Cross-sectional and longitudinal associations between the 24-hour movement behaviours, including muscle and bone strengthening activity, with bone and lean mass from childhood to adolescence

The Physical Activity and Nutrition in Children (PANIC) study (ClinicalTrials.gov registration number NCT01803776) is an 8-year controlled lifestyle intervention study in a population sample of Finnish children that continues as a follow-up study [33]. Children aged 6 to 9 years who were registered for the first grade in one of the 16 public schools in the city of Kuopio, Finland, in 2007 to 2009 were invited to participate in baseline examinations between 2007 and 2009. Children were eligible to participate if they had no disability that could prevent their participation in the assessments or the intervention and if both the child and their parents and/or caregivers were able to communicate in Finnish to fill out the questionnaires and participate in the intervention. Of the 736 children invited to participate at baseline, 512 attended the baseline examinations at age 6 to 9 years, of which 504 were included in the final baseline sample. At age 9 to 11 years, 438 attended examinations, which took place between 2009 and 2011. At age 15 to 17 years, 277 attended examinations which took place between 2015 and 2017. Additional information about the PANIC study is presented elsewhere [34‐36].

This study used longitudinal data from baseline (at age 6 to 9 years), 2-year follow-up (at age 9 to 11 years) and 8-year follow-up (at age 15 to 17 years). For the present analyses, we excluded participants who used oral corticosteroids at any timepoint, as this could influence BMC [37], and participants with musculoskeletal injuries and diseases. Complete and valid data for age, stature, general health, pubertal status, DXA outcomes, and at least one movement behaviour were available for 478 children (229 females, 249 males) at age 6 to 9 years, 384 children (197 females, 187 males) at age 9 to 11 years, and 222 adolescents (103 females, 119 males) at age 15 to 17 years. The participants included in these analyses did not differ in age, stature, pubertal status, weight status, TBLH BMC, lean mass, or fat mass to the participants who did not have complete data. Inclusion and exclusion criteria are displayed in Fig. 1. The study protocol was approved by the Research Ethics Committee of the Hospital District of Northern Savo, and the study was conducted according to the ethical guidelines of the Declaration of Helsinki. At baseline and 2-year follow-up, the parents and/or caregivers of the children provided their written informed consent, and the children provided their assent to participation. At 8-year follow-up, the parents and/or caregivers and the adolescents gave their written informed consent.

General health was assessed by a questionnaire including items on children’s and adolescent’s chronic diseases and allergies diagnosed by a physician and information on children’s and adolescent’s medication use, completed by parents and/or caregivers. Pubertal status was assessed by a research physician according to stages described by Tanner [38]. Females were defined as pubertal if their breast development had started (Tanner stage ≥ 2), and males were defined as pubertal if their testicular volume assessed by an orchidometer was ≥ 4 mL (Tanner stage ≥ 2) [38].

At all timepoints stature was measured three times to an accuracy of 0.1 cm. Body weight was measured twice using the InBody 720 bioelectrical impedance analysis device (Biospace, Seoul, South Korea) to an accuracy of 0.1 kg, with participants in a fasted state, and emptied bladder. For stature and body weight, the mean of the values was used in analyses. Body mass index (BMI) (kg/m²) was calculated, BMI standard deviation score (SDS) was calculated using the Finnish reference values, and the BMI cut-offs were applied to classify children and adolescents as thin, normal weight, or living with overweight or obesity as it related to their weight status [39, 40].

TBLH BMC (kg), areal bone mineral density (aBMD) (g/cm²), lean mass (kg), and fat mass (kg) were measured by a research nurse using the Lunar Prodigy Advance DXA device (GE Medical Systems, Madison, WI, USA) and the Encore software, Version 10.51.006 (GE Company, Madison, WI, USA). TBLH BMC was used as the bone outcome of interest, as this is more appropriate than TBLH aBMD in longitudinal studies of bone accrual [4, 41, 42]. TBLH lean mass was considered as a secondary outcome, as lean mass is a key determinant of BMC, and the relationship between PA and BMC is mediated by lean mass [14]. DXA provides valid and reliable data on BMC and body composition in children and adolescents (coefficient of variation = 0.01 – 4.37%) [43, 44].

