Sleep and physical activity patterns among Tanzanian, South African, and Côte d'Ivoire primary schoolchildren. Findings from the KaziAfya study - Christin Lang; Bonfoh Bassirou; Walter Cheryl; Honorati Masanja; Jürg Utzinger; Markus Gerber (Bern Open Publishing, 2023)
Introduction Sleep and physical activity habits during childhood are influenced by developmental, cultural and environmental factors. Poor sleep is associated with lower immune function, physical activity levels, and psychological functioning, thus contributing to a vicious cycle of increased vulnerability during this developmental period. Regular physical activity, in turn, is associated with better sleep, improved immune function, and higher psychological well-being. There is, however, a lack of research on sleep and physical activity patterns in Sub-Saharan Africa, especially among children from marginalized areas. Therefore, the present study has two objectives: First, it aims to fill a gap in the literature by reporting sleep and physical activity patterns among primary schoolchildren aged 6-12 years from Tanzania (Ifakara: N = 845), South Africa (Gqeberha: N = 1,287), and Côte d'Ivoire (Taabo: N = 1,027). Second, to investigate the relationship between habitual physical activity (7-day actigraphy) and sleep (parental and self-reported). Methods Thousand three-hundred and twenty children aged 5-12 years from each country were recruited. Sleep. Parents were asked to complete a few sleep-related questions regarding their child`s bed- and rise times. To assess sleep quality, children completed questions from the Pittsburgh Sleep Quality Index (Buysse et al., 1989). To screen for sleep disturbances, children also answered three items of the Insomnia Severity Index (Morin et al., 2011), addressing difficulty falling asleep, staying asleep and waking up too early in the morning. Physical Activity. Objective physical activity was assessed with an accelerometry (Actigraph wGT3x-BT, Shalimar, FL, USA) worn around the hip. The device was worn for 7 consecutive days to assess a full weekly period, with a sampling epoch of 15 sec (Rowlands, 2007). Time per day spent in MPA (>3 MET [metabolic equivalents of task]) and VPA (>6 MET) is determined based on the raw accelerometry counts and the ActiLife computer software, with cut-off values derived from Freedson et al. (1998). The ActiGraph accelerometrys have been validated with children (Crouter et al., 2013; Hänggi et al., 2013). Results Children assessed in Côte d'Ivoire and Tanzania showed higher levels of daily physical activity (MVPA) than those assessed in South Africa. Yet, mean group levels still exceeded the recommended amount of 60 min MVPA/day. Across all three countries, boys generally had higher MVPA levels than their female peers, and children from the poorest wealth quintile were also more active than their peers from the least poor quintile. Composite sleep health was significantly different between countries, with the highest scores reported in Tanzania, followed by Côte d'Ivoire and South Africa. After controlling for sex, it was found that MVPA significantly predicted composite sleep health among children in Tanzania (ß = 5.83, p = .002) and Côte d'Ivoire (ß = 3.41, p = .072), but not in South Africa (ß = 0.67, p > .05). Discussion/Conclusion Adequate sleep and physical activity is crucial for children's physical and mental development. Most of our understanding of the relationship between daily physical activity and sleep patterns is based on research conducted in Western high income countries. Currently, little is known about this association in children from Sub-Saharan African, specifically primary schoolchildren living in marginalized areas in Tanzania, South Africa, and Côte d'Ivoire. Results will reveal whether research from high-income countries is generalizable to low- or middle-income countries, and inform health policy makers on points for prevention and intervention in school-based settings. References Buysse, D. J., Reynolds, C. F., & Monk, T. H. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193-213. https://doi.org/10.1016/0165-1781(89)90047-4 Crouter, S. E., Horton, M., & Bassett, D. R. (2013). Validity of ActiGraph child-specific equations during various physical activities. Medicine & Science in Sports & Exercise, 45(7), 1403-1409. https://doi.org/10.1249/MSS.0b013e318285f03b Freedson, P. S., Melanson, E., & Sirard, J. (1998). Calibration of the Computer Science and Applications, Inc. accelerometer. Medicine & Science in Sports & Exercise, 30(5), 777-781. https://doi.org/10.1097/00005768-199805000-00021 Hänggi, J. M., Phillips, L. R. S., & Rowlands, A. V. (2013). Validation of the GT3X ActiGraph in children and comparison with the GT1M ActiGraph. Journal of Science and Medicine in Sport, 16(1), 40-44. https://doi.org/10.1016/j.jsams.2012.05.012 Morin, C. M., Belleville, G., Bélanger, L., & Ivers, H. (2011). The Insomnia Severity Index: Psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep, 34(5), 601-608. https://doi.org/10.1093/sleep/34.5.601 Rowlands, A. V. (2007). Accelerometer assessment of physical activity in children: An update. Pediatric Exercise Science, 19(3), 252-266. https://doi.org/10.1177/0013164497057002014