Gender- and Age-Related Differences in Sleep Determined by Home-Recorded Sleep Logs and Actimetry From 400 Adults

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1 Sleep. 18(2): American Sleep Disorders Association and Sleep Research Society Gender- and Age-Related Differences in Sleep Determined by Home-Recorded Sleep Logs and Actimetry From 400 Adults A. Reyner and J. A. Home Sleep Research Laboratory, Loughborough University, Leicestershire, u.k. Summary: Home-based sleep was monitored by morning logs and wrist actimetry for 15 nights in a sample of 400 adults (20-70 years old; 211 female, 189 male; one per household). Subjects on sleep-enhancing medications and/or whose sleep was severely disturbed by illness were excluded. Subjects were grouped into age bands: ("young" = years, "mid-aged" = years and "older" = years). Women retired to bed and fell asleep earlier than men. Men and women woke up earlier with increasing age. Sleep period time was markedly longer for women. Most reported awakenings were < 5 minutes. Women reported more awakenings, more total time spent awake during the night and poorer sleep quality; all these findings were most evident in the older women, who also took longer to fall asleep than any other group. Although these age effects are consistent with those reported elsewhere, the gender effects, some of which are much stronger than the age effects, have not been so evident before. Large-scale measurements of sleep in the general population have tended to use surveys involving oneoff questionnaires (e.g. 1-3). The method falls short of the electroencephalogram (EEG) in validity, but it is inexpensive and allows for testing many subjects, whereas the converse applies to the EEG. Between these extremes lie the more reliable subjective device of repeated morning sleep logs (SLs) and the more objective actimeters. The latter are being used increasingly in sleep research (4-6). The largest survey using repeated SLs was conducted by Tune (7,8) 28 years ago in the u.k. Five hundred nine men and women (20-79 years of age) kept SLs for about 50 nights. He found that daily sleep declined by about 27 minutes from 20 to 59 years of age, and then rose; the time offalling asleep became earlier with increasing age, and duration of awakenings increased with age (the latter increased in number for those over 50 years, especially in women). Fifty to seventy-nine year-olds went to sleep and awoke earlier than the rest. Tune (8) found no substantial gender differences in his population. A methodological problem was that all times were logged only to the nearest half hour. As the Accepted for publication September Address correspondence and reprint requests to A. Reyner, Sleep Research Laboratory, Department of Human Sciences, Loughborough University, Leicestershire LEll 3TU, U.K. work was undertaken a generation ago, sleep habits may have changed. As part of a large field study originally designed to assess the effects of aircraft noise on sleep [reported elsewhere (9)], which utilized SLs, actimetry and to a lesser extent the EEG, we were able to examine the general sleep habits of 400 subjects years of age, sleeping at home, for 15 nights each. Their sleep can be viewed as "normal", as only 1.2% of aircraft noises (most were not loud) caused a sleep disturbance shown by actimetry or EEG, and in only 5.8% of nights was there a subjective report of an awakening due to this noise (9). This contrasts with the more substantive and idiosyncratic effects of small children, a need to go to the toilet and the bedpartner (10). We present a contemporary guide to adult sleep habits in the adult population. METHODS Subjects. Subjects lived adjacent to Heathrow, Gatwick, Stansted and Manchester airports. At Heathrow and Gatwick nighttime flying is restricted. Stansted is a quiet airport with few night flights. Details of the sites are given elsewhere (9), but in summary: There were two survey sites per airport, with 50 subjects per site. Sixty percent of subjects had been living where they were for > 5 years, and the remainder between 6 months and 5 years. They were chosen from an initial 127

