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.

Dataset

This dataset was created by Dilara Özcerit

Contents

Dataset representing average male height data by country.

Anthropometry measures of the household population, by sex and age group.

This table contains 136080 series, with data for years 2005 - 2005 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (126 items: Canada; Central Regional Integrated Health Authority; Newfoundland and Labrador; Newfoundland and Labrador; Eastern Regional Integrated Health Authority; Newfoundland and Labrador ...), Age group (5 items: Total; 18 years and over;18 to 34 years ...), Sex (3 items: Both sexes; Males; Females ...), Body mass index (BMI), self-reported (9 items: Total population for the variable body mass index; self-reported; Normal weight; body mass index; self-reported 18.5 to 24.9;Overweight; body mass index; self-reported 25.0 to 29.9;Underweight; body mass index; self-reported under 18.5 ...), Characteristics (8 items: Number of persons; Low 95% confidence interval; number of persons; Coefficient of variation for number of persons; High 95% confidence interval; number of persons ...).

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.

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.

Provide average height data for students aged 6-15.

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.

Predictive mapping of areas at risk of developing high water tables, generally referred to as Average Height Above Valley Floor (AHAVF). Show full description

Height is an expression of the average height (m) of dominant and co-dominant trees of the leading species in the stand, expressed as Lorey’s mean height (LRY_HT). Available here as a height raster (GeoTIF) with a 20 m pixel resolution. Download: Here The Saskatchewan Ministry of Environment, Forest Service Branch, has developed a forest resource inventory (FRI) which meets a variety of strategic and operational planning information needs for the boreal plains. Such needs include information on the general land cover, terrain, and growing stock (height, diameter, basal area, timber volume and stem density) within the provincial forest and adjacent forest fringe. This inventory provides spatially explicit information as 10 m or 20 m raster grids and as vectors polygons for relatively homogeneous forest stands or naturally non-forested areas with a 0.5 ha minimum area and a 2.0 ha median area. Lorey's mean tree height (LRY_HT) is an expression of the average tree height (m) of dominant and co-dominant trees of the leading species in the stand whereby individual trees are weighted in proportion to their basal area. LRY_HT is available here as a color-mapped 16-bit unsigned integer raster grid in GeoTIFF format with a 20 m pixel resolution. An ArcGIS Pro layer file (*.lyrx) is supplied for viewing LRY_HT data in the following 5 m categories. Domain: [NULL, 0…35]. RANGE LABEL RED GREEN BLUE 0 <= LRY_HT < 3 0 NA NA NA 3 <= LRY_HT < 8 5 63 81 181 8 <= LRY_HT < 13 10 72 144 114 13 <= LRY_HT < 18 15 136 195 73 18 <= LRY_HT < 23 20 255 235 59 23 <= LRY_HT < 28 25 255 180 20 28 <= LRY_HT < 33 30 251 124 18 33 <= LRY_HT <= 35 35 244 67 54 For more information, see the Forest Inventory Standard of the Saskatchewan Environmental Code, Forest Inventory Chapter.

Forest Lorey's Height 2015Lorey's mean height. Average height of trees weighted by their basal area (m). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

HIS51 - Average Height. Published by Department of Health. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Average Height...

Canada CA: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data was reported at 11.400 % in 2024. This stayed constant from the previous number of 11.400 % for 2023. Canada CA: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 11.000 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 11.500 % in 2021 and a record low of 9.100 % in 2000. Canada CA: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Social: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.

Estimated annual average wave height (metres) created by a Pelamis Wave Model for Accessible Wave Energy Resource Atlas. Wave height values are measured as lower and upper values in metres as calculated by the Pelamis wave model. Annual average wave height covers an area known as the Irish Exclusive Economic Zone (EEZ). Data model produced in 2005. The Pelamis Wave Model was an oceanographic model using the Pelamis wave energy converter device. The Accessible Wave Energy Resource Atlas was produced to provide data and information on the accessible wave energy resource potential around Ireland. Wave model developed by ESB International (ESBI) as part of the Accessible Wave Energy Atlas Ireland published by the Marine Institute and Sustainable Energy Authority Ireland. Model completed for time period run. None

As per the results of a large scale survey in 2019, the average height of Indian respondents was five feet and *** inches. Among the surveyed Indian cities, Chennai had the tallest people, whereas Hyderabad had the shortest people in the country.

Forest Elevation(Ht) Mean 2015Mean height of lidar first returns (m). Represents the mean canopy height. Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018) Wulder et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

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.

LS means with the same letter are not significantly different. Statistical comparisons are within columns only. Data used to generate Table 2 can be found in S1 Dataset.

This statistic shows the average size of families with children in Canada from 2000 to 2020. Since 2000, the average size of families with children in Canada has remained the same at 3.5 people per family.