[This page is intended to provide a study summary, the sections of which are below. Please complete these sections, as applicable. The headings below are suggested headings. You can remove inapplicable sections, or add new ones relevant to your study]
Investigator Names and Contact Information
Michael S. Simon MD, MPH [ firstname.lastname@example.org ]
Community-level variables, including the residential environment, may affect access to and utilization of healthcare services, and can have an important impact on individual health. Our primary objective is to classify all WHI participants in the CT and OS (n=161,808) using a widely accepted rural-urban classification scheme by linking Rural Urban Commuting Area (RUCA) codes to the census tracts of geocoded participant addresses between 1993-2012. RUCA codes were developed to categorize an individual's place of residence in the context of healthcare access. These codes uniquely incorporate measures of population density alongside commuting patterns and proximity to urban areas, emphasizing functional relationships between locations likely to contribute to variation in healthcare availability and practices. Given that the WHI – Physical and Built Environment Scientific Interest Group (SIG) has existing access to census tract information for each WHI participant, and the simplicity of data linkage using geographic information systems (GIS), the Physical and Built Environment SIG has agreed to perform the data linkage for this study. A secondary objective of the study is to assess the extent to which changes in residential location during WHI study follow-up impact the RUCA classification of study participants. Thus, we seek not only to add an informative contextual variable for each WHI participant, but we also plan to describe the consistency of the RUCA classification over time given the longitudinal nature of the WHI cohort. Overall, incorporating RUCA into the WHI will pave the way for numerous future studies to investigate the relationship between rurality and various diseases associated with aging, including (but not limited to) cancer, cardiovascular disease, and diabetes.