The annual population growth in the United States increased by 0.1 percentage points (+27.03 percent) in 2023. In total, the population growth amounted to 0.49 percent in 2023. Population growth deals with the annual change in total population, and is affected by factors such as fertility, mortality, and migration.Find more key insights for the annual population growth in countries like Mexico and Canada.

The statistic shows the total population in the United States from 2015 to 2021, with projections up until 2027. In 2021, the total population of the U.S. amounted to approximately 332.18 million inhabitants.

The United States' economy over the last decade

The United States of America is the world’s largest national economy and the second most prominent trader globally, trailing just behind China. The country is also one of the most populated countries in the world, trailing only China and India. The United States' economy prospers primarily due to having a plentiful amount of natural resources and advanced infrastructure to cope with the production of goods and services, as well as the population and workforce to enable high productivity. Efficient productivity led to a slight growth in GDP almost every year over the past decade, despite undergoing several economic hardships towards the late 2000's.

In addition, the United States holds arguably one of the most important financial markets, with the majority of countries around the world having commercial connections with American companies. Dependency on a single market like the United States has however caused several global dilemmas, most evidently seen during the 2008 financial crisis. What initially started off as a bursting of the U.S. housing bubble lead to a worldwide recession and the necessity to reform national economics. The global financial crisis affected the United States most drastically, especially within the unemployment market as well as national debt, which continued to rise due to the United States having to borrow money in order to stimulate its economy.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

UCB Projection: Population: Natural Increase data was reported at 491.000 Person th in 2060. This records an increase from the previous number of 482.000 Person th for 2059. UCB Projection: Population: Natural Increase data is updated yearly, averaging 616.500 Person th from Jun 2017 (Median) to 2060, with 44 observations. The data reached an all-time high of 1,387.000 Person th in 2017 and a record low of 392.000 Person th in 2049. UCB Projection: Population: Natural Increase data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.G006: Population: Projection: US Census Bureau.

About this dataset

Context

The dataset tabulates the Natural Bridge population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Natural Bridge across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Natural Bridge was 35, a 2.94% increase year-by-year from 2022. Previously, in 2022, Natural Bridge population was 34, a decline of 0% compared to a population of 34 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Natural Bridge decreased by 10. In this period, the peak population was 45 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Natural Bridge is shown in this column.
• Year on Year Change: This column displays the change in Natural Bridge population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Natural Bridge Population by Year. You can refer the same here

There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Looking at an area’s unique combination of natural change and migration helps us understand why its population is changing, and how quickly the change is occurring.Natural IncreaseNatural change is the difference between births and deaths in a population. Often times, natural change is positive, which means that more babies are being born than people are dying. This positive natural change is referred to as natural increase. Examples of natural increase exist across the United States, one being the Salt Lake City metro area in Utah. Between 2014 and 2015, Salt Lake City had around 19,100 births and 6,400 deaths. Since there were about 12,700 more births than deaths, Salt Lake City had a natural increase of about 12,700 people, making natural increase a key reason why its population grew over the year.The opposite of natural increase is called natural decrease, where more people are dying than babies being born, which can cause a population to shrink. Areas with aging populations often have natural decrease. Two states had natural decrease between 2014 and 2015, Maine and West Virginia. Between 2014 and 2015, Maine had 450 more deaths than births and West Virginia had 940 more deaths than births. In both cases, natural decrease was one of the reasons why their populations shrank between 2014 and 2015 in our latest estimates.MigrationMigration is the movement of people from one area to another. It is often expressed as net migration, which is the difference between how many people move into and out of an area. When net migration is positive, a population has more people moving in than out. We split migration into domestic migration and international migration.Domestic migration refers to people moving between areas within the United States, and is often one of the largest contributors to population change. Regionally, the South gains the most net domestic migrants, with roughly 440,000 more people moving into southern states than leaving them between 2014 and 2015. Sometimes net domestic migration is negative, in which case more people are moving away than are moving in. The Chicago metro area in Illinois, Indiana, and Wisconsin lost about 80,000 people through migration between 2014 and 2015, which is consistent with a long-standing pattern of negative net domestic migration for the metro area.International migration refers to people moving into and out of the United States, and consists of a diverse group of people such as foreign-born immigrants from many countries around the world, members of the U.S. Armed Forces, and U.S. citizens working abroad. Some areas, like the Miami metro area in Florida, grow (in part) due to net international migration. Miami gained about 70,000 net international migrants between 2014 and 2015, making net international migration a major factor in Miami’s population growth.

