Dr. Clarann Weinert

Clarann Weinert, SC, PhD, RN, FAAN

Tool Developer

Montana State University
College of Nursing
[email protected]

Robert Boik

Robert Boik

Co-Tool Developer

Montana State University
Department of Math Sciences
[email protected]

Instrument Overview

The MSU Rurality Index was developed for use as a research instrument. It is a relative index which assigns the degree of rurality based on the ranking of a resident on selected characteristics relative to other residents in the study group. In contrast, an absolute measure like that used by the Census Bureau, assigns the category of rural based on satisfying fixed criteria. In this case, the criteria are applied identically to a resident of Manhattan, NY and Manhattan, MT. An absolute scale, such as those discussed earlier, have certain inherent limitations. However, they are currently used for planning federal programs, and for the distribution of resources. Yet, for the purposes of research, were more finely delineated degrees of rurality are necessary to examine relationships between rurality and a variety of health variables, the existing absolute measures are not adequate.

A primary reason for developing the MSU Rurality Index was that the usual indices potentially misrepresent the degree of rurality of study participants particularly in the western states were counties cover large geographical areas. For example, many families in the Montana Family Cancer Project lived in rural areas. Some families lived in remote rural areas of large counties that contain a major population center and would be classified as urban by the commonly employed absolute indicators. Other families lived in counties that do not contain a major population center, yet their degree of social, economic, and cultural isolation varied widely. These families would be classified as rural by the commonly employed absolute indicators, without regard to their degree of isolation.

A whole state like Montana could be considered as rural based on the large land mass, sparse population (less that 800,000), low over all population density (average of fewer than 5 persons per square mile), only two metropolitan areas Billings (approximately 90,000) and Great Falls (approximately 56,000), and the primary economies of farming/ranching, mining, logging, and recreation. By the OMB designation all but two of Montana's 56 counties are classified as nonmetropolitan yet on many dimensions these counties are very different from each other. For example, a nonmetropolitan county in eastern Montana may have a population density of less than 1 person per square mile, with great distances to travel to a town large enough to have even marginally adequate retail, health, and other necessary services. While a nonmetropolitan county in western Montana may be much smaller in square miles, have a more dense population, and relatively easy access to a small city, with a university, retail, health care, and essentially all needed services. Clearly, to adequately examine the critical variables of the Montana Family Cancer Project, such as resources utilization, support networks, and costs of managing the illness an index which reflected the degree of rurality was imperative.

For the purposes of developing the MSU Rurality Index a working definition of the concept of rurality included the two characteristics as noted by Lee (1991); low population density and diversity. The characteristic of low population density effects communication and transportation patterns; social network composition and interaction patterns; and availability of specialized services (Cordes, 1985). The concept of rurality incorporates diversity in demographic composition, life styles, values, occupations, and other social features.

Various strategies for developing a relative index of rurality are feasible. Carney, Burns, and Slinkmen (1991) developed an economic index by performing a principal components analysis on eleven county-based variables measured on each county in Texas. This strategy required substantial effort in data collection followed by somewhat standard data analytic techniques. The development of the MSU Rurality Index used an alternative strategy. Two key variables were carefully selected to reduce data collection effort and a slightly more complex analytic technique was employed. Overall, the cost is lower if a small amount of high quality data are collected and subjected to more extensive analysis.

The MSU Rurality Index is constructed from the following two variables: the population (as reported in the census) of the county of residence, and distance (in miles) to emergency care as indicated by self-report of study participants. The intent is to form a surrogate variable that reflects the degree of rurality. County population is a measure gauging the threshold size of the market necessary to support various types of health care and other services. For example, tertiary care or radiation treatment centers require a very large population level to make them economically viable.

Accessibility to various types of care and treatment will vary for people living in rural areas even within the same county. Thus, there is a need to differentiate among residents in rural areas within the same county as well as across counties. The MSU Rurality Index employs distance to emergency care to achieve this differentiation. Emergency assistance in a rural state is provided in a variety of ways ranging from a Emergency Room in a small hospital to the office of a sole provider such as a nurse practitioner or family practice physician. These services exist in a population center, albeit a small town. Thus, distance from even the most basic service of emergency care was selected to be used in the calculation of the degree of rurality. Distance to emergency care was selected over distance to other health care because in the case of an emergency, for example a serious laceration, a person would tend to seek the closest source of assistance. However, rural residents are known to skip the local hospital or health care provider to seek help for less emergent conditions in a larger or more specialized facility. Even though it is a considerably further distance to travel. Like all self-report measures there is a margin of error in reporting that is unavoidable. However, for the most part persons living in rural areas are very aware of distances, as traveling is a integral part of their way of life. Likewise, small discrepancies in the reported distances to emergency care will not, in the long run, substantially effect the calculation of the MSU Rurality Index.

The MSU Rurality Index value increases as the degree of rurality increase. Thus, a person living close to emergency care in a highly populated county would have a lower score (more urban) than a person who lived in the same county but at a greater distance from emergency care. Likewise, a person living in a sparsely populated county in a small town with emergency care available would have a lower score (more urban) than a person residing on a ranch in a more heavily populated county, but who is a longer distance from emergency care. When the MSU Rurality Index is calculated for a study sample a range of scores is developed that provides an indication of the degree of rurality for each participant that is not possible when the standard dichotomous indicators of rural/urban or metropolitan/nonmetropolitan are used. Because the MSU Rurality Index is calculated using only county population and distance to emergency care, it is not intended for use when all participants in a study live in the same county.

Weinert, C., & Boik, R. (1995). MSU Rurality Index: Development and evaluation. Research in Nursing and Health , 18, 453-464. Abstract


Updated: 06/14/2011 11:39:57