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Mortality by Socioeconomic Category in the United States

Author

Magali Barbieri, Ph.D., University of California-Berkeley

Table of Contents

Summary
Report
Podcast
Excel Data Files
Data Visualizations
Acknowledgements

Summary

This SOA-sponsored research report presents mortality analysis and rate estimates for the United States by year from 1982 through 2018, separately by socioeconomic quintile and decile. Details on the development of the estimates are summarized in the report. The life tables by socioeconomic category are available for download, and some of the results are presented in online graphs and maps, and a data summary report.

The results were produced by combining data from three sources:

Separately for each year of data, a Socioeconomic Index Score was computed for each county. The Socioeconomic Index Scores, in turn, were used to group counties into deciles, with each decile holding 10% of the total U.S. population. Mortality rates were then estimated for each decile. In addition, a parallel analysis was performed using quintiles rather than deciles.

This web page, the associated report and the online data visualizations were initially released by the SOA in November 2020, using mortality data from the CDC-Wonder database.

To address constraints in the CDC-Wonder data, the socioeconomic mortality analysis was repeated in December 2020, using a restricted dataset from the National Centers for Health Statistics with data back to 1982 and covering ages up to 110+. Rather than presenting this second (and broader) set of results alongside those generated using the CDC-Wonder data, the initial set of results (both the report and the data visualizations) was removed from the website, and replaced with an updated report and visualizations that reflect the new data. The results of the initial analysis and the updated analysis are broadly similar, but the updated analysis offers the advantage of a longer data history and data for individual ages 85+.

Report

Mortality by Socioeconomic Category in the United States

Video

Podcast

Excel Data Files

County-Level Socioeconomic Data

Mortality Rate Estimates by Age, Sex and Socioeconomic Index Quintile

Mortality Rate Estimates by Age, Sex and Socioeconomic Index Decile

Data Visualizations


These interactive dashboards are visualizations of key metrics found in the report. They provide filtering, drill-down, and other interactive capabilities that allow you to focus on specific subsets of the data.

Map of County-Level Socioeconomic Index Quintiles

Launch Interactive Dashboard

This map shows the socioeconomic index quintile of each county across time. Quintile "1" captures the bottom 20% of the population, while quintile "5" captures the upper 20%. The rankings for years 1990 and 2000 were determined using data from the Decennial Census, while the rankings from 2007 through 2016 were determined using data from the American Community Survey (ACS). Note that 5-year samples were used from the ACS. Thus, what is labeled as "2007" on the map is based on an ACS dataset that runs from 2005 through 2009. Similarly, "2008" is based on an ACS dataset that runs from 2006 through 2010. In other words, the data label is the mid-point of each 5-year ACS sample. Use the year control on the right side of the exhibit to advance across time. The upper portion of the year control enables a user to manually step forwards or backwards through time, while the lower portion of the control activates a loop which automatically cycles forwards or backwards through time, rather like playing a video.

Map of County-Level Socioeconomic Index Deciles

Launch Interactive Dashboard

This map shows the socioeconomic index decile of each county across time. Decile "1" captures the bottom 10% of the population, while decile "10" captures the upper 10%. The rankings for years 1990 and 2000 were determined using data from the Decennial Census, while the rankings from 2007 through 2016 were determined using data from the American Community Survey (ACS). Note that 5-year samples were used from the ACS. Thus, what is labeled as "2007" on the map is based on an ACS dataset that runs from 2005 through 2009. Similarly, "2008" is based on an ACS dataset that runs from 2006 through 2010. In other words, the data label is the mid-point of each 5-year ACS sample. Use the year control on the right side of the exhibit to advance across time. The upper portion of the year control enables a user to manually step forwards or backwards through time, while the lower portion of the control activates a loop which automatically cycles forwards or backwards through time, rather like playing a video.

Expected Lifetimes by Year, Sex, Age and Socioeconomic Index Quintile

Launch Interactive Dashboard

Using this graph's controls, you may select which sex, age group(s), socioeconomic index quintile(s) and years you wish to display. Note that the year labels on the graph's horizontal axis are determined automatically by Tableau, and are typically intermediate time points rather than end points. For example, if you select the year range from 1999 to 2018 to plot, the axis labels might be 2003, 2009 and 2015. While 1999 and 2018 are not shown as axis labels, the full user-specified time period is indeed plotted on the graph.

