Stability and change in daytime and nighttime sleep in children attending daycare

Abstract

Many young children experience insufficient or poor quality sleep, which may have implications for adjustment and cognitive performance. This study tested group-level changes and rank-order stability in both daytime and nighttime sleep parameters over a six-month period, from fall to spring, among children receiving high-quality, center-based daycare. A total of 68 preschoolers (54% girls; M _age = 3.80 years, SD = .68) participated. Sleep was assessed via actigraphy for seven days and nights; sleep duration (actual sleep minutes) and quality parameters were derived. Analyses of group-level changes indicated that children’s daytime and nighttime sleep duration did not change significantly from fall to spring. Nighttime sleep quality showed significant improvement, however, such that children had higher sleep efficiency in the spring than in the fall. Rank-order stability in both nighttime and daytime measures of sleep duration and quality was moderate, and stability in daytime sleep quality was low. Results add to a sparse literature examining stability in sleep parameters in young children using actigraphy.

Keywords

Preschool sleep actigraphy stability

Sleep disruptions (reduced duration, night awakenings) are common during early childhood (Byars, Yolton, Rausch, Lanphear, & Beebe, 2012). There is a growing literature concerning the ramifications of sleep problems for young children’s social and cognitive development (Bernier, Carlson, Bordeleau, & Carrier, 2010; Smedje, Broman, & Hetta, 2001). Yet, few published reports using objective sleep assessments have described typical sleep–wake patterns across a year of childcare. This gap in understanding is significant given that more than 75% of American children between the ages of 3 and 5 who receive out-of-home care are enrolled in center-based daycare (Department of Health and Human Services, 2016b) and spend, on average, 40 hours in center care each week (Department of Health and Human Services, 2016a). Children’s sleep patterning across a year of structured care may differ from sleep patterns among community samples of children who do not attend daycare. In the present study, we examined group-level change and rank-order stability in daytime and nighttime sleep–wake patterns over a six-month period (from fall to spring) for children attending a high-quality, center-based early education program.

Only a handful of studies have used actigraphy in comparison to parent report for the examination of short-term group-level change and rank-order stability of sleep–wake patterns among preschool-aged children. Although parent report has provided key information towards understanding children’s sleep, assessment of children’s sleep using actigraphy has some advantages, including 24-hour monitoring of sleep and detection of awakenings that may be missed by parents or daycare providers (Sadeh, 2015). In a typically developing sample (M _age = 41 months), Anders and colleagues (2011) found that children’s actigraph-assessed 24-hr sleep duration declined and nighttime sleep quality improved (i.e. greater sleep efficiency; fewer and shorter wake periods) over a six-month period. Staples, Bates, and Petersen (2015) also used actigraphy to measure children’s sleep duration, but not quality, at 30, 36, and 42 months. Cross-time analyses indicated that sleep minutes (24-hr period) declined significantly, which was explained by reduced daytime nap sleep minutes. Modest rank-order stability in children’s nighttime sleep minutes and 24-hr sleep minutes (rs ranged from .19 to .46) was also detected. Other longitudinal work that has assessed children from 20 to 42 months of age has found rank-order stability in nighttime sleep quality, but did not find stability in nighttime sleep minutes (Scher, Epstein, & Tirosh, 2004). Thus, the findings from prior research are somewhat mixed, but may suggest a decline in daytime sleep duration and corresponding increase in nighttime sleep quality across the preschool period, with some evidence of low to moderate stability in sleep duration and quality. These studies did not assess samples of children recruited from childcare centers and therefore were not designed to examine change or stability in sleep over time in children attending childcare.

