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From Undernutrition to Overnutrition: The Evolution of Overweight and Obesity among Young Men in Switzerland since the 19th Century

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Obesity Facts
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Objective: The global obesity epidemic continues, new approaches are needed to understand the causes. We analyzed data from an evolutionary perspective, stressing developmental plasticity. Methods: We present diachronical height, weight, and BMI data for 702,902 Swiss male conscripts aged 18-20 years, a representative, standardized and unchanged data source. Results: From 1875 to 1879, the height distribution was slightly left-skewed; 12.1% of the conscripts were underweight, overweight and obesity were rare. The BMI-to-height relationship was positive but not linear, and very short conscripts were particularly slim. Since the 1870s, Swiss conscripts became taller, a trend that markedly slowed in the 1990s. In contrast, weight increased in two distinct steps at the end of the 1980s and again after 2002. Since 2010, BMI did not increase but stabilized at a high level. Conclusions: The body of young men adapted differently to varying living conditions over time: First, less investment in height and weight under conditions of undernutrition and food uncertainty; second, more investment in height under more stable nutritional conditions; third, development of obesity during conditions of plateaued height growth, overnutrition, and decreasing physical activity. This example contributes to the evaluation of hypotheses on human developmental plasticity.
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© 2016 The Author(s)
Published by S. Karger GmbH, Freiburg
Original Article
Obes Facts 2016;9:259–272
From Undernutrition to Overnutrition: The
Evolution of Overweight and Obesity among
Young Men in Switzerland since the 19th
Century
Kaspar Staub
a, b Nicole Bender
a, c Joël Floris
a, d Christian Pfister
b
Frank J. Rühli
a
a Institute of Evolutionary Medicine, University of Zurich, Zurich , Switzerland;
b Institute of
History, University of Bern, Bern , Switzerland;
c Institute of Social and Preventive Medicine,
University of Bern, Bern , Switzerland;
d Department of Economics, University of Zurich,
Zurich , Switzerland
Abstract
Objective: The global obesity epidemic continues, new approaches are needed to understand
the causes. We analyzed data from an evolutionary perspective, stressing developmental
plasticity. Methods: We present diachronical height, weight, and BMI data for 702,902 Swiss
male c onscripts aged 18 –20 years , a representative, standardized and unchanged data source.
Results: From 1875 to 1879, the height distribution was slightly left-skewed; 12.1% of the con-
scripts were underweight, overweight and obesity were rare. The BMI-to-height relationship
was positive but not linear, and very short conscripts were particularly slim. Since the 1870s,
Swiss conscripts became taller, a trend that markedly slowed in the 1990s. In contrast, weight
increased in two distinct steps at the end of the 1980s and again after 2002. Since 2010, BMI
did not increase but stabilized at a high level. Conclusions: The body of young men adapted
differently to varying living conditions over time: First, less investment in height and weight
under conditions of undernutrition and food uncertainty; second, more investment in height
under more stable nutritional conditions; third, development of obesity during conditions of
plateaued height growth, overnutrition, and decreasing physical activity. This example con-
tributes to the evaluation of hypotheses on human developmental plasticity.
© 2016 The Author(s)
Published by S. Kar ger GmbH , Freibur g
Received: March 11, 2016
Accepted: May 16, 2016
Published online: August 20, 2016
Dr. Kaspar St aub
Institute of Evolutionary Medicine
University of Zurich
Winter thurerstrasse 190, 8 057 Zurich, Switzerland
kaspar.staub
@ iem.uzh.ch
www.karger.com/ofa
DOI: 10.1159/000446966
This article is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Interna-
tional License (CC BY-NC-ND) (http://www.karger.com/Services/OpenAccessLicense). Usage and distribu-
tion for commercial purposes as well as any distribution of modified material requires written permission.
Kaspar Staub and Nicole Bender contributed equally to this work (first authorship).
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Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
Introduction
Obesity has been a major public health issue worldwide and an important contributor to
the global burden of chronic disease and disability for decades [1, 2] . Obesity is associated
with several deleterious outcomes, such as type 2 diabetes, heart disease, depression,
increased all-cause mortality, and reduced life expectancy [3–5] . In 2014, 1.9 billion adults
worldwide were overweight, and it has been projected that these numbers will continue to
increase until the year 2030 [6] . In Switzerland, 41% of the adult population and 19% of
children and juveniles are currently overweight or obese [7] . Obesity and its associated
comorbidities were responsible for 11% of the Swiss healthcare expenditures in 2006, repre-
senting a considerable economic and public health burden [8] . Efforts to control the epidemic
of obesity by the World Health Organization consist of a range of long-term measures,
including primary prevention, weight maintenance, management of complications, and
weight loss [1] . However, the global obesity epidemic continues despite these measures, indi-
cating that new approaches are needed to understand not only how humans are becoming
more obese but also why.
In the past few decades, attempts have been made to explain the human susceptibility to
obesity from an evolutionary perspective [9–12] . The aim of evolutionary investigations of
human obesity is to understand the underlying ultimate causes of this trait and to gain insight
into novel approaches to obesity prevention and control. While several hypotheses have
focused on the evolution of human fat tissue at an early stage of human evolution, several
other hypotheses have been formulated to explain the variance in human obesity between
and within modern human populations. One of the first was the ‘thrifty gene’ hypothesis,
which explained the selection of gene variants that are advantageous in periods of famine but
at the same time predispose humans to obesity and related health issues in modern times of
plenty [13] . This hypothesis has been debated, and alternative explanations have been formu-
lated, such as the ‘developmental origins’ hypothesis, which emphasizes epigenetic and other
maternal effects in the pre- and postnatal period of life as a ‘fine-tuning’ mechanism to adapt
to a predicted environment [14] . This short-term adaptability to fast changes in the envi-
ronment is well described in many animal species [15] and has also been demonstrated in
human populations [16] .
Hypotheses on the evolutionary origins of human adiposity are primarily based on animal
studies or theoretical considerations, and human data to test them, especially historical data,
are sparse. Because weight measurement and personal scales were uncommon before the
1880s [17, 18] , there are only few studies assessing long-term trends in BMI distribution in
large human populations [19] or changes in the BMI to height relationship [20–23] . In this
study, we present BMI data of Swiss male conscripts, a representative, standardized and
unchanged data source spanning the past 140 years. We analyze temporal changes in height,
weight, and BMI from 1875 to 2014 and use these data to explore if historical events that
influenced food security and abundance in Switzerland had an impact on the BMI of young
Swiss men in the same time period or at the time of birth 19 years before.
