1. Marital Disruption and the Risk of Losing Health Insurance Coverage James Kirby AHRQ

2. Research Questions To what extent does marital disruption increase the risk of losing health insurance? To what extent does marital disruption increase the risk of losing health insurance? Does the association diminish over time? Does the association diminish over time?

3. Motivation Many individuals get their health insurance coverage through their spouse Many individuals get their health insurance coverage through their spouse Many marriages end in divorce Many marriages end in divorce Prior studies on coverage do not examine change Prior studies on coverage do not examine change Understanding how events affect coverage loss is important to evaluate changes in health care policy Understanding how events affect coverage loss is important to evaluate changes in health care policy

4. Theoretical Background Being married provides: Being married provides: – Opportunity for coverage – Incentives for coverage People plan their lives around their marital status People plan their lives around their marital status – Career, fertility, geographic location Decisions have staying power Decisions have staying power Two types of effects: Two types of effects: – “Stable” disadvantage of being unmarried – “Transitional” disadvantage of becoming unmarried

5. A Model of Change “Stable effect” “Transitional” effect “Recovery”

6. Analytic Approach Discrete-time, Proportional Hazards Model Discrete-time, Proportional Hazards Model General Linear Model with complimentary log- log link (instead of probit or logit) General Linear Model with complimentary log- log link (instead of probit or logit) Unit of Analysis: Person-Month Unit of Analysis: Person-Month Results interpreted with Hazard Ratios Results interpreted with Hazard Ratios

7. Data Sources Medical Expenditure Panel Survey (MEPS) Medical Expenditure Panel Survey (MEPS) – Analysis is restricted to 18+ 2 years of data collected at 5 interview rounds 2 years of data collected at 5 interview rounds Three most recent panels are pooled Three most recent panels are pooled Unit of Analysis: Person-month Unit of Analysis: Person-month

8. Key Variables Change in Insurance Coverage by Month Change in Insurance Coverage by Month Change in Marital Status Change in Marital Status – Married in ALL prior rounds – Unmarried in ALL prior rounds – Divorced/separated/widowed in ANY prior round – Unmarried  Married in ANY prior round Interaction between change in marital status and time since change Interaction between change in marital status and time since change

9. Controls for Multivariate Analysis Demographics Demographics – Race, Ethnicity, Age, Sex SES SES – Income, Education Attitudes about health insurance & risk Attitudes about health insurance & risk – Scale of four measures (α=0.78) Health Status Health Status – Subjective mental and general health – Disability (ADLs and IADLs) – Number of serious chronic conditions Children in household Children in household

10. Hazard Ratios for Coverage Loss by Marital Status HazardRatio Marital Status & Change Married  Married (reference) 1.00 Married  unmarried 2.20 * Unmarried  Unmarried 1.15 * Unmarried  Married 1.96 * Time Interactions Married  unmarried x time 0.97 * Unmarried  Married x time 0.96 *

11. Monthly hazard of losing health insurance coverage by marital status

13. Monthly hazard of gaining health insurance coverage by marital status

14. Summary Marital Disruption is positively associated with the risk of losing coverage, but so is marriage Marital Disruption is positively associated with the risk of losing coverage, but so is marriage The associations decline over time The associations decline over time – For every month that passes, hazard decreases by about 3% Getting married is also positively associated with gaining insurance coverage. There is no such association for marital disruption Getting married is also positively associated with gaining insurance coverage. There is no such association for marital disruption

15. Conclusions Marital transitions should be recognized as a risk factor for losing health insurance Marital transitions should be recognized as a risk factor for losing health insurance Eligibility is not the sole causal mechanism Eligibility is not the sole causal mechanism – Upheaval associated with marital change is a possible explanation for lapses in insurance coverage

16. Hazard Rate Models: Hazard Ratios HazardRatios LossGain Married  Married (reference) 1.001.00 Married  unmarried 2.20 * 0.95 Unmarried  Unmarried 1.15 * 0.85 * Unmarried  Married 1.96 * 1.63 * Married  unmarried x time 0.97 * 1.01 Unmarried  Married x time 0.96 *