Download Food Consumption Patterns and Dietary Habits Associated with

‫ غسة‬-‫جامعت األزهر‬
Al-AzharUniversity
Deanship of Postgraduate Studies
‫عمادة الدراساث العليا والبحث العلمي‬
and Scientific Research
‫كليت الصيدلت‬
Pharmacy College
Food Consumption Patterns and Dietary Habits
Associated with Weight Status in Healthy Young
Adult Students
A THESIS
Submitted in Partial Fulfillment of the Requirements for the
Award of the Master Degree of Clinical Nutrition
By
Tawfik S. Lubbad
Supervisors
Dr. Sulaiman El jabour
Ass. Prof. of Pharmaceutical
Chemistry
Faculty of Pharmacy
Al-Azhar University-Gaza
July, 2011
Dr. Abd Al Raziq Salama
Ass. Prof. of Food Science and
Technology
Faculty of Agriculture
Al-Azhar University-Gaza
Dedication
To my Parents
To my brothers and sisters
To my wife and my children
With deep love and appreciation I dedicate this effort
i
Acknowledgement
I would like to express my sincere gratitude to my supervisor Dr. Sulaiman Eljbour Assistant
Professor of pharmaceutical chemistry, department of pharmaceutical chemistry at Al-Azhar
University-Gaza Strip, for his wisdom and professionalism during the study and continuous
support.
Thanks also for Dr. Abd Al-Razeq Salama Assistant Professor of food science and technology,
department of food science and technology at Al-Azhar-University-Gaza Strip for his support
and help throughout this work.
Also great thanks for Dr. Kanaan AL Weheidi and Dr. Ihab AL Masri for their unlimited
support and cooperation.
I extend my thanks to all members of the Faculty of Pharmacy at Al-Azhar University-Gaza,
for encouraging students to participate in the study and their facilitates that enriched this study
requirements.
I would also like to thank pharmacy students at Al-Azhar University in Gaza for their every
possible effort that helped in collecting data. Finally, I thank all those who supported and
encouraged me.
Tawfik S. lubbad
ii
Abstract
The aim of this study is to survey the body measurements and dietary intake of
university students. This study was carried out to reveal the effect of food consumption
patterns, nutrient intake and dietary habits on weight status in healthy young adult students.
140 full time students (50 % male and 50% female), aged 19 and up to 30 years, were chosen
randomly from faculty of pharmacy at Al Azhar university in Gaza.
In this study, food frequency questionnaire was used to determine the sociodemographic factors, food consumption patterns and dietary habits. A three days recalls in
order to assess the calories, carbohydrates, proteins, fats, macronutrients and micronutrients
for foods and hematological and biochemical tests which include complete blood count (CBC)
and serum iron were conducted. A descriptive approach, cross-sectional design was used.
SPSS program version 15 was used for data analysis.
This research provides important information regarding anthropometric assessment, the
micronutrient and macronutrient intake of pharmacy students. Males and females had means
of weight (kg): 76.4 and 58.3 respectively and of height (m): 1.78 and 1.63 respectively. Three
days food records were collected, anthropometric measurements were made. Mean body mass
index (BMI) was significantly lower in females than males (p<0.01). The results also showed
that 24.2% of the pharmacy students had overweight. Socio-demographic factors that were
found to be significantly associated with overweight and obesity among pharmacy students
included marital status (P< 0.05). More than 50% of the respondents were meeting two thirds
of the recommended dietary allowance (RDA) for energy, protein, fat, iron, phosphorus, vitamin
A, thiamin, riboflavin and niacin. The mean intakes of carbohydrate, energy, protein, calcium,
phosphorus, thiamin, riboflavin and
niacin were higher in female comparing with male
students. The differences founded revealed that there association between medium intake of
salt among male, smoking habits among students, frequency intake of rice, bread made of
flour originating from non-governmental organizations (NGOs) and chips, and popcorn and
overweight among healthy students (P< 0.05).
In conclusion, healthy food consumption patterns and dietary habits need to be
implementing nutrition education intervention and prevention strategies in this group while
ensuring an adequate awareness to help students to overcome university period without
iii
acquire unhealthy dietary habits and develop greater intolerance of the dangers of overweight
and obesity among students.
iv
‫ملخص الذراسة‬
‫أنماط االستهالك الغذائي والعادات الغذائية المزتبطة بالىسن عنذ الطالب األصحاء‬
‫‪.‬‬
‫هذه‬
‫أهذاف البحث‬
‫‪140‬‬
‫‪:‬‬
‫‪140‬‬
‫‪70‬‬
‫‪70‬‬
‫‪50‬‬
‫‪30 19‬‬
‫‪50‬‬
‫‪(SPSS‬‬
‫‪76.4‬‬
‫)‪(58.3‬‬
‫‪1.78‬‬
‫‪1.63‬‬
‫‪v‬‬
24.2
p<0.01
P< 0.05
50
A)
.
P< 0.05
vi
Table of contents
Page
Dedication
i
Acknowledgements
ii
Abstract
iii
Summary (Arabic)
v
Table of contents
vii
List of tables
xi
List of figures
xiii
List of Appendices
xiv
List of abbreviations
xv
Chapter (1)
Introduction and Motivation
1.1
Background and motivation
1
1.2
Problem statement
3
1.3
Objectives
3
1.4
Hypothesis study
4
Chapter (2)
Literature Review
2.1
Introduction
5
2.2
Nutrition and health for healthy young adult students
6
2.3
Socio-demographic factors associated with weight status.
9
2.3.1
Gender
10
2.3.2
Age
10
2.3.3
Education Level
10
2.3.4
Socio-economic status
10
2.3.5
Physical activity
11
2.4
Food groups
11
2.4.1
Food Guide Pyramid for good eating practices
11
2.5
Dietary factors associated with weight status.
13
2.5.1
The effects of fruit and vegetables on body weight
13
2.5.2
The effects of calcium and dairy foods on body weight
15
vii
2.5.3
The effects of fiber and whole grains on body weight
16
2.5.4
The effects of dietary patterns on body weight
18
2.5.5
The effects of breakfast on body weight
19
2.5.6
The effects of physical activity on body weight
21
2.5.7
The effects of diet quality on body weight
22
Chapter (3)
Methodology
3.1
Introduction
25
3.2
Ethical considerations
25
3.3
Study Design
25
3.4
Subjects/ Setting
25
3.4.1
Setting of Study
25
3.4.2
Subjects
25
3.4.3
Inclusion and exclusion criteria
26
3.5
Measurements
26
3.5.1
Variables and operational definitions
26
3.5.1.1
26
3.5.1.2
Young Adulthood and Middle-Aged Adults: Ages 19
Through 30 Years and 31 through 50 Years
Socio-demographic factors
26
3.5.1.3
Eating practice
27
3.5.1.3.1
Usual daily dietary intake
27
3.5.1.3.2
Energy and macronutrient intake
27
3.5.1.3.3
Food Frequency questionnaire
27
3.5.1.3.4
Daily of food intake records design
27
3.5.1.4
Anthropometric measurements
28
3.5.1.5
Laboratory tests:
28
3.5.1.5.1
Complete Blood Count (CBC) Analysis
28
3.5.1.5.2
Measurement of Serum Iron
28
3.6
Pilot study
29
3.7
Data collection process
29
3.7.1
Steps in data collection process
29
3.8
Statistical analysis
30
viii
Chapter (4)
Results
Page
31
4.2
Socio-demographic characteristics of the pharmacy
students
Economical characteristics of the sample
4.3
Mean physical characteristics of the sample
32
4.4
Relationship between socio-demographic and BMI
33
4.5
Relationship between economical variables and BMI
34
4.6
Macronutrient and micronutrient intake of the students
35
4.7
The percentages of pharmacy students meeting RDA for
nutrients
Relationship between dietary habits and BMI
37
39
4.8.3
Relationship between BMI and breakfast at home
variable
Relationship between BMI and number of daily meals
variable
Relationship between BMI and eating out home variable
4.8.4
Relationship between BMI and skipped meal variable
41
4.8.5
Relationship between BMI and diet salt variable
41
4.8.6
Relationship between BMI and physical activity variable
42
4.8.7
Relationship between BMI and smoking habit variable
42
4.9
Basic food group consumption as stated in frequency per
week among the included pharmacy students associated
with their BMI classification
Relationship between BMI and protein rich food
consumption variables
Relationship between BMI and fruits and vegetables
consumption variables
Relationship between BMI and the grains consumption
variables
Association between flour origin and the range of serum
iron among healthy students
Obesogenic food consumption as stated in frequency per
week among the included pharmacy students associated
with their BMI classification
Relationship between BMI and soft and hot drinks
consumption variables
Relationship between BMI and chocolates, and dessert
consumption variables
Relationship between BMI and chips and popcorn
consumption variables
43
4.1
4.8
4.8.1
4.8.2
4.9.1
4.9.2
4.9.3
4.9.4
4.10
4.10.1
4.10.2
4.10.3
ix
32
39
39
40
43
44
45
47
48
48
49
49
4.10.4
50
Chapter (5)
Relationship between BMI and pizza and fast food
consumption variables
Discussion of Results
5.1
Relationship between socio-demographic and BMI
52
5.2
Relationship between economical variables and BMI
53
5.3
Mean physical characteristics of the sample
53
5.4
54
Chapter (6)
The percentages of pharmacy students meeting RDA for
nutrients
dietary habits as stated by the included pharmacy
students associated with their BMI classification
Basic food group consumption as stated in frequency per
week among the included pharmacy students associated
with their BMI classification
Association between flour originating and the range of
serum iron among healthy students
Obesogenic food consumption as stated in frequency per
week among the included pharmacy students associated
with their BMI classification
Conclusion and Recommendations
6.1
Conclusions
62
6.2
Recommendations
63
References
65
Annexes
90
5.5
5.6
5.7
5.8
x
57
58
60
60
List of Tables
List of Tables
Page
Table 1
Classification of Body Mass Index
2
Table 1
Components of the Healthy Eating Index
21
Table 2
25
Table 3
Serving recommendations according to the Food Guide
Pyramid
Portion sizes for adults
Table 4
Acceptable Macronutrient Distribution Ranges
26
Table 5
Classification of BMI
28
Table 6
Procedure for measurement of serum iron
29
Table 7
Economical characteristics of the sample
32
Table 8
Mean physical characteristics of the sample
33
Table 9
Relationship between marital status and BMI
34
Table 10
34
Table 15
Economical factors associated with overweight and
obesity
Macronutrient and micronutrient intake from 3 day
recalls
The percentages of pharmacy students meeting RDA for
nutrients
Relationship between BMI and breakfast at home
variable
Relationship between BMI and number of daily meals
variable
Relationship between BMI and eating out home variable
Table 16
Relationship between BMI and skipped meal variable
59
Table 17
Relationship between BMI and diet salt variable
41
Table 18
Relationship between BMI and physical activity variable
42
Table 19
Relationship between BMI and smoking habit variable
43
Table 20
Relationship between BMI and protein rich food
consumption variables
Relationship between BMI and fruits and vegetables
consumption variables
Relationship between BMI and the grains consumption
variables
ANOVA - flour origin
44
Association between flour origin and serum iron level
among healthy students.
