Corrigendum to "Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?" [SSM-Population Health 15 (2021) 100845].

[This corrects the article DOI: 10.1016/j.ssmph.2021.100845.].

The impact of two types of COVID-19-related discrimination and contemporaneous stressors on Chinese immigrants in the US South.

The global rise of the COVID-19 pandemic has been accompanied by an increase in anti-Asian discrimination with potentially deleterious effects on individuals of Asian descent. In the present study, we examine how two types of COVID-19-related anti-Asian discrimination and other contemporaneous stressors independently contribute to perceptions of stress in a population-representative sample of Chinese immigrants in North Carolina, as well as the moderating role of ethnic identity on the association between COVID-related discrimination and stress. Analyses rely on data collected among participants ages 18+ in the Chinese Immigrants in Raleigh-Durham (ChIRDU) study who completed surveys in 2018 and during the COVID-19 pandemic (July-September 2020). We utilize ordinary least squares regressions to examine associations of two types of COVID-related discrimination (measured by changes in perceptions of being feared by others and racism-related vigilance) and contemporaneous stressors (measured by general COVID-19-related stressors and acculturative stressors) with perceptions of stress by respondents' pre-pandemic reports of ethnic identity. Controlling for sociodemographic predictors and other stressors, racism-related vigilance is significantly associated with higher perceived stress for Chinese immigrants who identify as completely Chinese. For those who identify as at least partly American, new perceptions of being feared by others during the pandemic are significantly associated with higher perceived stress. Acculturative and COVID-related stressors are independently associated with higher perceived stress for both groups. These results suggest that COVID-related anti-Asian discrimination aggravates the psychological burden of multiple stressors in Chinese immigrants' lives by uniquely contributing to perceptions of stress alongside contemporaneous stressors. The results also highlight the heterogeneous mental health needs of Chinese immigrants and hold important implications for intervention development in the community studied here as well as in other Chinese communities in the US.

Using Social Networks to Sample Migrants and Study the Complexity of Contemporary Immigration: An Evaluation Study.

We test the effectiveness of a link-tracing sampling approach-network sampling with memory (NSM)-to recruit samples of rare immigrant populations with an application among Chinese immigrants in the Raleigh-Durham area of North Carolina. NSM uses the population network revealed by data from the survey to improve the efficiency of link-tracing sampling and has been shown to substantially reduce design effects in simulated sampling. Our goals are to (1) show that it is possible to recruit a probability sample of a locally rare immigrant group using NSM and achieve high response rates; (2) demonstrate the feasibility of the collection and benefits of new forms of network data that transcend kinship networks in existing surveys and can address unresolved questions about the role of social networks in migration decisions, the maintenance of transnationalism, and the process of social incorporation; and (3) test the accuracy of the NSM approach for recruiting immigrant samples by comparison with the American Community Survey. Our results indicate feasibility, high performance, cost-effectiveness, and accuracy of the NSM approach to sample immigrants for studies of local immigrant communities. This approach can also be extended to recruit multisite samples of immigrants at origin and destination.

Using Electronic Health Records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research.

Although local policies aimed at reducing childhood health inequities can benefit from local data, sample size constraints in population representative health surveys often prevent rigorous evaluations of child health disparities and health care patterns at local levels. Electronic Health Records (EHRs) offer a possible solution as they contain large amounts of information on pediatric patients within a health system. In this paper, we consider the suitability of using EHRs from a large health system to study local children's health by evaluating the extent to which the EHRs capture the county's child population. First, we compare the demographic characteristics of Duke University Health System pediatric patients who live in Durham County, NC (USA) to the child population estimates in the 2015-2019 American Community Survey. We then examine geographic variation in census tract rates of children captured in the EHR data and estimate negative binomial models to assess how tract characteristics are associated with these rates. We also perform these analyses for the subset of pediatric patients who have a well-child encounter. We find that the demographic characteristics of pediatric patients captured by the EHRs are similar to those of the county's child population. Although the county rate of children captured in the EHRs is high, there is variation across census tracts. On average, census tracts with higher concentrations of non-Hispanic Black residents have lower capture rates and tracts with higher concentrations of poverty have higher capture rates, with the poorest tracts showing the largest racial gap in rates of children captured by EHRs. Our findings suggest that EHRs from a large health system can be used to assess children's population health, but that EHR-based evaluations of children's health disparities and health care patterns should account for differences in who is captured by the EHRs based on census tract characteristics.

Parental Death and Mid-adulthood Depressive Symptoms: The Importance of Life Course Stage and Parent's Gender.

Traditional theories of grief suggest that individuals experience short-term increases in depressive symptoms following the death of a parent. However, growing evidence indicates that effects of parental bereavement may persist. Situating the short- and long-term effects of parental death within the life course perspective, we assess the combined influence of time since loss and life course stage at bereavement on mental health for maternal and paternal death. Using data from the National Longitudinal Study of Adolescent to Adult Health (N = 11,877) to examine biological parental death from childhood to mid-adulthood, we find that those who experience recent maternal or paternal death have heightened depressive symptoms. Furthermore, those who experience maternal death in childhood or paternal death in young adulthood exhibit long-term consequences for mental health. Our findings underscore the theoretical importance of early life course stages and parent's gender when determining whether depressive symptoms persist following parental bereavement.

Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?

A growing line of research underscores that sociodemographic factors may contribute to disparities in the impact of COVID-19. Further, stages of disease theory suggests that disparities may grow as the pandemic unfolds and more advantaged areas are better able to apply growing knowledge and mitigation strategies. In this paper, we focus on the role of county-level household overcrowding on disparities in COVID-19 mortality in U.S. counties. We examine this relationship across three theoretically important periods of the pandemic from April-October 2020, that mark both separate stages of community knowledge and national mortality levels. We find evidence that the percentage of overcrowded households is a stronger predictor of COVID-19 mortality during later periods of the pandemic. Moreover, despite a relationship between overcrowding and poverty at the county-level, overcrowding plays an independent role in predicting COVID-19 mortality. Our findings underscore that areas disadvantaged by overcrowding may be more vulnerable to the effects of COVID-19 and that this vulnerability may lead to changing disparities over time.