FUNCTIONAL AGING IN PILOTS: AN EXAMINATION OF A MATHEMATICAL MODEL BASED ON MEDICAL DATA ON GENERAL AVIATION PILOTS

In a recent series of papers, Gerathewohl reviewed several mathematical procedures employed in efforts to develop a functional age index. The purpose of the present study was to apply mathematical procedures to the Federal Aviation Administration (FAA) pilot medical data to examine the feasibility of devising a linear numbering system such that (1) the cumulative probability distribution functions (CPDF) for persons who are not diagnosed as having an acute pathology are lower on the scale than those diagnosed as having an acute pathology; and (2) the CDPF's for both groups overlap minimally. FAA pilot records were employed in a series of two group discriminant function analyses. The first group consisted of records where no pathology was listed. The second group consisted of records where a cardiovascular, cerebrovascular or diabetic pathology was listed. The analyses presented some pertinent results. Age is not as accurate in discriminating between the sudden incapacitating pathology and nonpathology groups as the linear discriminant composite. As age increase from post-50, to post-55, to post-60, classification accuracy using the discriminant index increase monotonically. Better measures that predict these pathologies with more accuracy would further separate the CPDF's of the pathology and nonpathology groups. Based on these results, a possible strategy for future study on pilot certification is discussed.

• Record URL:
  http://www.faa.gov/data_research/research/med_humanfacs/oamtechreports/1980s/media/am82-18.pdf
• 
• Corporate Authors:

  Federal Aviation Administration

  Office of Aerospace Medicine, 800 Independence Avenue, SW
  Washington, DC  United States  20591
• Authors:
  • Boone, J O
• Publication Date: 1982-6

Language

• English

Media Info

• Features: Figures; Tables;
• Pagination: 8 p.

Subject/Index Terms

• TRT Terms: Age groups; Aging (Biology); Certification; Classification; Discriminant analysis; Diseases and medical conditions; Distributions (Statistics); General aviation pilots; Mathematical models; Medical records; Pathology; Probability
• Identifier Terms: U.S. Federal Aviation Administration
• Subject Areas: Aviation; Data and Information Technology; Education and Training; Environment; Safety and Human Factors; Society;

Filing Info

• Accession Number: 00964721
• Record Type: Publication
• Report/Paper Numbers: FAA-AM-82-18
• Files: TRIS, USDOT
• Created Date: Oct 19 2003 12:00AM