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Erschienen in: BMC Medicine 1/2022

Open Access 01.12.2022 | Research article

Associations between gestational age and childhood sleep: a national retrospective cohort study

Erschienen in: BMC Medicine | Ausgabe 1/2022

Abstract

Background

Both sleep quality and quantity are essential for normal brain development throughout childhood; however, the association between preterm birth and sleep problems in preschoolers is not yet clear, and the effects of gestational age across the full range from preterm to post-term have not been examined. Our study investigated the sleep outcomes of children born at very-preterm (<31 weeks), moderate-preterm (32–33 weeks), late-preterm (34–36 weeks), early-term (37–38 weeks), full-term (39–40 weeks), late-term (41 weeks) and post-term (>41 weeks).

Methods

A national retrospective cohort study was conducted with 114,311 children aged 3–5 years old in China. Children’s daily sleep hours and pediatric sleep disorders defined by the Children’s Sleep Habits Questionnaire (CSHQ) were reported by parents. Linear regressions and logistic regression models were applied to examine gestational age at birth with the sleep outcomes of children.

Results

Compared with full-term children, a significantly higher CSHQ score, and hence worse sleep, was observed in very-preterm (β = 1.827), moderate-preterm (β = 1.409), late-preterm (β = 0.832), early-term (β = 0.233) and post-term (β = 0.831) children, all p<0.001. The association of pediatric sleep disorder (i.e. CSHQ scores>41) was also seen in very-preterm (adjusted odds ratio [AOR] = 1.287 95% confidence interval [CI] (1.157, 1.433)), moderate-preterm (AOR = 1.249 95% CI (1.110, 1.405)), late-preterm (AOR = 1.111 95% CI (1.052, 1.174)) and post-term (AOR = 1.139 95% CI (1.061, 1.222)), all p<0.001. Shorter sleep duration was also found in very-preterm (β = −0.303), moderate-preterm (β = −0.282), late-preterm (β = −0.201), early-term (β = −0.068) and post-term (β = −0.110) compared with full-term children, all p<0.01. Preterm and post-term-born children had different sleep profiles as suggested by subscales of the CSHQ.

Conclusions

Every degree of premature, early-term and post-term birth, compared to full-term, has an association with sleep disorders and shortened daily sleep duration. Preterm, early-term, and post-term should therefore all be monitored with an increased threat of sleep disorder that requires long-term monitoring for adverse sleep outcomes in preschoolers.
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12916-022-02443-9.
Jiajun Lyu, Haifeng Li and Lei Wang contributed equally.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
ANOVA
Analysis of variance
AOR
Adjusted odds ratio
ASD
Autism spectrum disorder
BMI
Body mass index
CI
Confidence interval
CNCMD
The Chinese National Cohort of Motor Development
CSHQ
The Children’s Sleep Habits Questionnaire
DAG
Directed acyclic graph
ICD 10
The International Classification of Diseases, Revision 10
NICU
Newborn intensive care unit
OSA
Obstructive sleep apnea
SES
Socioeconomic status
SPSS
Statistical Package for the Social Sciences

Background

It is well established that both sleep quality and quantity are essential for normal brain development throughout childhood, particularly for cognitive functions [1]. However, sleep problems are relatively common among young children, and according to parent reports, it has been suggested that approximately 20–30% of young children have various sleep problems [2]. In preterm infants younger than 1 year old, sleep problems are thought to be even more prevalent [3, 4].
However, the exact relationship between preterm birth and sleep problems beyond infancy is not yet clear. Studies have suggested that school-aged preterm children had different sleep patterns compared to full-term children, such as having earlier bedtimes and earlier wake times [57], but had no difference in overall sleep duration [6, 7]. Preterm children have been reported to have lower sleep quality, including more nocturnal awakenings [8, 9], and consistent with this more “shallow” and less “deep” non-rapid eye movement sleep [9]. It has been suggested that irreversible adverse factors related to preterm birth, such as brain injury, altered brain maturation, and respiratory problems may precipitate poor sleep. Furthermore, a range of parental factors related to preterm childcaring may also play a role. For example, increased parental concern about preterm children may be linked to earlier bedtimes, which may contribute to the different sleep outcomes of preterm children beyond infancy [10]. However, given the very limited studies available in the literature, variation in the degrees of prematurity and sample size makes it difficult to draw any clear conclusions about the sleep outcomes of preterm children beyond infancy.
Moreover, to our knowledge, no study has been conducted to date on the sleep outcomes of post-term-born children (>41 weeks). Studies have reported that post-term birth can negatively affect children’s short-term and long-term health outcomes [1115]. Post-term birth can increase the risk of neonatal encephalopathy and death during the first year of life [16]. It has also been reported that, with respect to longer-term effects, post-term birth increases the risks of cognitive impairments, severe mental disorders, neuropsychological disorders, and other behavioural and emotional problems in early childhood [1720]. Post-term delivery often has a higher risk for perinatal problems such as prolonged labour that can cause a perinatal lack of oxygen [21] and uteroplacental insufficiency [15]. These risk factors may predispose infants to abnormal brain development and respiratory problems [22] which may lead in turn to sleep problems in post-term children.
Therefore, in the current study, we used a retrospective cohort study design to systematically examine the effect of gestational age on sleep outcomes with a large sample of urban Chinese children. We hypothesized that compared with full-term children (39–40 weeks), that born very-preterm (<31 weeks), moderate-preterm (32–33 weeks), late-preterm (34–36 weeks), early-term (37–38 weeks) and post-term (>41 weeks) all had a higher incidence of sleep disorders and altered sleep outcomes.

Methods

Study design and participants

The present study was part of the Chinese National Cohort of Motor Development (CNCMD), which was designed to explore the neurobehavioral development and other health outcomes (including sleep health, cognition and language development) in Chinese preschool children [23]. A stratified cluster sampling plan was used to ensure that the participants included in the current study were representative of the Chinese population. The China 2018–2019 National Census provided the basis for the stratification by geographic region, age, sex, and socioeconomic status (SES). Ethnic information was not collected because more than 99% of the population in the targeted regions were Han according to the National Census. The government-supported maternity and children’s healthcare centre in each city were selected to invite their local kindergartens to participate in the study. Class teachers were responsible for distributing the notification to parents to complete an online questionnaire. Names and phone numbers of the researchers were provided in case the parents or teachers had queries about the study or about how to respond to the questionnaires. We used an electronic online questionnaire system to enhance the quality of the data by allowing the inclusion of pop-up instructions, error messages, links to further information and to set conditions to ensure participants could not skip questions. A data coordination centre was established to take charge of establishing, managing and maintaining the database, coordinating among health centres.
It is a normal practice for parents to keep in touch with their children’s nursery via smart devices in China, including all of the kindergartens involved in the current study. It was therefore assumed that all of the parents in the current study had relatively high proficiency in online questionnaire completion. All parents gave consent before starting to take part in the study.
From April 1, 2018, to December 31, 2019, a total of 155,377 children aged 3–5 years old from 2403 nurseries in 551 cities in China were recruited for the study. Children were excluded from the study if they had severe visual, hearing, intellectual impairments, cerebral palsy or other severe developmental disorders including autism spectrum disorder (ASD) who were required to receive special education needs and to attend special education schools/nurseries according to the local regulations. Only mainstream schools/nurseries were included in the study; this is the regular provision which excludes special education schools/nurseries. Children with any of the following conditions that may affect the accuracy of the information collected with the questionnaire were excluded from the study: (1) death of the mother; (2) illiterate parents; (3) children taking certain medications with known effects on sleep (such as aspirin, ritalin, amphetamine, caffeine, diazepam, phenobarbital) longer than 1 week at the time of the survey completion date [2427]. Children who were twins or had missing covariates were also excluded. Parents of 25,939 children chose not to participate or left the questionnaire before fully completing it. In all, 114,311 children were included in the final analysis (Fig. 1).
The study was approved by the Ethics Committee of Shanghai First Maternity and Infant Hospital (KS18156). All information acquired was kept confidential and was only accessible by the researchers.

Measures

Outcome variables

Sleep duration and sleep disorders of the children were measured with the Children’s Sleep Habits Questionnaire (CSHQ) [28]. There are 33 parent-rated items in the questionnaire that assesses the frequency of behaviours associated with common pediatric sleep difficulties. The CSHQ instructs parents to rate the frequency with which their child has displayed various sleep behaviours in a typical week during the previous 4 weeks. Ratings are combined to create eight subscales that relate to common sleep problems in children: Bedtime Resistance, Sleep Onset Delay, Sleep Duration, Sleep Anxiety, Night Wakings, Parasomnias, Sleep Disordered Breathing, and Daytime Sleepiness. Finally, all ratings are summed to create a total sleep disturbance index. A higher CSHQ score indicates more sleep difficulties, and a score of over 41 indicates a pediatric sleep disorder [28]. The CSHQ has been shown to be a valid and reliable measurement when it is used with Chinese children [29].
Two extra questions were also included in the parent questionnaire to collect information on the exact daily sleep hours of the children: “How many hours does your child sleep during the weekdays?” and “How many hours does your child sleep at the weekends (including daytime nap)?” Daily sleep hours were then calculated as the value of 5/7×Sleep hours during weekdays+2/7×Sleep hours at the weekends [30]. Daytime nap during the weekdays was not asked for because all of the recruited children attended nursery full-time and a standard daytime nap for the same duration was part of the daily routine in all nurseries.

Independent variables

Gestational age at birth was obtained from the mother’s medical records, which was based on ultrasound examination and date of last menstrual period (LMP). Following the literature [31], seven categories of gestational ages were decided: very-preterm (<31 weeks), moderate-preterm (32–33 weeks), late-preterm (34–36 weeks), early-term (37–38 weeks), completely full-term (39–40 weeks), late-term (41 weeks) and post-term (>41 weeks).

Covariates

We included a range of family, child and maternal characteristics as covariates according to the literature: (1). Child characteristics included the child’s age, sex, child body mass index (BMI), right-handedness, eyesight, birth weight, delivery mode, newborn intensive care unit (NICU) admission and developmental disorders (attention deficit syndrome, attention deficit and hyperactivity disorder, learning disabilities). Body mass index (BMI) is an indicator of obesity that is based on height and weight (BMI = weight(kg)/height(m)). Eyesight was grouped into normal and abnormal (including myopia, hyperopia, astigmatism). Co-sleeping was identified with a particular question: “How often does your child sleep in the parent(s)/caregiver(s) bed at night?” The answers were (1) usually, 5 to 7 nights per week; (2) sometimes, 2 to 4 nights per week; (3) rarely, 0 to 1 night per week. In this study, we defined co-sleeping as bed-sharing that occurred 5 to 7 nights per week [32]. (2) Family characteristics included the following variables: higher education of mother and father (yes vs. no); mother and father’s employment status (employed vs. unemployed); family annual per capita income; the number of children in the family (one vs. two or more); and family structure (single-family, nuclear family and extended family). The “single-family” means the child lives with one of his/her parents; the “nuclear family” refers to the child living only with his/her parents; and the “extended family” refers to the child living with his/her parents and grandparents, which is a traditional family structure in China. (3) Maternal health characteristics included the following variables: maternal age at delivery (<30, 30–34 and ≥35 years); smoking or passive smoking during pregnancy; and maternal complications during pregnancy. Maternal complications were defined according to the International Classification of Diseases, Revision 10 (ICD 10) [33]. The classification is defined as having one of the following maternal complications during pregnancy: gestational diabetes, hypertensive disorders, vaginal bleeding during pregnancy, risk of miscarriage, use of antibiotics, use of fertility drugs, intrauterine distress and foetal asphyxia.

Statistical analysis

Differences in the child, family and maternal health characteristics by sex and gestational age categories were analysed using independent t-tests, one-way analysis of variance (ANOVA) and chi-squared tests. Based on the previous literature [3438] and our exploratory analysis, the summarized directed acyclic graph (DAG) between gestational age, daily sleep hours and CSHQ scores (Additional file 1: Figure S1) was generated by using a web-based tool DAGitty (www.​dagitty.​net). As shown in the DAGs, maternal characteristics and family characteristics as confounders; age, gender, eyesight and co-sleep were considered as competing exposures. Birth weight, BMI, NICU admission, other developmental disorder, handedness and delivery mode were considered as mediators. The distribution of sleep hours and CSHQ scores were relatively symmetric, and multivariable linear regression analysis was conducted to examine the associations of gestational age with daily sleep hours and the CSHQ scores when adjusting for all confounders and competing exposures, while the mediators as the variables on the causal pathway were not included in the adjusted model [39]. Logistic regression analyses were then conducted to examine the associations between different gestational groups and sleep disorders when adjusting for all confounders and competing exposures, while mediators were not included in the adjusted model.
A statistical significance level was set at a p-value <0.05 (two-tailed). To correct for multiple testing, the Benjamini-Hochberg false discovery rate method was used to decrease the probability of false positives [40]. All analyses were performed with the Statistical Package for the Social Sciences (SPSS) (IBM-SPSS Statistics v24.0, Inc Chicago, IL) and R version 3.5.3.

