Falls are unexpected accidents and the leading cause of death and hospitalization among older adults. According to the 2006 “Dynamic Statistics of the Population” published by the Ministry of Health, Labor and Welfare, 20% of deaths in unexpected accidents were attributed to fall in older adults who were older than 65 years in Japan.1 Unfortunately, fall-related mortality rate increased by 46% from 2002 to 2010 in the United States.2 One-third of community-dwelling adults older than 65 years fall each year3 and between 30% and 50% of in-facility falls result in injuries.4
Some of the major consequences of falls in hospital among older adults are injuries, bruises, hip fractures, or brain injuries.5,6 These accidents may cause patients to be bedridden and lead to limited physical function, prolonged hospitalization, and increases in medical costs. Furthermore, fear of falling may lead to avoidance of daily activities such as walking, which contributes to a decrease in mobility and independent living ability. As a result, a cycle of lower extremity muscle weakening and further deterioration of balance occurs.7,8 Thus, researchers have investigated a cause of falls and intervened to prevent falls.9–11
Falls result from multiple factors.12,13 Age-related deterioration of musculoskeletal abilities leads to deficits in maintaining postural control. Consequently, when any mobility deteriorates, older adults tend to fall.12,13 In addition, if each mobility is not coordinated effectively among them, older adults will have a higher risk of falling.14 Furthermore, several studies have also reported that older adults tend to fall easily during a specific time frame and specific places.15,16 According to Hagino et al,17 52% of older adults participating in their study experienced falls in an early morning from 2:00 AM to 6:00 AM. Morris et al18 also measured incidents occurring between 5:00 AM and 8:00 AM in their study. Regardless of the different time frame, the causes of fall incidences seem to be affected by a decline in arousal levels and functional mobility. Time of day had a consistent influence on dynamic postural control.15 Some of factors, such as cognitive abilities, reaction time, strength, body temperature, and heart rate, may contribute to postural control and these factors related to physical activity are at optimal levels in early afternoon hours.16,19 Researchers also reported that neuromuscular function was affected by prior wake and circadian phase.15,20 Furthermore, Schlesinger et al21 and Uimonen et al22 reported that among sleep-deprived individuals, postural control was affected in the morning hours. However, a lack of research is found on arousal levels and mobility in the early morning hours after awaking. The assessment of time-dependent changes in arousal level and mobility may identify modifiable risk factors of falls and may help programs prevent falls in older adults. Thus, the aim of this study was to evaluate both arousal level and mobility in the early morning hours after awaking from 4:00 AM until 2:00 PM.
We chose a sleep duration of 5 hours (300 minutes). The sleep consists of the REM sleep of a light sleep and the non-REM sleep of a deep sleep, and it appears alternatively at 90 minutes to 120 minutes.23 Considering 90 minutes as 1 cycle, therefore, a length of sleep was 3 cycles (270 minutes) of sleep and preparation for falling asleep was 30 minutes.
We evaluated baseline mobility and arousal level 1 hour before sleep (10:00 PM). Consequently, the participants went to bed at 11:00 PM and woke up at 4:00 AM. After awaking in an early morning, the participants were assessed on the mobility and arousal levels again, and each assessment was also measured 2 hours later (6:00 AM), 6 hours later (10:00 AM), and 10 hours later (2:00 PM), respectively. The Stanford Sleepiness Scale (SSS)24 was chosen to measure the internal state of subjective sleepiness and was measured 7 times at 2-hour intervals starting after awaking at 4:00 AM. Once participants woke up, we asked them to keep awake without sleeping during the study. The assessment order of measurement was random, and the measurement took place in an exhibition hall of the public accommodations.
Fourteen healthy participants (11 women and 3 men; age range, 60-70 years; mean [SD], 64.5 [3.1] years) volunteered to participate in the study (Table 1). Participants were recruited via advertisement in a newsletter from a community center in Akita city. They were living in the community independent in their basic activities of daily living. All participants had no early-morning hypertension or history of falling. If participants had a history of neurological, vestibular, or musculoskeletal impairments, they were excluded. All participants read and signed an informed consent, revealing all details of the study protocol, which had been approved by the ethics committee of Akita University Graduate School of Medicine.
