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ANALYSIS OF THE DISTRIBUTION OF METABOLIC TYPES (META
POPULATION AND THEIR ASSOCIATION WITH DEMOGRAPHIC DATA
*,1Richard C. Geibel, 2
Anne van der Vegt,
1
Fresenius University of Applied Sciences, Im MediaPark 4, 50670 Köln, Germany
2
Center of Genetic Analysis and Prognosis, Lungengasse 48
ARTICLE INFO
ABSTRACT
Most weight loss programs focus on a low
weight loss however, this diet isn’t suitable for every person as many
for this problem is the individual genetic make
differently. An individual diet plan for sustainable weight loss that is based on the genetic make
and thus each person’s meta
MetaCheck. The aim of this study was to investigate, if there is only one type of diet that is suitable
for everyone, while considering the individual genetic predisposition. A statistical
randomly selected MetaCheck analysis results was carried out to analyze how the different Meta
types are distributed and whether there is any association between Meta
The results demonstrate that different Meta
population. Further
person’s risk for becoming overweight. In conclusion, general recommendations for everyone to lose
weight i
therapy, which is based on the individual Meta
Copyright©2017, Richard C. Geibel et al. This
is an open access article distributed under the Creative
use, distribution, and
reproduction in any medium, provided the original work is properly cited.
INTRODUCTION
Currently more than 2.1 billion people worldwide are
overweight, which is defined as a body mass index (BMI) over
25 kg/m² (
NCD Risk Factor Collaboration
which is defined as a BMI of 30 kg/m² and more, affects
around 671 mill
ion people worldwide and contributes to
diabetes, hypertension, cardiovascular diseases, and especially
cancer. From previous work, it was already known that obesity
is strongly associated with 5 different cancer types (e. g.
cancers of the colon, endometr
ium and kidney)
A recent meta-
analysis, which included more than 1,000
studies, identified eight additional cancer types linked
obesity, including postmenopausal breast cancer and ovarian
cancer (Lauby-Secretan, 2016).
Apart from an incr
for different diseases, studies show that obesity also leads to a
lower life expectancy and that a slightly elevated BMI already
leads to a higher mortality. On the other hand, Ochner and
colleagues point out that a weight reduction of only 5
the initial bodyweight can already decrease mortality and
significantly improve the state of health (
Ochner
*Corresponding author: Richard C. Geibel
Fresenius University of Applied Sciences, Im MediaPark 4, 50670
Köln, Germany
ISSN: 0975-833X
Vol.
Article History:
Received 20th August, 2017
Received in revised form
16th September, 2017
Accepted 14th October, 2017
Published online 30th November, 2017
Citation:
Richard C. Geibel, Anne van der Vegt, Orhan Özüak and Hossein Askari,
types) in the European population and their association with Demographic data
Key words:
Obesity, Meta-types, Meta-Check,
BMI, Diet plan, Weight loss,
Macronutrient, Weight management,
Weight loss program,
Genetic, Overweight.
RESEARCH ARTICLE
ANALYSIS OF THE DISTRIBUTION OF METABOLIC TYPES (META
-
TYPES) IN THE EUROPEAN
POPULATION AND THEIR ASSOCIATION WITH DEMOGRAPHIC DATA
Anne van der Vegt,
2Orhan Özüak and 1,2
Hossein Askari
Fresenius University of Applied Sciences, Im MediaPark 4, 50670 Köln, Germany
Center of Genetic Analysis and Prognosis, Lungengasse 48
–
50, 50676 Köln, Germany
ABSTRACT
Most weight loss programs focus on a low
-
carbohydrate diet. In terms of successful and sustainable
weight loss however, this diet isn’t suitable for every person as many
for this problem is the individual genetic make
-
up, since everyone metabolizes macronutrients
differently. An individual diet plan for sustainable weight loss that is based on the genetic make
and thus each person’s meta
bolic subtype (Meta-
type) is provided by the nutrigenetic analysis
MetaCheck. The aim of this study was to investigate, if there is only one type of diet that is suitable
for everyone, while considering the individual genetic predisposition. A statistical
randomly selected MetaCheck analysis results was carried out to analyze how the different Meta
types are distributed and whether there is any association between Meta
The results demonstrate that different Meta
-
types are distributed quite evenly
population. Further
the Meta-types
are not associated with age, gender or BMI and demonstrate no
person’s risk for becoming overweight. In conclusion, general recommendations for everyone to lose
weight isn’t a promising solution. Instead, there is a strong need for an individualized weight loss
therapy, which is based on the individual Meta
-type.
is an open access article distributed under the Creative
Commons Att
ribution License, which
reproduction in any medium, provided the original work is properly cited.
