Article(id=1325500802160263599, tenantId=1146029695717560320, journalId=1256213402557890569, issueId=1325500677975318675, articleNumber=null, orderNo=null, doi=10.16835/j.cnki.1000-9817.2025052, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730217600000, receivedDateStr=2024-10-30, revisedDate=1737734400000, revisedDateStr=2025-01-25, acceptedDate=null, acceptedDateStr=null, onlineDate=1793953617847, onlineDateStr=2026-11-06, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793953617847, onlineIssueDateStr=2026-11-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793953617847, creator=13701087609, updateTime=1793953617847, updator=13701087609, issue=Issue{id=1325500677975318675, tenantId=1146029695717560320, journalId=1256213402557890569, year='2025', volume='46', issue='2', pageStart='153', pageEnd='304', issueExtLink='null', onlineDate='null', pubDate='1740412800000', pubDateStr='2025-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793953588241, creator='13701087609', updateTime=1793953588241, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=186, endPage=190, ext={EN=ArticleExt(id=1325500805079499184, articleId=1325500802160263599, tenantId=1146029695717560320, journalId=1256213402557890569, language=EN, title=Latent class analysis of sleep disturbances among children and adolescents with neurodevelopmental disorders in Tianjin, columnId=1325500683088167114, journalTitle=Chinese Journal of School Health, columnName=Column on Physical and Mental Health of Children with Disabilities, runingTitle=null, highlight=null, articleAbstract=
Objective

To understand the latent categories of sleep disturbances among children and adolescents with neurodevelopmental disorders (NDDs) in Tianjin and their relationship with behavioral and social issues, so as to provide a basis for preventing and improving sleep disturbances in the population.

Methods

From September 2021 to June 2024, 272 children and adolescents aged 2-23 years with neurodevelopmental disorders were recruited from special education schools and designated rehabilitation institutions in Tianjin. Sleep disturbances were assessed using the Children's Sleep Habits Questionnaire (CSHQ). Behavioral and social issues and severity were evaluated using the Autism Behavior Checklist (ABC) and Childhood Autism Rating Scale (CARS). Latent class analysis (LCA) was employed to categorize the subjects into different sleep disturbances categories. Cochran-Armitage test was used to analyze the trend of detection rate of sleep disturbances in different age groups. Spearman rank correlation was used to analyze the correlation between the scores of each scale. The generalized linear model was used to analyze the influence of CARS and ABC scale scores. Covariance analysis was used to examine differences in behavioral and social issues among the different categories.

Results

Among 272 survey respondents, a total of 197(72.4%) children and adolescents with NDDs were identified with sleep disturbances. The detection rates of sleep disturbances were 88.9% for those aged 2-6 years, 70.6% for aged 7-12, 66.7% for aged 13-18 and 50.0% for 19-23 years old, which was decreased across age group (Z=3.58, P < 0.01). There was a positive correlation between the total CSHQ score and the total ABC score (r=0.16, P=0.01). The generalized linear model analysis showed that after adjusting age, gender, parents' education level and family monthly income, bedtime habit (β=3.60) and sleeping latency disorder (β=3.36) were positively correlated with CARS scores, while the bedtime habit (β=16.73) and waking up at night (β=17.46) were positively correlated with ABC scores (P < 0.05). LCA revealed that sleep disturbances in children and adolescents with NDDs could be classified into four categories. The covariance analysis results showed that there were statistically significant differences in the average scores of CSHQ (70.84±9.05, 50.96±6.64, 50.33±5.82, 43.84±5.44) and ABC (49.44±39.34, 53.04±39.75, 63.51±40.31, 38.14±34.23) among different categories of all partipants (F=92.09, 3.95, P < 0.05).

Conclusions

Sleep disturbances in children and adolescents with NDDs are severe and exhibit distinct categorical characteristics.

, authors=Penghong LI1, Yifan CHE2, Ziyu ZHAO1, Tingkai CUI*, 1, authorsList=Penghong LI, Yifan CHE, Ziyu ZHAO, Tingkai CUI, authorCompany=null, correspAuthors=Tingkai CUI, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2025 Chinese Journal of School Health. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1325500815233909176, articleId=1325500802160263599, tenantId=1146029695717560320, journalId=1256213402557890569, language=CN, title=天津市神经发育障碍儿童青少年睡眠障碍潜在类别分析, columnId=1325500683864113356, journalTitle=中国学校卫生, columnName=残疾儿童身心健康状况专栏, runingTitle=null, highlight=null, articleAbstract=
目的

