High-Dimensional Effect Heterogeneity of Tooth Loss on Mortality

Abstract

Tooth loss has been associated with increased mortality risk in older adults. This study examined heterogeneity in the association between tooth loss and mortality among older Japanese adults. Data were obtained from 69,265 individuals aged ≥65 y who participated in the 2013 wave of the Japan Gerontological Evaluation Study. Questionnaire survey responses were linked to mortality records from municipal registries for 9 y. The average treatment effect (ATE) of tooth loss (having <20 natural teeth) on all-cause mortality was estimated using a linear probability model with an inverse probability weighting estimator. Heterogeneity in the association was assessed by estimating conditional average treatment effects (CATEs) using the causal forest machine learning algorithm. A set of 44 covariates, including demographic, economic, social, health, and community-related factors, was incorporated as potential drivers of heterogeneity. During the follow-up period, 26.4% of participants with <20 teeth and 14.4% of those with ≥20 teeth died. Tooth loss was significantly associated with increased mortality risk by 3.2 percentage points after adjustment for covariates (average treatment effect = 0.032; 95% confidence interval, 0.023–0.040). A statistically significant heterogeneity in the estimated effects was observed (median CATE = 0.028; interquartile range = 0.010). Greater effects were identified among subgroups characterized by men, poor health status, and lower socioeconomic conditions. Heart disease, sex, and depression were the most influential contributors to this heterogeneity. Tooth loss was associated with mortality risk, with significant variation in the magnitude across population subgroups. Tooth loss may serve as an informative indicator of elevated mortality risk among older adults, particularly among vulnerable subgroups.