Currently more than 2.1 billion people worldwide are
overweight, which is defined as a body mass index (BMI) over
NCD Risk Factor Collaboration
, 2016). Obesity,
which is defined as a BMI of 30 kg/m² and more, affects
ion people worldwide and contributes to
diabetes, hypertension, cardiovascular diseases, and especially
cancer. From previous work, it was already known that obesity
is strongly associated with 5 different cancer types (e. g.
ium and kidney)
(Vainio, 2002).
analysis, which included more than 1,000
studies, identified eight additional cancer types linked
to
obesity, including postmenopausal breast cancer and ovarian
Apart from an incr
eased risk
for different diseases, studies show that obesity also leads to a
lower life expectancy and that a slightly elevated BMI already
leads to a higher mortality. On the other hand, Ochner and
colleagues point out that a weight reduction of only 5
-10 % of
the initial bodyweight can already decrease mortality and
Ochner
, 2015).
Fresenius University of Applied Sciences, Im MediaPark 4, 50670
However,
even a modest long
difficult for most overweight and obese people. One part of the
problem is that they are overloaded with a huge choice of
different weight loss programs and nutritional advises.
most popular weight los
s programs are focused on a diet,
which is very low in carbohydrates (low
successful and sustainable weight loss, this type of diet is not
suitable for every person in general as many studies clearly
demonstrate (Shai
, 2008 and
Johnston, 2014).
Some are more successful than others. Along
with this problem, lost bodyweight is often largely regained
after the diet intervention has been terminated
2016).
Corresponding to this, Ochner and colleagues po
that a mere recommendation to avoid calorically dense foods
might be no more effective for the typical weight losing patient
than
would be a recommendation to avoid sharp objects for
someone bleeding profusely
(
dietary
recommendations may have limited utility.
cause for these differences in weight loss success is the genetic
predisposition of every individual person as an increasing
number of studies demonstrate.
and family studies as
well as large population genetic studies,
the heritability of body weight or the BMI is estimated at 40
70 % (Locke, 2015;
Visscher,
metabolic genes can lead to great differences in the
International Journal of Current Research
Vol.
9, Issue, 11, pp.60257-60262, November, 2017
Richard C. Geibel, Anne van der Vegt, Orhan Özüak and Hossein Askari,
2017. “
Analysis of the distribution of metabolic types (meta
population and their association with Demographic data
”,
International Journal of Current Research
Available online at http://www.journalcra.com
z
TYPES) IN THE EUROPEAN
POPULATION AND THEIR ASSOCIATION WITH DEMOGRAPHIC DATA
Hossein Askari
Fresenius University of Applied Sciences, Im MediaPark 4, 50670 Köln, Germany
50, 50676 Köln, Germany
carbohydrate diet. In terms of successful and sustainable
weight loss however, this diet isn’t suitable for every person as many
studies demonstrate. One reason
up, since everyone metabolizes macronutrients
differently. An individual diet plan for sustainable weight loss that is based on the genetic make
-up
type) is provided by the nutrigenetic analysis
MetaCheck. The aim of this study was to investigate, if there is only one type of diet that is suitable
for everyone, while considering the individual genetic predisposition. A statistical
study with 16,641
randomly selected MetaCheck analysis results was carried out to analyze how the different Meta
-
types are distributed and whether there is any association between Meta
-types and demographic data.
types are distributed quite evenly
in the European
are not associated with age, gender or BMI and demonstrate no
person’s risk for becoming overweight. In conclusion, general recommendations for everyone to lose
sn’t a promising solution. Instead, there is a strong need for an individualized weight loss
ribution License, which
permits unrestricted
even a modest long
-term weight reduction is very
difficult for most overweight and obese people. One part of the
problem is that they are overloaded with a huge choice of
different weight loss programs and nutritional advises.