United States US: Birth Rate: Crude: per 1000 People data was reported at 12.400 Ratio in 2016. This stayed constant from the previous number of 12.400 Ratio for 2015. United States US: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 15.100 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 23.700 Ratio in 1960 and a record low of 12.400 Ratio in 2016. United States US: 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 United States – Table US.World Bank.WDI: 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 dataset, provided both in comma-separated values (.csv) and the more informative Stata (.dta) format, contains place/year demographic data on more than 300 rural Alaska communities annually for 1990 to 2022 -- about 10,000 place/years. For each of the available place/years, the data include population estimates from the Alaska Department of Labor and Workforce Development or (in Census years) from the US Census. For a subset consisting of 104 northern or western Alaska (Arctic/subarctic) towns and villages, the dataset also contains yearly estimates of natural increase (births minus deaths) and net migration (population minus last year's population plus natural increase). Natural increase was calculated from birth and death counts provided confidentially to researchers by the Alaska Health Analytics and Vital Records Section (HAVRS). By agreement with HAVRS, the community-level birth and death counts are not available for publication. Population, natural increase, and net migration estimates reflect mid-year values, or change over the past fiscal rather than calendar year. For example, the natural increase value for a community in 2020 is based on births and deaths of residents from July 1, 2019 to June 31, 2020. We emphasize that all values here are best estimates, based on records of the Alaska government organizations. The dataset contains 19 variables: placename Place name (string) placenum Place name (numeric) placefips Place FIPS code year Year borough Borough name boroughfips Borough FIPS code latitude Latitude (decimal, - denotes S) longitude Longitude (decimal, - denotes W) town Village {0:pop2020<2,000} or town {1:pop2020>2,000} village104 104 selected Arctic/rural communities {0,1} arctic43 43 Arctic communities {0,1}, Hamilton et al. 2016 north37 37 Northern Alaska communities {0,1), Hamilton et al. 2016 pop Population (2022 data) cpopP Change in population, percent natinc Natural increase: births-deaths natincP Natural increase, percent netmig Net migration estimate netmigP Net migration, percent nipop Population without migration Three of these variables flag particular subsets of communities. The first two subsets (43 or 37 places) were analyzed in earlier publications, so the flags might be useful for replications or comparisons. The third subset (104 places) is a newer, expanded group of Arctic/subarctic towns and villages for which natural increase and net migration estimates are now available. The flag variables are: If arctic43 = 1 Subset consisting of 43 Arctic towns and villages, previously studied in three published articles: 1. Hamilton, L.C. & A.M. Mitiguy. 2009. “Visualizing population dynamics of Alaska’s Arctic communities.” Arctic 62(4):393–398. https://doi.org/10.14430/arctic170 2. Hamilton, L.C., D.M. White, R.B. Lammers & G. Myerchin. 2012. “Population, climate and electricity use in the Arctic: Integrated analysis of Alaska community data.” Population and Environment 33(4):269–283. https://doi.org/10.1007/s11111-011-0145-1 3. Hamilton, L.C., K. Saito, P.A. Loring, R.B. Lammers & H.P. Huntington. 2016. “Climigration? Population and climate change in Arctic Alaska.” Population and Environment 38(2):115–133. https://doi.org/10.1007/s11111-016-0259-6 If north37 = 1 Subset consisting of 37 northern Alaska towns and villages, previously analyzed for comparison with Nunavut and Greenland in a paper on demographics of the Inuit Arctic: 4. Hamilton, L.C., J. Wirsing & K. Saito. 2018. “Demographic variation and change in the Inuit Arctic.” Environmental Research Letters 13:11507. https://doi.org/10.1088/1748-9326/aae7ef If village104 = 1 Expanded group consisting of 104 communities, including all those in the arctic43 and north37 subsets. This group includes most rural Arctic/subarctic communities that had reasonably complete, continuous data, and 2018 populations of at least 100 people. These data were developed by updating older work and drawing in 61 additional towns or villages, as part of the NSF-supported Arctic Village Dynamics project (OPP-1822424).

India population growth rate for 2023 was 0.88%, a 0.09% increase from 2022.

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

<li>India population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.03% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.82%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.97%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Population dynamics, its types. Population migration (external, internal), factors determining it, main trends. Impact of migration on population health.

