This paper documents a set of facts about the dramatic decline in birth rates in the United States between 2007 and 2020 and explores possible explanations for it. The overall reduction in the birth rate reflects both very large declines within certain groups of women, including teens and Hispanic women – and smaller declines among demographic groups that comprise a large population share, including college-educated white women. We explore potential economic, policy, and social factors that might be responsible for the overall decline. We conclude from our empirical examination of possible factors that there is not a readily identifiable economic or policy factor or set of factors this is likely responsible for a substantial share of the decline. Instead, the patterns observed suggest that widespread, hard to quantify changes in preferences for having children, aspirations for life, and the nature of parenting are more likely behind the recent decline in US births. We conclude with a brief discussion about the societal consequences for a declining birth rate and what the United States might do about it.

Over the past 30 years, the birth rate in the United States has been steadily declining, and in 2023, there were 10.7 births per 1,000 of the population. In 1990, this figure stood at 16.7 births per 1,000 of the population. Demographics have an impact The average birth rate in the U.S. may be falling, but when broken down along ethnic and economic lines, a different picture is painted: Native Hawaiian and other Pacific Islander women saw the highest birth rate in 2022 among all ethnicities, and Asian women and white women both saw the lowest birth rate. Additionally, the higher the family income, the lower the birth rate; families making between 15,000 and 24,999 U.S. dollars annually had the highest birth rate of any income bracket in the States. Life expectancy at birth In addition to the declining birth rate in the U.S., the total life expectancy at birth has also reached its lowest value recently. Studies have shown that the life expectancy of both men and women in the United States has been declining over the last few years. Declines in life expectancy, like declines in birth rates, may indicate that there are social and economic factors negatively influencing the overall population health and well-being of the country.

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.

Over the past 30 years, the birth rate in the United States has been steadily declining, and in 2022, there were 11 births per 1,000 of the population. In 1990, this figure stood at 16.7 births per 1,000 of the population. Demographics have an impact The average birth rate in the U.S. may be falling, but when broken down along ethnic and economic lines, a different picture is painted: Native Hawaiian and other Pacific Islander women saw the highest birth rate in 2022 among all ethnicities, and Asian women and white women both saw the lowest birth rate. Additionally, the higher the family income, the lower the birth rate; families making between 15,000 and 24,999 U.S. dollars annually had the highest birth rate of any income bracket in the States. Life expectancy at birth In addition to the declining birth rate in the U.S., the total life expectancy at birth has also reached its lowest value in recent years. Studies have shown that the life expectancy of both men and women in the United States has declined as of 2021. Declines in life expectancy, like declines in birth rates, may indicate that there are social and economic factors negatively influencing the overall population health and well-being of the country.

In 2024, the average number of children born per 1,000 people in China ranged at ****. The birth rate has dropped considerably since 2016, and the number of births fell below the number of deaths in 2022 for the first time in decades, leading to a negative population growth rate. Recent development of the birth rate Similar to most East-Asian countries and territories, demographics in China today are characterized by a very low fertility rate. As low fertility in the long-term limits economic growth and leads to heavy strains on the pension and health systems, the Chinese government decided to support childbirth by gradually relaxing strict birth control measures, that had been in place for three decades. However, the effect of this policy change was considerably smaller than expected. The birth rate increased from **** births per 1,000 inhabitants in 2010 to ***** births in 2012 and remained on a higher level for a couple of years, but then dropped again to a new low in 2018. This illustrates that other factors constrain the number of births today. These factors are most probably similar to those experienced in other developed countries as well: women preferring career opportunities over maternity, high costs for bringing up children, and changed social norms, to name only the most important ones. Future demographic prospects Between 2020 and 2023, the birth rate in China dropped to formerly unknown lows, most probably influenced by the coronavirus pandemic. As all COVID-19 restrictions were lifted by the end of 2022, births figures showed a catch-up effect in 2024. However, the scope of the rebound might be limited. A population breakdown by five-year age groups indicates that the drop in the number of births is also related to a shrinking number of people with child-bearing age. The age groups between 15 and 29 years today are considerably smaller than those between 30 and 44, leaving less space for the birth rate to increase. This effect is exacerbated by a considerable gender gap within younger age groups in China, with the number of females being much lower than that of males.

