries and if sugar intake modified the association. Methods: We used cross-sectional National Health and Nutrition Examination Survey (NHANES) data from 5,882 adults aged 40+ who completed the dental examination and Taste and Smell protocols in 2011–2014. Self-reported dysfunction was defined as reporting at least 1 problem with taste and smell. Objectively measured dysfunctions (2013–2014 only) included inability to identify bitter and salty solutions on whole-mouth taste tests and ≤5 odorants correctly identified on the 8-item Pocket Smell Test (PST). Caries was assessed by calibrated dental examiners. Logistic regression estimated the odds and 95% confidence intervals (CIs) for untreated caries among persons with dysfunction compared with those without dysfunction. Covariates included age, sex, race/ethnicity, smoking, flossing frequency, alcohol use, dry mouth, and diabetes. Effect modification by added sugar level (<10% vs. ≥10% of calories) was examined. Results were weighted to account for the NHANES survey design. Results: Fourteen percent of participants self-reported problems with smell, 9% with taste, and 9% with both. Measured taste dysfunction prevalence was 11% to 17%, and 12% had significant smell loss on the PST. Adjusted odds of untreated caries were higher in participants who self-reported both taste and smell problems compared to neither (odds ratio [OR] = 1.38; 95% CI, 1.03–1.84). Added sugar level modified the association between measured ability to taste bitterness and caries: nontasters with high added sugar intake had twice the odds of caries as tasters with low added sugar intake (OR = 2.03; 95% CI, 1.35–3.05). Smell dysfunction alone, self-reported or measured, was not significantly associated with caries. Conclusion: Perceived dysfunction of taste and smell and inability to taste bitterness at high added sugar intakes were associated with increased odds of untreated caries. Screening for chemosensory dysfunction may identify persons with greater risk of dental caries and facilitate referral to a dentist. Knowledge Transfer Statement: Screening for taste dysfunction in primary care and community-based settings may identify persons with greater risk of dental caries and facilitate referral to a dentist.

Objectives To systematically review the association between education and tooth loss.Methods We performed an electronic search of PubMed following PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines with a focused PICO (population/problem, intervention, comparison, outcome) question: are adults with low educational attainment more prone to tooth loss than adults with higher education? Observational studies published between 2000-2022 examining adults ≥18 years with clinical or self-reported tooth loss were included. Quality of the reports was established using the Newcastle-Ottawa Scale.Results We identified 30 studies (735,576 individuals) across 15 countries. The majority were cross-sectional (90%) and rated as low/moderate quality (67%). Educational level was assessed as years of schooling or categorical attainment. Tooth loss was measured through clinical examination (53.3%) or self-report (46.7%). Primary education or less was consistently linked to higher likelihood of edentulism (odds ratio [OR] range: 2-4.9), fewer remaining teeth (OR range: 1.2-5.8), and greater tooth loss (OR range: 1.2-2.1) relative to higher levels. A university degree significantly reduced the odds of edentulism or tooth loss (OR range 0.3-0.75) compared to lower levels.Conclusions Lower educational attainment is associated with increased tooth loss. These findings provide a foundation for developing evidence-based policies and targeted interventions to address tooth loss in vulnerable populations.

Introduction: Obesity is associated with increased periodontal disease prevalence and incidence. This retrospective cohort study examined whether body mass index (BMI) is an effect modifier of periodontal treatment outcomes in patients attending an urban dental school clinic. Methods: Data were extracted from electronic health records of 344 patients at a large urban dental school clinic who had at least 1 tooth with a probing pocket depth (PD) ≥5 mm at baseline and who subsequently received nonsurgical periodontal treatment. BMI was computed from self-reported weight and height and categorized as obese (≥30 kg/m ² ), overweight (25–29.9 kg/m ² ), or healthy (18–24.9 kg/m ² ). The primary treatment outcome of interest was defined as having no teeth with PD ≥5 mm in a quadrant on follow-up after nonsurgical periodontal therapy. That outcome was considered to represent treatment success in this study. Secondary outcomes included changes in mean PD and clinical attachment loss (CAL). Analyses included 879 treated quadrants among 344 patients (185 males, 159 females; mean age 49 ± 12 y at baseline; mean posttreatment follow-up of 6 ± 2 mo). Clinical outcomes in patients who were overweight or obese were compared to healthy-weight patients using generalized linear models for binary or continuous outcomes, accounting for clustering within patients. Covariates were age, gender, tobacco use, history of diabetes, insurance type, and number of baseline sites ≥5 mm. Results: Obesity was associated with a significantly lower likelihood of successful nonsurgical treatment (odds ratio = 0.47; 95% confidence interval, 0.25–0.88) than healthy weight. Being overweight was not associated with treatment success. Posttreatment reductions in the percentage of sites with pockets ≥5 mm and CAL ≥5 mm were greater in patients with healthy weight as compared to those either overweight or obese. However, posttreatment changes in mean PD and CAL did not differ among the BMI groups. Conclusions: Obesity adversely modifies the effectiveness of nonsurgical periodontal treatment among dental school clinic patients. Knowledge Transfer Statement: The results of this study may be used by dental providers to better understand and manage periodontal therapy in patients with obesity. Furthermore, patients will be better informed about their therapeutic options and outcome success.