Today
s programs are focused on a diet,
which is very low in carbohydrates (low
-carb diet). In terms of
successful and sustainable weight loss, this type of diet is not
suitable for every person in general as many studies clearly
, 2008 and
Schwarzfuchs, 2012 and
Some are more successful than others. Along
with this problem, lost bodyweight is often largely regained
after the diet intervention has been terminated
(Fothergill,
Corresponding to this, Ochner and colleagues po
int out
that a mere recommendation to avoid calorically dense foods
might be no more effective for the typical weight losing patient
would be a recommendation to avoid sharp objects for
(Ochner, 2015). The universal
recommendations may have limited utility.
A major
cause for these differences in weight loss success is the genetic
predisposition of every individual person as an increasing
number of studies demonstrate.
Based upon twin-, adoption-,
well as large population genetic studies,
the heritability of body weight or the BMI is estimated at 40
–
Visscher,
2012). Different variants of
metabolic genes can lead to great differences in the
INTERNATIONAL JOURNAL
OF CURRENT RESEARCH
Analysis of the distribution of metabolic types (meta
-
International Journal of Current Research
, 9, (11), 60257-60262.
metabolism of macronutrients that are
taken up with the food.
Considering these facts, the Center of Genetic Analysis and
Prognosis (CoGAP) in Germany developed the genetic
metabolic analysis MetaCheck as described in
and Özüak, 2016)
. In the scope of this analysis, different gen
variants are analyzed that are involved in the macronutrient
metabolism and are demonstrably known to lead to a different
food processing. As a result, CoGAP defines four different,
metabolic subtypes the so called Meta-
types (alpha, beta,
gamma, and del
ta), which differ in their ability of processing
carbohydrates, fats, and proteins. Meta-
type alpha processes
proteins well and should reduce the proportion of
carbohydrate-rich and fat-
containing food. The Meta
processes proteins and fats well a
nd should therefore focus on
low-
carb diet. Unlike alpha and beta, Meta
processes carbohydrates well, while Meta-
type delta is good in
processing carbohydrates and fats.
In addition to each
nutritional Meta-type one of two sport or
(endurance and speed) is defined for each person. The
endurance variant is characterized by a high caloric
consumption during endurance activities, while the speed
variant shows a higher caloric consumption during speed
based activit
ies. With the determined Meta
variant, the best suitable diet and exercise form for a successful
and sustainable weight loss can then be selected and an
individual nutritional plan as well as sport plan can be created
for each person. It is
worth mentioning that the MetaCheck is
not
exclusively for overweight and obese people but also for
everyone with normal weight that care for a healthy
metabolism.
The different gene variants and the resulting Meta
exercise-
types suggest that there can’t be just one type of diet,
which leads to a
successful and sustainable weight loss in
every person. Nevertheless, most weight loss programs only
recommend a combination of a low-
carb diet and regular
endurance sport, which would correspond to the combination
Meta-type “Beta/E”.
The primary aim of th
investigate, if there is in fact only one type of diet that is
suitable for everyone, while considering the individual genetic
predisposition. For this purpose, a statistical study with 16,641
randomly selected MetaCheck analysis results was
to analyze how the different Meta-
and exercise
distributed among the study
participants and how big the
differences are among the population regarding the genetic
predisposition for macronutrient metabolism. Further, it was
tested if the Meta-types and exercise-
types are statistically and
significantly associated with the
demographic data (in this
study: gender, age, and BMI) and the development
Hypothesis Development
In scope of this work several hypotheses were developed and
tested, to analyze different aspects and relationships of the four
Meta-types and two exercise-
types. The first hypothesis deals
with the question, if there is a statistically significant
association between the four different Meta
-
exercise-types.
Likewise, two more hypotheses were made to
analyze if there is a significant association between the Meta
types and different genders as well as between exercise
and different gend
ers. However, the main interesting
hypotheses are, if any of the four Meta-
types and two exercise
types are
significantly associated with overweight and obesity
(determined by the BMI), and therefore can be considered as a
risk factor for developing overwe
ight and obesity.
