About this dataset

Context

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

• Brisbane, CA annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Brisbane, CA 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 Brisbane income distribution by gender. You can refer the same here

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.

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.

VITAL SIGNS INDICATOR

Population (LU1)

FULL MEASURE NAME

Population estimates

LAST UPDATED

September 2016

DESCRIPTION

Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES

U.S. Census Bureau

1960-1990

Decennial Census

http://factfinder2.census.gov

California Department of Finance

1961-2016

Population and Housing Estimates

http://www.dof.ca.gov/research/demographic/

CONTACT INFORMATION

vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)

All legal boundaries and names for Census geography (metropolitan statistical area, county, city, tract) are as of January 1, 2010, released beginning November 30, 2010 by the U.S. Census Bureau. A priority development area (PDA) is a locally-designated infill area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are as current as July 2016. Population estimates for PDAs were derived from Census population counts at the block group level for 2000-2014 and at the tract level for 1970-1990.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average). Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average.

Estimates of density for tracts and PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area:

Big Three: San Jose, San Francisco, Oakland

Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside

InlandCoastalDelta: American Canyon, Benicia, Clayton, Concord, Cotati, Danville, Dublin, Lafayette, Martinez, Moraga, Napa, Novato, Orinda, Petaluma, Pleasant Hill, Pleasanton, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Walnut Creek, Antioch, Brentwood, Calistoga, Cloverdale, Dixon, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Livermore, Morgan Hill, Oakley, Pittsburg, Rio Vista, Sonoma, St. Helena, Suisun City, Vacaville, Windsor, Yountville

Unincorporated: all unincorporated towns

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

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

PM2.5 values baseline and sensitivity scenarios.

Health care costs and health outcomes for base case by sex over the life course of the Brisbane adult population (95% uncertainty interval).

The final Australian National Liveability Study 2018 datasets comprise a suite of policy relevant spatial indicators of local neighbourhood liveability and amenity access estimated for residential address points across Australia's 21 largest cities, and summarised at range of larger area scales (Mesh Block, Statistical Areas 1-4, Suburb, LGA, and overall city summaries). The indicators and measures included encompass topics including community and health services, employment, food, housing, public open space, transportation, walkability and overall liveability. The datasets were produced through analysis of built environment and social data from multiple sources including OpenStreetMap the Australian Bureau of Statistics, and public transport agency GTFS feed data. These are provided in CSV format under an Open Data Commons Open Database licence. The 2018 Australian National Liveability data will be of interest to planners, population health and urban researchers with an interest in the spatial distribution of built environment exposures and outcomes for data linkage, modelling and mapping purposes. Area level summaries for the data were used to create the indicators for the Australian Urban Observatory at its launch in 2020. A detailed description of the datasets and the study has been published in Nature Scientific Data, and notes and code illustrating usage of the data are located on GitHub. The spatial data were developed by the Healthy Liveable Cities Lab, Centre for Urban Research with funding support provided from the Australian Prevention Partnership Centre #9100003, NESP Clean Air and Urban Landscapes Hub, NHMRC Centre of Research Excellence in Healthy, Liveable Communities #1061404 and an NHMRC Senior Principal Research Fellowship GNT1107672; with interactive spatial indicator maps accessible via the Australian Urban Observatory. Any publications utilising the data are not necessarily the view of or endorsed by RMIT University or the Centre of Urban Research. RMIT excludes all liability for any reliance on the data.

Road trauma rates per 100 million kilometres travelled by transport mode.

Mode share travel targets.

The Australian luxury residential property market is estimated to have a market size of 23.88 million in 2025, with a projected CAGR of 5.75% from 2025 to 2033. The market is driven by the increasing demand for luxury properties from wealthy individuals and families, both domestic and international. Other key drivers include low interest rates, strong economic growth, and a growing population of high-net-worth individuals. Key trends in the market include the increasing popularity of apartments and condominiums, the rise of eco-friendly luxury developments, and the growing demand for properties in regional areas. Constraints to the market include the lack of affordable housing, government regulations, and rising construction costs. The market is segmented by type (apartments and condominiums, villas and landed houses) and city (Sydney, Perth, Melbourne, Brisbane, other cities). Major companies in the market include Stunning Homes, Medallion Homes, Summit South West, Atrium Homes, and James Michael Homes. Recent developments include: August 2023: Sydney-based boutique developer Made Property laid plans for a new apartment project along Sydney Harbour amid sustained demand for luxury waterfront properties. The Corsa Mortlake development, positioned on Majors Bay in the harbor city’s inner west, will deliver 20 three-bedroom apartments offering house-sized living spaces and ready access to a 23-berth marina accommodating yachts up to 20 meters. With development approval secured for the project, the company is moving quickly to construction. Made Property expects construction to be completed in late 2025., September 2023: A luxurious collection of private apartment residences planned for a prime double beachfront site in North Burleigh was released to the market for the first time with the official launch of ultra-premium apartment development Burly Residences, being delivered by leading Australian developer David Devine and his team at DD Living. The first stage of Burly Residences released to the market includes prestigious two and three-bedroom apartments – with or without multipurpose rooms – and four-bedroom plus multipurpose room apartments that deliver luxury and space with expansive ocean and beach views.. Key drivers for this market are: 4., Increasing Number of High Net-Worth Individuals (HNWIs). Potential restraints include: 4., Rising Interest Rates. Notable trends are: Ultra High Net Worth Population Driving the Demand for Prime Properties.

Australia's café and restaurant scene continues to thrive, with New South Wales leading the way with over 19,225 establishments in operation at the end of the 2024 financial year. The second-leading state in terms of the number of cafés and restaurants was Victoria. As Australia's two largest states in terms of population, the concentration of food service establishments in New South Wales and Victoria mirrors Australia's population distribution, reflecting the urban-centric nature of the country's café and restaurant landscape. Gastronomy: a key economic sector In recent years, the number of cafés and restaurants throughout the country has shown relatively consistent growth, exceeding 55,700 in the 2024 financial year, up from approximately 41,570 in 2017. Australia's cafés, restaurants, and takeaway food services turnover experienced steady annual increases for many years up until the start of the COVID-19 pandemic. Nevertheless, since 2021, the industry's revenue has been on the recovery, hitting a record of over 65 billion Australian dollars in 2024. Additionally, food services represent a key source of gross value added to the tourism industry. An added boost from coffee Coffee plays an important role in the Australian food service sector, with the beverage topping the list of regularly consumed drinks among Australians in a 2024 survey. Several international chains like McCafé operate alongside popular domestic coffee franchises, including The Coffee Club, in the country. Alongside this, the country's annual domestic coffee consumption remains robust, consistently exceeding two million sixty-kilogram bags in recent years, underscoring the enduring nature of Australia's coffee culture. Nonetheless, recent cost-of-living pressures have led to a shift in consumer behavior, with more Australians opting to brew their coffee at home.

Proportional multi-state life table Markov model input parameters.

Additional mean minutes per week of transport physical activity undertaken in the travel targets scenario compared to the baseline scenario (statu-quo), by age and sex.

Mode-specific mean (95% uncertainty interval (UI)) trips per weekday in 2009, by age and sex.