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Using Older Adult Walking Speeds from Controlled Trials as Inputs for Occupants in Simulations

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Abstract

There is a need to revisit movement dataset(s) currently used as egress determinants to assess whether they are truly representative of the current diverse occupant base. This is particularly important with our aging population as these sets contain very limited amounts of recent, age-specific data for older adults. This study provides data on walking speeds of older adults, obtained during standardized tests of walking, and compares those to default walking speeds used in current egress models. From experimental, short-distance walking trials (n = 451), it was seen that sex, increasing age, use of walking aids, those who have previously experienced a stroke (n = 116) and walking under cognitive load all resulted in decreases in walking speed. First iteration Pathfinder simulations showed that more realistic inputs for population walking speed resulted in simulated egress times that were on average 8 s slower compared to use of the current default range of walking speeds. Results suggest that the assumption of a uniform population in egress modelling, and consequently the standard practice of using a default walking speed for older adult occupants, should be reconsidered since, in reality the older adult population is extremely heterogeneous with regards to mobility, as reflected in the variability in walking speeds in this study.

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Notes

  1. This was assessed by a Mental State Examination and scored between 0-100 with higher scores indicating better global cognitive functioning [29]: individuals with lower cognitive functioning scores walk slower than individuals with higher cognitive functioning scores[10].

  2. The impacts of medication described are true across the age range, it is a result of the medication itself, not the age of the individual taking the medication.

  3. Existing tools such as FED calculations, are based on ‘healthy adults’ with additional corrections applied to account for vulnerable populations, although it is not clear how these corrections were determined [35].

  4. Defined as self-care functions, getting up from their bed or chair, walking around their home and ability to walk 5 blocks.

  5. Although there is debate within the community about the applicability of this historical data during the 1950s–1970s, this work does form the basis for many of the current egress calculations and models and in some cases can be selected as a default range.

  6. In Canada, continuum care facilities accommodate a variety of people. Most people will enter healthy and desire to live in a community setting, they are completely independent and reside in a residential condo. As they stay and age, if their functional ability decreases they can then move through different living options, for example they can move into retirement care (services such as housekeeping and some nursing care are offered), and then into a more long-term care setting (additional nursing and caretaker services).

  7. This would define an individual who attends post-stroke check-ups to assess recovery.

  8. If counting down by 3’s was too easy, then the participant was told to count down by 7’s instead, and if counting down by 3’s was too challenging the participant would count down by 1’s instead.

  9. Results of this statistical test are reported as t(df) = W-statistic, p value, d = effect size.

  10. A note on sample sizes utilized in the statistical analysis, for independent t-tests comparing sex and the descriptive statistics in Table 3, sample sizes of n = 238 females and n = 128 males (total n = 366) was used. For independent t-tests comparing aid use, sample sizes of n = 152 aid users, and n = 214 non-aid users (total n = 366) in Table 4 were used. Paired t-tests were conducted on a separate group of aid users, with a sample size of n = 85, who felt comfortable trying the preferred walking condition trial without their aid, Table 5.

  11. A sample size of 10 simulation runs per set was determined to be sufficient (\(\alpha\) = 0.05, power = 95%) to compare whether or not the means of predicted egress time were different between the two groups: older adult assigned and SFPE default.

References

  1. Lovreglio R, Ronchi E, Kinsey MJ (2020) An online survey of pedestrian evacuation model usage and users. Fire Technol 56(3):1133–1153

    Article  Google Scholar 

  2. Gates TJ, Noyce DA, Bill AR, Van Ee N (2006) Recommended walking speeds for timing of pedestrian clearance intervals based on characteristics of the pedestrian population. Transp Res Rec 1982(1):38–47

    Article  Google Scholar 

  3. Knoblauch RL, Pietrucha MT, Nitzburg M (1996) Field studies of pedestrian walking speed and start-up time. Transp Res Rec 1538(1):27–38

    Article  Google Scholar 

  4. Cabrera F, Munoz F, Perez C (2016) Walking patterns of elderly in a Peruvian public space. In: Proceedings of the 8th international conference on Pedestrian and evacuation dynamics, pp 12–17

  5. Balboa A, Cuesta A, Alvear D (2020) Measuring social influence and group formation during evacuation process. Collect Dyn 5:238–245

    Google Scholar 

  6. Yeo SK, He Y (2009) Commuter characteristics in mass rapid transit stations in Singapore. Fire Saf J 44(2):183–191

    Article  Google Scholar 

  7. Young T, Gales J, Kinsey M, Wong WC (2021) Variability in stadia evacuation under normal, high-motivation, and emergency egress. J Build Eng 40:102361

