Sleep problems and mental health in middle-aged and older autistic and non-autistic adults

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G. Quinton, Rebecca A. Charlton, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7677602/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Sleep is a vital biological function, and impaired sleep can lead to a range of problems, including poor health and wellbeing. Poor sleep and higher rates of sleep disorders are often reported by autistic children and adults, as well as middle-aged and older people with high autistic traits. However, these experiences and problems have seldom been studied in diagnosed autistic populations in midlife and old age. Methods: This study used data from the first wave of the AgeWellAutism cohort, from a sample of 265 autistic and 167 age- and gender-matched non-autistic adults aged 40 to 93 years (mean = ~60 years; ~50% female). Participants completed widely used and standardised measures of sleep quality and mental health symptoms. Results: The autistic group reported significantly more sleep difficulties than the non-autistic group, including poorer sleep quality, longer time to fall asleep, shorter duration, lower efficiency, more disturbances, greater reliance on sleep medication, and increased daytime tiredness and dysfunction. These differences remained significant after controlling for age and poor mental health (measured by symptoms of anxiety, depression and PTSD). Poor sleep was also associated with older age and mental health issues in both groups, with a stronger association between sleep problems and anxiety symptoms in the autistic versus non-autistic group. Conclusions: Consistent with prior autism trait-based research in the general population, middle-aged and older autistic adults report more extensive sleep problems and worse sleep quality than non-autistic adults. Sleep problems were associated with older age and poorer mental health. Though the study is cross-sectional, the findings highlight the need to explore causal links through intervention. Addressing anxiety, and mental health problems more broadly, may improve sleep quality in ageing autistic populations. Psychology Geriatrics & Gerontology Autism Sleep Mental Health Midlife Old Age Key Points Middle-aged and older autistic adults report significantly more sleep problems than non-autistic peers, including poor sleep quality, longer sleep onset, and increased daytime fatigue, even after accounting for age and mental health problems. Poor sleep in both autistic and non-autistic individuals was associated with older age and more mental health issues, particularly depression, anxiety, and PTSD symptoms. Sleep problems had a stronger relationship with anxiety symptoms in the autistic group versus the non-autistic group, suggesting anxiety may play an important role in sleep quality among ageing autistic individuals. The findings emphasize the need for targeted interventions to address anxiety and other mental health concerns to potentially improve sleep - and related outcomes in middle-aged and older autistic adults. INTRODUCTION Autism is a neurodevelopmental condition affecting around 1% of the global population, characterised by differences in social communication and rigid-repetitive behaviours. 1 , 2 Despite autism being a lifelong condition, the experiences and outcomes of middle-aged and older autistic adults, who likely make up half of all autistic people, have historically been overlooked. 3 Specifically, only 0.4% of indexed autism research between 1980 and 2020 focused on this older age group. 4 A growing evidence-base reveals that autistic people of all ages experience on average greater health burdens, poorer mental health and normative life outcomes, 4–11 more periods of crisis, 12–14 and lower quality of life 15 , 16 than their non-autistic peers. Research has also found that autistic children and adults often experience problems with sleep. 17 – 21 Sleep is a vital biological function 22 , with disrupted sleep predicting early mortality in the general population. 23 Sleep experiences change with age, with older adults often experiencing shorter sleep duration and more fragmented sleep, contributing to increased daytime fatigue, impaired cognitive function, mood disturbances and lower quality of life. 24 Sleep problems are particularly common among autistic individuals. 17 , 25 A meta-analysis by Morgan et al. (2020) 19 reviewed 14 empirical studies of autistic adults (mean age 21–40 years, total n = 194), finding more significant subjectively and objectively measured sleep problems compared to non-autistic peers. Subjective complaints (measured by self-report) included lower sleep efficiency (i.e., more time awake relative to sleep time in bed), longer sleep onset latency (i.e., taking longer to fall asleep), and higher prevalence of sleep problems. Objective problems (measured by actigraphy or polysomnography) included lower sleep efficiency, greater sleep fragmentation, longer sleep onset latency, and shorter total sleep time. Qualitative studies also document persistent sleep problems and their association with poorer health and wellbeing in autistic adults. 18 , 21 However studies have largely focused on autistic young adults, and neglected midlife and old age. As well as disrupted sleep, high rates of clinically diagnosed sleep disorders are reported in autistic populations. 17 , 25 Croen et al. (2015), 6 analysing private healthcare records from 1,507 individuals aged 19–79, found higher rates of insomnia and dyssomnia in autistic adults than in matched non-autistic comparisons (17.5% vs. 9.6%; OR = 1.9). Additionally, Bishop-Fitzpatrick et al. (2017) 5 reported that 85% (n = 121) of autistic adults aged 40 + had a dyssomnia diagnosis in Wisconsin-Medicaid health records. These cross-sectional findings highlight the prevalence of sleep problems in middle-aged and older autistic adults, though further longitudinal studies are needed to examine age-related changes. Sleep problems are also strongly linked to poor mental health. Lawson et al. (2020), 26 in a longitudinal study of 244 autistic and 165 non-autistic people aged 15–80, found positive associations between sleep problems, depression, anxiety, and lower quality of life in both groups. Further to these associations, PTSD symptoms may be especially relevant in autistic populations; trauma and PTSD are frequently reported in autistic groups, 27–29 and in the general population PTSD is associated with insomnia, nightmares, and disrupted sleep. 30 , 31 Considering PTSD symptoms alongside depression and anxiety may therefore provide a fuller understanding of the relationship between sleep and mental health in autistic adults. Although early research on sleep and mental health in older autistic populations was limited, recent lifespan studies have begun to examine age effects. Jovevska et al. (2020), 32 studying 297 autistic and non-autistic individuals aged 15–80 (mean age = ~ 34), found that autistic participants, particularly those in midlife (aged 40–59), reported poorer sleep quality and longer sleep onset latency than non-autistic peers. Mental health conditions predicted poorer sleep quality in autistic and non-autistic groups across all ages. Furthermore, Charlton et al. (2023), 33 in a larger sample of 730 autistic adults aged 18–78 (mean age = ~ 40), found that 85.5% met criteria for poor sleep quality based on self-report measures. Predictors of poor sleep quality included physical health problems, female gender (sex assigned at birth), and anxiety symptoms. Age had little overall impact on sleep quality, though older age correlated with shorter sleep latency and greater sleep disturbance. Similar patterns have also been found in studies specifically focusing on middle-aged and older people with high autistic traits. Stewart et al. (2020) 20 identified 187 adults aged 50–81 with high autistic traits in the PROTECT cohort (total n = 13,897) and showed that, despite similar total sleep durations, the high-trait group experienced markedly poorer sleep: they reported more difficulty falling asleep, greater daytime drowsiness, and lower overall sleep quality and satisfaction, with a higher prevalence of severe sleep problems than the low-trait group (21.4% vs. 10.3%; OR = 2.36). These sleep disturbances were strongly linked to poorer mental health, and there was a significant interaction such that individuals with both high autistic traits and severe sleep problems exhibited the highest levels of depression and anxiety among all trait–sleep combinations. These findings suggests that severe sleep problems may have a disproportionately negative impact on mental health in people with higher autistic traits. Taken together, these studies that include autistic/high autistic trait people in midlife and old age highlight that sleep problems may be cause for concern as autistic people age. Additionally, the rates of sleep problems, potential relationships with mental health problems (e.g., depression, anxiety, and PTSD symptoms), and the influence of age and gender require further exploration. The current study is a conceptual replication and expansion of Stewart et al. (2020) 20 trait-based study, examining sleep problems and mental health in middle-aged and older autistic adults versus age- and gender-matched non-autistic adults. We predict (i) higher self-reported sleep problems, and (ii) more current symptoms of depression, anxiety and PTSD in autistic adults compared to non-autistic adults. Additionally, (iii) those with clinically significant sleep problems will report worse mental health, especially in the autistic group. Further, (iv) older autistic adults (age 65+) will report higher rates of sleep problems and poorer mental health in comparison to midlife (age 40–64) autistic adults. Finally, (v) women will report higher rates of sleep problems and poor mental health than men, with this effect being stronger in the autistic group than non-autistic group. Sleep quality index scores were compared using an ANCOVA, with depression, anxiety, and PTSD symptoms as covariates to control for self-report bias. METHODS Study Design This pre-registered study (https://osf.io/973z8/) uses cross-sectional data from the first wave of the ‘AgeWellAutism’ study, conducted in Spring 2019. The AgeWellAutism study is an online survey investigating ageing on the autism spectrum (outlined in Stewart et al., (2024)). 