Abstract
Purpose
Sleep problems and nutritional abnormalities are common in children with autism spectrum disorder (ASD), yet the relationships between specific vitamin status, sleep characteristics, and ASD symptoms remain unclear. This study investigated the associations between neurodevelopment-related vitamin levels, sleep problems, and clinical features in children with ASD.
Patients and Methods
This cross-sectional study included 605 children with ASD aged 2–7 years. Blood vitamin levels were measured using high-performance liquid chromatography–tandem mass spectrometry. Sleep problems were assessed using the Children’s Sleep Habits Questionnaire (CSHQ) and ASD symptoms were evaluated using the Social Responsiveness Scale (SRS), Childhood Autism Rating Scale (CARS), and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2).
Results
Vitamin A (VA) deficiency was the most prominent nutritional abnormality, followed by vitamin D (VD) deficiency. VA levels differed significantly by sex, whereas VD levels varied across age groups. Several dimensions of sleep problems showed significant differences according to both sex and age. Lower VA levels were associated with greater sleep problems, including higher bedtime resistance, daytime sleepiness, and higher total CSHQ scores (all P < 0.05). Lower VD levels were associated with greater severity of core ASD symptoms (all P < 0.05), but not with sleep problems. Greater sleep problems were consistently associated with more severe ASD symptoms.
Conclusions
VA and VD deficiencies are prevalent among children with ASD. VA levels were associated with sleep problems, whereas VD status was associated with ASD symptom severity. These findings suggest that nutritional status may be associated with specific clinical features of ASD and warrant further investigation in longitudinal studies.
Keywords: autism, vitamin, sleep problems, children, autistic symptoms
Introduction
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, characterized by social and communication impairments, repetitive and stereotyped behaviors, and narrowed interests.1 Beyond core diagnostic features, children with ASD frequently experience multiple co-occurring conditions that substantially affect their daily functioning and quality of life.2 Sleep problems are highly prevalent in children with ASD, affecting more than 50% of individuals, and include difficulties with sleep initiation, bedtime resistance, night waking, and daytime sleepiness.3 Children with ASD may be particularly vulnerable to sleep problems due to the interaction of multiple neurobehavioral and biological factors. Sensory hypersensitivity to environmental stimuli, anxiety symptoms, behavioral rigidity, and difficulties with adaptive routines may interfere with sleep initiation and maintenance.4–7 In addition, abnormalities in circadian rhythm regulation and melatonin secretion have been reported in children with ASD, suggesting an intrinsic biological susceptibility to disrupted sleep-wake regulation.8 Importantly, sleep problems are associated with poorer daytime functioning, increased behavioral difficulties, and greater severity of autistic symptoms.9 Therefore, identifying biological factors associated with sleep problems may provide new insights into ASD heterogeneity and potential therapeutic targets.
Increasing evidence suggests that nutritional abnormalities may represent important factors associated with neurodevelopmental phenotypes in children with ASD.10 Vitamins involved in neuronal development, neurotransmitter metabolism, synaptic function, and circadian regulation may influence ASD-related clinical features through distinct biological pathways. Among these nutrients, vitamin A (VA) and vitamin D (VD) deficiencies have been frequently reported in children with ASD, while vitamin B6 (VB6), vitamin B12 (VB12), and folic acid (FA) also participate in essential neurophysiological processes that may be relevant to ASD-related clinical features and sleep regulation.10–12 These vitamins may influence neurodevelopment and sleep-related phenotypes through distinct biological pathways. VA primarily acts through retinoic acid (RA) signaling, which regulates neuronal differentiation, synaptic maturation, and neural circuit development, and may also interact with circadian regulatory pathways involved in sleep–wake regulation.13,14 VD contributes to neuronal growth, synaptic function, neurotransmitter regulation, and circadian-related processes that may affect sleep characteristics.15,16 VB6 serves as an essential cofactor for the synthesis of neurotransmitters, including serotonin, dopamine, and γ-aminobutyric acid, which are closely involved in neuronal excitability and sleep regulation.17 VB12 and FA participate in one-carbon metabolism, DNA methylation, nucleotide synthesis, and myelin maintenance, while VB12 has also been implicated in melatonin rhythm regulation.18,19
Despite growing interest in the relationship between nutrition and neurodevelopment, previous studies have mainly focused on individual nutrients or general nutritional status. The associations between multiple neurodevelopment-related vitamin levels, sleep problems, and ASD symptom severity in children with ASD remain insufficiently understood. Furthermore, it remains unclear whether different vitamins are associated with distinct clinical phenotypes, such as sleep-related characteristics or core autistic symptoms.
Therefore, in this study, we simultaneously measured blood levels of VA, VD, VB6, VB12, and FA using high-performance liquid chromatography-tandem mass spectrometry in children with ASD. We aimed to characterize the status of multiple neurodevelopment-related vitamins and investigate their associations with sleep problems and ASD symptom severity. Specifically, we sought to determine whether different vitamin levels showed distinct associations with sleep-related characteristics and core clinical symptoms in children with ASD. These findings may provide new insights into the potential associations between nutritional factors and ASD-related clinical manifestations.
Methods
Study Population
This was a cross-sectional study. Children with ASD were recruited from November 2019 to December 2023 at special education institutions and outpatient clinics of the Department of Child Health in Chongqing. Inclusion criteria were (1) age 2–7 years; (2) diagnosis by a developmental-behavioral pediatrician with experience in ASD according to DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, DSM-5) diagnostic criteria; and (3) legal guardian agreed and signed an informed consent form. Participants were excluded if they: (1) had other serious medical, neurological, or psychiatric conditions; (2) had acute or chronic infections within the 3 months preceding enrollment; (3) had used VA, VD, or B-complex vitamin supplements within the 3 months prior to enrollment; (4) had a legal guardian who declined to provide written informed consent; (5) did not complete both the sleep questionnaires and the blood nutrient assays; or (6) had hemolyzed or lipemic blood samples.
