Human Mortality Database

Measure of public health

The Human Mortality Database (HMD) is a joint initiative of the Department of Demographics at the University of California, Berkeley in the United States and the Max Planck Institute for Demographic Research in Rostock, Germany that provides detailed mortality and population data to researchers, students, journalists, policy analysts, and others interested in the history of human longevity.[1][2][3] The key people involved are John R. Wilmoth (Director) from the University of California, Berkeley, Vladimir Shkolnikov (Co-Director) from Max Planck Institute for Demographic Research, and Magali Barbieri (Associate Director) from the University of California, Berkeley, and INED, Paris.[1]

## History

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### Creation of the Berkeley Mortality Database, a precursor to the Human Mortality Database

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In 1997, John R. Wilmoth at the Department of Demography in the University of California, Berkeley started work on a database titled the Berkeley Mortality Database (BMD) with a grant from the National Institute of Aging in the United States.[4] The BMD included data across the entire age range, but was restricted to only four countries (France, Japan, Sweden, and the United States).[5]

For the most part, the Berkeley Mortality Database is now superseded by the Human Mortality Database, but the BMD is still available online because some types of data available in the BMD have not been transferred to the HMD.

### Creation and development of the Kannisto–Thatcher Database on Old Age Mortality

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The Kannisto–Thatcher Database on Old Age Mortality (KTD) was founded in 1993 by Väinö Kannisto and Roger Thatcher with the support and collaboration of James Vaupel, Kirill Andreev, and many others.[5] The KTD was first developed at Odense University Medical School in Denmark. Since 1996, it has been maintained and developed by the Max Planck Institute for Demographic Research.[5]

Unlike the BMD, the KTD focused only on mortality above the age of 80, but included 30 countries (compared to the BMD, that included data for only 4 countries).[5]

### Creation and development of the Human Mortality Database

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HMD began in 2000 as a collaborative project of the Department of Demographics at the University of California, Berkeley in the United States and the Max Planck Institute for Demographic Research in Rostock, Germany, with funding from the National Institute of Aging in the United States.[5] It used data from the BMD (which had launched in 1997) and was also strongly influenced by the Kannisto–Thatcher Database on Old Age Mortality. After about two years of development, the HMD was formally launched in May 2002. HMD inherited the coverage of all age groups from BMD and the coverage of a diverse range of countries from KTD, thus combining the best features of both databases.[5]

The methods protocol of HMD has steadily evolved and was last updated on May 31, 2007.[6]

### Short-term Mortality Fluctuations data series (STMF)

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In response to the COVID-19 pandemic, the HMD team decided in 2020 to establish a new data resource: Short-term Mortality Fluctuations (STMF) data series in order to provide objective and internationally comparable data.[7]

Weekly death counts provide the most objective and comparable way of assessing the scale of short-term mortality elevations across countries and time.

These data are collected for 38 countries: Austria, Australia (Doctor certified deaths), Belgium, Bulgaria, Chile, Canada, Croatia, Czech Republic, Denmark, England and Wales, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Israel, Italy, Latvia, Lithuania, Luxembourg, Netherlands, New Zealand, Northern Ireland, Norway, Poland, Portugal, Republic of Korea, Russia, Scotland, Slovenia, Slovakia, Spain, Sweden, Switzerland, Taiwan and the USA.

Sources are national Statistics Office or european organisation Eurostat, based on official Vital record (excepted for Australia: Doctor certified deaths)

STMF Data are published under a CC-BY 4.0 License. They are available through an online STMF visualization toolkit or downloadable in CSV or XLSX format.

## Reception

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### Academic reception

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HMD data has been cited in academic research in demographic research and other research that relies of demographic data. For instance, there has been considerable research on the biological and evolutionary factors determining mortality and the differences in mortality across human populations.[8][9][10][11] The data has also been cited in research that attempts to build better predictive models of human mortality.[12] It has also been cited in research on specific causes of mortality[13] and research on the social and economic consequences of changes in mortality.[14]

### Media reception

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HMD data has been cited in the New York Times,[15][16] the Washington Post,[17] and Foreign Affairs.[18]

