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.

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.

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.

The average for 2022 based on 196 countries was 18.19 births per 1000 people. The highest value was in the Central African Republic: 45.42 births per 1000 people and the lowest value was in Hong Kong: 4.4 births per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

United States Total Fertility Rate: Black data was reported at 1,581.000 % in 2023. This records a decrease from the previous number of 1,639.000 % for 2022. United States Total Fertility Rate: Black data is updated yearly, averaging 2,062.000 % from Dec 1985 (Median) to 2023, with 39 observations. The data reached an all-time high of 2,480.000 % in 1990 and a record low of 1,581.000 % in 2023. United States Total Fertility Rate: Black data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G013: Fertility Rate.

A flexible model to reconstruct education-specific fertility rates: Sub-saharan Africa case study

The fertility rates are consistent with the United Nation World Population Prospects (UN WPP) 2022 fertility rates.

The Bayesian model developed to reconstruct the fertility rates using Demographic and Health Surveys and the UN WPP is published in a working paper.

Abstract

The future world population growth and size will be largely determined by the pace of fertility decline in sub-Saharan Africa. Correct estimates of education-specific fertility rates are crucial for projecting the future population. Yet, consistent cross-country comparable estimates of education-specific fertility for sub-Saharan African countries are still lacking. We propose a flexible Bayesian hierarchical model to reconstruct education-specific fertility rates by using the patchy Demographic and Health Surveys (DHS) data and the United Nations’ (UN) reliable estimates of total fertility rates (TFR). Our model produces estimates that match the UN TFR to different extents (in other words, estimates of varying levels of consistency with the UN). We present three model specifications: consistent but not identical with the UN, fully-consistent (nearly identical) with the UN, and consistent with the DHS. Further, we provide a full time series of education-specific TFR estimates covering five-year periods between 1980 and 2014 for 36 sub-Saharan African countries. The results show that the DHS-consistent estimates are usually higher than the UN-fully-consistent ones. The differences between the three model estimates vary substantially in size across countries, yielding 1980-2014 fertility trends that differ from each other mostly in level only but in some cases also in direction.

Funding

The data set are part of the BayesEdu Project at Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna) funded from the “Innovation Fund Research, Science and Society” by the Austrian Academy of Sciences (ÖAW).

We provide education-specific total fertility rates (ESTFR) from three model specifications: (1) estimated TFR consistent but not identical with the TFR estimated by the UN (“Main model (UN-consistent)”; (2) estimated TFR fully consistent (nearly identical) with the TFR estimated by the UN ( “UN-fully -consistent”, and (3) estimated TFR consistent only with the TFR estimated by the DHS ( “DHS-consistent”).

For education- and age-specific fertility rates that are UN-fully consistent, please see https://doi.org/10.5281/zenodo.8182960

Variables

Country: Country names

Education: Four education levels, No Education, Primary Education, Secondary Education and Higher Education.

Year: Five-year periods between 1980 and 2015.

ESTFR: Median education-specific total fertility rate estimate

sd: Standard deviation

Upp50: 50% Upper Credible Interval

Lwr50: 50% Lower Credible Interval

Upp80: 80% Upper Credible Interval

Lwr80: 80% Lower Credible Interval

Model: Three model specifications as explained above and in the working paper. DHS-consistent, Main model (UN-consistent) and UN-fully consistent.

List of countries:

Angola, Benin, Burkina Faso, Burundi, Cote D'Ivoire, Cameroon, Central African Republic, Chad, Comoros, Congo, Democratic Republic of Congo, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Tanzania, Togo, Uganda, Zambia, Zimbabwe

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.

In 1925, the crude birth rate in South Africa was just under 49 births per thousand people, meaning that almost five percent of the population was born in that year. This figure would follow the country’s trends in fertility, remaining largely unchanged until the 1950s when, following the implementation of apartheid rule in the country in 1948, declines in fertility from the government's family planning programs would lead to the birth rate's rapid decline. Apart from a brief pause in the early-1980s, births rates would decline throughout the second half of the 20th century, falling to just under 24 births per thousand people by 2000. The crude birth rate would see a brief increase in the early 2000s, largely attributed to a diversion of healthcare funding away from contraceptives to funding for treatments for the HIV/AIDS epidemic in the country, but since then, birth rates have resumed their decline, and in 2020, it is estimated that South Africa had a birth rate just under 21 births for every thousand people.

Central African Republic CF: Fertility Rate: Total: Births per Woman data was reported at 6.012 Ratio in 2023. This records a decrease from the previous number of 6.023 Ratio for 2022. Central African Republic CF: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 6.011 Ratio from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 6.167 Ratio in 1981 and a record low of 5.784 Ratio in 2004. Central African Republic CF: Fertility Rate: Total: Births per Woman data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Health Statistics. Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.;(1) United Nations Population Division. World Population Prospects: 2024 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics.;Weighted average;Relevance to gender indicator: it can indicate the status of women within households and a woman’s decision about the number and spacing of children.

