Association Between Frailty Trajectory And All-cause Mortality In The Elderly

Objective:Frailty is a common geriatric syndrome,it can be adopted to predict the various adverse outcomes such as falls,disability,and death.However,most of the previous studies on frailty were based on single investigation results.The research on the trajectory of frailty development and its adverse outcome is relatively limited.On these grounds,the paper intends to conduct a large sample prospective study.The study can help identify subgroups of different development trajectories followed by the elderly in China and depict the trajectory curves of each subgroup.In addition,the influencing factors of different trajectories will be analyzed,and the longitudinal association between each trajectory and all-cause mortality will be discussed.Methods:The research data comes from the Chinese Longitudinal Healthy Longevity Survey(CLHLS).The participants included in the study were those who were over 65 years old and participated in three surveys consecutively from 2002 to 2008.By means of questionnaires,physical examinations,and laboratory tests,the database collected various kinds of information such as demographic characteristics,social and economic situation,cognitive function,self-care ability,chronic diseases of the elderly.Moreover,the database also collected the death date and pre-mortal health status of the deceased through a questionnaire for their family members.The frailty index is constructed with several health indicators.After fitting the Group-based trajectory modeling(GBTM),the frailty development trajectories of the young-old group(aged 60?79 years old)and the oldest-old group(aged 80 years and above)would be depicted.By rank-sum test and~2 test,the basic characteristics of different frailty trajectories were compared.Then based on the polynomial Logistic regression analysis,the paper explored the main factors affecting the attribution of the frailty trajectory of the elderly.In studying the relationship between different frailty trajectories and survival outcomes,the Kaplan-Meier survival curves of each trajectory group would be depicted.The Log-Rank method was used to identify whether there is a statistical difference in the all-cause mortality among different trajectory groups.Afterward,univariate and multivariate Cox proportional hazard regression analyses were used to estimate the hazard ratios(HR)of all-cause mortality and different frailty trajectories.Further stratified analyses were performed by gender(male and female).Results:A total of 3,555 subjects were eligible for this study,including 2,198 young-old and 1,357 oldest-old.Among the young-old group,there were three different development trajectory models, namely“low-stable model”,“medium-stable model”and“low start,rapidly increasing model”.Then from the perspective of demographic characteristics,it could be found that age,economic condition,religious belief,and smoking status can significantly affect the attribution of the frailty trajectory among the young-old group.Through a mean follow-up survey of 4.78 years,the mortalities of the elderly of three models were 33.32%,63.20,and75.63%.In the multivariate Cox regression model adjusted for various factors,compared with the“low-stable model”,the frailty trajectories of the“medium-stable model”and the“low start,rapidly increasing model”were related to an increased risk of all-cause mortality, and the corresponding HRs(95%CI)were 1.79(1.30-2.47)and 3.37(2.62-4.33).Then the group was stratified according to gender.In the female group,the frailty trajectories of the “medium-stable model”and the“low start,rapidly increasing model”were associated with an increased risk of all-cause mortality.As for the male group,the frailty trajectory of the “low start,rapidly increasing model”was statistically associated with an increased risk of all-cause mortality.Among the oldest-old group,there were four different frailty development trajectories, namely“low start,slowly increasing model”,“medium start,slowly increasing model”,“medium start,rapidly increasing model”and“high-level frailty model”.Factors such as age,gender,nationality,educational background,agricultural engagement,and regular exercise can significantly affect the trajectory of the oldest-old group.Through a mean follow-up survey of 3.06 years,the mortalities of the elderly of four models were 72.29%,88.20%,94.95%,and 95.35%.In the multivariate Cox regression model adjusted for various factors,compared with the“low start,slowly increasing model”,the frailty trajectories of the“medium start,slowly increasing model”,“medium start,rapidly increasing model”and“high-level frailty model”were related to an increased risk of all-cause mortality,and the corresponding HRs(95%CI)were 1.62(1.38-1.91),2.67(2.11-3.39)and 2.28(1.68-3.10).The results of gender stratification showed that in the male group and female group,the frailty trajectories of the“medium start,slowly increasing model”,“medium start,rapidly increasing model”and“high-level frailty model”were all associated with an increased risk of all-cause mortality.Conclusion:The young-old elderly and the oldest-old elderly showed different frailty development trajectories.Fast-development and high-level frailty trajectory may be risk factors for all-cause mortality.