Relationship between BMI and soft and hot drinks
48
Table 11
Table 12
Table 13
Table 14
Table 21
Table 22
Table 23
Table 24
Table 25
xi
25
36
37
39
40
40
45
46
47
49
Table 26
Table 27
Table 28
consumption variables
Relationship between BMI and chocolates, and dessert
consumption variables
Relationship between BMI and chips and popcorn
consumption variables
Relationship between BMI and pizza and fast food
consumption variables
xii
50
50
51
List of Figures
No
Figure
Page
1
Food guide pyramid
12
2
Permanent place of residence of male and female pharmacy students
31
3
Academic level of male and female pharmacy
31
4
Mother's educational level
32
5
Father's educational level
32
6
BMI categories
33
xiii
List of Appendices
No
List of Appendices
page
A
Sample letter of request to Dean of Faculty of Pharmacy to
conduct research with pharmacy students
Ethical approval for the study was granted by Ethical Committee
of Helsinki
Sample of 3 day recalls
90
95
E
Sample of Socio-demographic, anthropometric, dietary habits,
food consumption patterns, obesogenic factors, medical history,
and physical activity questionnaire.
Arbitration of questionnaire
101
F
The way to record the quantity of food intakes
104
B
C
D
xiv
91
92
List of abbreviations
List of abbreviations
AI
Adequate Intakes
AMDR
Acceptable Macronutrient Distribution Ranges
BMI
Body Mass Index
CARDIA
Coronary Artery Risk Development in Young Adults
CBC
Complete Blood Count
CDC's
Centers for Disease Control and Prevention
CVDs
Cardiovascular Diseases
DG
Dietary Guidelines
dl
Deciliter
DRIs
Dietary Reference Intakes
EARs
Estimated Average Requirements
EDTA
Ethylene Diamine Tetraacetic Acid
FAO
Food and Agriculture Organization
FFQ
Food Frequency Questionnaire
IUG
Islamic university-Gaza
IASO
International Association for the Study of Obesity
IRS
Insulin Resistance Syndrome
Kcal
Kilocalorie
kJ
Kilojoules
NCD
Noncommunicable Diseases
NCHS
National Center for Health Statistics
NGOs
Non-Governmental Organizations
NHANES
National Health and Nutrition Examination Survey
RBCs
Red Blood Cells
RDA
Recommended Dietary Allowance
RMR
Resting Metabolic Rate
SD
Standard Deviation
TEE
Total Energy Intake
xv
UNRWA
United Nations Relief Working Agency
US
United States
WBCs
White Blood Cells
WHO
World Health Organization
Wt
Weight
xvi
CHAPTER (1)
1. Introduction
1.1 Background and motivation
The term overweight means excessive body weight in relation to height,
(Laquatra, 2004). Overweight was defined as a BMI 95th percentile compared to age-and
sex-specific, National Center for Health Statistics (NCHS) reference data (Kuczmarski et
al., 2000). Whereas obesity indicates excessive high amount of fat or adipose tissue in
relation to lean body mass (Stunkard & Wadden, 1993 and Kopelman, 2000).
Obesity is considered as the most prevalent serious public health problem of
nowadays (Roberts and Mayer, 2000). Obesity is a worldwide problem that is rapidly
affecting both developed and developing countries. According to a recent report from the
World Health Organization (WHO, 2004), it is estimated that worldwide more than 1
billion adults are overweight, at least 300 million of them clinically obese. Almost twothirds of the American adults, 60% of the English people above 16 years and 60% of
Australians above 25 years are overweight or obese. According to World Health
Organization (WHO, 1998), the number of overweight people was predicted to approach
1.5 billion by the year 2015. Obesity is a major contributor to the global burden of chronic
disease and disability. Often coexisting in developing countries with under-nutrition,
obesity is a complex condition, with serious social and psychological dimensions, affecting
virtually all ages and socioeconomic groups.
Epidemiologic studies commonly use body mass index (BMI), calculated from
2
weight and height [weight (kg)/ square height (m )], as an indicator of overweight and
obesity (Flegal et al., 2000). According to the WHO (2000), overweight and obesity are
defined as abnormal or excessive fat accumulation that presents a risk to health. However,
BMI is an imperfect measure of body fatness (Roche et al., 1981 and Wellens et al.,
1996), largely because it does not directly measure fat mass. According to Deurenberg et
al., 1998, the relationship between percent body fat and BMI differs in the ethnic groups
studied. For the same level of body fat, age and gender, American Blacks have a 1.3 kg/m2
and Polynesians a 4.5 kg/m2 lower BMI compared to Caucasians. In contrast, in Chinese,
Ethiopians, Indonesians and Thais BMI are 1.9, 4.6, 3.2 and 2.9 kg/m2 lower compared to
Caucasians, respectively. Slight differences in the relationship between percent body fat
and BMI of American Caucasians and European Caucasians were also found. The
1
differences found in the body fat BMI relationship in different ethnic groups could be due
to differences in energy balance as well as to differences in body build.
BMI categorizes individuals as underweight, normal weight, overweight and obese
(Laquatra, 2004). Adult obesity is defined in stages. Stage I obesity is a BMI of 30 to
34.9; stage II obesity is a BMI of 35 to 39.9; and stage III obesity is a BMI of 40 or higher.
Stage III obesity was formerly known as ―morbid obesity‖ (David et al., 2008).
Table 1: Classification of BMI (Laquatra, 2004)
2
Classification
Body Mass Index (kg/m )
Underweight
< 18.5
Normal weight
18.5 – 24.9
Overweight
25.0 – 29.9
Obesity class I
30.0 – 34.9
Obesity class П
35.0 – 39.0
Extreme obesity class Ш
≥ 40
Obesity and overweight pose a major risk for serious diet-related chronic diseases,
including type 2 diabetes, cardiovascular disease, hypertension and stroke, and certain
forms of cancer (Murphy et al., 2000, Van den Brandt et al., 2000 and Smith et al.,
2001). The health consequences range from increased risk of premature death, to serious
chronic conditions that reduce the overall quality of life ((WHO, 1997). The increasing
incidence of child obesity is also a subject of special concern.
The obesity is now so common within the world's population that it is beginning to
replace undernutrition and infectious diseases as the most significant contributor to ill
health. This rising epidemic reflects the profound changes in society and in behavioral
patterns of communities over recent decades. While genes are important in determining a
person's susceptibility to weight gain, the actual energy balance is determined by calorie
intake and physical activity. Thus societal changes and worldwide nutrition transition are
driving the obesity epidemic (WHO, 2003).
