Analytics, Demography, Latvia, Society

"Latest population number estimates show two trends. The number of Latvia counties with positive natural increase is growing. In some counties birth rate is rather high – close to or even above 15 babies per 1 000 population” says CSB President Aija Žīgure. “Meanwhile, in largest part of the country, especially in frontier regions of Latvia, population number keeps declining, with the sharpest reduction observed in Latgale region."

Change in resident population by administrative territory; 2015 (per 1 000 population)

The highest rise in population number was observed in Mārupe (of 6.2 %), Garkalne (of 3.1 %), Canrikava (of 2.5 %), and Ādaži (of 2 %) county. Population number in absolute terms grew by 1 094 in Mārupe county, by 244 in Garkalne county, by 170 in Carnikava county, and by 204 in Ādaži county. Last year, increase in the population number under 2 % was recorded in Babīte (1.6 %), Ikšķile (1.5 %), Stopiņi and Ķekava (1.4 % in each) counties of Pierīga region and in Ozolnieki county of Zemgale region (of 0.9 %).

Population increase in both counties outside Riga region was promoted by internal migration – in Priekuļi county mainly by immigrants from Cēsis, while in Ozolnieki county – mainly from Riga, in addition Ozolnieki county had also positive natural increase.

Population number in counties and changes thereof are influenced also by social care centres, places of detention, etc. located there. For example, in 2015 one of the reasons behind population number decline in Rauna county was shutdown of the social care centre “Rauna”, resulting in centre residents moving to social care institutions in other counties.

In 17 counties (six counties more than in 2014) the number of immigrants exceeded the number of emigrants – from 13 persons in Krustpils to 861 persons in Mārupe county. Apart from the mentioned counties, the highest immigrant predominance over emigrants (i.e., net migration) was recorded in the counties with the greatest population increase:  Garkalne, Carnikava, Salaspils, Ādaži, Ķekava, Stopiņi, Babīte, Ikšķile, Olaine, Ozolnieki, Engure, Saulkrasti and Sēja county. Positive net migration was observed also in Priekuļi and Baldone county.

In 2015, birth number exceeded the death number in 14 counties – Mārupe, Ķekava, Ādaži, Garkalne, Babīte, Stopiņi, Ikšķile, Sala, Krimulda, Sigulda, Salaspils, Inčukalns, Carnikava and Ozolnieki county.

Last year, 10 or more babies per 1 000 population were born in 51 % of all Latvia counties. The greatest number of births was recorded in Mārupe (19.5 newborn per 1 000 population), Ķekava (17.1), Jaunpils (14.7), Ādaži (14.5), and Babīte (14.1) county of Pierīga region, Ozolnieki county of Zemgale reigon (14.4), and Ventspils county of Kurzeme region (14.3). While the smallest number of births was registered in Strenči county of Vidzeme region (4.3 newborn per 1 000 population), Aknīste county of Zemgale region (5.4), as well as Kārsava county of Latgale region (5.9).

The highest number of deaths (more than 20 deaths per 1 000 population) was observed in Krustpils county of Zemgale region (24.9), Jaunpiebalga (24.4), Lubāna (23.7), and Varakļāni (23.0) county of Vidzeme region, as well as Mērsrags (24.2), Vaiņode (22.5), and Skrunda (21.4) county of Kurzeme region. Last year, Latgale region had the greatest number of counties (six) in which high death rate was recorded – Baltinava (22.4), Ilūkste (22.1), Viļaka (21.0), Zilupe (20.7), Balvi (20.4), and Daugavpils (20.2) county. In 2015, the lowest death number per 1 000 population was observed in counties with the higher birth number – Mārupe (6.7 deaths per 1 000 population), Garkalne (7.4), and Ādaži (7.6 county).

Natural increase by region; 2015 (per 1 000 population)

Population number in administrative territories at the beginning of 2016 is available in the CSB database section Population and Social Processes. Population number in breakdown by county has been specified, and the data are published in the CSB database.

Population number estimates are based on data from 40 different data sources. The methodology is available on the CSB website.