Cross-sectional and longitudinal studies of sleep changes using parent reports are consistent with those using actigraphy and suggest that children’s sleep–wake cycles undergo several transitions from infancy through early childhood. Infants sleep about 14 hours a day and take multiple daily naps (Iglowstein, Jenni, Molinari, & Largo, 2003). Sleep duration then declines year by year from toddlerhood through early childhood, with a primary night sleep period emerging at about age 2 (and a concomitant decrease in daytime sleep; Iglowstein et al., 2003). By age 5, children sleep about 11 hours a day and are likely to stop taking daily naps. In terms of inter-individual variability, studies suggest that children’s sleep duration is moderately stable from early to middle childhood, such that those who tend to sleep shorter or longer in early childhood also tend to do so later in childhood (Jenni, Molinari, Caflisch, & Largo, 2007). Taken together, results from studies using actigraphy and parent report of young children’s sleep suggest an overall decline in sleep duration and improvement in sleep quality over time. There are important individual differences in these trajectories, however. For example, Weinraub et al. (2012) found that about two-thirds of infants follow a steady trajectory of one nighttime awakening per week from 6 to 36 months, whereas the remaining one-third show a gradual decline from seven to one night awakenings per week across this age period. In a longitudinal study of young children’s sleep duration across ages 0–1 to 6–7 years old, Magee, Gordon, and Caputi (2014) identified distinct trajectories, including typical, initially short, persistently short, and poor (marked by more sleep problems in addition to shorter duration) sleepers. Identifying the factors implicated in sleep pattern changes during early childhood, beyond typical central nervous system maturation and normative changes in family routines at bedtime, is of growing interest in the literature.

Research on children’s daycare experiences in relation to sleep parameters is limited and primarily focused on napping. For example, Ward, Gay, Anders, Alkon, and Lee (2008) found that 3 to 5-year-old children who took daily naps at daycare had shorter nighttime sleep durations and more frequent night awakenings, assessed with actigraphy, than children who did not nap while in daycare. Acebo et al. (2005) also reported a negative association between naptime and nighttime sleep duration among 1 to 5-year-old children, though their study did not assess whether the children were enrolled in childcare. El-Sheikh, Arsiwalla, Staton, Dyer, and Vaughn (2013) did not detect significant associations between daytime and nighttime sleep duration or number of night wakings in a sample of preschool-aged children, but they did find that daytime and nighttime sleep efficiency scores were positively associated. They suggested that these inconsistencies across studies may be attributed in part to more rigidly structured nap schedules in daycare settings, as compared with more flexible nap schedules at home. Differences between daycare programs with regard to length of naptime opportunity may also influence the degree to which nighttime sleep is affected. For example, in the Ward et al. (2008) study, children were given a 150-minute window for naptime, whereas in the El-Sheikh et al. (2013) study the naptime window was 120 minutes.

The present study addressed whether daytime and nighttime sleep duration and quality change or remain stable from fall to spring across a six-month period of daycare. There is evidence that the transition to daycare can be stressful for children, as indicated by elevated cortisol levels (Bernard, Peloso, Laurenceau, Zhang, & Dozier, 2015), which may disrupt sleep. Furthermore, the transition to kindergarten has been associated with a decrease in weekday sleep (Cairns & Harsh, 2014). Sleep efficiency has been found to increase across the transition, perhaps due to greater sleep pressure. Because the daycare environment may share similarities to school with regard to structure and scheduling, a decline in sleep duration and an increase in sleep quality may also be expected across the school year for children attending childcare. Many of the children in the present study (79%) were not new to the daycare setting and therefore may not have experienced the same degree of stress or disruption as a child who was just beginning childcare. However, they were all starting the school year with new teachers in a new classroom, a transition which may evoke some stress and disruption to routine. To our knowledge, prior work has not examined how sleep may change from fall to spring within samples of children attending childcare.

The current study had two goals. First, we used objective assessments of sleep duration and quality obtained with actigraphy to assess whether the means for these parameters shifted across a six-month period in daytime and nighttime sleep among a sample of children attending a high-quality, center-based childcare program. Second, we examined the stability of daytime and nighttime sleep duration and sleep quality within the sample. This would identify rank-order stability or changes in children’s sleep and whether, for example, those with shorter sleep duration or low-quality sleep would continue to have poor sleep over time.

Based on previous findings (Anders, Iosif, Schwichtenberg, Tang, & Goodlin-Jones, 2011; Iglowstein et al., 2003), we hypothesized that average sleep duration, particularly daytime sleep duration, would decrease over the six-month interval as a result of normative developmental change. However, we expected improvement in daytime and nighttime sleep quality based on prior work suggesting that an increase in sleep quality may be expected following a transition in schooling (Cairns & Harsh, 2014). We also anticipated that moderate rank-order stability for the sleep parameters would be observed from fall to spring. Although findings in this research area are mixed, we hypothesized that the consistency and regular routines of the daycare environment would contribute to a greater likelihood of detecting stability in our sleep parameters.

