...mortality data by race/ethnicity, education, income…?
What type of information will I NOT find here?
Where can I find such information?
What areas do you plan to add in the near future?
Do you plan to extend existing data series farther back in time?
How often is the USMDB updated?
What do people use these data for?
Why are some period death rates larger than 1.0?
Do I have to register?
At the moment, while still under review, access to the website is granted to users with explicit permision from the USMDB team with a universal i.d. and password. We soon will require you to individually register before accessing the data in order to obtain basic contact information (i.e., your name, e-mail address, affiliation, and title) because we may occasionally need to contact you with important messages about the database (e.g., updates, other critical information). We also use it to track usage for different types of users. Your information is for internal use only and we will never distribute it to a third party without your authorization. Once we implement individual registration, we will updated the FAQ with more information on how to register.
Are the data free?
Yes.
Do you have data on cause of death?
Not yet, but we are planning to provide access to some cause-of-death data in the future. Meanwhile, you can obtain cause-of-death data for the United States as a whole (and for the US States and counties above 100,000 population for years before 2004) on the NCHS website, at https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm)
Do you have data by county?
Yes (as of September 28, 2021) 5x1 period life tables for all US Counties by sex for the period 1982-2018 are available here.
Do you have infant mortality rates (IMR)?
Yes. We consider q(0) -- the probability of dying in the 1st year of life -- from the life table to be the best indicator of infant mortality. The q(x)'s for a given calendar year are provided in the 1x1 life tables. For example, in the United States as a whole, q(0) was 0.02294 for girls in 1959, meaning that for 1,000 female births, 23 died before reaching their first birthday (the infant mortality rate was 22.94 per thousand).
Note that the "infant mortality rate" calculated as the probability of dying during the first year of life, q(0), is NOT in fact a rate but a probability.
Do you have fertility data?
No, the USMDB includes mortality data series only.
Do you have mortality data by race/ethnicity, by education, by income…?
No. The USMDB currently includes mortality data only for tht total population (and by sex and age).
Do you have data by month or by day?
No. The USMDB does not provide data by month or by day but only by year.
The Human Mortality Database is the result of a collaboration between the Department of Demography at the University of California, Berkeley (UC Berkeley); the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany; and, more recently, the French Institute for Demographic Studies (INED) in Paris, France. Both UC Berkeley and INED were heavily involved in establishing the USMDB, which relied largely on the methodological tools developed within the HMD with the involvement of MPIDR and other past contributors.
In the Human Mortality Database, users have access to all of the original data that have been used to compute the life tables (input death counts by sex and age, input birth counts by sex, census population by sex and age, and annual population estimates by sex and age when and where available). Because of confidentiality issues related to the problem of small numbers, we are not authorized to publish the raw death counts that were used for the USMDB lifetable calculations below the national level for years since 2004. In fact, we had to work within a protected environment (the University of California, Berkeley Research Data Center) to access these restrictive data and had to carry out all of our calculations there. We do not have permission to take the tabulation of raw death counts outside of the Research Data Center.
Original tabulations of death counts by geography, sex and age
Mortality data by cause of death – at least not yet
Population forecasts/projections of any kind
Data on morbidity (i.e., illness/disease)
Data on fertility
Mortality data at the county level or other small areas (metropolitan areas, zip codes, census blocks, etc…)
Mortality data by race/ethnicity, education or income
Proportion of people with blond hair and blue eyes
Mortality data, death counts and birth counts by month or by day
Where can I find such information?
Ask a librarian (it's their job!).
The Human Mortality Database has already inspired the development of two other regional databases: the Canadian Human Mortality Database (or CHMD, at http://www.bdlc.umontreal.ca/chmd/) and the Japanese Mortality Database (at http://www.ipss.go.jp/p-toukei/JMD/index-en.asp). Both databases were developed by teams independent from the HMD (i.e. at the University of Montreal for the CHMD and at the National Institute for Population and Security Research for the Japanese Mortality Database).
The USMDB team has initiated work to develop a French Mortality Database, with data series at the level of the Départements but additional resources are needed before this project can take off.
Furthermore, the Max Planck Institute for Demographic Research (MPIDR), one of the two founding institutions for the Human Mortality Database, is currently investigating the possibility to construct a regional German Mortality Database.
As far as we know, there is no other plans to develop regional database under the HMD umbrella at this point.
What areas do you plan to add in the near future?
We are trying to raise funding to add US county-level life tables in the future.
Do you plan to extend existing data series farther back in time?
Possibly. Theoretically, state-level vital statistics have been collected in a systematic way since 1933. Before 1933, the vital registration system was not considered as fully reliable in some parts of the country. However, the data necessary for lifetable calculations are not readily available so a lot of work is required before such calculations can be carried out. We are not ruling out the possibility to carry out such work in the future but we do not have the resources necessary at the moment to do so.
How often is the USMDB updated?
The USMDB will be updated once a year as new mortality and population data become available.
Who can use these data?
Anyone may use the USMDB data (after registering), but USMDB users are typically professional demographers, actuaries, and other persons with demographic training. The USMDB is designed for users who have a basic knowledge of demographic methods. If you cannot answer the following question, "What is a life table?", then your ability to make effective use of these data will be rather limited.
In the future, we plan to develop additional tools (Excel spreadsheets of basic mortality indicators by area and calendar year, state report cards, dynamic graphic utilities…) to provide access to the USMDB data to people without demographic training (journalists, policy makers, physicians, state health planners, and the general public).
What do people use these data for?
These data are used primarily for research and teaching purposes. For example, researchers use these data to study trends in the US geographic inequalities in mortality. Demographers and actuaries may also use these data to assess mortality risk among specific populations (i.e., by area, sex, age) for financial purposes. Others use these data for mortality and population projections and forecasts. In addition, educators use the USMDB for teaching courses in demography and actuarial science. Students often use the data for homework assignments in demographic methods or other courses.
Why are some period death rates larger than 1.0?
At older ages, the number of deaths and the exposure-to-risk, derived independently, eventually become quite small so that the former sometimes becomes larger than the latter, resulting in observed population death rates M(x) higher than 1. Because of such results, we smooth M(x) values at ages 80 and over before calculating the life table. This smoothing procedure ensures that the life table m(x) series remains below 1. Please, see the Human Mortality Database Methods Protocol (used to produce the USMDB lifetable series) for more details.
A Lexis triangle is half of a Lexis square. Lexis was a leading demographer who developed a graphical form of analysis of how events occur over age and time. The usual term is 'Lexis diagram' which will provide far more information in a search than the derived term 'lexis triangle'. Please see the Human Mortality Database Methods Protocol to understand how this is used in the USMDB project.