The present paper contributes to the understanding of short-term (historical) develop-
ments of height and weight in a male human population during the transition from the 19th
century, a time of food uncertainty, to a modern, Western society. This knowledge can inform
our understanding of human developmental plasticity and may therefore contribute to the
critical evaluation of hypotheses on human short-term adaptability to changes in living stan-
dards, improved disease environment, and food availability and quality.
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DOI: 10.1159/000446966
Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
Subjects and Methods
Conscript Data in Public Health Research
Finland, Norway, Denmark, Austria, and Switzerland are currently the only countries in Western Europe
that continue to rely on full, regular conscription [24] . The anthropometric data collected during conscription
yield an annual picture of the anthropometric health status of young men at a prescribed age [25] . Despite
being limited to young male populations, the anthropometric status of conscripts is a particularly valuable
tool for public health research for two reasons: first, being obese in adolescence increases the risk of being
obese as an adult; and second, the morbidity and mortality risks associated with obesity in men in particular
increase with age [26] .
The Swiss Conscription Process
Since 1875, all 19-year-old male Swiss citizens have been conscripted for military duty and undergo a
medical examination for military fitness [27] ; this examination was and still is based on detailed standardized
rules and instructions [28] . The medical commission maintained annual detailed control books containing
measurements for each conscript [29] . The height and weight measurement procedure has remained
unchanged over time, which further assures the validity and comparability of the analyzed datasets. The
height and weight of each conscript while in underpants, including those who subsequently received an
exemption, were measured by two physicians based on specific measurement regulations and identical stan-
dards that did not change over time. By regulation, weight was only measured from 1875 to 1879 and again
after 1932.
The mandatory, multiple-day recruitment of the Swiss Armed Forces was renewed and expanded in
2004 [30, 31] . The regulations still specify that all young men are summoned for conscription during the year
in which they turn 19. However, conscription either before or after this year is possible upon request. The
assessment still collects data on anthropometric status (measured height and weight, rounded to integers)
as well as other data. These assessments, which are mandatory for every conscript regardless of if they subse-
quently receive a deferral or an exemption, are conducted under professional medical supervision at six
dedicated conscription centers (Lausanne, Sumiswald, Windisch, Rüti, Mels, and Monte Ceneri) that have
identical qualitative standards for technical equipment and organizational structures (Verordnung über die
Rekrutierung (VREK), 511.11, Art. 3 and Art. 9).
Data Sources
By systematic inquiries at all of the cantonal State Archives, we located each control book containing the
medical examinations for the 1875–1879 conscription years that existed in Switzerland. An existing dataset
from an earlier publication [32] (which included full cohorts from the cantons Basel-Stadt, Basel-Land, Bern,
Zürich) was thereby substantially expanded (by a factor of 2.7 for 1875–1879 and by 1.2 for the 1930s) by
the addition of full conscription cohorts from three other cantons: Geneva, Valais, and Solothurn (various
cantons did not archive the control books of the medical examination of conscripts until recently). Thus, the
1875–1879 dataset used in this study contains every surviving weight measurement taken during conscription
in Switzerland at that time. Overall, the regional selection of our historical data is driven by data existence
(1875–1879) or availability (the 1930s). However, to improve reliability, our selection includes rural and
urban as well as German- and French-speaking cantons of Switzerland. For the conscription years from 1952
to 1987, only quinquennial average height and weight values from official publications of the Swiss Federal
Statistical Office [33–35] exist. Anonymous, individual conscription records from 1992 to 2014 were provided
by the Swiss Armed Forces (Logistikbasis der Armee – Sanität, (LBA San)) under contractual agreement with
the study authors. The data consisted of date of birth, date of conscription, height, weight, and stage of
conscription (NIAX code ‘S’ for first, regular visit versus reassessment).
Data Availability and Ethics Statement
The individual historical data from 1875 to 1879 and 1933 to 1939 were accessed and transcribed in
anonymized form from control registers in the Cantonal State Archives after receiving permission to inspect
them and completing signed data protection contracts. The data from 1992 to 2014 and the permission to
use them are available from the Swiss Armed Forces (LBA San) upon submission and approval of a study
protocol. According to the signed bilateral data contract, the Swiss Armed Forces fully anonymized the
records by removing all names, social security numbers, and residential addresses prior to delivering the
data. Because Swiss conscription is mandatory and the anthropometric measurements used in this study
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Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
were nonclinical, government data, informed consent was not required. According to Swiss federal law
(Bundesgesetz über die militärischen Informationssysteme (MIG), BG 510.91, Art. 2, 9, 24–29), the Swiss
Armed Forces are authorized to make the data accessible in anonymous form for academic research. In the
case of analyses based on anonymized and nonclinical government data, additional ethical approval is not
needed (Swiss data privacy act, SR 235.1; 19.6.1992 and Federal Act on Research involving Human Beings
HRA, 810.30; 1.1.2014) [30, 31] .
Data Preparation
The 1875–1879 dataset initially contained 9,589 conscripts. We excluded four conscripts younger than
18 years, 999 conscripts older than 21 years, 107 conscripts whose height was not recorded, 10 conscripts
with a stature below 130 cm, and 955 conscripts whose weight was missing. The cleaned 1875–1879 dataset
contained 7,514 conscripts. The 1932–1939 dataset contained 16,163 conscripts after transcription; 8
conscripts younger than 18 years, 595 conscripts older than 21 years, 102 conscripts with missing height,
1 conscript with a stature below 130 cm, and 7 conscripts without a recorded weight were excluded. In the
end, the 1932–1939 dataset included 15,450 conscripts. The modern data sample from 1992 to 2014 was
delivered containing 877,897 conscripts. We excluded 166 double entries, 6,489 women (who joined the
Army voluntarily), 87,074 men with a NIAX conscription status other than ‘S’ (for regular first time
appearance), 22 conscripts without a recorded age, 4,537 conscripts younger than 18 years of age, 73,054
conscripts older than 21 years, 26,530 conscripts without a recorded height (all of them before 2004), 45
conscripts below 130 cm, 12 conscripts taller than 215 cm, 23 conscripts with missing weight data, and 7
conscripts lighter than 30 kg. In the end, the modern dataset contained 679,938 conscripts. The overall
dataset analyzed in the present study included individual height, weight, and BMI data for 702,902 conscripts
aged 18 to 20 years. If we add the more than 241,828 conscripts (no sample size available for 1952) whose
height and weight was analyzed and aggregated in the official publications by the Swiss Federal Statistical
Office from 1952 to 1987, the total number of conscripts analyzed in this publication totals almost one
million.
