Marital status is recognized as an important social determinant of health, income, and social support, but is rarely available in administrative data. We assessed the feasibility of using exact address data and zip code history to identify cohabiting couples using the 2018 Medicare Vital Status file and ZIP codes in the 2011–2014 Master Beneficiary Summary Files. Medicare beneficiaries meeting our algorithm displayed characteristics consistent with assortative mating and resembled known married couples in the Health and Retirement Study linked to Medicare claims. Address information represents a promising strategy for identifying cohabiting couples in administrative data including healthcare claims and other data types.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Allison, P.D., Christakis, N.A.: Fixed-effects methods for the analysis of nonrepeated events. Sociol. Methodol. 36, 155–172 (2006)
Barford, A., Dorling, D., Smith, G.D., Shaw, M.: Life expectancy: women now on top everywhere. BMJ 332, 808 (2006)
Calvillo-King, L., Arnold, D., Eubank, K.J., Lo, M., Yunyongying, P., Stieglitz, H., Halm, E.A.: Impact of social factors on risk of readmission or mortality in pneumonia and heart failure: systematic review. J. Gen. Intern. Med. 28, 269–282 (2013)
Case, A., Paxson, C.: Sex differences in morbidity and mortality. Demography 42, 189–214 (2005)
Christakis, N.A., Allison, P.D.: Mortality after the hospitalization of a spouse. N. Engl. J. Med. 354, 719–730 (2006)
Christakis, N.A., Allison, P.D.: Inter-spousal mortality effects: caregiver burden across the spectrum of disabling disease. In: Cutler, D.M., Wise, D.A. (eds.) Health at Older Ages: The Causes and Consequences of Declining Disability Among the Elderly, pp. 455–477. University of Chicago Press, Chicago (2009)
Christakis, N.A., Iwashyna, T.J.: Spousal illness burden is associated with delayed use of hospice care in terminally ill patients. J. Palliat. Med. 1, 3–10 (1998)
Christakis, N.A., Iwashyna, T.J., Zhang, J.X.: Care after the onset of serious illness: a novel claims-based dataset exploiting substantial cross-set linkages to study end-of-life care. J. Palliat. Med. 5, 515–529 (2002)
Elwert, F., Christakis, N.A.: Widowhood and race. Am. Sociol. Rev. 71, 16–41 (2006)
Elwert, F., Christakis, N.A.: The effect of widowhood on mortality by the causes of death of both spouses. Am. J. Pub. Health 98, 2092–2098 (2008a)
Elwert, F., Christakis, N.A.: Wives and ex-wives: a new test for homogamy bias in the widowhood effect. Demography 45, 851–873 (2008b)
ESRI: Geocoding options properties. In: Environmental Systems Research Institute (ed.) ArcGIS for Desktop (2019)
Gilden, D.M., Kubisiak, J.M., Kahle-Wrobleski, K., Ball, D.E., Bowman, L.: A claims-based examination of health care costs among spouses of patients with Alzheimer’s disease. J. Gerontol. A Biol. Sci. Med. Sci. 72, 811–817 (2017)
Iwashyna, T.J., Christakis, N.A.: Marriage, widowhood, and health-care use. Soc. Sci. Med. 57, 2137–2147 (2003)
Iwashyna, T.J., Zhang, J.X., Lauderdale, D.S., Christakis, N.A.: A methodology for identifying married couples in Medicare data: mortality, morbidity, and health care use among the married elderly. Demography 35, 413–419 (1998)
Iwashyna, T.J., Brennan, G., Zhang, J.X., Christakis, N.A.: Finding married couples in medicare claims data. Health Serv. Outcomes Res. Methodol. 3, 75–86 (2002)
Jin, L., Chrisatakis, N.A.: Investigating the mechanism of marital mortality reduction: the transition to widowhood and quality of health care. Demography 46, 605–625 (2009)
Juster, F.T., Suzman, R.: An overview of the Health and Retirement Study. J. Hum. Resour. 30, S7–S56 (1995)
Luy, M., Minagawa, Y.: Gender gaps—life expectancy and proportion of life in poor health. Health Rep. 25, 12–19 (2014)
Monden, C.: Partners in health? Exploring resemblance in health between partners in married and cohabiting couples. Sociol. Health Illn. 29, 391–411 (2007)
National Academies of Sciences Engineering Medicine: Accounting for Social Risk Factors in Medicare Payment. National Academies Press, Washington (2017)
