The IPUMS Contextual Determinants of Health (CDOH) data series includes measures of disparities, policies, and counts, by state or county, for historically marginalized populations in the United States including Black, Asian, Hispanic/Latina/o/e/x, and LGBTQ+ persons, and women. The IPUMS CDOH data are made available through ICPSR/DSDR for merging with the National Couples' Health and Time Study (NCHAT), United States, 2020-2021 (ICPSR 38417) by approved restricted data researchers. All other researchers can access the IPUMS CDOH data via the IPUMS CDOH website. Unlike other IPUMS products, the CDOH data are organized into multiple categories related to Race and Ethnicity, Sexual and Gender Minority, Gender, and Politics. The CDOH measures were created from a wide variety of data sources (e.g., IPUMS NHGIS, the Census Bureau, the Bureau of Labor Statistics, the Movement Advancement Project, and Myers Abortion Facility Database). Measures are currently available for states or counties from approximately 2015 to 2020. The Sexual and Gender measures in this release include the proportion of a state's population identifying as LGBTQ+ in the U.S. Census Bureau's Household Pulse Survey, Phases 3.2 (07/21/2021-10/11/2021), 3.3 (12/01/2021-02/07/2022), 3.4 (03/02/2022-05/09/2022), and 3.5 (06/01/2022-08/08/2022). To work with the IPUMS CDOH data, researchers will need to first merge the NCHAT data to DS1 (MATCH ID and State FIPS Data). This merged file can then be linked to the IPUMS CDOH datafile (DS2) using the STATEFIPS variable.

About this dataset

Context

The dataset tabulates the population of Wildwood by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Wildwood across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 56.53% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Wildwood is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Wildwood 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 Wildwood Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Longview by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Longview across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.95% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Longview is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Longview 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 Longview Population by Race & Ethnicity. You can refer the same here

In 2022, around 80 percent of transgender people in the United States had considered suicide, while around 40 percent had attempted suicide. There has been an upward trend in both the considered and attempted suicide rate since 2000, when 61 percent of transgender people considered committing suicide and 28 percent had attempted it.

Important notice

The Office for Statistics Regulation confirmed on 12/09/2024 that the gender identity estimates from Census 2021 are no longer accredited official statistics and are classified as official statistics in development.

For further information please see: Sexual orientation and gender identity quality information for Census 2021

These datasets provide Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales for gender identity by sex, gender identity by age and gender identity by sex and age.

Gender identity

Gender identity refers to a person's sense of their own gender, whether male, female or another category such as non-binary. This may or may not be the same as their sex registered at birth.

Non-binary

Someone who is non-binary does not identify with the binary categories of man and woman. In these results the category includes people who identified with the specific term "non-binary" or variants thereon. However, those who used other terms to describe an identity that was neither specifically man nor woman have been classed in "All other gender identities".

Sex

This is the sex recorded by the person completing the census. The options were "Female" and "Male".

Trans

An umbrella term used to refer to people whose gender identity is different from their sex registered at birth. This includes people who identify as a trans man, trans woman, non-binary or with another minority gender identity.

Trans man

A trans man is someone who was registered female at birth, but now identifies as a man.

Trans woman

A trans woman is someone who was registered male at birth, but now identifies as a woman.

Usual resident

A usual resident is anyone who on Census Day, 21 March 2021, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.

Notes:

• To ensure that individuals cannot be identified in the data, population counts have been rounded to the nearest five and counts under 10 have been suppressed.

• Percentages have been calculated using rounded data.

Selected socioeconomic characteristics of the transgender or non-binary population aged 15 and older, by age group. Marital status, presence of children under age 12 in the household, education, employment, personal income, Indigenous identity, the visible minority population, immigrant status, language(s) spoken most often at home, place of residence (population centre/rural), self-rated general health, and self-rated mental health. Estimates are obtained from combined cycles of the Canadian Community Health Survey, 2019 to 2021.

About this dataset

Context

The dataset tabulates the population of Howell by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Howell across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.01% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Howell is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Howell 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 Howell Population by Race & Ethnicity. You can refer the same here

Population and percent identify transgender or gender non-conforming by Service Planning Area (SPA) from California Health Interview Survey (CHIS), 2015-2021 and 2019-2021 pooled years.Symbolized on the Equity Explorer by % Adults Transgender or Gender Non-conforming, years 2015-2021 (field = tgi_adult_pct_2015_2021).

About this dataset

Context

The dataset tabulates the population of Norwich town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Norwich town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.11% of total population being male. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Norwich town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Norwich town 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 Norwich town Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Albany by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Albany across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.71% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Albany is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Albany 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 Albany Population by Race & Ethnicity. You can refer the same here

TB treatment outcomes for transgender women and male sex workers in Sindh, Pakistan.