了解天津市神经发育障碍儿童青少年睡眠障碍潜在类别及其与行为、社交问题的关系,为预防和改善神经发育障碍儿童青少年睡眠障碍提供依据。

方法

2021年9月至2024年6月,在天津市特殊教育学校和定点康复机构招募272名2~23岁神经发育障碍儿童青少年,采用儿童睡眠习惯问卷(CSHQ)评估睡眠障碍,孤独症儿童行为量表(ABC)、儿童孤独症评定量表(CARS)评估社交、行为问题及孤独症症状严重程度。采用潜在类别分析(LCA)将研究对象分为不同睡眠障碍类别,Cochran-Armitage检验分析不同年龄组睡眠障碍检出率的趋势性;采用Spearman秩相关分析各量表评分的关联,广义线性模型分析睡眠障碍对CARS、ABC量表得分的影响;采用协方差分析不同类别间儿童青少年行为、社交问题的差异。

结果

272名调查对象中,有197名(72.4%)神经发育障碍儿童青少年检出睡眠障碍。不同年龄组睡眠障碍检出率分别为2~6岁88.9%、7~12岁70.6%、13~18岁66.7%、19~23岁50.0%,随年龄增长呈下降趋势(Z=3.58,P < 0.01);CSHQ总分与ABC总分呈正相关(r=0.16,P=0.01)。广义线性模型分析表明,在调整年龄、性别、父母文化程度、家庭月总收入后,就寝习惯(β=3.60)和入睡潜伏期障碍(β=3.36)与CARS得分呈正相关,就寝习惯(β=16.73)和夜醒(β=17.46)与ABC得分呈正相关(P值均 < 0.05)。LCA分析表明,神经发育障碍儿童青少年睡眠障碍可分为4个类别;协方差分析结果显示,不同类别(类别1~4)研究对象CSHQ(70.84±9.05,50.96±6.64,50.33±5.82,43.84±5.44)和ABC(49.44±39.34,53.04±39.75,63.51±40.31,38.14±34.23)平均得分差异均有统计学意义(F值分别为92.09,3.95,P值均 < 0.05)。

结论

神经发育障碍儿童青少年睡眠障碍较严重且可分为不同潜在类别。

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李芃宏(1997-),男,天津市人,在读博士,主要研究方向为儿童青少年神经心理发育

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崔庭凯,E-mail:
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Comparison of sleep disturbances detection rates among children and adolescents with neurodevelopmental disorders by ages and genders

, figureFileSmall=null, figureFileBig=null, tableContent=
组别选项人数统计值睡眠障碍就寝习惯入睡潜伏期睡眠持续时间睡眠焦虑夜醒异态睡眠睡眠呼吸障碍白天嗜睡
性别男199148(74.4)42(21.1)33(16.6)69(34.7)33(16.6)19(9.6)14(7.0)23(11.6)24(12.1)
女7349(67.1)11(15.1)9(12.3)24(32.9)6(8.2)6(8.2)4(5.5)9(12.3)10(13.7)
χ2值1.411.240.740.083.040.110.210.030.13
P值0.240.270.390.780.080.740.650.860.72
年龄/岁2~66356(88.9)21(33.3)9(14.3)27(42.9)10(15.9)6(9.5)1(1.6)3(4.8)8(12.7)
7~1211984(70.6)23(19.3)17(14.3)35(29.4)19(16.0)11(9.2)13(10.9)15(12.6)14(11.8)
13~187248(66.7)6(8.3)14(19.4)27(37.5)7(9.7)5(6.9)2(2.8)10(13.9)9(12.5)
19~23189(50.0)3(16.7)2(11.1)4(22.2)3(16.7)3(16.7)2(11.1)4(22.2)3(16.7)
Z值3.583.18-0.401.100.70-0.21-0.58-2.13-0.29
P值< 0.01< 0.010.690.270.490.830.570.030.77
合计272197(72.4)53(19.5)42(15.4)93(34.2)39(14.3)25(9.2)18(6.6)32(11.8)34(12.5)
), ArticleFig(id=1325500851283952098, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=CN, label=表1, caption=

不同性别和年龄神经发育障碍儿童青少年睡眠障碍检出率比较

, figureFileSmall=null, figureFileBig=null, tableContent=
组别选项人数统计值睡眠障碍就寝习惯入睡潜伏期睡眠持续时间睡眠焦虑夜醒异态睡眠睡眠呼吸障碍白天嗜睡
性别男199148(74.4)42(21.1)33(16.6)69(34.7)33(16.6)19(9.6)14(7.0)23(11.6)24(12.1)
女7349(67.1)11(15.1)9(12.3)24(32.9)6(8.2)6(8.2)4(5.5)9(12.3)10(13.7)
χ2值1.411.240.740.083.040.110.210.030.13
P值0.240.270.390.780.080.740.650.860.72
年龄/岁2~66356(88.9)21(33.3)9(14.3)27(42.9)10(15.9)6(9.5)1(1.6)3(4.8)8(12.7)
7~1211984(70.6)23(19.3)17(14.3)35(29.4)19(16.0)11(9.2)13(10.9)15(12.6)14(11.8)
13~187248(66.7)6(8.3)14(19.4)27(37.5)7(9.7)5(6.9)2(2.8)10(13.9)9(12.5)
19~23189(50.0)3(16.7)2(11.1)4(22.2)3(16.7)3(16.7)2(11.1)4(22.2)3(16.7)
Z值3.583.18-0.401.100.70-0.21-0.58-2.13-0.29
P值< 0.01< 0.010.690.270.490.830.570.030.77
合计272197(72.4)53(19.5)42(15.4)93(34.2)39(14.3)25(9.2)18(6.6)32(11.8)34(12.5)
), ArticleFig(id=1325500851699188195, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=EN, label=Tab.2, caption=

