ABSTRACT
Purpose
To examine whether reduced functional occlusal support is associated with incident hip fracture in older adults and whether this association varies according to denture‐related status.
Methods
We conducted a retrospective cohort study using a large administrative claims database in Japan. Adults aged 65 years or older with baseline tooth‐chart information and no prior hip fracture were included. Functional occlusal support was classified using the Eichner classification, a prosthodontically relevant measure of posterior occlusal support. The primary outcome was incident hip fracture identified from medical claims. Cox proportional hazards models were used with sequential adjustment for demographic characteristics, osteoporosis‐related factors, neurologic and vascular comorbidities, and hospitalization history. Additional analyses included piecewise Cox models by follow‐up interval and a 1‐year landmark analysis.
Results
Among 3 349 245 participants, lower functional occlusal support was associated with a higher risk of hip fracture. In the fully adjusted model, hazard ratios were 1.21 for Eichner class B and 1.44 for class C, compared with class A. The association varied according to denture‐related status, with significant interaction terms for class B and class C. Findings were broadly consistent in time‐interval and landmark analyses. Median follow‐up was 5.66 years, during which 93 921 hip fractures occurred, corresponding to an overall incidence rate of 5.17 per 1000 person‐years.
Conclusions
Reduced functional occlusal support was associated with a higher risk of hip fracture in older adults. These findings suggest that prosthodontically relevant functional oral status may have clinical significance beyond oral outcomes alone, although causal interpretation is limited in claims‐based observational data.
Keywords: claims database, denture‐related status, Eichner classification, hip fracture, occlusal support, older adults
In a large Japanese claims‐based cohort of older adults, lower functional occlusal support defined by the Eichner classification was associated with a higher risk of incident hip fracture. Compared with Eichner class A, the adjusted hazard ratios were 1.21 for class B and 1.44 for class C. The association varied according to denture‐related status.
1. Introduction
As populations age, falls and fragility fractures remain major health concerns in older adults, making their prevention important from both clinical and public health perspectives [1]. Hip fracture is among the most serious fall‐related outcomes in later life because it is associated with functional decline, loss of independence, and excess mortality [2, 3].
In the oral health domain, tooth loss and reduced occlusal support may impair masticatory efficiency and alter dietary intake, thereby affecting nutritional status and contributing to declines in physical function and frailty [4, 5, 6]. In this context, functional aspects of oral status, such as occlusal support and masticatory function, may provide clinically relevant information beyond the simple count of remaining teeth. Recent evidence has also suggested that reduced oral function is associated with a higher risk of falls in older adults [7].
One possible pathway linking oral function to fracture risk is impaired postural control. Reduced occlusal support may be associated with altered balance and mobility through changes in masticatory function, postural regulation, and related physical performance [8, 9]. From a clinical prosthodontic perspective, this suggests that poor functional oral status may be linked not only to oral impairment but also to serious fall‐related outcomes such as hip fracture.
Importantly, reduced occlusal support is a potentially modifiable condition. Previous studies have suggested that poor dental status is associated with incident falls and fall‐related fractures in older adults, and that denture use may attenuate these associations [10, 11]. However, longitudinal evidence on the association between occlusal support and hip fracture risk remains limited, and the extent to which this association varies according to denture‐related status remains unclear, particularly in large real‐world populations. A recent study reported an association between the number of teeth and incident hip fracture in adults aged 75 years or older, but data focusing on functional occlusal support remain scarce [12]. Therefore, using a large anonymized administrative claims database in Japan, we conducted a retrospective cohort study to examine whether lower functional occlusal support was associated with a higher risk of incident hip fracture in older adults and whether this association varied according to denture‐related status. Occlusal support was assessed using the Eichner classification.
2. Materials and Methods
2.1. Data Source
This retrospective cohort study used a large anonymized administrative claims database maintained by DeSC Healthcare Inc., which includes medical, dental, and pharmacy claims data [13]. The contracted dataset covered healthcare utilization records from April 1, 2014, to March 31, 2025. The database comprises beneficiaries of employment‐based health insurance societies and their dependents and allows longitudinal follow‐up through a unique anonymized identifier.