South Africa ZA: Birth Rate: Crude: per 1000 People data was reported at 20.981 Ratio in 2016. This records a decrease from the previous number of 21.297 Ratio for 2015. South Africa ZA: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 30.616 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 40.222 Ratio in 1960 and a record low of 20.981 Ratio in 2016. South Africa ZA: Birth Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

The Central African Republic: Fertility rate, births per woman: The latest value from 2023 is 6.01 births per woman, a decline from 6.02 births per woman in 2022. In comparison, the world average is 2.41 births per woman, based on data from 196 countries. Historically, the average for the Central African Republic from 1960 to 2023 is 6 births per woman. The minimum value, 5.78 births per woman, was reached in 2002 while the maximum of 6.17 births per woman was recorded in 1981.

Abstract

The Reversing the Stall in Fertility Decline in Western Kenya Project, also referred to as the Packard Western Kenya Project, is a community-based family planning initiative implemented in two large western Kenyan counties: Busia and Siaya. The project was funded by the David and Lucile Packard Foundation and builds on the lessons and achievements of a demonstration project phase, which ran from November 2009 to September 2012. The demonstration project covered Busia and Siaya districts (later counties) which, as of September 2012, had an estimated total population of 1.654 million (739,000 in Busia and 915,000 in Siaya). These counties had the highest fertility rates in the country at an average total fertility rate (TFR) of 5.5 against a national TFR of 4.6. Modern contraceptive use prevalence in the two areas stood at around 32%. The Reversing the Stall in Fertility Decline in Western Kenya Project is implemented by a consortium of partners with diverse strengths. The implementation model allows partners to oversee and implement aspects of the project in which they have expertise. The consortium is led by the African Population and Health Research Center (APHRC), which coordinates all project activities. Marie Stopes Kenya (MSK) and Family Health Options Kenya (FHOK) are responsible for service delivery in Busia and Siaya respectively. The Great Lakes University of Kisumu (GLUK) is responsible for the monitoring and evaluation of project activities. The team also works in close collaboration with the Ministry of Health (MoH) at the county government and national government levels; the Centre for the Study of Adolescence (CSA), which works with youth; the Forum for Women Educationalists (FAWE) Kenya, which works with school- going youth; and the Christian Health Association of Kenya (CHAK), which works with religious leaders and groups.

The expansion phase of this project began in October 2012, seeking to bring to scale activities that had been started in the demonstration phase (2009-2012). These activities included:

 i) Capacity-building through the training of service providers, peer educators, religious leaders, Community Health Volunteers (CHVs) and community members

 ii) Delivery of family planning (FP) services  at community facilities and through  outreach activities.

 iii) Generating demand for FP services through community sensitization meetings, e.g., barazas, women's and youth group meetings, distribution of information education communication (IEC) materials and use of social media

iv) Advocacy, policy engagement and influencing policy through advocacy meetings and distribution of advocacy materials

 v) Monitoring, documenting and disseminating the project's achievements, lessons and best practices.

Geographic coverage

The project was implemented in the following sub-counties in Busia County; Matayos, Nambale, Samia, Butula, Teso North & South. In Siaya County the following sub-counties were covered; Alego Usonga, Ugenya, Ugunja, Bondo & Rarieda

Analysis unit

Household individuals & facility family planning clients

Universe

Women 15-49 and Men 15-59

Sampling deviation

Not Applicable

Mode of data collection

Face-to-face [f2f]

Research instrument

These tools were utilized by the CHVs and service providers to record data on persons reached with FP services and information. They included household information form, client service statistics log and mobilization activity register. CHVs collected household information door-to-door while distributing pills & condoms and capturing the distribution data. Servive providers captured data on clients serviced at the health facilities. Tools used for data collection included satisfaction cards, which were available at the health facilities, and the reporting tool for the peer advocates for life skills (PALS), both in and out of school. These tools were printed in triplicate, with one copy for the health facility, one for the partners and one retained by the CHV/service provider. The MIS was then stationed at GLUK to capture data generated during the expansion phase.

Cleaning operations

The entry and analysis of monitoring data from the MIS was done on a monthly basis to determine progress in achieving the project indicators against defined targets. The MIS was then stationed at GLUK to capture data generated during the expansion phase. To ensure data quality control, training was conducted for all M&E staff, including data entry clerks, on the new system. The entry and analysis of monitoring data from the MIS was done on a monthly basis to determine progress in achieving the project indicators against defined targets. This data was summarized in simple reports and shared with partners on a monthly basis.

The copy of a Packard Western Kenya (PWK) project report sent to the health facility would be summarized and captured on the MoH FP register stationed at the facility level and channeled to the sub-county health records and information officer, and to the MoH system. The copy to partners would be sent for entry into the MIS stationed at GLUK and analyzed, and the statistics sent to partners to complete their reports, which were sent to APHRC and finally to the Packard Foundation

Response rate

Not Applicable

Sampling error estimates

Not Applicable

For most of the past two centuries, falling birth rates have been associated with societal progress. During the demographic transition, where pre-industrial societies modernize in terms of fertility and mortality, falling death rates, especially among infants and children, are the first major change. In response, as more children survive into adulthood, women have fewer children as the need to compensate for child mortality declines. This transition has happened at different times across the world and is an ongoing process, with early industrial countries being the first to transition, and Sub-Saharan African countries being the most recent to do so. Additionally, some Asian countries (particularly China through government policy) have gone through their demographic transitions at a much faster pace than those deemed more developed. Today, in countries such as Japan, Italy, and Germany, birth rates have fallen well below death rates; this is no longer considered a positive demographic trend, as it leads to natural population decline, and may create an over-aged population that could place a burden on healthcare systems.