Comparison of sleep time among children and adolescents with neurodevelopmental disorders by ages(x±s)

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄/岁人数平时晚上上床时间a周末晚上上床时间a平时晚上睡着时间a周末晚上睡着时间a平时早晨醒来时间a周末早晨醒来时间a平时早晨起床时间a
2~66321:15±0.7321:39±0.8121:47±0.8022:09±0.856:45±0.747:19±0.866:56±0.70
7~1211921:14±0.7721:39±0.7521:43±0.7322:06±0.736:33±0.547:11±0.836:45±0.52
13~187221:11±0.8521:37±0.9021:38±0.9122:02±0.876:32±0.717:17±1.086:46±0.73
19~231821:07±1.1421:30±1.1321:36±1.0921:59±1.176:27±0.977:03±0.926:42±0.97
合计27221:13±0.8121:38±0.8321:42±0.8222:05±0.836:35±0.687:23±1.726:48±0.66
F值0.190.180.440.331.690.571.24
P值0.900.910.730.810.170.640.30
年龄/岁人数周末早晨起床时间a平时白天小睡时长/hb周末白天小睡时长/hb平时入睡用时/hb周末入睡用时/hb平时起床用时/hb周末起床用时/hb
2~6637:48±0.790.60(0.00, 0.90)0.60(0.00, 1.20)0.30(0.20, 0.40)0.30(0.10, 0.50)0.05(0.00, 0.20)0.30(0.19, 0.30)
7~121197:40±0.770.10(0.00, 0.60)0.30(0.00, 0.60)0.30(0.16, 0.30)0.30(0.15, 0.30)0.10(0.00, 0.20)0.30(0.10, 0.30)
13~18727:51±0.960.60(0.30, 0.90)0.60(0.60, 0.90)0.30(0.05, 0.30)0.30(0.00, 0.30)0.10(0.00, 0.20)0.30(0.30, 0.30)
19~23187:40±0.760.60(0.60, 0.71)0.60(0.60, 1.20)0.30(0.10, 0.60)0.30(0.10, 0.60)0.10(0.00, 0.30)0.30(0.30, 0.06)
合计2727:54±1.680.60(0.00, 0.61)0.60(0.00 0.90)0.30(0.15, 0.30)0.30(0.10, 0.30)0.10(0.00, 0.20)0.30(0.10, 0.30)
F/H值0.7519.7117.501.491.940.403.18
P值0.52< 0.01< 0.010.690.580.940.37
), ArticleFig(id=1325500852512883172, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=CN, label=表2, caption=

不同年龄神经发育障碍儿童青少年睡眠时间比较(x±s)

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄/岁人数平时晚上上床时间a周末晚上上床时间a平时晚上睡着时间a周末晚上睡着时间a平时早晨醒来时间a周末早晨醒来时间a平时早晨起床时间a
2~66321:15±0.7321:39±0.8121:47±0.8022:09±0.856:45±0.747:19±0.866:56±0.70
7~1211921:14±0.7721:39±0.7521:43±0.7322:06±0.736:33±0.547:11±0.836:45±0.52
13~187221:11±0.8521:37±0.9021:38±0.9122:02±0.876:32±0.717:17±1.086:46±0.73
19~231821:07±1.1421:30±1.1321:36±1.0921:59±1.176:27±0.977:03±0.926:42±0.97
合计27221:13±0.8121:38±0.8321:42±0.8222:05±0.836:35±0.687:23±1.726:48±0.66
F值0.190.180.440.331.690.571.24
P值0.900.910.730.810.170.640.30
年龄/岁人数周末早晨起床时间a平时白天小睡时长/hb周末白天小睡时长/hb平时入睡用时/hb周末入睡用时/hb平时起床用时/hb周末起床用时/hb
2~6637:48±0.790.60(0.00, 0.90)0.60(0.00, 1.20)0.30(0.20, 0.40)0.30(0.10, 0.50)0.05(0.00, 0.20)0.30(0.19, 0.30)
7~121197:40±0.770.10(0.00, 0.60)0.30(0.00, 0.60)0.30(0.16, 0.30)0.30(0.15, 0.30)0.10(0.00, 0.20)0.30(0.10, 0.30)
13~18727:51±0.960.60(0.30, 0.90)0.60(0.60, 0.90)0.30(0.05, 0.30)0.30(0.00, 0.30)0.10(0.00, 0.20)0.30(0.30, 0.30)
19~23187:40±0.760.60(0.60, 0.71)0.60(0.60, 1.20)0.30(0.10, 0.60)0.30(0.10, 0.60)0.10(0.00, 0.30)0.30(0.30, 0.06)
合计2727:54±1.680.60(0.00, 0.61)0.60(0.00 0.90)0.30(0.15, 0.30)0.30(0.10, 0.30)0.10(0.00, 0.20)0.30(0.10, 0.30)
F/H值0.7519.7117.501.491.940.403.18
P值0.52< 0.01< 0.010.690.580.940.37
), ArticleFig(id=1325500852907147749, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=EN, label=Tab.3, caption=

