Low-income Households Research Articles

Rental Market Risk and Radical Right Support

A growing literature examines how economic threat affects support for anti-establishment parties. While most existing work focuses on transforming labor markets as a source of anxiety, we advance the literature by studying changes in urban development and rent price appreciation. Our analysis examines the case of Germany, the country with the highest share of rental housing in the European Union. Combining individual-level geo-referenced panel data with a longitudinal data set on the cost of rental housing at the postcode level, we demonstrate that rising local rent levels increase support for radical right parties among long-term residents with lower household incomes, in particular in urban areas. Our results suggest that urban development, not unlike labor market transformation, represents an important and so far neglected source of economic insecurity and social concern with important political implications.

Green economy for sustainable financial inclusion among low-income households in achieving vision 2030 and economic growth in Bangladesh

Several studies have explored green economy and the needs for improvement on the standard of living among low-income families or households in many developing countries including Bangladesh. Similarly, there is an emphasis on economic growth and vision 2030 is regarded stressed. Nonetheless, there is less attention in exploring green economy in propelling sustainable financial inclusion among low-income families and households in Bangladesh in order to attain vision 2030 and overall economic growth. The primary objective is to explore green economy in fostering sustainable financial inclusion among low-income families and households in Bangladesh in enhancing economic growth and vision 2030 in Bangladesh. Content Analysis (CA) and systematic literature review (SLR) as an integral part of qualitative research. Secondary data were gathered through different sources such as: Web of Science (WOS), related journals, published references, research papers, library sources and reports. The results indicated that poverty is a prime challenge impeding sustainable financial inclusion among low-income families and households in Bangladesh. The study has further established the potential of green economy in improving well-beings and social fairness in fostering sustainable and inclusive finance among families or households with low-income in the country. The paper also highlighted the necessity of implementing policy relating to vision 2030 by enhancing sustainable and inclusive finance among low-income households in particular and overall economic growth in the country in general. In conclusion, it has been reiterated that green economy has been a mechanism for achieving sustainable development in general and poverty eradication among low-income households in Bangladesh. It is therefore suggested that the government and economic policymakers should provide enabling environment for improving green economy among low-income households in achieving Vision 2030 and overall economic growth in the country.

Significant Disparities in Hepatocellular Carcinoma Outcomes by Race/Ethnicity and Sociodemographic Factors.

Hepatocellular carcinoma (HCC) disproportionately affects racial/ethnic minorities. We evaluated the impact of income and geography on racial/ethnic disparities across the HCC care cascade in the U.S. Using National Cancer Institute registry data spanning 2000-2020, adults with HCC were evaluated to determine race/ethnicity-specific differences in tumor stage at diagnosis, delays and gaps in treatment, and survival. Adjusted regression models evaluated predictors of HCC outcomes. Among 112,389 adults with HCC, cohort characteristics were as follows: 49.8% non-Hispanic White [NHW], 12.0% African American, 20.5% Hispanic, 16.5% Asian/Pacific Islander, 1.1% American Indian/Alaska Native. Compared to NHW patients, AA patients had lower odds of localized-stage HCC at diagnosis (aOR, 0.84), lower odds of HCC treatment receipt (aOR, 0.77), greater odds of treatment delays (aOR, 1.12), and significantly greater risk of death (aHR, 1.10). Compared to NHW from large-metro areas, AA from large metro areas had 8% higher mortality risk (aHR, 1.08) whereas AA from small-medium metro areas had 17% higher mortality risk (aHR, 1.17) (all P<0.05). Among a population-based cohort of U.S. adults with HCC, significant race/ethnicity-specific disparities across the HCC care continuum were observed. Lower household income and more rural geography among racial/ethnic minorities are also associated with disparities in HCC outcomes, particularly among AA patients. Our study shows that lower income and less urban/more rural geography among racial/ethnic minorities is also associated with disparities in HCC outcomes, particularly among AA patients with HCC. This contextualizes the complex relationship between sociodemographic factors and HCC outcomes through an intersectional lens.

