A study on prospective associations between adiposity and 7-year changes in movement behaviors among older women based on compositional data analysis
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
33757454
PubMed Central
PMC7988941
DOI
10.1186/s12877-021-02148-3
PII: 10.1186/s12877-021-02148-3
Knihovny.cz E-zdroje
- Klíčová slova
- Compositional data analysis, Exercise, Fatness, Obesity, Sitting, Time-use epidemiology,
- MeSH
- adipozita * MeSH
- akcelerometrie MeSH
- analýza dat * MeSH
- index tělesné hmotnosti MeSH
- lidé MeSH
- longitudinální studie MeSH
- prospektivní studie MeSH
- průřezové studie MeSH
- senioři MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Evropa MeSH
INTRODUCTION: It is unclear whether adiposity leads to changes in movement behaviors, and there is a lack of compositional analyses of longitudinal data which focus on these associations. Using a compositional approach, this study aimed to examine the associations between baseline adiposity and 7-year changes in physical activity (PA) and sedentary behavior (SB) among elderly women. We also explored the longitudinal associations between change in adiposity and change in movement-behavior composition. METHODS: This longitudinal study included 176 older women (mean baseline age 62.8 (4.1) years) from Central Europe. Movement behavior was assessed by accelerometers and adiposity was measured by bioelectrical impedance analysis at baseline and follow-up. A set of multivariate least-squares regression analyses was used to examine the associations of baseline adiposity and longitudinal changes in adiposity as explanatory variables with longitudinal changes in a 3-part movement-behavior composition consisting of SB, light PA (LPA) and moderate-to-vigorous PA (MVPA) as outcome variables. RESULTS: No significant associations were found between baseline adiposity and longitudinal changes in the movement-behavior composition (p > 0.05). We found significant associations of changes in body mass index (BMI) and fat mass percentage (FM%) with changes in the movement-behavior composition. An increase in BMI was associated with an increase of SB at the expense of LPA and MVPA (β = 0.042, p = 0.009) and with a decrease of MVPA in favor of SB and LPA (β = - 0.059, p = 0.037). An increase in FM% was significantly associated only with an increase of SB at the expense of LPA and MVPA (β = 0.019, p = 0.031). CONCLUSIONS: This study did not support the assumption that baseline adiposity is associated with longitudinal changes in movement behaviors among elderly women, but we found evidence for change-to-change associations, suggesting that a 7-year increase in adiposity is associated with a concurrent increase of SB at the expense of LPA and MVPA and with a concurrent decrease of MVPA in favor of LPA and SB. Public health interventions are needed to simultaneously prevent weight gain and promote physically active lifestyle among elderly women.
Faculty of Science Palacký University Olomouc Olomouc Czech Republic
Institute for Health and Sport Victoria University Melbourne Australia
School of Health and Life Science Glasgow Caledonian University Glasgow UK
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Zhu W, Cheng Z, Howard VJ, Judd SE, Blair SN, Sun Y, et al. Is adiposity associated with objectively measured physical activity and sedentary behaviors in older adults? BMC Geriatr. 2020;20(1):1–8. doi: 10.1186/s12877-019-1374-x. PubMed DOI PMC
de Rezende LFM, Rey-Lopez JP, VKR M, do Carmo Luiz O. Sedentary behavior and health outcomes among older adults: a systematic review. BMC Public Health. 2014;14:333. doi: 10.1186/1471-2458-14-333. PubMed DOI PMC
Svozilová Z, Pelclová J, Pechová J, Přidalová M, Zając-Gawlak I, Tlučáková L, et al. Associations between adiposity and physical activity and sedentary behaviour patterns in older women. Acta Gymnica. 2019;49(2):83–91. doi: 10.5507/ag.2019.006. DOI
Wanner M, Richard A, Martin B, Faeh D, Rohrmann S. Associations between self-reported and objectively measured physical activity, sedentary behavior and overweight/obesity in NHANES 2003-2006. Int J Obes. 2017;41(1):186–193. doi: 10.1038/ijo.2016.168. PubMed DOI
Hughes VA, Frontera WR, Roubenoff R, Evans WJ, Fiatarone Singh MA. Longitudinal changes in body composition in older men and women: role of body weight change and physical activity. Am J Clin Nutr. 2002;76(2):473–481. doi: 10.1093/ajcn/76.2.473. PubMed DOI
Raguso CA, Kyle U, Kossovsky MP, Roynette C, Paoloni-Giacobino A, Hans D, Genton L, Pichard C. A 3-year longitudinal study on body composition changes in the elderly: role of physical exercise. Clin Nutr. 2006;25(4):573–580. doi: 10.1016/j.clnu.2005.10.013. PubMed DOI
Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, et al. Sedentary behavior research network (SBRN)–terminology consensus project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):1–17. doi: 10.1186/s12966-017-0525-8. PubMed DOI PMC
Tucker JM, Tucker LA, Lecheminant J, Bailey B. Obesity increases risk of declining physical activity over time in women: a prospective cohort study. Obesity. 2013;21(12):715–720. doi: 10.1002/oby.20415. PubMed DOI
Pedišić Ž, Grunseit A, Ding CJY, Banks E, Stamatakis E, et al. High sitting time or obesity: which came first? Bidirectional association in a longitudinal study of 31,787 Australian adults. Obesity. 2014;22(10):2126–2130. doi: 10.1002/oby.20817. PubMed DOI PMC
Chastin SFM, Palarea-Albaladejo J, Dontje ML, Skelton DA. Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach. PLoS One. 2015;10(10):e0139984. doi: 10.1371/journal.pone.0139984. PubMed DOI PMC
Pedišić Ž. Measurement issues and poor adjustments for physical activity and sleep undermine sedentary behaviour research - the focus should shift to the balance between sleep, sedentary behaviour. Standing and Activity Kinesiology. 2014;46(1):135–146.