Generalized linear model analysis of sleep disturbances and behavior and social disturbances of children and adolescents with neurodevelopmental disorders[β(95%CI), n=272]

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自变量CARSABC
睡眠障碍2.06(-0.81~4.92)8.43(-1.99~18.85)
就寝习惯3.60(0.35~6.86)*16.73(4.92~28.54)*
入睡潜伏期3.36(0.05~6.68)*6.71(-6.37~19.79)
睡眠持续时间0.15(-2.60~2.89)3.73(-5.96~13.42)
睡眠焦虑2.35(-1.58~6.28)6.93(-7.06~20.92)
夜醒4.30(-0.35~8.95)17.46(2.17~32.74)*
异态睡眠2.39(-3.01~7.78)11.35(-8.52~31.22)
睡眠呼吸障碍4.11(-0.00~8.21)7.89(-7.94~23.73)
白天嗜睡-1.32(-5.26~2.62)5.22(-8.71~19.15)
), ArticleFig(id=1325500854127690214, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=CN, label=表3, caption=

神经发育障碍儿童青少年睡眠障碍与行为、社交问题广义线性模型分析[β值(95%CI),n=272]

, figureFileSmall=null, figureFileBig=null, tableContent=
自变量CARSABC
睡眠障碍2.06(-0.81~4.92)8.43(-1.99~18.85)
就寝习惯3.60(0.35~6.86)*16.73(4.92~28.54)*
入睡潜伏期3.36(0.05~6.68)*6.71(-6.37~19.79)
睡眠持续时间0.15(-2.60~2.89)3.73(-5.96~13.42)
睡眠焦虑2.35(-1.58~6.28)6.93(-7.06~20.92)
夜醒4.30(-0.35~8.95)17.46(2.17~32.74)*
异态睡眠2.39(-3.01~7.78)11.35(-8.52~31.22)
睡眠呼吸障碍4.11(-0.00~8.21)7.89(-7.94~23.73)
白天嗜睡-1.32(-5.26~2.62)5.22(-8.71~19.15)
), ArticleFig(id=1325500855423730151, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=EN, label=Tab.4, caption=

Potential class analysis of sleep disturbances in children and adolescents with neurodevelopmental disorders(n=272)

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类别数dfAIC值BIC值aBIC值EntropyPLMR值PBLRT值类别概率
181 792.911 821.761 796.39———1.00
2171 693.991 755.291 701.390.995< 0.01< 0.010.95/0.05
3261 687.571 781.321 698.880.8500.560.020.84/0.11/0.05
4351 681.321 807.521 696.550.966< 0.010.030.72/0.15/0.08/0.05
5441 682.391 841.051 701.530.9590.060.040.72/0.14/0.09/0.03/0.03
), ArticleFig(id=1325500856321311208, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=CN, label=表4, caption=

神经发育障碍儿童青少年睡眠障碍潜在类别分析(n=272)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别数dfAIC值BIC值aBIC值EntropyPLMR值PBLRT值类别概率
181 792.911 821.761 796.39———1.00
2171 693.991 755.291 701.390.995< 0.01< 0.010.95/0.05
3261 687.571 781.321 698.880.8500.560.020.84/0.11/0.05
4351 681.321 807.521 696.550.966< 0.010.030.72/0.15/0.08/0.05
5441 682.391 841.051 701.530.9590.060.040.72/0.14/0.09/0.03/0.03
), ArticleFig(id=1325500857084674537, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=EN, label=Tab.5, caption=

Comparison of sleep with behavior and social problems in children and adolescents with neurodevelopmental disorders grouped by different potential sleep disturbances classes(x±s)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别人数CSHQCARSABC
11370.84±9.0531.30±11.5349.44±39.34
22350.96±6.6431.94±10.5253.04±39.75
34050.33±5.8233.10±11.8463.51±40.31
419643.84±5.4428.36±8.5638.14±34.23
F值92.092.543.95
P值< 0.010.060.01
), ArticleFig(id=1325500857193726442, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325500802160263599, language=CN, label=表5, caption=

