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Gepubliceerd in:

10-05-2019

Different associations of routine work time with exercise behavior and objectively measured physical activity among middle-aged and older adults: a daily and longitudinal analysis

Auteurs: Kazuhiro Harada, Kouhei Masumoto, Narihiko Kondo

Gepubliceerd in: Journal of Behavioral Medicine | Uitgave 1/2020

Abstract

This study examined whether routine work time was associated with exercise time, moderate-to-vigorous physical activity (MVPA), and step counts (SC) among middle-aged and older adults. A 7-day diary survey was conducted with 158 adults, and 138 participated in the 1-year follow-up survey for measuring routine work time and exercise time. An accelerometer was used to measure MVPA and SC, and a questionnaire assessed perceived barriers and self-efficacy. Daily analyses revealed that while longer routine work time was associated with shorter exercise time after adjusting for perceived exercise barriers and exercise self-efficacy, it was associated with higher amounts of MVPA and SC. Longitudinal analysis showed that increased routine work time was associated with decreased exercise time and increased MVPA and SC. Changes in perceived barriers and self-efficacy did not mediate these associations. Actual lack of time would inhibit exercise behavior independently of perceived barriers and self-efficacy but elevates MVPA and SC.

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Ainsworth, B. E., Haskell, W. L., Herrmann, S. D., Meckes, N., Bassett, D. R., Tudor-Locke, C., et al. (2011). 2011 Compendium of physical activities: A second update of codes and MET values. Medicine and Science in Sports and Exercise,43, 1575–1581. https://doi.org/10.1249/MSS.0b013e31821ece12 CrossRefPubMed

Angrave, D., Charlwood, A., & Wooden, M. (2015). Long working hours and physical activity. Journal of Epidemiology and Community Health,69, 738–744. https://doi.org/10.1136/jech-2014-205230 CrossRefPubMed

Bautista, L., Reininger, B., Gay, J. L., Barroso, C. S., & McCormick, J. B. (2011). Perceived barriers to exercise in Hispanic adults by level of activity. Journal of Physical Activity and Health,8, 916–925. https://doi.org/10.1111/j.1600-6143.2008.02497.x.Plasma CrossRefPubMed

Boehm, J., Franklin, R. C., Newitt, R., McFarlane, K., Grant, T., & Kurkowski, B. (2013). Barriers and motivators to exercise for older adults: A focus on those living in rural and remote areas of Australia. The Australian Journal of Rural Health,21, 141–149. https://doi.org/10.1111/ajr.12032 CrossRefPubMed

Cavallo, D. N., Brown, J. D., Tate, D. F., DeVellis, R. F., Zimmer, C., & Ammerman, A. S. (2014). The role of companionship, esteem, and informational support in explaining physical activity among young women in an online social network intervention. Journal of Behavioral Medicine,37, 955–966. https://doi.org/10.1007/s10865-013-9534-5 CrossRefPubMed

Conroy, D. E., Maher, J. P., Elavsky, S., Hyde, A. L., & Doerksen, S. E. (2013). Sedentary behavior as a daily process regulated by habits and intentions. Health Psychology,32, 1149–1157. https://doi.org/10.1037/a0031629 CrossRefPubMedPubMedCentral

Evenson, K. R., Wen, F., & Herring, A. H. (2016). Associations of accelerometry-assessed and self-reported physical activity and sedentary behavior with all-cause and cardiovascular mortality among US adults. American Journal of Epidemiology,184, 621–632. https://doi.org/10.1093/aje/kww070 CrossRefPubMedPubMedCentral

Gorman, E., Hanson, H. M., Yang, P. H., Khan, K. M., Liu-Ambrose, T., & Ashe, M. C. (2014). Accelerometry analysis of physical activity and sedentary behavior in older adults: A systematic review and data analysis. European Review of Aging and Physical Activity,11, 35–49. https://doi.org/10.1007/s11556-013-0132-x CrossRefPubMed

Gunnell, K. E., Crocker, P. R. E., Mack, D. E., Wilson, P. M., & Zumbo, B. D. (2014). Goal contents, motivation, psychological need satisfaction, well-being and physical activity: A test of self-determination theory over 6 months. Psychology of Sport and Exercise,15, 19–29. https://doi.org/10.1016/j.psychsport.2013.08.005 CrossRef