The positive imbalance between energy intake and energy expenditure can be
attributed to a number of factors including: socio-demographic and socio-economic
factors, eating practices, nutritional knowledge, and decreased physical activity (Burns et
al., 1987; Cavalli-Soforza et al., 1996; Kruger et al., 2002; Steyn et al., 2003; FerroLuzzi & Puska, 2004; Moreno et al., 2004 and Grafova 2006). Therefore establishing an
association between either of these factors and body weight could assist in developing
2
strategies to control body weight or minimize health risks associated with excess body
weight. According to Dryden (2005), eating habits that contributed to weight gain in
college students included eating less than five servings of fruits and vegetables per day,
and in addition many did not get enough exercise. Decreased physical activity due to
increasingly sedentary nature of many forms of work, changing modes of transportation
and increasing urbanization, all contribute to positive energy expenditure which
contributes to overweight and obesity (Kruger et al., 2002 and Klumbiene et al., 2004).
1.2 Problem statement
University lifestyle students are characterized by unhealthy dietary patterns and
reduced physical activity. Relatively few studies have attempted to document these
patterns in students and to date. The purpose of this study is to reveal the effect of food
consumption patterns, nutrient intake and dietary habits on weight status in healthy young
adult students. Many university students may be overweight or obese due to sociodemographic and socio-economic factors, food consumption patterns, dietary habits,
nutritional knowledge, and decreased physical activity. Obesity is a risk factor and
exacerbates many chronic conditions, such as hypertension, cardiovascular disease,
respiratory diseases, diabetes mellitus type 2, cancer and other diseases.
Information obtained from this study could help in developing and implementing
nutrition education intervention and strategies for university students furthermore could
lead to improvement in food consumption patterns, dietary habits, regular physical activity
and weight management and thus improves health care among young adults.
1.3 Objectives:
The objectives of the study were to determine in the following points healthy young
adult students:
• Socio-demographic factors and mean physical characteristics of the sample associated
with BMI.
• Macronutrient and micronutrient intake from three days recalls and the percentages of
pharmacy students meeting RDA for nutrients associated with overweight and obesity.
• Dietary habits, food consumption patterns and obesogenic food consumption as stated by
the included pharmacy students associated with their BMI classification.
3
1.4 Hypothesis of the study
The current study is trying to verify the authenticity of a number of assumptions in
healthy young adults assuming that there are no differences between the following:
• Anthropometry and sociodemographic variables in relation to the body mass index.
• Macronutrient and micronutrient intake from three days recalls and the percentages of
pharmacy students meeting RDA for nutrients associated with overweight and obesity.
• Dietary habits, food consumption patterns and obesogenic food consumption as stated by
the included pharmacy students associated with their BMI classification.
4
CHAPTER (2)
2. Literature review
2.1 Introduction
Body weight is the sum of bones, muscles, organs, body fluids and adipose tissues.
These body components are subjected to normal change as a result of growth, reproductive
status and variation in physical activity, socio-demographic factors e.g. aging, eating
practices and nutritional knowledge (Laquatra, 2004). Maintaining constant bodyweight
is coordinated by a complex system of neural, hormonal and chemical mechanisms that
keep the balance between energy intake and energy expenditure within precise limits.
Abnormalities of these mechanisms result in exaggerated weight fluctuations such as
underweight, overweight and obesity with overweight and obesity being the most common
worldwide (Laquatra, 2004).
Obesity is becoming a worldwide problem affecting all levels of society and is thus
being described as a global epidemic (WHO, 1998). Because childhood obesity often
persists until adulthood, an increasing number of adults will be at an increased risk of these
conditions as well as of cardiovascular disease, osteoarthritis and certain types of cancer
(Fontaine et al., 2003 and Manson et al., 2003).
Certain food groups and nutrients have been related to healthy dietary patterns and
a decreased risk of obesity. Diets mainly consisting of foods such as low-fat milk products,
a variety of fruits and vegetables, whole grains and high fiber intake are associated with
lower energy intakes (Drapeau et al., 2004) and smaller gains in body mass index (BMI
2
kg/ m ) over time (Togo et al., 2001 and Newby et al., 2004). Also, healthy dietary
patterns are associated with healthy lifestyle factors such as being more physically active
(Brodney et al., 2001 and Sjoberg et al., 2003) and regular consumption of main meals
including breakfast (Sjoberg et al., 2003).
Studies have suggested that several characteristics of dietary behavior such as
eating frequency, the temporal distribution of eating events across the day, breakfast
skipping, and the frequency of meals eaten away from home, together referred to as ―eating
patterns,‖ may influence body weight. (Yunsheng et al., 2003). Changes in eating
behaviors, diet quality, and physical activity may result in an increased risk of obesity
(Demory et al., 2004). Dietary patterns are important precursors of disease and good
health. Dietary patterns predict cardiovascular disease (Huijbregts et al., 1997) and colon
cancer (Slattery et al., 1998) and are related to body mass index (BMI) and plasma
5
micronutrients levels (Haveman et al., 1998). Furthermore, eating habits have also
changed and current habits include low consumption of fruits, green vegetables and milk;
increasing consumption of snacks, sweets, soft drinks and skipping breakfast. These eating
habits result in continuous increase in adiposity (Hanley et al., 2000)
Children develop their eating habits and food preferences as they grow (Birch and
Fisher, 1998). Many different factors influence food habits in a complex interactive way.
Parents and the family environment are very important for young children to learn and
develop food preferences and eating habits in a dual way (Story et al., 2002). On the other
hand as providers of the food children eat, family members are also have great influence on
the children norms related to food and eating practices. As children grow and start school,
teachers, peers and other people at school together with the media and social leaders
become more important. Progressively children are more independent and start making
their own food choices. The peer group is a key for adolescents and has a major influence
in developing food habits and lifestyles (Cusatis and Shannon, 1996).
The transition period from late adolescence to young adulthood (persons aged 1824 years) is a particularly difficult time where many behavioral and physiological changes
occur (Cusatis et al., 2000 and Lytle et al., 2000). An important subset of persons aged
18-24 are college students, who experience a transitional period compacted with
environmental changes characterized by unhealthy dietary patterns and reduced physical
activity which place students at a greater risk of weight gain (Brevard et al., 1996;
Mokdad et al., 1999 and Carson et al., 2002). Such as overweight and obesity,
cardiovascular disease, diabetes, hypercholesterolemia, high fat, hypertension, lowered
immune resistance, iron deficiency anemia, some types of cancer, osteoporosis and dental
caries (WHO, 2002). Lower education and socio-economical family background is
associated with less healthier dietary patterns. Other studies point these population groups
as higher risk for overweight both for children and adults in the family (Serra and
Aranceta, 2001).
2.2 Nutrition and health for healthy young adult students:
Healthy nutrition should be an integral part of daily life that contributes to the
physiological, mental and social wellbeing of individuals (FAO and WHO, 1992). A
healthy diet means that the amount and variety of foods is adequate to provide the body
with all the nutrients required in adequate proportions. No single nutrient is inherently
good or bad, but the proportion in which it is provided by the diet is important. In other
6
words, no single food is enough – except for breast milk for newborns – and a variety of
foods are needed in the diet. The frequency with which they are part of the diet is what
makes the diet healthy or unhealthy. Food and eating are important and powerful
expressions of cultural and social identity (Rachael, 1999). Food provides the nutrients
needed to form and maintain body tissues (protein, iron and calcium), energy for physical
activity and metabolism (fat and carbohydrate) and nutrients for regulating body processes
(vitamins and minerals). Studies support the theory that good nutrition contributes to
improving the wellbeing of children and their potential learning ability, therefore
contributing to better school performance (Pollit, 1990).
Cardiovascular diseases and cancer are the leading causes of adult death
(European Commission, 1996). Diet and inadequate physical activity are related to the
development of these chronic diseases. Various studies show that the risk factors for these
processes, such as overweight or high levels of serum cholesterol, start in early youth
(Nicklas et al., 1993b). Obese children and adolescents tend to become obese adults (Guo
et al., 1994 and Dietz, 1997). A healthy diet and physical fitness from early life will
probably positively affect health in adulthood by potentially reducing chronic disease.
Outlining food consumption patterns is key in assessing dietary adequacy and
safety, representing important aspects in evaluating the relationship between diet and
health, including the role of consumers' attitudes, preferences and lifestyle related to socioeconomic situation and cultural models. As food consumption patterns change over time,
public health authorities and the food industry need to monitor the dietary intakes of the
population (Haraldsdottir et al., 2001).
Changes in dietary habits and physical activity have been implicated as potential
causes of obesity. Previous research has shown that weight depends on energy balance
defined as the relation between energy intake and energy expenditure (Yunsheng et al.,
2003) Although weight gain results from an imbalance between energy intake and
expenditure, little is known about dietary factors contributing to weight gain and the
development of obesity. Numerous clinical trials, mostly short term, have examined the
role of individual macronutrients such as fat, carbohydrates, and protein in weight loss
among overweight and obese individuals, but few studies are conclusive, and the effects of
dietary modification of the macronutrient composition on weight loss remain controversial
(Astrup et al., 2004). In addition, little is known about what dietary characteristics
determine long term energy balance, which is a different question from which dietary
intervention may be effective for short-term weight loss. Most likely, the overall eating
7
pattern, rather than intakes of single nutrients or foods, affects long-term weight gain or
maintenance because dietary patterns reflect cumulative effects of the diet. However, few
studies evaluated the role of dietary patterns in long-term body weight regulation (Newby
et al., 2004).