2 128 L. A. REYNER AND J. A. HORNE TABLE 1. Subject selection: age and gender profiles for each site No. Volunteers years years years Total addresses SS Site a visited b I'view Ie I'view 2 d Final' Ff W F M F M F M I Total 3,896 1, Age group totals Age group (%) a Sites 1 and 3 = Heathrow; sites 2 and 4 = Gatwick; sites 5 and 6 = Manchester; sites 7 and 8 = Stansted. b No. addresses visited = doors knocked on initially. e SS I'view = interviews successfully obtained (one per household). d I'view 2 = those successfully interviewed further about sleep habits., Final = those volunteering for sleep study and meeting the selection criteria. f F, M = female, male. door-to-door questionnaire survey on environmental living conditions (10,11). At each of the eight sites about 200 adults were interviewed initially (n = 1,638), one per household. Seventy-five percent of the subjects lived with a partner, 14% were single and 11% separated. By socioeconomic class they were equally (50%) divided between two categories: professional and skilled and semi-skilled and manual. Forty-five percent of the households had one or more children < 16 years old. These social statistics are typical of the U.K. population (11). Subjects were then asked if they could be interviewed at a later date about their sleep habits, and 971 agreed. At that second interview they were asked to volunteer for a sleep study assessing general sleep habits. Their data were then scrutinized for potential subjects who were: a) available during the measurement period (many were not available); b) not hearing impaired; c) not suffering from nighttime illness seriously disrupting sleep; and d) not taking sleep-promoting medications or having a large alcohol intake. Of the respondents, 4.4% were currently on hypnotics and were excluded because we wished to study nonmedicated sleep. Of the remainder, 2% were excluded because of (physical) illness-impaired sleep. All other nonmedicated self-diagnosed "poor sleepers" were included. There were 447 people who were willing to be subjects, were available at the specific measurement period and met the other criteria. Four hundred of them were selected randomly. Table 1 gives a site-byage-gender breakdown of subject selection. Subjects were grouped in the following age ranges: "young" = years, "mid-age" = years and "older" = years. They were paid $8 per night and were not told about the aircraft noise aspect of the study until the end. Sleep. Vol. 18. No Daily sleep logs. Daily sleep logs were obtained for 95.3% of the 6,000 subject nights. Each morning, subjects had to report times of getting into bed, lights out, falling asleep, final waking up and getting up; number and times of interim awakenings; alertness on morning awakening (5-point scale); and sleep quality (5-point scale). Actimeters. The "Swiss-type" (Gaehwiler Electronics, Hombrectikon) actimeters were worn on 97.2% of the 6,000 nights. Data (actigrams) were logged in 30- second epochs and filtered into binary form to register movement or nil movement for each epoch. Sleep onset, estimated from another filter derived from a sample of 178 simultaneously recorded sleep EEGs (9), was equivalent to the start of a continuous period of stage 2 sleep or deeper after lights out (9,12). All data were averaged over the 15-night measurement period. RESULTS No significant differences were found between sites for any of the following parameters. Time of getting into bed- "Bedtime" (SLs only). When analyzed by ANOV A, a significant gender effect was seen [F = 5.4 (1,394); p < 0.02], with women reporting an II-minute earlier bedtime (2317 hours, SE = 3.2 minutes) than men (2328 hours, SE = 3.7 minutes). There was no other significant effect. Time of lights out (SLs only). There were no significant effects for age group or gender, although older women tended to have an earlier lights out time. Sleep onset latency (lights out to sleep onset, SLs only). Actimetry cannot indicate when subjects attempt to go to sleep. SLs showed significant effects of age group [F = 4.14 (2,394); p < 0.017], gender [F =