Method

Participants

Participants were 68 children aged 2 to 5 years (M _age = 3.80 years, SD = .68, range 2.5–5 years; 54% girls) from a larger investigation examining children’s social adaptation and cognitive functioning in preschool. Participants were recruited from a university-managed early education center, accredited by the National Association for the Education of Young Children and located in a metropolitan area in the Southeastern United States. Approximately 67% of participants were European American, 25% were African American, and 8% were of other races/ethnicities. Children were from middle-class families (more than 90% of parents had university-level degrees and worked in professions requiring postgraduate training). All children in the sample were enrolled in the childcare center for five days a week. On average, children spent 6–8 hours each weekday in the center. Children participated during one of the two academic years: 2013–2014 and 2014–2015. The majority of the children (79%) had been in enrolled at the center in the previous school year; 21% were new to the center in the academic year they completed assessments. All children in the sample were in new classrooms and had new teachers at the beginning of the academic year in which they participated in the study.

Procedures

Sleep data were collected using actigraphs placed on the child’s non-dominant wrist for seven consecutive days and nights. A research staff member placed the actigraph on the child’s wrist at naptime on the first day of data collection. Parents and teachers were instructed that the child was to wear the actigraph at all times, except when bathing or engaged in water play. A research staff member observed naptime at the childcare center and kept daily records of when each child wearing an actigraph fell asleep and woke up. Parents kept a daily record of the child’s sleep and wake times for nights and weekends. These records were used to corroborate actigraphy data. Protocol specified that if sleep or wake times differed by more than 45 minutes between the actigraphy and adult records, the actigraphy data were not scored; however, there were no discrepancies greater than 45 minutes for this sample. Parents also recorded the child’s use of medication for acute illnesses (e.g. Tylenol, Benadryl), and sleep routines. Days during which the child used medication were recorded but excluded from actigraphy analyses. Sleep data collection occurred twice in an academic year, once in the fall (from October to December), and once in the spring (from April to June), excluding holidays. There was an average of a six-month period between the two waves of sleep data collection.

In this center, all children were required to lie down on their cots in a darkened room at approximately 12:30 p.m. and to stay on the cot, whether or not they were sleeping, until approximately 2:30 p.m. If children awoke prior to 2:30 pm, they could look at a book quietly. Eight classrooms in the center participated in year one and five classrooms participated in year two of the study. Independent t-tests suggested no significant differences in sleep parameters or demographic variables between children who participated in year one versus those who participated in year two.

Measures

Sleep

Sleep parameters were assessed using Octagonal Basic Motionloggers (Ambulatory Monitoring Inc., Ardsley, NY, USA), which record movement in one-minute epochs and score each epoch using the well-validated Sadeh algorithm (Sadeh, Sharkley, & Carskadon, 1994). Missing actigraphy data were due to the child’s use of medication and exclusion of these nights from analyses, parents forgetting to put the actigraph back on the child after bathing, and actigraph malfunction or loss (some children took them off). In the fall, three children refused to wear the actigraph; in the spring, two children refused to wear the actigraph, three children moved away, and two children lost or broke their actigraph. To enhance estimation of regular sleep, actigraphy data for children with fewer than four nights and days were not included in analyses (Acebo et al., 1999).

Per recommendations in the literature (Sadeh, 2015), we examined multiple sleep parameters and scored them according to established guidelines (Ambulatory Monitoring, 2002). The following well-recognized and frequently used variables were derived for daytime and nighttime sleep: (a) sleep minutes – minutes scored as sleep between sleep onset and wake time; (b) sleep efficiency – percentage of epochs scored as sleep between sleep onset and wake time (Sadeh et al., 1994). Sleep minutes provided an estimate of sleep duration and sleep efficiency provided a measure of sleep quality (Kelly, Marks, & El-Sheikh, 2014). Reliability estimates for these sleep parameters across the days and nights of data collection yielded high internal consistency estimates (Cronbach αs ranged from .76–.92 in the fall and .84–.93 in the spring), and thus, as is common in this literature, each sleep parameter was averaged across the available days and nights. We also compared children’s daytime and nighttime sleep duration between weekdays and weekends. In the fall, children napped for an average of 80.76 minutes (SD = 21.74) and had 483.16 minutes (SD = 39.74) of nighttime sleep during the week. On the weekend, they had 54.06 minutes (SD = 48.66) nap and 503.81 minutes (SD = 45.16) nighttime sleep (paired sample t (42) = 3.86 and t (51) = -3.69, ps < .001 for daytime and nighttime sleep minutes respectively). In the spring, they had 83.02 minutes (SD = 21.29) nap and 493.84 minutes (SD = 54.63) nighttime sleep during the week versus 50.22 minutes (SD = 50.51) nap and 505.27 minutes (SD = 60.75) nighttime sleep during the weekend (t (39) = 4.22, p < .001 and t (48) = -1.82, p = .07 for daytime and nighttime sleep minutes respectively). Because we did not have hypotheses regarding weekday vs. weekend sleep, and because high internal consistency was observed for all sleep parameters across the seven days or nights of actigraphy assessments, data from both weekday and weekend were used to estimate the average duration and quality of daytime and nighttime sleep. Note, however, that we conducted all analyses with weekday data (excluding weekend actigraphy data) and the results were identical to those reported henceforth.