Studies have suggested that several characteristics of dietary behavior such as
eating frequency, the temporal distribution of eating events across the day, breakfast
skipping, and the frequency of meals eaten away from home, together referred to as ―eating
patterns,‖ may influence body weight (Jenkins et al., 1994; Bellisle et al., 1998; Keim, et
al., 1997b and Stanton et al., 1989). However, these earlier studies of the effect of eating
patterns on body weight have not accounted for the effects of total energy intake and
physical activity, which may confound results and introduce misclassification of dietary
variables (Willett, 1990).
Dietary patterns are important precursors of disease and good health. Dietary
patterns predict cardiovascular disease (Huijbregts et al., 1997) and colon cancer
(Slattery et al., 1998) and are related to body mass index (BMI) and plasma micronutrients
levels (Haveman et al., 1998). In comparison to individual foods or nutrients, dietary
patterns are more realistic in describing the relation of diet to health and disease because
neither one nutrient nor one food adequately describes dietary behavior. Identification of a
good or bad food or nutrient is less helpful than describing healthy dietary or food patterns,
which assist people to understand the totality of diet while selecting foods that meet their
tastes and life styles (Gertraud et al., 2000).
Epidemiologic studies show that lifestyle habits, such as food intake during young
adulthood, may have long-term health implications and the food intake of young adults is
not as nutritionally sound as desired (Keim et al., 1997a). The eating behaviours and food
choice of university students are determined by an interaction of various different factors
(Jas, 1998). The first are biological factors such as changing energy demands, weight
change. The second one is sociocultural factors like availability, price of food. The third is
cultural factors. There are also psychological factors such as freedom from parental control
and the need to keep up with changes in the world in which they find themselves (Sanlier
and Unusan, 2007).
The transition period from late adolescence to young adulthood is a particularly
difficult time where many behavioral and physiological changes occur (Lytle et al., 2000
and Cusatis et al., 2000). Eating behaviors, diet quality and physical activity may change
throughout this transition resulting in an increased risk of obesity (Demory et al., 2004). It
8
has been found that the body mass index of young adults was higher than the BMI of
adolescents (Gordon et al., 2004). This transition period is also characterized by decreased
milk and fruit consumption but increased carbonated and/or sweetened beverage
consumption (Lien et al., 2001 and Demory et al., 2004).
Physical activity has also been shown to decline from adolescence to young
adulthood (Gordon et al., 2004). Decreased diet quality and decreased physical activity
characteristic of this transition period together serve as strong predictors of adult obesity
(Irwin, 2004). Certain nutrients and dietary patterns have been associated with successful
weight maintenance. Fruits and vegetables are high in water and fiber, incorporating them
in the diet can reduce energy density, promote satiety, and decrease energy intake (Rolls et
al., 2004 and Drapeau et al., 2004).
The 2005 Dietary Guidelines recommend three or more ounce-equivalents of whole
grains per day for healthy adults (US Department of Agriculture, 2005). Whole grains
are a good source of fiber and may help with weight maintenance by promoting a more
slowly processed meal, earlier feelings of satiety and increased micronutrient intake
(Martlett et al., 2002). Consumption of milk products has been associated with overall
diet quality and may have beneficial effects on body weight (Davies et al., 2000; Lin et
al., 2000 and US Department of Agriculture, 2005).
Dietary patterns that are low in fat and sugar, high in fruit and vegetables can
decrease body weight or prevent body-weight gain over time (Newby et al., 2003 and
Drapeau et al., 2004). Also, consuming four or more meals per day may significantly
reduce the risk of obesity compared to eating three or fewer meals per day (Yunsheng et
al., 2003). Particularly, meal patterns including regular breakfast consumption have been
associated with lower body weight and improved dietary intake (Sjoberg et al., 2003).
Adults who skip breakfast are at higher risk for weight gain and are more likely to have
less healthy behaviors such as increased snacking, sedentary lifestyle, smoking and high
BMI (Keski et al., 2003).
2.3 Socio-demographic factors associated with weight status.
Socio-demographic factors that influence body weight include gender, age,
educational level, occupational status, family size, socio-economic status and physical
activity will be discussed.
9
2.3.1 Gender
Gender plays an important role in influencing the rates of overweight and obesity
between men and women in those women are generally more overweight than men.
According to York et al., (2004), obesity is characterized by gender difference, with the
rate of obesity in women 3 to 5 times than that in men.
2.3.2 Age
Age has a significant influence on overweight and obesity. Literature has shown
that the incidences of overweight and obesity increase with age, particularly in post
menopause women (Lahmann et al., 2000 and Temple et al., 2001). According to
Temple et al., (2001), the incidence of obesity increases significantly with age, with 32 %
of women being obese at age 25 to 44 years, rising to 49 % at ages 45 to 64 years; while a
much lower prevalence of obesity was seen in men, 14 % at 35 to 65 years. With regards to
age and gender, studies by IASO (2004), revealed the prevalence of overweight including
obesity among young people aged 13 to19 years to be 17 % affecting more girls than boys
at a rate of 25 % and 7 %, respectively.
2.3.3 Education Level
Education attainment has been associated with body weight. It was found that
women with a low education attainment have higher weight gains compared to those with
higher education. Education attainment can lead to the acquisition of a different lifestyle
which may impact either positively or negatively on body weight (Sundquis & Johansson
(1998), Lahmann et al., 2000; Puoane et al., 2002 and Kruger et al., 2005).
2.3.4 Socio-economic status
Variation in socio-economic status has been related to the variation in rates of
overweight and obesity (Cavalli-Soforza et al., 1996; Moreno et al., 2004 and Kruger et
al., 2002). According to Ferro-Luzzi and Puska (2004), overweight and obesity tend to
be highest among low-income populations in developed countries, and among more
affluent people in developing countries. The authors concluded that as economies improve,
so is the risk of becoming obese as a result of improved access to food, decreased physical
activity, and consumption of a ‗Western‘ diet.
10
2.3.5 Physical activity
Physical activity can increase energy expenditure and contribute to weight loss.
According to Whitney et al., (2007), people may be obese not because they eat too much
but because they expend too little energy e.g. having none or very little physical activity.
Studies by Kruger et al., (2002) and Moreno et al., (2004) found that decreased physical
activity and consumption of ‗Western‘ diet are two most important factors contributing to
the high increase in overweight and obesity. Laquatra, (2004) explains that physical
activity results in energy expenditure due to an increase resting metabolic rate (RMR),
thus, contributing to body weight management.
2.4 Food groups
Food groups is a diet planning tool that sorts foods of similar origin and nutrient content
into groups and then specifies that people should eat a certain numbers of servings from
each group. Food groups assigns foods into five major groups: (1) fruits, (2) vegetables, (3)
grains, (4) meat, poultry, fish, legumes, eggs and nuts, (5) milk, yoghurt and cheese. Food
groups also indicate the most noticeable nutrient of each food group and lists foods within
each group sorted by nutrient density. Food groups also include a Food Guide Pyramid,
which presents the daily food guide in pictorial form (Cataldo et al., 2003).
2.4.1 Food Guide Pyramid for good eating practices
Food guide pyramid translates dietary guidelines of nutrient recommendations into
visual form of the kinds and amounts of food to eat each day (Earl, 2004). The food guide
pyramid was developed based on nutritional problems, food supplies, eating habits and
cultural beliefs of the American population. The aim of the food guide pyramid was (and
still is) to promote good health and reduce the risk of chronic diseases, such as, heart
disease, certain types of cancer, diabetes and stroke (Escott-Stump and Earl, 2008). The
food guide pyramid is built around five main food groups (e.g., grains, vegetables, fruits,
milks, meats and beans), with recommended daily amounts (Smolin and Grosvenor,
2008). The pyramid shape, with grains at the base, conveys a message that grains should be
abundant and form the foundation of a healthy diet. Fruits and vegetables share the next
level of the pyramid, indicating that they should have a prominent place in the diet. Meats
and milks appear in a smaller section near the top meaning that a few servings of each can
provide valuable nutrients. Fats, oils, and sweets occupy the part at the top of the pyramid,
indicating that they should be consumed sparingly and only after basic nutrient needs have
11
been met by foundation foods. An advantage of the food guide pyramid is that the
recommended number of portions from each food group is indicated which makes this
food guide pyramid a suitable tool for the evaluation of food intake of individuals and
groups of individuals.
