Nutrigenomic study approach

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NUTRIGENOMICS STUDY APPROACH OF GENETIC AND
ENVIRONMENTAL FACTOR EFFECT ON OBESITY
DR. PRANITA PRAVEEN ENDAIT
M.SC. DFSM (IGNOU)
GUIDE : DR. GEETA DHARMATTI
CO-GUIDE: DR. AMOL RAUT

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CONTENT
Introduction
Literature Review
Nutrigenomics Study Approach
System Development
Methodology
Result And Discussion
Conclusion
Bibliography

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INTRODUCTION
Obesity is a complex, multi-factorial disease that develops from the
interaction between genetic and the environmental factors.
Nutrigenomic approach allows us to explore these interactions and apply
them in the management of obesity.

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AIM
To find out the importance of nutrigenomical study approach in management of multi-
factorial obesity.
OBJECTIVES OF STUDY
To find out an association between environmental factors like Co-morbidities,
Addictions, Physical Activity, Regular Exercise , Sleep Hours, Sleep Apnea, Dietary
Factors , Drugs, Stress and obesity.
To find out an association between impacts of genetic factor more specifically
impact of PPARG and IL6 and obesity.
To discuss importance of nutrigenomics study approach understanding in obese
people having impact of PPARG and IL6 in obesogenic environment.

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Hypothesis
Nutrigenomic study approach is necessary in the effect of environmental
and genetical factor effect on multi-factorial obesity and obesity has been
found to have significant association with environmental factors and
genetic factors.

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SIGNIFICANCE OF THE STUDY
To understand that obesity is significant public health issue.
To understand that obesity is multi factorial disease.
To understand the role of genetic factors (PPARG and IL6) in the
development of obesity.
To understand the role of environmental factors in the development of
obesity.
To understand the nutrigenomics study approach.

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LITERATURE REVIEW
It provide the relevant scientific background to establish the theoretical basis
for this study.
Obesity have reached epidemic proportion worldwide, the US topped the list
with 13% while China and India together accounted for15%with 46 million
and 30 million obese people, respectively(1/3 of world’s population).
India is currently witnessing rising numbers of obese people. The percentage
of obese adults is highest in Punjab [30%], followed by Kerala [28%] and
Delhi [26%].
Obesity is a serious public health issue worldwide having well documented
relationship between high BMI and mortality and morbidity due to chronic
diseases.

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LITERATURE REVIEW: OBESITY ETIOLOGY
Obesity is a highly complex, chronic disorder with a multi factorial
etiology.
The obesity risk depends on two important mutually-interacting
factors:
A.Genetic variants [single-nucleotide polymorphisms]
B.Exposure to environmental risks [diet, physical activity etc.]

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A. Genetics of obesity:
The evidence for genetic influence on anthropometry has
previously been established which estimated to be 60-70%.
The latest update of Human Obesity Gene Map reported 127
candidate genes for which there is at least one study available
suggesting positive association with obesity which includes
PPARG and IL6.

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B. Environmental Factor of obesity:
1. Dietary Habits
a. Consumption of Energy Rich Food
b. Dinning Out
c. Diet Type and Obesity
2. Lack of Physical Activity
a. Television Viewing
b. Non Exercise Activity
3. Socio- Economic Factors
4. Emotional Stress
5. Endocrine and Metabolic Diseases
6. Co morbidities
C. Gene and Environment Interaction and Obesity

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OUTLINE OF DISSERTATION
The study is conducted in two parts.
1.Nutrigenomics study approach was thoroughly reviewed by
systematic review of scientific research articles.
2.The data of 107 patients (43 female and 64 male) were analyzed for
single nucleotide polymorphism (SNP) profile of obesity associated
genes ( PPARG and IL6) at GeneSupport.

