Over the past 23 years, there were constantly more men than women living on the planet. Of the 8.06 billion people living on the Earth in 2023, 4.05 billion were men and 4.01 billion were women. One-quarter of the world's total population in 2024 was below 15 years.

Alaska had the highest male to female ratio in the United States in 2020, with 109.2 men for every 100 women. The male to female ration was lowest in the District of Columbia, with 90.3 men for every 100 women.

The final frontier

Alaska, which was purchased from the Russian Empire in 1867, is the largest state in the U.S. and one of the newest states, having been admitted to the U.S. in 1959. Although oil production dominates the economy, Alaska has a very high poverty rate and consistently has the highest unemployment rate in the country.

It’s a man’s world

Alaska is one of 10 states in the U.S. that has more men than women. The male to female ratio in the United States as a whole is about even, but as the population ages, there tend to be more females than males. Even though the sex ratio in the U.S. is almost one to one, a little more than 56 percent all females participated in the labor force in 2021, compared with 67.6 percent of men.

Worldwide, the male population is slightly higher than the female population, although this varies by country. As of 2023, Hong Kong has the highest share of women worldwide with almost 55 percent. Moldova followed behind with 54 percent. Among the countries with the largest share of women in the total population, several were former Soviet-states or were located in Eastern Europe. By contrast, Qatar, the United Arab Emirates, and Oman had some of the highest proportions of men in their populations.

About this dataset

Context

The dataset tabulates the population of Ottawa County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Ottawa County. The dataset can be utilized to understand the population distribution of Ottawa County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Ottawa County. 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 Ottawa County.

Key observations

Largest age group (population): Male # 20-24 years (13,905) | Female # 20-24 years (13,489). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Ottawa County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Ottawa County is shown in the following column.
• Population (Female): The female population in the Ottawa County 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 Ottawa County 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 Ottawa County Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of San Diego by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for San Diego. The dataset can be utilized to understand the population distribution of San Diego by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in San Diego. 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 San Diego.

Key observations

Largest age group (population): Male # 25-29 years (68,680) | Female # 25-29 years (62,701). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 San Diego population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the San Diego is shown in the following column.
• Population (Female): The female population in the San Diego 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 San Diego 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 San Diego Population by Gender. You can refer the same here

There are more women than men in Germany, although the number of men has been slowly increasing in recent years, especially since 2015. In 2023, there were around 41.8 million males and 42.9 million females in Germany. Births and deaths Globally, the death rate had been slowly decreasing until 2019 but there was a sharp spike in 2020 and 2021, which can be attributed to the COVID-19 pandemic. The general decline, however, is probably due to medical advancements which mean that many diseases are now treatable or curable, that were not 50 years ago. The birth rate has also been decreasing across the world, but it is lowest in Europe and North America. Future challenges There are a number of challenges facing the German population in the future. Some of the most pressing ones are the growing urban population and especially its ageing structure in combination with slow birth rates, which will put increased pressure on the pension system. Because of this trend, old age security and pensions are already today in the top ten most pressing political issues in Germany.

About this dataset

Context

The dataset tabulates the population of Florida City by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Florida City. The dataset can be utilized to understand the population distribution of Florida City by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Florida City. 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 Florida City.

Key observations

Largest age group (population): Male # 10-14 years (540) | Female # 15-19 years (800). 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 Florida City population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Florida City is shown in the following column.
• Population (Female): The female population in the Florida City 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 Florida City 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 Florida City Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Palm Beach County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Palm Beach County. The dataset can be utilized to understand the population distribution of Palm Beach County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Palm Beach County. 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 Palm Beach County.

Key observations

Largest age group (population): Male # 55-59 years (50,401) | Female # 60-64 years (53,567). 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 Palm Beach County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Palm Beach County is shown in the following column.
• Population (Female): The female population in the Palm Beach County 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 Palm Beach County 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 Palm Beach County Population by Gender. You can refer the same here

In 1950, when Estonia's population was estimated at 1.1 million people, approximately 57 percent of the population was female, while 43 percent was male; this equated to a difference of more than 160,000 people. In the past century, as with many former-Soviet states, Estonia has consistently had one of the most disproportionate gender ratios in the world. The reason for this was due to the large number of men who were killed in wars during the first half of the twentieth century, which was particularly high across the Soviet Union, as well as a much higher life expectancy among women. The difference in the number of men and women in Estonia has gradually decreased over the past seven decades, but in 2020, there are still 70,000 more females than males, in a population of 1.3 million people; this equates to total shares of roughly 53 percent and 47 percent of the total population respectively.

About this dataset

Context

The dataset tabulates the population of Ontario town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Ontario town. The dataset can be utilized to understand the population distribution of Ontario town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Ontario town. 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 Ontario town.