MVPA, muscle and bone strengthening activity, sedentary behaviour, and sleep were assessed, as these behaviours are outlined in the Canadian 24-hour Movement Guidelines for Children and Youth [10], the Australian 24-hour Movement Guidelines for Children and Young People [11] and, with the exception of sleep, the WHO Guidelines on Physical Activity and Sedentary Behaviour for Children and Adolescents [12].

Analyses were performed with Stata/SE for Mac software, Version 17.0 (StataCorp LLC, College Station, TX, USA). There were no differences between the children who did meet the inclusion criteria and those who did not meet the inclusion criteria in terms of age, stature, BMI categories, and pubertal status at age 6 to 9 years, age 9 to 11 years, and age 15 to 17 years. Further, the adolescents at age 15 to 17 years who met the inclusion criteria for the longitudinal analysis did not differ in terms of age, stature, BMI categories and pubertal status at age 6 to 9 years, age 9 to 11 years and age 15 to 17 years from those who did not. Therefore, we proceeded with a complete-case analysis.

The means and standard deviations (SDs) or the medians and interquartile ranges (IQRs) were calculated stratified by sex, for each timepoint. We stratified all further analyses by sex, based on the biological differences in stature, TBLH BMC, lean mass and fat mass between females and males in the studied age group [6, 64, 65].

Cross-sectional analyses were carried out at age 6 to 9 years, age 9 to 11 years, and age 15 to 17 years. Linear regression was used to assess the associations of minutes per day of MVPA, sport and exercise, sedentary time, screen time, and sleep with TBLH BMC and TBLH lean mass. Analyses were adjusted for age, stature, pubertal status, study group (control or intervention), and TBLH fat mass. When considering TBLH BMC as the outcome, we adjusted additionally for lean mass. Further, estimates for MVPA and sedentary time were mutually adjusted for each other, as correlation analyses for females and males separately at age 6 to 9 years, age 9 to 11 years, and age 15 to 17 years showed moderate to strong inverse relationships between these two variables (age 6 to 9 years, females: r = -0.58, p < 0.001, males: r = -0.59, p < 0.001; age 9 to 11 years, females: r = -0.60, p < 0.001, males: r = -0.72, p < 0.001; age 15 to 17 years, females: r = -0.63, p < 0.001, males: -0.66, p < 0.001).

Further longitudinal analyses were conducted by grouping the participants based on their activity status at age 6 to 9 years and age 15 to 17 years. This was only done for sport and exercise participation, as the sample size of participants with valid measurements at age 6 to 9 years and age 15 to 17 years was greatly limited for the device-measured variables (MVPA, sedentary time, sleep). A median split of average time spent in sport and exercise per day was used to categorise the participants. Participants were categorised as 1) persistently inactive (below median at age 6 to 9 years and age 9 to 11 years), 2) decreasingly active (above median at age 9 to 11 years and below median at age 15 to 17 years), 3) increasingly active (below median at age 6 to 9 years and above median at age 15 to 17 years), and 4) persistently active (above median at age 6 to 9 years and age 15 to 17 years).

Linear regression with robust standard errors was used to assess differences in TBLH BMC and lean mass at age 15 to 17 years between the persistently inactive, decreasingly active, increasingly active, and persistently active groups, adjusted for age, stature, pubertal status, study group, and fat mass at age 15 to 17 years, with additional adjustment for TBLH lean mass at age 15 to 17 years and TBLH BMC at age 6 to 9 years when considering TBLH BMC as the outcome, and with TBLH lean mass at age 6 to 9 years when considering TBLH lean mass as the outcome. Estimated marginal means for each group were computed and pairwise comparisons between each pairing were performed. All analyses were then repeated, replacing the age 6 to 9 years data with the age 9 to 11 years data. For all analyses, statistical significance was set at alpha level 0.05.

At age 6 to 9 years, males were taller, and had greater TBLH BMC and lean mass, and lower fat mass than females (Table 1). Males had greater MVPA, greater sport and exercise participation, no difference in sedentary time, greater screen time, and no difference in sleep duration compared to females (Table 2). A greater proportion of males met the guidelines for MVPA and muscle and bone strengthening activity than females, a greater proportion of females met the guidelines for screen time, and there was no difference in the proportion of females and males meeting the sleep guidelines (Table 2).

