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Abstract

Masticatory function has been implicated in overall health decline, making it a potential target for public health interventions. We aimed 1) to assess whether perceived masticatory function is associated with all-cause mortality and 2) to quantify the impact of perceived masticatory function on all-cause mortality with a doubly robust causal inference approach. Data from a nationally representative longitudinal study of older people in Singapore were utilized. Perceived masticatory function was treated as a time-varying exposure (measured at the first 2 time points). It was categorized into 6 groups, ranging from group 1 (able to chew the toughest foods) to group 6 (unable to chew even the softest foods), reflecting increasing levels of chewing difficulty. All-cause mortality information until December 31, 2015, was assessed. Multivariable Cox regression models assessed the association between perceived masticatory function and all-cause mortality. Then, the longitudinal modified treatment policies approach was applied to estimate the effect of hypothetical preventive scenarios to preserve perceived masticatory function on mortality over 6 y. A total of 4,990 individuals were included in the analysis. The mean age at baseline was 72.8 y (SD, 8.1). For each level decrease in perceived masticatory function, the hazard ratio was 1.09 (95% CI, 1.05 to 1.14; P < 0.05). When perceived masticatory function was dichotomized into a binary variable with group 1 (no chewing difficulty) vs groups 2 to 6 (any level of difficulty), the hazard ratio was 1.25 (95% CI, 1.10 to 1.43; P < 0.05). The best hypothetical preventive scenario where all participants preserved maximum perceived masticatory function throughout the follow-up increased survival probability by 3% (relative risk, 1.03; 95% CI, 1.01 to 1.05; P < 0.05). Increased perceived masticatory function is associated and causally linked with reduced all-cause mortality among older adults in an Asian population. Policies aimed at preserving perceived masticatory function may be beneficial for older people’s longer life spans and healthy life expectancy.

Keywords

aging epidemiology oral health mastication public health nonparametric statistics

Introduction

Impaired masticatory function, defined as the inability to chew harder foods effectively, may be a marker of overall health in older adults (Kimble et al. 2022). It results from tooth loss and may result in poorer nutritional intake, systemic inflammation, and health complications (Kimura et al. 2013). While tooth loss is independently associated with increased mortality risk (Koka and Gupta 2018; Nakazawa et al. 2023; Kiuchi et al. 2024), the specific contribution of impaired masticatory function to mortality risk has received less attention.

Several pathways have been proposed to explain this relationship. Chewing difficulty can lead to poor dietary intake due to a reduction in the consumption of fiber-rich and protein-dense foods that are essential for metabolic and cardiovascular health (Nowjack-Raymer and Sheiham 2003; D’Aiuto and Donos 2007; Ono et al. 2022). This leads to a decline in muscle strength, exacerbating physical frailty and increasing mortality risk (Xu et al. 2022). Maintaining teeth and replacing missing teeth may promote better nutritional intake and overall muscle strength, contributing to improved health outcomes (Moriya et al. 2012; Matsuo et al. 2021).

This study hypothesized that decreased perceived masticatory function is associated with higher mortality rates among older adults in Singapore. Singapore has one of the most rapidly aging populations, with almost 20% of residents aged ≥60 y in 2017, which is projected to rise to 40% by 2050 (Malhotra et al. 2019). This makes Singapore a valuable setting for investigating aging-related health outcomes with implications for population-level health policies.

While associations provide initial evidence, establishing causality requires an approach that evaluates the impact of modifying the exposure. Therefore, a causal inference approach was used to estimate the impact of modifying perceived masticatory function on mortality. The longitudinal modified treatment policy (LMTP) approach was applied to assess the impact of hypothetical interventions on perceived masticatory function. LMTP is a method that dynamically shifts an individual’s exposure values based on one’s observed exposure levels. This offers a realistic and flexible framework for causal estimation, addressing key limitations of traditional causal models, such as positivity violations and reliance on strict parametric assumptions (Díaz et al. 2023; Hoffman et al. 2024; Miki et al. 2024).

The aim of this study was to assess whether perceived masticatory function was associated with all-cause mortality. A second aim was to determine the impact of perceived masticatory function on all-cause mortality via a causal approach by emulating multiple counterfactual scenarios using the LMTP approach.

Methods

The article was written in accordance with the STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology; von Elm et al. 2008).

Data and Analytic Sample

This study utilized 3 waves of the PHASE data (Panel on Health and Ageing among Singaporean Elderly), a nationally representative cohort of community-dwelling older adults (≥60 y), collected at 3 time points (2009, 2011 to 2012, and 2015; Chan et al. 2019). Participants were selected from a stratified random sample of 8,400 older adults drawn from the national database of dwellings; 1,195 addresses were invalid and excluded. Among those remaining, 2,215 individuals declined participation or were uncontactable. Wave 1 (2009) included 4,990 participants, with 3,103 followed up in wave 2 (2011 to 2012). Mortality data were available in waves 2 and 3 (2015).

