Assessment of Neurodevelopment in Infants With and Without Exposure to Asymptomatic or Mild Maternal SARS-CoV-2 Infection During Pregnancy.

Importance: Associations between prenatal SARS-CoV-2 exposure and neurodevelopmental outcomes have substantial public health relevance. A previous study found no association between prenatal SARS-CoV-2 infection and parent-reported infant neurodevelopmental outcomes, but standardized observational assessments are needed to confirm this finding. Objective: To assess whether mild or asymptomatic maternal SARS-CoV-2 infection vs no infection during pregnancy is associated with infant neurodevelopmental differences at ages 5 to 11 months. Design, Setting, and Participants: This cohort study included infants of mothers from a single-site prospective cross-sectional study (COVID-19 Mother Baby Outcomes [COMBO] Initiative) of mother-infant dyads and a multisite prospective cohort study (Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 in Pregnancy and Infancy [ESPI]) of pregnant individuals. A subset of ESPI participants was subsequently enrolled in the ESPI COMBO substudy. Participants in the ongoing COMBO study were enrolled beginning on May 26, 2020; participants in the ESPI study were enrolled from May 7 to November 3, 2021; and participants in the ESPI COMBO substudy were enrolled from August 2020 to March 2021. For the current analysis, infant neurodevelopment was assessed between March 2021 and June 2022. A total of 407 infants born to 403 mothers were enrolled (204 from Columbia University Irving Medical Center in New York, New York; 167 from the University of Utah in Salt Lake City; and 36 from the University of Alabama in Birmingham). Mothers of unexposed infants were approached for participation based on similar infant gestational age at birth, date of birth, sex, and mode of delivery to exposed infants. Exposures: Maternal symptomatic or asymptomatic SARS-CoV-2 infection. Main Outcomes and Measures: Infant neurodevelopment was assessed using the Developmental Assessment of Young Children, second edition (DAYC-2), adapted for telehealth assessment. The primary outcome was age-adjusted standard scores on 5 DAYC-2 subdomains: cognitive, gross motor, fine motor, expressive language, and receptive language. Results: Among 403 mothers, the mean (SD) maternal age at delivery was 32.1 (5.4) years; most mothers were of White race (240 [59.6%]) and non-Hispanic ethnicity (253 [62.8%]). Among 407 infants, 367 (90.2%) were born full term and 212 (52.1%) were male. Overall, 258 infants (63.4%) had no documented prenatal exposure to SARS-CoV-2 infection, 112 (27.5%) had confirmed prenatal exposure, and 37 (9.1%) had exposure before pregnancy or at an indeterminate time. In adjusted models, maternal SARS-CoV-2 infection during pregnancy was not associated with differences in cognitive (ß = 0.31; 95% CI, -2.97 to 3.58), gross motor (ß = 0.82; 95% CI, -1.34 to 2.99), fine motor (ß = 0.36; 95% CI, -0.74 to 1.47), expressive language (ß = -1.00; 95% CI, -4.02 to 2.02), or receptive language (ß = 0.45; 95% CI, -2.15 to 3.04) DAYC-2 subdomain scores. Trimester of exposure and maternal symptom status were not associated with DAYC-2 subdomain scores. Conclusions and Relevance: In this study, results of a novel telehealth-adapted observational neurodevelopmental assessment extended a previous finding of no association between prenatal exposure to maternal SARS-CoV-2 infection and infant neurodevelopment. Given the widespread and continued high prevalence of COVID-19, these data offer information that may be helpful for pregnant individuals who experience asymptomatic or mild SARS-CoV-2 infections.

Modelling how face masks and symptoms-based quarantine synergistically and cost-effectively reduce SARS-CoV-2 transmission in Bangladesh.