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NUTRIGENOMIC STUDY APPROACH OF OBESITY
Throughout the 20th century, Nutritional Science focused on finding
vitamin and minerals, defining their use and preventing the deficiency
diseases that they caused.
As nutrition related health problems of the developed world shifted to
over nutrition, obesity and type-2 diabetes, the focus of modern medicine
and of nutritional science changed.
To prevent the development of these types of disease, nutrition research is
investigating on how nutrition can optimize and maintain cellular, tissue,
organ and whole body homeostasis.
This requires understanding how nutrients act at the molecular level
which in turn involves a multitude of nutrient-related interactions at the
gene, protein and metabolic levels.
As a result, nutrition research shifted from epidemiology and physiology
to molecular biology and genetics and nutrigenomics was born.

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Global Status of Nutrigenomic Research: US and UK have the highest
contribution, while India is in 16th position.
Indian Status of Nutrigenomics Research: India has a keen interest in
the field of nutrigenomics. In the year 2005, 2008 and 2009 Indian
authors gave a broader description of nutrigenomics.

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UNDERSTANDING THE CONCEPT OF
NUTRIGENOMICS
Genome : The genome is the entire DNA sequence, the genetic
fingerprint, of an organism. The human genome is estimated to encode up
to 30 000 genes.
Genomics: Genomics is the study of the genome; an approach of
mapping, sequencing, and analysis of all genes present in the genome.
Nutrigenomics: Nutrigenomics, is the study of how food and genes
interact and aims to understand the effects of diet on an individual’s genes
and health.

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NUTRIGENOMIC STUDY APPROACH OF
OBESTY
Nutrigenomics:
Nutrigenomic research in obesity has provided insights in three major
areas helping us in system development,
1.The identity of many genes in which polymorphisms can affect the
proportions to develop obesity.
2.Characteristic changes in patterns of gene expression in adipose tissues
associated with obesity and their biological consequences.
3.Discoveries made in the field of nutrigenomics translate into more
effective dietary strategies to improve overall health by identifying
unique targets for prevention.

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Genetic factors responsible for obesity
Genotype in obesity Genes
Thriftiness
[Low Metabolic Rate, Inadequate Thermo genesis]
Β-2-Adrenergic Receptor And Β-3 [ADRB2; ADRB3],
Uncoupling Protein 1, 2, And [UCP1, UCP2, UCP3]
Hyperplasia [Abnormal] Regulation of Hunger And
Satiety
Dopamine Receptor D2 [DRD2];5 Hydroxytryptamine
[Serotonin] Receptor 2C [ HTR2C];Leptin [LEP];
Leptin Receptor [LEPR]; Melanocortin Receptor 4
[MC4R]; Nuclear Receptor Subfamily 3,Groupc,Member
1 [NR3C]
Low Rate Of Lipid Oxidation Oxidation Angiotensin-Converting Enzyme [ACE],
Adiponectin [ADIPOQ], Guanine Nucleotide Binding
Protein, Β -3 Subunit [GNB3], Hormone Sensitive Lipase
[LIPE],Low Density Lipoprotein Receptor [LDLR]]
Adipogenesis [Fat Storage] Peroxisome Proliferators-Activated Receptor Γ [PPARG];
Interleukin-6 [IL6];Vitamin D Receptor [VDR], Resist In
[RETN],

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Genes identified for the current research
Adipogenesis [Fat Storage]:
Adipocyte stay in dynamic state, start expanding when energy intake is
higher than expenditure under the influence of insulin and undergo
mobilization when energy expenditure exceeds the intake.
Functions of adipose tissue:
I.Adipocytes are the main storage site for excess energy in the form of
triglycerides.
II.Adipose tissue has mechanical functions such as insulation and
protection against mechanical forces.
III. Adipose tissue functions as an endocrine organ.

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Adipogenesis and Peroxisome Proliferator-
Activated Receptor G [PPARG]
PPARG is having key role in the regulation of gene
expression in adipose tissue.
PPARG is a factor that plays a key role in activation of
adipocyte differentiation and is an important modulator of
gene expression in adipocytes.
The PPARG is a nuclear hormone receptor that serves as a
master regulator of adipocytes-specific genes contributing
to adipocytes differentiation, susceptibility to obesity, and
insulin sensitivity.

