Brazil BR: Population in Largest City data was reported at 22,806,704.000 Person in 2024. This records an increase from the previous number of 22,619,736.000 Person for 2023. Brazil BR: Population in Largest City data is updated yearly, averaging 15,288,036.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 22,806,704.000 Person in 2024 and a record low of 4,493,182.000 Person in 1960. Brazil BR: Population in Largest City 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 in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

About this dataset

Context

The dataset tabulates the Brazil median household income by race. The dataset can be utilized to understand the racial distribution of Brazil income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Brazil, IN median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Brazil, IN (2021, in 2022 inflation-adjusted dollars)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Brazil median household income by race. You can refer the same here

Brazil BR: Population in Largest City: as % of Urban Population data was reported at 12.223 % in 2024. This records an increase from the previous number of 12.203 % for 2023. Brazil BR: Population in Largest City: as % of Urban Population data is updated yearly, averaging 12.971 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 15.235 % in 1980 and a record low of 11.954 % in 2005. Brazil BR: Population in Largest City: as % 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 in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.;United Nations, World Urbanization Prospects.;Weighted average;

Abstract This paper compares the occupational structure of cities in Brazil and United States aiming to evaluate the extent to which the economic structure of these urban agglomerations is associated with the different stages of development, specifically when comparing a rich country with a developing one. Using a harmonized occupational database and microdata from the Brazilian 2010 Demographic Census and the U.S. American Community Survey (2008-2012), results show that Brazilian cities have a stronger connection between population size, both with occupational structure and human capital distribution, than the one found for cities in the United States. These findings suggest a stronger primacy of large cities in Brazil’s urban network and a more unequal distribution of economic activity across cities when compared to USA, indicating a strong correlation between development and occupational structure.

About this dataset

Context

The dataset tabulates the Brazil household income by age. The dataset can be utilized to understand the age-based income distribution of Brazil income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Brazil, IN annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Brazil, IN household incomes: Comparative analysis across 16 income brackets

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Brazil income distribution by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Brazil: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 149(4.48%) households where the householder is under 25 years old, 1,000(30.05%) households with a householder aged between 25 and 44 years, 1,136(34.13%) households with a householder aged between 45 and 64 years, and 1,043(31.34%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the city of Brazil, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 median household income by age. You can refer the same here

ABSTRACT What would the types of electoral speeches be for the health sector registered by applications to municipal governments? To investigate this issue, a qualitative study was carried out with a hermeneutical analysis of electoral program documents, registered by majority candidates in the first round of the municipal elections of 2016 in the Brazilian metropolises of São Paulo (SP) and Rio de Janeiro (RJ). In most of the speeches there was no description of specific institutional strategies for health, much less its terms of viability and feasibility. Four distinct discursive profiles were emphasized, in which the propositions for health policies were either reduced to the managerial aspect or subsumed by discursive commonplaces. Contextually, there was an emphasis on normative discourses and performative appeals, without consubstantiation in practical discourses.

About this dataset

Context

The dataset tabulates the Brazil household income by gender. The dataset can be utilized to understand the gender-based income distribution of Brazil income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Brazil, IN annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Brazil, IN annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Brazil income distribution by gender. You can refer the same here

Includes the epidemiological data, wastewater SARS-COV-2 quantification (.csv files), and the R code used for the analysis (.html from Rmarkdown).

The capybara is the largest living rodent, attracting attention due to its large size, its formation of large herds, and because it is commonly seen in urban environments. Thus, understanding the dynamics of capybara populations living in urban environments is relevant, especially given the conflicts observed between the species and humans in these environments. Here, we investigated the hypothesis of overpopulation of the capybara in Lago Paranoá, a lake in a large neotropical city, BrasÃlia, Brazil. To do this, we investigated their spatial distribution at the site and estimated the capybara population using a variation of the mark-recapture method and compared it to known population estimates for the species. We found that the capybaras in our study area mainly form small flocks of 1 to 9 animals and occupy almost the entire shore of Lake Paranoá. We estimated the occurrence of 0.30 to 0.52 ind./ha (average = 0.41 ind./ha), demonstrating that the number of capybaras in our region is ..., , # Population estimate and spatial distribution of capybaras in Lake Paranoá, BrasÃlia, Brazil

Dataset DOI: 10.5061/dryad.fttdz094g

Description of the data and file structure

Over a year (10/2021 - 09/2022), the shore of Lake Paranoá was covered with the help of a voadeira (aluminum boat with an outboard motor) at a speed of around 20 km/h and approximately 30 m from the shore (Figure 2). The same route was covered every month for 12 months. We standardized the counts for the afternoon, after 4 pm, based on the literature, which reports greater activity of the species at dusk and dawn (Moreira et al., 2013c). Due to the large expanse of the shore of Lake Paranoá, complete monitoring took place over four sampling days, totaling around 8 hours of sampling per month. Counts were carried out on consecutive days whenever possible, except in cases of adverse weather conditions. When activities were canceled, the count was restarted on the next day with suitab...,

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Brazil. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Brazil, the median household income for the households where the householder is White increased by $6,638(15.70%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $42,287 in 2011 and $48,925 in 2021.
• Black or African American: Even though there is a population where the householder is Black or African American, there was no median household income reported by the U.S. Census Bureau for both 2011 and 2021.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/brazil-in-median-household-income-by-race-trends.jpeg" alt="Brazil, IN median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Brazil.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-inflation-adjusted dollars.