Pedišić Ž, Dumuid D, Olds T. 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(2):252–269. doi: 10.26582/k.49.2.14. DOI
Dumuid D, Stanford TE, Martin-Fernández JA, Pedišić Ž, Maher CA, Lewis LK, Hron K, Katzmarzyk PT, Chaput JP, Fogelholm M, Hu G, Lambert EV, Maia J, Sarmiento OL, Standage M, Barreira TV, Broyles ST, Tudor-Locke C, Tremblay MS, Olds T. Compositional data analysis for physical activity, sedentary time and sleep research. Stat Methods Med Res. 2018;27(12):3726–3738. doi: 10.1177/0962280217710835. PubMed DOI
Gupta N, Mathiassen SE, Mateu-Figueras G, Heiden M, Hallman DM, Jørgensen MB, Holtermann A. A comparison of standard and compositional data analysis in studies addressing group differences in sedentary behavior and physical activity. Int J Behav Nutr Phys Act. 2018;15(1):1–12. doi: 10.1186/s12966-018-0685-1. PubMed DOI PMC
Gába A, Pelclová J, Štefelová N, Přidalová M, Zając-Gawlak I, Tlučáková L, Pechová J, Svozilová Z. Prospective study on sedentary behaviour patterns and changes in body composition parameters in older women: a compositional and isotemporal substitution analysis. Clin Nutr. 2020. 10.1016/j.clnu.2020.10.020. PubMed
Pelclová J, Štefelová N, Dumuid D, Pedišić Ž, Hron K, Gába A, Olds T, Pechová J, Zając-Gawlak I, Tlučáková L. Are longitudinal reallocations of time between movement behaviours associated with adiposity among elderly women? A compositional isotemporal substitution analysis. Int J Obes. 2020;44(4):857–864. doi: 10.1038/s41366-019-0514-x. PubMed DOI PMC
Cuberek R, Pelclová J, Gába A, Pechová J, Svozilová Z, Přidalová M, et al. Adiposity and changes in movement-related behaviors in older adult women in the context of the built environment: a protocol for a prospective cohort study. BMC Public Health. 2019;19(1):1–7. doi: 10.1186/s12889-019-7905-8. PubMed DOI PMC
Gába A, Kapuš O, Cuberek R, Botek M. Comparison of multi- and single-frequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of body composition in post-menopausal women: effects of body mass index and accelerometer-determined physical activity. J Hum Nutr Diet. 2014;28(4):390–400. doi: 10.1111/jhn.12257. PubMed DOI
Park KS, Lee DH, Lee J, Kim YJ, Jung KY, Kim KM, Kwak SH, Choi SH, Park KS, Jang HC, Lim S. Comparison between two methods of bioelectrical impedance analyses for accuracy in measuring abdominal visceral fat area. J Diabetes Complicat. 2016;30(2):343–349. doi: 10.1016/j.jdiacomp.2015.10.014. PubMed DOI
WHO Expert Committee . Physical Status: the use and interpretation of anthropometry. WHOTechnical Report Series no. 854. Geneva: WHO; 1995. PubMed
Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000;72(3):694–701. doi: 10.1093/ajcn/72.3.694. PubMed DOI
Gorman E, Hanson HM, Yang PH, Khan KM, Liu-Ambrose T, Ashe MC. Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis. Eur Rev Aging Phys Act. 2014;11(1):35–49. doi: 10.1007/s11556-013-0132-x. PubMed DOI PMC
Freedson PS, Melanson E, Sirard J. Calibration of the computer science and applications. Inc accelerometer Med Sci Sports Exerc. 1998;30(5):777–781. doi: 10.1097/00005768-199805000-00021. PubMed DOI
R Core Team . R Foundation for Statistical computing, Vienna, Austria. 2020.
van den Boogaart GK, Tolosana R, Bren M. Package ‘compositions’. 2015.
Pawlowsky-Glahn V, Egozcue JJ, Tolosana-Delgado R. Modeling and analysis of compositional data. London: Wiley; 2015.
Dumuid D, Pedišić Ž, Palarea-Albaladejo J, Martín-Fernández JA, Hron K, Olds T. Compositional data analysis in time-use epidemiology: what, why, how. Int J Environ Res Public Health. 2020;17(7):2220. doi: 10.3390/ijerph17072220. PubMed DOI PMC
Filzmoser P, Hron K, Templ M. Applied compositional data analysis. With worked examples in R. Cham: Springer International Publishing; 2018.
