About this dataset

Context

The dataset presents median household incomes for various household sizes in Brazil, IN, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Brazil did not include 6-person households. Across the different household sizes in Brazil the mean income is $94,186, and the standard deviation is $88,214. The coefficient of variation (CV) is 93.66%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households. Please note that the U.S. Census Bureau uses $250,001 as a JAM value to report incomes of $250,000 or more. In the case of Brazil, there were 1 household sizes where the JAM values were used. Thus, the numbers for the mean and standard deviation may not be entirely accurate and have a higher possibility of errors. However, to obtain an approximate estimate, we have used a value of $250,001 as the income for calculations, as reported in the datasets by the U.S. Census Bureau.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $27,461. It then further increased to $270,229 for 7-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/brazil-in-median-household-income-by-household-size.jpeg" alt="Brazil, IN median household income, by household size (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.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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. You can refer the same here

In 2023, there were 51.22 million nuclear households in Brazil, making it the most common sort of household. In addition, 14 million households were unipersonal, consisting of only one individual.

Brazil Number of Household: Type of Floor: Central West: Other Material data was reported at 36.789 Unit th in 2017. This records an increase from the previous number of 31.776 Unit th for 2016. Brazil Number of Household: Type of Floor: Central West: Other Material data is updated yearly, averaging 34.282 Unit th from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 36.789 Unit th in 2017 and a record low of 31.776 Unit th in 2016. Brazil Number of Household: Type of Floor: Central West: Other Material data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Domestic Trade and Household Survey – Table BR.HF029: Number of Household: by Type of Floor: Central West.

The 2003 Santarem dataset consists of 8 interconnected datasets and 1 linking file. The primary unit of analysis is the rural property or lot. Each lot in the sample contains a minimum of 1 household with a mean of 1.33 households per lot in the final sample. Within households, data were collected on subsets of individuals as well as additional properties used by the households in the study. These 2003 Santarem data come from interviews with farm families in an agricultural zone south of the city of Santarem in the Brazilian state of Para. Santarem is a relatively old settlement within the Brazilian Amazon that has experienced waves of regional settlement in the 1930s, mid-century, and the 1970s. The study region is adjacent to the confluence of the Amazon and Tapajos Rivers and the northern terminus of the BR-163 (the Cuiaba-Santarem Highway). BR-163 links intensive agropastoral production (particularly mechanized soybean farming) in the state of Mato Grosso to Santarem, where the multinational corporation Cargill runs a deepwater port (opened in 2003) for loading soybeans onto oceangoing ships. The opening of this port has accelerated the process of urbanization and led to a transformation from a landscape of small family farming to a landscape of mechanized agriculture (description adapted from VanWey, Leah K., and Kara B. Cebulko, 2007, Journal of Marriage and the Family 69: 1257-1270). The discourse on deforestation has focused on the alarming rates of deforestation in the Amazon Basin to the neglect of the dynamic and reciprocal influences between the human population and the environment. Deforestation is a process mediated by human intervention, from the act of clearing to how such a clearing is used and managed over time. It would be helpful to know whether observable rates of forest removal represent a stage in the developmental cycle of households or represents the simple and direct impact of increasing population in these environments. From the point of view of theory and method, it is necessary to develop new approaches that effectively link demographic process to the interactive relationship of population to specific aspects of an environmental matrix. This project addressed multiple scales, from household dynamics to landscape dynamics and has developed methods by which to scale between them. We hypothesize that as households occupy frontier areas past the first generation, they move from a strategy of managing their land under the constraints of available household labor to a strategy that gives greater recognition of the constraints posed by land quality and of the risks to their farm operation coming from external socioeconomic forces and biophysical constraints. In the first generation, the labor available to a household is determined by the size of the household making the initial trip to the frontier (primarily young couples is common in frontier regions) and later by the fertility of these initial migrants. As these initial migrants age and their children enter adulthood (thereby becoming the second generation), labor supply is determined by the reproductive and land use choices of these children. Given the precipitous decline in female fertility, other factors gain salience in the second generation: the suitability of the land for various uses, the availability of off-farm employment and educational opportunities (both locally and those requiring migration), and macroeconomic factors affecting the economic viability of farming. These decisions then directly determine the entries into and exits from the household. This study investigated five basic questions: (1) Does the changing availability of household labor over the household life cycle affect the trajectory of deforestation and land use change in the same way for later generations of Amazonian farmers as for first generation in-migrants? (2) What are the determinants of changing household labor supply? Specifically, what are the biophysical and socioeconomic determinants of entries into and exits from the household through fertility, migration, and marriage? (3) How are the decisions of households regarding land use and labor allocation constrained by soil quality, access to water supplies, interannual drought events (e.g. El Nino type events), and other resource scarcities? (4) Are there notable differences in land use choices made by la