Figure 1: Food guide pyramid (Cataldo et al., 2003)
Table 2: Serving recommendations according to the Food Guide Pyramid (Earl,
2004)
Food groups
Adults
Bread, cereal, rice and pasta
6 – 11 servings /day
Fruit
2 – 4 servings / day
Vegetables
3 – 5 servings / day
Meat and meat alternatives
2 – 3 servings / day
Milk and milk products
2 – 3 servings / day
Fats and sweets
Use sparingly
12
Table 3: Portion sizes for adults (Mathai, 2004)
Grain group
1 slice of bread
½ cup of cooked rice or
Fruit group
Meat group
1 piece of fruit or melon
30g of cooked lean meat,
wedge
poultry, or fish, 1 egg
½ cup of juice
½ cup of cooked dry beans
½ cup of canned fruit
2 tablespoons of peanut
pasta
½ cup of cooked porridge
butter (add one fat exchange)
½ cup of ready-to-eat cereal
½ cup of dried fruit
1/3 cup samp
Vegetable group
Milk group
Fats and sweets
½ cup of chopped raw or
1cup of milk or ½ yogurt
Use sparingly
30g of cheese
2 teaspoons sugar
cooked vegetables
1 cup of raw leafy
vegetables
2 hardboiled sweets
10 ml of mayonnaise
5ml oil, 10ml margarine
(medium fat)
2.5 Dietary factors associated with weight status.
2.5.1 The effect of fruits and vegetables on body weight:
Noncommunicable diseases (NCD), including cardiovascular diseases (CVDs),
diabetes, obesity, cancers and respiratory diseases, account for 59% of the 56.5 million
deaths annually worldwide and for 45.9% of the global burden of disease. Five of the ten
leading global disease burden risk factors identified by WHO 2002 – high blood pressure,
high cholesterol, obesity, physical inactivity and insufficient consumption of fruits and
vegetables – are among the major causes of these diseases (WHO, 2002).
According to the WHO 2002, low fruits and vegetables intake is estimated to cause
about 31% of ischaemic heart disease and 11% of stroke worldwide. Overall, it is
estimated that up to 2.7 million lives could potentially be saved each year if fruits and
vegetables consumption were sufficiently increased.
13
Observational epidemiologic studies have suggested that dietary nutrients such as
potassium, antioxidants, and folic acid—abundant in fruits and vegetables are associated
with a lower incidence and mortality from cardiovascular disease and certain cancers
(Khaw et al., 1987; Morrison et al., 1996 and Khaw, 1999;).
A recently published (WHO) report recommends as a population-wide intake goal
the consumption of a minimum of 400g of fruits and vegetables per day (excluding
potatoes and other starchy tubers) for the prevention of chronic diseases such as heart
disease, cancer, diabetes and obesity, as well as for the prevention and alleviation of
several micronutrient deficiencies, especially in less developed countries (WHO, 2003).
Eating a variety of vegetables and fruits clearly ensures an adequate intake of most
micronutrients, dietary fibers and a host of essential non-nutrient substances. As well,
increased fruit and vegetable consumption can help displace foods high in saturated fats,
sugar or salt and may also reduce a person‘s risk of chronic diseases such as stroke,
cardiovascular disease (CVD), type 2 diabetes, and certain cancers (WHO, 2003 and US
Department of Agriculture, 2005). Several intervention trials that advised subjects to
increase fruit and vegetable intake found that subjects successfully maintained their body
weight (Zino et al., 1997; Maskarinec et al., 1999 and Smith-Warner et al., 2000).
Energy density is defined as the amount of energy per unit weight of food (kcal/g
or kJ/g) (Yao et al., 2001). Water is the component of food that has the biggest impact on
energy density, as it adds weight to food without increasing calories, and therefore
decreases energy density (Grunwald et al., 2001). Energy density is reduced by higher
intake of fruits and vegetables (Haslam et al., 2005). Incorporating more fruits and
vegetables can reduce the overall energy density of the diet, promote satiety and decrease
the total energy intake and increase diet quality (Rolls et al., 2004; Rolls. 2005 and
Ledikwe, 2006).
Previous research has shown that increased satiety and decreased energy intake at
subsequent meals was associated with reducing the energy density of a preload by
increasing the water content (Rolls et al., 1998 and Rolls et al., 1999). Furthermore
significant decreases in BMI were also found as fruit and vegetable intake increased in
subjects from the National Health and Nutrition Examination Survey Epidemiologic
Follow-up Study (Bazzano et al., 2002).
The mechanisms for the inverse association between fruit and vegetable intakes and
body weight are uncertain. Fruits and vegetables could increase satiety in a similar way
due to their low energy density and high water content (Poppitt et al., 1996 and Yao et
14
al., 2001). The energy density of foods also affects satiation, or the processes involved in
the termination of a meal. Satiation is studied by measuring intake when foods are freely
available (Beth, 2005). In one particular study, the satiety index of 38 common foods was
compared and researchers concluded that fruits received the highest satiety rating (Holt et
al., 1995).
Promoting increased fruits and vegetable consumption for successful weight loss
and weight maintenance emphasizes a positive message rather than a negative approach to
weight. Encouraging increased consumption of healthy foods instead of restricting
particular foods, which is often associated with dieting, is a healthy option for the public to
follow (Rolls et al., 2004).
2.5.2 The effects of calcium and dairy foods on body weight:
During the past 25 years, researches have demonstrated the potentially beneficial
roles for calcium and/or dairy foods with regard to a variety of disorders. These disorders
include osteoporosis, hypertension, certain cancers, insulin resistance syndrome and
obesity (Nicklas et al., 2003). Low levels of dietary calcium and dairy products increase
the risk of hypertension and insulin resistance syndrome (IRS) (McCarron et al., 1999;
Griffith et al., 1999 and Pereira et al., 2002). The Coronary Artery Risk Development in
Young Adults (CARDIA) study showed that dairy product consumption was inversely
proportional to all components of the IRS, including obesity (Pereira et al., 2002).
For adults (including women who are pregnant or breastfeeding) and for children
age 1 year or older, the safe upper limit of calcium intake is 2500 mg per day (National
Academy of Sciences, 2009). Low calcium intake has been identified as a potential
contributing factor to obesity (Zemel et al., 2004). Calcium and total dairy intakes have
been associated with decreased body fat and increased dietary variety and may be one
important adjustable factor in a person‘s diet that may decrease their risk of developing
obesity later in life (Skinner et al., 2003 and Weinberg et al., 2004).
Epidemiologic and experimental studies suggest that dairy products may have
favorable effects on body weight in children (Carruth and Skinner, 2001) and adults
(Davies et al., 2000; Lin et al., 2000 and Zemel et al., 2000). Intracellular calcium has
been shown to play a key role in metabolic disorders associated with obesity and insulin
resistance (Draznin et al., 1987; Draznin et al., 1988 and Byyny et al., 1992). Many
epidemiological studies have identified an inverse relationship between calcium intake,
body fat, BMI and body weight (Jackmain et al., 2003 and Zemel et al., 2004).
15
For example, Lin et al., 2000 found that calcium intake in young women (as a ratio
to caloric intake) was inversely related to weight and fat gain over a period of 2 years. In
preschool children, Carruth and Skinner, 2001 found that calcium was inversely related
to fat mass. Other study conducted by McCarron, 1983 revealed an inverse relationship
between calcium intake and body weight in the National Health and Nutrition Examination
Survey I. More recently, Zemel et al., 2000 reported a similar result from National Health
and Nutrition Examination Survey III, in that the relative risk of being in the highest
quartile for adiposity was 0.16 for those in the highest quartile for calcium intake
(compared with those in the lowest quartile).
In a study of adipose cells in transgenic mice, high-calcium, medium-dairy and
high-dairy diets reduced lipogenesis, stimulated lipolysis and reduced body fat
accumulation at equivalent levels of energy intake (Zemel, 2002).
Dietary calcium has also been associated with a reduction in body fat in mice and
humans, particularly younger and older women (Lin et al., 2000; Lovejoy et al., 2001 and
Zemel et al., 2004). Children‘s dietary scores were positively related to calcium intake and
negatively related to carbonated/sweetened beverage intake (Skinner et al., 2003). In
adults, total dairy intake was associated with higher micronutrient intakes without
influencing fat or dietary cholesterol, suggesting that people who consume more dairy
foods may also make healthier choices related to their diet (Weinberg et al., 2004).
2.5.3 The effects of fiber and whole grains on body weight:
Over the past 20 years, major governmental, scientific and nonprofit organizations
have recommended whole grains as part of a healthful diet. Grain foods form the base of
The Food Guide Pyramid, which recommends consuming six to eleven servings each day,
including ―several‖ whole-grain servings (Cleveland et al., 2000).
Whole grains are rich sources of dietary fibers, starch, vitamins (particularly
vitamin E), minerals, complex carbohydrates, phyto-oestrogens, antioxidants and other
substances that have been related to body weight regulation and reduction of insulin
resistance and cardiovascular disease risk factors (Slavin et al., 1999 and Anderson et al.,
2000).