Outcome: All-Cause Mortality

The primary outcome was all-cause mortality and was assessed from waves 1 to 3. For participants reported as deceased by next of kin but not recorded in the National Registry of Births and Death, the date of death was determined by next of kin through a decedent questionnaire. If unavailable, it was approximated as the midpoint between the last interview and next-of-kin contact at the next wave. Survival time was calculated in days from baseline to death or censoring.

Exposure: Perceived Masticatory Function

Perceived masticatory function was used as a time-varying exposure between waves 1 and 2. Participants were asked during the interview, “The following foods are ordered from hardest to softest to chew. What is the hardest group you are able to bite and chew?” If participants were unable to respond due to health reasons such as hospitalization, institutionalization, dementia, or hearing and speaking difficulties, their proxies were asked. Response options were grouped by food toughness and chewing muscle activity (Nasu and Saito 2006; Nascimento et al. 2024). A texturometer measured the toughness of local foods commonly consumed by older adults in Singapore, making it easier for participants to understand and relate to the response options, and foods were arranged in descending order of toughness (Appendix Fig. 1).

Perceived masticatory function was assessed in 2 ways: 6-group categorization with increasing difficulty from group 1 to 6; binary classification, where group 1 indicated no chewing difficulty and groups 2 to 6 indicated any difficulty.

Confounders

Confounders included demographic, lifestyle, health, and social variables. Demographic variables included age, sex, ethnicity, education, housing type, and living arrangement. Self-reported smoking status (never and former/current) was also included. Chronic diseases diagnosed by a medical professional included cancer, cerebrovascular disease, and diabetes mellitus (yes/no). Depressive symptoms were measured by the Center for Epidemiologic Studies Depression Scale score, based on an 11-item checklist (Kohout et al. 1993).

Statistical Analysis

Kaplan-Meier survival analysis compared survival probabilities across the 6 levels of perceived masticatory function, and differences in survival distributions were assessed through log-rank tests. A multivariable Cox proportional hazards regression model estimated hazard ratios (HRs) for the association between perceived masticatory function and all-cause mortality. The proportional hazards assumption was evaluated by scaled Schoenfeld residuals, and variables violating the assumption were stratified to ensure validity within each stratum. Collinearity was assessed by variance inflation factor, with values >2.5 indicating multicollinearity.

Confounders included variables measured at wave 1. When the causal impact of perceived masticatory function on mortality was assessed via the LMTP approach, the same baseline demographic variables were included as time-invariant covariates, while time-varying confounders across waves 1 and 2 consisted of smoking status, self-reported diabetes mellitus, cancer, cerebrovascular disease, and depressive symptoms.

The LMTP framework was used to assess the impact of preserving or improving perceived masticatory function on mortality (Díaz et al. 2023) by emulating hypothetical counterfactual scenarios where individuals had higher levels of perceived masticatory function over time (Figure 1). Statistical parameters for each scenario were estimated by targeted maximum likelihood estimation (TMLE) to provide doubly robust estimates (Schuler and Rose 2017). TMLE combines g-computation, which models the outcome conditional on exposure and covariates, with inverse probability weighting, as derived from the propensity score model, to adjust for confounding and censoring. To enhance the flexible nonparametric estimation of these models, the Super Learner algorithm was used (Schomaker et al. 2019). This approach combines multiple predictive methods—generalized linear models, generalized additive models, extreme gradient boosting, and neural networks—into a weighted ensemble to minimize the cross-validated prediction error.

Figure 1.

Proposed direct acyclic graph illustrating temporal associations among variables. W (baseline time-invariant covariates): age, sex, ethnicity, education, housing type, living arrangement. L0 and L1 (time-varying covariates): smoking status, self-reported cancer, cerebrovascular disease, diabetes mellitus, depressive symptoms. A0 and A1 (exposures): perceived masticatory function at wave 1 (2009) and wave 2 (2011 to 2012). Y1 and Y2 (outcome): all-cause mortality.

The following hypothetical scenarios of perceived masticatory function preservation were emulated:

Scenario 1: What if individuals who could not chew foods from group 6 retained the ability to chew foods in group 5 at each time point?

Scenario 2: What if individuals who could not chew foods from groups 5 and 6 retained the ability to chew foods in group 4 at each time point?

Scenario 3: What if individuals who could not chew foods from groups 4, 5, and 6 retained the ability to chew foods in group 3 at each time point?

Scenario 4: What if individuals who could not chew foods from groups 3, 4, 5, and 6 retained the ability to chew foods in group 2 at each time point?

Scenario 5: What if everyone had full perceived masticatory function at each time point?

