Latvia vs Lithuania: Health risks - Regions — Circulatory system diseases mortality crude
Health risks - Regions — Circulatory system diseases mortality crude over time
- Latvia
- Lithuania
How they compare
Latvia currently reports 727.39 Per 100 000 inhabitants against 636.04 Per 100 000 inhabitants in Lithuania, a difference of 91.35 Per 100 000 inhabitants.
That makes Latvia's figure about 1.1 times Lithuania's.
The two have swapped places 2 times across 14 shared years of data; in 2011 it was Latvia ahead.
Latvia ranks 3rd and Lithuania ranks 5th of 41 countries.
Latvia has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Latvia | Lithuania | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 803.31 Per 100 000 inhabitants | 780.67 Per 100 000 inhabitants | 22.63 Per 100 000 inhabitants | Latvia |
| 2020s | 808.05 Per 100 000 inhabitants | 745.86 Per 100 000 inhabitants | 62.19 Per 100 000 inhabitants | Latvia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher health risks - regions — circulatory system diseases mortality crude, Latvia or Lithuania?
- Latvia, at 727.39 Per 100 000 inhabitants against 636.04 Per 100 000 inhabitants in Lithuania as of 2024.
- What is the difference in health risks - regions — circulatory system diseases mortality crude between Latvia and Lithuania?
- 91.35 Per 100 000 inhabitants, with Latvia ahead.
- How many years of comparable data are there for Latvia and Lithuania?
- 14 years are reported by both, from 2011 to 2024.
- How do Latvia and Lithuania rank globally for health risks - regions — circulatory system diseases mortality crude?
- Latvia ranks 3rd and Lithuania ranks 5th of 41 countries.
- Where does this data come from?
- Organisation for Economic Co-operation and Development, published as Health risks - Regions — Circulatory system diseases mortality crude rate. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
This dataset provides indicators on health risks in large regions (TL2), and small regions (TL3) when data is available. Indicators include obesity rates, air pollution exposure, mortality rates due to circulatory and respiratory diseases. Data definition and source Obesity rate is the percentage of population 15 years old or more with a BMI>30 kg/m2. The Body Mass Index (BMI) is a single number that evaluates an individual's weight status in relation to height (weight/height2) with weight in kilograms and height in meters. Population exposure to fine particule PM2.5 provide an estimate of the population-weighted average of PM2.5 concentration. Respiratory system diseases mortality rate is the number of deaths from diseases of the respiratory system (group J00-J99 of the International Classification of Deseases), for 100 000 inhabitants. Circulatory system diseases mortality rate rate is the number of deaths from diseases of the circulatory system (group I00-I99) for 100 000 inhabitants. PM2.5 air pollution indicators are computed using geospatial data from the Global Burden of Disease (GBD) 2019 project. Respiratory and circulatory related mortality data are collected from Eurostat (reg_hlth) for EU regions and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. Definition of regions Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). For more information, see the OECD Territorial grid (pdf) and the OECD Territorial Correspondence Table (xlsx). Use of data on small regions When socio-demographic data are analysed along with economic data using the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting, see the list of OECD metropolitan regions (xlsx) and the EU methodology (link). Cite this dataset OECD Regions, Cities and Local Areas database http://oe.cd/geostats. Further information OECD Regions and Cities Statistical Atlas OECD Regions and Cities at a Glance For questions and/or comments, please email RegionStat@oecd.org.