Safety net of last resort: the evolution, determinants and adequacy of Dutch minimum income support

Dutch minimum income support provides a generous social safety net compared to most other European Union (EU) member states but has not been able to structurally reduce poverty. This inadequacy did not come about overnight but is the result of six decades of policy decisions. In this article, we aim to explain the current income shortfalls of people on minimum income support by studying the historical evolution and determinants of the Dutch minimum income scheme. We demonstrate that it has on average maintained a constant level of purchasing power over the period 1980–2023. This fits well with the notion that poverty is of an absolute nature, and that a social minimum should guarantee a stable level of purchasing power. It fits less well with relative or contextual approaches to poverty, and the view that a social minimum should adapt to changing norms when a society grows richer. To uncover the reasons for the growing gap between general prosperity and the minimum income benefit, we decompose it into smaller gaps by illustrating the evolution of prosperity, labour productivity, gross wages, collectively agreed wages, the minimum wage and the minimum income benefit. We show that each of these gaps matters and argue that this provides valuable insights into the structural, institutional and political forces that have shaped Dutch minimum income support since its introduction in 1965. Based on these results, we argue against the current ad hoc measures of the government and in favour of a more structural approach to supporting low-income households.

Consumption Dynamics in Mixed-Income Neighborhoods with Connected Households

AbstractWe investigate the dynamics of household consumption in a setting in which households are connected across income classes. Low- and high-income households form preferences endogenously, conditional on their own and their neighbor’s past consumption. The modeling effort relies on a stochastic dynamic model of interdependent consumer choice in which the demand for commodities evolves according to a non-linear difference equation with stochastic initial states. The analysis targets a region of the parameter space that corresponds to salient features of a mixed-income neighborhood in which households are connected. Standard methods of asymptotic analysis of dynamic systems (e.g. bifurcation analysis) are combined with numerical simulation, statistical modelling of extreme events and statistical estimation techniques to investigate the dynamics. From the mathematical point of view, our analysis reveals the existence of intricate bifurcation pattern, coexistence of multiple attractors, complex basins and long transients. The essential economic finding states that key features of household consumption vary significantly in the influence the high-income households exert on the preference formation of the low-income households. In particular, we find that the prevalence of long transients, i.e. long waiting times before convergence to asymptotic states occur, is inversely related to the type of connectedness considered. We demonstrate that the dynamics of the consumption trajectory evolving over an extended time period before it settles on long-run simple consumption pattern, may not at all be captured by an asymptotic state. Thus, policies targeting the economies in mixed-income neighborhoods that are solely based on information about long-run consumption states, might trigger unwanted, unanticipated effects.

The challenge of making EVs just affordable enough: Assessing the impact of subsidies on equity and emission reduction in Ireland

Governments support the switch to electric vehicles (EVs) through subsidies and other incentives, as this is expected to help meet climate targets. This research examines the affordability of EVs for Irish households, focusing on equity implications and the impact of affordability on achieving decarbonisation goals. Affordability is estimated for eight scenarios, considering both current and reduced EV prices, and assessed across Ireland. The research finds that flat-rate subsidies do not adequately support lower-income households, impede EV adoption, and could jeopardise the achievement of emission reduction targets. Need-based subsidies would ensure more inclusive EV uptake. If current prices are considered, the target for the number of EVs on the road by 2030 can be met only with the purchase of small-sized EVs. This suggests that achieving EV targets is unlikely without promoting smaller vehicles. The current €3500 EV grant may be insufficient for many households without extended loan terms. Therefore, differentiated subsidies based on income and household size are recommended to increase EV adoption. Households in remote rural areas, where forced car ownership is high, require higher subsidies. In contrast, urban areas could receive lower subsidies to promote the use of more sustainable transport modes, such as cycling, shared mobility, and public transport.

Return-to-hometown entrepreneurship and employment of low-income households: Evidence from national returned entrepreneurial enterprise data of China

Employment is widely regarded as the most effective approach for eradicating poverty among low-income groups and preventing them from returning to poverty. Using national returned entrepreneurial enterprise data of China, this study empirically analyzes how “return-to-hometown entrepreneurship (RHE)” achieves antipoverty through a mediation effect model that incorporates moderating effects. Our findings reveal that: (1) RHE considerably enhances employment in low-income households. In particular, annual income and enterprise investment scale have a substantial positive impact on boosting the employment of low-income households. (2) Development- and value-oriented enterprises boost employment of low-income households more than survival-oriented enterprises. (3) The mechanism analysis indicates that entrepreneurship training plays a positive moderating role between the income of enterprises and the number of employed low-income households. Tax relief, loan guarantees, and industrial support policies have played multimediating roles in achieving antipoverty by RHE. These findings indicate that an effective interface between poverty alleviation and rural revitalization requires the government to attract additional high-quality RHE enterprises and actively fulfill its important institutional role in entrepreneurial training and various return-to-hometown entrepreneurial support policies.

