Maternal Gestational Diabetes Mellitus, Type 1 Diabetes, and Type 2 Diabetes During Pregnancy and Risk of ADHD in Offspring

Xiang, Anny H.; Wang, Xinhui; Martinez, Mayra P.; Getahun, Darios; Page, Kathleen A.; Buchanan, Thomas A.; Feldman, K

doi:10.2337/dc18-0733

Cited by 99 publications

(114 citation statements)

References 37 publications

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“…A total of 128 540 children had complete and valid data on the four maternal exposure variables and covariates including maternal age, race/ethnicity, household income, birthweight, and gender. The validity of data has been established in previous publications …”

Section: Methodsmentioning

confidence: 95%

“…The primary exposure variables were (a) maternal prepregnancy obesity or overweight, (b) excessive gestational weight gain (EGWG), (c) maternal diabetes during pregnancy, and (d) breastfeeding > 6 months. Previous studies have described the constructions of these exposure variables . Briefly, maternal prepregnancy BMI was calculated from the weight and height data closest to the last menstrual period (LMP) recorded in EMR and was classified as normal (BMI < 25 kg/m 2 ), overweight (25 ≤ BMI < 30 kg/m 2 ) or obese (BMI ≥ 30 kg/m 2 ).…”

Section: Methodsmentioning

confidence: 99%

“…Maternal diabetes was classified as pre‐existing T1D or T2D or GDM with or without receiving antidiabetic medication treatments or no diabetes during pregnancy. Pre‐existing T2D status was determined based on combinations of International Classification of Diseases codes, glucose and glycated haemoglobin A1c levels, as well as use of antidiabetic medications prior to pregnancy . T1D was identified according to Klompas algorithm using information extracted from EMR .…”

Section: Methodsmentioning

confidence: 99%

“…Pre‐existing T2D status was determined based on combinations of International Classification of Diseases codes, glucose and glycated haemoglobin A1c levels, as well as use of antidiabetic medications prior to pregnancy . T1D was identified according to Klompas algorithm using information extracted from EMR . GDM was determined based on plasma glucose measurements of 1‐hour 50‐g glucose challenge test (≥200 mg/dL) or 3‐hour 100‐g or 2‐hour 75‐g oral glucose tolerance tests with at least two values meeting the following criteria: fasting ≥ 95 mg/dL, 1 hour ≥ 180 mg/dL, 2 hours ≥ 155 mg/dL, or 3 hours ≥ 140 mg/dL.…”

Section: Methodsmentioning

confidence: 99%

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BMI growth trajectory from ages 2 to 6 years and its association with maternal obesity, diabetes during pregnancy, gestational weight gain, and breastfeeding

et al. 2019

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Objective: To identify latent BMI growth trajectories from ages 2 to 6 years and examine their independent associations with maternal prepregnancy obesity or overweight, pre-existing type 1 (T1D) or type 2 diabetes (T2D) or gestational diabetes (GDM) with or without requiring antidiabetic medications during pregnancy, excessive gestational weight gain (EGWG), and breastfeeding ≤ 6 months. Research design and method: Data included 71 892 children born at KaiserPermanente Southern California hospitals in 2007 to 2011 with complete information on maternal risk factors. Group-based trajectory modelling was used to identify latent BMI trajectory groups. Logistic regression was used to assess independent associations adjusted for covariates.Results: Three distinct BMI trajectory groups were identified: Group 1 (59% of the cohort) had stable low BMI, Group 2 (35% of the cohort) had stable median BMI, and Group 3 (6% of the cohort) had high and increasing BMI over time. Relative to Groups 1 and 2 combined, the adjusted odds ratio (OR) (95% CI) of being in Group 3 associated with maternal exposures were 5.6 (5.1-6.2) for prepregnancy obesity, 2.4 (2.2-2.7) for prepregnancy overweight, 2.1 (1.2-3.7) for T1D, 1.6 (1.4-1.8) for T2D, 1.4 (1.3-1.6) for GDM requiring medication treatment, 1.1 (1.0-1.3) for GDM not requiring medication, 1.3 (1.2-1.4) for EGWG, and 1.2 (1.2-1.3) for breastfeeding ≤ 6 months. Conclusion:Child's high and increasing BMI trajectory was strongly associated with maternal prepregnancy obesity and overweight, modestly associated with maternal T1D, T2D, and GDM requiring medication treatment and EGWG, and slightly associated with breastfeeding ≤ 6 months. GDM not requiring medication treatment during pregnancy had little association.