The required sample size was estimated using PASS 15 software based on the expected prevalence of sleep problems in children with ASD. Assuming a 95% confidence level (1−α = 0.95), a two-sided confidence interval width of 0.10, and an expected prevalence of sleep problems ranging from 50% to 80%, the minimum required sample size was calculated to be 402 participants. A total of 605 children with ASD were included in the present study, exceeding the estimated sample size requirement.
Basic Information
A questionnaire was used to obtain basic information, including sex, date of birth, nutrient supplementation in the last 3 months.
Sleep Assessment
Sleep problems were assessed using the validated Chinese version of the Children’s Sleep Habits Questionnaire (CSHQ), which has demonstrated acceptable reliability and validity in Chinese pediatric populations (Cronbach’s α = 0.73).20 The CSHQ is completed by the child’s primary caregiver to assess sleep.21 The questionnaire consists of 33 scored items divided into eight main dimensions,21,22 which can be categorized into medically and behaviorally based sleep problems,23 with the former including the dimensions of parasomnias and sleep-disordered breathing (SDB), and the latter including the remaining 6 sub-dimensions. The CSHQ first proposed by Owens used a score of 41 as the threshold, and now several domestic and international studies have used a score of 48.24–26 The Sleep Hygiene Guidelines for Children 0 to 5 Years of Age, implemented by our National Health and Wellness Commission in 2018, suggests that a total score higher than 54 is considered poor sleep quality. The total CSHQ score above 54 as the principal definition of an overall sleep problem in the logistic models, with 41 and 48 reported descriptively for comparability with prior literature.
Autistic Symptom Assessment
Autistic symptoms were assessed using the Social Responsiveness Scale (SRS), Childhood Autism Rating Scale (CARS), and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2).27–29 Higher scores on these measures indicate greater severity of autistic symptoms. The SRS was completed by the child’s primary caregiver based on the child’s behaviors during the previous six months, whereas the CARS and ADOS-2 were administered and scored by trained psychological assessors according to standardized assessment procedures and direct observations of the child’s behaviors.
Blood Collection and Sample Processing
Children participating in the study underwent fasting venipuncture for blood collection at 8:00-10:00 am. About 2 mL of blood was collected in a purple-tipped tube for plasma collection and centrifuged within 2 hours. The upper layer of liquid was plasma, which was used for the detection of VD and VA. 2–5 mL of blood was collected from red-tipped tubes for serum collection, and the blood was allowed to stand in a 37℃ water bath until the blood had completely coagulated, and was then centrifuged. The upper layer of liquid was serum, which was used for the detection of VB6, VB12, and folic acid.
Nutrient Measurement and Evaluation
Separated serum and plasma were transported on dry ice to the central laboratory of Chengdu Hehe Medical Laboratory for quantitative determination of nutrient levels using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). In this study, non-derivatization treatment was used for sample pre-treatment. The active ingredients were extracted after pretreatment such as protein removal, extraction, and purification. The HPLC-MS/MS instrument was equipped with an electrospray ionization source using positive ion scanning mode in multiple reaction monitoring modes.
VA normal (VAN): ≥ 0.3 mg/L; Marginal VA deficiency (MVAD): 0.2–0.3 mg/L; VA deficiency (VAD): < 0.2 mg/L. Marginal deficiency and deficiency were uniformly categorized into the VAD group for discussion in this study.
VD normal (VDN): ≥ 20 ng/mL; VD insufficiency: 12–20 ng/mL; VD deficiency (VDD): <12 ng/mL. In this study, VD insufficiency and deficiency were unified into the VDD group for discussion.
Normal levels of VB6 are 3.0–35.0 ng/mL, VB12 is 132.84–676.01 pmol/L, and folic acid is 7.25–44.41 nmol/L. Below the lower limit of normal levels suggests deficiency.
Quality Control
Before the start of the study, all researchers were uniformly trained, including biological sample collection and processing, assessment specifications and procedures. During the study, the researchers were required to uniformly instruct parents to fill in the questionnaire. The collected blood samples were pre-treated at the Children’s Hospital of Chongqing Medical University and then transported via dry ice to Hehe Medical Laboratory for uniform testing within one week. Data entry was performed by two-person independent checking.
Statistical Analysis
Statistical analysis was performed using R-4.4.1 and GraphPad Prism 8.0. Normality test: Kolmogorov–Smirnov (KS) and Shapiro–Wilk (SW) tests combined with graphical tests (histograms, P-P charts, Q-Q charts). Data description: continuous variables were expressed as mean ± standard deviation (M ± SD) or median (25th percentile to 75th percentile) [M (P25-P75)] according to their conformity to normal distribution; categorical variables are expressed as frequency (percentage) [n (%)]. Two independent samples t-test was used for the comparison of two groups with normal distribution, and one-way ANOVA for multiple comparisons; the Mann–Whitney test was used for comparison of two groups with non-normal distribution, and Kruskal–Wallis test for multiple comparisons. The chi-square test was used for categorical variables. Post hoc two-by-two comparisons were made using Bonferroni correction. Linear regression and logistic regression were used to explore the relationship between each nutrient level, scores of autism symptom and CSHQ scores. All linear and logistic regression models were adjusted for age and sex. All statistical tests were two-sided, and differences were considered statistically significant at P < 0.05.
Results
Basic Information of Children with ASD Included
A total of 605 children with ASD aged 2–7 years, including 494 boys and 111 girls, with a mean age of 3.93 years (Table 1). All 605 children with ASD completed the sleep questionnaire, with the proportions of scores over 41, 48, and 54 were 92.23%, 50.08%, and 17.52%, respectively.
Table 1.