Expected Lifetimes by Year, Sex, Age and Socioeconomic Index Decile

Launch Interactive Dashboard

Using this graph's controls, you may select which sex, age group(s), socioeconomic index decile(s) and years you wish to display. Note that the year labels on the graph's horizontal axis are determined automatically by Tableau, and are typically intermediate time points rather than end points. For example, if you select the year range from 1999 to 2018 to plot, the axis labels might be 2003, 2009 and 2015. While 1999 and 2018 are not shown as axis labels, the full user-specified time period is indeed plotted on the graph.

Mortality Rate Estimates by Year, Sex, Age Group and Socioeconomic Index Quintile

Launch Interactive Dashboard

This exhibit contains 2 graphs, each displaying mortality rates by socioeconomic index quintile. Each rate is the probability that an individual who is alive at the beginning of the age interval will die before the end of that age interval. For example, the rate for ages 10 through 19 is the probability that an individual who is alive at age 10 will die before reaching the age of 20. Age zero is placed in a group by itself.

Graph 1 shows mortality rates on a standard scale, while Graph 2 shows the same rates on a logarithmic scale. On a logarithmic scale, the values 0.1%, 1%, 10% and 100% are equally spaced.

You may select which sex, age group(s), socioeconomic index quintile(s) and years you wish to display. Note that the year labels on the graph's horizontal axis are determined automatically by Tableau, and are typically intermediate time points rather than end points. For example, if you select the year range from 1999 to 2018 to plot, the axis labels might be 2003, 2009 and 2015. While 1999 and 2018 are not shown as axis labels, the full user-specified time period is indeed plotted on the graph.

Mortality Rate Estimates by Year, Sex, Age Group and Socioeconomic Index Decile

Launch Interactive Dashboard

This exhibit contains 2 graphs, each displaying mortality rates by socioeconomic index decile. Each rate is the probability that an individual who is alive at the beginning of the age interval will die before the end of that age interval. For example, the rate for ages 10 through 19 is the probability that an individual who is alive at age 10 will die before reaching the age of 20. Age zero is placed in a group by itself.

Graph 1 shows mortality rates on a standard scale, while Graph 2 shows the same rates on a logarithmic scale. On a logarithmic scale, the values 0.1%, 1%, 10% and 100% are equally spaced.

You may select which sex, age group(s), socioeconomic index decile(s) and years you wish to display. Note that the year labels on the graph's horizontal axis are determined automatically by Tableau, and are typically intermediate time points rather than end points. For example, if you select the year range from 1999 to 2018 to plot, the axis labels might be 2003, 2009 and 2015. While 1999 and 2018 are not shown as axis labels, the full user-specified time period is indeed plotted on the graph.

Mortality Improvement Rate Estimates by Year, Sex, Age Group and Socioeconomic Index Quintile

Launch Interactive Dashboard

This exhibit contains 3 graphs, comparing mortality rates at the beginning and end of a user-specified time interval. Use the "First Year" and "Last Year" parameters on the right side of the screen to specify this interval. Additional parameters are available to determine which sex and quintiles to graph.

Each mortality rate is defined as the probability that an individual of age "x" dies before reaching age "x+10". For example, for age group 60-69, the graph shows the probability that an individual who is exactly 60 years old will die before reaching the age of 70.

Graph 1 shows annualized rates of mortality improvement across the user-specified period. Consider the following example: the mortalilty rate in 2000 is 10%, and the mortality rate in 2010 is 8%. In this case, the annualized rate of mortality improvement would be computed as follows: 1 - (8% / 10%) ^ (1 / 10) = 2.2%.

Graph 2 shows the mortality rate in the final year of the user-specified period, divided by the mortality rate in the initial year. A value of 100% indicates that the initial and final mortality rates are identical. A value greater than 100% indicates that mortality has increased, while a value less than 100% increases that mortality has decreased.

Graph 3 compares mortality rates in the first and final years.

