March 10, 2016
Do Very High BMI and Gestational Diabetes Increase the Likelihood of Having a Child with Autism?
By: Henci Goer, BA | 0 Comments
The research and interest in discovering what might be the underlying causes of autism continues to climb as the number of diagnoses of children and adults with autism increases every year. Today on the blog, author Henci Goer puts several recent studies under the microscope to see if the researchers' conclusions hold water. Are pregnant people who have a high BMI and are diagnosed with gestational diabetes more likely to have children with autism? - Sharon Muza, Science & Sensibility Community Manager.
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Within the last couple of years, a flurry of studies has appeared, all concluding that gestational diabetes mellitus (GDM), very high BMI (> 29), or the two in combination increase the likelihood of autism in the child. Two of them popped up on the internet in February under the titles: "Maternal Obesity, Diabetes Associated with Higher Risk for Autism" and "Maternal Obesity and Gestational Diabetes May Raise Risk of Autism," no doubt alarming any pregnant person with a GDM diagnosis who ran across them. Let's see what they have to say and how strong a case they make.
Maternal Diabetes and the Risk of Autism Spectrum Disorders in the Offspring: A Systematic Review and Meta-Analysis (Xu 2014)
Taking them in reverse order of publication, we have a systematic review and pooled analyses (meta-analysis) of three population-based studies and nine case-control studies published in 2014. Studies included women with pre-pregnancy diabetes, both Type 1 (insulin deficiency) and Type 2 (insulin resistance), as well as diabetes first diagnosed in pregnancy (GDM), which, I should add, doesn't preclude having prior glucose metabolism problems but just means it was first picked up in pregnancy.
Pooled analysis of the population studies found that maternal diabetes increased the likelihood of having a child with autism by nearly 50% (odds ratio: 1.48). Pooled analysis of the case-control studies found that diabetes increased the odds by nearly 75% (odds ratio: 1.73). Population studies found that GDM increased odds by a little over 40% (odds ratio: 1.43) and pre-pregnancy diabetes by 75% (odds ratio: 1.74). Oddly, case-control studies found that GDM more than doubled the likelihood of autism (odds ratio: 2.23). It makes no sense that milder cases would have a stronger association, nor have other studies found this, which makes this finding questionable. None of the case-control studies reported outcomes separately for pre-pregnancy diabetes.
Four of the 12 studies made no adjustments or matching for confounding factors, that is, factors that could obscure the true relationship between diabetes and autism. Of the studies making adjustments or matching cases with controls, important factors were left out. For example, only one study, a study of 219,000 children (Burstyn 2010), adjusted for gestational age despite prematurity having a strong association with autism (Connolly 2016; Li 2016). That study, by the way, found that the statistically significant association with GDM disappeared after adjusting for gestational age and other factors and was weakened in women with pre-pregnancy diabetes (odds ratios: 1.87 vs. 1.65).
Conclusion: It is unclear whether GDM is associated with increased likelihood of autism because studies fail to account for or match for confounding factors. More severe disturbances in glucose metabolism may have an association. Association, it should be noted, doesn't equate with causation.
Association of Maternal Diabetes with Autism in Offspring (Xiang 2015)
A study published in 2015 of 322,000 children compared outcomes in women with no diabetes with women with pre-pregnancy Type 2 diabetes; GDM diagnosed before 27 weeks' gestation, which indicates more severe metabolic disorder; and GDM diagnosed after 27 weeks. After accounting for multiple confounding factors, GDM diagnosed at or before 26 weeks was associated with increased likelihood of autism (hazard ratio: 1.42), but GDM diagnosed after 26 weeks was not.
Interestingly, taking anti-diabetic medication (oral medication or insulin) increased likelihood of an autism diagnosis by more than 40% (hazard ratio: 1.44), which the authors attribute to women with more severe disorder being more likely to be prescribed medications. That may be true, but I wouldn't let medications that manipulate maternal and possibly fetal glucose metabolism off the hook so easily. Fantus (2015) questions whether metformin is safe for use in pregnancy, and a study found glyburide to be associated with serious adverse newborn outcomes compared with insulin (Carmelo Castillo 2015). According to ACOG's (2013) Practice Bulletin on GDM management, we have no long-term studies of the effects of oral anti-diabetic medications during pregnancy on children. Insulin too must be carefully managed in order not to provoke maternal episodes of low blood sugar, which could be harmful to the developing fetus.