The Timed “Up and Go” test (TUG) evaluates gait and balance. This test is a reliable and valid test for quantifying mobility that is useful in following clinical change over time.25 We followed the method of Podsiadlo and Richardson.25 The participants got up out of a chair, seat height of 40 cm, and walked a distance of 3 m, then turned and walked back to the chair, and sat down again as fast as they could. The participants did not wear regular footwear and did not use any customary walking aid. No physical assistance was given. The time of speed was measured 2 times by using a stopwatch, and the fastest walk speed was adopted.
We used the Functional Reach Test (FRT) measuring instrument, GB-200 (OG-Giken, Japan), and followed a method of Duncan.26 This test is a valid tool for measuring the limits of stability.26 This test is useful for detecting balance impairment, change in balance performance over time.27 The participants were instructed to stand with their feet shoulder distance apart and then raise their arms up, flex the shoulders to 90°, so that it is parallel to the floor. The participants were instructed to reach forward as far as they could without moving their feet and push a lever of device by tip of a finger. The distance of FRT was measured 2 times, and the maximum distance was adopted.
Balance can be defined as the ability to maintain the body's center of gravity over its base of support.28 Force platforms are most commonly used to quantify position of the center of gravity. Force platform balance measurements provide valid information of postural control that can be used to predict falls.27,29 The participants performed a force platform test (Zebris Foot Print for Windows: Inter-Reha, Tokyo, Japan) that recorded ground reaction forces. Force platform data were sampled at 32 Hz and used to calculate the movements of center of pressure. The value of environment area (ENV AREA) was produced by computing center-of-pressure movement during 30 seconds. The test participants were asked to maintain a static upright standing position, Romberg position, for 30 seconds, while closing their eyes. The ENV AREA shows the good function of balance when this environment area is narrow.30 The ENV AREA was measured 2 times, and the narrow area was adopted.
AROUSAL AND SLEEPINESS MEASURES
Arousal level is the state of being awake or reactive to stimuli and it is measured by the critical frequency of fusion (CFF) test. The CFF is believed to reflect central nervous system arousal and vigilance.31,32 The test was performed with a Flicker Fusion electronic device (T.K.K.501c: Takei Scientific Instruments Co, Ltd, Nigata, Japan). Participants were seated comfortably in front of the Flicker Fusion device and rested their forehead on the upper brim of the tube so that both eyes were enclosed by the tube. The participants had to gaze at the flickering light, which was presented automatically with flicker frequencies ranging from 2.0 to 6.0 Hz in the alternating descending and ascending order. In the descending mode, flicker was decreased by 2.0 Hz/s and participants had to press the button when they just started to see a flickering. In the ascending mode, the flicker frequency was gradually increased by 2.0 Hz/s and participants responded when they could no longer detect flickering. The participants had 2 trials. The first trial indicated the alternating descending light and the second trial indicated the alternating ascending light. From the CFF data, 2 trial scores were computed and we adopted the mean of 2 values as CFF. Lower values of CFF indicated that the degree of arousal level was lower.
The self-assessed stage of sleepiness was measured by the SSS.24 The SSS is a quick way to evaluate the level of sleepiness at this moment during the study. It could be of use in pinpointing the circadian rhythms of subject by tracking a subject's sleepiness and wakefulness throughout the day. The SSS was obtained every 2 hours after awaking at 4:00 AM until 4:00 PM. Participants were asked to choose 1 of the 7 statements on the SSS that best described their typical sleepiness at this moment during the study. A result of 4 or less may indicate that you could be suffering from a lack of sleep.
The acquired data were analyzed using SPSS statistical software (IBM SPSS Statistics version 18.0, Chicago, Illinois). The repeated-measures analysis of variance was used to test for significant differences among the measurement times for each assessment. Dunnett's multiple comparisons tests were then applied to compare the different measurement times. The level of statistical significance was set at P < .05.
