Study design
Data for this study were collected from the Taiwan Longitudinal Study on Aging (TLSA), which examined healthy aging and longevity in participants aged ≥ 50 years. The TLSA was initiated in 1989 using stratified, multistage national probability sampling [28, 29], with a longitudinal and cross-sectional data set collected every 3 to 4 years. Informed consent was obtained from the participants. The present study used the data set from 2003 to 2015 with a total of 5267 community-dwelling participants. The protocol of this study was approved by the Research Ethics Committee of the National Health Research Institutes, Taiwan (EC1110104-E).
Visits
Baseline data were obtained from all participants in 2003, and they were subsequently interviewed at approximately 4-year intervals over a 12-year period (total of 4 study visits). Please see Appendix A for the construction of TLSA sample. Of the 5267 participants for which baselines data were obtained in 2003, 4330, 3579, and 2890 successfully completed the interviews in 2007, 2011, and 2015, respectively.
Measurements
The participants underwent a comprehensive interview to answer the survey questions. The cognitive status of participants was assessed using 9 items of the Short Portable Mental Status Questionnaire (SPMSQ) and 3 sets of recall questions. Mobility was recorded using a self-reported scale addressing the difficulties in performing 9 mobility tasks. General health status was considered by collecting the following data: the number of comorbid illnesses, walking device use, depressive symptoms surveyed using the Center for Epidemiological Studies-Depression (CES-D), living status, body mass index (BMI), the number of falls within 1 year, and visual and hearing impairments.
Demographics and health information
Data on age group, sex, walking device use, perceived mobility difficulty, body weight and height, the number of comorbid illness, and fall experiences were obtained through interviews and questionnaires during the study visits. Age was coded as interval groups as follows: 50–54, 55–59, 60–64, 65–69, 70–74, and ≥ 75 years.
Cognition
Cognitive status was assessed using the subset of SPMSQ and 3 additional questions, namely 3-item, 10-item, and backward serial recalls. The subset of SPMSQ includes the following domains: (1) orientation, (2) calculation, (3) short-term memory, and (4) language. One item of SPMSQ was excluded from the analysis because it was not assessed in 2003. The total scores range from 0 to 30, with a higher score indicating more favorable cognitive status. The Cronbach’s alpha value of the 9 items of SPMSQ with recall questions in this database ranged from 0.62—0.89 for the 4 waves, indicating an acceptable internal consistency of the scale.
Mobility
The mobility assessment consisted of 9 self-report items on participants’ difficulty to perform the following tasks without any assistance [30, 31]: (1) 15-min standing, (2) 2-h standing, (3) squatting, (4) arm lifting overhead, (5) hand grabbing and pinching, (6) object holding (up to 12 kg), (7) running (20–30 m), (8) walking (200–300 m), and (9) stair climbing (2–3 floors). Participants rated the degree of difficulty they experienced in completing the tasks on a scale of 0 to 3 (0 = no difficulties, 1 = some difficulty, 2 = considerable difficulty, 3 = unable to complete). A summary score for mobility difficulty was used in the inferential analysis. The Cronbach’s alpha value of the 9 items ranged from 0.93—0.94 for the 4 waves in this database, indicating a good internal consistency.
Walking and walking device use
Walking status was determined by asking participants to rate their walking status, level of difficulty in indoor walking, and whether they use an assistive device such as a cane or a walker.
Depressive symptoms
The 10-item CES-D was used to screen for depressive symptoms in the study. The CES-D was developed and validated by Radloff [32] and contains questions that measures depressed mood, feelings of guilt and worthlessness, feelings of helplessness and hopelessness, psychomotor retardation, loss of appetite, and sleep disturbance. The participants rated how often they perceived depressive symptoms in the preceding week. Scores range from 0 to 30, with high scores indicating greater depressive symptoms. The instrument was commonly used for community-dwelling older population and showed adequate reliabilities (Cronbach’s alpha: 0.7—0.93) [33, 34]. One item of CES-D was excluded from the analysis because it was not assessed in 2003.
Engagement of leisure activities and physical activities
The scale of leisure activity engagement consisted of 9 self-report items on whether the participant engage in the following 3 types of activities: (1) passive activities: watching television, listening to radio, and reading, (2) social activities: playing chess, gathering with relatives, friends or neighbors, and group activities (3) physical activities: gardening, walking, biking, and jogging . Physical activities was determined by asking participants the duration when they perform regular exercise each time.
Statistical analysis
Descriptive statistics including means, standard deviations, and frequencies were calculated. The variables of interest in the multivariate analysis were demographic characteristics, functional status and mobility, cognitive scores, depressive symptoms, sensory impairment, and number of comorbid illnesses. To examine whether the mobility difficulties of participants were associated with self-reported longitudinal cognitive scores, and sensory impairment, linear mixed-effects regression models were adopted. Probabilities and 95% confidence intervals were calculated for each predictor variable. The association of repeated falls with mobility, walking aid use, and living alone was examined using cumulative logit regression (SAS PROC GENMOD). PROC GENMOD enabled us to obtain models with nonnormally distributed data and specification of both time-varying (ie, fall occurrence, mobility difficulty, cognitive scores, depressive symptoms, number of comorbid illnesses, sensory impairment, and walking device use) and time-constant (ie, sex) variables.
This model tested the contributions of demographic characteristics (age group, sex, living alone), walking aid use, and cognitive scores on mobility difficulty. We controlled for the potential confounding effect of BMI, education, number of comorbid illnesses, and sensory impairment as these factors have been associated with both mobility and falls in previous studies.
Multiple imputations were used to address missing values caused by attrition. The SAS MI procedure was used to generate 10 imputed data sets based on the Markov chain Monte Carlo method. Analysis results for the 10 imputed data sets were combined using PROC MIANALYSE. We used SAS 9.4 (SAS Institute, Cary, NC, USA) to complete all analyses.