The CLHLS is an ongoing, prospective cohort study investigating the determinants of health and longevity among older Chinese adults. The study includes participants from 22 of China’s 31 provinces. The sample was selected using a multistage, stratified cluster sampling method, randomly choosing 631 cities and counties with the largest Han Chinese population. These sample sites represent approximately 85% of the Chinese population (21). The study commenced in 1998, with follow-up interviews conducted every 2–4 years. New participants were enrolled during the follow-up to minimize attrition due to death and loss of follow-up. All included individuals were interviewed face-to-face about determinants of health, including family relationships, socioeconomic characteristics, mental health, physical capacity, chronic disease, and other lifestyle-related measurements. A detailed account of the study design and methods is available (22).

Since the data on cause-specific deaths were only available in the 2018 wave, we used the baseline data from the 2014 wave of CLHLS and conducted a follow-up during the 2018 wave, with a response rate of 79.0%. During the 2014 wave, the study expanded to 23 provinces, adding Chengmai City in Hainan Province (Supplementary Figure S1). The 2014 wave included 7,192 participants. The exclusion criteria in the present study were: age <65 years (n = 85), those who were lost to follow-up (n = 1,511) or had incorrect death dates (n = 6), and missing data on the number of natural teeth and/or denture use (n = 187). Finally, 5,403 participants were included to analyze the association between the number of natural teeth, denture use, and all-cause and cause-specific mortality in older adults. A detailed description of the inclusion and exclusion process is shown in Supplementary Figure S2. We compared the baseline characteristics of the overall participants and the included participants in the 2014 wave (Supplementary Table S1). We found that the included participants more likely resided in rural areas, were economically dependent, and reported a lower rate of heart disease.

The number of natural teeth was assessed by asking participants about the number of natural teeth they had at baseline. Participants were categorized into four groups based on their number of natural teeth: 0, 1–9, 10–19, and ≥20. Denture use was assessed by asking participants whether they had false teeth at baseline. Participants were categorized into two groups based on their denture use: with dentures and without dentures.

The cause of death was determined based on the International Classification of Diseases, 10th Revision (ICD-10) codes. The primary outcome was all-cause mortality. Cause-specific mortality was also examined for the following categories: cardiovascular disease (CVD) (codes I00-I99), respiratory disease (codes J00-99), cancer (codes C00-C97), and other causes. Mortality data were obtained from the participant’s next of kin or local doctors. Survival time was calculated from the first interview to the date of death or the last follow-up.

We controlled the potential confounding variables associated with the number of natural teeth, denture use, and mortality. These include age (continuous), sex, education (0 years, 1–6 years, or >6 years), residence (rural area or urban area), marital status [married or other (divorced, widowed, or never married)], living with family members [living with family member(s) or others (living alone or in an institution)], economic status (independence or dependence), smoking (never, current, or former), drinking (never, current, or former), regular exercise (never, current, or former), fruit intake (never, occasionally, or almost daily), vegetable intake (never, occasionally, or almost daily), meat intake (never, occasionally, or almost daily), fish intake (never, occasionally, or almost daily), and egg intake (never, occasionally, or almost daily), body mass index (BMI), chronic complications included self-reported hypertension (yes or no), heart disease (yes or no), diabetes mellitus (yes or no), respiratory disease (including bronchitis, emphysema, pneumonia) (yes or no), and cancer (yes or no). In addition, we classified BMI as underweight (<18.5 kg/m²), normal (18.5–23.9 kg/m²), overweight (24–27.9 kg/m²), and obese (≥28 kg/m²) (23). Supplementary Figure S3 shows the possible associations between variables.

Missing data would reduce statistical power and biased estimates of the relationship. Therefore, we adopted a multiple imputation method based on the chain equation and five repetitions methods to solve the missing data (ranging from 0.2% to 8.3%) (Supplementary Table S2). Baseline characteristics of the study are presented as percentages for categorical variables and mean and standard deviations (SDs) for continuous variables.

