The North Carolina Health Data Explorer The Health Data Explorer provides access to health data for North Carolina counties in an interactive, user-friendly atlas of maps, tables, and charts. It allows users to select, visualize, explore and download data on major disease mortality, disparities between groups, social and economic factors, and health behaviors. It is produced by East Carolina University s Center for Health Services Research and Development and Center for Health Disparities Research, using Instant Atlas and Flash. A concise Introduction provides directions on how to use the Explorer. Click here for a PDF copy of all the instructions and the FAQs. Simple Maps Double Maps and Scatter Plots Map and compare counties on over 100 outcome or predisposing variables. Explore racial and regional disparities. Download data in Excel format. Map and compare counties on two dimensions and explore relationships between outcomes and predisposing variables by scatter plot and correlations with linear regression. Explore outliers. Multivariate mapping and exploration Choices of regions Explore relationships between outcomes and multiple predisposing variables or by region. Review the regions, over a dozen sub-state regions to select from. Frequently Asked Questions Beta Test Version Report Problems / suggest improvements by contacting Katherine Jones, PhD
How to use the North Carolina Health Data Explorer To use the Simple Map, choose the data indicator you would like to see by clicking on the select data button on the top left of the page. A drop down menu will allow you to select data, and then the data will display on the map. (**To select your data on the drop down menu, place your curser directly over the word count or rate. To select a list of the data sources, place your curser over the little page icon, and a source list will open). Along with the map, the data will also be displayed on the chart at the bottom right. The counties will be grouped into five categories (or quintiles ), which will be displayed in the Counties by Quintile legend.
The data can be filtered by region using the filter by region button. When you select for a region, the Health Data Explorer presents only the data for that region. To remove the region filter, scroll down to the bottom of the region list and choose remove filter. Explore the Double Map The Double Map and Scatter Plot displays two data indicators simultaneously, as well as a scatter plot that shows the relationship between those two indicators. When the page opens, the two maps will (by default) be displaying the same indicator. The user should click on the Select Y-axis data and Select X-axis data buttons to choose which indicators to display.
Whichever indicators the user chooses will automatically be displayed together in the scatter plot. The horizontal and vertical labels on the scatter plot show which data are displayed. If you wish to include data for only one particular region, click the Filter by Region button. If the data are filtered by region, the filter will apply to both indicators and both maps. The scatter plot shows the relationship between the two variables using a linear regression model. The model estimates a line that is the best fit for the data on the scatter plot. The formula for the line is displayed at the top of the graph, and the plot of the line is displayed on the graph. (For additional information on how to use the scatter plot and how to and interpret the regression line, see the Frequently Asked Questions). Exploring the Multivariate Map Open the Multivariate Application and click on the button labeled X-axis (Independent Variable) to choose the first variable. Then, choose the second variable by clicking on the button labeled Y-axis (Dependent Variable). It is located just above the scatter plot. The scatter plot will graph the relationship between these two variables, and will display a correlation coefficient and a regression equation for the variables. You can also visually add in the influence of two more variables by adjusting the size and the color of the scatter plot bubble with the Map (color) Variable button and the Size Variable button. The size of the bubble is proportionate to the value of the "Size Variable." The color of the bubble may be used to represent categories such as regions, or ordinal values such as quintiles (generally a darker color indicates a higher value).