Ofstedal, M.B., Weir, D.R.: Recruitment and retention of minority participants in the Health and Retirement Study. J. Gerontol. 51(Suppl 1), S8–S20 (2011)
Smith, K.P., Christakis, N.A.: Association between widowhood and risk of diagnosis with a sexually transmitted infection in older adults. Am. J. Pub Health 99, 2055–2062 (2009)
Smock, P.J., Schwartz, C.R.: The Demography of families: a review of patterns and change. J. Marriage Fam. 82, 9–34 (2020)
Sonnega, A., Faul, J.D., Ofstedal, M.B., Langa, K.M., Phillips, J.W.R., Weir, D.R.: Cohort profile: the Health and Retirement Study (HRS). Int. J. Epidemiol. 43, 576–585 (2014)
Subramanian, S.V., Elwert, F., Christakis, N.: Widowhood and mortality among the elderly: the modifying role of neighborhood concentration of widowed individuals. Soc. Sci. Med. 66, 873–884 (2008)
Waite, L. J. & Gallagher, M. (2000) The case for marriage: Why married people are happier, healthier, and better off financially. (pp. Chapters 1 & 5), New York: Doubleday.
Wilson, J., Swift, J., Goldberg, D.W.: Geocoding Best Practices: Review of Eight Commonly Used Geocoding Systems. University of Southern California GIS Research Laboratory, Los Angeles, CA (2008)
Wood, R.G., Goesling, B., Avellar, S.: The Effects of Marriage on Health: A Synthesis of Recent Research Evidence. Mathematica Policy Research, Princeton, NJ (2007)
Wu, J.-R., Moser, D.K., Lennie, T.A., Burkhart, P.V.: Medication adherence in patients who have heart failure: a review of the literature. Nurs. Clin. North Am. 43, 133–153 (2008)
Young, N.L., Cheah, D., Waddell, J.P., Wright, J.G.: Patient characteristics that affect the outcome of total hip arthroplasty: a review. Can. J. Surg. 41, 188 (1998)
Zivin, K., Christakis, N.A.: The emotional toll of spousal morbidity and mortality. Am. J. Geriatr. Psychiatry 15, 772–779 (2007)
We acknowledge funding from the National Institute on Aging (R21AG053698) and the Social Security Administration (Retirement Research Consortium through the University of Michigan Retirement Research Center Award RRC08098401-10). The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff of the Board of Governors of the Federal Reserve System, the National Institute on Aging or the Social Security Administration.
Conflict of interest
The authors have no conflicts of interest.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix 1: Address cleaning
We geocoded the addresses in the Vital Status file using ArcGIS in order to obtain cleaned versions of the imputed addresses as well as each beneficiary’s census block. We concatenated apartment numbers and PO box numbers to each beneficiary’s cleaned address if available. The spelling sensitivity default in ArcGIS controls the amount of variation the geocoder will allow when identifying addresses in the reference data (Wilson et al. 2008). In other words, it standardizes directional terms such as “St.” and “Street” and names such as “Universe’ and “University,” which helped us avoid undercounting addresses that contained spelling errors or abbreviated words (Wilson et al. 2008, ESRI).
Appendix 2: Assortative mating
Among the identified couples 97% are different sex, 96% are of the same race, and 82% are within five years of each other. Among those who did not meet the couple definition (Not-Identified), only 78% were different sex, 53% were of the same race, and 51% were within five years of each other. Randomly assigning beneficiaries to partners in their census block suggests that our couple identification strategy is stronger than chance alone given that 83% of these randomly identified couples are of the same race, only 50% are opposite sex and 49% are within 5 years of each other, deviating severely from what we hypothesize a couple to resemble (Tables
About this article
Cite this article
Matta, S., Hsu, J.W., Iwashyna, T.J. et al. Identifying cohabiting couples in administrative data: evidence from Medicare address data. Health Serv Outcomes Res Method 21, 238–247 (2021). https://doi.org/10.1007/s10742-020-00229-1