Economic growth and modernization of society are generally associated with fertility rate decreases but which forces trigger this is unclear. In this paper we assess how fertility changes with increased labor market participation of women in rural Senegal. Evidence from high-income countries suggests that higher female employment rates lead to reduced fertility rates but evidence from developing countries at an early stage of demographic transition is largely absent. We concentrate on a rural area in northern Senegal where a recent boom in horticultural exports has been associated with a sudden increase in female off-farm employment. Using survey data we show that employed women have a significantly higher age at marriage and at first childbirth, and significantly fewer children. As causal identification strategy we use instrumental variable and difference-in-differences estimations, combined with propensity score matching. We find that female employment reduces the number of children per woman by 25%, and that this fertility-reducing effect is as large for poor as for non-poor women and larger for illiterate than for literate women. Results imply that female employment is a strong instrument for empowering rural women, reducing fertility rates and accelerating the demographic transition in poor countries. The effectiveness of family planning programs can increase if targeted to areas where female employment is increasing or to female employees directly because of a higher likelihood to reach women with low-fertility preferences. Our results show that changes in fertility preferences not necessarily result from a cultural evolution but can also be driven by sudden and individual changes in economic opportunities.

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.

The outbreak of the COVID-19 in early 2020 and the recurring epidemic in later years have disturbed China’s economy. Moreover, China’s demographic dividend has been disappearing due to its fastest aging population and declining birth rate. The birth rates in eastern provinces of China are much lower than those of the western provinces. Considering the impacts of the COVID-19 and aging population, this paper focused on the relationship between birth rate and the disposable income and tried to find effective measures to raise China’s birth rate. We discovered through regression analysis that the link between per capita disposable income and birth rate is initially "reverse J" and later "inverted J", indicating that per capita disposable income will influence the birth rate. Women’s employment rate and educational level are negatively correlated with the birth rate. To raise the fertility rate in China, it is necessary to increase the marriage rate and the willingness to have children by raising the per capita disposable income and introducing effective tax relief policies.

The fertility rates have fallen in all five Nordic countries over the last years. However, in 2021, the birth rates increased again in all five Nordics countries, besides in Sweden, where the fertility rate stayed the same. This can be explained by the higher number of babies born during the COVID-19 pandemic. In 2022, Iceland had the highest fertility rate of the Nordic countries, with *** children born per woman in reproductive age. The global trend of decreasing fertility The Nordics are not the only region with decreasing fertility rates. Globally, fertility rates have been on a steady decline since 2000. While lower-income countries have had more significant declines, they still have more children born per woman than higher-income countries. In 2000, almost * children were born per woman in low-income countries, decreasing to **** in 2021. By comparison, nearly **** children were born per woman in high-income countries, falling slightly to **** by 2021. Overall, in 2023, Niger, Angola, and the Democratic Republic of Congo had the highest fertility rates, while Taiwan, South Korea, and Singapore had the lowest fertility rates. Impacts of low fertility Greater access to education, challenges between work-life balance, and the costs of raising children can all be linked to falling fertility rates. However, this decline is not without consequences, and many countries are facing social and economic challenges because of aging and shrinking populations. For example, in Japan, where nearly ** percent of the country is aged 65 or older, an increasing proportion of the government expenditure is going towards social security benefits. Moreover, the very low unemployment rate in Japan can partially be attributed to having a shrinking labor force and fewer people to support the economy.

