Study design and population
The IDEFICS/I.Family cohort, retrospectively registered under ISRCTN62310987, is a population-based study which aimed to examine lifestyle-related diseases in children and adolescents from eight European countries including Belgium, Cyprus, Estonia, Germany, Hungary, Italy, Spain, and Sweden [12]. The IDEFICS study (Identification and prevention of dietary- and lifestyle-induced health effects in children and infants) comprised a baseline survey (T0, September 2007 – June 2008, n = 16,299 children aged 2.2–9.9 years) and two follow-up surveys at T1 (September 2010 – May 2011, n = 11,041 children aged 4–11.9 years), including 2555 newly recruited children [13]; and at T2, only conducted to assess dissemination of the intervention messages (by mail), not the full survey protocol. The follow-up surveys revealed only weak effects of the intervention [14], thus data from T0 and T1 were pooled together to incorporate a larger sample. Participants from T0 and T1 of the IDEFICS study as well as their parents and siblings were invited to participate in an enhanced third follow-up, the I. Family study (T3, in 2013–2014), where n = 7105 participated in the third follow-up which aimed to gather additional information pertaining to the entire family [15]. Requirements with respect to ethics approval and written or verbal (for children aged under 12 years) consent was obtained from local ethics committees by participating centres in all eight countries.
The present analysis included longitudinal data from the IDEFICS baseline and follow-up surveys (T0/T1) as well as data from the I.Family survey (T3). Accelerometer data was collected in a subsample at T0/T1 and T3 and physical fitness data was only collected at T0/T1. As these measures were only collected in subsamples of the IDEFICS and I. Family populations, a total of n = 4, 329 children were considered for this analysis. From this smaller sample, an additional n = 19 children were excluded as there was less than 3 years between the baseline (T0 or T1) and follow-up (T3) assessments, as such a total of n = 4310 children were included in the present descriptive analysis. Given our research questions about the associations between physical activity and physical fitness from childhood through adolescence, children must have i) completed at least one of the fitness tests at T0/T1, ii) provided parent survey information at T0/T1 and T3 and iii) had valid accelerometer data at T3 to be included in the final analyses. Children were not required to have accelerometer data at T0/T1 as a “missing category” was created for those who were not included in the accelerometry subsample. A total of n = 1, 280 children provided valid accelerometer data at T0/T1 and n = 1, 894 children provided valid accelerometer data at T3. The number of children included in the sample for the present analysis who completed fitness tests ranged from 2106 (40 m Shuttle run Test) to 4230 (Backsaver sit and reach test). Figure 1 provides a flow-chart of the sample size based on the IDEFICS / I.Family cohort and considered exclusion criteria.
Covariate information
In all centres, children were asked to wear light clothing and remove shoes while height and weight measurements were taken by nurses who were trained to follow standardized protocols. Height was measured to the nearest 0.1 cm using a clinical Seca 225 stadiometer (Seca, Hamburg, Germany). Weight was measured to the nearest 0.1 kg using a BC420 SMA scale (Tanita, Amsterdam, Netherlands). Body mass index (BMI) was classified (thin/normal or overweight/obese) according to cut-offs established by Cole and Lobstein [16].
Survey data was collected from parents regarding age, sex, income, and socio-economic status (SES). The highest educational level of parents was classified according to the international Standard Classification of Education (ISCED) to assess SES [17]. ISCED classifications were collapsed into low (ISECD 0–4) and high (ISCED 5+) categories. An additional missing category was created for any participants who did not have data reported on ISCED status. During I. Family assessments, information on pubertal development (i.e., voice change in boys and occurrence of the first menstrual period in girls) was used to classify children into pre/early pubertal or pubertal status. In some countries, Tanner stages were also assessed, and where information on pubertal status was missing, Tanner stages 1&2 were classified as pre-pubertal and Tanner stage 3 was classified as pubertal [18].
