Lin Zhou

Mr. Lin Zhou

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 June 2024 in JMIR Public Health and Surveillance
Verified
Journal Article
Open access
Wei LiangWei Liang
Wei Liang
YWYanping Wang
Yanping Wang
QHQian Huang
Qian Huang
Borui ShangBorui Shang
Borui Shang
NSNing Su
Ning Su
YDYanping Duan
Yanping Duan
Background: It is known that 24-hour movement behaviors, including physical activity (PA), sedentary behavior (SB), and sleep, are crucial components affecting older adults’ health. Canadian 24-hour movement guidelines for older adults were launched in 2020, emphasizing the combined role of these 3 movement behaviors in promoting older adults’ health. However, research on the prevalence and correlates of guideline adherence and its associations with health-related outcomes is limited, especially among Chinese older adults. Objective: This study aimed to investigate the prevalence and correlates of meeting 24-hour movement guidelines among Chinese older adults. Furthermore, this study aimed to examine the associations of guideline adherence with older adults’ physical and mental health outcomes. Methods: Using a stratified cluster random sampling approach, a total of 4562 older adults (mean age 67.68 years, SD 5.03 years; female proportion: 2544/4562, 55.8%) were recruited from the latest provincial health surveillance of Hubei China from July 25 to November 19, 2020. Measures included demographics, movement behaviors (PA, SB, and sleep), BMI, waist circumference, waist-hip ratio (WHR), percentage body fat (PBF), systolic and diastolic blood pressure, physical fitness, depressive symptoms, and loneliness. Generalized linear mixed models were employed to examine the associations between variables using SPSS 28.0 (IBM Corp). Results: Only 1.8% (83/4562) of participants met all 3 movement guidelines, while 32.1% (1466/4562), 3.4% (155/4562), and 66.4% (3031/4562) met the individual behavioral guidelines for PA, SB, and sleep, respectively. Participants who were older, were female, and lived in municipalities with lower economic levels were less likely to meet all 3 movement guidelines. Adhering to individual or combined movement guidelines was associated with greater physical fitness and lower values of BMI, waist circumference, WHR, PBF, depressive symptoms, and loneliness, with the exception of the relationship of SB+sleep guidelines with loneliness. Furthermore, only meeting SB guidelines or meeting both PA and SB guidelines was associated with lower systolic blood pressure. Conclusions: This is the first study to investigate adherence to 24-hour movement guidelines among Chinese older adults with regard to prevalence, correlates, and associations with physical and mental health outcomes. The findings emphasize the urgent need for promoting healthy movement behaviors among Chinese older adults. Future interventions to improve older adults’ physical and mental health should involve enhancing their overall movement behaviors and should consider demographic differences.

17 January 2024 in BMC Public Health
Verified
Journal Article
Open access
PDF file
Yuxiu HeYuxiu He
Yuxiu He
LZLin Zhou
Lin Zhou
WLWei Liang
Wei Liang
QLQi Liu
Qi Liu
WLWanxin Liu
Wanxin Liu
SWShijian Wang
Shijian Wang
Objective: This cross-sectional study examined the socio-ecological factors influencing fundamental motor skills (FMS) in Chinese school-aged children. Methods: A total of 1012 parent-child pairs were randomly sampled between March-1st and April-15th, 2022. Based on the socio-ecological model of Children’s FMS, three levels of factors: individual-level (e.g., demographic, physical, psychological, and behavioral characteristics of children), family-level (e.g., caregiver demographics, parental support, and socioeconomic status), and environmental factors (e.g., availability of physical activity equipment) were assessed using self-reported scales (e.g., the Self-perception Profile for Children, the Physical Activity Enjoyment Scale, and the 12-item Psychological Well-Being Scale for Children) and objective measures (e.g., ActiGraph GT3X, the Chinese National Student Physical Fitness Standard, and the Test of Gross Motor Development-Third Edition). Multi-level regression models were employed using SPSS. Results: The results demonstrated that children’s age, sex, physical fitness, parental support, and the quality of home and community physical activity environments consistently influenced all three types of FMS, including locomotor, ball, and composite skills. Additionally, seven individual-level factors (children’s age, sex, body mass index, light physical activity, sleep duration, perceived motor competence, and physical fitness) were associated with different types of FMS. Conclusions: The findings underscore the multidimensional and complex nature of FMS development, with individual-level factors playing a particularly significant role. Future research should adopt rigorous longitudinal designs, comprehensive assessment tools covering various FMS skills, and objective measurement of parents’ movement behaviors to better understand the strength and direction of the relationship between socio-ecological factors and children’s FMS.

