1. Proceedings
  2. I3M
  3. 2018
  4. IWISH
  5. 10.46354/i3m.2018.iwish.011

The association of demographic and health factors with working capability in elderly

  • a Laura Aponte-Becerra , 
  • b Antonio Padovano , 
  • b Francesco Longo  , 
  • a Vasileios-Arsenios Lioutas  , 
  • c Peter Novak  , 
  • d Long Ngo  , 
  • g Regina McGlinchey  , 
  • g Catherine Fortier  , 
  • a Vera Novak   
  • a Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School. Boston, MA., USA
  • b Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, Arcavacata di Rende (CS), Italy
  • c Autonomic Laboratory, Department of Neurology, Brigham and Women's Faulkner Hospital, Harvard Medical School, Boston, MA., USA 
  • d Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Harvard Medical School,  Boston, MA., USA
  • f Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA., USA.
Cite as
Aponte-Becerra L., Padovano A., Longo F., Lioutas V.A., Novak P., Ngo L., McGlinchey R.,
Fortier C., Novak V. (2018). The association of demographic and health factors with working capability in elderly. Proceedings of the 7th International Workshop on Innovative Simulation for Healthcare (IWISH 2018), pp. 63-70. DOI: https://doi.org/10.46354/i3m.2018.iwish.011

Abstract

With an aging work-force, factors determining working capability, such as cognitive functions or communication skills, need to be assessed precisely. We addressed the gap of current knowledge based on self-rated measures by using objective measures and standardized questionnaires. Cross-sectional analysis included baseline data from the Memory Advancement by Intranasal Insulin in Type 2 Diabetes trial (MemAID), which consisted of 168 subjects, 84 men, 67.6±9.05 years old (mean ±SD), 44% diabetic, and 78 currently working. The subjects’ working status, demographic characteristics, health factors – including body mass index, hemoglobin A1c (HbA1c - a measure of insulin resistance), number of co-morbidities – and a set of objective measures of their health status – including cognitive speed processing, visual learning, memory, walking speed, depression, and disability scores – were analyzed to detect relevant associations, which were then used to construct a logistic regression model aimed to determine significant determinants of the probability of working in older adults (≥50 years of age). Results show that hemoglobin A1c and normal walking speed have a strong association with the probability of working in older adults."

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