Controls

To reduce confounds, child age, sex, ethnicity, and whether children were new to the center were considered as controls in all analyses and were retained if they were significantly associated with model variables.

Plan of Analysis

To address the first study aim, repeated measures ANCOVAs were conducted to examine mean differences from fall to spring for each sleep parameter, with statistically significant controls retained. Path analyses testing whether fall sleep parameters were significantly associated with spring sleep parameters tested the second study aim, which concerned the rank-order stability for sleep over time within the sample. The sleep parameters were covaried with one another at each time point to examine unique associations. Model fit was considered acceptable if it satisfied two of three criteria: χ2/df ≤ 3, comparative fit index ≥ .90, and RMSEA ≤ 0.08 (Browne & Cudeck, 1993). Analyses were tested using SPSS 21 for the first aim, and using the SPSS Amos Graphics add-on for SPSS 21 for the second aims.

The percent of the sample with complete data ranged from 63% (spring naptime) to 85% (fall nighttime). Full information maximum likelihood estimation (FIML) was used to handle missing data in the path modeling analyses (FIML cannot be used for ANCOVA analyses). Use of path modeling with FIML allowed for all data points to be included in the analyses and reduced the number of statistical tests run because the nighttime and daytime parameters could each be included in the same model (i.e. one nighttime model and one daytime model). The amount of missingness was well within the acceptable range for FIML, which has been shown to be the best statistical method to account for missing data because it results in the least biased estimates and lowest rates of Type I errors (Enders & Bandalos, 2001).

Results

Preliminary Analyses

All variables were normally distributed with acceptable skewness values (range of -1.8 to .00) and no outliers (no cases > 4 SDs from the means). Bivariate correlations between demographic covariates (age, sex, ethnicity, whether this was their first year at the center) and the sleep parameters are presented in Table 1. All children napped for an average of 30 minutes or more during the daytime across the assessment period.

Table 1.

Bivariate Correlations between Covariates and Main Study Variables.

	1	2	3	4	5	6	7	8	9	10	11	12
1. Age	–
2. Sex	.23
3. Ethnicity	.18	−.17
4. First year of child care	.29*	−.03	.35**
5. Fall night sleep minutes	−.31*	.01	−.10	−.10
6. Fall night sleep efficiency	.04	.08	.07	.09	.60
7. Spring night sleep minutes	−.20	.11	−.18	−.34*	.50**	.22
8. Spring night sleep efficiency	−.16	.01	−.04	−.13	.34*	.37**	.81**
9. Fall nap sleep minutes	−.67**	−.17	−.16	−.25	.35*	.12	.19	.17
10. Fall nap sleep efficiency	−.12	.32*	−.27	.02	.22	.18	.12	.17	.09
11. Spring nap sleep minutes	−.68**	−.23	.00	−.28	.17	−.10	.07	.08	.76**	.00
12. Spring nap sleep efficiency	.17	.19	.05	−.03	.23	−.13	.61**	.56**	−.05	.26	−.17	–

Note. Total N = 68. Sex: Boy = 0, girl = 1; Ethnicity: Caucasian = 0, other ethnicity = 1; First year of child care: No = 0, Yes = 1.

*p < .05, **p < .01.

Mean-level Changes in Sleep Parameters

For the first study question, repeated measures ANCOVAs tested the significance of mean-level differences in sleep parameters from fall to spring (see Table 2). Of the potential controls, only child age and sex were significantly associated with the sleep parameter means and were retained in all models. Analyses of the nighttime data including the age and sex covariates showed that the difference in overall sleep minutes from fall to spring was not significant, however, a significant mean difference was obtained for nighttime sleep efficiency, p < .05. On average, children had better nighttime sleep efficiency in the spring than in the fall. Parallel analyses conducted for daytime naps did not reveal significant mean-level differences for either sleep parameter.

