Changes in the Relationship Between Income and Life Expectancy Before and During the COVID-19 Pandemic, California, 2015-2021.

Importance: The COVID-19 pandemic caused a large decrease in US life expectancy in 2020, but whether a similar decrease occurred in 2021 and whether the relationship between income and life expectancy intensified during the pandemic are unclear. Objective: To measure changes in life expectancy in 2020 and 2021 and the relationship between income and life expectancy by race and ethnicity. Design, Setting, and Participants: Retrospective ecological analysis of deaths in California in 2015 to 2021 to calculate state- and census tract-level life expectancy. Tracts were grouped by median household income (MHI), obtained from the American Community Survey, and the slope of the life expectancy-income gradient was compared by year and by racial and ethnic composition. Exposures: California in 2015 to 2019 (before the COVID-19 pandemic) and 2020 to 2021 (during the COVID-19 pandemic). Main Outcomes and Measures: Life expectancy at birth. Results: California experienced 1 988 606 deaths during 2015 to 2021, including 654 887 in 2020 to 2021. State life expectancy declined from 81.40 years in 2019 to 79.20 years in 2020 and 78.37 years in 2021. MHI data were available for 7962 of 8057 census tracts (98.8%; n = 1 899 065 deaths). Mean MHI ranged from $21 279 to $232 261 between the lowest and highest percentiles. The slope of the relationship between life expectancy and MHI increased significantly, from 0.075 (95% CI, 0.07-0.08) years per percentile in 2019 to 0.103 (95% CI, 0.098-0.108; P < .001) years per percentile in 2020 and 0.107 (95% CI, 0.102-0.112; P < .001) years per percentile in 2021. The gap in life expectancy between the richest and poorest percentiles increased from 11.52 years in 2019 to 14.67 years in 2020 and 15.51 years in 2021. Among Hispanic and non-Hispanic Asian, Black, and White populations, life expectancy declined 5.74 years among the Hispanic population, 3.04 years among the non-Hispanic Asian population, 3.84 years among the non-Hispanic Black population, and 1.90 years among the non-Hispanic White population between 2019 and 2021. The income-life expectancy gradient in these groups increased significantly between 2019 and 2020 (0.038 [95% CI, 0.030-0.045; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI: 0.005-0.044; P = .02] years per percentile among Asian individuals; 0.015 [95% CI, 0.010-0.020; P < .001] years per percentile among Black individuals; and 0.011 [95% CI, 0.007-0.015; P < .001] years per percentile among White individuals) and between 2019 and 2021 (0.033 [95% CI, 0.026-0.040; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI, 0.010-0.038; P = .002] years among Asian individuals; 0.024 [95% CI, 0.011-0.037; P = .003] years per percentile among Black individuals; and 0.013 [95% CI, 0.008-0.018; P < .001] years per percentile among White individuals). The increase in the gradient was significantly greater among Hispanic vs White populations in 2020 and 2021 (P < .001 in both years) and among Black vs White populations in 2021 (P = .04). Conclusions and Relevance: This retrospective analysis of census tract-level income and mortality data in California from 2015 to 2021 demonstrated a decrease in life expectancy in both 2020 and 2021 and an increase in the life expectancy gap by income level relative to the prepandemic period that disproportionately affected some racial and ethnic minority populations. Inferences at the individual level are limited by the ecological nature of the study, and the generalizability of the findings outside of California are unknown.

Return to work and lost earnings after acute respiratory distress syndrome: a 5-year prospective, longitudinal study of long-term survivors.

BACKGROUND: Delayed return to work is common after acute respiratory distress syndrome (ARDS), but has undergone little detailed evaluation. We examined factors associated with the timing of return to work after ARDS, along with lost earnings and shifts in healthcare coverage. METHODS: Five-year, multisite prospective, longitudinal cohort study of 138 2-year ARDS survivors hospitalised between 2004 and 2007. Employment and healthcare coverage were collected via structured interview. Predictors of time to return to work were evaluated using Fine and Grey regression analysis. Lost earnings were estimated using Bureau of Labor Statistics data. RESULTS: Sixty-seven (49%) of the 138 2-year survivors were employed prior to ARDS. Among 64 5-year survivors, 20 (31%) never returned to work across 5-year follow-up. Predictors of delayed return to work (HR (95% CI)) included baseline Charlson Comorbidity Index (0.77 (0.59 to 0.99) per point; p=0.04), mechanical ventilation duration (0.67 (0.55 to 0.82) per day up to 5 days; p<0.001) and discharge to a healthcare facility (0.49 (0.26 to 0.93); p=0.03). Forty-nine of 64 (77%) 5-year survivors incurred lost earnings, with average (SD) losses ranging from US$38 354 (21,533) to US$43 510 (25,753) per person per year. Jobless, non-retired survivors experienced a 33% decrease in private health insurance and concomitant 37% rise in government-funded coverage. CONCLUSIONS: Across 5-year follow-up, nearly one-third of previously employed ARDS survivors never returned to work. Delayed return to work was associated with patient-related and intensive care unit/hospital-related factors, substantial lost earnings and a marked rise in government-funded healthcare coverage. These important consequences emphasise the need to design and evaluate vocation-based interventions to assist ARDS survivors return to work.

