Background: The relationship between activity levels and body fat in children is unclear, despite a large number of studies. The issue is clouded by the wide variety of methods used to assess children's activity levels. It is important to assess whether the type of activity measure influences the fatness-activity relationship. This is a first step to uncovering the role of modifying variables such as gender, age, maturity, etc.
Primary objective: This study uses meta-analytic procedures to synthesize the results of such studies and to assess whether the type of activity measure used has an effect on the strength of the relationship observed.
Methods and procedures: Fifty studies were located that satisfied the inclusion criteria. Seventy-eight per cent of the studies showed a negative relationship, 18% no relationship and 4% a positive relationship between physical activity and body fatness. Data were analysed using the meta-analytic procedures described by Rosenthal (Meta-analytic Procedures for Social Research, Sage, 1991).
Main outcomes and results: The mean effect size indicated a small to moderate, inverse relationship (r = -0.16). Mean effect sizes differed significantly (F(3,52) = 8.04, p < 0.001) according to the activity measure used: questionnaire, r = -0.14; motion counters, r = -0.18; observation, r = -0.39; heart rate (HR), r = 0.00. Observation measures elicited a significantly stronger relationship with body fat than did questionnaire or heart rate measures (p < 0.05). However, there was no significant difference between the effect sizes elicited by observation and motion counters. Correlational analyses revealed no effect of age group or gender on the strength of the relationship between fatness and activity.
Conclusions: This meta-analysis suggests there is a small to moderate relationship between body fat and activity in children. It is important to note, however, that the size of the relationship depends on the activity measure used. It is therefore recommended that direct measures of movement, such as observation or motion counter methods, are used to assess the relationship of activity levels with health.