Key observations

Largest age group (population): Male # 60-64 years (502) | Female # 60-64 years (527). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Ontario town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Ontario town is shown in the following column.
• Population (Female): The female population in the Ontario town 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 Ontario town 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 Ontario town Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Moriarty by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Moriarty. The dataset can be utilized to understand the population distribution of Moriarty by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Moriarty. 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 Moriarty.

Key observations

Largest age group (population): Male # 5-9 years (143) | Female # 30-34 years (113). 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 Moriarty population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Moriarty is shown in the following column.
• Population (Female): The female population in the Moriarty 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 Moriarty 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 Moriarty Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Chattanooga by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Chattanooga. The dataset can be utilized to understand the population distribution of Chattanooga by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Chattanooga. 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 Chattanooga.

Key observations

Largest age group (population): Male # 30-34 years (8,099) | Female # 25-29 years (7,767). 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 Chattanooga population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Chattanooga is shown in the following column.
• Population (Female): The female population in the Chattanooga 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 Chattanooga 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 Chattanooga Population by Gender. You can refer the same here

Since 1990, the employment rate of women in the United States has stayed more or less steady, reaching a peak of 57.5 percent in 2000. In 1990, the female employment rate was 54.3 percent, and in 2023, the employment rate was 55.4. Women in the workforce

There have historically been less women then men in the workforce. Additionally, women face many hurdles to equal treatment when they are employed, such as wage discrepancies, sexual harassment, and being expected to carryout the majority of household and family related tasks even while working full-time.

Women have historically been the primary caregivers and homemakers through many cultures worldwide. Despite this, the number of women joining the workforce has increased globally. Women in history faced the additional barrier of not being able to attend university, which barred them from gaining an education and access to professional job. However, as our cultures have modernized, women have been granted equal access to university in many societies. In 2014 in the United States, the number of university degrees awarded to women exceeded that of men for the first time. In 2021, 39.1 percent of women had completed at least four years of university compared to 36.6 percent of men. Despite this, the unemployment rate of women in the United States has fluctuated significantly since 1990. In 2021, Nebraska was the state with the highest percentage of women participating in the civilian labor force, second to the District of Columbia.

The wage gap

Today, the wage gap is still a problem for women, although improvements have been made. There is no state in the U.S. where women earn more than men, but women in Vermont had the smallest wage gap to men in 2021. Additionally, there are no occupations in which women out-earn men, even in occupations that traditionally employ more women. A more detailed look at wage inequality in the United States can be found here.

About this dataset

Context

The dataset tabulates the population of New Mexico by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for New Mexico. The dataset can be utilized to understand the population distribution of New Mexico by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in New Mexico. 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 New Mexico.

Key observations

Largest age group (population): Male # 15-19 years (73,240) | Female # 60-64 years (73,240). 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 New Mexico population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the New Mexico is shown in the following column.
• Population (Female): The female population in the New Mexico 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 New Mexico 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 New Mexico Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Clifton by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Clifton. The dataset can be utilized to understand the population distribution of Clifton by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Clifton. 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 Clifton.

Key observations

Largest age group (population): Male # 40-44 years (351) | Female # 10-14 years (78). 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 Clifton population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Clifton is shown in the following column.
• Population (Female): The female population in the Clifton 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 Clifton 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 Clifton Population by Gender. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in China. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In China, the median income for all workers aged 15 years and older, regardless of work hours, was $58,750 for males and $30,313 for females.

These income figures highlight a substantial gender-based income gap in China. Women, regardless of work hours, earn 52 cents for each dollar earned by men. This significant gender pay gap, approximately 48%, underscores concerning gender-based income inequality in the city of China.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.12 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 China median household income by race. You can refer the same here

In 2023, the total population of Colombia amounted to over 52 million. The number of women who lived in Colombia exceeded the number of men in approximately 747,000. Population figures in this South American country show a maintained upward trend at least since 2008.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Delhi. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Delhi, the median income for all workers aged 15 years and older, regardless of work hours, was $36,124 for males and $20,750 for females.

These income figures highlight a substantial gender-based income gap in Delhi. Women, regardless of work hours, earn 57 cents for each dollar earned by men. This significant gender pay gap, approximately 43%, underscores concerning gender-based income inequality in the town of Delhi.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.05 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Delhi median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Cambridge. The dataset can be utilized to gain insights into gender-based income distribution within the Cambridge population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Cambridge, among individuals aged 15 years and older with income, there were 47,329 men and 48,100 women in the workforce. Among them, 27,053 men were engaged in full-time, year-round employment, while 22,665 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 2.59% fell within the income range of under $24,999, while 4.05% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 54.26% of men in full-time roles earned incomes exceeding $100,000, while 42% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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 Cambridge median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Canton by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Canton. The dataset can be utilized to understand the population distribution of Canton by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Canton. 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 Canton.

Key observations

Largest age group (population): Male # 5-9 years (2,612) | Female # 25-29 years (2,750). 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 Canton population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Canton is shown in the following column.
• Population (Female): The female population in the Canton 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 Canton 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 Canton Population by Gender. You can refer the same here