Almost 80% of the 4 billion projected increase in world population by 2100 comes from 37 Mid-African Countries (MACs), caused mostly by slow declines in Total Fertility Rate (TFR). Historically, TFR has declined in response to increases in wellbeing associated with economic development. We show that, when Infant Survival Rate (ISR, a proxy for wellbeing) has increased, MAC fertility has declined at the same rate, in relation to ISR, as it did in 61 comparable Other Developing Countries (ODCs) whose average fertility is close to replacement level. If MAC ISR were to increase at the historic rate of these ODCs, and TFR declined correspondingly, then the projected world population in 2100 would be decreasing and 1.1 billion lower than currently projected. Such rates of ISR increase, and TFR decrease, are quite feasible and have occurred in comparable ODCs. Increased efforts to improve the wellbeing of poor MAC populations are key.

South Africa ZA: UCB Projection: Crude Birth Rate: per 1000 Persons data was reported at 13.500 NA in 2050. This records a decrease from the previous number of 13.600 NA for 2049. South Africa ZA: UCB Projection: Crude Birth Rate: per 1000 Persons data is updated yearly, averaging 20.050 NA from Jun 1985 (Median) to 2050, with 66 observations. The data reached an all-time high of 33.600 NA in 1985 and a record low of 13.500 NA in 2050. South Africa ZA: UCB Projection: Crude Birth Rate: per 1000 Persons data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s South Africa – Table ZA.US Census Bureau: Demographic Projection.

BackgroundDespite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In sub-Saharan Africa (SSA), the Millennium Development Goals (MDGs) for child mortality were met only by a few countries. Valid concerns exist as to whether the region would meet new Sustainable Development Goals (SDGs) for under-5 mortality. We therefore examine further sources of variation by assessing age patterns, trends, and forecasts of mortality rates.Methods and findingsData came from 106 nationally representative Demographic and Health Surveys (DHSs) with full birth histories from 31 SSA countries from 1990 to 2017 (a total of 524 country-years of data). We assessed the distribution of age at death through the following new demographic analyses. First, we used a direct method and full birth histories to estimate under-5 mortality rates (U5MRs) on a monthly basis. Second, we smoothed raw estimates of death rates by age and time by using a two-dimensional P-Spline approach. Third, a variant of the Lee–Carter (LC) model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) to adjust, validate, and minimize the risk of bias in survival, truncation, and recall in mortality estimation. Our mortality model revealed substantive declines of death rates at every age in most countries but with notable differences in the age patterns over time. U5MRs declined from 3.3% (annual rate of reduction [ARR] 0.1%) in Lesotho to 76.4% (ARR 5.2%) in Malawi, and the pace of decline was faster on average (ARR 3.2%) than that observed for infant (IMRs) (ARR 2.7%) and neonatal (NMRs) (ARR 2.0%) mortality rates. We predict that 5 countries (Kenya, Rwanda, Senegal, Tanzania, and Uganda) are on track to achieve the under-5 sustainable development target by 2030 (25 deaths per 1,000 live births), but only Rwanda and Tanzania would meet both the neonatal (12 deaths per 1,000 live births) and under-5 targets simultaneously. Our predicted NMRs and U5MRs were in line with those estimated by the UN IGME by 2030 and 2050 (they overlapped in 27/31 countries for NMRs and 22 for U5MRs) and by the Institute for Health Metrics and Evaluation (IHME) by 2030 (26/31 and 23/31, respectively). This study has a number of limitations, including poor data quality issues that reflected bias in the report of births and deaths, preventing reliable estimates and predictions from a few countries.ConclusionsTo our knowledge, this study is the first to combine full birth histories and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in SSA. We demonstrate that countries with a rapid pace of mortality reduction (ARR ≥ 3.2%) across ages would be more likely to achieve the SDG mortality targets. However, the lower pace of neonatal mortality reduction would prevent most countries from achieving those targets: 2 countries would reach them by 2030, 13 between 2030 and 2050, and 13 after 2050.

In 2023, the crude birth rate in live births per 1,000 inhabitants in South Africa was 18.78. Between 1960 and 2023, the figure dropped by 21.04, though the decline followed an uneven course rather than a steady trajectory.

Trends in adolescent fertility rates in Sierra Leone by different inequality dimensions, 2008–2019.

In 2023, there were five countries, where the average woman of childbearing age can expect to have over six 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 6.13 and 6.12 children per woman, Somalia and Chad were the countries 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.

Inequality measures of adolescent fertility rates in Sierra Leone, 2008–2019.