Whole grain intake is associated with decreased risk of developing CVD, diabetes,
hypertension, all-cause mortality, and may reduce total blood cholesterol (Cleveland et al.,
2000 and Steffen et al., 2003). Whole-grain foods may protect against chronic diseases by
altering serum cholesterol profiles, exerting antioxidant properties and anti-thrombotic
16
action, and through their favorable effects on vascular reactivity and insulin sensitivity
(Anderson and Hanna, 1999). The majority of grain products consumed in the United
States are highly refined (Slavin et al., 1999 and Putnam et al., 2002). This falls below
the minimum three servings/day recommended in the 2005 Dietary Guidelines (DG).
Refined grains are the counterpart to whole grains, but evidence is conflicting about
associations with metabolic and anthropometric variables (Liu et al., 2003; McKeown et
al., 2004; Bazzano et al., 2005 and Sahyoun et al., 2006), although some evidence shows
that consumption of refined grains is associated with a risk of cancer (Slattery et al., 1997
and Levi et al., 2000).
Refined-grain products have higher starch content but lower fiber content (i.e.,
greater energy density) than do whole grains. Concentrations of vitamins, minerals,
essential fatty acids, and phytochemicals that are important in carbohydrate metabolism are
also lower in refined grains (Liu, 2002).
Fruits, vegetables, whole grains, and legumes are generally lower in fat, added
sugars and promote earlier satiety compared to more calorically dense foods (Martlett et
al., 2002). Fibers enhance satiety, and the secretion of gut hormones (Koh-Banerjee and
Rimm, 2003), thereby affecting body weight and body composition through its effect on
energy intake.
Data from the Third National Health and Nutrition Examination Survey (NHANES
III, 1988 to 1991) gives mean values of 16.6 to 20.0 g/day of fiber needed for men and 12.5
to 14.7 g/day for women in age groups of 20 to 29 through 80 year and older (Alajma et
al., 1994). Some authorities recommend 20 to 30 grams of fiber daily, with an upper limit
of 35 grams (Butrum et al., 1988, Public Health Service, 1988 and American Diabetes
Association, 1998).
Diets with increased whole grain intakes are associated with a healthier dietary
profile, including greater intakes of fruits and vegetables, fiber, iron, zinc, calcium, folate,
and vitamin E and lower intake of saturated fatty acids, meat, cholesterol (McKeown et
al., 2002; Liu et al., 2003 and Steffen et al., 2003).
Women with high intake of whole grains smoked less, exercised more, and were
more likely to use postmenopausal hormones. A general opposite effect was seen in
women with greater intake of refined-grain products (Liu et al., 2003).
While whole-grain foods have been hypothesized to protect against obesity,
epidemiological data that directly examine whole grain versus refined grain intake in
relation to obesity are sparse. In the Iowa Women‘s Health Study whole grain intake was
17
inversely correlated with body weight and fat distribution in comparison with a weaker
direct relationship for refined grain consumption and body size (Jacobs et al., 1998).
There were inverse dose-response relations of both BMI and waist circumference
with whole grain intake (Steffen et al., 2003). The inherent high-fiber content of most
whole-grain foods may prevent weight gain or promote weight loss (McKeown et al.,
2002).
Proposed mechanisms for the role of high fiber diets that contain whole grains
include favorable effects on weight loss and weight maintenance by decreasing energy
intake due to its bulk, low energy density and through promoting earlier satiety (KohBanerjee et al., 2003).
The intake of whole grains may also slow starch digestion or absorption, which
leads to relatively lower insulin and glucose responses that favor the oxidation and
lipolysis of fat rather than its storage (Liu et al., 2003). Refined-grain foods more than
double the glycaemic and insulinaemic responses compared with whole-grain foods (KohBanerjee et al., 2003).
2.5.4 The effects of dietary patterns on body weight:
Some studies have suggested that eating patterns, which describe eating frequency,
the temporal distribution of eating events across the day, breakfast skipping, and the
frequency of eating meals away from home, together referred to as "eating patterns," may
influence body weight (Yunsheng et al., 2003). However, these earlier studies of the effect
of eating patterns on body weight have not accounted for the effects of total energy intake
and physical activity, which may confound results and introduce misclassification of
dietary variables (Willett, 1990).
Berrigan et al., 2003 analyzed patterns of health behaviors in US adults, described
by adherence to the public health recommendations for exercise, tobacco, alcohol, dietary
fat and fruit and vegetable intake using data from NHANES III (1988-1994). The healthy
dietary pattern which was high in fruit, reduced-fat dairy products, high-fiber cereal, whole
grains, low in red & processed meats, fast food, and soda showed smaller gains in both
BMI and waist circumference than did the other dietary patterns (white bread, sweets,
alcohol, meat and potatoes) (Newby et al., 2003).
Consuming higher amounts of high energy/low nutrient foods, red and processed
meat, fat, sugar and low diet variety are associated with an increased risk of obesity and
greater gains in BMI over time (Togo et al., 2001 and Newby et al., 2003).
18
There is a relation between healthy dietary pattern and lifestyle factors (Sjoberg et
al., 2003). Being more physically active is associated with lower BMI and an improved
diet profile, consuming a higher percent of energy from dietary fiber, protein and
micronutrients such as folate, calcium, vitamin A, vitamin C and vitamin E (Brodney et
al., 2001). On the other hand decreased diet quality is associated with less exercise and
frequency of eating meals away from home (Fung et al., 2001 and Yunsheng et al.,
2003). Both breakfasts and dinners eaten away from home were significantly higher in
total calories, percentage of calories from total fat, and saturated fat but lower in
percentage of calories from protein, carbohydrate, and fiber than were breakfasts or dinners
eaten at home. (Yunsheng et al., 2003).
Irregular main meal intake may be related to poorer lifestyle factors and decreased
diet quality compared to regular main meal intake. (Sjoberg et al., 2003). The number of
eating episodes was inversely associated with the risk of obesity. Furthermore it was found
that an increased risk of obesity if number of meals reported three or fewer eating episodes
per day (Yunsheng et al., 2003). Breakfast skipping in these subjects was also associated
with an increased risk of obesity (Ma et al., 2003).
2.5.5 The effects of breakfast on body weight:
Breakfast's status as the most important meal of the day is more than just an old
saying. Breakfast has been defined as the first meal after awakening, a meal consumed at a
certain time of day, a certain type of food consumed, and whatever a person perceives as
"breakfast" (Boston et al., 2008).
Most commonly, breakfast is defined as any food or beverage consumed between 5
AM and 10 AM on weekdays or 5 AM to 11 AM on weekends (Affenito et al., 2005 and
Barton et al., 2005). The proportion of people regularly consuming breakfast is in decline,
and skipping breakfast is associated with other lifestyle choices such as low levels of
physical activity and high levels of soft-drink consumption (Rampersaud et al., 2005).
Furthermore skipping breakfast is more common among children and adolescents of low
socioeconomic position (Rampersaud et al., 2005).A cross-sectional association between
skipping breakfast and obesity has been shown in adults (Ma et al., 2003 and Song et al.,
2005). Female are more likely to skip breakfast that usually comprises total nutrient
sufficiency (DiMeglio, 2000). Regular breakfast consumption has been associated with
healthier diet choices and lifestyle behaviors in children, adolescents and adults (KeskiRahkonen et al., 2003 and Nicklas et al., 2004). Regular consumption of breakfast cereal
19
is associated with lower body mass index (BMI) in adults (Cho et al., 2003) and children
(Albertson et al., 2003), and greater energy intake at breakfast is associated with lower
BMI in adolescents (Summerbell et al., 1996). A large prospective study conducted in
men
showed
a
decreased risk
of
weight
gain
among
regular
consumers
of breakfast cereal (Bazzano et al., 2005).
Moderately obese women lose more weight when they consume 70% of their daily
energy intake before noon instead of in the afternoon and evening. Additionally, lean
individuals lose weight when consuming a 2000-calorie meal at breakfast but tend to gain
weight if the meal is eaten at dinner (Cho et al., 2003).
Regular breakfast consumption was also inversely related to serum total cholesterol
and obesity, two risk factors for cardiovascular disease that may continue into adulthood
(Nicklas et al., 2004).
Moreover, many studies have shown significant relationships between skipping breakfast
and depressive symptoms, stress, catching cold, chronic disease (Yang et al., 2006), and
high body mass index (BMI) in adolescents (Keski-Rahkonen et al. ,2003; Ma et al.,
2003 and Kumar et al., 2004). Breakfast skipping may also be an indicator of risk to
weight gain: among those who skip breakfast, increased snacking, lunch skipping,
sedentary lifestyle, and obesity are more common than among breakfast eaters (KeskiRahkonen, et al, 2003). Skipping breakfast is associated with low levels of
physical activity, fruit and vegetable intake, increased levels of dietary fat, soft-drink
consumption, smoking, infrequent exercise, low education level at age 16, and high BMI.
Breakfast skipping is more prevalent in lower socioeconomic status groups (KeskiRahkonen et al., 2003; Ma et al., 2003 and Rampersaud et al., 2005). Reasons given for
skipping breakfast commonly include lack of time for the preparation & consumption of
food and concerns about excess body weight (Bellisle et al., 1995; Ruxton et al., 1997
and Chapman et al., 1998). Breakfast skipping can lead to overeating later in the day for
example, having one big meal in the evening (Schlundt et al., 1992 and Martin et al.,
2000).
