Pregnancy-Specific Anxiety Tool (PSAT): Instrument Development and Psychometric Evaluation

Objective: Pregnancy-specific anxiety (PSA) is a distinct construct from general anxiety and depression. The purpose of this study was to develop, evaluate, and validate the Pregnancy-Specific Anxiety Tool (PSAT), to measure PSA and its severity.

Methods: The study was carried out in 2 stages. Stage 1 involved item development and content and face validation. Stage 2 included psychometric evaluation to examine item distributions and correlational structure, dimensionality, internal consistency reliability, stability, and construct, convergent, and criterion validity, using 2 independent samples (initial sample N = 494, May-October 2018; validation sample N = 325, July 2019-May 2020).

Results: Eighty-two items were evaluated for face validity and 41 items were considered in stage 2 based on feedback from participants and experts. Model fit from exploratory factor analysis and patterns of item-factor loadings suggested a 6-factor model with 33 items. The 6 factors included items pertaining to health and well-being of the baby, labor and the pregnant person's well-being, postpartum, support, career and finance, and indicators of severity. Confirmatory factor analysis carried out using the initial sample showed good fit with the validation sample. The area under the curve (AUC) for the diagnosis of adjustment disorders (AD) was 0.73 (95% CI, 0.67-0.79), and for AD/any anxiety disorders, the AUC was 0.80 (95% CI, 0.75-0.85).

Conclusions: The PSAT can be useful for screening and monitoring of PSA, and pregnant people with scores higher than 10 should be considered for further assessment.

Portable HEPA Filter Air Cleaner Use during Pregnancy and Children's Cognitive Performance at Four Years of Age: The UGAAR Randomized Controlled Trial

BACKGROUND

Developmental exposure to air pollution is associated with diminished cognitive abilities in observational studies, but no randomized controlled trial has examined the effect of reducing air pollution on cognition in children.

OBJECTIVES

We sought to quantify the impact of reducing exposure to particulate matter (PM) during pregnancy on children's cognitive performance at 4 y of age.

METHODS

In this single-blind, parallel-group, randomized controlled trial in Ulaanbaatar, Mongolia, we randomly assigned 540 nonsmoking pregnant women (268 intervention and 272 control) to receive 1-2 portable high-efficiency particulate air (HEPA) filter air cleaners or no air cleaners. The air cleaners were used from a median of 11 wk gestation until the end of pregnancy. The primary outcome was full-scale intelligence quotient (FSIQ) assessed using the Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition (WPPSI-IV) when children were a median of 48 months old. We imputed missing outcome data using multiple imputation with chained equations, and our primary analysis was by intention to treat.

RESULTS

After excluding known miscarriages, stillbirths, neonatal deaths, and medical conditions that impeded cognitive testing and imputation, 475 (233 control and 242 intervention) children were included in our analyses. In an unadjusted analysis, the mean FSIQ of children who were randomly assigned to the intervention group was 2.5 points [95% confidence interval (CI): -0.4, 5.4 points] higher than that of children in the control group. After adjustment to account for an imbalance in preterm birth between groups, the effect estimate increased to 2.8 points (95% CI: -0.1, 5.7).

CONCLUSIONS

Reducing PM air pollution during pregnancy may improve cognitive performance in childhood. https://doi.org/10.1289/EHP10302.

Pregnant people's responses to the COVID-19 pandemic: a mixed-methods, descriptive study

BACKGROUND

Given the extent of the COVID-19 pandemic and uncertainty around the timing of its containment, understanding the experiences and responses of the perinatal population is essential for planning responsive maternity care both during and after the pandemic. The aim of this study was to explore the experiences of pregnant people and their responses to the COVID-19 pandemic, and to identify how health care providers can support this population.

METHODS

This was a mixed-methods, descriptive study with cross-sectional and qualitative descriptive components. We conducted the study between Mar. 20 and May 31, 2020, in British Columbia, Canada. Any pregnant person at any gestational age living in BC was eligible to participate. We collected quantitative data using online survey tools, including the Edinburgh Postnatal Depression Scale (EPDS) and the 7-item Generalized Anxiety Disorder questionnaire (GAD-7). We collected qualitative data using open-ended questions to explore people's thoughts, feelings and experiences during the pandemic. Participants were recruited using study posters distributed via prenatal care clinics and classes, LifeLabs and social media across the province. We used thematic and descriptive analyses to analyze the data, and we integrated the qualitative and quantitative findings at the interpretation level.