LZLin Zhou
Lin Zhou
Wei LiangWei Liang
Wei Liang
Yuxiu HeYuxiu He
Yuxiu He
YDYanping Duan
Yanping Duan
RRRyan E Rhodes
Ryan E Rhodes
YCYingzhe Cheng
Yingzhe Cheng
24 h movement behaviors, specifically physical activity (PA), sedentary behavior, and sleep, play a crucial role in the prevention and intervention of childhood obesity. This study aimed to examine the association of 24 h movement behaviors with weight status and body composition among Chinese primary school children. Using a random stratified sampling, 978 eligible participants (9.1 ± 1.4 years, 53.2% boys) were recruited from 1 May to 15 July 2021. Demographics included children’s age, gender, grade, parents’ education level, and household income. Movement behaviors were measured by validated self-reported scales. Weight status and body composition (percent of body fat, PBF; fat-free mass, FFM; skeletal muscle mass, SMM) were measured objectively. Results indicated that participants who were younger, boys, and at lower grade showed higher guidelines adherence. PA was inversely associated with PBF, while screen time (ST) was positively associated with overweight/obesity risk and FFM. Sleep showed no association with any health indicators. Meeting the behavioral guidelines was associated with better weight status and lower PBF, yet not with FFM and SMM. Interventions to improve the Children’s weight status and PBF should involve enhancing their overall movement behaviors and considering their demographic differences. More research on examining the association of movement guidelines adherence with body composition indicators is needed.

3 June 2024 in Journal of Medical Internet Research
Verified
Journal Article
Open access
WCWenfei Cai
Wenfei Cai
Wei LiangWei Liang
Wei Liang
HLHuaxuan Liu
Huaxuan Liu
RZRundong Zhou
Rundong Zhou
JZJie Zhang
Jie Zhang
Yide YangYide Yang
Yide Yang
Background: In the current digital era, eHealth literacy plays an indispensable role in health care and self-management among older adults with noncommunicable diseases (NCDs). Measuring eHealth literacy appropriately and accurately ensures the successful implementation and evaluation of pertinent research and interventions. However, existing eHealth literacy measures focus mainly on individuals’ abilities of accessing and comprehending eHealth information (Web1.0), whereas the capabilities for web-based interaction (Web2.0) and using eHealth information (Web3.0) have not been adequately evaluated. Objective: This study aimed to examine the reliability, validity, and measurement invariance of the eHealth Literacy Scale-Web3.0 (eHLS-Web3.0) among older adults with NCDs. Methods: A total of 642 Chinese older adults with NCDs (mean age 65.78, SD 3.91 years; 55.8% female) were recruited in the baseline assessment, of whom 134 (mean age 65.63, SD 3.99 years; 58.2% female) completed the 1-month follow-up assessment. Baseline measures included the Chinese version of the 24-item 3D eHLS-Web3.0, the Chinese version of the 8-item unidimensional eHealth Literacy Scale (eHEALS), and demographic information. Follow-up measures included the 24-item eHLS-Web3.0 and accelerometer-measured physical activity and sedentary behavior. A series of statistical analyses, for example, Cronbach α, composite reliability coefficient (CR), confirmatory factor analysis (CFA), and multigroup CFA, were performed to examine the internal consistency and test-retest reliabilities, as well as the construct, concurrent, convergent, discriminant, and predictive validities, and the measurement invariance of the eHLS-Web3.0 across gender, education level, and residence. Results: Cronbach α and CR were within acceptable ranges of 0.89-0.94 and 0.90-0.97, respectively, indicating adequate internal consistency of the eHLS-Web3.0 and its subscales. The eHLS-Web3.0 also demonstrated cross-time stability, with baseline and follow-up measures showing a significant intraclass correlation of 0.81-0.91. The construct validity of the 3D structure model of the eHLS-Web3.0 was supported by confirmatory factor analyses. The eHLS-Web3.0 exhibited convergent validity with an average variance extracted value of 0.58 and a CR value of 0.97. Discriminant validity was supported by CFA results for a proposed 4-factor model integrating the 3 eHLS-Web3.0 subscales and eHEALS. The predictive validity of the eHLS-Web3.0 for health behaviors was supported by significant associations of the eHLS-Web3.0 with light physical activity (β=.36, P=.004), moderate to vigorous physical activity (β=.49, P<.001), and sedentary behavior (β=–.26, P=.002). Finally, the measurement invariance of the eHLS-Web3.0 across gender, education level, and residence was supported by the establishment of configural, metric, strong, and strict invariances. Conclusions: The present study provides timely empirical evidence on the reliability, validity, and measurement invariance of the eHLS-Web3.0, suggesting that the 24-item 3D eHLS-Web3.0 is an appropriate and valid tool for measuring eHealth literacy among older adults with NCDs within the Web3.0 sphere.

