Reliability and validity of the early years physical activity questionnaire (EY-PAQ)

Measuring physical activity (PA) and sedentary time (ST) in young children (<5 years) is complex. Objective measures have high validity but require specialist expertise, are expensive, and can be burdensome for participants. A proxy-report instrument for young children that accurately measures PA and ST is needed. The aim of this study was to assess the reliability and validity of the Early Years Physical Activity Questionnaire (EY-PAQ). In a setting where English and Urdu are the predominant languages spoken by parents of young children, a sample of 196 parents and their young children (mean age 3.2 ± 0.8 years) from Bradford, UK took part in the study. A total of 156 (79.6%) questionnaires were completed in English and 40 (20.4%) were completed in transliterated Urdu. A total of 109 parents took part in the reliability aspect of the study, which involved completion of the EY-PAQ on two occasions (7.2 days apart; standard deviation (SD) = 1.1). All 196 participants took part in the validity aspect which involved comparison of EY-PAQ scores against accelerometry. Validty anaylsis used all data and data falling with specific MVPA and ST boundaries. Reliability was assessed using intra-class correlations (ICC) and validity by Bland–Altman plots and rank correlation coefficients. The test re-test reliability of the EY-PAQ was moderate for ST (ICC = 0.47) and fair for moderate-to-vigorous physical activity (MVPA)(ICC = 0.35). The EY-PAQ had poor agreement with accelerometer-determined ST (mean difference = −87.5 min·day−1) and good agreement for MVPA (mean difference = 7.1 min·day−1) limits of agreement were wide for all variables. The rank correlation coefficient was non-significant for ST (rho = 0.19) and significant for MVPA (rho = 0.30). The EY-PAQ has comparable validity and reliability to other PA self-report tools and is a promising population-based measure of young children’s habitual MVPA but not ST. In situations when objective methods are not possible for measurement of young children’s MVPA, the EY-PAQ may be a suitable alternative but only if boundaries are applied

Concentration curves for SRHS in Chile before (2000) and after (2013) the healthcare reform in Chile of 2005.

<p>Concentration curves for SRHS in Chile before (2000) and after (2013) the healthcare reform in Chile of 2005.</p

Concentration Indexes (CIs) for income related inequality in SRHS in Chile before (2000) and after (2013) the equity-centered healthcare reform of 2005.

<p>Concentration Indexes (CIs) for income related inequality in SRHS in Chile before (2000) and after (2013) the equity-centered healthcare reform of 2005.</p

Decomposition of the Erreygers CIs: the relative contribution of each legitimate and illegitimate factor to inequality in SRHS in Chile before (2000) and after (2013) the healthcare reform in Chile of 2005*.

<p>Decomposition of the Erreygers CIs: the relative contribution of each legitimate and illegitimate factor to inequality in SRHS in Chile before (2000) and after (2013) the healthcare reform in Chile of 2005*.</p

Descriptive statistics of variables in this study, crude and stratified by “above average” (i.e. above-average) SRHS.

<p>*Chi2 test or t-test p value <0.05 at 95% confidence level when comparing categories of “above average” SRHS between year 2000 and 2013</p><p>**Chi2 test or t-test p value <0.001 at 95% confidence level when comparing categories of “above average” SRHS between year 2000 and 2013</p><p>***Currency exchange rates obtained from the International Monetary Fund web source (available in: <a href="http://www.imf.org/external/np/fin/data/param_rms_mth.aspx" target="_blank">http://www.imf.org/external/np/fin/data/param_rms_mth.aspx</a>)</p><p>Descriptive statistics of variables in this study, crude and stratified by “above average” (i.e. above-average) SRHS.</p

Proportion of the adult population reporting “above average” SRHS within each equivalized household income quintile in year 2000 and 2013.

<p>Proportion of the adult population reporting “above average” SRHS within each equivalized household income quintile in year 2000 and 2013.</p

Mean SRHS (range 0 “below average” to 1 “above average”) in years 2000 and 2013, by age groups and healthcare provision entitlement^*.

<p>*Other provision and none/don´t know excluded from this table as they represent small numbers and are more difficult to interpret in terms of social gradients</p><p>Mean SRHS (range 0 “below average” to 1 “above average”) in years 2000 and 2013, by age groups and healthcare provision entitlement<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0138227#t001fn001" target="_blank">^*</a>.</p

Summary of study variables included as legitimate and illegitimate factors for inequality in SRHS, CASEN surveys 2000 and 2013.

<p>Summary of study variables included as legitimate and illegitimate factors for inequality in SRHS, CASEN surveys 2000 and 2013.</p

Additional file 1: of Is small size at birth associated with early childhood morbidity in white British and Pakistani origin UK children aged 0–3? Findings from the born in Bradford cohort study

Table S1. Comparison of models of predicted child outcome measures (with 95% CI), by ethnicity, low birth-weight and small for gestational age (SGA-GROW) with and without adjustment for socio-economic variables (predicted rates with 95% CI). Table S2. Comparison of adjusted* incidence rate ratios (95% CI) of child outcome measures by ethnicity, low birth-weight and small for gestational age (SGA-GROW) with and without adjustment for socioeconomic variables. (DOC 89 kb

Coefficients used to derive the childhood obesity risk score from a multivariable logistic regression model for each equation comprising baby’s sex, birthweight z-score, weight change z-score and maternal BMI. Probability childhood obesity = 1/(1+ e <sup>

a<p>Weight change z-score from birth to 6, 9 or 12 months in equation 1, 2 and 3 samples respectively.</p