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Nutrigenomic Study Approach Of PPARG
Genetic Factor Impact on Obesity
PPARG and diet:
1.Fatty acid concentrations may activate PPARG, whereby obesity promotes
increases in free fatty acid levels, which lead to further adipogenesis via PPARG
transactivation.
2.In contrast to the relative lack of altered PPARG expression associated with
obesity, fasting provoked a substantial decrease in the levels of PPARG.
PPARG and gender obesity:
1.An association between the PPARG Pro12Ala variant and body mass index was
detected, with male carriers and no effect with women carriers indicating a
gender specific effect which contributes to the susceptibility in male population.
2.A study conducted in Spanish obese woman showed that Pro12Ala SNP
resulted in increased fat oxidation and higher satiety suggesting benefits in food
intake control.
PPARG and physical activity:
1.The Pro12 Ala polymorphism of the PPARG gene modifies the association of
physical activity and body mass changes in Polish women.

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Adipogenesis and Interleukin-6 [IL6]
Adipose tissue is considered a metabolically active endocrine organ, a
primary source of obesity-induced inflammation.
In humans, higher circulating IL-6 levels have been associated with
obesity induced inflammation and visceral fat deposition.
Visceral adipose tissue secretes about two to three times more IL-6 than
subcutaneous tissue, secreting also other molecules that stimulate
further IL-6 expression.

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Nutrigenomic Study Approach Of IL6 Genetic Factor
Impact on Obesity
IL6 and diet:
1.Dietary intake and lifestyle choices have impact on low-grade
inflammation. A high-fat meal promotes postprandial inflammation.
2.During hypo-energetic diets or energy restriction, metabolic efficiency
is improved and inflammatory processes are reduced.
3.Vegetarian diet, and the diet; synonymous with the US dietary
guidelines, reduces chronic low-grade inflammation.

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4. IL-6 and dietary fatty acids:
 In human studies, increased long-chain n-3 PUFA intake and fish consumption
were associated with decreased plasma IL-6 concentrations in men.
 Consuming a SFA-enriched diet for eight weeks resulted in increased
expression of genes involved in inflammatory processes in AT including IL-
6.
 N-6 PUFAs (linoleic acid and arachidonic acid): LA is the precursor of the n-6
PUFA arachidonic acid [AA]. A high LA intake has on occasion been
considered pro-inflammatory.
 N-3 PUFAs (α-linoleic acid, eicosapentanoic acid and decosahexanoic acid):
Association studies between dietary intake of ALA and inflammatory markers
suggest a modest anti-inflammatory effect of ALA.

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IL6 and physical activity:
1. A number of excellent reviews have addressed the positive
influence of physical activity and fitness on low-grade
inflammation.
2.Contracting muscle fibers secrete IL-6, exerting a local effect
within the muscle, as well as releasing IL-6 into the circulation. It
is significantly elevated with exercise, this increase is followed by
the appearance of IL-1ra and the anti-inflammatory cytokine IL-10.
3.The individuals with GG genotype lost weight significantly after
aerobic exercises training. This effect was not observed in
heterozygous neither the homozygous CC individuals who did not
reduced the fat mass and insulin levels after the physical activity.
In addition it was observed a higher incidence of G allele in
subjects with normal weight

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Nutrition and life style recommendations
The diet plan will help to change the environment in body for the better
health. We can not change the genes but can focus on diet and exercise
plan.
PPARG
1.Weight maintenance will be challenge after weight loss. Maintaining fat
in diet will be important for the weight management. Percentage of fat
and type of fat will be as per RDA.
2.If the person is exercising on regular basis then use fat as the source of
calories post exercise.
3.If inadequate exercise and excess calorie intake there are chances of
weight gain, increased central obesity.

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Nutrition and life style recommendations
IL6:
IL6 is mainly associated with inflammation . So diet recommended is
balanced fat with n-6:n-3 ratio as per RDA.
n-3 essential fatty acid common in canola, soybean oil and some nuts,
but in greatest concentrations in flaxseed and flaxseed oil. The long
chain n-3 PUFAs, EPA and DHA are found in seafood, especially oily
fish and in some algal oils.
Lower inflammatory markers include whole grains, fiber, vegetables,
fruit, fish, vitamin C, vitamin E and carotenoids.
Moderate consumption of wine and beer also decreases low-grade
inflammation.
Exercise has moderate impact towards weight gain prevention.