At age 9 to 11 years, males had greater TBLH BMC and lean mass, and lower fat mass than females. A greater proportion of females were pubertal compared to males (Table 1). Males had greater MVPA, greater sport and exercise participation, no difference in sedentary time, greater screen time, and less sleep compared to females (Table 2). A greater proportion of males met the guidelines for MVPA, there were no differences in the proportion of females and males meeting the muscle and bone strengthening guidelines, a greater proportion of females met the guidelines for screen time, and there were no differences in the proportion of females and males meeting the sleep guidelines.

At age 15 to 17 years, males were taller, heavier, and slightly older than females, with greater TBLH BMC and lean mass, and lower fat mass than females (Table 1). More females had achieved Tanner stage 5 compared to males. Males had greater MVPA, no difference in sport and exercise participation, no difference in sedentary time, greater screen time and less sleep compared to females (Table 2). There were no differences in the proportion of females and males meeting the MVPA guidelines, the muscle and bone strengthening guidelines, and the screen time guidelines, and a greater proportion of females met the sleep guidelines compared to males.

At age 6 to 9 years, sedentary time was negatively associated with TBLH lean mass (Table 3). There were no other associations of the movement behaviours with TBLH BMC or TBLH lean mass at age 6 to 9 years (Table 3). At age 9 to 11 years, sport and exercise participation was positively associated with TBLH BMC (Table 3). MVPA was positively associated with TBLH lean mass, and sleep was negatively associated with TBLH lean mass at age 9 to 11 years (Table 3). At age 15 to 17 years, sleep was positively associated with TBLH BMC (Table 3). MVPA and sport and exercise participation were positively associated with TBLH lean mass at age 15 to 17 years (Table 3).

At age 6 to 9 years, sport and exercise participation was positively associated with TBLH BMC and lean mass and sedentary time was positively associated with TBLH lean mass (Table 3). There were no other associations between the movement behaviours with TBLH BMC or TBLH lean mass at age 6 to 9 years. At age 9 to 11 years, MVPA, sport and exercise participation, and sedentary time were positively associated with TBLH lean mass. At age 15 to 17 years, screen time was negatively associated with TBLH BMC, and sport and exercise participation was positively associated with TBLH lean mass (Table 3).

MVPA at age 6 to 9 years was positively associated with TBLH BMC at age 15 to 17 years (Table 4). Sport and exercise participation at age 9 to 11 years was positively associated with TBLH BMC and lean mass at age 15 to 17 years (Table 4). MVPA at age 9 to 11 years was positively associated with TBLH lean mass at age 15 to 17 years (Table 4).

In terms of sport and exercise participation, from age 6 to 9 years to age 15 to 17 years, 38 females were persistently inactive, 13 were decreasingly active, 26 were increasingly active and 25 were persistently active. Increasingly active females from age 6 to 9 years to age 15 to 17 years had greater TBLH BMC at age 15 to 17 years than persistently inactive females (Fig. 2). Persistently active females from age 6 to 9 years to age 15 to 17 years had greater TBLH lean mass at age 15 to 17 years than persistently inactive and decreasingly active females, and increasingly active females had greater TBLH lean mass than persistently inactive females. From age 9 to 11 years to age 15 to 17 years, 36 females were persistently inactive, 16 were decreasingly active, 20 were increasingly active, and 31 were persistently active. Persistently active females from age 9 to 11 years to age 15 to 17 years had greater TBLH BMC at age 15 to 17 years than persistently inactive females. Persistently active females from age 9 to 11 years to age 15 to 17 years had greater TBLH lean mass at age 15 to 17 years than persistently inactive, decreasingly active, and  increasingly active females.

Sleep at age 6 to 9 years was positively associated with TBLH lean mass at age 15 to 17 years (Table 4). Sport and exercise participation at age 9 to 11 years was positively associated with TBLH BMC and lean mass at age 15 to 17 years (Table 4).