3 GENDER- AND AGE-RELATED DIFFERENCES IN SLEEP 129 2S 'il 20! i'j.~ IS Mean Sleep Onset Latency from Sleep Logs --C--Males ---t:r- Females D!ltl! from Shl~12 Logs: Males 20-34y IS.61 I 3S-49y SO S2 Females 20-34y S-49y IS.2 SO-70y <1..J ~ 10 ~ Vi S o ~ 20-34y 35-49y Age Group SO-70y FIG. 1. Mean sleep onset latency from sleep logs (1,394); p < 0.001], and a significant age by gender interaction [F = 4.87 (2,394); p < 0.008]. Tukey's post hoc comparisons for p < 0.05 indicated no significant difference between the age bands for men, but significant differences for the women between the young versus older, and mid-age versus older groups. Overall, the older women reported taking significantly longer to fall asleep than did all other groups (Fig. 1). Time of sleep onset. This was measured by SL and actimetry (after applying the sleep onset algorithm). Sleep log data averaged within subjects revealed significant gender [F = 4.31 (1,394); p < 0.038] and age [F = 4.16 (2,394); p < 0.016] effects, but no interaction (Fig. 2). Tukey tests showed a significantly (p < 0.05) earlier sleep onset time for men in the younger group versus mid-age and older groups. Overall, women estimated falling asleep 7 minutes earlier (2346 hours, SE = 2.4 minutes) than men (2353 hours, SE = 2.3 minutes). With actimetry (Fig. 2) there were also significant effects of gender [F = 7.54 (1,394); p < 0.006] and age [F = 3.44 (2,394); p < 0.033], but no interaction effect. Tukey tests revealed no specific effects, although the trend was for women to fall asleep earlier than men, and for sleep onset time to become later with increasing age. Time of sleep onset, estimated by actimetry and SL, gave an identical mean value of 2349 hours across all subjects. However, it can be seen from Fig. 2 that the actual times differed according to the two methods, with the age trends tending to be reversed. Older subjects thought that they fell asleep later than they appeared to from actimeters, whereas it was the converse for young men. Wake-up time (SLs only). This is seen in Fig. 3. The overall wake-up time was 0702 hours (SE = 2.9 minutes). There was a significant effect of age [F = (2,394); p < 0.001] and there was an age by gender interaction [F = 5.59 (2,394); p < 0.001]. Tukey tests (p < 0.05) showed young men waking up significantly later than older men and a significant gender difference between the mid-age groups only, with men waking up significantly earlier than women. Get-up (arising) time (SLs only). These findings showed similar characteristics to those of wake-up time. There was a significant age effect [F = (2,394); p < 0.001] and an age by gender interaction [F = 5.01 (2,394); p < 0.007]. Tukey tests (p < 0.05) showed that young men arose significantly later (0753 hours; SE = 6.9 minutes) than did the mid-age (0706 hours; SE = 6.7 minutes) and older men (0713 hours; SE = 7.3 minutes), and there was a significant difference in get-up time between mid-age men (op cit.) and women (0734 hours; SE = 5.0 minutes). Time in bedfrom waking to arising (SLs only). The mean overall value for time in bed was 23 minutes (SE = 0.8 minutes). There was a significant age effect [F = Sleep. Vol. 18. No

4 130 L. A. REYNER AND J. A. HORNE Data from Sleep Logs: Mean Time of Sleep Onset from Sleep Logs and Actimetry Males 20-34y 23: y 23: :59 4 0:13 Females 23: : :52 4 0:06 Actimelly Data: 123'58 ~. --c-- Males-Sleep Log Males 0:02 8 0: Females-Sleep Log 23:45 8 f-< 23'51 Females 20-34y 23:45 7 ~ Malcs-Actimelry 35-49y 23: y 23: x- Females-Actimelry ] 23:44 en 23:37 23: ~----_+_--- I 20 34y 35 49y Age Group 50-7Oy FIG. 2. Mean times of sleep onset from sleep logs and actimetry (2,394); p < 0.001]. A Tukey test (p < 0.001) showed that members of the older group lay in bed longer (26 minutes; SE = 2.2 minutes) than the young (21 minutes; SE = 1.0 minute) and mid-age (21 minutes; SE = 1.0 minute) groups. Sleep period time (sleep onset until morning awakening). Data from SLs showed significant age [F = (2,394); p < 0.001], gender [F = 6.21 (1,394); p < 0.013] and interaction effects [F = 5.47 (2,394); p < 0.005]. Tukey tests (p < 0.05) indicated that young men slept significantly longer than mid-age and older men, and that mid-age women slept significantly longer than their male counterparts (see Fig. 4). Reported awakenings during sleep (SLs only). Out of the 5,716 nights when the SL was completed, 3,546 contained a report of at least one awakening (Fig. 5). A total of 6,457 awakenings were recorded, of