Explore the mortality rate maps

In a January 2021 article, the Breast Cancer Research Foundation reported that that while the rate of new cases of breast cancer between White and Black women are more similar, the death rate among Black women diagnosed with breast cancer is 40 percent higher than the death rate for White women. Because of lack of health care and preventive measures on top of social, economic, and behavioral factors, the gap between new breast cancer cases and outcomes is complex. The first version of this lesson analyzed data available in 2017. Two years later, Black women still suffered the highest proportion of deaths due to breast cancer.

Chart showing female breast cancer mortality by race and ethnicity in 2017

For this lesson, you are a GIS analyst for a research advocacy group whose mission is to close the racial inequity gap of breast cancer mortality rates in the United States. Your first goal in this lesson is to confirm there is a racial disparity gap for breast cancer mortality rates. To do so, you'll map available data on breast cancer mortality rates for Black and White women. In some parts of the United States, mortality data has been suppressed, hidden, or simply unavailable by the data provider. Data can be suppressed due to high rates of unreported numbers or privacy concerns. Your goal is to create a map you can share with partnering advocacy organizations and elected officials to raise awareness and advocate for additional resources to address this important public health need.

Note:

For this lesson, you will only analyze two racial groups. It is considered best practice to consider data for all racial and ethnic groups in a given population when conducting a racial equity analysis. You are encouraged to use the workflow of this lesson to analyze the disparity between other racial and ethnic groups on your own.

Create a dataset

First, you'll download the breast cancer mortality data. Then, you'll use the data to create a dataset on Insights.

  1. Download the Breast_Cancer_Mortality_2018.gdb compressed folder.
  2. Sign in to Insights using your licensed ArcGIS account.
    Note:

    To access Insights, your ArcGIS organization's administrator must grant you a license for it. If you don't have an organizational account or if your organization does not have Insights licenses, you can sign up for a free trial.

    If this is your first time signing in to your Insights account, the Welcome to Insights window appears.

  3. If necessary, in the Welcome to Insights window, click Skip.

    The Insights home page appears. In Insights, you work in a workbook. Workbooks contain connections to your datasets and cards with maps, charts, or other data. Before you create a workbook, you'll create a dataset with the data you downloaded.

  4. Click the Datasets tab.

    Datasets tab

    The Datasets page appears. This page lists datasets that you've created or that were shared with you by members of your organization.

  5. Click New dataset.

    New dataset button

    The New dataset window appears.

  6. Click Browse my computer. Browse to and add the Breast_Cancer_Mortality_2018.gdb compressed folder.

    Next, you'll change the name, file type, and metadata of the dataset before it is hosted on ArcGIS Online. ArcGIS Online datasets must have a unique name within your organization, so you'll change the name to include your name or initials.

  7. In the New dataset window, enter the following:
    • For Name, change the name to Breast_Cancer_Mortality and add your name or initials to the end.
    • For Type, choose File geodatabase.
    • For Tags, type Breast Cancer, Mortality Rates, racial equity, public health.
    • For Summary, type A file geodatabase containing information about breast cancer mortality rates for Black and White women by United States counties.

    Name and Type parameters for the new dataset

  8. Click Add.

    The dataset is added to your Datasets page.

Map mortality rates of Black women

To view the data, in a new workbook, you'll create a map of the breast cancer mortality rates among Black women.

  1. In the list of datasets, click the title of the Breast_Cancer_Mortality dataset.

    Available datasets

    The Add to page window appears with the Breast_Cancer_Mortality dataset selected.

    Add data to workbook.
  2. Click Add.

    The dataset is added to a new workbook. A map card displays the dataset's spatial data (counties in the continental United States).

    New workbook with mortality dataset

  3. If necessary, use your mouse wheel to zoom to the contiguous United States.
  4. In the lower left of the workbook, click Page 1. Rename the page Explore mortality rates.

    Page renamed to Explore mortality rates.

  5. On the ribbon, click Untitled Workbook and rename the workbook Breast Cancer Mortality Rates with your name or initials at the end.
    Rename workbook.

