A large body of evidence indicates that higher levels of physical activity (PA) in late life are associated with reduced risks of several chronic diseases and all-cause mortality (Nelson et al., 2007). On the other hand, sedentary behavior (SED), defined as any waking behavior characterized by an energy expenditure [less than or equal to] 1.5 metabolic equivalent units (METs) while in a sitting or reclining posture, is increasingly recognized as a life-style factor raising the risk of cardiovascular disease, type 2 diabetes and mortality, independent of PA levels (Biswas et al., 2015; Chomistek et al., 2013; Koster et al., 2012). Therefore, accurate measurement of the PA and SED levels in community-dwelling older population under free living conditions is needed to improve the understanding of daily PA and SED, and to inform public health strategies to increase PA and reduce SED in older adults.
Traditionally, epidemiological studies rely on subjective measures, such as questionnaires and behavioral records, in the assessment of PA in community-dwelling older people. However, such measures are often reported to either over- or underestimate PA levels due to recall bias, particularly in older adults (Kowalski et al., 2012). Moreover, many of the existing subjective tools fail to measure SED and light-intensity PA adequately (Shephard, 2003), while these two might be major determinants of daily PA level for older adults (Colbert et al., 2014; Meijer et al., 2001). Alternatively, accelerometers are capable of measuring PA objectively, and thus have been widely accepted as valid measures of PA in a number of populations including older adults (Copeland and Esliger, 2009; Lee and Shiroma, 2014). More recently, a tri-axial accelerometer with its prediction models accounting for the type of activity performed has been shown to yield more accurate estimation of PA intensity (Midorikawa et al., 2007; Ohkawara et al., 2011), which might potentially improve the understanding of daily PA and SED in older adults.
To date, there are only a few large-scale studies that objectively assessed PA and SED using accelerometers in older adults while most of accelerometer-based studies were carried out in the western population (Arnardottir et al., 2013; Davis et al., 2011; Evenson et al., 2012; Hansen et al., 2012; Jefferis et al., 2014; Lohne-Seiler et al., 2014). Little is known regarding accelerometer-derived PA and SED levels in older adults in countries of different cultures and environments, such as Japan. Moreover, although the Japanese society undergoing the world's fastest aging, Japan has the highest healthy life expectancy at birth (Tamiya et al., 2011). Thus, data from older adults in Japan may provide unique insight into the current levels of PA and SED in older adults. The main aims of this study were therefore to 1) describe levels of PA and SED in Japanese community-dwelling older people, using tri-axial accelerometers, 2) examine the variation of PA and SED with respect to sex, age, and body mass index (BMI).
The present study was performed as part of the baseline survey of Sasaguri Genkimon Study (SGS) conducted from May to August 2011. The design of the SGS is described in detail elsewhere (Narazaki et al., 2013; 2014). Briefly, it is an ongoing community-based prospective study in the town of Sasaguri, a suburban town on Kyushu Island located in the southwest part of Japan, aiming to explore modifiable lifestyle factors causing older adults to require long-term care. Subjects of the baseline study (SGS-1) were all residents of the town, who were 65 years or older and not certified as individuals requiring long-term care by Japan's Long-term Care Insurance System (Tsutsui and Muramatsu, 2005) at the end of January 2011 (n = 4,979: 15.7% of residents of the town, men: 43.6%). Sixty-six subjects were excluded due to being dead or moving out by the onset of the study. A set of study information sheets and a questionnaire were mailed to all remaining subjects (n = 4,913), and 2,629 individuals, hereafter referred to as the participants of the SGS-1, agreed to take part in SGS-1 by 1) visiting the nearest community center or municipal office of the town, 2) agreeing to take an individual home-testing session if they were unable to come or not available on the testing day (recruitment rate: 53.5%). All participants of SGS-1 were invited to take part in the study of objectively measured PA during the SGS-1. Of these, we excluded 582 individuals who did not wear the accelerometer, 300 individuals providing less than 4 days of valid accelerometer data, and 8 participants missing BMI data (Figure 1). Given that individuals with long-term care needs were excluded from the SGS during the prescreening process and quality of the accelerometer data depends on participants' compliance (Wilcox et al., 2002), no additional exclusion criterion was decided to maximize the sample size. Thus, 1,739 participants were included in the present analysis (66.1% of the baseline sample) (Figure 1). All the participants provided written informed consent, and the study was conducted in accordance with the declaration of Helsinki and was approved by the Institutional Review Board of the Institute of Health Science, Kyushu University.
PA was measured by a tri-axial accelerometer (Active style Pro HJA-350IT, Omron Healthcare, Kyoto, Japan). Participants were instructed to wear the accelerometer on either the right or left side of their waist for consecutive 7 days and to remove the accelerometer only before going to bed or water activities. A simple instruction and a log diary were also provided to encourage the compliance to accelerometer protocols.
Technical specification and data acquisition system for the Active style Pro have been previously reported (Ohkawara et al., 2011; Oshima et al., 2010). Briefly, data was collected in 1-minute epochs for the data analysis. An established model, in combination with PA classification algorithm for discrimination between locomotive and non-locomotive activities, was used to estimate the intensity of PA (Ohkawara et al., 2011). METs determined by the Active style Pro have been reported to be closely correlated with METs calculated by the indirect calorimetry, with an average percentage of differences less than 10% (Ohkawara et al., 2011). Accordingly, intensity of PA captured was expressed in METs (Ohkawara et al., 2011). Non-wearing time was defined as at least 60 consecutive minutes of zero counts, with allowance for 2 minutes with counts greater than zero. Data for participants with at least 4 valid wear days (at least 10 hours of wear time per day) were included in the analysis, which is in line with previous studies to estimate habitual PA in older adults(Arnardottir et al., 2013; Hansen et al., 2012; Lohne-Seiler et al., 2014).
METs-based cut-points were used to define SED, light PA (LPA), and moderate-to-vigorous PA (MVP A) as following: [less than or equal to] 1.5 METs for LPA, 1.6-2.9 METs for LPA, and [greater than or equal to] 3 METs for MVP A (Ainsworth et al., 2000; Owen et al., 2010). Number of steps (steps per day) was also calculated...