2.2. Study Design and Participants
We conducted a retrospective cohort study of adults aged 65 years or older who had dental claims containing tooth‐chart information sufficient to assess occlusal support during the observation period. Sufficient tooth‐chart information was defined as tooth‐level records for maxillary and mandibular permanent teeth that allowed determination of the presence or absence of opposing contacts required for Eichner classification. The baseline date was defined as the first record with assessable tooth‐chart information. Individuals with a history of proximal femoral fracture before baseline were excluded. To reduce potential misclassification related to month‐level date imputation, we also excluded individuals with an incident proximal femoral fracture recorded on the baseline date. The final analytic cohort comprised 3 349 245 participants. Details of participant selection are shown in Figure 1.
FIGURE 1.
Flowchart of participant selection.
This study was approved by the Ethics Committee of Osaka Dental University (approval No. 111438). The requirement for informed consent was waived because of the retrospective use of anonymized data, in accordance with applicable regulations and the Declaration of Helsinki.
2.3. Assessment of the Number of Remaining Teeth
The number of remaining teeth at baseline was derived from tooth‐chart information recorded in dental claims. Following the approach of Tamada et al. [14], only permanent teeth recorded as present were counted. When tooth charts were recorded multiple times within the same service month, the maximum number of present teeth recorded in that month was used. The baseline number of remaining teeth was defined as the total number of present permanent teeth recorded in the baseline month. Third molars were included in this count; therefore, the maximum possible number of teeth was 32.
2.4. Definition of Edentulism
Edentulism was defined as the absence of any permanent teeth at baseline. Because a value of zero teeth may also occur when tooth‐chart information is not entered, we minimized misclassification by confirming edentulism only when zero permanent teeth were recorded for at least two consecutive months within the 12 months before baseline. Tooth‐chart information recorded for other dental services, including denture‐related care, was used even when periodontal examinations were not performed.
2.5. Assessment of Occlusal Support and Eichner Classification
Functional occlusal support was assessed using baseline tooth‐chart information and categorized according to the Eichner classification. Permanent maxillary and mandibular teeth were identified, and posterior occlusal support was evaluated bilaterally across four support zones: the right and left premolar regions and the right and left molar regions. A support zone was considered present when at least one pair of opposing teeth was present in that zone. Third molars were excluded from this assessment. Participants were classified as Eichner class A (four support zones; corresponding to Eichner subgroup A), class B (one to three support zones or anterior contact without posterior occlusal support, corresponding to Eichner subgroups B1‐B4), or class C (no occlusal contacts, corresponding to Eichner subgroup C). Edentulous participants were included in class C. The Eichner classification was fixed at baseline and used for subsequent analyses. This classification reflects the extent of posterior occlusal support and is clinically relevant in prosthodontic assessment.
2.6. Definition of Denture‐Related Status
Denture‐related status was determined from dental claims during the 12 months before baseline as a claims‐based proxy for denture‐related care. Participants were classified as having denture‐related care if at least one dental procedure code corresponding to denture‐related care was recorded during this period, including placement, adjustment, repair, remake, or relining of removable partial or complete dentures. All other participants were classified as having no denture‐related care. Denture‐related status was ascertained independently of the number of remaining teeth and the Eichner classification and was fixed at baseline.
2.7. Outcome Definition
The primary outcome was incident hip fracture, defined as proximal femoral fracture identified in medical claims using ICD‐10 codes S72.0, S72.1, or S72.2 [15, 16]. To exclude prevalent fractures, individuals with any of these codes recorded before baseline were excluded. To reduce potential misclassification related to month‐level date imputation, individuals with an incident proximal femoral fracture recorded on the baseline date were also excluded from the primary analysis. Follow‐up started on the baseline date and continued until the first incident hip fracture, death, loss of insurance eligibility, or the end of the database period (March 31, 2025), whichever came first. Follow‐up time was calculated in days, with days since baseline used as the time scale.
2.8. Covariates
Covariates were defined using claims recorded during the 12 months before baseline. Age at baseline was categorized in 5‐year increments (65–69 years [reference], 70–74, 75–79, 80–84, 85–89, and ≥ 90 years), and sex was treated as a binary variable.
Factors directly related to fracture risk included a history of osteoporosis (ICD‐10 codes M80, M81, or M82), use of osteoporosis medications (ATC codes M05B or H05A), and systemic corticosteroid use (ATC code H02). As neurologic and vascular factors potentially related to falls and fracture risk, we defined a history of dementia (ICD‐10 codes F00, F01, F02, F03, or G30), a history of cerebrovascular disease (ICD‐10 codes I60‐I69), and use of central nervous system medications (ATC codes N05 or N06). Hospitalization history was defined as at least one inpatient claim during the 12 months before baseline. All covariates other than age were treated as binary variables.