For the individual data, BMI was calculated as BMI = weight (kg) / height squared (m
2 ) and was then
categorized using the World Health Organization (WHO) classifications [36] . For the published data from
1952 to 1987, we calculated the average BMI from the average height and average weight (supplementary
table S1, available at http://content.karger.com/ProdukteDB/produkte.asp?doi=446966 ). Comparisons with
the individually calculated BMI of the 1930s and again after 1992 showed that an overestimation of the indi-
vidually calculated average BMI may have occurred by only 0.02–0.03 kg/m
2 (supplementary table s4, last
column, available at http://content.karger.com/ProdukteDB/produkte.asp?doi=446966 ). The standard devi-
ation (SD) of the height and weight for the average data from 1952–1987 were estimated from the individual
data from the1930s and early 1990s to calculate the 95% confidence intervals (95% CIs) (supplementary
table S1, available at http://content.karger.com/ProdukteDB/produkte.asp?doi=446966 ). For the historical
data from 1875 to 1879 and 1932 to 1939, we calculated age at conscription in integer numbers as the
difference between an individual’s year of conscription and year of birth. The distribution of the age groups
(supplementary table S2, available at http://content.karger.com/ProdukteDB/produkte.asp?doi=446966 )
showed that until 1939, the large majority of the conscripts (>80%) were 19 years old when measured. For
the modern data, we calculated age at conscription from the date of birth and date of conscription and cate-
gorized it into three 1-year intervals from 18–19 to 20–21 years of age. The age group distribution showed
that for the modern data, the percentage of the 19-year-old conscripts decreased to >45% (still the largest
age group), and the proportion of conscripts who were 18 or 20 years old at conscription increased because
of the new regulations allowing earlier and later conscription. However, there was a slight tendency towards
an older age at conscription for the most recent conscription years (mean age at conscription was 19.0 years
in 1994 versus 19.3 years in 2014).
R e p r e s e n t a t i v e n e s s
Earlier studies on similar datasets have suggested that the register books for 1875–1879 contain nearly
complete birth cohorts [32, 37] and that the modern data has maintained high coverage (>95% of the living
young Swiss men) [30] . The 5% in absentia exemptions were not restricted to short or obese young men only
but covered the full range of chronic diseases and physical and psychological disabilities not necessarily
related to height or weight [38] .
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DOI: 10.1159/000446966
Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
S t a t i s t i c s
We primarily used descriptive statistics (means with 95% CIs, medians, SDs, skewness etc.) to analyze
the data as well as graphical methods (kernel density estimations and quantile-quantile plots) to observe
changes in the shape of the distributions. Because of the large size of the dataset, only minimal methods (two
sample t-tests with equal variance) were applied to test the differences between means. In the case of the
BMI-to-height relationship, we applied local polynomials to smooth the BMI means from the full height
scatter plots. In order to numeralize this relationship and similar to other studies [20, 21] , we additionally
performed a linear regression with 10 cm height categories as dummy variables to model the changes over
time. All of the analyses and graphs were performed using Stata (version 13; Stata Corp., College Station, TX,
USA).
Results
Over the 135 years of observation, Swiss conscripts became on average significantly taller
by 13.57 cm (95% CI 13.40–13.74 cm; t(40485) = 100; p = 0.0000), from 164.78 cm (95% CI
164.62–164.94 cm) in 1875–1879 to 178.35 cm (95% CI 178.28–178.42 cm) in 2014. The
average weight increased by a total of 17.99 kg (95% CI 17.68–18.29 kg; t(40485) = 110; p =
0.0000) from 56.17 kg (95% CI 56.00–56.34 kg) in 1875–1879 to 74.16 kg (95% CI 74.02–
74.30) in 2014. Consequently, the average BMI also significantly increased by 2.66 kg/m
2 (95%
CI 2.57–2.75 kg/m
2 ; t(40484) = 59.34; p = 0.0000), from 20.63 kg/m
2 (95% CI 20.59–20.67
kg/m
2 ) in 1975–79 to 23.29 kg/m
2 (95% CI 23.25–23.33 kg/m
2 ) in 2014 (supplementary table
S4, available at http://content.karger.com/ProdukteDB/produkte.asp?doi=446966 ) .
These trends were not linear. The average height increased by 1.9 cm per decade between
the 1952–1962 conscription years, by 1.5 cm per decade between 1962 and 1972, by 1.4 cm
per decade between 1972 and 1982, and by 1.3 cm between 1982 and 1992 (birth years
1963–1973). After the 1970s birth years, the positive height trend markedly slowed (0.0 cm
increase per decade between the 1992–2002 conscription years and 0.9 cm per decade
between 2002 and 2012). In contrast to height, the trend in average weight – which for a long
time increased in parallel with height (supplementary fig. 1, available at http://content.
karger.com/ProdukteDB/produkte.asp?doi=446966 ) – did not slow up in recent decades but
increased in two strong steps, one at the end of the 1980s conscription years and again after
2002. These height and weight changes were reflected in the average BMI, which was stable
during the second half of the 20th century and then mirrored the two large increases in weight
approximately 1990 and after 2002 ( fig. 1 ). During the last 3–4 conscription years after 2010,
the average BMI no longer increased but stabilized on a high level. An age sensitivity test
showed that the observed pattern was stable for the 19-year-old conscripts only (the largest
age group) ( fig. 1 ).
Not only did the averages change over time, but the shape and the position of the distri-
butions did as well. Height, which was slightly left-skewed (–0.35) in the 1875–1879 data,
mainly shifted upwards on the x-axis over time and was symmetrically distributed ( fig. 2 , left
side). In contrast, weight and BMI – also almost symmetrically distributed in 1875–1879 and
1933–1939 – became increasingly right-skewed in 1994 and 2014 (supplementary table S4,
available at http://content.karger.com/ProdukteDB/produkte.asp?doi=446966 ). Although the
lower end of the BMI distribution hardly changed between the 1930s and 1994; the upper
quantiles became increasingly higher ( fig. 2 , right side).
Accordingly, the prevalence of underweight, overweight, and obesity changed. From
1875 to 1879, 12.1% of the conscripts were underweight (BMI<18.5 kg/m
2 by modern WHO
definition) at conscription, whereas overweight (1.6%) and obesity (0.1%) were barely prev-
alent (supplementary table S3, available at http://content.karger.com/ProdukteDB/produkte.
asp?doi=446966 ). From 1933 to 1939, 91.3% of the conscripts had a normal weight, under-
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DOI: 10.1159/000446966
Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
1
(For legend see next page.)
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Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
Fig. 2. The change in the height, weight, and BMI distributions over time (left graph) and a Quantile-Quantile
(QQ) plot of the BMI distributions from 1875–1879, 1994, and 2014 against the 1933–1939 distribution to
illustrate the change in shape at the upper tails of the modern distributions (right graph).
Fig. 1. The change in average height, weight and BMI for 18- to 20-year-old young men in Switzerland be-
tween 1875–1879 and 2014. Grey areas = 95% CIs, orange line = sensitivity analysis: 19-year-old conscripts
only, 1952–1987 = published data only.