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Methodology
Study design:
A descriptive correlational study
Site of the study:
Subjects enrolled for weight maintenance panel up to 2015 in
GeneSupport Laboratory Pune.

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Sampling:
◦ Sampling technique: Random sampling
◦ Sampling size: 64 male and 43 female
◦ Target group: Subjects enrolled for weight maintenance panel up to
2015 in GeneSupport Laboratory Pune
Subject Protection and Safety:
Patients identity is not disclosed by GeneSupport Lab.
◦ Consent forms are with GeneSupport Laboratory.

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Inclusion criteria:
Subjects above 18 years from both the genders were
selected.
Exclusion criteria:
Subject with incomplete filled SNP profiles in excel sheet
and screening forms.

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Methodology
The data consists of two types of reports
A.Excel sheet of SNP profile of impact of PPARG and IL6.
B.The screening reports consist of details of presence/absence of
1.Co morbidities (HT, DM, CVD and IHD, asthma and thyroid.)
2.Sleep apnea
3.Addiction (smoking, alcohol consumption)
4.Regular exercise
5.Sleep hours
6.Activity levels
7.Diet type
8.Outside eating
9.Regular fasts
10.Disinterest in foods
11.Drugs and
12.Stress.

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Methodology: Data Analysis
T-test
Chi-square test
SEM model with standardized estimate using AMOS
SPSS software

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Significance Environmental Factors When Compared
With BMI
1. DM against BMI:
0.00%
25.00%
50.00%
75.00%
100.00%
125.00%
Yes No
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

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Chi-Square Test: DM against BMI
Chi-Square Test Value Df P-Value
Pearson Chi-Square 19.409 5 0.002
Interpretation: Since p-value for the chi-square is less
than that of 0.05 indicates significant association
between DM and BMI. It shows that as the BMI
increases the presence of DM increases. It means as the
obesity level increases the chances of association of DM
also increase. The post hoc analysis for determining the
significant cells is carried out the result of the post hoc
test follows:

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Result of the Post Hoc Test: DM against BMI
Cell
Adjusted Residual
[Adjusted Z-Score]
Cell
Chi-Square
Cell
P-Value
Interpretation
1,1 -1.7 2.89 0.089 NS
1,2 -1.3 1.69 0.194 NS
1,3 -0.5 0.25 0.617 NS
1,4 -0.7 0.49 0.484 NS
1,5 3.4 11.56 0.001 Significance
1,6 2.1 4.41 0.036 NS
2,1 1.7 2.89 0.089 NS
2,2 1.3 1.69 0.194 NS
2,3 0.5 0.25 0.617 NS
2,4 0.7 0.49 0.484 NS
2,5 -3.4 11.56 0.001 Significance
2,6 -2.1 4.41 0.036 NSInterpretation: If the cell p-value is less than that of boneferroni p-value = 0.004 then the
cell frequency is considered to be significant. Hence the Obese class II in DM positive is
significantly more in positive while as DM Negative is significantly smaller in obese
class II.

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2. HT against BMI
0.00%
25.00%
50.00%
75.00%
100.00%
125.00%
Yes No
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

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Chi-Square Test: HT against BMI:
Chi-Square Test Value Df P-value
Pearson Chi-Square 27.334 5 .000
Interpretation: Since p-value for the chi-square is less than that of 0.05 indicates
significant association between HT and BMI. It shows that as the BMI increases
the presence of HT increases. It means as the obesity level increases the chances
of association of HT also increase.

