Summary: Previous research indicates that the COVID-19 pandemic catalyzed alterations in behaviors that may impact exposures to environmental endocrine-disrupting chemicals. This includes changes in the use of chemicals found in consumer products, food packaging, and exposure to air pollutants. Within the Environmental influences on Child Health Outcomes (ECHO) program, a national consortium initiated to understand the effects of environmental exposures on child health and development, our objective was to assess whether urinary concentrations of a wide range of potential endocrine-disrupting chemicals varied before and during the pandemic.

Summary: The Environmental influences on Child Health Outcomes (ECHO) Cohort has enrolled over 60,000 children to examine how early environmental factors (broadly defined) are associated with key child health outcomes. The ECHO Cohort may be well-positioned to contribute to our understanding of rural environments and contexts, which has implications for rural health disparities research. The present study examined the outcome of child obesity to not only illustrate the suitability of ECHO Cohort data for these purposes but also determine how various definitions of rural and urban populations impact the presentation of findings and their interpretation.

FIndings: Various rural/urban definitions and classification schemes produce similar obesity prevalence (17%) when collapsed into binary categories (rural vs urban) and for urban participants in general. When all categories within a classification scheme are examined, however, the rural child obesity prevalence ranges from 5.8% to 24%.

Conclusions: Collapsing rural-urban classification schemes into binary groupings erases nuance and context needed for interpreting findings, ultimately impacting health disparities research. Future work should leverage both individual- and community-level datasets to provide context, and all categories of classification schemes should be used when examining rural populations.

Summary: Sparse research exists on predictors of element concentrations measured in deciduous teeth. Findings from this study offer insights into predictors of dentin elements and potential confounders in exposure-health outcome relationships during critical developmental periods.

Summary: Using street view data, in replace of remotely sensed (RS) data, to study the health impact of greenspace has become popular. However, direct comparisons of these two methods of measuring greenspace are still limited, and their findings are inconsistent. On the other hand, almost all studies of greenspace focus on urban areas. The effectiveness of greenspace in rural areas remains to be investigated. In this study, we compared measures of greenspace based on the Google Street View data with those based on RS data by calculating the correlation between the two and evaluating their associations with birth outcomes.

Our study area consists of the States of New Hampshire and Vermont, USA, which are largely rural. Our results show that the correlations between the two types of greenness measures were weak to moderate, and the greenness at an eye-level view largely reflects the immediate surroundings. Neither the street view data- nor the RS data-based measures identify the influence of greenspace on birth outcomes in our rural study area. Interestingly, the environmental diversity was largely negatively associated with birth outcomes, particularly gestational age. Our study revealed that in rural areas, the effectiveness of greenspace and environmental diversity may be considerably different from that in urban areas.