2.9. Statistical Analysis
Time‐to‐event analyses were performed for incident hip fracture. Hip fracture‐free survival was estimated using the Kaplan–Meier method, and differences among Eichner classes were assessed using the log‐rank test. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. Model 0 was unadjusted; Model 1 was adjusted for age and sex; Model 2 was additionally adjusted for osteoporosis‐related factors; and Model 3 was further adjusted for dementia, cerebrovascular disease, central nervous system medication use, and prior hospitalization. Model 4 additionally included denture‐related status and an interaction term between Eichner class and denture‐related status to assess effect modification.
The proportional hazards assumption was evaluated using Schoenfeld residuals. Because time dependency was suggested for the primary exposure, we performed piecewise Cox analyses across follow‐up intervals of 0–2, 2–5, and 5–10 years, with administrative censoring at 10 years for this analysis. To assess potential reverse causation, we also performed a 1‐year landmark analysis excluding fractures within the first year after baseline and defining the risk set from day 365 onward; only participants who remained under observation for at least 1 year were included. All analyses were performed using R version 4.5.2 (R Foundation for Statistical Computing, Vienna, Austria). ChatGPT (OpenAI) was used to assist with drafting R scripts for dataset construction and statistical analyses. All generated code was reviewed, tested, and revised by the authors as needed, and the authors take full responsibility for the integrity of the analyses and the content of the manuscript.
3. Results
3.1. Participant Characteristics
The final analytic cohort comprised 3 349 245 individuals, including 1 357 106 in Eichner class A, 1 587 740 in class B, and 404 399 in class C (Table 1). Age distributions differed significantly across groups (p < 0.001), with a higher proportion of very old adults in class C (aged ≥ 90 years: 1.7% in class A, 3.8% in class B, and 9.7% in class C). Sex also differed significantly across groups (p < 0.001).
TABLE 1.
Baseline characteristics according to Eichner classification.
| Eichner class A | Eichner class B | Eichner class C | p | |
|---|---|---|---|---|
| (n = 1 357 106) | (n = 1 587 740) | (n = 404 399) | ||
| Age group | ||||
| 65–69 years | 318 289 (23.5) | 232 741 (14.7) | 29 940 (7.4) | < 0.001 |
| 70–74 years | 216 516 (16.0) | 212 037 (13.4) | 35 901 (8.9) | |
| 75–79 years | 561 418 (41.4) | 680 146 (42.8) | 146 677 (36.3) | |
| 80–84 years | 167 815 (12.4) | 261 734 (16.5) | 89 346 (22.1) | |
| 85–90 years | 69 987 (5.2) | 140 245 (8.8) | 63 491 (15.7) | |
| 90+ years | 23 081 (1.7) | 60 837 (3.8) | 39 044 (9.7) | |
| Sex | ||||
| Male | 560 905 (41.3) | 634 109 (39.9) | 167 141 (41.3) | < 0.001 |
| Female | 796 201 (58.7) | 953 631 (60.1) | 237 258 (58.7) | |
| Osteoporosis | ||||
| Yes | 99 817 (7.4) | 126 630 (8.0) | 36 720 (9.1) | < 0.001 |
| No | 1 257 289 (92.6) | 1 461 110 (92.0) | 367 679 (90.9) | |
| Use of anti‐osteoporosis medications | ||||
| Yes | 107 024 (7.9) | 133 542 (8.4) | 41 109 (10.2) | < 0.001 |
| No | 1 250 082 (92.1) | 1 454 198 (91.6) | 363 290 (89.8) | |
| Systemic corticosteroid use | ||||
| Yes | 276 318 (20.4) | 318 566 (20.1) | 87 029 (21.5) | < 0.001 |
| No | 1 080 788 (79.6) | 1 269 174 (79.9) | 317 370 (78.5) | |
| Dementia | ||||
| Yes | 33 704 (2.5) | 56 703 (3.6) | 25 031 (6.2) | < 0.001 |