Fig. 3. The shift in direction of the mean BMI-to-height relationship over time. Smoothing method = Local
Polynomials, Grey area = 95% CIs, red dashed line = linear regression line, vertical grid lines = 5th, 50th, and
95th height percentiles.
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Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
weight was reduced to 4.9%, and only a total of 3.8% had a BMI 25.0 kg/m
2 . In 1994, after
the first large increase in average BMI, the prevalence of overweight had increased to 11.8%
and obesity to 2.5%. Finally, between 1994 and 2014, overweight was multiplied by a factor
of 1.56 to 18.4% and obesity by a factor of 2.28 to 5.7%. Overall, a total of 24.1% of the young
men appearing at conscription in 2014 had a BMI 25 kg/m
2 .
The BMI-to-height relationship changed direction over time ( fig. 3 ). In 1875–1879, the
relationship was positive between the 5th and the 90th percentiles (the taller the conscripts,
the higher their BMI). The relationship was stable for the conscripts above the 90th height
percentile (no higher BMI). For the very short conscripts below the 5th height percentile, the
positive BMI-to-height relationship became even more pronounced; they were not only very
short but also very slim. From 1933 to 1936, the general direction of the BMI-to-height rela-
tionship changed direction and was negative above the 5th height percentile (the taller the
conscripts, the lower their BMI). In contrast, very short conscripts below the 5th height
percentile were still significantly slimmer. In 1994 and 2014, the general BMI-to-height rela-
tionship stayed negative, but the double burden (very short conscripts also being very slim)
at the lower end of the height distributions had disappeared. The linear regression confirmed
the direction and the significance of the coefficients ( table 1 ).
Discussion
This study analyzed the most recent anthropometric data available from mandatory
conscription in Switzerland from 1992 to 2014 and incorporated it into the historical context
from 1875 to 1879 to assess temporal changes. In general, Swiss conscripts changed their
growth pattern from first growing in length to then growing mainly in width. Over the 135
years analyzed, Swiss conscripts became significantly taller by an average of 13.57 cm, from
164.78 cm in 1875–1879 to 178.35 cm in 2014. This increase in average height started in the
1870s birth years and markedly slowed after the 1970s birth years. In contrast to height, the
increase in average weight did not decelerate during the last two to three decades but
increased in two distinct periods at the end of the 1980s and again after 2002. The weight and
BMI distributions became increasingly right-skewed, and the share of overweight and obese
young men increased to 18.4% and 5.7%, respectively, in 2014. From 1875 to 1879, the BMI-
to-height relationship was positive (the taller the conscripts the higher their BMI), and very
short conscripts were also very slim, indicating a double burden of undernutrition.
The positive trend in average height in general and among the Swiss conscripts in
particular has been well documented [38, 39] . Among other clustering co-factors (positive
assortative pair mating, epigenetics), greatly improved living conditions (nutrition, disease
environment, and physical workloads) may be primarily responsible for the secular height
trend [40, 41] . During the 1870s, when the positive trend started, the Swiss railway system
became international, allowing authorities to balance the shortages in food supply by
importing cheap mass products [42] . Consequently, the historic price index became more
stable and less volatile, while the historic wage index continued to increase ( fig. 4 , left side)
[43] . As a result, real wages increased, more money was available to families for nutrition,
and the daily per capita caloric intake increased from 2,601 kcal in 1870 to 3,041 kcal in 1912
[44] . In recent decades, the rate of increase in height has markedly slowed in Central and
Northern Europe. The current consensus in the literature is that because of the Central and
Northern European countries’ stable environments, the genetic endpoint of the population
has been reached at a mean level of 178–180 cm [39, 45] .
The relatively strong left-skewness of the height distribution (short men being overrep-
resented) and the 12.1% prevalence of underweight young men at conscription in the late
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DOI: 10.1159/000446966
Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
Table 1. Linear regression results of BMI per height category
Height
category
1877 1936 1994 2014
N coef. SE P>|t| N coef. SE P>|t| N coef. SE P>|t| N coef. SE P>|t|
130–139 16 –1.02 0.49 0.036 5 –3.58 0.86 <0.001
140–149 142 –2.14 0.17 <0.001 27 –2.1 6 0.37 <0.001 2 –0.88 2.15 0.684 1 1.02 3.77 0.787
150–159 1,409 –0.35 0.06 <0.001 631 –0.27 0.08 0.001 88 –0.06 0.33 0.859 68 0.43 0.46 0.347
160–169 4,131 reference 6,033 reference 2667 0.18 0.06 0.005 2,632 0.14 0.08 0.080
170–179 1,712 0.1 0.06 0.067 7,567 –0.17 0.03 <0.001 13,152 reference 16,155 reference
180–189 104 0.04 0.19 0.825 1,153 –0.42 0.06 <0.001 8,110 –0.18 0.04 <0.001 12,588 –0.06 0.04 0.174
190–199 32 –1 0.34 0.003 803 –0.4 0.11 <0.001 1,481 –0.08 0.1 0.460
>200 2 –1.42 1.36 0.298 13 –0.95 0.84 0.260 47 0.09 0.55 0.868
cons 20.72 0.03 <0.001 21.61 0.02 <0.001 22.33 0.03 <0.001 23.3 0.03 <0.001
N 7,514 15,450 24,835 32,972
R-squared 0.0277 0.0073 0.0018 0.0002
Adj R-sq 0.0271 0.0069 0.0016 0.0001
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19th century both indicate that malnutrition was common at the eve of the secular height
trend [38] . This may be one of the causes of the positive BMI-to-height relationship and the
dual burden of malnutrition (both short and thin) at the lower end of the height distribution
in the 1875–1879 conscripts. That the tall 5% conscripts did not have higher BMI values may
be explained by the fact that it may have been more difficult for taller people to obtain enough
calories [21] . The relatively low living standard in Switzerland is also reflected in having real
wages that were lower than those of other European countries at the end of the 19th century
[46] . It was only until the First World War when Switzerland witnessed less volatile prices
and matched the height and wage level of other countries in Central Europe [38] . Until the
conscription years in the 1980s, average height and weight increased in parallel.
This study adds to the literature that the obesity epidemic in Switzerland started at the
end of the 1980s, proceeded in two strong upward steps, and stabilized in the last 3–4
conscription years. The first upward step at the end of the 1980s coincided with the intro-
duction of American fast food restaurants [47, 48] and a marked price reduction of fuel in
Switzerland ( fig. 4 , right side); this suggests that the nutritional and physical activity patterns
may have changed during that period. The most recent high-level BMI stabilization mirrors
the results from recent studies on Swiss schoolchildren [49] .