    Article  Google Scholar 

  8. Jin T, Yamada T (1989) Experimental study of human behavior in smoke filled corridors. In: Proceedings of the second international symposium on fire safety science, pp 511–520

  9. Was J, Porzycki J, Schmidt-Polończyk N (2020) Grouping behaviour and decision making in road tunnels evacuation in smoke conditions experimental approach. Collect Dyn 5:93–97

    Google Scholar 

  10. Fitzpatrick AL, Buchanan CK, Nahin RL, DeKosky ST, Atkinson HH, Carlson MC, Williamson JD (2007) Associations of gait speed and other measures of physical function with cognition in a healthy cohort of elderly persons. J Gerontol Ser A Biol Sci Med Sci 62(11):1244–1251

    Article  Google Scholar 

  11. Deshpande N, Metter EJ, Bandinelli S, Guralnik J, Ferrucci L (2009) Gait speed under varied challenges and cognitive decline in older persons: a prospective study. Age Ageing 38(5):509–514

    Article  Google Scholar 

  12. Kuligowski E, Peacock R, Wiess E, Hoskins B (2015) Stair evacuation of people with mobility impairments. Fire Mater 39(4):371–384

    Article  Google Scholar 

  13. Boyce KE, Shields T, Silcock G (1999) Toward the characterization of building occupancies for fire safety engineering: capabilities of disabled people moving horizontally and on an incline. Fire Technol 35:51–67

    Article  Google Scholar 

  14. Rahouti A, Lovreglio R, Nilsson D, Kuligowski E, Jackson P, Rothas F (2021) Investigating evacuation behaviour in retirement facilities: case studies from new Zealand. Fire Technol 57:1015–1039. https://doi.org/10.1007/s10694-020-01058-x

    Article  Google Scholar 

  15. Folk L, Gonzales K, Gales J, Kinsey M, Carattin E, Young T (2020) Emergency egress for the elderly in care home fire situations. Fire Mater 44(4):585–606

    Article  Google Scholar 

  16. Rahouti A, Lovreglio R, Jackson P, Datoussaïd S (2020) Evacuation data from a hospital outpatient drill the case study of north shore hospital. Collect Dyn 5:142–149

    Google Scholar 

  17. Rahouti A, Lovreglio R, Gwynne S, Jackson P, Datoussaïd S, Hunt A (2020) Human behaviour during a healthcare facility evacuation drills: investigation of pre-evacuation and travel phases. Saf Sci 129:104754

    Article  Google Scholar 

  18. Gwynne S, Galea E, Parke J, Hickson J (2003) The collection of pre-evacuation times from evacuation trials involving a hospital outpatient area and a university library facility. Fire Saf Sci 7:877–888

    Article  Google Scholar 

  19. Geoerg P, Berchtold F, Gwynne S, Boyce K, Holl S, Hofmann A (2019) Engineering egress data considering pedestrians with reduced mobility. Fire Mater 43(7):759–781

    Article  Google Scholar 

  20. Schadschneider A, Klingsch W, Klüpfel H, Kretz T, Rogsch C, Seyfried A (2008) Evacuation dynamics: Empirical results, modeling and applications. arXiv preprint arXiv:0802.1620

  21. Haghani M (2020) Empirical methods in pedestrian, crowd and evacuation dynamics: part i. Experimental methods and emerging topics. Saf Sci 129:104743

    Article  Google Scholar 

  22. Gwynne SM, Kuligowski E, Spearpoint M, Ronchi E (2015) Bounding defaults in egress models. Fire Mater 39(4):335–352

    Article  Google Scholar 

  23. Flynn JD (2010) Characteristics of home fire victims. National Fire Protection Association, Quincy

    Google Scholar 

  24. Holborn P, Nolan P, Golt J (2003) An analysis of fatal unintentional dwelling fires investigated by London fire brigade between 1996 and 2000. Fire Saf J 38(1):1–42

    Article  Google Scholar 

  25. Thomas IPB (2004) Occupants, ignition and fire outcomes. In: Proceedings of 3rd international conference, human behaviour in fire, pp 45–56

  26. Miller I (2005) Human behaviour contributing to unintentional residential fire deaths, 1997–2003. New Zealand Fire Service Commission, Wellington

    Google Scholar 

  27. Harpur A, Boyce K, McConnel N (2014) An investigation into the circumstances surrounding elderly dwelling fire fatalities and the barriers to implementing fire safety strategies among this group. Fire Saf Sci 11(1):1144–1159

    Article  Google Scholar 

  28. U.S. Fire Administration: Fire Risks for the Older Adult (1999). http://www.usfa.fema.gov/downloads/pdf/publications/older.pdf