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Section: Methodsmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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BMI growth trajectory from ages 2 to 6 years and its association with maternal obesity, diabetes during pregnancy, gestational weight gain, and breastfeeding

et al. 2019

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“…An exaggerated central nervous system inflammatory response to a pre-/perinatal insult in the developing fetus has been hypothesized as a potential cause of ADHD [3]. Studies showing an association between maternal diseases with an immune component and offspring ADHD provide support to the role of maternal immune activation during pregnancy in development of ADHD [4][5][6]. In a Norwegian nationwide case-control study, maternal diagnoses of multiple sclerosis, rheumatoid arthritis, asthma, hypothyroidism, and type 1 diabetes were associated with an increased risk of ADHD in offspring [4].…”

Section: Introductionmentioning

confidence: 99%

Maternal serum C-reactive protein (CRP) and offspring attention deficit hyperactivity disorder (ADHD)

Chudal

Brown

Gyllenberg

et al. 2019

Eur Child Adolesc Psychiatry

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Exposure to infection and inflammation during the fetal period are associated with offspring neuropsychiatric disorders. Few previous studies have examined this association with ADHD with mixed findings. This study aims to examine the association between early gestational maternal C-reactive protein (CRP), prospectively assayed in stored maternal sera and the risk of ADHD in offspring. This study is based on the Finnish Prenatal studies of ADHD (FIPS-ADHD) with a nested case-control design. It includes all singleton-born children in Finland between January 1, 1998 and December 31, 1999 and diagnosed with ADHD. A total of 1079 cases and equal number of controls were matched on date of birth, sex and place of birth. Maternal CRP levels were assessed using a latex immunoassay from archived maternal serum specimens, collected during the first and early second trimester of pregnancy. Elevated maternal CRP when analyzed as a continuous variable was not associated with offspring ADHD (OR 1.05, 95% CI 0.96-1.15). No significant associations were seen in the highest quintile of CRP (OR 1.18, 95% CI 0.88-1.58). The results were similar in both sexes as well as among ADHD cases with or without comorbid ASD or conduct disorder. In this first study examining CRP, a biomarker for inflammation, during early pregnancy in relation to offspring ADHD, we report no significant associations. The lack of any association, when considered with positive findings seen in ASD and schizophrenia, and negative findings in bipolar disorder suggests different pathways linking maternal immune activation and development of various neuropsychiatric disorders.

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Management of Preexisting Diabetes in Pregnancy

Alexopoulos

Blair

Peters

2019

JAMA

106

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Importance: The presence of preexisting type 1 or type 2 diabetes in pregnancy increases the risk of adverse maternal and neonatal outcomes, such as preeclampsia, caesarian section, pre-term delivery, macrosomia and congenital defects. Approximately 0.9% of the 4,000,000 births in the United States are complicated by preexisting diabetes. Observations: Women with diabetes have increased risk for adverse maternal and neonatal outcomes and similar risks are present for either type 1 or type 2 diabetes. Both forms of diabetes require similar intensity of diabetes care. Preconception planning is very important to avoid unintended pregnancies, and to minimize risk of congenital defects. Hemoglobin A1c goal at conception is <6.5% and during pregnancy is <6.0%. It is also critical to screen for and optimize comorbid illnesses such as retinopathy and nephropathy. Medications known to be unsafe in pregnancy, such as angiotensin-converting enzyme inhibitors and statins, should be discontinued. Obese women should be screened for obstructive sleep apnea, which is often undiagnosed and can result in poor outcomes. Blood pressure goals must be considered carefully, as lower treatment thresholds may be required for women with nephropathy. During pregnancy, continuous glucose monitor use can improve glycemic control and neonatal outcomes for women with type 1 diabetes. Insulin is first-line therapy for all women with preexisting diabetes; injections and insulin pump therapy are both effective approaches. Rates of severe hypoglycemia are increased during pregnancy; therefore glucagon should be available and close contacts trained in its use. Low-dose aspirin is recommended soon after 12 weeks of gestation to minimize the risk of preeclampsia. The importance of discussing long-acting reversible contraception before and after pregnancy cannot be overstated, to allow for appropriate preconception planning. Conclusions and Relevance: Preexisting diabetes in pregnancy is complex and is associated with significant maternal and neonatal risk, but optimization of glycemic control, medication regimens and careful attention to comorbid conditions can help mitigate these risks, and ensure quality diabetes care before, during and after pregnancy.

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Maternal Gestational Diabetes Mellitus, Type 1 Diabetes, and Type 2 Diabetes During Pregnancy and Risk of ADHD in Offspring

Cited by 99 publications

References 37 publications

BMI growth trajectory from ages 2 to 6 years and its association with maternal obesity, diabetes during pregnancy, gestational weight gain, and breastfeeding

BMI growth trajectory from ages 2 to 6 years and its association with maternal obesity, diabetes during pregnancy, gestational weight gain, and breastfeeding

Maternal serum C-reactive protein (CRP) and offspring attention deficit hyperactivity disorder (ADHD)

Management of Preexisting Diabetes in Pregnancy

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