You can experiment with any of the variables on the application. Just keep in mind that the slope of the line (the scatter plot) will always be determined by the relationship between the X and the Y variables. The X variable will always be the independent (or causal ) variable, and the Y variable will always be the dependent (or outcome ) variable. Then, look for interesting patterns in the Size and Color variables. Do all the big dots (generally the big values) cluster toward the right or to the left of the plot? Or do they not seem clustered at all? Do colors of the circles or dots cluster above the line or below the line? Or to the left or to the right? Frequently Asked Questions How does the scatter plot work? The scatter plot diagram in the Double Map shows the correlation between the variable in Map 1 (plotted along the Y axis) with the variable in Map 2 (plotted along the X axis). By convention, the variable along the X axis is the independent variable (the one upon which the outcome variable may depend, the one that theoretically causes the outcome), and the variable along the Y axis is the dependent (or outcome) variable. The user can choose which data to plot on the X and Y axes by clicking on the data buttons and selecting an indicator. For instance, one might theorize that counties where the rate of obesity is high might show a higher prevalence of diabetes. To plot this relationship, set the Select Data drop-down menu on Map 2 (the bottom map) to show the rate for obesity. By default, this also plots the obesity rate along the X axis
(horizontal) of the scatter plot. Then, set the Select Data drop-down menu for Map 1 (the top map) to show the rate for the prevalence of diabetes. By default, this plots diabetes prevalence on the Y axis (vertical). The scatter plot now shows the association between the obesity rate and the prevalence of diabetes in North Carolina counties. In general, this is a positive relationship. As the rate of obesity increases in NC counties, the prevalence of diabetes also increases. The scatter plot shows the relationship between the two variables using a linear regression model. The model estimates a line that is the best fit for the data on the scatter plot. The formula for the line is displayed at the top of the graph, and the plot of the line is displayed on the graph. The number in front of the X indicates the average change in the Y variable that accompanies a one unit change in the X variable. It is also the slope of the line. If it is negative, it indicates an inverse (negative) relationship between X and Y, i.e. as X goes up, Y goes down. The size of the correlation coefficient (r) indicates how well the linear regression model explains the relationship between the two variables. The absolute value of the correlation coefficient can range between 0 and 1, with higher values of r demonstrating a stronger association between the two variables. When a variable is correlated against itself (the same variable is plotted on the X axis and the Y axis), the correlation coefficient is always equal to +1. If r is close to zero, this means there is little relationship between the two variables. If it is close to one, there is a close relationship. The square of r (R 2 ) is the coefficient of determination and describes how well the model explains the relationship, i.e. an r of 0.5 yields an R 2 of 0.25, which means that the independent variable (X) explains 25% of the variation in the dependent variable (Y). If r=0.9, then R 2 = 0.81, and explains 81% of the variation.
How Does the Multivariate Map work? To get a feel for using the Multivariate Map with multiple variables, start by looking at the relationship between just two variables. Click on the X Axis button and pick a variable, then click on the Y axis button and pick another variable. Then click on the Map (color) Variable and pick none, and click on the Size Variable and pick none. The color-less scatter plot that results shows the relationship between the X and Y variables only. For instance, pick poverty for the X variable and diabetes prevalence for the Y variable. This scatter plot shows that there is a positive relationship between poverty and diabetes (higher poverty rates are associated with higher rates of diabetes). The strength and direction of the relationship are shown in the regression equation and the correlation coefficient. Now add in two additional variables. Keep the same two variables for X and Y, but click on the Map (Color) Variable and pick geographic regions. When you click this, the application changes the color of the dots based on what region each county is in: Eastern North Carolina, the Piedmont, or Western North Carolina. The scatter plot still shows the relationship between the X and Y variables, but now you can see if counties in one region or another are clustered on the high end, the low end, or not clustered at all. (**Note: Only the color variable will produce a result for the regions. This is because the regions are categorical variables.) Next, click on the Size Variable and pick Population (make sure you are using the Multivariate Map from Series 2: Social Life and Economy for this example). The application automatically scales the size of the dot to make it proportionate to the size of the population in that county. Counties with large populations get a big dot and counties with small populations get a small dot. Look at the scatter plot again to see if the big counties are clustered on one end of the scatter plot or the other. The scatter plot
still shows the relationship between poverty and diabetes, but including the population variable allows you to see if that relationship varies consistently in any way that seems related to population size. You can experiment with any of the variables on the application. Just keep in mind that the slope of the line (the scatter plot) will always be determined by the relationship between the X and the Y variables. The X variable will always be the independent (or causal ) variable, and the Y variable will always be the dependent (or outcome ) variable. Then, look for interesting patterns in the Size and Color variables. Do all the big dots (generally the big values) cluster toward the right or to the left of the plot? Or do they not seem clustered at all? Do all the darkly shaded dots (generally the big values) cluster above the line or below the line? In the scatter plot you just made, change the Map (color) Variable to none and the Size Variable to Percent white. Now the scatter plot shows the relationship between poverty and diabetes, but the counties with a high percentage of residents who are white are shown by big dots and the counties with a small percentage of whites are shown by small dots. Do you notice any clustering? How about if you change the Size Variable to Percent black? What sorts of differences might this indicate in the relationship between poverty and diabetes for different racial groups?