    Before you map the data, you'll look at the information it contains.

  6. In the data pane, point to the Mortality dataset. Click the Dataset options button and choose View data table.

    View data table

    The Mortality table appears. It displays all attribute data in the dataset. For each county, there is population data for Black, White, male, and female populations.

  7. In the table, scroll right until you see the breast cancer mortality rate columns.
    Note:

    The names of the columns may be truncated due to size. To see the full name of a column, point to the column's name.

    Columns for breast cancer mortality rates in the table

    These columns contain the Black Mortality Rate, White Mortality Rate, and total breast cancer mortality rate for each county. Many counties have values of zero. Zero is typically used as a placeholder value for suppressed or unavailable data. Data is often suppressed when there are too few cases in a county to maintain individual privacy.

  8. Close the table.

    Next, you'll change the map card's symbology to view the available data for Black women.

    The dataset expands and its attribute field names are listed. Next to most of the symbol names is a sigma symbol. This symbol indicates that the values in the field are considered numbers. For the mortality rate fields, you'll change the field so that its values are considered rates or ratios.

  9. In the data pane, click the Mortality dataset.
  10. For the Black Mortality Rate field, click the sigma symbol and choose Rate/Ratio.

    Rate/Ratio option

    The sigma symbol changes to an A/B symbol, which indicates that its values are now considered rates or ratios.

  11. Drag the Black Mortality Rate field to the map card and into the Style Mortality by Black Mortality Rate drop zone.

    Black Mortality Rate field in the Style Mortality by Black Mortality Rate drop zone

    The map style changes to display Black mortality rates using the default Natural Breaks classification with five classes. Most counties have zero as their value and are depicted with a light yellow color, the lowest class. You'll filter the zero values out of the map.

  12. On the map card's ribbon, click the Card filter button.

    Card filter button

    The New filter pane appears.

  13. For Filter by, choose Black Mortality Rate.

    A chart appears. It shows the distribution of values from the minimum value to the maximum value. You'll use this chart to set the filter.

  14. Click the node at the left side of the chart, change its value to 1, and press Enter.

    Filter lower limit to 1.

  15. Click Apply. Close the Card Filters pane.

    The map is updated to show only counties with reported data on Black women's mortality rates.

    Map of Black breast cancer mortality rates with filter applied

    Most of the available data is in the east and southeast of the country. In most other areas, there are large gaps in the data.

    When you filtered the data, a new filtered Mortality dataset was added to the bottom of the data pane. You'll rename the filtered dataset to keep it distinct from the original dataset.

  16. Scroll to the bottom of the data pane. Point to the filtered Mortality dataset and click the Rename dataset button.

    Rename dataset button

  17. Change the dataset name to Black Mortality Rate and press Enter.
  18. On the map card, next to the Black Mortality Rate layer name, click the arrow.

    Arrow to open the legend

    The Layer options pane appears. It contains the legend, indicating various mortality classes. One class indicates areas where breast cancer mortality rates are as high as 58 average deaths per 100,000 women.

    Mortality rate classes
  19. Close the Layer options pane.

    You'll rename the map card to better reflect its content.

  20. Click a blank area on your page to deactivate the map card. On the map card, click Card 1, type Black Mortality Rate, and press Enter.

    Rename card

Map mortality rates of White women

You'll create a second map to display breast cancer mortality rates among White women.

  1. In the data pane, for the original Mortality dataset, for the White Mortality Rate field, click the sigma symbol and choose Rate/Ratio.
  2. Drag the White Mortality Rate field to the empty space next to the Black Mortality Rate map card and into the Map drop zone.

    White Mortality Rate field in the Map drop zone

    A new map card is created, displaying White women's breast cancer mortality rates with the same symbology as the Black Mortality Rate map. Like you did with the other map, you'll filter out zero values.