In terms of sport and exercise participation, from age 6 to 9 years to age 15 to 17 years, 36 males were persistently inactive, 20 were decreasingly active, 20 were increasingly active, and 36 were persistently active. Increasingly active and persistently active males from age 6 to 9 years to age 15 to 17 years had greater TBLH BMC at age 15 to 17 years than persistently inactive and decreasingly active males (Fig. 3). Persistently active males from age 6 to 9 years to age 15 to 17 years had greater TBLH lean mass at age 15 to 17 years than persistently inactive and decreasingly active males. From age 9 to 11 years to age 15 to 17 years, 37 males were persistently inactive, 15 were decreasingly active, 15 were increasingly active, and 37 were persistently active. Persistently active males from age 9 to 11 years to age 15 to 17 years had greater TBLH BMC at age 15 to 17 years than persistently inactive, decreasingly active and increasingly active males. Persistently active males from age 9 to 11 years to age 15 to 17 years had greater TBLH lean mass at age 15 to 17 years than persistently inactive and increasingly active males.

The null cross-sectional associations of MVPA with TBLH BMC in both sexes that we observed are in contrast with the results of some previous studies, as outlined in a 2020 systematic review, which have found consistent positive cross-sectional associations of MVPA with whole-body DXA bone outcomes in males and in both sexes combined, but inconsistent associations in females [71]. Whereas we observed a longitudinal relationship between MVPA with TBLH BMC in females only, the systematic review found relatively consistent positive longitudinal associations between MVPA and whole body bone outcomes in females and males [71]. The differences between our findings and those of previous studies may be due to the different devices used to capture PA. In our study, a combined heart rate and movement sensor was used to estimate energy expenditure from acceleration and heart rate, providing a more accurate assessment of energy expenditure than acceleration alone, as was used in previous studies [45, 71]. Therefore, our measure of MVPA includes activities which increase heart rate with relatively small increases in acceleration, such as cycling, whereas previous studies have captured MVPA based purely on acceleration. As acceleration is more related to musculoskeletal loading than heart rate, previous studies may have been more likely to capture mechanically loaded MVPA only [72]. Given that mechanical loading is important for bone adaptation [73], this may have led to stronger associations between MVPA and bone outcomes in studies which have used acceleration-only estimates of MVPA compared to MVPA based on acceleration and heart rate, as used in our study, though this may also depend on how the accelerometry data is treated [74]. However, as the WHO PA guidelines do not stipulate that the recommended average 60 minutes daily MVPA should be mechanically loaded [12], previous studies may have overestimated the importance of MVPA for bone, as described in the guidelines. Our findings suggest that MVPA is largely not related to BMC in children and adolescents, though females who do more MVPA in childhood may have improved BMC in adolescence.

There is a lack of previous research investigating the associations of accelerometer-assessed MVPA with DXA-assessed lean mass. We observed inconsistent cross-sectional relationships between MVPA and lean mass in females and males, whereas previous studies have reported null associations in females and males [75, 76], or positive associations in females only, between MVPA and lean mass in children and adolescents [77]. Whilst we found that the association between MVPA and lean mass persisted longitudinally in females only, Zymbal and colleagues [14] observed that both females and males who accumulated more MVPA from age 5 to age 17 years had greater leg lean soft tissue at age 17 years [14]. It is unclear what accounts for the different observations across studies. As the longitudinal study by Zymbal and colleagues [14] used lower-limb measures of lean mass, it is plausible that the observed associations would be stronger than in other studies using whole body measures of lean mass, as the lower-limb is loaded during normal weight-bearing activity, and the accelerometer placement at the hip would be expected to be more sensitive to loading at the hip and lower-limb [78]. However, given the conflicting findings, further high-quality longitudinal studies are needed to extend our understanding of the relationship between MVPA and lean mass, though our findings indicate that concurrent MVPA may be important for lean mass in females and males, and that females who do more MVPA in childhood may have improved lean mass in adolescence.