Aim: To illustrate the use of joint models (JMs) for longitudinal and survival data in estimating risk factors of tooth loss as a function of time‐varying endogenous periodontal biomarkers (probing pocket depth [PPD], alveolar bone loss [ABL] and mobility [MOB]).Materials and Methods: We used data from the Veterans Affairs Dental Longitudinal Study, a longitudinal cohort study of over 30 years of follow‐up. We compared the results from the JM with those from the extended Cox regression model which assumes that the time‐varying covariates are exogenous.Results: Our results showed that PPD is an important risk factor of tooth loss, but each model produced different estimates of the hazard. In the tooth‐level analysis, based on the JM, the hazard of tooth loss increased by 4.57 (95% confidence interval [CI]: 2.13–8.50) times for a 1‐mm increase in maximum PPD, whereas based on the extended Cox model, the hazard of tooth loss increased by 1.60 (95% CI: 1.37–1.87) times.Conclusions: JMs can incorporate time‐varying periodontal biomarkers to estimate the hazard of tooth loss. As JMs are not commonly used in oral health research, we provide a comprehensive set of R codes and an example dataset to implement the method.

Introduction: Obesity is associated with greater utilization of medical resources, but it is unclear if a similar relationship exists for dental care. Objectives: This retrospective cohort study compared periodontal disease treatment among obese, overweight, and normal-weight patients attending an urban US dental school clinic. Methods: Periodontal, demographic, and medical history data for 3,443 adult patients examined between July 1, 2010, and July 31, 2019, were extracted from electronic health records. Body mass index (BMI) was computed from self-reported height and weight and categorized as obese (≥30 kg/m²), overweight (25–29.9 kg/m²), or normal (18–24.9 kg/m²). Periodontal disease was categorized using clinical probing measures. Procedure codes defined treatment type (surgical, nonsurgical, local chemotherapeutics, or none). Logistic regression models controlling for initial periodontal disease severity, age, gender, tobacco use, history of diabetes, dental insurance type, and follow-up (log of days) estimated odds ratios (ORs) and 95% confidence intervals (CIs) of any treatment among obese and overweight relative to normal-weight patients. The association between BMI and a periodontal treatment intensity score, based on treatment type, number of teeth treated, and number of visits, was evaluated with multivariable negative binomial regression. Results: Mean age at baseline was 44 ± 15 y, and severe periodontal disease was present in 32% of obese, 31% of overweight, and 21% of normal-weight patients. Average follow-up was 3.9 ± 1.6 y. Obese and overweight patients were more likely to have nonsurgical scaling and root planing or surgical procedures than normal-weight patients. Adjusted odds of any treatment were higher among obese (OR = 1.34; 95% CI, 1.14–1.72) and overweight (OR = 1.18; 95% CI, 0.97–1.42) relative to normal weight. Obese and overweight patients had 40% and 24% higher treatment intensity scores, respectively, than normal-weight patients. Conclusion: These results indicate obese and overweight individuals require more intensive periodontal treatment compared to normal-weight individuals, independent of initial disease severity. Knowledge of Transfer Statement: The results of this study can be used by dental providers and policymakers to better understand patient characteristics that influence the variability in frequency and length of periodontal treatment. Knowledge of a patient’s body mass index may be useful in identifying patients who possibly will have a poorer periodontal prognosis.