  29. Teng E, Chui H (1987) The modified mini-mental state examination (3ms). Can J Psychiatry 41(2):114–21

    Google Scholar 

  30. Douglas A, Letts L, Richardson J (2011) A systematic review of accidental injury from fire, wandering and medication self-administration errors for older adults with and without dementia. Arch Gerontol Geriatr 52(1):1–10

    Article  Google Scholar 

  31. Lionelli G, Pickus E, Beckum O, Decoursey R, Korentager R (2005) A three decade analysis of factors affecting burn mortality in the elderly. Burns 31(8):958–963

    Article  Google Scholar 

  32. Keck M, Lumenta D, Andel H, Kamolz L, Frey M (2009) Burn treatment in the elderly. Burns 35(8):1071–1079

    Article  Google Scholar 

  33. Khadim M, Rashid A, Fogarty B, Khan K (2009) Mortality estimates in the elderly burn patients: the northern Ireland experience. Burns 35(1):107–113

    Article  Google Scholar 

  34. Purser DA (2015) Fire safety and evacuation implications from behaviours and hazard development in two fatal care home incidents. Fire Mater 39(4):430–452

    Article  Google Scholar 

  35. Kuligowski ED (2016) Human behavior in fire. SFPE handbook of fire protection engineering, 2070–2114

  36. Gordon RL, Reiss RA, Haenel H, Case E, French RL, Mohaddes A, Wolcott R et al (1996) Traffic control systems handbook. United States. Federal Highway Administration. Office of Technology Applications, Technical report

  37. Manual HC (2000) Highway capacity manual. Washington, DC 2(1):1

    Google Scholar 

  38. Board UA (2005) Revised draft guidelines for accessible public rights-of-way. United States Access Board, Washington

    Google Scholar 

  39. Gwynne SM, Boyce K (2016) Engineering data. IN: SFPE handbook of fire protection engineering, pp 2429–2551

  40. Fruin J (1971) Pedestrian planning and design: Elevator world. Educational Services Division, PO Box 6507

  41. Pauls J (1982) Effective-width model for crowd evacuation flow on stairs. National Research Council of Canada, Ottawa, Ontario, pp 21–24

    Google Scholar 

  42. Pauls JL (1995) Movement of people. In: SFPE Handbook of fire protection engineering

  43. Pauls J (1980) Effective-width model for evacuation flow in buildings. In: Proceedings, engineering applications workshop, pp 215–232

  44. Predtechenskii V, Milinskii A (1978) Planning for foot traffic in buildings. Amerind, New Dehli

    Google Scholar 

  45. Kaneko M, Morimoto Y, Kimura M, Fuchimoto K, Fuchimoto T (1991) A kinematic analysis of walking and physical fitness testing in elderly women. Can J Sport Sci 16(3):223–228

    Google Scholar 

  46. Himann JE, Cunningham DA, Rechnitzer PA, Paterson DH (1988) Age-related changes in speed of walking. Med Sci Sports Exerc 20(2):161–166

    Article  Google Scholar 

  47. Bassey E, Bendall M, Pearson M (1988) Muscle strength in the triceps Surae and objectively measured customary walking activity in men and women over 65 years of age. Clin Sci 74(1):85–89

    Article  Google Scholar 

  48. Öberg T, Karsznia A, Öberg K (1993) Basic gait parameters: reference data for normal subjects, 10–79 years of age. J Rehab Res Dev 30:210–210

    Google Scholar 

  49. Bohannon RW, Andrews AW, Thomas MW (1996) Walking speed: reference values and correlates for older adults. J Orthop Sports Phys Therapy 24(2):86–90

    Article  Google Scholar 

  50. Cunningham DA, Rechnitzer PA, Pearce ME, Donner AP (1982) Determinants of self-selected walking pace across ages 19 to 66. Journal of gerontology 37(5):560–564

    Article  Google Scholar 

  51. Murray MP, Kory RC, Clarkson BH (1969) Walking patterns in healthy old men. J Gerontol 24(2):169–178

    Article  Google Scholar 

  52. Geoerg P, Polzin RM, Schumann J, Holl S, Hofmann A (2018) Small-scale studies on evacuation characteristics of pedestrians with physical, mental or age-related disabilities. J Phys Conf Ser 1107:072006

    Article  Google Scholar 

  53. Sharifi MS, Stuart D, Christensen K, Chen A (2015) Traffic flow characteristics of heterogeneous pedestrian stream involving individuals with disabilities. Transp Res Rec 2537(1):111–125