Fourteen community-dwelling older adults (11 women and 3 men) with a mean age of 64.5 years participated in the study (Table 1). The time differences in the value of TUG, FRT, REC AREA, and CFF tests are reported in Table 2 and the time differences in the value of SSS are reported in Table 3.
A significant difference was found between before sleep and after awaking in TUG test (F4,52 = 5.02 P = .002) (Table 2). Dunnett's multiple comparisons test revealed significant differences between before sleep at 10:00 PM and after awaking at 4:00 AM measures. The speed of TUG test after awaking at 4:00 AM was slower than that before sleep at 10:00 PM.
No significant difference was found in FRT (Table 2). However, the distance of FRT after awaking, that is, from 4:00 AM to 2:00 PM, was shorter than that before sleep at 10:00 PM.
No significant difference between before sleep and after awaking in ENV AREA was found (Table 2). However, the areas of ENV AREA after awaking at 4:00 AM, 6:00 AM, 10:00 AM, and 2:00 PM were larger than that before sleep at 10:00 PM.
No significant difference was found in CFF (Table 2). However, the value of CFF before sleep at 10:00 PM was higher than that at any other time measured.
Significant differences were found between before sleep at 10:00 PM and after awaking in SSS (F2.714, 35.287 = 6.447; P < .001) (Table 3). Dunnett's multiple comparisons test revealed significant differences between at 10:00 PM and after awaking at 4:00 AM (P < .0001), at 6:00 AM (P < .0001), and at 4:00 PM (P = .009).
Timed Up and Go Test After Awaking
The TUG Test has been used to assess mobility in community-dwelling older adults. The TUG test was found to be a sensitive and specific measure for identifying older adults who are prone to fall.33,34 In this study, the speed of TUG test after awaking at 4:00 AM was slower than that before sleep at 10:00 PM and significant difference was found in TUG test between before sleep and after awaking.
The TUG test and muscle power, balance, and walking speed are correlated33,35,36 and central nervous systems and motor systems are related closely. Previous studies have shown that maximal isometric strength is affected by circadian rhythms.37–39 According to Nicolas et al,40 isometric muscular strength was the lowest at 6:00 AM and this muscular strength became the highest between 5:00 PM and 7:00 PM. Furthermore, to produce the same muscular strength, the central nervous system must be activated more in the morning, 6:00 AM, than in the late afternoon, 6:00 PM.38 To maintain skeletal muscle tone and proper motor execution, brain cortex or brainstem should be integrated motor system and sensory system properly.41 Therefore, the decline of functional mobility tends to be caused by the work time when the activity in the biological rhythm is low. Consequently, it seems that the increase in TUG test time just after waking up must have been affected by the decrease in arousal levels and the decrease in functional mobility after waking up. To increase fall prevention in older adults in the early morning hours, it is important to evaluate how arousal levels directly affect TUG test and if an interaction effect between TUG test and arousal levels is available.
Functional Reach Test After Awaking
Functional Reach Test was designed as an evaluation of anterior and posterior dynamic postural stability. It is commonly used in research to assess balance ability and to predict the risk of falling.42,43 The cutoff value of FRT was suggested as 220 to 254 mm. Therefore, it is important to evaluate how arousal levels directly affect FRT. In this study, no significant difference was found between before sleep and after awaking in the FRT.
A study of postural balance and the risk of falling in older adults revealed that control of lateral stability may be an important area for fall preventive interventions.44 Induced anterior movement task performances, therefore, were not hard tasks and it did not reflect the shorter FRT distance even though older adults woke up at an early morning hours.
Postural Sway (ENV AREA) After Awaking
The ability of upright standing stability is assessed by the postural sway. Postural sway measurements have been used as predictors of falls among older adults.29 To predict falls, therefore, it is important to evaluate how arousal levels affect postural sway and if there is an interaction affect postural sway and arousal levels in the early morning hours. In our study, no relationship was found between EA LNG/EA before sleep and after awaking even though arousal level was decreased after awaking at 4:00 AM.
