In 2024, the Southeast was the most populated region in Brazil, according to the estimations. In that year, more than 88 million people lived in the four states of this region: Espírito Santo, Minas Gerais, Rio de Janeiro and São Paulo. The Central-West region, where the country's capital, Brasília, is located, was the least populated region in the South American country in 2021, with only 17 million inhabitants. Throughout the past decade, Brazil's population has grown at slower rates than before.

Brazil and the United States are the two most populous countries in the Americas today. In 1500, the year that Pedro Álvares Cabral made landfall in present-day Brazil and claimed it for the Portuguese crown, it is estimated that there were roughly one million people living in the region. Some estimates for the present-day United States give a population of two million in the year 1500, although estimates vary greatly. By 1820, the population of the U.S. was still roughly double that of Brazil, but rapid growth in the 19th century would see it grow 4.5 times larger by 1890, before the difference shrunk during the 20th century. In 2024, the U.S. has a population over 340 million people, making it the third most populous country in the world, while Brazil has a population of almost 218 million and is the sixth most populous. Looking to the future, population growth is expected to be lower in Brazil than in the U.S. in the coming decades, as Brazil's fertility rates are already lower, and migration rates into the United States will be much higher. Historical development The indigenous peoples of present-day Brazil and the U.S. were highly susceptible to diseases brought from the Old World; combined with mass displacement and violence, their population growth rates were generally low, therefore migration from Europe and the import of enslaved Africans drove population growth in both regions. In absolute numbers, more Europeans migrated to North America than Brazil, whereas more slaves were transported to Brazil than the U.S., but European migration to Brazil increased significantly in the early 1900s. The U.S. also underwent its demographic transition much earlier than in Brazil, therefore its peak period of population growth was almost a century earlier than Brazil. Impact of ethnicity The demographics of these countries are often compared, not only because of their size, location, and historical development, but also due to the role played by ethnicity. In the mid-1800s, these countries had the largest slave societies in the world, but a major difference between the two was the attitude towards interracial procreation. In Brazil, relationships between people of different ethnic groups were more common and less stigmatized than in the U.S., where anti-miscegenation laws prohibited interracial relationships in many states until the 1960s. Racial classification was also more rigid in the U.S., and those of mixed ethnicity were usually classified by their non-white background. In contrast, as Brazil has a higher degree of mixing between those of ethnic African, American, and European heritage, classification is less obvious, and factors such as physical appearance or societal background were often used to determine racial standing. For most of the 20th century, Brazil's government promoted the idea that race was a non-issue and that Brazil was racially harmonious, but most now acknowledge that this actually ignored inequality and hindered progress. Racial inequality has been a prevalent problem in both countries since their founding, and today, whites generally fare better in terms of education, income, political representation, and even life expectancy. Despite this adversity, significant progress has been made in recent decades, as public awareness of inequality has increased, and authorities in both countries have made steps to tackle disparities in areas such as education, housing, and employment.

In 2023, it was estimated that more than four million Brazilians were living outside Brazil. The United States had the largest community, with over two million Brazilian citizens. Portugal was the second country with the largest Brazilian community, namely 513,000 citizens. Brazilians abroad The Brazilian community sought economic opportunities in the United States in the 1980s, leading to the establishment of communities in New York and Boston. Facilitated by the common language and Portugal's favorable laws for the Community of Portuguese-speaking countries, Lisbon became the most popular destination in Europe. This city harbors more than 77,000 Brazilians, with women making up the majority of these. Immigration in Brazil Although more than four million Brazilians live outside of Brazil, the country has had a positive migration rate since 2010, meaning that more people are arriving than leaving. One factor contributing to this is the current humanitarian crisis in Venezuela, which has increased the number of refugees arriving in Brazil each year.

In 2022, approximately 11.45 million people lived in São Paulo, making it the largest municipality in Brazil and one of the most populous cities in the world. The homonymous state of São Paulo was also the most populous federal entity in the country.

Brazil's cities

Brazil is home to two large metropolises: São Paulo with close to 11.45 million inhabitants, and Rio de Janeiro with around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 85 percent of inhabitants living in cities.

While smaller than some of the other cities, Brasília was chosen to be the capital because of its relatively central location. The city is also well-known for its modernist architecture and utopian city plan which is quite controversial - criticized by many and praised by others.

Sports venues capitals

A number of Brazil’s medium-sized and large cities were chosen as venues for the 2014 World Cup, and the 2015 Summer Olympics also took place in Rio de Janeiro. Both of these events required large sums of money to support infrastructure and enhance mobility within a number of different cities across the country. Billions of dollars were spent on the 2014 World Cup, which went primarily to stadium construction and renovation, but also to a number of different mobility projects. Other short-term spending on infrastructure for the World Cup and the Rio Olympic Games was estimated at around 50 billion U.S. dollars. While these events have poured a lot of money into urban infrastructure, a number of social and economic problems within the country remain unsolved.

Brazil BR: Population Living in Slums: % of Urban Population data was reported at 14.897 % in 2016. This stayed constant from the previous number of 14.897 % for 2014. Brazil BR: Population Living in Slums: % of Urban Population data is updated yearly, averaging 21.511 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 34.740 % in 2000 and a record low of 14.897 % in 2016. Brazil BR: Population Living in Slums: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Population and Urbanization Statistics. Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.;United Nations Human Settlements Programme (UN-HABITAT);Weighted average;

In 202, according to the estimation, the Brazilian state of São Paulo was home to nearly 46 million people, making it the most populous state in the South American country. With less than half of São Paulo's population, Minas Gerais was the second most populous state in Brazil at that time. These two states are located in the South-East region of the country. Along with Rio de Janeiro and Espírito Santo, these states constitute Brazil's most populated region.