The following scenarios were emulated for individuals who had <28 teeth without a denture and were experiencing some degree of impaired perceived masticatory function, to explore the potential impact of providing them with dentures:

Scenario 6: What if non–denture-wearing individuals were provided with dentures at each time point and improved perceived mastication by a maximum of 1 level?

Scenario 7: What if non–denture-wearing individuals were provided with dentures and improved perceived mastication to the second-highest chewing group?

Scenario 8: What if non–denture-wearing individuals were provided with dentures, which resulted in maximal perceived masticatory function?

Denture use was self- or proxy-reported and referred to removable prostheses. Illustrated scenarios are found in Appendix Figures 1 to 4. The causal estimand was the difference in mortality (by wave 3) between emulated hypothetical scenarios of better perceived masticatory function and the observed reality for the entire sample. Covariate-adjusted effects of perceived masticatory function on all-cause mortality were estimated via the LMTP approach. Counterfactual risk ratios and 95% CIs were estimated to calculate the relative reduction in mortality risk associated with each intervention. The absolute risk reduction and corresponding reduction in mortality per 100,000 people for each intervention were estimated to quantify the absolute impact of preserving perceived masticatory function. Additionally, the population attributable fraction, representing the reduction of mortality attribution to each scenario, was estimated with bootstrapped 95% CIs (1,000 iterations). E-values were calculated to estimate the impact of unmeasured confounding (VanderWeele and Ding 2017).

Missing data were imputed by chained equations (10 datasets; Van Buuren and Groothuis-Oudshoorn 2011) and pooled per Rubin’s rules. Denture data were unavailable for wave 2. If denture status was the same at waves 1 and 3, it was assumed unchanged at wave 2. If it differed, the change was assumed to have occurred by wave 2. All data were conducted in R (version 4.4.2; R Core Team). The lmtp package was utilized to estimate the causal effects through TMLE.

Results

In total, 4,990 individuals were included in the Cox model and LMTP analysis. While 3,103 individuals remained at wave 2, the LMTP approach accounted for deaths (n = 585, 11.7%) and censoring (n = 1,302, 26.9%) between waves 1 and 2, ensuring that the full cohort contributed to the analysis (Fig. 2). Appendix Tables 1 to 3 provide participant characteristics by all-cause mortality and perceived masticatory function as a binary variable before multiple imputation, with the distribution of missing data. Among participants who responded to the perceived masticatory function question, 4,521 provided self-reported responses, while 448 were proxy obtained.

Figure 2.

Flowchart of participants from baseline (2009) to end of follow-up (2015).

The mean ± SD age of the participants at baseline was 72.8 ± 8.1 y. Higher age, female sex, lower education level, living in smaller housing, smoking, poorer mental health scores, the presence of cerebrovascular disease, and diabetes mellitus were significantly associated with the binary perceived masticatory function variable (P < 0.001; Appendix Table 4).

An overall 1,094 participants (21.9%) were deceased by the end of follow-up. Perceived masticatory function distribution differed significantly between those alive and deceased (Table 1). There was a significant difference in the unadjusted survival curves among the perceived masticatory function groups. Survival probability was highest for group 1 and decreased progressively across groups throughout the follow-up period. When perceived masticatory function was dichotomized into a binary variable, those with chewing difficulty had a significantly lower probability of survival (Appendix Fig. 5).

Table 1.

Distribution of Baseline (Year 2009) Characteristics of Participants by All-Cause Mortality until December 31, 2015, after Multiple Imputation.

	Mean ± SD or Column %
Characteristic	Alive (n = 3,896)	Dead (n = 1,094)
Age, y	71.3 ± 7.4	78.2 ± 8.2
Sex
Male	43.6	50.7
Female	56.4	49.3
Ethnicity
Chinese	72.4	68.6
Malay	16.0	20.8
Indian	10.4	9.2
Others	1.1	1.4
Education
Primary school or below	70.0	83.2
Above primary school	30.0	16.8
Housing
1- or 2-room HDB	7.8	9.7
3-room HDB	26.8	27.1
4- or 5-room HDB/private	65.3	63.2
Living arrangement
Not living alone	93.8	95.3
Living alone	6.2	4.7
Smoker
Never or former	89.9	86.2
Current	10.1	13.8
CESD Scale score: 11 items	3.3 ± 0.1	4.2 ± 0.1
CESD ≥7
No	85.7	79.0
Yes	14.3	21.0
Perceived masticatory function
Group 1	77.9	58.0
Group 2	3.2	2.9
Group 3	5.6	7.5
Group 4	8.9	16.8
Group 5	3.5	9.7
Group 6	0.9	5.0
Cancer
No	97.5	94.3
Yes	2.5	5.7
Cerebrovascular disease
No	96.8	90.4
Yes	3.2	9.6
Diabetes mellitus
No	77.9	68.0
Yes	22.1	32.0

CES-D, Center for Epidemiologic Studies Depression; HDB, Housing Development Board.

