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 | Over time trends for many countries
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 | PLOT Shift of BMI distribution and optimal BMI level, modern American non-Hispanic white males (solid) and Union Army veterans (dotted) – Floud, Fogel, Harris, Hong (2011)
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| TIMESERIES US BMI Trend ((non-Hispanic) white males) - (1870-2000) – Floud, Fogel, Harris, Hong (2011)
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| TABLE Changes in the body mass index of British schoolchildren, 1905–2007 – Floud, Fogel, Harris, Chul Hong (2011)
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| TABLE Changes in the height, weight, and body mass index of regular army recruits, 1860/4–1970/4 – Floud, Fogel, Harris, Chul Hong (2011)
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| TIMESERIES Average BMI, by age and birth cohort, (1800-1979) – Floud, Fogel, Harris, Hong (2011)
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| TOP Lancet study Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants
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| WORLDMAP Global obesity in 1980 and in 2008 and the change between – The Economist (Lancet Study)
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| Einer der drei Karten (die anderen beiden zeigen Level 1980 und 2008) 
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| GRAPH Age-standardized prevalence (%) of obesity (body mass index ≥30 kg/m2) among adults aged 20 years and over by WHO region, (1980 to 2008) - WHO (2012)
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| Wachsendes Problem: Von zwölf OECD-Ländern mit aktualisierten Daten hat Fettleibigkeit in den vergangenen fünf Jahren kaum irgendwo so stark zugenommen wie in der Schweiz. Insgesamt sind hier mit neun Prozent der Erwachsenen allerdings noch immer weit weniger Menschen adipös als im OECD-Schnitt.
Mehr Infos zum Thema findet Ihr unter: http://bit.ly/1wkgbbF
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| TIMESERIES Obesiy change 2002 to 2010 – Worldbank
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| Obesity in US States 1999-2009
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| Animated Map showing the increase of obesity in the US
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| USMAP & TIMESERIES Weighing in: Obesity in America (1990-2012) – The Economist
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| Men’s BMI by Age Group in the US, 1864–2009
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| Screen Shot 2015-09-11 at 16.47.32
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| TIMESERIES Obesity in the US 2008-2009 – Gallup (2011)
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| [ref]The source is: Gallup (2011) – Public Opinion 2010. Edited by Frank Newport. Rowman & Littlefield Publishers.[/ref]
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| USMAP GIF Obesity trends among US adults (1985-2010) (upload.wikimedia.org)
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| US Map of decreasing US obesity
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| TABLE Distribution of Weight Classes and Frequency of Eating Disorders in the Tyrol 1997 – Oddy, Atkins, Amilien [Eds.] (2009)
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| [ref]This is taken from Josef Nussbaumer and Andreas Exenberger – Century of hunger, Century of plenty: how Abundance Arrived in Alpine Valleys in Oddy, Atkins, Amilien (2009) – The Rise of Obesity in Europe - A Twentieth Century Food History. Ashgate E-Book.
[/ref]
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| Sources: Kinzl et al., 1998a ; Kinzl et al., 1998b.
Notes: Data from 1,000 telephone interviews (two stage random, representative) among
women and men each in the Tyrol; the definition of BES is different between men (‘binge
eating disorder, partial picture’) and women (‘binge eating syndrome’).
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| SCATTER Percentage of Obese Persons in the Population According to Age Groups in East and West Germany, 1987/88 – Oddy, Atkins, Amilien [Eds.] (2009)
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| [ref]This is taken from Oddy, Atkins, Amilien (2009) – The Rise of Obesity in Europe - A Twentieth Century Food History. Ashgate E-Book.
[/ref]
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| Source: Redrawn after Ernährungsbericht 1992, 34.
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| Ernährungsbericht 1992 [Nutrition Report], ed. by the Deutsche Gesellschaft für
Ernährung, Frankfurt a.M., 1992.