which 4,751 attributed a cause (e.g. children, worries, etc.) and 1,706 were "don't know". Overall, women reported more awakenings [average 1.2 per night vs for men: F = (1,5710); p < 0.001], and mean awakenings per subject increased with age for both sexes [F = 80.2 (2,5710); p < 0.001]. Tukey tests (p < 0.05) showed that the older group reported significantly more awakenings (average 1.3 per night) than did the young (average 0.9) and midage (average 1.0) groups, and that women in all age groups had significantly more awakenings than men. Excluding "don't know", the most frequent overall attributed causes were "toilet" and "children" for the older men and young women, respectively (9). Disturbance due to the bedpartner is another major cause of awakening (10). The SL question concerning duration of awakening is open ended. Most reports on the estimated duration of awakenings were < 5 minutes. There were significant effects of gender [F = 70.1 (1,5710); p < 0.001] and age [F= 63.8 (2,5710); p < 0.001]. Tukey tests showed that for all age groups, women reported longer total time awake than men (12.7 minutes; SE = 1.7 vs. 8.2 minutes; SE = 1.4 minutes) and both men and women in the older group were awake longer (18.0 minutes; SE = 3.0 minutes) during the night than young men and women (12.1 minutes; SE = 2.4 minutes). Sleep quality (SL). The five-point self-rated sleep quality scale in the SL revealed that on 10.3% of the mornings, subjects claimed to have slept "rather badly" and on 1.4% of mornings, "extremely badly". Males in the young, mid- and older age groups had average scale values of 2.51, 2.57 and 2.59, respectively, and for women values were 2.53, 2.63 and 2.64, respectively. (Sleep quality scale values range from 1 = Extremely well to 5 = Extremely badly.) There was a significant age effect in sleep quality [F= 6.0 (2,5710); p < 0.003] and a nonsignificant trend for women to report poorer sleep quality. Tukey tests (p < 0.05) showed that the mean sleep quality rating for the young group was significantly better than for the older groups. Downloaded Sleep. from Vol No

5 GENDER- AND AGE-RELATED DIFFERENCES IN SLEEP 131 7:41 T 7:27 Mean Wake Up Time from Sleep Logs Datil from SIIlIl!! Lggs: Males 20-34y 7: y 6: y 6:43 6 Females 20-34y 7: y 7: y 6:58 6 ]' 7:12 ~ Q).S 6' ;3- Q) ~ 6: Males-Sleep Log ---c:r--- Females-Sleep Log 6:29 6: \ y 35-49y 50-70y Age Group FIG. 3. Mean wake-up times from sleep logs. Sleep Period Time as measured by Sleep Log 7:55 I 7:41 Diltil frqm SleeQ LogS: Males 20-34y 35-49y Females 20-34y 35-49y 50-70y 7: : :44 9 7:37 6 7:34 9 7:05 9 7:27 ]' ~ 7:12 3' ~ 6:58 j 6: Males-Sleep Log ---c:r--- Females-Sleep Log 6:29 6: y 35-49y 50-70y Age Group FIG. 4. Sleep period time from sleep logs. Sleep, Vol. 18, No.2, 1995

6 132 L. A. REYNER AND J. A. HORNE Self-reported awakenings (as a percentage of total awakenings) by sex and age group (6457 reported awakenings) Women 20-34y Women 35-49y ---fr-- Women 50-70y --- Men 20-34y ---- Men 35-49y Men 50-70y 0 ~ " '8 " s:: "... '" '" u 1-< ~ ~ ~ ~ " :E 1-< ~ -'C u " ~ 0 ~ ]" ~ -a> 0 ] "0 0 :3... ct:: " ~ '" s:: - Cause of Reported Awakening FIG. 5. Self-reported awakenings as recorded by sleep logs. Sleep quality can also be gauged from a second fivepoint scale in the SL, relating to the level of feeling refreshed or tired after having been awake for 15 minutes. Sleep quality values range from 1 = Very refreshed to 5 = Very tired. Males in the young, midand older age groups have average values of2.99, 2.85 and 2.70, respectively, and women score 3.02, 2.89 and 2.84, respectively. Again, there were significant effects of age group [F= 33.8 (2,5710); p < 0.001] and gender [F = 7.7 (1,5710); p < 0.006], but no interaction. Tukey tests (p < 0.05) indicated that subjects in the young groups felt significantly more tired 15 minutes after awakening than those in the mid-age groups, who in tum felt significantly more tired than the older groups. Women in the mid-age and older groups also felt significantly more tired and less refreshed 15 minutes after awakening than did men from the same age groups. Sleep quality (actimetry). Previous research has shown that movement during sleep as measured by actimetry is strongly related to sleep log