The Influence of a 9-Week Movement Program on the Body Composition of 7- to 8-Year-Old Schoolchildren in the Eastern Cape of South Africa.
Mere IdamokoroAnita Elizabeth PienaarBarry GerberMaria M van GentPublished in: International journal of environmental research and public health (2023)
Pediatric obesity has become a growing global epidemic which has negative health consequences, including for South African children. This study aimed to determine the immediate and sustainable influences of a 9-week movement program on the body composition of 7 to 8-year-old school children in a rural area of South Africa. A two group, pre-test, post-test and re-test after six months experimental design was used to compare anthropometric measurements of the intervention group (IG) and control group (CG). Ninety-three schoolchildren (IG = 57; CG = 36) participated in the study. A 9-week movement program was followed twice a week for 30 min during school hours with an emphasis on improving BMI. Hierarchical Linear Modelling (HLM) was used to analyze the data with time, sex and group as predictors. Effect sizes was computed based on the Cohen's d to assess the practical significance of findings. The intervention positively changed the waist circumference. The subscapular skinfold and BMI showed statistical and practically significant sustainable changes because of the intervention, although gender influenced these effects. School based movement interventions, focusing on improving fundamental movement skills (FMS), have the potential to contribute to a healthier BMI, skinfold thickness and circumferences among young children.
Keyphrases
- body composition
- south africa
- body mass index
- resistance training
- bone mineral density
- randomized controlled trial
- hiv positive
- weight gain
- mental health
- physical activity
- healthcare
- type diabetes
- metabolic syndrome
- young adults
- tyrosine kinase
- insulin resistance
- public health
- electronic health record
- placebo controlled
- magnetic resonance imaging
- weight loss
- risk assessment
- artificial intelligence
- body weight
- medical students
- neural network
- human immunodeficiency virus
- human health