How can I save the image or print the Health Data Explorer? There are several ways to print the Health Data Explorer, or to save it as an image file. You can print the Health Data Explorer by using the print command on your Windows File menu. Use Print Preview to preview it before you print it. You can also print by using the menu button on the map (the menu button is the small triangle located at the bottom of the zoom slider). To print, click the menu button and pick print preview, then hit print. Use the printer s preference menu to change the orientation from portrait to landscape.
You can use the same menu button to export to an image file. Click the menu button, then click export. Choose your format (jpeg or png). Then click export and select your destination file. You can also capture the image using SnagIt or another screen capture tool. Follow the SnagIt (or other tool s) instructions to save as a pdf, gif, jpeg, or other type of image file. If you copy the image to use somewhere else, please be sure to cite it properly: North Carolina Health Data Explorer. Center for Health Services Research and Development, East Carolina University, Greenville, NC, 2010. To view the Health Data Explorer as a full screen image, hit the F11 key on your keyboard. If you hit F11 a second time, you will return to your regular toolbar image. How can I include regions in my map? There are a number of ways to include regions in your map. To filter your data by region, use the Filter by Region button at the top of the application. (For the Multivariate Map, the Filter button is at the top right corner). When you pick a region from the drop down menu, the application will include data from only that region, and will exclude data from all other North Carolina regions. On the Double Map and Multivariate Map, when you filter by region the scatter plot will display the relationship between the X and Y variables for only that subset of the data. To remove the region filter, scroll to the bottom of the drop down menu and pick remove region.
On the Multivariate Map you can also include regions as a variable by picking a region for the Color Variable. When you do this the Health Explorer retains all the counties, but sorts the data by region and assigns a different color to each region. The user can then eye-ball the data for regional trends and patterns. Can I Download Data from the Health Data Explorer? The data from the Health Data Explorer can be downloaded by specific disease. To access the data go to the Simple Map and page down to the Single Disease links at the bottom. Then, click on the link to data button. This will open an excel file with mortality rates by county. Data for each of the disease mortality rates are available via their single map applications. The social, economic, and environmental data are available via the Social, Economic and Environment Single Map. Users should be sure to properly cite the data: North Carolina Health Data Explorer. Center for Health Services Research and Development, East Carolina University, Greenville, NC, 2010. Users may also want to verify the social, economic and environment data at its source to ensure it is up to date (all sources are listed in the data file and in the data source link on the appplication).
North Carolina Health Data Explorer Simple Map The Simple Map allows the user to map and compare counties on over 100 different indicators. The user can map different data indicators for all the counties in North Carolina by clicking on the select data button. Users can also screen for regions of the state by clicking on the filter by region button. A concise introduction provides directions on how to use the Explorer. The Health Data Explorer is organized around four data themes or series: Series 1: Mortality Rates and Healthcare Resources - The Mortality Rates and Healthcare Resources Series includes mortality rates for major causes of death, counts, age-adjusted total mortality rates, and white and non-white rates and disparity rate ratios. It also includes rates of health professionals per 10,000 population. Series 2: Social Life and Economy The Social Life and Economy Series includes mortality data along with social and economic data (income, poverty rate, unemployment rate, education level). Series 3: The Environment The Environment Series includes mortality data and data on selected environmental influences by county (hazardous waste, air pollution, agriculture). Series 4: Health Behaviors The Health Behaviors Series includes mortality data along with data on health behaviors (personal exercise, consumption of fruits and vegetables, alcohol consumption). This data is taken from the Behavioral Risk Factor Surveillance System (BRFSS), conducted annually by the US Centers for Disease Control and Prevention. BRFSS data is sample data, so it is presented with 95% confidence intervals.
