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Gepubliceerd in: Quality of Life Research 1/2022

03-06-2021

Association between 24-hour movement behaviors and health-related quality of life in children

Auteurs: Xiuqin Xiong, Kim Dalziel, Natalie Carvalho, Rongbin Xu, Li Huang

Gepubliceerd in: Quality of Life Research | Uitgave 1/2022

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Abstract

Purpose

To assess the associations between adherence to 24-hour movement behaviors guidelines and child general health and functional status measured by health-related quality of life.

Methods

The Longitudinal Study of Australian Children (2004–2016) a nationally representative sample with data available for children aged 2–15 years was used. Physical activity time, recreational screen time, and sleep time were calculated from time use diaries and classified as ‘meeting guidelines’ or ‘not’ based on the age-specific 24-h movement guidelines. Child general health and functional status were measured using the multidimensional Pediatric Quality of Life Inventory (PedsQL). Associations between meeting guidelines and PedsQL were assessed using linear mixed effects models.

Results

8919 children were included. Each additional guideline met was associated with a 0.52 (95% confidence interval [CI] 0.39–0.65) increase in PedsQL total score. Compared with meeting no guidelines, the effect of meeting physical activity guidelines alone (β = 0.93, 95% CI 0.42–1.44) was larger compared to meeting screen (β = 0.66, 95% CI 0.06–1.27) or sleep time (β = 0.47, 95% CI 0.04–0.89) guidelines alone. The highest increment was observed in meeting both screen time and physical activity guidelines (β = 1.89, 95% CI 1.36–2.43). Associations were stronger in children from lower-income families (β for meeting all versus none = 2.88, 95% CI 1.77–3.99) and children aged 14–15 years (β = 4.44, 95% CI 2.49–6.40).

