Changes in regional variation in mortality over five decades – The contribution of age and socioeconomic population composition

Research output: Contribution to journalArticleScientificpeer-review


Existing evidence suggests that within-country area variation in mortality has increased in several high-income countries. Little is known about the role of changes in the population composition of areas in these trends. In this study, we look at mortality variation across Finnish municipalities over five decades. We examine trends by sex, age categories and two broad cause of death groups and assess the role of individual-level compositional factors. Analyses rely on individual-level register data on the total Finnish population aged 30 years and over. We estimated two-level Weibull survival-models with individuals nested in areas for 10 periods between 1972 and 2018 to assess municipal-level variation in mortality. Median hazard ratio (MHR) was used as our summary measure and analyses were adjusted for age and socioeconomic characteristics. The results show a clear overall growth in area variation in mortality with MHR increasing from 1.14 (95% CI 1.12–1.15) to 1.28 (CI 1.26–1.30) among men and 1.17 (CI 1.15–1.18) to 1.30 (CI 1.27–1.32) among women. This growth, however, was fully attenuated by adjustment for age. Area differentials were largest and increased most among men at ages 30–49, and particularly for external causes. This increase was largely due to increasing differentiation in the socioeconomic composition of municipalities. In conclusion, our study shows increases in mortality differentials across municipalities that are mostly attributable to increasing differentiation between municipalities in terms of individual compositional factors.
Original languageEnglish
Article number100850
JournalSSM - Population Health
Number of pages10
Publication statusPublished - Sep 2021
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 5141 Sociology
  • Mortality
  • Health inequalities
  • Regional variation
  • Long-term trends
  • Multilevel modelling

Cite this