| No | 1 323 402 (97.5) | 1 531 037 (96.4) | 379 368 (93.8) | |
| Cerebrovascular disease | ||||
| Yes | 78 560 (5.8) | 105 746 (6.7) | 34 376 (8.5) | < 0.001 |
| No | 1 278 546 (94.2) | 1 481 994 (93.3) | 370 023 (91.5) | |
| Use of CNS medications | ||||
| Yes | 314 264 (23.2) | 395 821 (24.9) | 116 613 (28.8) | < 0.001 |
| No | 1 042 842 (76.8) | 1 191 919 (75.1) | 287 786 (71.2) | |
| Hospitalization within the preceding 12 months | ||||
| Yes | 129 751 (9.6) | 175 176 (11.0) | 61 111 (15.1) | < 0.001 |
| No | 1 227 355 (90.4) | 1 412 564 (89.0) | 343 288 (84.9) | |
| Denture‐related status at baseline | ||||
| With denture‐related care | 156 226 (11.5) | 815 502 (51.4) | 317 685 (78.6) | < 0.001 |
| Without denture‐related care | 1 200 880 (88.5) | 772 238 (48.6) | 86 714 (21.4) | |
Note: Values are presented as number (percentage). All variables were assessed at baseline. p‐values were calculated using the chi‐square test. History of osteoporosis, medication use, steroid use, dementia, cerebrovascular disease, CNS medication use, hospitalization, and denture‐related status were defined using claims data during the 12 months before baseline, when Eichner classification was determined from dental claims.
Abbreviation: CNS, central nervous system.
The prevalence of osteoporosis (7.4% in class A, 8.0% in class B, and 9.1% in class C), use of anti‐osteoporosis medications (7.9%, 8.4%, and 10.2%, respectively), dementia (2.5%, 3.6%, and 6.2%), cerebrovascular disease (5.8%, 6.7%, and 8.5%), use of central nervous system medications (23.2%, 24.9%, and 28.8%), and hospitalization within the previous 12 months (9.6%, 11.0%, and 15.1%) were all highest in class C (all p < 0.001). The proportion with denture‐related care at baseline was 11.5% in class A, 51.4% in class B, and 78.6% in class C (p < 0.001).
3.2. Follow‐Up and Event Incidence
The median follow‐up was 5.66 years (interquartile range [IQR], 3.08–7.08), corresponding to a total of 18 152 375 person‐years of follow‐up. During follow‐up, 93 921 hip fractures occurred, yielding an overall incidence rate of 5.17 per 1000 person‐years. Incidence rates by Eichner class were 3.54 in class A, 5.56 in class B, and 9.61 in class C per 1000 person‐years, indicating a graded increase in hip fracture incidence with decreasing occlusal support.
3.3. Kaplan–Meier Curves for Hip Fracture‐Free Survival
Figure 2 shows hip fracture‐free survival according to Eichner classification. Across the follow‐up period, hip fracture‐free survival was highest in class A, followed by class B, and lowest in class C. The log‐rank test indicated significant differences among the three groups (p < 0.001). The curves separated early after baseline, and this separation persisted throughout follow‐up.
FIGURE 2.
Kaplan–Meier curves for hip fracture‐free survival according to Eichner classification.
3.4. Cox Proportional Hazards Models
We examined the association between Eichner classification and incident hip fracture using Cox proportional hazards models (Table 2). In the unadjusted model (Model 0), compared with class A, both class B and class C had a higher risk of hip fracture (class B: HR 1.55, 95% CI 1.53–1.57; class C: HR 2.62, 95% CI 2.57–2.67; both p < 0.001). After adjustment for age and sex (Model 1), the estimates were attenuated, but elevated risks persisted for both class B (HR 1.16, 95% CI 1.14–1.18) and class C (HR 1.34, 95% CI 1.32–1.37) (both p < 0.001).
TABLE 2.