For the Cox regression analysis, there was no evidence of multicollinearity (variance inflation factors <2.5). Cancer violated the proportional hazards assumption, with significant scaled Schoenfeld residuals (P < 0.05). The model was stratified by cancer to ensure that the proportional hazards assumption was satisfied within each stratum (Appendix Table 5). Individuals with chewing difficulty (groups 2 to 6) had a higher risk of mortality as compared with those with no difficulty (group 1), with a multivariable HR of 1.25 (95% CI, 1.10 to 1.43). Each level decrease in perceived masticatory function was also associated with an increased risk of mortality, with a multivariable HR of 1.09 (95% CI, 1.05 to 1.14).

Table 2 presents mean expected outcome estimates (TMLE estimates) for the observed data and each emulated hypothetical preventive scenario, based on the Super Learner and generalized linear models. The greatest improvement was observed in scenario 6, where participants retained the highest perceived masticatory function with an increased survival of 3% (relative risk, 1.03; 95% CI, 1.01 to 1.05). Scenario 4, where participants in groups 6, 5, 4, and 3 were shifted to groups 5, 4, 3, and 2, also resulted in significant improvement in survival probability (relative risk, 1.02; 95% CI, 1.01 to 1.04). However, shifting participants in the poorest perceived masticatory function groups (groups 6, 5, and 4) to slightly higher levels (groups 5, 4, and 3) did not produce a significant effect in reducing mortality (scenario 3). The absolute risk reduction was significant for scenarios 4 to 6, with the largest estimated mortality reduction of 2,059 deaths per 100,000 individuals (95% CI, 550 to 3,568) in scenario 6. Based on the population attributable fraction, 0.55% (95% CI, 0.16% to 0.91%) of mortality cases could be prevented for scenario 4, increasing up to 0.70% (95% CI, 0.18% to 1.19%) when individuals preserved the highest level of perceived masticatory function (Table 3).

Table 2.

Survival Probability across Perceived Masticatory Function Groups and Scenarios.

	With Super Learner Model			With Generalized Linear Model
Scenario	Survival Probability (Relative Risk)	95% CI	E-value	Survival Probability (Relative Risk)	95% CI	E-value
1: Shift group 6 to 5	1.01	1.00 to 1.01	1.08	1.01	1.00 to 1.01	1.08
2: Shift groups 6, 5 to 5, 4	1.01	1.00 to 1.02	1.10	1.01	1.00 to 1.02	1.10
3: Shift groups 6, 5, 4 to 5, 4, 3	1.02	1.00 to 1.03	1.14	1.02	1.00 to 1.03	1.14
4: Shift groups 6, 5, 4, 3 to 5, 4, 3, 2	1.02	1.01 to 1.04	1.17	1.03	1.01 to 1.04	1.17
5: Shift groups 6, 5, 4, 3, 2 to 5, 4, 3, 2, 1	1.02	1.00 to 1.03	1.14	1.02	1.01 to 1.04	1.14
6: All in group 1, full masticatory function	1.03	1.01 to 1.05	1.19	1.03	1.01 to 1.05	1.19
7: Dentures improve mastication by 1 level	1.00	0.99 to 1.01	1.03	1.00	0.99 to 1.01	1.02
8: Dentures improve mastication to the second highest level	1.00	0.99 to 1.02	1.06	1.01	0.99 to 1.02	1.07
9: Dentures restore full masticatory function	1.00	1.00 to 1.01	1.07	1.01	1.00 to 1.02	1.08

Models adjusted for age, sex, ethnicity, education, housing type, living arrangement, smoking status, self-reported cancer, cerebrovascular disease, diabetes mellitus, and depressive symptoms.

Table 3.

Estimated Proportional and Absolute Reduction in Mortality with Better Perceived Masticatory Function.

Scenario	Population Attributable Fraction, % (95% CI)	Absolute Risk Reduction (95% CI)	Mortality Reduction per 100,000 People (95% CI)
1	0.137 (0.018 to 0.253)	0.004 (0.001 to 0.007)	401 (60 to 742)
2	0.239 (0.005 to 0.481)	0.007 (0.000 to 0.014)	695 (−23 to 1,414)
3	0.404 (−0.120 to 0.888)	0.012 (−0.003 to 0.027)	1,196 (−339 to 2,730)
4	0.552 (0.156 to 0.910)	0.016 (0.004 to 0.022)	1,596 (445 to 2,747)
5	0.431 (0.113 to 0.755)	0.013 (0.003 to 0.022)	1,252 (293 to 2,211)
6	0.695 (0.184 to 1.19)	0.021 (0.005 to 0.036)	2,059 (550 to 3,568)
7	−0.023 (−0.313 to 0.264)	−0.001 (−0.009 to 0.008)	−63 (−940 to 814)
8	0.091 (−0.301 to 0.551)	0.003 (−0.009 to 0.015)	275 (−944 to 1,493)
9	0.113 (−0.133 to 0.373)	0.003 (−0.004 to 0.011)	347 (−387 to 1,082)

Among the 1,663 participants (33.3%) who did not have dentures at wave 1, emulated scenarios where dentures were provided to those with chewing disabilities with <28 teeth (n = 409, 8.20%) showed no significant effect on survival. Even in the most optimistic scenario (scenario 9), where denture use eliminated all chewing disabilities, there was no significant improvement in mortality outcomes.