Conclusions

The integration of screen time and physical activity guidelines is associated with the highest PedsQL improvement. The association between guidelines adherence and PedsQL appears stronger for adolescents and those from low-income families.
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Literatuur
1.
go back to reference Tremblay, M. S., et al. (2012). Canadian sedentary behaviour guidelines for the early years (aged 0–4 years). Applied Physiology, Nutrition and Metabolism, 37(2), 370–391.CrossRef Tremblay, M. S., et al. (2012). Canadian sedentary behaviour guidelines for the early years (aged 0–4 years). Applied Physiology, Nutrition and Metabolism, 37(2), 370–391.CrossRef
2.
go back to reference Tremblay, M. S., et al. (2012). Canadian physical activity guidelines for the early years (aged 0–4 years). Applied Physiology, Nutrition, and Metabolism, 37(2), 345–356.PubMedCrossRef Tremblay, M. S., et al. (2012). Canadian physical activity guidelines for the early years (aged 0–4 years). Applied Physiology, Nutrition, and Metabolism, 37(2), 345–356.PubMedCrossRef
3.
go back to reference Health, U. D. O. (2011). Start active, stay active: a report on physical activity for health from the four home countries’ chief medical officers. Crown Copyright London. Health, U. D. O. (2011). Start active, stay active: a report on physical activity for health from the four home countries’ chief medical officers. Crown Copyright London.
4.
go back to reference Australian Government Department of Health. (2010). Move and play every day national physical activity recommendations for children 0–5 years. Australian Government, Department of Health.  Australian Government Department of Health. (2010). Move and play every day national physical activity recommendations for children 0–5 years. Australian Government, Department of Health.
5.
go back to reference Marker, A. M., Steele, R. G., & Noser, A. E. (2018). Physical activity and health-related quality of life in children and adolescents: A systematic review and meta-analysis. Health Psychology, 37(10), 893–903.PubMedCrossRef Marker, A. M., Steele, R. G., & Noser, A. E. (2018). Physical activity and health-related quality of life in children and adolescents: A systematic review and meta-analysis. Health Psychology, 37(10), 893–903.PubMedCrossRef
6.
go back to reference Poitras, V. J., et al. (2016). Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Applied Physiology, Nutrition, and Metabolism, 41(6), S197–S239.PubMedCrossRef Poitras, V. J., et al. (2016). Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Applied Physiology, Nutrition, and Metabolism, 41(6), S197–S239.PubMedCrossRef
7.
go back to reference Lubans, D., et al. (2016). Physical activity for cognitive and mental health in youth: A systematic review of mechanisms. Pediatrics, 138(3). Lubans, D., et al. (2016). Physical activity for cognitive and mental health in youth: A systematic review of mechanisms. Pediatrics, 138(3).
8.
go back to reference Lissak, G. (2018). Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environmental Research, 164, 149–157.PubMedCrossRef Lissak, G. (2018). Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environmental Research, 164, 149–157.PubMedCrossRef
9.
go back to reference Stiglic, N., & Viner, R. M. (2019). Effects of screentime on the health and well-being of children and adolescents: A systematic review of reviews. British Medical Journal Open, 9(1), e023191. Stiglic, N., & Viner, R. M. (2019). Effects of screentime on the health and well-being of children and adolescents: A systematic review of reviews. British Medical Journal Open, 9(1), e023191.
10.
go back to reference Chaput, J. P., et al. (2016). Systematic review of the relationships between sleep duration and health indicators in school-aged children and youth. Applied Physiology, Nutrition and Metabolism, 41(6 Suppl 3), S266–S282.CrossRef Chaput, J. P., et al. (2016). Systematic review of the relationships between sleep duration and health indicators in school-aged children and youth. Applied Physiology, Nutrition and Metabolism, 41(6 Suppl 3), S266–S282.CrossRef
11.
go back to reference Chaput, J. P., et al. (2017). Systematic review of the relationships between sleep duration and health indicators in the early years (0–4 years). BMC Public Health, 17(Suppl 5), 855.PubMedPubMedCentralCrossRef Chaput, J. P., et al. (2017). Systematic review of the relationships between sleep duration and health indicators in the early years (0–4 years). BMC Public Health, 17(Suppl 5), 855.PubMedPubMedCentralCrossRef
12.
go back to reference Tremblay, M. S., et al. (2016). Canadian 24-hour movement guidelines for children and youth: An integration of physical activity, sedentary behaviour, and sleep. Applied Physiology, Nutrition and Metabolism, 41(6 Suppl 3), S311–S327.CrossRef Tremblay, M. S., et al. (2016). Canadian 24-hour movement guidelines for children and youth: An integration of physical activity, sedentary behaviour, and sleep. Applied Physiology, Nutrition and Metabolism, 41(6 Suppl 3), S311–S327.CrossRef
13.
