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Julian David Pillay, Tracy Lynn Kolbe-Alexander, Willem van Mechelen and Estelle Victoria Lambert

Background:

Pedometer-based recommendations for accumulating steps/d largely focus on volume, with less emphasis on intensity and fitness/health outcomes. We aim to examine this relationship.

Methods:

A convenience sample (N = 70, 35 men, 32 ± 8yrs) wore a pedometer (4 days). The pedometer classified steps as “aerobic” (≥ 60 steps/minute, minimum duration of 1 minute) or “non-aerobic” (< 60 steps/minute and/or < 1 minute). Estimated maximal oxygen uptake (VO2max), derived from a 12-minute submaximal step-test, and health outcomes: blood pressure (BP), body mass index (BMI), percentage body fat (%BF), and waist circumference (WC) were correlated with pedometer data. Participants were grouped according to number and intensity of steps: LOW (< 5000 steps/d), HIGH-LOW (≥ 5000 steps/d, no aerobic steps), HIGH-HIGH (≥ 5000 steps/d, including some aerobic steps). Analyses of covariance, adjusting for age, gender, and total steps/d were used to compare groups.

Results:

Average steps/d was 6520 ± 2306. Total steps/d and total time spent accumulating “aerobic” steps (minutes/day) were inversely associated with %BF, BMI, WC, and systolic BP (P < .05). After adjusting for gender and total steps/d, %BF was different between all 3 groups, VO2max was different between the LOW and HIGH-HIGH groups, WC was lower in the HIGH-HIGH versus the other 2 groups (P < .03, respectively).

Conclusion:

Intensity seems an important factor to consider in steps/d cut-points.

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Monika Uys, Catherine Elizabeth Draper, Sharief Hendricks, Anniza de Villiers, Jean Fourie, Nelia Steyn and Estelle Victoria Lambert

Background:

The purpose of this study was to assess factors that influence physical activity (PA) levels during break-times in South African primary school children.

Methods:

The System for Observing Play and Leisure Activities in Youth (SOPLAY) was used to observe PA levels during break-times at low-income schools (4 intervention, 4 control). The intervention was based on action-planning including: school environment, curriculum, and family involvement. Categories of observed activity included Sedentary, Eating, Walking, or Vigorous PA. Contextual factors assessed included teacher supervision, equipment, and crowding. Chi-square tests were used to determine associations between PA levels and contextual factors.

Results:

In the 970 observations made, 31% of learners were sedentary, 14% were eating, 29% were walking, and 26% were engaged in vigorous PA. There were no differences in break-time PA between intervention and control groups (NS). With supervision, children were more likely to eat and less likely to do vigorous PA (P = .035). Playground crowding was associated with lower levels of vigorous activity and more sedentary behavior (P = .000).

Conclusions:

PA during break-time was adversely affected by over-crowding and lower with supervision. The results suggest that interventions may be targeted at the school policy environment to reduce these barriers to PA.