Guthold, R., Stevens, G. A., Riley, L. M., & Bull, F. C. (2018). Worldwide trends in insufficient physical activity from 2001 to 2016: A pooled analysis of 358 population-based surveys with 1·9 million participants. The Lancet Global Health,6, e1077–e1086. https://doi.org/10.1016/S2214-109X(18)30357-7 CrossRefPubMed

Harada, K., Masumoto K., & Kondo, N. (in press). Spousal concordance for objectively measured sedentary behavior and physical activity among middle-aged and older couples. Journal of Physical Activity and Health

Harada, K., Masumoto K., & Kondo, N. (2017). Gaiko-sei ga undo-sosyaru-sapoto to undo-kodo tono kan-ren ni oyobosu eikyo [Social support and exercise behavior: moderating role of extraversion]. Nihon Kenko Kyoiku Gakkaishi, 25, 258–268. https://doi.org/10.11260/kenkokyoiku.25.258 (in Japanese)

Harada, K., Masumoto K., & Kondo, N. (2018). Spousal concordance for objectively measured sedentary behavior and physical activity among middle-aged and older couples. Research Quarterly for Exercise and Sport, 89, 440–449. https://doi.org/10.1080/02701367.2018.1510171 CrossRefPubMed

Harada, K., Masumoto K., & Kondo, N. (2019). Daily and longitudinal associations of out-of-home time with objectively measured physical activity and sedentary behavior among middle-aged and older adults. Journal of Behavioral Medicine, 42, 315–329. https://doi.org/10.1007/s10865-018-9976-x CrossRefPubMed

Inoue, S., Ohya, Y., Tudor-Locke, C., Tanaka, S., Yoshiike, N., & Shimomitsu, T. (2011). Time trends for step-determined physical activity among Japanese adults. Medicine and Science in Sports and Exercise,43, 1913–1919. https://doi.org/10.1249/MSS.0b013e31821a5225 CrossRefPubMed

Ishii, K., Inoue, S., Ohya, Y., Odagiri, Y., Takamiya, T., & Shimomitsu, T. (2009a). Kani-ban undo syukan no sokusin-yoin sogai-yoin syakudo no kaihatsu [Development of a short version of the perceived benefits and barriers to exercise scale]. Tairyoku Kagaku [Japanese Journal of Physical Fitness and Sports Medicine],58, 507–516. https://doi.org/10.7600/jspfsm.58.507. (in Japanese) CrossRef

Ishii, K., Inoue, S., Ohya, Y., Odagiri, Y., Takamiya, T., Suijo, K., et al. (2009b). Sociodemographic variation in the perception of barriers to exercise among Japanese adults. Journal of Epidemiology,19, 161–168. https://doi.org/10.2188/jea.je20080094 CrossRefPubMedPubMedCentral

Japan Sports Agency, Ministry of Education, Culture, Sports, Science, and Technology. (2018). Supotsu no jisshi jokyo tou ni kansuru seron chosa [Survey on Sports and Exercise Activities] (in Japanese) Retrieved May 7, 2019 from http://www.mext.go.jp/sports/b_menu/houdou/30/02/1401750.htm

Kirk, M. A., & Rhodes, R. E. (2011). Occupation correlates of adults’ participation in leisure-time physical activity: A systematic review. American Journal of Preventive Medicine,40, 476–485. https://doi.org/10.1016/j.amepre.2010.12.015 CrossRefPubMed

Korkiakangas, E. E., Alahuhta, M. A., Husman, P. M., Keinanen-Kiukaanniemi, S., Taanila, A. M., & Laitinen, J. H. (2011). Motivators and barriers to exercise among adults with a high risk of type 2 diabetes—A qualitative study. Scandinavian Journal of Caring Sciences,25, 62–69. https://doi.org/10.1111/j.1471-6712.2010.00791.x CrossRefPubMed

Kyu, H. H., Bachman, V. F., Alexander, L. T., Mumford, J. E., Afshin, A., Estep, K., et al. (2016). Physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events: Systematic review and dose-response meta-analysis for the Global Burden of Disease Study 2013. BMJ,354, 1–10. https://doi.org/10.1136/bmj.i3857 CrossRef

