Data Utilization and Preparation

In this section, we will discuss the data layer of the app. It will be consisted of two parts:

• Data Sets Utilized
• Data Processing

Primarily there are two data sets used in this app: CDC WONDER Detailed Mortality Data and County Health Ranking Social Determinants Data. The former one is consisted only with county level mortality rate while the later one is actually an aggregation of several data sets.

Data sources

CDC WONDER Mortality

The county level mortality data is grouped in three-year-block. More detailed discussion of why we are grouping mortality rate in such a manner can be found in Other Restrictions under Data Sources section. The primary reason is to deal with missing values, e.g. the mortality rate could be suppressed if it is not prevalent enough (less than 9 reports per 10⁵ people). Here we will briefly discuss the reason for choosing a specific subset to mortality data.

To understand the major causes of mortality, we selected the leading causes of death and their definitions were take from Stein et al. "The Epidemic of Despair Among White Americans: Trends in the Leading Causes of Premature Death, 1999–2015", American Journal of Public Health, 107(10):1541–1547, 2017.

Link to the website can be found here: CDC WONDER Multiple Causes of Deaths

ICD-10 Code

The cause of death is selected based on the ICD-10 code. Currently, the selected causes of deaths are: Despair (F10-F19, X40-X49, X60-X84, Y10-Y19), Cancer (C00-C97), Cardiovascular Disease (I00-I99), Assault (X85-Y09), and All Cause death as defined by CDC Wonder. Other causes of death could be added but care must be taken that they are prevalent enough so that CDC Wonder does not suppress rates for many counties. For less prevalent causes in the future, the mortality rates could be calculate for 4 or 5 year chunks, instead of 3, to ensure more reliable mortality rate estimation.

Age Range

In order to correspond with the result reported by the paper mentioned above, we only choose a subset of the population. Only reported death of 25-64 were selected for further analysis and visualization.

County Health Ranking Social Determinants

To investigate the possible causes of mortality rate trend behind, we collected social determinants data from County Health Ranking website. Though the data set is downloaded from a single website, it is actually an aggregation of multiple data sources like CDC Wonder, Census Bureau, and USDA Food Environment Atlas. Links to the primary sources can be found under Data Sources section.

Data Processing

Before carrying out analysis and corresponding data visualization, we need to use loaders to transform the raw data files first. There are several reasons for doing this instead of importing the raw data files directly:

• Common factors or identifiers, e.g. county names, have to have the same string representations as well as the same data types.
• Missing values should be either removed or imputed.
• Not all of the social determinants data are relevant. So some filtering operations, either by algorithm or by hand, are needed.

For more information, please refer to the Data Preparation section.