TY - JOUR
T1 - Factors contributing to differences in physical activity levels in (pre)frail older adults living in rural areas of China
AU - Zhang, Xin
AU - Zheng, Xiaoping
AU - Hobbelen, Hans
AU - van Munster, Barbara
AU - Tong, Qian
AU - Yu, Tianzhuo
AU - Li, Feng
AU - Lamoth, Claudine J C
N1 - Copyright: © 2025 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2025/11/4
Y1 - 2025/11/4
N2 - INTRODUCTION: Physical Activity (PA) is essential for enhancing the physical function of pre-frail and frail older adults. However, among this group, PA-levels vary significantly. Identifying the factors contributing to these differences could support tailored PA interventions. This study aims to examine factors associated with physical activity levels among pre-frail and frail older adults in rural China.METHODS: This is a cross-sectional study. A total of 284 (pre)frail older adults (aged ≥60 years) were included from ten rural healthcare centers in Northeast China. Participants were categorized into low-moderate and high physical activity groups assessed using the Short Form International Physical Activity Questionnaire. Four-dimensional data were collected, including demographics, health behaviors, objective physical performance measures, and self-reported perceived health profiles. Extreme Gradient Boosting (XGBoost), a machine learning algorithm, was employed for binary classification (low-moderate vs. high physical activity). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and F1-score. To enhance interpretability, SHapley Additive exPlanations (SHAP) were utilized to identify key predictive variables.RESULTS: Mean age of participants was 70 years (59% female, 86% farmers). The low-moderate group averaged 1,187 MET/week, while the high physical activity group reached 8,162 MET/week. Physical performance tests showed significantly better scores in the high PA group. The XGBoost model achieved 82.4% accuracy (AUC: 0.769, specificity: 90%, sensitivity: 63%). SHAP analysis revealed that self-reported social support, general health, ambulation, and physical performance measures were the most important factors.CONCLUSION: The high physical activity group demonstrated better physical function than the low-moderate physical activity group; though, both groups showed poorer physical function compared to the general older population. Self-reported health perceptions and social support significantly correlated with physical activity levels. Addressing these factors through targeted interventions-including community-based social support programs and structured mobility-enhancing exercises-may contribute to improved health outcomes and enhanced quality of life in this population.
AB - INTRODUCTION: Physical Activity (PA) is essential for enhancing the physical function of pre-frail and frail older adults. However, among this group, PA-levels vary significantly. Identifying the factors contributing to these differences could support tailored PA interventions. This study aims to examine factors associated with physical activity levels among pre-frail and frail older adults in rural China.METHODS: This is a cross-sectional study. A total of 284 (pre)frail older adults (aged ≥60 years) were included from ten rural healthcare centers in Northeast China. Participants were categorized into low-moderate and high physical activity groups assessed using the Short Form International Physical Activity Questionnaire. Four-dimensional data were collected, including demographics, health behaviors, objective physical performance measures, and self-reported perceived health profiles. Extreme Gradient Boosting (XGBoost), a machine learning algorithm, was employed for binary classification (low-moderate vs. high physical activity). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and F1-score. To enhance interpretability, SHapley Additive exPlanations (SHAP) were utilized to identify key predictive variables.RESULTS: Mean age of participants was 70 years (59% female, 86% farmers). The low-moderate group averaged 1,187 MET/week, while the high physical activity group reached 8,162 MET/week. Physical performance tests showed significantly better scores in the high PA group. The XGBoost model achieved 82.4% accuracy (AUC: 0.769, specificity: 90%, sensitivity: 63%). SHAP analysis revealed that self-reported social support, general health, ambulation, and physical performance measures were the most important factors.CONCLUSION: The high physical activity group demonstrated better physical function than the low-moderate physical activity group; though, both groups showed poorer physical function compared to the general older population. Self-reported health perceptions and social support significantly correlated with physical activity levels. Addressing these factors through targeted interventions-including community-based social support programs and structured mobility-enhancing exercises-may contribute to improved health outcomes and enhanced quality of life in this population.
KW - Humans
KW - Aged
KW - Female
KW - Male
KW - China
KW - Exercise/physiology
KW - Rural Population
KW - Cross-Sectional Studies
KW - Frail Elderly/statistics & numerical data
KW - Middle Aged
KW - 80 and over
KW - Surveys and Questionnaires
KW - mensen
KW - op leeftijd
KW - vrouwelijk
KW - mannelijk
KW - China
KW - beweging/fysiologie
KW - plattelandsbevolking
KW - cross-sectionele studies
KW - kwetsbare ouderen/statistieken en numerieke gegevens
KW - middelbare leeftijd
KW - 80 en ouder
KW - vragenlijsten en enquêtes
U2 - 10.1371/journal.pone.0335607
DO - 10.1371/journal.pone.0335607
M3 - Article
C2 - 41187200
SN - 1932-6203
VL - 20
JO - PLoS ONE
JF - PLoS ONE
IS - 11 November
M1 - e0335607
ER -