不同潜在睡眠障碍类别神经发育障碍儿童青少年睡眠与行为、社交问题比较(x±s)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别人数CSHQCARSABC
11370.84±9.0531.30±11.5349.44±39.34
22350.96±6.6431.94±10.5253.04±39.75
34050.33±5.8233.10±11.8463.51±40.31
419643.84±5.4428.36±8.5638.14±34.23
F值92.092.543.95
P值< 0.010.060.01
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天津市神经发育障碍儿童青少年睡眠障碍潜在类别分析
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李芃宏 1 , 车亦凡 2 , 赵梓瑜 1 , 崔庭凯 *, 1
中国学校卫生 | 残疾儿童身心健康状况专栏 2025,46(2): 186-190
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中国学校卫生 |残疾儿童身心健康状况专栏 2025 , 46 (2) : 186 -190
天津市神经发育障碍儿童青少年睡眠障碍潜在类别分析
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李芃宏(1997-),男,天津市人,在读博士,主要研究方向为儿童青少年神经心理发育

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李芃宏1, 车亦凡2, 赵梓瑜1, 崔庭凯*, 1
作者信息
  • 1天津医科大学公共卫生学院,天津 300070
  • 2天津大学图书馆
通讯作者:
崔庭凯,E-mail:
作者简介:

李芃宏(1997-),男,天津市人,在读博士,主要研究方向为儿童青少年神经心理发育

Latent class analysis of sleep disturbances among children and adolescents with neurodevelopmental disorders in Tianjin
Penghong LI1, Yifan CHE2, Ziyu ZHAO1, Tingkai CUI*, 1
Affiliations
  • 1School of Public Health, Tianjin Medical University, Tianjin (300070), China
出版时间: 2025-02-25 doi: 10.16835/j.cnki.1000-9817.2025052
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目的

了解天津市神经发育障碍儿童青少年睡眠障碍潜在类别及其与行为、社交问题的关系,为预防和改善神经发育障碍儿童青少年睡眠障碍提供依据。

方法

2021年9月至2024年6月,在天津市特殊教育学校和定点康复机构招募272名2~23岁神经发育障碍儿童青少年,采用儿童睡眠习惯问卷(CSHQ)评估睡眠障碍,孤独症儿童行为量表(ABC)、儿童孤独症评定量表(CARS)评估社交、行为问题及孤独症症状严重程度。采用潜在类别分析(LCA)将研究对象分为不同睡眠障碍类别,Cochran-Armitage检验分析不同年龄组睡眠障碍检出率的趋势性;采用Spearman秩相关分析各量表评分的关联,广义线性模型分析睡眠障碍对CARS、ABC量表得分的影响;采用协方差分析不同类别间儿童青少年行为、社交问题的差异。

结果

272名调查对象中,有197名(72.4%)神经发育障碍儿童青少年检出睡眠障碍。不同年龄组睡眠障碍检出率分别为2~6岁88.9%、7~12岁70.6%、13~18岁66.7%、19~23岁50.0%,随年龄增长呈下降趋势(Z=3.58,P < 0.01);CSHQ总分与ABC总分呈正相关(r=0.16,P=0.01)。广义线性模型分析表明,在调整年龄、性别、父母文化程度、家庭月总收入后,就寝习惯(β=3.60)和入睡潜伏期障碍(β=3.36)与CARS得分呈正相关,就寝习惯(β=16.73)和夜醒(β=17.46)与ABC得分呈正相关(P值均 < 0.05)。LCA分析表明,神经发育障碍儿童青少年睡眠障碍可分为4个类别;协方差分析结果显示,不同类别(类别1~4)研究对象CSHQ(70.84±9.05,50.96±6.64,50.33±5.82,43.84±5.44)和ABC(49.44±39.34,53.04±39.75,63.51±40.31,38.14±34.23)平均得分差异均有统计学意义(F值分别为92.09,3.95,P值均 < 0.05)。

结论

神经发育障碍儿童青少年睡眠障碍较严重且可分为不同潜在类别。

神经发育障碍  /  睡眠  /  潜在类别分析  /  儿童  /  青少年
Objective

To understand the latent categories of sleep disturbances among children and adolescents with neurodevelopmental disorders (NDDs) in Tianjin and their relationship with behavioral and social issues, so as to provide a basis for preventing and improving sleep disturbances in the population.

Methods

From September 2021 to June 2024, 272 children and adolescents aged 2-23 years with neurodevelopmental disorders were recruited from special education schools and designated rehabilitation institutions in Tianjin. Sleep disturbances were assessed using the Children's Sleep Habits Questionnaire (CSHQ). Behavioral and social issues and severity were evaluated using the Autism Behavior Checklist (ABC) and Childhood Autism Rating Scale (CARS). Latent class analysis (LCA) was employed to categorize the subjects into different sleep disturbances categories. Cochran-Armitage test was used to analyze the trend of detection rate of sleep disturbances in different age groups. Spearman rank correlation was used to analyze the correlation between the scores of each scale. The generalized linear model was used to analyze the influence of CARS and ABC scale scores. Covariance analysis was used to examine differences in behavioral and social issues among the different categories.