Under the guidance of Moldoev M.I. Sir By Riya Patil and Rutuja Sonar

Abstract

Population dynamics influence development and vice versa, at various scale levels: global, continental/world-regional, national, regional, and local. Debates on how population growth affects development and how development affects population growth have already been subject of intensive debate and controversy since the late 18th century, and this debate is still ongoing. While these two debates initially focused mainly on natural population growth, the impact of migration on both population dynamics and development is also increasingly recognized. While world population will continue growing throughout the 21st century, there are substantial and growing contrasts between and within world-regions in the pace and nature of that growth, including some countries where population is stagnating or even shrinking. Because of these growing contrasts, population dynamics and their interrelationships with development have quite different governance implications in different parts of the world.

1. Population Dynamics

Population dynamics refers to the changes in population size, structure, and distribution over time. These changes are influenced by four main processes:

Birth rate (natality)

Death rate (mortality)

Immigration (inflow of people)

Emigration (outflow of people)

Types of Population Dynamics

Natural population change: Based on birth and death rates.

Migration-based change: Caused by people moving in or out of a region.

Demographic transition: A model that explains changes in population growth as societies industrialize.

Population distribution: Changes in where people live (urban vs rural).

2. Population Migration

Migration refers to the movement of people from one location to another, often across political or geographical boundaries.

Types of Migration

External migration (international):

Movement between countries.

Examples: Refugee relocation, labor migration, education.

Internal migration:

Movement within the same country or region.

Examples: Rural-to-urban migration, inter-state migration.

3. Factors Determining Migration

Migration is influenced by push and pull factors:

Push factors (reasons to leave a place):

Unemployment

Conflict or war

Natural disasters

Poverty

Lack of services or opportunities

Pull factors (reasons to move to a place):

Better job prospects

Safety and security

Higher standard of living

Education and healthcare access

Family reunification

4. Main Trends in Migration

Urbanization: Mass movement to cities for work and better services.

Global labor migration: Movement from developing to developed countries.

Refugee and asylum seeker flows: Due to conflict or persecution.

Circular migration: Repeated movement between two or more locations.

Brain drain/gain: Movement of skilled labor away from (or toward) a country.

5. Impact of Migration on Population Health

Positive Impacts:

Access to better healthcare (for migrants moving to better systems).

Skills and knowledge exchange among health professionals.

Remittances improving healthcare affordability in home countries.

Negative Impacts:

Migrants’ health risks: Increased exposure to stress, poor living conditions, and occupational hazards.

Spread of infectious diseases: Especially when health screening is lacking.

Strain on health services: In receiving areas, especially with sudden or large influxes.

Mental health challenges: Due to cultural dislocation, discrimination, or trauma.

Population dynamics is one of the fundamental areas of ecology, forming both the basis for the study of more complex communities and of many applied questions. Understanding population dynamics is the key to understanding the relative importance of competition for resources and predation in structuring ecological communities, which is a central question in ecology.

Population dynamics plays a central role in many approaches to preserving biodiversity, which until now have been primarily focused on a single species approach. The calculation of the intrinsic growth rate of a species from a life table is often the central piece of conservation plans. Similarly, management of natural resources, such as fisheries, depends on population dynamics as a way to determine appropriate management actions.

Population dynamics can be characterized by a nonlinear system of difference or differential equations between the birth sizes of consecutive periods. In such a nonlinear system, when the feedback elasticity of previous events on current birth size is larger, the more likely the dynamics will be volatile. Depending on the classification criteria of the population, the revealed cyclical behavior has various interpretations. Under different contextual scenarios, Malthusian cycles, Easterlin cycles, predator–prey cycles, dynastic cycles, and capitalist–laborer cycles have been introduced and analyzed

Generally, population dynamics is a nonlinear stochastic process. Nonlinearities tend to be complicated to deal with, both when we want to do analytic stochastic modelling and when analysing data. The way around the problem is to approximate the nonlinear model with a linear one, for which the mathematical and statistical theories are more developed and tractable. Let us assume that the population process is described as:

(1)Nt=f(Nt−1,εt)

where Nt is population density at time t and εt is a series of random variables with identical distributions (mean and variance). Function f specifies how the population density one time step back, plus the stochastic environment εt, is mapped into the current time step. Let us assume that the (deterministic) stationary (equilibrium) value of the population is N* and that ε has mean ε*. The linear approximation of Eq. (1) close to N* is then:

(2)xt=axt−1+bϕt

where xt=Nt−N*, a=f

f(N*,ε*)/f

N, b=ff(N*,ε*)/fε, and ϕt=εt−ε*

The term population refers to the members of a single species that can interact with each other. Thus, the fish in a lake, or the moose on an island, are clear examples of a population. In other cases, such as trees in a forest, it may not be nearly so clear what a population is, but the concept of population is still very useful.

