Association Between Autism Spectrum Disorders and Cardiometabolic Diseases

Currently, 1 in 44 children receive an autism diagnosis by the age of 8 years in the United States 1 ; despite improvements in recognition of autism, autistic people still have poor long-term outcomes regarding their health and health care. Overall, autistic people are dying much younger than expected, 2,3 with several studies now suggesting that autistic people are, on average, dying 12 to 30 years younger than others. 3 Unfortunately, risk of dying by suicide is also elevated among autistic people, 2-4 with as many as 1 in 3 reporting a previous suicide attempt. 4 However, the growing literature on premature mortality also points to physical health problems that are currently underresearched and underexplored. 2,3 In particular, there is a paucity of research on the chronic physical health problems among autistic people as they age, with only a handful of studies assessing chronic health burden among those older than 35 years. A new study published in this issue of JAMA Pediatrics by Dhanasekara and colleagues 5 provides important context for clinicians across specialties, as all clinicians will have autistic patients. 1 This innovative article "Association Between Autism Spectrum Disorders and Cardiometabolic Diseases: A Systematic Review and Meta-analysis," serves to fill an important gap in knowledge by meta-analyzing data from 34 previous studies, bringing together autistic individuals across the life span and across the world. 5 Unfortunately, its findings indicate that autistic people are far more likely to experience cardiovascular and metabolic conditions than nonautistic peers, including approximately 1.5 times increased risk of heart disease, 1.6 times increased risk of diabetes, and 1.7 times increased risk of dyslipidemia. 5 In other words, on average, for every 10 nonautistic people that will develop heart disease, diabetes, or dyslipidemia, 15 or more autistic people will develop each of these conditions.Using a robust analysis method, the study provided further detail that autistic people are 1.6 and 2.5 times more likely to have type 1 and type 2 diabetes, respectively. 5 This finding may seem surprising, given the different pathophysiological mechanisms for each. However, previous studies show that autistic individuals have higher rates of autoimmune diseases (such as type 1 diabetes), though the mechanisms by which this is occurring are not well understood. 6 Separately, the links to type 2 diabetes presented in the study intimate that a combination of genetic and lifestyle-related factors may also contribute to risk of cardiometabolic diseases among autistic people. 7 The study also highlighted particular risks for autistic children, as they were at approximately 2.8 times increased risk of diabetes and 2.5 times increased risk of hypertension com-

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See 3 more Smart Citations

Autism, Physical Health Conditions, and a Need for Reform

Weir

2023

Considerations Regarding Autism Spectrum Disorders and Cardiometabolic Diseases

Jin

Shi

2023

To the Editor In their systematic review and meta-analysis, Dhanasekara et al 1 evaluated the association between autism spectrum disorders and cardiometabolic diseases. The findings suggest that autism was associated with an increased risk of diabetes, dyslipidemia, and atherosclerotic heart disease. Children with autism may have a higher risk of developing diabetes and hypertension. We commend the authors for their effort to synthesize the conflicting findings in the literature to guide the prevention of cardiometabolic diseases. However, we have 2 comments on this article.First, a major concern is the criteria for data extraction from the studies that report cardiometabolic results (ie, diabetes and hypertension) only in adults or children vs those reporting results in both adults and children is unclear. For example, we observed that 2 studies by Chen et al 2 and Flygare Wallén et al 3 reported effect estimates of relative risk (or these were calculated by Dhanasekara et al 1 ) for adults and children separately, but these 2 studies are categorized into different subgroups (eFigure 2 in Supplement 1 1 ). Considering this issue, we suggest that studies that included adults and children can be included in both subgroups if relevant outcomes for each age group are reported separately. 4 To be more informative when evaluating the difference by age groups, we propose conducting a sensitivity analysis from only those cohort studies that report results for both adults and children. It may help decrease between-study variations for adults and children.Second, it is challenging to analyze this topic due to confounding factors. Though the authors considered several sociodemographic variables in meta-regression analyses, residual confounding, a typical limitation of observational studies, might still exist. We suggest this issue might be worth mentioning in the Discussion. In addition, cardiometabolic outcomes usually take a long time (even decades) to develop. 2,5 To strengthen the findings, it would be instructive to report the length of follow-up in each study identified; a sensitivity analysis by different follow-up periods (such as 5 or 10 years) could then be performed to examine the robustness of the associations.

Considerations Regarding Autism Spectrum Disorders and Cardiometabolic Diseases—Reply

Dhanasekara

Kahathuduwa

2023

Self Cite

COMMENT & RESPONSEIn Reply On behalf of our coauthors, we appreciate Jin and Shi taking time to review our article 1 and sharing their thoughts in a Letter to the Editor. We address the 2 concerns raised by the authors in this response.First, the authors raised a concern regarding criteria for data extraction and categorizing outcomes of studies that included children vs adults vs pooled children and adults citing our classification of the studies by Chen et al 2 and Flygare Wallén et al 3 into different subgroups as an example. We entirely agree with the authors on the fact that, when possible, studies that report data on subgroups should be separately analyzed in subgroup sensitivity analyses (eg, children vs adults). All eligible studies that reported results of sensitivity analyses were carefully screened before they were assigned to subgroups based on age (eFigures 2 and 4 1 ) or diagnosis (Figure 2 1 ). Flygare Wallén et al 3 reported the raw data separating the data by age group, allowing us to compute the relative risks for the subgroups of children vs adults. However, Chen et al 2 reported raw data only for the whole sample, which included adolescents and young adults. Even though Chen et al reported hazard ratios regarding development of diabetes for adolescents and young adults separately, the data could not be used as surrogates for relative risks given that they were hazard ratios and were adjusted outcomes derived after controlling for demographic factors. Attempting to calculate relative risks using hazard ratios adjusted for multiple variables is likely to introduce more bias and further deviate the pooled outcomes.Second, the authors suggest adjusting the outcomes for the duration of follow-up. It is redundant to consider the duration of follow-up of the studies when the exposure (ie, autism) is likely to have started approximately at the time of birth with a fixed or small margin of error in time compared to the age of the individual. As such, we cannot think of a method better than grouping by age and including age as a moderator in meta-regression analyses to account for the duration of exposure.We agree with the concern that between-study heterogeneity and unmeasured confounding could lead to bias in any meta-analysis. We have tried our best to adhere to the best practices outlined in the Cochrane handbook, 4 chapters 10.10 and 13.5.