Previous studies have shown that the effect of sleep shortage on postural sways is correlated to a decrease in alertness levels and deprivation of sleep affected postural sway and cognitive performance.20,45,46 After a shortage of sleep, the bilateral posterior-parietal prefrontal areas are less activated prompting lower levels of activity in the central executive system and the activity of neuron decreases mainly in the corticothalamic network that mediated attention and higher-order cognitive performance.45 However, in our study, sleeping for 5 hours before waking up did not affect higher levels of brain function and it did not affect postural stability. Consequently, the load task of standing was also not difficult enough to maintain postural stability.
Critical Frequency of Fusion After Awaking
The value of CFF reflects the activity of the cerebral cortex and this has been used for the evaluation index of arousal levels. It is important to evaluate how awaking in the early hours directly affects arousal level. In this study, the value of CFF after awaking decreased gradually in each assessment time.
Because the CFF reflects central nervous system arousal, the lower value of CFF indicates a reduction in the degree of arousal levels. Therefore, the value of CFF in this study indicated a tendency of decreased arousal levels. However, significant relationships did not exist among assessment times. A previous study reported that frontal lobe function is affected by sleep inertia, but no significant difference was found when performance was compared before and after sleep.47 Therefore, additional research is needed to better understand the relationship between sleep and arousal level, attention, and the function of frontal lobe.
Stanford Sleepiness Scale After Awaking
The SSS is a quick way to evaluate the level of sleepiness at this moment during the study. To evaluate the level of sleepiness after waking, it is important to assess the severity of daytime sleepiness at a specific time. Significant differences were found between before sleep at 10:00 PM and after awaking in our study. This study revealed significant differences between sleep at 10:00 PM and after waking at 4:00 AM, at 6:00 AM, and at 4:00 PM, respectively (Table 4).
Usually, people have 2 peak times at around 9:00 AM and 9:00 PM with a low time at around 3:00 PM. Recent research indicates the relationship between subjective sleepiness and objective performance. Dorrian et al48 found moderate to high correlations between subjective sleepiness and objective performances. They also found that objective performance deteriorated at a corresponding rate to subjective sleepiness rating.48 Furthermore, those relationships were also significantly related under increasing sleepiness levels.48 Therefore, it seems that the increase in sleepiness just after waking up must have affected the decrease in arousal levels and the decrease in functional mobility after waking up.
The decrease in arousal levels may affect mobility in early morning hours and could be a contributing factor in the incidences of falls for older adults. The awareness of the degree of arousal levels may increase fall prevention in older adults in the early morning hours. To more comprehensively understand the risk factors causing falls in older adults, arousal needs to be further examined.
1. Health and Welfare Statistics Association. Annual statistical report of national health conditions. J Health Welfare Stat. 2008;55:47–58.
2. Sise RG, Calvo RY, Spain DA, Weiser TG, Staudenmayer KL. The epidemiology of trauma-related mortality in the United States from 2002 to 2010. J Trauma Acute Care Surg. 2014;76(4):913–919.
3. Tinetti ME, Williams CS. Falls, injuries due to falls, and the risk of admission to a nursing home. N Engl J Med. 1997;337(18):1279–1284.
4. Schwendimann R, Buhler H, De Geest S, Milisen K. Falls and consequent injuries in hospitalized patients: effects of an interdisciplinary falls prevention program. BMC Health Serv Res. 2006;6:69.
5. Fischer ID, Krauss MJ, Dunagan WC, et al. Patterns and predictors of inpatient falls and fall-related injuries in a large academic hospital. Infect Control Hosp Epidemiol. 2005;26(10):822–827.
6. Giles LC, Whitehead CH, Jeffers L, McErlean B, Thompson D, Crotty M. Falls in hospitalized patients: can nursing information systems data predict falls? Comput Inform Nurs. 2006;24(3):167–172.
