This statistic represents the average height of men in the top 20 countries worldwide as of 2016. On average, men are ***** centimeters tall in Bosnia & Herzegovina.

This statistic represents the average height of women in the top 20 countries worldwide as of 2016. On average, women are ***** centimeters tall in the Netherlands.

This statistic represents the average height of men and women in selected countries worldwide as of 2008. On average, men are ***** centimeters and women are ***** centimeters tall in Australia.

This is a data set from the publication

Hatton, T. J., & Bray, B. E. (2010). Long run trends in the heights of European men, 19th–20th centuries. Economics & Human Biology, 8(3), 405–413. http://doi.org/10.1016/j.ehb.2010.03.001The data set represents average height of the men from several European countries born in the cohorts 1856-1980, 5-years averages.

Dutch, French, Italian (1818-1940): http://www.nber.org/chapters/c7435.pdf Dutch (1955-2009): http://www.nature.com/pr/journal/v73/n3/pdf/pr2012189a.pdf Swedish (1841-1952): http://pediatrisk-endokrinologi.no/2008/1/Werner_2008_1.pdf Danish and Germans (1856-1980): http://privatewww.essex.ac.uk/~hatton/Tim_height_paper.pdf Americans (1710-1980): http://www.cambridge.org/us/academic/subjects/history/economic-history/changing-body-health-nutrition-and-human-development-western-world-1700 All 2013 heights: http://www.averageheight.co/average-male-height-by-country Means and medians are not too different (rarely more than 1 cm difference) because within-country heights for specific gender are generally normally distributed.

In the shown time-period the mean height of men and women has generally increased in England. According to the survey, the average height of males rose slightly during the period in consideration, from 174.4 centimeters in 1998 to 176.2 centimeters (approximately 5'9") in 2022. In comparison, the mean height of women was 162.3 centimeters (5'4") in 2022, up from 161 in 1998. Reasons for height increasing While a large part of an adult’s final height is based on genetics, the environment in which a person grows up is also important. Improvements in nutrition, healthcare, and hygiene have seen the average heights increase over the last century, particularly in developed countries. Average height is usually seen as a barometer for the overall health of the population of a country, as the most developed are usually among the ‘tallest’ countries. Average waist circumference also increasing The prevalence of obesity among adults in England has generally been trending upward since 2000. In that year, 21 percent of men and women in England were classified as obese. By 2021, however, this share was 26 percent among women and 25 percent among men. Every adult age group in England had an average BMI which was classified as overweight, apart from those aged 16 to 24, indicating there is a problem with overweightness in England.

While they may not have made it out of the group stages of the 2018 World Cup, the Serbian national team were top of the table when it came to the average height of their players – their squad boasted an average height of 185.6 centimeters per player. The first-choice goalkeeper for Serbia, Vladimir Stojković, was one of the tallest members of the team at 195 centimeters. At the other end of the scale, the squad of Saudi Arabia came in at an average of just 176.2 centimeters, making them the shortest squad at the 2018 World Cup.

Youth vs. Experience The oldest squad at the 2018 World Cup belonged to Costa Rica. Their squad had an average age of 29.6 years, almost four years older than the squad of Nigeria, who had the youngest squad at the tournament. However, neither youth nor experience triumphed in this instance as both teams failed to get out of their groups. Indeed, the result of the World Cup, with France emerging victorious after beating Croatia in the final, went very much to form. The France squad was the most expensive squad at the tournament, with a combined market value of 1.08 billion euros. Panama’s squad, on the other hand, had a combined transfer value of just 9.13 million euros.

Homegrown talents The Premier League is often called the best league in the world, so it is unsurprising that the entire England squad at the World Cup plied their trade in the English top division. In contrast, there were three national squads in which all of the players played their domestic football abroad – none of the players in the squads of Croatia, Sweden, or Iceland played their club football on home soil. Manchester City was the most represented club team at the World Cup in 2018, with 16 of its players participating. Real Madrid came a close second with 15 members of the squad taking part in the tournament.

These are the results obtained by conducting the experiment "Average Height of 19-year-old Males and Females and GDP per Capita in 2019 for 164 Countries".