Download Data from the Health Data Explorer Data from the Health Data Explorer can be downloaded by specific disease. To access the data click on any one of the Disease Maps (below). Then, click on the link to data button. Heart Disease Simple Map Cancer All Simple Map COPD Simple Map Stroke Simple Map All Other Unintentional Injuries Simple Map Alzheimer s Disease Simple Map Diabetes Simple Map Pneumonia and Influenza Simple Map Nephritis, Nephrotic Syndrome and Nephrosis Simple Map Motor Vehicles Simple Map Septicemia Simple Map Lung Cancer Simple Map Colon Cancer Simple Map Social and Economic Variables North Carolina Health Data Explorer Double Map The Double Map presents the relationship between two selected data indicators, shown on two side-byside maps. The data is also shown on a data table, and the relationship between the two data indicators is plotted on a scatter plot. A concise introduction provides directions on how to use the Explorer. For information on how to interpret the scatter plot, see the Frequently Asked Questions.
The Health Data Explorer is organized around four data themes or series: Series 1: Mortality Rates and Healthcare Resources - The Mortality Rates and Healthcare Resources Series includes mortality rates for major causes of death, counts, age-adjusted total mortality rates, and white and non-white rates and disparity rate ratios. It also includes rates of health professionals per 10,000 population. Series 2: Social Life and Economy The Social Life and Economy Series includes mortality data along with social and economic data (income, poverty rate, unemployment rate, education level). Series 3: The Environment The Environment Series includes mortality data and data on selected environmental influences by county (hazardous waste, air pollution, agriculture). Series 4: Health Behaviors The Health Behaviors Series includes mortality data along with data on health behaviors (personal exercise, consumption of fruits and vegetables, alcohol consumption). This data is taken from the Behavioral Risk Factor Surveillance System (BRFSS), conducted annually by the US Centers for Disease Control and Prevention. BRFSS data is sample data, so it is presented with 95% confidence intervals. North Carolina Health Data Explorer Multivariate Map The Multivariate Map displays the relationship between two user-selected variables in a bubble scatter plot. The influence of two additional indicators or dimensions may also be shown by way of the color and diameter of the bubble s circle. The color of the circle (light or dark) represents a variable s size. The diameter of the circle represents another variable s size. A concise introduction provides directions on how to use the Explorer. For information on how to interpret the multivariate scatter plot, see the Frequently Asked Questions.
The Health Data Explorer is organized around four data themes or series: Series 1: Mortality Rates and Healthcare Resources - The Mortality Rates and Healthcare Resources Series includes mortality rates for major causes of death, counts, age-adjusted total mortality rates, and white and non-white rates and disparity rate ratios. It also includes rates of health professionals per 10,000 population. Series 2: Social Life and Economy The Social Life and Economy Series includes mortality data along with social and economic data (income, poverty rate, unemployment rate, education level). Series 3: The Environment The Environment Series includes mortality data and data on selected environmental influences by county (hazardous waste, air pollution, agriculture). Series 4: Health Behaviors The Health Behaviors Series includes mortality data along with data on health behaviors (personal exercise, consumption of fruits and vegetables, alcohol consumption). This data is taken from the Behavioral Risk Factor Surveillance System (BRFSS), conducted annually by the US Centers for Disease Control and Prevention. BRFSS data is sample data, so it is presented with 95% confidence intervals. Explore the Regions Map The North Carolina Health Data Explorer presents data for all 100 North Carolina counties, but users can also filter data by one of several types of regions, including physical geography regions, Area Health Education Center regions, and economic development regions.
For more information on the regions, as well as maps that show which counties are in which region, click on the Regions Map. The Regions application displays the regions without any other data, so the user can see which counties they include.