Table 2.

Means and Standard Deviations (SD) of Main Study Variables.

	Fall		Spring		Spring–Fall Change	Repeated MeasureANCOVA (F)	Partial Eta Squared
	Mean (SD)	95% CI	Mean (SD)	95% CI	Mean	Repeated MeasureANCOVA (F)	Partial Eta Squared
Nighttime sleep (actigraphy)
Sleep minutes	492.42 (37.29)	481.96–502.88	502.08 (49.10)	488.05–516.11	9.66	.02	.00
Sleep efficiency	88.70 (5.45)	87.11–90.33	90.89 (5.46)	89.31–92.46	2.19	4.14*	.08
Daytime sleep (actigraphy)
Sleep minutes	83.95 (19.50)	78.79–89.10	87.17 (22.94)	81.44–92.89	3.22	2.27	.06
Sleep efficiency	97.22 (2.97)	96.30–98.13	97.17 (2.74)	96.24–98.11	−0.05	1.68	.05

Note. N = 49 for longitudinal nighttime sleep data; N = 36 for longitudinal daytime sleep data.

*p < .05.

Stability of Children’s Sleep over Time

Addressing the second study aim, path analyses were conducted separately for nighttime and daytime sleep. Regarding demographic variables, older age was associated with a smaller increase in nighttime sleep efficiency and daytime sleep duration from fall to spring, βs = −.16, −.34, ps < .05, respectively. Being new to the center also predicted lower increase in nighttime sleep duration, β = −.32, p < .01 and marginally predicted lower increase in nighttime sleep efficiency, β = −.20, p < .10 from fall to spring. With respect to study hypotheses, model fit for both nighttime and daytime sleep stability parameter estimates was good, χ2/df < 1.5, comparative fit index > .90, and RMSEA < 0.08. The models indicated that both nighttime sleep parameters had significant cross-time stability, βs = .49 and .45, ps < .001 for sleep minutes and efficiency, respectively. Thus, children who slept longer and had better sleep quality in the fall were also more likely to sleep longer and have better quality sleep in the spring. Parallel analyses for daytime sleep revealed significant stability for daytime sleep minutes, β = .54, p < .001, and low (trend-level) stability for daytime sleep efficiency, β = .28, p < .10. The strength of the regression coefficients for the nighttime versus daytime stability parameters were compared using an SPSS macro (Weaver & Wuensch, 2013). There was not a significant difference between the nighttime and daytime stability coefficients for sleep minutes or sleep efficiency.

Discussion

In this study, sleep parameters were examined from fall to spring (over a six-month period) for a sample of preschool children attending a high-quality, center-based childcare program. Results of analyses testing mean differences in sleep over the academic year revealed that average daytime and nighttime sleep duration, as well as daytime sleep quality, did not change over the two waves of assessment. However, nighttime sleep quality showed improvement over this same period, such that children had greater sleep efficiency in the spring than in the fall of the academic year. Further, moderate levels of stability were found for nighttime sleep minutes, daytime sleep minutes, and nighttime sleep efficiency. Low stability was detected for daytime sleep efficiency.

Our finding of a mean-level increase in nighttime sleep quality is consistent with prior literature suggesting that sleep quality tends to improve over time for young children (Anders et al., 2011). In one of the few other studies examining group-level changes in sleep in young children using actigraphy, Anders, Iosif, Schwichtenberg, Tang, and Goodlin-Jones (2011) also reported overall improvement in preschool-age children’s nighttime sleep quality (increases in sleep efficiency) over a six-month period. Similar findings regarding decreasing night awakenings have been found using parent report of sleep (Galland, Taylor, Elder, & Herbison, 2012). Together, these results are consistent with the notion that sleep becomes more consolidated as children mature during early childhood (El-Sheikh et al., 2013; Iglowstein et al., 2003). In addition to normative developmental changes, it is possible that greater sleep disruption at the beginning of the school year relative to the end could be attributed in part to the potential stress or challenge of adapting to a new classroom and new teachers as well as any adjustments to the sleep schedule needed to accommodate the school day. Our results add to this prior literature with community samples of children by demonstrating that improvement in sleep quality may be expected across a year of childcare when the care is high quality. Importantly, however, the preliminary analyses indicated that children who were new to the center experienced a smaller increase in sleep duration from the fall to spring relative to the children who had been previously enrolled, and there was a trend-level finding suggesting that they also experienced a smaller increase in nighttime sleep efficiency. These results could suggest that improvement in nighttime sleep is not uniform, and is more likely to be detected across the school year among children who are familiar with the childcare setting even though they are not familiar with the particular teacher or classroom. The transition may take longer among children for whom the entire experience is novel and potentially more stressful.