The deviation from 2000 to 2002 in conscripts’ average weight and BMI cannot currently
be explained. Further tests have shown that the entire weight distribution was affected. The
medical service of the Swiss Armed Forces ensured that the measurement standards (cali-
brated scales, cantonal sample composition, sample size etc.) did not change during the 3
Fig. 4. Swiss historic consumer price and wage index from 1850–1910 (left graph, (1,850 = 100%, source:
SWISTOVAL [43, 46, 61] )) and deflated prices (CHF from 2010) for regular and unleaded petrol in Switzer-
land from 1977–2005 (right graph, source: Swiss Federal Statistics [62, 63] ).
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years under question. Potential explanations must be sought either regarding the data
(artifact etc.) or regarding environmental factors (at the time of birth or conscription);
however, no explanations are known at the moment. Furthermore, no dataset from other
Swiss sources or from conscription in neighboring countries can be used for comparison
because of their lack of annual precision.
The phenomenon of the stabilizing secular height trend and the incipient obesity epidemic
can also be observed 30 years earlier in the USA [19, 50] . The levels of obesity (BMI 30 kg/m
2 )
among conscripts in 2010 and 2011 were slightly lower in Switzerland (5.8%) compared to
other European countries with mandatory conscription (Germany 8.5%, Denmark 8.7%, and
Austria 8.4%) [51, 52] .
From the evolutionary perspective, our results are compatible with a plastic human
growth and weight change response to changing environmental conditions. These results are
consistent with hypotheses on fetal programming [53] , epigenetic effects on the genotype
[54] , and transgenerational maternal effects [55] . Our data do not enable the distinction
between these developmental mechanisms, and further studies are needed to investigate this
point. However, we did confirm that short-term adaptations in humans can occur. Specifi-
cally, we showed how the bodies of young men adapted differently to opposing living condi-
tions in Switzerland, with less investment in height and weight under conditions of undernu-
trition, an investment in increasing height under more stable nutritional conditions, and an
increase in weight and the development of obesity under conditions of overnutrition and
decreasing physical activity.
The present study has several limitations. First, it reflects the changes in body shape of
18- to 20-year-old men with Swiss citizenship only. Second, the data did not allow for the
controlling of the migration background of the young men. Third, the cantonal coverage of the
historical data is incomplete because of the limited control book survival in the archives.
Fourth, government authorities decided not to measure weight between 1880 and 1931,
causing a weight gap in the time series for these years. Fifth, the quality of the recent data
from 1992 to 2003 may be slightly limited, which is reflected in the relatively high number of
missing height values before 2004 and the mysterious discontinuity in the weight distri-
bution from 2000 to 2002. Sixth, the primary group of 19-year-old young men became rela-
tively less important over the observed cross-sections, and the share of 20-year-old conscripts
increased in recent years. However, similar studies have demonstrated that the different age
groups typically show identical height and BMI patterns [30, 39] . Seventh, we are aware of
the difficulty in using contemporary WHO categories for BMI as a framework for historical
data, as health-relevant risk cut-off points in BMI may have shifted over time [56] . Eighth, BMI
is generally limited as indicator for body shape, and technical studies are still debating on the
most adequate way of relating body height and weight [57–60] . Ninth, we cannot control for
the fact that delayed physical growth may also be an explanatory factor. The gap in physical
development between healthy young men who achieved their final height by the age of 19
and those who continued to grow after 19 until their mid-20s was certainly wider in the 19th
century than it is today [38] . Moreover, socioeconomic factors may play a critical role in
explaining the changes in BMI, as suggested by earlier studies [32] . Future studies should thus
focus on the differences between groups from different socioeconomic positions within the
presented anthropometric patterns to investigate potential confounding factors.
We presented secular trends in height and weight in Swiss conscripts from the late 19th
century to today and showed an increase over time in first height and later in BMI under
improving nutritional conditions. Our results can be seen as an example of human develop-
mental plasticity. The changes in the environmental conditions observed in this study are
currently occurring in different regions of the world, and our data predict that similar changes
in height and weight may occur in these transitional regions either now or in the near future.
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Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
Acknowledgments
The authors wish to thank Andreas Stettbacher, Chief Medical Surgeon of the Swiss Armed Forces (for
providing the individual conscription data 1992–2014); Franz Frey and Tiziano Angelelli, Logistikbasis der
Armee – Sanität (for their support); Michael Hotz and Anja Wiederkehr for collecting parts of the historical
data; Ulrich Woitek, Tobias Schoch, Radoslaw Panczak, Marcel Zwahlen, Jonathan Wells, Barry Bogin, Maciej
Henneberg, Randolph Nesse, Bernard Harris, John Komlos, and Michael Hermanussen (for helpful comments).
Funding
Swiss Federal Office of Public Health (2013–2014), Swiss National Science Foundation (2005–2009,
Project No. 109802), Swiss Foundation for Nutrition Research (2005–2009), and Mä xi Foundation Zurich
(since 2010)
Disclosure Statement
None declared.
References
 1 World Health Organization (WHO): Obesity and overweight. Updated fact sheet No 311 [Internet]
2015;Available from: www.who.int/mediacentre/factsheets/fs311/en/ (last accessed July 19, 2016).
 2 Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al: Global, regional, and national prevalence
of overweight and obesity in children and adults during 1980–2013:a systematic analysis for the Global
Burden of Disease Study 2013. Lancet 2014;
6736: 1–16.
 3 WHO: Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. World Health
Organ Tech Rep Ser 2000;
894:i–xii, 1–253.
 4 Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K, et al: General and abdominal adiposity
and risk of death in Europe. N Engl J Med 2008;
359: 2105–2120.
 5 Bjørge T, Engeland A, Tverdal A, Smith GD: Body mass index in adolescence in relation to cause-specific
mortality: a follow-up of 230,000 Norwegian adolescents. Am J Epidemiol 2008;
168: 30–37.
 6 Kelly T, Yang W, Chen CS, Reynolds K, He J: Global burden of obesity in 2005 and projections to 2030. Int J Obes
2008;
32: 1431–1437.
 7 Federal Office of Public Health (BAG): Übergewicht & Adipositas. Ernährung und Bewegung 2015; www.bag.
admin.ch/themen/ernaehrung_bewegung/05207/05218/?lang=de (last accessed July 19, 2016.
 8 Schneider H, Venetz W, Gallani-Berado C: Overweight and obesity in Switzerland: Cost burden of adult obesity
in 2007. Basel, Federal Office of Public Health, 2009.
 9 Kuzawa CW: Adipose tissue in human infancy and childhood: an evolutionary perspective. Am J Phys Anthropol
1998;
107: 177–209.