Characteristics of Basic Information of Children with ASD Included
| Variables | Characteristics |
|---|---|
| Age, Mean±SD | 3.93±1.07 |
| Sex, n (%) | |
| Boys | 494 (81.65) |
| Girls | 111 (18.35) |
| Ethnicity, n(%) | |
| Han | 551 (91.07) |
| Others | 54 (8.93) |
| Picky eating, n(%) | |
| Yes | 232 ((38.35) |
| No | 343 (56.69) |
| Missing | 30 (4.96) |
| Mother’s education level, n(%) | |
| Middle school or below | 109 (18.02) |
| High school | 150 (24.79) |
| College | 317 (52.40) |
| Master’s degree or above | 21 (3.47) |
| Missing | 8 (1.32) |
| Father’s education level, n(%) | |
| Middle school or below | 105 (17.36) |
| High school | 132 (21.82) |
| College | 324 (53.55) |
| Master’s degree or above | 36 (5.95) |
| Missing | 8 (1.32) |
| Annual family income, n(%) | |
| < 60,000 yuan | 170 (28.10) |
| 60,000 to 150,000 yuan | 311 (51.40) |
| ≥ 150,000 yuan | 105 (17.36) |
| Missing | 19 (3.14) |
Notes: Data are presented as mean ± standard deviation (SD), or number (%).
Abbreviation: ASD, autism spectrum disorder.
Sex-Related Differences in Sleep Problems and Nutritional Status Among Children with ASD
As shown in Table 2, sleep characteristics differed between boys and girls with ASD. The prevalence of sleep-disordered breathing was higher in boys than in girls (8.30% vs 1.80%, P = 0.016), whereas excessive daytime sleepiness was more prevalent in girls (14.41% vs 8.30%, P = 0.046). No significant sex differences were observed in the proportion of children with total CSHQ scores exceeding 41, 48, or 54. Regarding nutritional status, insufficiency and deficiency of VA and VD were separately grouped into the VAD and VDD categories for discussion. We found that VA deficiency was the most common deficiency among the assessed vitamins and was significantly more prevalent in boys than in girls (44.00% vs 32.41%, P = 0.027). VD deficiency was the second most common deficiency, with prevalence rates of 21.31% in boys and 17.59% in girls, without a significant sex difference. VB12 levels were within the normal range in all participants, and no vitamin B12 deficiency was observed.
Table 2.
Comparison of the Prevalence of Sleep Problems and Nutrient Deficiency in Girls and Boys with ASD
| Variables | Girls | Boys | χ2 | P |
|---|---|---|---|---|
| Prevalence of sleep problems (n=605) | ||||
| Bedtime resistance | 83 (74.77) | 374 (75.70) | 0.043 | 0.836 |
| Sleep onset delay | 29 (26.13) | 103 (20.85) | 1.479 | 0.224 |
| Sleep duration | 27 (24.32) | 114 (23.08) | 0.079 | 0.779 |
| Sleep anxiety | 45 (40.54) | 198 (40.08) | 0.008 | 0.929 |
| Night waking | 2 (1.80) | 24 (4.86) | 2.059 | 0.151 |
| Parasomnia | 14 (12.61) | 73 (14.78) | 0.345 | 0.557 |
| Sleep-disordered breathing | 2 (1.80) | 41 (8.30) | 5.796 | 0.016 |
| Daytime sleepiness | 16 (14.41) | 41 (8.30) | 3.971 | 0.046 |
| Total score (>41) | 106 (95.50) | 452 (91.50) | 2.021 | 0.155 |
| Total score (>48) | 50 (45.05) | 253 (51.21) | 1.380 | 0.240 |
| Total score (>54) | 18 (16.22) | 88 (17.81) | 0.160 | 0.689 |
| Nutrient deficiency rates | ||||
| Vitamin A (n=599) | 35 (32.41) | 216 (44.00) | 4.880 | 0.027 |
| Vitamin D (n=596) | 19 (17.59) | 104 (21.31) | 0.902 | 0.342 |
| Vitamin B6 (n=305) | 2 (3.64) | 5 (2.00) | 0.538 | 0.463 |
| Vitamin B12 (n=598) | 0 (0.00) | 0 (0.00) | ||
| Folic acid (n=425) | 2 (2.67) | 8 (2.29) | 0.022 | 0.882 |
Notes: The chi-square test was used in the analysis; χ2: Chi-square test statistic; Bold P values indicate statistical significance (P < 0.05). The insufficiency and deficiency of VA and VD were separately grouped into the VAD and VDD categories.
Abbreviations: ASD, autism spectrum disorder.
Age-Related Differences in Sleep Problems and Nutritional Status Among Children with ASD
As shown in Table 3, bedtime resistance was the most frequently reported sleep problem across all age groups, with prevalence rates of 75.00%, 82.59%, 75.31%, and 60.61% in the 2–3, 3–4, 4–5, and ≥5 years groups, respectively. Sleep onset delay was more common in children aged 2–3 years than in those aged ≥5 years (29.17% vs 12.12%, P < 0.05). Parasomnia symptoms were significantly more prevalent in younger children aged 2–4 years compared with older age groups (P < 0.05).
Table 3.
