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.

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.

Graph and download economic data for Fertility Rate, Total for the United States (SPDYNTFRTINUSA) from 1960 to 2023 about fertility, rate, and USA.

Graph and download economic data for Crude Birth Rate for the United States (SPDYNCBRTINUSA) from 1960 to 2023 about birth, crude, rate, and USA.

The average for 2022 based on 195 countries was 18.38 births per 1000 people. The highest value was in Niger: 45.03 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 2022. Below is a chart for all countries where data are available.

Germany FSO Projection: Population: High Birth Rate Based Trend data was reported at 71,236.000 Person th in 2060. This records a decrease from the previous number of 71,533.000 Person th for 2059. Germany FSO Projection: Population: High Birth Rate Based Trend data is updated yearly, averaging 78,472.000 Person th from Dec 2014 (Median) to 2060, with 47 observations. The data reached an all-time high of 81,691.000 Person th in 2019 and a record low of 71,236.000 Person th in 2060. Germany FSO Projection: Population: High Birth Rate Based Trend data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.G003: Population: Projection: Federal Statistics Office Germany.

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.

Crude birth rates, age-specific fertility rates and total fertility rates (live births), 2000 to most recent year.

United States US: Fertility Rate: Total: Births per Woman data was reported at 1.800 Ratio in 2016. This records a decrease from the previous number of 1.843 Ratio for 2015. United States US: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 2.002 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 3.654 Ratio in 1960 and a record low of 1.738 Ratio in 1976. United States US: 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 USA – Table US.World Bank: 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: 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; 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.

The graph illustrates the number of babies born in the United States from 1995 to 2025. The x-axis represents the years, labeled from '95 to '25, while the y-axis shows the annual number of births. Over this 30-year period, birth numbers peaked at 4,316,233 in 2007 and reached a low of 3,596,017 in 2023. The data reveals relatively stable birth rates from 1995 to 2010, with slight fluctuations, followed by a gradual decline starting around 2017. The information is presented in a line graph format, effectively highlighting the long-term downward trend in U.S. birth numbers over the specified timeframe.

India: The number of crude births per 1000 people, per year: The latest value from 2022 is 16.27 births per 1000 people, a decline from 16.42 births per 1000 people in 2021. In comparison, the world average is 18.38 births per 1000 people, based on data from 195 countries. Historically, the average for India from 1960 to 2022 is 30.5 births per 1000 people. The minimum value, 16.27 births per 1000 people, was reached in 2022 while the maximum of 42.51 births per 1000 people was recorded in 1960.

In 2021, there were **** births per 1,000 people in Northern Ireland, compared with eleven in the previous year. Between 2000 and 2008, Northern Ireland's birth rate increased from **** to **** but started to decline gradually until 2012 when it dropped from **** to **** in just one year. During this provided time period, the birth rate in Northern Ireland was highest in 1971, when it was **** and was at its lowest in 2020 when there were just eleven births per 1,000 people. Falling birth rates in the UK For the United Kingdom as a whole, the birth rate fell to **** births per 1,000 people in 2020, before a slight uptick to **** in 2021. After a postwar peak of **** births per 1,000 people in 1964, the UK birth rate fell sharply to just **** by 1977. Between 1977 and 2012 the birth rate fluctuated between **** and ****, but declined in every year between 2012 and 2020. In 2021, the UK's fertility rate (the number of births per women) fell to just ****, compared with **** in 1964. Since 1973, the UK has fallen below the minimum replacement level fertility rate of ***, and without immigration would likely see its population decline in the long term. Global demographic trends The considerable decline in the UK's fertility rate in recent decades is not an isolated phenomenon. As of 2024, Africa was, at ****, the only continent to have a fertility rate higher than the global average of ****. Several countries, mainly in East Asia and Europe, have far lower fertility rates than the UK or the global average, however. South Korea provides the most dramatic example of this trend, with its fertility rate falling from **** in 1960 to just **** by 2020. By the *****, it is expected that, as Africa's fertility rate converges with the rest of the world, the global population will peak at around **** billion and start to decline.

Introduction: Though awareness of climate change rose globally with the release of former Vice President Al Gore’s movie and book An Inconvenient Truth in 2006, there has seemingly never been a connection drawn between Gore’s works and subsequent fertility trends in the United States, particularly along political lines. Objectives: The primary objective of this project is to determine whether the release of the movie and book An Inconvenient Truth in 2006 sparked an inflection point within a year or two in the United States for birth rates, and whether those rates differ between red and blue states. The secondary objective is to determine whether there was a drop in birth rates after that inflection point. Methods: This project used natality data – birth rates per state per year from 2003-2020 – from the Centers for Disease Control and Prevention, joined with state political party data from the 2020 Presidential election from Wisevoter. Data were cleaned using Excel and analyzed using Tableau visualizations. Results: The year 2007 was indeed an inflection point in the United States for birth rates, as both red and blue states recorded their highest birth rates at this point in the 2003-2020 span. The birth rate in red states was higher than that of blue states throughout the span but both rates had a positive correlation, running parallel throughout the span. Conclusions: The United States birth rate declined after 2007 in both red and blue states, but it is unclear whether the release of An Inconvenient Truth influenced this decline.

