Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

Human Mortality Database (HMD)
Human Mortality Database (HMD)

Topic
Health and Performance
Relevance for this Topic
Country Europe
URL
More Topics

Governance

Contact information

John R. Wilmoth, Director (University of California, Berkeley); Vladimir Shkolnikov, Co-Director (Max Planck Institute for Demographic Research, Rostock); Project Coordinator Magali Barbieri (INED)
University of California, Berkeley and Max Planck Institute for Demographic Research
Konrad-Zuse-Straße 1
18057 Rostock
Germany
Email: hmd(at)mortality.org
Url: http://www.mortality.org/

Timeliness, transparency

N/A

Type of data


Registry

Type of Study


collection of mortality data and life tables

Data gathering method


Original raw data provided by national statistical offices


Access to data


Tables can be downloaded, free of charge, after registration

Conditions of access


Must register online


N/A


Anonymised microdata, aggregated tables


Excel


Data and documentation are available in English.


Coverage


Availability depending on the country. Most of the tables are available for the period 1925-2009


The project was initiated in 2000. Data dates back to 19th century.


N/A


N/A


Australia, Australia, Belarus, Belgium, Bulgaria, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Lithuania, Iceland, Ireland, Israel, Italy, Japan, Latvia, Lithuania, Luxembourg, Netherlands, New Zealand, Norway, Poland, Portugal, Russia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Taiwan, U.K., U.S.A., Ukraine. No regional division except for UK and Germany. Mortality series are provided separately for England, Wales, Scotland and Northern Ireland; East and West Germany.


N/A


The Human Mortality Database (HMD) was created to provide detailed mortality data to researchers, students, journalists, policy analysts, and others interested in the history of human longevity. The HMD contains original calculations of death rates and life tables for national populations, as well as the input data used in constructing those tables. The input data consists of death counts from vital statistics, plus census counts, birth counts, and population estimates from various sources. The data allows for comparative studies of mortality and analyses of time trends in mortality decline. It is also possible to use the data for assessing mortality risk among specific populations (i.e. by country, sex, age), as well for making mortality and population projections.


• Hill, K. Choi, Y., & Timaeus, I. "Unconventional approaches to mortality estimation". Demographic Research 13(12) (2002): 281-300. • Gómez-Redondo, R., & Boe, C. "Decomposition analysis of Spanish life expectancy at birth". Demographic Research 13(20) (2005): 521-546. • Kruger, D. J., & Nesse, R. M. "An evolutionary life-history framework for understanding sex differences in human mortality rates". Human Nature 17(1) (2006): 74-97. • Li, N., & Lee, R. "Coherent mortality forecasts for a group of populations: An extension of the Lee-Carter method". Demography 42(3) (2005): 575-594. • Vaupel, J. W. "Biodemography of human ageing". Nature 464(7288) (2010): 536-542. • Christensen, K., et al. "Ageing populations: the challenges ahead". The Lancet 374(9696) (2009): 1196-1208.


Linkage


Despite the different sources used (national providers), all the datasets are subjected to the same harmonisation criteria.


No


Data quality


Estimated data is clearly stated. Data is carefully checked to avoid errors.


N/A


N/A


Applicability


The HMD is a clear and succinct database on mortality indicators, perfectly suitable for conducting studies on changes in life expectancy and longevity. One of the main advantages of the HMD is the standardisation and international comparability of the data. For the sake of comparability, general principles described in the Methods Protocol (available online) are followed for all populations in the HMD. However, exact uniformity of methods is not always possible because data at the required level of detail are not available in all situations. Therefore, in a few special cases, special methods to accommodate the realities of the available data were developed. Information on these special methods is accessible via the webpage.


  • The information about this dataset was compiled by the author:
  • Diana Lopez-Falcon
  • (see Partners)