Heterogeneity of the Association between Obesity and COVID-19 Mortality and the Roles of Policy Interventions: U.S. National-Level Analysis

This article examines the heterogeneity of the association between obesity and COVID-19 mortality across various dimensions, including COVID vaccination rates, mask mandates, gathering restrictions, and household income. Using multivariate regression analysis on U.S. county-level data over 2020-2021, we found that county-level adult obesity rates were positively associated with COVID death rates. Our results suggest that on average, a 10-percentage-point decrease in adult obesity rate is associated with a decrease in COVID deaths by 4.79 to 5.98 percent in the United States. Considering that the average adult obesity rate in the U.S. is higher than the global average, this finding may explain why deaths due to COVID were disproportionately large in the U.S. In addition, we found that association between obesity and COVID death rate is much more pronounced in groups with low vaccination rates, weak mask mandate, loose gathering restriction, or low household income, indicating the importance of COVID response policies and income to obese people facing a pandemic. Our results contribute to policy discussions surrounding preparation for COVID like pandemics. Food policies and health promotion strategies that encourage physical well-being to reduce obesity prevalence may help reduce mortality in future pandemics.

Climate Crisis on Energy Bills: Who Bears the Greater Burden of Extreme Weather Events?

The increasing frequency of extreme weather events driven by global climate change poses a critical threat to energy system vulnerability and household energy security. Using meteorological data from NOAA and Chinese weather stations (2012-2022), this study examines the impact of extreme climate risks on household energy poverty. Our findings reveal two significant transmission channels: infrastructure disruption and price fluctuation. Extreme weather events compromise energy infrastructure stability and cause supply interruptions, while temperature extremes trigger energy price volatility and increase household expenditure burdens. We further find that regions with weak infrastructure, areas prone to natural disasters, and low-income households are particularly vulnerable to these impacts. These findings suggest that climate change may exacerbate social inequality through energy poverty channels.

Affordable energy-saving switch control system for homes with disabled persons

The need for energy conservation has become increasingly urgent in today's world, especially as energy costs continue to rise and the demand for sustainable living grows. For persons with physical disabilities, simple tasks like turning light switches on and off can be challenging, resulting in higher energy usage, increased electricity bills, and increased physical strain. Existing solutions often prioritize energy efficiency but overlook affordability and accessibility, making them impractical for low-income households. To address these issues, this paper proposes an affordable automated energy-saving lighting switch control system using Arduino Uno, ultrasonic sensors for human presence detection, and a relay to control lighting. A person-counter mechanism ensures accurate operation based on room occupancy. Experimental results shows that the proposed system achieves 100% accuracy in detecting human presence in a room, effectively reducing energy consumption from 0.4 kWh to 0.2 kWh per day, which corresponds to 50% energy savings. Additionally, it is 42.41% less expensive than the most affordable system compared in the paper. These findings underscore the system’s potential to offer an affordable, accessible, and energy-efficient solution that enhances the convenience and comfort of disabled persons while contributing to energy conservation efforts.

Inequalities in accessibility to daily opportunities in the metropolitan region of Belo Horizonte (Brazil)

Despite the historical core-periphery urbanization pattern marked by profound inequalities in Latin American cities, the emergence of new suburban structures may introduce more complex dynamics of accessibility. In this study, we conduct a novel investigation into inequalities in accessibility to non-work urban opportunities in the Metropolitan Region of Belo Horizonte (MRBH), utilizing a combined analysis of a cumulative opportunity accessibility indicator and population distribution to assess both social and spatial discrepancies. The findings reveal that low-income households experience significantly lower accessibility to urban opportunities, while the development of new suburban structures results in high accessibility levels in high-income neighborhoods. These results highlight two contrasting processes of segregation: low-income groups being displaced to distant peripheral areas with limited accessibility, while high-income groups settling in low-density residential developments with abundant motorized accessibility to nearby opportunities.