  3. In the new map card, zoom in to the contiguous United States.
  4. On the ribbon of the map card, click the Card filter button. In the New Filter window, for Filter by, choose White Mortality Rate.
  5. Click the node at the left side of the chart, change the value to 1, and press Enter. Click Apply and close the Card Filters pane.

    The filter is applied.

    Filter White breast cancer mortality rates.

  6. In the data pane, point to the new filtered Mortality dataset, click Rename dataset, and change the name to White Mortality Rate.

    Rename dataset

  7. Click a blank area of the page to deactivate the map card. Click Card 1, type White Mortality Rate, and press Enter.

    Now that you've created both map cards, you'll change the basemap of both to a simple gray basemap that will emphasize the data.

  8. On the workbook toolbar, click the Basemaps button and choose Light Gray Canvas.

    Light Gray Canvas option

    The basemap is changed for both map cards. (You can change the basemap for only one card by first clicking the card to activate it and then changing the basemap.)

  9. On the White Mortality Rate map card, next to the White Mortality Rate layer name, click the arrow.
    White mortality classes

    The legend indicates that the range of mortality rates is lower than for Black women, with the highest rate being 48 average deaths per 100,000 women.

  10. Close the Layer options pane.
  11. On the ribbon of the White Mortality Rate map card, click the Sync extents button.

    Sync extents button

    The extents of both map cards become synced. Now, when you pan or zoom on one map card, the other map card will automatically pan and zoom the same way.

  12. Pan and zoom in on either map to see the data in more detail.

    Synced map cards

    Across the United States, many more counties have data for white mortality rates than for Black mortality rates. Because of the discrepancy between the number of counties that reported data, the default classification scheme may not be the most appropriate for displaying the data.

  13. Zoom out to the extent of the contiguous United States. On the workbook ribbon, click the Save button.

    Save button

Classify the data

By default, the data was classified using the Natural Breaks (Jenks) classification method. This method divides data into classes based on a combination of statistical measures (mean, median, quantiles) and gaps that exist naturally in the data.

The Black and White mortality rate datasets have a large difference in the number of features. To better compare the mortality rates in both maps, you'll change the classification scheme to the Quantile classification method, which divides classes so that each class has an equal percentage of features. This method accounts for differences in the number of features between each dataset, which will make it easier to compare them.

  1. On the White Mortality Rate map card, next to the White Mortality layer name, click the arrow.
  2. In the Layer options pane, click the Options tab.

    Options tab

    The Options tab includes options for symbology and classification.

  3. Click Classification to display the classification type and number of classes. For Classification type, choose Quantile.

    You'll reduce the number of classes to 4. That way, each class will contain about 25 percent of the dataset's features.

  4. For Number of classes, type 4.

    Quantile classification type with 4 classes

    The classification method is automatically updated on the map. In the Layer options pane, the histogram shows the distribution of the data, excluding the suppressed values you removed with the filter. You can view more statistical information on the back of the map card.

  5. Close the Layer options pane. On the toolbar of the White Mortality Rate map card, click the Flip card button.

    Flip card button

    The card flips around and displays statistics for the data.

    White mortality statistics

    The Count statistic indicates that there are 1,581 counties with data for White women, which is about 49 percent of all 3,220 United States counties and county equivalents. The Mean statistic indicates that the average breast cancer mortality rate for White women is about 21.

  6. Click the Flip card button to flip the card back to the map.

    Back arrow

    Next, you'll repeat the process for the Black Mortality Rate map card.

  7. On the Black Mortality Rate map card, next to the Black Mortality layer name, click the arrow. In the Layer options pane, click the Options tab.
  8. Click Classification to display the classification type and number of classes. For Classification type, choose Quantile. For Number of classes, type 4.
  9. On the ribbon of the Black Mortality Rate map card, click the Flip card button.
    Black mortality statistics

    For Black women, there is data for 341 counties (just over 10 percent of all counties and county equivalents). The mean mortality rate for Black women is 28.88, which is 8 deaths per 100,000 higher than for White women. Compared to the available data in 2015, the gap between Black and White breast cancer mortality rate decreased about 2 deaths per 100,000 women.