ratings of subjective sleep quality (9). When the number of 30-second epochs containing movement are divided by sleep period time, there was a significant decline in average movement with age [F = (2,5678); p < 0.001], with men having more movement than women [F = (1,5678); p < 0.001]. There was also an interaction [F = (2,5678); p < 0.001], which can be seen in Fig. 6. Tukey tests (p < 0.05) showed that the incidence of movement is significantly reduced at each age level, and that for the middle age group, men had more movement. Also, all three women's groups had significantly different amounts of movement from each other. DISCUSSION AND CONCLUSIONS This study gives a general overview of sleep and sleep habits in a representative sample of the U.K. population in terms of age and gender. The sample was also typical in terms of socioeconomic status, marital circumstance and those subjects with children < 16 years of age (11). It was not our intention to break down our sample further into those subjects whose sleep might be particularly affected by external constraints such as employment, retirement and having young children in the house, as these categories are not straightforward in relation to the possible impact on sleep. For example, subjects could be unemployed because they were raising children or caring for relatives and still be subject to a daily routine. Children in the household may or may not affect the sleep of parents, depending on how much attention they require at night. Other studies describing "normal" sleep habits (7,8,13,14) have not attempted to consider these intervening variables and have simply described their population in terms of age and gender. Women tended to go to bed and fall asleep earlier, Downloaded Sleep. from Vol. 18, No.2, 1995

7 GENDER- AND AGE-RELATED DIFFERENCES IN SLEEP 133 Mean incidence (%) per hour of sleep of epochs containing movements DatB frqm Actigra1!hy; Mean SE Males 20-34y y y Females 20-34y S-49y Oy <>-- Males -i>-- Females ~ 20-34y 35-49y Age group 50-70y FIG. 6. Average number of 30-second epochs containing movement per hour of sleep. claimed to sleep longer, but had more awakenings. They had longer interim wakefulness, poorer sleep quality and felt more tired shortly after morning awakening. Most of these findings were particularly evident in the older women, who also reported significantly longer to fall asleep times. Both men and women woke up significantly earlier with increasing age. The time between waking up and getting up was constant between young and mid-age groups, with both men and women arising approximately 20 minutes after waking up (older subjects took about 10 minutes longer). Although actimetry and SLs showed different trends for sleep onset time with respect to aging, the actual time difference between the methods was small. The young men had a later sleep onset time as judged by actimetry, compared with their SL reports. The reverse was the case for mid-age men, who, by actimetry, seemed to fall asleep sooner than they claimed. It is possible that this perception of sleep onset changes with age, which may account for the contrasts found in determining sleep onset by SL versus actimetry. It is also possible that actimetry does not discriminate entirely between very relaxed wakefulness and sleep, especially in the elderly, who may lie awake at night for long periods; further research is needed in this area. Interestingly, with respect to sleep onset time, which is later when judged by actimetry rather than sleep log, it must be noted that it is our actimetry data, and not our SL findings which support those of Tune (7,8). However, 25 years ago, when Tune conducted his investigation, people did indeed go to sleep earlier (e.g. because there were fewer televisions per U.K. household and broadcasting ended earlier at night). In which case, it would be our SL data that correspond with those of Tune. The actimetry data (the more objective measure of sleep quality) show similar trends to subjective feelings of refreshment or tiredness when judged 15 minutes after awakening, rather than sleep quality judged immediately on awakening. The data also show that the younger age groups showed more movement in their sleep, claimed good