After 2021, the amount of subsidy granted to Bolsa Familia families almost tripled. In December 2022, the amount was 383 reais higher than in the same period of the previous year. In 2024, the amount increased to 678 reais per month.

Abstract

This study is an experiment designed to compare the performance of three methodologies for sampling households with migrants:

• a stratified sample using the census to sample census tracts randomly, in which each household is then listed and screened to determine whether or not it has a migrant, with the full length questionnaire then being applied in a second phase only to the households of interest;
• a snowball survey in which households are asked to provide referrals to other households with migrant members;
• an intercept point survey (or time-and-space sampling survey), in which individuals are sampled during set time periods at a prespecified set of locations where households in the target group are likely to congregate.

Researchers from the World Bank applied these methods in the context of a survey of Brazilians of Japanese descent (Nikkei), requested by the World Bank. There are approximately 1.2-1.9 million Nikkei among Brazil’s 170 million population.

The survey was designed to provide detail on the characteristics of households with and without migrants, to estimate the proportion of households receiving remittances and with migrants in Japan, and to examine the consequences of migration and remittances on the sending households.

The same questionnaire was used for the stratified random sample and snowball surveys, and a shorter version of the questionnaire was used for the intercept surveys. Researchers can directly compare answers to the same questions across survey methodologies and determine the extent to which the intercept and snowball surveys can give similar results to the more expensive census-based survey, and test for the presence of biases.

Geographic coverage

Sao Paulo and Parana states

Analysis unit

Japanese-Brazilian (Nikkei) households and individuals

The 2000 Brazilian Census was used to classify households as Nikkei or non-Nikkei. The Brazilian Census does not ask ethnicity but instead asks questions on race, country of birth and whether an individual has lived elsewhere in the last 10 years. On the basis of these questions, a household is classified as (potentially) Nikkei if it has any of the following: 1) a member born in Japan; 2) a member who is of yellow race and who has lived in Japan in the last 10 years; 3) a member who is of yellow race, who was not born in a country other than Japan (predominantly Korea, Taiwan or China) and who did not live in a foreign country other than Japan in the last 10 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) Stratified random sample survey

Two states with the largest Nikkei population - Sao Paulo and Parana - were chosen for the study.

The sampling process consisted of three stages. First, a stratified random sample of 75 census tracts was selected based on 2000 Brazilian census. Second, interviewers carried out a door-to-door listing within each census tract to determine which households had a Nikkei member. Third, the survey questionnaire was then administered to households that were identified as Nikkei. A door-to-door listing exercise of the 75 census tracts was then carried out between October 13th, 2006, and October 29th, 2006. The fieldwork began on November 19, 2006, and all dwellings were visited at least once by December 22, 2006. The second wave of surveying took place from January 18th, 2007, to February 2nd, 2007, which was intended to increase the number of households responding.

2) Intercept survey

The intercept survey was designed to carry out interviews at a range of locations that were frequented by the Nikkei population. It was originally designed to be done in Sao Paulo city only, but a second intercept point survey was later carried out in Curitiba, Parana. Intercept survey took place between December 9th, 2006, and December 20th, 2006, whereas the Curitiba intercept survey took place between March 3rd and March 12th, 2007.