RESULTS

The study sample included 96 participants with mean (± standard deviation) maternal and gestational ages of 32 ± 3.92 years and 22.73 ± 8.93 weeks, respectively. Most (93%; n = 89) identified as female. Of the participants, 54% (n = 50) and 35% (n = 34) reported anxiety and depressive symptoms, as measured by the GAD-7 and EPDS, respectively. Overarching themes that emerged from the qualitative data included uncertainty about birth plans and setting, added burden to existing health and social disparities, perceived or projected lack of support or limited support, concerns about early development, and struggle over managing multiple demands. Perceived maternity care needs included mental health support, maintaining prenatal care, frequent and proactive check-ins to build rapport, and recommendations specific to the pandemic.

INTERPRETATION

We found that the impact of the COVID-19 pandemic on the pregnant population has been substantial. The findings of this mixed-methods study can be used to help plan informed and evidence-based health care interventions to mitigate adverse effects and support mothers and families.

Bacteroides-dominant gut microbiome of late infancy is associated with enhanced neurodevelopment

Dysbiosis of gut microbiota has been retrospectively linked to autism spectrum disorders but the temporal association between gut microbiota and early neurodevelopment in healthy infants is largely unknown. We undertook this study to determine associations between gut microbiota at two critical periods during infancy and neurodevelopment in a general population birth cohort.Here, we analyzed data from 405 infants (199 females) from the CHILD (Canadian Healthy Infant Longitudinal Development) Cohort Study. Neurodevelopmental outcomes were objectively assessed using the Bayley Scale of Infant Development (BSID-III) at 1 and 2 years of age. Microbiota profiling with 16S rRNA gene sequencing was conducted on fecal samples obtained at a mean age of 4 and 12 months.Using clustering methods, we identified three groups of infants based on relative abundance of gut microbiota at 12 months: Proteobacteria-dominant cluster (22.4% higher abundance at 12 months), Firmicutes-dominant cluster (46.0% higher abundance at 12 months) and Bacteroidetes-dominant cluster (31.6% higher abundance at 12 months). Relative to the Proteobacteria-dominant cluster, the Bacteroidetes-dominant cluster was associated with higher scores for cognitive (4.8 points; FDRp = .02), language (4.2 points; FDRp≤0.001), and motor (3.1 points; FDRp = .03) development at age 2 in models adjusted for covariates. When stratified by sex, only male infants with a Bacteroidetes-dominant microbiota had more favorable cognitive (5.9 points, FDRp = .06) and language (7.9 points; FDRp≤0.001) development. Genus Bacteroides abundance in gut microbiota was positively correlated with cognitive and language scores at age 2. Fully adjusted linear mixed model analysis revealed a positive association between Bacteroidetes-dominant cluster and change in cognitive and language performance from 1 to 2 years, predominantly among males. No associations were evident between 4-month microbiota clusters and BSID-II scores. Noteworthy is that enhanced sphingolipid synthesis and metabolism, and antagonism or competition between Bacteroides and Streptococcus were characteristic of a Bacteroidetes-dominant gut microbiota.This study found strong evidence of positive associations between Bacteroidetes gut microbiota in late infancy and subsequent neurodevelopment, most prominently among males but not females.

Portable HEPA filter air cleaner use during pregnancy and children's body mass index at two years of age: The UGAAR randomized controlled trial

IMPORTANCE

Gestational exposure to particulate matter (PM) air pollution may increase the risk of childhood obesity, but the impact of reducing air pollution during pregnancy on obesity-related outcomes in childhood has not been examined.

OBJECTIVE

To assess the impact of reducing gestational PM exposure on body mass index (BMI) at two years of age.

METHODS

In this single-blind, parallel group randomized controlled trial in Ulaanbaatar Mongolia, we randomly assigned 540 pregnant women to receive 1-2 portable high efficiency particulate air (HEPA) filter air cleaners or no air cleaners. We measured height and weight when children were a mean age of 23.8 months. Our primary outcome was age- and sex-specific BMI z-score based on the World Health Organization 2007 Growth Charts. Secondary outcomes included age- and sex-specific weight z score, overweight/obesity (defined as BMI z-score > 2.00), and catch-up growth (defined using various cut-offs to identify children with relatively low birth weight for sex and gestational age and relatively high age- and sex-specific weight in childhood). We imputed missing outcome data using multiple imputation with chained equations and our primary analysis was by intention to treat (ITT). We estimated intervention effects on continuous and binary outcomes using linear and logistic regression, respectively.

