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Purpose: To examine changes in obesity prevalence among US adults after the COVID-19 pandemic by level of stay-at-home order and sociodemographic characteristics. Design: Quasi-experimental study using repeated cross-sectional data. Setting: Behavioral Risk Factor Surveillance System (BRFSS). Sample: Pooled data for US adults ages ≥26 years (n = 1,107,673) from BRFSS (2018-2021). Measures: States/territories were classified into three levels of stay-at-home order: none, advisory/only for persons at risk, or mandatory for all. Individual-level sociodemographic characteristics were self-reported. Analysis: The difference-in-differences method was conducted with weighted multiple logistic regression analysis to examine obesity (body mass index ≥30 kg/m2) prevalence by stay-at-home order level and sociodemographic characteristics before/after the COVID-19 pandemic (January 2018-February 2020 vs March 2020-February 2022). Results: After adjusting for a secular trend and multiple covariates, adults in states/territories with mandatory stay-at-home orders experienced a larger increase in obesity prevalence (adjusted odds ratio: 1.05; 95% confidence interval: 1.01, 1.11) than adults in states/territories with no stay-at-home order. Younger adults (vs ≥65 years) and individuals with

Road traffic accidents are one of the leading causes of death for the young segment of the population. Prevention strategies can mitigate the occurrence of road accidents, and successful actions should take into account the most relevant causes of accidents. We use a comprehensive dataset which reports information from police records on all road traffic accidents with injures and/or deaths in Italy between 2014 and 2020 to explore the relationships among economic forces, driving behaviours and accident frequency and severity. More specifically, the natural experiment setting provided by the 2020 COVID-19-related movement restrictions allows to capture the effect of traffic intensity and other factors on the frequency of serious accidents and mortality. The empirical findings confirm a direct relationship between the level of economic activity and the frequency of accidents, whereas there is no clear link with their severity. Instead, lockdown periods are associated with a relatively higher occurrence of fatal road traffic accidents, due to both riskier driving behaviours at times of reduced traffic, and changes in transportation habits reflected by a higher probability of accidents involving bicycles and motorcycles. • Economic variables are a major determinant of road traffic accidents (RTAs) in Italy. • RTA frequency follows the economic cycle, but mortality is unrelated. • COVID-19-related stay-at-home orders reduced the number of RTAs, injuries and deaths. • Lockdown periods were associated with a higher rate of fatal accidents. • Road safety strategies should consider behavioral responses to movement restrictions. [ABSTRACT FROM AUTHOR]

• Child maltreatment reporting dropped by as much as 31 percent in Colorado during the pandemic. • Counterfactual estimates predict thousands of referrals and victims went unreported. • Victims of neglect were most likely being missed. • Data and clever techniques to measure child maltreatment need to be readily available. As a result of the COVID-19 pandemic, schools closed abruptly in March 2020, and Colorado issued a stay-at-home order during the month of April. Subsequently, child maltreatment reporting dropped by 31 percent. This article documents the decline in referrals and reports during 2020 and 2021 in Colorado and predicts counterfactual estimates using two strategies. One strategy assumes the underlying behavior for child maltreatment was unchanged from 2019 to 2020 and 2021, while the second strategy assumes the economic distress and protective factors brought about by the pandemic altered the underlying prevalence of child maltreatment. Consequently, these two approaches yield similar results when investigating referrals, but they differ when investigating screened-in referrals and substantiated reports. I find that the largest reduction in reporting comes from the stay-at-home order, followed by school closings. Lastly, counterfactual estimates suggest that these missed children were suffering from neglect and not abuse. These findings quantify another hardship brought about by the pandemic, underreporting child maltreatment, and underscore the role mandatory reporters play in detecting child maltreatment. [ABSTRACT FROM AUTHOR]