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.;;

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;

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 140(4.03%) households where the householder is under 25 years old, 1,151(33.13%) households with a householder aged between 25 and 44 years, 1,096(31.55%) households with a householder aged between 45 and 64 years, and 1,087(31.29%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 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) 2019-2023 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 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.

This dataset provides a regional detailed overview of the Brazil digital music consumption in Spotify between 2021-2023. It includes acoustic features and all genres/artists that are listened at least one time in those years. The data is provided by the Spotify API for Developers and the SpotifyCharts wich are used to collect the acoustic features and the summarized most listened songs in city, respectively.

Data description

It contemplates 17 cities of 16 different states in Brazil that achieved 5190 unique tracks, 487 different genres and 2056 artists. The covered cities are: Belém, Belo Horizonte, Brasília, Campinas, Campo Grande, Cuiabá, Curitiba, Florianópolis, Fortaleza, Goiânia, Manaus, Porto Alegre, Recife, Rio de Janeiro, Salvador, São Paulo and Uberlândia. Each city has 119 different weekly's charts wich the week period is described by the file name.

Acoustic features

The covered acoustic features are provided by Spotify and are described as: - Acousticness: Measures from 0.0 to 1.0 of wheter the track is acoustic; 1.0 indicates a totally acoustic song and 0.0 means a song without any acoustic element - Danceability: Describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable. - Energy: is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy. - Instrumentalness: Predicts whether a track contains no vocals. "Ooh" and "aah" sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly "vocal". The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0. - Key: The key the track is in. Integers map to pitches using standard Pitch Class notation. E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1. - Liveness: Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live. - Loudness: The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typically range between -60 and 0 db. - Mode: Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1 and minor is 0. - Speechiness: Detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values below 0.33 most likely represent music and other non-speech-like tracks. - Tempo: The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration. - Time Signature: An estimated time signature. The time signature (meter) is a notational convention to specify how many beats are in each bar (or measure). The time signature ranges from 3 to 7 indicating time signatures of "3/4", to "7/4". - Valence: A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).

Data Science Applications:

• Time Series Analysis: Identify seasonal behaviors and the deviation of each city during those 2 years
• Trend Analysis: Identify patterns and trends in digital music consumption based in genres and/or acoustic features in each city to understand seasonal changes
• Clustering Tasks: Group cities based on genre and/or acoustic features to identify different regional patterns between Brazil's regions and describe the difference between each group

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 140(4.21%) households where the householder is under 25 years old, 1,113(33.48%) households with a householder aged between 25 and 44 years, 1,082(32.55%) households with a householder aged between 45 and 64 years, and 989(29.75%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 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) 2018-2022 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

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...,

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.

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.

Characteristics of the study population according to completed gestational weeks, municipality of São Paulo, Brazil, 2012–2018 (n = 440,119).