  10. Click the Flip card button. Save the workbook.

While there is more data available for White women, the range of the data values you mapped suggests the article's claims are true: Black women have higher breast cancer mortality rates than White women. Next you will map the degree to which breast cancer mortality rates differ between Black and White women.


Map the mortality rate difference

Previously, you looked at maps showing that across the United states, the majority of counties with reported breast cancer mortality rates were generally higher for Black women than White women. However, the discrepancy in the amount of data reported for each demographic group still makes direct comparison difficult.

Next, you'll focus only on counties that have reported data for both groups. You'll map the difference between mortality rates for these counties to better compare the data.

Identify dual-data counties

First, you'll create an advanced filter to select counties that have data for both Black women and White women. You'll create a page in your workbook to keep the analysis separate from the analysis you completed in the previous lesson.

  1. If necessary, open your Breast Cancer Mortality workbook in Insights.
  2. Drag the original Mortality dataset from the data pane to the New page button.

    Mortality layer dragged to New page button.

    A page is created with the Mortality layer in the data pane.

  3. Click the page name, Page 2, and rename it Mortality rate difference.
  4. Drag the Mortality dataset from the data pane to the blank space of the page and into the Map drop zone.

    A map card is created with the original, unfiltered dataset. Next, you'll create an advanced filter that is based on an expression instead of a single attribute field.

  5. In the new map card, zoom in to center on the contiguous United States.
  6. On the toolbar of the map card, click the Card filter button.
  7. In the New Filter pane, click Advanced.

    Advanced button

    You want to filter the layer to show counties that have data for both Black women and White women. You'll create an expression that ensures these criteria are met.

  8. Click Write or copy and paste expressions here and build or copy and paste the expression BlackMortalityRate_Num>0 AND White_Mortality>0.
    Note:

    Alternatively, you can create the expression using the lists of fields and operators below the expression field. If you copy and pasted the expression, the expression you copied are the field names, and after you paste the expression, the fields display the field alias.

    Expression to filter for both Black and White mortality rate

    The AND operator in this query specifies that the selected records must meet both criteria.

  9. Click Apply.

    The card is filtered to display only counties with data for both Black and White women.

    Map with advanced filter applied

  10. Close the Card Filters pane. In the data pane, rename the new filtered Mortality dataset Dual-Data Mortality.

    Rename dataset.

  11. Save the workbook.

Calculate the mortality rate difference

Next, you'll create a field in the filtered dataset and calculate the difference in mortality rates between Black and White women.

  1. In the data pane, point to the Dual-Data Mortality dataset, click Dataset options, and choose View data table.

    The table opens. The table has 318 records, meaning 318 counties had breast cancer mortality rate data for both Black and White women.

  2. Click the Field button.

    Field button

    A field is created. You can change the field name and create an expression to calculate the field's values.

  3. Click the New Field heading, type Mortality Rate Difference, and press Enter.

    Rename field.
  4. Click Enter calculate function and build or copy and paste the expression BlackMortalityRate_Num-White_Mortality.

    Function to calculate mortality rate difference

    Note:

    The fields display in the expression builder as the field alias.

    The green check mark next to the equation indicates that the equation is valid.

  5. Click Run.

    Values are calculated for the Mortality Rate Difference field.

    Positive values indicate that the breast cancer mortality rate is higher for Black women than White women. Most of the values are positive, but there are a few values that are zero or negative. These values indicate counties where the breast cancer mortality rate is the same or higher for White women.

  6. Close the table and save the workbook.

Symbolize the values

Next, you'll symbolize the dataset to visualize the Mortality Rate Difference field you calculated. Your finished map will show where a gap in breast cancer mortality rates exists in the United States.

