Prevalence and determinants of driving habits in the oldest old: Results of the multicenter prospective AgeCoDe-AgeQualiDe study

Arch Gerontol Geriatr. May-Jun 2019;82:245-250. doi: 10.1016/j.archger.2019.03.006. Epub 2019 Mar 7.


Aim: To present data on the prevalence of driving habits and to identify the determinants of driving habits among the oldest old in Germany.

Methods: Cross-sectional data were used from the "Study on Needs, health service use, costs and health-related quality of life in a large sample of oldest-old primary care patients (85+)" (AgeQualiDe), including primary care patients aged 85 years and above (n = 549 at FU 9, mean age was 90.3 years; 86-101 years). Driving habits were measured (driving a car; frequency of driving a car and driving duration). Correlates were quantified using widely established scales (e.g., Geriatric Depression Scale, Instrumental Activities of Daily Living Scale). Multiple regression models were used to identify the determinants of driving habits.

Results: Sixteen percent (87 out of 549) drove a car. Among the car-drivers, about 80% drove at least several times a week and about two-thirds drove longer distances (>15 min). Multiple logistic regressions showed that among the oldest old being a male was more likely to be a current driver compared to being a female. Other significant factors were subjective memory impairment, severe visual impairment, functional and cognitive impairment. Correlates of frequency of driving a car and driving duration were further identified.

Conclusion: About one in six very old Germans is still a regular car driver. Several determinants of driving habits among the oldest old were identified. Future longitudinal studies are required to clarify the factors leading to changes in driving habits.

Keywords: Automobile driving; Driving cessation; Driving exposure; Driving habits; Oldest old.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged, 80 and over
  • Automobile Driving* / psychology
  • Cross-Sectional Studies
  • Female
  • Habits
  • Humans
  • Logistic Models
  • Male
  • Prevalence
  • Prospective Studies