In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Proportion of population in Pacific Island Countries and Territories (PICTs) living in Low Elevation Coastal Zones (LECZ) of 0-10 and 0-20 meters above sea level. LECZ were delineated using the bathub method overlaid on the Advanced Land Observing Satellite (ALOS) Global Digital Surface Model (AW3D30). Populations within the LECZs were estimated using the Pacific Community (SPC) Statistics for Development Division’s 100m2 population grids.

Find more Pacific data on PDH.stat.

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

Over the past three decades, the share of the global population living in rural areas has decreased continuously. Since 2007, less than **** of the world's population lived in rural areas, a share that had dropped to ***** percent as of 2023. The urbanization is expected to continue over the coming decades.

Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water.

Mali ML: Population Living in Slums: % of Urban Population data was reported at 56.300 % in 2014. This records a decrease from the previous number of 65.900 % for 2009. Mali ML: Population Living in Slums: % of Urban Population data is updated yearly, averaging 65.900 % from Dec 1990 (Median) to 2014, with 7 observations. The data reached an all-time high of 94.200 % in 1990 and a record low of 56.300 % in 2014. Mali ML: Population Living in Slums: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Population and Urbanization Statistics. Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, and durability of housing.; ; UN HABITAT, retrieved from the United Nation's Millennium Development Goals database. Data are available at : http://mdgs.un.org/; Weighted Average;

On 1 January 2016, the world officially began implementation of the 2030 Agenda for Sustainable Development—the transformative plan of action based on 17 Sustainable Development Goals—to address urgent global challenges over the next 15 years. The Sustainable Development Goals Database in UNdata presents data for the global SDG indicators that were compiled through the UN System in preparation for the Secretary-Generals annual report on “Progress towards the Sustainable Development Goals.” The data series respond to the revised global indicator framework that was agreed by the Statistical Commission at its forty-eighth session in March 2017. The database contains SDG indicator series and additional indicator series. The list of SDG indicators is subject to refinement by the United Nations Statistical Commission.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

The FGGD extreme poverty map is a global vector datalayer at scale 1:5 000 000. The map depicts the differences among countries with respect to the national population estimated to be living in extreme poverty as of the latest year for which data was available in 2005. Data have been compiled by FAO from data reported in World Bank, WDI Online, as of April 2005.

Data publication: 2007-06-25

Supplemental Information:

This dataset is contained in Module 3 "Socio-economics and nutrition indicators" of Food Insecurity, Poverty and Environment Global GIS Database (FGGD) (FAO, 2007).

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Mirella Salvatore

Resource constraints:

copyright

Online resources:

Share of population living in extreme poverty, by country, varying years

Brazil BR: Population Living in Slums: % of Urban Population data was reported at 14.897 % in 2016. This stayed constant from the previous number of 14.897 % for 2014. Brazil BR: Population Living in Slums: % of Urban Population data is updated yearly, averaging 21.511 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 34.740 % in 2000 and a record low of 14.897 % in 2016. Brazil BR: Population Living in Slums: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Population and Urbanization Statistics. Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.;United Nations Human Settlements Programme (UN-HABITAT);Weighted average;

Sweden - Population living in households considering that they suffer from noise was 10.70% in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Sweden - Population living in households considering that they suffer from noise - last updated from the EUROSTAT on July of 2025. Historically, Sweden - Population living in households considering that they suffer from noise reached a record high of 17.30% in December of 2020 and a record low of 10.70% in December of 2023.

Netherlands - Population living in households considering that they suffer from noise was 28.20% in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Netherlands - Population living in households considering that they suffer from noise - last updated from the EUROSTAT on June of 2025. Historically, Netherlands - Population living in households considering that they suffer from noise reached a record high of 33.10% in December of 2005 and a record low of 23.60% in December of 2011.

This scatter chart displays vulnerable employment (% of total employment) against urban population living in areas where elevation is below 5 meters (% of total population) in Guyana. The data is about countries per year.

The Federal Poverty Level is a measure of poverty issued every year by the US Department of Health and Human Services. The 2022 FPL thresholds for a family of four correspond to annual incomes of $27,750 (100% FPL), $55,500 (200% FPL), and $83,250 (300% FPL).The Federal Poverty Level is used to determine eligibility for certain programs and benefits. Living in poverty has a profound impact on health and wellbeing. People living in poverty are at high risk for economic hardship, housing insecurity, food insecurity, chronic stress, and inadequate access to healthcare.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This line chart displays urban population living in areas where elevation is below 5 meters (% of total population) by date using the aggregation average, weighted by population in Russia. The data is about countries per year.

Aim: Geographic range expansion depends on ecological and evolutionary processes that may hamper local adaptations in populations living at range edges by constraining phenotypic variability. This study investigates the spatial patterns of the intraspecific variability of skull traits throughout the geographic range of a marsupial from the Brazilian Atlantic Forest. We aimed to answer whether the distance from the range edge and the environmental suitability explain the geographic variation of morphological variability of the species. Location: Atlantic Forest, Brazil. Taxon: Marmosops incanus (Didelphimorphia, Didelphidae). Methods: We analysed adult specimens deposited in the main biological collections in southeastern Brazil. The morphological variability extent and integration within populations were characterised by 13 linear measures of the skull, using a multivariate approach. Environmental suitability for the species’ occurrence was estimated by Ecological Niche Models, using climatic and vegetation productivity as predictors and three different modelling methods. Distance from the range edge was calculated based on the minimum linear distance between populations and the closest range limit. We fitted linear regressions and selected the best models that explained the spatial variation of morphological variability based on the Akaike information criterion. Results: The extent of morphological variability of M. incanus is positively correlated with morphological integration and increases with local environmental suitability and distance from the range edges. However, the relationship between morphological variability and environmental suitability depends on the niche modelling method. Main conclusions: Unfavourable environmental conditions constrain morphological variability within populations of the Gray slender opossum and may hamper local adaptation in peripheral populations living in less suitable environments. In addition to environmental conditions, geographic location of populations also plays an important role in phenotypic variability among populations. We stress the boundary effect of the species range on the local adaptation of peripheral populations and its possible consequences for the range expansion dynamics. Methods Please see the README.md document and the metadata.txt located within the /data directory for data collection and analysis information. More details on methods can be found in the accompanying published article: Braz, A.G.; Figueiredo, M.S.L.; Weber, M.M.; Grelle, C.E.V. 2023 Morphological variability decreases in populations living in less suitable environments and close to the range edges. Journal of Biogeography, doi: 10.1111/jbi.14687

This bar chart displays urban population living in areas where elevation is below 5 meters (% of total population) by country full name using the aggregation average, weighted by population. The data is about countries.

This horizontal bar chart displays urban population living in areas where elevation is below 5 meters (% of total population) by currency using the aggregation average, weighted by population. The data is about countries.

This dataset is about countries per year in Mexico. It has 64 rows. It features 4 columns: country, urban population living in areas where elevation is below 5 meters , and population.

This scatter chart displays male population (people) against urban population living in areas where elevation is below 5 meters (% of total population). The data is about countries.