Results from this longitudinal study suggest that increasing total PA and MVPA were associated with an improved body composition phenotype in a sample of older adults with overweight or obesity and the MetS. Greater total SB, and to a lesser extent TV-viewing sedentary time were associated with a worsen body composition. Overall, this study highlights that replacing 30 minute a day of IT with an equal amount of MVPA, LPA and time in bed resulted in significantly improved markers of body composition.
These findings are consistent with previous cross-sectional research in adult populations [3, 32, 40], which have found a hazardous relationship between SB and markers of body composition, including body fat, VAT and muscle mass [3, 9, 32, 40, 41]. The present results showed that greater SB is associated with greater body fat and lower muscle mass in an aging population, resulting in greater cardiometabolic risk and disability. In line with our findings, other authors found that increasing total PA and MVPA improves body composition [3, 8, 40] and reduce the accumulation of VAT [8, 10, 42, 43], yet no effects associated to LPA and body composition have been reported with the present results based on self-reported data.
Limited research using the ISM in older adults is available and only, isolated reports in general adult populations with chronic conditions, such as the MetS [44, 45], or using data from DXA scans are available[32]. However, no research using the same methods as this study in older adults has been found, limiting the opportunities for comparison. Cross-sectional research conducted in adults (≥ 18 years)[46, 47] showed similar beneficial effects of replacing a unit of time spent inactive with equal amounts of LPA, MVPA or sleep in body composition markers using anthropometric measures. However, if this relationship persists over time remains unclear.
Our results showed that replacing IT for LPA is associated with improved body composition changes (body fat and muscle mass), although the greatest benefit has been observed with MVPA. Similar results have been observed in previous cross-sectional research in adults[32] and in longitudinal studies performed with children [48, 49]. Therefore, the present results build on previous knowledge in other populations and indicate that replacing IT with any other activity behaviour has a beneficial impact on body composition in older adults with an incremental effect according to the intensity level. Indeed, replacing 30 min/day of IT with equal amounts of time in bed, LPA and MVPA was associated with a decrease in body fat of -0.09%, 0.13%, and − 0.54%, respectively. Therefore, these results showed the close interactions between IT, PA and health, and highlight the need for them to be treated jointly. These research also highlights that to promote the greater body composition changes MVPA is the most effective form of PA [8, 17, 32, 40, 43, 50], yet, increasing LPA in older adults with chronic conditions would also be of benefit for an improved health profile [13, 40, 47, 51–54]. Overall, small beneficial changes in body composition were observed when replacing IT by time in bed, which is similar to previous research [32, 52] which could be due to measurement errors, thus further research using gold standard measures to assess sleep in older adults are recommended.
Marked strengths of this study were the use of a longitudinal design in a large cohort of older men and women, with overweight/obesity and MetS across different communities in Spain using objective measurements. However, this study involved a homogeneous sample of Caucasian men and women within narrow ranges of BMI, age and with worsen metabolic health profile, limiting the opportunities for extrapolation into other ethnicities and with healthier individuals. Therefore, it is recommended for future research to be replicated in different ethnic groups with different lifestyles and fat distribution. It is important to highlight the novelty of the present study, with repeated measures of body composition using gold standard methods, such as DXA [55, 56], and the measurement of exposure variables with validated questionnaires and with accelerometer data in a subsample. Several complex and sophisticated statistical analyses were performed to assess our results. Some limitations to highlight are the use of questionnaires to obtain data on PA and SB within the larger sample, although these were validated methods and have facilitated the access to a larger sample size. It is important to mention that the GENEactiv is not able to differentiate between sitting and standing position or to differentiate time in bed from sleeping [29–31], thus further similar research using other monitors capable to differentiate between these behaviours is recommended. Finally, there was a considerable loss of data from the DXA scan at 6 and 12 months’ visits. Nevertheless, results were mostly consistent when imputing missing data in those subjects using the LOCF method.