10 In brief, the AgeWellAutism study was steered by 12 middle-aged and older autistic adults prior to launch, with recruitment conducted via social media platforms, research databases, Autistica's Research Network, and adverts in community centres and older adult residential communities. Participants were entered into a draw for one of twenty £20 Amazon UK gift vouchers. Inclusion criteria were being 40 years of age or above, having access to an internet-enable device, and being able to read and type in English. The study had no specific exclusion criteria. Full ethical approval was granted by the PNM Research Ethics Subcommittee at King's College London (HR-18/19–10941). Participants In total, 502 completed surveys were recorded, with 70 responses excluded due to suspected spam. The final sample had 432 participants aged 40-93 years. Participants who disclosed that they either had an autism diagnosis (n=254) or self-identified as autistic (n=11) formed an autistic group (n=265); both subgroups had comparable Ritvo Autism and Asperger Diagnostic Scale (RAADS-14) 34 autistic trait scores ( t (1,263)=1.54, p= .124), with mean scores in both subgroups exceeding the cut-off for clinically significant autistic traits. Timing of autism diagnoses/self-identification ranged from as recently as the year of survey completion to 43 years earlier (mean years since diagnosis=10.3 years), with 17 (6.4%) diagnosed in childhood (i.e., prior to 18 years of age). The remaining participants formed the non-autistic group (n=167). The autistic and non-autistic groups were matched on age (autistic mean age=60.5 years; non-autistic mean age=60.6 years) and gender ratio (autistic group men=46.8%; non-autistic group men=50.3%). Both groups were comparable in education level and in country of residence, with around 98% living in the UK. However, the autistic sample self-reported lower employment rates and a higher likelihood of living with non-marital family members. Data on socio-economic status and race/ethnicity were not collected. For some analyses, age was dichotomised into midlife (aged 40-64 years; autistic n=158, non-autistic n=106) and old age (aged 65+; autistic n=107, non-autistic n=61) subgroups. This stratification avoids assuming a linear age-outcome relationship and supports interpretability for clinicians and researchers. See Table 1 for demographic characteristics of the autistic and non-autistic groups. -------------------------------------------------------------------------------- TABLE 1 HERE -------------------------------------------------------------------------------- Materials Demographic Characteristics – Participants provided detailed self-reported demographic information, including age, gender, highest educational attainment, employment status, who they live with, and country of residence. Participants were also asked whether they had an autism diagnosis or if they self-identified as autistic. If yes, they were then asked when they received their diagnosis or began to self-identify. Sleep – Sleep problems were measured using the Pittsburgh Sleep Quality Index (PSQI) questionnaire, 35 a 24-item questionnaire assessing objective sleep behaviours and subjective difficulties over the past month. PSQI items are transformed into seven subscales (overall sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, requiring sleep medication and daytime dysfunction), scored from 0 (no problems) to 3 (greatest dysfunction). These subscales are totalled to obtain a global sleep problems score (range: 0-21). In the current sample, the internal consistency of the PSQI was very good in the autistic group (Cronbach’s α=.82) and good in the non-autistic group (Cronbach’s α=.78). Depression – Symptoms of depression were measured using the Patient Health Questionnaire (PHQ-9), 36 a nine-item questionnaireusing a four-point scale, assessing a range of problems over the past two weeks. Using the conventional cut-off score of ≥10, the PHQ-9 has a sensitivity of 88% and a specificity of 88% for major depressive disorder. The PHQ-9 has been validated for use in autistic adults. 37 In the current sample, the internal consistency of the PHQ-9 was very good in the autistic group (Cronbach’s α=.88) and good in the non-autistic group (Cronbach’s α=.71). Anxiety – Symptoms of anxiety were measured using the Generalised Anxiety Disorder questionnaire (GAD-7). 38 The GAD-7 is a seven-item questionnaire using a four-point scale assessing the severity of anxiety symptoms over the past two weeks. Using the conventional cut-off score of ≥10, the GAD-7 has a sensitivity of 89% and a specificity of 82% for generalised anxiety disorder. The GAD-7 has been validated for use in autistic younger adult populations. 39 In the current sample, the internal consistency of the GAD-7 was acceptable in both autistic (Cronbach’s α=.78) and non-autistic groups (Cronbach’s α=.74). PTSD – Symptoms of PTSD were measured using the Post Traumatic Stress Disorder Checklist (PCL-6). 40 The PCL-6 is a six-item questionnaire using a 5-point scale assessing PTSD symptom frequency in the past month. Using the conventional cut-off of ≥17, the PCL-6 has a sensitivity of 80% and a specificity of 76% for PTSD. To the authors knowledge, the PCL-6 has not yet been validated in autistic samples. In the current sample, the internal consistency of the PCL-6 was excellent in the autistic group (Cronbach’s α=.90) and good in the non-autistic group (Cronbach’s α=.79). Data Analysis All analyses were conducted using SPSS (v25.0; IBM Corp., 2017). Group differences (autistic vs. non-autistic) in demographics were assessed using t -tests (continuous variables) and chi-square (χ 2 ) tests (categorical variables). χ 2 tests also examined differences in sleep problem subscales between autism groups, as well as gender (men vs. women) and age (midlife, age 40-64 vs. old age, age 65+), with adjusted residuals identifying specific differences. ANOVAs assessed group differences in total sleep quality index scores, as well as symptoms of depression, anxiety, and PTSD. ANCOVAs further adjusted sleep quality index scores for symptoms of depression and anxiety, and age. Bivariate correlations (with Fisher’s r-to-z transformations) examined associations between sleep quality index scores and mental health symptoms within each group. Gender and age group effects and interactions on sleep problem subscales and sleep quality index scores were explored using layered χ 2 tests and 2x2 ANOVA. All analyses were controlled for using the False Discovery Rate (FDR) method 41 with a final α-value of .029. RESULTS Sleep Problems The autistic group were significantly more likely to report difficulties with their sleep compared to the non-autistic group. These difficulties included poorer sleep quality (χ2=71.1, p< .001), longer sleep latency (χ2=24.2, p< .001), shorter sleep duration (χ2=15.6, p< .001), lower sleep efficiency (χ2=21.0, p< .001), more sleep disturbances (χ2=101.8, p< .001), greater use of sleep medication (χ2=27.5, p< .001), and more often experiencing daytime tiredness and dysfunction (χ2=95.1, p< .001). Adjusted residual values indicate that the autistic group more frequently reported moderate-to-severe difficulties in these sleep domains than the comparison group. See Table 2. When considering gender differences, autistic women reported significantly greater difficulties in sleep duration (χ2=13.39, p= .004), sleep disturbance (χ2=11.39, p= .010) and daytime dysfunction (χ2=13.38, p= .004) compared to autistic men. Adjusted residual values indicate that autistic women more frequently experienced moderate-to-severe difficulties in these sleep domains than autistic men. No other gender differences were found in the autistic group, and no gender differences were found in the non-autistic group. See Supplementary Table 1. When viewing sleep problems as a combined composite score, the autistic group reported significantly higher sleep quality index scores than the non-autistic group (F(1,429)=121.29, pmen), this did not survive multiple comparison correction (F(1,429)=29.14, p= .040). A significant interaction between autism group and gender (F(3,427)=12.89, p< .001) indicated that within the autistic group, women reported significantly more sleep problems than men, whereas no gender differences emerged in the non-autistic group. A similar pattern of results was found when accounting for age and current symptoms of depression and anxiety. See Supplementary Table 2. -------------------------------------------------------------------------------- TABLES 2 AND 3 HERE -------------------------------------------------------------------------------- Symptoms of poor Mental Health The autistic group reported significantly higher symptoms of depression (F(1,430)=237.35, p< .001), anxiety (F(1,430)=192.98, p< .001), and PTSD (F(1,430)=267.31, p< .001) than the non-autistic group.Additionally, a significantly higher proportion of autistic versus non-autistic individuals met clinical cut-off thresholds for depression (18.9% vs. 6.6%; χ²=12.74, p< .001), anxiety (35.5% vs. 7.8%; χ²=42.14, p< .001) and PTSD symptoms (26.8% vs. 1.2%; χ²=47.79, pmen) was found in PTSD symptoms (F(1,430)=42.90, p< .001). The gender difference in PTSD symptoms was significantly greater in the autistic group than in the non-autistic group (F(3,424)=9.97, p= .002), with the difference between women and men in PTSD scores being greater in the autistic group than non-autistic group. No other main effects of gender or interactions were found in depression and anxiety scores. See Supplementary Table 2. Associations between sleep problems, mental health, and age In the autistic group, sleep problems (measured by sleep quality index score) were significantly correlated with depression symptoms ( r= .386, p< .001), anxiety symptoms ( r= .459, p< .001), PTSD symptoms ( r= .364, p< .001), and older age ( r= .345, p< .001). Similarly, in the non-autistic group, sleep problems were significantly associated with depression symptoms ( r= .259, p< .001), anxiety symptoms ( r= .186, p< .001), PTSD symptoms ( r= .221, p= .004), and older age ( r= .226, p= .003). The strength of association differed between autistic and non-autistic groups only for sleep and anxiety (z=3.27, p< .001). No group differences were found in the association strengths between sleep problems and depression symptoms, PTSD symptoms, or age. Sleep Problems in Midlife and Old Age When comparing midlife (age 40-64) and old age (age 65+) groups, differences emerged within each group. Older autistic adults reported significantly more sleep difficulties than middle-aged autistic adults in sleep quality (χ2=9.55, p= .008), sleep duration (χ2=9.02, p= .029), sleep efficiency (χ2=8.31, p= .016), sleep disturbances (χ2=44.97, p< .001), requirement of sleep medicines (χ2=8.05, p= .018), and daytime tiredness and dysfunction (χ2=25.53, p< .001). No differences were found in sleep latency. Adjusted residual values indicate that the old age autistic sub-group more often reported moderate-to-severe difficulties in these sleep domains than the midlife autistic sub-group. Older non-autistic adults also reported significantly more sleep difficulties than middle-aged non-autistic adults in sleep efficiency (χ2=7.75, p= .021), sleep disturbances (χ2=16.51, p< .001), and daytime tiredness and dysfunction (χ2=9.79, p= .020). No differences were found in sleep quality, duration, or requirement of medication use. Adjusted residual values indicate that older non-autistic adults more frequently experienced moderate-to-severe difficulties in these sleep domains than middle-aged non-autistic adults. See Supplementary Table 3. When viewing sleep problems as a combined composite score, main effects of autism group (autistic > non-autistic; F(1,427)=54.23, p midlife; F(1,427)=20.51, p< .001) were found. An interaction between autism group and age was also found (F(3,424)=5.33, p= .021), with autism and old age having a compounded effect on sleep problems. See Supplementary Table 4. DISCUSSION This study addresses a significant gap in the literature regarding sleep problems and associated mental health problems in a large sample of autistic adults in midlife and old age compared to age- and gender-matched non-autistic adults. Our findings indicate that middle-aged and older autistic adults reported significantly more severe and cumulative sleep problems than their non-autistic peers, even after accounting for age, anxiety, and depression. While older age and symptoms of depression and PTSD were associated with sleep problems, a particularly strong association was found between sleep problems and anxiety in the autistic group. When further exploring the effect of age on sleep, our analyses suggested that older age and being autistic may compound sleep problems. Taken together, these findings highlight the need for greater awareness of sleep problems in ageing autistic populations. Consistent with prior research examining sleep problems in middle-aged and older high autistic trait populations (i.e., Stewart et al., 2020) 20 and diagnosed autistic lifespan samples (i.e., Jovevska et al., 2020; Charlton et al., 2023), 32,33 our study found autistic participants reported significantly more severe individual and cumulative sleep difficulties than non-autistic peers. This pattern interacted with gender, with autistic women reporting more problems than men, and with age, with older autistic adults reporting more difficulties than those in midlife. Although sleep problems are well documented in younger autistic populations 17 , 19 , 42 including women and girls, 43,44 our findings suggest age is a key contributor to the high rates observed in midlife and older adulthood. Contributing factors may include sensory differences, 45,46 greater physical and mental health burdens, 7,8,47 and menopause-related symptoms. 