  1. If necessary, in the data pane, click the arrow next to the Dual-Data Mortality dataset to expand it.

    Arrow to expand the filtered Dual-Data Mortality dataset

  2. For the Mortality Rate Difference field, click the sigma symbol and choose Rate/Ratio.
  3. Drag the Mortality Rate Difference field to the current map card and into the Style Dual-Data Mortality by Mortality Rate Difference drop zone.
    Style Dual-Data Mortality by Mortality Rate Difference

    The map is updated to display the Mortality Rate Difference field with graduated colors.

    Map symbolized by the Mortality Rate Difference field.

  4. Click the blank area of the page to deactivate the map card. Rename the map card Mortality rate difference.
  5. On the Mortality rate difference map card, next to the Mortality Rate Difference layer name, click the arrow.

    The legend appears. The mortality rate difference values range from 27 to -9.

    Mortality rate difference values range
  6. In the Layer options pane, click the Options tab. Click Classification to display the classification type and number of classes.

    The data is classified by Natural Breaks with five classes. In this dataset, negative numbers represent counties that had higher mortality rates for White women, zeros represent counties with an equal mortality rate, and positive numbers represent counties that had higher mortality rates for Black women. You'll reduce the number of classes to three to show these categories on the map.

  7. For Number of classes, type 3.
  8. On the Classification histogram, click the first class break and change the value to -1.

    First class break changed to -1.

    Because you are manually setting the class breaks, the Classification type automatically updates to Manual.

  9. Change the second class break to 0.

    Second class break changed to 0.

    You have created three classes: one for negative numbers, one for zeros, and one for positive numbers. Currently, the categories are symbolized with a color ramp, which implies a progression of values. Because each category has a distinct meaning, you'll adjust the symbology so that each category has a distinct color, too.

  10. Click the Style tab.

    Style tab

  11. For Color palette, choose the red, yellow, and blue color palette.

    Red, yellow, and blue color palette

    The map updates to symbolize the counties with the color palette you chose. Smaller counties can be difficult to see because of their thick white outlines, so you'll reduce the outline thickness and change the color.

  12. Change Outline thickness to 0.5 px.

    Outline thickness changed to 0.5 px.

  13. For Outline color, choose the gray color in the first column, fifth row (hex value #ADADAD).

    Outline color changed to #ADADAD.

  14. Close the Layer options pane. On the workbook toolbar, click the Basemaps button and choose Light Gray Canvas.
  15. Pan and zoom the map to view the data.

    The majority of counties that have reported data have higher mortality rates for Black women. This map shows where the variation in mortality rates occurs, proving that the gap in mortality rates is a national problem.

    Final mortality rate difference map

    The majority of counties are blue, meaning that breast cancer mortality rates are higher for Black women compared to White women. Red counties are those where the breast cancer mortality rates are higher for White women compared to Black women, and yellow counties are those where the mortality rates are the same.

  16. Return to the full extent of the data and save the workbook.

You've analyzed data about mortality rates for Black women and White women and symbolized it to show the large scope of the problem. Next, you will map the breast cancer mortality rates as a rate ratio and identify hot spots of high and low racial disparities.


Map the mortality rate ratio

Previously, you mapped the differences in breast cancer mortality rates for Black women and White women. Next, you'll determine how wide the mortality rate gap is in each county. You'll calculate this gap using a rate ratio, which compares rates (such as mortality rates) in two groups that differ by demographic characteristics.

Using this statistic, you'll perform a hot spot analysis to map clusters of statistically significant gaps.

Calculate the mortality rate ratio

A rate ratio gives the likelihood of an outcome for a specific group. For example, a rate ratio of 5 in a specific county would mean that a Black woman with breast cancer in that county is five times more likely to die of the disease than a White woman.

The rate ratio is calculated by dividing the rate for the primary group of interest (in your case, Black women) by the rate for a comparison group (White women). You'll create a page in your workbook to perform the calculation.

  1. If necessary, open your Breast Cancer Mortality workbook in Insights.
  2. Drag the Dual-Data Mortality dataset from the data pane to the New page button.

    Filtered Dual-Data Mortality dataset dragged to the New page button.

    A page is created with the Dual-Data Mortality dataset included in the data pane.