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Result of the Post Hoc Test: HT against BMI
Cell
Adjusted Residual [Adjusted
z-score]
Cell
Chi-Square
Cell
P-value
Interpretation
1,1 -1.7 2.89 0.0891 NS
1,2 -2.5 6.25 0.0124 NS
1,3 -1.3 1.69 0.1936 NS
1,4 0.7 0.49 0.4839 NS
1,5 2.9 8.41 0.0037 Significance
1,6 3.3 10.89 0.0010 Significance
2,1 1.7 2.89 0.0891 NS
2,2 2.5 6.25 0.0124 NS
2,3 1.3 1.69 0.1936 NS
2,4 -0.7 0.49 0.4839 NS
2,5 -2.9 8.41 0.0037 Significance
2,6 -3.3 10.89 0.0010 Significance

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Interpretation: If the cell p-value is less than that of boneferroni p-value = 0.004
then the cell frequency is considered to be significant. Here the cell p-value for
[1,5]; [1,6] and [2,5]; [2,6] is less than 0.004 so considered that the HT positive is
significantly more in obese class II and III while as HT Negative is significantly
smaller in obese class II and III.

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3. Diet Type and BMI:
0.00%
22.50%
45.00%
67.50%
90.00%
Vegetarian Eggetarian Non-vegetarian
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

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Chi-Square Test: Diet Type against BMI
Chi-Square Test
Value Df P-Value
Pearson Chi-Square
27.592 10 .002
significant association between Diet type and BMI. Number of people on
vegetarian diet is more in normal weight category.

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Result of the Post Hoc Test: Diet Type against BMI:
Cell
Adjusted
Residual
Cell
Chi-Square
Cell
P-Value
Interpretation
1,1 1.1 1.21 0.2713 NS
1,2 3.9 15.21 0.0001 Significant
1,3 0.3 0.09 0.7642 NS
1,4 -1.2 1.44 0.2301 NS
1,5 -2.8 7.84 0.0051 NS
1,6 -1.6 2.56 0.1096 NS
2,1 -0.8 0.64 0.4237 NS
2,2 -1.8 3.24 0.0719 NS
2,3 1.1 1.21 0.2713 NS
2,4 0.1 0.01 0.9203 NS
2,5 0.8 0.64 0.4237 NS
2,6 0 0 1.0000 NS
3,1 -0.4 0.16 0.689 NS
3,2 -2.3 5.29 0.021 NS
3,3 -1.4 1.96 0.162 NS
3,4 1.1 1.21 0.271 NS
3,5 2.1 4.41 0.036 NS
3,6 1.7 2.89 0.089 NS

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then the cell frequency is considered to be significant. Hence the Normal weight
people in Diet Vegetarian are significantly more in while as for other diet it is not
significant.

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4. Stress and BMI:
0.00%
25.00%
50.00%
75.00%
100.00%
125.00%
Never Sometimes Always
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

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Chi-Square Test: Stress and BMI:
Interpretation: Since p-value for the chi-square is less than that of 0.05
indicates significant association between stress and BMI. It shows that as the
BMI increases the presence of Stress increases. It means as the obesity level
increases the chances of association of DM also increase

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Result of the Post Hoc Test: Stress and BMI
Cell
Adjusted
Residual
Cell
Chi-Square
Cell
P-Value
Interpretation
1,1 3.6 12.96 0.0003 Significant
1,2 4.1 16.81 0.0000 Significant
1,3 -2.00 4.00 0.0455 NS
1,4 -0.4 0.16 0.6892 NS
1,5 -2.7 7.29 0.0069 Close To Significance Threshold
1,6 -1.5 2.25 0.1336 NS
2,1 -1.7 2.89 0.0891 NS
2,2 -1.2 1.44 0.2301 NS
2,3 1.9 3.61 0.0574 NS
2,4 0.00 0.00 1.0000 NS
2,5 0.7 0.49 0.4839 NS
2,6 -1.3 1.69 0.1936 NS
3,1 -2.0 4.0 0.0455 NS
3,2 -3.0 9.0 0.0027 Significant
3,3 0.2 0.04 0.8415 NS
3,4 0.5 0.25 0.6171 NS
3,5 2.0 4.0 0.0455 NS
3,6 2.7 7.29 0.0069 Close To Significance Threshold

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then the cell frequency is considered to be significant. Hence the analyzed data
shows significant association between never experienced stress and underweight and
normal weight [1,1and 1, 2]. The number of people is smaller in never experienced
stress and obese class II shows close to significant threshold [1, 5]. The number of
people is smaller who never experienced stress and normal weight [3, 2].