Results

Sample demographic characteristics

A total of 114,311 children aged 4.40±0.79 years old were enrolled in the final analysis. Among all the children, 54,617 (47.8%) were girls and 59,694 (52.2%) were boys. A total of 2379 (2.08%) were very-preterm births; 1893 (1.66%) were moderate-preterm births; 10,238 (9.96%) were late-preterm births; 29,179 (25.53%) were early-term births; 58,043 (50.78%) were full-term births; 7016 (6.14%) were late-term births; 5563 (4.87%) were post-term births (Table 1). Co-sleeping was common, and 82.02% of the children shared a bed with their parents (Table 2). The average daily sleep hours is 10.715±2.693 (Table 1), and 87,773 children (76.78%) were reported to have sleep disorders (Table 3). The prevalence of sleep disorders was 81.21%, 80.67%, 78.62.%, 76.58%, 76.02%, 76.82% and 79.17%, in very-preterm, moderate-preterm, late-preterm, early-term, full-term, late-term and post-term births, respectively (Table 3). The child, family and maternal health during pregnancy characteristics in the study population are shown in Table 2.
Table 1
The description of daily sleep hours and CSHQ score stratified by age and gestational in preschoolers (n = 114,311)
 
N, %
Daily sleep hours
(means, SD)
CSHQ score
(means, SD)
Total
114311, 100.00%
10.715±2.693
46.706±7.576
 Very-preterm (<31W)
2379, 2.08%
10.409±3.135
48.380±8.787
 Moderate-preterm (32–33W)
1893, 1.66%
10.433±2.951
47.940±8.556
 Late-preterm (34–36W)
10238, 8.96%
10.505±2.885
47.340±8.137
 Early-term (37–38W)
29179, 25.53%
10.689±2.699
46.664±7.582
 Full-term (39–40W)
58043, 50.78%
10.780±2.616
46.464±7.355
 Late-term (41–41W)
7016, 6.14%
10.852±2.529
46.539±7.124
 Post-term (>41W)
5563, 4.87%
10.614±2.928
47.365±8.138
3 years old
37823, 100.00%
46.666±7.052
46.592±6.863
 Very-preterm (<31W)
726, 1.92%
10.339±3.231
48.906±8.893
 Moderate-preterm (32–33W)
530, 1.40%
10.432±2.97
48.502±8.75
 Late-preterm (34–36W)
3022, 7.99%
10.623±2.826
47.254±7.500
 Early-term (37–38W)
9824, 25.97%
10.802±2.639
46.846±7.293
 Full-term (39–40W)
19647, 51.94%
10.879±2.552
46.666±7.052
 Late-term (41–41W)
2435, 6.44%
10.851±2.499
47.689±7.942
 Post-term (>41W)
1639, 4.33%
10.664±2.853
46.846±7.293
4 years old
43847, 100.00%
10.708±2.685
46.781±7.545
 Very-preterm(<31W)
938, 2.14%
10.451±3.102
48.263±8.404
 Moderate-preterm (32–33W)
768, 1.75%
10.530±2.918
47.965±8.281
 Late-preterm (34–36W)
3890, 8.87%
10.530±2.857
47.511±8.096
 Early-term (37–38W)
10997, 25.08%
10.654±2.711
46.748±7.544
 Full-term (39–40W)
22276, 50.80%
10.766±2.609
46.493±7.303
 Late-term (41–41W)
2779, 6.34%
10.654±2.711
46.800±7.283
 Post-term (>41W)
2199, 5.02%
10.885±2.459
47.514±8.343
5 years old
32641, 100.00%
10.615±2.768
46.422±7.968
 Very-preterm (<31W)
715, 2.19%
10.424±3.082
48.000±9.152
 Moderate-preterm (32–33W)
595, 1.82%
10.308±2.975
47.398±8.711
 Late-preterm (34–36W)
3326, 10.19%
10.368±2.965
47.222±8.720
 Early-term (37–38W)
8358, 25.61%
10.604±2.748
46.339±7.948
 Full-term (39–40W)
16120, 49.39%
10.678±2.699
46.177±7.770
 Late-term (41–41W)
1802, 5.52%
10.802±2.673
46.065±7.203
 Post-term (>41W)
1725, 5.28%
10.534±2.953
46.957±8.124
Daily sleep hours = 5/7*sleep hours on weekdays +2/7*sleep hours at the weekends
CSHQ Children’s Sleep Habit Questionnaire, SD standard deviation
Table 2
The child and family characteristics in the study population (n = 114,311)
Characteristics
Total
Sex
p
Gestational age at birth
p
(n = 114,311)
Male
Female
Very-preterm
Moderate-preterm
Preterm
Early-term
Full-term
Late-term
Post-term
 
(n = 59,694)
(n = 54,617)
<31W
32–33W
34–36W
37–38W
39–40W
41–41W
>41W
   
(n = 2379)
(n = 1893)
(n = 10,238)
(n = 29,179)
(n = 58,043)
(n = 7016)
(n = 5563)
Child characteristics
Children’s age (M, SD)
4.408, 0.798
4.413, 0.797
4.403, 0.800
0.0423
4.446, 0.790
4.501, 0.781
4.490, 0.801
4.411, 0.804
4.389, 0.797
4.347, 0.782
4.472, 0.789
<0.001
Gender (n%)
           
<0.001
Male
59,694, 52.221
59,694, 100.000
0, 0.000
 
1268, 53.3
1014, 53.566
5568, 54.386
16,010, 54.868
29,670, 51.117
3373, 48.076
2791, 50.171
 
Female
54,617, 47.779
0, 0.000
54,617, 100.000
 
1111, 46.7
879, 46.434
4670, 45.614
13,169, 45.132
28,373, 48.883
3643, 51.924
2772, 49.829
 
BMI (M, SD)
15.602, 1.607
15.754, 1.622
15.435, 1.574
<0.001
15.660, 1.709
15.661, 1.666
15.660, 1.702
15.609, 1.617
15.576, 1.576
15.582, 1.574
15.698, 1.669
<0.001
Right-handedness (n%)
   
<0.001
       
0.007
No
8187, 7.162
4763, 7.979
3424, 6.269
 
212, 8.911
148, 7.818
763, 7.453
2103, 7.207
4039, 6.959
520, 7.412
402, 7.226
 
Yes
106,124, 92.838
54,931, 92.021
51,193, 93.731
 
2167, 91.089
1745, 92.182
9475, 92.547
27,076, 92.793
54,004, 93.041
6496, 92.588
5161, 92.774
 
Eyesight (n%)
   
0.506
       
0.147
Normal
103,199, 90.279
53,858, 90.223
49,341, 90.34
 
2133, 89.66
1691, 89.329
9202, 89.881
26,353, 90.315
52,463, 90.386
6302, 89.823
5055, 90.868
 
Abnormal
11,112, 9.721
5836, 9.777
5276, 9.66
 
246, 10.34
202, 10.671
1036, 10.119
2826, 9.685
5580, 9.614
714, 10.177
508, 9.132
 
Birth weight (n%)
   
<0.001
       
<0.001
<2500g
3700, 3.237
1727, 2.893
1973, 3.612
 
365, 15.343
383, 20.232
1019, 9.953
925, 3.17
808, 1.392
93, 1.326
107, 1.923
 
≥2500g
110,611, 96.763
57,967, 97.107
52,644, 96.388
 
2014, 84.657
1510, 79.768
9219, 90.047
28,254, 96.83
57,235, 98.608
6923, 98.674
5456, 98.077
 
Delivery mode
   
<0.001
       
<0.001
Vaginal delivery
59,625, 52.160
30,421, 50.962
29,204, 53.471
 
1208, 50.778
928, 49.023
5070, 49.521
13,925, 47.723
31,639, 54.51
3893, 55.487
2962, 53.245
 
Delivery with caesarean section
54,686, 47.840
29,273, 49.038
25,413, 46.529
 
1171, 49.222
965, 50.977
5168, 50.479
15,254, 52.277
26,404, 45.49
3123, 44.513
2601, 46.755
 
NICU admission
   
<0.001
       
<0.001
No
102,833, 89.959
53,301, 89.290
49,532, 90.69
 
1891, 79.487
1399, 73.904
8206, 80.152
26,290, 90.099
53,501, 92.175
6420, 91.505
5126, 92.145
 
Yes
11,478, 10.041
6393, 10.710
5085, 9.31
 
488, 20.513
494, 26.096
2032, 19.848
2889, 9.901
4542, 7.825
596, 8.495
437, 7.855
 
Other developmental disorders
   
<0.001
       
<0.001
No
113,565, 99.347
59,244, 99.246
54,321, 99.458
 
2359, 99.159
1867, 98.627
10174, 99.375
28,971, 99.287
57,702, 99.413
6977, 99.444
5515, 99.137
 
Yes
746, 0.653
450, 0.754
296, 0.542
 
20, 0.841
26, 1.373
64, 0.625
208, 0.713
341, 0.587
39, 0.556
48, 0.863
 
Co-sleeping
   
0.427
       
0.142
Yes
93,755, 82.020
48,941, 81.900
44,814, 82.000
 
1935, 81.337
1530, 80.824
8395, 81.998
23,914, 81.956
47,717, 82.21
5754, 82.013
4510, 81.071
 
No
20,556, 17.980
10,753, 18,100
9803, 18.000
 
444, 18.663
363, 19.176
1843, 18.002
5265, 18.044
10,326, 17.79
1262, 17.987
1053, 18.929
 
Family characteristics
Higher education of mother (n%)
   
0.00195
       
<0.001
No
51,393, 44.959
27,098, 45.395
24,295, 44.482
 
1086, 45.649
862, 45.536
4578, 44.716
13,540, 46.403
24,070, 41.469
2929, 41.747
2870, 51.591
 
Yes
62,918, 55.041
32,596, 54.605
30,322, 55.518
 
1293, 54.351
1031, 54.464
5660, 55.284
15,639, 53.597
33,973, 58.531
4087, 58.253
2693, 48.409
 
Higher education of father (n%)
   
0.00498
       
<0.001
No
52,335, 45.783
27,566, 46.179
24,769, 45.35
 
1061, 44.599
851, 44.955
4496, 43.915
13,709, 46.982
24,759, 42.656
2940, 41.904
2825, 50.782
 
Yes
61,976, 54.217
32,128, 53.821
29,848, 54.65
 
1318, 55.401
1042, 55.045
5742, 56.085
15,470, 53.018
33,284, 57.344
4076, 58.096
2738, 49.218
 
Mother’s occupation (n%)
   
0.00255
       
0.013
Employed
71,455, 62.509
37,561, 62.923
33,894, 62.058
 
1505, 63.262
1165, 61.543
6231, 60.861
18,247, 62.535
36,361, 62.645
4439, 63.27
3507, 63.042
 
Unemployed
42,856, 37.491
22,133, 37.077
20,723, 37.942
 
874, 36.738
728, 38.457
4007, 39.139
10,932, 37.465
21,682, 37.355
2577, 36.73
2056, 36.958
 
Father’s occupation (n%)
   
0.249
       
<0.001
Employed
90,554, 79.217
47,367, 79.35
43,187, 79.072
 
1834, 77.091
1452, 76.704
7755, 75.747
23,101, 79.17
46,381, 79.908
5655, 80.601
4376, 78.663
 
Unemployed
23,757, 20.783
12,327, 20.65
11,430, 20.928
 
545, 22.909
441, 23.296
2483, 24.253
6078, 20.83
11,662, 20.092
1361, 19.399
1187, 21.337
 
Family annual per capita income (RMB) b(n%)
   
0.0326
       
<0.001
Below
21,988, 19.235
11,340, 18.997
10,648, 19.496
 
526, 22.11
431, 22.768
2371, 23.159
5418, 18.568
10,683, 18.405
1296, 18.472
1263, 22.704
 
Above or equal to
92,323, 80.765
48,354, 81.003
43,969, 80.504
 
1853, 77.89
1462, 77.232
7867, 76.841
23,761, 81.432
47,360, 81.595
5720, 81.528
4300, 77.296
 
Family structure (n%)
   
0.0395
        
  
<0.001
Single families
2807, 2.456
1412, 2.365
1395, 2.554
 
89, 3.741
59, 3.117
340, 3.321
748, 2.563
1242, 2.140
155, 2.209
174, 3.128
 
Nuclear families
70,142, 61.361
36,724, 61.520
33,418, 61.186
 
1544, 64.901
1225, 64.712
6581, 64.28
17,989, 61.651
35,235, 60.705
4058, 57.839
3510, 63.095
 
Extended families
41,362, 36.184
21,558, 36.114
19,804, 36.260
 
746, 31.358
609, 32.171
3317, 32.399
10,442, 35.786
21,566, 37.155
2803, 39.952
1879, 33.777
 
The number of children in the family (n%)
   
<0.001
       
<0.001
One
64,273, 56.226
34,319, 57.492
29,954, 54.844
 
1390, 58.428
1125, 59.429
5616, 54.854
15,516, 53.175
33,105, 57.035
4201, 59.877
3320, 59.680
 
Two or more
50,038, 43.774
25,375, 42.508
24,663, 45.156
 
989, 41.572
768, 40.571
4622, 45.146
13,663, 46.825
24,938, 42.965
2815, 40.123
2243, 40.320
 
Maternal health characteristics
Maternal age at delivery (n%)
   
0.414
       
<0.001
<30
84,676, 74.075
44,158, 73.974
40,518, 74.186
 
1766, 74.233
1354, 71.527
7068, 69.037
20,500, 70.256
44,021, 75.842
5686, 81.043
4281, 76.955
 
30–34
21,956, 19.207
11,582, 19.402
10,374, 18.994
 
417, 17.528
367, 19.387
2224, 21.723
6293, 21.567
10,666, 18.376
1049, 14.952
940, 16.897
 
≥35
7679, 6.718
3954, 6.624
3725, 6.820
 
196, 8.239
172, 9.086
946, 9.24
2386, 8.177
3356, 5.782
281, 4.005
342, 6.148
 
Smoking or passive smoking during pregnancy (n%)
   
0.685
       
<0.001
No
82,461, 72.137
43,031, 72.086
39,430, 72.194
 
1677, 70.492
1336, 70.576
7154, 69.877
21,197, 72.645
42,124, 72.574
5019, 71.536
3954, 71.077
 
Yes
31,850, 27.863
16,663, 27.914
15,187, 27.806
 
702, 29.508
557, 29.424
3084, 30.123
7982, 27.355
15,919, 27.426
1997, 28.464
1609, 28.923
 
Maternal complications during pregnancy c(n%)
   
0.147
       
<0.001
No
108,934, 95.296
56,938, 95.383
51,996, 95.201
 
2242, 94.241
1755, 92.71
9612, 93.886
27,515, 94.297
55,634, 95.85
6783, 96.679
5393, 96.944
 
Yes
5377, 4.704
2756, 4.617
2621, 4.799
 
137, 5.759
138, 7.29
626, 6.114
1664, 5.703
2409, 4.15
233, 3.321
170, 3.056
 
Other developmental disorders included attention deficit syndrome, attention deficit and hyperactivity disorder, learning disabilities
Table 3
The age-specific association between gestational age and sleep disorder in preschoolers (n=114,311)
 
