ArticleSSM - population health2023
Potential gaps in income support policies for those in poor health: The case of the earned income tax credit-A cross sectional analysis.
Article in SSM - population health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- The Effect of the Earned Income Tax Credit on Physical and Mental health-Results from the Atlanta Paycheck Plus Experiment.The Milbank quarterly · 2024Trial
- Conducting Actionable Economic Policy Research to Address Community Violence Inequities.Prevention science : the official journal of the Society for Prevention Research · 2026Article
- The fundamental importance of social insurance for health equity.Health affairs scholar · 2025Article
- Reassessing the non-linear causal link between long-duration commuting and self-rated health: do behavioral preferences and built environment matter?Frontiers in public health · 2024Article
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Authors and funding
3 authors.
Funding
Abstract
Background: The federal Earned Income Tax Credit (EITC) is the primary income support program for low-income workers in the U.S., but its design may hinder its effectiveness when poor health limits, but does not preclude, work. Methods: Cross-sectional analysis of nationally-representative U.S. Census Current Population Survey (CPS) data covering 2019. Working-age adults eligible to receive federal EITC were included in this study. Poor health, as indicated by self-report of at least one problem with hearing, vision, cognitive function, mobility, dressing and bathing, or independence, was the exposure. The main outcome was federal EITC benefit category, categorized as no benefit, phase-in (income too low for the maximum benefit), plateau (maximum benefit), phase-out (income above threshold for maximum benefit), or earnings too high to receive any benefit. We estimated EITC benefit category probabilities by health status using multinomial logistic regression. We further examined whether other government benefits provided additional income support to those in poor health. Results: 41,659 participants (representing 87.1 million individuals) were included. 2,724 participants (representing 5.6 million individuals) reported poor health. In analyses standardized over age, gender, race, and ethnicity, those in poor health, compared with those not in poor health, were more likely to be in the no benefit (2.40% vs. 0.30%, risk difference 2.10 percentage points [95%CI 1.75 to 2.46 percentage points]), and phase-in (9.28% vs. 2.74%, risk difference 6.54 percentage points [95%CI 5.82 to 7.26 percentage points]) categories. Differences in resources by health status persisted even after accounting for other government benefits. Conclusions: EITC program design creates an important gap in income support for those for whom poor health limits work, which is not closed by other programs. Filling this gap is an important public health goal.
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