Mortality Improvement Rate Estimates by Year, Sex, Age Group and Socioeconomic Index Decile

Launch Interactive Dashboard

This exhibit contains 3 graphs, comparing mortality rates at the beginning and end of a user-specified time interval. Use the "First Year" and "Last Year" parameters on the right side of the screen to specify this interval. Additional parameters are available to determine which sex and quintiles to graph.

Each mortality rate is defined as the probability that an individual of age "x" dies before reaching age "x+10". For example, for age group 60-69, the graph shows the probability that an individual who is exactly 60 years old will die before reaching the age of 70.

Graph 1 shows annualized rates of mortality improvement across the user-specified period. Consider the following example: the mortalilty rate in 2000 is 10%, and the mortality rate in 2010 is 8%. In this case, the annualized rate of mortality improvement would be computed as follows: 1 - (8% / 10%) ^ (1 / 10) = 2.2%.

Graph 2 shows the mortality rate in the final year of the user-specified period, divided by the mortality rate in the initial year. A value of 100% indicates that the initial and final mortality rates are identical. A value greater than 100% indicates that mortality has increased, while a value less than 100% increases that mortality has decreased.

Graph 3 compares mortality rates in the first and final years.

Survival Probabilities by Year, Sex and Socioeconomic Index Quintile

Launch Interactive Dashboard

This exhibit contains 3 graphs, each of which shows the probability of surviving from an initial age to a subsequent age "X". In graphs 1, 2 and 3, the initial age is 60, 20 and 0, respectively. You may select which year(s), sex (or sexes) and socioeconomic index quintile(s) you wish to display.

Survival Probabilities by Year, Sex and Socioeconomic Index Decile

Launch Interactive Dashboard

This exhibit contains 3 graphs, each of which shows the probability of surviving from an initial age to a subsequent age "X". In graphs 1, 2 and 3, the initial age is 60, 20 and 0, respectively. You may select which year(s), sex (or sexes) and socioeconomic index decile(s) you wish to display.

National-Level Mortality Rate Estimates: Comparison with SSA

Launch Interactive Dashboard

Quintiles and deciles do not play a role in this exhibit. Rather, the entire dataset was used to estimate national-level mortality rates. These rates are labeled "NCHS-CDC" in the graph below, and are compared to rates developed by the Social Security Adminstration (SSA). Note that the SSA rates are smoothed, while the NCHS-CDC rates are unsmoothed. Also, the NCHS-CDC analysis based death rates on NCHS deaths and Census populations for all ages, while SSA bases death rates on NCHS deaths and Census populations for under 65, and also incorporates Medicare deaths and enrollments for ages 65 and older.

Each mortality rate is the probability that an individual who is alive at age "x" dies before reaching age "x+1".

Graph 1 shows mortality rates on a standard scale, while Graph 2 shows the same rates on a logarithmic scale. On a logarithmic scale, the values 0.1%, 1%, 10% and 100% are equally spaced.

You may use the controls on the right-hand side of the graph to select which sex (or sexes), and ages to display. Use the year control to advance across time. The upper portion of the year control enables a user to manually step forwards or backwards through time, while the lower portion of the control activates a loop which automatically cycles forwards or backwards through time, rather like playing a video.

Acknowledgements

Thank you to the following individuals who served on the Project Oversight Group:

Philip Adams, FSA, CERA, MAAA
Mary Bahna-Nolan, FSA, CERA, MAAA
Mark Bye, ASA
Jean-Marc Fix, FSA, MAAA
Sam Gutterman, FSA, CERA, MAAA, FCAS, FCA, HONFIA
Edward Hui, FSA
Al Klein, FSA, MAAA
Larry Pinzur, PhD
Marianne Purushotham, FSA, MAAA
Manny Santos, FSA, FCIA
Joel Sklar, ASA, MAAA
Larry Stern, FSA, MAAA
Dale Hall, FSA, CERA, MAAA, SOA Managing Director of Research
Jan Schuh, SOA Sr. Research Administrator
Ronora Stryker, ASA, MAAA, SOA Sr. Practice Research Actuary
Patrick Wiese, ASA, SOA Modeling Actuary

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