In controlling for the associations between child characteristics and the sleep variables, we detected a link between older child age and less of an increase in nighttime sleep efficiency from fall to spring. This finding is seemingly at odds with our study results and those of prior work indicating that sleep quality tends to improve over time during the preschool period. We speculate that the nighttime sleep of older children in our sample may be more interrupted when they are required to take a long rest period during the day, as required by the state of Alabama where the data were collected. This is consistent with prior work showing that preschool-aged children who napped at daycare had shorter actigraph-assessed nighttime sleep and more frequent night awakenings (Ward, Gay, Anders, Alkon, & Lee, 2008). It is also consistent with the association between older child age and shorter daytime sleep in the current sample, which may suggest that the nap was less necessary for (at least some) older children. There may be less impact on the nighttime sleep of younger children, who may require longer daytime sleep. Further research is needed regarding the impact of long daytime rest periods on children’s nighttime sleep as they develop.

Prior studies suggested that children’s daytime sleep duration decreases over early childhood, whereas their nighttime sleep time may not show significant age-related declines (Acebo et al., 2005). We did not find significant mean differences in either daytime or nighttime sleep duration from fall to spring over the academic year. This discrepancy may be attributed to differences in sample characteristics or the context(s) of sleep assessment across studies. Studies reporting declines in children’s daytime sleep often recruited a community sample of children who may or may not have attended a childcare center (Anders et al., 2011). In this sample, children’s daytime nap took place in a highly structured setting, where they were all required to rest regardless of sleep need, and this may have constrained variability in daytime sleep measures. Another possible explanation is that this study only covered a six-month time span. Had sleep been measured over longer intervals (e.g. one year), we might have seen significant declines in children’s daytime sleep duration.

Children in our study slept on average 8.25 hours (actual sleep minutes vs. time in bed) with a 1.5 hour daytime nap, resulting in about 9.75 hours total sleep over a 24-hr period. This is less than the 10–13 hours of sleep (time in bed) recommended by the National Sleep Foundation for preschool children (Hirshkowitz et al., 2015). We note that if time in bed was used, children in our study slept about 9.2 hours at night and 10.7 total, which does fall within the guidelines recommended by the National Sleep Foundation and is consistent with parental report data used in other normative studies (Acebo et al., 2005; Ward et al., 2008). It will be important to continue studies of sleep during early childhood to determine whether recommended sleep times based on parental estimates of sleep reflect children’s actual sleep time and needs, or simply time in bed.

The literature on rank-order stability and normative changes for sleep parameters in early childhood using objective data (i.e. actigraphy) is sparse, but generally corroborates our findings of moderate stability in nighttime sleep duration and quality. Scher, Epstein, and Tirosh (2004) did not find significant rank-order stability for overall nighttime sleep minutes in a sample of children assessed from 20 to 42 months, but did report a significant association for sleep efficiency that is comparable to the value detected in our sample. In a study of relatively younger children, Staples et al. (2015) reported cross-time correlations for nighttime sleep duration that were similar in magnitude to those of the present study. Our results replicate and extend prior literature concerning stability in sleep parameters by demonstrating that stability in nighttime sleep duration and quality, in addition to daytime sleep duration, may be expected in the context of high-quality childcare. It may be that the predictability and controlled environment of the childcare setting from which the sample for the current study was drawn facilitated the detection of more evidence of rank-order stability in nighttime and daytime sleep patterning, in comparison to the greater variability that children may experience in community samples. Lower stability for daytime sleep quality, on the other hand, could perhaps be attributed to the very high estimates for daytime sleep efficiency (> 95%). These estimates may suggest that because the children were instructed to lay quietly on their cots and read if they were not sleeping, the actigraphs may not have been able to distinguish between wake and sleep as accurately as during the night. Naptime sleep duration, on the other hand, may have remained relatively stable because of the rest period required by the daycare center.