Comparison of the Prevalence of Sleep Problems in Children with ASD at Different Age Groups, n (%)
| Variables | 2–3y | 3–4y | 4–5y | ≥5y | χ2 | p |
|---|---|---|---|---|---|---|
| Prevalence of sleep problems (n=605) | ||||||
| Bedtime resistance | 90 (75.00) | 185 (82.59)d | 122 (75.31) | 60 (60.61)b | 17.996 | <0.001 |
| Sleep onset delay | 35 (29.17)d | 52 (23.21) | 33 (20.37) | 12 (12.12)a | 9.711 | 0.021 |
| Sleep duration | 22 (18.33) | 57 (25.45) | 42 (25.93) | 20 (20.20) | 3.390 | 0.335 |
| Sleep anxiety | 47 (39.17) | 91 (40.63) | 67 (41.36) | 38 (38.38) | 0.296 | 0.961 |
| Night waking | 5 (4.17) | 10 (4.46) | 3 (1.85) | 8 (8.08) | 5.821 | 0.121 |
| Parasomnia | 30 (25.00)c,d | 35 (15.63) | 14 (8.64)a | 8 (8.08)a | 18.797 | <0.001 |
| Sleep-disordered breathing | 3 (2.50) | 14 (6.25) | 16 (9.88) | 10 (10.10) | 7.333 | 0.062 |
| Daytime sleepiness | 10 (8.33) | 25 (11.16) | 17 (10.49) | 5 (5.05) | 3.395 | 0.335 |
| Total score (≥41) | 113 (94.17)d | 214 (95.54)d | 149 (91.98) | 82 (82.83)a,b | 16.272 | 0.001 |
| Total score (≥48) | 60 (50.00) | 128 (57.14)d | 80 (49.38) | 35 (35.35)b | 13.089 | 0.004 |
| Total score (≥54) | 25 (20.83) | 43 (19.20) | 29 (17.90) | 9 (9.09) | 6.231 | 0.101 |
| Nutrient deficiency rates | ||||||
| Vitamin A (n=599) | 50 (41.67) | 93 (41.70) | 69 (43.95) | 39 (39.39) | 0.532 | 0.912 |
| Vitamin D (n=596) | 6 (5.04)b,c,d | 36 (16.36)a,d | 44 (27.67)a | 37 (37.76)a,b | 42.047 | <0.001 |
| Vitamin B6 (n=305) | 0 (0.00) | 3 (2.33) | 2 (2.50) | 2 (4.88) | 2.527 | 0.470 |
| Vitamin B12 (n=598) | 0 (0.00) | 0 (0.00) | 0 (0.00) | 0 (0.00) | ||
| Folic acid (n=425) | 1 (0.85) | 2 (0.90) | 3 (1.88) | 4 (4.04) | 4.716 | 0.194 |
Notes: The 2–3y, 3–4y, 4–5y, ≥5y groups are represented by a, b, c, and d, respectively. A superscript letter indicates that the corresponding group differs significantly from the age group represented by that letter (P < 0.05). ASD: autism spectrum disorder; n (%): number (percentage). Data was shown as n (%); χ2: Chi-square test statistic; Chi-square test was used in the analysis. Multiple comparisons were corrected by the Bonferroni method. The insufficiency and deficiency of VA and VD were separately grouped into the VAD and VDD categories.
The proportion of children with CSHQ total scores >41 was 94.17%, 95.54%, 91.98%, and 82.83% in the 2–3, 3–4, 4–5, and ≥5 years groups, respectively. The proportions with scores >48 were 50.00%, 57.14%, 49.38%, and 35.35%, respectively. Both proportions were significantly lower in the ≥5 years group compared with younger age groups.
Regarding nutritional status, VA deficiency showed a consistently high prevalence across all age groups (approximately 40%). VD deficiency increased significantly with age, with prevalence rates of 5.04%, 16.36%, 27.67%, and 37.76% in the 2–3, 3–4, 4–5, and ≥5 years groups, respectively (P < 0.001).
Associations Between Vitamin Levels, Sleep Characteristics, and Autistic Symptoms
Linear regression analyses were performed to examine the associations between vitamin levels and CSHQ subscale scores, as well as autistic symptom scores (Table 4). VA levels were negatively associated with bedtime resistance, daytime sleepiness, and total CSHQ scores (all P < 0.05). VD levels were negatively associated with CARS and ADOS-2 scores (all P < 0.05), but were not significantly associated with sleep outcomes. Serum folate levels were negatively associated with sleep duration problems (P < 0.001). In addition, higher severity of sleep problems across CSHQ domains was associated with higher autistic symptom scores (all P < 0.05).
Table 4.
Associations Between Nutrient Levels, Sleep Scores, and Autism Symptom Scores
| Variables | VA | VD | VB6 | VB12 | FA | SRS | CARS | ADOS-2 |
|---|---|---|---|---|---|---|---|---|
| Score of sleep problems | ||||||||
| Bedtime resistance | −3.006* (−5.347, −0.666) | −0.012 (−0.033, 0.009) | 0.006 (−0.018, 0.03) | 0.000 (−0.001, 0.001) | 0.010 (−0.008, 0.029) | 0.017*** (0.009, 0.026) | −0.007 (−0.04, 0.026) | −0.025 (−0.071, 0.02) |
| Sleep onset delay | −0.672 (−1.406, 0.062) | 0.001 (−0.005, 0.008) | 0.002 (−0.007, 0.01) | 0.000 (0.000, 0.000) | 0.001 (−0.004, 0.007) | 0.005*** (0.003, 0.008) | 0.013* (0.002, 0.023) | 0.018* (0.003, 0.032) |
| Sleep duration | 0.133 (−1.357, 1.623) | −0.007 (−0.020, 0.007) | −0.012 (−0.029, 0.005) | 0.000 (−0.001, 0.000) | −0.020*** (−0.032, −0.009) | 0.009** (0.003, 0.014) | 0.022* (0.001, 0.042) | 0.04** (0.012, 0.067) |
| Sleep anxiety | −0.624 (−2.395, 1.146) | −0.001 (−0.017, 0.014) | −0.001 (−0.022, 0.019) | 0.000 (0.000, 0.001) | 0.008 (−0.006, 0.022) | 0.012*** (0.006, 0.019) | −0.012 (−0.036, 0.013) | −0.018 (−0.051, 0.016) |
| Night waking | 0.216 (−0.695, 1.128) | 0.002 (−0.006, 0.010) | −0.002 (−0.012, 0.008) | 0.000 (0.000, 0.000) | 0.002 (−0.006, 0.009) | 0.005** (0.002, 0.009) | 0.014* (0.001, 0.026) | 0.02* (0.002, 0.038) |
| Parasomnia | 0.565 (−1.032, 2.162) | 0.002 (−0.013, 0.016) | −0.001 (−0.02, 0.018) | 0.000 (0, 0.001) | 0.004 (−0.009, 0.016) | 0.015*** (0.009, 0.021) | 0.02 (−0.002, 0.042) | 0.002 (−0.029, 0.032) |
| Sleep-disordered breathing | −0.321 (−1.058, 0.417) | −0.001 (−0.007, 0.006) | −0.005 (−0.013, 0.003) | 0.000 (0.000, 0.000) | −0.002 (−0.008, 0.004) | 0.003* (0.000, 0.005) | 0.006 (−0.004, 0.015) | −0.005 (−0.019, 0.009) |
