Predicting Receipt of Social Security Administration Disability Benefits Using Biomarkers and Other Physiological Measures: Evidence from the Health and Retirement Study

Predicting Receipt of Social Security Administration Disability Benefits Using Biomarkers and Other Physiological Measures: Evidence from the Health and Retirement Study

Published: Apr 01, 2019
Publisher: Journal of Aging and Health, vol. 31, no. 4
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Authors

Lakhpreet Gill

Jessica Faul

Kevin Bradway

David Stapleton

Key Findings

Physiological measures have moderate power to predict SSA disability benefit receipt.

Objectives

The objective of this study was to assess how well physiological measures, including biomarkers and genetic indicators, predict receipt of Social Security Administration (SSA) disability benefits among U.S. adults aged 51 to 65 years.

Method

We used data from the 2006 to 2012 waves of the Health and Retirement Study (HRS), linked to SSA administrative data. Using logistic regression, we predicted benefit receipt (either Social Security Disability Insurance or Supplemental Security Income) using 19 distinct physiological markers, adjusting for age, sex, race, and select medication use. We then calculated the propensity (i.e., predicted probability) that each HRS respondent received benefits and assessed how well propensity score–based classifications could identify beneficiaries and nonbeneficiaries.

Results

Thirteen percent of respondents received benefits. Using the propensity score cut point that maximized the sum of sensitivity and specificity, the model correctly predicted 75.9% of beneficiaries and 73.5% of nonbeneficiaries.

Discussion

Physiological measures have moderate power to predict SSA disability benefit receipt.

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