Discussion

Preserving perceived masticatory function was associated with a slight reduction in all-cause mortality after confounding adjustment. This association remained consistent whether perceived masticatory function was classified as an ordinal or simplified as a binary variable. Emulating scenarios with better-preserved perceived masticatory function demonstrated a modest positive impact of 1% to 3% on survival probabilities, supporting the importance of maintaining oral functionality in promoting longevity among older adults. The largest impact on survival probability was when all participants retained the highest perceived masticatory function, resulting in a 1.03-fold increase in survival probability. This corresponded to an absolute mortality reduction of 2,059 deaths per 100,000 individuals and a 0.70% reduction in mortality attributable to maximal perceived masticatory function preservation. This reduction is comparable to other modest but significant survival benefits observed in different population contexts. For example, in individuals with type 2 diabetes, a 5-kg/m² increase in body mass index corresponded to a 5% reduction in all-cause mortality—a phenomenon referred to as the obesity paradox—which may be explained by greater metabolic reserves and higher muscle mass (Liu et al. 2015).

This study reinforces the importance of masticatory function as a public health issue (Tonetti et al. 2017; Peres et al. 2019). It supports the hypothesis that better masticatory function enables the consumption of a more diverse and nutrient-rich diet, which in turn supports systemic health and reduces mortality risk (Nowjack-Raymer and Sheiham 2003; Xu et al. 2022). Prior studies showed an association between masticatory function and mortality (Onder et al. 2007; Jang et al. 2021; Abe et al. 2024; Du et al. 2025), with one estimating that higher masticatory performance reduces mortality by >15% in older adults (Abe et al. 2024). Another study showed that phenotypic age acceleration mediates this relationship (Du et al. 2025). However, these studies are associative and did not account for time-varying confounders; they also lacked direct causal comparisons and relied on parametric assumptions.

The reported HRs represent an averaged effect over time, which does not capture time-varying effects. To address this, causal inference methods were used to supplement the analyses, allowing for robust estimation of counterfactual survival probabilities. Additionally, the absolute risk differences and population attributable fractions were reported, which provide better interpretability in terms of public health policy impact. The causal estimate presented here is likely conservative, as it is grounded in real-world scenarios by comparing counterfactual estimates against the observed exposure rather than a hypothetical scenario where everyone is uniformly exposed or not exposed. While the estimates are small, they reflect the reality that mortality is determined by multiple factors beyond oral health. Various hypothetical emulations were also utilized to show the variation in outcomes that depends on the degree of scenarios in preserving perceived masticatory function. Estimates incorporated machine learning algorithms to enable flexible modeling of complex relationships for robust estimates.

This study utilized perceived masticatory function, rather than tooth number, as an exposure. Perceived masticatory function is a function of occlusal stability, intercuspation, periodontal health, prosthetic use, and neuromuscular coordination. Although this study did not assess the causal impact of tooth number on mortality, impaired chewing function is a more proximal indicator than tooth number in the hypothesized pathway, leading to inadequate nutritional intake, including reduced consumption of whole grains, nuts, and fiber-rich foods, while increasing consumption of softer, processed foods high in carbohydrates and sodium, thereby contributing to a higher risk of mortality (English et al. 2021; Ramezani et al. 2024). Reduced chewing function from periodontitis may also play a role due to mobility and loss of teeth (Liu et al. 2024; Du et al. 2025) rather than through systemic inflammation (Winning et al. 2021).

This study suggests that achieving maximum chewing function for all older adults may not be necessary, supporting the feasibility of retaining a shortened dental arch (Käyser 1981). The small incremental gains in survival from scenarios 4 to 6 suggest a threshold effect, where improvements beyond a certain point yield diminishing returns. Instead, targeting the more severe chewing disabilities by just 1 level may provide benefits at a population level. This study also found that prosthetic interventions with removable dental prostheses did not alter survival probability. While perceived masticatory function is causally linked to mortality, rehabilitation does not necessarily reduce it.