10 Wells JCK: The Evolutionary Biology of Human Body Fatness : Thrift and Control. Cambridge, Cambridge
University Press, 2010.
11 Power ML, Schulkin J: The Evolution of Obesity. Baltimore, Johns Hopkins University Press, 2009.
12 Wells JCK: Thrift: a guide to thrifty genes, thrifty phenotypes and thrifty norms. Int J Obes 2009;
33: 1331–
1338.
13 Neel J: Diabetes mellitus: a ‘thrifty’ genotype rendered detrimental by ‘progress’? Am J Hum Genet 1962;
14:
353–362.
14 Gluckman PD, Hanson MA: The developmental origins of the metabolic syndrome. Trends Endocrinol Metab
2004;
15: 183–187.
15 West-Eberhard M: Developmental Plasticity and Evolution. New York, Oxford University Press, 2003.
16 Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES, et al: Persistent epigenetic differences asso-
ciated with prenatal exposure to famine in humans. Proc Natl Acad Sci U S A 2008;
105: 17046–17049.
17 Merta S: Wege und Irrwege zum modernen Schlankheitskult. Diätkost und Körperkultur als Suche nach neuen
Lebensstilformen 1880–1930. Stuttgart, Franz Steiner, 2003.
18 Baumann N: «Sonnenlichtnahrung» versus gutbürgerliche Fleischeslust. Die «richtige» Ernährung im Span-
nungsfeld von Ernährungswissenschaft, Körpervermessung und Lebensreformbewegung im schweizeri-
schen Raum zwischen 1890 und 1930. Schweiz Zeitschr Geschichte 2008;
58: 298–317.
19 Komlos J, Brabec M: The trend of BMI values of US adults by deciles, birth cohorts 1882–1986 stratified by
gender and ethnicity. Econ Hum Biol 2011;
9: 234–250.
Downloaded by:
62.202.188.58 - 8/21/2016 7:05:49 PM
271
Obes Facts 2016;9:259 –272
DOI: 10.1159/000446966
Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
20 Sperrin M, Marshall AD, Higgins V, Renehan AG, Buchan IE: Body mass index relates weight to height differ-
ently in women and older adults: serial cross-sectional surveys in England (1992–2011). J Public Health (Oxf)
2015 ; DOI: 10.1093/pubmed/fdv067.
21 Cohen DA., Sturm R: Body mass index is increasing faster among taller persons. Am J Clin Nutr 2008;
87: 445–
448.
22 Diverse Populations Collaborative Group: Weight-height relationships and body mass index: some observa-
tions from the Diverse Populations Collaboration. Am J Phys Anthropol 2005;
128: 220-229.
23 Micozzi MS, Albanes D, Jones DY, Chumlea WC: Correlations of body mass indices with weight, stature, and
body composition in men and women in NHANES I and II. - Am J Clin Nutr 1986;
44: 725–731.
24 Floud R: The heights of Europeans since 1750: a new source for European economic history; in Komlos J (ed):
Stature, Living Standards, and Economic Development: Essays in Anthropometric History. Chicago, The
University of Chicago Press, 1994, pp 9–24.
25 Staub K, Woitek U, Rühli F: Impact and pitfalls of conscription data; in Hermanussen M (ed): Auxology.
Stuttgart, Schweizerbart, 2013, pp 146–149.
26 Engeland A, Bjørge T, Selmer RM, Tverdal A, Bjorge T, Selmer RM, et al: Height and body mass index in relation
to total mortality. Epidemiology 2003;
14: 293–299.
27 Kurz HR: Geschichte der Schweizer Armee. Frauenfeld, Huber, 1985.
28 Schweizer Armee: Instruction über die Untersuchung und Ausmusterung der Militärpflichtigen. Bern, 1875.
29 Wolf P: Die Schweizerische Bundesgesetzgebung: nach Materien geordnete Sammlung der Gesetze, Beschlüsse,
Verordnungen und Staatsverträge der Schweizerischen Eidgenossenschaft sowie der Konkordate. Basel,
1891.
30 Panczak R, Zwahlen M, Woitek U, Rühli FJ, Staub K: Socioeconomic, temporal and regional variation in body
mass index among 188,537 Swiss male conscripts born between 1986 and 1992. PLoS One 201412;
9:e96721.
31 Panczak R, Held L, Moser A, Jones P, Ruhli F, Staub K: Finding big shots: small-area mapping and spatial
modelling of obesity among Swiss male conscripts. BMC Obes 2016;
3: 1–12.
32 Staub K, Rühli FJ, Woitek U, Pfister C: BMI distribution/social stratification in Swiss conscripts from 1875 to
present. Eur J Clin Nutr 2010;
64: 335–340.
33 Eidgenössisches statistisches Amt: Turnprüfung bei der Rekrutierung 1972. Bern, 1974.
34 Bundesamt für Statistik: Turnprüfung bei der Aushebung 1977. Bern, 1980.
35 Bundesamt für Statistik: Aushebung: schulische und berufliche Ausbildung sowie körperliche Leistungs-
fähigkeit von Stellungspflichtigen und MFD-Anwärterinnen. Neuchâtel, 1989.
36 World Health Organization (WHO): BMI Classification. 2014; http://apps.who.int/bmi/index.
jsp?introPage=intro_3.html (last accessed July 2016).
37 Kinkerlin H: Die Bevölkerung des Kantons Basel-Stadt am 1. Dezember 1880. Basel, 1880.
38 Staub K, Floris J, Woitek U, Rühli F: From left-skewness to symmetry: how body-height distribution among
Swiss conscripts has changed shape since the late 19th century. Ann Hum Biol 2014;
4460: 1–8.
39 Staub K, Rühli F, Woitek U, Pfister C: The average height of 18- and 19-year-old conscripts (N=458,322) in
Switzerland from 1992 to 2009, and the secular height trend since 1878. Swiss Med Wkly 2011;
141:w13238.
40 Lieberman DE: The Story of the Human Body: Evolution, Health, and Disease. New York, Pantheon Books,
2014.
41 Bogin B: Patterns of Human Growth, 2nd ed. Cambridge, Cambridge University Press, 1999.
42 Pfister C: Ernä hrungslandschaften vor dem Zeitalter der Eisenbahn; in Bundesamt für Gesundheit (BAG) (ed):
Dritter schweizerischer Ernä hrungsbericht. Bern, Bundesamt für Gesundheit (BAG), 1991, pp 354–364.
43 Pfister C, Studer R: SWISTOVAL – der Historische Geldwertrechner für die Schweiz ab 1800. Traverse 2010;
1: 272–284.
