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Visiting multiple prescribers is a common method for obtaining prescription opioids for nonmedical use and has played an important role in fueling the United States opioid epidemic, leading to increased drug use disorder and overdose. Recent studies show that centrality of the bipartite network formed by prescription ties between patients and prescribers of opioids is a promising indicator for drug seeking. However, node prominence in bipartite networks is typically estimated with methods that do not fully account for the two-mode topology of the underlying network. Although several algorithms have been proposed recently to address this challenge, it is unclear how these algorithms perform on real-world networks. Here, we compare their performance in the context of identifying opioid drug seeking behaviors by applying them to massive bipartite networks of patients and providers extracted from insurance claims data. We find that two variants of bipartite centrality are significantly better predictors of subsequent opioid overdose than traditional centrality estimates. Moreover, we show that incorporating non-network attributes such as the potency of the opioid prescriptions into the measures can further improve their performance. These findings can be reproduced on different datasets. Our results demonstrate the potential of bipartiteness-aware indices for identifying patterns of high-risk behavior. [ABSTRACT FROM AUTHOR]

Background: The efficacy of testing and tracing programs to reduce COVID-19 transmission hinges not only on widespread access to testing, but also on the public's willingness to participate in them. To the extent that testing intentions are patterned by social determinants of health, this constitutes an understudied mechanism of disparities in COVID-19 morbidity and mortality. Design: Using data from a representative household probability sample, the Person to Person Health Interview Study (n = 935), sociodemographic, economic, and psychological determinants of testing considerations were evaluated across six domains: treatment affordability, ability to work if positive, hospital effectiveness, symptom severity, proximity to infected, and risk of transmitting to others. Results: Findings demonstrated significant differences in testing motivations across race/ethnicity, education level, socioeconomic status, and worry about self and loved ones. Notably, Black (p<0.01) and Latino (p<0.05) respondents and those experiencing financial strain (p<0.001) were disproportionately likely to indicate that resource factors would influence their decision to get tested. Desire to reduce transmission and concern about proximity to the infected were reported among those who expressed COVID-19 worries (p<0.001). Conclusion: Public health efforts to combat the COVID-19 pandemic must address social, economic, and psychological factors that enable and constrain individual behavior. Increasing access to preventative interventions and technologies, including vaccines, is unlikely to markedly reduce morbidity and mortality without effective messaging and economic support to improve uptake in vulnerable populations. [ABSTRACT FROM AUTHOR]

Crises lay bare the social fault lines of society. In the United States, race, gender, age, and education have affected vulnerability to COVID-19 infection. Yet, consequences likely extend far beyond morbidity and mortality. Temporarily closing the economy sent shock waves through communities, raising the possibility that social inequities, preexisting and current, have weakened economic resiliency and reinforced disadvantage, especially among groups most devastated by the Great Recession. We address pandemic precarity, or risk for material and financial insecurity, in Indiana, where manufacturing loss is high, metro areas ranked among the hardest hit by the Great Recession nationally, and health indicators stand in the bottom quintile. Using longitudinal data (n = 994) from the Person to Person Health Interview Study, fielded in 2019-2020 and again during Indiana's initial stay-at-home order, we provide a representative, probability-based assessment of adverse economic outcomes of the pandemic. Survey-weighted multivariate regressions, controlling for preexisting inequality, find Black adults over 3 times as likely as Whites to report food insecurity, being laid off, or being unemployed. Residents without a college degree are twice as likely to report food insecurity (compared to some college), while those not completing high school (compared to bachelor's degree) are 4 times as likely to do so. Younger adults and women were also more likely to report economic hardships. Together, the results support contentions of a Matthew Effect, where pandemic precarity disproportionately affects historically disadvantaged groups, widening inequality. Strategically deployed relief efforts and longer-term policy reforms are needed to challenge the perennial and unequal impact of disasters. [ABSTRACT FROM AUTHOR]

