Human Height

OWID presents work from many different people and organizations. When citing this entry, please also cite the original data source. This entry can be cited as:

Max Roser (2016) – ‘Human Height’. Published online at OurWorldInData.org. Retrieved from: https://ourworldindata.org/human-height/ [Online Resource]

# Empirical View

Human height is determined by a combination of genetics and environmental factors making it an active area of research in both the sciences and social sciences. Recent breakthroughs in sequencing the human genome have allowed identification of 697 genetic variants that influence the height of an individual.1 Although genetics plays an important role in understanding variation within a given population, human growth can be limited by poor childhood nutrition and illness. This makes height strongly correlated with living standards and hence a good proxy for them. Changes to heights over time and within countries paints a picture of economic development. One major advantage of using height as a proxy is the availability of data in the pre-statistical period.

It is important to stress that height is not used as a direct measure of well-being. In the absence of any abnormality or extremes, we should not expect that changing an individual’s height makes them any more or less happy all other things being equal.

# Global Perspective of Increase of Human Height

Human height has steadily increased over the past two centuries across the globe. This trend is in line with general improvements in health and nutrition during this period. Historical data on heights tends to come from soldiers (conscripts), convicted criminals, slaves and servants. It is for this reason much of the historical data focuses on men. Recent data on heights uses additional sources including surveys and medical records.

# Height development by world regions – Baten & Blum (2012)2
Height development by World Regions (Interpolation) – Baten & Blum (2012) 0

# The Last Two Millennia

Over the last two millennia, human height, based off of skeletal remains, has stayed fairly steady, oscillating around 170cm. With the onset of modernity, we see a massive spike in heights in the developed world. It is worth noting that using skeletal remains is subject to measurement error with respect to the estimated height and time period.

# Male heights from skeletons in Europe, 1-2000 – Clark3
Male heights from skeletons in Europe, (1–2000) – Clark

# Mesolithic Times, Middle Ages, Subsistence Societies and Modern Foragers

Though in general, human height has increased around the world, the following tables demonstrate that this trend is not universal. This first table shows the heights of men in modern foraging and subsistence societies. Many of these heights are lower than in the second table, which shows the heights of skeletal remains in various pre-modern periods. This would seem to indicate that human height is closely related to the lifestyle prevalent in a society, including the type of food consumed, the type of work undertaken, and the climate.

# Heights of adult males in modern foraging and subsistence societies – Clark (2008)4

PeriodGroupLocationAgesHeight (centimeters)
1892Plains Indians (a)United States23–49172
1970sAnbarra (b)AustraliaAdults172*
1970sRembarranga (c)AustraliaAdults171*
1910Alaskan Inuit (d)United StatesAdults170*
1890Northern Pacific Indians (e)United StatesAdults167*
1944Sandawe (f)TanzaniaAdults167*
1891Shoshona (g)United States20–59166
1970sFox Basin Inuit (c)CanadaAdults166*
1880sSolomon Islanders (h)Solomon Is.Adults165*
1906Canadian Inuitd (d)CanadaAdults164*
1969!Kung (i)Bostwana21–40163
1980sAche (j)ParaguayAdults163*
1970sHadza (c)TanzaniaAdults163*
1985Hiwi (j)VenezuelaAdults156*
1980sBatak (c)PhilippinesAdults155*
1980sAgta (c)PhilippinesAdults155*
1980sAka (c)Central African RepublicAdults155*
# Heights from skeletal remains by period, from mesolithic times until now, globally – Clark (2008)5

PeriodLocationObservationsHeight (centimeters)
Mesolithic (a)Europe82168
Neolithic (a,b)Europe190167
Denmark103173
1600–1800 ( c)Holland143167
1700–1800 ( c)Norway1956165
1700–1850 ( c)London211170
Pre-Dynastic (d)Egypt60165
Dynastic (d)Egypt126166
2500 BC (e)Turkey72166
1700 BC (f)Lerna, Greece42166
2000–1000 BC (g)Harappa, India169
300 BC–AD 250 (h)Japan (Yayoi)151161
1200–1600 (h)Japan (medieval)20159
1603–1867 (h)Japan (Edo)36158
1450 (i)Marianas, Taumako70174
1650 (i)Easter Island14173
1500–1750 (i)New Zealand124174
1400–1800 (i)Hawaii173

# The Effects of Immigration on Height Differences

In a pioneering study of Japanese immigrants to Hawaii published in 1939, Harry Shapiro found there to be a significant difference between the heights of Hawaiian-born Japanese and the Japanese immigrant population.6 Shapiro concluded that environmental factors, particularly diet and healthcare, play a significant role in determining height and other physical characteristics. The underlying idea here is that migration from poor countries to rich ones may lead to dramatic changes between generations. In a similar study, Marcus Goldstein (1943) found there to be differences in the heights and other characteristics of the children of Mexican immigrants and their parents, as well as with native born Mexican children.7

# Correlates, Determinants & Consequences

# Other Development Indicators and Human Height

Since height is used as a proxy for development, it should be strongly correlated with other indicators of development. The most common indicators of development are income, education and health.

