Saturday, September 7, 2024
9/7/2024
Project Summary The correlation between health and income is one of the most persistent observations in the social sciences, supported by research across countries, demographic groups, and time periods. The relationship between income and health is large, emerges early in life, and is present across many indicators considered proxies for health. Despite the striking nature of the association, there is relatively little evidence in the U.S. context on whether income has a causal impact on health outcomes, and less information on what mechanisms may be responsible for such a causal relationship if one exists. Income and health may be correlated because higher income has a direct impact on health (e.g., by allowing individuals to purchase medical care), or health may directly affect income (e.g., because poor health makes it difficult to work). It may also be the case that a third factor—such as education—influences both income and health, driving the observed correlation between the variables. Without the ability to randomize variation in income, discerning the true nature of this relationship is difficult. We propose to provide new evidence from a large-scale, randomized intervention in the U.S. on the relationship between income and mental and physical health through a randomized evaluation of a sustained unconditional cash transfer program being implemented by two non-profit organizations. This program will randomly assign participants to a treatment group that receives $1,000 per month or to a control group that receives $50. Both groups will receive the transfer monthly for three years. We will examine treatment/control differences to estimate the effect of the additional income on behaviors and environmental factors (e.g., nutrition, food security, exercise, substance use, sleep quality, and neighborhood characteristics) that could affect longer-term health outcomes (Aim 1) and on medical care access and utilization (Aim 2). In order to understand the effect of the increase in income on health, we will assess treatment/control differences in subjective measures of physical and mental health as well as blood pressure, height, weight, and blood spots that can be analyzed to provide cholesterol, A1c (a measure of glycated hemoglobin that indicates diabetes risk), and C-reactive protein (Aim 3). We will measure the outcomes associated with these aims using a combination of in person and online survey questions, nutrition diaries (ASA 24), time diaries, and biomarkers collected in person by trained enumerators. We will also conduct long term follow up after the end of the payments. This study will provide groundbreaking, policy-relevant new information on the impact of income on health, healthy behaviors, and well-being.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