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| TABLE-TIMESERIES Percentage of Population Aged 16–64 Defined as Obese in England (1966-2007) – Oddy, Atkins, Amilien [Eds.] (2009)
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| [ref]This is taken from Oddy, Atkins, Amilien (2009) – The Rise of Obesity in Europe - A Twentieth Century Food History. Ashgate E-Book.
[/ref]
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| Sources: Comptroller and Auditor General 2001; WHO, Global Database on Body Mass
Index; UK National Statistics
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| BARCHART Many young women in developing countries are overweight – World Development Report (2007)
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| Source: Demographic and Health Surveys conducted between
2000 and 2003.
Note: Anthropometric measurements were taken for all married
and unmarried women interviewed. BMI-for-age cutoffs from a reference
population were used to classify 15- to 24-year-old women
as overweight (above the 85th percentile cutoff) and underweight
(below the 5th percentile cutoff).
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| Rights and Permissions
The material in this publication is copyrighted. Copying and/or transmitting portions or all of this work without permission may be a violation of applicable law. The International Bank for Reconstruction and Development / The World Bank encourages dissemination of its work and will normally grant permission to reproduce portions of the work promptly.
For permission to photocopy or reprint any part of this work, please send a request with complete information to the Copyright Clearance Center Inc., 222 Rosewood Drive, Danvers, MA 01923, USA; telephone: 978-750-8400; fax: 978-750-4470; Internet: www.copyright.com.
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| World maps and cross-country today
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| Adult obesity rates by country, 2009 [4500 x 2234] [OC] (i.imgur.com)
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| Obesity In Europe [1920x2054] (cliniccompare.co.uk)
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| WORLDMAP World Map of Prevalence of Obesity
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| BARCHART Obesity Rates in Selected Countries (% of adults with BMI of 30 or over) (2009) – The Economist [OECD data]
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| BARCHART Übergewichtige Kinder Anteil zwischen 5-17 Jahre – OECD cross-section
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| Zu Halloween vielleicht besser Saures? In den OECD-Ländern ist eines von fünf Kindern zu dick. In Griechenland, den USA und Italien ist etwa ein Drittel übergewichtig.
Mehr unter http://bit.ly/SuMOR6 (Health at a Glance 2011, S. 56/57)
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| INTERACTIVE-WORLDMAP & DATA World Map of Prevalence of Obesity (2002, 2005, & 2010) by Gender – Guardian
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| USMAP Mapping U.S. obesity rates at the county level
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| BARCHART Overweight + obesity - women - by age (%) - Source: Eurostat (hlth_ehis_de1)
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| TIMESERIES Growth in sugar consumption around the world (1700-2000) – Simon (1996) - The State of Humanity
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| Simon (1996) - The State of Humanity
Figure 13.5 Growth in sugar consumption around the world
Sources : France 1730-89: Robert Stein, The French Sugar Busin ess in the Eighteenth Century, Baton Rouge, Louisiana State University Press, 1988, 164. Belgium 1812 and 1846: Appendix to Geert Bekaert, "Caloric Consumption in Industrializing Belgium," Journal of Economic History, Sept. 1991. France 1790-1849 and all but Britain in 1850-99: Michael Mulhall, Dictionary of Statistics, London : George Routledge and Sons, 1899, 550. 1955: E. W. Mayo, ed ., Sugar Reference Book, vol. xxv, New York: Mona Palmer, 1957, 112-120. All other: Noel Deer, The History of Sugar, London : Chapman and Hall Ltd., 1950, 532.