| Daytime sleepiness | −3.442* (−6.195, −0.689) | −0.023 (−0.048, 0.001) | −0.019 (−0.054, 0.015) | 0.000 (−0.001, 0.001) | −0.017 (−0.038, 0.005) | 0.018** (0.007, 0.028) | 0.019 (−0.022, 0.059) | 0.011 (−0.044, 0.067) |
| Total score | −6.675* (−12.633, −0.717) | −0.041 (−0.094, 0.013) | −0.033 (−0.102, 0.036) | −0.001 (−0.002, 0.001) | −0.021 (−0.068, 0.026) | 0.078*** (0.056, 0.099) | 0.088* (0.004, 0.173) | 0.062 (−0.053, 0.176) |
| Score of autistic symptoms | ||||||||
| SRS | −7.301 (−33.091, 18.489) | −0.229 (−0.528, 0.070) | −0.132 (−0.414, 0.151) | −0.001 (−0.009, 0.007) | −0.196 (−0.397, 0.004) | |||
| CARS | 2.968 (−4.719, 10.655) | −0.130** (−0.216, −0.044) | 0.018 (−0.054, 0.091) | −0.001 (−0.003, 0.002) | −0.027 (−0.086, 0.031) | |||
| ADOS-2 | −1.320 (−7.234, 4.595) | −0.088* (−0.158, −0.018) | −0.018 (−0.074, 0.039) | −0.001 (−0.002, 0.001) | −0.044 (−0.091, 0.002) |
Notes: The results are presented as β coefficients with 95% confidence intervals: β (95% CI). Linear regression analysis.VA, VD, VB6, VB12, FA, SRS, CARS and ADOS as independent variables; score of sleep problems and score of autistic symptoms as dependent variables; adjusting for age and sex; *P<0.05; **P<0.01; ***P<0.001.
Abbreviations: VA, Vitamin A; VD,Vitamin D; VB6, Vitamin B6; VB12,Vitamin B12; FA, Folic acid; SRS, Social Responsiveness Scale; CARS, Childhood Autism Rating Scale; ADOS-2, Autism Diagnostic Observation Schedule, Second Edition.
Associations Between Nutrient Levels and Sleep Problems
We performed logistic regression to analyze the associations between nutrient deficiencies and various sleep problems (Figure 1). Given the significant influence of age and sex on sleep, adjustments were made for these factors as confounders in the analysis. Our findings indicate that children with VA deficiency exhibited more problems with bedtime resistance, parasomnia and sleep problem (54 as cutoff). Folate deficiency had more problems with daytime sleepiness. This finding appeared inconsistent with the linear regression result, which showed only a negative association between serum folate levels and sleep-duration problems. This may be because the sleep-duration association was based on continuous serum folate levels in the full analytic sample, whereas the daytime-sleepiness association was identified by comparing the small folate-deficient subgroup with participants without folate deficiency. However, the regression results for vitamin deficiencies, particularly vitamin B6 and folate deficiencies, should be interpreted with caution because the wide confidence intervals indicate limited precision.
Figure 1.
Correlation between nutrient deficiencies and sleep problems. (a–d) Occurrence of various sleep problems in ASD children with deficiencies in VA (a), VD (b), VB6 (c), and FA (d). The insufficiency and deficiency of VA and VD were separately grouped into the VAD and VDD categories. Logistic regression was performed with the occurrence of each sleep problem as the dependent variable and the presence of nutrient deficiency as the independent variable, adjusted for age and sex. Or (95%CI): odds ratio (95% confidence interval). Bold P values indicate statistical significance (P < 0.05). ASD children with VB6 deficiency showed no sleep problems related to night waking, sleep-disordered breathing, or overall sleep problems (using a cutoff score of 41). FA deficiency exhibited no night waking problems and had normal overall sleep scores (using a cutoff of 41).
Discussion
In this study, we examined the associations of multiple neurodevelopment-related vitamins with both sleep characteristics and autistic symptoms. In contrast to previous studies that focused on single nutrients or overall sleep problems, we evaluated multiple vitamins and different dimensions of sleep problems and autistic symptoms within the ASD population. Our findings showed that VA levels were associated with several sleep-related measures, whereas VD levels were associated with autism symptom severity but not sleep outcomes. These findings suggest that nutritional status may be related to different aspects of clinical heterogeneity in children with ASD.
Sex-related differences in sleep characteristics were observed in our cohort. Boys with ASD showed a higher prevalence of sleep-disordered breathing, whereas girls showed a higher prevalence of daytime sleepiness. Previous studies have also reported greater daytime sleepiness among girls with ASD, although sex differences in other sleep domains have been inconsistent across studies. D’Agati et al reported sex differences in sleep problems among children with ASD and ADHD, highlighting that daytime sleepiness may be more prominent in girls with ASD; however, other sleep domains did not consistently differ by sex.30 The higher prevalence of sleep-disordered breathing observed in boys in our study may partly reflect sex-related susceptibility to upper airway obstruction. In the general pediatric population, boys have been reported to show distinct age- and sex-related characteristics of obstructive sleep apnea, which may be related to differences in airway anatomy and respiratory physiology.31 However, whether these mechanisms fully explain the sex difference in sleep-disordered breathing among children with ASD remains unclear.
