Maternal health around pregnancy and autism risk: a diagnosis-wide, population-based study

Caregiver Narratives of Children with Autism Spectrum Disorder: Exploring Symptom Recognition, Diagnosis, and Interventions

The diagnosis of autism spectrum disorder (ASD) poses myriad challenges for families, yet there is a scarcity of research focusing on their journey from recognizing initial anomalies to implementing interventions. This qualitative study examines how caregivers in Sylhet, Bangladesh, perceive and manage ASD in their children, including early symptom identification, diagnostic processes, and intervention strategies. Data for this study were collected through semi-structured interviews, case studies, and observations involving 22 caregivers of children with ASD. Participants were chosen using purposive-convenience sampling, and data collection continued until interpretive saturation was achieved. The study findings unveil nuanced caregiver perceptions of ASD causation, influenced by sociocultural factors, religious beliefs, and genetic predispositions. These determinants wield significant influence over treatment modalities and the child's developmental trajectory. Importantly, the prevalence of supernatural beliefs and myths often surpasses biomedical explanations, highlighting gaps in awareness, educational outreach, and understanding of ASD. Nevertheless, religious beliefs and rituals concurrently serve as adaptive coping mechanisms, offering solace amidst uncertainty. Furthermore, a striking observation emerges: despite parents frequently identifying anomalies in their children within a 24-month, a substantial delay of 3 to 5 years persists between initial symptom recognition and formal diagnosis. This delay predominantly stems from caregiver hesitancy driven by societal stigmatization, familial dismissal attitudes, and limited diagnostic and specialized services. This study highlights the challenging diagnostic journey and caregiving for children with ASD in Bangladesh, stressing the need for systemic improvements in services, awareness, and research to enhance the well-being of individuals with ASD.

Preeclampsia Onset, Days to Delivery, and Autism Spectrum Disorders in Offspring: Clinical Birth Cohort Study

BACKGROUND

Maternal preeclampsia is associated with a risk of autism spectrum disorders (ASD) in offspring. However, it is unknown whether the increased ASD risk associated with preeclampsia is due to preeclampsia onset or clinical management of preeclampsia after onset, as clinical expectant management of preeclampsia allows pregnant women with this complication to remain pregnant for potentially weeks depending on the onset and severity. Identifying the risk associated with preeclampsia onset and exposure provides evidence to support the care of high-risk pregnancies and reduce adverse effects on offspring.

OBJECTIVE

This study aimed to fill the knowledge gap by assessing the ASD risk in children associated with the gestational age of preeclampsia onset and the number of days from preeclampsia onset to delivery.

METHODS

This retrospective population-based clinical cohort study included 364,588 mother-child pairs of singleton births between 2001 and 2014 in a large integrated health care system in Southern California. Maternal social demographic and pregnancy health data, as well as ASD diagnosis in children by the age of 5 years, were extracted from electronic medical records. Cox regression models were used to assess hazard ratios (HRs) of ASD risk in children associated with gestational age of the first occurrence of preeclampsia and the number of days from first occurrence to delivery.

RESULTS

Preeclampsia occurred in 16,205 (4.4%) out of 364,588 pregnancies; among the 16,205 pregnancies, 2727 (16.8%) first occurred at <34 weeks gestation, 4466 (27.6%) first occurred between 34 and 37 weeks, and 9012 (55.6%) first occurred at ≥37 weeks. Median days from preeclampsia onset to delivery were 4 (IQR 2,16) days, 1 (IQR 1,3) day, and 1 (IQR 0,1) day for those first occurring at <34, 34-37, and ≥37 weeks, respectively. Early preeclampsia onset was associated with greater ASD risk (P=.003); HRs were 1.62 (95% CI 1.33-1.98), 1.43 (95% CI 1.20-1.69), and 1.23 (95% CI 1.08-1.41), respectively, for onset at <34, 34-37, and ≥37 weeks, relative to the unexposed group. Within the preeclampsia group, the number of days from preeclampsia onset to delivery was not associated with ASD risk in children; the HR was 0.995 (95% CI 0.986-1.004) after adjusting for gestational age of preeclampsia onset.

CONCLUSIONS

Preeclampsia during pregnancy was associated with ASD risk in children, and the risk was greater with earlier onset. However, the number of days from first preeclampsia onset to delivery was not associated with ASD risk in children. Our study suggests that ASD risk in children associated with preeclampsia is not increased by expectant management of preeclampsia in standard clinical practice. Our results emphasize the need to identify effective approaches to preventing the onset of preeclampsia, especially during early pregnancy. Further research is needed to confirm if this finding applies across different populations and clinical settings.

