Chart and table of population level and growth rate for the Brisbane, Australia metro area from 1950 to 2025.

About this dataset

Context

The dataset tabulates the Brisbane population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Brisbane. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 3,026 (64.14% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Brisbane population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Brisbane is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Brisbane is shown in the following column.

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 Brisbane Population by Age. You can refer the same here

Australia Population: Resident: Estimated: Annual: Queensland: Greater Brisbane data was reported at 2,413,457.000 Person in 2017. This records an increase from the previous number of 2,362,672.000 Person for 2016. Australia Population: Resident: Estimated: Annual: Queensland: Greater Brisbane data is updated yearly, averaging 2,171,862.000 Person from Jun 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 2,413,457.000 Person in 2017 and a record low of 1,908,265.000 Person in 2006. Australia Population: Resident: Estimated: Annual: Queensland: Greater Brisbane data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G002: Estimated Resident Population.

About this dataset

Context

The dataset tabulates the population of Brisbane by race. It includes the population of Brisbane across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Brisbane across relevant racial categories.

Key observations

The percent distribution of Brisbane population by race (across all racial categories recognized by the U.S. Census Bureau): 49.19% are white, 0.02% are Black or African American, 1.65% are American Indian and Alaska Native, 32.32% are Asian, 0.51% are Native Hawaiian and other Pacific Islander, 6.21% are some other race and 10.09% are multiracial.

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 (excluding ethnicity) for the Brisbane
• Population: The population of the racial category (excluding ethnicity) in the Brisbane is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Brisbane total 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 Brisbane Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Brisbane, CA population pyramid, which represents the Brisbane population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Brisbane, CA, is 27.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Brisbane, CA, is 23.4.
• Total dependency ratio for Brisbane, CA is 50.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Brisbane, CA is 4.3.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Brisbane population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Brisbane for the selected age group is shown in the following column.
• Population (Female): The female population in the Brisbane for the selected age group is shown in the following column.
• Total Population: The total population of the Brisbane for the selected age group is shown in the following column.

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 Brisbane Population by Age. You can refer the same here

As of October 2024, approximately ****** Japanese residents lived in the Brisbane metropolitan area. This represents an increase from around ****** residents in the previous year.

About this dataset

Context

The dataset tabulates the population of Brisbane by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Brisbane. The dataset can be utilized to understand the population distribution of Brisbane by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Brisbane. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Brisbane.

Key observations

Largest age group (population): Male # 45-49 years (312) | Female # 5-9 years (217). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Brisbane population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Brisbane is shown in the following column.
• Population (Female): The female population in the Brisbane is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Brisbane for each age group.

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 Brisbane Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the Brisbane population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Brisbane. The dataset can be utilized to understand the population distribution of Brisbane by age. For example, using this dataset, we can identify the largest age group in Brisbane.

Key observations

The largest age group in Brisbane, CA was for the group of age 40 to 44 years years with a population of 490 (10.39%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Brisbane, CA was the 85 years and over years with a population of 77 (1.63%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Brisbane is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Brisbane total 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 Brisbane Population by Age. You can refer the same here

The Brisbane Community Profiles provide detailed statistical information for Greater Brisbane and Brisbane City using information from the Australian Bureau of Statistics, Commonwealth and Queensland Government sources.

Profiles are generated using the latest demographic, social and economic data to gather information about the people who live in an area (Resident Profile) the workers and businesses that operate in the area (Workforce Profile) or how the area has changed over time (Time Series Profile).

The Data and resources section of this dataset contains further information for this dataset.

To select and view data use the link in the Data and resources section below.

The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:

Year Month GCCSA (Greater Capital City Statistical Area, which is used to define capital cities) Date (using the first day of the month) fulltime: Fulltime workers parttime: Parttime workers n. Overall workers outorin. Estimated indoor or outdoor status

This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.

Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers. The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."

ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).

To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).

ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.

人口：居民：估计：年度：昆士兰：大布里斯班 在06-01-2017达2,413,457.000人，相较于06-01-2016的2,362,672.000人有所增长。人口：居民：估计：年度：昆士兰：大布里斯班 数据按年更新，06-01-2006至06-01-2017期间平均值为2,171,862.000人，共12份观测结果。该数据的历史最高值出现于06-01-2017，达2,413,457.000人，而历史最低值则出现于06-01-2006，为1,908,265.000人。CEIC提供的人口：居民：估计：年度：昆士兰：大布里斯班 数据处于定期更新的状态，数据来源于Australian Bureau of Statistics，数据归类于全球数据库的澳大利亚 – 表 AU.G002：估计常住人口。

The Australian Marine Microbial Biodiversity Initiative (AMMBI) provides methodologically standardized, continental scale, temporal phylogenetic amplicon sequencing data describing Bacteria, Archaea and microbial Eukarya assemblages. Sequence data is linked to extensive physical, biological and chemical oceanographic contextual information. Samples are collected monthly to seasonally from multiple depths at seven National Reference Stations (NRS) sites: Darwin Harbour (Northern Territory), Yongala (Queensland), North Stradbroke Island (Queensland), Port Hacking (New South Wales), Maria Island (Tasmania), Kangaroo Island (South Australia), Rottnest Island (Western Australia). The Integrated Marine Observing System (IMOS) NRS network is described at http://imos.org.au/facilities/nationalmooringnetwork/nrs/ North Stradbroke Island NRS is located 6.6 nm north east of North Stradbroke Island at a depth of 60 m over sandy substrate. It is 30 km southeast of the major city of Brisbane, Queensland (population 2.099 million), at the opening to large, shallow, Moreton Bay. The site is impacted by the southerly flowing EAC and its eddies, which may cause periodic nutrient enrichment through upwelling. This latitude is the biogeographic boundary for many tropical and subtropical species. The water column is well mixed between May-August and stratified for the remainder of the year and salinity may at times be affected by floodwaters from the nearby Brisbane River outflow.