44 Brugger H: Die Schweizerische Landwirtschaft 1850–1914. Frauenfeld, Huber, 1978.
45 Larnkaer A, Attrup Schroder S, Schmidt IM, Horby Jorgensen M, Fleischer Michaelsen K, Attrup Schrøder S, et
al: Secular change in adult stature has come to a halt in northern Europe and Italy. Acta Paediatr 2006;
95:
754–755.
46 Studer R: When did the Swiss get so rich? comparing living standards in Switzerland and Europe, 1800–1913.
J Eur Econ Hist 2008;
2: 405–452.
47 Balke H, Nocito A: A trip through the history of obesity(in German). Praxis (Bern 1994) 2013;
102: 77–83.
48 Brownell K, Horgen K: Food fight: the inside story of the food industry, America’s obesity crisis, and what can
be done about it. Columbus, McGraw-Hill, 2003.
49 Aeberli I, Henschen I, Molinari L, Zimmermann MB: Stabilization of the prevalence of childhood obesity in
Switzerland. Swiss Med Wkly 2010;
140:w13046.
50 Komlos J, Brabec M: The trend of mean BMI values of US adults, birth cohorts 1882–1986 indicates that the
obesity epidemic began earlier than hitherto thought. Am J Hum Biol 2010;
22: 631–638.
51 Poglitsch M, Kefurt R, Mittlböck M, Bohdjalian A, Langer FX, Ludvik B, et al: Prevalence of obesity and over-
weight in male 18-year-olds in Austria from 2006 to 2010: an update. Eur Surg 2011;
43: 181–186.
52 Staub K, Woitek U, Rühli FJ: Grenzüberschreitende Zusammenarbeit mit anthropometrischen und
medizinischen Daten der Rekrutierung. Swiss Rev Mil Disaster Med 2013;
1: 41–45.
53 Hales CN, Barker DJP: Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Int
J Epidemiol 2013;
42: 1215–1222.
Downloaded by:
62.202.188.58 - 8/21/2016 7:05:49 PM
272
Obes Facts 2016;9:259 –272
DOI: 10.1159/000446966
Staub et al.: From Undernutrition to Overnutrition: The Evolution of Overweight and
Obesity among Young Men in Switzerland since the 19th Century
www.karger.com/ofa
© 2016 The Author(s). Published by S. Karger GmbH, Freiburg
54 Stöger R: The thrifty epigenotype: an acquired and heritable predisposition for obesity and diabetes? BioEssays
2008;
30: 156–166.
55 Archer E: The childhood obesity epidemic as a result of nongenetic evolution: the maternal resources
hypothesis. Mayo Clin Proc 2015;
90: 77–92.
56 Henderson M: The bigger the healthier: are the limits of BMI Risk changing over time? Econ Hum Biol 2005;
3: 339–366.
57 Keys A, Fidanza F, Karvonen MJ, Kimura N, Taylor HL: Indices of relative weight and obesity. J Chronic Dis 1972;
25:
329–343.
58 Henneberg M:
Body weight-height relationship exponential solution. Am J Hum Biol 1989; 1: 483–491.
59 Ulijaszek SJ, Henneberg M, Henry CJK: One reason why waist-to-height ratio is usually better related to chronic
disease risk and outcome than body mass index. Int J Food Sci Nutr 2013;64:
269–273.
60 Wells JCK: Commentary: The paradox of body mass index in obesity assessment: not a good index of adiposity,
but not a bad index of cardio-metabolic risk. Int J Epidemiol 2014;43:
672–674.
61 Studer R, Schuppli P: Deflating Swiss prices over the past five centuries. Hist Methods 2008;
41: 137–156.
62 Bundesamt für Statistik: Landesindex der Konsumentenpreise: Treibstoff Jahresdurchschnittspreise pro Liter
in Franken. Neuchatel, 2009.
63 Ritzmann-Blickenstorfer H: Historische Statistik der Schweiz-Historical Statistics of Switzerland. Zürich,
Chronos, 1996.
Downloaded by:
62.202.188.58 - 8/21/2016 7:05:49 PM
... The positive secular trends that we found for weight in the current study are in line with those found in the adult population in Switzerland (45). This likely reflects the growing obesity epidemic worldwide (46), including Switzerland (45). ...
... The positive secular trends that we found for weight in the current study are in line with those found in the adult population in Switzerland (45). This likely reflects the growing obesity epidemic worldwide (46), including Switzerland (45). Only since about 2012, after the cohort studied here reached adulthood, has the secular trend in children's weight leveled off (8,47,48). ...
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Introduction Human physical growth, biological maturation, and intelligence have been documented as increasing for over 100 years. Comparing the timing of secular trends in these characteristics could provide insight into what underlies them. However, they have not been examined in parallel in the same cohort during different developmental phases. Thus, the aim of this study was to examine secular trends in body height, weight, and head circumference, biological maturation, and intelligence by assessing these traits concurrently at four points during development: the ages of 4, 9, 14, and 18 years. Methods Data derived from growth measures, bone age as an indicator of biological maturation, and full-scale intelligence tests were drawn from 236 participants of the Zurich Longitudinal Studies born between 1978 and 1993. In addition, birth weight was analyzed as an indicator of prenatal conditions. Results Secular trends for height and weight at 4 years were positive (0.35 SD increase per decade for height and an insignificant 0.27 SD increase per decade for weight) and remained similar at 9 and 14 years (height: 0.46 SD and 0.38 SD increase per decade; weight: 0.51 SD and 0.51 SD increase per decade, respectively) as well as for weight at age 18 years (0.36 SD increase per decade). In contrast, the secular trend in height was no longer evident at age 18 years (0.09 SD increase per decade). Secular trends for biological maturation at 14 years were similar to those of height and weight (0.54 SD increase per decade). At 18 years, the trend was non-significant (0.38 SD increase per decade). For intelligence, a positive secular trend was found at 4 years (0.54 SD increase per decade). In contrast, negative secular trends were observed at 9 years (0.54 SD decrease per decade) and 14 years (0.60 SD decrease per decade). No secular trend was observed at any of the four ages for head circumference (0.01, 0.24, 0.17, and − 0.04 SD increase per decade, respectively) and birth weight (0.01 SD decrease per decade). Discussion The different patterns of changes in physical growth, biological maturation, and intelligence between 1978 and 1993 indicate that distinct mechanisms underlie these secular trends.
... Both developed and developing countries are overwhelmed by obesity. Although current trends show a steady sharp increase in obesity prevalence in low-and middleincome countries [11], there have been some indications that in high-income countries, the rate of obesity increase has been stabilized after the decade 2000-2010, suggesting a possible plateau [12][13][14][15]. There have been also some encouraging reports for stable or even declining obesity rates in children and adolescents in high-income countries, reinforcing the obesity plateau theory also in the young populations [16][17][18][19][20][21]. ...