Population dynamics is essentially the study of the changes in the numbers through time of a single species. This is clearly a case where a quantitative description is essential, since the numbers of individuals in the population will be counted. One could begin by looking at a series of measurements of the numbers of particular species through time. However, it would still be necessary to decide which changes in numbers through time are significant, and how to determine what causes the changes in numbers. Thus, it is more sensible to begin with models that relate changes in population numbers through time to underlying assumptions. The models will provide indications of what features of changes in numbers are important and what measurements are critical to make, and they will help determine what the cause of changes in population levels might be.

To understand the dynamics of biological populations, the study starts with the simplest possibility and determines what the dynamics of the population would be in that case. Then, deviations in observed populations from the predictions of that simplest case would provide information about the kinds of forces shaping the dynamics of populations. Therefore, in describing the dynamics in this simplest case it is essential to be explicit and clear about the assumptions made. It would not be argued that the idealized population described here would ever be found, but that focusing on the idealized population would provide insight into real populations, just as the study of Newtonian mechanics provides understanding of more realistic situations in physics.

Population migration

The vast majority of people continue to live in the countries where they were born —only one in 30 are migrants.

In most discussions on migration, the starting point is usually numbers. Understanding changes in scale, emerging trends, and shifting demographics related to global social and economic transformations, such as migration, help us make sense of the changing world we live in and plan for the future. The current global estimate is that there were around 281 million international migrants in the world in 2020, which equates to 3.6 percent of the global population.

Overall, the estimated number of international migrants has increased over the past five decades. The total estimated 281 million people living in a country other than their countries of birth in 2020 was 128 million more than in 1990 and over three times the estimated number in 1970.

There is currently a larger number of male than female international migrants worldwide and the growing gender gap has increased over the past 20 years. In 2000, the male to female split was 50.6 to 49.4 per cent (or 88 million male migrants and 86 million female migrants). In 2020 the split was 51.9 to 48.1 per cent, with 146 million male migrants and 135 million female migrants. The share of

Between 1970 and 1989, the Soviet Union's population experienced a rate of natural increase that was consistently higher (sometimes by a significant margin) than that of the United States. In 1970, these increases were fairly similar at 9.2 and 8.8 per 1,000 population respectively, however the margin was considerably larger by the middle of the decade.

Although the Soviet Union's birth and death rates were both higher than those of the U.S. in most of these years, the larger disparity in birth rates is the reason for the USSR's higher rate of natural increase. However, while the USSR had a higher rate of natural increase, this did not mean that the Soviet population grew faster than that of the United States; the U.S. had a much higher net migration rate, which brought population growth rates much closer in the 1970s and 1980s.

United States US: Death Rate: Crude: per 1000 People data was reported at 8.400 Ratio in 2016. This records a decrease from the previous number of 8.440 Ratio for 2015. United States US: Death Rate: Crude: per 1000 People data is updated yearly, averaging 8.700 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 9.800 Ratio in 1968 and a record low of 7.900 Ratio in 2009. United States US: Death 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 United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths 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;

This statistic shows the 20 countries with the highest population growth rate in 2024. In SouthSudan, the population grew by about 4.65 percent compared to the previous year, making it the country with the highest population growth rate in 2024. The global population Today, the global population amounts to around 7 billion people, i.e. the total number of living humans on Earth. More than half of the global population is living in Asia, while one quarter of the global population resides in Africa. High fertility rates in Africa and Asia, a decline in the mortality rates and an increase in the median age of the world population all contribute to the global population growth. Statistics show that the global population is subject to increase by almost 4 billion people by 2100. The global population growth is a direct result of people living longer because of better living conditions and a healthier nutrition. Three out of five of the most populous countries in the world are located in Asia. Ultimately the highest population growth rate is also found there, the country with the highest population growth rate is Syria. This could be due to a low infant mortality rate in Syria or the ever -expanding tourism sector.

Graph and download economic data for Employment Level - Native Born (LNU02073413) from Jan 2007 to Jun 2025 about native born, 16 years +, household survey, employment, and USA.

Explore the Saudi Arabia World Development Indicators dataset , including key indicators such as Access to clean fuels, Adjusted net enrollment rate, CO2 emissions, and more. Find valuable insights and trends for Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, and India.