Sleep disorder (CSHQ>41)
N, %
Crude OR (95% CI)
p
p*
Adjusted ORa (95% CI)
p
p*
Yes
No
Total
87,773, 76.78%
26,538, 23.22%
      
 Very-preterm(<31W)
1932, 81.21%
447, 18.79%
1.322 (1.188, 1.47)
<0.001
<0.001
1.287 (1.157, 1.433)
<0.001
<0.001
 Moderate-preterm(32–33W)
1527, 80.67%
366, 19.33%
1.276 (1.135, 1.435)
<0.001
<0.001
1.249 (1.110, 1.405)
<0.001
<0.001
 Late-preterm (34–36W)
8049, 78.62%
2189, 21.38%
1.125 (1.065, 1.188)
<0.001
<0.001
1.111 (1.052, 1.174)
<0.001
<0.001
 Early-term (37–38W)
22,345, 76.58%
6834, 23.42%
0.97 (0.938, 1.002)
0.069
0.828
0.958 (0.927, 0.991)
0.012
0.014
 Full-term (39–40W)
44,126, 76.02%
13917, 23.98%
Reference
  
Reference
  
 Late-term (41–41W)
5390, 76.82%
1626, 23.18%
1.014 (0.953, 1.078)
0.663
0.663
0.976 (0.917, 1.039)
0.451
0.451
 Post-term (>41W)
4404, 79.17%
1159, 20.83%
1.162 (1.083, 1.247)
<0.001
<0.001
1.139 (1.061, 1.222)
<0.001
<0.001
3 years old
29,658, 78.40%
8165, 21.60%
      
 Very-preterm(<31W)
599, 82.51%
127, 17.49%
1.308 (1.074, 1.594)
0.008
0.048
1.267 (1.039, 1.545)
0.019
0.114
 Moderate-preterm(32–33W)
435, 82.08%
95, 17.92%
1.27 (1.012, 1.594)
0.039
0.078
1.24 (0.987, 1.558)
0.065
0.195
 Late-preterm (34–36W)
2377, 78.66%
645, 21.34%
1.022 (0.925, 1.129)
0.667
0.667
0.996 (0.901, 1.100)
0.930
0.930
 Early-term (37–38W)
7691, 78.29%
2133, 21.71%
0.981 (0.925, 1.04)
0.523
0.667
0.968 (0.912, 1.027)
0.277
0.415
 Full-term (39–40W)
15,317, 77.96%
4330, 22.04%
Reference
  
Reference
  
 Late-term (41–41W)
1918, 78.77%
517, 21.23%
1.029 (0.923, 1.147)
0.606
0.667
0.985 (0.883, 1.099)
0.787
0.930
 Post-term (>41W)
1321, 80.60%
318, 19.40%
1.152 (1.01, 1.314)*
0.035
0.078
1.111 (0.974, 1.269)
0.118
0.236
4 years old
33,962, 77.46%
9885, 22.54%
      
 Very-preterm(<31W)
772, 82.30%
166, 17.70%
1.352 (1.137, 1.608)
0.001
0.002
1.295 (1.088, 1.542)
0.004
0.008
 Moderate-preterm(32–33W)
636, 82.81%
132, 17.19%
1.401 (1.155, 1.699)
0.001
0.002
1.35 (1.112, 1.639)
0.002
0.006
 Late-preterm (34–36W)
3120, 80.21%
770, 19.79%
1.178 (1.076, 1.29)
<0.001
<0.001
1.155 (1.055, 1.266)
0.002
0.006
 Early-term (37–38W)
8520, 77.48%
2477, 22.52%
0.942 (0.892, 0.995)
0.031
0.0372
0.931 (0.882, 0.984)
0.011
0.016
 Full-term (39–40W)
17,022, 76.41%
5254, 23.59%
Reference
  
Reference
  
 Late-term (41–41W)
2140, 77.01%
639, 22.99%
0.974 (0.882, 1.075)
0.597
0.597
0.945 (0.855, 1.045)
0.269
0.269
 Post-term (>41W)
1752, 79.67%
447, 20.33%
1.139 (1.018, 1.276)
0.024
0.036
1.097 (0.979, 1.229)
0.111
0.133
5 years old
24,153, 74.00%
8488, 26.00%
      
 Very-preterm(<31W)
561, 78.46%
154, 21.54%
1.321 (1.098, 1.589)
0.003
0.006
1.293 (1.074, 1.557)
0.007
0.014
 Moderate-preterm(32–33W)
456, 76.64%
139, 23.36%
1.189 (0.978, 1.447)
0.083
0.1245
1.155 (0.949, 1.407)
0.151
0.226
 Late-preterm (34–36W)
2552, 76.73%
774, 23.27%
1.195 (1.088, 1.313)
<0.001
<0.001
1.172 (1.066, 1.288)
0.001
0.006
 Early-term (37–38W)
6134, 73.39%
2224, 26.61%
0.986 (0.929, 1.047)
0.651
0.651
0.979 (0.922, 1.04)
0.491
0.589
 Full-term (39–40W)
11,787, 73.12%
4333, 26.88%
Reference
  
Reference
  
 Late-term (41–41W)
1332, 73.92%
470, 26.08%
1.028 (0.915, 1.154)
0.646
0.651
1.002 (0.892, 1.126)
0.975
0.975
 Post-term (>41W)
1331, 77.16%
394, 22.84%
1.225 (1.084, 1.384)
0.001
0.003
1.209 (1.069, 1.368)
0.002
0.006
CSHQ Children’s Sleep Habit Questionnaire, CI confidence interval, OR odds ratio
aAdjusted for age, gender, eyesight, co-sleep, maternal characteristics and family characteristics
p* value corrected after multiple testing
bStatistically significant results (p < 0.05) are in bold

Association of gestational age with childhood daily sleep hours and sleep disorder

Compared with completely full-term-born children, higher CSHQ scores were observed in very-preterm, moderate-preterm, late-preterm, early-term and post-term categories. Very-preterm, moderate-preterm, late-preterm and post-term birth were associated with higher CSHQ scores (β = 1.827, 1.409, 0.832, and 0.831 respectively, each p<0.001, p correction<0.001, Table 4), and very-preterm, moderate-preterm, late-preterm, early-term and post-term categories were associated with shorter daily sleep hours (β = −0.303, −0.282, −0.201, −0.068 and −0.110 respectively, each p<0.01, p correction <0.01, Table 4) after controlling for confounders and competing exposures. These positive associations of gestational age with the CSHQ scores were also found within all three age groups (Table 4). The significance of post-term with daily sleep hours was only shown in the 3-year-old group (Table 4).
Table 4
The age-specific association between gestational age and score with daily sleep hours and CSHQ score in preschoolers(n=114,311)
 