go back to reference Tremblay, M. S. (2020). Introducing 24-hour movement guidelines for the early years: A new paradigm gaining momentum. Journal of Physical Activity & Health, 17(1), 92–95.CrossRef Tremblay, M. S. (2020). Introducing 24-hour movement guidelines for the early years: A new paradigm gaining momentum. Journal of Physical Activity & Health, 17(1), 92–95.CrossRef
14.
go back to reference Lang, C., et al. (2016). The relationship between physical activity and sleep from mid adolescence to early adulthood. A systematic review of methodological approaches and meta-analysis. Sleep Medicine Reviews, 28, 32–45.PubMedCrossRef Lang, C., et al. (2016). The relationship between physical activity and sleep from mid adolescence to early adulthood. A systematic review of methodological approaches and meta-analysis. Sleep Medicine Reviews, 28, 32–45.PubMedCrossRef
15.
go back to reference Park, S. (2014). Associations of physical activity with sleep satisfaction, perceived stress, and problematic Internet use in Korean adolescents. BMC Public Health, 14(1), 1143.PubMedPubMedCentralCrossRef Park, S. (2014). Associations of physical activity with sleep satisfaction, perceived stress, and problematic Internet use in Korean adolescents. BMC Public Health, 14(1), 1143.PubMedPubMedCentralCrossRef
16.
go back to reference Magee, C. A., Lee, J. K., & Vella, S. A. (2014). Bidirectional relationships between sleep duration and screen time in early childhood. JAMA Pediatrics, 168(5), 465–470.PubMedCrossRef Magee, C. A., Lee, J. K., & Vella, S. A. (2014). Bidirectional relationships between sleep duration and screen time in early childhood. JAMA Pediatrics, 168(5), 465–470.PubMedCrossRef
17.
go back to reference Varni, J. W., et al. (2003). The PedsQLTM* 4.0 as a pediatric population health measure: Feasibility, reliability, and validity. Ambulatory Pediatrics, 3(6), 329–341.PubMedCrossRef Varni, J. W., et al. (2003). The PedsQLTM* 4.0 as a pediatric population health measure: Feasibility, reliability, and validity. Ambulatory Pediatrics, 3(6), 329–341.PubMedCrossRef
18.
go back to reference Fayers, P. M., & Machin, D. (2013). Quality of life: The assessment, analysis and interpretation of patient-reported outcomes. Wiley. Fayers, P. M., & Machin, D. (2013). Quality of life: The assessment, analysis and interpretation of patient-reported outcomes. Wiley.
19.
go back to reference Guyatt, G. H., Feeny, D. H., & Patrick, D. L. (1993). Measuring health-related quality of life. Annals of Internal Medicine, 118(8), 622–629.PubMedCrossRef Guyatt, G. H., Feeny, D. H., & Patrick, D. L. (1993). Measuring health-related quality of life. Annals of Internal Medicine, 118(8), 622–629.PubMedCrossRef
20.
go back to reference Dolan, P. (2000). The measurement of health-related quality of life for use in resource allocation decisions in health care. Handbook of health economics, 1, 1723–1760.CrossRef Dolan, P. (2000). The measurement of health-related quality of life for use in resource allocation decisions in health care. Handbook of health economics, 1, 1723–1760.CrossRef
21.
go back to reference Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA, 273(1), 59–65.PubMedCrossRef Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA, 273(1), 59–65.PubMedCrossRef
22.
go back to reference Didsbury, M. S., et al. (2016). Socio-economic status and quality of life in children with chronic disease: A systematic review. Journal of Paediatrics and Child Health, 52(12), 1062–1069.PubMedCrossRef Didsbury, M. S., et al. (2016). Socio-economic status and quality of life in children with chronic disease: A systematic review. Journal of Paediatrics and Child Health, 52(12), 1062–1069.PubMedCrossRef
23.
go back to reference Mohler-Kuo, M., & Dey, M. (2012). A comparison of health-related quality of life between children with versus without special health care needs, and children requiring versus not requiring psychiatric services. Quality of Life Research, 21(9), 1577–1586.PubMedCrossRef Mohler-Kuo, M., & Dey, M. (2012). A comparison of health-related quality of life between children with versus without special health care needs, and children requiring versus not requiring psychiatric services. Quality of Life Research, 21(9), 1577–1586.PubMedCrossRef
24.
go back to reference Stalsberg, R., & Pedersen, A. V. (2010). Effects of socioeconomic status on the physical activity in adolescents: A systematic review of the evidence. Scandinavian Journal of Medicine & Science in Sports, 20(3), 368–383.CrossRef Stalsberg, R., & Pedersen, A. V. (2010). Effects of socioeconomic status on the physical activity in adolescents: A systematic review of the evidence. Scandinavian Journal of Medicine & Science in Sports, 20(3), 368–383.CrossRef
25.
go back to reference Welk, G. J., Wood, K., & Morss, G. (2003). Parental influences on physical activity in children: An exploration of potential mechanisms. Pediatric exercise science, 15(1), 19–33.CrossRef Welk, G. J., Wood, K., & Morss, G. (2003). Parental influences on physical activity in children: An exploration of potential mechanisms. Pediatric exercise science, 15(1), 19–33.CrossRef
26.
