Abstract
Background/Objectives
Whether variation in sleep and physical activity explain marked ethnic and socioeconomic disparities in childhood obesity is unclear. As time spent in one behaviour influences time spent in other behaviours across the 24-hour day, compositional analyses are essential. The aims of this study were to determine how ethnicity and socioeconomic status influence compositional time use in children, and whether differences in compositional time use explain variation in body mass index (BMI) z-score and obesity prevalence across ethnic groups.
Methods
In all, 690 children (58% European, 20% Māori, 13% Pacific, 9% Asian; 66% low-medium deprivation and 34% high deprivation) aged 6–10 years wore an ActiGraph accelerometer 24-hours a day for 5 days yielding data on sedentary time, sleep, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Height and weight were measured using standard techniques and BMI z-scores calculated. Twenty-four hour movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes were back-transformed.
Results
European children spent more time asleep (predicted difference in minutes, 95% CI: 16.1, 7.4–24.9) and in MVPA (6.6 min, 2.4–10.4), and less time sedentary (−10.2 min, −19.8 to −0.6) and in LPA (−12.2 min, −21.0 to −3.5) than non-European children. Overall, 10% more sleep was associated with a larger difference in BMI z-score (adjusted difference, 95% CI: −0.13, −0.25 to −0.01) than 10% more MVPA (−0.06, −0.09 to −0.03). Compositional time use explained 35% of the increased risk of obesity in Pacific compared with European children after adjustment for age, sex, deprivation and diet, but only 9% in Māori and 24% in Asian children.
Conclusions
Ethnic differences in compositional time use explain a relatively small proportion of the ethnic differences in obesity prevalence that exist in children.
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References
Chung A, Backholer K, Wong E, Palermo C, Keating C, Peeters A. Trends in childhood and adolescent obesity prevalence in economically advanced countries according to socioeconomic position: a systematic review. Obes Rev. 2016;173:276–95.
NCD Risk Factor Collaboration (NCD-Risk). Worldwide trends in body-mass index, underweight, overweight and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adoelscents, and adults. Lancet. 2017; 390: 2627–42.
Ministry of Health. New Zealand Health Survey. Annual Data Explorer. Wellington, New Zealand: Ministry of Health; 2017.
Salmond CE, Crampton P. Development of New Zealand’s deprivation index (NZDep) and its uptake as a national policy tool. Can J Public Health. 2012;103(8 Suppl 2):S7–S11.
Zilanawala A, Davis-Kean P, Nazroo J, Sacker A, Simonton S, Kelly Y. Race/ethnic disparities in early childhood BMI, obesity and overweight in the United Kingdom and United States. Int J Obes. 2015;39:520–9.
Marmot M. Social determinants of health inequality. Lancet. 2005;365:1099–104.
Adler NE, Cutler DM, Fielding JE, Galea S, Glymour MM, Koh HK, et al. Addressing social determinants of health and health disparities. A vital direction for health and health care. Washington, DC: National Academy of Medicine; 2016.
Carter PJ, Taylor BJ, Williams SM, Taylor RW. A longitudinal analysis of sleep in relation to BMI and body fat in children: the FLAME study. Brit Med J. 2011;342:d2717.
Fatima Y, Doi SAR, Mamun AA. Longitudinal impact of sleep on overweight and obesity in children and adolescents: a systematic review and bias-adjusted meta-analysis. Obes Rev. 2015;16:137–49.
Saunders TJ, Gray CE, Poitras VJ, Chaput J-P, Janssen I, Katzmarzyk PT, et al. Combinations of physical activity, sedentary behaviour and sleep: relationships with health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41(Suppl 3):S283–S293.
Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RF, MB W, et al. Correlates of physical activity; what are some people physically active and others not? Lancet. 2012;380:258–71.
Dixon B, Pena M-M, Taveras EM. Lifecourse approach to racial/ethnic disparities in childhood obesity. Adv Nutr. 2012;3:73–82.
Knutson KL. Sociodemographic and cultural determinants of sleep deficiency: implications for cardiometabolic disease risk. Soc Sci Med. 2013;79:7–15.
Cameron AJ, Spence AC, Laws R, Hesketh JD, Lioret S, Campbell KJ. A review of the relationship between socioeconomic position and the early-life predictors of obesity. Curr Obes Rep. 2015;4:650–362.
Chaput J-P, Saunders TJ, Carson V. Interactions between sleep, movement and other non- movement behaviours in the pathogenesis of childhood obesity. Obes Rev. 2017;18(Suppl 1):7–14.
Williams SM, Taylor BJ, Taylor RW. Do more active children sleep more? A repeated cross-sectional analysis using accelerometry. PLoS ONE. 2014. https://doi.org/10.1371/journal.pone.0093117.
Dumuid D, Stanford TE, Martin-Fernandez J-A, Pedisic Z, Maher CA, Lewis LK, et al. Compositional data analysis for physical activity, sedentary time and sleep research. Stat Meth Med Res. 2017. https://doi.org/10.1177/09062280217710835.
Pedisic Z, Dumind D, Olds TS. Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology. 2017;49:252–69.
Farmer VL, Williams SM, Mann JI, Schofield G, McPhee JC, Taylor RW. The effect of increasing risk and challenge in the school playground on physical activity and weight in children: a cluster randomised controlled trial (PLAY). Int J Obes. 2017;41:793–800.
Didham R, Callister P. The effect of ethnic prioritisation on ethnic health analysis: a research note. N Z Med J. 2012;125:59–66.
Salmond C, Crampton P, Atkinson J. NZDep2006 Index of Deprivation. Wellington, NZ: Department of Public Health, University of Otago; 2007.
de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85:660–7.