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| SCATTER Undernutrition and obesity by the level of GDP per capita - WHO (2006)
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| [ref]WHO (2006) - World Health Statistics - 2006. World Health Organization. [/ref]
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| BARCHART Health Habits by BMI Category – Gallup (2011)
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| [ref]The source is: Gallup (2011) – Public Opinion 2010. Edited by Frank Newport. Rowman & Littlefield Publishers.[/ref]
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| BARCHART In the last 7 days on many days did you exercise for at least 30 minutes or more? by BMI Category – Gallup (2011)
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| [ref]The source is: Gallup (2011) – Public Opinion 2010. Edited by Frank Newport. Rowman & Littlefield Publishers.[/ref]
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| BARCHART Overweight + obesity - women (%) - by educational level - Source: Eurostat (hlth_ehis_de1)
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| BARCHART Overweight + obesity - men (%) - by educational level - Source: Eurostat (hlth_ehis_de1)
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| SCATTER Relationship between BMI and education – Schultz & Strauss (2008)
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| [ref]This is taken from a chapter iin T. Paul Schultz, John Strauss (2008) - Handbook of Development Economics, Volume 4. North Holland.
[/ref]
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| BARCHART Obesity by Education Levels - OECD Cross Section
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| OECD Statistik des Tages
Bildung macht thin! Menschen mit geringem Bildungsstand sind häufiger extrem übergewichtig als Gutgebildete. Im OECD-Schnitt sind 25 Prozent der Personen mit Abschluss 10. Klasse adipös, aber nur 13 Prozent der Uni- und Fachhochschulabsolventen.
Mehr unter http://bit.ly/16wrIXf (Education at a Glance 2013, S. 154)
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| BARCHART by Education Level and Change from 1988-94 to 2005-8
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| BARCHART Among men, obesity prevalence is generally similar at all income levels, with a tendency to be slightly higher at higher income levels: Prevalence of Obesity among adults ages 20 or olver, by poverty income ratio, sex, and race and ethnicity US (2005-8)
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| DISTRIBUTIONS&TABLE Distribution of BMI of males and females in 6 countries – Schultz & Strauss (2008)
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| Distribution of BMI in 6 countries
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| Notes. MHSS is the 1996 Matlab Health and Socioeconomic Survey (Rahman et al., 1999). CHNS is the
1991 wave of the China Health and Nutrition Survey (Popkin, 1993). IFLS is the 2000 wave of the Indonesia
Family Life Survey (Frankenberg and Karoly, 1995; Frankenberg and Thomas, 2000; Strauss et al., 2004).
SADHS is the 1998 South African Demographic Health Survey (Demographic and Health Surveys, 2002).
MxFLS is the 2002 wave of the Mexican Family Life Survey (Rubalcava and Teruel, 2004). NHANES III is
the National Health and Nutrition Examination SurveyWave III (National Center for Health Statistics, 1994).
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| [ref]This is taken from a chapter iin T. Paul Schultz, John Strauss (2008) - Handbook of Development Economics, Volume 4. North Holland.
[/ref]
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| SCATTER Obesity by Age – Gallup
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| Nineteenth Century and Modern Black and White BMI distributions
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| BARCHART Obesity in the United States by Age, Gender, and Race/Ethnicity – Gallup (2011)
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| [ref]The source is: Gallup (2011) – Public Opinion 2010. Edited by Frank Newport. Rowman & Littlefield Publishers.[/ref]
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| SCATTER Obesity in the United States, by Age and Race – Gallup (2011)
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| [ref]The source is: Gallup (2011) – Public Opinion 2010. Edited by Frank Newport. Rowman & Littlefield Publishers.[/ref]
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| Quote: The wholesome foodies don’t argue that obesity and class are unrelated, but they frequently argue that the obesity gap between the classes has been created by the processed-food industry, which, in the past few decades, has preyed mostly on the less affluent masses. Yet Lenard Lesser, a physician and an obesity researcher at the Palo Alto Medical Foundation Research Institute, says that can’t be so, because the obesity gap predates the fast-food industry and the dietary dominance of processed food. “The difference in obesity rates in low- and high-income groups was evident as far back as we have data, at least back through the 1960s,” he told me. One reason, some researchers have argued, is that after having had to worry, over countless generations, about getting enough food, poorer segments of society had little cultural bias against overindulging in food, or putting on excess pounds, as industrialization raised incomes and made rich food cheaply available.