From March on, the number of births in Italy experienced a decrease. The coronavirus pandemic might have had an impact of the country's birth rate as well. In particular, during the second wave of infections registered between October and December 2020, the number of births dropped by 7.7 percent compared to the same period of 2019. However, Italy's birth rate has been decreasing constantly in the last decades.

The continuous decline in the birth rate can lead to a series of social and economic problems. Accurately predicting the birth rate of a region will help national and local governments to formulate more scientifically sound development policies. This paper proposes a discrete-aware model BRP-Net based on attention mechanism and LSTM, for effectively predicting the birth rate of prefecture-level cities. BRP-Net is trained using multiple variables related to comprehensive development of prefecture-level cities, covering factors such as economy, education and population structure that can influence the birth rate. Additionally, the comprehensive data of China’s prefecture-level cities exhibits strong spatiotemporal specificity. Our model leverages the advantages of attention mechanism to identify the feature correlation and temporal relationships of these multi-variable time series input data. Extensive experimental results demonstrate that the proposed BRP-Net has higher accuracy and better generalization performance compared to other mainstream methods, while being able to adapt to the spatiotemporal specificity of variables between prefecture-level cities. Using BRP-Net to achieve precise and robust prediction estimates of the birth rate in prefecture-level cities can provide more effective decision-making references for local governments to formulate more accurate and reasonable fertility encouragement policies.

The low birth-weight rate measures the percentage of live births with weights below 2500 grams. A low birth-weight can affect health outcomes later in life, and is an illustrative indicator for the overall health of the measured population.

The low birth-weight rate in Champaign County has been above 8 percent since 2011, the earliest Reporting Year available in the dataset. This is close to the statewide rate, which returned to 8.4 percent from Reporting Year 2021 through present after a slight decrease in recent years. The lowest county low birth-weight rate in the state is 5.6 percent (Carroll County in the northwest corner of the state), while the highest county low birth-weight rate in the state is 11.9 percent (Pulaski County in southernmost Illinois).

This data was sourced from the University of Wisconsin's Population Health Institute's and the Robert Wood Johnson Foundation’s County Health Rankings & Roadmaps. Each year’s County Health Rankings uses data from years prior. Therefore, the 2023 County Health Rankings (“Reporting Year” in the table) uses data from 2014-2020 (“Data Years” in the table).

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2023.

About this dataset

Context

The dataset tabulates the data for the Impact, TX population pyramid, which represents the Impact 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 Impact, TX, is 0.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Impact, TX, is 41.7.
• Total dependency ratio for Impact, TX is 41.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Impact, TX is 2.4.

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 Impact population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Impact for the selected age group is shown in the following column.
• Population (Female): The female population in the Impact for the selected age group is shown in the following column.
• Total Population: The total population of the Impact 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 Impact Population by Age. You can refer the same here

BackgroundThe birth rate is an important indicator of the health of the population. However, persistently low birth rate has become a pressing demographic challenge for many countries, including China. This has significant implications for sustainable population planning.MethodsThis study applied hot spot analysis and the spatiotemporal geographically weighted regression (GTWR) modeling, used panel data of 286 cities in China from 2012 to 2021 to explore the spatiotemporal heterogeneity of the relationship between the socioeconomic development and birth rate.ResultsThe research has found that 2017 was an important turning point in China’s demographic transition. The hot spot analysis reveals that the birth rate hot spots are characterized by a multipolar kernel distribution, shifting from spatial diffusion to convergence, with the cold spots mainly located in the northeast. And the GTWR modeling found that the relationship between socioeconomic development and birth rate varies and change dynamically over space and time. Key findings include: (1) the negative impact of GDP per capita on birth rates has intensified; (2) housing prices exhibit both wealth and crowding-out effects on birth rates, and there are obvious regional differences between the north and the south; (3) fiscal education expenditure on birth rates has the most pronounced income effect in the eastern region.ConclusionThis study adopts spatiotemporal perspective to reveal the spatiotemporal heterogeneity of the association between socioeconomic development and birth rate. It provides new evidence on the influence of macro factors on fertility in China. And emphasizes the importance of incorporating regional variations into population policy design.