60258
Richard C. Geibel et al. Analysis of the distributi
taken up with the food.
Considering these facts, the Center of Genetic Analysis and
Prognosis (CoGAP) in Germany developed the genetic
metabolic analysis MetaCheck as described in
(Askari, 2015
. In the scope of this analysis, different gen
e
variants are analyzed that are involved in the macronutrient
metabolism and are demonstrably known to lead to a different
food processing. As a result, CoGAP defines four different,
types (alpha, beta,
ta), which differ in their ability of processing
type alpha processes
proteins well and should reduce the proportion of
containing food. The Meta
-type beta
nd should therefore focus on
carb diet. Unlike alpha and beta, Meta
-type gamma
type delta is good in
In addition to each
exercise variants
(endurance and speed) is defined for each person. The
endurance variant is characterized by a high caloric
consumption during endurance activities, while the speed
variant shows a higher caloric consumption during speed
-type
ies. With the determined Meta
-type and sport
variant, the best suitable diet and exercise form for a successful
and sustainable weight loss can then be selected and an
individual nutritional plan as well as sport plan can be created
worth mentioning that the MetaCheck is
exclusively for overweight and obese people but also for
everyone with normal weight that care for a healthy
The different gene variants and the resulting Meta
- and
types suggest that there can’t be just one type of diet,
successful and sustainable weight loss in
every person. Nevertheless, most weight loss programs only
carb diet and regular
endurance sport, which would correspond to the combination
The primary aim of th
is study is to
investigate, if there is in fact only one type of diet that is
suitable for everyone, while considering the individual genetic
predisposition. For this purpose, a statistical study with 16,641
randomly selected MetaCheck analysis results was
carried out
and exercise
-types are
participants and how big the
differences are among the population regarding the genetic
predisposition for macronutrient metabolism. Further, it was
types are statistically and
demographic data (in this
study: gender, age, and BMI) and the development
of obesity.
In scope of this work several hypotheses were developed and
tested, to analyze different aspects and relationships of the four
types. The first hypothesis deals
with the question, if there is a statistically significant
-
types and the two
Likewise, two more hypotheses were made to
analyze if there is a significant association between the Meta
-
types and different genders as well as between exercise
-types
ers. However, the main interesting
types and two exercise
-
significantly associated with overweight and obesity
(determined by the BMI), and therefore can be considered as a
ight and obesity.
Considering the questions above, the following five hypotheses
were developed:
A.) Meta-types and exercise-
types
H0: There is no statistically
Meta-types and exercise-types
H1: There is a statistically
significant association between
Meta-types and exercise-types
B.) Meta-types and gender
H0:
There is no statistically significant association between
Meta-types and gender
H1:
There is a statistically significant association between
Meta-types and gender
C.) Exercise-
types and gender
H0:
There is no statistically significant association between
exercise-types and gender
H1:
There is a statistically significant association between
exercise-types and gender
D.) Meta-Types and BMI
H0: There is no statistically
Meta-types and BMI
H1: There is a statistically
significant association between
Meta-types and BMI
E.) Exercise-types and BMI
H0:
There is no statistically significant association between
exercise-types and BMI
H1:
There is a statistically significant association between
exercise-types and BMI
MATERIALS AND
METHODS
To determine the sample size with the highest possible
statistical power
a population size of 743,000,000 or more
people, a confidence level of 99
(also called margin of error) of 1 % were chosen and with the
following sample size calculator equation calculated:
(N = population size, e = margin of error, z = z
The Meta- and exercise-
type as well as the body ma
all study participants were determined with the nutrigenetic
MetaCheck analysis during 2012 and 2016. All necessary data
for gender, age, height, and bodyweight were collected and
analyzed in an anonymous manner. For the study, randomly
selected
participants were evaluated based on their BMIs as
normal (18–24.9 kg/m2
), overweight (25 kg/m
and obese (≥30 kg/m2).