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| SCATTER Comparison of relative risk of loweconomic productivity (non labor force participation and poverty) by BMI and relative wealth and earnings by height, modern non-Hispanic white American males and Union Army veterans – Floud, Fogel, Harris, Hong (2011)
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| My Source: Roderick Floud, Robert W. Fogel, Bernard Harris, Sok Chul Hong (2011) - The Changing Body Health, Nutrition, and Human Development in the Western World Since 1700
Original Source: Estimated from the Union Army veterans’ datasets and the 1997–2006
NHIS datasets.
Notes: Each BMI group’s relative risk of non-LFP is measured by the group’s
proportion of population not in the labor force divided by the average LFP rate of the
entire sample. The poverty rate is calculated as the proportion of samples whose
reported earnings are below each year’s poverty line. Each BMI group’s relative risk
of poverty is measured by the group’s poverty proportion divided by the average
poverty rate of the entire sample. We use modern Americans at ages 40 to 59. For
nineteenth-century comparison, we searched for Union Army veterans in the 1900
US federal census, and used the variable of occupation in the census records. To
look into the relationship between height and wealth in the nineteenth century, we
searched for veterans found in the 1860 US federal census, and use the sum of
real estate and personal property wealth. Their height was measured at the time
of enlistment.
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| SCATTER Comparison of relative risk of low economic productivity (non labor force participation and poverty) by BMI and relative wealth and earnings by height, modern non-Hispanic white American males and Union Army veterans
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| COMPLEX-GRAPH Waaler surface of the relative mortality risk for height and weight among Norwegian males aged 50–63 with a plot of estimated French and English heights and weights since 1700 at ages 25–39 – Floud, Fogel, Harris, Hong (2011)
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| My Source: Roderick Floud, Robert W. Fogel, Bernard Harris, Sok Chul Hong (2011) - The Changing Body Health, Nutrition, and Human Development in the Western World Since 1700
Original Source: French: The data points for 1705 and 1785 are based on the discussion in
Section 3.3 of Chapter 3. For 1867 and 1967 see Figure 2.4 in Fogel 2004b; the point
for 1867 is from Baxter 1875, 1: 58–59; the point for 1967 is from Eveleth and Tanner
1976. The height for the 1990 data point is from Cavelaars et al. 2000; the BMI for
1990 is assumed to be the same as the 1980 BMI in Rolland-Cachera et al. 1991.
Source British: The data points for 1700 and 1800 are based on the discussion in Section
3.5 of Chapter 3. For a brief description of the procedure used to estimate the
British point for 1800, also see Fogel 1997. Points for 1838, 1878, 1923, and 1978
are from Floud 1998, Table 6. The points for 1993 and 2001 are from the Health
Survey for England (see Tables 4, 5, and 6 at www.doh.gov.uk/stats/trends1.htm).
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| SCATTER Comparison of relative mortality risk with BMI among men 50 years of age, Union Army Veterans around 1900 and Modern Norwegians. (source: Costa & Steckel, 1997) – Rodrik & Rosenzweig (2010)
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| Note: in the Norwegian data, BMI for 79,084 men was measured at ages 45-49, and the period of risk was 7 years.
BMI of 550 Union Army Veterans was measured at ages 45-64, and observation period was 25 years.
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| [ref]This is taken from a chapter in Dani Rodrik & Mark R Rosenzweig (2010) - Handbook of development economics. Volume 5. Elsevier. North-Holland.
[/ref]
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| TIMESERIES Relative risk of mortality as estimated from Union Army survival sample US white males age 50-59 about 1870, and NHANES-I, US white males age 50-59 about 1972 – Rodrik & Rosenzweig (2010)
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| source: Su, 2005, Tables 4-6 and Figure 4; model 1 reported based on all deaths).