Although the positive cross-sectional associations of sport and exercise participation with TBLH BMC and lean mass were inconsistent across timepoints, we did find that sport and exercise participation at age 9 to 11 years was consistently positively associated with TBLH BMC and lean mass at age 15 to 17 years in females and males. Further, females and males who did more sports and exercise from childhood to adolescence had greater TBLH BMC and lean mass at age 15 to 17 years. Studies considering relationships between recreational sport and exercise participation with bone and lean mass in children and adolescents are scarce. In the Western Australia Pregnancy Cohort (Raine) Study, males who consistently participated in sport from age 5 to 17 years had greater whole-body BMC at age 20 than those who dropped out over time [79]. However, there were no differences in whole-body BMC in females based on their sport participation from age 5 to 17 years, and lean mass was not considered as an outcome [79]. The null association in females observed in the Raine cohort differs to our observations in females, potentially due to differences in measurement methods or covariates [79]. Whereas we considered average minutes per day of sport and exercise as our exposure in in both cross-sectional and longitudinal analyses, and categorised sport and exercise amounts into 4 groups as our exposure in further longitudinal analyses based on the average minutes per day from age 6 to 9 years to age 15 to 17 years, the Raine study used a binary indicator of whether the participants took part in any organised sport or not, which may contribute to the differences in findings [79]. A meta-analysis of exercise interventions, including jumping and/or circuit training, found a small, but statistically significant and beneficial effect of exercise on whole body BMC, further supporting our observations [80]. However, there was no effect of exercise interventions on lean mass [80]. It is possible that the activities captured within our measure of sport and exercise participation were more diverse than those used in intervention studies, offering a potential explanation for the relationship between sport and exercise participation and lean mass that we observed. Given the scarcity of studies investigating the relationships of sport and exercise participation with BMC and lean mass, further work is needed to better understand these relationships in general populations. Even so, our findings indicate that sport and exercise participation may be important for current BMC and lean mass, and that sport and exercise participation in childhood is important for BMC and lean mass in adolescence. Further, consistently participating in high levels sport and exercise across childhood and adolescence may lead to a greater BMC and lean mass at age 15 to 17 years. Given the current primary focus on aerobic activity in the WHO guidelines [12], our findings emphasise that the unique importance of muscle and bone strengthening activity for muscle and bone health should be promoted alongside MVPA, and included in future surveillance relating to the guidelines.

The null cross-sectional and longitudinal associations of sedentary time with BMC that we observed is consistent with the conclusion of a systematic review of previous studies looking at accelerometer-measured sedentary behaviour with bone outcomes in children and adolescents [23]. However, whilst we found screen time was cross-sectionally negatively associated with TBLH BMC at age 15 to 17 years in males, the systematic review highlighted insufficient evidence for an associations of self- or parental-reported sedentary behaviour, which includes screen time, with total body bone outcomes [23]. In terms of lean mass, we observed inconsistent negative cross-sectional associations between sedentary time and lean mass in females, inconsistent positive cross-sectional associations between sedentary time and lean mass in males, and null longitudinal associations of sedentary time and screen time with lean mass. Previous studies have observed negative cross-sectional associations [25] and, similar to our findings, null longitudinal associations [24] between measures of sedentary behaviour and fat-free mass. The positive cross-sectional relationships between sedentary time and lean mass in males are unexpected, as there is no apparent biological reason why being sedentary would increase lean mass once fat mass is controlled for, as we did, though as the relationships do not persist longitudinally, it is possible that unmeasured confounding factors may be influencing the cross-sectional relationships. Although it is important to highlight that evidence supporting the inclusion of sedentary behaviour in the movement guidelines is largely based on adiposity, other cardiometabolic risk factors and psychosocial risk factors, our findings, combined with previous evidence, indicate that largely sedentary behaviour was not detrimental to BMC and lean mass [12, 23].

Sleep was largely unrelated to BMC in our study population, except for a positive association at age 15 to 17 years in females. Although there is limited research considering the associations between sleep and bone health, the largely null associations between sleep and TBLH BMC that we observed is consistent with previous research. In a population sample of European children and adolescents, adherence to the sleep guidelines, assessed with questionnaires, was not associated with bone stiffness index, as measured by quantitative ultrasound, though lean mass was not accounted for [28], and similar null findings have been observed in adults [27]. Taken together, our findings suggest that sleep duration is largely not related to BMC in children and adolescents, though it may be beneficial in adolescent females. In our sample, sleep was negatively cross-sectionally related to TBLH lean mass in females only at age 9 to 11 years, though this did not persist longitudinally. In males, sleep at age 6 to 9 years was positively associated with TBLH lean mass at age 15 to 17 years. Generally, previous studies have observed null associations between sleep duration and lean mass in children and adolescents [31, 81, 82]. However, in girls and boys age 10 to 12 years, sleep duration was positively associated with fat-free mass [25]. Differences in measures of sleep duration and lean mass may contribute to the different observations between studies. Whereas our study used DXA measures of lean mass, previous studies used DXA-assessed fat-free mass, which includes bone [31, 82], or estimated fat-free mass from skinfold measures [25, 81]. Further, some studies used device-measured sleep duration [31, 82], as did ours, whereas other studies used a self or parental report [25, 81]. Given the conflicting findings, further research would be valuable in better understanding the relationship between device-measured sleep duration and DXA-assessed lean mass, though our findings indicate that a longer sleep duration in childhood may contribute to a greater lean mass in adolescence in males.