  3. Rename Page 3 to Mortality rate ratio.
  4. Drag the Dual-Data Mortality dataset from the data pane to the page and into the Map drop zone.

    A map card is created. Because you created this page using the filtered dataset, the data is already filtered to show only counties with data for both Black women and White women.

    To calculate the rate ratio, you'll use a spatial analysis tool.

  5. Confirm that the map card is activated. Click the Action button.

    Action button

    The Analytics pane appears. It has two tabs. The Spatial analysis tab lists spatial analysis tools, whereas the Find answers tab provides access to both spatial and nonspatial tools and functions.

  6. Click the Find answers tab.

    Questions you want to answer

    On this tab, the analysis capabilities are organized by the questions you want to answer.

  7. Click How is it related and choose Calculate Ratio.

    Choose the Calculate Ratio tool.

    The Calculate Ratio tool appears. You'll choose the field of interest and the comparison field by which to divide it.

  8. For numerator, choose Black Mortality Rate. For denominator, choose White Mortality Rate. For Name the result field, type Mortality Rate Ratio.

    Calculate Ratio tool parameters

  9. Click Run.

    The tool runs. When it finishes, the data table opens and a new field is added to the end with the rate ratio calculations.

  10. Scroll to the end of the table. Click the arrows next to the Mortality Rate Ratio field twice to sort the field in descending order.

    Arrows to sort the Mortality Rate Ratio field in descending order

    Values greater than 1 are counties where the breast cancer mortality rate is higher for Black women compared to White women. Values less than or equal to 1 are counties where the breast cancer mortality rate is the same or lower for Black women compared to White women.

  11. Close the table.

Symbolize the values

For your previous maps, you used colors to indicate differences in values. For the rate ratio map, you'll still use colors to indicate whether the mortality rate is higher or lower for both Black and White women. However, you'll also give each county a circle symbol and change the symbol's size based on how large the rate ratio is. This style will convey the magnitude of the rate ratios.

  1. In the data pane, expand the Dual-Data Mortality dataset and drag the Mortality Rate Ratio field to the map.

    Drag Mortality Rate Ratio to map.

    The map is styled by graduated colors using the Mortality Rate Ratio field.

    Mortality rate ratio map

  2. On the ribbon, click the Basemap button and choose Light Gray Canvas. Click a blank space on the page to deactivate the map card and rename it Mortality rate ratio.

    First, you'll filter the dataset so you can update the style only for counties where the mortality rate is higher for Black women than White women.

  3. Click the map card to activate it and click the Card filter button. In the New Filter pane, for Filter by, choose Mortality Rate Ratio.

    A histogram chart appears with all the values for the selected field.

  4. Click the node on the left side of the chart, change its value to 1, and press Enter. Click Apply.

    The filter applies. The map now shows only counties where the rate ratio is higher than 1 (meaning the breast cancer mortality rates for Black women are higher than White women). Next, you'll rename the new filtered dataset and change the symbology for these counties.

  5. In the data pane, rename the new filtered Dual-Data Mortality dataset to Higher Black Mortality Rate.
    Rename dataset.
  6. On the map card, next to the Mortality Rate Ratio layer name, click the arrow. In the Layer options pane, click the Options tab.
  7. For Symbol type, choose Counts and Amounts (Size).

    Counts and Amounts (Size) option

    The symbols on the map change to circles with varying sizes based on their value. You'll adjust the number of classes, the class breaks, and the color of the symbols to create a more legible and appealing map.

  8. Click Classification and change Number of classes to 3.
  9. On the Classification histogram, drag and change the second highest class break to 2.0, and the next lowest class break to 1.5.
    Note:

    In this case, it's best to update the highest class break first because sometimes the class breaks will overlap if updated from lowest to highest.

    Histogram of mortality rate ratios with class breaks

    Next, you'll update the symbol's color. You'll also give it transparency to make it easier to see overlapping symbols.

  10. Click the Style tab. For Fill color, choose the medium pink color (hex value #FF73DF). Set Transparency to 50 percent.

