Periodontitis is associated with an increased hazard of mortality in a longitudinal cohort study over 50 years

AIM

To evaluate the association between periodontal disease and all-cause mortality in a longitudinal cohort study over 50 years.

MATERIALS AND METHODS

Participants (N = 1156) in the Veterans Affairs Dental Longitudinal Study, aged 25-85 years at enrollment in 1968, received comprehensive medical and oral exams approximately every 3 years through 2007. Periodontal status was defined using person-level, mean whole-mouth radiographic alveolar bone loss (ABL) scores using a five-point Schei ruler, each unit representing 20% increments of ABL. Time-varying Cox regression models estimated hazard ratios (HRs) for the association between continuous and categorical ABL and mortality, adjusting for covariates.

RESULTS

Each one-unit increase in mean ABL score was associated with a 14% increase in the hazard of mortality (adjusted HR = 1.14, 95% confidence interval [CI] 1.02, 1.27). When assessed categorically, HRs for average scores of 2 to <3 and 3 to ≤5 showed increasing associations with hazard of mortality, relative to 0 to <1 (adjusted HR = 1.17, 95% CI 0.94, 1.46; and HR = 1.65, 95% CI 0.94, 2.85, respectively). By contrast, we observed null associations for average scores of 1 to <2 relative to 0 to <1 (adjusted HR = 1.00, 95% CI 0.86, 1.17).

CONCLUSIONS

Time-varying periodontal status assessed using radiographic ABL was positively associated with all-cause mortality even after confounder adjustment.

Causal and Associational Language in Observational Health Research: A Systematic Evaluation

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

Exploring periodontitis misclassification mechanisms under partial-mouth protocols

AIM

To investigate the sources of periodontitis misclassification under partial-mouth protocols (PMPs) and to explore possible approaches to enhancing protocol validity.

MATERIALS AND METHODS

Using data from 10,680 adults with 244,999 teeth from the National Health and Nutrition Examination Survey, we compared tooth-, site-, and quadrant-specific periodontal parameters and case identification under full-mouth protocols and PMPs. Separately, we utilized population measures of tooth-specific periodontal severity to generate PMPs with tooth selection based on the population ranking of clinical severity and assessed the sensitivity of case identification.

RESULTS

Symmetry of clinical severity was generally confirmed, with the exception of lingual inter-proximal sites, which yielded greater sensitivity in identifying periodontitis compared to buccal sites due to more severe pocketing and attachment loss on average. Misclassification of severe periodontitis occurred more frequently under commonly implemented PMPs compared to ranking-based selection of teeth, which yielded sensitivity estimates of 70.1%-79.4% with the selection of 8 teeth and reached 90% with the selection of only 14 teeth.

CONCLUSIONS

Clinical symmetry and sources of periodontitis misclassification were confirmed. The proposed selection of teeth based on population rankings of clinical severity yielded optimal sensitivity estimates for the detection of severe periodontitis and may present a favourable alternative to current options.

Edentulism is associated with increased risk of all-cause mortality in adult men

BACKGROUND

Prior reports of positive associations between edentulism and all-cause mortality have been limited by onetime assessments of edentulism and inadequate control of known confounding variables. The authors aimed to assess the association between edentulism and mortality using a longitudinal clinical oral health cohort.

METHODS

The authors used data from the Department of Veterans Affairs Dental Longitudinal Study, an ongoing, closed-panel cohort study from 1968 through 2019 (N = 1,229). Dentition status was evaluated through triennial clinical examinations. Mortality was assessed via the National Death Registry. The authors used Cox regression models to estimate the association between edentulism and all-cause mortality after covariate adjustment. Furthermore, the authors calculated propensity scores and assessed hazard ratios (HRs) in a trimmed, matched, and inverse probability weighted sample.

RESULTS

Participants who were edentulous (N = 112) had 1.24 (95% CI, 1.00 to 1.55) times the hazard of all-cause mortality compared with those who were nonedentulous, after adjustment with time-varying covariates. Use of propensity scores in the model resulted in slightly elevated HRs compared with the standard Cox model, regardless of propensity score method; adjusted HRs were 1.35 (95% CI, 1.01 to 1.80) after matching, 1.26 (95% CI, 1.00 to 1.59) after trimming, and 1.29 (95% CI, 1.18 to 1.42) after inverse probability weighting.

CONCLUSIONS

Edentulism was associated with an increased risk of all-cause mortality in a cohort that captured incident edentulism. This association was consistent after multiple methods to account for confounding.

PRACTICAL IMPLICATIONS

The findings of this study suggest that edentulism is associated with an increase in risk of mortality, after accounting for salient confounding variables using multiple approaches. Efforts to improve equitable access to tooth-preserving treatments are critical.

Simulation of Random Differential Periodontitis Outcome Misclassification with Perfect Specificity

INTRODUCTION

Misclassification of clinical periodontitis can occur by partial-mouth protocols, particularly when tooth-based case definitions are applied. In these cases, the true prevalence of periodontal disease is underestimated, but specificity is perfect. In association studies of periodontal disease etiology, misclassification by this mechanism is independent of exposure status (i.e., nondifferential). Despite nondifferential mechanisms, differential misclassification may be realized by virtue of random errors.

