Migration in Dores do Turvo/MG (2017–2022)

Dores do Turvo/MG had a reference population (aged 5 or over in 2022) of 4,710 people. In the 2017–2022 five-year period, the municipality received 615 in-migrants and lost 255 out-migrants to other municipalities in Brazil, resulting in a net migration of +355 people (75.85 per 1,000 population) and a migration effectiveness index (IEM) of 0.411. This classifies the municipality, for the period, as one of migratory attraction. In addition, 15 arrived with an unreported origin and 0 came from abroad.

Indicators

Migration indicators for Dores do Turvo/MG, 2017–2022
Indicator	Estimate	95% CI	Precision
In-migrants	615	491 to 739	good
Out-migrants	255	140 to 370	use with caution
Net migration	+355	186 to 524	not classified
Net migration rate, TLM (per 1,000 pop.)	75.85	-	-
Migration effectiveness index (IEM)	0.411	-	-

Sample of in-migrants: 100-499 observations. Sample of out-migrants: 20-49 observations. 95% confidence interval computed as estimate ± 1.96 × standard error.

Top origins and destinations

Top 10 origins of in-migrants to Dores do Turvo/MG
Origin	People	Precision
Ubá/MG · view pair in the atlas	105	use with caution
São Paulo/SP · view pair in the atlas	80	low precision
Belo Horizonte/MG · view pair in the atlas	55	low precision
Alto Rio Doce/MG · view pair in the atlas	50	low precision
Rio de Janeiro/RJ · view pair in the atlas	35	low precision
Juiz de Fora/MG · view pair in the atlas	30	low precision
Senador Firmino/MG · view pair in the atlas	25	low precision
Brás Pires/MG · view pair in the atlas	20	low precision
Barbacena/MG · view pair in the atlas	15	low precision

Top 10 destinations of out-migrants from Dores do Turvo/MG
Destination	People	Precision
Ubá/MG · view pair in the atlas	110	low precision
Senador Firmino/MG · view pair in the atlas	40	low precision
Silveirânia/MG · view pair in the atlas	15	low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
Category	Estimate	Share	Sample
First move from municipality of birth	260	42.3%	50-99
Multi-step migration	200	32.5%	50-99
Return to municipality of birth	155	25.2%	20-49

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	165	42.9%	50-99
Completed high school, incomplete higher education	130	33.8%	20-49
Completed higher education	55	14.3%	5-19
Completed elementary, incomplete high school	35	9.1%	5-19

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	190	31.1%	50-99
¼ to ½ minimum wage	175	28.7%	50-99
1 to 2 minimum wages	105	17.2%	20-49
More than 2 minimum wages	80	13.1%	20-49
Up to ¼ of a minimum wage	55	9.0%	5-19
Other / suppressed	5	0.8%	<5

Age and sex
Category	Estimate	Share	Sample
Ages 25–39, female	95	15.3%	20-49
Ages 40–59, female	85	13.7%	20-49
Ages 40–59, male	80	12.9%	20-49
Ages 15–24, female	75	12.1%	20-49
Ages 25–39, male	70	11.3%	20-49
Ages 5–14, female	60	9.7%	20-49
Ages 15–24, male	55	8.9%	5-19
Ages 5–14, male	40	6.5%	5-19
Ages 60 and over, male	35	5.6%	5-19
Ages 60 and over, female	25	4.0%	5-19

Out-migrants (departures)

Migrant type
Category	Estimate	Share	Sample
First move from municipality of birth	160	62.7%	20-49
Multi-step migration	75	29.4%	5-19
Other / suppressed	20	7.8%	<5

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	90	51.4%	5-19
Other / suppressed	45	25.7%	<5
Completed high school, incomplete higher education	40	22.9%	5-19

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	90	35.3%	5-19
¼ to ½ minimum wage	75	29.4%	5-19
1 to 2 minimum wages	50	19.6%	5-19
Other / suppressed	40	15.7%	5-19

Age and sex
Category	Estimate	Share	Sample
Other / suppressed	100	39.2%	5-19
Ages 25–39, female	55	21.6%	5-19
Ages 15–24, female	45	17.6%	5-19
Ages 40–59, female	35	13.7%	5-19
Ages 25–39, male	20	7.8%	5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	1,840	60.0%	>=500
Completed high school, incomplete higher education	615	20.1%	100-499
Completed elementary, incomplete high school	350	11.4%	100-499
Completed higher education	260	8.5%	50-99

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	1,820	41.8%	>=500
¼ to ½ minimum wage	1,105	25.4%	100-499
1 to 2 minimum wages	750	17.2%	100-499
More than 2 minimum wages	360	8.3%	100-499
Up to ¼ of a minimum wage	315	7.2%	100-499
Other / suppressed	5	0.1%	<5

Age and sex
Category	Estimate	Share	Sample
Ages 40–59, male	675	16.5%	100-499
Ages 40–59, female	615	15.1%	100-499
Ages 60 and over, female	480	11.8%	100-499
Ages 60 and over, male	480	11.8%	100-499
Ages 25–39, male	420	10.3%	100-499
Ages 25–39, female	390	9.6%	100-499
Ages 15–24, female	295	7.2%	50-99
Ages 15–24, male	275	6.7%	50-99
Ages 5–14, female	230	5.6%	50-99
Ages 5–14, male	220	5.4%	50-99

Commuting (work and study)

Commuting indicators for Dores do Turvo/MG
Employed persons (aged 10 and over)	1,980
Commute out to work in another municipality	125
Commute in from another municipality to work here	65
Net commuting	−60
Out-commuting rate (%)	6.33
Commuting attraction index	0.958
Median commuting time	30 min

Open Dores do Turvo/MG in the interactive atlas →

Methodological note

Estimates from the sample microdata of the 2022 Demographic Census (IBGE, controlled access), fixed-date migration question (residence on July 31, 2017 compared with residence on July 31, 2022). Every estimate is rounded to multiples of 5 and has passed statistical disclosure control (no cell with fewer than 5 people or 3 sampled households). See the full methodology and the glossary.

How to cite this page

Daniel Pessini Sobreira. Atlas da migração interna no Brasil [Atlas of internal migration in Brazil]: Dores do Turvo/MG. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/dores-do-turvo-mg-3123304/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.