Results

Among 272 survey respondents, a total of 197(72.4%) children and adolescents with NDDs were identified with sleep disturbances. The detection rates of sleep disturbances were 88.9% for those aged 2-6 years, 70.6% for aged 7-12, 66.7% for aged 13-18 and 50.0% for 19-23 years old, which was decreased across age group (Z=3.58, P < 0.01). There was a positive correlation between the total CSHQ score and the total ABC score (r=0.16, P=0.01). The generalized linear model analysis showed that after adjusting age, gender, parents' education level and family monthly income, bedtime habit (β=3.60) and sleeping latency disorder (β=3.36) were positively correlated with CARS scores, while the bedtime habit (β=16.73) and waking up at night (β=17.46) were positively correlated with ABC scores (P < 0.05). LCA revealed that sleep disturbances in children and adolescents with NDDs could be classified into four categories. The covariance analysis results showed that there were statistically significant differences in the average scores of CSHQ (70.84±9.05, 50.96±6.64, 50.33±5.82, 43.84±5.44) and ABC (49.44±39.34, 53.04±39.75, 63.51±40.31, 38.14±34.23) among different categories of all partipants (F=92.09, 3.95, P < 0.05).

Conclusions

Sleep disturbances in children and adolescents with NDDs are severe and exhibit distinct categorical characteristics.