7. Zijlstra GAR, Haastregt JCMV, Rossum EV, Eijk JTMV, Kempen GIJM. Interventions to reduce fear of falling in community-living older people: a systematic review. J Am Geriatr Soc. 2007;55(4):603–615.
8. Daubney ME, Culham EG. Lower-extremity muscle force and balance performance in adults aged 65 years and older. Phys Ther. 1994;79(12):1177–1185.
9. Wurzer B, Waters DL, Hale LA, Leon de La Barra S. Long-term participation in peer-led fall prevention classes predicts lower fall incidence. Arch Phys Med Rehabil. 2014;95(6):1060–1066.
10. Rugelj D. The effect of functional balance training in frail nursing home residents. Arch Gerontol Geriatr. 2010;50(2):192–197.
11. Sherrington C, Whitney JC, Lord SR, Herbert RD, Cumming RG, Close JC. Effective exercise for the prevention of falls: a systematic review and meta-analysis. J Am Geriatr Soc. 2008;56(12):2234–2243.
12. Graafmans WC, Ooms ME, Hofstee HMA, Bezemer PD, Bouter LM, Lips P. Falls in the elderly: a prospective study of risk factors and risk profiles. Am J Epidemiol. 1996;143(11):1129–1136.
13. Tinetti ME. Preventing falls in elderly persons. N Engl J Med. 2003;348(1):42–49.
14. Moreland JD, Richardson JA, Goldsmith CH, Class CM. Muscle weakness and falls in older adults: a systematic review and meta-analysis. J Am Geriatr Soc. 2004;52(7):1121–1129.
15. Gribble PA, Tucker WS, White PA. Time-of-day influences on static and dynamic. J Athl Train. 2007;42(1):35–41.
16. Winget CM, DeRoshia CW, Holley DC. Circadian rhythms and athletic performance. Med Sci Sports Exerc. 1985;17(5):498–516
17. Hagino H, Katagiri H, Okano T, Yamamoto K, Teshima R. Increasing incidence of hip fracture in Tottori Prefecture, Japan: trend from 1986 to 2001. Osteoporos Int. 2005;16(12):1963–1968.
18. Morris EV, Isaacs B. The prevention of falls in a geriatric hospital. Age Aging. 1980;9(3):181–185.
19. Cappaert T. Time of day effect on athletic performance: an update. J Strength Cond Res. 1999;13(4):412–421.
20. Liu Y, Higuchi S, Motohashi Y. Changes in postural sway during a period of sustained wakefulness in male adults. Occup Med. 2001;51(8):490–495.
21. Schlesinger A, Redfern MS, Dahl RE, Jennings JR. Postural control, attention and sleep deprivation. Neuroreport. 1998;5.9(1):49–52.
22. Uimonen S, Laitakari K, Bloigu R, Sorri M. The repeatability of posturographic measurements and the effects of sleep deprivation. J Vestib Res. 1994;4(1):29–36.
23. Honma K. Biological rhythms and sleep. Nihon Rinsho. 2012;70(7):1090–1093.
24. Hoddes E, Zarcone V, Smythe H, Phillips R, Dement W. Quantification of sleepiness: a new approach. Psychophysiology. 1973;10(4):431–436.
25. Podsiadlo D, Richardson. The Timed “Up and Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39(2):142–148.
26. Duncan PW, Weiner DK, Chandler J, Studenski S. Functional reach: a new clinical measure of balance. J Gerontol. 1990;45(6):M192–M197.
27. Berg K, Norman KE. Functional assessment of balance and gait. Clin Geriatr Med. 2009;12(4):705–723.
28. Pajala S, Era P, Koskenvuo M, Kaprio J, Törmäkangas T, Rantanen T. Force platform balance measures as predictors of indoor and outdoor falls in community-dwelling women aged 63-76 years. J Gerontol A Biol Sci Med Sci. 2008;63(2):171–178.
29. Piirtola M, Era P. Force platform measurements as predictors of falls among older people—a review. Gerontology. 2006;52(1):1–16.
