Obesity and Body Segment Parameters in Working Adults

Details

• Personal Author:
  Cham R
• Description:
  Sources of anthropometric data, specifically body segment inertial parameters, are of critical importance in ergonomics and occupational biomechanics. Current models predicting such anthropometric variables are developed based on data collected in normal-weight young adults. Yet, over 60% of all US workers are either overweight or obese and this obesity epidemic worsens with increasing age with more than 75% of workers over the age of 60 years old being overweight or obese. Thus, there is a need to generate new models to predict body segment parameters that better reflect the working population. In this project, we developped new datasets of body segment parameters that include body mass index (BMI) as a factor across the age span of working adults using Dual Energy X-Ray Absorption (DXA) methods. More specifically, our goal in this project was two-fold: (1) quantify the impact of obesity on body segment parameters in full-time workers aged 21 to 70 years old (Aim #1), and (2) develop BMI specific regression models for the prediction of body segment parameters in the same population (Aim #2). To achieve these aims, full-time workers between the ages of 21 and 70 years old were recruited for participation in this project. They were asked to come in for one visit. During this visit, a whole-body DXA scan was collected to derive in-vivo measures of body segment parameters. Body measurements were also collected. Standard multivariate regression models were used to achieve the aims of the proposed project. In Aim #1, the results indicate that there are several statistically and practically significant linear and quadratic effects of age, BMI, and the interaction between age and BMI on a number of BSPs in the working male and female population. Thus, it is important to consider BMI and age effects when deriving BSPs in men and women. In Aim 2, the findings indicate that the accuracy of BSPs predictions can be significantly improved (14-47%) by considering body shape, i.e. including key body measurements relevant to the BSP of interest in the prediction models. In summary, the proposed project addressed a gap in the ergonomics and occupational biomechanics litterature by developing validated models that accurately predict body segment parameters in working adults, taking into account body mass, age, gender and body shape. [Description provided by NIOSH]
• Subjects:
  Age Factors Biomechanical Phenomena Ergonomics Occupational Health Safety Sex Characteristics
• Keywords:
  Age Factors Biomechanical Modeling Biomechanics BMI Body Mass Index Body Regions Gender Factors Obesity Sex Factors Weight Factors X-ray Absorption

  More +
• Series:
  Grant Final Reports
• Publisher:
  National Institute for Occupational Safety and Health
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Final Grant Report
• Place as Subject:
  OSHA Region 3 ; Pennsylvania
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  OEP - Office of Extramural Programs
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  1-24
• NIOSHTIC Number:
  nn:20052300
• NTIS Accession Number:
  PB2018-101422
• Citation:
  Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, R01-OH-010106, 2017 Nov; :1-24
• Contact Point Address:
  Rakié Cham, PhD, Department of Bioengineering, University of Pittsburgh 4420 Bayard St, Suite #305, Pittsburgh, PA 15213
• Email:
  rcham@pitt.edu
• Federal Fiscal Year:
  2018
• Performing Organization:
  University of Pittsburgh at Pittsburgh
• Peer Reviewed:
  False
• Start Date:
  20130901
• Source Full Name:
  National Institute for Occupational Safety and Health
• End Date:
  20170831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:661ded5aa637360739fa14e21d0315d29c704ffaae86ab378965a4df89d6ec9390ec0c94760a3ab52e61a5dba3e091620ee1e42678989dd4c78c75599f4e165b
• Download URL:
  https://stacks.cdc.gov/view/cdc/218699/cdc_218699_DS1.pdf
• File Type:
  [PDF - 1.43 MB ]