    Fill color and Transparency

  11. Set Outline thickness to 0.5 px. For Outline color, choose the black color in the second column, bottom row (hex value #1A1A1A).

    Outline color

  12. For Size (min - max), set the max size to 20.

    Max symbol size set to 20 px.

  13. Close the Layer options pane. On the map card, zoom in to view the symbols better.

    Map with counties symbolized by size.

    You've symbolized counties with breast cancer mortality rates that are higher for Black women compared to White women. Next, you'll add another layer to the map to symbolize counties where the breast cancer mortality rate is higher for White women.

  14. Drag the Dual-Data Mortality dataset from the data pane to the map card and into the Add new layer drop zone.

    A layer with all of the rate ratios is added to the map.

    Added layer

    You'll filter this layer to only show counties with higher mortality rates for White women.

  15. On the map card ribbon, click the Card filter button. In the Card Filters pane, click New Filter.

    You can choose to filter fields from either of the datasets on the map. Both datasets are named Dual-Data Mortality, so it can be difficult to distinguish between them. The layer that was added first will be displayed first in the list of fields. You want the second Dual-Data Mortality dataset, which you just added.

  16. For Filter by, click Choose a field to expand the menu of available fields. Click the first Dual-Data Mortality dataset to collapse its fields.

    Only the fields for the second Dual-Data Mortality dataset remain visible.

    First Dual-Data Mortality dataset with fields collapsed

  17. For the second Dual-Data Mortality dataset, choose the Mortality Rate Ratio field.

    The field is selected. You'll filter it to only show values less than 1.

  18. On the histogram chart, click the upper threshold and change its value to 1.

    Upper value for histogram chart

  19. Click Apply and close the Card Filters pane.

    The dataset is filtered. Next, you'll rename the new filtered dataset and change its symbology to be a different color than the other layer.

  20. In the data pane, rename the new filtered Dual-Data Mortality dataset to Higher White Mortality Rate.
  21. On the map card, next to the Higher White Mortality Rate layer name, click the arrow. In the Layer options pane, click the Options tab.

    Layer options

  22. In the Layer options enter the following:
    • For Style by, choose Mortality Rate Ratio.
    • For Symbol type, choose Counts and Amounts (Size).
    • Expand Classification and for Number of classes, type 1.

    Layer options pane

  23. Click the Style tab. For Fill color, choose the medium blue color (hex value #73B2FF). Change Transparency to 25 percent.

    Fill color set to teal with 50 percent transparency.

  24. For Outline thickness, type 0.5 px. For Outline color, choose the black color in the second column, bottom row (hex value #1A1A1A).

    The symbol for counties where mortality rates are higher for White women are now drawn on the map using a different color than counties where mortality rates are higher for Black women.

  25. Close the Layer options pane. Save the workbook.

    Final map

Perform hot spot analysis

Based on your map, it appears that most counties with the highest mortality rates are located in the south central and eastern coastal parts of the United States. To confirm this assessment, you'll run a hot spot analysis in ArcGIS Online.

Hot spot analysis finds statistically significant clusters of high and low values using the Getis-Ord Gi* statistic (pronounced G-i-star). Where mortality rate ratios are high and clustered together spatially, you have a hot spot. Cold spots, on the other hand, are clusters of low values.

First, you'll share your data so you can perform the hot spot analysis in ArcGIS Online.

  1. In the data pane, point to the Dual-Data Mortality dataset, click the Dataset options button, and choose Share data.

    Share data option

    The Share data window appears.

  2. In the Share data window, enter the following:
    • For Title, type Mortality Ratio.
    • For Tags, type breast cancer, mortality rates, public health, racial equity.
    • For Description, type The ratio of breast cancer mortality rates for Black women and White women in the United States.

    Share data window

  3. Click Share.

    The data is shared as a hosted feature layer that can be accessed in ArcGIS Online.

  4. In the data pane, click Open item.

    Open item link

    The item page for the feature layer opens in a new browser tab.