go back to reference Cleland, V., et al. (2011). A longitudinal study of the family physical activity environment and physical activity among youth. SAGE Publications.CrossRef Cleland, V., et al. (2011). A longitudinal study of the family physical activity environment and physical activity among youth. SAGE Publications.CrossRef
27.
go back to reference Xiao, Q., et al. (2020). Sleep characteristics and health-related quality of life in 9- to 11-year-old children from 12 countries. Sleep Health, 6(1), 4–14.PubMedCrossRef Xiao, Q., et al. (2020). Sleep characteristics and health-related quality of life in 9- to 11-year-old children from 12 countries. Sleep Health, 6(1), 4–14.PubMedCrossRef
28.
go back to reference Lacy, K. E., et al. (2012). Screen time and physical activity behaviours are associated with health-related quality of life in Australian adolescents. Quality of Life Research, 21(6), 1085–1099.PubMedCrossRef Lacy, K. E., et al. (2012). Screen time and physical activity behaviours are associated with health-related quality of life in Australian adolescents. Quality of Life Research, 21(6), 1085–1099.PubMedCrossRef
29.
go back to reference Motamed-Gorji, N., et al. (2019). Association of screen time and physical activity with health-related quality of life in Iranian children and adolescents. Health and Quality of Life Outcomes, 17(1), 2.PubMedPubMedCentralCrossRef Motamed-Gorji, N., et al. (2019). Association of screen time and physical activity with health-related quality of life in Iranian children and adolescents. Health and Quality of Life Outcomes, 17(1), 2.PubMedPubMedCentralCrossRef
30.
go back to reference Sampasa-Kanyinga, H., et al. (2017). Associations between meeting combinations of 24-h movement guidelines and health-related quality of life in children from 12 countries. Public Health, 153, 16–24.PubMedCrossRef Sampasa-Kanyinga, H., et al. (2017). Associations between meeting combinations of 24-h movement guidelines and health-related quality of life in children from 12 countries. Public Health, 153, 16–24.PubMedCrossRef
31.
go back to reference Hinkley, T., et al. (2020). Prospective associations with physiological, psychosocial and educational outcomes of meeting Australian 24-Hour Movement Guidelines for the Early Years. International Journal of Behavioral Nutrition and Physical Activity, 17(1), 36.CrossRef Hinkley, T., et al. (2020). Prospective associations with physiological, psychosocial and educational outcomes of meeting Australian 24-Hour Movement Guidelines for the Early Years. International Journal of Behavioral Nutrition and Physical Activity, 17(1), 36.CrossRef
32.
go back to reference Boase, J., & Ling, R. (2013). Measuring mobile phone use: Self-report versus log data. Journal of Computer-Mediated Communication, 18(4), 508–519.CrossRef Boase, J., & Ling, R. (2013). Measuring mobile phone use: Self-report versus log data. Journal of Computer-Mediated Communication, 18(4), 508–519.CrossRef
33.
go back to reference Fisher, R. J. (1993). Social desirability bias and the validity of indirect questioning. Journal of consumer research, 20(2), 303–315.CrossRef Fisher, R. J. (1993). Social desirability bias and the validity of indirect questioning. Journal of consumer research, 20(2), 303–315.CrossRef
34.
go back to reference Soloff, C., Lawrence, D., & Johnstone, R. (2005). LSAC sample design (Technical Paper No. 1). Australian Institute of Family Studies. Soloff, C., Lawrence, D., & Johnstone, R. (2005). LSAC sample design (Technical Paper No. 1). Australian Institute of Family Studies.
35.
go back to reference Baxter, J. (2007). Children’s time use in the longitudinal study of Australian children: Data quality and analytical issues in the 4-year cohort. Australian Institute of Family Studies. Baxter, J. (2007). Children’s time use in the longitudinal study of Australian children: Data quality and analytical issues in the 4-year cohort. Australian Institute of Family Studies.
36.
go back to reference Tang, F. (2017). Random forest missing data approaches. University of Miami. Tang, F. (2017). Random forest missing data approaches. University of Miami.
38.
go back to reference Liu, J., et al. (2015). Association among number, order and type of siblings and adolescent mental health at age 12. Pediatrics International, 57(5), 849–855.PubMedCrossRef Liu, J., et al. (2015). Association among number, order and type of siblings and adolescent mental health at age 12. Pediatrics International, 57(5), 849–855.PubMedCrossRef
39.
go back to reference Sanders, T., et al. (2019). Type of screen time moderates effects on outcomes in 4013 children: Evidence from the longitudinal study of Australian children. International Journal of Behavioral Nutrition and Physical Activity, 16(1), 117.CrossRef Sanders, T., et al. (2019). Type of screen time moderates effects on outcomes in 4013 children: Evidence from the longitudinal study of Australian children. International Journal of Behavioral Nutrition and Physical Activity, 16(1), 117.CrossRef
40.
go back to reference Spurrier, N. J., et al. (2003). Socio-economic differentials in the health-related quality of life of Australian children: Results of a national study. Australian and New Zealand Journal of Public Health, 27(1), 27–33.PubMedCrossRef Spurrier, N. J., et al. (2003). Socio-economic differentials in the health-related quality of life of Australian children: Results of a national study. Australian and New Zealand Journal of Public Health, 27(1), 27–33.PubMedCrossRef
