Age Standardization in Health Statistics: History and Future Perspectives
5 affiliations
- 1National Cancer Center Institute for Cancer Control, Tokyo, Japan
- 2Cancer Surveillance Branch, The International Agency for Research on Cancer (IARC), Lyon, France
- 3Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA (EJF-contractor)
- 4Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- 5Korea Central Cancer Registry, National Cancer Center, Goyang, Korea
Abstract
Age standardization is a key statistical method used in health statistics to adjust rates, such as mortality or incidence, enabling comparisons across populations or time points with different age structures. This review traces its historical development, global and country-specific practices, and future directions. The method dates back to the 19th century, with major adoption in the 20th century through Segi and Doll’s World Standard Population. While the World Health Organization (WHO) introduced an updated standard in 2000, the International Agency for Research on Cancer (IARC) continues to use Segi and Doll’s standard in the Cancer Incidence in Five Continents series, prioritizing consistency and comparability in long-term cancer surveillance. Case studies from the IARC, the United States, Japan, and the Republic of Korea (Korea) illustrate different responses to changing demographics. The United States adopted the 2000 standard with expanded age detail for the elderly population. Japan introduced the 2015 Japan Standard Population to account for its rapidly aging society, though regional data limitations presented challenges. Korea, experiencing one of the fastest aging transitions globally, updated to a 2020 standard for more accurate national and sub-national reporting. The review also emphasizes that age standardization can obscure important age-specific trends. Methods like Joinpoint clustering help detect divergent trends by age groups. Looking forward, age standardization remains essential amid global demographic shifts. However, updates of standard populations must balance improved relevance with the need for continuity and robust data. International coordination and digital tools will support more flexible and transparent health statistics in the future.
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BibTeX
@article{katanoda2026standardization,
title = {{Age Standardization in Health Statistics: History and Future Perspectives}},
author = {Kota Katanoda and Freddie Bray and Eric J. Feuer and Angela B. Mariotto and Hirokazu Tanaka and Aesun Shin and Kyu-Won Jung and Tomohiro Matsuda},
journal = {Journal of Epidemiology},
year = {2026},
month = nov,
doi = {10.2188/jea.je20250668},
url = {https://doi.org/10.2188/jea.je20250668},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Age Standardization in Health Statistics: History and Future Perspectives
AU - Kota Katanoda
AU - Freddie Bray
AU - Eric J. Feuer
AU - Angela B. Mariotto
AU - Hirokazu Tanaka
AU - Aesun Shin
AU - Kyu-Won Jung
AU - Tomohiro Matsuda
PY - 2026
DA - 2026/11/05
JO - Journal of Epidemiology
DO - 10.2188/jea.je20250668
UR - https://doi.org/10.2188/jea.je20250668
AB - Age standardization is a key statistical method used in health statistics to adjust rates, such as mortality or incidence, enabling comparisons across populations or time points with different age structures. This review traces its historical development, global and country-specific practices, and future directions. The method dates back to the 19th century, with major adoption in the 20th century through Segi and Doll’s World Standard Population. While the World Health Organization (WHO) introduced an updated standard in 2000, the International Agency for Research on Cancer (IARC) continues to use Segi and Doll’s standard in the Cancer Incidence in Five Continents series, prioritizing consistency and comparability in long-term cancer surveillance. Case studies from the IARC, the United States, Japan, and the Republic of Korea (Korea) illustrate different responses to changing demographics. The United States adopted the 2000 standard with expanded age detail for the elderly population. Japan introduced the 2015 Japan Standard Population to account for its rapidly aging society, though regional data limitations presented challenges. Korea, experiencing one of the fastest aging transitions globally, updated to a 2020 standard for more accurate national and sub-national reporting. The review also emphasizes that age standardization can obscure important age-specific trends. Methods like Joinpoint clustering help detect divergent trends by age groups. Looking forward, age standardization remains essential amid global demographic shifts. However, updates of standard populations must balance improved relevance with the need for continuity and robust data. International coordination and digital tools will support more flexible and transparent health statistics in the future.
SN - 0917-5040
SN - 1349-9092
ER -