This data set contains estimated teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) by county and year.

DEFINITIONS

Estimated teen birth rate: Model-based estimates of teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) for a specific county and year. Estimated county teen birth rates were obtained using the methods described elsewhere (1,2,3,4). These annual county-level teen birth estimates “borrow strength” across counties and years to generate accurate estimates where data are sparse due to small population size (1,2,3,4). The inferential method uses information—including the estimated teen birth rates from neighboring counties across years and the associated explanatory variables—to provide a stable estimate of the county teen birth rate.
Median teen birth rate: The middle value of the estimated teen birth rates for the age group 15–19 for counties in a state.
Bayesian credible intervals: A range of values within which there is a 95% probability that the actual teen birth rate will fall, based on the observed teen births data and the model.

NOTES

Data on the number of live births for women aged 15–19 years were extracted from the National Center for Health Statistics’ (NCHS) National Vital Statistics System birth data files for 2003–2015 (5).

Population estimates were extracted from the files containing intercensal and postcensal bridged-race population estimates provided by NCHS. For each year, the July population estimates were used, with the exception of the year of the decennial census, 2010, for which the April estimates were used.

Hierarchical Bayesian space–time models were used to generate hierarchical Bayesian estimates of county teen birth rates for each year during 2003–2015 (1,2,3,4).

The Bayesian analogue of the frequentist confidence interval is defined as the Bayesian credible interval. A 100*(1-α)% Bayesian credible interval for an unknown parameter vector θ and observed data vector y is a subset C of parameter space Ф such that
1-α≤P({C│y})=∫p{θ │y}dθ,
where integration is performed over the set and is replaced by summation for discrete components of θ. The probability that θ lies in C given the observed data y is at least (1- α) (6).

County borders in Alaska changed, and new counties were formed and others were merged, during 2003–2015. These changes were reflected in the population files but not in the natality files. For this reason, two counties in Alaska were collapsed so that the birth and population counts were comparable. Additionally, Kalawao County, a remote island county in Hawaii, recorded no births, and census estimates indicated a denominator of 0 (i.e., no females between the ages of 15 and 19 years residing in the county from 2003 through 2015). For this reason, Kalawao County was removed from the analysis. Also , Bedford City, Virginia, was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. For consistency, Bedford City was merged with Bedford County, Virginia, for the entire 2003–2015 period. Final analysis was conducted on 3,137 counties for each year from 2003 through 2015. County boundaries are consistent with the vintage 2005–2007 bridged-race population file geographies (7).

SOURCES

National Center for Health Statistics. Vital statistics data available online, Natality all-county files. Hyattsville, MD. Published annually.

For details about file release and access policy, see NCHS data release and access policy for micro-data and compressed vital statistics files, available from: http://www.cdc.gov/nchs/nvss/dvs_data_release.htm.

For natality public-use files, see vital statistics data available online, available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

National Center for Health Statistics. U.S. Census populations with bridged race categories. Estimated population data available. Postcensal and intercensal files. Hyattsville, MD. Released annually.

For population files, see U.S. Census populations with bridged race categories, available from: https://www.cdc.gov/nchs/nvss/bridged_race.htm.

REFERENCES

1. Khan D, Rossen LM, Hamilton B, Dienes E, He Y, Wei R. Spatiotemporal trends in teen birth rates in the USA, 2003–2012. J R Stat Soc A 181(1):35–58. 2017. Available from: http://onlinelibrary.wiley.com/doi/10.1111/rssa.12266/abstract.

2. Khan D, Rossen LM, Hamilton BE, He Y, Wei R, Dienes E. Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012. Spat Spatiotemporal Epidemiol 21:67–75. 2017. Available from: http://www.sciencedirect.com/science/article/pii/S1877584516300442.

3. Rue H, Martino S, Lindgren F. INLA: Functions which allow to perform a full Bayesian analysis of structured additive models using Integrated Nested Laplace Approximation. R package, version 0.0. 2009.

4. Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J R Stat Soc B 71(2):319–92. 2009.

5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Mathews TJ. Births: Final data for 2015. National Vital Statistics Reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf (1.9 MB).

6. Carlin BP, Louis TA. Bayesian methods for data analysis. Boca Raton, FL: CRC Press, 2009.

7. National Center for Health Statistics. County geography changes: 1990–2012. Available from: http://www.cdc.gov/nchs/data/nvss/bridged_race/County_Geography_Changes.pdf (39 KB).