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| [ref]This is taken from a chapter in Dani Rodrik & Mark R Rosenzweig (2010) - Handbook of development economics. Volume 5. Elsevier. North-Holland.
[/ref]
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| SCATTER The relationship between BMI and prospective risk among Norwegian adults aged 50-64 at risk between 1963 and 1979 – Simon (1996)
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| Simon (1996) - The State of Humanity
Figure 5.4 The relationship between BMI and prospective risk among Norwegian adults aged 50-64 at risk between 1963 and 1979
Source: Waaler (1984). -- Waaler, Hans Th. (1984): "Height, Weight and Mortality: The Norwegian Experience." Acta Medica Scandinana supplement no. 679. Stockholm.
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| TIMESERIES Relative morbidity risk by BMI among Union Army veterans at ages 40 to 59 and relative risk of activity limitation by BMI among modern American non-Hispanic white males at ages 40 to 59 – Fogel & Grotte (2011)
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| SCATTER Comparison of relative and absolute mortality risk by height and BMI at ages 40–59, modern American non-Hispanic white males (solid) and Union Army veterans (dotted) – Floud, Fogel, Harris, Hong (2011)
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| SCATTER Relationship between BMI and prospective risk among Norwegian adults aged 50–64 at risk (1963–1979) – Floud, Fogel, Harris, Hong (2011)
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| SCATTER Relative risk of mortality, morbidity, and poverty by BMI among modern Americans at ages 40–59 in 1986–1992, non-Hispanic white (solid), Hispanic (dashed), and black (small dashed) – Floud, Fogel, Harris, Hong (2011)
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| Older adults - Build muscle and you'll live longer: New research suggests that older adults with more muscle mass are less likely to die prematurely. The findings add to the growing evidence that overall body composition - and not body mass index (BMI) - is a better predictor of all-cause mortality
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| Quote: a study published in February in the journal Obesity found that obese young adults and middle-agers in the U.S. are likely to lose almost a decade of life on average, as compared with their non-obese counterparts.
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| BARCHART Prevalence of Chronic Conditions by BMI Category – Gallup (2011)
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| [ref]The source is: Gallup (2011) – Public Opinion 2010. Edited by Frank Newport. Rowman & Littlefield Publishers.[/ref]
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| – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
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| Measurement, Data Quality & Definitions
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| DEFINITION Body mass index (BMI) – FAO (2013)
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| Body mass index (BMI). The ratio of weight-for-height measured as the
weight in kilograms divided by the square of height in metres.
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| [ref]This is the definition in FAO, IFAD & WFP (2013) – The State of Food Insecurity in the World 2013 - The multiple dimensions of food security, Food and Agriculture Organization of the United Nations (FAO), the International Fund for Agricultural Development (IFAD) or of the World Food Programme (WFP), FAO, Rome, 2013. Online here.http://www.fao.org/publications/sofi/en/[/ref]
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| FAO DEFINITION for Overnourished population' Share of population with food intake that is in excess of maximum dietary energy requirements continuously. FAO. 2003. Proceedings Measurement and assessment of food deprivation and undernutrition. International Scientific Symposium Rome, 26-28 June 2002. An Inter-agency Initiative to Promote Information and Mapping Systems on Food Insecurity and Vulnerability (FIVIMS). Rome.
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| Correlates, Determinants, & Consequences
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| – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
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| DATA-SOURCE World Health Organization (WHO), Global Database on Body Mass Index which is online here and where the data can be mapped, graphed as timeseries and downloaded. http://apps.who.int/bmi/index.jsp
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| Prevalence of overweight (% of children under 5) Explore in World DataBank
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 new child growth standards released in 2006.
Code: SH.STA.OWGH.ZS Database: WDI Topic: Health,Nutrition
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| DATA Sugar per person (1961-2004) - Gapminder
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| DATA Body Mass Index (1980-2008) - through Gapminder (health->Risk Factors)
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| – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
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