The Virginia Center for Healthy Communities, initially funded through the Turning Point grant by the Robert Wood Johnson Foundation, developed the Virginia Atlas of Community Health in consultation with Community Health Resource Center, Inc. The Virginia Center for Healthy Communities has developed this resource to enhance community health improvement strategies. On behalf of the Virginia Center for Healthy Communities, we would like to thank you for your interest in the Virginia Atlas of Community Health. Please use the “Comment” button or email shoran@communityhealthinfo.com to report any potential problems and suggestions.

The health of Virginia is determined by the health of its local communities. Each local community has its own particular health concerns and system of health services. In virtually every community there are local public health agencies, hospitals and health systems, clinics, health professionals, faith communities, and other organizations working to improve the health of the local citizenry. These local organizations need comprehensive, accurate information on community health status in order to focus their limited resources on the most pressing problems and measure their progress. They also need information on the supply of community health services available to help address community health needs.

While various state agencies and other organizations do publish a wide range of community health information, it is sometimes of limited use to local organizations involved in community health improvement. From a local perspective, the major weaknesses of existing data sources are: 1) data must be obtained from multiple sources with sometimes incompatible reporting formats; 2) data are not always accompanied by adequate narrative to help local organizations interpret information about their area; and 3) the data typically are provided at the locality, regional, or state level, and not useful for planning projects within smaller geographic areas. Consequently, local organizations with an interest in community health improvement are forced to proceed without adequate information or spend thousands of dollars in staff or consultant time to develop the information they need.

The magnitude of need for better information on community health was illustrated in a 2001 survey conducted by the Virginia Center for Healthy Communities. In this survey, a wide range of community health organizations (including hospitals, health departments, free clinics, community health centers, and others) were asked to describe their level of interest in various types of technical assistance for community health improvement. More than 100 respondents from across the Commonwealth said they would be very or somewhat interested in receiving help to obtain demographic- and health-related data on their communities.

In an effort to meet the need for more useful, affordable information on community health, the Virginia Center for Healthy Communities developed the Virginia Atlas of Community Health. The Virginia Atlas of Community Health includes dozens of community health indicators at the locality and ZIP code level. This interactive web site allows the user to view tables and maps that can help them to gain a better understanding of the health of their community at the locality and ZIP code level. The user may also download tables into Microsoft Excel files for local level analysis. A special feature of the Atlas is the availability of ZIP code level indicators. In many localities that are highly populated and/or geographically large, city or county level statistics can mask important geographic variation in health status within the locality. ZIP code level analysis allows the user to look within city or county boundaries for community health “hot spots” that might not be apparent from city or county level statistics. ZIP code level analysis also allows adjacent cities and counties to identify community health problems that cross city and county borders.

Our hope is that the Virginia Atlas of Community Health will help to foster the development of community health improvement projects across the Commonwealth. Information from the Atlas may be used to:

• Stimulate interest in community health improvement by helping local leaders compare their community’s health status to that of other communities;
• Help local organizations identify their most pressing health needs, particularly within small geographic areas;
• Provide information on community health resources to help local organizations identify community service gaps;
• Provide data to justify funding requests from federal, state, local, and private sources;
• Provide data for evaluating improvements in community health over time; and
• Provide all of this information at a fraction of the cost of consultants or internal staff time.

The Atlas contains community health indicators at two geographic levels: the locality level and the ZIP code level. Locality level indicators describe the health of Virginia’s 135 cities and counties. ZIP code level indicators describe the health of Virginia’s more than 800 populated ZIP codes. Please refer to Exhibit 1 for a complete list of available indicators. The user should note:

• The city/county level indicators and the ZIP code level indicators are distinct data sets. ZIP code boundaries are not always designed to match city and county boundaries. Also, some community health indicators are available at the city and county level, but are not available for smaller geographic regions such as ZIP codes.
• The ZIP code level Atlas displays the raw number of selected deaths and hospital discharges in each ZIP code. The Atlas does not display death or discharge rates because in many cases the total population of the ZIP code is too small to yield ratios that are meaningful for analysis.

Uninsured estimates were derived by applying income-specific uninsured rate estimates to population estimates at the city, county, and zip code level. Uninsured rate estimates were calculated using multiple national and state surveys to derive an estimated uninsured rate for people above and below 200 percent of poverty. Population estimates for each income group were derived by applying 200-percent-of-poverty rates from the 2000 Census to total population estimates for 2005. The uninsured rates estimates were then applied to the population estimates to derive an estimated number of uninsured individuals above and below 200 percent of poverty in 2005. This method is obviously subject to error and CHRC does not guarantee the accuracy of the estimates. Estimates should be used for program and policy planning only, and should not be used to compare uninsured rates across geographic areas.

Ambulatory care sensitive conditions are conditions for which hospitalization should be avoidable if the patient adequate ambulatory care. Ambulatory care sensitive conditions have been defined by the Agency for Healthcare Research and Quality, the Institute of Medicine, and others. The list of ambulatory sensitive conditions presented in the Atlas represents most but not all of the commonly identified ambulatory care sensitive conditions. Some were left out because the number of admissions statewide was too small to be meaningful in the context of the Atlas.

Ambulatory care sensitive conditions were identified by CHRC staff using inpatient hospital discharge data from Virginia Health Information, Inc. (Please note the VHI disclaimer included as a footnote to Exhibit 1.) Conditions were identified using recommended definitions based on diagnosis codes. The analysis includes only primary diagnosis codes with the exception of dehydration, which includes both primary and secondary diagnosis codes.

Please note that the zip-code level indicators are probably conservative for many zip codes. Zip code boundaries change over time. Many cases in the VHI database for 2005 included no-longer-existing zip codes as the patient’s place of residence. It is not possible from available information to allocate all of these addresses to the proper zip code. Therefore, some cases were left out of the analysis, with the probable effect of depressing the actual number of cases reported in the zip-code level reports.

For each Adult Health Behavior indicator, we used multivariate analysis (logistic regression) to explore relationships between a set of predictor variables and the variable of interest. We tested age, race, Hispanic ethnicity, sex, HSA, and income. We found age, race, and sex to be the most consistent statistically significant predictor variables. Income was also significant in a number of cases.

We then turned our sights to developing synthetic estimates. The basic methodology was to develop age, sex, and race specific estimates for each indicator from the 5,000+ cases in the Virginia database for 2003-2004. We then derived estimates of the total population by age, sex, and race from the 2000 Census and 2005 population estimates from SRC Corp. We then developed BRFSS estimates for 2005 by applying the age, sex, and race specific BRFSS estimates for 2003 to the age, sex, and race specific population estimates for 2005.

We left income out of the equation for multiple reasons. First, income was a factor in some, but not all BRFSS variables. Second, we were only able to synthetically estimate income as a percentage of poverty from the 2003 BRFSS data (no actual estimates were provided). Third, there were not enough BRFSS cases to support reliable estimates of BRFSS indicators by age AND race AND sex AND income. Fourth, we would have had to synthetically estimate actual poverty levels for 2005, as no actual data are available.

Exhibit 1. Atlas Indicators and Sources