For comparing the different sets of
data, mean values
and percentages
bodyweight were calculated.
intergroup comparisons of categorical variables.
variables were expressed as numbers. P values lower than 0.01
were considered as statistically significant. The calculations
were performed using the IBM SPSS Statistics V2
Richard C. Geibel et al. Analysis of the distributi
on of metabolic types (meta-
types) in the european population
and their association with demographic data
Considering the questions above, the following five hypotheses
types
significant association between
significant association between
There is no statistically significant association between
There is a statistically significant association between
types and gender
There is no statistically significant association between
There is a statistically significant association between
significant association between
significant association between
There is no statistically significant association between
There is a statistically significant association between
METHODS
To determine the sample size with the highest possible
a population size of 743,000,000 or more
people, a confidence level of 99
%, and a confidence interval
(also called margin of error) of 1 % were chosen and with the
following sample size calculator equation calculated:
(N = population size, e = margin of error, z = z
-score)
type as well as the body ma
ss index of
all study participants were determined with the nutrigenetic
MetaCheck analysis during 2012 and 2016. All necessary data
for gender, age, height, and bodyweight were collected and
analyzed in an anonymous manner. For the study, randomly
participants were evaluated based on their BMIs as
), overweight (25 kg/m
2–29.9 kg/m2),
For comparing the different sets of
and percentages
of age, BMI, and
Chi-square tests were used in
intergroup comparisons of categorical variables.
Categorical
variables were expressed as numbers. P values lower than 0.01
were considered as statistically significant. The calculations
were performed using the IBM SPSS Statistics V2
2 besides
types) in the european population
excel 2016.0. To assess if the four different Meta-types and the
two different exercise-types are evenly distributed throughout
the study samples, the total abundance of the four different
Meta-types and two exercise-types as well as their percentages
were used for statistical analysis. The Chi-Square Goodness-
of-Fit Test was used to analyze if the distribution of the Meta-
and exercise-types is homogenous. With a chi-square test of
independence, it was analyzed if there is a significant
association between the variables. The study was reviewed and
approved by the ethics committee of the Fresenius University
of Applied Sciences Köln, Germany.
RESULTS
As described in the method section, a sample size calculator
equation was used, to determine the sample size with the
highest possible statistical power for a population size of
743,000,000 or more people. The result was that a sample size
of 16,641 MetaCheck-results are needed. Therefore, exactly
16,641 randomly selected samples were included in this study,
to gain the highest possible statistical power. Of the 16,641
included participants 12,389 (74.4 %) were female and 4,252
(25.6 %) were male. Mean overall age was 43.6 (+/- 12.8)
(Tab. 1). On average Women were 43.5 (+/-12.8) and men
44.0 (+/-12.6) years old. Mean overall bodyweight of all study
participants was 81.4 (+/-18.6) kg.
Women had a mean bodyweight of 77.0 (+/-17.0) kg; men 94.5
(+/-17.1) kg. Mean overall BMI was 28.0 (+/-5.7) kg/m2.
Women had a mean BMI of 27.6 (+/-5.9) kg/m2, whereas men
had a mean BMI of 29.0 (+/-4.9) kg/m2. Tab. 2 shows the
different amounts and percentages of the four different Meta-
types, two exercise-types and combinations of Meta- and
exercise-types. 4,969 (29.86 %) of 16,641 participants could be
assigned to Meta-type Alpha, 3,929 (23.61%) to Meta-type
Beta, 4,272 (25.67 %) to Meta-type Gamma, and 3,471 to
Meta-type Delta (20.86 %). 10,410 (62.56 %) participants
could be categorized as exercise-type E (Endurance). 6,231
(37.44 %) were assigned to exercise-type S (Speed). The Meta-
type/exercise-type combination that shows the highest
occurrence is G/E (19.97 %), whereas D/S is the combination
that is represented in the lowest numbers (4.71 %). The results
of the Chi-Square Goodness-of-Fit test showed highly
significant differences regarding the abundance of the four
Meta-types within the study population: X2(3, N=16,
641)=287.27, p=0,00(α≤0.01). The difference in distribution of
the two exercise-types is also highly significant: X2(1,
N=16,641) =1049.46, p=0,00 (α≤0.01). A chi-square test of
independence was performed to examine a possible relation
between the different Meta-types and exercise-types (Tab. 3).
The relation between these variables was highly significant,
X2(3, N=16,641) = 1,402.77; p<.00001.