Background: Economic inequality in the United States is extreme, but little is known about the national origin of affluent households. Households in the top one percent by total wealth own vastly disproportionate quantities of household assets and have correspondingly high levels of economic, social, and political influence. The overrepresentation of white natives (i.e., those born in the U.S.) among high-wealth households is well-documented, but changing migration dynamics suggest that a growing portion of top households may be immigrants. Methods: Because no single survey dataset contains top wealth holders and data about country of origin, this paper uses two publicly-available data sets: the Survey of Consumer Finances (SCF) and the Survey of Income and Program Participation (SIPP). Multiple imputation is used to impute country of birth from the SIPP into the SCF. Descriptive statistics are used to demonstrate reliability of the method, to estimate the prevalence of immigrants among top wealth holders, and to document patterns of asset ownership among affluent immigrants. Results: Significant numbers of top wealth holders who are usually classified as white natives may be immigrants. Many top wealth holders appear to be European and Canadian immigrants, and increasing numbers of top wealth holders are likely from Asia and Latin America as well. Results suggest that of those in the top one percent of wealth holders, approximately 3% are European and Canadian immigrants, .5% are from Mexico or Cuban, and 1.7% are from Asia (especially Hong Kong, Taiwan, Mainland China, and India). Ownership of key assets varies considerably across affluent immigrant groups. Conclusion: Although the percentage of top wealth holders who are immigrants is relatively small, these percentages represent large numbers of households with considerable resources and corresponding social and political influence. Evidence that the propensity to allocate wealth to real and financial assets varies across immigrant groups suggests that wealth ownership is more global than previous research suggests and that immigrant groups are likely to become more prevalent in top wealth positions in the U.S. As the representation of immigrants in top wealth positions grows, their economic, social, and political influence is likely to increase as well. [ABSTRACT FROM AUTHOR]

Background: Physicians do not prescribe opioid analgesics for pain treatment equally across groups, and such disparities may pose significant public health concerns. Although research suggests that institutional constraints and cultural stereotypes influence doctors' treatment of pain, prior quantitative evidence is mixed. The objective of this secondary analysis is therefore to clarify which institutional constraints and patient demographics bias provider prescribing of opioid analgesics.Methods: We used electronic medical record data from an emergency department of a large U.S hospital during years 2008-2014. We ran multi-level logistic regression models to estimate factors associated with providing an opioid prescription during a given visit while controlling for ICD-9 diagnosis codes and between-patient heterogeneity.Results: A total of 180,829 patient visits for 63,513 unique patients were recorded during the period of analysis. Overall, providers were significantly less likely to prescribe opioids to the same individual patient when the visit occurred during higher rates of emergency department crowding, later times of day, earlier in the week, later years in our sample, and when the patient had received fewer previous opioid prescriptions. Across all patients, providers were significantly more likely to prescribe opioids to patients who were middle-aged, white, and married. We found no bias towards women and no interaction effects between race and crowding or between race and sex.Conclusions: Providers tend to prescribe fewer opioids during constrained diagnostic situations and undertreat pain for patients from high-risk and marginalized demographic groups. Potential harms resulting from previous treatment decisions may accumulate by informing future treatment decisions. [ABSTRACT FROM AUTHOR]

Chinese immigrants are a diverse and growing group whose members provide a unique opportunity to examine within-immigrant group differences in adaptation. In this paper, we move beyond thinking of national-origin groups as homogenous and study variation among Chinese immigrants in wealth ownership, a critical indicator of adaptation that attracts relatively little attention in the immigration literature. We develop an analytical approach that considers national origin, tenure in the U.S., and age to examine heterogeneity in economic adaptation among the immigrant generation. Our results show that variations among Chinese immigrants explain within-group differences in net worth, asset ownership, and debt. These differences also account for important variation between Chinese immigrants, natives, and other immigrant groups and provide important, new insight into the processes that lead to immigrant adaptation and long-term class stability. [ABSTRACT FROM AUTHOR]