Germany vs Lithuania: Demographic indicators by access to city typology — Deaths
Demographic indicators by access to city typology — Deaths over time
- Germany
- Lithuania
How they compare
Lithuania currently reports 12.08 Per 1 000 inhabitants against 11.66 Per 1 000 inhabitants in Germany, a difference of 0.42 Per 1 000 inhabitants.
The two have swapped places 2 times across 14 shared years of data; in 2011 it was Lithuania ahead.
Germany ranks 7th and Lithuania ranks 5th of 35 countries.
Lithuania has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Germany | Lithuania | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 10.7 Per 1 000 inhabitants | 13.31 Per 1 000 inhabitants | 2.61 Per 1 000 inhabitants | Lithuania |
| 2020s | 11.84 Per 1 000 inhabitants | 13.79 Per 1 000 inhabitants | 1.95 Per 1 000 inhabitants | Lithuania |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher demographic indicators by access to city typology — deaths, Germany or Lithuania?
- Lithuania, at 12.08 Per 1 000 inhabitants against 11.66 Per 1 000 inhabitants in Germany as of 2024.
- What is the difference in demographic indicators by access to city typology — deaths between Germany and Lithuania?
- 0.42 Per 1 000 inhabitants, with Lithuania ahead.
- How many years of comparable data are there for Germany and Lithuania?
- 14 years are reported by both, from 2011 to 2024.
- How do Germany and Lithuania rank globally for demographic indicators by access to city typology — deaths?
- Germany ranks 7th and Lithuania ranks 5th of 35 countries.
- Where does this data come from?
- Organisation for Economic Co-operation and Development, published as Demographic indicators by access to city typology — Deaths. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
This data set provides indicators on demography by territorial typology according to the population's access to cities. Data source and definition The data by typology includes share of population, dependency rates, fertility and mortality rates, population mobility within and outside countries. Data is collected from Eurostat (reg_dem) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. The indicators are aggregated data at the national level, using the typology of small (TL3) regions to calculate totals or averages for all metropolitan large regions, metropolitan midsize regions, near a midsize/large FUA regions, near a small FUA regions and remote regions. Territorial typology on population's access to cities Territorial typologies helps to assess differences in socio-economic trends in regions, both within and across countries and to highlight the specific issues faced by each type of region. The OECD territorial typology on access to cities uses the concept of functional urban areas (FUA) – composed of urban centres and their commuting areas – and classifies small (TL3) regions (Fadic et al., 2019) according to the following criteria: Metropolitan regions, if more than half of the population live in a FUA. Metropolitan regions are further classified into: metropolitan large, if more than half of the population live in a (large) FUA of at least 1.5 million inhabitants; and metropolitan midsize, if more than half of the population live in a (midsize) FUA of at 250 000 to 1.5 million inhabitants. Non-metropolitan regions, if less than half of the population live in a midsize/large FUA. These regions are further classified according to their level of access to FUAs of different sizes: near a midsize/large FUA if more than half of the population live within a 60-minute drive from a midsize/large FUA (of more than 250 000 inhabitants) or if the TL3 region contains more than 80% of the area of a midsize/large FUA; near a small FUA if the region does not have access to a midsize/large FUA and at least half of its population have access to a small FUA (i.e. between 50 000 and 250 000 inhabitants) within a 60-minute drive, or contains 80% of the area of a small FUA; and remote, otherwise. List of OECD regions and typologies are presented in the OECD Territorial correspondence table (xlsx). Maps of For more information, see the OECD Territorial grid (pdf). Cite this dataset OECD Regions, Cities and Local Areas database http://oe.cd/geostats Further information OECD Regions and Cities Statistical Atlas The report OECD Regions and Cities at a Glance Contact: RegionStat@oecd.org