The impact of rural human capital on household energy consumption structure: Evidence from Shaanxi Province in China

The structure of rural household energy consumption is crucial for rural residents' living standards and quality of life, constituting an integral component of energy transition and promoting Chinese-style modernization. Meanwhile, rural human capital is a prerequisite for agricultural and rural modernization. Drawing on survey data from 791 households in Shaanxi Province, this study empirically examines the impact and mechanisms of human capital on the household energy consumption structure with the ordinary least square (OLS) model and instrumental variable (IV) method. The findings indicate that human capital significantly reduces traditional energy consumption while increasing the adoption of transitional and advanced energy. This conclusion remains robust after rigorous testing. Mechanism analysis reveals that human capital facilitates the shift from traditional to transitional and advanced energy by enhancing purchasing power, environmental awareness, and the frequency of energy-saving technology usage within households. Further analysis demonstrates that higher levels of human capital correlate with a greater likelihood of households transitioning from traditional energy to transitional and advanced energy. Particularly, households with a high school education exhibit a significant increase in the consumption of transitional and advanced energy while notably reducing traditional energy consumption. Moreover, compared to low-income households, human capital has a significantly positive effect on increasing the adoption of advanced energy in high-income households. Hence, prioritizing investment in rural education, providing more educational resources, improving school facilities, and implementing incentive policies to emphasize education within households are recommended strategies to enhance rural residents' human capitals. This, in turn, facilitates their adoption of transitional and advanced energy, reducing dependence on traditional energy.

Income Changes and Depression Status Following the Impact of Household Income Levels During the COVID-19 Period

Objectives: This study investigated income changes and depressive symptoms that occurred following the impact of household income levels during the COVID-19 period using the 2021 Community Health Survey. Methods: A survey was conducted on 185,145 adults aged 19 and older, who responded that the change in household income compared to before the COVID-19 pandemic (January 2020) as “decreased” or “unchanged.” As for the dependent variables, the case was considered depressive if at least one of the following criteria was met: anxiety/depression on EQ-5D, having depression experience, depression using the PHQ-9 score (0-4 points: Not depressed. More than 5 points: Depression), or having suicidal thoughts. The independent variables were defined as quartiles by dividing household income changes during the COVID-19 and annual household income by the number of household members, and the confounding variables were defined as general characteristics, income, health behavior, and status. Results: As the results, the group whose household income decreased during the COVID-19 period was 1.34 times more likely to suffer from depression than the unchanged household income group. In addition, it was confirmed that the possibility of depression increased 1.19 times as the household income level went to the low-income group by 1 quartile compared to the 3rd and 4th quartiles. Conclusions: In conclusion, this study, which consists of a cross-sectional survey, has limitations as it can reveal causal relationships, but overall, depression was higher in people with lower household income, and moreover, the more the income decreased, there were more cases of individuals reporting depressive symptoms. Therefore, in the future, in the event of a new infectious disease outbreak, such as COVID-19, careful national attention is needed from the public health perspective of each household income group, such as supporting essential goods for low-income families and developing mental health programs.

Uneven Burdens: The Intersection of Brownfields, Pollution, and Socioeconomic Disparities in New Jersey, USA

Brownfields, abandoned or underutilized lands having the potential for contamination due to industrial activities, pose health risks to nearby residents and raise environmental justice (EJ) concerns. This study examines the relationship between brownfield distribution and socioeconomic factors in New Jersey, a state with over 700 brownfield sites, using correlation, spatial autoregression, and instrumental variable regression methods. Results show that brownfields are associated with higher combined EJ stressors, indicating compounding environmental pollution and health risks in affected areas. Brownfields are disproportionately correlated with lower household income, higher rates of uninsured individuals, lower educational attainment, and a greater percentage of people of color. When accounting for spatial autocorrelation, relationships between income, education, and brownfield distributions are reduced, reflecting New Jersey’s historical, environmental, and social contexts. Overall, the presence of people of color maintains the strongest association with brownfield distribution. This study highlights ongoing EJ challenges faced by disadvantaged groups and emphasizes the need for targeted mitigation measures to enhance sustainability and equity. New Jersey serves as a critical case study given its ethnic diversity, growing urban population, and status as the state with the highest population density in the United States, illustrating broader trends of disproportionate exposure to environmental pollution among marginalized communities.