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5. Outside Eating and BMI:
0.00%
20.00%
40.00%
60.00%
80.00%
Once in a month Once in a 15 days Weekly once Weekly twice Daily
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

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Chi-square test: Outside Eating and BMI:
significant association between outside eating and BMI. As the frequency of
eating outside increases the level of obesity increases.

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Result of the Post Hoc Test: Outside Eating and BMI
Cell
Adjusted
Residual
Cell
Chi-Square
Cell
P-Value
Interpretation
1,1 -0.8 0.64 0.4237 NS
1,2 4.4 19.36 0.0000 Significant
1,3 0.6 0.36 0.5485 NS
1,5 -1 1 0.3173 NS
1,6 -0.6 0.36 0.5485 NS
2,1 0.4 0.16 0.6892 NS
2,2 2.5 6.25 0.0124 Close To Significance Thresholds
2,3 0.6 0.36 0.5485 NS
2,5 -1.2 1.44 0.2301 NS
2,6 1 1 0.3173 NS
3,1 1.2 1.44 0.2301 NS
3,2 -1.1 1.21 0.2713 NS
3,3 0.4 0.16 0.6892 NS
3,4 0.8 0.64 0.4237 NS
3,5 -1 1 0.3173 NS
3,6 -1 1 0.3173 NS
4,1 0 0 1.000 NS
4,2 -1.7 2.89 0.089 NS
4,3 0.7 0.49 0.484 NS
4,4 0.7 0.49 0.484 NS
4,5 0.3 0.09 0.764 NS
4,6 -0.9 0.81 0.368 NS
5,1 -1.3 1.69 0.194 NS
5,2 -1.9 3.61 0.057 NS
5,3 -2 4 0.046 Close To Significance Threshold
5,4 1.6 2.56 0.110 NS
5,5 2.5 6.25 0.012 Close To Significance Threshold
5,6 1.7 2.89 0.08913 NS

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Interpretation: If the cell p-value is less than that of boneferroni p-value = 0.001 at cell 5,
6 indicates the cell frequency is significant. Hence the analyzed data show significant
association between once in a month outside eating and normal weight [1, 2]. There is
positive close to significance threshold at cell [2, 2] once in 15 days and normal weight.
There is negative close to significance threshold at cell [2, 4] once in 15 days and obese
class I. There is negative close to significance threshold at cell [5, 3] daily OE and
overweight. Hence the analyzed data there is positive close to significance threshold at
cell [5, 5] daily OE and obese class II.

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Chi-square test
1. DM against BMI Pearson Chi-
Square
19.409 5 0.002
2. HT against BMI Pearson Chi-
Square
27.334 5 .000
3. Diet Type against
BMI
Pearson Chi-
Square
27.592 10 .002
4. Stress and BMI Pearson Chi-
Square
45.227 10 0.000
5. Outside Eating and
BMI Pearson Chi-
Square
51.023 20 0.000

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Environment
al Factor
Under
Weight
Normal
Weight
Over
Weight
Obese
I
Obese
II
Obese III
1. DM
2. HT
3. Vegetarian
Diet
4.
Stress Never
Experienced
Stress Always
Experienced

55
Significance Environmental Factors When Compared
With BMI
Environmental
Factor
Under
Weight
Normal
Weight
Over
Weight
Obese
I
Obese
II
Obese
III
1 DM
2 HT
3 Diet Type
Vegetarian Diet
4 Stress
Never Experienced
Always Experienced
5 Outside Eating
Once In Month
Once In 15 Days
Daily

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Significance genetical parameters when
compared with BMI
1. IL-6 Impacts with BMI
0.00%
22.50%
45.00%
67.50%
90.00%
Beneficial Low Impact Medium Impact High Impact
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

57
Chi-square test: IL-6 Impacts with BMI
significant association between IL-6 and BMI. It shows that as the BMI increases
there are increased impact of IL6. It means as the obesity level increases the
chances of association of increased impact of IL6 also increase.