About this dataset

Context

The dataset tabulates the population of East Liverpool by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of East Liverpool across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.85% of total population being male. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the East Liverpool is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of East Liverpool 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 East Liverpool Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Bronx borough by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Bronx borough across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 52.74% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Bronx borough is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Bronx borough 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 Bronx borough Population by Race & Ethnicity. You can refer the same here

Police-reported hate crime, by type of motivation (race or ethnicity, religion, sexual orientation, language, disability, sex, age), selected regions and Canada (selected police services), 2014 to 2023.

The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).The variables for part 1 of the dataset are:Census usually resident population countCensus night population countAge (5-year groups)Age (life cycle groups)Median ageBirthplace (NZ born/overseas born)Birthplace (broad geographic areas)Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’Māori descent indicatorLanguages spoken (total responses)Official language indicatorGenderCisgender and transgender status – census usually resident population count aged 15 years and overSex at birthRainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and overSexual identity for the census usually resident population count aged 15 years and overLegally registered relationship status for the census usually resident population count aged 15 years and overPartnership status in current relationship for the census usually resident population count aged 15 years and overNumber of children born for the sex at birth female census usually resident population count aged 15 years and overAverage number of children born for the sex at birth female census usually resident population count aged 15 years and overReligious affiliation (total responses)Cigarette smoking behaviour for the census usually resident population count aged 15 years and overDisability indicator for the census usually resident population count aged 5 years and overDifficulty communicating for the census usually resident population count aged 5 years and overDifficulty hearing for the census usually resident population count aged 5 years and overDifficulty remembering or concentrating for the census usually resident population count aged 5 years and overDifficulty seeing for the census usually resident population count aged 5 years and overDifficulty walking for the census usually resident population count aged 5 years and overDifficulty washing for the census usually resident population count aged 5 years and over.The variables for part 2 of the dataset are:Individual home ownership for the census usually resident population count aged 15 years and overUsual residence 1 year ago indicatorUsual residence 5 years ago indicatorYears at usual residenceAverage years at usual residenceYears since arrival in New Zealand for the overseas-born census usually resident population countAverage years since arrival in New Zealand for the overseas-born census usually resident population countStudy participationMain means of travel to education, by usual residence address for the census usually resident population who are studyingMain means of travel to education, by education address for the census usually resident population who are studyingHighest qualification for the census usually resident population count aged 15 years and overPost-school qualification in New Zealand indicator for the census usually resident population count aged 15 years and overHighest secondary school qualification for the census usually resident population count aged 15 years and overPost-school qualification level of attainment for the census usually resident population count aged 15 years and overSources of personal income (total responses) for the census usually resident population count aged 15 years and overTotal personal income for the census usually resident population count aged 15 years and overMedian ($) total personal income for the census usually resident population count aged 15 years and overWork and labour force status for the census usually resident population count aged 15 years and overJob search methods (total responses) for the unemployed census usually resident population count aged 15 years and overStatus in employment for the employed census usually resident population count aged 15 years and overUnpaid activities (total responses) for the census usually resident population count aged 15 years and overHours worked in employment per week for the employed census usually resident population count aged 15 years and overAverage hours worked in employment per week for the employed census usually resident population count aged 15 years and overIndustry, by usual residence address for the employed census usually resident population count aged 15 years and overIndustry, by workplace address for the employed census usually resident population count aged 15 years and overOccupation, by usual residence address for the employed census usually resident population count aged 15 years and overOccupation, by workplace address for the employed census usually resident population count aged 15 years and overMain means of travel to work, by usual residence address for the employed census usually resident population count aged 15 years and overMain means of travel to work, by workplace address for the employed census usually resident population count aged 15 years and overSector of ownership for the employed census usually resident population count aged 15 years and overIndividual unit data source.Download lookup file for part 1 from Stats NZ ArcGIS Online or Stats NZ geographic data service.Download lookup file for part 2 from Stats NZ ArcGIS Online or Stats NZ geographic data service.FootnotesTe Whata Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.Geographical boundaries Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018. Subnational census usually resident population The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. Population counts Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. Caution using time series Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data). Study participation time seriesIn the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.About the 2023 Census dataset For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings. Data quality The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.Concept descriptions and quality ratingsData quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.Disability indicatorThis data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.Using data for good Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.Confidentiality The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3)

About this dataset

Context

The dataset tabulates the population of San Antonio by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of San Antonio across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.45% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the San Antonio is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of San Antonio 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 San Antonio Population by Race & Ethnicity. You can refer the same here

Percentage of persons aged 15 years and over by frequency with which they feel lonely, by gender and other selected sociodemographic characteristics: age group; immigrant status; visible minority group; Indigenous identity; persons with a disability, difficulty or long-term condition; LGBTQ2+ people; highest certificate, diploma or degree; main activity; and urban and rural areas.

Quality assessment of qualitative studies with the QualSyst tool.