Table 1. Mean age, bodyweight, and BMI of study participants
Mean x;ˉ Standard deviation Median
Age (years) 43.6 12.8 45
Women 43.5
Men 44.0
Bodyweight (kg) 81.4 18.6 79
Women 77.0
Men 94.5
BMI 28.0 5.7 26.9
Women 27.6
Men 29.0
Table 2. Distribution of Meta- and exercise-types
Meta-type Percentages Number
Alpha (A) 29.86 % 4,969
Beta (B) 23.61% 3,929
Gamma (G) 25.67 % 4,272
Delta (D) 20.86 % 3,471
Exercise type Percentages Number
Endurance (E) 62.56 % 10,410
Speed (S) 37.44 % 6,231
Meta- and exercise type Percentages Number
A/E 14.72 % 2,450
A/S 15.14 % 2,519
B/E 11.72 % 1,950
B/S 11.89 % 1,979
G/E 19.97 % 3,323
G/S 5.70 % 949
D/E 16.15 % 2,687
D/S 4.71 % 784
Table 3. Relation of Meta- and exercise-types
Results Chi-Square test - Meta-types and exercise-types
E (Endurance) S (Speed) Row Totals
Alpha 2,450 (3,108.42) (139.47) 2,519 (1,860.58) (233.00) 4,969
Beta 1,950 (2,457.84) (104.93) 1,979 (1,471.16) (175.30) 3,929
Gamma 3,323 (2,672.41) (158.39) 949 (1,599.59) (264.61) 4,272
Delta 2,687 (2,171.33) (122.47) 784 (1,299.67) (204.60) 3,471
Column Totals 10,410 6,231 16,641 (Grand Total)
The chi-square statistic is 1402.7712. The p-value is < 0.00001. The result is highly significant at p < .01.
60259 International Journal of Current Research, Vol. 9, Issue, 11, pp.60257-60262, November, 2017
The Meta-types Gamma and Delta show a significant
difference between the distribution of exercise-types. A further
chi-square test of independence was performed to examine the
relation between the different Meta-types and gender (Tab. 4)
as well as the two exercise-types and gender (Tab. 5). The
relation between these variables was not statistically
significant, X2 (3,N=16,641)=3.32, p=0.344588 and X2
(1,N=16641)= 0.0469, p=0.828595, respectively.
To evaluate if there is an association between the Meta- or
exercise-types and BMI, a chi-square test of independence was
performed. For both, Meta-types and exercise-types, no
statistically significant differences in relation to BMI can be
reported: X2 (9, N=16,641)=10.00 (Tab. 6); p=0.35 and X2 (3,
N=16,641) = 1.16; p=0.76 (Tab. 7), respectively.
DISCUSSION & CONCLUSION
With more than 2.1 billion people being overweight or obese,
obesity has become a critical global issue. Most popular weight
loss programs focus today on a common low-carb diet, which
is however not promising for everyone. The aim of this study
was to analyze if the four metabolic subtypes and the two
exercise-types that are defined by the genetic predisposition,
are distributed evenly throughout the European population.
Equally important was to evaluate with this research whether it
is reasonable that a low carb diet and endurance sport are so
frequently recommended for the therapy of obesity.
Furthermore, it was tested if there is a relation between the
Meta- or exercise-types and gender, and if there is an
association between Meta- or exercise types and BMI. Among
the 16,641 study participants, 12,389 were women and 4,252
were men. The mean bodyweight for women was 77.0 (+/-
17.0) kg with a mean BMI of 27.6 (+/-5.9) kg/m2, while men
had a mean bodyweight of 94.5 (+/-17.1) kg and a mean BMI
of 29.0 (+/-4.9) kg/m2 (Tab. 1). It is not surprising that the men
in our cohort are heavier and have a greater BMI, since men
have a greater proportion of muscles and are on average larger
in height. Nevertheless, women usually are more health-
conscious then men and therefore tend to take steps for losing
weight by doing the nutrigenetic test MetaCheck much earlier.