Consultations with Nikkei community organizations, local researchers and officers of the bank Sudameris, which provides remittance services to this community, were used to select a broad range of locations. Interviewers were assigned to visit each location during prespecified blocks of time. Two fieldworkers were assigned to each location. One fieldworker carried out the interviews, while the other carried out a count of the number of people with Nikkei appearance who appeared to be 18 years old or older who passed by each location. For the fixed places, this count was made throughout the prespecified time block. For example, between 2.30 p.m. and 3.30 p.m. at the sports club, the interviewer counted 57 adult Nikkeis. Refusal rates were carefully recorded, along with the sex and approximate age of the person refusing.

In all, 516 intercept interviews were collected.

3) Snowball sampling survey

The questionnaire that was used was the same as used for the stratified random sample. The plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (a) a Nikkei household with a member currently in Japan; (b) a Nikkei household with a member who has returned from Japan; (c) a Nikkei household without members in Japan and where individuals had not returned from Japan.

The snowball survey took place from December 5th to 20th, 2006. The second phase of the snowballing survey ran from January 22nd, 2007, to March 23rd, 2007. More associations were contacted to provide additional seed names (69 more names were obtained) and, as with the stratified sample, an adaptation of the intercept survey was used when individuals refused to answer the longer questionnaire. A decision was made to continue the snowball process until a target sample size of 100 had been achieved.

The final sample consists of 60 households who came as seed households from Japanese associations, and 40 households who were chain referrals. The longest chain achieved was three links.

Mode of data collection

Face-to-face [f2f]

Research instrument

1) Stratified sampling and snowball survey questionnaire

This questionnaire has 36 pages with over 1,000 variables, taking over an hour to complete.

If subjects refused to answer the questionnaire, interviewers would leave a much shorter version of the questionnaire to be completed by the household by themselves, and later picked up. This shorter questionnaire was the same as used in the intercept point survey, taking seven minutes on average. The intention with the shorter survey was to provide some data on households that would not answer the full survey because of time constraints, or because respondents were reluctant to have an interviewer in their house.

2) Intercept questionnaire

The questionnaire is four pages in length, consisting of 62 questions and taking a mean time of seven minutes to answer. Respondents had to be 18 years old or older to be interviewed.

Response rate

1) Stratified random sampling 403 out of the 710 Nikkei households were surveyed, an interview rate of 57%. The refusal rate was 25%, whereas the remaining households were either absent on three attempts or were not surveyed because building managers refused permission to enter the apartment buildings. Refusal rates were higher in Sao Paulo than in Parana, reflecting greater concerns about crime and a busier urban environment.

2) Intercept Interviews 516 intercept interviews were collected, along with 325 refusals. The average refusal rate is 39%, with location-specific refusal rates ranging from only 3% at the food festival to almost 66% at one of the two grocery stores.

The Brazil family office market reached approximately USD 807.39 Million in 2024. The market is projected to grow at a CAGR of 7.80% between 2025 and 2034, reaching a value of around USD 1711.08 Million by 2034.

Florianópolis, SC, and Rio de Janeiro, RJ, had the most expensive housing in Brazil in July 2024. The average house price in Florianópolis, the capital of Southern Brazil's Santa Catarina state, cost close to 1.4 million Brazilian reals, whereas in Rio de Janeiro, it was about 1.2 million Brazilian reals. From the 12 cities under observation, João Pessoa had the most affordable housing, with the average house price at 600,000 Brazilian reals. House prices in Brazil have grown year-on-year since 2018.

Brazil Wholesale Trade: CNAE 2.0: Other Equipment, Personal Items & Household: Self Employed: Family Members data was reported at 700.000 Person in 2017. This records an increase from the previous number of 326.000 Person for 2016. Brazil Wholesale Trade: CNAE 2.0: Other Equipment, Personal Items & Household: Self Employed: Family Members data is updated yearly, averaging 326.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 857.000 Person in 2013 and a record low of 134.000 Person in 2007. Brazil Wholesale Trade: CNAE 2.0: Other Equipment, Personal Items & Household: Self Employed: Family Members data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Wholesale Trade, Retail Trade, Repair of Automotive and Motorcycles Sector – Table BR.RJB012: Wholesale Trade: Financial Data: CNAE 2.0: Other Equipment, Personal Items and Household.