Indicator, Access to clean fuels and technologies for cooking, rural (% of rural population), Access to electricity (% of population), Adjusted net enrollment rate, primary, female (% of primary school age children), Adjusted net national income (annual % growth), Adjusted savings: education expenditure (% of GNI), Adjusted savings: mineral depletion (current US$), Adjusted savings: natural resources depletion (% of GNI), Adjusted savings: net national savings (current US$), Adolescents out of school (% of lower secondary school age), Adolescents out of school, female (% of female lower secondary school age), Age dependency ratio (% of working-age population), Agricultural methane emissions (% of total), Agriculture, forestry, and fishing, value added (current US$), Agriculture, forestry, and fishing, value added per worker (constant 2015 US$), Alternative and nuclear energy (% of total energy use), Annualized average growth rate in per capita real survey mean consumption or income, total population (%), Arms exports (SIPRI trend indicator values), Arms imports (SIPRI trend indicator values), Average working hours of children, working only, ages 7-14 (hours per week), Average working hours of children, working only, male, ages 7-14 (hours per week), Cause of death, by injury (% of total), Cereal yield (kg per hectare), Changes in inventories (current US$), Chemicals (% of value added in manufacturing), Child employment in agriculture (% of economically active children ages 7-14), Child employment in manufacturing, female (% of female economically active children ages 7-14), Child employment in manufacturing, male (% of male economically active children ages 7-14), Child employment in services (% of economically active children ages 7-14), Child employment in services, female (% of female economically active children ages 7-14), Children (ages 0-14) newly infected with HIV, Children in employment, study and work (% of children in employment, ages 7-14), Children in employment, unpaid family workers (% of children in employment, ages 7-14), Children in employment, wage workers (% of children in employment, ages 7-14), Children out of school, primary, Children out of school, primary, male, Claims on other sectors of the domestic economy (annual growth as % of broad money), CO2 emissions (kg per 2015 US$ of GDP), CO2 emissions (kt), CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion), CO2 emissions from transport (% of total fuel combustion), Communications, computer, etc. (% of service exports, BoP), Condom use, population ages 15-24, female (% of females ages 15-24), Container port traffic (TEU: 20 foot equivalent units), Contraceptive prevalence, any method (% of married women ages 15-49), Control of Corruption: Estimate, Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval, Control of Corruption: Standard Error, Coverage of social insurance programs in 4th quintile (% of population), CPIA building human resources rating (1=low to 6=high), CPIA debt policy rating (1=low to 6=high), CPIA policies for social inclusion/equity cluster average (1=low to 6=high), CPIA public sector management and institutions cluster average (1=low to 6=high), CPIA quality of budgetary and financial management rating (1=low to 6=high), CPIA transparency, accountability, and corruption in the public sector rating (1=low to 6=high), Current education expenditure, secondary (% of total expenditure in secondary public institutions), DEC alternative conversion factor (LCU per US$), Deposit interest rate (%), Depth of credit information index (0=low to 8=high), Diarrhea treatment (% of children under 5 who received ORS packet), Discrepancy in expenditure estimate of GDP (current LCU), Domestic private health expenditure per capita, PPP (current international $), Droughts, floods, extreme temperatures (% of population, average 1990-2009), Educational attainment, at least Bachelor's or equivalent, population 25+, female (%) (cumulative), Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least completed lower secondary, population 25+, female (%) (cumulative), Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, total (%) (cumulative), Electricity production from coal sources (% of total), Electricity production from nuclear sources (% of total), Employers, total (% of total employment) (modeled ILO estimate), Employment in industry (% of total employment) (modeled ILO estimate), Employment in services, female (% of female employment) (modeled ILO estimate), Employment to population ratio, 15+, male (%) (modeled ILO estimate), Employment to population ratio, ages 15-24, total (%) (national estimate), Energy use (kg of oil equivalent per capita), Export unit value index (2015 = 100), Exports of goods and services (% of GDP), Exports of goods, services and primary income (BoP, current US$), External debt stocks (% of GNI), External health expenditure (% of current health expenditure), Female primary school age children out-of-school (%), Female share of employment in senior and middle management (%), Final consumption expenditure (constant 2015 US$), Firms expected to give gifts in meetings with tax officials (% of firms), Firms experiencing losses due to theft and vandalism (% of firms), Firms formally registered when operations started (% of firms), Fixed broadband subscriptions, Fixed telephone subscriptions (per 100 people), Foreign direct investment, net outflows (% of GDP), Forest area (% of land area), Forest area (sq. km), Forest rents (% of GDP), GDP growth (annual %), GDP per capita (constant LCU), GDP per unit of energy use (PPP $ per kg of oil equivalent), GDP, PPP (constant 2017 international $), General government final consumption expenditure (current LCU), GHG net emissions/removals by LUCF (Mt of CO2 equivalent), GNI growth (annual %), GNI per capita (constant LCU), GNI, PPP (current international $), Goods and services expense (current LCU), Government Effectiveness: Percentile Rank, Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval, Government Effectiveness: Standard Error, Gross capital formation (annual % growth), Gross capital formation (constant 2015 US$), Gross capital formation (current LCU), Gross fixed capital formation, private sector (% of GDP), Gross intake ratio in first grade of primary education, male (% of relevant age group), Gross intake ratio in first grade of primary education, total (% of relevant age group), Gross national expenditure (current LCU), Gross national expenditure (current US$), Households and NPISHs Final consumption expenditure (constant LCU), Households and NPISHs Final consumption expenditure (current US$), Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $), Households and NPISHs final consumption expenditure: linked series (current LCU), Human capital index (HCI) (scale 0-1), Human capital index (HCI), male (scale 0-1), Immunization, DPT (% of children ages 12-23 months), Import value index (2015 = 100), Imports of goods and services (% of GDP), Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24), Incidence of HIV, all (per 1,000 uninfected population), Income share held by highest 20%, Income share held by lowest 20%, Income share held by third 20%, Individuals using the Internet (% of population), Industry (including construction), value added (constant LCU), Informal payments to public officials (% of firms), Intentional homicides, male (per 100,000 male), Interest payments (% of expense), Interest rate spread (lending rate minus deposit rate, %), Internally displaced persons, new displacement associated with conflict and violence (number of cases), International tourism, expenditures for passenger transport items (current US$), International tourism, expenditures for travel items (current US$), Investment in energy with private participation (current US$), Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate), Development