Several additional limitations in the current study warrant discussion. First, sleep data were collected from a small sample of children attending a high-quality daycare center in the southeastern region of the US and a majority of them were from middle-class European American families. Sleep–wake patterns reported here may reflect characteristics of this sample and might not generalize to children attending different forms of daycare or who are from other socioeconomic status groups or different locales and countries. Additionally, it is important to consider how daycare sleep policy may affect results. In the state where the study was conducted, state regulations require that the rest period shall not be less than 45 minutes or longer than 2.5 hours. It is possible that the lack of change in daytime sleep parameters detected in the current study was due at least in part to these regulations. The mandatory daycare rest period may have masked meaningful individual differences in children’s propensity for daytime sleep, in addition to interfering with normative developmental reductions in daytime sleep across the preschool-age period. Children’s sleep–wake patterns may be different depending on naptime regulations. Furthermore, children’s sleep was assessed in the fall and then again in the spring, such that both assessments took place following the transition to a new classroom and new teachers. A third data collection point in the following fall term would permit testing of group-level change and stability in sleep across this transition. The fall assessment also took place between one and four months (October–December) after the class transition in September. An earlier assessment might allow for a better assessment of children’s sleep right at the transition to a new childcare classroom. Finally, a comparison group of children who did not attend childcare would also allow for examination of whether the findings were unique to children cared for in daycare centers.

Despite these limitations, to our knowledge this is one of the first longitudinal studies that examined sleep–wake patterns using actigraphy for children in high-quality, center-based daycare. The analyses suggested that while rank-order stability in children’s nighttime and daytime sleep was maintained over a six-month period, at the group level their nighttime sleep quality showed normative improvement over time. Future studies will be needed to further understand the underlying biological and environmental factors that are related to these associations.

Footnotes

Acknowledgments

The authors are grateful for the support of the directors and teachers at the Harris Early Learning Center of Birmingham and for the patience of the children and parents who have participated in the study.

Funding

This study has been supported in part by NSF grant BCS 1251322 and by Hatch project ALA042-1-14021.

ORCID iD

Brian E. Vaughn

References

Acebo

Sadeh

Seifer

Tzischinsky

Hafer

Carskadon

M. A.

(2005). Sleep/wake patterns derived from activity monitoring and maternal report for healthy 1-to 5-year-old children. Sleep, 28, 1568–1577. doi:10.1093/sleep/28.12.1568

Acebo

Sadeh

Seifer

Tzischinsky

Wolfson

A. R.

Hafer

Carskadon

M. A.

(1999). Estimating sleep patterns with activity monitoring in children and adolescents: How many nights are necessary for reliable measures? Sleep, 22, 95–103. doi:10.1093/sleep/22.1.95

Ambulatory Monitoring. (2002). ActionW User’s Guide Version 2.4. Ardsley, NY: Ambulatory Monitoring.

Anders

T. F.

Iosif

A. M.

Schwichtenberg

A. J.

Tang

Goodlin-Jones

B. L.

(2011). Six-month sleep–wake organization and stability in preschool-age children with autism, developmental delay, and typical development. Behavioral Sleep Medicine, 9, 92–106. doi:10.1080/15402002.2011.55799

Bernard

Peloso

Laurenceau

J. P.

Zhang

Dozier

(2015). Examining change in cortisol patterns during the 10-week transition to a new child-care setting. Child Development, 86, 456–471. doi:10.1111/cdev.12304

Bernier

Carlson

S. M.

Bordeleau

Carrier

(2010). Relations between physiological and cognitive regulatory systems: Infant sleep regulation and subsequent executive functioning. Child Development, 81, 1739–1752. doi:10.1111/j.1467-8624.2010.01507.x

Browne

M. W.

Cudeck

(1993). Alternative ways of assessing model fit. In Bollen

K. A.

Long

J. S.

(Eds.), Testing Structural Equation Models (pp. 136–262). Newbury Park, CA: Sage.

Byars

K. C.

Yolton

Rausch

Lanphear

Beebe

D. W.

(2012). Prevalence, patterns, and persistence of sleep problems in the first 3 years of life. Pediatrics, 129, e276–e284. doi:10.1542/peds.2011-0372

Cairns

Harsh

(2014). Changes in sleep duration, timing, and quality as children transition to kindergarten. Behavioral Sleep Medicine, 12, 507–516. doi:10.1080/15402002.2013.838765

10.

