Factors influencing fatigue of construction workers in hypoxic environments: A survey study

被引:0
|
作者
Huang, Yuecheng [1 ]
Yu, Yiqin [1 ]
Wang, Yao [1 ]
Gu, Botao [1 ]
Zhang, Zhihuai [1 ]
Miao, Chungang [1 ]
Fang, Dongping [2 ]
机构
[1] Tsinghua Univ, Dept Construct Management, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Sch Civil Engn, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
OPTIMAL RECOVERY-TIME; PHYSIOLOGICAL SYMPTOMS; HIGH-ALTITUDE; RISK; ACCIDENT; PERFORMANCE; EXHAUSTION; WORKING; SLEEP; CONSEQUENCES;
D O I
10.1016/j.ssci.2024.106569
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The number of construction projects at high altitude has continued to increase in recent years. Studies have shown that high-altitude environments pose significant challenges to construction workers and that hypoxia can cause cognitive and physical impairments. However, it remains unclear whether and how high-altitude exposure affects construction workers ' fatigue, which limits the effectiveness of occupational safety and health management in high-altitude projects. To address this concern, this cross-sectional study analyzed data from 646 workers at construction sites located at altitudes around 4000 m, aiming to identify factors contributing to fatigue. Using Bayesian network modeling, the study explored the interdependencies between shift conditions, sleep quality, work overload, and duration of high-altitude exposure on pre-service and work fatigue. The analysis revealed that sleep quality and shift patterns are primary predictors of pre-service fatigue, with work overload also playing a significant role. Pre-service fatigue emerged as a critical mediator for work fatigue, especially when combined with high workload. Notably, the duration of high-altitude exposure influenced both pre-service fatigue and work fatigue. These insights emphasize the need for comprehensive fatigue management strategies that consider individual and job-related factors to enhance safety outcomes. The study advocates for targeted fatigue monitoring and management practices, including pre-service training and real-time fatigue monitoring, to ensure the health and safety of workers in high-altitude construction environments.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] CLASSIFICATION FACTORS INFLUENCING FATIGUE IN WORKERS
    BULAT, V
    TRAVAIL HUMAIN, 1969, 32 (3-4): : 285 - &
  • [2] A Study of Factors Influencing Construction Workers' Intention to Share Safety Knowledge
    Mei, Yujie
    Huang, Jianping
    Liu, Jianqiang
    Jia, Lu
    BUILDINGS, 2024, 14 (02)
  • [3] Study on Influencing Factors of Construction Workers' Unsafe Behavior Based on Text Mining
    Li, Ping
    He, Youshi
    Li, Zhengguang
    FRONTIERS IN PSYCHOLOGY, 2022, 13
  • [4] Study and Action Plan on the Key Factors Influencing Unsafe Behaviors by Construction Workers
    Wang, Yingchen
    Cui, Jingyao
    Zhang, Yikai
    Geng, Xiaoxiao
    BUILDINGS, 2024, 14 (07)
  • [5] A Study on the Factors Influencing Overall Fatigue and Musculoskeletal Pains in Automobile Manufacturing Production Workers
    Kim, Jun Won
    Jeong, Byung Yong
    Park, Myoung Hwan
    APPLIED SCIENCES-BASEL, 2022, 12 (07):
  • [6] Empirical research on the influencing factors of the occupational stress for construction workers
    Lv, Xing
    Wu, Xiang
    Ci, Huipeng
    Liu, Qing
    Yao, Yongzheng
    3RD INTERNATIONAL CONFERENCE ON ENERGY MATERIALS AND ENVIRONMENT ENGINEERING, 2017, 61
  • [7] Identifying the Factors Influencing Hazard Recognition Capability of Construction Workers
    Abubakar, Mu'awiya
    Ibrahim, Yahaya Makarfi
    Bala, Kabir
    Ibrahim, Ahmed Doko
    Abdullahi, Muhammad
    CONSTRUCTION RESEARCH CONGRESS 2020: SAFETY, WORKFORCE, AND EDUCATION, 2020, : 268 - 278
  • [8] Factors Affecting Construction Workers' Fatigue Based on Statistical Analysis
    Yang, Xin-gang
    He, Xiao-yun
    Wang, Qi-quan
    FORTHCOMING NETWORKS AND SUSTAINABILITY IN THE IOT ERA (FONES-IOT 2021), VOL 2, 2022, 130 : 274 - 279
  • [9] Study on influencing factors of professionalization of migrant workers in construction Industry based on Logistic regression model
    He Xiaoyu
    Zhu Donghua
    Zhao Yanjing
    Liu Tingting
    2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, AND INTELLIGENT COMPUTING (CAMMIC 2022), 2022, 12259
  • [10] AN ARTIFICIAL NEURAL NETWORK MODEL FOR PREDICTING FATIGUE OF CONSTRUCTION WORKERS IN HUMID ENVIRONMENTS
    Yi, Wen
    Chan, Albert P. C.
    IMPLEMENTING INNOVATIVE IDEAS IN STRUCTURAL ENGINEERING AND PROJECT MANAGEMENT, 2015, : 1267 - 1272