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The death rate in Latin America & the Caribbean decreased by *** deaths per 1,000 inhabitants (-**** percent) compared to the previous year. The crude death rate refers to the number of deaths in a given year, expressed per 1,000 population. When studied in combination with the crude birth rate, the rate of natural population increase can be determined.Find more statistics on other topics about Latin America & the Caribbean with key insights such as number of tuberculosis infections , total life expectancy at birth, and total fertility rate.

In 2023, the population of Africa was projected to grow by 2.34 percent compared to the previous year. The population growth rate on the continent has been constantly over 2.3 percent from 2000 onwards, and it peaked at 2.59 percent between 2012 and 2013. Despite a slowdown in the growth rate, the continent's population will continue to increase significantly in the coming years. The second-largest population worldwide In 2022, the total population of Africa amounted to around 1.4 billion. The number of inhabitants had grown steadily in the previous decades, rising from approximately 810 million in 2000. Driven by a decreasing mortality rate and a higher life expectancy at birth, the African population was forecast to increase to about 2.5 billion individuals by 2050. Africa is currently the second most populous continent worldwide after Asia. However, forecasts showed that Africa could gradually close the gap and almost reach the size of the Asian population in 2100. By that year, Africa might count 3.9 billion people, compared to 4.7 billion in Asia. The world's youngest continent The median age in Africa corresponded to 18.8 years in 2023. Although the median age has increased in recent years, the continent remains the youngest worldwide. In 2023, roughly 40 percent of the African population was aged 15 years and younger, compared to a global average of 25 percent. Africa recorded not only the highest share of youth but also the smallest elderly population worldwide. As of the same year, only three percent of Africa's population was aged 65 years and older. Africa and Latin America were the only regions below the global average of 10 percent. On the continent, Niger, Uganda, and Angola were the countries with the youngest population in 2023.