Kaplan–Meier survival analysis was utilized to construct survival curves for the number of natural teeth and the denture use, with log-rank testing assessing differences between the groups. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific mortality associated with the number of natural teeth (as a categorical or a continuous variable) and denture use. Model 1 was adjusted for baseline age, sex, residence, living arrangement, economic status, education, and marital status. Model 2 was further adjusted for smoking status, drinking status, regular exercise, fruit intake, vegetable intake, meat intake, fish intake, and egg intake, and further adjusted for denture use in the natural tooth model and further adjusted for the number of natural teeth in the denture use model. Model 3 was further adjusted for BMI, hypertension, heart disease, diabetes mellitus, respiratory disease, and cancer. To examine the individual impacts of tooth loss and denture use on mortality, we adjusted for denture use in the natural tooth model and the number of natural teeth in the denture use model. The crude incidence rate (IR) (per 1,000 person-years) of all-cause and cause-specific mortality was estimated. Linear trend tests were performed using the median values of varying categories of natural teeth numbers as a continuous variable. We used restricted cubic spline curves to examine the association of continuous values of natural teeth (20 natural teeth as reference) with all-cause and specific-cause mortality, with four knots at the 5th, 35th, 65th, and 95th percentiles of change in the natural teeth distribution. We conducted subgroup and interaction analyses by age, gender, denture use, residence, economic status, and BMI to investigate potential effect-modifying effects.

Furthermore, we conducted sensitivity analyses to examine the robustness of our main findings. First, we analyzed complete cases to evaluate the potential effects of the multiple imputation method. Second, to mitigate the potential influence of short-term follow-up, we excluded deaths within the first year, as the impact of oral health on mortality is often a chronic process. Third, we excluded participants with major chronic diseases at baseline, such as heart disease, respiratory disease, and cancer, to minimize some potential reverse causality. Finally, we used inverse probability weighting (IPW) based on the propensity scores to adjust for potential selection bias (24). The weights were the inverse of the probability of follow-up versus loss to follow-up, given the baseline covariates obtained via binary logistic regression. To assess the effectiveness of our propensity score modeling, we calculated a standardized mean difference (SMD) (all SMD <0.10).

All analyses were performed using R software version 4.1.3 (R Foundation for Statistical Computing), with a two-tailed p < 0.05 as the significance threshold.

A total of 5,403 older adults were included. The participants had a mean age of 85.4 years, with 53.8% being female. Table 1 presents the characteristics of the study population. Of all the participants, 80.6% reported having experienced tooth loss, and 35.7% of these individuals had lost all their teeth. The overall rate of denture usage was 35.1%, which increased proportionally with the number of teeth lost. Participants with fewer natural teeth tended to be older, female, unmarried, living alone, residing in rural areas, illiterate, economically dependent, using dentures, and underweight. Moreover, they were less likely to smoke, consume alcohol, exercise regularly, and suffer from hypertension, heart disease, diabetes mellitus, and respiratory diseases. They were likelier to have insufficient vegetables, fruits, meat, and fish intake.

Over a median follow-up of 3.4 years (interquartile range: 2.3 to 4.1, 16794.3 person-years), 2,126 (39.3%) participants died, with 435 (20.5%) deaths attributed to CVD, 216 (10.2%) to respiratory diseases, 107 (5.0%) to cancer, and 1,368 (64.3%) to other causes. Kaplan–Meier curves indicate that individuals with fewer teeth have a significantly lower chance of survival (Figure 1). Specifically, participants with 0 teeth had the lowest probability of survival, followed by those with 1–9 teeth, 10–19 teeth, and those with 20 or more natural teeth (log-rank test: p < 0.001) (Figure 1).

Individuals with 0 teeth and 1–9 teeth exhibited a substantially higher risk of all-cause mortality (0 teeth: HR 1.66, 95% CI 1.41–1.96; 1–9 teeth: HR 1.43, 95% CI 1.21–1.68) than those with 20+ teeth (Table 2). In addition, cause-specific analyses reveal that individuals with 0 and 1–9 natural teeth had significantly higher mortality from CVD (0 teeth: HR 1.83, 95% CI 1.28–2.63; 1–9 teeth: HR 1.57, 95% CI 1.10–2.24), cancer (0 teeth: HR 2.21, 95% CI 1.13–4.33; 1–9 teeth: HR 2.11, 95% CI 1.13–3.92), and other causes (0 teeth: HR 1.71, 95% CI 1.38–2.12; 1–9 teeth: HR 1.42, 95% CI 1.15–1.76) than those with 20+ teeth, but not from respiratory disease (Table 2). Furthermore, the hazard ratios (HRs) for the risk of death for the number of teeth (continuous variable) were as follows: 0.98 (0.97–0.98) for all-cause mortality, 0.98 (0.96–0.99) for cardiovascular disease (CVD) mortality, 0.97 (0.95–0.99) for cancer mortality, and 0.98 (0.97–0.98) for mortality from other causes (Table 2).