41.
go back to reference Huang, L., Freed, G. L., & Dalziel, K. (2020). Children with special health care needs: How special are their health care needs? Academic Pediatrics. Huang, L., Freed, G. L., & Dalziel, K. (2020). Children with special health care needs: How special are their health care needs? Academic Pediatrics.
42.
go back to reference Fitzmaurice, G. M., & Ravichandran, C. (2008). A primer in longitudinal data analysis. Circulation, 118(19), 2005–2010.PubMedCrossRef Fitzmaurice, G. M., & Ravichandran, C. (2008). A primer in longitudinal data analysis. Circulation, 118(19), 2005–2010.PubMedCrossRef
43.
go back to reference Humphrey, S. E., & LeBreton, J. M. (2019). The handbook of multilevel theory, measurement, and analysis. American Psychological Association.CrossRef Humphrey, S. E., & LeBreton, J. M. (2019). The handbook of multilevel theory, measurement, and analysis. American Psychological Association.CrossRef
44.
go back to reference Bell, A., & Jones, K. (2015). Explaining fixed effects: Random effects modeling of time-series cross-sectional and panel data. Political Science Research and Methods, 3(1), 133–153.CrossRef Bell, A., & Jones, K. (2015). Explaining fixed effects: Random effects modeling of time-series cross-sectional and panel data. Political Science Research and Methods, 3(1), 133–153.CrossRef
45.
go back to reference Torres-Reyna, O. (2007). Panel data analysis fixed and random effects using Stata (v. 4.2). Data & statistical services (Vol. 112). Priceton University. Torres-Reyna, O. (2007). Panel data analysis fixed and random effects using Stata (v. 4.2). Data & statistical services (Vol. 112). Priceton University.
46.
go back to reference Neuhaus, J. M., & Kalbfleisch, J. D. (1998). Between-and within-cluster covariate effects in the analysis of clustered data. Biometrics, 54(2), 638–645.PubMedCrossRef Neuhaus, J. M., & Kalbfleisch, J. D. (1998). Between-and within-cluster covariate effects in the analysis of clustered data. Biometrics, 54(2), 638–645.PubMedCrossRef
48.
go back to reference Saunders, T. J., et al. (2016). Combinations of physical activity, sedentary behaviour and sleep: Relationships with health indicators in school-aged children and youth. Applied Physiology, Nutrition and Metabolism, 41(6 Suppl 3), S283–S293.CrossRef Saunders, T. J., et al. (2016). Combinations of physical activity, sedentary behaviour and sleep: Relationships with health indicators in school-aged children and youth. Applied Physiology, Nutrition and Metabolism, 41(6 Suppl 3), S283–S293.CrossRef
49.
go back to reference Zhu, X., Haegele, J. A., & Healy, S. (2019). Movement and mental health: Behavioral correlates of anxiety and depression among children of 6–17 years old in the US. Mental Health and Physical Activity, 16, 60–65.CrossRef Zhu, X., Haegele, J. A., & Healy, S. (2019). Movement and mental health: Behavioral correlates of anxiety and depression among children of 6–17 years old in the US. Mental Health and Physical Activity, 16, 60–65.CrossRef
50.
go back to reference Harding, D.J. (1997). Measuring children's time use: A review of methodologies and findings. Center for Research on Child Wellbeing. Working paper, 97-1. Harding, D.J. (1997). Measuring children's time use: A review of methodologies and findings. Center for Research on Child Wellbeing. Working paper, 97-1.
51.
52.
go back to reference Hinkley, T., et al. (2016). Preschool and childcare center characteristics associated with children’s physical activity during care hours: An observational study. International Journal of Behavioral Nutrition and Physical Activity, 13(1), 117.CrossRef Hinkley, T., et al. (2016). Preschool and childcare center characteristics associated with children’s physical activity during care hours: An observational study. International Journal of Behavioral Nutrition and Physical Activity, 13(1), 117.CrossRef
53.
go back to reference Pedišić, Ž, & Bauman, A. (2015). Accelerometer-based measures in physical activity surveillance: Current practices and issues. British Journal of Sports Medicine, 49(4), 219.PubMedCrossRef Pedišić, Ž, & Bauman, A. (2015). Accelerometer-based measures in physical activity surveillance: Current practices and issues. British Journal of Sports Medicine, 49(4), 219.PubMedCrossRef
54.
go back to reference Osoba, D., et al. (1998). Interpreting the significance of changes in health-related quality-of-life scores. Journal of clinical oncology, 16(1), 139–144.PubMedCrossRef Osoba, D., et al. (1998). Interpreting the significance of changes in health-related quality-of-life scores. Journal of clinical oncology, 16(1), 139–144.PubMedCrossRef
Metagegevens
Titel
Association between 24-hour movement behaviors and health-related quality of life in children
Auteurs
Xiuqin Xiong
Kim Dalziel
Natalie Carvalho
Rongbin Xu
Li Huang
Publicatiedatum
03-06-2021
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 1/2022
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-021-02901-6

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