Adapting the Index of Relative Rurality (IRR) to Estimate Rurality at the ZIP Code Level: A Rural Classification System in Health Services Research

BACKGROUND

Accurate analysis of health problems facing rural residents depends on how rurality is defined. Health services research relies frequently on the rural urban commuting area (RUCA) codes to estimate rurality at the small area level. We modified the county-level Index of Relative Rurality (IRR) to the ZIP code level (IRRZIP ) to create an alternative small-area-level rural classification system. We then compared how the 2 rural classification systems differ in how rural areas and populations are defined and in methodological analysis.

METHODS

We linked data for veterans (n = 37,466) who attended the VA Pittsburgh Healthcare System to 2000 United States Census and the US Department of Agriculture's Economic Research Service data.

RESULTS

The RUCA and the IRRZIP do not consistently classify the same ZIP code areas and populations as rural. Using the IRRZIP , each 10th increment in increased rurality was associated with a 2.6 increased odds of receiving primary care at a satellite clinic.

CONCLUSIONS

The IRRZIP is a straightforward measure that is easy to use and interpret and may be a relevant alternative rural classification system that can be used in health services research.

Do Modifiable Cardiovascular Risk Factors Differ By Rural Classification in Women Who Enroll in a Weight Loss Intervention?

PURPOSE

If clinicians and researchers are aware of specific cardiovascular risks associated with women's rural status, whether it be large or small/isolated rural areas, it may help in developing more relevant rural resources. The purpose of this study was to examine whether there were differences in modifiable cardiovascular risk factors of overweight and obese rural women living in large or small/isolated rural areas.

SAMPLE

This secondary analysis examined baseline cross-sectional data from the "Web-based Weight Loss and Weight Maintenance Intervention for Older Rural Women" clinical trial. Analysis included data from 299 rural Midwestern women, ages 40-69 years with a baseline body mass index of 28-45 kg/m2, who provided rural classification data and were randomized into groups.

METHODS

Demographic and biomarker baseline data were used. Chi-square and independent t-tests were used for data analyses.

FINDINGS

There are no significant differences found in overweight and obese women with cardiovascular risk factors when compared to rural classification, with one exception. Total cholesterol was associated with rural classification (p=0.047), where women living in large rural areas were more likely to have elevated total cholesterol levels (≥240 mg/dL) compared to women living in small/isolated areas (18.5% vs. 10.0%, respectively). Demographic characteristics such as age and education demonstrated no significant differences by rural classification; however, the majority of women in this study were of high socioeconomic status.

CONCLUSIONS

Although this secondary analysis found that rural women have similar cardiovascular risk factors and demographic characteristics, this study highlights the need for clinicians to carefully consider the rural community characteristics for primary prevention.