A 10-minute daily increase in MVPA at age 6 to 9 years was associated with 0.008 kg greater TBLH BMC at age 15 to 17 years in females, which equates to around 0.4 % of mean level of BMC at age 15 to 17 years. A 10-minute daily increase in MVPA at age 9 to 11 years was associated with 0.272 kg greater TBLH lean mass in females, which equates to around 0.8 % of the mean level of TBLH lean mass at age 15 to 17 years. A 10-minute daily increase in sport and exercise participation at age 9 to 11 years was associated with 0.020 kg greater TBLH BMC and 0.343 kg greater TBLH lean mass at age 15 to 17 years in females, which equates to around 1.0 % of the mean level of both BMC and lean mass at age 15 to 17 years. A 10-minute daily increase in sleep at age 6 to 9 years was associated with 0.382 kg greater TBLH lean mass at age 15 to 17 years in males, which equates to around 0.8 % of the mean level of lean mass at age 15 to 17 years. A 10-minute daily increase in sport and exercise at age 9 to 11 years was associated with 0.027 kg greater TBLH BMC and 0.721 greater TBLH lean mass at age 15 to 17 years in males, which equates to around 1.2 % of the mean level of BMC and 1.5 % of the mean level of lean mass at age 15 to 17 years. Given that theoretical modelling suggests a 10% increase in peak bone mass may delay the onset of osteoporosis by 13 years in later life [83], and that lean mass in key positive determinant of BMC [8], promoting MVPA, sport and exercise participation and sleep in childhood may contribute to delaying the onset of osteoporosis in later life.

The strengths of our study include the population-based sample of children with an 8-year follow-up into adolescence, device-measured MVPA, sedentary time and sleep, combined with questionnaire-assessed sport and exercise participation as a proxy for muscle and bone strengthening activity and screen time, and the measurement of BMC and lean mass by DXA. There are several limitations that should be considered when interpreting our findings. As we did not have a direct measure of muscle and bone strengthening activity, we were not able to directly assess the relationship between muscle and bone strengthening activity with BMC and lean mass. We used questionnaire-assessed participation in sport and organised exercise as a proxy measure for muscle and bone strengthening activity. Although previous studies assessing muscle and bone strengthening activities have measured participation in activities which would fall into the sport and organised exercise category, such as push-ups and weight-lifting, there may be other activities, such as swimming, which we have captured and would not be considered bone strengthening [84‐87]. However, it has been reported that the most popular types of organised sports and exercise in Finland for boys are football (soccer), ice hockey, and floorball (a type of indoor hockey), and for girls are dance, gymnastics, aerobics, football (soccer), and horseback riding, all of which reflect muscle and bone strengthening activities [55, 88]. Even so, future studies with a direct assessment of muscle and bone strengthening activity would be valuable in better understanding the relationship between muscle and bone strengthening activity with BMC and lean mass in children and adolescents. The use of the 60-second epoch to capture MVPA may have led to an underestimation of MVPA, particularly when the participants were children [89], which may have influenced the observed relationships between MVPA with BMC and lean mass [90]. Further, we did not consider the relationships between LPA with BMC and lean mass in this study, so the associations between LPA with BMC and lean mass in children and adolescents remain unknown. Although DXA is the gold-standard for the assessment of BMC and lean mass in children, it is not possible to obtain true volumetric bone mineral density estimates from DXA, and as such the determinants of volumetric bone mineral density in our sample remain unknown. Further, as our sample had relatively high levels of MVPA at age 6 to 9 years and age 9 to 11 years, it is unknown whether these findings extend to less active children. Finally, although we adjusted for important covariates, residual confounding remains a potential limitation in all observational studies, and causality cannot be assumed.