In 2023, the average total fertility rate in Taiwan ranged at around **** children per woman over lifetime. This extremely low figure is not expected to increase over the coming years. Taiwan’s demographic development Taiwan was once known for its strong population growth. After the retreat of the Republican government to the island in 1949, the population grew quickly. However, during Taiwan’s rapid economic development thereafter, the fertility rate dropped substantially. This drastic change occurred in most East Asian countries as well, of which many have some of the lowest fertility rates in the world today. As a result, populations in many East Asian regions are already shrinking or are expected to do so soon.In Taiwan, population decreased in 2020 for the first time, and the declining trend is expected to accelerate in the years ahead. At the same time, life expectancy has increased considerably, and Taiwan’s population is now aging at fast pace, posing a huge challenge to the island’s social security net. Addressing challenges of an aging society Most east Asian countries could, until recently, afford generous public pensions and health care systems, but now need to adjust to their changing reality. Besides providing incentives to raise children, the Taiwanese government also tries to attract more immigrants by lowering requirements for permanent residency. As both strategies have been met with limited success, the focus remains on reforming the pension system. This is being done mainly by raising the retirement age, promoting late-age employment, increasing pension contributions, and lowering pension payments.

This is the code replication archive for the paper, "The COVID-19 Baby Bump in the United States," published in the Proceedings of the National Academy of Sciences. The underlying natality microdata are restricted, so this archive contains only the code to replicate our analysis.We use natality microdata covering the universe of U.S. births for 2015-2021 and California births from 2015 through February 2023 to examine childbearing responses to the COVID-19 pandemic. We find that 60% of the 2020 decline in U.S. fertility rates was driven by sharp reductions in births to foreign-born mothers although births to this group comprised only 22% of all U.S. births in 2019. This decline started in January 2020. In contrast, the COVID-19 recession resulted in an overall “baby bump” among U.S.-born mothers which marked the first reversal in declining fertility rates since the Great Recession. Births to U.S.-born mothers fell by 31,000 in 2020 relative to a pre-pandemic trend but increased by 71,000 in 2021. The data for California suggest that U.S. births remained elevated through February 2023. The baby bump was most pronounced for first births and women under age 25, suggesting that the pandemic led some women to start families earlier. Above age 25, the baby bump was most pronounced for women ages 30-34 and women with a college education. The 2021-2022 baby bump is especially remarkable given the large declines in fertility rates that would have been projected by standard statistical models.

The birth rate, also known as the crude birth rate, is a key demographic indicator that measures the number of live births occurring in a population per 1,000 people annually. This vital statistic provides insight into population growth and is often used by policymakers, researchers, and governments to understand trends in fertility, family planning, and societal development. A high birth rate generally indicates a growing population, while a low birth rate may suggest declining growth or aging demographics. Factors influencing birth rates include cultural, economic, social, and environmental conditions. Countries with advanced healthcare systems and access to education often see lower birth rates, as families may opt for fewer children. In contrast, regions with limited access to family planning and healthcare may experience higher birth rates. Understanding the birth rate is crucial for managing resources, planning social services, and predicting future population changes on both national and global scales.

Turkey fertility rate for 2025 is 1.97, a 0.71% decline from 2024.

<ul style='margin-top:20px;'>

<li>Turkey fertility rate for 2024 was <strong>1.98</strong>, a <strong>31.13% increase</strong> from 2023.</li>
<li>Turkey fertility rate for 2023 was <strong>1.51</strong>, a <strong>7.36% decline</strong> from 2022.</li>
<li>Turkey fertility rate for 2022 was <strong>1.63</strong>, a <strong>4.68% decline</strong> from 2021.</li>
</ul>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.

This dataset presents the estimated percentage of babies born alive before 37 weeks of pregnancy are completed, by country. Preterm birth is a leading cause of neonatal morbidity and mortality. Understanding national rates supports efforts to improve antenatal care, timely interventions, and newborn outcomes. These estimates are adapted from Liang et al. (2024), based on the Global Burden of Disease Study 2021, and provide a globally comparable measure of preterm birth burden.Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

Market Overview: The global baby care products market is poised to reach $215.6 billion by 2033, exhibiting a CAGR of 6.2% from 2025 to 2033. The increasing birth rate, rising disposable income, and growing awareness of infant health and well-being drive market growth. Innovations in product formulations, such as organic and eco-friendly ingredients, and the expansion of online sales channels are emerging trends. However, factors like the declining fertility rate in developed economies and the high cost of premium products pose challenges to the market. Segmentation and Regional Analysis: The baby care products market is segmented based on application (diapers and wipes, toiletries, feeding equipment, and others) and type (organic, non-organic). Key players in the industry include Artsana, Beiersdorf, Johnson & Johnson, and Pigeon. Regionally, Asia-Pacific dominates the market, followed by North America and Europe. The rising birth rate and growing middle class in developing economies provide significant growth opportunities in these regions. Emerging markets in South America, the Middle East & Africa, and Southeast Asia are also expected to offer substantial revenue streams in the coming years.