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. 2024 Dec 10:12:1457151.
doi: 10.3389/fpubh.2024.1457151. eCollection 2024.

Factors related to sedentary behavior in older adult stroke patients in China: a study based on decision tree and logistic regression model

Shuxian Liu #  1 , Juan Li #  2 , Xi Chen  1 , Xiaowen Jiang  1 , Rong Tang  1 , Yumei Lv  1
Affiliations

Factors related to sedentary behavior in older adult stroke patients in China: a study based on decision tree and logistic regression model

Shuxian Liu et al. Front Public Health. .

Abstract

Objective: This study investigates the factors influencing sedentary behavior in older adult Chinese stroke patients using decision trees and logistic regression models.

Methods: Convenience sampling method was employed to enroll 346 respondents aged ≥60 years with stroke from the Department of Neurology of three tertiary-level A hospitals in Heilongjiang province, based on the inclusion criteria. The Sedentary Behavior Questionnaire for Older Adults, the International Physical Activity Questionnaire Short Form (IPAQ-S), the Pittsburgh Sleep Quality Index (PSQI), the Self-Rating Depression Scale (SDS), and the Social Support Scale (SSRS) were used to assess sedentary behavior, physical activity level, sleep quality, depressive symptoms, and social support, respectively. Decision tree and logistic regression models were employed to analyze the factors related to sedentary behavior in older adult stroke patients.

Results: Of the 346 respondents, 233 (67.3%) had sedentary behavior. The logistic regression model showed that education level (OR = 2.843, 95%CI: 1.219-6.626), BMI (OR = 3.686, 95%CI: 1.838-7.393), longest consecutive sitting time (OR = 3.853, 95%CI: 1.867-7.953), and sleep quality (OR = 3.832, 95%CI: 1.716-8.557) were identified as risk factors for sedentary behavior in older adult stroke patients, while drink alcohol (OR = 0.386, 95%CI: 0.184-0.809) and physical activity level (OR = 0.064, 95%CI: 0.030-0.140) were identified as protective factors for sedentary behavior. Besides, the decision tree model showed that physical activity level, longest consecutive sitting time, sleep quality, BMI, depressive symptoms, and age were associated with sedentary behavior. The sensitivity and specificity of the logistic regression model were 69.9 and 93.1%, respectively, and the area under the receiver operating characteristic (ROC) curve was 0.900 (95% CI: 0.863-0.938). The sensitivity and specificity of the decision tree model were 66.4, and 93.1% respectively, and the area under the ROC curve was 0.860 (95% CI: 0.816-0.904).

Conclusion: Our findings indicated that physical activity level, longest consecutive sitting time, sleep quality, and BMI were key factors associated with sedentary behavior. To achieve the purpose of improving rehabilitation effect and quality of life, this study combining decision trees with logistic regression models was of high value in studying factors influencing sedentary behavior in older adult stroke patients.

Keywords: cerebral apoplexy; decision tree; influencing factors; logistic regression model; older adult patients; sedentary behavior.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Classification and regression tree model (N = 346).
Figure 2
Figure 2
Receiver operating characteristic (ROC) curve predicted by decision tree and logistic regression model.
See this image and copyright information in PMC

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References

    1. Collaborators Gb FV, Ba S, Co J, Ga R. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the global burden of disease study 2019. Lancet Neurol. (2021) 20:795–820. doi: 10.1016/S1474-4422(21)00252-0 - DOI - PMC - PubMed
    1. Thayabaranathan T, Kim J, Cadilhac DA, Thrift AG, Donnan GA, Howard G, et al. . Global stroke statistics 2022. Int J Stroke. (2022) 17:946–56. doi: 10.1177/17474930221123175 - DOI - PMC - PubMed
    1. Fitzsimons CF, Nicholson SL, Morris J, Mead GE, Chastin S, Niven A. Stroke survivors' perceptions of their sedentary behaviours three months after stroke. Disabil Rehabil. (2022) 44:382–94. doi: 10.1080/09638288.2020.1768304, PMID: - DOI - PubMed
    1. Liu J, Liu Y, Ma W, Liu J, Tong Y, Wang C, et al. . Age-period-cohort analysis of ischemic stroke deaths attributable to physical inactivity in different income regions. Sci Rep. (2024) 14:6547. doi: 10.1038/s41598-024-57309-2, PMID: - DOI - PMC - PubMed
    1. 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) 14:75. doi: 10.1186/s12966-017-0525-8 - DOI - PMC - PubMed

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