In 2025, there are six countries, all in Sub-Saharan Africa, where the average woman of childbearing age can expect to have between 5-6 children throughout their lifetime. In fact, of the 20 countries in the world with the highest fertility rates, Afghanistan and Yemen are the only countries not found in Sub-Saharan Africa. High fertility rates in Africa With a fertility rate of almost six children per woman, Chad is the country with the highest fertility rate in the world. Population growth in Chad is among the highest in the world. Lack of healthcare access, as well as food instability, political instability, and climate change, are all exacerbating conditions that keep Chad's infant mortality rates high, which is generally the driver behind high fertility rates. This situation is common across much of the continent, and, although there has been considerable progress in recent decades, development in Sub-Saharan Africa is not moving as quickly as it did in other regions. Demographic transition While these countries have the highest fertility rates in the world, their rates are all on a generally downward trajectory due to a phenomenon known as the demographic transition. The third stage (of five) of this transition sees birth rates drop in response to decreased infant and child mortality, as families no longer feel the need to compensate for lost children. Eventually, fertility rates fall below replacement level (approximately 2.1 children per woman), which eventually leads to natural population decline once life expectancy plateaus. In some of the most developed countries today, low fertility rates are creating severe econoic and societal challenges as workforces are shrinking while aging populations are placin a greater burden on both public and personal resources.

The statistic shows the 20 countries with the lowest fertility rates in 2024. All figures are estimates. In 2024, the fertility rate in Taiwan was estimated to be at 1.11 children per woman, making it the lowest fertility rate worldwide. Fertility rate The fertility rate is the average number of children born per woman of child-bearing age in a country. Usually, a woman aged between 15 and 45 is considered to be in her child-bearing years. The fertility rate of a country provides an insight into its economic state, as well as the level of health and education of its population. Developing countries usually have a higher fertility rate due to lack of access to birth control and contraception, and to women usually foregoing a higher education, or even any education at all, in favor of taking care of housework. Many families in poorer countries also need their children to help provide for the family by starting to work early and/or as caretakers for their parents in old age. In developed countries, fertility rates and birth rates are usually much lower, as birth control is easier to obtain and women often choose a career before becoming a mother. Additionally, if the number of women of child-bearing age declines, so does the fertility rate of a country. As can be seen above, countries like Hong Kong are a good example for women leaving the patriarchal structures and focusing on their own career instead of becoming a mother at a young age, causing a decline of the country’s fertility rate. A look at the fertility rate per woman worldwide by income group also shows that women with a low income tend to have more children than those with a high income. The United States are neither among the countries with the lowest, nor among those with the highest fertility rate, by the way. At 2.08 children per woman, the fertility rate in the US has been continuously slightly below the global average of about 2.4 children per woman over the last decade.

The total fertility rate of the world has dropped from around 5 children per woman in 1950, to 2.2 children per woman in 2025, which means that women today are having fewer than half the number of children that women did 75 years ago. Replacement level fertility This change has come as a result of the global demographic transition, and is influenced by factors such as the significant reduction in infant and child mortality, reduced number of child marriages, increased educational and vocational opportunities for women, and the increased efficacy and availability of contraception. While this change has become synonymous with societal progress, it does have wide-reaching demographic impact - if the global average falls below replacement level (roughly 2.1 children per woman), as is expected to happen in the 2050s, then this will lead to long-term population decline on a global scale. Regional variations When broken down by continent, Africa is the only region with a fertility rate above the global average, and, alongside Oceania, it is the only region with a fertility rate above replacement level. Until the 1980s, the average woman in Africa could expect to have 6-7 children over the course of their lifetime, and there are still several countries in Africa where women can still expect to have 5 or more children in 2025. Historically, Europe has had the lowest fertility rates in the world over the past century, falling below replacement level in 1975. Europe's population has grown through a combination of migration and increasing life expectancy, however even high immigration rates could not prevent its population from going into decline in 2021.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for San Jose, CA, is 24.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for San Jose, CA, is 20.5.
• Total dependency ratio for San Jose, CA is 45.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for San Jose, CA is 4.9.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Jose Population by Age. You can refer the same here

Historical chart and dataset showing Africa fertility rate by year from 1950 to 2025.

Somalia was the African country with the highest fertility rate in 2023. There, each woman had an average of around 6.1 children in her reproductive years. Fertility levels in Africa remain high despite a steady decline The fertility rate in Africa has gradually decreased since 2000 and is projected to decline further in the coming years. Factors including improved socio-economic conditions and educational opportunities, lower infant mortality, and decreasing poverty levels have driven the declining birth rate on the continent. Nevertheless, Africa remains the continent with the highest fertility rate worldwide. As of 2023, women in Africa had an average of 4.07 children in their reproductive years. Africa was the only continent registering a fertility rate higher than the global average, which was set at 2.4 children per woman. Worldwide, the continent also had the highest adolescent fertility rate as of 2022, with West and Central Africa leading with 105 births per 1,000 girls aged 15 to 19 years. Africa’s population keeps growing According to projections, over 46 million births will be registered in Africa in 2023. Contrary to the declining fertility rate, the absolute number of births on the continent will continue to grow in the coming years to reach around 49.4 million by 2030. In general, Africa’s population – amounting to over 1.48 billion inhabitants as of 2023 – is forecast to increase considerably and achieve 2.5 billion in 2050. Countries such as Niger, Angola, and Equatorial Guinea are key drivers of population growth in Africa, registering the highest average population growth rate on the continent between 2020 and 2025. For instance, in that period, Niger’s population was forecast to expand by 3.7 percent each year.

