Study design

The current analyses used data from a longitudinal study (B-PROACT1V) conducted at the University of Bristol (UK). The aim of the study was to examine the physical activity and sedentary behaviours of children and their parents during primary school. Extensive detail on the first phase of data collection has been previously published [13, 23]. Briefly, study recruitment began in January 2012, with data collection conducted between February 2012 and July 2013 when the children were in their second year of schooling (known as Year 1 in the UK – children were aged 5 to 6 years). Two hundred fifty primary schools within Bristol, Bath and North Somerset were invited to take part in the study, from which 57 schools consented to participate and data collection was conducted. All children in Year 1 (or Y1 and Y2 in schools with combined classes) were eligible, with 1299 children and at least one of their parents consenting to participate (see Fig. 1).

Fig. 1 Flow diagram of recruitment to the Year 4 phase of the B-PROACT1V study (STROBE) Full size image

The second phase of data collection was conducted when the children were in Year 4 (aged 8 to 9 years) between March 2015 and July 2016. All 57 schools that participated in the first phase were invited to participate in the second phase; 10 schools declined for various reasons (e.g., Ofsted (government) inspections, staff changes, scheduling issues), with the remaining 47 schools agreeing to participate. Where possible, schools were recruited in the same order as the Year 1 data collection to closely replicate the data collection timeline and average difference between the dates of the Year 1 and 4 data collections was 6.9 days. The median difference in age between the time of data collection for each phase for children who took part in Year 1 and Year 4 was 3.00 years and 95% of the age differences ranged between 2.79 and 3.65 years. All children in Year 4 (or Y4 and Y5 in schools with combined classes) were eligible (n = 2047) regardless of whether they had participated in the first phase of data collection. In total, 1223 (59.7%) children and at least one of their parents consented and took part in the Year 4 data collection. One family consented but was not available for data collection.

Data collection at Year 4

Researchers arranged to visit each school to conduct a briefing presentation with the Year 4 children to explain the study. After the presentation, children were given an information pack to take home to their parents/carers. Child participation in the study was dependent on at least one parent or carer (maximum of two parents/carers) also agreeing to participate in the study. Ethical approval for the study was granted from the School for Policy Studies Research Ethics Committee at the University of Bristol and written parental consent was provided for both parent and child participation [24].

Child height was measured to the nearest 0.1 cm using a SECA Leicester stadiometer (HAB International, Northampton). Weight was recorded to the nearest 0.1 kg using a SECA 899 digital scale (HAB International, Northampton). The children were then given a waist-worn ActiGraph wGT3X accelerometer, shown how and when to wear it, and given a pack to take home to their parents.

Parent packs contained either one or two accelerometers, depending on the number of parents/carers participating. Parents received instructions on how and when to wear the accelerometer. If indicated on the consent form, the packs also contained paper versions of the parent questionnaires. Alternatively, parents were sent a link to a secure online version of the questionnaire. The parent questionnaires assessed demographic variables and a number of psychosocial constructs that are not reported here.

Children and parents were instructed to wear the accelerometers for five full days (3 week days and 2 weekend days). During data collection a mobile phone SMS reminder system was in operation to inform parents about the when the accelerometers and questionnaires were being sent home and when to return the devices. At the end of the 5 days, parents were instructed to return the accelerometers and completed paper questionnaires to a marked returns box at the child’s school. If accelerometers or questionnaires were not returned directly, parents were sent reminder texts, calls and/or emails. If after 2 weeks, devices or questionnaires were still outstanding a letter and prepaid envelope were sent directly to the child’s home address. As a thank you for participating children were given a water bottle and a Frisbee upon completion of data collection.

Accelerometer data processing

Accelerometer data were processed using Kinesoft (v3.3.75; Kinesoft, Saskatchewan, Canada) and each day was considered valid if there was at least 500 min of data after excluding intervals ≥60 min of zero counts allowing up to two minutes of interruptions. For the complete case analysis, at least one valid weekday and at least one valid weekend day of data were required at both the Year 1 and Year 4 assessments. To maximise the sample size, if a participant had at least one valid day of data at either time point, this partial data was included in the imputation models (see below) to provide an indication of physical activity for the participant. Average counts per minute (CPM), average number of sedentary minutes per day and average number of MVPA minutes per day overall and separately by weekdays and weekend days for the children and their parents were derived. Minutes spent in MVPA were derived using population-specific cut points for children and adults [25, 26].