The CSV file contains the raw data produced by processing, filtering and merging the input datasets. There are two rows for each of the 164 countries. In both rows, the country name, country code and GDP per capita are given. However, one row contains the average height of 19-year-old males (indicated by the value 'Boys' in the 'Sex' column) whereas the other displays the average height of 19-year-old females (indicated by the value 'Girls').

Furthermore, there are two PNG files which display the regression plots for the average height of 19-year-old males and females, respectively. Note that the x-scale (for the GDP per capita) is logarithmic.

Moldova MD: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data was reported at 5.800 % in 2012. This records a decrease from the previous number of 11.000 % for 2005. Moldova MD: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data is updated yearly, averaging 8.400 % from Dec 2005 (Median) to 2012, with 2 observations. The data reached an all-time high of 11.000 % in 2005 and a record low of 5.800 % in 2012. Moldova MD: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Moldova – Table MD.World Bank.WDI: Health Statistics. Prevalence of stunting, male, is the percentage of boys under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Cambodia KH: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data was reported at 24.500 % in 2021. This records a decrease from the previous number of 33.000 % for 2014. Cambodia KH: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data is updated yearly, averaging 41.500 % from Dec 1996 (Median) to 2021, with 7 observations. The data reached an all-time high of 61.100 % in 1996 and a record low of 24.500 % in 2021. Cambodia KH: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cambodia – Table KH.World Bank.WDI: Social: Health Statistics. Prevalence of stunting, male, is the percentage of boys under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.;;Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF). Estimates are from national survey data. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Eritrea ER: Prevalence of Wasting: Weight for Height: Male: % of Children Under 5 data was reported at 16.600 % in 2010. This records a decrease from the previous number of 16.800 % for 2002. Eritrea ER: Prevalence of Wasting: Weight for Height: Male: % of Children Under 5 data is updated yearly, averaging 16.800 % from Dec 1995 (Median) to 2010, with 3 observations. The data reached an all-time high of 20.700 % in 1995 and a record low of 16.600 % in 2010. Eritrea ER: Prevalence of Wasting: Weight for Height: Male: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Eritrea – Table ER.World Bank: Health Statistics. Prevalence of wasting, male,is the proportion of boys under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Supplementary files for article Supplementary information files for Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants.BackgroundComparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents.MethodsFor this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence.FindingsWe pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls.InterpretationThe height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks.

Global and regional Canopy Height Maps (CHM). Created using machine learning models on high-resolution worldwide Maxar satellite imagery.

Sudan SD: Prevalence of Stunting: Height for Age: % of Children Under 5 data was reported at 38.200 % in 2014. This records an increase from the previous number of 34.100 % for 2010. Sudan SD: Prevalence of Stunting: Height for Age: % of Children Under 5 data is updated yearly, averaging 38.200 % from Dec 2006 (Median) to 2014, with 3 observations. The data reached an all-time high of 38.300 % in 2006 and a record low of 34.100 % in 2010. Sudan SD: Prevalence of Stunting: Height for Age: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sudan – Table SD.World Bank: Health Statistics. Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

This file contains a time series of globally-averaged sea level change, or "global mean sea level" (GMSL) in units of centimeters. The estimate is based on satellite observations of sea surface height anomaly, measured by reference radar altimeter missions such as TOPEX/Poseidon, the Jason series, and Sentinel-6. The indicator values were calculated using NASA-SSH Simple Gridded Sea Surface Height from Standardized Reference Missions Only Version 1 https://podaac.jpl.nasa.gov/dataset/NASA_SSH_REF_SIMPLE_GRID_V1 . GMSL was calculated as the area-weighted average over each map in the time series of Simple Gridded Sea Surface Height. Because maps are computed using 10-days of observations, but are computed once every 7 days, there is a small amount of overlap between data used to compute successive time steps. A version of the estimate smoothed over 60 days is also provided. Expert users, please note that this estimate has NOT been adjusted for Glacial Isostatic Adjustment, to account for the slight long-term depression of the sea floor. Users who study the sea level budget will need to account for this effect in order to properly evaluate closure of the budget. The file with the filename "NASA_SSH_GMSL_INDICATOR.txt" is always the most up-to-date time series containing the most recent data.