Loprinzi, P. D., & Joyner, C. (2016). Accelerometer-determined physical activity and mortality in a national prospective cohort study: Considerations by visual acuity. Preventive Medicine,87, 18–21. https://doi.org/10.1016/j.ypmed.2016.02.005 CrossRefPubMed

Maher, J. P., & Conroy, D. E. (2017). Daily life satisfaction in older adults as a function of (in)activity. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences,72(4), 593–602. https://doi.org/10.1093/geronb/gbv086 CrossRefPubMed

Marcus, B. H., Rakowski, W., & Rossi, J. S. (1992a). Assessing motivational readiness and decision making for exercise. Health Psychology,11, 257–261. https://doi.org/10.1037/0278-6133.11.4.257 CrossRefPubMed

Marcus, B. H., Selby, V. C., Niaura, R. S., & Rossi, J. S. (1992b). Self-efficacy and the stages of exercise behavior change. Research Quarterly for Exercise and Sport,63, 60–66. https://doi.org/10.1080/02701367.1992.10607557 CrossRefPubMed

Murakami, H., Kawakami, R., Nakae, S., Nakata, Y., Ishikawa-Takata, K., Tanaka, S., et al. (2016). Accuracy of wearable devices for estimating total energy expenditure: Comparison with metabolic chamber and doubly labeled water method. JAMA Internal Medicine,176, 702–703. https://doi.org/10.1001/jamainternmed.2016.0152 CrossRefPubMed

Nakata, Y., Ohkawara, K., Oshima, H., & Tanaka, S. (2012). San-jiku kasokudokei “Active Style Pro” wo mochiita shintaikatsudo-hyoka ni oite “epoch length” ga kaiseki-kekka ni oyobosu eikyo [Effects of epoch length on outcome measures of physical activity with a triaxial accelerometer Active Style Pro]. Undo Ekigaku Kenkyu [Research in Exercise Epidemiology],14, 143–150. (in Japanese).

Ohkawara, K., Oshima, Y., Hikihara, Y., Ishikawa-Takata, K., Tabata, I., & Tanaka, S. (2011). Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm. The British Journal of Nutrition,105, 1681–1691. https://doi.org/10.1017/S0007114510005441 CrossRefPubMed

Oka, K. (2003). Chunensya ni okeru undo kodo no henyodankai to undo serufu-efikasi no kankei [Stages of change for exercise behavior and self-efficacy for exercise among middle-aged adults]. Nihon Kōshū Eisei Zasshi [Japanese Journal of Public Health], 50, 208–215. https://doi.org/10.11236/jph.50.3_208(in Japanese)

Oshima, Y., Kawaguchi, K., Tanaka, S., Ohkawara, K., Hikihara, Y., Ishikawa-Takata, K., et al. (2010). Classifying household and locomotive activities using a triaxial accelerometer. Gait and Posture,31, 370–374. https://doi.org/10.1016/j.gaitpost.2010.01.005 CrossRefPubMed

Physical Activity Guidelines Advisory Committee. (2018). 2018 Physical activity guidelines advisory committee scientific report. Washington, DC: U.S. Department of Health and Human Services, 2018

Rebar, A. L., Dimmock, J. A., Jackson, B., Rhodes, R. E., Kates, A., Starling, J., et al. (2016). A systematic review of the effects of non-conscious regulatory processes in physical activity. Health Psychology Review,10, 395–407. https://doi.org/10.1080/17437199.2016.1183505 CrossRefPubMed

Reichert, F. F., Barros, A. J. D., Domingues, M. R., & Hallal, P. C. (2007). The role of perceived personal barriers to engagement in leisure-time physical activity. American Journal of Public Health,97, 515–519. https://doi.org/10.2105/AJPH.2005.070144 CrossRefPubMedPubMedCentral

Reis, R. S., Salvo, D., Ogilvie, D., Lambert, E. V., Goenka, S., & Brownson, R. C. (2016). Scaling up physical activity interventions worldwide: Stepping up to larger and smarter approaches to get people moving. The Lancet,388, 1337–1348. https://doi.org/10.1016/S0140-6736(16)30728-0 CrossRef

