Data Source

Registry

Type of Study

collection of mortality data and life tables

Data gathering method

Original raw data provided by national statistical offices

Ease

Tables can be downloaded, free of charge, after registration

Conditions of access

Formal agreements (e.g. fees, research contracts, institutional agreements, etc.)

Must register online

Time elapsed between application and reception of data

N/A

Type of available data (e.g. anonymised microdata, aggregated tables, etc.)

Anonymised microdata, aggregated tables

Formats available

Excel

Language issues

Data and documentation are available in English.

Years of collection, reference years, and sample sizes

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

First year of collection

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

Stratification if applicable

N/A

Base used for sampling

N/A

Geographical coverage and breakdowns

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.

Age range

N/A

Coverage of main and cross-cutting topics

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.

Further Reading

• 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.

Standardisation

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

Possibility of linkage among databases

No

Entry errors if applicable

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

Breaks

N/A

Consistency of terminology or coding used during collection

N/A

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.