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Objective: This study examines how overwork and traditional household specialization—defined as households with one dedicated female homemaker and one dedicated male breadwinner—are associated with wealth across socioeconomic strata. Background: Although overwork and household specialization are clearly associated with income, less is known about how these behaviors affect household wealth. Household wealth is only moderately correlated with household income and is influenced by many factors that do not affect income, suggesting that overwork and specialization have different associations with wealth than with income. Moreover, because wealth is so unevenly distributed, overwork and specialization likely have different associations with wealth across socioeconomic strata. Method: With data from the Survey of Consumer Finances, a nationally representative survey of households that includes an oversample of high‐wealth households, the authors estimate unconditional quantile regression models to investigate how overwork and household specialization are associated with household wealth across socioeconomic strata and over time. Results: Overwork has the greatest absolute benefits at the top of the wealth distribution but the greatest relative benefits in lower portions of the wealth distribution. Specialization yields distinct advantages for high‐wealth households that have grown over time, whereas specialization comes with trade‐offs for low‐wealth households that outweigh its benefits. Conclusion: The financial trade‐offs associated with overwork and specialization vary considerably across the wealth distribution. Contrary to findings in income‐based research, overwork premiums appear most crucial to the financial well‐being of underprivileged households, whereas specialization premiums are evident only for the economic elite. [ABSTRACT FROM AUTHOR]

Background and aims: Prescription drug‐seeking (PDS) from multiple prescribers is a primary means of obtaining prescription opioids; however, PDS behavior has probably evolved in response to policy shifts, and there is little agreement about how to operationalize it. We systematically compared the performance of traditional and novel PDS indicators. Design Longitudinal study using a de‐identified commercial claims database. Setting: United States, 2009–18. Participants: A total of 318 million provider visits from 21.5 million opioid‐prescribed patients. Measurements We applied binary classification and generalized linear models to compare predictive accuracy and average marginal effect size predicting future opioid use disorder (OUD), overdose and high morphine milligram equivalents (MME). We compared traditional indicators of PDS to a network centrality measure, PageRank, that reflects the prominence of patients in a co‐prescribing network. Analyses used the same data and adjusted for patient demographics, region, SES, diagnoses and health services. Findings The predictive accuracy of a widely used traditional measure (N + unique doctors and N + unique pharmacies in 90 days) on OUD, overdose and MME decreased between 2009 and 2018, and performed no better than chance (50% accuracy) after 2015. Binarized PageRank measures however exhibited higher predictive accuracy than the traditional binary measures throughout 2009‐2018. Continuous indicators of PDS performed better than binary thresholds, with days of Rx performing best overall with 77–93% predictive accuracy. For example, days of Rx had the highest average marginal effects on overdose and OUD: a 1 standard deviation increase in days of Rx was associated with a 6–8% [confidence intervals (CIs) = 0.058–0.061 and 0.078–0.082] increase in the probability of overdose and a 4–5% (CIs = 0.038–0.043 and 0.047–0.053) increase in the probability of OUD. PageRank performed nearly as well or better than traditional indicators of PDS, with predictive performance increasing after 2016. Conclusions: In the United States, network‐based measures appear to have increasing promise for identifying prescription opioid drug‐seeking behavior, while indicators based on quantity of providers or pharmacies appear to have decreasing utility. [ABSTRACT FROM AUTHOR]