El-Sheikh

Arsiwalla

D. D.

Staton

Dyer

W. J.

Vaughn

B. E.

(2013). Associations between preschoolers’ daytime and nighttime sleep parameters. Behavioral Sleep Medicine, 11, 91–104. doi:10.1080/15402002.2011.625460

11.

Enders

C. K.

Bandalos

D. L.

(2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling, 8, 430–457. doi:10.1207/S15328007SEM0803_5

12.

Galland

B. C.

Taylor

B. J.

Elder

D. E.

Herbison

(2012). Normal sleep patterns in infants and children: A systematic review of observational studies. Sleep Medicine Reviews, 16, 213–222. doi:10.1016/j.smrv.2011.06.001

13.

Hirshkowitz

Whiton

Albert

S. M.

Alessi

Bruni

DonCarlos

… Adams Hillard

P. J.

(2015). National sleep foundation’s sleep time duration recommendations: Methodology and results summary. Sleep Health, 1, 40–43. doi:10.1016/j.ecresq.2012.08.001

14.

Iglowstein

Jenni

O. G.

Molinari

Largo

R. H.

(2003). Sleep duration from infancy to adolescence: Reference values and generational trends. Pediatrics, 111, 302–307. doi:10.1542/peds.111.2.302

15.

Jenni

O. G.

Molinari

Caflisch

J. A.

Largo

R. H.

(2007). Sleep duration from ages 1 to 10 years: Variability and stability in comparison with growth. Pediatrics, 120, e769–e776. doi:10.1542/peds.2006-3300

16.

Kelly

R. J.

Marks

B. T.

El-Sheikh

(2014). Longitudinal relations between parent–child conflict and children’s adjustment: The role of children’s sleep. Journal of Abnormal Child Psychology, 42, 1175–1185. doi:10.1007/s10802-014-9863-z

17.

Magee

C. A.

Gordon

Caputi

(2014). Distinct developmental trends in sleep duration during early childhood. Pediatrics, 133, e1561–e1567. doi:10.1542/peds.2013-3806

18.

Sadeh

(2015). III. Sleep assessment methods. Monographs of the Society for Research in Child Development, 80, 33–48. doi:10.1111/mono.12143

19.

Sadeh

Sharkey

Carskadon

M. A.

(1994). Activity-based sleep-wake identification: An empirical test of methodological issues. Sleep, 17, 201–207. doi:10.1093/sleep/17.3.201

20.

Scher

Epstein

Tirosh

(2004). Stability and changes in sleep regulation: A longitudinal study from 3 months to 3 years. International Journal of Behavioral Development, 28, 268–274. doi:10.1080/01650250344000505

21.

Smedje

Broman

J. E.

Hetta

(2001). Associations between disturbed sleep and behavioural difficulties in 635 children aged six to eight years: A study based on parents’ perceptions. European Child & Adolescent Psychiatry, 10, 1–9. doi:10.1007/s007870170041

22.

Staples

A. D.

Bates

J. E.

Petersen

I. T.

(2015). Ix. Bedtime routines in early childhood: Prevalence, consistency, and associations with nighttime sleep. Monographs of the Society for Research in Child Development, 80, 141–159. doi:10.1111/mono.12149

23.

U.S. Department of Health and Human Services. (2016a). Average monthly hours for children in care by age group and care type. Retrieved from https://www.acf.hhs.gov/occ/resource/fy-2014-final-data-table-14

24.

U.S. Department of Health and Human Services. (2016b). Average monthly percentages of children in child care by age category and care type. Retrieved from https://www.acf.hhs.gov/occ/resource/fy-2014-final-data-table-14

25.

Ward

T. M.

Gay

Anders

T. F.

Alkon

Lee

K. A.

(2008). Sleep and napping patterns in 3-to-5-year old children attending full-day childcare centers. Journal of Pediatric Psychology, 33, 666–672. doi:10.1093/jpepsy/jsm102

26.

Weaver

Wuensch

K. L.

(2013). SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients. Behavior Research Methods, 45, 880–895. doi:10.3758/s13428-012-0289-7

27.

Weinraub

Bender

R. H.

Friedman

S. L.

Susman

E. J.

Knoke

Bradley

… Williams

(2012). Patterns of developmental change in infants’ nighttime sleep awakenings from 6 through 36 months of age. Developmental Psychology, 48, 1511. doi:10.1037/a0027680