Site details from Brown, M. V. et al. Continental scale monitoring of marine microbiota by the Australian Marine Microbial Biodiversity Initiative. Sci. Data 5:180130 doi: 10.1038/sdata.2018.130 (2018). Site location: North Stradbroke Island National Reference Station (NRS), Queensland, Australia Note on data download/processing: Data downloaded from Australian Microbiome Initiative via Bioplatforms Australia Data Portal on 17 June 2022. The search filter applied to download data from Bioplatforms Australia Data portal are stored in the Darwin Core property (identificationRemarks). Taxonomy is assigned according to the taxonomic database (SILVA 138) and method (Sklearn) which is stored in the Darwin Core Extension DNA derived data property (otu_db). Prefix were removed from the taxonomic names as shown in the example (e.g. d_Bacteria to Bacteria). Scientific name is assigned to the valid name available from the highest taxonomic rank. This collection is published as Darwin Core Occurrence, so the event level measurements need to be replicated for every occurrence. Instead of data replication, the event level eMoF data are made available separately at https://www.marine.csiro.au/data/services/obisau/emof_export.cfm?ipt_resource=bioplatforms_mm_nrs_nsi Please see https://www.australianmicrobiome.com/protocols/acknowledgements/ for citation examples and links to the data policy.

Yearly registered births – breakdown by Month

Change in prevalent cases and mortality over the life course of the Brisbane adult population (95% uncertainty interval).

This dataset is the June 2022 release of Geoscape Planning for a single SA2 area (Brisbane City) with SA2 code (31105). Buildings is a spatial dataset which represents Australia's built environment derived from remotely sensed imagery and aggregated data sources. The Buildings dataset has relationships with the G-NAF, Cadastre, Property and Administrative Boundaries products produced by Geoscape Australia. Users should note that these related Geoscape products are not part of Buildings. For more information regarding Geoscape Buildings, please refer to the Data Product Description and the June 2022 Release Notes. Please note: As per the licence for this data, the coverage area accessed by you can not be greater than a single Level 2 Statistical Area (SA2) as defined by the Australian Bureau of Statistics. If you require additional data beyond a single SA2 for your research, please request a quote from AURIN. Buildings is a digital dataset representing buildings across Australia. Data quality and potential capture timelines will vary across Australia based on two categories, each category has been developed based on a number of factors including the probability of the occurrence of natural events (e.g. flooding), population distribution and industrial/commercial activities. Areas with a population greater than 200, or with significant industrial/commercial activity in a visual assessment have been defined as 'Urban' and all other regions have been defined as 'Rural'. This dataset has been restricted to the Brisbane City SA2 by AURIN.

This data collection accompanies “Froese, J.G., Rees, M., Murray, J.V., Wilson, C. & Gentle, M. (2022). Modelling feral pig habitat suitability in Queensland to inform disease preparedness and response. Final report prepared for the Queensland Department of Agriculture and Fisheries. Brisbane: CSIRO.”

It contains a series of spatial data products describing ‘feral pig habitat suitability’, ‘potential feral pig density (carrying capacity)’ and ‘feral/domestic pig interaction risk’ across Queensland for 12 temporal scenarios. Scenarios were selected to represent variability in environmental conditions across Queensland along two axes – intra-annual seasonal cycles (summer, autumn, winter, spring) and inter-annual climate cycles (wet, moderate and dry). They were represented by the periods September 2010 – August 2011 (wet climate cycle), December 2012 – November 2013 (moderate climate cycle) and March 2018 – February 2019 (dry climate cycle). The data are provided in TIFF raster file format (coordinate reference system = EPSG 3577: GDA94 / Australian Albers; spatial resolution = 100m). Lineage: The methods to derive these spatial data products built on previously published research on spatially explicit, resource-based feral pig habitat models (Froese et al. 2017; Murray et al. 2015). ‘Habitat suitability’ for feral pig breeding was modelled in a Bayesian network framework dependent on four fundamental resource requirements: food, water, heat refuge and anthropogenic disturbance. Several improvements to increase the robustness and reproducibility of published research methods were implemented and applied to the 12 modelled scenarios.

Estimates of ‘potential feral pig density (carrying capacity)’ were derived for each of these 12 modelled scenarios. This was based on a hypothesized sigmoid relationship that took into account the modelled ‘habitat suitability index (HSI)’ in a particular season, cross-seasonal variability in the modelled HSI within a climate cycle (wet, moderate or dry) and pig densities in Queensland previously reported in the empirical literature.

The potential feral pig density estimates were combined with a ‘weighted domestic pig herd density’ layer that was derived from data on the location and biosecurity status of all registered domestic pigs in Queensland (held by the Queensland Department of Agriculture and Fisheries) to calculate ‘feral/domestic pig interaction risk’ (i.e., the relative risk that feral pig populations at a given landscape location may interact with a nearby domestic pig herd) for each of the 12 modelled scenarios.

Details on study objectives, methods and results are provided in the client report: “Froese, J.G., Rees, M., Murray, J.V., Wilson, C. & Gentle, M. (2022). Modelling feral pig habitat suitability in Queensland to inform disease preparedness and response. Final report prepared for the Queensland Department of Agriculture and Fisheries. Brisbane: CSIRO.” (contact Matthew Gentle: Matthew.Gentle@daf.qld.gov.au)

These are returns of householders, March 1829 and of population for 1833 and 1836.

(4/5525 part; microfilm copy SR Reel 895). 1 vol (part).

Note:
This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

Births that occurred by hospital name. Birth events of 5 or more per hospital location are displayed

Queensland Top 100 Baby Names

PM2.5 values baseline and sensitivity scenarios.