In 1998, formal demographic censusing of wild ginseng (Panax quinquefolius L.) populations was initiated in West Virginia. By 2004, thirty populations had been added to the census effort, spanning seven states (IN-2, KY-6, MD-1, NY-2, PA-2, VA-5, WV-12) and a wide variety of land use histories and eastern deciduous forest communities. The censusing effort continued without interruption at all populations until June, 2016. Annually, each population was visited twice. The first visit generally occurred between late May and the end of June. The second visit generally occurred in the first three weeks of August. The purpose of the spring census was to assess the population status at the time of year when the largest number of individuals were visible aboveground (post-germination, prior to substantial losses due to browsing and other causes). Detailed measures of plant size were made, with an emphasis on total leaf area calculation. In addition, a variety of plant condition notations were made, with the ultimate goal of determining mortality and recruitment in the population, as well as individual size transitions. The primary purpose of the second census each year was to assess seed production on each plant. In addition, further notations of plant condition were made to assess changes over the growing season. To maintain methodological consistency with field personnel turnover, the lead author participated in fieldwork throughout the study, visiting each population at least once every two years. In addition, after being trained themselves, graduate students trained undergraduate conservation interns to assure consistent methods were used each year. The data are suitable for demographic modeling, and the unique spatial and temporal extent allow the exploration of important questions about variability in population growth and viability of ginseng, America’s premiere wild harvested medicinal plant.

Peer reviewed publications derived from this dataset:

McGraw, J. B., S. M. Sanders, and M. E. Van der Voort. 2003. Distribution and Abundance of Hydrastis canadensis L. (Ranunculaceae) and Panax quinquefolius L. (Araliaceae) in the Central Appalachian Region. Journal of the Torrey Botanical Club 130(2): 62-69.

Furedi, M. A. and J. B. McGraw. 2004. White-tailed deer: Dispersers or predators of American ginseng seeds? American Midland Naturalist 152:268-276.

McGraw, J. B. and M. A. Furedi. 2005. Deer browsing and population viability of a forest understory plant. Science 307: 920-922.

McGraw, J. B., M. A. Furedi, K. Maiers, C. Carroll, G. Kauffman, A. Lubbers, J. Wolf, R. Anderson, R. Anderson, B. Wilcox, D. Drees, M. E. Van der Voort, M. Albrecht, A. Nault, H. MacCulloch, and A. Gibbs. 2005. Berry ripening and harvest season in wild American ginseng. Northeastern Naturalist 12(2): 141-152.

Van der Voort, M. E. and J. B. McGraw. 2006. Effects of harvester behavior on population growth rate affects sustainability of ginseng trade. Biological Conservation 130: 505-516.

Mooney, E. H. and J. B. McGraw. 2007. Unintentional effects of harvest on selection in wild American ginseng. Conservation Genetics 8: 57-67.

Wixted, K. and J. B. McGraw. 2009. A Panax-centric view of invasive species. Biological Invasions 11(4): 883-893.

Mooney, E. H. and J. B. McGraw. 2009. Relationship between age, size and reproduction in populations of American ginseng, Panax quinquefolius (Araliaceae), across a range of harvest pressures. Ecoscience 16(1): 84-94.

McGraw, J. B., S. Souther, and A. E. Lubbers. 2010. Rates of harvest and compliance with regulations in natural populations of American ginseng (Panax quinquefolius L.). Natural Areas Journal 30: 202-210.

Souther, S. and J. B. McGraw. 2011. Vulnerability of wild American ginseng to an extreme early spring temperature fluctuation. Population Ecology 53(1):119-129.

Souther, S. and J. B. McGraw. 2011. Local adaptation to temperature and its implications for species conservation in a changing climate. Conservation Biology 25(5): 922-931.

McGraw, J. B., A. E. Lubbers, M. E. Van der Voort, E. H. Mooney, M. A. Furedi, S. Souther, J. B. Turner, J. Chandler. 2013. Ecology and conservation of ginseng (Panax quinquefolius) in a changing world. Annals of the New York Academy of Sciences 1286: 62-91. {ISSN 0077-8923. DOI: 10.1111/nyas.12032. (Invited Review)}

Wagner, A. and J. B. McGraw. 2013. Sunfleck effects on physiology, growth, and local demography of American ginseng (Panax quinquefolius L.). Forest Ecology and Management 291:220-227.

Souther, S. and J. B. McGraw. 2014. Synergistic effects of climate change and harvest on extinction risk of American ginseng. Ecological Applications 24(6): 1463-1477.

Hruska, A. M., S. So

The crude birth rate in the United States declined to 10.7 live births per 1,000 inhabitants in 2023. The rate thereby reached its lowest value in recent years. The crude birth rate refers to the number of live births in a given year, expressed per 1,000 population. When studied in combination with the crude death rate, the rate of natural population increase can be determined.Find more statistics on other topics about the United States with key insights such as death rate, total fertility rate, and life expectancy of men at birth.