Neurodevelopmental disorders  /  Sleep  /  Latent class analysis  /  Child  /  Adolescent
李芃宏, 车亦凡, 赵梓瑜, 崔庭凯. 天津市神经发育障碍儿童青少年睡眠障碍潜在类别分析. 中国学校卫生, 2025 , 46 (2) : 186 -190 . DOI: 10.16835/j.cnki.1000-9817.2025052
Penghong LI, Yifan CHE, Ziyu ZHAO, Tingkai CUI. Latent class analysis of sleep disturbances among children and adolescents with neurodevelopmental disorders in Tianjin[J]. Chinese Journal of School Health, 2025 , 46 (2) : 186 -190 . DOI: 10.16835/j.cnki.1000-9817.2025052
近年来,随着神经发育障碍研究的不断深入,该群体的睡眠障碍引起广泛关注[1-3]。睡眠障碍在这一群体中较为普遍,且可能严重影响其日常功能和生活质量[2, 4]。由于这些障碍通常伴随一系列行为、社交及感官处理问题[5],睡眠障碍不仅会加重神经发育障碍的症状,还可能对认知、情绪及行为产生负面影响[6],进一步增加家庭和社会的负担。因此,了解和改善神经发育障碍儿童睡眠障碍具有重要意义。
神经发育障碍儿童的睡眠障碍主要包括入睡困难、夜醒频繁、睡眠时间短、睡眠呼吸障碍等[7]。然而,由于内部异质性较高[8],神经发育障碍儿童的睡眠障碍作为整体进行分析可能会掩盖某些关联。潜在类别分析(latent class analysis, LCA)能够识别出样本中的异质性,可为每个潜在类别提供明确的特征描述,旨在深入理解每个群体的具体属性和差异,提高统计分析效能和减少因数据异质性引起的偏倚[9-10]。因此本研究旨在对天津市神经发育障碍儿童青少年睡眠障碍进行潜在类别分析,并探讨其与行为、社交问题的关系,以便深入理解神经发育障碍儿童青少年的睡眠障碍特点,从而为制定个性化的预防和干预措施提供参考。
2021年9月至2024年6月,在天津市特殊教育学校和定点康复机构招募神经发育障碍儿童青少年志愿者作为研究对象。纳入标准为三级甲等医院诊断为孤独症谱系障碍(autism spectrum disorder, ASD)、智力障碍(intellectual disability, ID)、脑瘫、精神障碍、粘多糖症、多重障碍、唐氏综合征、发育迟缓者,排除标准为患有视力、听力或肢体残疾者。共纳入272名2~23岁神经发育障碍儿童青少年,其中男童199名,女童73名; ASD儿童青少年137名,ID儿童青少年107名,其他类型神经发育障碍儿童青少年28名; 平均年龄为(10.77±4.81)岁。所有研究对象的法定监护人均签署知情同意书; 本研究符合《赫尔辛基宣言》,研究方案获得天津医科大学伦理审查委员会批准(批号:TMUhMEC2017020)。
采用儿童睡眠习惯问卷(Children's Sleep Habits Questionnaire, CSHQ)[11-12]调查研究对象睡眠障碍。问卷由研究对象监护人或熟悉其情况的教师填写,共48项,前15项调查儿童睡眠时间等信息,不作计分,睡眠时间部分包括平时/周末晚上上床时间、平时/周末晚上睡着时间、平时/周末早晨醒来时间、平时/周末早晨起床时间、平时/周末白天小睡时长、平时/周末入睡用时、平时/周末起床用时等内容; 后33项为计分项,调查过去1个月的睡眠情况,包括就寝习惯(5项)、入睡潜伏期(1项)、睡眠持续时间(3项)、睡眠焦虑(4项)、夜醒(3项)、异态睡眠(6项)、睡眠呼吸障碍(3项)、白天嗜睡(8项)8个维度,每项根据发生频率分别赋值1~3分。总分>41分为睡眠障碍,各维度得分按顺序分别≥10.8,≥2.3,≥5.3,≥7.8,≥5.3,≥10.6,≥4.5,≥15.2分为存在该维度睡眠障碍。CSHQ平行信度为0.89,重测信度为0.85,结构效度为0.77。
采用孤独症儿童行为量表(Autism Behavior Checklist, ABC)评估儿童社交、行为问题,同时收集一般人口学资料。ABC量表分为感觉、社会交往、躯体运动、语言、生活自理5个因子,共57个条目,每个条目根据负荷系数计分(分值不等),总分0~158分[13],分数越高表示问题越严重。ABC平行信度为0.82~0.90,重测信度为0.87~0.94,结构效度为0.70。
采用儿童孤独症评定量表(Childhood Autism Rating Scale, CARS)进行评估,该量表共15个条目,每个条目赋值1~4分,分值越高,表明症状越严重,总分15~60分,≥30分表明疑似孤独症[13]。该量表重测信度为0.91,结构效度为0.79。
在现场调查前,对所有参与调查和评估的工作人员进行集中培训,包括调查的目的、内容、注意事项、评估技能等,经考核通过后参与实际调查。问卷回收后,由经培训的工作人员进行逻辑核查,并采用双录入方式录入数据,以保证数据准确性。
采用SAS 9.4统计软件对数据进行统计分析,不符合正态分布的变量采用M(P25, P75)描述,组间比较采用Kruskal-Wallis秩和检验; 符合正态分布的变量采用(x±s)进行描述,运用t检验或协方差分析进行组间比较,采用Bonferroni法进行组间两两比较; 分类变量以频数和率表示,运用χ2检验比较组间差异。Cochran-Armitage检验分析不同年龄组睡眠障碍检出率的趋势性。采用Spearman秩相关分析各量表评分的关联。以CARS和ABC得分为因变量,以睡眠障碍及CSHQ各维度得分为自变量进行广义线性模型分析,探讨睡眠障碍对CARS、ABC量表得分的影响。采用Mplus 8.3统计软件对研究对象CSHQ各维度是否异常进行LCA分析,将研究对象分为不同睡眠障碍类型组。以P < 0.05为有统计学意义。
272名神经发育障碍儿童青少年中,有197名(72.4%)检出睡眠障碍,ASD、ID和其他类型发育障碍研究对象睡眠障碍检出率分别为75.2%(103/137),65.4%(70/107)和85.7%(24/28),组间差异无统计学意义(χ2=5.63,P=0.06)。男、女生在睡眠障碍以及各睡眠维度的障碍检出率差异均无统计学意义(P值均>0.05)。随年龄增长,神经发育障碍儿童青少年睡眠障碍检出率呈下降趋势(Z=3.58,P < 0.01)。在8个睡眠障碍维度中,神经发育障碍儿童青少年睡眠持续时间障碍检出率最高(34.2%),其次为就寝习惯(19.5%)和入睡潜伏期(15.4%)。不同年龄组间平时白天小睡时长、周末白天小睡时长差异均有统计学意义(P值均 < 0.05)。见表1~2。
