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An Instrumented Pull Test to Characterize Postural Responses
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Lifting capacity prediction model using physical performance measures among construction workers.

Sidhiprada Mohapatra1, Aparajita Verma1, N Girish2

  • 1Department of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, India.

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|January 21, 2022
PubMed
Summary
This summary is machine-generated.

A new model predicts construction workers' lifting capacity using simple physical tests. This helps prevent workplace injuries by assessing workers

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Area of Science:

  • Occupational Health and Safety
  • Ergonomics
  • Musculoskeletal Injury Prevention

Background:

  • Manual materials handling is a primary cause of workplace musculoskeletal injuries.
  • Accurate assessment of lifting capacity is crucial for injury prevention but difficult to perform on-site.
  • There is a need for an accessible method to evaluate lifting capacity in occupational settings.

Purpose of the Study:

  • To develop a predictive model for estimating lifting capacity in construction workers.
  • To utilize readily measurable physical parameters for this prediction model.
  • To provide a practical tool for workplace injury risk assessment.

Main Methods:

  • Recruited 65 construction workers for the study.
  • Assessed socio-demographic data, core strength and endurance, grip strength, and lower limb flexibility.
  • Determined lifting capacity using the progressive isoinertial lifting evaluation.
  • Developed a prediction model using stepwise multiple linear regression analysis.

Main Results:

  • Identified age, BMI, grip strength, flexibility, prone plank, and trunk lateral flexor endurance as significant predictors of lifting capacity.
  • A regression model was successfully developed using these key variables.
  • The model demonstrated the influence of specific physical attributes on a worker's ability to lift.

Conclusions:

  • The developed regression model offers a practical and easy method for estimating lifting capacity among construction workers.
  • This tool can be administered by site supervisors with minimal training, aiding in pre-placement and return-to-work evaluations.
  • Implementing this model can contribute to reducing the incidence of low back disorders and other musculoskeletal injuries in the construction industry.