58
Result of the Post Hoc Test: IL-6 Impacts with BMI
Cell
Adjusted
Residual
Cell
Chi-Square
Cell
P-Value
Interpretation
1,1 -0.3 0.09 0.7642 NS
1,2 2.7 7.29 0.0069 NS
1,3 -0.6 0.36 0.5485 NS
1,4 -0.8 0.64 0.4237 NS
1,5 -0.3 0.09 0.7642 NS
1,6 -0.2 0.04 0.8415 NS
2,1 0.1 0.01 0.9203 NS
2,2 3 9 0.0027 NS
2,3 3.3 10.89 0.0010 NS
2,4 -3.2 10.24 0.0014 NS
2,5 -2.9 8.41 0.0037 NS
2,6 -0.7 0.49 0.4839 NS
3,1 1.1 1.21 0.2713 NS
3,2 -1 1 0.3173 NS
3,3 -1 1 0.3173 NS
3,4 1.3 1.69 0.1936 NS
3,5 -0.5 0.25 0.6171 NS
3,6 0 0 1.0000 NS
4,1 -1.1 1.21 0.271 NS
4,3 -2.5 6.25 0.012 NS
4,4 2.2 4.84 0.028 NS
4,5 3.6 12.96 0.000 Significant
4,6 0.7 0.49 0.484 NS

59
Interpretation: If the cell p-value is less than that of boneferroni p-value = 0.002 at cell 3, 4
indicates that the cell frequency is significant. There is negative association between high
impact and normal weight. The number of people is significantly less in high impact of IL6
and in normal weight while there is positive association between high impact and obese
class II.

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2. PPARG impact with BMI
0.00%
25.00%
50.00%
75.00%
100.00%
125.00%
Beneficial Low Impact Medium Impact High Impact
Underweight
Normal
Overweight
Obese Class I
Obese Class II
Obese Class III

61
Chi-Square Test: PPARG impact with BMI:
Chi-Square Test Value Df P-value
significant association between PPRAG and BMI. It shows that as the BMI
increases there are increased impact of PPARG. It means as the obesity level
increases the chances of association of increased impact of PPARG also
increase.

62
Result of the Post Hoc Test: PPARG impact with BMI
Cell
Adjusted
Residual
Cell
Chi-Square
Cell
p-value
Interpretation
1,1 3.3 10.89 0.0010 Significant
1,2 6.5 42.25 0.0000 Significant
1,3 -2.7 7.29 0.0069 Close to significance threshold
1,4 -2.9 8.41 0.0037 NS
1,5 -0.5 0.25 0.6171 NS
1,6 -0.8 0.64 0.4237 NS
2,1 1.4 1.96 0.1615 NS
2,2 -0.6 0.36 0.5485 NS
2,3 0.2 0.04 0.8415 NS
2,4 -0.7 0.49 0.4839 NS
2,5 0.7 0.49 0.4839 NS
2,6 -0.7 0.49 0.4839 NS
3,1 0.8 0.64 0.4237 NS
3,2 0 0 1.0000 NS
3,3 1.4 1.96 0.1615 NS
3,4 -1.6 2.56 0.1096 NS
3,5 0.3 0.09 0.7642 NS
3,6 -0.6 0.36 0.5485 NS
4,1 -3.9 15.21 0.000 Significant
4,2 -4.5 20.25 0.000 Significant
4,3 1.1 1.21 0.271 NS
4,4 3.5 12.25 0.000 Significant
4,5 -0.2 0.04 0.841 NS
4,6 1.4 1.96 0.162 NS

63
Interpretation: If the cell p-value is less than that of boneferroni p-value = 0.002 at cell 1, 6
indicates that the cell frequency is significant. There is positive association between beneficial
impact and underweight and normal weight. The number of people is significantly more with
beneficial impact of PPARG in underweight and normal weight. There is negative association
between beneficial impact and overweight. The number of people is significantly less with
beneficial impact of PPARG and overweight. There is positive association between high
impact and obese class I. The number of people is significantly more with high impact PPARG
and obese class I.