Daily sleep hours (10.715±2.693)
CSHQ score (46.706±7.576)
Crude β
(95% CI)
p
p*
Adjusted βa
(95% CI)
p
p*
Crude β (95% CI)
p
p*
Adjusted βa
(95% CI)
p
p*
Total
 Very-preterm (<31W)
−0.371 (−0.482, −0.261)
<0.001
<0.001
−0.303 (−0.413, −0.193)
<0.001
<0.001
1.917 (1.606, 2.227)
<0.001
<0.001
1.827 (1.518, 2.136)
<0.001
<0.001
 Moderate-preterm (32–33W)
−0.348 (−0.471, −0.224)
<0.001
<0.001
−0.282 (−0.405, −0.159)
<0.001
<0.001
1.473 (1.127, 1.82)
<0.001
<0.001
1.409 (1.064, 1.754)
<0.001
<0.001
 Late-preterm (34–36W)
−0.275 (−0.332, −0.219)
<0.001
<0.001
−0.201 (−0.258, −0.145)
<0.001
<0.001
0.878 (0.719, 1.037)
<0.001
<0.001
0.832 (0.673, 0.991)
<0.001
<0.001
 Early-term (37–38W)
−0.091 (−0.129, −0.053)
<0.001
<0.001
−0.068 (−0.106, −0.031)
<0.001
<0.001
0.200 (0.094, 0.307)
<0.001
<0.001
0.233 (0.127, 0.339)
<0.001
<0.001
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.072 (0.005, 0.138)
0.035
0.0035
0.067 (0.001, 0.133)
0.048
0.048
0.075 (0.112, 0.263)
0.430
0.430
0.005 (0.182, 0.191)
0.959
0.959
 Post-term (>41W)
−0.166 (−0.240, −0.092)
<0.001
<0.001
−0.110 (−0.184, −0.036)
0.003
0.0036
0.901 (0.693, 1.109)
<0.001
<0.001
0.831 (0.624, 1.039)
<0.001
<0.001
3 years old
 Very-preterm(<31W)
−0.54 (−0.735, −0.345)
<0.001
<0.001
−0.473 (−0.667, −0.279)
<0.001
<0.001
2.240 (1.704, 2.776)
<0.001
<0.001
2.154 (1.620, 2.688)
<0.001
<0.001
 Moderate-preterm(32–33W)
−0.448 (−0.675, −0.221)
<0.001
<0.001
−0.397 (−0.623, −0.171)
0.001
0.002
1.836 (1.211, 2.46)
<0.001
<0.001
1.810 (1.188, 2.433)
<0.001
<0.001
 Late-preterm (34–36W)
−0.256 (−0.357, −0.155)
<0.001
<0.001
−0.191 (−0.291, −0.09)
<0.001
<0.001
0.588 (0.31, 0.865)
<0.001
<0.001
0.546 (0.268, 0.823)
<0.001
<0.001
Early-term (37–38W)
−0.077 (−0.141, −0.014)
0.017
0.0204
0.059 (0.123, 0.004)
0.068
0.081
0.180 (0.005, 0.356)
0.044
0.052
0.231 (0.056, 0.406)
0.01
0.012
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.028 (0.139, 0.082)
0.617
0.617
0.032 (0.142, 0.078)
0.571
0.571
0.074 (0.379, 0.231)
0.634
0.634
0.163 (0.467, 0.141)
0.293
0.293
 Post-term (>41W)
−0.215 (−0.348, −0.083)
0.001
0.0015
−0.166 (−0.298, −0.034)
0.014
0.021
0.927 (0.562, 1.292)
<0.001
<0.001
0.845 (0.481, 1.209)
<0.001
<0.001
4 years old
 Very-preterm(<31W)
−0.315 (−0.491, −0.14)
<0.001
<0.001
−0.248 (−0.423, −0.073)
0.005
0.010
1.771 (1.279, 2.263)
<0.001
<0.001
1.648 (1.157, 2.139)
<0.001
<0.001
 Moderate-preterm(32–33W)
−0.237 (−0.43, −0.043)
0.016
0.024
0.161 (0.353, 0.032)
0.102
0.122
1.472 (0.93, 2.014)
<0.001
<0.001
1.374 (0.833, 1.914)
<0.001
<0.001
 Late-preterm (34–36W)
−0.236 (−0.328, −0.145)
<0.001
<0.001
−0.166 (−0.258, −0.074)
<0.001
<0.001
1.018 (0.762, 1.275)
<0.001
<0.001
0.954 (0.697, 1.211)
<0.001
<0.001
 Early-term (37–38W)
−0.113 (−0.174, −0.051)
<0.001
<0.001
−0.089 (−0.151, −0.028)
0.004
0.010
0.255 (0.083, 0.427)
0.0036
0.0043
0.283 (0.111, 0.455)
0.001
0.0012
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.118 (0.012, 0.224)
0.029
0.0348
0.109 (0.004, 0.215)
0.042
0.063
0.308 (0.011, 0.605)
0.042
0.042
0.262 (0.034, 0.557)
0.083
0.083
 Post-term (>41W)
−0.126 (−0.244, −0.009)
0.035
0.035
0.077 (0.194, 0.04)
0.198
0.198
1.022 (0.692, 1.352)
<0.001
<0.001
0.900 (0.571, 1.229)
<0.001
<0.001
5 years old
 Very-preterm(<31W)
−0.254 (−0.462, −0.047)
0.016
0.032
0.196 (0.403, 0.011)
0.063
0.094
1.823 (1.227, 2.419)
<0.001
<0.001
1.731 (1.137, 2.326)
<0.001
<0.001
 Moderate-preterm(32–33W)
−0.37 (−0.597, −0.144)
0.001
0.003
−0.329 (−0.555, −0.104)
0.004
0.012
1.221 (0.57, 1.872)
<0.001
<0.001
1.112 (0.463, 1.761)
<0.001
<0.001
 Late-preterm (34–36W)
−0.31 (−0.414, −0.207)
<0.001
<0.001
−0.249 (−0.353, −0.146)
<0.001
<0.001
1.046 (0.749, 1.343)
<0.001
<0.001
0.953 (0.655, 1.251)
0.001
0.0015
 Early-term (37–38W)
0.074 (0.147, 0.001)
0.046
0.0552
0.05 (0.123, 0.023)
0.182
0.182
0.162 (0.048, 0.372)
0.130
0.156
0.176 (0.034, 0.386)
0.101
0.120
Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.124 (0.011, 0.259)
0.071
0.071
0.129 (0.005, 0.264)
0.056
0.094
0.112 (0.499, 0.275)
0.571
0.571
0.175 (0.561, 0.211)
0.375
0.375
 Post-term (>41W)
0.145 (0.282, 0.007)
0.039
0.0552
0.091 (0.228, 0.046)
0.179
0.182
0.78 (0.385, 1.175)
<0.001
<0.001
0.724 (0.330, 1.118)
<0.001
<0.001
Daily sleep hours=5/7*sleep hours on weekdays +2/7*sleep hours at the weekends
CSHQ Children’s Sleep Habit Questionnaire, CI confidence interval
aAdjusted for age, gender, eyesight, co-sleep, maternal characteristics and family characteristics
p* value corrected after multiple testing
bStatistically significant results (p < 0.05) are in bold
The associations between very-preterm, moderate-preterm, late-preterm and post-term categories with the CSHQ subscale scores were found in six subscales but not bedtime resistance or sleep onset delay (Table 5).
Table 5
The age-specific association between gestational age with subscale score of CSHQ in preschoolers of different age (n=114,311)
Gestational age
Bedtime resistance
Sleep onset delay
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Total
 Very-preterm(<31W)
0.056 (−0.036, 0.149)
0.234
0.2808
0.116 (0.025, 0.207)
0.012
0.036
0.057 (0.028, 0.085)
<0.001
<0.001
0.049 (0.021, 0.078)
0.001
0.006
 Moderate-preterm(32–33W)
0.08 (−0.023, 0.183)
0.129
0.1935
0.149 (0.047, 0.25)
0.004
0.024
0.054 (0.022, 0.086)
0.001
0.003
0.047 (0.016, 0.079)
0.003
0.009
 Late-preterm (34–36W)
−0.037 (−0.084, 0.011)
0.128
0.1935
0.048 (0.002, 0.095)
0.043
0.082
0.021 (0.007, 0.036)
0.005
0.010
0.016 (0.001, 0.031)
0.032
0.064
 Early-term (37–38W)
−0.046 (−0.078, −0.014)
0.004
0.012
−0.008 (−0.04, 0.023)
0.603
0.603
−0.001 (−0.011, 0.008)
0.772
0.772
−0.002 (−0.011, 0.008)
0.745
0.745
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.088 (0.032, 0.144)
0.002
0.012
0.054 (−0.001, 0.109)
0.055
0.082
0.017 (0, 0.034)
0.057
0.085
0.012 (−0.005, 0.03)
0.160
0.240
 Post-term (>41W)
−0.003 (−0.065, 0.059)
0.921
0.921
0.052 (−0.009, 0.113)
0.096
0.115
0.013 (−0.006, 0.032)
0.183
0.219
0.01 (−0.009, 0.029)
0.323
0.387
3 years old
 Very-preterm(<31W)
0.095 (−0.066, 0.256)
0.249
0.394
0.149 (−0.010, 0.308)
0.067
0.402
0.095 (0.043, 0.147)
<0.001
<0.001
0.090 (0.038, 0.142)
0.001
0.006
 Moderate-preterm(32–33W)
0.065 (−0.123, 0.252)
0,498
0.597
0.125 (−0.060, 0.310)
0.187
0.561
0.076 (0.016, 0.136)
0.014
0.042
0.069 (0.009, 0.129)
0.025
0.075
 Late-preterm (34–36W)
−0.107 (−0.19, −0.024)
0.012
0.072
−0.04 (−0.123, 0.042)
0.339
0.591
0.001 (−0.026, 0.027)
0.961
0.961
−0.004 (−0.031, 0.022)
0.743
0.743
 Early-term (37–38W)
−0.053 (−0.105, 0.0001)
0.05
0.072
−0.018 (−0.07, 0.034)
0.493
0.591
−0.009 (−0.026, 0.008)
0.285
0.496
−0.008 (−0.025, 0.009)
0.382
0.573
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.052 (−0.039, 0.144)
0.263
0.394
0.024 (−0.066, 0.115)
0.597
0.597
0.015 (−0.015, 0.044)
0.331
0.496
0.009 (−0.021, 0.038)
0.570
0.684
 Post-term (>41W)
0.015 (−0.095, 0.124)
0.795
0.795
0.046 (−0.063, 0.154)
0.408
0.591
−0.011 (−0.046, 0.025)
0.551
0.661
−0.016 (−0.051, 0.019)
0.380
0.573
4 years old
 Very-preterm(<31W)
0.069 (−0.076, 0.215)
0.351
0.526
0.111 (−0.033, 0.255)
0.131
0.196
0.011 (−0.034, 0.056)
0.637
0.637
0.001 (−0.044, 0.046)
0.964
0.964
 Moderate-preterm(32–33W)
0.13 (−0.03, 0.291)
0.112
0.234
0.183 (0.024, 0.342)
0.024
0.134
0.061 (0.011, 0.111)*
0.017
0.102
0.050 (0.0001, 0.1)
0.049
0.201
 Late-preterm (34–36W)
0.007 (−0.069, 0.083)
0.855
0.904
0.07 (−0.005, 0.146)
0.067
0.134
0.008 (−0.016, 0.032)
0.508
0.609
0.001 (−0.023, 0.024)
0.948
0.964
 Early-term (37–38W)
−0.041 (−0.092, 0.01)
0.117
0.234
−0.006 (−0.056, 0.045)
0.830
0.830
0.008 (−0.007, 0.024)
0.301
0.451
0.008 (−0.008, 0.024)
0.336
0.504
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.111 (0.023, 0.199)*
0.014
0.084
0.081 (−0.006, 0.168)
0.067
0.134
0.028 (0.001, 0.056)
0.043
0.112
0.025 (−0.002, 0.053)
0.067
0.201
 Post-term (>41W)
0.006 (−0.092, 0.104)
0.904
0.094
0.029 (−0.068, 0.125)
0.561
0.672
0.03 (−0.001, 0.06)
0.056
0.112
0.023 (−0.007, 0.054)
0.133
0.266
5 years old
 Very-preterm(<31W)
0.06 (−0.115, 0.235)
0.500
0.500
0.086 (−0.088, 0.259)
0.333
0.424
0.085 (0.033, 0.137)*
0.001
0.003
0.074 (0.022, 0.126)
0.005
0.015
 Moderate-preterm(32–33W)
0.126 (−0.065, 0.317)
0.197
0.487
0.125 (−0.064, 0.314)
0.196
0.392
0.038 (−0.019, 0.095)
0.191
0.286
0.028 (−0.029, 0.085)
0.332
0.505
 Late-preterm (34–36W)
0.071 (−0.016, 0.158)
0.112
0.487
0.102 (0.015, 0.189)
0.021
0.126
0.067 (0.041, 0.093)*
<0.001
<0.001
0.054 (0.028, 0.08)
<0.001
<0.001
 Early-term (37–38W)
−0.031 (−0.093, 0.031)
0.325
0.487
−0.003 (−0.064, 0.059)
0.934
0.934
−0.003 (−0.022, 0.015)
0.710
0.852
−0.006 (−0.025, 0.012)
0.490
0.588
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.059 (−0.055, 0.173)
0.311
0487
0.053 (−0.059, 0.166)
0.354
0.424
−0.003 (−0.037, 0.031)
0.860
0.860
−0.006 (−0.04, 0.027)
0.709
0.709
 Post-term (>41W)
0.049 (−0.067, 0.165)
0.411
0.493
0.084 (−0.031, 0.199)
0.151
0.392
0.025 (−0.01, 0.059)
0.162
0.286
0.017 (−0.018, 0.051)
0.337
0.505
Gestational age
Night wakings
Parasomnia
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Total
 Very-preterm(<31W)
0.237 (0.191, 0.282)
<0.001
<0.01
0.227 (0.181, 0.272)
<0.001
<0.01
0.526 (0.433, 0.619)
<0.001
<0.001
0.515 (0.422, 0.608)
<0.001
<0.001
 Moderate-preterm(32–33W)
0.166 (0.116, 0.217)
<0.001
<0.001
0.163 (0.112, 0.214)
<0.001
<0.001
0.341 (0.237, 0.445)
<0.001
<0.001
0.337 (0.233, 0.441)
<0.001
<0.001
 Late-preterm (34–36W)
0.122 (0.099, 0.146)
<0.001
<0.001
0.117 (0.093, 0.14)
<0.001
<0.001
0.241 (0.193, 0.288)
<0.001
<0.001
0.238 (0.19, 0.286)
<0.001
<0.001
 Early-term (37–38W)
0.036 (0.02, 0.052)
<0.001
<0.001
0.037 (0.022, 0.053)
<0.001
<0.001
0.079 (0.047, 0.111)
<0.001
<0.001
0.085 (0.053, 0.117)
<0.001
<0.001
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.012 (−0.04, 0.015)
0.386
0.386
−0.018 (−0.046, 0.009)
0.190
0.190
−0.001 (−0.057, 0.056)
0.983
0.983
−0.011 (−0.067, 0.045)
0.694
0.694
 Post-term (>41W)
0.089 (0.059, 0.12)
<0.001
<0.001
0.083 (0.052, 0.113)
<0.001
<0.001
0.228 (0.165, 0.29)
<0.001
<0.001
0.221 (0.158, 0.283)
<0.001
<0.001
3years old
 Very-preterm(<31W)
0.246 (0.163, 0.329)
<0.001
<0.01
0.24 (0.157, 0.323)
<0.001
<0.01
0.607 (0.445, 0.769)
<0.001
<0.01
0.599 (0.437, 0.76)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.21 (0.113, 0.307)
<0.001
<0.001
0.213 (0.117, 0.31)
<0.001
<0.001
0.459 (0.27, 0.648)
<0.001
<0.001
0.464 (0.275, 0.652)
<0.001
<0.001
 Late-preterm (34–36W)
0.083 (0.04, 0.126)
<0.001
<0.001
0.082 (0.039, 0.126)
<0.001
<0.001
0.172 (0.088, 0.256)
<0.001
<0.001
0.174 (0.09, 0.258)
<0.001
<0.001
 Early-term (37–38W)
0.024 (−0.003, 0.052)
0.078
0.0936
0.029 (0.002, 0.056)
0.035
0.042
0.07 (0.017, 0.123)
0.009
0.010
0.081 (0.028, 0.134)
0.003
0.0036
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.001 (−0.047, 0.047)
0.995
0.995
−0.007 (−0.055, 0.04)
0.759
0.759
−0.003 (−0.096, 0.089)
0.941
0.941
−0.017 (−0.109, 0.075)
0.715
0.715
 Post-term (>41W)
0.093 (0.036, 0.149)
<0.001
<0.001
0.089 (0.033, 0.146)
0.002
0.003
0.217 (0.107, 0.327)
<0.001
<0.001
0.212 (0.102, 0.322)
<0.001
<0.001
4 years old
 Very-preterm(<31W)
0.23 (0.158, 0.302)
<0.001
<0.01
0.213 (0.142, 0.285)
<0.001
<0.01
0.511 (0.363, 0.658)
<0.001
<0.01
0.493 (0.345, 0.64)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.157 (0.078, 0.236)
<0.001
<0.001
0.141 (0.062, 0.22)
<0.001
<0.001
0.29 (0.127, 0.452)
<0.001
<0.001
0.277 (0.115, 0.44)
0.001
0.0012
 Late-preterm (34–36W)
0.159 (0.121, 0.196)
<0.001
<0.001
0.144 (0.106, 0.182)
<0.001
<0.001
0.283 (0.207, 0.36)
<0.001
<0.001
0.273 (0.195, 0.35)
<0.001
<0.001
 Early-term (37–38W)
0.037 (0.012, 0.062)
0.004
0.0048
0.038 (0.013, 0.063)
0.003
0.0036
0.083 (0.032, 0.135)
0.002
0.0024
0.087 (0.035, 0.138)
0.001
0.012
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.006 (−0.049, 0.038)
0.801
0.801
−0.008 (−0.052, 0.035)
0.709
0.709
0.055 (−0.035, 0.144)
0.230
0.230
0.05 (−0.039, 0.139)
0.274
0.274
 Post-term (>41W)
0.107 (0.058, 0.155)
<0.001
<0.001
0.09 (0.041, 0.138)
<0.001
<0.001
0.293 (0.194, 0.392)
<0.001
<0.001
0.274 (0.175, 0.373)
<0.001
<0.001
5 years old
 Very-preterm(<31W)
0.249 (0.165, 0.333)
<0.001
<0.01
0.233 (0.15, 0.317)
<0.001
<0.01
0.478 (0.301, 0.656)
<0.001
<0.01
0.461 (0.284, 0.639)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.161 (0.069, 0.252)
0.001
0.0015
0.15 (0.059, 0.242)
0.001
0.002
0.326 (0.132, 0.52)
0.001
<0.001
0.312 (0.118, 0.506)
0.002
0.004
 Late-preterm (34–36W)
0.132 (0.09, 0.174)
<0.001
<0.001
0.116 (0.075, 0.158)
<0.001
<0.001
0.271 (0.182, 0.359)
0.001
0.002
0.253 (0.164, 0.343)
<0.001
<0.001
 Early-term (37–38W)
0.05 (0.021, 0.08)
0.001
0.0015
0.047 (0.017, 0.076)
0.002
0.003
0.084 (0.021, 0.146)
0.009
0.0108
0.085 (0.022, 0.148)
0.008
0.009
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.045 (−0.099, 0.01)
0.107
0.107
−0.051 (−0.105, 0.003)
0.065
0.065
−0.086 (−0.202, 0.029)
0.143
0.143
−0.095 (−0.211, 0.02)
0.106
0.106
 Post-term (>41W)
0.081 (0.026, 0.136)
0.004
0.0048
0.069 (0.014, 0.124)
0.014
0.016
0.175 (0.057, 0.293)
0.004
0.006
0.164 (0.046, 0.282)
0.006
0.009
Gestational age
Sleep duration
Sleep anxiety
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Total
 Very-preterm(<31W)
0.255 (0.193, 0.316)
<0.001
<0.01
0.194 (0.133, 0.256)
<0.001
<0.001
0.241 (0.175, 0.308)
<0.001
<0.01
0.180 (0.114, 0.246)
<0.001
<0.001
 Moderate-preterm(32–33W)
0.235 (0.166, 0.304)
<0.001
<0.001
0.17 (0.102, 0.239)
<0.001
<0.001
0.225 (0.151, 0.299)
<0.001
<0.001
0.160 (0.087, 0.233)
<0.001
<0.001
 Late-preterm (34–36W)
0.149 (0.118, 0.181)
<0.001
<0.001
0.078 (0.047, 0.11)
<0.001
<0.001
0.14 (0.106, 0.174)
<0.001
<0.001
0.069 (0.035, 0.103)
<0.001
<0.001
 Early-term (37–38W)
0.036 (0.014, 0.057)
0.001
0.0012
0.012 (−0.009, 0.033)
0.255
0.306
0.035 (0.012, 0.057)
0.003
0.0036
0.011 (−0.011, 0.034)
0.324
0.388
 Full-term (39–40W)
Reference
  