OBJECTIVES

To gauge the amount of uncertainty around the expectation of differential periodontitis outcome misclassification due to random error only, we estimated the probability of differential outcome misclassification, its magnitude, and expected impacts via simulation methods using values from the periodontitis literature.

METHODS

We simulated data sets with a binary exposure and outcome that varied according to sample size (200, 1,000, 5,000, 10,000), exposure effect (risk ratio; 1.5, 2), exposure prevalence (0.1, 0.3), outcome incidence (0.1, 0.4), and outcome sensitivity (0.6, 0.8). Using a Bernoulli trial, we introduced misclassification by randomly sampling individuals with the outcome in each exposure group and repeated each scenario 10,000 times.

RESULTS

The probability of differential misclassification decreased as the simulation parameter values increased and occurred at least 37% of the time across the 10,000 repetitions. Across all scenarios, the risk ratio was biased, on average, toward the null when the sensitivity was higher among the unexposed and away from the null when it was higher among the exposed. The extent of bias for absolute sensitivity differences ≥0.04 ranged from 0.05 to 0.19 regardless of simulation parameters. However, similar trends were not observed for the odds ratio where the extent and direction of bias were dependent on the outcome incidence, sensitivity of classification, and effect size.

CONCLUSIONS

The results of this simulation provide helpful quantitative information to guide interpretation of findings in which nondifferential outcome misclassification mechanisms are known to be operational with perfect specificity.

KNOWLEDGE TRANSFER STATEMENT

Measurement of periodontitis can suffer from classification errors, such as when partial-mouth protocols are applied. In this case, specificity is perfect and sensitivity is expected to be nondifferential, leading to an expectation for no bias when studying periodontitis etiologies. Despite expectation, differential misclassification could occur from sources of random error, the effects of which are unknown. Proper scrutiny of research findings can occur when the probability and impact of random classification errors are known.

A quantitative bias analysis to assess the impact of unmeasured confounding on associations between diabetes and periodontitis

AIM

To investigate unmeasured confounding in bidirectional associations between periodontitis and diabetes using quantitative bias analysis.

METHODS

Subsamples from the Veterans Affairs Dental Longitudinal Study were selected. Adjusted for known confounders, we used Cox proportional hazards models to estimate associations between pre-existing clinical periodontitis and incident Type II Diabetes (n = 672), and between pre-existing diabetes and incident severe periodontitis (n = 521), respectively. Hypothetical confounders were simulated into the dataset using Bernoulli trials based on pre-specified distributions of confounders within categories of each exposure and outcome. We calculated corrected hazard ratios (HR) over 10,000 bootstrapped samples.

RESULTS

In models using periodontitis as the exposure and incident diabetes as the outcome, adjusted HR = 1.21 (95% CI: 0.64-2.30). Further adjustment for simulated confounders positively associated with periodontitis and diabetes greatly attenuated the association or explained it away entirely (HR = 1). In models using diabetes as the exposure and incident periodontitis as the outcome, adjusted HR = 1.35 (95% CI: 0.79-2.32). After further adjustment for simulated confounders, the lower bound of the simulation interval never reached the null value (HR ≥ 1.03).

CONCLUSIONS

Presence of unmeasured confounding does not explain observed associations between pre-existing diabetes and incident periodontitis. However, presence of weak unmeasured confounding eliminated observed associations between pre-existing periodontitis and incident diabetes. These results clarify the bidirectional periodontitis-diabetes association.

The impact of periodontitis exposure misclassification bias from partial-mouth measurements on association with diabetes and cardiovascular disease

AIM

To quantify exposure misclassification bias arising from use of partial-mouth protocols in studies of periodontitis-systemic disease associations.

MATERIALS AND METHODS

Using data from 10,134 adults participating in the National Health and Nutrition Examination Survey, we classified periodontal status based on full-mouth clinical examinations and three commonly used partial-mouth protocols. Associations between periodontitis and self-reported diabetes and cardiovascular disease were evaluated under each protocol using adjusted logistic regression. Percent relative bias was calculated to evaluate magnitude and direction of bias.

RESULTS

Misclassification primarily resulted in underestimation of associations, the extent of which depended on both the outcome under study and exposure severity. Bias due to misclassification of severe periodontitis was negligible for cardiovascular disease (0%-4.1%) compared to diabetes (177.7%-234.1%). In contrast, bias in moderate periodontitis associations was comparable across each outcome-diabetes (28.4%-39.5%) and cardiovascular disease (8.9%-46.7%). Results did not meaningfully change based on the partial-mouth protocol implemented. Stratified analyses showed increased bias among those with ≤15 teeth. Use of mean attachment loss as a continuous exposure resulted in minimal-to-no bias.

CONCLUSIONS

Exposure misclassification bias due to use of partial-mouth protocols can yield inaccurate conclusions about periodontitis-systemic disease associations, the extent of which may depend on periodontitis classification and the association under study.