    Article  Google Scholar 

  54. Kuligowski ED (2005) Review of 28 egress models

  55. Beurskens R, Bock O (2012) Age-related deficits of dual-task walking: a review. Neural Plast 2012:131608

    Article  Google Scholar 

  56. Kalaria RN, Ballard C (2001) Stroke and cognition. Curr Atheroscler Rep 3(4):334–339

    Article  Google Scholar 

  57. Hollman JH, Youdas JW, Lanzino DJ (2011) Gender differences in dual task gait performance in older adults. Am J Men’s Health 5(1):11–17

    Article  Google Scholar 

  58. Condello G, Forte R, Monteagudo P, Ghinassi B, Di Baldassarre A, Capranica L, Pesce C (2019) Autonomic stress response and perceived effort jointly inform on dual tasking in aging. Brain Sci 9(11):290

    Article  Google Scholar 

  59. Hillel I, Gazit E, Nieuwboer A, Avanzino L, Rochester L, Cereatti A, Croce UD, Rikkert MO, Bloem BR, Pelosin E et al (2019) Is every-day walking in older adults more analogous to dual-task walking or to usual walking—elucidating the gaps between gait performance in the lab and during 24/7 monitoring. Eur Rev Aging Phys Act 16(1):1–12

    Article  Google Scholar 

  60. Cole KR, Shields RK (2019) Age and cognitive stress influences motor skill acquisition, consolidation, and dual-task effect in humans. J Motor behav. https://doi.org/10.1080/00222895.2018.1547893

    Article  Google Scholar 

  61. Hausdorff JM, Schweiger A, Herman T, Yogev-Seligmann G, Giladi N (2008) Dual task decrements in gait among healthy older adults: contributing factors. J Gerontol Ser A Biol Sci Med Sci 63(12):1335

    Article  Google Scholar 

  62. 2018 Stroke Report (2018). https://www.heartandstroke.ca/-/media/pdf-files/canada/stroke-report/strokereport2018.ashx?rev=8491d9c349f7404491f36be67f649c0b

  63. Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN et al (2020) Heart disease and stroke statistics-2020 update: a report from the American heart association. Circulation 141(9):139–596

    Article  Google Scholar 

  64. Moroney J, Bagiella E, Desmond D, Paik M, Stern Y, Tatemichi T (1996) Risk factors for incident dementia after stroke: role of hypoxic and ischemic disorders. Stroke 27(8):1283–1289

    Article  Google Scholar 

  65. Pohjasvaara T, Erkinjuntti T, Vataja R, Kaste M (1997) Dementia three months after stroke: baseline frequency and effect of different definitions of dementia in the Helsinki stroke aging memory study (sam) cohort. Stroke 28(4):785–792

    Article  Google Scholar 

  66. Bonita R, Beaglehole R (1988) Recovery of motor function after stroke. Stroke 19(12):1497–1500

    Article  Google Scholar 

  67. Timmermans C, Roerdink M, Janssen TW, Meskers CG, Beek PJ (2018) Dual-task walking in challenging environments in people with stroke: cognitive-motor interference and task prioritization. Stroke Res Treat 2018:7928597

    Google Scholar 

  68. Thomson S, Badiuk B, Parokaran Varghese J, Thai V, McIlroy WE, Van Ooteghem K (2022) Standing, transition, and walking ability in older adults: The case for independently evaluating different domains of mobility function. Gerontology 68(11):1246–1257

    Article  Google Scholar 

  69. Inc CS. GaitRite Walkways. https://www.gaitrite.com/gait-analysis-walkways

  70. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing. https://www.R-project.org/

  71. Engineering, T.: PathFinder (546)

  72. Agyemang C, Kinateder M (2022) A review of the biomechanics of staircase descent: implications for building fire evacuations. Fire Technol 58:1–35

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank study participants and participating sites of the Canadian Partnership for Stroke Recovery Rehab Affiliates study as well as Schlegel Villages together with the Schlegel-UW Research Institute for Aging, for their contributions to the studies in which these data were collected.

Funding

NSERC CGS-D.

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Author notes

  1. John Gales, Karen Van Ooteghem and Elizabeth Weckman have contributed equally to this work.

Authors and Affiliations

  1. Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Canada

    Bronwyn Forrest & Elizabeth Weckman

  2. Department of Civil Engineering, York University, Toronto, Canada

    John Gales

  3. Department of Kinesiology, University of Waterloo, Waterloo, Canada

    Karen Van Ooteghem

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  1. Bronwyn Forrest
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  2. John Gales
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Correspondence to Bronwyn Forrest.

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Forrest, B., Gales, J., Van Ooteghem, K. et al. Using Older Adult Walking Speeds from Controlled Trials as Inputs for Occupants in Simulations. Fire Technol (2024). https://doi.org/10.1007/s10694-024-01574-0

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