1 1 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. Users can also print maps and export image files from the Explorer. 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. 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. Multivariate mapping and exploration 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. 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.
2 2 Time Series Explore changes in variables over a 10 year period. 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.
3 3 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.
4 4 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 Technical Notes). Exploring the Multivariate Map Open the Multivariate Application and click on the button labeled Y-axis (Dependent Variable) to choose the first variable. Then, choose the second variable by clicking on the button labeled X-axis (Independent 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).
5 5 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? Time Series Application The Health Data Explorer Time Series Application presents county-level mortality data for leading causes of death over the most recent 10 year period. To open the Time Series Application, return to the Explorer main page and scroll down until you find the Time Series link. With the application open, use the select data button to choose a disease. You may select either the mortality rate or the count (number of deaths), and pick one year to view the data. The map will display the mortality for that disease for that year by county (by quintile). When you roll the cursor over any county on the map, the time series data for that county for all 10 years will display on the time series chart below. If you click the county it will remain highlighted and will continue to display on the chart. Then, roll over another county and that county will also display on the chart in a different color, so you may compare them. To compare the county to a region or the state, roll over that region on the Region/State/US table. To compare a county to its peer** counties, click on the Filter by Region button and scroll down until you locate the county of interest. Click on its peer group and Explorer will display only that data. Roll over the counties on the bar chart and their 10 year trend line will display on the map.
6 6 **Peer counties are the three or four other counties in the state that are considered similar to the target county, based on health needs and risk factors. Peer counties are described in more detail in the NC-CATCH Training Manual, page 14, which can be found at this web site: Saving or Printing Images Images from the Health Data Explorer can be printed or copied into a jpg or png file. For instructions on how to do this, see the FAQ section of the web page. Downloading Data Data can also be exported from the Explorer. To do this, go to the bottom of the simple map instructions page and open the application with the data you are looking for. Once the application is open, click the Link to Data button to open an excel file with data. TECHNICAL NOTES 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 Y axis is the dependent variable (the outcome variable) and the variable along the X axis is the independent variable (the one that theoretically causes the outcome). 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 1 (the top map) to show the rate for the prevalence of diabetes. By default, this also plots the diabetes prevalence along the Y axis (vertical) of the scatterplot. Then, set the Select Data drop-down menu for Map 2 (the bottom map) to show the rate of obesity. By default, this plots obesity on the X axis (horizontal). 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.
7 7 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 Y axis button and pick a variable, then click on the X 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 colorless scatterplot that results show the relationship between the Y and X variables only. For instance, pick diabetes prevalence for the Y variable and poverty for the X variable. This scatter plot shows that there is a positive relationship between poverty and
8 8 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.
9 9 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?
10 10 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.
11 11 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. Once you have exported the image you can insert it into Word or Powerpoint. You can also use the crop tool in Powerpoint to crop the image if you only want to use part of it. 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 Systems Research and Development, East Carolina University, Greenville, NC, 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.
12 12 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 Systems Research and Development, East Carolina University, Greenville, NC, 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 application).
13 13 FREQUENTLY ASKED QUESTIONS What is the correct way to cite the Explorer? Cite the Explorer as follows: North Carolina Health Data Explorer. Center for Health Systems Research and Development, East Carolina University, Greenville, NC. ( ) Where does the data in the Explorer come from? The data in the Explorer is gathered from a number of different public sources and compiled by staff at the Center for Health Systems Research and Development at East Carolina University. The mortality data originates with North Carolina Vital Statistics from the State Center for Health Statistics. The Center for Health Systems Research and Development compiles this data. Other data in the Explorer is gathered from a variety of sources, including: The NC State Center for Health Statistics ( The North Carolina State Data Center ( Log In to North Carolina ( The North Carolina Rural Economic Development Center s Rural Data Bank ( The North Carolina Department of Health and Human Services Division of Public Health Epidemiology Branch ( The US Census ( Users can access a complete source list for all the data items in the Explorer by clicking on the Data Source Info button in the application. A word file will open that lists all the data in the order it appears in the Explorer, along with source information for that item. The data items and their source information are also listed alphabetically by title at the bottom of the document. How often is the data in the Explorer updated? The mortality data in the Explorer is updated when new vital statistics data become available from the State Center for Health Statistics (about once a year). The 2009 mortality data was posted by the SCHS in April of 2011 in a text file format. The Center for Health Systems Research and Development compiled that data into a format suitable for the Explorer and updated it in the Explorer in October, When new data is released we will make every effort to process it and post it to the Explorer. The Center for Health Systems Research and Development will also track and update the other publicly available data sources in the Explorer on roughly an annual schedule. However, users may want to check the sources for specific data items to ensure that a newer version of the data item is not available. All data sources can be found by clicking on the Data Source Info button in the Explorer application. Is it possible to compare data for more than one year in the Explorer? The Simple Map, Double Map and Multivariate Map applications display mortality data for one year at a time. The Time Series application allows the user to look at mortality data for a series of 10 years. To access the Time Series application, go to the bottom of the main Explorer page and click the Time Series link.
14 14 Can a Time Series be created for comparing race and sex by county? Currently the Explorer does not have this capability. Whenever we can, however, we will try to build new features into the Explorer, so don t hesitate to tell us your ideas. Also note: the Center for Health Systems Research and Development publishes a Health Indicator series on our web site that contains 28-year time series data for selected counties and regions. See the link at: Is it possible to get the data by age range? Currently the Explorer does not have data by age range. 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 (jpg or png). Then click export and select your destination file. Once you have exported the image, copy it and you can paste it into Word or Powerpoint. You can also use the crop tool in Powerpoint to crop the image if you only want to use part of it. 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. (SnagIt is available for the Mac or Windows. Follow this link for info: &utm_medium=paidsearch&sissr=1) If you copy the image to use somewhere else, please cite it as follows: North Carolina Health Data Explorer. Center for Health Systems Research and Development, East Carolina University, Greenville, NC, Can I Download Data from the Health Data Explorer? The data from the 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.
15 15 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 application). Will the Healthy North Carolina 2020 Objectives be adopted into the Explorer? We are working on getting these objectives into the Explorer, and we hope to create a special section for them soon. The NC CATCH system has a feature that geocodes data to census tracts. Is this sort of function possible with the Explorer? Is it planned? Due to size limitations with the software that runs the Explorer, we do not expect to be able to offer this sort of function. Do you have data on: Fast food restaurants or supermarkets per capita? Yes, we just added it. Health care professionals that accept Medicaid or safety net providers? No, if you know of a good source for this data at the county level let us know and we will add it. Oral health measures? Currently, we have percent 5 th graders with untreated tooth decay, percent kindergarteners with untreated tooth decay, and percent Medicaid eligible receiving dental services age 0-5, age 6-14, and age These are in Series 1 of the Explorer. We will also be adding additional BRFSS oral health data soon.
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