Sociodemographic Differences in COVID-19 Pandemic Experiences Among Families in the United States.

Importance: Few population-based studies in the US collected individual-level data from families during the COVID-19 pandemic. Objective: To examine differences in COVID-19 pandemic-related experiences in a large sociodemographically diverse sample of children and caregivers. Design, Setting, and Participants: The Environmental influences on Child Health Outcomes (ECHO) multi-cohort consortium is an ongoing study that brings together 64 individual cohorts with participants (24 757 children and 31 700 caregivers in this study) in all 50 US states and Puerto Rico. Participants who completed the ECHO COVID-19 survey between April 2020 and March 2022 were included in this cross-sectional analysis. Data were analyzed from July 2021 to September 2022. Main Outcomes and Measures: Exposures of interest were caregiver education level, child life stage (infant, preschool, middle childhood, and adolescent), and urban or rural (population <50 000) residence. Dependent variables included COVID-19 infection status and testing; disruptions to school, child care, and health care; financial hardships; and remote work. Outcomes were examined separately in logistic regression models mutually adjusted for exposures of interest and race, ethnicity, US Census division, sex, and survey administration date. Results: Analyses included 14 646 children (mean [SD] age, 7.1 [4.4] years; 7120 [49%] female) and 13 644 caregivers (mean [SD] age, 37.6 [7.2] years; 13 381 [98%] female). Caregivers were racially (3% Asian; 16% Black; 12% multiple race; 63% White) and ethnically (19% Hispanic) diverse and comparable with the US population. Less than high school education (vs master's degree or more) was associated with more challenges accessing COVID-19 tests (adjusted odds ratio [aOR], 1.88; 95% CI, 1.06-1.58), lower odds of working remotely (aOR, 0.04; 95% CI, 0.03-0.07), and more food access concerns (aOR, 4.14; 95% CI, 3.20-5.36). Compared with other age groups, young children (age 1 to 5 years) were least likely to receive support from schools during school closures, and their caregivers were most likely to have challenges arranging childcare and concerns about work impacts. Rural caregivers were less likely to rank health concerns (aOR, 0.77; 95% CI, 0.69-0.86) and social distancing (aOR, 0.82; 95% CI, 0.73-0.91) as top stressors compared with urban caregivers. Conclusions: Findings in this cohort study of US families highlighted pandemic-related burdens faced by families with lower socioeconomic status and young children. Populations more vulnerable to public health crises should be prioritized in recovery efforts and future planning.

US Childhood Asthma Incidence Rate Patterns From the ECHO Consortium to Identify High-risk Groups for Primary Prevention.

Importance: Asthma is the leading chronic illness in US children, but most descriptive epidemiological data are focused on prevalence. Objective: To evaluate childhood asthma incidence rates across the nation by core demographic strata and parental history of asthma. Design, Setting, and Participants: For this cohort study, a distributed meta-analysis was conducted within the Environmental Influences on Child Health Outcomes (ECHO) consortium for data collected from May 1, 1980, through March 31, 2018. Birth cohort data of children from 34 gestational weeks of age or older to 18 years of age from 31 cohorts in the ECHO consortium were included. Data were analyzed from June 14, 2018, to February 18, 2020. Exposures: Caregiver report of physician-diagnosed asthma with age of diagnosis. Main Outcome and Measures: Asthma incidence survival tables generated by each cohort were combined for each year of age using the Kaplan-Meier method. Age-specific incidence rates for each stratum and asthma incidence rate ratios by parental family history (FH), sex, and race/ethnicity were calculated. Results: Of the 11 404 children (mean [SD] age, 10.0 [0.7] years; 5836 boys [51%]; 5909 White children [53%]) included in the primary analysis, 7326 children (64%) had no FH of asthma, 4078 (36%) had an FH of asthma, and 2494 (23%) were non-Hispanic Black children. Children with an FH had a nearly 2-fold higher incidence rate through the fourth year of life (incidence rate ratio [IRR], 1.94; 95% CI, 1.76-2.16) after which the rates converged with the non-FH group. Regardless of FH, asthma incidence rates among non-Hispanic Black children were markedly higher than those of non-Hispanic White children during the preschool years (IRR, 1.58; 95% CI, 1.31-1.86) with no FH at age 4 years and became lower than that of White children after age 9 to 10 years (IRR, 0.67; 95% CI, 0.50-0.89) with no FH. The rates for boys declined with age, whereas rates among girls were relatively steady across all ages, particularly among those without an FH of asthma. Conclusions and Relevance: Analysis of these diverse birth cohorts suggests that asthma FH, as well as race/ethnicity and sex, were all associated with childhood asthma incidence rates. Black children had much higher incidences rates but only during the preschool years, irrespective of FH. To prevent asthma among children with an FH of asthma or among Black infants, results suggest that interventions should be developed to target early life.

Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment.

Purpose: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness related to oxygen exposure in premature infants. Since oxygen monitoring protocols have reduced the incidence of treatment-requiring ROP (TR-ROP), it remains unclear whether oxygen exposure remains a relevant risk factor for incident TR-ROP and aggressive ROP (A-ROP), a severe, rapidly progressing form of ROP. The purpose of this proof-of-concept study was to use electronic health record (EHR) data to evaluate early oxygen exposure as a predictive variable for developing TR-ROP and A-ROP. Design: Retrospective cohort study. Participants: Two hundred forty-four infants screened for ROP at a single academic center. Methods: For each infant, oxygen saturations and fraction of inspired oxygen (FiO2) were extracted manually from the EHR until 31 weeks postmenstrual age (PMA). Cumulative minimum, maximum, and mean oxygen saturation and FiO2 were calculated on a weekly basis. Random forest models were trained with 5-fold cross-validation using gestational age (GA) and cumulative minimum FiO2 at 30 weeks PMA to identify infants who developed TR-ROP. Secondary receiver operating characteristic (ROC) curve analysis of infants with or without A-ROP was performed without cross-validation because of small numbers. Main Outcome Measures: For each model, cross-validation performance for incident TR-ROP was assessed using area under the ROC curve (AUC) and area under the precision-recall curve (AUPRC) scores. For A-ROP, we calculated AUC and evaluated sensitivity and specificity at a high-sensitivity operating point. Results: Of the 244 infants included, 33 developed TR-ROP, of which 5 developed A-ROP. For incident TR-ROP, random forest models trained on GA plus cumulative minimum FiO2 (AUC = 0.93 ± 0.06; AUPRC = 0.76 ± 0.08) were not significantly better than models trained on GA alone (AUC = 0.92 ± 0.06 [P = 0.59]; AUPRC = 0.74 ± 0.12 [P = 0.32]). Models using oxygen alone showed an AUC of 0.80 ± 0.09. ROC analysis for A-ROP found an AUC of 0.92 (95% confidence interval, 0.87-0.96). Conclusions: Oxygen exposure can be extracted from the EHR and quantified as a risk factor for incident TR-ROP and A-ROP. Extracting quantifiable clinical features from the EHR may be useful for building risk models for multiple diseases and evaluating the complex relationships among oxygen exposure, ROP, and other sequelae of prematurity.