Reference
  
Reference
     
 Late-term (41–41W)
−0.002 (−0.039, 0.036)
0.937
0.937
0.006 (−0.031, 0.043)
0.740
0.740
−0.011 (−0.051, 0.029)
0.590
0.590
−0.003 (−0.042, 0.037)
0.890
0.890
 Post-term (>41W)
0.128 (0.087, 0.17)
<0.001
<0.001
0.084 (0.043, 0.125)
<0.001
<0.001
0.121 (0.076, 0.165)
<0.001
<0.001
0.076 (0.032, 0.12)
0.001
0.0015
3 years old
 Very-preterm(<31W)
0.338 (0.228, 0.449)
<0.001
<0.01
0.277 (0.168, 0.387)
<0.001
<0.01
0.341 (0.223, 0.459)
<0.001
<0.001
0.277 (0.16, 0.394)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.313 (0.184, 0.442)
<0.001
<0.001
0.253 (0.125, 0.381)
<0.001
<0.001
0.313 (0.178, 0.449)
<0.001
<0.001
0.255 (0.121, 0.39)
<0.001
<0.001
 Late-preterm (34–36W)
0.159 (0.102, 0.216)
<0.001
<0.001
0.094 (0.037, 0.151)
0.001
0.002
0.139 (0.078, 0.199)
<0.001
<0.001
0.075 (0.015, 0.135)
0.015
0.030
 Early-term (37–38W)
0.044 (0.008, 0.081)
0.016
0.019
0.024 (−0.012, 0.06)
0.186
0.223
0.041 (0.003, 0.079)
0.036
0.043
0.021 (−0.017, 0.059)
0.281
0.337
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.001 (−0.063, 0.063)
0.989
0.989
0.006 (−0.056, 0.068)
0.851
0.851
−0.012 (−0.079, 0.054)
0.717
0.717
−0.006 (−0.072, 0.06)
0.854
0.854
 Post-term (>41W)
0.116 (0.04, 0.191)
0.003
0.004
0.077 (0.003, 0.152)
0.043
0.064
0.094 (0.015, 0.172)
0.002
0.003
0.056 (−0.022, 0.135)
0.157
0.235
4 years old
 Very-preterm(<31W)
0.199 (0.1, 0.297)
<0.001
<0.01
0.142 (0.044, 0.24)
0.005
0.010
0.192 (0.086, 0.297)
<0.001
<0.01
0.136 (0.031, 0.241)
0.011
0.024
 Moderate-preterm(32–33W)
0.239 (0.131, 0.348)
<0.001
<0.001
0.176 (0.069, 0.284)
0.001
0.006
0.212 (0.096, 0.328)
<0.001
<0.001
0.149 (0.033, 0.264)
0.012
0.024
 Late-preterm (34–36W)
0.136 (0.085, 0.187)
<0.001
<0.001
0.075 (0.023, 0.126)
0.004
0.010
0.13 (0.075, 0.185)
<0.001
<0.001
0.071 (0.016, 0.126)
0.011
0.024
 Early-term (37–38W)
0.041 (0.006, 0.075)
0.020
0.0240
0.018 (−0.017, 0.052)
0.310
0.310
0.047 (0.01, 0.083)
0.013
0.015
0.023 (−0.013, 0.06)
0.213
0.255
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
0.022 (−0.037, 0.082)
0.462
0.462
0.031 (−0.028, 0.09)
0.307
0.310
0.017 (−0.047, 0.08)
0.606
0.606
0.027 (−0.036, 0.09)
0.400
0.400
 Post-term (>41W)
0.101 (0.035, 0.167)
0.003
0.004
0.065 (0, 0.131)
0.051
0.076
0.101 (0.03, 0.172)
0.005
0.007
0.064 (−0.007, 0.134)
0.076
0.114
5 years old
 Very-preterm(<31W)
0.222 (0.108, 0.336)
<0.001
<0.001
0.178 (0.065, 0.291)
0.002
0.009
0.177 (0.055, 0.299)
0.005
0.010
0.137 (0.015, 0.258)
0.028
0.048
 Moderate-preterm(32–33W)
0.127 (0.003, 0.251)
0.045
0.067
0.088 (−0.035, 0.211)
0.162
0.243
0.123 (−0.013, 0.258)
0.076
0.114
0.085 (−0.05, 0.219)
0.219
0.285
 Late-preterm (34–36W)
0.125 (0.068, 0.181)
<0.001
<0.001
0.069 (0.013, 0.126)
0.016
0.032
0.119 (0.058, 0.181)
<0.001
<0.001
0.062 (0.001, 0.123)
0.048
0.096
 Early-term (37–38W)
0.015 (−0.026, 0.055)
0.477
0.477
−0.008 (−0.048, 0.032)
0.693
0.693
0.007 (−0.036, 0.051)
0.746
0.746
−0.015 (−0.059, 0.028)
0.488
0.488
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.028 (−0.102, 0.046)
0.458
0.477
−0.033 (−0.106, 0.041)
0.385
0.462
−0.041 (−0.122, 0.039)
0.313
0.375
−0.048 (−0.128, 0.032)
0.238
0.285
 Post-term (>41W)
0.148 (0.073, 0.224)
<0.001
<0.001
0.113 (0.038, 0.188)
0.003
0.009
0.148 (0.066, 0.23)
<0.001
<0.001
0.111 (0.029, 0.192)
0.008
0.048
Gestational age
Sleep disorder breathing
Daytime sleepiness
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Crude β (95% CI)
p
p*
Adjusted β a (95% CI)
p
p*
Total
 Very-preterm(<31W)
0.221 (0.182, 0.26)
<0.001
<0.01
0.208 (0.169, 0.247)
<0.001
<0.01
0.424 (0.315, 0.533)
<0.001
<0.01
0.377 (0.268, 0.486)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.157 (0.113, 0.2)
<0.001
<0.001
0.143 (0.1, 0.187)
<0.001
<0.001
0.32 (0.198, 0.441)
<0.001
<0.001
0.279 (0.158, 0.401)
<0.001
<0.001
 Late-preterm (34–36W)
0.118 (0.098, 0.138)
<0.001
<0.001
0.105 (0.085, 0.125)
<0.001
<0.001
0.196 (0.14, 0.252)
<0.001
<0.001
0.161 (0.105, 0.217)
<0.001
<0.001
 Early-term (37–38W)
0.036 (0.022, 0.049)
<0.001
<0.001
0.034 (0.021, 0.047)
<0.001
<0.001
0.04 (0.002, 0.077)*
0.038
0.0456
0.049 (0.012, 0.086)
0.010
0.012
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.022 (−0.046, 0.001)
0.064
0.064
−0.022 (−0.046, 0.002)
0.067
0.067
0.013 (−0.053, 0.079)
0.699
0.699
−0.007 (−0.072, 0.059)
0.843
0.843
 Post-term (>41W)
0.097 (0.071, 0.123)
<0.001
<0.001
0.085 (0.059, 0.111)
<0.001
<0.001
0.29 (0.217, 0.364)
<0.001
<0.001
0.242 (0.169, 0.314)
<0.001
<0.001
3years old
 Very-preterm(<31W)
0.275 (0.21, 0.339)
<0.001
<0.01
0.267 (0.202, 0.332)
<0.001
<0.01
0.42 (0.223, 0.617)
<0.001
<0.01
0.369 (0.174, 0.565)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.123 (0.048, 0.199)
0.001
0.0015
0.117 (0.041, 0.192)
0.002
0.003
0.401 (0.171, 0.63)
0.001
0.0015
0.377 (0.149, 0.605)
0.001
0.0015
 Late-preterm (34–36W)
0.062 (0.028, 0.095)
<0.001
<0.001
0.056 (0.022, 0.09)
0.001
0.002
0.168 (0.067, 0.27)
0.001
0.0015
0.133 (0.031, 0.234)
0.010
0.0015
 Early-term (37–38W)
0.028 (0.007, 0.049)
0.010
0.0012
0.029 (0.008, 0.05)
0.008
0.0096
0.038 (−0.026, 0.102)
0.246
0.246
0.052 (−0.012, 0.116)
0.112
0.112
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.026 (−0.063, 0.011)
0.168
0.168
−0.029 (−0.065, 0.008)
0.129
0.129
−0.099 (−0.211, 0.013)
0.084
0.1008
−0.131 (−0.242, −0.02)
0.021
0.025
 Post-term (>41W)
0.088 (0.044, 0.133)
<0.001
<0.001
0.081 (0.037, 0.125)
0.001
0.002
0.335 (0.201, 0.468)
<0.001
<0.001
0.283 (0.15, 0.416)
<0.001
<0.001
4 years old
 Very-preterm(<31W)
0.179 (0.117, 0.241)
<0.001
<0.01
0.165 (0.103, 0.228)
<0.001
<0.01
0.444 (0.27, 0.617)
<0.001
<0.01
0.395 (0.222, 0.568)
<0.001
<0.01
 Moderate-preterm(32–33W)
0.16 (0.092, 0.229)
<0.001
<0.001
0.148 (0.08, 0.216)
<0.001
<0.001
0.33 (0.139, 0.521)
0.001
0.0015
0.291 (0.101, 0.481)
0.003
0.0036
 Late-preterm (34–36W)
0.139 (0.107, 0.171)
<0.001
<0.001
0.127 (0.095, 0.16)
<0.001
<0.001
0.2 (0.109, 0.291)
0.001
0.0015
0.175 (0.084, 0.265)
<0.001
<0.001
 Early-term (37–38W)
0.03 (0.008, 0.052)
0.007
0.0084
0.028 (0.006, 0.05)
0.011
0.0132
0.084 (0.023, 0.144)
0.007
0.0084
0.093 (0.033, 0.154)
0.003
0.0036
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.009 (−0.047, 0.028)
0.630
0.630
−0.008 (−0.046, 0.029)
0.658
0.658
0.099 (−0.006, 0.203)
0.065
0.065
0.087 (−0.017, 0.191)
0.102
0.102
 Post-term (>41W)
0.115 (0.073, 0.157)
<0.001
<0.001
0.104 (0.062, 0.145)
<0.001
<0.001
0.313 (0.197, 0.43)
<0.001
<0.001
0.262 (0.146, 0.378)
<0.001
<0.001
5 years old
 Very-preterm(<31W)
0.217 (0.14, 0.295)
<0.001
<0.01
0.205 (0.128, 0.282)
<0.001
<0.01
0.377 (0.177, 0.576)
<0.001
<0.01
0.36 (0.161, 0.558)
0.001
0.003
 Moderate-preterm(32–33W)
0.174 (0.09, 0.258)
<0.001
<0.001
0.163 (0.079, 0.247)
<0.001
<0.001
0.194 (−0.023, 0.412)
0.080
0.120
0.172 (−0.045, 0.389)
0.120
0.180
 Late-preterm (34–36W)
0.136 (0.098, 0.175)
<0.001
<0.001
0.124 (0.085, 0.162)
<0.001
<0.001
0.184 (0.085, 0.284)
<0.001
<0.001
0.174 (0.074, 0.273)
0.001
0.003
 Early-term (37–38W)
0.052 (0.024, 0.079)
<0.001
<0.001
0.049 (0.021, 0.076)
<0.001
<0.015
−0.019 (−0.089, 0.051)
0.599
0.599
−0.006 (−0.076, 0.065)
0.877
0.877
 Full-term (39–40W)
Reference
  
Reference
  
Reference
  
Reference
  
 Late-term (41–41W)
−0.034 (−0.084, 0.016)
0.184
0.184
−0.035 (−0.085, 0.015)
0.166
0.166
0.042 (−0.088, 0.171)
0.528
0.599
0.011 (−0.118, 0.14)
0.868
0.877
 Post-term (>41W)
0.075 (0.023, 0.126)
0.004
0.0048
0.067 (0.016, 0.118)
0.010
0.012
0.188 (0.056, 0.321)#
0.005
0.010
0.169 (0.037, 0.300)
0.012
0.024
CSHQ Children’s Sleep Habit Questionnaire, CI confidence interval, OR odds ratio
aAdjusted for age, gender, eyesight, co-sleep, maternal characteristics, and family characteristics
p* value corrected after multiple testing
bStatistically significant results (p < 0.05) are in bold
Gestational age predicted pediatric sleep disorder (i.e. CHSQ>41; adjusted odds ratio (AOR) = 1.287 95% CI (1.157, 1.433), 1.249 95% CI (1.110, 1.405), 1.111 95%CI (1.052, 1·174), and 1.139 95%CI (1.061, 1.222), for the very-preterm, moderate-preterm, late-preterm, and post-term birth, respectively, each p<0.001, p correction <0.001, Table 3), after controlling for all the confounders and competing exposures. The associations were also evident in different age groups, mainly in the preterm and post-term categories (Table 3).
Based on these results in linear and logistic regression models, the associations between gestational ages and childhood daily sleep hours and childhood sleep disorders have been established, especially in preterm (including very-preterm, moderate-preterm and late-preterm) and post-term when compared with completely full-term birth (Figs. 2 and 3).