48 , 49 Broader ageing processes, such as reduced melatonin secretion 50 and increased medication use, 51 may also exacerbate problems. These biological, physiological, and social factors likely contribute to the heightened prevalence and severity of sleep difficulties in older autistic adults. Given that disrupted sleep predicts mortality risk in the general population, 23 addressing sleep problems in autistic populations is crucial. Our findings, together with existing literature, point to age- and gender-specific risk factors in autistic populations that warrant attention in clinical care. A second key finding was the strong association between sleep problems and mental health difficulties. This aligns with prior work in both the general population, 52 and autistic/high autistic trait populations. 20 , 25 , 32 , 33 While present in both autistic and non-autistic groups, the link with anxiety was significantly stronger for autistic participants. Studies consistently report strong associations between anxiety and sleep disruption in autistic children and adults. 53 – 56 This likely reflects the bidirectional relationship between sleep and mental health: poor sleep worsens depression, anxiety, and PTSD by impairing emotional regulation and increasing stress sensitivity, 57,58 while elevated mental health symptoms, particularly anxiety, disrupt sleep through arousal, worry, and difficulty relaxing. 59 Despite this, sleep is rarely addressed systematically in clinical practice. 60 Explicitly considering sleep when supporting autistic adults may therefore help reduce the high rates of anxiety and related difficulties. 26 When contextualising these findings, several strengths and limitations should be noted. A key strength was the involvement of autistic adults in shaping survey content and language use. The study also recruited a large, gender-balanced sample of middle-aged and older adults using multiple methods and included an age- and gender-matched non-autistic comparison group, enabling well-powered analyses. Importantly, it contributes to an under-researched area, as most autism research focuses on childhood or young adulthood, offering new insights into age-related sleep problems. Limitations include reliance on self-report instruments (e.g., PSQI). While these can predict functional difficulties, 61 subjective reports may diverge from objective measures such as actigraphy, with individuals often overestimating sleep latency and underestimating sleep time. 62 Future work should integrate both methods to clarify perceived versus actual sleep problems. The study also lacked detailed medication data (e.g., use of sleep aids or psychotropics), which could influence reported rates. Recruitment bias may further limit generalisability, as older research participants are typically healthier than the wider population. 63 Finally, the cross-sectional design precludes conclusions about age-related changes or causal links between sleep and mental health. 64 Longitudinal studies combining validated self-report tools, objective measures, medication data, and representative samples are needed to clarify these associations in ageing autistic populations. In conclusion, this study replicates and expands on existing findings that autistic adults in midlife and old age experience significantly higher rates of sleep difficulties and mental health symptoms compared to non-autistic adults. Sleep problems were not only more common but also more severe and cumulative in the autistic group, and these difficulties remained evident even after accounting for anxiety, depression, and age. Furthermore, sleep disturbance was more strongly linked to anxiety in autistic individuals, pointing to a potentially unique interplay between sleep and mental health in this population. Older autistic adults may be at elevated risk, emphasising the need for lifespan-oriented and autism-informed clinical interventions. These findings highlight the importance of integrating sleep assessments into routine mental health care for autistic adults, particularly as they age. Given the bidirectional relationship between sleep disturbance and psychiatric symptoms, targeting sleep may offer a valuable pathway to improving overall well-being in this population. Future research using longitudinal designs, objective sleep measures, and more diverse, representative samples will be essential to advance evidence-based, personalised care. Declarations AUTHOR CONTRIBUTIONS Authors FH, RAC and GRS conceived the AgeWellAutism study. GRS designed the online survey and selected materials. GRS conceived the current study. SR, AB and GRS conducted analyses. SR wrote the manuscript under the supervision of GRS. AB, FH and RAC reviewed the final draft. All authors have read and approved the final manuscript. CONFLICTS OF INTEREST None to declare. ACKNOWLEDGEMENTS The authors are grateful to the 12 autistic adults who offered suggestions on content and provided feedback on the language-use and accessibility of the study materials. At the time of data collection, GRS was funded by an UKRI/ESRC LISS-DTP PhD studentship (ES/P000703/1). GRS is currently funded by a British Academy Postdoctoral Research Fellowship (PFSS23\230043). FH is part-funded by the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre and King’s College London (KCL). The funders have had no role in the data collection, analysis, interpretation, or any other aspect pertinent to the study. The authors have not been paid to write this article by any agency. 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BMJ Open 2(6):e000833. 10.1136/bmjopen-2012-000833 Savitz DA, Wellenius GA (2023) Can Cross-Sectional Studies Contribute to Causal Inference? It Depends. Am J Epidemiol 192(4):514–516. 10.1093/aje/kwac037 Tables Table 1. Demographic characteristics of the autistic and non-autistic groups. Autistic group (n=265) non-Autistic group (n=167) Group Difference Effect Size Age (years) M (SD) 60.59 (12.89) 60.53 (13.54) F(1,430)=0.01, p= .960 d =0.01 [-0.19-0.19] [95% CI] [59.03-62.15] [58.46-62.60] Min-Max 40 - 91 40 - 93 Gender men : women : nb/t 124 : 137 : 4 84 : 83 χ2=2.86, p= .239 d =0.10 [-0.09-0.29] % 46.8% : 51.7% : 1.5% 50.3% : 49.7% Living situation Spouse or Partner 98 (37.0%) 79 (47.3%) χ2=4.52, p= .034^ v=.102 Children 71 (26.8%) 39 (23.4%) χ2=.64, p= .424 v=.038 Sibling 34 (12.8%) 0 χ2=23.26, p< .001*** v=.232 Parent 22 (8.3%) 7 (4.2%) χ2=2.76, p= .096 v=.0.80 Other Family Member 10 (3.8%) 0 χ2=6.45, p= .011* v=.122 Roommate/Friend 21 (7.9%) 12 (7.2%) χ2=.08, p= .778 v=.014 Supported Housing 44 (16.6%) 20 (12.0%) χ2=1.74, p= .187 v=.063 Alone independently 52 (19.6%) 58 (34.7%) χ2=12.32, p< .001*** v=.169 Education history No formal qualifications 28 10.6% 4 2.4% χ2=1.05, p= .310 v=.209 School to 16 62 23.40% 27 16.2% School to 18 77 29.10% 66 39.5% Undergraduate 59 22.3% 51 30.5% Postgraduate 39 14.7% 19 11.4% Current employment status Employed 75 (28.3%) 88 (52.7%) χ2=45.65, p< .001*** v=.325 Retired 125 (47.2%) 74 (44.3%) Unemployed 65 (24.5%) 5 (3.0%) Autism Diagnosis Diagnosed 254 (95.8%) 0 - - - Self-identified 11 (4.2%) 0 Years since Autism Diagnosis/Identity M (SD) 10.26 (8.22) - - - Min-Max 0 - 43 Note: nb/t = non-binary and trans. ^ Does not survive FDR correction. FDR adjusted a-value=* p< .029, ** p< .01, *** p< .001. Table 2. Frequencies and group differences of sleep problem domains of the autistic and non-autistic groups. Sleep Problems Score Group Difference Effect Size No difficulty Some difficulty Moderate difficulty Severe Difficulty Sleep Quality Autistic 139 (52.7%) ╪ 89 (33.7%) ╪ 36 (13.6%) ╪ 0 - χ2=71.1, p< .001*** v=.406 non-Autistic 153 (91.6%) ╪ 12 (7.2%) ╪ 2 (1.2%) ╪ 0 - Sleep Latency Autistic 14 (5.3%) 32 (12.1%) ╪ 141 (53.4%) 77 (29.2%) χ2=24.2, p< .001*** v=.237 non-Autistic 6 (3.6%) 52 (31.1%) ╪ 75 (44.9%) 34 (20.4%) Sleep Duration Autistic 119 (45.1%) ╪ 79 (29.9%) 53 (20.1%) ╪ 13 (4.9%) ╪ χ2=15.6, p< .001*** v=.190 non-Autistic 97 (58.1%) 50 (29.9%) 20 (12.0%) ╪ 0 - Sleep Efficiency Autistic 142 (53.8%) 63 (23.9%) ╪ 59 (22.3%) ╪ 0 - χ2=21.0, p< .001*** v=.221 non-Autistic 92 (55.1%) 63 (37.7%) ╪ 12 (7.2%) ╪ 0 - Sleep Disturbance Autistic 4 (1.5%) ╪ 121 (45.8%) ╪ 125 (47.3%) ╪ 14 (5.3%) ╪ χ2=101.8, p< .001*** v=.485 non-Autistic 28 (16.8%) ╪ 124 (74.3%) ╪ 15 (9.0%) ╪ 0 - Medication Use Autistic 151 (57.2%) ╪ 88 (33.3%) ╪ 25 (9.5%) ╪ 0 - χ2=27.5, p< .001*** v=.251 non-Autistic 134 (80.2%) ╪ 31 (18.6%) ╪ 2 (1.2%) ╪ 0 - Daytime Dysfunction Autistic 9 (3.4%) ╪ 117 (44.4%) 118 (44.1%) ╪ 20 (8.0%) ╪ χ2=95.1, p< .001*** v=.471 non-Autistic 54 (32.3%) ╪ 86 (51.5%) 25 (15.0%) ╪ 2 (1.2%) ╪ Note: ╪ indicates significant adjusted residual value. FDR adjusted a-value = * p< .029, ** p< .01, *** p< .001. Table 3. Descriptive statistics and group differences of sleep problems and mental health problems of the autistic and non-autistic groups. Autistic group (n=265) non-Autistic group (n=167) Group Difference Effect Size Sleep Quality Index (max score = 21) M (SD) 7.85 (2.95) 4.95 (2.12) F(1,430)=121.29, p< .001*** d=1.12 [0.88 - 1.29] [95% CI] [7.50-8.21] [4.63-5.28] Min-Max 1 - 16 1 - 14 r Depression r= .386*** r= .259*** z=1.43, p= .152 - r Anxiety r= .459*** r= .186* z=3.27, p< .001*** r PTSD r= .364*** r= .221** z=1.57, p= .116 r Age r= .345*** r= .226** z=1.30, p= .193 Depression (max score = 27, cut-off ≥10) M (SD) 9.82 (5.39) 2.99 (2.39) F(1,430)=237.35, p< .001 d=1.52 [1.30-1.74] [95% CI] [9.16-10.46] [2.62-3.36] Range 0 - 18 0 - 13 % above cut-off 50 (18.9%) 11 (6.6%) χ2=12.74, p< .001*** v=.558 Anxiety (max score = 21, cut-off ≥10) M (SD) 6.36 (3.36) 2.49 (1.60) F(1,430)=192.98, p< .001 d=1.37 [1.15-1.58] [95% CI] [5.95-6.76] [2.23-2.73] Range 0 - 18 0 - 11 % above cut-off 94 (35.5%) 13 (7.8%) χ2=42.14, p< .001*** v=.228 PTSD (max score = 24, cut-off ≥17) M (SD) 12.17 (6.32) 3.35 (3.65) F(1,430)=267.31, p< .001*** d=1.61 [1.39-1.84] [95% CI] [11.40-12.93] [2.80-3.92] Range 0 - 24 0 - 23 % above cut-off 71 (26.8%) 2 (1.2%) χ2=47.79, p< .001*** v=.333 Note: FDR adjusted a-value = * p< .029, ** p< .01, *** p< .001. Supplementary Tables Supplementary Tables 1 to 4 are not available with this version. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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G. Quinton","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Alice","middleName":"M. G.","lastName":"Quinton","suffix":""},{"id":518785762,"identity":"bcdea267-57ca-46b0-a1fd-1ac4ce281e12","order_by":3,"name":"Rebecca A. Charlton","email":"","orcid":"https://orcid.org/0000-0002-3326-8762","institution":"Goldsmith University of London","correspondingAuthor":false,"prefix":"","firstName":"Rebecca","middleName":"A.","lastName":"Charlton","suffix":""},{"id":518785763,"identity":"62554b3d-2c33-4913-ac38-7f546ff5c33d","order_by":4,"name":"Francesca Happé","email":"","orcid":"https://orcid.org/0000-0001-9226-4000","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Happé","suffix":""},{"id":518785764,"identity":"deea44c2-2d97-473e-a036-1fe214351d7d","order_by":5,"name":"Gavin R. Stewart","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYJCCAwhmRQIDH4SVQFCLBIR1JoGBjRgtDHAtB9uI0CLvfsbwcAFDXR2/RPKzzx/npcmzMTA//MDYloZTi+GZHIPDMxgOS0jOSDOecXBbjmEbA5uxBGNbDm4tDWkJh3kYDkgY3E4wZji4rSIB6DAzBsa2Ctxa+p+BtNRJ2N9O/8xwcA5IC/s3vFrkJZIPALUwSxhI5wBtacgBauEB2YLbYQYSj4FaDA5Lzrj/ppjhzLE0wzZmnmKJhHO4vS/fn9j8maeijp+/5/hmhoqaZHl+9vaNHz6UJeO25QCYRBZiZsAfkfINeCRHwSgYBaNgFIABAA9bTUokG2C4AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-9262-888X","institution":"King's College London","correspondingAuthor":true,"prefix":"","firstName":"Gavin","middleName":"R.","lastName":"Stewart","suffix":""}],"badges":[],"createdAt":"2025-09-22 13:54:07","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7677602/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7677602/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92024207,"identity":"5aba4e0a-3873-4ed7-91c3-9ff914581333","added_by":"auto","created_at":"2025-09-23 18:36:21","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":175801,"visible":true,"origin":"","legend":"","description":"","filename":"IJGPAWA2019Sleepmanuscriptv1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7677602/v1/56969507450d966564d2fff2.docx"},{"id":92024203,"identity":"b202b042-2738-4f04-918f-f796a380b5c5","added_by":"auto","created_at":"2025-09-23 18:36:21","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs7677602.json","url":"https://assets-eu.researchsquare.com/files/rs-7677602/v1/9182e54fbed8ad99a2c51a75.json"},{"id":92024204,"identity":"155a8b16-7ede-4e0e-b4bc-9c64ae59ac8f","added_by":"auto","created_at":"2025-09-23 18:36:21","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":185575,"visible":true,"origin":"","legend":"","description":"","filename":"rs76776020enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7677602/v1/dc5d3afd31270c784ef92e66.xml"},{"id":92024205,"identity":"5553cdb1-2ccd-4c04-bd39-04ecdad649ee","added_by":"auto","created_at":"2025-09-23 18:36:21","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":181563,"visible":true,"origin":"","legend":"","description":"","filename":"rs76776020structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7677602/v1/b721b7071e92215c475225a5.xml"},{"id":92024206,"identity":"fd601240-478c-470e-bf4c-11f2e4df4ff2","added_by":"auto","created_at":"2025-09-23 18:36:21","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":198337,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7677602/v1/3e51ce805aa87d463fe098e3.html"},{"id":92024777,"identity":"a331e302-3aee-481b-9fbc-316da706b128","added_by":"auto","created_at":"2025-09-23 18:44:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1065244,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7677602/v1/3ce5279e-f439-4c3e-82db-92a76d9914bc.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSleep problems and mental health in middle-aged and older autistic and non-autistic adults\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Key Points","content":"\u003col\u003e\n \u003cli\u003eMiddle-aged and older autistic adults report significantly more sleep problems than non-autistic peers, including poor sleep quality, longer sleep onset, and increased daytime fatigue, even after accounting for age and mental health problems.\u003c/li\u003e\n \u003cli\u003ePoor sleep in both autistic and non-autistic individuals was associated with older age and more mental health issues, particularly depression, anxiety, and PTSD symptoms.\u003c/li\u003e\n \u003cli\u003eSleep problems had a stronger relationship with anxiety symptoms in the autistic group versus the non-autistic group, suggesting anxiety may play an important role in sleep quality among ageing autistic individuals.\u003c/li\u003e\n \u003cli\u003eThe findings emphasize the need for targeted interventions to address anxiety and other mental health concerns to potentially improve sleep - and related outcomes in middle-aged and older autistic adults.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eAutism is a neurodevelopmental condition affecting around 1% of the global population, characterised by differences in social communication and rigid-repetitive behaviours.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Despite autism being a lifelong condition, the experiences and outcomes of middle-aged and older autistic adults, who likely make up half of all autistic people, have historically been overlooked.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Specifically, only 0.4% of indexed autism research between 1980 and 2020 focused on this older age group.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e A growing evidence-base reveals that autistic people of all ages experience on average greater health burdens, poorer mental health and normative life outcomes,\u003csup\u003e4\u0026ndash;11\u003c/sup\u003e more periods of crisis,\u003csup\u003e12\u0026ndash;14\u003c/sup\u003e and lower quality of life\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e than their non-autistic peers. Research has also found that autistic children and adults often experience problems with sleep.\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eSleep is a vital biological function\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, with disrupted sleep predicting early mortality in the general population.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Sleep experiences change with age, with older adults often experiencing shorter sleep duration and more fragmented sleep, contributing to increased daytime fatigue, impaired cognitive function, mood disturbances and lower quality of life.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Sleep problems are particularly common among autistic individuals.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e A meta-analysis by Morgan et al. (2020)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e reviewed 14 empirical studies of autistic adults (mean age 21\u0026ndash;40 years, total n\u0026thinsp;=\u0026thinsp;194), finding more significant subjectively and objectively measured sleep problems compared to non-autistic peers. Subjective complaints (measured by self-report) included lower sleep efficiency (i.e., more time awake relative to sleep time in bed), longer sleep onset latency (i.e., taking longer to fall asleep), and higher prevalence of sleep problems. Objective problems (measured by actigraphy or polysomnography) included lower sleep efficiency, greater sleep fragmentation, longer sleep onset latency, and shorter total sleep time. Qualitative studies also document persistent sleep problems and their association with poorer health and wellbeing in autistic adults.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e However studies have largely focused on autistic young adults, and neglected midlife and old age.\u003c/p\u003e\u003cp\u003eAs well as disrupted sleep, high rates of clinically diagnosed sleep disorders are reported in autistic populations.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Croen et al. (2015),\u003csup\u003e6\u003c/sup\u003e analysing private healthcare records from 1,507 individuals aged 19\u0026ndash;79, found higher rates of insomnia and dyssomnia in autistic adults than in matched non-autistic comparisons (17.5% vs. 9.6%; OR\u0026thinsp;=\u0026thinsp;1.9). Additionally, Bishop-Fitzpatrick et al. (2017)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e reported that 85% (n\u0026thinsp;=\u0026thinsp;121) of autistic adults aged 40\u0026thinsp;+\u0026thinsp;had a dyssomnia diagnosis in Wisconsin-Medicaid health records. These cross-sectional findings highlight the prevalence of sleep problems in middle-aged and older autistic adults, though further longitudinal studies are needed to examine age-related changes.\u003c/p\u003e\u003cp\u003eSleep problems are also strongly linked to poor mental health. Lawson et al. (2020),\u003csup\u003e26\u003c/sup\u003e in a longitudinal study of 244 autistic and 165 non-autistic people aged 15\u0026ndash;80, found positive associations between sleep problems, depression, anxiety, and lower quality of life in both groups. Further to these associations, PTSD symptoms may be especially relevant in autistic populations; trauma and PTSD are frequently reported in autistic groups,\u003csup\u003e27\u0026ndash;29\u003c/sup\u003e and in the general population PTSD is associated with insomnia, nightmares, and disrupted sleep.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Considering PTSD symptoms alongside depression and anxiety may therefore provide a fuller understanding of the relationship between sleep and mental health in autistic adults.\u003c/p\u003e\u003cp\u003eAlthough early research on sleep and mental health in older autistic populations was limited, recent lifespan studies have begun to examine age effects. Jovevska et al. (2020),\u003csup\u003e32\u003c/sup\u003e studying 297 autistic and non-autistic individuals aged 15\u0026ndash;80 (mean age\u0026thinsp;=\u0026thinsp;~\u0026thinsp;34), found that autistic participants, particularly those in midlife (aged 40\u0026ndash;59), reported poorer sleep quality and longer sleep onset latency than non-autistic peers. Mental health conditions predicted poorer sleep quality in autistic and non-autistic groups across all ages. Furthermore, Charlton et al. (2023),\u003csup\u003e33\u003c/sup\u003e in a larger sample of 730 autistic adults aged 18\u0026ndash;78 (mean age\u0026thinsp;=\u0026thinsp;~\u0026thinsp;40), found that 85.5% met criteria for poor sleep quality based on self-report measures. Predictors of poor sleep quality included physical health problems, female gender (sex assigned at birth), and anxiety symptoms. Age had little overall impact on sleep quality, though older age correlated with shorter sleep latency and greater sleep disturbance.\u003c/p\u003e\u003cp\u003eSimilar patterns have also been found in studies specifically focusing on middle-aged and older people with high autistic traits. Stewart et al. (2020)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e identified 187 adults aged 50\u0026ndash;81 with high autistic traits in the PROTECT cohort (total n\u0026thinsp;=\u0026thinsp;13,897) and showed that, despite similar total sleep durations, the high-trait group experienced markedly poorer sleep: they reported more difficulty falling asleep, greater daytime drowsiness, and lower overall sleep quality and satisfaction, with a higher prevalence of severe sleep problems than the low-trait group (21.4% vs. 10.3%; OR\u0026thinsp;=\u0026thinsp;2.36). These sleep disturbances were strongly linked to poorer mental health, and there was a significant interaction such that individuals with both high autistic traits and severe sleep problems exhibited the highest levels of depression and anxiety among all trait\u0026ndash;sleep combinations. These findings suggests that severe sleep problems may have a disproportionately negative impact on mental health in people with higher autistic traits.\u003c/p\u003e\u003cp\u003eTaken together, these studies that include autistic/high autistic trait people in midlife and old age highlight that sleep problems may be cause for concern as autistic people age. Additionally, the rates of sleep problems, potential relationships with mental health problems (e.g., depression, anxiety, and PTSD symptoms), and the influence of age and gender require further exploration.