BACKGROUND: Non-pharmaceutical interventions (NPIs) used to limit SARS-CoV-2 transmission vary in their feasibility, appropriateness and effectiveness in different contexts. In Bangladesh a national lockdown implemented in March 2020 exacerbated poverty and was untenable long-term. A resurgence in 2021 warranted renewed NPIs. We sought to identify NPIs that were feasible in this context and explore potential synergies between interventions. METHODS: We developed an SEIR model for Dhaka District, parameterised from literature values and calibrated to data from Bangladesh. We discussed scenarios and parameterisations with policymakers with the aid of an interactive app. These discussions guided modelling of lockdown and two post-lockdown measures considered feasible to deliver; symptoms-based household quarantining and compulsory mask-wearing. We compared NPI scenarios on deaths, hospitalisations relative to capacity, working days lost, and cost-effectiveness. RESULTS: Lockdowns alone were predicted to delay the first epidemic peak but could not prevent overwhelming of the health service and were costly in lost working days. Impacts of post-lockdown interventions depended heavily on compliance. Assuming 80% compliance, symptoms-based household quarantining alone could not prevent hospitalisations exceeding capacity, whilst mask-wearing prevented overwhelming health services and was cost-effective given masks of high filtration efficiency. Combining masks with quarantine increased their impact. Recalibration to surging cases in 2021 suggested potential for a further wave in 2021, dependent on uncertainties in case reporting and immunity. CONCLUSIONS: Masks and symptoms-based household quarantining synergistically prevent transmission, and are cost-effective in Bangladesh. Our interactive app was valuable in supporting decision-making, with mask-wearing being mandated early, and community teams being deployed to support quarantining across Dhaka. These measures likely contributed to averting the worst public health impacts, but delivering an effective response with consistent compliance across the population has been challenging. In the event of a further resurgence, concurrent messaging to increase compliance with both mask-wearing and quarantine is recommended.

Estimates of burden and consequences of infants born small for gestational age in low and middle income countries with INTERGROWTH-21st standard: analysis of CHERG datasets.

Objectives To estimate small for gestational age birth prevalence and attributable neonatal mortality in low and middle income countries with the INTERGROWTH-21st birth weight standard.Design Secondary analysis of data from the Child Health Epidemiology Reference Group (CHERG), including 14 birth cohorts with gestational age, birth weight, and neonatal follow-up. Small for gestational age was defined as infants weighing less than the 10th centile birth weight for gestational age and sex with the multiethnic, INTERGROWTH-21st birth weight standard. Prevalence of small for gestational age and neonatal mortality risk ratios were calculated and pooled among these datasets at the regional level. With available national level data, prevalence of small for gestational age and population attributable fractions of neonatal mortality attributable to small for gestational age were estimated.Setting CHERG birth cohorts from 14 population based sites in low and middle income countries.Main outcome measures In low and middle income countries in the year 2012, the number and proportion of infants born small for gestational age; number and proportion of neonatal deaths attributable to small for gestational age; the number and proportion of neonatal deaths that could be prevented by reducing the prevalence of small for gestational age to 10%.Results In 2012, an estimated 23.3 million infants (uncertainty range 17.6 to 31.9; 19.3% of live births) were born small for gestational age in low and middle income countries. Among these, 11.2 million (0.8 to 15.8) were term and not low birth weight (≥2500 g), 10.7 million (7.6 to 15.0) were term and low birth weight (<2500 g) and 1.5 million (0.9 to 2.6) were preterm. In low and middle income countries, an estimated 606 500 (495 000 to 773 000) neonatal deaths were attributable to infants born small for gestational age, 21.9% of all neonatal deaths. The largest burden was in South Asia, where the prevalence was the highest (34%); about 26% of neonatal deaths were attributable to infants born small for gestational age. Reduction of the prevalence of small for gestational age from 19.3% to 10.0% in these countries could reduce neonatal deaths by 9.2% (254 600 neonatal deaths; 164 800 to 449 700).Conclusions In low and middle income countries, about one in five infants are born small for gestational age, and one in four neonatal deaths are among such infants. Increased efforts are required to improve the quality of care for and survival of these high risk infants in low and middle income countries.

Risk Factors for Childhood Stunting in 137 Developing Countries: A Comparative Risk Assessment Analysis at Global, Regional, and Country Levels.

