Frailty is defined as a medical syndrome that can increase the risk of adverse outcomes including all-cause mortality (Chang and Lin, 2015), hospitalization (Kojima, 2016), and disability (Vermeiren et al., 2016). Meanwhile, previous studies have demonstrated that frailty is a dynamic condition and frailty status can transition between better and worse over time (Lee et al., 2014). This aspect of frailty presents an opening for potential preventative and restorative interventions. Lifestyle is considered one of the main keystones in the development of frailty, and a healthy lifestyle can help older adults to manage frailty (Feng et al., 2017). As a common component of lifestyle, daily sedentary behavior (SB) and physical activity (PA) may play an important role in the development of frailty (Kehler et al., 2018a; 2018b).
One recent review summarized the epidemiological evidence concerning the impact of SB on frailty (Kehler et al., 2018b). In this review, almost all studies used subjective assessment of SB such as TV watching time or self-reported sedentary or inactive lifestyle found a significant negative association between SB and frailty indicted that promoting physical activity may be a feasible way to prevent frailty. However, evidence of the association between objective assessment of SB and frailty was inconsistent. Of all studies that examined the association between objectively measured total sedentary time and frailty among community-dwelling older adults (Bastone Ade et al., 2015; Blodgett et al., 2015; Castaneda-Gameros et al., 2018; Del Pozo-Cruz et al., 2017; Jansen et al., 2015; Kehler et al., 2018a; Manas et al., 2018; Nagai et al., 2018; Song et al., 2015), only three studies found significant associations (Blodgett et al., 2015; Del Pozo-Cruz et al., 2017; Song et al., 2015). One reason causing this inconsistency might be most studies conventionally operationalize sedentary time as total sedentary time without considering SB accumulation patterns. Indeed, increasing evidence showed that the SB accumulated in different length bouts (prolonged uninterrupted bouts vs. short bouts) might result in distinct health outcomes (Bellettiere et al., 2019; Diaz et al., 2017). In a recent study of Toledo Healthy Study on Aging (THSA), no significant association was found between the duration of SB bouts lasting [greater than or equal to] 10 min and the score of the Frailty Trait Scale (Del Pozo-Cruz et al., 2017). However, a significant association was found between the duration of SB bouts lasting [greater than or equal to] 30 min and the levels of frailty in females from the National Health and Nutrition Examination Survey (NHANES) (Kehler et al., 2018a, Kehler et al., 2019). Therefore, further studies are needed to examine whether the association between SB and frailty depends on the bout length definition.
As for the association between objective assessment of PA and frailty, a recent review found that a higher amount of total moderate-to-vigorous physical activity (MVPA) time was consistently associated with frailty (Kehler and Theou, 2019). Although WHO recommended that older adults aged 65 years and older should accumulate at least 150 minutes of MVPA per week in bouts [greater than or equal to] 10 min (WHO, 2010), meeting such recommendation may be challenging, especially in the older adult with frailty (Blodgett et al., 2015). A recent systematic review found that both MVPA in bouts of [greater than or equal to] 10 min (bouted MVPA) and
Japan has the largest proportion of the elderly population and has the most rapid aging rate than that of any other country, while the life expectancy is the highest in the world (Arai et al., 2015). Moreover, according to a recent systematic review and meta-analysis, the prevalence of frailty in Japan was lower than in other countries (7.5% vs 9.9%) (Kojima et al., 2017). Comprehensively examine the associations of objectively assessed different patterns of SB and PA with frailty in Japan may provide a unique insight into the management of frailty. Thus, the purposes of the present study were to investigate if different SB, PA patterns and the number of steps are associated with frailty status and tried to determine the optimal cut-off value of PA and SB variables, and steps to discriminate between frailty and non-frailty in Japanese community-dwelling older adults.
Cross-sectional data were derived from the baseline survey of the Itoshima Frail Study (IFS), which was carried out from September to December in 2017. The design of IFS has been described in detail elsewhere (Chen et al., 2020). Briefly, the IFS is an ongoing community-based prospective study in Itoshima City, located in northwest Japan. Its aiming is to explore modifiable lifestyle factors causing/protecting against frailty. The inclusion criteria of IFS were primary residents of Itoshima city, aged 65-75 years, who were not certified as requiring nursing care by the National Long-term Care Insurance System. Of approximately 10,000 older adults, 5,000 were randomly selected according to the residential area, sex, and age. A set of study information sheets and questionnaires were mailed to subjects, inviting them to community cent ers f or furth er assessments. Of the 5,000 individuals contacted, 1,631 submitted questionnaires and 949 completed further assessments, for a response rate of 32.6% and 19.0%, respectively. Of the 949 subjects, we excluded 19 individuals who did not have accelerometer data, 69 individuals with less than 4 days of valid accelerometer data, and 42 individuals with missing data of covariates. This study was approved by the Institutional Review Board of the K. University, Japan. All participants provided written informed consent.
Frailty status was assessed by a Japanese version of the FRAIL scale (FRAIL-J, Table 1), which has shown good reliability and construct validity in our previous study (Chen et al., 2020). The FRAIL-J includes two biological components (fatigue and loss of weight), two functional components (resistance and ambulation) and one deficit accumulation component (illness). The total score ranges from 0-5 points, with one point assigned to each component. Although the original FRAIL scale set a 3-point score as the cut-off point to identify frailty, our previous study showed that, compared to a 3-point cut-off, a 2-point cutoff had better criterion validity and could be the optimal one in Japanese older adults (Chen et al., 2020). Indeed, a 2-point cutoff for the FRAIL scale was also recommended in the Brazilian and Chinese versions (Aprahamian et al., 2017, Dong et al., 2018). Therefore, in the present study, a score of 0 would indicate robust participants, 1 as prefrailty, and 2-5 as frailty.
SB and PA variables
SB and PA were measured objectively using a waist-mounted, tri-axial, accelerometer (Active style Pro HJA-350IT, Omron Healthcare, Kyoto, Japan) for seven consecutive days after the health assessment. The previous study reported that METs determined by the Active Style Pro HJA-350IT were closely correlated with METs calculated by the indirect calorimetry, with an average percentage of differences less than 10%. Accordingly, the Active Style Pro directly estimates the intensity of activities as METs (Ohkawara et al., 2011). Participants were instructed by trained personnel to wear the accelerometer on either side of their waist during their waking hours, and to remove the device only before going to bed or when engaging in water activities. Simple instruction and a log diary were also provided to encourage compliance with accelerometer protocols. Data were recorded in 60-s periods for the data analysis. The SAS macro program provided by the National Cancer Institute (National Cancer Institute, 2015) was modified for our accelerometer to compute daily non-wear time, as described elsewhere (Chen et al., 2017, Honda et al., 2016). Non-wearing time was defined as at least 60 consecutive min of no activity, with an allowable 2 min to reach up to 1.0 METs. Data for participants with at least 4 valid wear days (at least 10 h of wear time per day) were included in the analysis.
Sedentary time was defined as a minute in which activity intensity was [less than or equal to] 1.5 METs, for example, resting in the sitting and lying or using computer (Ohkawara et al., 2011). A sedentary bout was defined as a period of sedentary time accumulated without interruption. Previous studies used 10 or 30 min/day as the cut-off value to define prolonged sedentary duration (Del Pozo-Cruz et al., 2017; Kehler et al., 2018a), however, a consensus is still lacking on the best measure of sedentary accumulation patterns. Therefore, apart from 10-min and 30-min bout of sedentary time, mean sedentary bout duration was also calculated by dividing total sedentary...