There are several limitations in this study. First, perceived masticatory function was subjectively assessed, making it susceptible to response, accuracy, reliability, and social desirability biases. Objective methods, such as comminution tests, would have provided more reliable assessments, although this may be infeasible in population-based studies. Nonetheless, the 6-level categorical scale provides more granularity than binary classifications (Tanaka et al. 2018; Watanabe et al. 2024). Second, chewing function is part of a broader set of symptoms of oral frailty, a multidimensional condition contributing to increased mortality (Dibello et al. 2021). However, this study lacked data on oral motor skills, pain, dysphagia, and dry mouth. Moreover, the role of masticatory function within the context of frailty syndrome remains underexplored. Frailty syndrome is characterized by reduced physiologic reserves and diminished overall muscle strength, which may explain its close association with masticatory function. The absence of frailty as a study variable may have limited the assessment of effect modification, where the impact of masticatory dysfunction on mortality could be stronger in frail individuals. Third, while adjustments were made for confounders, unmeasured confounders remain possible. E-values were reported to estimate the strength of the unmeasured confounder needed to explain away the association. Additionally, interventional studies are required to assess whether improving masticatory function in older persons not only reduces mortality but increases quality of life and nutritional adequacy.

The study findings may not be generalizable to other populations due to differences in dietary preferences. Variations in food texture and types of commonly consumed foods across countries, which differ in nutritional value, may influence the relationship between perceived masticatory function and overall health outcomes. Although this study was based on the hypothesis that better perceived masticatory function supports better nutritional status and thereby reduces mortality risk, the lack of significance with denture rehabilitation may be explained by the small number of non–denture wearers with chewing difficulties and the possibility that rehabilitation is not the sole causal pathway. Nutritional intake may also be shaped by individual dietary habits, societal food norms, and access to nutrient-rich soft foods. Furthermore, there was insufficient data to examine cause-specific mortality, which limits the ability to discern whether certain causes of death are more strongly associated with perceived masticatory function while others may be unrelated. Additionally, alternative pathways linking perceived masticatory function to cognitive health and reduced mortality warrant further investigation. The dataset also did not include information on the presence of fixed prostheses or the condition of existing natural teeth. As such, we were limited to modeling scenarios based on the available variables and could not emulate more specific treatment pathways. Fixed prostheses may improve perceived masticatory function more than removable prostheses, potentially leading to greater mortality risk reduction. However, the magnitude of this effect depends on the prevalence of such rehabilitations in the population, and any additional benefits must be weighed against their higher costs.

Conclusion

Worsened perceived masticatory function is associated with increased mortality in older adults. However, the causal effect is modest. Nonetheless, health policies that support chewing function may contribute to longer life expectancy in Singapore.

Author Contributions

J.R.H. Tay, contributed to conception, design, data acquisition, analysis, and interpretation, drafted and critically revised the manuscript; U. Cooray, contributed to conception, design, data acquisition, analysis, and interpretation, critically revised the manuscript; A. Chan, M.S. Tonetti, G.G. Nascimento, M.A. Peres, contributed to design, data analysis and interpretation, critically revised the manuscript. All authors gave final approval and agree to be accountable for all aspects of the work.

Supplemental Material

sj-docx-1-jdr-10.1177_00220345251363851 – Supplemental material for Perceived Masticatory Function and Mortality: A Causal Study

Supplemental material, sj-docx-1-jdr-10.1177_00220345251363851 for Perceived Masticatory Function and Mortality: A Causal Study by J.R.H. Tay, U. Cooray, A. Chan, M.S. Tonetti, G.G. Nascimento and M.A. Peres in Journal of Dental Research

Footnotes

J.R.H. Tay received PhD funding from the Singapore National Medical Research Council Research Training Fellowship (RTF24jan-0007).

A supplemental appendix to this article is available online.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: Ministry of Social and Family Development,Singapore;Singapore Ministry of Health’s National Medical Research Council under its Singapore Translational Research Investigator Award “Establishing a Practical and Theoretical Foundation for Comprehensive and Integrated Community,Policy and Academic Efforts to Improve Dementia Care in Singapore” (NMRC-STAR-0005-2009) and its Clinician Scientist–Individual Research Grant–New Investigator Grant “Singapore Assessment for Frailty in Elderly-Building upon the Panel on Health and Aging of Singaporean Elderly” (NMRC-CNIG-1124-2014);and Duke-NUS Geriatric Research Fund.

Ethics Committee Approval

PHASE waves 2 and 3 and analysis of deidentified data of PHASE wave 1 were approved by the institutional review board at the National University of Singapore (reference codes 10-441,11-020E,and B-14-235). The analysis of deidentified data of all 3 waves of PHASE was approved by the institutional review board at SingHealth (reference code 2022-2669). Ethics approval from the National University of Singapore Institutional Review Board (NUS-IRB-2024-979) was obtained to conduct this present work.

ORCID iDs

J.R.H. Tay

U. Cooray

M.S. Tonetti

G.G. Nascimento

Availability of Data

The data that support the findings of this study are available from the Centre for Ageing Research and Education,Duke-NUS Medical School. Restrictions apply to the availability of these data,which were used under license for this study. Data are available from the authors upon reasonable request,with the permission of Duke-NUS Medical School.