RESULTS

After excluding known miscarriages, still births, and neonatal deaths our analysis included 480 children (235 control and 245 intervention). The mean (SD) child BMI z score was 0.79 (1.0); 9.8% of children were overweight or obese. The mean BMI z score of children who were randomly assigned to the intervention group was 0.16-units lower (95% CI: -0.35, 0.04) than children in the control group. The intervention was also associated with reductions in overweight/obesity (odds ratio = 0.59; 95% CI: 0.31, 1.12). Catch-up growth occurred less frequently in the intervention group, but effect estimates varied depending on the specific definition of catch-up growth and confidence intervals consistently spanned no effect.

CONCLUSIONS

We found that the use of portable air cleaners during pregnancy was associated with improvements in obesity-related outcomes, although some effect estimates lacked precision. Reducing PM exposure during pregnancy may lead to improvements in cardiometabolic health in childhood.

Development and Validation of SDBeasy Score as a Predictor of Behavioral Outcomes in Childhood

Rationale: There are limited tools to identify which children are at greatest risk for developing sleep-disordered breathing (SDB)-associated behavioral morbidity.Objectives: To examine associations between age of onset and duration of parent-reported symptoms of SDB and behavioral problems at the age of 5 years.Methods: Data were collected and analyses were completed for participants in the CHILD (Canadian Healthy Infant Longitudinal Development) cohort at the Edmonton and Toronto sites. We generated an SDBeasy score on the basis of the age of onset and duration of SDB symptoms as reported by parents completing the Pediatric Sleep Questionnaire. Using CHILD-Edmonton data, we completed multivariate linear regression to determine whether the SDBeasy score was associated with behavioral problems at the age 5 years of age as assessed by using the Child Behavior Checklist (CBCL). We then validated the SDBeasy score using CHILD-Toronto data.Measurements and Main Results: At the 5-year visit, 581 of 716 (81%) CHILD-Edmonton participants still enrolled had CBCL data. Of the 581 children with data, 77% (446 of 581) had an SDBeasy score of 0 (never had SDB symptoms), whereas 20 of 581 children (3.4%) had persistent SDB symptoms from infancy through 5 years of age (SDBeasy score of 24). Children had a 0.35-point-higher CBCL total behavioral score at 5 years for each 1-point increase in their SDBeasy score (95% confidence interval, 0.24-0. 5; P < 0.01). We found consistent results among CHILD-Toronto participants; children had a 0.26-point-higher CBCL total behavioral score at 5 years for each 1-point increase in their SDBeasy score (95% confidence interval, 0.08-0.44; P = 0.005).Conclusions: The SDBeasy score, based on the Pediatric Sleep Questionnaire, enables identification of children with higher behavioral-problem scores.

The relationship between machine-learning-derived sleep parameters and behavior problems in 3- and 5-year-old children: results from the CHILD Cohort study

STUDY OBJECTIVES

Machine learning (ML) may provide insights into the underlying sleep stages of accelerometer-assessed sleep duration. We examined associations between ML-sleep patterns and behavior problems among preschool children.

METHODS

Children from the CHILD Cohort Edmonton site with actigraphy and behavior data at 3-years (n = 330) and 5-years (n = 304) were included. Parent-reported behavior problems were assessed by the Child Behavior Checklist. The Hidden Markov Model (HMM) classification method was used for ML analysis of the accelerometer sleep period. The average time each participant spent in each HMM-derived sleep state was expressed in hours per day. We analyzed associations between sleep and behavior problems stratified by children with and without sleep-disordered breathing (SDB).

RESULTS

Four hidden sleep states were identified at 3 years and six hidden sleep states at 5 years using HMM. The first sleep state identified for both ages (HMM-0) had zero counts (no movement). The remaining hidden states were merged together (HMM-mov). Children spent an average of 8.2 ± 1.2 h/day in HMM-0 and 2.6 ± 0.8 h/day in HMM-mov at 3 years. At age 5, children spent an average of 8.2 ± 0.9 h/day in HMM-0 and 1.9 ± 0.7 h/day in HMM-mov. Among SDB children, each hour in HMM-0 was associated with 0.79-point reduced externalizing behavior problems (95% CI -1.4, -0.12; p < 0.05), and a 1.27-point lower internalizing behavior problems (95% CI -2.02, -0.53; p < 0.01).