sleep quality immediately on awakening, but felt relatively tired 15 minutes later. This is in contrast to the older age groups, who showed reduced movement in their sleep, reported bad sleep quality on awakening, but then felt refreshed 15 minutes later. The group that showed unusual patterns in this was the women in the older age group. This group showed more movement and felt more tired 15 minutes after awakening than would be expected. Our findings regarding awakenings showed similar trends to those reported previously. The data concerning self-reported awakenings support those of Tune (7) and of EEG studies, which indicated increasing awak- Sleep. Vol. 18. No

8 134 L. A. REYNER AND J. A. HORNE enings during the night associated with increasing age (13) and showed that, once awakened, older subjects take longer to return to sleep (14). However, there were gender differences not only in the number and duration of awakenings, but also in the cause of awakenings, with women being woken up by children more than men. This was not apparent in Tune's studies. Our aging effects are not substantial, and we would agree with Tune that older subjects cannot be said to have poorer sleep than our young subjects. Such a conclusion has also been drawn by Bliwise (15), who noted in his review that the main reason sleep may appear to deteriorate with age is poor health. If this factor is partialled out, then there is no such aging effect. Most of our subjects were in good health. However, it should be remembered that we did exclude a small minority of potential subjects who took hypnotics and whose sleep was disturbed by pain (see Methods); thus we had some bias here. Many of these age trends are consistent with those found by other researchers in addition to Tune. However, our gender effects, some of which were stronger than the age effects, can be found in both the subjective and especially the objective measurements of sleep. This gender effect has not been so evident in most other studies (which also had smaller sample sizes). Acknowledgements: We thank the following people for their help with data collection and analysis: Ian Diamond, Ben Emm, Ken Hume, Ceril Jones, Heather Lomas, John Ollerhead, Francesca Pankhurst and Alan Woodley. This article contains some data that were collected as part of a field study of aircraft noise and sleep disturbance and was financed by the U.K. Department of Transport. REFERENCES 1. Webb WB. Sleep characteristics of human subjects. Bull Br Psychol Soc 1965;18: McGhie A, Russel SM. The subjective assessment of normal sleep patterns. J Ment Sci 1962;108: Zepelin HA. Life span perspective on sleep. In: A Mayes, ed. Sleep mechanisms and/unctions. London: Van Nostrand, 1983: Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin Jc. Automatic sleep/wake identification from wrist activity. Sleep 1992; 15: Middlekoop HAM, van Hiltern RJ, Kramer CGS, Kamphuisen HAC. Actigraphically recorded motor activity and immobility across sleep cycles. J Sleep Res 1992;2: Tryon WW. Activity measurement in psychology and medicine. New York: Plenum Press, Tune GS. Sleep and wakefulness in 509 normal human adults. Br J Med PsychoI1969;42: Tune GS. The influence of age and temperament on the adult human sleep-wakefulness pattern. Br J PsychoI1969;60: Home JA, Pankhurst FP, Reyner LA, Hume K, Diamond I. A field study of sleep disturbance: effects of aircraft noise and other factors on 5,742 nights of actimetrically monitored sleep in a large subject sample. Sleep 1994;17: Pankhurst FL, Home JA. The influence of bed-partners on movement during sleep. Sleep 1994; 17 (in press). II. Diamond I, Jones C, MacKean J, Ollerhead J. Sleep disturbance due to aircraft noise: social survey report. Southampton University U.K., Department of Social Statistics, Report SRSG(92) 8, Ollerhead JB, et al. Report of a field study of aircraft noise and sleep disturbance. U.K. Department of Transport, Williams RL, Karacan I, Hursch CJ. Electroencephalography (EEG) o/human sleep: clinical applications. New York: Wiley, Webb WB, Campbell SS. Awakenings and the return to sleep in an older population. Sleep 1980;3: Bliwise DL. Sleep in normal ageing and dementia. Sleep 1993; 16: Downloaded Sleep, Vol. from 18, No.2, 1995