Discussion

The current population-based prospective cohort study was the first to investigate the association between gestational age across the full range of sleep outcomes in preschoolers. Our study demonstrated that 3–5-year-old children born very-preterm (<31 weeks), moderate-preterm (32–33 weeks), late-preterm (34–36 weeks), early-term (37–38 weeks) and post-term (>41 weeks) were more likely to have sleep problems including having shorter daily sleep hours and a higher odds of sleep disorders, compared to their full-term-born peers, as reported by their parents. Moreover, preterm and post-term children have different sleep profiles as suggested by the different subscales of the CSHQ.
In the present study, a prevalence of sleep disorders was reported with a nationally representative sample in China. Sleep disorder defined with a CSHQ score higher than 41 was found to be prevalent in up to 81.27% of the very-preterm group, 80.67% of the moderate-preterm group, 78.62% of the late-preterm group, 76.58% of the early-term group, 76.02% of the full-term group and 79.17% of the post-term group. The remarkably high incidence of CHSQ-indicated sleep disorders is consistent with previous studies which also reported a very high prevalence of sleep disorders measured by the CSHQ in Chinese [4144] and Japanese preschoolers [41], compared to a prevalence of sleep disorders reported in other populations 20–30% in the western population [2, 45]. Our results suggest the cultural features in sleep behaviours of children, and a local standard is required when using the CSHQ to define sleep disorders in children in East Asian countries.
In the present study, we found that sleep disorder as defined by CSHQ scores was significantly higher in all preterm groups compared with the full-term group. Our findings were consistent with previous work which also found that preterm children were more likely to have adverse sleep outcomes compared with full-term children even beyond infancy. The association between preterm birth and sleep problems in children beyond infancy have been reported by studies in both preschool ages [4648] and school ages [10], and our results further suggest that preterm-born preschoolers, especially very-preterm (<31 weeks), were more likely to have sleep disorder consistently across our age range from 3 to 5 years old. Moreover, when we compared individual sleep subscales in the CSHQ, including Bedtime Resistance, Sleep Onset Delay, Sleep Duration, Sleep Anxiety, Night Wakings, Parasomnias, Sleep Disordered Breathing and Daytime Sleepiness, a significant difference between the very-preterm/moderate-preterm and full-term groups was found in all subscales. The preterm groups also showed significantly shorter daily sleep hours compared to full-term children. These results suggest that preterm children may have a global sleep problem. The results are different from a previous study that found preterm preschoolers had higher total scores in the CSHQ but not on any of the subscales [47], which may be associated with their small sample sizes (137 preterms vs. 145 full-term children aged 4–6 years old). As demonstrated by previous studies, circadian rhythms of the foetus are developing in the second trimester and mature in the third trimester [49, 50]. The cycles of foetal activity were reported to show a significant increase in cycle length with advancing gestation [51]. The last few weeks of gestation (37–41 weeks) could therefore be considered as the critical period for sleep patterns as circadian rhythms are established. On the other hand, the shorter daily sleep duration and more sleep problems in bedtime resistance and sleep onset delay of preterm children may also reflect other factors associated with preterm birth. A growing body of evidence indicates that unmodulated parental care and noncircadian environmental conditions may be detrimental to the establishment of circadian rhythms [5255]. More behaviour problems and more social segregation have also been observed in children born preterm compared to full-term [56, 57]. As a consequence, these factors may also contribute to the shorter sleep duration and sleep problems of preterm children. Extrinsic and behavioural aspects of the sleep problems of preterm children might be worth investigating in future research.
The current study also shows that some sleep outcomes of early-term children (37–38 weeks) were more likely to be affected compared with those of full-term children. Not only preterm birth but also early-term birth can cause disruption at specific periods during the development of neural connections for specific brain areas which can affect sleep patterns [58]. A systematic review has suggested that early-term infants had poorer outcomes in school performance, neurodevelopment, behaviour and emotional status and long-term social outcomes [58]. Sleep disturbance might be associated with a loss of active cortical and cerebellar development between 34 and 40 weeks of gestation [59]. A cohort study also found that early-term deliveries were associated with a higher rate of pediatric obstructive sleep apnea (OSA), which decreases gradually as gestational age advances [60]. The sleep problems of early-term-born children may be mild and the differences are only revealed with large samples, as in the current study. In the present study, the altered sleep outcomes in early-term-born children faded in the 5-year age group. The results further suggested that the mild sleep problems observed in 3- and 4-year-old early-term-born children can be moderated by biological maturation or relevant social factors as children mature. To our knowledge, our study is the first to report sleep problems in early-term birth, which suggests that children born early-term should also be monitored more carefully due to the higher odds of experiencing sleep problems.
One important finding of the current study is that an association between post-term birth (>41 weeks) and altered sleep outcomes were observed. Previous studies have suggested that post-term birth may be associated with a range of adverse neurological, developmental, behavioural and emotional outcomes in early childhood [14, 19, 61]. Mechanisms concerning post-term birth with a higher risk of sleep disorder and shorter daily sleep hours might involve placental deterioration or insufficiency causing foetal hypoxia or nutritional deficiencies, which in turn could result in injury to the foetal brain [62]. Meconium aspiration, which is more common in post-term birth, may result in neonatal asphyxia thereby increasing the risk for brain injury and later neurodevelopmental problems [62, 63]. Lower melatonin concentration in post-term children might also contribute to a higher risk of sleep problems in post-term-born children [64].
Moreover, it should also be noted that the post-term children had different sleep profiles from preterm children as shown by subscales of the CSHQ. Preterm children showed more difficulties getting to bed (i.e. Bedtime Resistance) and longer periods of awake before sleep (i.e. Sleep Onset Delay) compared to post-term children. There were similar rates of co-sleeping in our preterm and post-term groups, and differences in these sleep behaviour problems between children born preterm and post-term might reflect other parental styles of managing bedtime routines. For example, increased parental concerns with preterm-born children could result in earlier bedtimes [65]. Previous studies also found that increased time was spent in bed in preterm children, irrespective of sleep duration [7], thus arbitrarily reducing sleep efficiency. These findings suggested that parental concern related to preterm does not automatically lead to longer sleep durations, but may lead to a longer sleep onset delay of preterm children. Similarly, the bedtime resistance of preterm children may also be associated with the altered parent-child relationship and the parenting style [66]. Previous research has shown that children with difficulties falling asleep/bedtime resistance are more likely to have parents with a higher level of parental stress [67]. Extinction for bedtime resistance involves requiring children to go to bed and stay in bed and minimizing parental attention thereafter. However, if parents have increased concerns about preterm children, this can lead to the development of substantial bedtime resistance behaviours [68]. On the other hand, parents of post-term-born children may overlook the long-term effect of the prolonged gestation of their child [69], which protects these children from the possible influences of social factors that could cause the delay in sleep onset times and bedtime resistance. Moreover, the shorter daily sleep duration of post-term children compared to full-term births was only observed in the 3- and 4-year-old group, but not in the 5-year-old group, which also suggested the sleep duration of post-term children can be improved by biological maturation or relevant social factors such as a more structured daily sleep routine in nursery. These environmental and behavioural aspects of the sleep problems of preterm and post-term children will need to be further examined in future research.

Strengths and limitations

The main strength of our study was that we included and controlled for a wide range of possible confounding variables including prenatal, antenatal, and postnatal characteristics, and child and family characteristics. Another strength was that we used a nationwide large population sample, and we examined the gestational ages across the full range from preterm to post-term. Our study also had several limitations. First, we did not include all the covariates when analysing the relationship of gestational age with sleep outcomes. For example, some covariates such as maternal sleep of the mothers during pregnancy were not included in the current study but have been shown to affect childhood sleep [30]. Second, the reliance on parent-report information may raise the possibility of a differential misclassification. For example, parents of preterm children, especially very-preterm, may exaggerate the sleep problems of their preterm-born children. Thus large-scale studies using objective measures of sleep such as polysomnography PSG or actigraphy instead of parent reports would add substantially to the theoretical and practical utility of future findings. Fourthly, multiple testing exists in our analysis which may increase the probability of false positives. However, we used the Benjamini-Hochberg false discovery rate method for correction. Finally, it should be noted that some of the reported effect sizes were relatively small. However, the results still have clinical and public health relevance as preterm, early-term and post-term birth can affect a large segment of the population, and the results of the current study can also provide evidence for determining a composite risk.

Conclusions

This cohort study demonstrated that every degree of preterm, early-term and post-term birth negatively affected sleep outcomes, including an increased tendency of parent-reported pediatric sleep disorders and shorter daily sleep hours compared to full-term children. Preterm and post-term births also showed different sleep profiles with preterm children having more sleep behaviour problems. The findings address a much-needed gap in the literature to date and provide important new evidence to support the associations between gestational age and childhood sleep outcomes. The findings suggest that children born preterm, early-term and post-term should be monitored more carefully concerning their sleep health. The potential biological mechanisms between gestational age and childhood sleep should be further studied.

Acknowledgements

We thank Guixia Chen, Yao Lin, Hongyan Guan, Bolin Cui, Minhui Cao, Lan Zhang, Tingting Wang, Wenjing Wang, and Xujie Mao for their help with the data acquisition. We are grateful to the class teachers in all participating kindergartens for distributing the notification to parents to complete the online questionnaire.