BACKGROUND: Stunting affects one-third of children under 5 y old in developing countries, and 14% of childhood deaths are attributable to it. A large number of risk factors for stunting have been identified in epidemiological studies. However, the relative contribution of these risk factors to stunting has not been examined across countries. We estimated the number of stunting cases among children aged 24-35 mo (i.e., at the end of the 1,000 days' period of vulnerability) that are attributable to 18 risk factors in 137 developing countries. METHODS AND FINDINGS: We classified risk factors into five clusters: maternal nutrition and infection, teenage motherhood and short birth intervals, fetal growth restriction (FGR) and preterm birth, child nutrition and infection, and environmental factors. We combined published estimates and individual-level data from population-based surveys to derive risk factor prevalence in each country in 2010 and identified the most recent meta-analysis or conducted de novo reviews to derive effect sizes. We estimated the prevalence of stunting and the number of stunting cases that were attributable to each risk factor and cluster of risk factors by country and region. The leading risk worldwide was FGR, defined as being term and small for gestational age, and 10.8 million cases (95% CI 9.1 million-12.6 million) of stunting (out of 44.1 million) were attributable to it, followed by unimproved sanitation, with 7.2 million (95% CI 6.3 million-8.2 million), and diarrhea with 5.8 million (95% CI 2.4 million-9.2 million). FGR and preterm birth was the leading risk factor cluster in all regions. Environmental risks had the second largest estimated impact on stunting globally and in the South Asia, sub-Saharan Africa, and East Asia and Pacific regions, whereas child nutrition and infection was the second leading cluster of risk factors in other regions. Although extensive, our analysis is limited to risk factors for which effect sizes and country-level exposure data were available. The global nature of the study required approximations (e.g., using exposures estimated among women of reproductive age as a proxy for maternal exposures, or estimating the impact of risk factors on stunting through a mediator rather than directly on stunting). Finally, as is standard in global risk factor analyses, we used the effect size of risk factors on stunting from meta-analyses of epidemiological studies and assumed that proportional effects were fairly similar across countries. CONCLUSIONS: FGR and unimproved sanitation are the leading risk factors for stunting in developing countries. Reducing the burden of stunting requires a paradigm shift from interventions focusing solely on children and infants to those that reach mothers and families and improve their living environment and nutrition.

Do wealth disparities contribute to health disparities within racial/ethnic groups?

BACKGROUND: Though wide disparities in wealth have been documented across racial/ethnic groups, it is largely unknown whether differences in wealth are associated with health disparities within racial/ethnic groups. METHODS: Data from the Survey of Consumer Finances (2004, ages 25-64) and the Health and Retirement Survey (2004, ages 50+), containing a wide range of assets and debts variables, were used to calculate net worth (a standard measure of wealth). Among non-Hispanic black, Hispanic and non-Hispanic white populations, we tested whether wealth was associated with self-reported poor/fair health status after accounting for income and education. RESULTS: Except among the younger Hispanic population, net worth was significantly associated with poor/fair health status within each racial/ethnic group in both data sets. Adding net worth attenuated the association between education and poor/fair health (in all racial/ethnic groups) and between income and poor/fair health (except among older Hispanics). CONCLUSIONS: The results add to the literature indicating the importance of including measures of wealth in health research for what they may reveal about disparities not only between but also within different racial/ethnic groups.

Assessing alternative measures of wealth in health research.

OBJECTIVES: We assessed whether it would be feasible to replace the standard measure of net worth with simpler measures of wealth in population-based studies examining associations between wealth and health. METHODS: We used data from the 2004 Survey of Consumer Finances (respondents aged 25-64 years) and the 2004 Health and Retirement Survey (respondents aged 50 years or older) to construct logistic regression models relating wealth to health status and smoking. For our wealth measure, we used the standard measure of net worth as well as 9 simpler measures of wealth, and we compared results among the 10 models. RESULTS: In both data sets and for both health indicators, models using simpler wealth measures generated conclusions about the association between wealth and health that were similar to the conclusions generated by models using net worth. The magnitude and significance of the odds ratios were similar for the covariates in multivariate models, and the model-fit statistics for models using these simpler measures were similar to those for models using net worth. CONCLUSIONS: Our findings suggest that simpler measures of wealth may be acceptable in population-based studies of health.