Sex differences in ASD clinical manifestations have been widely recognized, with previous studies reporting differences in developmental profiles, autistic symptoms, and co-occurring conditions between boys and girls with ASD.3,32,33 Such clinical heterogeneity may also contribute to variations in sleep presentations. In addition, differences in age distribution, cultural background, sleep-related behaviors, assessment instruments, and study design may partially explain the inconsistent findings across studies. Further investigations using objective sleep measurements and larger samples are needed to better characterize sex-related differences in sleep among children with ASD.
We also identified age-related differences in sleep characteristics. Parasomnia symptoms were more prevalent in children aged 2–4 years compared with older age groups. The parasomnia domain of the CSHQ includes several heterogeneous behaviors, including sleep talking, nightmares, night terrors, sleepwalking, and enuresis, which may have different developmental trajectories. Previous longitudinal studies in typically developing children have demonstrated that some parasomnia symptoms, such as sleep terrors, are more common during early childhood and tend to decline with age, although other symptoms may follow different patterns.34,35 Hence, the higher prevalence of parasomnia symptoms in younger children with ASD may partly reflect age-related characteristics of individual sleep behaviors included in this domain. However, because the present study was based on cross-sectional age comparisons, longitudinal studies are required to determine whether these differences represent developmental changes in sleep patterns among children with ASD.
Regarding nutritional status, VA deficiency was the most common abnormality among the assessed vitamins and was significantly more prevalent in boys than girls. This finding is consistent with previous multicenter epidemiological data from Chinese children with ASD showing sex-related differences in VA status.36 VA deficiency remained common across age groups, suggesting that suboptimal VA status may persist throughout early childhood in children with ASD. VD deficiency was the second most common abnormality, although no significant sex difference was observed. We also found an age-related increase in VD deficiency. These differences may reflect variations in dietary intake, vitamin supplementation, and lifestyle factors such as outdoor activity and sunlight exposure. Elucidating the specific contributions of these factors will require dedicated studies with detailed dietary and behavioral assessments.
Among the vitamins examined, VA levels showed significant associations with several sleep-related outcomes. Evidence regarding the relationship between VA status and sleep remains limited, particularly in children with ASD. Previous studies have suggested that VA-related nutrients may be involved in sleep regulation. A population-based study reported an association between dietary carotenoid intake and sleep duration in adults,37 while a randomized controlled trial found that crocetin, a carotenoid-derived compound, improved subjective sleep quality, supporting a potential role of VA-related pathways in sleep regulation.38 Our findings suggest that VA status may represent one nutritional factor associated with sleep heterogeneity in children with ASD. This observation is biologically plausible, as animal studies have shown that VA deficiency can alter sleep-related electrophysiological activity and disrupt retinoic acid receptor expression and circadian-related molecular rhythms.39–41 However, these experimental findings cannot establish a causal relationship in children with ASD, and longitudinal studies incorporating objective sleep assessments are needed to determine whether altered VA status contributes to sleep problems in this population.
The relationship between nutritional status and clinical manifestations in ASD is likely complex. The associations observed in this study do not indicate that vitamin abnormalities directly cause sleep disturbances or autistic symptoms, but rather suggest that nutritional status may represent one factor associated with variation in clinical presentation. Given the substantial heterogeneity of ASD, identifying potentially modifiable biological factors associated with specific symptom domains may help improve understanding of individual differences among children with ASD. Future studies integrating longitudinal nutritional assessment, objective sleep monitoring, and detailed clinical characterization are needed to clarify these relationships.
This study has several limitations. First, sleep characteristics were assessed using a caregiver-reported questionnaire, which may not fully capture objective sleep patterns. Future studies incorporating objective sleep assessments, such as actigraphy or polysomnography, may provide further insights. Second, the cross-sectional design limits the ability to determine temporal relationships or causal effects between vitamin status, sleep problems, and autistic symptoms. Third, vitamin status may be influenced by dietary patterns, nutritional supplementation, and other metabolic factors. As this was a single-center study, regional differences in dietary habits may limit the generalizability of our findings to children from other populations. In addition, lipid-related variables were not available in the present study, and circulating concentrations of fat-soluble vitamins may not fully reflect body stores. Future multicenter longitudinal studies incorporating comprehensive nutritional and metabolic assessments are needed to further clarify the relationships among vitamin status, sleep characteristics, and autistic symptoms. Further studies including a control group would also help determine whether the associations between nutrient status and sleep are generalizable.
Conclusion
In conclusion, VA and VD abnormalities were common among children with ASD. Lower plasma VA levels were associated with more severe sleep problems, whereas lower plasma VD levels were associated with greater ASD symptom severity but not sleep disturbances. These findings highlight a potential association between nutritional status and clinical heterogeneity in ASD, which warrants further investigation in longitudinal studies.
Acknowledgments
We would like to thank the families and children who contributed to this study. Thanks to the researchers who participated in the survey. We would like to thank the Chief Medical Expert Studio of Chongqing (No.YWBF[2018]263) for supporting this study.
Funding Statement
This survey was supported by the National Natural Science Foundation of China (81771223, 82372559, 82304119).
Data Sharing Statement
The datasets used during the current study are available from both corresponding authors on reasonable request.
Ethics Approval
This study was registered in the China Clinical Trial Registry (ChiCTR2000031194) and approved by the Medical Ethics Committee of the Children’s Hospital of Chongqing Medical University (Ethics Approval Nos. [2018]121-1 and [2021]453). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from the legal guardians of all participants prior to enrollment.