Declarations

The study was approved by the Ethics Committee of Shanghai First Maternity and Infant Hospital (KS18156). All information acquired was kept confidential and was only accessible by the researchers.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Literatur
2.
Zurück zum Zitat Mindell JA, Owens JA. A clinical guide to pediatric sleep: diagnosis and management of sleep problems. 3rd ed. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins; 2015. Mindell JA, Owens JA. A clinical guide to pediatric sleep: diagnosis and management of sleep problems. 3rd ed. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins; 2015.
3.
Zurück zum Zitat de Groot ER, Knoop MS, van den Hoogen A, Wang X, Long X, Pillen S, Benders M, Dudink J. The value of cardiorespiratory parameters for sleep state classification in preterm infants: a systematic review. Sleep Med Rev. 2021;58: 101462.PubMedCrossRef de Groot ER, Knoop MS, van den Hoogen A, Wang X, Long X, Pillen S, Benders M, Dudink J. The value of cardiorespiratory parameters for sleep state classification in preterm infants: a systematic review. Sleep Med Rev. 2021;58: 101462.PubMedCrossRef
4.
Zurück zum Zitat Werth J, Atallah L, Andriessen P, Long X, Zwartkruis-Pelgrim E, Aarts RM. Unobtrusive sleep state measurements in preterm infants - a review. Sleep Med Rev. 2017;32:109–22.PubMedCrossRef Werth J, Atallah L, Andriessen P, Long X, Zwartkruis-Pelgrim E, Aarts RM. Unobtrusive sleep state measurements in preterm infants - a review. Sleep Med Rev. 2017;32:109–22.PubMedCrossRef
5.
Zurück zum Zitat Hibbs AM, Storfer-Isser A, Rosen C, Ievers-Landis CE, Taveras EM, Redline S. Advanced sleep phase in adolescents born preterm. Behav Sleep Med. 2014;12(5):412–24.PubMedCrossRef Hibbs AM, Storfer-Isser A, Rosen C, Ievers-Landis CE, Taveras EM, Redline S. Advanced sleep phase in adolescents born preterm. Behav Sleep Med. 2014;12(5):412–24.PubMedCrossRef
6.
Zurück zum Zitat Maurer N, Perkinson-Gloor N, Stalder T, Hagmann-von Arx P, Brand S, Holsboer-Trachsler E, Wellmann S, Grob A, Weber P, Lemola S. Salivary and hair glucocorticoids and sleep in very preterm children during school age. Psychoneuroendocrinology. 2016;72:166–74.PubMedCrossRef Maurer N, Perkinson-Gloor N, Stalder T, Hagmann-von Arx P, Brand S, Holsboer-Trachsler E, Wellmann S, Grob A, Weber P, Lemola S. Salivary and hair glucocorticoids and sleep in very preterm children during school age. Psychoneuroendocrinology. 2016;72:166–74.PubMedCrossRef
7.
Zurück zum Zitat Stangenes KM, Fevang SK, Grundt J, Donkor HM, Markestad T, Hysing M, Elgen IB, Bjorvatn B. Children born extremely preterm had different sleeping habits at 11 years of age and more childhood sleep problems than term-born children. Acta Paediatr. 2017;106(12):1966–72.PubMedCrossRef Stangenes KM, Fevang SK, Grundt J, Donkor HM, Markestad T, Hysing M, Elgen IB, Bjorvatn B. Children born extremely preterm had different sleeping habits at 11 years of age and more childhood sleep problems than term-born children. Acta Paediatr. 2017;106(12):1966–72.PubMedCrossRef
8.
Zurück zum Zitat Yiallourou SR, Arena BC, Wallace EM, Odoi A, Hollis S, Weichard A, Horne RSC. Being born too small and too early may alter sleep in childhood. Sleep. 2018;41(2):1–11. Yiallourou SR, Arena BC, Wallace EM, Odoi A, Hollis S, Weichard A, Horne RSC. Being born too small and too early may alter sleep in childhood. Sleep. 2018;41(2):1–11.
9.
Zurück zum Zitat Perkinson-Gloor N, Hagmann-von Arx P, Brand S, Holsboer-Trachsler E, Grob A, Weber P, Lemola S. The role of sleep and the hypothalamic-pituitary-adrenal axis for behavioral and emotional problems in very preterm children during middle childhood. J Psychiatr Res. 2015;60:141–7.PubMedCrossRef Perkinson-Gloor N, Hagmann-von Arx P, Brand S, Holsboer-Trachsler E, Grob A, Weber P, Lemola S. The role of sleep and the hypothalamic-pituitary-adrenal axis for behavioral and emotional problems in very preterm children during middle childhood. J Psychiatr Res. 2015;60:141–7.PubMedCrossRef
10.
Zurück zum Zitat Visser SSM, van Diemen WJM, Kervezee L, van den Hoogen A, Verschuren O, Pillen S, Benders M, Dudink J. The relationship between preterm birth and sleep in children at school age: a systematic review. Sleep Med Rev. 2021;57: 101447.PubMedCrossRef Visser SSM, van Diemen WJM, Kervezee L, van den Hoogen A, Verschuren O, Pillen S, Benders M, Dudink J. The relationship between preterm birth and sleep in children at school age: a systematic review. Sleep Med Rev. 2021;57: 101447.PubMedCrossRef
11.
Zurück zum Zitat Persson M, Opdahl S, Risnes K, Gross R, Kajantie E, Reichenberg A, Gissler M, Sandin S. Gestational age and the risk of autism spectrum disorder in Sweden, Finland, and Norway: a cohort study. PLoS Med. 2020;17(9): e1003207.PubMedPubMedCentralCrossRef Persson M, Opdahl S, Risnes K, Gross R, Kajantie E, Reichenberg A, Gissler M, Sandin S. Gestational age and the risk of autism spectrum disorder in Sweden, Finland, and Norway: a cohort study. PLoS Med. 2020;17(9): e1003207.PubMedPubMedCentralCrossRef
12.
Zurück zum Zitat Odd D, Glover Williams A, Winter C, Draycott T. Associations between early term and late/post term infants and development of epilepsy: a cohort study. PLoS ONE. 2018;13(12):e0210181.PubMedPubMedCentralCrossRef Odd D, Glover Williams A, Winter C, Draycott T. Associations between early term and late/post term infants and development of epilepsy: a cohort study. PLoS ONE. 2018;13(12):e0210181.PubMedPubMedCentralCrossRef
13.
Zurück zum Zitat Lahti M, Eriksson JG, Heinonen K, Kajantie E, Lahti J, Wahlbeck K, Tuovinen S, Pesonen AK, Mikkonen M, Osmond C, et al. Late preterm birth, post-term birth, and abnormal fetal growth as risk factors for severe mental disorders from early to late adulthood. Psychol Med. 2015;45(5):985–99.PubMedCrossRef Lahti M, Eriksson JG, Heinonen K, Kajantie E, Lahti J, Wahlbeck K, Tuovinen S, Pesonen AK, Mikkonen M, Osmond C, et al. Late preterm birth, post-term birth, and abnormal fetal growth as risk factors for severe mental disorders from early to late adulthood. Psychol Med. 2015;45(5):985–99.PubMedCrossRef
14.
Zurück zum Zitat El Marroun H, Zeegers M, Steegers EA, van der Ende J, Schenk JJ, Hofman A, Jaddoe VW, Verhulst FC, Tiemeier H. Post-term birth and the risk of behavioural and emotional problems in early childhood. Int J Epidemiol. 2012;41(3):773–81.PubMedCrossRef El Marroun H, Zeegers M, Steegers EA, van der Ende J, Schenk JJ, Hofman A, Jaddoe VW, Verhulst FC, Tiemeier H. Post-term birth and the risk of behavioural and emotional problems in early childhood. Int J Epidemiol. 2012;41(3):773–81.PubMedCrossRef
15.
Zurück zum Zitat Caughey AB, Snegovskikh VV, Norwitz ER. Postterm pregnancy: how can we improve outcomes? Obstet Gynecol Surv. 2008;63(11):715–24.PubMedCrossRef Caughey AB, Snegovskikh VV, Norwitz ER. Postterm pregnancy: how can we improve outcomes? Obstet Gynecol Surv. 2008;63(11):715–24.PubMedCrossRef
17.
Zurück zum Zitat Simon L, Nusinovici S, Flamant C, Cariou B, Rouger V, Gascoin G, Darmaun D, Roze JC, Hanf M. Post-term growth and cognitive development at 5 years of age in preterm children: evidence from a prospective population-based cohort. PLoS ONE. 2017;12(3):e0174645.PubMedPubMedCentralCrossRef Simon L, Nusinovici S, Flamant C, Cariou B, Rouger V, Gascoin G, Darmaun D, Roze JC, Hanf M. Post-term growth and cognitive development at 5 years of age in preterm children: evidence from a prospective population-based cohort. PLoS ONE. 2017;12(3):e0174645.PubMedPubMedCentralCrossRef
18.
Zurück zum Zitat Movsas TZ, Paneth N. The effect of gestational age on symptom severity in children with autism spectrum disorder. J Autism Dev Disord. 2012;42(11):2431–9.PubMedCrossRef Movsas TZ, Paneth N. The effect of gestational age on symptom severity in children with autism spectrum disorder. J Autism Dev Disord. 2012;42(11):2431–9.PubMedCrossRef
19.
Zurück zum Zitat Glover Williams A, Odd D. Investigating the association between post-term birth and long term cognitive, developmental and educational impacts: a systematic review and meta-analysis. J Matern Fetal Neonatal Med. 2020;33(7):1253–65.PubMedCrossRef Glover Williams A, Odd D. Investigating the association between post-term birth and long term cognitive, developmental and educational impacts: a systematic review and meta-analysis. J Matern Fetal Neonatal Med. 2020;33(7):1253–65.PubMedCrossRef
20.
Zurück zum Zitat Campbell MK, Ostbye T, Irgens LM. Post-term birth: risk factors and outcomes in a 10-year cohort of Norwegian births. Obstet Gynecol. 1997;89(4):543–8.PubMedCrossRef Campbell MK, Ostbye T, Irgens LM. Post-term birth: risk factors and outcomes in a 10-year cohort of Norwegian births. Obstet Gynecol. 1997;89(4):543–8.PubMedCrossRef
21.
Zurück zum Zitat Norwitz ER, Snegovskikh VV, Caughey AB. Prolonged pregnancy: when should we intervene? Clin Obstet Gynecol. 2007;50(2):547–57.PubMedCrossRef Norwitz ER, Snegovskikh VV, Caughey AB. Prolonged pregnancy: when should we intervene? Clin Obstet Gynecol. 2007;50(2):547–57.PubMedCrossRef
22.
Zurück zum Zitat Jetti A, Poovali S, Stanley KP. Prolonged pregnancy. Obstet Gynaecol Reprod Med. 2008;18(1):7–11.CrossRef Jetti A, Poovali S, Stanley KP. Prolonged pregnancy. Obstet Gynaecol Reprod Med. 2008;18(1):7–11.CrossRef
23.
Zurück zum Zitat Hua J, Barnett AL, Williams GJ, Dai X, Sun Y, Li H, Chen G, Wang L, Feng J, Liu Y, et al. Association of gestational age at birth with subsequent suspected developmental coordination disorder in early childhood in China. JAMA Netw Open. 2021;4(12):e2137581.PubMedPubMedCentralCrossRef Hua J, Barnett AL, Williams GJ, Dai X, Sun Y, Li H, Chen G, Wang L, Feng J, Liu Y, et al. Association of gestational age at birth with subsequent suspected developmental coordination disorder in early childhood in China. JAMA Netw Open. 2021;4(12):e2137581.PubMedPubMedCentralCrossRef
24.
Zurück zum Zitat Weibel J, Lin YS, Landolt HP, Berthomier C, Brandewinder M, Kistler J, Rehm S, Rentsch KM, Meyer M, Borgwardt S, et al. Regular caffeine intake delays REM sleep promotion and attenuates sleep quality in healthy men. J Biol Rhythms. 2021;36(4):384–94.PubMedPubMedCentralCrossRef Weibel J, Lin YS, Landolt HP, Berthomier C, Brandewinder M, Kistler J, Rehm S, Rentsch KM, Meyer M, Borgwardt S, et al. Regular caffeine intake delays REM sleep promotion and attenuates sleep quality in healthy men. J Biol Rhythms. 2021;36(4):384–94.PubMedPubMedCentralCrossRef
25.
Zurück zum Zitat Vigliano P, Galloni GB, Bagnasco I, Delia G, Moletto A, Mana M, Cortese S. Sleep in children with attention-deficit/hyperactivity disorder (ADHD) before and after 6-month treatment with methylphenidate: a pilot study. Eur J Pediatr. 2016;175(5):695–704.PubMedCrossRef Vigliano P, Galloni GB, Bagnasco I, Delia G, Moletto A, Mana M, Cortese S. Sleep in children with attention-deficit/hyperactivity disorder (ADHD) before and after 6-month treatment with methylphenidate: a pilot study. Eur J Pediatr. 2016;175(5):695–704.PubMedCrossRef
26.
Zurück zum Zitat Francois D, Roberts J, Hess S, Probst L, Eksioglu Y. Medical management with diazepam for electrical status epilepticus during slow wave sleep in children. Pediatr Neurol. 2014;50(3):238–42.PubMedCrossRef Francois D, Roberts J, Hess S, Probst L, Eksioglu Y. Medical management with diazepam for electrical status epilepticus during slow wave sleep in children. Pediatr Neurol. 2014;50(3):238–42.PubMedCrossRef
27.
Zurück zum Zitat Tyagi P, Dixit U, Tyagi S, Jain A. Sedative effects of oral midazolam, intravenous midazolam and oral diazepam. J Clin Pediatr Dent. 2012;36(4):383–8.PubMedCrossRef Tyagi P, Dixit U, Tyagi S, Jain A. Sedative effects of oral midazolam, intravenous midazolam and oral diazepam. J Clin Pediatr Dent. 2012;36(4):383–8.PubMedCrossRef
28.
Zurück zum Zitat Owens JA, Spirito A, McGuinn M. The Children’s Sleep Habits Questionnaire (CSHQ): psychometric properties of a survey instrument for school-aged children. Sleep. 2000;23(8):1043–51. Owens JA, Spirito A, McGuinn M. The Children’s Sleep Habits Questionnaire (CSHQ): psychometric properties of a survey instrument for school-aged children. Sleep. 2000;23(8):1043–51.
29.
Zurück zum Zitat Liu Z, Wang G, Tang H, Wen F, Li N: Reliability and validity of the Children's Sleep Habits Questionnaire in preschool-aged Chinese children. Sleep Biol Rhythms. 2014;12(3):187–93. Liu Z, Wang G, Tang H, Wen F, Li N: Reliability and validity of the Children's Sleep Habits Questionnaire in preschool-aged Chinese children. Sleep Biol Rhythms. 2014;12(3):187–93.
30.
Zurück zum Zitat Lyu J, Ye X, Chen Y, Xia Y, Zhu J, Tong S, Yin Y, Qu J, Li S. Children’s sleep may depend on maternal sleep duration during pregnancy: a retrospective study. Nat Sci Sleep. 2020;12:197–207. Lyu J, Ye X, Chen Y, Xia Y, Zhu J, Tong S, Yin Y, Qu J, Li S. Children’s sleep may depend on maternal sleep duration during pregnancy: a retrospective study. Nat Sci Sleep. 2020;12:197–207.
31.
Zurück zum Zitat Zambrana IM, Vollrath ME, Sengpiel V, Jacobsson B, Ystrom E. Preterm delivery and risk for early language delays: a sibling-control cohort study. Int J Epidemiol. 2016;45(1):151–9.PubMedCrossRef Zambrana IM, Vollrath ME, Sengpiel V, Jacobsson B, Ystrom E. Preterm delivery and risk for early language delays: a sibling-control cohort study. Int J Epidemiol. 2016;45(1):151–9.PubMedCrossRef
32.
Zurück zum Zitat Ma J, Li S, Jiang F, Jin X, Shen X, Li F. Co-sleeping and childhood enuresis in China. J Dev Behav Pediatr. 2014;35(1):44–9.PubMedCrossRef Ma J, Li S, Jiang F, Jin X, Shen X, Li F. Co-sleeping and childhood enuresis in China. J Dev Behav Pediatr. 2014;35(1):44–9.PubMedCrossRef
33.
Zurück zum Zitat Barta A. New and revised ICD-10-CM obstetric guidelines. J AHIMA. 2013;84(11):70–2.PubMed Barta A. New and revised ICD-10-CM obstetric guidelines. J AHIMA. 2013;84(11):70–2.PubMed
34.
Zurück zum Zitat Versteeg M, Kappe RF, Knuiman C. Predicting student engagement: the role of academic belonging, social integration, and resilience during COVID-19 emergency remote teaching. Front Public Health. 2022;10:849594.PubMedPubMedCentralCrossRef Versteeg M, Kappe RF, Knuiman C. Predicting student engagement: the role of academic belonging, social integration, and resilience during COVID-19 emergency remote teaching. Front Public Health. 2022;10:849594.PubMedPubMedCentralCrossRef
35.