\u003c/p\u003e\u003cp\u003eThe current study is a conceptual replication and expansion of Stewart et al. (2020)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e trait-based study, examining sleep problems and mental health in middle-aged and older autistic adults versus age- and gender-matched non-autistic adults. We predict (i) higher self-reported sleep problems, and (ii) more current symptoms of depression, anxiety and PTSD in autistic adults compared to non-autistic adults. Additionally, (iii) those with clinically significant sleep problems will report worse mental health, especially in the autistic group. Further, (iv) older autistic adults (age 65+) will report higher rates of sleep problems and poorer mental health in comparison to midlife (age 40\u0026ndash;64) autistic adults. Finally, (v) women will report higher rates of sleep problems and poor mental health than men, with this effect being stronger in the autistic group than non-autistic group. Sleep quality index scores were compared using an ANCOVA, with depression, anxiety, and PTSD symptoms as covariates to control for self-report bias.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis pre-registered study (https://osf.io/973z8/) uses cross-sectional data from the first wave of the \u0026lsquo;AgeWellAutism\u0026rsquo; study, conducted in Spring 2019. The AgeWellAutism study is an online survey investigating ageing on the autism spectrum (outlined in Stewart et al., (2024)).\u003csup\u003e10\u003c/sup\u003e In brief, the AgeWellAutism study was steered by 12 middle-aged and older autistic adults prior to launch, with recruitment conducted via social media platforms, research databases, Autistica\u0026apos;s Research Network, and adverts in community centres and older adult residential communities. Participants were entered into a draw for one of twenty \u0026pound;20 Amazon UK gift vouchers. Inclusion criteria were being 40 years of age or above, having access to an internet-enable device, and being able to read and type in English. The study had no specific exclusion criteria. Full ethical approval was granted by the PNM Research Ethics Subcommittee at King\u0026apos;s College London (HR-18/19\u0026ndash;10941).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, 502 completed surveys were recorded, with 70 responses excluded due to suspected spam. The final sample had 432 participants aged 40-93 years.\u0026nbsp;Participants who disclosed that they either had an autism diagnosis (n=254) or self-identified as autistic (n=11) formed an autistic group (n=265); both subgroups had comparable Ritvo Autism and Asperger Diagnostic Scale (RAADS-14)\u003csup\u003e34\u003c/sup\u003e autistic trait scores (\u003cem\u003et\u003c/em\u003e(1,263)=1.54, \u003cem\u003ep=\u003c/em\u003e.124), with mean scores in both subgroups exceeding the cut-off for clinically significant autistic traits. Timing of autism diagnoses/self-identification ranged from as recently as the year of survey completion to 43 years earlier (mean years since diagnosis=10.3 years), with 17 (6.4%) diagnosed in childhood (i.e., prior to 18 years of age). The remaining participants formed the non-autistic group (n=167).\u003c/p\u003e\n\u003cp\u003eThe autistic and non-autistic groups were matched on age (autistic mean age=60.5 years; non-autistic mean age=60.6 years) and gender ratio (autistic group men=46.8%; non-autistic group men=50.3%). Both groups were comparable in education level and in country of residence, with around 98% living in the UK. However, the autistic sample self-reported lower employment rates and a higher likelihood of living with non-marital family members. Data on socio-economic status and race/ethnicity were not collected. For some analyses, age was dichotomised into midlife (aged 40-64 years; autistic n=158, non-autistic n=106) and old age (aged 65+; autistic n=107, non-autistic n=61) subgroups. This stratification avoids assuming a linear age-outcome relationship and supports interpretability for clinicians and researchers. See Table 1 for demographic characteristics of the autistic and non-autistic groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e--------------------------------------------------------------------------------\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 1 HERE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e--------------------------------------------------------------------------------\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDemographic Characteristics\u0026nbsp;\u0026ndash;\u0026nbsp;\u003c/em\u003eParticipants provided detailed self-reported demographic information, including age, gender, highest educational attainment, employment status, who they live with, and country of residence.\u0026nbsp;Participants were also asked whether they had an autism diagnosis or if they self-identified as autistic. If yes, they were then asked when they received their diagnosis or began to self-identify.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSleep \u0026ndash;\u0026nbsp;\u003c/em\u003eSleep problems were measured using the Pittsburgh Sleep Quality Index (PSQI) questionnaire,\u003csup\u003e35\u003c/sup\u003e a 24-item questionnaire assessing objective sleep behaviours and subjective difficulties over the past month. PSQI items are transformed into seven subscales (overall sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, requiring sleep medication and daytime dysfunction), scored from 0 (no problems) to 3 (greatest dysfunction). These subscales are totalled to obtain a global sleep problems score (range: 0-21). In the current sample, the internal consistency of the PSQI was very good in the autistic group (Cronbach\u0026rsquo;s \u0026alpha;=.82) and good in the non-autistic group (Cronbach\u0026rsquo;s \u0026alpha;=.78).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDepression\u003c/em\u003e \u0026ndash; Symptoms of depression were measured using the Patient Health Questionnaire (PHQ-9),\u003csup\u003e36\u003c/sup\u003e a nine-item questionnaireusing a four-point scale, assessing a range of problems over the past two weeks. Using the conventional cut-off score of \u0026ge;10, the PHQ-9 has a sensitivity of 88% and a specificity of 88% for major depressive disorder. The PHQ-9 has been validated for use in autistic adults.\u003csup\u003e37\u003c/sup\u003e In the current sample, the internal consistency of the PHQ-9 was very good in the autistic group (Cronbach\u0026rsquo;s \u0026alpha;=.88) and good in the non-autistic group (Cronbach\u0026rsquo;s \u0026alpha;=.71).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnxiety\u003c/em\u003e \u0026ndash; Symptoms of anxiety were measured using the Generalised Anxiety Disorder questionnaire (GAD-7).\u003csup\u003e38\u003c/sup\u003e The GAD-7 is a seven-item questionnaire using a four-point scale assessing the severity of anxiety symptoms over the past two weeks. Using the conventional cut-off score of \u0026ge;10, the GAD-7 has a sensitivity of 89% and a specificity of 82% for generalised anxiety disorder. The GAD-7 has been validated for use in autistic younger adult populations.\u003csup\u003e39\u003c/sup\u003e In the current sample, the internal consistency of the GAD-7 was acceptable in both autistic (Cronbach\u0026rsquo;s \u0026alpha;=.78) and non-autistic groups (Cronbach\u0026rsquo;s \u0026alpha;=.74).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePTSD\u0026nbsp;\u003c/em\u003e\u0026ndash; Symptoms of PTSD were measured using the Post Traumatic Stress Disorder Checklist (PCL-6).\u003csup\u003e40\u003c/sup\u003e The PCL-6 is a six-item questionnaire using a 5-point scale assessing PTSD symptom frequency in the past month. Using the conventional cut-off of \u0026ge;17, the PCL-6 has a sensitivity of 80% and a specificity of 76% for PTSD. To the authors knowledge, the PCL-6 has not yet been validated in autistic samples. In the current sample, the internal consistency of the PCL-6 was excellent in the autistic group (Cronbach\u0026rsquo;s \u0026alpha;=.90) and good in the non-autistic group (Cronbach\u0026rsquo;s \u0026alpha;=.79).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted using SPSS (v25.0; IBM Corp., 2017). Group differences (autistic vs. non-autistic) in demographics were assessed using \u003cem\u003et\u003c/em\u003e-tests (continuous variables) and chi-square (\u0026chi;\u003csup\u003e2\u003c/sup\u003e) tests (categorical variables). \u0026chi;\u003csup\u003e2\u0026nbsp;\u003c/sup\u003etests also examined differences in sleep problem subscales between autism groups, as well as gender (men vs. women) and age (midlife, age 40-64 vs. old age, age 65+), with adjusted residuals identifying specific differences. ANOVAs assessed group differences in total sleep quality index scores, as well as symptoms of depression, anxiety, and PTSD. ANCOVAs further adjusted sleep quality index scores for symptoms of depression and anxiety, and age. Bivariate correlations (with Fisher\u0026rsquo;s r-to-z transformations) examined associations between sleep quality index scores and mental health symptoms within each group. Gender and age group effects and interactions on sleep problem subscales and sleep quality index scores were explored using layered \u0026chi;\u003csup\u003e2\u0026nbsp;\u003c/sup\u003etests and 2x2 ANOVA. All analyses were controlled for using the False Discovery Rate (FDR) method\u003csup\u003e41\u003c/sup\u003e with a final \u0026alpha;-value of .029.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSleep Problems\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe autistic group were significantly more likely to report difficulties with their sleep compared to the non-autistic group. These difficulties included poorer sleep quality\u0026nbsp;(χ2=71.1, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), longer sleep latency (χ2=24.2, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), shorter sleep duration (χ2=15.6, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), lower sleep efficiency (χ2=21.0, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), more sleep disturbances (χ2=101.8, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), greater use of sleep medication (χ2=27.5, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), and more often experiencing daytime tiredness and dysfunction (χ2=95.1, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001). Adjusted residual values indicate that the autistic group more frequently reported moderate-to-severe difficulties in these sleep domains than the comparison group. See Table 2.\u003c/p\u003e\n\u003cp\u003eWhen considering gender differences, autistic women reported significantly greater difficulties in sleep duration (χ2=13.39, \u003cem\u003ep=\u003c/em\u003e.004), sleep disturbance (χ2=11.39, \u003cem\u003ep=\u003c/em\u003e.010) and daytime dysfunction (χ2=13.38, \u003cem\u003ep=\u003c/em\u003e.004) compared to autistic men. Adjusted residual values indicate that autistic women more frequently experienced moderate-to-severe difficulties in these sleep domains than autistic men. No other gender differences were found in the autistic group, and no gender differences were found in the non-autistic group. See Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003eWhen viewing sleep problems as a combined composite score, the autistic group reported significantly higher sleep quality index scores than the non-autistic group (F(1,429)=121.29, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), indicating more cumulative sleep problems. See Table 3.