30. Bauer C, Gröger I, Rupprecht R, Gassmann KG. Intrasession reliability of force platform parameters in community-dwelling older adults. Arch Phys Med Rehabil. 2008;89(10):1977–1982.
31. Curran S, Hindmarch I, Wattis JP, Shillingford C. Critical flicker fusion in normal elderly subjects: a cross-sectional community study. Curr Psychol Res Rev. 1990;9(1):25–34.
32. Curran S, Wattis J. Critical Flicker Fusion threshold: a useful research tool in patients with Alzheimer's disease. Human Psychopharmacol. 1998;13(5):337–355
33. Shumway-Cook A, Brauer S, Woollacott M. Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Phys Ther. 2000;80(9):896–903.
34. Thrane G, Joakimsen RM, Thornquist E. The association between Timed Up and Go Test and history of falls: The Tromso study. BMC Geriatr. 2007;7:1–7.
35. Samson MM, Meeuwsen IB, Crowe A, Dessens JA, Duursma SA, Verhaar HJ. Relationships between physical performance measures, age, height, and body weight in healthy adults. Age Aging. 2000;29(3):235–242.
36. Sieri T, Beretta G. Fall risk assessment in very old males and females living in nursing homes. Disabil Rehabil. 2004;26(12):718–723.
37. Atkinson G, Coldwells A, Reilly T, Waterhouse J. A comparison of circadian rhythms in work performance between physically active and inactive subjects. Ergonomics. 1993;36(1–3):273–281.
38. Gauthier A, Davenne D, Martin A, Cometti G, Van Hoecke J. Diurnal rhythm of the muscular performance of elbow flexors during isometric contractions. Chronobiol Int. 1996;13(2):135–146.
39. Guette M, Gondin J, Martin A. Time-of-day effect on the torque and neuromuscular properties of dominant and non-dominant quadriceps femoris. Chronobiol Int. 2005;22(3):541–548.
40. Nicolas A, Gauthier A, Trouillet J, Davenne D. The influence of circadian rhythm during a sustained submaximal exercise and on recovery process. J Electromyogr Kinesiol. 2008;18(2):284–290.
41. Takakusaki K, Habaguchi T, Ohtinata-Sugimoto J, Saitoh K, Sakamoto T. Basal ganglia efferents to the brainstem centers controlling postural muscle tone and locomotion: a new concept for understanding motor disorders in basal ganglia dysfunction. Neuroscience. 2003;119(1):293–308.
42. Duncan PW, Studenski S, Chandler J, Prescott B. Functional reach: predictive validity in a sample of elderly male veterans. J Gerontol. 1992;47(3):M93–M98.
43. Rockwood K, Awalt E, Carver D, MacKnight C. Feasibility and measurement properties of the Functional Reach and Timed Up and Go tests in the Canadian study of health and aging. J Gerontol A Biol Sci Med Sci. 2000;55(2):M70–M73.
44. Maki BE, Holliday PJ, Topper AK. A prospective study of postural balance and risk of falling an ambulatory and independent elderly population. J Gerontol Med Sci. 1994;49(2):M72–M84.
45. Thomas M, Sing H, Belenky G, et al. Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24h of sleep deprivation on waking human regional brain activity. J Sleep Res. 2000;9(4):335–352.
46. Fabbri M, Martoni M, JosèEsposito M, Brighetti G, Natale V. Postural control after a night without sleep. Neuropsychologia. 2006;44(12):2520–2525.
47. Matchock RL, Mordkoff JT. Visual attention, reaction time, and self-reported alertness upon awakening from sleep bouts of varying lengths. Exp Brain Res. 2007;178(2):228–239.
48. Dorrian J, Roach GD, Fletcher A, Dawason D. Simulated train diving: fatigue, self-awareness and cognitive disengagement. Appl Ergon. 2007;38(2):155–166.
Keywords:Copyright © 2016 the Section on Geriatrics of the American Physical Therapy Association
arousal level; early morning; physical function