In contrast, eating breakfast is associated with increased eating frequency.
Increased eating frequency may in turn promote less efficient energy utilization by
increasing dietary induced thermogenesis, leading to lower BMI (Cho et al., 2003). In
general, individuals who eat breakfast regularly have more adequate micronutrient intakes
and lower percentages of calories from fat (Chapman et al., 1998). Common breakfast
foods that are high in calcium include milk, yogurt and cheese. Huang et al., 1997
20
concluding that eating breakfast, especially cereals and breads, reduced fat intake and
helped increase fiber intake of young adults. Calcium and fiber intakes, along with vitamin
D, vitamin C and phosphorus are significantly higher in breakfast eaters and intakes of
these nutrients increase with frequency of breakfast consumption (Nicklas et al., 1998 and
Rampersaud et al., 2005;).
Breakfast consumers have a higher daily intake of vitamins A, B6, B12, and calcium
and have better eating habits than nonconsumers of breakfast (Siega-Riz et al., 1998).
Children and adolescents who skipped breakfast failed to meet the recommended dietary
allowance (RDA) recommendations for several vitamins and minerals including vitamin A,
vitamin D, calcium, and iron (Nicklas et al., 2004 and Rampersaud et al., 2005).
Researchers found that more than one third of breakfast skippers consumed less than 50%
of the RDA for vitamins A, E, B6, and folate, and nearly one fourth consumed less than
50% of the RDA allowance for energy, vitamin C, calcium, and iron (Williams, 2008).
Furthermore, researchers found that young adults who skipped breakfast did not
meet two thirds of the RDA recommendations and the odds for dietary inadequacy were 2
to 5 times higher compared to those who ate breakfast (Nicklas et al., 1998 and Nicklas et
al., 2004). Breakfast consumption has declined during the past 25 years in all age groups,
especially among adolescents (Nicklas et al., 2004). The percentages of young adults
skipping breakfast are 2 times higher than what is reported for younger children (Nicklas
et al., 1998 and Barton et al., 2005). Eating habits become more regular with age; equally
well breakfast eating may become less common among the younger generations, who will
continue their lower rates of breakfast consumption through adulthood (Keski-Rahkonen
et al., 2003).
2.5.6. The effects of physical activity on body weight.
An epidemic of overweight and obesity is evident among all age groups, including
children and adolescents (Ogden et al., 2002). Current obesity rates among all age groups
are two-to-three times higher than they were just 20 years ago (Hedley et al., 2004). The
greatest deterioration in physical activity has been observed between the ages of 15 and 18
years, and a continuous decline is common between 18 and 29 years of age (Caspersen et
al., 2000). According to the Behavioral Risk Factor Surveillance System (BRFSS; 1991–
1998), the greatest increases in obesity rates were among 18–29-year-olds and those who
had some college education (Mokdad et al., 1999).
21
The transition period between adolescence and early adulthood is accompanied by
lifestyle changes that predispose young adults to become less physically active (Telama et
al., 2000; Van Mechelen et al., 2000 and CDCs, 2001). Eating behaviors, diet quality and
physical activity may change throughout this transition resulting in an increased risk of
obesity (Demory-Luce et al., 2004). A10-year annual assessment of physical activity in
2,322 girls beginning at ages 9 to 10, showed significant reductions in physical activity by
age 18 to 19 years (Kimm et al., 2000).
Johnson et al., 1998 study examined health behaviors and their relation to various
types of physical activity among university seniors. The researchers recruited 576 seniors
(mean age 24.5 ± 2 years) to participate in a study comparing two health courses.
Hierarchical multiple regressions were conducted to determine whether health behaviors of
men and women were associated with physical activity after adjusting for potential
demographic confounders. Physical activity measures included leisure-time moderate and
vigorous activities, flexibility, and strengthening activities. They found that not eating
healthy foods was associated with consuming fatty foods by men and women. For women,
vigorous physical activity was related to eating healthy foods, and strengthening activities
were related to eating fewer fatty foods. Researchers concluded that physical activity had
modest associations with eating behaviors in college students but not with other healthrelated behaviors. Haberman and Luffey, 1998 study indicated that only 39% of the
students reported exercising 3 or more times per week; 76% of the students reported that
they ate the same foods day after day.
On average, students reported engaging in aerobic exercise, male students were
more likely to report aerobic exercise and more days per week than female students.
Students aged ≤ 19 years were more likely to report aerobic exercise than students aged ≥
20 years, suggesting that physical activity may decrease over time (Huang et al., 2002).
The National College Health Risk Behavior Survey suggests that as many as 35% of
college students may be overweight or obese (Huang et al., 2004).
2.5.7. The effects of diet quality on body weight.
Recent epidemiologic studies of diet and health outcomes including obesity have
changed the focus to the overall diet quality and dietary pattern instead of single nutrients,
such as dietary fat (Hu et al., 2000 and Fung et al., 2001a&b). This concept was
emphasized in the Dietary Approach to Stop Hypertension (DASH) trial, where a diet rich
in fruits, vegetables, and whole grains with only small amount of fat and meat has been
22
shown to be effective in reducing blood pressure (Appel et al., 1997. A previous research
has found a link between diet quality, as measured by the Healthy Eating Index (HEI), and
obesity (Guo et al., 2004).
The Healthy Eating Index (HEI) is a measure of diet quality that assesses
conformance to federal dietary guidelines across 10 dietary components, five of which are
food based (grains, vegetables, fruits, dairy, and meats). Four components measure
compliance with dietary guidelines for fat, saturated fat, cholesterol and sodium (Duffy et
al., 2008). The use of dietary indexes based on nutritional recommendations or dietary
guidance are centered on established knowledge of healthy eating. Scores for each
component range from 0 to 10, with 10 indicating the highest score and 100 indicating the
highest attainable HEI score (Kennedy et al., 1995).
Table 4: Components of the Healthy Eating Index (Bowman et al., 1998).
Score
ranges †
Criteria for maximum
score
Criteria for minimum
score
Grain consumption
Vegetable
consumption
Fruit consumption
Milk consumption
Meat consumption
0–10
6–11 servings
0 serving
0–10
3–5 servings
0 serving
0–10
0–10
0–10
Total fat intake
0–10
Saturated fat intake
0–10
Cholesterol intake
Sodium intake
0–10
0–10
Food variety
0–10
2–4 servings
2–3 servings
2–3 servings
30% or less of total
energy intake
Less than 10% of total
energy intake
300 mg or less
2400 mg or less
8 or more different items
in a day
0 serving
0 serving
0 serving
45% or more of total
energy intake
15% or more of total
energy intake
450 mg or more
4800 mg or more
3 or fewer different items
in a day
Component
The findings of Anding, et al., 2001 suggest that college women practice diet and
health behaviors that contradict the 1995 Dietary Guidelines (DG) for Americans.
Participants reported diets that were nutritionally adequate but exceeded national
recommendations for fat, sugar, and sodium. Their reports of exercise habits suggested that
the lifestyles of 66% of the respondents were sedentary. Mean total fat intake was 37% (±
4%) per day. Monounsaturated, polyunsaturated, and saturated fat accounted for 10% (±
4%), 5% (± 3%), and 11% (± 4%) of calories, respectively. Two thirds (66%) of the
23
participants exceeded recommended levels of saturated fat, and 20% exceeded desired
levels for cholesterol. Sodium consumption averaged 3,204 ± 1,941 milligrams. More than
half (57%) of the respondents reported sodium intakes that exceeded 2,400 mg per day. All
respondents were noncompliant with Dietary Guidelines (DG) for dietary variety.
Furthermore, Racette et al., 2005 assessed the weight, exercise, and dietary
patterns of 764 college students and found that 29% of students reported not exercising,
70% ate less than five servings of fruits and vegetables daily and more than 50% ate fried
or high-fat fast foods at least three times during the previous week. On the other hand, data
collected on serum cholesterol, blood pressure, and self-reported health behavior in two
hundred and twenty six college students aged 18 to 26 years participated in coronary heart
disease risk screening by providing blood samples. Researchers found that half or more of
the participants consumed a diet high in saturated fats and more than 30% did not consume
adequate amounts of fiber or get enough cardiovascular exercise (Spencer, 2002).
Huang et al., 2002 surveyed 738 college students aged 18 to 27 years to assess
overweight, obesity, dietary habits, and physical activity. A high percentage of subjects
were overweight and engaged in less than healthy dietary habits, such as low fruit and
vegetable intake, low fiber intake and low physical activity, however, no significant
associations were found between diet and physical activity.
24
CHAPTER (3)
3. Methodology
3.1 Introduction
The study assessed the association between food consumption patterns, nutrient
intake ,dietary habits and body weight in pharmacy college students at Al-Azhar
University in Gaza Strip. The ethical considerations, study design, study population,
variables ,work definitions, techniques, and statistical analyses that were used to achieve
the aim of the study are described in this chapter.
