Effects of a Cancer Diagnosis on Economic Prosperity in the Long Run: Evidence from Linked Survey and Credit Data.
Author(s): Warren, John Robert; Thomas, Amanda; Grodsky, Eric; Muller, ChandraYear: 2024
Title: Effects of a Cancer Diagnosis on Economic Prosperity in the Long Run: Evidence from Linked Survey and Credit Data.
Publication title: Innovation in Aging
Volume: 8
Issue: Supplement_1
Pages: 31-31
ISBN: 2399-5300
DOI: 10.1093/geroni/igae098.0092
URL: https://doi.org/10.1093/geroni/igae098.0092
Keywords: Cancer Diagnosis
Credit Data
Education Data
Financial Security
Linked Data
Topic: EDUCATION
HEALTH
WORK
DEMOGRAPHICS
Data: HS&B:80
Abstract:
Although 40% of Americans will experience cancer in their lifetime, little is known about the long-term impacts of cancer diagnosis on debt, wealth, and financial precarity later in life. Using data from High School and Beyond (HSB) —a large (n~25,500) nationally representative study of high school students followed from 1980 through 2022—linked to consumer credit records (2004-2023), we estimate changes in debt, credit, and other economic measures resulting from after a cancer diagnosis. We also consider how these processes vary across demographic, educational, and family background groups. Approximately 13,900 individuals from the original cohort responded to the 2021/2022 survey, with more than 1,000 indicating a lifetime diagnosis other than skin cancer; another 490 cohort members died from various forms of cancer by 2021/2022. The most common cancers reported were breast (n=350) and prostate/vaginal (n=150 each) with more than one-third diagnosed in early adulthood (≤ 45 years old). Preliminary results using cross-sectional measures of financial well-being indicate reduced annual income earnings and heightened financial precarity as compared to otherwise similar people without a cancer diagnosis. With linked consumer credit data, we are well-equipped to expand knowledge about the effects of a cancer diagnosis on financial health by analyzing fluctuations in indicators such as credit score, medical and other forms of debt, bankruptcy, and estimated wealth in the months and years after a cancer diagnosis. Our analyses will model these outcomes, inclusive of key confounders (age, education, type of cancer, etc.) both for the full sample of demographic and socioeconomic subgroups.