This can explain the bodyweight and BMI differences among
men and women in the cohort. Furthermore, the health
awareness of women is the reason that more women do the
MetaCheck than men. Our findings showed that even though in
general more men are suffering from overweight than women
(Mensink et al., 2013), there is no difference in distribution of
the four Meta-types and the two exercise types among the two
genders (Tab. 4 and 5). This clearly indicates that there is no
association between a distinct Meta- or exercise-type and
gender and therefore no Meta-type or exercise-type is more
abundant among men or women. Another important question
was, whether any of the four Meta-types and two exercise-
Table 4. Relation of Meta-types and gender
Results Chi-Square test - Exercise-types and gender
Women Men Row Totals
E (Endurance) 7,756 (7,750.10) (0.00) 2,654 (2,659.90) (0.01) 10,410
S (Speed) 4,633 (4,638.90) (0.01) 1,598 (1,592.10) (0.02) 6,231
Column Totals 12,389 4,252 16,641 (Grand Total)
The chi-square statistic is 0.0469.The p-value is 0.828595. The result is not significant, when p<0.01.
Table 5. Relation of exercise-types and gender
Results Chi-Square test - Meta-types and gender
Women Men Row Totals
Alpha 3,677 (3,699.35) (0.14) 1,292 (1,269.65) (0.39) 4,969
Beta 2,933 (2,925.09) (0.02) 996 (1,003.91) (0.06) 3,929
Gamma 3,219 (3,180.45) (0.47) 1,053 (1,091.55) (1.36) 4,272
Delta 2,560 (2,584.11) (0.22) 911 (886.89) (0.66) 3,471
Column Totals 12,389 4,252 16,641 (Grand Total)
The chi-square statistic is3.322. The p-value is 0.344588. The result is not significant, when p<0.01.
Table 6. Relation Meta-types and BMI
Resultat Chi-Quadrat-Test - BMI & Meta-types
BMI Alpha Beta Gamma Delta Row Totals
<18.5 21 (30.16) (2.78) 27 (23.85) (0.42) 25 (25.93) (0.03) 28 (21.07) (2.28) 101
18.5 - 24.9 1,710 (1,675.74) (0.70) 1,340 (1,325.01) (0.17) 1,428 (1,440.69) (0.11) 1,134 (1,170.56) (1.14) 5,612
25 – 29.9 1,707 (1,749.80) (1.05) 1,379 (1,383.57) (0.02) 1,522 (1,504.35) (0.21) 1,252 (1,222.29) (0.72) 5,860
≥30 1,531 (1,513.30) (0.21) 1,183 (1,196.57) (0.15) 1,297 (1,301.03) (0.01) 1,057 (1,057.09) (0.00) 5,068
Column Totals 4,969 3,929 4,272 3,471 16,641 (Grand Total)
The chi-square statistic is10.0012. The p-value is 0.350388. The result is not significant, when p<0.01.
Table 7. Relation exercise-types and BMI
Results Chi-Quadrat-Test - BMI &Sport-types
BMI E (Endurance) S (Speed) Row Totals
<18,5 62 (63.18) (0.02) 39 (37.82) (0.04) 101
18,5 - 24,9 3,503 (3,510.66) (0.02) 2,109 (2,101.34) (0.03) 5,612
25 – 29.9 3,645 (3,665.80) (0.12) 2,215 (2,194.20) (0.20) 5,860
≥30 3,200 (3,170.36) (0.28) 1,868 (1,897.64) (0.46) 5,068
Column Totals 10,410 6,231 16,641 (Grand Total)
The chi-square statistic is 1.1592.The p-value is 0.762795. The result is not significant, when p<0.01.
60260 Richard C. Geibel et al. Analysis of the distribution of metabolic types (meta-types) in the european population
and their association with demographic data
types can be significantly associated with overweight and
obesity and therefore be considered as a risk factor for
developing overweight and obesity. The statistical analysis in
this study shows that neither a distinct Meta-type nor one of
the two exercise-types can be significantly associated with
BMI (Tab. 6 und 7), thus, no Meta-type or exercise-type
demonstrates a person’s risk for becoming overweight.
