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Determination of Waste Management Workers’ Physical and Psychological Load: A Cross-Sectional Study Using Biometric Data

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  • Itsuki Kageyama

    (Graduate School of Technology Management, Ritsumeikan University, 2-150 Iwakuracho, Osaka 567-8570, Japan
    Merge System Co., Fukuoka 810-0041, Japan
    These authors contributed equally to this work.)

  • Nobuki Hashiguchi

    (Graduate School of Technology Management, Ritsumeikan University, 2-150 Iwakuracho, Osaka 567-8570, Japan
    These authors contributed equally to this work.)

  • Jianfei Cao

    (Graduate School of Technology Management, Ritsumeikan University, 2-150 Iwakuracho, Osaka 567-8570, Japan)

  • Makoto Niwa

    (Graduate School of Technology Management, Ritsumeikan University, 2-150 Iwakuracho, Osaka 567-8570, Japan)

  • Yeongjoo Lim

    (Graduate School of Technology Management, Ritsumeikan University, 2-150 Iwakuracho, Osaka 567-8570, Japan)

  • Masanori Tsutsumi

    (Merge System Co., Fukuoka 810-0041, Japan)

  • Jiakan Yu

    (School of Environment and Society, Tokyo Institute of Technology, Tokyo 108-0023, Japan)

  • Shintaro Sengoku

    (School of Environment and Society, Tokyo Institute of Technology, Tokyo 108-0023, Japan)

  • Soichiro Okamoto

    (College of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-Higashi, Shiga 525-8577, Japan)

  • Seiji Hashimoto

    (College of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-Higashi, Shiga 525-8577, Japan)

  • Kota Kodama

    (Graduate School of Technology Management, Ritsumeikan University, 2-150 Iwakuracho, Osaka 567-8570, Japan
    Center for Research and Education on Drug Discovery, The Graduate School of Pharmaceutical Sciences, Hokkaido University, Sapporo 060-0812, Japan)

Abstract

Waste management workers experience high stress and physical strain in their work environment, but very little empirical evidence supports effective health management practices for waste management workers. Hence, this study investigated the effects of worker characteristics and biometric indices on workers’ physical and psychological loads during waste-handling operations. A biometric measurement system was installed in an industrial waste management facility in Japan to understand the actual working conditions of 29 workers in the facility. It comprised sensing wear for data collection and biometric sensors to measure heart rate (HR) and physical activity (PA) based on electrocardiogram signals. Multiple regression analysis was performed to evaluate significant relationships between the parameters. Although stress level is indicated by the ratio of low frequency (LF) to high frequency (HF) or high LF power in HR, the results showed that compared with workers who did not handle waste, those who did had lower PA and body surface temperature, higher stress, and lower HR variability parameters associated with higher psychological load. There were no significant differences in HR, heart rate interval (RRI), and workload. The psychological load of workers dealing directly with waste was high, regardless of their PA, whereas others had a low psychological load even with high PA. These findings suggest the need to promote sustainable work relationships and a quantitative understanding of harsh working conditions to improve work quality and reduce health hazards.

Suggested Citation

  • Itsuki Kageyama & Nobuki Hashiguchi & Jianfei Cao & Makoto Niwa & Yeongjoo Lim & Masanori Tsutsumi & Jiakan Yu & Shintaro Sengoku & Soichiro Okamoto & Seiji Hashimoto & Kota Kodama, 2022. "Determination of Waste Management Workers’ Physical and Psychological Load: A Cross-Sectional Study Using Biometric Data," IJERPH, MDPI, vol. 19(23), pages 1-23, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15964-:d:988801
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    References listed on IDEAS

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    1. Nonvignon Marius Kêdoté & Ghislain Emmanuel Sopoh & Steve Biko Tobada & Aymeric Joaquin Darboux & Pérince Fonton & Marthe Sandrine Sanon Lompo & Julius Fobil, 2022. "Perceived Stress at Work and Associated Factors among E-Waste Workers in French-Speaking West Africa," IJERPH, MDPI, vol. 19(2), pages 1-9, January.
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    Cited by:

    1. Sameena Naaz & Sarah Ali Khan & Farheen Siddiqui & Shahab Saquib Sohail & Dag Øivind Madsen & Asad Ahmad, 2022. "OdorTAM: Technology Acceptance Model for Biometric Authentication System Using Human Body Odor," IJERPH, MDPI, vol. 19(24), pages 1-17, December.

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