The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer. A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data. The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.

Macedonia MK: Prevalence of Stunting: Height for Age: Female: % of Children Under 5 data was reported at 4.300 % in 2011. This records a decrease from the previous number of 9.200 % for 2005. Macedonia MK: Prevalence of Stunting: Height for Age: Female: % of Children Under 5 data is updated yearly, averaging 5.300 % from Dec 1999 (Median) to 2011, with 4 observations. The data reached an all-time high of 9.200 % in 2005 and a record low of 0.900 % in 2004. Macedonia MK: Prevalence of Stunting: Height for Age: Female: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Macedonia – Table MK.World Bank: Health Statistics. Prevalence of stunting, female, is the percentage of girls under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Values of the average height of reference level with respect to the mean sea level, href (m), are provided from 0° to 360° in longitude and from +90° to −90° in latitude with a resolution of 1.5° in longitude and latitude. Values of the average height of reference level with respect to the mean sea level at any location in the world can be calculated using bilinear interpolation as described in Annex 1 to Recommendation ITU-R P.1144.

Note: Countries are presented from shortest to tallest differential from the global mean; Adjusted  =  adjusted for year of birth, household wealth, education, and place of residence (urban or rural); SE  =  Standard Error.

The Global Ecosystem Dynamics Investigation (GEDI) mission aims to characterize ecosystem structure and dynamics to enable radically improved quantification and understanding of the Earth’s carbon cycle and biodiversity. The GEDI instrument produces high resolution laser ranging observations of the 3-dimensional structure of the Earth. GEDI is attached to the International Space Station (ISS) and collects data globally between 51.6° N and 51.6° S latitudes at the highest resolution and densest sampling of any light detection and ranging (lidar) instrument in orbit to date. Each GEDI Version 2 granule encompasses one-fourth of an ISS orbit and includes georeferenced metadata to allow for spatial querying and subsetting.The GEDI instrument was removed from the ISS and placed into storage on March 17, 2023. No data were acquired during the hibernation period from March 17, 2023, to April 24, 2024. GEDI has since been reinstalled on the ISS and resumed operations as of April 26, 2024.The purpose of the GEDI Level 2A Geolocated Elevation and Height Metrics product (GEDI02_A) is to provide waveform interpretation and extracted products from each GEDI01_B received waveform, including ground elevation, canopy top height, and relative height (RH) metrics. The methodology for generating the GEDI02_A product datasets is adapted from the Land, Vegetation, and Ice Sensor (LVIS) algorithm. The GEDI02_A product is provided in HDF5 format and has a spatial resolution (average footprint) of 25 meters.The GEDI02_A data product contains 156 layers for each of the eight beams, including ground elevation, canopy top height, relative return energy metrics (e.g., canopy vertical structure), and many other interpreted products from the return waveforms. Additional information for the layers can be found in the GEDI Level 2A Dictionary.Known Issues

• Data acquisition gaps: GEDI data acquisitions were suspended on December 19, 2019 (2019 Day 353) and resumed on January 8, 2020 (2020 Day 8).
• Incorrect Reference Ground Track (RGT) number in the filename for select GEDI files: GEDI Science Data Products for six orbits on August 7, 2020, and November 12, 2021, had the incorrect RGT number in the filename. There is no impact to the science data, but users should reference this document for the correct RGT numbers.
• Known Issues: Section 8 of the User Guide provides additional information on known issues.

• Metadata has been updated to include spatial coordinates.
• Granule size has been reduced from one full ISS orbit (5.83 GB) to four segments per orbit (1.48 GB).
• Filename has been updated to include segment number and version number.
• Improved geolocation for an orbital segment.
• Added elevation from the SRTM digital elevation model for comparison.
• Modified the method to predict an optimum algorithm setting group per laser shot.
• Added additional land cover datasets related to phenology, urban infrastructure, and water persistence.
• Added selected_mode_flag dataset to root beam group using selected algorithm.
• Removed shots when the laser is not firing.
• Modified file name to include segment number and dataset version. Read our doc on how to get AWS Credentials to retrieve this data: https://data.lpdaac.earthdatacloud.nasa.gov/s3credentialsREADME