Tooth loss is prevalent in older adults and associated with functional capacity decline. Studies on the susceptibility of some individuals to the effects of tooth loss are lacking. This study aimed to investigate the heterogeneity of the association between tooth loss and higher-level functional capacity in older Japanese individuals employing a machine learning approach. This is a prospective cohort study using the data of adults aged ≥65 y in Japan ( N = 16,553). Higher-level functional capacity, comprising instrumental independence, intellectual activity, and social role, was evaluated using the Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC). The scale ranged from 0 (lowest function) to 13 (highest function). Doubly robust targeted maximum likelihood estimation was used to estimate the population-average association between tooth loss (having <20 natural teeth) and TMIG-IC total score after 6 y. The heterogeneity of the association was evaluated by estimating conditional average treatment effects (CATEs) using the causal forest algorithm. The result showed that tooth loss was statistically significantly associated with lower TMIG-IC total scores (population-average effect: −0.14; 95% confidence interval, −0.18 to −0.09). The causal forest analysis revealed the heterogeneous associations between tooth loss and lower TMIG-IC total score after 6 y (median of estimated CATEs = −0.13; interquartile range = 0.12). The high-impact subgroup (i.e., individuals with estimated CATEs of the bottom 10%) were significantly more likely to be older and male, had a lower socioeconomic status, did not have a partner, and had poor health conditions compared with the low-impact subgroup (i.e., individuals with estimated CATEs of the top 10%). This study found that heterogeneity exists in the association between tooth loss and lower scores on functional capacity. Implementing tooth loss prevention policy and clinical measures, especially among vulnerable subpopulations significantly affected by tooth loss, may reduce its burden more effectively.

中文翻译：

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牙齿缺失与功能限制的异质关联

牙齿脱落在老年人中很常见，并且与功能能力下降有关。缺乏对某些个体对牙齿脱落影响的敏感性的研究。本研究旨在采用机器学习方法研究日本老年人牙齿缺失与高级功能能力之间关联的异质性。这是一项前瞻性队列研究，使用日本 65 岁以上成年人的数据（N = 16,553）。使用东京都老年学研究所能力指数（TMIG-IC）评估高级功能能力，包括工具独立性、智力活动和社会角色。等级范围从 0（最低功能）到 13（最高功能）。使用双稳健目标最大似然估计来估计 6 年后牙齿缺失（天然牙齿少于 20 颗）与 TMIG-IC 总分之间的群体平均关联。通过使用因果森林算法估计条件平均治疗效果 (CATE) 来评估关联的异质性。结果显示，牙齿脱落与较低的 TMIG-IC 总分在统计学上显着相关（人群平均效应：-0.14；95% 置信区间，-0.18 至 -0.09）。因果森林分析揭示了 6 年后牙齿脱落与较低 TMIG-IC 总分之间的异质关联（估计 CATE 的中位数 = -0.13；四分位数范围 = 0.12）。与低影响力亚组（即估计 CATE 处于最低 10% 的个体）相比，高影响力亚组的年龄和男性的可能性明显更高，社会经济地位较低，没有伴侣，健康状况较差。影响子群体（即估计 CATE 位于前 10% 的个人）。这项研究发现牙齿缺失与功能能力得分较低之间的关联存在异质性。实施预防牙齿缺失的政策和临床措施，特别是在受牙齿缺失严重影响的弱势亚群中，可能会更有效地减轻其负担。