Conclusion: Elevated glucose levels beginning in late pregnancy, the milder, more common variant lumped under the "GDM" diagnosis, has no association with autism. The same may not be true of more severe metabolic disturbances.
The Association of Maternal Obesity and Diabetes with Autism and Other Developmental Disabilities (Li 2016)
Next up is one of the two studies reported on the internet this past month. Investigators examined the relationships among very high BMI (> 29), diabetes (pre-pregnancy and GDM), autism, and other developmental disorders in an urban, socio-economically disadvantaged population of 2700 mother-child pairs. They found that after adjusting for year of birth, sex of child, maternal age, number of children, smoking, and preterm birth, pre-pregnancy diabetes was associated with autism (hazard ratio: 2.25) and other developmental disorders as was very high BMI (hazard ratio: 1.92). Neither GDM nor high BMI alone were. GDM combined with very high BMI, however, was (hazard ratio: 3.04), and very high BMI combined with pre-pregnancy diabetes increased the strength of the relationship (hazard ratio: 3.91).
This population wasn't typical. The prevalence of autism was 3.7%, nearly 4 times the 1.1% rates reported in both Xiang 2015 and Xu 2014, which tells you something was different even if you didn't know the population was low-income and urban. And indeed, women and children suffered from the health disadvantages one would predict. For example, 1 child in 3 had a developmental disorder, one child in three was born at less than 37 weeks' gestation, and one in six was born at less than 34 weeks. One in eight women had preeclampsia, one in five used drugs in pregnancy, and one in ten had alcohol use in pregnancy in their records.
Conclusion: Children in disadvantaged families are at increased risk for poor health outcomes, including autism and other developmental disorders, but which factors-or more likely-combination of factors and how they interrelate isn't clear. Other potential factors such as chronic extreme stress or exposure to toxins in the workplace or home environment (lead, for example) not captured in the participants' medical records may also contribute. Neither GDM nor very high BMI in isolation are associated with increased risk of autism.
Maternal Metabolic Risk Factors for Autism Spectrum Disorder-An Analysis of Electronic Medical Records and Linked Birth Data (Connolly 2016)
The other 2016 study covered on the internet last month compared 503 autism cases drawn from a hospital database with 38,800 birth records from children living in the same zip codes to determine factors associated with autism. After adjusting for maternal age, race, and year of birth, very high BMI (>29), but not high BMI (BMI 25-29), was associated with an increase in likelihood of autism (odds ratio: 1.30) compared with children of mothers with neither very high BMI nor GDM. Women with both very high BMI and GDM had substantially increased likelihood of having a child with autism (OR: 2.53). GDM in the absence of very high BMI did not increase likelihood of autism. Interestingly, newborn complications (not defined) were more common among cases (20% vs. 14%) as was preterm birth (19% vs. 13%), but investigators didn't take these factors into account when adjusting for differences between groups.
Conclusion: GDM in women with BMI of 29 or less isn't associated with increased likelihood of autism. The association with GDM in women with very high BMI might have been weaker or disappeared entirely had investigators adjusted for other potential confounding factors that differed between groups.
What Do These Studies Tell Us?
First and foremost, the decision back in 1984 to call any degree of excess blood sugar in pregnancy, whether of early or late onset, "diabetes" has muddied the waters ever since in attempts to determine its potential adverse consequences. As we saw in these three studies and the systematic review of 12 more, research conclusions that apply to only a segment of the population with the "GDM" label are being applied to everyone. The confusion was deliberate (Summary and Recommendations 1985). Delegates debated whether to call excess, but subdiabetic, blood sugar levels after drinking a concentrated glucose solution in late pregnancy "glucose intolerance of pregnancy,"" but they went with "diabetes" so that insurance companies would pay for high-risk management and women would take the diagnosis seriously. This was equivalent to saying that everyone with a cough and fever has tuberculosis. As you can see from these studies, severity and timing of onset matter. We should not be subjecting women to high-risk management unless we have confidence that its benefits outweigh its risks.
Second, any woman with a GDM diagnosis will be monitored and treated to normalize blood sugar values. If you're going to claim hyperglycemia is associated with adverse outcomes, you had better report outcomes according to whether treatment worked because if you don't, you have no basis for your claim. All of these studies reported outcomes based on GDM diagnosis alone.