# Correlation between (log) income per capita and height – Baten & Blum (2012)8
Correlation between (log) Income per Capita and Height – Baten & Blum (2012)0

There appears to be a very strong positive correlation between income and height.

# Wages, education and height of males in Brazil and the United States – Todaro & Smith (2011)9

 

Wages, Education, and Height of Males in Brazil and the United States – Todaro & Smith (2011)0

We see here that wages and height are positively correlated in Brazil, with a much weaker correlation in the United States. There exists a similar relationship between education and height within both countries. Differences in the compulsory schooling age between the two countries may go some way to explaining the weaker relationship found in the United States.

# Relative mortality by body height rates among Norwegian men aged 40–59, 1963–1979 – Floud, Fogel, Harris, Hong (2011)10
Relative mortality by body height rates among Norwegian men aged 40–59 in 1963–1979 – Floud, Fogel, Harris, Hong (2011)

We see a decline in the relative mortality of men aged 40-59 as height increases, suggesting that taller individuals may be healthier than their shorter counterparts.

# Why are Africans so tall?

When we exclude the richest countries from our sample we find that the positive correlation between income and height becomes negative. This result is due to Africans being significantly taller than their Asian and Latin American counterparts. Research by Deaton also finds a negative correlation exists for nutrition, risk of disease and women’s education when comparing Africa to the same group of countries. While this may appear to indicate that the difference could be down to genetic factors, Deaton argues that this is unlikely to be the case since we do not observe any significant difference between the heights of Americans of Caucasian descent compared with Americans of African descent. Instead Deaton suggests it may be due to dietary differences and child mortality. Dietary differences (vegetarian diets in Asia) and the way each respective population has adapted to poverty could generate the observed results. Additionally, higher rates of child mortality in Africa cause the smallest and weakest children to die early before reaching maturity.

# Average height and real per-capita income in year of birth – Deaton (2007)11

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# Data Quality & Definition

Accurately measuring the height of an individual is a straightforward task and so we should be confident that there is relatively little measurement error in the recorded data. This is unlikely to be the case when measuring the height of skeletons. What is more, the techniques used to date skeletal remains (such as radio carbon dating) only provide a probabilistic estimate.

Another factor to consider is the potential sample bias from the historical sources. Since the height data is largely composed of soldiers, criminals, salves and servants, these groups may not be representative of the wider population. This problem has been highlighted by academics researching human height.12 In fact, the observed drop in height during the industrial revolution — usually attributed to the negative health impacts of industrialisation — can be explained by the labour market conditions that existed at the time. They argue that “as economies grew, tight labour markets discouraged military enlistments by the most productive workers, with those enlisting (and being measured) increasingly over-representing the less advantaged members of society.”

By comparing the heights of soldiers in the US army with countries that enforced conscription we can see the bias more clearly. In countries that had conscription, the average height of conscripts was increasing over the period, meanwhile in the US where entry was voluntary, the heights of soldiers was falling

# Mean heights of volunteer soldiers in the US and in selected countries with conscription – Vox13

Mean heights of volunteer soldiers in the US and in selected countries with conscription - Vox

Another issue is that there existed almost no systematic recording of women’s heights meaning there is very little historical data on the heights of women.

# Data Sources

# Tübingen Height Data Hub
  • Data: Many different datasets on human height
  • Geographical coverage: Global
  • Time span: Some of the data goes as far back as the 17th century.
  • Available at: It is online at the University of Tübingen here.
  • The authors of this data are Jörg Baten, John Komlos, John Murray et al.

# Clio Infra project
  • Data: Heights by birth decade and country (male height equivalent in cm)
  • Geographical coverage: 165 countries
  • Time span: 1810-1989
  • Available at: Online at Clio Infra here
  • The authors are Jörg Baten (University of Tuebingen) and Mathias Blum (Technical University Munich).