Restricted cubic spline analysis shows a linear trend in the correlation between the number of natural teeth and mortality due to all-cause, CVD, respiratory disease, and other causes (Figure 2; Supplementary Figure S4). However, no linear or non-linear relationship was found between the number of natural teeth and cancer mortality (Supplementary Figure S4).

The Kaplan–Meier analyses of denture use indicate that participants with dentures had higher survival than those without (Supplementary Figure S5). In addition, individuals with dentures demonstrated a lower risk of all-cause mortality (HR 0.79, 95% CI 0.71–0.88), CVD mortality (HR 0.80, 95%CI 0.64–1.00), respiratory disease mortality (HR 0.66, 95% CI 0.48–0.92), and mortality attributed to other causes (HR 0.77, 95% CI 0.68–0.88) than those without dentures. However, no significant difference was observed in cancer mortality (Table 2).

The Kaplan–Meier survival curves stratified by the number of natural teeth and denture use show that individuals with 0 teeth without dentures exhibited the lowest survival rates, whereas those with 10–19 teeth with dentures had the highest survival rates (Supplementary Figure S6). In addition, individuals with 0 teeth without dentures, 0 teeth with dentures, and 1–9 teeth without dentures had a significantly higher risk of all-cause mortality, CVD mortality, and other cause mortality than those with 20+ teeth with/without dentures (Table 3). Specifically, the HRs for all-cause mortality were 1.71, 1.37, and 1.48. The corresponding HRs for CVD mortality were 1.85, 1.55, and 1.65. The HRs for other causes of mortality were 1.76, 1.38, and 1.45. Moreover, individuals who had 0 teeth without dentures were also at a significantly higher risk of respiratory disease mortality (HR 1.75, 95% CI 1.06–2.87) than those who had 20+ teeth with/without dentures, while those who had 0 teeth with dentures and 1–9 teeth without dentures had a significantly higher risk of cancer mortality (HR 2.27, 95% CI 1.20–4.29 and HR 2.35, 95% CI 1.20–4.57, respectively) (Table 3). In contrast, individuals with 10–19 teeth with/without dentures and 1–9 teeth with dentures were not found to have a significantly high risk of all-cause mortality or cause-specific mortality when compared to those with 20+ teeth with/without dentures (Table 3).

Supplementary Figure S7 reveals that the association between the number of natural teeth and all-cause mortality was more pronounced in older adults aged <80 years (than those aged ≥80 years) (p-value for interaction = 0.03). Among individuals aged ≥80 years, only those with fewer than 10 teeth had a higher risk of all-cause mortality. No other variables, including sex, residence, BMI, economic status, and denture use, significantly modified the association between the number of natural teeth and denture use and all-cause and cause-specific mortality (Supplementary Figures S8–12).

The associations between the number of natural teeth and denture use with all-cause and cause-specific mortality remained consistent after excluding participants with missing covariate values (Supplementary Table S3). Similarly, after removing participants who died within one year of follow-up, no essential changes in the results were observed (Supplementary Table S3). Additionally, no substantive changes in the results were observed when excluding participants with pre-existing conditions such as heart disease, respiratory disease, and cancer (Supplementary Table S3). Finally, after conducting IPW using propensity scores, no substantive differences were observed in the results (Supplementary Table S3).

This study provides a valuable contribution to the existing literature on the role of the number of natural teeth and dentures in predicting all-cause and cause-specific mortality in older adults. This study’s strengths include using a large sample of older adults, examining the number of natural teeth, and using dentures as separate measures of dental health. The number of natural teeth and the use of dentures provide different information about oral health status and are dependent and correlated variables. Therefore, separately analyzing them may allow for a more nuanced understanding of the relationship between oral health status and other variables of interest. It can also provide valuable information for researchers and policymakers in designing interventions and policies to improve oral health outcomes. However, this study has several limitations to consider. First, the study was based on the self-reported number of natural teeth and denture use, which may be subjected to reporting bias. Second, we could not assess the effect of changes in dental health over time, as dental health was only assessed at baseline. Third, we did not have information on the cause of tooth loss, which could affect the association between the number of natural teeth and mortality. Fourth, the study was limited to older adults in China, and the findings may not be generalizable to other populations. Finally, as with any analysis, residual confusion caused by unmeasured factors cannot be eliminated.