Spearman相关分析表明,CSHQ总分与ABC总分呈正相关(r=0.16,P=0.01),而与CARS总分的相关性无统计学意义(r=0.12,P=0.08)。广义线性模型分析表明,在调整年龄、性别、父母文化程度、家庭月收入后,就寝习惯(β=3.60)和入睡潜伏期障碍(β=3.36)与CARS得分呈正相关,就寝习惯(β=16.73)和夜醒(β=17.46)与ABC得分呈正相关(P值均 < 0.05)。见表3。
潜在类别分析结果显示,当神经发育障碍儿童青少年睡眠障碍分为4组时,赤池信息准则(akaike information criterion, AIC)值和调整后的贝叶斯信息准则(adjusted bayesian information criterion, aBIC)值最小,且似然比检验(Lo-Mendell-Rubin test, LMR)和基于Bootstrap的似然比检验(Boostrap likelihood ratio test, BLRT)检验P值均小于0.05,因此本研究采用4个类别分类进行后续统计分析。见表4。
图1显示各睡眠领域条件概率,类别1占总体的4.8%(13名),主要特点为睡眠焦虑、异态睡眠和睡眠呼吸障碍; 类别2占8.5%(23名),主要特点为入睡潜伏期和睡眠持续时间异常; 类别3占14.7%(40名),主要特点为就寝习惯不良; 类别4占72.1%(196名),各类睡眠障碍均不突出,仅睡眠持续时间存在轻微异常。
协方差分析结果显示,不同类别研究对象CSHQ和ABC平均得分差异均有统计学意义(P值均 < 0.05)。两两比较结果显示,类别1研究对象CSHQ平均得分最高,类别4的CSHQ平均得分最低,类别4的ABC得分低于类别3,差异均有统计学意义(P值均 < 0.05)。见表5。
本研究发现,天津市72.4%的神经发育障碍儿童青少年存在睡眠障碍,表明神经发育障碍儿童青少年睡眠障碍普遍且严重,与近期同类研究结果相似[14-15]。本研究中未发现不同性别神经发育障碍儿童青少年睡眠障碍存在差异,与同类研究结果一致[16-17]。本研究中ASD、ID和其他类型神经发育障碍在睡眠障碍检出率上差异无统计学意义,表明睡眠障碍在不同类型神经发育障碍儿童中严重程度相近[3]。神经发育障碍儿童睡眠障碍可能与中枢神经系统生化因素、脑器质病变等生物学因素密切相关[18-19],同时也受生长环境、行为习惯、母亲孕期等因素影响[20]。对于处于生长发育期的儿童青少年而言,获得充足且优质的睡眠十分重要,各类睡眠障碍可能会加剧其核心症状,并诱发心理问题的出现。
本研究结果发现,睡眠障碍的检出率随年龄增加呈下降趋势,尤其是年龄较小的神经发育障碍儿童睡眠障碍检出率最高。此外,在睡眠障碍的各维度中,就寝习惯问题检出率随年龄增长呈下降趋势,但睡眠呼吸障碍随年龄增长呈上升趋势。纵向研究表明,对神经发育障碍儿童睡眠进行干预可缓解其睡眠障碍[21-22]。因此,早期干预对于改善神经发育障碍儿童的睡眠障碍具有重要意义。
本研究结果发现,神经发育障碍儿童青少年CSHQ与ABC总分均呈正相关,说明睡眠与行为、社交问题存在关联。有研究表明,行为问题可能通过焦虑、抑郁等不良情绪对睡眠产生影响[23],且行为问题对未来的睡眠障碍也具有一定的预测作用[6]。同时,行为干预也可有效缓解睡眠障碍[22]。本研究还发现,不同睡眠障碍潜在类别的儿童青少年,其行为、社交问题严重程度不同,未来可深入探究行为干预对不同睡眠障碍类型神经发育障碍儿童青少年的效果以及内在机制,同时也应在进行康复干预时考虑到对睡眠障碍的影响,从而提高干预效果。
针对正常儿童青少年的研究表明,这一群体的睡眠障碍具有不同类型的特征[24-26]。本研究通过LCA,将神经发育障碍儿童青少年的睡眠障碍分为4个类别,类别1研究对象的CSHQ得分高于其他类别,表明该组儿童的睡眠障碍最为严重,需重点关注和干预,同时也应注意睡眠障碍对儿童认知发展和日常功能的不良影响[27-28]。类别2,3,4的研究对象在异态睡眠、睡眠呼吸障碍、睡眠焦虑方面与类别1的条件概率相差明显,但这3个类别间的上述3个维度差异不明显,可能与本研究所选用的CSHQ量表的维度设置和研究对象自身特点有关,后续可针对不同睡眠障碍评估工具及睡眠障碍分类进行深入研究。
本研究也存在一些局限性:首先,研究对象仅限于天津市特殊教育学校和定点康复机构,样本代表性有限; 同时由于样本量限制,未能对不同年龄段的研究对象进行潜在类别分析,不同年龄段的睡眠类别是否存在差异还有待进一步研究,未来研究应扩大样本范围,涵盖更多地区和机构。其次,本研究主要依赖监护人或教师填写的问卷进行评估,可能存在一定的主观偏差。最后,由于研究为横断面研究,无法确定睡眠障碍与行为、社交问题的因果关系,未来应考虑进行纵向研究,以进一步探讨变量间的关系。
  • 天津市教委科研计划项目(2021KJ256)
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2025年第46卷第2期
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doi: 10.16835/j.cnki.1000-9817.2025052
  • 接收时间:2024-10-30
  • 首发时间:2026-11-06
  • 出版时间:2025-02-25
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  • 收稿日期:2024-10-30
  • 修回日期:2025-01-25
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天津市教委科研计划项目(2021KJ256)
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    1天津医科大学公共卫生学院,天津 300070
    2天津大学图书馆

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