Multivariable Cox proportional hazards models for hip fracture.
| Model0 | Model1 | Model2 | Model3 | Model4 | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | p | HR | 95% CI | p | HR | 95% CI | p | HR | 95% CI | p | HR | 95% CI | p | |
| Eichner classification (reference: Eichner class A) | |||||||||||||||
| Eichner class B | 1.55 | 1.53–1.57 | < 0.001 | 1.16 | 1.14–1.18 | < 0.001 | 1.16 | 1.14–1.18 | < 0.001 | 1.16 | 1.14–1.18 | < 0.001 | 1.21 | 1.18–1.23 | < 0.001 |
| Eichner class C | 2.62 | 2.57–2.67 | < 0.001 | 1.34 | 1.32–1.37 | < 0.001 | 1.34 | 1.32–1.37 | < 0.001 | 1.33 | 1.30–1.35 | < 0.001 | 1.44 | 1.39–1.49 | < 0.001 |
| Age (reference: 65–69 years) | |||||||||||||||
| 70–74 years | 0.88 | 0.84–0.92 | < 0.001 | 0.88 | 0.84–0.92 | < 0.001 | 0.86 | 0.82–0.90 | < 0.001 | 0.86 | 0.82–0.90 | < 0.001 | |||
| 75–79 years | 2.72 | 2.63–2.80 | < 0.001 | 2.70 | 2.62–2.79 | < 0.001 | 2.64 | 2.55–2.72 | < 0.001 | 2.62 | 2.54–2.71 | < 0.001 | |||
| 80–84 years | 7.06 | 6.84–7.29 | < 0.001 | 7.04 | 6.81–7.27 | < 0.001 | 6.54 | 6.33–6.75 | < 0.001 | 6.47 | 6.26–6.68 | < 0.001 | |||
| 85–90 years | 12.59 | 12.19–13.01 | < 0.001 | 12.54 | 12.14–12.96 | < 0.001 | 11.11 | 10.75–11.49 | < 0.001 | 10.98 | 10.62–11.35 | < 0.001 | |||
| 90+ years | 18.61 | 17.97–19.27 | < 0.001 | 18.53 | 17.89–19.18 | < 0.001 | 15.76 | 15.21–16.33 | < 0.001 | 15.54 | 15.00–16.10 | < 0.001 | |||
| Sex (reference: Male) | |||||||||||||||
| Female | 2.11 | 2.08–2.14 | < 0.001 | 2.09 | 2.06–2.13 | < 0.001 | 2.08 | 2.05–2.11 | < 0.001 | 2.08 | 2.05–2.11 | < 0.001 | |||
| Osteoporosis | 1.19 | 1.17–1.22 | < 0.001 | 1.08 | 1.06–1.11 | < 0.001 | 1.08 | 1.06–1.11 | < 0.001 | ||||||
| Use of anti‐osteoporosis medications | 0.93 | 0.91–0.94 | < 0.001 | 0.92 | 0.90–0.94 | < 0.001 | 0.92 | 0.90–0.94 | < 0.001 | ||||||
| Systemic corticosteroid use | 0.97 | 0.95–0.99 | < 0.001 | 0.92 | 0.90–0.93 | < 0.001 | 0.92 | 0.90–0.93 | < 0.001 | ||||||
| Dementia | 1.82 | 1.78–1.86 | < 0.001 | 1.82 | 1.78–1.86 | < 0.001 | |||||||||
| Cerebrovascular disease | 1.10 | 1.07–1.12 | < 0.001 | 1.10 | 1.07–1.12 | < 0.001 | |||||||||
| Use of CNS medications | 1.18 | 1.17–1.20 | < 0.001 | 1.18 | 1.17–1.20 | < 0.001 | |||||||||
| Hospitalization within the preceding 12 months | 1.21 | 1.18–1.23 | < 0.001 | 1.20 | 1.18–1.23 | < 0.001 | |||||||||
| Denture‐related status at baseline (reference: No) | 1.21 | 1.18–1.25 | < 0.001 | ||||||||||||
| Interaction: Eichner B × Denture‐related status | 0.81 | 0.79–0.84 | < 0.001 | ||||||||||||
| Interaction: Eichner C × Denture‐related status | 0.78 | 0.74–0.82 | < 0.001 | ||||||||||||
Note: Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models. Model 0 was unadjusted. Model 1 was adjusted for age and sex. Model 2 was additionally adjusted for osteoporosis history, osteoporosis medication use, and steroid use. Model 3 was further adjusted for dementia, cerebrovascular disease, central nervous system (CNS) medication use, and hospitalization within 12 months before baseline. Model 4 additionally included denture‐related status at baseline and interaction terms between Eichner classification and denture‐related status. Reference categories were Eichner class A, age 65–69 years, male sex, and no denture‐related care at baseline. Medication use and comorbidities were defined using claims recorded within 12 months before baseline.