Brazil Retail Trade: CNAE 2.0: Non Specialised with Predominance of Food Products: Self Employed: Family Members data was reported at 27,236.000 Person in 2017. This records a decrease from the previous number of 28,682.000 Person for 2016. Brazil Retail Trade: CNAE 2.0: Non Specialised with Predominance of Food Products: Self Employed: Family Members data is updated yearly, averaging 35,426.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 53,301.000 Person in 2012 and a record low of 14,378.000 Person in 2015. Brazil Retail Trade: CNAE 2.0: Non Specialised with Predominance of Food Products: Self Employed: Family Members data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Wholesale Trade, Retail Trade, Repair of Automotive and Motorcycles Sector – Table BR.RJD005: Retail Trade: Financial Data: CNAE 2.0: Non Specialised with Predominance of Food Products.

The following types of information are covered by each WAS survey:household composition (for example, number of adults); household spending;household durable goods ownership;employment and earnings; attitudes, mainly the measurement of 'feminist' or 'machismo' views; demographic information, such as age; household financial management (i.e. who organises money).Standard Measures Likert Scales were used, many of which are based on the British Household Panel Study (BHPS) questionnaire (held at the UK Data Archive under SN 5151). See documentation for details. Face-to-face interview 1992 2007 ADMINISTRATIVE AREAS AGE ALCOHOL USE ATTITUDES BEVERAGES Brazil CARE OF DEPENDANTS CASTE CEREAL PRODUCTS CEREALS CHILD CARE CHILDREN CLEANING CONFECTIONERY CONSUMER GOODS CONSUMPTION COOKING Consumption and con... DAIRY PRODUCTS DECISION MAKING DIVORCE DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... DOMESTIC SERVICES DOMESTIC VIOLENCE ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND ELECTRIC POWER EMPLOYMENT EMPLOYMENT HISTORY EQUALITY BETWEEN TH... ETHNIC GROUPS EXPENDITURE Egypt FAMILIES FAMILY INCOME FAMILY LIFE FAMILY MEMBERS FAMILY PLANNING FAMILY ROLES FINANCIAL RESOURCES FISH AS FOOD FOOD FOSSIL FUELS FRUIT GENDER Gender and gender r... HOME SHARING HOTELS HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD INCOME HOUSEHOLDS HOUSING HOUSING FINANCE INCOME INFIDELITY India Indonesia Kenya LANGUAGES USED AT HOME LAUNDRIES LOANS Labour and employment MARITAL STATUS MARRIED MEN MARRIED WOMEN MARRIED WOMEN WORKERS MEALS MEAT Nigeria OCCUPATIONS PERSONAL FINANCE MA... PLACE OF BIRTH PLACE OF RESIDENCE RELIGIOUS AFFILIATION RENTS RESTAURANTS SAVINGS SELF EMPLOYED SOCIAL CLASS SPOUSE S EDUCATIONA... SPOUSES South Africa TELEPHONES TIME BUDGETS TOWNS VEGETABLE OILS VEGETABLES WOMEN S MOVEMENT WORKING MOTHERS WORKING WOMEN

Brazil Retail Trade: CNAE 2.0: Fabrics, Haberdashery Articles, Clothing & Footwear: Self Employed: Family Members data was reported at 8,318.000 Person in 2017. This records a decrease from the previous number of 18,987.000 Person for 2016. Brazil Retail Trade: CNAE 2.0: Fabrics, Haberdashery Articles, Clothing & Footwear: Self Employed: Family Members data is updated yearly, averaging 19,874.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 50,477.000 Person in 2011 and a record low of 5,090.000 Person in 2015. Brazil Retail Trade: CNAE 2.0: Fabrics, Haberdashery Articles, Clothing & Footwear: Self Employed: Family Members data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Wholesale Trade, Retail Trade, Repair of Automotive and Motorcycles Sector – Table BR.RJD008: Retail Trade: Financial Data: CNAE 2.0: Fabrics, Haberdashery Articles, Clothing and Footwear.

