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      An investigation of the diet, exercise, sleep, BMI, and health outcomes of autistic adults

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          Abstract

          Background

          Studies of autistic children suggest that restricted eating, reduced physical activity, and sleep disorders are common; however, no studies attempt to broadly describe the diet, exercise, and sleep patterns of autistic adults or consider relationships between lifestyle behaviors and the widely reported increased risks of obesity and chronic conditions. To address this, the authors developed the largest study of lifestyle patterns of autistic adults and assessed their relationships to body mass index, health outcomes, and family history.

          Methods

          We administered an anonymized, online survey to n = 2386 adults ( n = 1183 autistic) aged 16–90 years of age. We employed Fisher’s exact tests and binomial logistic regression to describe diet, exercise, and sleep patterns; mediation of seizure disorders on sleep; body mass index (BMI); relationships of lifestyle factors to BMI, cardiovascular conditions, and diabetic conditions; and sex differences among autistic adults.

          Results

          Autistic adults, and particularly autistic females, exhibit unhealthy diet, exercise, and sleep patterns; they are also more likely to be underweight or obese. Limited sleep duration and high rates of sleep disturbances cannot be accounted for by epilepsy or seizure disorders. Lifestyle factors are positively related to higher risk of cardiovascular conditions among autistic males, even more than family history.

          Limitations

          Our sample may not be representative of all autistic and non-autistic people, as it primarily comprised individuals who are white, female, have a high school education or higher, and reside in the UK. Our sampling methods may also exclude some individuals on the autism spectrum, and particularly those with moderate to severe intellectual disability. This is a cross-sectional sample that can test for relationships between factors (e.g., lifestyle factors and health outcomes) but cannot assess the direction of these relationships.

          Conclusions

          Autistic adults are less likely to meet minimal health recommendations for diet, exercise, and sleep—and these unhealthy behaviors may relate to excess risk of cardiovascular conditions. Although the present study can only provide preliminary, correlational evidence, our findings suggest that diet, exercise, and sleep should be considered and further investigated as key targets for reducing the now widely reported and dramatically increased risks of health comorbidity and premature death among autistic individuals compared to others. Physicians should work cooperatively with patients to provide health education and develop individualized strategies for how to better manage challenges with diet, exercise, and sleep.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13229-021-00441-x.

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          Most cited references78

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          Diagnostic and Statistical Manual of Mental Disorders

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            Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016

            Problem/Condition Autism spectrum disorder (ASD). Period Covered 2016. Description of System The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (40% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively). Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). Interpretation The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. Public Health Action These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.
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              The incidence of co-morbidities related to obesity and overweight: A systematic review and meta-analysis

              Background Overweight and obese persons are at risk of a number of medical conditions which can lead to further morbidity and mortality. The primary objective of this study is to provide an estimate of the incidence of each co-morbidity related to obesity and overweight using a meta-analysis. Methods A literature search for the twenty co-morbidities identified in a preliminary search was conducted in Medline and Embase (Jan 2007). Studies meeting the inclusion criteria (prospective cohort studies of sufficient size reporting risk estimate based on the incidence of disease) were extracted. Study-specific unadjusted relative risks (RRs) on the log scale comparing overweight with normal and obese with normal were weighted by the inverse of their corresponding variances to obtain a pooled RR with 95% confidence intervals (CI). Results A total of 89 relevant studies were identified. The review found evidence for 18 co-morbidities which met the inclusion criteria. The meta-analysis determined statistically significant associations for overweight with the incidence of type II diabetes, all cancers except esophageal (female), pancreatic and prostate cancer, all cardiovascular diseases (except congestive heart failure), asthma, gallbladder disease, osteoarthritis and chronic back pain. We noted the strongest association between overweight defined by body mass index (BMI) and the incidence of type II diabetes in females (RR = 3.92 (95% CI: 3.10–4.97)). Statistically significant associations with obesity were found with the incidence of type II diabetes, all cancers except esophageal and prostate cancer, all cardiovascular diseases, asthma, gallbladder disease, osteoarthritis and chronic back pain. Obesity defined by BMI was also most strongly associated with the incidence of type II diabetes in females (12.41 (9.03–17.06)). Conclusion Both overweight and obesity are associated with the incidence of multiple co-morbidities including type II diabetes, cancer and cardiovascular diseases. Maintenance of a healthy weight could be important in the prevention of the large disease burden in the future. Further studies are needed to explore the biological mechanisms that link overweight and obesity with these co-morbidities.
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                Author and article information

                Contributors
                emw60@medschl.cam.ac.uk
                sb205@cam.ac.uk
                Journal
                Mol Autism
                Mol Autism
                Molecular Autism
                BioMed Central (London )
                2040-2392
                8 May 2021
                8 May 2021
                2021
                : 12
                : 31
                Affiliations
                [1 ]GRID grid.5335.0, ISNI 0000000121885934, Autism Research Centre, Department of Psychiatry, , University of Cambridge, ; Douglas House, 18B Trumpington Road, Cambridge, England CB2 8AH
                [2 ]GRID grid.5335.0, ISNI 0000000121885934, MRC Epidemiology Unit and Department of Pediatrics, Institute of Metabolic Science, , University of Cambridge, ; Cambridge Biomedical Campus,, Cambridge, England CB2 0QQ
                Author information
                http://orcid.org/0000-0001-5434-9193
                http://orcid.org/0000-0003-2272-2090
                http://orcid.org/0000-0003-4689-7530
                http://orcid.org/0000-0001-9217-2544
                Article
                441
                10.1186/s13229-021-00441-x
                8106173
                33964967
                01e9933d-d616-4839-8434-486763557e80
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 15 January 2021
                : 27 April 2021
                Funding
                Funded by: Autism Research Trust
                Award ID: RG72423
                Award Recipient :
                Funded by: Rosetrees Trust (GB)
                Award ID: G102199
                Award Recipient :
                Funded by: Cambridge and Peterborough NHS Foundation Trust
                Award ID: G102307
                Award Recipient :
                Funded by: Corbin Charitable Trust
                Funded by: Medical Research Council
                Award ID: MC_UU_12015/2
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 214322\Z\18\Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Funded by: Innovative Medicines Initiative 2 Joint Undertaking
                Award ID: Grant Agreement No 777394
                Award Recipient :
                Funded by: Innovative Medicines Initiative 2 Joint Undertaking
                Award ID: Grant Agreement No 777394
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Neurosciences
                healthcare,physical health,comorbidities,adult outcomes,nutrition,exercise,sleep
                Neurosciences
                healthcare, physical health, comorbidities, adult outcomes, nutrition, exercise, sleep

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