Abbreviations: CI, confidence interval; CNS, central nervous system; HR, hazard ratio.
The results were essentially unchanged after further adjustment for osteoporosis‐related factors (Model 2) and after additional adjustment for dementia, cerebrovascular disease, central nervous system medication use, and prior hospitalization (Model 3). In the fully adjusted model, compared with class A, hip fracture risk remained higher in both class B (HR 1.21, 95% CI 1.18–1.23) and class C (HR 1.44, 95% CI 1.39–1.49).
To assess effect modification by denture‐related status, Model 4 additionally included denture‐related status and interaction terms between Eichner classification and denture‐related status. In this model, the main effect of denture‐related status within Eichner class A was HR 1.21 (95% CI 1.18–1.25). The interaction terms were significant for both class B × denture‐related status (HR 0.81, 95% CI 0.79–0.84) and class C × denture‐related status (HR 0.78, 95% CI 0.74–0.82) (all p < 0.001), indicating that the association between poorer occlusal support and hip fracture risk differed according to denture‐related status.
3.5. Assessment of Proportional Hazards and Time‐Interval Analyses
Schoenfeld residuals suggested deviation from the proportional hazards assumption for Eichner classification; therefore, we performed piecewise Cox analyses by dividing follow‐up into 0–2 years, 2–5 years, and 5–10 years (Table 3). In all intervals, both class B and class C had a significantly higher hip fracture risk than class A. In the fully adjusted piecewise models, the HRs for class B versus class A were 1.15 (95% CI 1.12–1.18) in years 0–2, 1.14 (95% CI 1.11–1.16) in years 2–5, and 1.14 (95% CI 1.10–1.20) in years 5–10. The corresponding HRs for class C versus class A were 1.30 (95% CI 1.26–1.34), 1.28 (95% CI 1.24–1.32), and 1.24 (95% CI 1.17–1.32), respectively. These findings were consistent with the primary analysis.
TABLE 3.
Piecewise Cox proportional hazards models for hip fracture according to Eichner classification, by follow‐up interval (0–2, 2–5 and 5–10 years).
| Eichner group A/B/C | Period | HR (95% CI) | p |
|---|---|---|---|
| Eichner class B versus class A | 0–2 years | 1.15 (1.12–1.18) | < 0.001 |
| Eichner class C versus class A | 0–2 years | 1.30 (1.26–1.34) | < 0.001 |
| Eichner class B versus class A | 2–5 years | 1.14 (1.11–1.16) | < 0.001 |
| Eichner class C versus class A | 2–5 years | 1.28 (1.24–1.32) | < 0.001 |
| Eichner class B versus class A | 5–10 years | 1.14 (1.10–1.20) | < 0.001 |
| Eichner class C versus class A | 5–10 years | 1.24 (1.17–1.32) | < 0.001 |
Note: Piecewise Cox proportional hazards models were used because the proportional hazards assumption for Eichner classification was not fully satisfied. Follow‐up time since baseline was divided into 0–2, 2–5, and 5–10 years. Follow‐up was administratively censored at 10 years. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Eichner class A group as the reference category. Models were adjusted for age category, sex, osteoporosis diagnosis, osteoporosis medication use, systemic corticosteroid use, dementia, cerebrovascular disease, central nervous system medication use, and hospitalization within the 12 months before baseline. p‐values are two‐sided.
Abbreviations: CI, confidence interval; HR, hazard ratio.
3.6. One‐Year Landmark Analysis (Assessment of Reverse Causation)
To assess potential reverse causation, we performed a 1‐year landmark analysis excluding fractures that occurred within the first year after baseline (Table 4). In Model 3, compared with class A, both class B and class C remained associated with a significantly higher risk of hip fracture (class B: HR 1.15, 95% CI 1.13–1.17; class C: HR 1.28, 95% CI 1.25–1.31; both p < 0.001). Similar patterns were observed in Model 4. The HRs were 1.16 (95% CI 1.14–1.19) for class B and 1.28 (95% CI 1.23–1.33) for class C. Denture‐related status within Eichner class A was associated with HR 1.18 (95% CI 1.14–1.22), and the interaction terms remained significant for both class B × denture‐related status (HR 0.88, 95% CI 0.84–0.91) and class C × denture‐related status (HR 0.88, 95% CI 0.83–0.93) (all p < 0.001).