Babies with Low Birth Weight - This indicator shows the percentage of live births that are a low birth weight (2500 grams or less). Babies born with a low birth weight are at increased risk for serious health consequences including disabilities and death. Low birth weight babies weigh less than 2,500 grams (5.5 pounds). Maryland’s low birth weight percentage is higher than the national average. Link to Data Details

We analyze the impact of birth seasonality (seasonal oscillations in the birth rate) on the dynamics of acute, immunizing childhood infectious diseases. Previous research has explored the effect of human birth seasonality on infectious disease dynamics using parameters appropriate for the developed world. We build on this work by including in our analysis an extended range of baseline birth rates and amplitudes, which correspond to developing world settings. Additionally, our analysis accounts for seasonal forcing both in births and contact rates. We focus in particular on the dynamics of measles. In the absence of seasonal transmission rates or stochastic forcing, for typical measles epidemiological parameters, birth seasonality induces either annual or biennial epidemics. Changes in the magnitude of the birth fluctuations (birth amplitude) can induce significant changes in the size of the epidemic peaks, but have little impact on timing of disease epidemics within the year. In contrast, changes to the birth seasonality phase (location of the peak in birth amplitude within the year) significantly influence the timing of the epidemics. In the presence of seasonality in contact rates, at relatively low birth rates (20 per 1000), birth amplitude has little impact on the dynamics but does have an impact on the magnitude and timing of the epidemics. However, as the mean birth rate increases, both birth amplitude and phase play an important role in driving the dynamics of the epidemic. There are stronger effects at higher birth rates.

Many developed countries have recently experienced sharp increases in home birth rates. This paper investigates the impact of home births on the health of low-risk newborns using data from the Netherlands, the only developed country where home births are widespread. To account for endogeneity in location of birth, we exploit the exogenous variation in distance from a mother's residence to the closest hospital. We find that giving birth in a hospital leads to substantial reductions in newborn mortality. We provide suggestive evidence that proximity to medical technologies may be an important channel contributing to these health gains. (JEL I11, I12, J13, J16)

BackgroundNon-pharmaceutical interventions (NPIs), such as social distancing and hand washing, have been associated with a decline in the preterm birth rate worldwide. We aimed to evaluate whether the preterm birth rate in Korea during the coronavirus disease 2019 lockdown has changed compared to that in previous years.MethodA birth registry from the Korea Statistical Information Service, which is a nationwide official database, was used to include all births claimed to have occurred between 2011 and 2020. Newborns with gestational age (GA) less than 22 weeks and birth weight less than 220 g were excluded. The pre-NPI period was designated as January 2011 to January 2020, and the NPI period was defined as February 2020 to December 2020. We assessed the effect of NPI on the incidence of prematurity per 100 births using an interrupted time-series quasi-experimental design and implementing an autoregressive integrated moving average (ARIMA) model.ResultsFrom 2011 to 2020, a total of 3,931,974 live births were registered, among which 11,416 were excluded. Consequently, the final study population included 3,920,558 live births (both singleton and multiple births) among which 275,009 (7.0%) were preterm. The preterm birth rate was significantly higher during the NPI period (8.68%) compared to that in the pre-NPI period (6.92%) (P 

Since 2000, Russia has consistently had the lowest population growth rate of the BRICS countries, and it even experienced a population decline throughout most of the 2000s, and again in the late 2010s. For Brazil, China, and India, population growth has gradually fallen over time, as their demographic development progresses. South Africa has had the highest population growth rate since 2010, as its population recovered from the initial impact of the HIV/AIDS pandemic, before it started falling as birth rates fall more in line with death rates.

The Asian tiger mosquito, Aedes albopictus, is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae. albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae. albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae. albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae. albopictus with a focus on Japan.