Author Contributions
Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data curation, Visualization, Writing-original draft, and Writing-review and editing, H.C.; Investigation and Writing-original draft, X.X.; Investigation and Writing-review and editing, Q.M., Q.W., J.C., and T.L.; Conceptualization, Resources, and Writing-review and editing, T.Y. and Q.Z. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
Dr Tingyu Li and Dr Ting Yang report this work was supported by the National Natural Science Foundation of during the conduct of the study. The authors declare no other conflicts of interest.
References
- 1.Lord C, Elsabbagh M, Baird G, Veenstra-Vanderweele J. Autism spectrum disorder. Lancet. 2018;392(10146):508–12. doi: 10.1016/s0140-6736(18)31129-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Bougeard C, Picarel-Blanchot F, Schmid R, Campbell R, Buitelaar J. Prevalence of autism spectrum disorder and co-morbidities in children and adolescents: a systematic literature review. Front Psychiatry. 2021;12:744709. doi: 10.3389/fpsyt.2021.744709 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Estes A, Munson J, St John T, et al. Sleep problems in autism: sex differences in the school-age population. Autism Res. 2023;16(1):164–173. doi: 10.1002/aur.2848 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Mazurek MO, Petroski GF. Sleep problems in children with autism spectrum disorder: examining the contributions of sensory over-responsivity and anxiety. Sleep Med. 2015;16(2):270–279. doi: 10.1016/j.sleep.2014.11.006 [DOI] [PubMed] [Google Scholar]
- 5.Manelis-Baram L, Meiri G, Ilan M, et al. Sleep disturbances and sensory sensitivities co-vary in a longitudinal manner in pre-school children with autism spectrum Disorders. J Autism Dev Disord. 2022;52(2):923–937. doi: 10.1007/s10803-021-04973-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Hunter JE, McLay LK, France KG, Blampied NM. Sleep and stereotypy in children with autism: effectiveness of function-based behavioral treatment. Sleep Med. 2021;80:301–304. doi: 10.1016/j.sleep.2021.01.062 [DOI] [PubMed] [Google Scholar]
- 7.Dell’osso L, Massoni L, Battaglini S, Cremone IM, Carmassi C, Carpita B. Biological correlates of altered circadian rhythms, autonomic functions and sleep problems in autism spectrum disorder. Ann Gen Psychiatry. 2022;21(1):13. doi: 10.1186/s12991-022-00390-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Baranwal N, Yu PK, Siegel NS. Sleep physiology, pathophysiology, and sleep hygiene. Prog Cardiovasc Dis. 2023;77:59–69. doi: 10.1016/j.pcad.2023.02.005 [DOI] [PubMed] [Google Scholar]
- 9.Chen H, Yang T, Chen J, et al. Sleep problems in children with autism spectrum disorder: a multicenter survey. BMC Psychiatry. 2021;21(1):406. doi: 10.1186/s12888-021-03405-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Karhu E, Zukerman R, Eshraghi RS, et al. Nutritional interventions for autism spectrum disorder. Nutr Rev. 2020;78(7):515–531. doi: 10.1093/nutrit/nuz092 [DOI] [PubMed] [Google Scholar]
- 11.Zhu J, Guo M, Yang T, et al. Nutritional status and symptoms in preschool children with autism spectrum disorder: a two-center comparative study in Chongqing and Hainan Province, China. Front Pediatr. 2020;8:469. doi: 10.3389/fped.2020.00469 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Liu X, Liu J, Xiong X, et al. Correlation between nutrition and symptoms: nutritional survey of children with autism spectrum disorder in Chongqing, China. Nutrients. 2016;8(5). doi: 10.3390/nu8050294 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Chen L, Lau AG, Sarti F. Synaptic retinoic acid signaling and homeostatic synaptic plasticity. Neuropharmacology. 2014;78:3–12. doi: 10.1016/j.neuropharm.2012.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ransom J, Morgan PJ, McCaffery PJ, Stoney PN. The rhythm of retinoids in the brain. J Neurochem. 2014;129(3):366–376. doi: 10.1111/jnc.12620 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Pertile RAN, Brigden R, Raman V, Cui X, Du Z, Eyles D. Vitamin D: a potent regulator of dopaminergic neuron differentiation and function. J Neurochem. 2023;166(5):779–789. doi: 10.1111/jnc.15829 [DOI] [PubMed] [Google Scholar]
- 16.Gao Q, Kou T, Zhuang B, Ren Y, Dong X, Wang Q. The association between Vitamin D deficiency and sleep disorders: a systematic review and meta-analysis. Nutrients. 2018;10(10):1395. doi: 10.3390/nu10101395 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Almeida MR, Mabasa L, Crane C, et al. Maternal vitamin B6 deficient or supplemented diets on expression of genes related to GABAergic, serotonergic, or glutamatergic pathways in hippocampus of rat dams and their offspring. Mol Nutr Food Res. 2016;60(7):1615–1624. doi: 10.1002/mnfr.201500950 [DOI] [PubMed] [Google Scholar]
- 18.Selhub J. Folate, vitamin B12 and vitamin B6 and one carbon metabolism. J Nutr Health Aging. 2002;6(1):39–42. [PubMed] [Google Scholar]
- 19.Khosropanah A, Hosseini SA, Keshavarz A. Nutritional modulators of sleep: a narrative review of vitamins, minerals, amino acids, and their neurobiological and chronoepigenetic mechanisms. Chronobiol Int. 2026;43(7):951–964. doi: 10.1080/07420528.2026.2648011 [DOI] [PubMed] [Google Scholar]
- 20.Li SH, Jin XM, Shen XM, et al. Development and psychometric properties of the Chinese version of Children’s Sleep Habits Questionnaire. Zhonghua er ke za zhi. 2007;45(3):176–180. Chinese. [PubMed] [Google Scholar]