Zurück zum Zitat Pringle KG, Lee YQ, Weatherall L, Keogh L, Diehm C, Roberts CT, Eades S, Brown A, Smith R, Lumbers ER, et al. Influence of maternal adiposity, preterm birth and birth weight centiles on early childhood obesity in an Indigenous Australian pregnancy-through-to-early-childhood cohort study. J Dev Orig Health Dis. 2019;10(1):39–47.PubMedCrossRef Pringle KG, Lee YQ, Weatherall L, Keogh L, Diehm C, Roberts CT, Eades S, Brown A, Smith R, Lumbers ER, et al. Influence of maternal adiposity, preterm birth and birth weight centiles on early childhood obesity in an Indigenous Australian pregnancy-through-to-early-childhood cohort study. J Dev Orig Health Dis. 2019;10(1):39–47.PubMedCrossRef
36.
Zurück zum Zitat Aronsen S, Conway R, Lally P, Roberts A, Croker H, Beeken RJ, Fisher A. Determinants of sleep quality in 5835 individuals living with and beyond breast, prostate, and colorectal cancer: a cross-sectional survey. J Cancer Surviv. 2021:1–3. Aronsen S, Conway R, Lally P, Roberts A, Croker H, Beeken RJ, Fisher A. Determinants of sleep quality in 5835 individuals living with and beyond breast, prostate, and colorectal cancer: a cross-sectional survey. J Cancer Surviv. 2021:1–3.
37.
Zurück zum Zitat Garfield V. The association between body mass index (BMI) and sleep duration: where are we after nearly two decades of epidemiological research? Int J Environ Res Public Health. 2019;16(22):4327. Garfield V. The association between body mass index (BMI) and sleep duration: where are we after nearly two decades of epidemiological research? Int J Environ Res Public Health. 2019;16(22):4327.
38.
Zurück zum Zitat Williamson AL, Derado J, Barney BJ, Saunders G, Olsen IE, Clark RH, Lawson ML. Longitudinal BMI growth curves for surviving preterm NICU infants based on a large US sample. Pediatrics. 2018;142(3). Williamson AL, Derado J, Barney BJ, Saunders G, Olsen IE, Clark RH, Lawson ML. Longitudinal BMI growth curves for surviving preterm NICU infants based on a large US sample. Pediatrics. 2018;142(3).
39.
Zurück zum Zitat Tennant PWG, Murray EJ, Arnold KF, Berrie L, Fox MP, Gadd SC, Harrison WJ, Keeble C, Ranker LR, Textor J, et al. Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. Int J Epidemiol. 2021;50(2):620–32.PubMedCrossRef Tennant PWG, Murray EJ, Arnold KF, Berrie L, Fox MP, Gadd SC, Harrison WJ, Keeble C, Ranker LR, Textor J, et al. Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. Int J Epidemiol. 2021;50(2):620–32.PubMedCrossRef
40.
Zurück zum Zitat Benjamini Y, Hochberg Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J R Stat Soc B. 1995;57(1):289–300. Benjamini Y, Hochberg Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J R Stat Soc B. 1995;57(1):289–300.
41.
Zurück zum Zitat Takahashi M, Wang G, Adachi M, Jiang F, Jiang Y, Saito M, Nakamura K. Differences in sleep problems between Japanese and Chinese preschoolers: a cross-cultural comparison within the Asian region. Sleep Med. 2018;48:42–8.PubMedCrossRef Takahashi M, Wang G, Adachi M, Jiang F, Jiang Y, Saito M, Nakamura K. Differences in sleep problems between Japanese and Chinese preschoolers: a cross-cultural comparison within the Asian region. Sleep Med. 2018;48:42–8.PubMedCrossRef
42.
Zurück zum Zitat Liu Z, Wang G, Geng L, Luo J, Li N, Owens J. Sleep patterns, sleep disturbances, and associated factors among Chinese urban kindergarten children. Behav Sleep Med. 2016;14(1):100–17.PubMedCrossRef Liu Z, Wang G, Geng L, Luo J, Li N, Owens J. Sleep patterns, sleep disturbances, and associated factors among Chinese urban kindergarten children. Behav Sleep Med. 2016;14(1):100–17.PubMedCrossRef
43.
Zurück zum Zitat Wang G, Xu G, Liu Z, Lu N, Ma R, Zhang E. Sleep patterns and sleep disturbances among Chinese school-aged children: prevalence and associated factors. Sleep Med. 2013;14(1):45–52.PubMedCrossRef Wang G, Xu G, Liu Z, Lu N, Ma R, Zhang E. Sleep patterns and sleep disturbances among Chinese school-aged children: prevalence and associated factors. Sleep Med. 2013;14(1):45–52.PubMedCrossRef
44.
Zurück zum Zitat Li W, Wang G, Yu Z, Ip P, Leng Y, Zhang Y, Zhao J, Zhang J, Jiang Y, Deng Y, et al. Grandparental care and sleep disturbances in preschool children: a population-based prospective cohort study. Sleep Med. 2021;82:165–71.PubMedCrossRef Li W, Wang G, Yu Z, Ip P, Leng Y, Zhang Y, Zhao J, Zhang J, Jiang Y, Deng Y, et al. Grandparental care and sleep disturbances in preschool children: a population-based prospective cohort study. Sleep Med. 2021;82:165–71.PubMedCrossRef
45.
46.
Zurück zum Zitat Romeo DM, Leo G, Lapenta L, Leone D, Turrini I, Brogna C, Gallini F, Cota F, Vento G, Mercuri E. Sleep disorders in low-risk preschool very preterm children. Sleep Med. 2019;63:137–41.PubMedCrossRef Romeo DM, Leo G, Lapenta L, Leone D, Turrini I, Brogna C, Gallini F, Cota F, Vento G, Mercuri E. Sleep disorders in low-risk preschool very preterm children. Sleep Med. 2019;63:137–41.PubMedCrossRef
47.
Zurück zum Zitat Durankus F, Aladag Ciftdemir N, Vatansever Ozbek U, Duran R, Acunas B. Comparison of sleep problems between term and preterm born preschool children. Sleep Med. 2020;75:484–90.PubMedCrossRef Durankus F, Aladag Ciftdemir N, Vatansever Ozbek U, Duran R, Acunas B. Comparison of sleep problems between term and preterm born preschool children. Sleep Med. 2020;75:484–90.PubMedCrossRef
48.
Zurück zum Zitat Manacero S, Nunes ML. Longitudinal study of sleep behavior and motor development in low-birth-weight preterm children from infancy to preschool years. J Pediatr (Rio J). 2021;97(1):44–51.CrossRef Manacero S, Nunes ML. Longitudinal study of sleep behavior and motor development in low-birth-weight preterm children from infancy to preschool years. J Pediatr (Rio J). 2021;97(1):44–51.CrossRef
49.
Zurück zum Zitat Li SF, Wang Y, Li GF, Zhao YY, Chen L, Zhang S. Diurnal rhythm of fetal heart rate in third trimester of pregnancy. Zhonghua Fu Chan Ke Za Zhi. 2018;53(12):849–54.PubMed Li SF, Wang Y, Li GF, Zhao YY, Chen L, Zhang S. Diurnal rhythm of fetal heart rate in third trimester of pregnancy. Zhonghua Fu Chan Ke Za Zhi. 2018;53(12):849–54.PubMed
50.
Zurück zum Zitat Seron-Ferre M, Valenzuela GJ, Torres-Farfan C. Circadian clocks during embryonic and fetal development. Birth Defects Res C Embryo Today. 2007;81(3):204–14.PubMedCrossRef Seron-Ferre M, Valenzuela GJ, Torres-Farfan C. Circadian clocks during embryonic and fetal development. Birth Defects Res C Embryo Today. 2007;81(3):204–14.PubMedCrossRef
51.
Zurück zum Zitat Granat M, Lavie P, Adar D, Sharf M. Short-term cycles in human fetal activity. I. Normal pregnancies. Am J Obstet Gynecol. 1979;134(6):696–701.PubMedCrossRef Granat M, Lavie P, Adar D, Sharf M. Short-term cycles in human fetal activity. I. Normal pregnancies. Am J Obstet Gynecol. 1979;134(6):696–701.PubMedCrossRef
52.
Zurück zum Zitat Johnson DA, Billings ME, Hale L. Environmental determinants of insufficient sleep and sleep disorders: implications for population health. Curr Epidemiol Rep. 2018;5(2):61–9.PubMedPubMedCentralCrossRef Johnson DA, Billings ME, Hale L. Environmental determinants of insufficient sleep and sleep disorders: implications for population health. Curr Epidemiol Rep. 2018;5(2):61–9.PubMedPubMedCentralCrossRef
53.
Zurück zum Zitat Mileva-Seitz VR, Bakermans-Kranenburg MJ, Battaini C, Luijk MP. Parent-child bed-sharing: the good, the bad, and the burden of evidence. Sleep Med Rev. 2017;32:4–27.PubMedCrossRef Mileva-Seitz VR, Bakermans-Kranenburg MJ, Battaini C, Luijk MP. Parent-child bed-sharing: the good, the bad, and the burden of evidence. Sleep Med Rev. 2017;32:4–27.PubMedCrossRef
54.
Zurück zum Zitat Paul IM, Savage JS, Anzman-Frasca S, Marini ME, Mindell JA, Birch LL: INSIGHT responsive parenting intervention and infant sleep. Pediatrics 2016;138(1). Paul IM, Savage JS, Anzman-Frasca S, Marini ME, Mindell JA, Birch LL: INSIGHT responsive parenting intervention and infant sleep. Pediatrics 2016;138(1).
55.
Zurück zum Zitat Wilson KE, Miller AL, Lumeng JC, Chervin RD. Sleep environments and sleep durations in a sample of low-income preschool children. J Clin Sleep Med. 2014;10(3):299–305.PubMedPubMedCentralCrossRef Wilson KE, Miller AL, Lumeng JC, Chervin RD. Sleep environments and sleep durations in a sample of low-income preschool children. J Clin Sleep Med. 2014;10(3):299–305.PubMedPubMedCentralCrossRef
56.
Zurück zum Zitat Talge NM, Holzman C, Wang J, Lucia V, Gardiner J, Breslau N. Late-preterm birth and its association with cognitive and socioemotional outcomes at 6 years of age. Pediatrics. 2010;126(6):1124–31.PubMedCrossRef Talge NM, Holzman C, Wang J, Lucia V, Gardiner J, Breslau N. Late-preterm birth and its association with cognitive and socioemotional outcomes at 6 years of age. Pediatrics. 2010;126(6):1124–31.PubMedCrossRef
57.
Zurück zum Zitat Arpi E, Ferrari F. Preterm birth and behaviour problems in infants and preschool-age children: a review of the recent literature. Dev Med Child Neurol. 2013;55(9):788–96.PubMedCrossRef Arpi E, Ferrari F. Preterm birth and behaviour problems in infants and preschool-age children: a review of the recent literature. Dev Med Child Neurol. 2013;55(9):788–96.PubMedCrossRef
58.
Zurück zum Zitat Dong Y, Chen SJ, Yu JL. A systematic review and meta-analysis of long-term development of early term infants. Neonatology. 2012;102(3):212–21.PubMedCrossRef Dong Y, Chen SJ, Yu JL. A systematic review and meta-analysis of long-term development of early term infants. Neonatology. 2012;102(3):212–21.PubMedCrossRef
59.
Zurück zum Zitat Arpino C, Compagnone E, Montanaro ML, Cacciatore D, De Luca A, Cerulli A, Di Girolamo S, Curatolo P. Preterm birth and neurodevelopmental outcome: a review. Childs Nerv Syst. 2010;26(9):1139–49.PubMedCrossRef Arpino C, Compagnone E, Montanaro ML, Cacciatore D, De Luca A, Cerulli A, Di Girolamo S, Curatolo P. Preterm birth and neurodevelopmental outcome: a review. Childs Nerv Syst. 2010;26(9):1139–49.PubMedCrossRef
60.
Zurück zum Zitat Walfisch A, Wainstock T, Beharier O, Landau D, Sheiner E. Early term deliveries and the risk of pediatric obstructive sleep apnoea in the offspring. Paediatr Perinat Epidemiol. 2017;31(2):149–56.PubMedCrossRef Walfisch A, Wainstock T, Beharier O, Landau D, Sheiner E. Early term deliveries and the risk of pediatric obstructive sleep apnoea in the offspring. Paediatr Perinat Epidemiol. 2017;31(2):149–56.PubMedCrossRef
61.
Zurück zum Zitat Smithers LG, Searle AK, Chittleborough CR, Scheil W, Brinkman SA, Lynch JW. A whole-of-population study of term and post-term gestational age at birth and children’s development. BJOG. 2015;122(10):1303–11. Smithers LG, Searle AK, Chittleborough CR, Scheil W, Brinkman SA, Lynch JW. A whole-of-population study of term and post-term gestational age at birth and children’s development. BJOG. 2015;122(10):1303–11.
62.
Zurück zum Zitat Galal M, Symonds I, Murray H, Petraglia F, Smith R. Postterm pregnancy. Facts Views Vis Obgyn. 2012;4(3):175–87.PubMedPubMedCentral Galal M, Symonds I, Murray H, Petraglia F, Smith R. Postterm pregnancy. Facts Views Vis Obgyn. 2012;4(3):175–87.PubMedPubMedCentral
63.
Zurück zum Zitat Chand S, Salman A, Abbassi RM, Siyal AR, Ahmed F, Leghari AL, Kabani AS, Ali S. Factors leading to meconium aspiration syndrome in term- and post-term neonates. Cureus. 2019;11(9): e5574.PubMedPubMedCentral Chand S, Salman A, Abbassi RM, Siyal AR, Ahmed F, Leghari AL, Kabani AS, Ali S. Factors leading to meconium aspiration syndrome in term- and post-term neonates. Cureus. 2019;11(9): e5574.PubMedPubMedCentral
64.
Zurück zum Zitat Yurtcu N, Caliskan C, Celik S. Serum melatonin as a biomarker for assessment of late-term and postterm pregnancies in women without spontaneous onset of labor. Z Geburtshilfe Neonatol. 2021;225(06):499–505. Yurtcu N, Caliskan C, Celik S. Serum melatonin as a biomarker for assessment of late-term and postterm pregnancies in women without spontaneous onset of labor. Z Geburtshilfe Neonatol. 2021;225(06):499–505.
65.
Zurück zum Zitat Peltz JS, Rogge RD, Connolly H. Parents still matter: the influence of parental enforcement of bedtime on adolescents' depressive symptoms. Sleep. 2020;43(5). Peltz JS, Rogge RD, Connolly H. Parents still matter: the influence of parental enforcement of bedtime on adolescents' depressive symptoms. Sleep. 2020;43(5).
66.
Zurück zum Zitat Bruni O, Lo Reto F, Miano S, Ottaviano S. Daytime behavioral correlates of awakenings and bedtime resistance in preschool children. Suppl Clin Neurophysiol. 2000;53:358–61.PubMedCrossRef Bruni O, Lo Reto F, Miano S, Ottaviano S. Daytime behavioral correlates of awakenings and bedtime resistance in preschool children. Suppl Clin Neurophysiol. 2000;53:358–61.PubMedCrossRef
67.
Zurück zum Zitat Larsen KL, Erp LA, Jordan M, Jordan SS. Bedtime routines of young children, parenting stress, and bedtime resistance: mediation models. Child Psychiatry Hum Dev. 2021:1–9. Larsen KL, Erp LA, Jordan M, Jordan SS. Bedtime routines of young children, parenting stress, and bedtime resistance: mediation models. Child Psychiatry Hum Dev. 2021:1–9.
68.
Zurück zum Zitat Moore BA, Friman PC, Fruzzetti AE, MacAleese K. Brief report: evaluating the Bedtime Pass Program for child resistance to bedtime–a randomized, controlled trial. J Pediatr Psychol. 2007;32(3):283–7.PubMedCrossRef Moore BA, Friman PC, Fruzzetti AE, MacAleese K. Brief report: evaluating the Bedtime Pass Program for child resistance to bedtime–a randomized, controlled trial. J Pediatr Psychol. 2007;32(3):283–7.PubMedCrossRef
69.
Zurück zum Zitat Schierding W, Antony J, Karhunen V, Vaarasmaki M, Franks S, Elliott P, Kajantie E, Sebert S, Blakemore A, Horsfield JA, et al. GWAS on prolonged gestation (post-term birth): analysis of successive Finnish birth cohorts. J Med Genet. 2018;55(1):55–63.PubMedCrossRef Schierding W, Antony J, Karhunen V, Vaarasmaki M, Franks S, Elliott P, Kajantie E, Sebert S, Blakemore A, Horsfield JA, et al. GWAS on prolonged gestation (post-term birth): analysis of successive Finnish birth cohorts. J Med Genet. 2018;55(1):55–63.PubMedCrossRef
Metadaten
Titel
Associations between gestational age and childhood sleep: a national retrospective cohort study
Publikationsdatum
01.12.2022
Erschienen in
BMC Medicine / Ausgabe 1/2022
Elektronische ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-022-02443-9

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