11 March 2026 in Frontiers in Medicine
Verified
Journal Article
Open access
PDF file
NSNing Su
Ning Su
JHJiayu Hu
Jiayu Hu
BSBorui Shang
Borui Shang
XWXiang Wang
Xiang Wang
WLWei Liang
Wei Liang
HLHao Liu
Hao Liu
Background: Older adults increasingly rely on digital health resources, yet evidence regarding the relationship between eHealth literacy (eHL) and 24-hour movement behaviors (24-HMB), including physical activity (PA), sedentary behavior (SB), and sleep, remains underexplored. This study examined the associations between eHL and 24-HMB in Chinese older adults and examined self-efficacy as a potential mediator and moderator. Methods: Using a convenience sampling approach, 564 community-dwelling older adults (aged 60–74 years) were recruited from four urban Chinese cities via an online survey. A total of 553 valid cases were retained for analyses. eHL was assessed using the eHealth Literacy Scale–Web 3.0, and self-efficacy was assessed using a validated Self-Efficacy Scale. PA and SB were assessed objectively using ActiGraph GT3X+ accelerometers over three consecutive days (two weekdays and one weekend day). Sleep duration was derived from accelerometer-based estimates anchored by daily sleep logs. Multiple linear regression analyses were conducted to examine associations, and mediation and moderation were tested using PROCESS macro (Model 4 and Model 1, respectively), adjusting for age, sex, and education. Results: After adjustment for covariates ( n = 553), higher eHL was associated with greater light physical activity (LPA) ( b = 0.43, p < 0.001) and moderate-to-vigorous physical activity (MVPA) ( b = 0.19, p < 0.001) as well as lower SB ( b = −0.43, p < 0.001). eHL was also positively associated with self-efficacy ( b = 0.47, p < 0.001). Mediation analyses showed small but statistically significant indirect effects via self-efficacy for LPA [0.04, 95% CI (0.00, 0.09)], MVPA [0.08, 95% CI (0.03, 0.13)], and SB [−0.06, 95% CI (−0.10, −0.02)], whereas no mediation was observed for sleep duration [0.02, 95% CI (−0.03, 0.07)]. Moderation analyses showed significant interactions for LPA ( F = 76.82, p < 0.001), SB ( F = 75.07, p < 0.001), and sleep duration ( F = 4.74, p < 0.001), but not MVPA. Interaction effects for sleep were small in magnitude and should therefore be interpreted with caution. Mediation models explained 26% of the variance in LPA, 6% in MVPA, and 30% in SB. Conclusion: In this cross-sectional, urban, device-using sample of older adults, higher eHL was associated with a more favorable 24-HMB profile, particularly higher LPA and lower SB, while associations with sleep duration were weaker. Self-efficacy showed modest indirect associations consistent with partial mediation for PA and SB and also acted as a moderator of several associations. Given the observational design and modest effect sizes, findings should be interpreted cautiously and require confirmation in longitudinal or experimental studies with more representative sampling and improved sleep assessment.

29 May 2025 in Applied Psychology: Health and Well-Being
Verified
Journal Article
Open access
Wei LiangWei Liang
Wei Liang
GLGuifang Liu
Guifang Liu
NSNing Su
Ning Su
RRRyan E Rhodes
Ryan E Rhodes
YDYanping Duan
Yanping Duan
ZXZhu han Xiao
Zhu han Xiao
Parental supportive behavior (PSB) plays a pivotal role in shaping children's 24‐hour movement behaviors (24‐HMB), including light physical activity (LPA), moderate‐to‐vigorous physical activity (MVPA), sedentary screen time (SST), and sleep. However, the psychosocial determinants and the changing process of PSB remain understudied. Using a three‐wave prospective design over four months, this study examined the psychosocial mechanisms of PSB towards children's 24‐HMB based on an adapted health action process approach (HAPA) framework among 812 parents (36.61 ± 3.80 years; 68.7% female). The adapted HAPA model demonstrated acceptable fit indices (CFI = .952–.980, TLI = .946–.967), incorporating the original HAPA model along with past behavior and affective attitude. The model explained 31.6%–54.8% of the variance in PSB across the four outcomes (LPA, MVPA, SST, and sleep). Motivational self‐efficacy and outcome expectancy consistently predicted intentions, while intentions and action control emerged as stable predictors of PSB across all four outcomes. The prediction of planning, and volitional self‐efficacy on PSB varied by movement behaviors. Both past behavior and positive affective attitude were directly associated with PSB, while their inclusion attenuated most pathways in the original HAPA model. Further, intention and action control served as prominent mediators between past behavior, affective attitude, and PSB across all outcomes. Future research could leverage the adapted HAPA framework to guide the development of parent‐based interventions aimed at improving children's 24‐HMB.