Movement Behavior Analysis Among Working-Age Populations Across Generations in Bangkok Metropolitan Area: A 24-Hour Time-Use Study
Keywords:
movement behavior, time use, working-age, physical activityAbstract
This study aimed to analyze differences in 24-hour movement behaviors among working-age populations across different generations in Bangkok Metropolitan Area, examined through the International Classification of Activities for Time-Use Statistics (ICATUS 2016) framework. The analysis encompassed three primary movement behavior dimensions: sleep, sedentary behavior, and physical activity. The sample consisted of 218 working-age individuals who completed time-use diaries recording activities every 10 minutes for 4 consecutive working days. Data were analyzed using descriptive statistics, one-way ANOVA, and T-test for between-group comparisons. The results revealed that sedentary behavior consumed the highest proportion of daily time, averaging 11.10 hours per day (46.2%), followed by sleep at 8.08 hours (33.8%). Moderate-to-vigorous physical activity (MVPA) averaged 0.92 hours (3.8%), which when calculated based on the 4-day observation period exceeds the daily average derived from the World Health Organization recommendations (150 minutes/week). However, it should be noted that this average reflected data collected over 4 specific recorded days rather than a full calendar week. Statistically significant intergenerational differences in behavioral patterns were observed, with Generation X exhibiting the shortest sleep duration. These disparities underscore an imbalance in daily time allocation, suggesting that health policies and interventions should be generation-specific to effectively promote sustainable health behaviors among urban workers.
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References
Liangruenrom N, Suttikasem K, Widyastari DA, Potharin D, Katewongsa P. Reliability
and validity of time-use surveys in assessing 24-hour movement behaviors in adults.
Journal of Exercise Science & Fitness 2025;23(2):133–40.
United Nations. International classification of activities for time-use statistics 2016
[Internet]. New York: United Nations Publication [Internet]. 2021 [cited 2025 Jun 14].
Available from: https://unstats.un.org/unsd/gender/timeuse/23012019%20ICATUS.pdf
สำนักงานสถิติตแห่งชาติ. การสำรวจการใช้เวลาของประชากร พ.ศ. 2558. กรุงเทพมหานคร :
สำนักงานสถิติตแห่งชาติ; 2559.
Liangruenrom N, Craike M, Dumuid D, Biddle SJH, Tudor-Locke C, Ainsworth B, et al.
Standardised criteria for classifying the International Classification of Activities for
Time-use Statistics (ICATUS) activity groups into sleep, sedentary behaviour, and
physical activity. International Journal of Behavioral Nutrition and Physical Activity
;16(1):1-10.
Liangruenrom N, Dumuid D, Pedisic Z. Physical activity, sedentary behaviour,
and sleep in the Thai population: A compositional data analysis including 135,
participants from two national time-use surveys. PLoS One 2023;18(1):1-19.
Topothai T, Tangcharoensathien V, Edney SM, Suphanchaimat R, Lekagul A,
Waleewong O, et al. Patterns and correlates of physical activity and sedentary
behavior among Bangkok residents: a cross-sectional study. PLoS One 2023;18(10):
-15.
ฐิติพัฒน์ รื่นอารมย์. ความสัมพันธ์ระหว่างการปฏิบัติตามคำแนะนำการเคลื่อนไหว 24 ชั่วโมง
และองค์ประกอบของร่างกายของนักเรียนมัธยมศึกษาตอนต้น [วิทยานิพนธ์ครุศาสตรมหาบัณฑิต].
กรุงเทพมหานคร: จุฬาลงกรณ์มหาวิทยาลัย; 2565. 144 หน้า.
กรมอนามัย. คู่มือกิจกรรมทางกายเพื่อสุขภาพ (physical activity for health) [อินเทอร์เน็ต]
นนทบุรี: กรมอนามัย; 2563 [สืบค้นเมื่อ 14 มิ.ย. 2568]. Available from:
https://multimedia.anamai.moph.go.th/ebooks/physical-activity-for-health/
World Health Organization. WHO guidelines on physical activity and sedentary
behaviour [Internet]. 2020 [cited 2025 June 14]. Available from:
https://www.who.int/publications/i/item/9789240015128
Rasmussen CL, Dumuid D, Hron K, Gupta N, Jørgensen MB, Nabe-Nielsen K, et. al.
Day-to-day pattern of work and leisure time physical behaviours: are low
socioeconomic status adults couch potatoes or work warriors?. BMC Public Health
;21(1342):1-13.
Kracht CL, Burkart S, Groves CI, Balbim GM, Pfledderer CD, Porter CD, et al. 24-hour
movement behavior adherence and associations with health outcomes: an umbrella
review. Journal of Activity, Sedentary and Sleep Behaviors 2024;3(25):1-25.
Ferguson T, Curtis R, Fraysse F, Olds T, Dumuid D, Brown W, et al. The annual
rhythms in sleep, sedentary behavior, and physical activity of australian adults:
a prospective cohort study. Annuals of Behavioral Medicine 2024;58(4):286–95.
