Sachiko Ono

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Objective: To examine whether protein intake mediates the association between the number of remaining teeth and functional decline in older Japanese adults. Introduction: Tooth loss has been associated with reduced protein intake and functional decline in older adults. However, whether protein intake mediates this association remains unclear. Methods: We conducted a 6‐year longitudinal study using data from a cohort of community‐dwelling older adults. Participants aged ≥ 65 years were included. Exposure was the number of teeth (≥ 20, 10–19, and 0–9). The primary outcome was either functional decline or death, and the secondary outcome was weight change. Protein intake was measured using a diet history questionnaire. We used mediation analysis to examine the direct and indirect effects of the number of remaining teeth via protein intake on the outcomes. Results: Among 1400 eligible participants, the mean ages were 76.3, 76.6, and 78.9 years for groups with ≥ 20, 10–19, and 0–9 teeth, respectively. Protein intake did not mediate the association between the number of teeth and functional decline. In contrast, protein intake showed an indirect association between the number of remaining teeth and weight loss, particularly in individuals with 10–19 teeth than those with ≥ 20 teeth (indirect effect: −0.09% [−0.20, −0.01]). Conclusions: Although protein intake did not mediate the association between the number of remaining teeth and functional decline, it mediated the association between the number of remaining teeth and weight loss. Interventions targeting oral health and protein intake may prevent weight loss in older adults.

Background: Administrative claims data are increasingly used in oral health research, but their validity for identifying denture use has not been established. Objective: To evaluate the accuracy of algorithms based on dental claims codes for identifying denture users, dentist-reported oral health screening records were used as the reference standard. Methods: We analyzed data from 4,053 adults aged ≥65 y in the Longevity Improvement and Fair Evidence (LIFE) Study in Japan. Twelve algorithms incorporating 56 denture-related diagnosis and procedure codes were developed from claims in the 12 mo preceding the screening. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity analyses used a 6-mo claims window. A post hoc bias analysis was also performed. Results: During screening, 59.9% of the participants were classified as denture users. Algorithms based solely on diagnosis codes showed very high specificity (98.3%–100%) but low sensitivity (1.4%–20.8%). Among the procedure-based definitions, oral rehabilitation codes (algorithm f; denture adjustment or instruction) had the highest sensitivity (63.6%). The combined algorithm using both diagnosis and procedure codes (algorithm C) achieved the best balance, with 65.3% sensitivity, 96.6% specificity, 96.6% PPV, and 65.1% NPV. Similar findings were observed using the 6-mo claims data. Bias analysis indicated that the risks for denture use could be underestimated by 26% to 59%, with algorithm C showing the least bias. Conclusions: Denture use can be identified from dental claims data with moderate accuracy. Algorithms combining denture-related diagnosis and procedure codes or using oral rehabilitation codes provide practical definitions for research on oral and systemic health outcomes. Knowledge Transfer Statement: The result of this validated study can be identified as denture use from dental claims with moderate accuracy. In combination with validated denture use and the number of remaining teeth, it can expand opportunities to assess oral health status and its relationship with systemic health outcomes in large-scale epidemiologic studies using claims data.

Objectives: Administrative claims databases are increasingly used in dental research. However, inconsistencies in data coverage and the lack of a global overview remain as challenges. This review aimed to summarize worldwide studies using dental administrative claims databases, focusing on research questions, methodologies, and findings to identify key trends and knowledge gaps. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR), we conducted a scoping review of studies using dental administrative claims data published between January 2010 and December 2025. We structured the review question using the Population‐Concept‐Context framework. The original search through April 2022, as registered in PROSPERO, was updated in April 2026 using the same search strategy and eligibility criteria. We searched PubMed, Ovid MEDLINE, Ichushi‐Web, CiNii, Scopus, and Web of Science databases. Two reviewers independently screened the records, and disagreements were resolved by consensus. Cohort and case–control studies were critically appraised using the Newcastle–Ottawa Scale (NOS) to characterize the methodological quality of the mapped literature. Results: Following screening, 472 studies met the eligibility criteria. Most studies originated from the United States and Taiwan, indicating marked geographical concentration; the updated search added Switzerland and New Zealand. Research topics included treatment effectiveness, the epidemiology of rare conditions, healthcare utilization, and policy evaluation. Common limitations were insufficient clinical detail, variable data quality, and limited generalizability. Conclusions: This review highlights the expanding use of administrative claims databases in dental research and their inherent limitations. Future research should prioritize validating claims‐based diagnosis and procedure codes and linking claims data with clinical records.

Purpose Hematopoietic stem cell transplantation (HSCT) is associated with oral mucositis and infections due to intensive conditioning and immunosuppression. Although pretransplant oral management is recommended, its effectiveness remains unclear. This study examined the association between oral management by dentists before HSCT and the duration of severe oral mucositis, infections, and mortality using a nationwide inpatient database in Japan. Methods We conducted a retrospective cohort study using the Diagnosis Procedure Combination database. Patients who underwent HSCT between May 2018 and February 2022 were divided into two groups: those who received oral management by dentists before HSCT and those who did not. After 1:1 propensity score matching, we compared the duration of severe oral mucositis (defined as opioid use within 30 days after HSCT), infections (defined as concurrent use of antibiotics and blood cultures within 30 days after HSCT), and 30-day in-hospital mortality between the groups. Results Among the 15,911 eligible patients (mean age 49.0 ± 17.6 years), 5546 (34.9%) received pre-HSCT oral management. Propensity score matching yielded 4945 pairs. No significant differences were observed in the duration of severe oral mucositis or in-hospital mortality between groups. However, the patients receiving oral management had a lower incidence of infection than those without oral management (55.1 vs. 59.5%; risk difference, −4.4; 95% confidence interval, −6.4 to −2.5). Conclusion Pre-HSCT oral management by dentists may not reduce the duration of severe oral mucositis or all-cause mortality, but may reduce post-transplant infections. Further studies are warranted to clarify the components of oral management that most effectively affect oral mucositis and mortality.

Background: Administrative claims data are increasingly used in oral health research, however, their validity for identifying denture use has not been established. Objective: To evaluate the accuracy of algorithms based on dental claims codes for identifying denture users, dentist-reported oral health screening records were used as the reference standard. Methods: We analyzed data from 4,053 adults aged ≥65 years in the Longevity Improvement and Fair Evidence (LIFE) Study. Twelve algorithms incorporating 56 denture-related disease and procedure codes were developed from claims in the 12 months preceding the screening. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity analyses used a 6-month claims window. A post hoc bias analysis was also performed. Results: During screening, 59.9% of the participants were classified as denture users. Algorithms based solely on disease codes showed very high specificity (98.3–100%) but low sensitivity (1.4– 20.8%). Among the procedure-based definitions, oral rehabilitation (algorithm f) had the highest sensitivity (63.6%). The combined algorithm using both disease and procedure codes (algorithm C) achieved the best balance, with 65.3% sensitivity, 96.6% specificity, 96.6% PPV, and 65.1% NPV. Similar findings were observed using the 6-month claims data. Bias analysis indicated that the risks for denture use could be underestimated by 26–59%, with algorithm C showing the least bias. Conclusions: Denture use can be identified from dental claims data with moderate accuracy. Algorithms combining denture-related disease and procedure codes, or using oral rehabilitation codes, provide practical definitions for research on oral and systemic health outcomes.