Climate action and social equity: Mitigation strategies and carbon credits

Carbon taxes are a critical tool in global efforts to reduce greenhouse gas emissions, but they often have regressive effects, disproportionately burdening low-income households. This study examines the economic impact of carbon taxes on different income groups, with a focus on the regressive nature of these policies. Low-income households, which typically spend a higher percentage of their income on energy and carbon-intensive goods, are more adversely affected by carbon taxes. This analysis explores potential mitigation strategies, such as rebates, targeted subsidies, and income-based tax adjustments, to offset these regressive effects. Additionally, the study investigates the role of carbon credits in income distribution, analyzing how the allocation and trading of credits can influence social equity. The research also considers the broader implications of carbon taxes and credits on income distribution, highlighting the need for policies that balance environmental objectives with social equity. By examining the intersection of carbon pricing mechanisms and income inequality, this study provides insights into how policymakers can design carbon taxes and credits that minimize regressive impacts while promoting fair and equitable climate action. The findings underscore the importance of integrating social equity considerations into carbon pricing strategies to ensure that climate policies contribute to sustainable and inclusive economic growth.

Analyzing economic inflation's impact on food security and accessibility through econometric modeling

This study investigates the impact of economic inflation on food security and accessibility through the development of an econometric modeling approach. As inflation rates rise, the purchasing power of consumers diminishes, leading to increased food prices and potentially exacerbating food insecurity. This research aims to quantify the relationship between inflation and food security indicators, such as availability, access, utilization, and stability of food supplies. By employing time-series data and econometric techniques, the model captures the dynamic interactions between inflation rates, food prices, and socioeconomic factors affecting food security. The model incorporates key variables, including consumer price index (CPI), food inflation, income levels, and unemployment rates, to analyze their collective impact on food security across different demographics. The findings indicate that rising inflation significantly correlates with higher food prices, disproportionately affecting low-income households and vulnerable populations. This relationship highlights the necessity of understanding inflation's broader implications on food accessibility, especially in regions where food security is already a pressing issue. Future research directions are proposed, focusing on policy interventions aimed at stabilizing food prices and enhancing food security. Potential strategies include price controls, subsidies for staple foods, and targeted social safety nets for low-income households. Additionally, the study suggests further examination of supply chain factors contributing to food price volatility, such as transportation costs and global market dynamics, which can exacerbate inflation's effects on food security. This research contributes to the literature on food security by providing empirical evidence of inflation's impact on food accessibility and identifying critical areas for policy intervention. By addressing the complex interplay between inflation and food security, stakeholders, including policymakers and food industry leaders, can develop informed strategies to mitigate adverse effects and promote food security in inflationary environments.

Family income does not necessarily lead to a holistic e-learning experience during COVID-19: a study in Sri Lanka

The COVID-19 outbreak caused a disruption of the conventional education system worldwide. This resulted in a shift towards online mode of delivery. This study analyzed the pandemic’s effect on the education of students from diverse socioeconomic groups in Sri Lanka. The required data for this study was collected through a nation-wide field survey, covering 3020 households. The factor analysis (FA) performed identified seven significant factors. Thereafter, K-means and spectral clustering were used to cluster the population in order to identify the socioeconomic groups that were impacted in a similar manner. This resulted in the identification of three clusters whose demographics and relationship to the extracted factors were extensively analyzed and interpreted. The study concluded that students in high-income households were more emotionally affected, whereas students in low-income households were mostly affected by a lack of resources. The study also concluded that students from mid-income households were the least affected emotionally.

Spatial effects of ecological cognition on firewood collection by households in protected areas: An analysis based on the giant panda nature reserves

The issues of unbalanced and inadequate energy development in rural China remain prominent, particularly in areas rich in natural resources, such as nature reserves, where households still tend to rely on traditional energy utilization modes. On one hand, the traditional use of firewood for energy results in low energy efficiency and indoor air pollution; On the other hand, it exacerbates problems such as habitat degradation for wildlife and environmental collapse. Although previous studies have explored rural energy source utilization from varies of aspects, there are still limitations in examining the impact of ecological cognition on household behaviors from a spatial correlation perspective. This study conducts a field survey of rural households in the giant panda nature reserves in Sichuan and Shaanxi Provinces to explore the impact of ecological cognition on rural households' firewood collection behaviors. By incorporating a spatial weight matrix, the study further analyzes the spatial spillover effects and the spatial heterogeneity of ecological cognition on rural households' firewood collection. The results show that: (1) ecological cognition significantly reduces firewood collection behaviors; (2) household income also decreases the consumption of firewood energy; (3) ecological cognition exhibits spatial spillover effects on rural households' firewood collection, indicating that household ecological cognition can impact surrounding households' ecological cognition and indirectly affect their firewood collection behaviors; and (4) significant spatial heterogeneity exists inside and outside the protected area. Ecological cognition significantly influences the firewood utilization of rural households within protected areas through spatial spillover effects, whereas its impact outside the protected areas is minimal. Strengthening forest ecological education to further raise ecological awareness, focusing on low-income households to provide energy subsidies, and utilizing the spatial spillover effects to enhance information dissemination channels are recommended for policy implications.