- 21.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):1043–1051. [PubMed] [Google Scholar]
- 22.Byars KC, Yeomans-Maldonado G, Noll JG. Parental functioning and pediatric sleep disturbance: an examination of factors associated with parenting stress in children clinically referred for evaluation of insomnia. Sleep Med. 2011;12(9):898–905. doi: 10.1016/j.sleep.2011.05.002 [DOI] [PubMed] [Google Scholar]
- 23.Bonuck KA, Goodlin-Jones BL, Schechter C, Owens J. Modified children’s sleep habits questionnaire for behavioral sleep problems: a validation study. Sleep Health. 2017;3(3):136–141. doi: 10.1016/j.sleh.2017.03.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Reynolds AM, Soke GN, Sabourin KR, et al. Sleep problems in 2- to 5-year-olds with autism spectrum disorder and other developmental delays. Pediatrics. 2019;143(3). doi: 10.1542/peds.2018-0492 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Ishii R, Obara H, Nagamitsu S, et al. The Japanese version of the children’s sleep habits questionnaire (CSHQ-J): a validation study and influencing factors. Brain Dev. 2022;44(9):595–604. doi: 10.1016/j.braindev.2022.06.003 [DOI] [PubMed] [Google Scholar]
- 26.Deng Y, Zhang Z, Gui Y, et al. Sleep disturbances and emotional and behavioral difficulties among preschool-aged children. JAMA Network Open. 2023;6(12):e2347623. doi: 10.1001/jamanetworkopen.2023.47623 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Cen CQ, Liang YY, Chen QR, et al. Investigating the validation of the Chinese Mandarin version of the social responsiveness scale in a Mainland China child population. BMC Psychiatry. 2017;17(1):51. doi: 10.1186/s12888-016-1185-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Schopler E, Reichler RJ, DeVellis RF, Daly K. Toward objective classification of childhood autism: Childhood Autism Rating Scale (CARS). J Autism Dev Disord. 1980;10(1):91–103. doi: 10.1007/bf02408436 [DOI] [PubMed] [Google Scholar]
- 29.Adamou M, Jones SL, Wetherhill S. Predicting diagnostic outcome in adult autism spectrum disorder using the autism diagnostic observation schedule, second edition. BMC Psychiatry. 2021;21(1):24. doi: 10.1186/s12888-020-03028-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.D’agati E, Abate R, Gialloreti LE, et al. Sleep problems in attention-deficit/hyperactivity disorder and autism spectrum disorder: sex differences and parental stress. Psychiatry Res. 2020;291:113099. doi: 10.1016/j.psychres.2020.113099 [DOI] [PubMed] [Google Scholar]
- 31.Kang KT, Weng WC, Lee PL, Hsu WC. Age- and gender-related characteristics in pediatric obstructive sleep apnea. Pediatr Pulmonol. 2022;57(6):1520–1526. doi: 10.1002/ppul.25900 [DOI] [PubMed] [Google Scholar]
- 32.Angell AM, Deavenport-Saman A, Yin L, et al. Sex differences in co-occurring conditions among autistic children and youth in Florida: a retrospective cohort study (2012–2019). J Autism Dev Disord. 2021;51(10):3759–3765. doi: 10.1007/s10803-020-04841-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hartley SL, Sikora DM. Sex differences in autism spectrum disorder: an examination of developmental functioning, autistic symptoms, and coexisting behavior problems in toddlers. J Autism Dev Disord. 2009;39(12):1715–1722. doi: 10.1007/s10803-009-0810-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Petit D, Pennestri MH, Paquet J, et al. Childhood sleepwalking and sleep terrors: a longitudinal study of prevalence and familial aggregation. JAMA Pediatrics. 2015;169(7):653–658. doi: 10.1001/jamapediatrics.2015.127 [DOI] [PubMed] [Google Scholar]
- 35.Laberge L, Tremblay RE, Vitaro F, Montplaisir J. Development of parasomnias from childhood to early adolescence. Pediatrics. 2000;106(1 Pt 1):67–74. doi: 10.1542/peds.106.1.67 [DOI] [PubMed] [Google Scholar]
- 36.Yang T, Chen L, Dai Y, et al. Vitamin A status is more commonly associated with symptoms and neurodevelopment in boys with autism spectrum disorders-a multicenter study in China. Front Nutr. 2022;9:851980. doi: 10.3389/fnut.2022.851980 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Deng MG, Liu F, Wang K, Liang Y, Nie JQ, Liu J. Relationship between dietary carotenoid intake and sleep duration in American adults: a population-based study. Nutr J. 2023;22(1):68. doi: 10.1186/s12937-023-00898-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Umigai N, Takeda R, Mori A. Effect of crocetin on quality of sleep: a randomized, double-blind, placebo-controlled, crossover study. Complement Ther Med. 2018;41:47–51. doi: 10.1016/j.ctim.2018.09.003 [DOI] [PubMed] [Google Scholar]
- 39.Kitaoka K, Hattori A, Chikahisa S, Miyamoto K, Nakaya Y, Sei H. Vitamin A deficiency induces a decrease in EEG delta power during sleep in mice. Brain Res. 2007;1150:121–130. doi: 10.1016/j.brainres.2007.02.077 [DOI] [PubMed] [Google Scholar]
- 40.Navigatore-Fonzo LS, Golini RL, Ponce IT, et al. Retinoic acid receptors move in time with the clock in the hippocampus. Effect of a vitamin-A-deficient diet. J Nutr Biochem. 2013;24(5):859–867. doi: 10.1016/j.jnutbio.2012.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Golini RS, Delgado SM, Navigatore Fonzo LS, Ponce IT, Lacoste MG, Anzulovich AC. Daily patterns of clock and cognition-related factors are modified in the hippocampus of vitamin A-deficient rats. Hippocampus. 2012;22(8):1720–1732. doi: 10.1002/hipo.22007 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used during the current study are available from both corresponding authors on reasonable request.