Brazil Life & Non-Life Insurance Market size was valued at USD 134.0 Billion in 2024 and is projected to reach USD 233.7 Billion by 2032, growing at a CAGR of 7.2% from 2025 to 2032.

Key Market Drivers: Growing Middle Class and Rising Income Levels: The Brazilian Life & Non-Life Insurance Market is being driven by a growing middle class and rising income levels, which are increasing insurance affordability and demand. Brazil's average real household income increased to R$5,925 per month in 2023, from R$5,457 in 2019 (IBGE). This has increased purchasing power, resulting in a 12.8% increase in life insurance premiums in 2022, according to SUSEP, as the increasing middle class becomes more interested in life and personal accident coverage.

Brazilian Residential Real Estate Market size was valued at USD 65 Billion in 2023 and is projected to reach USD 100 Billion by 2031, growing at a CAGR of 5.3% from 2024 to 2031.

Key Market Drivers:

Growing Middle Class and Improved Access to Mortgage Financing: Between 2019 and 2023, Brazil's middle class climbed from 23% to 31%, increasing home demand. According to IBGE and the Central Bank of Brazil, mortgage lending increasing by 14% year on year to R$255 billion in 2023, demonstrating greater access to house finance.

Housing Shortage and Urbanization: Brazil is experiencing a housing deficiency of around 5.8 million units, with 87% concentrated in cities. According to the João Pinheiro Foundation and IBGE's census, the urbanization rate has reached 87.1%, resulting in significant housing demand in metropolitan areas. This highlights the importance of real estate development.

Latin America Manufactured Homes Market is Segmented by Type (Single Family and Multiple Family) and By Geography (Brazil, Mexico, Argentina, and the Rest of Latin America). The report offers market sizes and forecasts in value (USD billion) for all the above segments.

The Latin American manufactured homes market presents a compelling investment opportunity, exhibiting robust growth potential fueled by several key factors. The market, currently valued at approximately $XX million (the exact figure is not provided, but can be estimated based on the given CAGR of >6% and a plausible starting market size. For illustrative purposes, let's assume a 2025 market size of $2 billion, pending access to the actual figure ), is projected to experience significant expansion throughout the forecast period (2025-2033). This growth is primarily driven by increasing urbanization, a burgeoning middle class seeking affordable housing solutions, and government initiatives promoting sustainable and cost-effective construction methods. The rising demand for faster construction timelines and reduced construction costs compared to traditional site-built homes also significantly contributes to market expansion. Brazil, Mexico, and Argentina represent the largest market segments within Latin America, although growth opportunities exist across the entire region, with potential for expansion in secondary markets as affordability and awareness increase. While challenges remain, including the need for improved infrastructure and financing options in certain areas, the overall market outlook is positive, with continued growth anticipated throughout the forecast period. The market segmentation reveals key opportunities within the single-family and multi-family home categories. While single-family homes currently dominate the market share, multi-family housing projects are expected to witness significant growth driven by increasing population density in urban areas and the demand for rental accommodation. The competitive landscape features both local and international players, indicating considerable potential for market entry and consolidation in the coming years. Effective strategies will involve adapting designs to local climates and building codes, fostering strong relationships with local suppliers, and addressing logistical challenges to optimize supply chain efficiencies. Further research into specific regional dynamics within Latin America will be crucial for targeted investment and market penetration strategies. Recent developments include: January 2023 - Cavco Industries (producers of manufactured and modular homes in the United States) announced that it has completed the acquisition of manufactured home builder and retailer, Solitaire Homes. Solitaire Homes operates manufacturing facilities in New Mexico, Oklahoma, and Mexico, with retail locations across New Mexico, Oklahoma, and Texas., August 2022 - A wholly-owned subsidiary of Chinese company Weisu, called Vessel, and with manufacturing plants already established in China, Hawaii, and Japan, the new Vessel Mexico expects to begin manufacturing at the end of 2024. The new plant will be situated in Nuevo Leon (a northeast region of Mexico) to construct the modular houses. The vessel is aiming to start operations in Mexico at the end of 2023, with its first houses ready for sale in 2024. The vessel has further indicated its intention to launch in Colombia, Ecuador, Argentina, Peru, and Brazil.. Notable trends are: Low Construction Cost Propels the Demand for Manufactured Homes.

