Geocoding to Manage Missing Data in a Secondary Analysis of Community-Dwelling, Low-Income Older Adults

Managing missing data in a secondary analysis is daunting, particularly if the data of interest were not included in the parent study design. The current study describes the use of geocoding to replace missing data from a parent study for a secondary analysis of socioeconomic and neighborhood characteristics in community-dwelling older adults who are dually eligible for Medicare and Medicaid. Geocoding was used to link participants' addresses to data from the American Community Survey to replace missing income and neighborhood data. After geocoding, data completeness was 100% for neighborhood poverty and education composition, and 99.9% for income. Using geocoding provides the gerontological nurse researcher with a sample that is more reflective of the population. The current findings can be used to tailor neighborhood-centered interventions to promote health in low-income older adults. [Res Gerontol Nurs. 2017; 10(4):155-161.].