Statistical analyses
adiposity
REGRESSION, HEART, ADIPOSITY
Statistical analyses were performed using the IBM Statistical Package for the Social Sciences version 24.0 (SPSS Inc, Chicago, IL, USA). All variables were assessed for normality by visual inspection of histograms. Relationships between the central tendencies were examined using student T-tests, for normally-distributed data, or Mann Whitney-U tests for non-normal data. Heart rate recovery data was stratified according to the median (“Slow Heart Rate Recovery” >105 s and “Quick Heart Rate Recovery” <105 s). Differences between groups were explored using student T-tests, Mann Whitney-U tests or Chi-square tests as appropriate. Pearson correlation was used for normally distributed data, with Spearman’s correlation for non-normally distributed data to measure the correlation between heart rate recovery after the step test with adiposity and cardiovascular measures. Significant correlations were used to create multiple regression models using a forced entry approach to control for confounders which were selected a priori (effort in the step test, child sex, age at study visit, and exposure to breastfeeding). Perceived effort and age at appointment were controlled for to account for differences within the sample population. Models were adjusted for breastfeeding exposure and child sex because previous literature suggests they may influence child adiposity in preschool ages [