Mobility changes following COVID-19 stay-at-home policies varied by socioeconomic measures: An observational study in Ontario, Canada.

In Canada, lower income households and essential workers were disproportionately at risk of SARS-CoV-2. Early in the pandemic, stay-at-home restriction policies were used to limit virus transmission. There remains an evidence gap in how changes in mobility, in response to the policies, varied across socioeconomic measures in Canada. The study objective was to describe the variability in mobility change to two restrictions, by neighborhood-level income and by proportion essential workers across five regions in Ontario, Canada. The first restriction was implemented on March 17, 2020 in all five regions; and the second restriction was implemented in November 23, 2020 in two of the regions. Using cell-phone mobility data aggregated to the census tract, we compared the average mobility (% of devices that travelled outside their "primary location") three weeks before and after each restriction. We defined the adjusted mobility change via pre-restriction mobility subtracted from post-restriction, adjusted for 2019 levels. We used difference-in-differences analysis to quantify effect modification of the second restriction's effect by socioeconomic measures. With the first restriction, crude mobility fell from 77.7% to 41.6% across the five regions. The adjusted mobility change to the first restriction was largest in the highest-income neighborhoods (-43.3% versus -38.4%) and in neighborhoods with the fewest essential workers (-44.5% versus -37.6%). The overall adjusted mobility change to the second restriction was small: -0.96% (95% confidence intervals, -1.53 to -0.38%). However, there was evidence of effect modification by socioeconomic measures (less pronounced decrease in lower-income neighborhoods and more essential workers). The findings suggest a temporal saturation effect of restrictions over subsequent waves, and a saturation effect by income and occupation, leading to prevention gaps across populations by socioeconomic measures. Findings highlight the need for tailored approaches at the intersections of income and occupation when addressing epidemics of novel and resurging respiratory pathogens.

Outpatient Physical Therapy Attendance by Older Adults After Emergency Department Discharge was a Predictor for Lower 30-Day Revisits-But Demographic Factors Affected Attendance.

Given the high risk of functional loss and revisits among older adults presenting to the emergency department (ED), there is a need to understand how post-ED discharge outpatient physical therapy affects outcomes. This study sought to examine patient demographics and their association with outpatient physical therapy utilization after ED discharge and physical therapy attendance with 30-day ED revisits among older adults discharged to home. In this retrospective cohort study, we analyzed data from 1395 older adults (65years old and older) who had a referral to outpatient physical therapy upon discharge from 15 EDs between January 2021 and December 2022. Descriptive statistics and multivariate logistic regression were used to evaluate the likelihood of attending outpatient physical therapy and the odds of a 30-day ED revisit. Of the sample, 39.3% attended outpatient physical therapy. Older adults in the first and second neighborhood income quintile had a 51% lower odds of attending outpatient physical therapy than those in the fourth quintile. Patients with a diagnosis of vertigo had a 67% higher odds of attending outpatient physical therapy (OR = 1.67; 95% CI = 1.21-2.29) than those with back pain. Older adults who did not attend outpatient physical therapy within 30days of ED visit had a 88% higher odds of returning to the ED than those who did attend (OR = 1.88; 95% CI = 1.34-2.64). Older adults in the first and second income quintile had a 66% higher odds of revisiting the ED than those in the fourth quintile. Outpatient physical therapy attendance after ED discharge was a predictor of revisit within 30days. Patient diagnosis of vertigo and higher median household income were predictors of higher outpatient physical therapy attendance. However, a diagnosis of falls or mobility concerns and a lower household income status were associated with lower attendance. Physical therapy after ED discharge has the potential to reduce 30-day ED revisit but requires strategies to improve access equity across diagnostic groups and household income levels.