Chastin SFM, Buck C, Freiberger E, Murphy M, Brug J, Cardon G, et al. Systematic literature review of determinants of sedentary behaviour in older adults: a DEDIPAC study. Int J Behav Nutr Phys Act. 2015;12(1):1–12. doi: 10.1186/s12966-015-0292-3. PubMed DOI PMC
UKK Institute for Health Promotion Research. Aikuisten liikkumisen suositus [Movement recommendations for adults]. https://ukkinstituutti.fi/liikkuminen/liikkumisen-suositukset/liikkumisen-suositus-yli-65-vuotiaille. Accessed 11 Nov 2020.
Canadian Society for Exercise Physiology. Canadian 24-Hour Movement Guidelines for Adults ages 65 years and older: An Integration of Physical Activity, Sedentary Behaviour, and Sleep https://csepguidelines.ca/adults-65. Accessed 9 Nov 2020.
Jurakić D, Pedišić Ž. Croatian 24-hour guidelines for physical activity, sedentary behaviour, and sleep: a proposal based on a systematic review of literature. Medicus. 2019;28(2):143–153.
Harvey JA, Chastin SFM, Skelton DA. How sedentary are older people? A systematic review of the amount of sedentary behavior. J Aging Phys Act. 2015;23(3):471–487. doi: 10.1123/japa.2014-0164. PubMed DOI
Clark BK, Sugiyama T, Healy GN, Salmon J, Dunstan DW, Shaw JE, Zimmet PZ, Owen N. Socio-demographic correlates of prolonged television viewing time in australian men and women: the AusDiab study. J Phys Act Health. 2010;7(5):595–601. doi: 10.1123/jpah.7.5.595. PubMed DOI
Martin KR, Koster A, Murphy RA, Van Domelen DR, Hung MY, Brychta RJ, et al. Changes in daily activity patterns with age in U.S. men and women: national health and nutrition examination survey 2003-04 and 2005-06. J Am Geriatr Soc. 2014;62(7):1263–1271. doi: 10.1111/jgs.12893. PubMed DOI PMC
Doherty A, Jackson D, Hammerla N, Plötz T, Olivier P, Granat MH, et al. Large scale population assessment of physical activity using wrist worn accelerometers: the UK biobank study. PLoS One. 2017;12(2):1–14. doi: 10.1371/journal.pone.0169649. PubMed DOI PMC
Berkemeyer K, Wijndaele K, White T, Cooper AJM, Luben R, Westgate K, et al. The descriptive epidemiology of accelerometer-measured physical activity in older adults. Sci Rep. 2016;7(5):1–10. PubMed PMC
Troiano R, Berrigan D, Dodd K, Mâsse L, Tilert T, Mcdowell M. Physical activity in the United States measured by accelerometer. Med Sci Sport Exer. 2008;40(1):181–188. doi: 10.1249/mss.0b013e31815a51b3. PubMed DOI
Grgic J, Dumuid D, Bengoechea EG, Shrestha N, Bauman A, Olds T, et al. Health outcomes associated with reallocations of time between sleep, sedentary behaviour, and physical activity: a systematic scoping review of isotemporal substitution studies. Int J Behav Nutr Phys Act. 2018;15(1):1–68. doi: 10.1186/s12966-018-0691-3. PubMed DOI PMC
Janssen I, Clarke AE, Carson V, Chaput J-P, Giangregorio LM, Kho ME, et al. A systematic review of compositional data analysis studies examining associations between sleep, sedentary behaviour, and physical activity with health outcomes in adults. Appl Physiol Nutr Metab. 2020;45(10 Suppl 2):248–257. doi: 10.1139/apnm-2020-0160. PubMed DOI
Pulsford RM, Stamatakis E, Britton AR, Brunner EJ, Hillsdon MM. Sitting behavior and obesity: evidence from the Whitehall II study. Am J Prev Med. 2013;44(2):132–138. doi: 10.1016/j.amepre.2012.10.009. PubMed DOI PMC
Cohen J. A power primer. Psychol Bull. 1992;112(1):155–159. doi: 10.1037/0033-2909.112.1.155. PubMed DOI
Garfield V, Llewellyn CH, Steptoe A, Kumari M. Investigating the bidirectional associations of adiposity with sleep duration in older adults: the English longitudinal study of ageing (ELSA) Sci Rep. 2017;7:1–8. doi: 10.1038/srep40250. PubMed DOI PMC
Winkler EA, Gardiner PA, Clark BK, Matthews CE, Owen N, Healy GN. (2012). Identifying sedentary time using automated estimates of accelerometer wear time. Br J Sports Med. 2012;46(6):436–442. doi: 10.1136/bjsm.2010.079699. PubMed DOI PMC
Chudyk AM, McAllister MM, Cheung HK, McKay HA, Ashe MC. Are we missing the sitting? Agreement between accelerometer non-wear time validation methods used with older adults’ data. Cogent medicine. 2017;4(1):1313505. doi: 10.1080/2331205X.2017.1313505. PubMed DOI PMC
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