BR: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 22.000 % in 2022. This records a decrease from the previous number of 22.200 % for 2021. BR: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 24.500 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 26.500 % in 1989 and a record low of 18.200 % in 2020. BR: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No (dwellings in original sample are interpreted as households in IPUMS) - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Structurally independent living quarters, consisting of one or more rooms with a private entrance, serving up to three families. - Group quarters: Group living together under relations of administrative subordination; group of six or more persons not related by kinship; or a dwelling with more than 3 families.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Instituto Brasileiro de Geografia e Estatística

SAMPLE UNIT: Household (called "dwelling" in original sample)

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 4,953,759

Mode of data collection

Face-to-face [f2f]

Research instrument

Long and short enumeration forms. The short form contains general information about the characteristics of the dwelling and each of persons in the dwelling. The long form contains general and more specific information about the characteristics of the dwelling, families, and each of the people in the dwellings and was applied to a 25% sample of the population.

Response rate

COVERAGE: No official estimates, UNDERCOUNT: No official estimates

Brazil net migration for 2023 was 6,000, a 6.61% decline from 2022.

<ul style='margin-top:20px;'>

<li>Brazil net migration for 2022 was <strong>6,425</strong>, a <strong>68.47% decline</strong> from 2021.</li>
<li>Brazil net migration for 2021 was <strong>20,376</strong>, a <strong>64.18% decline</strong> from 2020.</li>
<li>Brazil net migration for 2020 was <strong>56,880</strong>, a <strong>17.79% decline</strong> from 2019.</li>
</ul>Net migration is the net total of migrants during the period, that is, the total number of immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.

The total population in Brazil was estimated at 212.6 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - Brazil Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Brazil BR: Population Density: People per Square Km data was reported at 25.643 Person/sq km in 2021. This records an increase from the previous number of 25.508 Person/sq km for 2020. Brazil BR: Population Density: People per Square Km data is updated yearly, averaging 18.346 Person/sq km from Dec 1961 (Median) to 2021, with 61 observations. The data reached an all-time high of 25.643 Person/sq km in 2021 and a record low of 9.013 Person/sq km in 1961. Brazil BR: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

In 2023, the total population of Brazil amounted to nearly *** million inhabitants. Over *** million women and *** million men reside in this Latin American country. Brazil is the most populated country in the region.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Brazil by race. It includes the distribution of the Non-Hispanic population of Brazil across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Brazil across relevant racial categories.

Key observations

Of the Non-Hispanic population in Brazil, the largest racial group is White alone with a population of 7,500 (95.12% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Brazil
• Population: The population of the racial category (for Non-Hispanic) in the Brazil is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Brazil total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil Population by Race & Ethnicity. You can refer the same here

Brazil Population: Residents: Age 35 to 39 Years data was reported at 15,758.000 Person th in 2015. This records an increase from the previous number of 15,085.000 Person th for 2014. Brazil Population: Residents: Age 35 to 39 Years data is updated yearly, averaging 13,612.500 Person th from Sep 2001 (Median) to 2015, with 14 observations. The data reached an all-time high of 15,758.000 Person th in 2015 and a record low of 12,717.000 Person th in 2001. Brazil Population: Residents: Age 35 to 39 Years data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Global Database’s Brazil – Table BR.GAA003: Population: Residents: by Region and Age.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Brazil BR: Rural Population data was reported at 26,429,509.000 Person in 2023. This records a decrease from the previous number of 26,795,765.000 Person for 2022. Brazil BR: Rural Population data is updated yearly, averaging 38,546,226.000 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 42,653,748.000 Person in 1973 and a record low of 26,429,509.000 Person in 2023. Brazil BR: Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Sum;

This statistic shows the total population of Brazil from 2020 to 2023, with a forecast through 2030. In 2023, the total population of Brazil was estimated at around 211.7 million inhabitants. Population of Brazil Brazil has a surprisingly low (and decreasing) population growth rate; despite it being home to the largest number of Catholics in the world, the majority of women in Brazil use some form of contraception, which is often government-subsidized or free, even though the Catholic Church retains its stance that the use of contraceptives is inherently wrong. Within the space of just one generation, families have gone from having more than six children to having just one or two, and the share of Catholics in the population is dwindling, too. The influence of 'telenovelas' — the overwhelmingly popular soap operas often with strong women figures and fewer than three children — could also be helping shape the population’s view of what an ideal family is. The fertility rate in Brazil fell below the replacement rate in 2006 and is still decreasing. The impending population imbalance in Brazil can be seen in the decreasing lower tier of the country’s age distribution. This follows a trend similar to the one Japan and many European countries are experiencing, which are now facing the problems of providing for an aging population with fewer young and working taxpayers. The trend is not quite as extreme in Brazil, giving it time to prepare for the fallout of decreasing family size. This preparation will be important to help the country maintain its emerging economic strength, which is watched with interest by many economists who have said that Brazil’s is one to watch — thus its position as one of the pillars of the “big four” BRIC countries.

Chart and table of population level and growth rate for the Sao Paulo, Brazil metro area from 1950 to 2025.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.

Abstract

Objectives: To provide general information about people with disabilities that can be used in the development of appropriate policies.

Reference Period: Month

Periodicity of Data Collection: Every 10 years

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: All age groups

Total population covered: All

Economic activities: All economic activities

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers, contributing family workers, members of producers' cooperatives

Establishments: NR (census was not designed to collect data on all types of establishments)

Other limitations: According to census methodology, employment data is collected only for people with 10 years or more

Classifications: Sex, age, level of education, type of living arrangements, status in employment, occupation, economic activity, type of disability

Cross-classification: Disability variable can be cross-classified by all variables

Kind of data

Census/enumeration data [cen]

Frequency of data collection

Periodicity of Data collection: Every 10 years