References

Abe

Tominaga

Saito

Shimizu

Maeda

Matsuura

Inoue

Ando

Matsuda

Kanno

, et al. 2024. Effect of oral health on functional disability and mortality in older adults in Japan: a cohort study. Lancet Healthy Longev. 5(11):100636. doi:10.1016/j.lanhl.2024.08.005

Chan

Saito

Matchar

Østbye

Malhotra

Ang

Malhotra

2019. Cohort profile: panel on health and ageing of Singaporean elderly (PHASE). Int J Epidemiol. 48(6):1750–1751f.

D’Aiuto

Donos

2007. Influence of tooth loss on cardiovascular mortality. Heart. 93(9):1022–1023.

Díaz

Williams

Hoffman

Schenck

. 2023. Nonparametric causal effects based on longitudinal modified treatment policies. J Am Stat Assoc. 118(542):846–857.

Dibello

Zupo

Sardone

Lozupone

Castellana

Dibello

Daniele

De Pergola

Bortone

Lampignano

, et al. 2021. Oral frailty and its determinants in older age: a systematic review. Lancet Healthy Longev. 2(8):e507–e520. doi:10.1016/s2666-7568(21)00143-4

Deng

Yin

Guo

Luo

Tonetti

Tjakkes

Visser

, et al. 2025. Association between chewing capacity and mortality risk: the role of diet and ageing. J Clin Periodontol. 52(5):695–706.

English

Ard

Bailey

Bates

Bazzano

Boushey

Brown

Butera

Callahan

de Jesus

, et al. 2021. Evaluation of dietary patterns and all-cause mortality: a systematic review. JAMA Netw Open. 4(8):e2122277. doi:10.1001/jamanetworkopen.2021.22277

Hoffman

Salazar-Barreto

Williams

Rudolph

Díaz

2024. Studying continuous, time-varying, and/or complex exposures using longitudinal modified treatment policies. Epidemiology. 35(5):667–675.

Jang

Kim

. 2021. Association between denture use, chewing ability, and all-cause mortality in middle-aged and older adults who exercised regularly in Korea. Sci Rep. 11(1):6061. doi:10.1038/s41598-021-85440-x

10.

Käyser

AF.

1981. Shortened dental arches and oral function. J Oral Rehabil. 8(5):457–462.

11.

Kimble

McLellan

Lennon

Papacosta

Weyant

Kapila

Mathers

Wannamathee

Whincup

Ramsay

. 2022. Association between oral health markers and decline in muscle strength and physical performance in later life: longitudinal analyses of two prospective cohorts from the UK and the USA. Lancet Healthy Longev. 3(11):e777–e788. doi:10.1016/s2666-7568(22)00222-7

12.

Kimura

Ogawa

Yoshihara

Yamaga

Takiguchi

Wada

Sakamoto

Ishimoto

Fukutomi

Chen

, et al. 2013. Evaluation of chewing ability and its relationship with activities of daily living, depression, cognitive status and food intake in the community-dwelling elderly. Geriatr Gerontol Int. 13(3):718–725.

13.

Kiuchi

Matsuyama

Takeuchi

Kusama

Cooray

Osaka

Aida

2024. Number of teeth and dementia-free life expectancy: a 10-year follow-up study from the Japan gerontological evaluation study. J Am Med Dir Assoc. 25(11):105258. doi:10.1016/j.jamda.2024.105258

14.

Kohout

Berkman

Evans

Cornoni-Huntley

1993. Two shorter forms of the CES-D depression symptoms index. J Aging Health. 5(2):179–193.

15.

Koka

Gupta

2018. Association between missing tooth count and mortality: a systematic review. J Prosthodont Res. 62(2):134–151.

16.

Liu

Shen

Qian

Lai

Yuan

Tonetti

. 2024. Low energy intake and nutritional maladaptation in terminal stage IV periodontitis. J Clin Periodontol. 51(9):1147–1156.

17.

Liu

Zhan

. 2015. Overweight, obesity and risk of all-cause and cardiovascular mortality in patients with type 2 diabetes mellitus: a dose-response meta-analysis of prospective cohort studies. Eur J Epidemiol. 30(1):35–45.

18.

Malhotra

Bautista

MAC

Müller

Koh

GCH

Theng

Hoskins

Wong

Miao

Lim

, et al. 2019. The aging of a young nation: population aging in Singapore. Gerontologist. 59(3):401–410.

19.

Matsuo

Kito

Ogawa

Izumi

Kishima

Itoda

Masuda

2021. Improvement of oral hypofunction by a comprehensive oral and physical exercise programme including textured lunch gatherings. J Oral Rehabil. 48(4):411–421.

20.