Meredith-Jones K, Williams SM, Galland BC, Kennedy G, Taylor RW. 24h accelerometry: Impact of sleep-screening methods on estimates of physical activity and sedentary time. J Sport Sci. 2016;34:679–85.
Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26:1557–65.
Magarey A, Golley R, Spurrier N, Goodwin E, Ong F. Reliability and validity of the Children’s Dietary Questionnaire: a new tool to measure children’s dietary patterns. Int J Pediatr Obes. 2009. https://doi.org/10.1080/17477160902846161.
Buis ML. FMLOGIT: Stata module fitting a fractional multinomial logit model by quasi maximum likelihood. Boston College Department of Economics; Boston, MA, 2008.
Martin-Fernandez J-A, Daunis-i-Estadella K, Mateu-Figueras G. On the interpretation of differences between groups for compositional data. SORT Stat Oper Res Trans. 2015;39:231–520.
Chastain SF, Palarea-Albaladejo J, Dontje ML, Skelton DA. Combined effects of time spent in physical activity, sedentary be- haviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach. PLoS ONE. 2015;10:e0139984.
Jann B, Zurich ETH. The Blinder-Oaxaca decomposition for linear regression models. Stata J. 2008;8:453–79.
Vaipuna TFW, Williams SM, Farmer V, Meredith-Jones K, Richards R, Galland BC, et al. Sleep patterns in children differ by ethnicity: cross-sectional and longitudinal analyses. Sleep Health. 2018;4:81–6.
Collings PJ, Brage S, Bingham DD, Costa S, West J, McEachan RRC, et al. Physical activity, sedentary time, and fatness in a biethnic sample of young children. Med Sci Sport Exerc. 2017;49:930–8.
Sardinha LS, Marques A, Minderico C, Ekelund U. Cross-sectional and prospective impact of reallocating sedentary time to physical activity on children’s body composition. Pediatr Obes. 2016;12:373–9.
del Pozo-Cruz B, Gant N, del Pozo-Cruz J, Maddison R. Relationships between sleep duration, physical activity and body mass index in young New Zealanders; an isotemporal substitution analysis. PLoS ONE. 2017;12:e0184472.
Carson V, Tremblay MS, Chaput JP, Chastin SFM. Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses. Appl Phyiol Nutr Metab. 2017;41:S294–S302.
Fairclough SJ, Dumuid D, Taylor S, Curry W, McGrane B, Stratton G, et al. Fitness, fatness and the reallocation of time between children’s daily movement behaviours: an analysis of compositional data. Int J Behav Nutr Phys Act. 2017;14:64.
Garcia-Hemoso A, Saavedra JM, Ramires-Velez R, Ekelund U, del Pozo-Cruz B. Reallocating sedentary time to moderate-to-vigorous physical activity but not to light-intensity physical activity to reduce adiposity among youths: a systematic review and meta-analysis. Obes Rev. 2017;18:1088–95.
Dumuid D, Stanford TE, Pedisic Z, Maher C, Lewis LK, Martin-Fernandez J-A, et al. Adiposity and the isotemporal subsitution of physical activity, sedentary time and sleep among school-aged children: a compositional data analysis approach. BMC Public Health. 2018;18:311.
Carson V, Tremblay MS, Chastin SFM. Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses. BMC Public Health. 2017;17 (Suppl 5):848.
Dumuid D, Pedišić Z, Stanford TE, Martin-Fernandez J-A, Hron K, Maher C, et al. The Compositional Isotemporal Substitution Model: a method for estimating changes in a health outcome for reallocation of time between sleep, physical activity and sedentary behaviour. Stat Methods Med Res. 2017;28:846–57.
Rossen LM. Neighbourhood economic deprivation explains racial/ethnic disparities in overweight and obesity among children and adolescents in the USA. J Epidemiol Commun Health. 2014;68:123–9.
Rush EC, Scragg R, Schaaf D, Juranovich G, Plank LD. Indices of fatness and relationships with age, ethnicity and lipids in New Zealand European, Māori and Pacific children. Eur J Clin Nutr. 2009;63:627–33.
Duncan JS, Duncan EK, Schofield G. Ethnic-specific body mass index cut-off points for overweight and obesity in girls. N Z Med J. 2009;123:22–9.
Tyrrell VJ, Richards GE, Hofman P, Gillies GF, Robinson E, Cutfield WS. Obesity in Auckland schoolchildren: a comparison of the body mass index and percentage body fat as the diagnostic criterion. Int J Obes. 2001;25:164–9.
Duncan JS, Duncan EK, Schofield G. Accuracy of body mass index (BMI) thresholds for predicting excess body fat in girls from five ethnicities. Asia Pacif J Clin Nutr. 2009;18:404–11.
Acknowledgements
The PLAY Study was funded by the Health Research Council of New Zealand, and the Otago Diabetes Research Trust. VLF was in receipt of a Medicine Award and subsequently a Lottery Health Research New Zealand PhD Scholarship during her PhD study. RWT is partially funded by a Fellowship from the Karitane Products Society (KPS) Limited. The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; or the decision to submit the article for publication.
Funding
The PLAY Study was funded by the Health Research Council of New Zealand, and the Otago Diabetes Research Trust. VLF was in receipt of a Medicine Award and subsequently a Lottery Health Research New Zealand PhD Scholarship during her PhD study. RWT is partially funded by a Fellowship from the Karitane Products Society (KPS) Limited.
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Trial registration: Australia New Zealand Clinical Trial registry ID: ACTRN12612000675820.
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Taylor, R.W., Haszard, J.J., Farmer, V.L. et al. Do differences in compositional time use explain ethnic variation in the prevalence of obesity in children? Analyses using 24-hour accelerometry. Int J Obes 44, 94–103 (2020). https://doi.org/10.1038/s41366-019-0377-1
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DOI: https://doi.org/10.1038/s41366-019-0377-1