Physical activity
Physical activity was assessed using Actigraph accelerometers (Actigraph, LLC, Pensacola, FL, USA) worn on the right hip during waking hours only. Full details regarding accelerometer data processing from the IDEIFICS study were previously reported by Konstabel et al. [19]. During the IDEFICS (T0/T1) protocol, children were asked to wear either the ActiTrainer or GT1M device for at least 3 days, including 1 weekend day. For the I. Family (T3) protocol, children were asked to wear either the GT1M or GT3X+ device for a period of 7 days. Previous research has confirmed that activity counts from the vertical axis are comparable between the GT1M and GT3X+ devices [20], thus activity counts from only the vertical axis were used for this analysis. Devices were set to collect data at a sample rate of 30 Hz and data was downloaded in 15 sec epochs using ActiLife software (version 6, ActiGraph, Pensacola, FL). It should be noted that some centres inadvertently used 60 sec epochs for a considerable portion of their initial data processing, therefore all data were reintegrated into 60 sec epochs. Non-wear time was identified using a 60 minute window, to detect 30 minutes of consecutive zero counts, with a 2 minute tolerance for breaks of non-zero counts as defined by Choi et al. [21]. Participants were included if they had a minimum of 360 minutes of valid wear time on at least one weekday and one weekend day to compromise between accuracy and sample size as discussed in Konstabel et al. [19]. Remaining valid data were then scored using the Evenson cut points scaled up for 60 sec epochs (SED: 0–100; LPA: 101–2295; MPA: 2296–4011; and VPA: 4012+) [22]. For the present analysis, average minutes per day spent in TPA (LPA + MPA + VPA), MVPA and average valid wear time (mean minutes per day) were calculated. Children were then classified as having met the WHO recommendations for physical activity for ages 5–17 years if they obtained at least 60 mins of MVPA per day based on their average minutes spent in MVPA [4]. As no children under 5 years were included in the PA analyses, only the WHO guidelines for 5–17-year-olds were used. A missing category was created for children who did not have valid accelerometer data at T0/T1; only children with accelerometer data at T3 were included in the analyses involving physical activity and fitness.
Physical fitness tests
Physical fitness testing was completed during T0 /T1 and the five test items were largely based on the ALPHA health-related fitness test battery which has shown reliability in children and adolescents [23,24,25]. Test items included: the Flamingo Balance test (FB), Backsaver Sit and Reach test (SAR), Handgrip Strength test (HGS), Standing Long Jump test (SLJ) and 40-m Sprint test (40mS). Additionally, the 20-m Shuttle Run test (20mSRT). To be included in the present analysis, children must have completed at least one of these fitness tests. All testing protocols have been described previously [23, 26] and full details are provided in Supplementary Table S1.
Briefly, during the FB test, children stood on one foot and the number of times their free leg touched the ground within 1 minute was recorded. For the SAR test, children reached as far as possible with one leg out straight, the furthest distanced reached (cm) was recorded. During the HGS test, children squeezed a dynameter (TKK 5101; Takei, Tokyo, Japan) as hard as possible and results were recorded in kilogram force (kgf) and then converted into Newtons (N). For the SLJ test, children were instructed to jump as far as possible and land with feet together, the distance was from the starting point to the most posterior heel was recorded (cm). For the 40mS test, children ran a 40-m distance as fast as possible, speed was recorded in kilometers per hour (km/h). Finally, the 20mSRT test was administered to assess cardio-respiratory fitness, children were instructed to run 20-m, back-and-forth while matching their pace to beep signals. Children continued until reaching fatigue or failing to complete the distance before the beep on two occasions. Estimate values of VO2 Max calculated using the Leger equation [27] were used for analysis which has shown to be a valid and reliable measure of VO2 max in children [27, 28]. Note that participants from Italy and Hungary did not undergo this test, and the survey center in Hungary used a different protocol that could not be unified with results from other centres.
Statistical analyses
Descriptive statistics in terms of means, standard deviations and proportions were calculated to describe the study participant characteristics (T0/T1 and T3), fitness test performance (T0/T1) and PA variables (T0/T1 and T3).
Research question 1: is baseline PA associated with follow-up PA?
To assess the longitudinal associations of PA behaviours, we first conducted linear regressions to assess the longitudinal association of meeting PA guidelines at T0/T1 with MVPA at follow-up. Subsequently, logistic regressions were conducted to predict whether children who met WHO guidelines at baseline were more likely to meet WHO guidelines at follow-up. These regressions were adjusted for age, sex, country, ISCED, income, BMI category all at T0/T1; and time between T0/T1 and T3 (gap), pubertal status and valid wear time at T3. These models were conducted for the entire sample, stratified by sex and thirdly, stratified by sex and pubertal status at T3.
Research question 2: is baseline physical fitness associated with follow-up PA?
To assess the associations between baseline levels of physical fitness with PA measures at follow-up, performance on each fitness test at T0/T1 were all individually regressed onto average time spent in MVPA at T3 using linear regressions. Subsequently, logistic regression models were conducted to predict whether children with higher performance on physical fitness tests at T0/T1 predicted higher likelihood of meeting WHO guidelines at T3. These models were adjusted for age, sex, country, ISCED, income, BMI category, meeting WHO guidelines all at T0/T1; and time between T0/T1 and T3 (gap), pubertal status and valid wear time at T3. All regressions were conducted for the entire sample, stratified by sex and thirdly, stratified by sex and pubertal status at T3.
Level of significance for all statistical analyses was set to α = 0.05 to obtain 95% confidence limits (95%CL) as a precision measure of beta estimates. In addition, standardized Beta coefficients were calculated. As a sensitivity analysis, we compared baseline characteristics of children who provided PA data based on accelerometry and who were included in this study with children who participated in T3 but had no PA measurements taken, due to different reasons. All statistical analyses were conducted in IBM SPSS Statistics (Version 26.0) analytics software.