Miki

Cooray

Kanai

Hagiwara

Murakami

Osaka

Ikeda

2024. Effects of hypothetical low versus moderate-to-high intensity weight management regimens on knee replacements. Am J Epidemiol [epub ahead of print 28 Nov 2024] in press. doi:10.1093/aje/kwae446

21.

Moriya

Tei

Murata

Sumi

Inoue

Miura

2012. Influence of dental treatment on physical performance in community-dwelling elderly persons. Gerodontology. 29(2):e793–e800. doi:10.1111/j.1741-2358.2011.00563.x

22.

Nakazawa

Kusama

Cooray

Yamamoto

Kiuchi

Abbas

Yamamoto

Kondo

Osaka

Aida

2023. Large contribution of oral status for death among modifiable risk factors in older adults: the Japan Gerontological Evaluation Study (JAGES) prospective cohort study. J Gerontol A Biol Sci Med Sci. 78(1):167–173.

23.

Nascimento

Malhotra

Leite

FRM

Peres

Chan

Peres

. 2024. Chewing disability is associated with cognitive impairment among older adults: a population-based cohort study. J Gerontol A Biol Sci Med Sci. 79(5):glae074. doi:10.1093/gerona/glae074

24.

Nasu

Saito

2006. Active life expectancy for elderly Japanese by chewing ability. Nihon Koshu Eisei Zasshi. 53(6):411–423. Article in Japanese.

25.

Nowjack-Raymer

Sheiham

2003. Association of edentulism and diet and nutrition in US adults. J Dent Res. 82(2):123–126.

26.

Onder

Liperoti

Soldato

Cipriani

Bernabei

Landi

2007. Chewing problems and mortality in older adults in home care: results from the aged in home care study. J Am Geriatr Soc. 55(12):1961–1966.

27.

Ono

Kato

Kokubo

Hasegawa

Kosaka

Maeda

Okamura

Miyamoto

Ikebe

2022. Tooth loss related with prevalence of metabolic syndrome in a general urban Japanese population: the Suita study. Int J Environ Res Public Health. 19(11):6441. doi:10.3390/ijerph19116441

28.

Peres

Macpherson

LMD

Weyant

Daly

Venturelli

Mathur

Listl

Celeste

Guarnizo-Herreño

Kearns

, et al. 2019. Oral diseases: a global public health challenge. Lancet. 394(10194):249–260.

29.

Ramezani

Pourghazi

Eslami

Gholami

Mohammadian Khonsari

Ejtahed

Larijani

Qorbani

2024. Dietary fiber intake and all-cause and cause-specific mortality: an updated systematic review and meta-analysis of prospective cohort studies. Clin Nutr. 43(1):65–83.

30.

Schomaker

Luque-Fernandez

Leroy

Davies

. 2019. Using longitudinal targeted maximum likelihood estimation in complex settings with dynamic interventions. Stat Med. 38(24):4888–4911.

31.

Schuler

Rose

2017. Targeted maximum likelihood estimation for causal inference in observational studies. Am J Epidemiol. 185(1):65–73.

32.

Tanaka

Takahashi

Hirano

Kikutani

Watanabe

Ohara

Furuya

Tetsuo

Akishita

Iijima

. 2018. Oral frailty as a risk factor for physical frailty and mortality in community-dwelling elderly. J Gerontol A Biol Sci Med Sci. 73(12):1661–1667.

33.

Tonetti

Bottenberg

Conrads

Eickholz

Heasman

Huysmans

López

Madianos

Müller

Needleman

, et al. 2017. Dental caries and periodontal diseases in the ageing population: call to action to protect and enhance oral health and well-being as an essential component of healthy ageing—consensus report of group 4 of the joint EFP/ORCA workshop on the boundaries between caries and periodontal diseases. J Clin Periodontol. 44 Suppl 18:S135–S144.

34.

Van Buuren

Groothuis-Oudshoorn

. 2011. mice: multivariate imputation by chained equations in R. J Stat Softw. 45:1–67.

35.

VanderWeele

Ding

2017. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 167(4):268–274.

36.

von Elm

Altman

Egger

Pocock

Gøtzsche

Vandenbroucke

. 2008. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 61(4):344–349.

37.

Watanabe

Yoshida

Watanabe

Yokoyama

Yamada

Kikutani

Yoshida

Miyachi

Kimura

2024. Oral frailty is associated with mortality independently of physical and psychological frailty among older adults. Exp Gerontol. 191:112446. doi:10.1016/j.exger.2024.112446

38.

Winning

Patterson

Linden

Cullen

Kee

Linden

. 2021. Systemic inflammation and the relationship between periodontitis, edentulism, and all-cause mortality: a 17-year prospective cohort study. J Clin Periodontol. 48(9):1260–1269.

39.

Wan

Ktoris

Reijnierse

Maier

. 2022. Sarcopenia is associated with mortality in adults: a systematic review and meta-analysis. Gerontology. 68(4):361–376.

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