## References

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1. ^ a b "The Human Mortality Database". Retrieved June 20, 2014.
2. ^ "Human Mortality Database (ICPSR 00138)". Inter-university Consortium for Political and Social Research. 19 June 2006. Retrieved June 20, 2014.
3. ^ "The Human Mortality Database (HMD)". DLab, University of California, Berkeley. Retrieved June 20, 2014.
4. ^ "The Berkeley Mortality Database". Department of Demography, University of California, Berkeley. Archived from the original on July 27, 2014. Retrieved June 20, 2014.
5. ^ a b c d e f "HMD History". Archived from the original on May 20, 2014. Retrieved June 20, 2014.
6. ^ Wilmoth, John R.; Andreev, K.; Jdanov, D.; Glei, D. A. (May 31, 2007). "Methods Protocol for the Human Mortality Database" (PDF). Human Mortality Database. Archived from the original (PDF) on May 20, 2014. Retrieved June 20, 2014.
7. ^ "The Human Mortality Database". Human Mortality Database. Retrieved February 22, 2022.
8. ^ Kruger, Daniel J.; Nesse, Randolph M. (Spring 2006). "An Evolutionary Life-History Framework for Understanding Sex Differences in Human Mortality Rates" (PDF). Human Nature. 17 (1): 74–97\. CiteSeerX 10.1.1.409.5723. doi:10.1007/s12110-006-1021-z. PMID 26181346. S2CID 5685894. Archived from the original (PDF) on May 15, 2013. Retrieved June 20, 2014.
9. ^ Flachsbarta, Friederike; Caliebeb, Amke; Kleindorpa, Rabea; Blanchéc, Hélène; von Eller-Ebersteind, Huberta; Nikolausd, Susanna; Schreibera, Stefan; Nebela, Almut (February 24, 2009). "Association of FOXO3A variation with human longevity confirmed in German centenarians". Proceedings of the National Academy of Sciences. 106 (8): 2700–2705\. Bibcode:2009PNAS..106.2700F. doi:10.1073/pnas.0809594106. PMC 2650329. PMID 19196970.
10. ^ Vaupel, James W. (March 24, 2010). "Biodemography of human ageing". Nature. 464 (7288): 536–542\. Bibcode:2010Natur.464..536V. doi:10.1038/nature08984. PMC 4010874. PMID 20336136.
11. ^ Burger, Oskar; Baudische, Annette; Vaupel, James W. (October 30, 2012). "Human mortality improvement in evolutionary context". Proceedings of the National Academy of Sciences. 109 (44): 18210–18214\. Bibcode:2012PNAS..10918210B. doi:10.1073/pnas.1215627109. PMC 3497824. PMID 23071331.
12. ^ Li, Nan; Lee, Ronald (August 2005). "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method". Demography. 42 (3): 575–594\. doi:10.1353/dem.2005.0021. PMC 1356525. PMID 16235614.
13. ^ Murray, Christopher JL; Lopez, Alan D; Chin, Brian; Feehan, Dennis; Hill, Kenneth H (December 23, 2006). "Estimation of potential global pandemic influenza mortality on the basis of vital registry data from the 1918—20 pandemic: a quantitative analysis". The Lancet. 368 (9554): 2211–2218\. doi:10.1016/S0140-6736(06)69895-4. PMID 17189032. S2CID 22787011.
14. ^ Christensen, Kaare; Doblhammer, Gabriele; Rau, Roland; Vaupel, James W. (October 3, 2009). "Ageing populations: the challenges ahead". The Lancet. 374 (9696): 1196–1208\. doi:10.1016/S0140-6736(09)61460-4. PMC 2810516. PMID 19801098.
15. ^ Eberstadt, Nicholas (October 25, 2008). "Rising Ambitions, Sinking Population". New York Times. Retrieved June 20, 2014.
16. ^ Tavernise, Sabrina (September 20, 2012). "Life Spans Shrink for Least-Educated Whites in the U.S." New York Times. Retrieved June 20, 2014.
17. ^ Irwin, Neil (January 10, 2014). "The Beatles were the Mitt Romney of the 1960s, and other policy lessons from the Fab Four". Washington Post. Retrieved June 20, 2014.
18. ^ "The Dying Bear: Russia's Demographic Disaster". Foreign Affairs. November–December 2011. Retrieved June 20, 2014.

## External links

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Official website