... Of note, no plateau in obesity was observed for Mexican-American people in the latter review, but only continuous increases [14]. Another longitudinal study in a large number of Swiss male conscripts provided clear indications for BMI stabilization at high levels and no further increases since 2010 [15]. ...
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Purpose of Review To provide an update on current obesity prevalence trends and summarize the available evidence suggesting a possible plateau or stabilization in obesity rates after the previous sudden global rise. Recent Findings The escalating global obesity epidemic represents one of the most serious public health challenges. There have been some indications that in high-income populations, the rate of obesity increase in adults has been stabilized after the decade 2000–2010, suggesting a possible plateau. Current evidence also suggests that obesity rates have been stabilized in children and adolescents of most economically advanced countries since 2000, which is possibly related to healthier dietary habits and increased levels of physical activity. On the other hand, there is a steady uninterrupted rise in low-income nations, and the universal trend is obesity escalation rather than slowdown, mainly driven by sharp increases in the obesity prevalence of low-income populations. Furthermore, an increasing number of high- and middle-income countries are currently experiencing an epidemic of severe obesity. In high-income populations, severe obesity is expected to double its prevalence from 10 to 20% between 2020 and 2035, posing an enormous threat for healthcare systems. Even if transiently stabilized, the obesity prevalence remains globally at unacceptably high levels, and there is no guarantee that the current stability (if any) will be maintained for long. Summary In this review, we explore the underlying drivers of the global obesity epidemic; we provide possible explanations for the reported slowdown of the obesity rates in some countries; and we overall take a critical perspective on the obesity plateau hypothesis, emphasizing the urgent need for immediate effective actions at population and regional level in order to halt the alarming obesity escalation and its serious health risks.
... Compared to 2007, the mean BMI of 18-30-year-olds in 2017 was about 2 kg.m −2 higher [6]. Staub et al. (2016) showed that the weight and BMI of Swiss conscripts increased in two distinct steps: at the end of the 1980s and again after 2002. Since 2010, the BMI has stabilized at a high level [7]. ...
... Staub et al. (2016) showed that the weight and BMI of Swiss conscripts increased in two distinct steps: at the end of the 1980s and again after 2002. Since 2010, the BMI has stabilized at a high level [7]. Nutritional and/or physical activity patterns may have changed during those periods. ...
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... Studies from the annual weight monitoring of conscripts (12) and school children (13) have shown that the prevalence of excess weight, at least among young people, has not increased since approximately 2010. For the adult population, the prevalence of excess weight varies between 25 and 50 %, depending on the study, reflecting differences in the design and the composition of the study population in terms of sex, age and socio-economic and ethnic backgrounds. ...
... A limitation was that not all studies included all variables under examination; therefore, certain subanalyses were restricted to data from a subset of datasets. The surveys included were from different years, but recent studies have shown that the average weight of Swiss schoolchildren and Swiss conscripts has remained stable since 2010 (12,13) . Moreover, the distribution of BMI is very similar between the SHS 2012 and 2017, as well as between the SFP 2010 and 2017. ...
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Excess weight is caused by multiple factors and has increased sharply in Switzerland since the 1990s. Its consequences represent a major challenge for Switzerland, both in terms of health and the economy. Until now, there has been no cross-dataset overview study on excess weight in adults in Switzerland. Therefore, our aim was to conduct the first synthesis on excess weight in Switzerland. We included all existing nationwide Swiss studies (eight total), which included information on body mass index (BMI). Mixed multinomial logistic regression analyses were performed to assess the associations between different socio-demographic, lifestyle cofactors and the World Health Organization (WHO) categories for BMI. Along with lifestyle factors, socio-demographic factors were among the strongest determinants of BMI. In addition, self-rated health status was significantly lower for underweight, pre-obese and obese men and women than for normal weight persons. The present study is the first to synthesise all nationwide evidence on the importance of several socio-demographic and lifestyle factors as risk factors for excess weight. In particular, the highlighted importance of lifestyle factors for excess weight opens up the opportunity for further public health interventions.
... But in contrast to the aforementioned literature on causes of deaths, there was no association with dying more frequently from cancer for taller men, and shorter height was not associated with cardiovascular mortality. The anthropometric history of Switzerland over the last 200 years has been extensively reviewed (Trüb et al., 2020;Staub et al., 2016Staub et al., , 2014Schoch, Staub, and Pfister 2012). The results are in line with the general anthropometric literature: increasing average height since the end of the 19th century and clearly visible but decreasing social gradient in height, while at the same time life expectancy at birth, GDP per capita, and real wages increased. ...
... Young men from the lower middle class and the elite class had lower estimated BMI than unskilled workers. Body fat and overweight hardly occur in this historical period and can therefore not explain the socioeconomic differences (Staub et al., 2016). The explanations are rather to be found in the work-related physical activity and the associated larger muscle masses in lower social classes (Schoch, Staub, and Pfister 2012). ...
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... However, it has become disadvantageous in today's world, where high-calorie foods are readily available, and sedentary lifestyles are common. Scholars such as Bellisari 1 and Staub et al. 2 note that the genetic predisposition to store fat, known as the "thrifty genotype, " was advantageous in the past but now presents challenges in an era of caloric surplus. Rapid dietary and lifestyle changes, driven by the availability of processed foods, have outpaced our evolutionary adaptations, creating a disconnect between our biological heritage and contemporary behaviors. ...
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Historically, human evolution favored metabolic processes that encouraged fat storage as a survival mechanism during food scarcity, essential for maintaining energy reserves in ancestral environments. However, this adaptation has become a liability in today's world, where high-calorie foods are abundant and sedentary lifestyles prevail. Scholars like Bellisari and Staub et al. argue that the genetic predisposition to store fat, termed the "thrifty genotype," was beneficial in the past but now poses challenges in an era of caloric surplus. Rapid changes in diet and lifestyle, driven by the availability of processed foods, have outstripped our evolutionary adaptations, creating a disconnect between our biological heritage and modern behaviors.
... Creatinine is one of the metabolic measures best correlated with body weight. There is evidence that height and weight in the population under normal conditions are normally distributed, however, overweight and obesity result in a thick tail in the weight distribution 40 . Similarly, it has been shown that the distribution of liver enzymes in a lean population is close to Gaussian, whereas a population including the overweight and obese will be markedly skewed 41 . ...
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Aim: To investigate whether the increase in adult stature in European countries is continuing. Methods: The secular trend in growth after 1990 for various European countries was assessed by national conscript data. Results: In Scandinavia and the Netherlands, the height has reached a plateau at 179 - 181 cm, and in Italy a plateau at 174 cm. In Belgium, Portugal and Spain, height continued to increase.