Walking steps and patterns of the Chinese adult population: A year-round study

Yan, Hai

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https://hdl.handle.net/2142/124544 Copy

Description

Title

Walking steps and patterns of the Chinese adult population: A year-round study

Author(s)

Yan, Hai

Issue Date

2024-04-26

Director of Research (if dissertation) or Advisor (if thesis)

Zhu, Weimo

Doctoral Committee Chair(s)

Sydnor, Synthia

Committee Member(s)

• Chiu, Chung-Yi
• Zhang, Guanqun

Department of Study

Kinesiology & Community Health

Discipline

Kinesiology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Walking
• Steps
• Accelerometer
• Chinese

Abstract

Walking has emerged as the predominant physical activity (PA) among adults, proving to be an effective strategy for enhancing PA levels, particularly in sedentary populations. Its association with reduced risks of obesity, cardiovascular diseases, cancer, stroke, and other chronic ailments underscores its significance in promoting overall health. Despite its proven benefits, as China undergoes rapid modernization, the nation grapples with escalating rates of obesity and chronic diseases, necessitating a comprehensive understanding of walking behaviors among its populace. This study aimed to address this knowledge gap by analyzing accelerometer data collected from Chinese individuals throughout 2018, supplemented with demographic information. The original data with year-round information (N = 100,000) was obtained from the database of Shenzhen Lifesense Medical Electronics Company and 5,000 participants were randomly selected. Children and adolescents were excluded from the data as their walking behaviors were not quite the same as those of adults and were less reliable. Wear time criterion of at least 10 hours per day for a minimum of 4 days, including at least one weekend day was applied. As a result, data of 4,959 individuals remained and was included in this study. A total of 3,191 participants were males and 1,768 were females, with an average age of 45.64 yr. (SD = 12.49 yr.). Findings revealed that the average daily step counts for the Chinese population in 2018 based on the year-round data was 13,641 ± 3,611, with males averaging 13,743 ± 3,664 steps per day and females 13,455 ± 3,505 steps per day. While assessing adherence to the widely recommended 10,000 steps per day recommendation, it was demonstrated that 86.13% of participants met this benchmark. The risk of cardiovascular and metabolic diseases measured by waist-to-height ratio (WHtR) was not associated with the average number of steps walked per day, and there was no significant difference in the number of steps walked between people at high risk of cardiovascular and metabolic diseases and healthy people (t = 1.45, p < .05, Cohen’s d = 0.02). Gender disparities in average daily step counts, the daily (i.e., the diurnal patterns in PA), weekly (workday vs. weekend), monthly (beginning vs. middle vs. end of the month) and seasonal active groups were not evident. Although results from statistical test indicated that males walked more than females in general (t = 2.69, p < .05, Cohen’s d = 0.08), and they were more active in the morning (t = 5.46, p < 0.05) and on workdays (t = 2.45, p < 0.05) while less active in the evening (t = -2.42, p < 0.05) and on weekends (t = -3.24, p < 0.05) compared to females, evaluation on effect size (ES) suggested that the observed statistical significance was most likely attributable to the substantial sample size. On the other hand, daily and weekly active groups exhibited distinct patterns across age groups. Older individuals tended to engage in more PA during the morning hours while reducing their activity levels in the evening, χ2 (21, 4,958) = 401.46, p = 0.00., Cohen’s ω = 5.70. As age groups increased from 20-29 yr. to 80-89 yr., the percentage of morning active group increased from 11.45% to 66.67% and the percentage of evening active group decreased from 5.31% to 0, while the percentage of workday active group increased from 59.18% to 72.22% and the percentage of weekend active group decreased from 40.82% to 27.78%. Accumulated steps in the morning and on workdays and weekends were associated with higher step counts (r = 0.70, 0.995, 0.968, respectively). No temporal variations in walking behavior were observed in monthly and seasonal active periods. These findings highlight the potential of accelerometer data in understanding walking patterns and offering personalized PA recommendations. By utilizing accelerometer data and data mining techniques, future research can revolutionize PA analysis, leading to more tailored interventions and improved public health policies and urban planning strategies to promote PA and mitigate the burden of chronic diseases.

Graduation Semester

2024-05

Type of Resource

Thesis

Copyright and License Information

Copyright 2024 Hai Yan

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