Third, the list of maternal factors associated with autism is as long as your arm (Ornoy 2015; Roberts 2016). It includes:
- infections such as cytomegalovirus (which rarely causes symptoms)
- prolonged fever and inflammation
- folic acid deficiency
- serotonin reuptake inhibitors (a family of antidepressant drugs)
- exposure to heavy metals
- heavy smoking
- possibly cocaine
- intimate partner violence
Researchers attempting to evaluate associations with GDM should make sure that their case populations don't have increased prevalence of confounding risk factors compared with their non-GDM comparison group. Failure to do this means that their results cannot be generalized to populations with differing characteristics.
Based on these studies, healthy women with mildly elevated blood sugar after eating that first appears in late pregnancy aren't at excess risk of having an autistic child even if they are overweight. It is less clear whether women with more severe glucose metabolism disturbances or who are very high BMI or both are at excess risk. If they are, the excess is likely to be small. For example, Xiang (2015) reported a 1.0% autism rate among the children of nondiabetic women. GDM diagnosed before 27 weeks of gestation increased risk by 0.44%, which would be an absolute increase from 10 in every 1000 women with normal pregnancy sugar metabolism to 14 per 1000 in women with more severe GDM, or 4 more children per 1000.
First, you can't take medical reporting (or study summaries, for that matter) at face value. Second, GDM covers a range of conditions with differing potential consequences. Maternal hyperglycemia is also associated with other health issues that can impact the child's health. Women may wish to consider where they fall on this spectrum when determining a care plan with their doctor or midwife.
ACOG. (2013). Practice Bulletin No. 137: Gestational diabetes mellitus. Obstetrics and Gynecology, 122(2 Pt 1), 406-416.
Burstyn, I., Sithole, F., & Zwaigenbaum, L. (2010). Autism spectrum disorders, maternal characteristics and obstetric complications among singletons born in Alberta, Canada. Chronic Diseases in Canada, 30(4), 125-134.
Camelo Castillo, W., Boggess, K., Sturmer, T., Brookhart, M. A., Benjamin, D. K., Jr., & Jonsson Funk, M. (2015). Association of Adverse Pregnancy Outcomes With Glyburide vs Insulin in Women With Gestational Diabetes. JAMA Pediatr, 169(5), 452-458.
Connolly, N., Anixt, J., Manning, P., Ping, I. L. D., Marsolo, K. A., & Bowers, K. (2016). Maternal metabolic risk factors for autism spectrum disorder-An analysis of electronic medical records and linked birth data. Autism Res. 10.1002/aur.1586
Fantus, I. G. (2015). Is metformin ready for prime time in pregnancy? Probably not yet.Diabetes/Metabolism Research and Reviews, 31(1), 36-38.
Li, M., Fallin, M. D., Riley, A., Landa, R., Walker, S. O., Silverstein, M., . . . Wang, X. (2016). The Association of Maternal Obesity and Diabetes With Autism and Other Developmental Disabilities.Pediatrics, 137(2), 1-10.
Ornoy, A., Weinstein-Fudim, L., & Ergaz, Z. (2015). Prenatal factors associated with autism spectrum disorder (ASD). Reproductive Toxicology, 56, 155-169.
Roberts, A. L., Lyall, K., Rich-Edwards, J. W., Ascherio, A., & Weisskopf, M. G. (2016). Maternal exposure to intimate partner abuse before birth is associated with autism spectrum disorder in offspring. Autism, 20(1), 26-36.
Summary and recommendations of the Second International Workshop-Conference on Gestational Diabetes. (1985 ). Diabetes, 34(Suppl 2), 123-126.
Xiang, A. H., Wang, X., Martinez, M. P., Walthall, J. C., Curry, E. S., Page, K., . . . Getahun, D. (2015). Association of maternal diabetes with autism in offspring. JAMA, 313(14), 1425-1434.
Xu, G., Jing, J., Bowers, K., Liu, B., & Bao, W. (2014). Maternal diabetes and the risk of autism spectrum disorders in the offspring: a systematic review and meta-analysis. Journal of Autism and Developmental Disorders, 44(4), 766-775.
About Henci Goer
Henci Goer, award-winning medical writer and internationally known speaker, is the author of The Thinking Woman's Guide to a Better Birth and Optimal Care in Childbirth: The Case for a Physiologic Approach, She is the winner of the American College of Nurse-Midwives "Best Book of the Year" award. An independent scholar, she is an acknowledged expert on evidence-based maternity care. Henci is preparing to launch her latest venture - Childbirth U - an online resource to help families make informed choices in childbirth.
TagsResearch Medical Interventions Pregnancy Complications New Research Henci Goer Babies Evidence Based Medicine Gestational Diabetes Childbrith Education Autism Obesity High BMI