Rural Health Research Gateway

Impact of Employment Transitions on Health Insurance Coverage of Rural Residents

Funder: Office of Rural Health Policy (ORHP)
Research center: Maine Rural Health Research Center
Phone: 207.780.4430
Lead researchers: Andrew F. Coburn, PhD
Erika Ziller, MS
Contact: Erika Ziller, MS, 207.780.4615, eziller@usm.maine.edu
Project funded: September 2006
Anticipated completion date:December 2007
Topic: Health insurance and the uninsured

While we have substantial information on static insurance coverage rates for rural residents, our knowledge about how coverage changes with employment transitions is limited. For example, among those rural residents with private health insurance coverage, we do not know what impact a job change or reduction in hours may have on coverage. This project will use the National Longitudinal Survey of Youth (NLSY), an ongoing nationally representative survey conducted by the Bureau of Labor Statistics to determine the relationship between employment changes and health insurance status among rural residents. The NLSY contains data for 12,686 individuals who were 14-22 years old when they were first surveyed in 1979. Interviews were conducted annually from 1979 through 1994, and biennially from 1994 through 2002. We will investigate the following questions:

  1. Among employed adults with private health insurance, what proportion experience an employment transition (defined as a change in jobs or hours worked) between 1993 and 2002? Does this differ for rural and urban residents?
  2. For each type of employment transition (transition to new job, change in hours worked at the same job, or transition to no job), what is the likelihood that an employed worker with private insurance will become uninsured? How does the likelihood of becoming uninsured compare for rural and urban workers?
  3. Among workers that maintain coverage after each type of employment transition, how long does this coverage last? Are there rural-urban differences? What demographic or job characteristics predict the likelihood of maintaining stable coverage?
  4. Among those that lose coverage, how long does the uninsured spell last? Are there rural-urban differences in these spell lengths? What demographic or job characteristics predict the likelihood of losing coverage?