IntroductionTerritory view based on families’ vulnerability strata allows identifying different health needs that can guide healthcare at primary care scope. Despite the availability of tools designed to measure family vulnerability, there is still a need for substantial validity evidence, which limits the use of these tools in a country showing multiple socioeconomic and cultural realities, such as Brazil. The primary objective of this study is to develop and gather evidence on the validity of the Family Vulnerability Scale for Brazil, commonly referred to as EVFAM-BR (in Portuguese).MethodsItems were generated through exploratory qualitative study carried out by 123 health care professionals. The data collected supported the creation of 92 initial items, which were then evaluated by a panel of multi-regional and multi-disciplinary experts (n = 73) to calculate the Content Validity Ratio (CVR). This evaluation process resulted in a refined version of the scale, consisting of 38 items. Next, the scale was applied to 1,255 individuals to test the internal-structure validity by using the Exploratory Factor Analysis (EFA). Dimensionality was evaluated using Robust Parallel Analysis, and the model underwent cross-validation to determine the final version of EVFAM-BR.ResultsThis final version consists of 14 items that are categorized into four dimensions, accounting for an explained variance of 79.02%. All indicators were within adequate and satisfactory limits, without any cross-loading or Heywood Case issues. Reliability indices also reached adequate levels (α = 0.71; ω = 0.70; glb = 0.83 and ORION ranging from 0.80 to 0.93, between domains). The instrument scores underwent a normalization process, revealing three distinct vulnerability strata: low (0 to 4), moderate (5 to 6), and high (7 to 14).ConclusionThe scale exhibited satisfactory validity evidence, demonstrating consistency, reliability, and robustness. It resulted in a concise instrument that effectively measures and distinguishes levels of family vulnerability within the primary care setting in Brazil.

Brazil Retail Trade: CNAE 2.0: Other New Products: Self Employed: Family Members data was reported at 20,878.000 Person in 2017. This records an increase from the previous number of 8,706.000 Person for 2016. Brazil Retail Trade: CNAE 2.0: Other New Products: Self Employed: Family Members data is updated yearly, averaging 10,361.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 23,016.000 Person in 2013 and a record low of 6,189.000 Person in 2010. Brazil Retail Trade: CNAE 2.0: Other New Products: Self Employed: Family Members data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Wholesale Trade, Retail Trade, Repair of Automotive and Motorcycles Sector – Table BR.RJD021: Retail Trade: Financial Data: CNAE 2.0: Other New Products.

Brazil BR: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data was reported at 11.608 % in 2017. This records a decrease from the previous number of 13.184 % for 2012. Brazil BR: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data is updated yearly, averaging 13.184 % from Dec 2009 (Median) to 2017, with 3 observations. The data reached an all-time high of 17.639 % in 2009 and a record low of 11.608 % in 2017. Brazil BR: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day 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: Health Statistics. The average time women spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.;National statistical offices or national database and publications compiled by United Nations Statistics Division. The data were downloaded on February 14, 2023, from the Global SDG API: https://unstats.un.org/sdgs/UNSDGAPIV5/swagger/index.html;;This is the Sustainable Development Goal indicator 5.4.1[https://unstats.un.org/sdgs/metadata/].

BR: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data was reported at 5.133 % in 2017. This records an increase from the previous number of 3.035 % for 2012. BR: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data is updated yearly, averaging 5.133 % from Dec 2009 (Median) to 2017, with 3 observations. The data reached an all-time high of 5.972 % in 2009 and a record low of 3.035 % in 2012. BR: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day 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: Health Statistics. The average time men spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.;National statistical offices or national database and publications compiled by United Nations Statistics Division. The data were downloaded on February 14, 2023, from the Global SDG API: https://unstats.un.org/sdgs/UNSDGAPIV5/swagger/index.html;;This is the Sustainable Development Goal indicator 5.4.1[https://unstats.un.org/sdgs/metadata/].