\u003c/p\u003e\n\u003cp\u003eWhile a significant main effect of gender was initially found (women\u0026gt;men), this did not survive multiple comparison correction (F(1,429)=29.14, \u003cem\u003ep=\u003c/em\u003e.040). A significant interaction between autism group and gender (F(3,427)=12.89, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001) indicated that within the autistic group, women reported significantly more sleep problems than men, whereas no gender differences emerged in the non-autistic group. A similar pattern of results was found when accounting for age and current symptoms of depression and anxiety. See Supplementary Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e--------------------------------------------------------------------------------\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLES 2 AND 3 HERE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e--------------------------------------------------------------------------------\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSymptoms of poor Mental Health\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe autistic group reported significantly higher symptoms of depression (F(1,430)=237.35, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), anxiety (F(1,430)=192.98, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), and PTSD (F(1,430)=267.31, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001) than the non-autistic group.Additionally, a significantly higher proportion of autistic versus non-autistic individuals met clinical cut-off thresholds for depression (18.9% vs. 6.6%; χ²=12.74, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), anxiety (35.5% vs. 7.8%; χ²=42.14, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001) and PTSD symptoms (26.8% vs. 1.2%; χ²=47.79, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001). See Table 3.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Few gender differences were found. A main effect of gender (women\u0026gt;men) was found in PTSD symptoms (F(1,430)=42.90, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001). The gender difference in PTSD symptoms was significantly greater in the autistic group than in the non-autistic group (F(3,424)=9.97, \u003cem\u003ep=\u003c/em\u003e.002), with the difference between women and men in PTSD scores being greater in the autistic group than non-autistic group. No other main effects of gender or interactions were found in depression and anxiety scores. See Supplementary Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAssociations between sleep problems, mental health, and age\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the autistic group, sleep problems (measured by sleep quality index score) were significantly correlated with depression symptoms (\u003cem\u003er=\u003c/em\u003e.386, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), anxiety symptoms (\u003cem\u003er=\u003c/em\u003e.459, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), PTSD symptoms (\u003cem\u003er=\u003c/em\u003e.364, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), and older age (\u003cem\u003er=\u003c/em\u003e.345, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001). Similarly, in the non-autistic group, sleep problems were significantly associated with depression symptoms (\u003cem\u003er=\u003c/em\u003e.259, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), anxiety symptoms (\u003cem\u003er=\u003c/em\u003e.186, \u003cem\u003ep\u0026lt;\u003c/em\u003e .001), PTSD symptoms (\u003cem\u003er=\u003c/em\u003e.221, \u003cem\u003ep=\u003c/em\u003e.004), and older age (\u003cem\u003er=\u003c/em\u003e.226, \u003cem\u003ep=\u003c/em\u003e.003). The strength of association differed between autistic and non-autistic groups only for sleep and anxiety (z=3.27, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001). No group differences were found in the association strengths between sleep problems and depression symptoms, PTSD symptoms, or age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSleep Problems in Midlife and Old Age\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen comparing midlife (age 40-64) and old age (age 65+) groups, differences emerged within each group. Older autistic adults reported significantly more sleep difficulties than middle-aged autistic adults in sleep quality\u0026nbsp;(χ2=9.55, \u003cem\u003ep=\u003c/em\u003e.008), sleep duration (χ2=9.02, \u003cem\u003ep=\u003c/em\u003e.029), sleep efficiency (χ2=8.31, \u003cem\u003ep=\u003c/em\u003e.016), sleep disturbances (χ2=44.97, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), requirement of sleep medicines (χ2=8.05, \u003cem\u003ep=\u003c/em\u003e.018), and daytime tiredness and dysfunction (χ2=25.53, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001). No differences were found in sleep latency. Adjusted residual values indicate that the old age autistic sub-group more often reported moderate-to-severe difficulties in these sleep domains than the midlife autistic sub-group. Older non-autistic adults also reported significantly more sleep difficulties than middle-aged non-autistic adults in sleep efficiency (χ2=7.75, \u003cem\u003ep=\u003c/em\u003e.021), sleep disturbances (χ2=16.51, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001), and daytime tiredness and dysfunction (χ2=9.79, \u003cem\u003ep=\u003c/em\u003e.020). No differences were found in sleep quality, duration, or requirement of medication use.\u0026nbsp;Adjusted residual values indicate that older non-autistic adults more frequently experienced\u0026nbsp;moderate-to-severe difficulties in these sleep domains than middle-aged non-autistic adults. See Supplementary Table 3.\u003c/p\u003e\n\u003cp\u003eWhen viewing sleep problems as a combined composite score, main effects of autism group (autistic \u0026gt; non-autistic; F(1,427)=54.23, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001) and age group (old age\u0026nbsp;\u0026gt; midlife; F(1,427)=20.51, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001) were found.\u0026nbsp;An interaction between autism\u0026nbsp;group\u0026nbsp;and age\u0026nbsp;was also\u0026nbsp;found (F(3,424)=5.33, \u003cem\u003ep=\u003c/em\u003e.021), with autism and old age having a compounded effect on sleep problems. See Supplementary Table 4.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study addresses a significant gap in the literature regarding sleep problems and associated mental health problems in a large sample of autistic adults in midlife and old age compared to age- and gender-matched non-autistic adults. Our findings indicate that middle-aged and older autistic adults reported significantly more severe and cumulative sleep problems than their non-autistic peers, even after accounting for age, anxiety, and depression. While older age and symptoms of depression and PTSD were associated with sleep problems, a particularly strong association was found between sleep problems and anxiety in the autistic group. When further exploring the effect of age on sleep, our analyses suggested that older age and being autistic may compound sleep problems. Taken together, these findings highlight the need for greater awareness of sleep problems in ageing autistic populations.\u003c/p\u003e\u003cp\u003eConsistent with prior research examining sleep problems in middle-aged and older high autistic trait populations (i.e., Stewart et al., 2020)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and diagnosed autistic lifespan samples (i.e., Jovevska et al., 2020; Charlton et al., 2023),\u003csup\u003e32,33\u003c/sup\u003e our study found autistic participants reported significantly more severe individual and cumulative sleep difficulties than non-autistic peers. This pattern interacted with gender, with autistic women reporting more problems than men, and with age, with older autistic adults reporting more difficulties than those in midlife.\u003c/p\u003e\u003cp\u003eAlthough sleep problems are well documented in younger autistic populations\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e including women and girls,\u003csup\u003e43,44\u003c/sup\u003e our findings suggest age is a key contributor to the high rates observed in midlife and older adulthood. Contributing factors may include sensory differences,\u003csup\u003e45,46\u003c/sup\u003e greater physical and mental health burdens,\u003csup\u003e7,8,47\u003c/sup\u003e and menopause-related symptoms.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e Broader ageing processes, such as reduced melatonin secretion\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e and increased medication use,\u003csup\u003e51\u003c/sup\u003e may also exacerbate problems. These biological, physiological, and social factors likely contribute to the heightened prevalence and severity of sleep difficulties in older autistic adults. Given that disrupted sleep predicts mortality risk in the general population,\u003csup\u003e23\u003c/sup\u003e addressing sleep problems in autistic populations is crucial. Our findings, together with existing literature, point to age- and gender-specific risk factors in autistic populations that warrant attention in clinical care.\u003c/p\u003e\u003cp\u003eA second key finding was the strong association between sleep problems and mental health difficulties. This aligns with prior work in both the general population,\u003csup\u003e52\u003c/sup\u003e and autistic/high autistic trait populations.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e While present in both autistic and non-autistic groups, the link with anxiety was significantly stronger for autistic participants. Studies consistently report strong associations between anxiety and sleep disruption in autistic children and adults.\u003csup\u003e\u003cspan additionalcitationids=\"CR54 CR55\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e This likely reflects the bidirectional relationship between sleep and mental health: poor sleep worsens depression, anxiety, and PTSD by impairing emotional regulation and increasing stress sensitivity,\u003csup\u003e57,58\u003c/sup\u003e while elevated mental health symptoms, particularly anxiety, disrupt sleep through arousal, worry, and difficulty relaxing.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e Despite this, sleep is rarely addressed systematically in clinical practice.\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e Explicitly considering sleep when supporting autistic adults may therefore help reduce the high rates of anxiety and related difficulties.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eWhen contextualising these findings, several strengths and limitations should be noted. A key strength was the involvement of autistic adults in shaping survey content and language use. The study also recruited a large, gender-balanced sample of middle-aged and older adults using multiple methods and included an age- and gender-matched non-autistic comparison group, enabling well-powered analyses. Importantly, it contributes to an under-researched area, as most autism research focuses on childhood or young adulthood, offering new insights into age-related sleep problems.\u003c/p\u003e\u003cp\u003eLimitations include reliance on self-report instruments (e.g., PSQI). While these can predict functional difficulties,\u003csup\u003e61\u003c/sup\u003e subjective reports may diverge from objective measures such as actigraphy, with individuals often overestimating sleep latency and underestimating sleep time.\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e Future work should integrate both methods to clarify perceived versus actual sleep problems. The study also lacked detailed medication data (e.g., use of sleep aids or psychotropics), which could influence reported rates. Recruitment bias may further limit generalisability, as older research participants are typically healthier than the wider population.