Correlation analysis of maternal condition during pregnancy with head circumference and autism spectrum disorder: A propensity score-matched study

To determine whether health status during pregnancy is associated with autism spectrum disorder (ASD) and abnormal head circumference (HC) in the offspring. This study included 41 Han children with ASD who visited the Children's Health Clinic of the Second Hospital of Shandong University between March 2018 and February 2019, and 264 Han children with typical development (TD) who visited the clinic during the same period. Physical measurements were performed on the children. The questionnaire obtained information on maternal risk factors that may be related to the increased risk of ASD and folic acid (FA) supplementation. We designed an observational case-control study using propensity score matching and multivariate logistic regression analysis. The incidence of macrocephaly in the ASD group was 22.0%, significantly higher than that in the TD group (1.8%). The incidence of microcephaly in the ASD group was 17.1% (n = 7), significantly higher than that in the TD group (1.8%). The differences between the comparisons were statistically significant. Maternal FA supplementation during pregnancy was significantly associated with ASD (P < .05), with an odds ratio (95% confidence interval of 3.69 (1.76, 7.76)). Also was associated with macrocephaly (P < .05), odds ratio (95% confidence interval) were 8.13 (1.63, 40.61) and 4.16 (1.18, 14.60), respectively. The incidence of abnormal HC was higher in the ASD group than that in the TD group. Maternal FA supplementation during pregnancy may be negatively associated with the occurrence of ASD and abnormal HC in the offspring. Further examination of the role of maternal health status in the etiology of ASD is recommended.

Somatic comorbidities of mental disorders in pregnancy

BACKGROUND

Mental and physical health conditions are frequently comorbid. Despite the widespread physiological and behavioral changes during pregnancy, the pattern of comorbidities among women in pregnancy is not well studied. This study aimed to systematically examine the associations between mental and somatic disorders before and during pregnancy.

METHOD

The study used data from mothers of a nationally representative birth cohort of children born in Israel (1997-2008). We compared the risk of all major somatic disorders (International Classification of Diseases, Ninth Revision) in pregnant women with and without a mental disorder. All analyses were adjusted for maternal age, child's birth year, family socioeconomic status, and the total number of maternal encounters with health services around pregnancy period.

RESULTS

The analytical sample included 77,030 mother-child dyads, with 30,083 unique mothers. The mean age at child's birth was 29.8 years. Prevalence of diagnosis of mental disorder around pregnancy in our sample was 4.4%. Comorbidity between mental and somatic disorders was two times higher than the comorbidity between pairs of different somatic disorders. Of the 17 somatic disorder categories, seven were positively associated with mental health disorders. The highly prevalent comorbidities associated with mental disorders in pregnancy included e.g. musculoskeletal (OR = 1.30; 95% CI = 1.20-1.42) and digestive system diseases (OR = 1.23; 95% CI = 1.13-1.34).

CONCLUSIONS

We observed that associations between maternal diagnoses and mental health stand out from the general pattern of comorbidity between nonmental health diseases. The study results confirm the need for screening for mental disorders during pregnancy and for potential comorbid conditions associated with mental disorders.

Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics

Intelligent health diagnosis for young children aims at maintaining and promoting the healthy development of young children, aiming to make young children have a healthy state and provide a better future for their physical and mental health development. The biological basis of intelligence is the structure and function of human brain and the key to improve the intelligence level of infants is to improve the quality of brain development, especially the early development of brain. Based on machine learning and health information statistics, this paper studies the development of infant health diagnosis and intelligence, physical and mental health. Pre-process the sample data, and use the filtering method based on machine learning and health information statistics for feature screening. Compared with traditional statistical methods, machine learning and health information statistical methods can better obtain the hidden information in the big data of children's physical and mental health development, and have better learning ability and generalization ability. The machine learning theory is used to analyze and mine the infant's health diagnosis and intelligence development, establish a health state model, and intuitively show people the health status of their infant's physical and mental health development by means of data. Moreover, the accumulation of these big data is very important in the field of medical and health research driven by big data.

Labor epidural analgesia and risk of autism Spectrum disorders in offspring: A systematic review and meta-analysis

Background

The effect of labor epidural anesthesia (LEA) on the risk of autism spectrum disorder (ASD) in offspring has been investigated recently, and available results are inconsistent.

Methods

We searched the PubMed and EMBASE databases for relevant studies and performed a systematic review and meta-analysis of the literature. Subgroup analyses were conducted to assess the sources of heterogeneity. Both fixed and random effects models were used was used to estimate overall relative risk.

Results

Our results showed that LEA was associated with an increased risk of ASD in offspring [HR = 1.3, 95% confidence interval (CI): 1.25-1.35; P < 0.001] after combining crude estimates from the included studies. This association was gradually reduced, but still statistically significant, when potential confounding factors were considered (HR 1.13, 95% CI 1.03-1.25, P = 0.014). However, there was no significant association when we combined data of siblings from other pregnancies (HR = 1.07, 95% CI: 0.99-1.16, P = 0.076), implying that the association was due to confounding factors.

Conclusion

The statistically significant association between LEA and ASD in the offspring can be partially explained by unmeasured confounding.

Systematic Review Registration

Identifier CRD42022302892.