Joblessness and Lost Earnings after Acute Respiratory Distress Syndrome in a 1-Year National Multicenter Study.

RATIONALE: Following acute respiratory distress syndrome (ARDS), joblessness is common but poorly understood. OBJECTIVES: To evaluate the timing of return to work after ARDS, and associated risk factors, lost earnings, and changes in healthcare coverage Methods: Over 12-month longitudinal follow-up, ARDS survivors from 43 U.S. ARDSNet hospitals provided employment and healthcare coverage data via structured telephone interviews. Factors associated with the timing of return to work were assessed using Fine and Gray regression analysis. Lost earnings were estimated using Bureau of Labor Statistics data. MEASUREMENTS AND MAIN RESULTS: Of 922 consenting survivors, 386 (42%) were employed before ARDS (56% male; mean ± SD age, 45 ± 13 yr), with seven dying by 12-month follow-up. Of 379 previously employed 12-month survivors, 166 (44%) were jobless at 12-month follow-up. Accounting for competing risks of death and retirement, half of enrolled and previously employed survivors returned to work by 13 weeks after hospital discharge, with 68% ever returning by 12 months. Delays in return to work were associated with longer hospitalization and older age among nonwhite survivors. Over 12-month follow-up, 274 (71%) survivors accrued lost earnings, averaging $26,949 ± $22,447 (60% of pre-ARDS annual earnings). Jobless survivors experienced a 14% (95% confidence interval, 5-22%; P = 0.002) absolute decrease in private health insurance (from 44% pre-ARDS) and a 16% (95% confidence interval, 7-24%; P < 0.001) absolute increase in Medicare and Medicaid (from 33%). CONCLUSIONS: At 12 months after ARDS, nearly one-half of previously employed survivors were jobless. Post-ARDS joblessness is associated with readily identifiable patient and hospital variables and accompanied by substantial lost earnings and a shift toward government-funded healthcare coverage.

Lost Generations: Long-Term Effects of the COVID-19 Crisis on Job Losers and Labour Market Entrants, and Options for Policy.

This paper discusses the potential long-run effects of large-scale unemployment during the COVID-19 crisis in the labour market on vulnerable job losers and labour market entrants in the United States. The paper begins by contrasting measures of the scale of job loss during the crisis. These measures are paired with estimates from past recessions indicating that the costs of job loss and unemployment can reduce workers' earnings and raise their mortality for several decades. Focusing only on a subset of vulnerable job losers, the potential lifetime earnings losses from job loss related to the COVID-19 pandemic are predicted to be up to $2 trillion. Related losses in employment could imply a lasting reduction in the overall employment-population ratio. For these workers, losses in potential life years could be up to 24 million. Even at the low range, the resulting estimates are substantially larger than losses in potential life years from deaths directly due to COVID-19. New labour market entrants are at risk to suffer long-term losses in earnings and mortality as well. Based partly on experiences in other countries, the paper discusses potential reforms to short-time compensation programmes and unemployment insurance, which could help limit the short- and long-term harm from layoffs going forward.

Average Earnings and Long-Term Mortality: Evidence from Administrative Data.

In this paper we exploit a unique database that merges longitudinal earnings data on Pennsylvanian workers with national death records to study the detailed nature of the correlation between earnings and mortality. We find that the estimates typically reported in the literature, which are based on single years of earnings data, are likely to understate substantially the strength of the association between income and mortality. In particular, relative to a single year of earnings, the average of earnings over a six-year period predicts a 70 percent greater impact of income on mortality. In addition, controlling for the mean level of earnings over a period, we find that greater earnings volatility is associated with higher mortality. We also examine the lag structure of the relationship between earnings and mortality. We find that conditional on a small number of years of recent earning levels, there is little or no correlation between earnings levels in earlier years and current mortality. This runs counter to the interpretation of the earnings-mortality correlation that views workers as "buying health" by allocating a steady fraction of their earnings to the accumulation of a health stock. It is also inconsistent with interpretations of the earnings- mortality link emphasizing the correlation of both variables with an unobserved, time-invariant trait, such as the rate at which workers discount the future. We find that explaining the patterns of correlation appears to require a relatively complex theory that we leave to future research.

Unemployment Insurance and Disability Insurance in the Great Recession.

Social Security Disability Insurance (SSDI) awards rise during recessions. If marginal applicants are able to work but unable to find jobs, countercyclical Unemployment Insurance (UI) benefit extensions may reduce SSDI uptake. Exploiting UI extensions in the Great Recession as a source of variation, we find no indication that expiration of UI benefits causes SSDI applications and can rule out effects of meaningful magnitude. A supplementary analysis finds little overlap between the two programs' recipient populations: only 28% of SSDI awardees had any labor force attachment in the prior calendar year, and of those, only 4% received UI.