\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e Finally, the cross-sectional design precludes conclusions about age-related changes or causal links between sleep and mental health.\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e Longitudinal studies combining validated self-report tools, objective measures, medication data, and representative samples are needed to clarify these associations in ageing autistic populations.\u003c/p\u003e\u003cp\u003eIn conclusion, this study replicates and expands on existing findings that autistic adults in midlife and old age experience significantly higher rates of sleep difficulties and mental health symptoms compared to non-autistic adults. Sleep problems were not only more common but also more severe and cumulative in the autistic group, and these difficulties remained evident even after accounting for anxiety, depression, and age. Furthermore, sleep disturbance was more strongly linked to anxiety in autistic individuals, pointing to a potentially unique interplay between sleep and mental health in this population. Older autistic adults may be at elevated risk, emphasising the need for lifespan-oriented and autism-informed clinical interventions. These findings highlight the importance of integrating sleep assessments into routine mental health care for autistic adults, particularly as they age. Given the bidirectional relationship between sleep disturbance and psychiatric symptoms, targeting sleep may offer a valuable pathway to improving overall well-being in this population. Future research using longitudinal designs, objective sleep measures, and more diverse, representative samples will be essential to advance evidence-based, personalised care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors FH, RAC and GRS conceived the AgeWellAutism study. GRS designed the online survey and selected materials. GRS conceived the current study. SR, AB and GRS conducted analyses. SR wrote the manuscript under the supervision of GRS. AB, FH and RAC reviewed the final draft. All authors have read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICTS OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the 12 autistic adults who offered suggestions on content and provided feedback on the language-use and accessibility of the study materials. At the time of data collection, GRS was funded by an UKRI/ESRC LISS-DTP PhD studentship (ES/P000703/1). GRS is currently funded by a British Academy Postdoctoral Research Fellowship (PFSS23\\230043). FH is part-funded by the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre and King\u0026rsquo;s College London (KCL). The funders have had no role in the data collection, analysis, interpretation, or any other aspect pertinent to the study. The authors have not been paid to write this article by any agency. This paper represents independent research conducted by the authors, and the views expressed are those of the author(s) and not necessarily those of the BA, NIHR, NHS or KCL.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmerican Psychiatric Association (2022) \u003cem\u003eDiagnostic and Statistical Manual of Mental Disorders\u003c/em\u003e. DSM-5-TR. 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Am J Epidemiol 192(4):514\u0026ndash;516. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/aje/kwac037\u003c/span\u003e\u003cspan address=\"10.1093/aje/kwac037\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"889\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"bottom\" style=\"width: 889px;\"\u003e\n \u003cp\u003e\u003cem\u003eTable 1. Demographic characteristics of the autistic and non-autistic groups.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 172px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutistic group\u003cbr\u003e\u0026nbsp;(n=265)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-Autistic group\u003cbr\u003e\u0026nbsp;(n=167)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e60.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(12.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e60.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e(13.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 185px;\"\u003e\n \u003cp\u003eF(1,430)=0.01,\u003cbr\u003e\u003cem\u003ep=\u003c/em\u003e.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cem\u003ed\u003c/em\u003e=0.01\u003cbr\u003e\u0026nbsp;[-0.19-0.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003e[95% CI]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e[59.03-62.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e[58.46-62.60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eMin-Max\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e40 - 91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e40 - 93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003emen : women : nb/t\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e124 : 137 : 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e84 : 83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026chi;2=2.86,\u003cbr\u003e\u003cem\u003ep=\u003c/em\u003e.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cem\u003ed\u003c/em\u003e=0.10\u003cbr\u003e\u0026nbsp;[-0.09-0.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e46.8% : 51.7% : 1.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e50.3% : 49.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiving situation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eSpouse or Partner\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;98 (37.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;79 (47.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=4.52, \u003cem\u003ep=\u003c/em\u003e.034^\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eChildren\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;71 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;39 (23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=.64, \u003cem\u003ep=\u003c/em\u003e.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eSibling\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;34 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=23.26, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eParent\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;22 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;7 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=2.76, \u003cem\u003ep=\u003c/em\u003e.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eOther Family Member\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;10 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=6.45, \u003cem\u003ep=\u003c/em\u003e.011*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eRoommate/Friend\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;21 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;12 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=.08, \u003cem\u003ep=\u003c/em\u003e.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eSupported Housing\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;44 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;20 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=1.74, \u003cem\u003ep=\u003c/em\u003e.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eAlone independently\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;52 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;58 (34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026chi;2=12.32, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eNo formal qualifications\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e10.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e2.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026chi;2=1.05,\u003cbr\u003e\u003cem\u003ep=\u003c/em\u003e.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eSchool to 16\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e23.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e16.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eSchool to 18\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e29.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e39.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eUndergraduate\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e22.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e30.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003ePostgraduate\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e11.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent employment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eEmployed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e(52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026chi;2=45.65,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 122px;\"\u003e\n \u003cp\u003ev=.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eRetired\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(47.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e(44.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eUnemployed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e(3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutism Diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eDiagnosed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(95.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 55px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 122px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eSelf-identified\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears since Autism Diagnosis/Identity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e10.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e(8.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 122px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cem\u003eMin-Max\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e0 - 43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 889px;\"\u003e\n \u003cp\u003eNote: nb/t = non-binary and trans. ^ Does not survive FDR correction. FDR adjusted a-value=* \u003cem\u003ep\u0026lt;\u003c/em\u003e.029, ** \u003cem\u003ep\u0026lt;\u003c/em\u003e.01, *** \u003cem\u003ep\u0026lt;\u003c/em\u003e.001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTable 2. Frequencies and group differences of sleep problem domains of the autistic and non-autistic groups.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"8\" valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eSleep Problems Score\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003cbr\u003e\u0026nbsp;Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003cbr\u003e\u0026nbsp;Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo difficulty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSome difficulty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate difficulty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere Difficulty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Quality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(52.7%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(33.7%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(13.6%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=71.1,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(91.6%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(7.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(1.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Latency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(12.1%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(53.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e(29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=24.2,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(31.1%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(44.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e(20.