  5. Click Open in Map Viewer Classic.

    Open in Map Viewer Classic button

    Note:

    ArcGIS Online offers two map viewers for viewing, using, and creating maps. For more information on the map viewers available, see FAQ.

    This lesson uses Map Viewer Classic.

    The layer opens in Map Viewer Classic with the Change Style pane open. You don't need to change the layer symbology before running your analysis.

  6. In the Change Style pane, click Cancel. If necessary, navigate to the full extent of the United States.
  7. On the ribbon, click the Analysis button.

    Analysis button

  8. In the Perform Analysis pane, click the Analyze Patterns toolbox and click Find Hot Spots.

    The Find Hot Spots tool appears.

  9. For Find clusters of high and low, choose Mortality Rate Ratio.

    Parameters for the Find Hot Spots tool

  10. For Result layer name, add your name or initials to the end of the layer name to make sure it is unique in your organization. Uncheck Use current map extent and click Run Analysis.

    The tool runs. When it is finished, the hot spots layer is added to the map and the Contents pane. It can be difficult to see the layer clearly because of the Mortality Ratio layer and the basemap.

  11. In the Contents pane, uncheck the Mortality Ratio layer.
  12. On the ribbon, click Basemap and choose Light Gray Canvas.

    Change basemap.

    The layer is more visible, but the city names and other labels obscure some areas of the map. You'll remove them.

  13. In the Contents pane, click the arrow next to the Light Gray Canvas basemap.

    Arrow to expand the Light Gray Canvas layer

    The basemap layer expands. It includes two components: Light Gray Reference and Light Gray Base. The reference layer is the one with the labels.

  14. Point to the Light Gray Reference layer, click the More Options button, and choose Remove.

    Remove option

  15. In the Remove window, click Yes, Remove Layer.

    The map is now displayed without city labels.

    Hot spots map on Map Viewer

    The hot spots indicating clusters of counties where the breast cancer mortality rate for Black women is higher than the mortality rate for White women are shown in bright red. Cold spots, which are clusters of counties where breast cancer death rates for both Black and White women are similar, are shown in blue.

  16. Click the Show Map Legend button.

    Show Map Legend button

    The legend appears.

    Map legend

    The output from the Find Hot Spots tool tells you how confident you can be that the spatial clustering of high or low values is statistically significant. A hot spot with a 99 percent confidence level, for example, means there is only one chance out of 100 that a tight spatial cluster of high values is due to random chance. Finding a spatial cluster of high values that is statistically significant gives you confidence that the clustering is not the result of some random process, but rather suggests other factors may be contributing to the higher concentration of disparities (such as differences in environment, local land use policy, access to quality health care, genetics, life style choices, and so on).

    On your map, there are few areas with 99 percent confidence. However, there are several areas with 95 or 90 percent confidence.

  17. Optionally, save the web map.

For the counties with available data on breast cancer mortality, your analysis identified clusters of disproportionately high mortality rates among Black women compared to the mortality rate of White women. There is a hot spot clustered in the southern region of the United States, particularly in Louisiana, Arkansas, and Mississippi, similar to the patterns identified in the Mortality Rate Ratio map. But the hot spot cluster around North Carolina and South Carolina was not easily visible in previous maps. There is also a distinct cold spot cluster in the Northeast, indicating there was less of a racial disparity in the breast cancer mortality rate between Black women and White women in this region.

Your findings of geographic clusters of racial disparity between Black and White women breast cancer mortality rates affirms the growing body of scientific evidence that the legacy of racial segregation and access to breast cancer care has contributed to the racial disparity still evident today.

In this lesson, you explored the available data on breast cancer mortality for Black and White women in the United States. You mapped the difference in breast cancer mortality rates between the two racial groups and determined whether there was a racial disparity in breast cancer mortality rates, and if so, where it is located. You calculated the mortality rate ratio and analyzed hot spots to determine statistically significant clusters.

You can find more lessons in the Learn ArcGIS Lesson Gallery.