Child characteristics

Child gender and the number of siblings were reported by the parent. An age-adjusted BMI z-score was derived using the 1990 UK child growth reference, and categorised as under/normal weight (<85th percentile), overweight (≥85th percentile) or obese (≥ 95th percentile) [27]. Indices of Multiple Deprivation (IMD) scores, based upon the English Indices of Deprivation (http://data.gov.uk/dataset/index-of-multiple-deprivation), were assigned to each child-parent dyad based on their reported home postcode where higher IMD scores indicate a greater level of deprivation. Each school was asked to provide information on whether the child had moved school or remained in the same school between Year 1 and Year 4 (three schools refused to provide this information). The parent questionnaire at Year 4 also asked whether the child had moved school between Year 1 and Year 4.

Parent characteristics

Parent gender, age, height, weight, ethnicity and employment status were reported in the two parental questionnaires. Body mass index was calculated from self-reported height and weight (BMI = kg/m2).

Statistical analysis

Child and parent characteristics measured during the Year 1 phase of B-PROACT1V were examined as potential predictors of the child’s participation in the Year 4 phase using univariable logistic regression models. Odds ratios for participation at Year 4 versus not participating are presented for each characteristic.

To enable us to include information from all study participants in our analysis, and thus potentially increase statistical power and precision of estimates of change in physical activity, we used multiple imputation of missing data. This method also allows demographic factors that are predictive of missingness (but are not necessarily required in the analysis model) to be accounted for in the imputation procedure and can therefore reduce selection bias compared with analysis including only individuals with complete data [28]. We imputed data for the 1837 children who participated in either Year 1 or Year 4 using chained equations; this included imputing complete Year 4 data if the child participated in Year 1 but not Year 4 and vice versa. Twenty imputed datasets were created using 20 cycles of regression switching and results were then averaged over these datasets using Rubin’s rules [29]. Separate imputation models were used for boys and girls to allow for possible differences in missing data patterns that would influence results and to allow exploration of different patterns of change in physical activity between Year 1 and Year 4 by child gender. All child and parent accelerometer measures and child and parent characteristics that were potential predictors of missingness (child BMI, IMD and number of siblings and female/male parent response, age, BMI, ethnicity and employment status) at either year, were included in multiple imputation models. We also included a categorical variable indicating which school the child attended in order to account for the clustering of children within schools. For the three children who attended a different school at Year 4 from that in Year 1, we used their Year 1 school as this seemed most likely to influence their physical activity change between Year 1 and Year 4. The distributions of all included variables have been compared in the observed data and in the multiple imputation datasets.

The children’s physical activity levels (mean and SD) in Year 1 and Year 4 and the change in these between Year 1 and Year 4 were summarised for the imputed datasets and are presented separately for boys and girls. Confidence intervals for the change in physical activity were derived using robust standard errors to account for clustering of children within schools. Paired t-tests (based on these robust standard errors) were used to assess whether there was statistical evidence of a change in physical activity between Year 1 and Year 4. The female and male parents’ physical activity levels in Year 1 and Year 4 were also summarised and compared in the same way. Additionally, the mean and SD of each of the physical activity measures at Year 1 and Year 4 have been summarised for children and parents in the complete case analyses and the change in these measures was assessed, as in the imputed data, using paired t tests with robust standard errors.

There was a high degree of missing data for the male parents since male parents were less likely to participate in any aspect of the study than female parents. To check whether this was affecting our findings, we also imputed to the 864 children and parent triads where a male parent responded at either Year 1 or Year 4 and repeated the analysis of male parents’ physical activity levels in this subgroup as a sensitivity analysis. All analyses were performed in Stata version 14.0 (StataCorp, 2015).