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Duration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(45.1%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(20.1%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e(4.9%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=15.6,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(58.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(12.0%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Efficiency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(53.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(23.9%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(22.3%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=21.0,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.221\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(37.7%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(7.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Disturbance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(1.5%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(45.8%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(47.3%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e(5.3%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=101.8,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(16.8%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(74.3%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(9.0%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication Use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(57.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(33.3%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(9.5%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=27.5,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(80.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(18.6%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(1.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDaytime Dysfunction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003eAutistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(3.4%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(44.1%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e(8.0%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026chi;2=95.1,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003ev=.471\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003enon-Autistic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(32.3%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\n \u003cp\u003e(15.0%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e(1.2%) ╪\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eNote: ╪ indicates significant adjusted residual value. FDR adjusted a-value = * \u003cem\u003ep\u0026lt;\u003c/em\u003e.029, ** \u003cem\u003ep\u0026lt;\u003c/em\u003e.01, *** \u003cem\u003ep\u0026lt;\u003c/em\u003e.001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eTable 3. Descriptive statistics and group differences of sleep problems and mental health problems of the autistic and non-autistic groups.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutistic group\u003cbr\u003e\u0026nbsp;(n=265)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-Autistic group\u003cbr\u003e\u0026nbsp;(n=167)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003cbr\u003e\u0026nbsp;Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Quality Index\u003cbr\u003e\u003c/strong\u003e(max score = 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e7.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(2.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 23px;\"\u003e\n \u003cp\u003eF(1,430)=121.29,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 15px;\"\u003e\n \u003cp\u003ed=1.12\u003cbr\u003e\u0026nbsp;[0.88 - 1.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e[95% CI]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e[7.50-8.21]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e[4.63-5.28]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eMin-Max\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1 - 16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1 - 14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003er Depression\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.386***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.259***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003ez=1.43, \u003cem\u003ep=\u003c/em\u003e.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003er Anxiety\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.459***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.186*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003ez=3.27, \u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003er PTSD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.364***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.221**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003ez=1.57, \u003cem\u003ep=\u003c/em\u003e.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003er Age\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.345***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003er=\u003c/em\u003e.226**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003ez=1.30, \u003cem\u003ep=\u003c/em\u003e.193\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;(max score = 27, cut-off \u0026ge;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e9.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(5.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 23px;\"\u003e\n \u003cp\u003eF(1,430)=237.35,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 15px;\"\u003e\n \u003cp\u003ed=1.52\u003cbr\u003e\u0026nbsp;[1.30-1.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e[95% CI]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e[9.16-10.46]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e[2.62-3.36]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 - 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0 - 13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e% above cut-off\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026chi;2=12.74,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ev=.558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety\u003cbr\u003e\u003c/strong\u003e(max score = 21, cut-off \u0026ge;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e6.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(3.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 23px;\"\u003e\n \u003cp\u003eF(1,430)=192.98,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 15px;\"\u003e\n \u003cp\u003ed=1.37\u003cbr\u003e\u0026nbsp;[1.15-1.58]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e[95% CI]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e[5.95-6.76]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e[2.23-2.73]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 - 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0 - 11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e% above cut-off\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026chi;2=42.14,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ev=.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTSD\u003cbr\u003e\u003c/strong\u003e(max score = 24, cut-off \u0026ge;17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e12.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(6.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(3.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 23px;\"\u003e\n \u003cp\u003eF(1,430)=267.31,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 15px;\"\u003e\n \u003cp\u003ed=1.61\u003cbr\u003e\u0026nbsp;[1.39-1.84]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e[95% CI]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e[11.40-12.93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e[2.80-3.92]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 - 24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0 - 23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e% above cut-off\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e(26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026chi;2=47.79,\u003cbr\u003e\u003cem\u003ep\u0026lt;\u003c/em\u003e.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ev=.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eNote: FDR adjusted a-value = * \u003cem\u003ep\u0026lt;\u003c/em\u003e.029, ** \u003cem\u003ep\u0026lt;\u003c/em\u003e.01, *** \u003cem\u003ep\u0026lt;\u003c/em\u003e.001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Supplementary Tables","content":"\u003cp\u003eSupplementary Tables 1 to 4 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"King's College London","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Autism, Sleep, Mental Health, Midlife, Old Age","lastPublishedDoi":"10.21203/rs.3.rs-7677602/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7677602/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003eSleep is a vital biological function, and impaired sleep can lead to a range of problems, including poor health and wellbeing. Poor sleep and higher rates of sleep disorders are often reported by autistic children and adults, as well as middle-aged and older people with high autistic traits. However, these experiences and problems have seldom been studied in diagnosed autistic populations in midlife and old age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eThis study used data from the first wave of the AgeWellAutism cohort, from a sample of 265 autistic and 167 age- and gender-matched non-autistic adults aged 40 to 93 years (mean = ~60 years; ~50% female). Participants completed widely used and standardised measures of sleep quality and mental health symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe autistic group reported significantly more sleep difficulties than the non-autistic group, including poorer sleep quality, longer time to fall asleep, shorter duration, lower efficiency, more disturbances, greater reliance on sleep medication, and increased daytime tiredness and dysfunction. These differences remained significant after controlling for age and poor mental health (measured by symptoms of anxiety, depression and PTSD). Poor sleep was also associated with older age and mental health issues in both groups, with a stronger association between sleep problems and anxiety symptoms in the autistic versus non-autistic group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eConsistent with prior autism trait-based research in the general population, middle-aged and older autistic adults report more extensive sleep problems and worse sleep quality than non-autistic adults. Sleep problems were associated with older age and poorer mental health. Though the study is cross-sectional, the findings highlight the need to explore causal links through intervention. Addressing anxiety, and mental health problems more broadly, may improve sleep quality in ageing autistic populations.\u003c/p\u003e","manuscriptTitle":"Sleep problems and mental health in middle-aged and older autistic and non-autistic adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 18:36:16","doi":"10.21203/rs.3.rs-7677602/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"718d4649-3fc9-4d83-bddd-adafda7abf4f","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55127557,"name":"Psychology"},{"id":55127558,"name":"Geriatrics \u0026 Gerontology"}],"tags":[],"updatedAt":"2025-09-23T18:36:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 18:36:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7677602","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7677602","identity":"rs-7677602","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}