64
Chi-square test
IL-6
Impacts
with BMI
PPARG
impact with
BMI

65
Significance genetic factors when compared with BMI
Genetical Factor
Under
Weight
Normal
Weight
Over
Weight
Obese
I
Obese
II
Obese
III
1.
IL6
• High Impact
2. PPARG
•Beneficial Impact
• High Impact

66
Nutrigenomic Study Approach is Necessary in the
Effect of Environmental and Genetical Factor
Effect on Obesity.
Model Fit: SEM Model
Estimates
Standardized
Estimate
Unstandardiz
ed
Estimate
S.E. C.R. P-Value
BMI <--- stress 0.23 0.31 0.084 3.7 0.0000
BMI <--- DM 0.14 0.35 0.166 2.1 0.0370
BMI <--- HT 0.19 0.47 0.177 2.7 0.0077
BMI <--- DT 0.24 0.31 0.081 3.9 0.0000
BMI <--- IL6 0.19 0.24 0.082 2.9 0.0030
BMI <--- PPARG 0.27 0.27 0.065 4.2 0.0000
BMI <--- OE 0.14 0.15 0.069 2.1 0.0320

67
Interpretation: p-value for Stress, DM, HT, DT, OE, IL6 and PPARG is less than that of
0.05 indicates that Stress, DM, HT, DT, OE, IL6 and PPARG has significant impact on
BMI. DM, HT, DT, OE, Stress, IL6 and PPARG showed significant impact on obesity.
When relative p values were studied stress, DT and PPARG showed same highest impact
while IL6 and HT showed relatively higher impact and OE and DM showed relatively
weak impact with respect to BMI. It gives the result that PPARG and DT have highest
impact while IL6and HT have mild impact as compared to DT and PPARG and OE and
DM have weak impact.

68
Path Diagram to Represent the Results with Regression:

69
Standardized Estimate
OE Stress DM HT Alco DT IL6 PPRAG
1. OE 1 0.19 0.2 0.35 0.05 0.41 0.25
2. Stress 0.19 1 0.06 0.13 0.07 0.24 0.12 0.42
3. DM 0.2 0.06 1 0.5 0.06 0.05 0.12 -0.03
4. HT 0.35 0.13 0.5 1 0.13 0.27 0.04
5. DT 0.05 0.24 0.05 0.13 -0.22 1 0.2 0.24
6. IL6 0.41 0.12 0.12 0.27 0.2 1 0.27
7. PPRAG 0.25 0.42 -0.03 0.04 0.24 0.27 1

70
Standardized Estimate
PPARG and Stress showed highest correlation with value of 0.42
IL6 and OE showed correlation with value of 0.41
HT and OE showed correlation with value of 0.35
IL6 and HT showed correlation with value of 0.27
PPARG and OE showed correlation with value of 0.25
DT and Stress showed correlation with value of 0.24

71
Results
Results showed that obesity is influenced by both environmental and
genetic factors.
In these subjects obesity has been found to have significant association
with environmental factors for DM, HT, DT, OE and stress and genetic
factors IL6 and PPARG.
The p-values less than that of 0.05 indicates that DM, HT, DT, OE,
Stress, IL6 and PPARG have significant impact on obesity.
When relative p values were studied stress, DT and PPARG showed
highest impact while IL6 and HT showed relatively lesser impact and OE
and DM showed least impact with respect to obesity.
The results indicate that as the impact of genetic factors is as significant
as environmental factors on obesity.

72
Conclusions:
In conclusion, it appears that both genetic and environmental factors
influence onset and management on obesity.
Nutrigenomics study approach is necessary for the management and
prevention of obesity.
Further it will help in giving personalized nutrition and weight
management regimen for weight maintenance.

73
Recommendations for future research:
Study can be carried out in large number of participants.
Study can be carried out in different parts of the country.
Detailed anthropometric assessment can be done personally.
Enhanced nutrigenomic study approach will help in giving
personalized nutrition.
An interventional study can be done by giving personalized nutrition
to study the effect of diet on obesity.

74
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