CONCLUSIONS

ML-sleep states were not associated with behavior problems in the general population of children. Children with SDB who had greater sleep duration without movement had lower behavioral problems. The ML-sleep states require validation with polysomnography.

Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study

BACKGROUND

Pre-school children spend an average of two-hours daily using screens. We examined associations between screen-time on pre-school behavior using data from the Canadian Healthy Infant Longitudinal Development (CHILD) study.

METHODS

CHILD participant parents completed the Child Behavior Checklist (CBCL) at five-years of age. Parents reported their child's total screen-time including gaming and mobile devices. Screen-time was categorized using the recommended threshold of two-hours/day for five-years or one-hour/day for three-years. Multiple linear regression examined associations between screen-time and externalizing behavior (e.g. inattention and aggression). Multiple logistic regression identified characteristics of children at risk for clinically significant externalizing problems (CBCL T-score≥65).

RESULTS

Screen-time was available for over 95% of children (2,322/2,427) with CBCL data. Mean screen-time was 1·4 hours/day (95%CI 1·4, 1·5) at five-years and 1·5 hours/day (95%CI: 1·5, 1·6) at three-years. Compared to children with less than 30-minutes/day screen-time, those watching more than two-hours/day (13·7%) had a 2·2-point increase in externalizing T-score (95%CI: 0·9, 3·5, p≤0·001); a five-fold increased odd for reporting clinically significant externalizing problems (95%CI: 1·0, 25·0, p = 0·05); and were 5·9 times more likely to report clinically significant inattention problems (95%CI: 1·6, 21·5, p = 0·01). Children with a DSM-5 ADHD T-score above the 65 clinical cut-off were considered to have significant ADHD type symptoms (n = 24). Children with more than 2-hours of screen-time/day had a 7·7-fold increased risk of meeting criteria for ADHD (95%CI: 1·6, 38·1, p = 0·01). There was no significant association between screen-time and aggressive behaviors (p>0.05).

CONCLUSION

Increased screen-time in pre-school is associated with worse inattention problems.

Parent-Reported Symptoms of Sleep-Disordered Breathing Are Associated With Increased Behavioral Problems at 2 Years of Age: The Canadian Healthy Infant Longitudinal Development Birth Cohort Study

Study Objectives

To examine the association between the age of onset and duration of parent-reported symptoms of sleep-disordered breathing (SDB) and behavioral problems at age 2.

Methods

Parent-reported SDB symptoms were assessed quarterly between 3 months and 2 years among 583 Canadian Healthy Infant Longitudinal Development Edmonton-site participants. Parent-reported SDB symptoms were clustered into phenotypes using group-based trajectory analysis based on age of onset and duration of symptoms. Home-based polysomnography (PSG) was completed at 1 year. The Child Behavior Checklist preschool-version (Mean T-score 50, standard deviation 10 points) assessed total, externalizing (attention), and internalizing (anxiety, depression) behaviors at 2 years.

Results

Four phenotypes were identified: no SDB (64.7%), early-onset SDB (15.7%, peak symptoms at 9 months), late-onset (14.2%, peak symptoms at 18 months), and persistent SDB symptoms (5.3%, peak symptoms from 3 through 24 months). Persistent SDB (9.5 points, 95% CI 1.7, 17.2; p = .02) predicted the greatest magnitude of effect of total behavior problems, compared with children without SDB. Children with early-onset SDB (3.5 points, 95% CI 1.6, 5.4; p ≤ .001) and late-onset SDB (6.1 points 95% CI 4.0, 8.3; p ≤ .001) had increased total behavioral problems than children without SDB to 2 years. Additional analyses showed that the SDB phenotypes' trajectories were important for internalizing but not for externalizing behavior problems. There were no significant associations between home-PSG and parent-reported behavior problems.

Conclusions

Findings suggest that the age of onset and duration of parent-reported SDB symptoms prior to age 2 have adverse consequences for overall behavior problems.