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 median household income by race. You can refer the same here

Abstract Background: Hypertension is the main risk factor for cardiovascular diseases. Technical quality of sphygmomanometers is a prerequisite for the correct measurement of arterial pressure. Objectives: To evaluate sphygmomanometers available in emergency services in the city of Belo Horizonte, Brazil. Methods: We performed a cross-sectional, observational, non-interventional study to evaluate characteristics of the sphygmomanometers available in adult emergency services of public and private hospitals in the city of Belo Horizonte, Brazil. We evaluated 337 sphygmomanometers of 25 hospitals - 15 (of 16) public hospitals and 10 (of 12) private hospitals. Results: Twenty-six percent (88/337) of devices were considered inadequate regarding the INMETRO (National Institute of Metrology, Quality and Technology) standards, 39.2% (132/337) for calibration dates, and 54% (188/337) for the mismatching between cuff's and device's brands. In 13 of 25 hospitals (52%), there were no spare cuffs in different sizes for different arm circumferences. Higher adequacy was found for aneroid and mercury sphygmomanometers used in private hospitals (p = 0.038 and p < 0.001, respectively) and electronic devices used in public hospitals (p < 0.001) compared with others. Conclusion: Seventy-eight percent of sphygmomanometers available in emergency services had technical inadequacies, and half of these services had no spare cuffs in different sizes available. These findings serve as a warning of the conditions of the equipment used in healthcare services provided to the general population in Brazil.

Congenital syphilis (CS) is a significant public health problem in Brazil. Despite efforts to increase syphilis testing and treatment among pregnant women, rates of CS in the country remain high. We conducted a retrospective case-control study to identify potential associations between the mothers’ sociodemographic characteristics, clinical factors related to the current and previous pregnancies, and the occurrence of CS among newborns in Fortaleza, a populous city with one of the highest incidences of CS in Brazil. Data from newborns diagnosed with CS between 2017 and 2020 were extracted from SINAN, the national database for notifiable diseases. Data from women who had delivered an infant with CS were extracted from SINASC, the national database for registration of live births, and linked with their infant’s data. CS cases and non-CS controls were matched by year of birth at a ratio of 1:3 respectively. Potential associations were estimated using a multivariate regression model accounting for sociodemographic, obstetric, and antenatal care-related factors. Epidemiological data from 8,744 live births were included in the analysis, including 2,186 cases and 6,588 controls. The final multivariate regression model identified increased odds of delivering an infant with CS among pregnant women and girls aged below 20 years (OR 1.29), single women (OR 1.48), women who had less than 8 years of formal education (OR 2.42), women who delivered in a public hospital (OR 6.92), women who had more than 4 previous pregnancies (OR 1.60), and women who had one or more prior fetal loss (OR 1.19). The odds of delivering an infant with CS also increased as the number of antenatal visits decreased. Women who did not attend any antenatal visits had 3.94 times the odds of delivering an infant with CS compared to women who attended 7 or more visits. Our study found that increased odds of delivering an infant with CS were highly associated with factors related to socioeconomic vulnerability. These determinants not only affect the access to essential antenatal care services, but also the continuity and quality of such preventive measures. Future policies aimed at reducing the incidence of CS should not only target those pregnant women and adolescents with identifiable risk factors for testing, but also assure high quality care, treatment and follow-up for this group.

Problems of access and quality of sanitary sewage disproportionately impact the health of populations in urban peripheries of low-and middle-income countries. The condominial sewer system is a practical, low-cost, effective, and simplified engineering approach compared to conventional sewer systems. In support of meeting the sanitation needs in highly populated urban settings, there is a need to understand the residents’ perceptions regarding the advantages and disadvantages of this sanitation model compared to conventional sewer systems. We conducted a cross-sectional study from September to December 2021 in two urban communities of Salvador, Bahia, Brazil, where condominial and conventional sewer systems had been implemented in the last five years. Of the 203 residents we interviewed, 50.7% lived in a site served by a condominial sewer system. Residents in the condominial sewer site reported not connecting to public sewage network (23.7% vs. 11.2%; p = 0.022) more often than in the conventional site. They reported more collective action to solve urban sanitation problems (69.9% vs. 54.0%; p = 0.020), such as manhole cleaning and unclogging efforts to fix plumbing. Despite these challenges, these residents expressed that the current service quality is better than it was in the previous two years. Our results suggest that even within urban periphery communities of a large Brazilian city, disparities exist in access to and quality of sanitation services that may be linked to sewage system implementation. Implementing simplified sewer systems is important to meet the growing sanitation demands of urban areas. However, these systems should also play a role in reducing sanitation disparities and the adoption of participatory approaches to meet the needs of populations in the most disadvantaged conditions. Despite challenging conditions, there is the potential for community engagement and active participation in sanitation-related matters, which could enhance the implementation and long-term sustainability of these systems.

Sociodemographic characteristics of study population.