TABLE 4.
One‐year landmark (delayed‐entry) Cox proportional hazards models for hip fracture according to Eichner classification and baseline denture‐related status (Models 3 and 4).
| Model 3 | Model 4 | |||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| Eichner class B versus class A | 1.15 (1.13–1.17) | < 0.001 | 1.16 (1.14–1.19) | < 0.001 |
| Eichner class C versus class A | 1.28 (1.25–1.31) | < 0.001 | 1.28 (1.23–1.33) | < 0.001 |
| Denture‐related status (within Eichner class A) | — | — | 1.18 (1.14–1.22) | < 0.001 |
| Interaction: Eichner class B × denture‐related status | — | — | 0.88 (0.84–0.91) | < 0.001 |
| Interaction: Eichner class C × denture‐related status | — | — | 0.88 (0.83–0.93) | < 0.001 |
Note: This sensitivity analysis used a 1‐year landmark approach to mitigate potential reverse causation. By design, participants who experienced a hip fracture within 1 year after baseline were excluded, and follow‐up started at 1 year after baseline using a delayed‐entry Cox model. The time scale was days since baseline, and risk sets were defined with left truncation at day 365. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Eichner class A without denture‐related care as the reference category. Model 3 was adjusted for age category, sex, osteoporosis diagnosis, osteoporosis medication use, systemic corticosteroid use, dementia, cerebrovascular disease, central nervous system medication use, and hospitalization within the 12 months before baseline. Model 4 additionally included denture‐related status and interaction terms between Eichner classification and denture‐related status to assess effect modification. p‐values are two‐sided.
Abbreviations: CI, confidence interval; HR, hazard ratio.
4. Discussion
In this large administrative claims‐based cohort of older adults, lower functional occlusal support was associated with a higher risk of hip fracture, and this association persisted after adjustment for multiple potential confounders. In addition, the association between occlusal support and hip fracture risk differed according to denture‐related status in interaction analyses. The main findings were also supported by piecewise Cox analyses and a 1‐year landmark analysis, suggesting that the observed associations were not limited to early follow‐up and were not fully explained by reverse causation. The marked attenuation of the hazard ratios after adjustment for age and sex suggests that a substantial proportion of the crude association was explained by baseline differences in age and general health status across Eichner classes. Thus, reduced occlusal support should not be interpreted as an isolated determinant of hip fracture risk; rather, it may partly reflect broader health vulnerability in later life. Although the associations remained after multivariable adjustment, the adjusted effect sizes were modest in magnitude and should be interpreted accordingly.
Previous studies have linked poor oral status to falls and fracture‐related outcomes in older adults, including studies using the number of remaining teeth, oral hygiene indicators, or broader indicators of oral health as exposure measures [10, 11, 12, 17, 18, 19]. However, the number of remaining teeth does not necessarily reflect the presence of antagonistic contacts or posterior occlusal support. A notable feature of the present study is that functional occlusal status was assessed using the Eichner classification derived from tooth‐chart information. By focusing on posterior occlusal support rather than tooth count alone, our findings extend previous evidence and suggest that prosthodontically relevant functional oral status may be associated with clinically important outcomes beyond the oral cavity. This interpretation is also consistent with previous evidence indicating that oral functional measures, such as occlusal force, are associated with incident functional disability in later life [20].
Although falls were not directly observed in this study, several pathways may plausibly link reduced occlusal support to hip fracture risk. Poor oral function may contribute to nutritional impairment, frailty, and reduced physical performance, all of which are relevant to fall risk in later life [4, 5, 6, 7, 21]. In addition, experimental and epidemiologic evidence has suggested that occlusion and mastication may be related to postural regulation, balance control, and physical fitness in older adults [8, 9, 22, 23]. From a prosthodontic perspective, these findings support the possibility that reduced occlusal support is not only a marker of oral impairment but may also be linked to broader health vulnerability in later life. Nevertheless, because potential mediators such as frailty severity, physical performance, nutritional status, and bone mineral density were not directly measured, the mechanistic interpretation of our findings remains inferential.