Resnick, B., & Jenkins, L. S. (2000). Testing the reliability and validity of the self-efficacy for exercise scale. Nursing Research,49, 154–159. https://doi.org/10.1097/00006199-200005000-00007 CrossRefPubMed

Rhodes, R. E., & Quinlan, A. (2014). Predictors of physical activity change among adults using observational designs. Sports Medicine,45, 423–441. https://doi.org/10.1007/s40279-014-0275-6 CrossRef

Salmon, J., Owen, N., Bauman, A., Schmitz, M. K. K., & Booth, M. (2000). Leisure-time, occupational, and household physical activity among professional, skilled, and less-skilled workers and homemakers. Preventive Medicine,30, 191–199. https://doi.org/10.1006/pmed.1999.0619 CrossRefPubMed

Sechrist, K. R., Walker, S. N., & Pender, N. J. (1987). Development and psychometric evaluation of the exercise benefits/barriers scale. Research in Nursing and Health,10, 357–365. https://doi.org/10.1002/nur.4770100603 CrossRefPubMed

Statistics Bureau, Japanese Ministry of Internal Affairs and Communications. (2017a). Survey on time use and leisure activities. Retrieved May 7, 2019 from http://www.stat.go.jp/english/data/shakai/2016/k-gaiyou.html

Statistics Bureau, Japanese Ministry of Internal Affairs and Communications. (2017b). 2015 Population census. Retrieved May 7, 2019 from https://www.e-stat.go.jp/en/stat-search/file-download?statInfId=000031569351&fileKind=1

Tanaka, C., & Tanaka, S. (2013). San-jigen kasokudokei de hyoka suru shintaikatsudo-ryo ni okeru “epoch length” no yakuwari, oyobi himan tono kankei [Role of epoch length on daily locomotive and non-locomotive physical activity using a triaxial accelerometer and relationships with obesity in adults]. Tairyoku Kagaku [Japanese Journal of Physical Fitness and Sports Medicine],62, 71–78. https://doi.org/10.7600/jspfsm.62.71. (in Japanese) CrossRef

Tudor-Locke, C., Han, H., Aguiar, E. J., Barreira, T. V., Schuna, J. M., Kang, M., et al. (2018). How fast is fast enough? Walking cadence (steps/min) as a practical estimate of intensity in adults: A narrative review. British Journal of Sports Medicine,52, 776–788. https://doi.org/10.1136/bjsports-2017-097628 CrossRefPubMedPubMedCentral

Tudor-Locke, C., Johnson, W. D., & Katzmarzyk, P. T. (2011). Relationship between accelerometer-determined steps/day and other accelerometer outputs in US adults. Journal of Physical Activity and Health,8, 410–419. https://doi.org/10.1123/jpah.8.3.410 CrossRefPubMed

Tulloch, H., Sweet, S. N., Fortier, M., Capstick, G., Kenny, G. P., Sigal, R. J., et al. (2013). Exercise facilitators and barriers from adoption to maintenance in the diabetes aerobic and resistance exercise trial. Canadian Journal of Diabetes,37, 367–374. https://doi.org/10.1016/j.jcjd.2013.09.002 CrossRefPubMed

U.S. Department of Health and Human Services. (2018). Physical activity guidelines for American (2nd ed.). Washington, DC: U.S. Department of Health and Human Services.

Yates, T., Haffner, S. M., Schulte, P. J., Thomas, L., Huffman, K. M., Bales, C. W., et al. (2014). Association between change in daily ambulatory activity and cardiovascular events in people with impaired glucose tolerance (NAVIGATOR trial): A cohort analysis. The Lancet,383, 1059–1066. https://doi.org/10.1016/S0140-6736(13)62061-9 CrossRef

Titel: Different associations of routine work time with exercise behavior and objectively measured physical activity among middle-aged and older adults: a daily and longitudinal analysis
Auteurs: Kazuhiro Harada
Kouhei Masumoto
Narihiko Kondo
Publicatiedatum: 10-05-2019
Uitgeverij: Springer US
Gepubliceerd in: Journal of Behavioral Medicine / Uitgave 1/2020
Print ISSN: 0160-7715
Elektronisch ISSN: 1573-3521
DOI: https://doi.org/10.1007/s10865-019-00051-2

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