Jun Duan

Introduction: Tooth loss is associated with increased mortality risk; however, the mechanism underlying this is still not clear. The objective of this study was to explore whether frailty mediates the association between tooth loss and mortality risk among the oldest old individuals.Methods: The participants were followed up from 1998 to 2018 in the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Frailty was constructed following a standard procedure. Mortality, frailty, and tooth loss were applied as the outcome, mediator, and independent variables, respectively. The Cox model was fitted, including possible confounders, for causal mediation analysis. A total effect (TE), an average causal mediation effect (ACME), an average direct effect (ADE), and a proportion mediated (PM) effect were calculated.Results: During the 129,936 person-years at risk, 31,899 individuals with a mean age of 91.79 years were included. The TE and ADE of severe tooth loss on mortality were 0.12 (95% CI: 0.08, 0.15) and 0.09 (95% CI: 0.05, 0.13); the ACME of frailty was 0.03 (95% CI: 0.02, 0.03) with 21.56% of the TE being mediated.Discussion: This study illustrated that tooth loss is associated with mortality, and frailty appeared to mediate the relationship. It is recommended that oral health indicators and frailty status be incorporated into routine geriatric assessments to promote optimal oral health and non-frailty status.

A variety of measurement methods were used comprehensively in this paper to conduct empirical research on the CE, spatial pattern characteristics and influencing causes of the YREB. Both the total factor CE and the single factor CE were discovered relatively stable. Starting around 2013, the development of the tail cities of the YREB has gradually improved. In addition to Sichuan, Hunan, Chongqing, Hubei and other places where the increase in CE had exceeded that of other cities, the development of CE in Shanghai has also increased significantly. The CE of the YREB had increased with a significant positive spatial autocorrelation and a significant spatial aggregation effect between 2006 and 2017. The spatial spillover effect of CE in the YREB is mainly transmit through factors such as economic growth, energy structure, industrial structure, government intervention, population density, foreign direct investment and the level of marketization, and the spatial interaction between each factor and CE cannot be ignored.