The findings regarding denture‐related status also warrant careful interpretation. In the present database, denture‐related status was defined using denture‐related claims and should therefore be regarded as a claims‐based proxy for denture‐related care rather than a direct measure of denture wearing, fit, or functional rehabilitation. It may also reflect healthcare utilization, access to care, or health‐seeking behaviour. Therefore, these findings should not be interpreted as evidence that denture treatment itself reduces hip fracture risk. Rather, they suggest that the association between poorer occlusal support and hip fracture risk may vary according to denture‐related status. In individuals with more severe loss of occlusal support, denture‐related claims may also reflect differences in healthcare access, treatment uptake, and health behaviours. Even so, because restoration of occlusal support is potentially modifiable in clinical practice, these findings support further investigation of whether prosthodontic rehabilitation could contribute to broader multifactorial strategies for reducing falls and fractures in older adults [22, 23].
The additional analyses strengthen the robustness of the main findings. First, because the proportional hazards assumption was not fully satisfied for Eichner classification, we performed piecewise Cox analyses across different follow‐up intervals. The broadly similar hazard ratios across follow‐up intervals suggest that the association was not restricted to a specific early or late phase of follow‐up, although the clinical mechanisms underlying this temporal pattern remain uncertain. Second, the 1‐year landmark analysis yielded broadly similar results, suggesting that the observed associations were not solely attributable to acute health deterioration or care‐seeking behaviours around baseline. We also acknowledge that the landmark analysis may introduce selection bias by excluding individuals with early events and should therefore be interpreted as a sensitivity analysis rather than a primary causal model.
This study has several strengths. It included a very large number of older adults, allowing precise estimation of associations. Functional occlusal support was assessed using tooth‐chart information rather than self‐report, and multiple sensitivity analyses were performed to address time dependency and potential reverse causation. The analyses also adjusted for several clinically relevant fracture‐related factors, including osteoporosis‐related variables, neurologic and vascular comorbidities, and recent hospitalization.
Several limitations should also be acknowledged. First, hip fracture was identified using administrative claims and ICD‐10 codes, and individual‐level validation within this database was not possible. However, similar definitions have been used in prior administrative data studies [15, 16]. Second, falls were not directly observed, and important factors such as bone mineral density, frailty, physical performance, fall propensity, nutritional status, institutionalization, and living environment were unavailable in this claims database. Because these variables are plausibly related to both occlusal support and hip fracture risk, substantial residual confounding remains possible. Accordingly, the present findings should be interpreted as evidence of association rather than causation. Third, denture‐related status was captured only as a claims‐based proxy and may not have adequately reflected true clinical exposure. Fourth, the study population consisted of beneficiaries of employment‐based health insurance and their dependents, which may not fully represent the general older population. In particular, this population may differ systematically in socioeconomic background, health status, and healthcare access. Therefore, caution is needed when generalizing these findings to the broader older population.
Reduced functional occlusal support was associated with a higher risk of hip fracture in this large cohort of older adults, and the association varied according to denture‐related status. Although causal inference is limited by the claims‐based design and the possibility of residual confounding, these findings suggest that functional oral status and posterior occlusal support may have clinical relevance beyond oral outcomes alone. Further studies are needed to clarify mechanisms and to determine whether improving oral function through prosthodontic rehabilitation can contribute to broader strategies for maintaining health and function in later life.
5. Conclusion
Lower functional occlusal support was independently associated with a higher risk of hip fracture in older adults. This association varied according to denture‐related status in the interaction analyses and remained broadly consistent in piecewise Cox and 1‐year landmark analyses. These findings suggest that posterior occlusal support, as a prosthodontically relevant measure of functional oral status, may have clinical significance beyond oral outcomes alone.
Author Contributions
Kenji Maekawa: conceptualization, methodology, writing – original draft, formal analysis, supervision, investigation, visualization, funding acquisition, software. Takuya Mino: validation, writing – review and editing, resources. Yoko Kurosaki: data curation, writing – review and editing, project administration.
Funding
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgements
The authors thank Editage for English language editing.
Contributor Information
Kenji Maekawa, Email: maekawa-k@cc.osaka-dent.ac.jp.
Takuya Mino, Email: mino-t@cc.osaka-dent.ac.jp.
Yoko Kurosaki, Email: kurosaki-y@cc.osaka-dent.ac.jp.
Data Availability Statement
The data that support the findings of this study were obtained from DeSC Healthcare Inc. under contract and are not publicly available due to third‐party restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study were obtained from DeSC Healthcare Inc. under contract and are not publicly available due to third‐party restrictions.