Historical chart and dataset showing Nigeria fertility rate by year from 1950 to 2025.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Indiana, is 30.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Indiana, is 25.5.
• Total dependency ratio for Indiana is 55.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Indiana is 3.9.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Indiana Population by Age. You can refer the same here

Niger had the highest birth rate in the world in 2024, with a birth rate of 46.6 births per 1,000 inhabitants. Angola, Benin, Mali, and Uganda followed. Except for Afghanistan, all 20 countries with the highest birth rates in the world were located in Sub-Saharan Africa. High infant mortality The reasons behind the high birth rates in many Sub-Saharan African countries are manyfold, but a major reason is that infant mortality remains high on the continent, despite decreasing steadily over the past decades, resulting in high birth rates to counter death rates. Moreover, many nations in Sub-Saharan Africa are highly reliant on small-scale farming, meaning that more hands are of importance. Additionally, polygamy is not uncommon in the region, and having many children is often seen as a symbol of status. Fastest-growing populations As the high fertility rates coincide with decreasing death rates, countries in Sub-Saharan Africa have the highest population growth rates in the world. As a result, Africa's population is forecast to increase from 1.4 billion in 2022 to over 3.9 billion by 2100.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Exeter, PA, is 27.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Exeter, PA, is 44.9.
• Total dependency ratio for Exeter, PA is 72.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Exeter, PA is 2.2.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Exeter Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for China, TX, is 25.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for China, TX, is 39.1.
• Total dependency ratio for China, TX is 64.6.
• Potential support ratio, which is the number of youth (working age population) per elderly, for China, TX is 2.6.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for China Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for San Francisco, CA, is 16.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for San Francisco, CA, is 24.1.
• Total dependency ratio for San Francisco, CA is 40.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for San Francisco, CA is 4.1.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Francisco Population by Age. You can refer the same here

Today, globally, women of childbearing age have an average of approximately 2.2 children over the course of their lifetime. In pre-industrial times, most women could expect to have somewhere between five and ten live births throughout their lifetime; however, the demographic transition then sees fertility rates fall significantly. Looking ahead, it is believed that the global fertility rate will fall below replacement level in the 2050s, which will eventually lead to population decline when life expectancy plateaus. Recent decades Between the 1950s and 1970s, the global fertility rate was roughly five children per woman - this was partly due to the post-WWII baby boom in many countries, on top of already-high rates in less-developed countries. The drop around 1960 can be attributed to China's "Great Leap Forward", where famine and disease in the world's most populous country saw the global fertility rate drop by roughly 0.5 children per woman. Between the 1970s and today, fertility rates fell consistently, although the rate of decline noticeably slowed as the baby boomer generation then began having their own children. Replacement level fertility Replacement level fertility, i.e. the number of children born per woman that a population needs for long-term stability, is approximately 2.1 children per woman. Populations may continue to grow naturally despite below-replacement level fertility, due to reduced mortality and increased life expectancy, however, these will plateau with time and then population decline will occur. It is believed that the global fertility rate will drop below replacement level in the mid-2050s, although improvements in healthcare and living standards will see population growth continue into the 2080s when the global population will then start falling.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Milton, NC, is 30.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Milton, NC, is 81.3.
• Total dependency ratio for Milton, NC is 112.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Milton, NC is 1.2.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Milton Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Ferris, TX, is 53.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Ferris, TX, is 18.4.
• Total dependency ratio for Ferris, TX is 72.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Ferris, TX is 5.4.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Ferris Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Atwater, CA, is 37.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Atwater, CA, is 20.0.
• Total dependency ratio for Atwater, CA is 57.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Atwater, CA is 5.0.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Atwater Population by Age. You can refer the same here

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. In the United States in 1800, the average woman of childbearing age would have seven children over the course of their lifetime. As factors such as technology, hygiene, medicine and education improved, women were having fewer children than before, reaching just two children per woman in 1940. This changed quite dramatically in the aftermath of the Second World War, rising sharply to over 3.5 children per woman in 1960 (children born between 1946 and 1964 are nowadays known as the 'Baby Boomer' generation, and they make up roughly twenty percent of todays US population). Due to the end of the baby boom and increased access to contraception, fertility reached it's lowest point in the US in 1980, where it was just 1.77. It did however rise to over two children per woman between 1995 and 2010, although it is expected to drop again by 2020, to just 1.78.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Houston, TX, is 28.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Houston, TX, is 17.7.
• Total dependency ratio for Houston, TX is 46.6.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Houston, TX is 5.7.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Houston Population by Age. You can refer the same here

In 2025, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth.

In 2024, the fertility rate in Africa was *** children per woman. The average number of newborn infants per woman on the continent decreased compared to 2000, when women had approximately **** children throughout their reproductive years. By 2030, fertility in Africa is projected to decline to around *** births per woman, yet it will remain high. The highest fertility rate worldwide Despite its gradually declining rate, fertility in Africa is the highest in the world. In 2023, the average fertility rate on the continent stood at **** children per woman, compared to a global average of **** births per woman. In contrast, Europe and North America were the continents with the lowest proportion of newborns, each registering a fertility rate below two children per woman. Additionally, Africa records the highest fertility rate among the young female population aged 15 to 19 years. In 2022, West and Central Africa had an adolescent fertility rate of nearly *** children per 1,000 girls, the highest value worldwide. Lower fertility in Northern Africa Fertility levels vary significantly across Africa. In 2023, Somalia, Chad, Niger, the Democratic Republic of Congo, and the Central African Republic were the countries with the highest fertility rates on the continent. In those countries, women had an average of over *** children in their reproductive years. The number of adolescent girls giving birth also differed within Africa. For instance, the adolescent fertility rate in North Africa stood at around **** children per 1,000 young women in 2023. On the other hand, Sub-Saharan Africa registered a higher rate of approximately **** children per 1,000 girls as of the same year. In general, higher poverty levels, inadequate social and health conditions, and increased infant mortality are some main drivers of higher fertility rates.