Interestingly, in this study a statistically highly significant
relation between Meta-types and exercise-types can be
reported. The Meta-types that metabolize carbohydrates well
(Gamma and Delta), were connected to exercise-type “E” 3 to
3.5 times more often than to exercise-type S. This finding
indicates the influence of evolutionary processes that led to the
formation of different metabolic types. During the human
evolution, the human genes had to adapt constantly to
changing living conditions and environments. As hunter-
gatherers, our ancestors consumed mainly meat which is rich
in protein and fats. Carbohydrates only represented a small
proportion of the consumed energy. Furthermore, hunter-
gatherers needed to move quickly for hunting or escaping
predators. When humans transitioned from hunter-gatherers to
agricultural societies, the dietary habits as well as the physical
demands changed. Now instead of speed, endurance was
important for agricultural activities. Furthermore, with the
growing of food crops, carbohydrates were increasingly
included in the human diet. The results of this study indicate
that the Meta-types Gamma and Delta are still strongly
associated/connected with the exercise-type E. This kind of
association could not be observed for the Meta-types Alpha
and Beta, for which an evenly distribution of the exercise-types
can be reported.
As mentioned in the introduction most popular weight loss
programs today are focused on a low-carb diet and are often
generally recommended in combination with endurance sports
for overweight and obese people. With regard to the Meta
Check this recommendation would correspond to the
combination of Meta-type Beta and exercise-type E. Our study
showed, however, that this specific combination only applied
to 11.72 % of the population (Tab. 2). The finding that the four
Meta-types are distributed evenly among the study participants
suggests that it is not useful to give universal recommendations
(e.g. low diet and endurance based sports) for everyone to lose
weight effectively. Instead, an individual therapy for each
person is necessary. This result is in line with a cohort study
conducted by Zeevi et al. (2015), where the glycemic
responses of 800 study participants were compared after the
participants received identical meals. A high variability was
found in the blood sugar curves and therefore in the
metabolism of carbohydrates. Zeevi et al. conclude that
universal dietary recommendations may have limited utility
(Zeevi et al., 2015). The efficacy of individualized dietary and
recommendations that consider the individual’s unique genetic
make-up were already proven in a retroperspective
comparative study that was carried out at the Centre for Sport
and Health Research (ZfG) of the German Sport University in
2013 (Kurscheid and Loewe, 2013). Patients that adjusted their
nutrition and sports activities according to their MetaCheck
results experienced a 5 times higher reduction in BMI
compared to the control group that received general dietary
recommendations. In line with this analysis, a retrospective
study of the Stanford University published in March 2010
shows that a genetically adapted diet results in a greater weight
loss success than a non-genotype based diet (Mindy Dopler
Nelson et al., 2010). On average, the participants in the study
who followed a genetically adapted diet successfully lost more
than twice (about 2.5 times) as much weight than the
comparison group with a non-genotype based diet. However,
not all diets are successful in the long term, since lost
bodyweight is often largely regained after quitting the diet
intervention. Therefore, the sustainability of the weight loss
success with MetaCheck was investigated in an empirical
study, which was carried out in 2016 (Özüak et al., 2016).
Nearly 91 % of the subjects reported that they could maintain
their new weight, which underpins the sustainability of the
weight reduction with MetaCheck.
To conclude, the results of this study demonstrate that different
metabolic subtypes are indeed distributed quite evenly
throughout the European study population and that there is not
one major Meta-type. These findings as well as the findings of
previous studies clearly indicate that a general
recommendation for everyone to lose weightin a sustainable
way is not an appropriate and promising solution. Instead,
there is a strong need for anindividualized weight loss therapy
which is based on the individual genetic make-upto avoid the
often-described absence of weight loss success and weight
regain. Overweight has already become a worldwide health
problem and considering the individual genetic make-up via a
nutrigenetic test like MetaCheck might be the solution for this
worldwide growing problem.
Conflict of Interests
This study was financed by the Center of Genetic Analysis and
Prognosis (Köln, Germany). R.C. Geibel was funded by the
Fresenius University of Applied Sciences (Köln, Germany). A.
van der Vegt, O. Özüak and H. Askari were funded by the
Center of Genetic Analysis and Prognosis (Köln, Germany).
Other additional financial or personal benefits regarding the
study did not exist.
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60262 Richard C. Geibel et al. Analysis of the distribution of metabolic types (meta-types) in the european population
and their association with demographic data