In 1998, formal demographic censusing of wild ginseng (Panax quinquefolius L.) populations was initiated in West Virginia. By 2004, thirty populations had been added to the census effort, spanning seven states (IN-2, KY-6, MD-1, NY-2, PA-2, VA-5, WV-12) and a wide variety of land use histories and eastern deciduous forest communities. The censusing effort continued without interruption at all populations until June, 2016. Annually, each population was visited twice. The first visit generally occurred between late May and the end of June. The second visit generally occurred in the first three weeks of August. The purpose of the spring census was to assess the population status at the time of year when the largest number of individuals were visible aboveground (post-germination, prior to substantial losses due to browsing and other causes). Detailed measures of plant size were made, with an emphasis on total leaf area calculation. In addition, a variety of plant condition notations were made, with the ultimate goal of determining mortality and recruitment in the population, as well as individual size transitions. The primary purpose of the second census each year was to assess seed production on each plant. In addition, further notations of plant condition were made to assess changes over the growing season. To maintain methodological consistency with field personnel turnover, the lead author participated in fieldwork throughout the study, visiting each population at least once every two years. In addition, after being trained themselves, graduate students trained undergraduate conservation interns to assure consistent methods were used each year. The data are suitable for demographic modeling, and the unique spatial and temporal extent allow the exploration of important questions about variability in population growth and viability of ginseng, America’s premiere wild harvested medicinal plant.

Publications derived from this dataset:

Peer reviewed publications:

McGraw, J. B., S. M. Sanders, and M. E. Van der Voort. 2003. Distribution and Abundance of Hydrastis canadensis L. (Ranunculaceae) and Panax quinquefolius L. (Araliaceae) in the Central Appalachian Region. Journal of the Torrey Botanical Club 130(2): 62-69.

Furedi, M. A. and J. B. McGraw. 2004. White-tailed deer: Dispersers or predators of American ginseng seeds? American Midland Naturalist 152:268-276.

McGraw, J. B. and M. A. Furedi. 2005. Deer browsing and population viability of a forest understory plant. Science 307: 920-922.

McGraw, J. B., M. A. Furedi, K. Maiers, C. Carroll, G. Kauffman, A. Lubbers, J. Wolf, R. Anderson, R. Anderson, B. Wilcox, D. Drees, M. E. Van der Voort, M. Albrecht, A. Nault, H. MacCulloch, and A. Gibbs. 2005. Berry ripening and harvest season in wild American ginseng. Northeastern Naturalist 12(2): 141-152.

Van der Voort, M. E. and J. B. McGraw. 2006. Effects of harvester behavior on population growth rate affects sustainability of ginseng trade. Biological Conservation 130: 505-516.

Mooney, E. H. and J. B. McGraw. 2007. Unintentional effects of harvest on selection in wild American ginseng. Conservation Genetics 8: 57-67.

Wixted, K. and J. B. McGraw. 2009. A Panax-centric view of invasive species. Biological Invasions 11(4): 883-893.

Mooney, E. H. and J. B. McGraw. 2009. Relationship between age, size and reproduction in populations of American ginseng, Panax quinquefolius (Araliaceae), across a range of harvest pressures. Ecoscience 16(1): 84-94.

McGraw, J. B., S. Souther, and A. E. Lubbers. 2010. Rates of harvest and compliance with regulations in natural populations of American ginseng (Panax quinquefolius L.). Natural Areas Journal 30: 202-210.

Souther, S. and J. B. McGraw. 2011. Vulnerability of wild American ginseng to an extreme early spring temperature fluctuation. Population Ecology 53(1):119-129.

Souther, S. and J. B. McGraw. 2011. Local adaptation to temperature and its implications for species conservation in a changing climate. Conservation Biology 25(5): 922-931.

McGraw, J. B., A. E. Lubbers, M. E. Van der Voort, E. H. Mooney, M. A. Furedi, S. Souther, J. B. Turner, J. Chandler. 2013. Ecology and conservation of ginseng (Panax quinquefolius) in a changing world. Annals of the New York Academy of Sciences 1286: 62-91. {ISSN 0077-8923. DOI: 10.1111/nyas.12032. (Invited Review)}

Wagner, A. and J. B. McGraw. 2013. Sunfleck effects on physiology, growth, and local demography of American ginseng (Panax quinquefolius L.). Forest Ecology and Management 291:220-227.

Souther, S. and J. B. McGraw. 2014. Synergistic effects of climate change and harvest on extinction risk of American ginseng. Ecological Applications 24(6): 1463-1477.