Migration in Vale de São Domingos/MT (2017–2022)

Vale de São Domingos/MT had a reference population (aged 5 or over in 2022) of 2,710 people. In the 2017–2022 five-year period, the municipality received 585 in-migrants and lost 350 out-migrants to other municipalities in Brazil, resulting in a net migration of +235 people (87.33 per 1,000 population) and a migration effectiveness index (IEM) of 0.253. This classifies the municipality, for the period, as one of migratory attraction. In addition, 0 arrived with an unreported origin and 5 came from abroad.

Indicators

Migration indicators for Vale de São Domingos/MT, 2017–2022
Indicator	Estimate	95% CI	Precision
In-migrants	585	471 to 699	good
Out-migrants	350	198 to 502	use with caution
Net migration	+235	44 to 426	not classified
Net migration rate, TLM (per 1,000 pop.)	87.33	-	-
Migration effectiveness index (IEM)	0.253	-	-

Sample of in-migrants: 100-499 observations. Sample of out-migrants: 50-99 observations. 95% confidence interval computed as estimate ± 1.96 × standard error.

Top origins and destinations

Top 10 origins of in-migrants to Vale de São Domingos/MT
Origin	People	Precision
Pontes e Lacerda/MT · view pair in the atlas	215	use with caution
Jauru/MT · view pair in the atlas	115	use with caution
Cuiabá/MT · view pair in the atlas	35	low precision
Nova Lacerda/MT · view pair in the atlas	30	low precision
Porto Esperidião/MT · view pair in the atlas	20	low precision

Top 10 destinations of out-migrants from Vale de São Domingos/MT
Destination	People	Precision
Pontes e Lacerda/MT · view pair in the atlas	110	low precision
Porto Esperidião/MT · view pair in the atlas	60	low precision
Vila Bela da Santíssima Trindade/MT · view pair in the atlas	55	low precision
Jauru/MT · view pair in the atlas	45	low precision
Conquista D'Oeste/MT · view pair in the atlas	30	low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
Category	Estimate	Share	Sample
Multi-step migration	390	66.7%	100-499
First move from municipality of birth	190	32.5%	50-99
Other / suppressed	5	0.9%	<5

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	195	51.3%	50-99
Completed higher education	70	18.4%	20-49
Completed high school, incomplete higher education	60	15.8%	20-49
Completed elementary, incomplete high school	55	14.5%	5-19

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	220	37.6%	50-99
1 to 2 minimum wages	150	25.6%	20-49
¼ to ½ minimum wage	115	19.7%	20-49
Up to ¼ of a minimum wage	55	9.4%	5-19
More than 2 minimum wages	45	7.7%	5-19

Age and sex
Category	Estimate	Share	Sample
Ages 40–59, female	115	19.7%	20-49
Ages 40–59, male	75	12.8%	20-49
Ages 25–39, male	65	11.1%	20-49
Ages 25–39, female	65	11.1%	20-49
Ages 5–14, female	60	10.3%	20-49
Ages 15–24, female	50	8.5%	5-19
Ages 5–14, male	50	8.5%	5-19
Ages 15–24, male	45	7.7%	5-19
Ages 60 and over, male	30	5.1%	5-19
Ages 60 and over, female	30	5.1%	5-19

Out-migrants (departures)

Migrant type
Category	Estimate	Share	Sample
Multi-step migration	280	80.0%	20-49
Return to municipality of birth	50	14.3%	5-19
Other / suppressed	20	5.7%	<5

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	115	46.0%	5-19
Completed high school, incomplete higher education	70	28.0%	5-19
Completed higher education	40	16.0%	5-19
Completed elementary, incomplete high school	25	10.0%	5-19

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
More than 2 minimum wages	130	37.1%	5-19
½ to 1 minimum wage	115	32.9%	5-19
1 to 2 minimum wages	45	12.9%	5-19
¼ to ½ minimum wage	40	11.4%	5-19
Other / suppressed	20	5.7%	5-19

Age and sex
Category	Estimate	Share	Sample
Other / suppressed	90	25.7%	5-19
Ages 40–59, female	80	22.9%	5-19
Ages 25–39, male	70	20.0%	5-19
Ages 40–59, male	50	14.3%	5-19
Ages 15–24, female	35	10.0%	5-19
Ages 5–14, female	25	7.1%	5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	870	55.1%	100-499
Completed high school, incomplete higher education	330	20.9%	100-499
Completed higher education	195	12.3%	50-99
Completed elementary, incomplete high school	185	11.7%	50-99

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	950	41.0%	100-499
1 to 2 minimum wages	725	31.3%	100-499
¼ to ½ minimum wage	315	13.6%	100-499
More than 2 minimum wages	225	9.7%	50-99
Up to ¼ of a minimum wage	100	4.3%	20-49

Age and sex
Category	Estimate	Share	Sample
Ages 40–59, male	365	17.3%	100-499
Ages 40–59, female	310	14.7%	50-99
Ages 60 and over, male	250	11.8%	50-99
Ages 25–39, female	225	10.6%	50-99
Ages 25–39, male	215	10.2%	50-99
Ages 60 and over, female	215	10.2%	50-99
Ages 5–14, male	185	8.7%	50-99
Ages 5–14, female	130	6.1%	20-49
Ages 15–24, male	125	5.9%	20-49
Ages 15–24, female	95	4.5%	20-49

Commuting (work and study)

Commuting indicators for Vale de São Domingos/MT
Employed persons (aged 10 and over)	850
Commute out to work in another municipality	35
Commute in from another municipality to work here	90
Net commuting	+60
Out-commuting rate (%)	4.03
Commuting attraction index	1.069
Median commuting time	30 min

Open Vale de São Domingos/MT 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]: Vale de São Domingos/MT. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/vale-de-sao-domingos-mt-5108352/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.