Hakimi S, Kaur S, Ross-White A, Martin LJ, Rosenberg MW. A systematic review
examining associations between physical activity, sedentary behaviour, and sleep
duration with quality of life in older adults aged 65 years and above. Applied
Physiology, Nutrition, and Metabolism 2023;48(2):97–162.
Akksilp K, Topothai T, Pimsarn N, Chinnapanwanich P, Mungmee W, Chen C, et al.
Physical activity and sedentary behavior interventions in Thailand: a systematic
review. Journal of Physical Activity and Health 2026:1–14.
Corp I. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp; 2019.
Lee Y, Son JS, Eum YH, Kang OL. Association of sedentary time and physical activity
with the 10-year risk of cardiovascular disease: Korea National Health and Nutrition
Examination Survey 2014-2017. Korean Journal of Family Medicine 2020;41(6):
–80.
Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, et al.
Amount of time spent in sedentary behaviors in the United States, 2003-2004.
Am J Epidemiol 2008;167(7):875–81.
Thorp AA, Healy GN, Winkler E, Clark BK, Gardiner PA, Owen N, et al. Prolonged
sedentary time and physical activity in workplace and non-work contexts: a cross-
sectional study of office, customer service and call centre employees. International
Journal of Behavioral Nutrition and Physical Activity 2012;9(128):1-9.
Church TS, Thomas DM, Tudor-Locke C, Katzmarzyk PT, Earnest CP, Rodarte RQ, et al.
Trends over 5 decades in U.S. occupation-related physical activity and their
associations with obesity. PLoS One 2011;6(5):1-7.
Gremaud AL, Carr LJ, Simmering JE, Evans NJ, Cremer JF, Segre AM, et al. Gamifying
accelerometer use increases physical activity levels of sedentary office workers.
Journal of the American Heart Association 2018;7(13):1-12.
ระวีวรรณ มาพงษ์. กลยุทธ์การลดพฤติกรรมเนือยนิ่งของพนักงานออฟฟิศที่ทำงานแบบผสมผสาน
หรือทำงานไกล: กลยุทธ์สู่การนำไปใช้. วารสารวิชาการสาธารณสุข 2565;32(2):362–74.
Zderic T, Hamilton M. Physical inactivity amplifies the sensitivity of skeletal muscle
to the lipid-induced downregulation of lipoprotein lipase activity. Journal of Applied
Physiology 2006;100(1):249–57.
Parry S, Straker L. The contribution of office work to sedentary behaviour associated
risk. BMC Public Health 2013;13(296):1-10.
Chau JY, Grunseit AC, Chey T, Stamatakis E, Brown WJ, Matthews CE, et al. Daily
sitting time and all-cause mortality: a meta-analysis. PLoS One 2013;8(11):1-14.
van der Ploeg HP, Chey T, Korda RJ, Banks E, Bauman A. Sitting time and all-cause
mortality risk in 222 497 Australian adults. Arch Intern Med. 2012;172(6):494–500.
World Health Organization. WHO guidelines on physical activity and sedentary
behaviour [Internet]. 2020 [cited 2025 June 14]. Available from:
https://iris.who.int/server/api/core/bitstreams/faa83413-d89e-4be9-bb01-
b24671aef7ca/content
Diaz KM, Howard VJ, Hutto B, Colabianchi N, Vena JE, Safford MM, et al. Patterns of
sedentary behavior and mortality in U.S. middle-aged and older adults: a national
cohort study. Ann Intern Med 2017;167(7):465–75.
Ekelund U, Steene-Johannessen J, Brown WJ, Fagerland MW, Owen N, Powell KE, et al.
Does physical activity attenuate, or even eliminate, the detrimental association of
sitting time with mortality? A harmonised meta-analysis of data from more than
million men and women. Lancet 2016;388(10051):1302–10.
Mamun AA, Scott J, Najman JM, Williams GM, Alati R, Fatima Y. Generational changes
in young adults’ sleep duration: a prospective analysis of mother-offspring dyads.
Sleep Health 2020;6(2):240–5.
Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology:
conceptual models, empirical challenges and interdisciplinary perspectives.
International Journal of Epidemiology 2002;31(2):285–93.
Wilkes C. Generational Differences In Fitness: Gen Z is 10 times more likely to use
TikTok for fitness advice than baby boomers [Internet]. [Cited 2025 June 14].
Available from: https://www.garagegymreviews.com/generational-differences-in-
fitness
Clemes SA, O’Connell SE, Edwardson CL. Office workers’ objectively measured
sedentary behavior and physical activity during and outside working hours.
Journal of Occupational and Environmental Medicine 2014;56(3):298–303.
ระวีวรรณ มาพงษ์. การพัฒนาโปรแกรมการลดพฤติกรรมเนือยนิ่งในพนักงานออฟฟิศตามโครงสร้าง
ของทฤษฎีกระบวนการรับรู้ทางสังคม [วิทยานิพนธ์วิทยาศาสตรดุษฎีบัณฑิต]. กรุงเทพมหานคร :
จุฬาลงกรณ์มหาวิทยาลัย; 2563. 217 หน้า.
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