3.2 Ethical considerations
Ethical approval for the study was granted by Ethical Committee of Helsinki.
Permission to conduct study at the pharmacy college was obtained from dean of faculty of
pharmacy prior to the study. Participants were informed about the procedure to be used
during the research duration and had the right to discontinue the study. All students
provided written consent to participate in the research.
3.3 Study Design
A descriptive approach, cross-sectional design was used to determine association
between food consumption patterns, nutrient intake ,dietary habits and weight status in
healthy young adult students in a convenience sample of pharmacy college students at AlAzhar University in Gaza Strip.
Dietary intake was self-reported on 3-day food records and compared to dietary
guidelines for compliance with recommendations by Food Guide Pyramid. Face to face
questionnaire was considered to gather information from student's sample which includes
demographic, social, anthropometric information's and physical activity as well as
information on dietary habits, main meals and their food & beverage intake every day.
3.4 Subjects/ Setting
3.4.1 Setting of Study
Faculty of Pharmacy at Al-Azhar University Gaza Strip.
3.4.2 Subjects
The subjects were 140 healthy students (70 male and 70 female students) selected
to participate in the study. They were from the first, second, third, fourth and fifth level and
master of clinical nutrition, in the faculty of pharmacy at Al-Azhar University in Gaza.
25
The age range of these students was 19-30 years, assuming similarities in physical
activities and standard living conditions in order to decrease confounding variables.
3.4.3 Inclusion and exclusion criteria
Both male and female students who were registered for an undergraduate and post
graduate degree in the faculty of pharmacy at Al-Azhar University in Gaza were included.
Unhealthy students were excluded (suffer from chronic diseases).
3.5 Measurements
Nutrition status is assessed in different ways including anthropometrics, dietary
intakes, biochemical and hematological methods. All these methods can be applied to
assess nutritional status of individuals or groups (Al-rewashdeh and Al-dmoor, 2010).
3.5.1. Variables and operational definitions
Variables are descriptions or explanations of the terms that are measured to fulfill
the objectives of the research. Variables and operational definitions included in this study
were: Socio-demographic factors, food consumption patterns, eating habits and body mass
index.
3.5.1.1 Young Adulthood and Middle-Aged Adults: Ages 19 up to 30 Years and 31 up
to 50 Years
The recognition of the possible value of higher nutrient intakes during early
adulthood on achieving optimal genetic potential for peak bone mass was the reason for
dividing adulthood into ages 19 up to 30 years and 31 up to 50 years. Moreover, mean
energy expenditure decreases during this 30-year period, and needs for nutrients related to
energy metabolism may also decrease. For some nutrients, the Dietary Reference Intakes
(DRIs) may be the same for the two age groups. However, for other nutrients, especially
those related to energy metabolism, Estimated Average Requirements (EARs) and
Recommended Dietary Allowances (RDAs) are likely to differ for these two age groups
(National Academy of Sciences, 2005).
3.5.1.2 Socio-demographic factors
Socio-demographic factors include gender, age, education level, socio-economic
status and physical activity.
26
3.5.1.3 Eating practices
Eating practices refer to usual daily dietary intake, energy and macronutrient
intake, food consumption pattern and food frequency (Hammond, 2000).
3.5.1.3.1 Usual daily dietary intake
Usual daily food intake refers to the number of portions consumed from food
groups indicated in the Food Guide Pyramid, expressed as below, within or above
requirements (Earl, 2004).
3.5.1.3.2 Energy and macronutrient intake
Macronutrients are expressed as a percentage of total energy intakes and compared
with the Recommended Dietary Allowance (RDA) and Adequate Intakes (AI) of the
Dietary Reference Intakes (DRIs), and the acceptable macronutrients distribution ranges
for good health (Earl, 2004).
3.5.1.3.3 Food frequency questionnaire
Food frequency questionnaire (FFQ) (Appendix D) was used in the study to
determine the frequency of food consumption categorized as, ‗consumes it daily‘,
‗weekly‘, according to Nelson (2000). The questionnaire concentrated on food items
commonly consumed by most people, namely: sweets, chocolates, chips (crisps), cakes,
biscuits, cool drinks, coffee, tea, sugar, milk, eggs, soy beans, legumes, chicken, red meat,
fish, bread, cereal, margarine, fruit juice, fruit, vegetables, and salted stick.
3.5.1.3.4 Daily food record/diary
Daily food record/diary is a method of data collection, subjects were asked to
record, at the time of consumption, the identity and amounts of all foods and beverages
consumed (Hammond, 2000) for a period of three days.
The diet section of the study was based on the 3-day self-reported nutrient intake of
the respondents. The respondents were asked to provide as much information as possible
about serving size, method of cooking and all details of food consumption (i.e. fish with
skin or without skin). The transformation of food into energy and nutrients has been done
by a computer program that includes the food composition tables. Cut-off points were
calculated according to recommended daily intake. Students daily intake of energy and
27
nutrients are classified as sufficient (67-133%), insufficient (<67%) and over sufficient
(>133%) (Sanlier and Unusan, 2007).
3.5.1.4 Anthropometric measurements
The most commonly used anthropometric measurements to assess the nutritional
status for adults are height (m), weight (kg) and Body Mass Index. These measures are
then compared to reference standards to assess the risk for various diseases (Abu-Samak
et al., 2008 and Latiffah & Hanachi, 2008). All subjects were wearing light clothes, no
shoes and before ingesting more than one cup of liquid. The total body weight was
measured with firm digital portable scale with precision of 0.5 kg with the shoulder in a
relaxed position and arms hanging freely.
3.5.1.5 Laboratory tests:
3.5.1.5.1 Complete Blood Count (CBC) Analysis:
Blood sample were collected from volunteered students (140) by venipuncture in
ethylene diamine tetraacetic acid (EDTA) tubes and then transferred in suitable condition
to laboratory to perform complete blood counts (CBC) which include white blood cells
(WBCs), red blood cells (RBCs), hemoglobin (Hb), hematocrit (Hct), mean corpuscular
volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin
concentration (MCHC), red cell distribution width (RDW), and platelets (PLT) were
measured by using the hematology automated analyzer Micros 60 OT (Horiba ABX,
Montpellier, France).
3.5.1.5.2 Measurement of serum iron
Serum iron concentration was measured by the Iron Cromazurol method (Tietz,
1987). The assay was carried out by using Mindray semi-auto chemistry analyzer BA-88A.
2+
The method depends on the reaction of Fe
with cromazurol B at room temperature
yielding an intensive colored complex, The intensity of the color is proportional to the iron
concentration.
28
Procedure for measurement of serum iron
Blank
Sample
Standard
Sample
-
100 l
-
Standard
-
-
100 l
Distilled water
100 l
-
-
Reagent A
2.5 ml
2.5 ml
2.5 ml
Mix and, after 10 minutes read the absorbance (A) of standard and samples at 630 (620640 nm against blank. The color is stable 1 hour protected from light.
Iron g/dl= A sample/A standard x 200
3.6 Pilot study
A pilot study was performed on 10 students who met the established inclusion of
the target group. These students were randomly selected and then excluded from the main
study. The aim of the pilot study was to discern any errors and limitations that might have
appeared in the questionnaire, 3-day food records, anthropometrics measurements and
whole blood samples were collected to perform complete blood counts. Adaptations and
corrections were then done accordingly, based on the outcomes of the pilot study.
Procedure, information sheet, data analysis and any errors were adjusted before research
was done. The responses from the pilot study revealed that a few questions on the
questionnaire were not clear and had to be reworded accordingly. The food frequency
questionnaire (FFQ) was also modified slightly.
3.7 Data collection process
The data on socio-demographic, food consumption patterns, dietary habits and
indicators of body weight status were assessed by the researcher and recorded. All data were
collected during the second semester of the academic year (2009-2010). The detailed steps
of data collection process were as follows:
3.7.1 Steps in data collection process
Step 1
- Obtaining Permission to conduct study at the pharmacy college was obtained from Dean
of Faculty of Pharmacy prior to the study (Appendix A).
- Obtaining Ethical approval for the study was granted by Ethical Committee of Helsinki
(Appendix B).
29
- Participants were informed about the procedure to be used during the research duration
and had the right to discontinue the study.
- Conducting pilot study
- Adjusting the questionnaires based on the outcomes of the pilot study.
Step 2
- Questionnaire was used to determine socio-demographic factors, dietary habits and food
consumption patterns which influence body weight (Appendix D).
- 3-day recalls were used to determine eating practices (Appendix C).
- Complete Blood Count (CBC) analysis and measurement of serum iron were used to
determine iron deficiency anemia.
3.8 Statistical analysis
The obtained results are expressed as mean ± standard deviation. To find the
influence of gender on anthropometric measurements, food intake, dietary habits and
physical activity level, student‘s t-test was used. Association between variables was
determined using Pearson correlation coefficient. Level of significance was set at 0.05.
ANOVA was used to compare the mean difference in flour source and serum iron
measured. Statistical analysis was performed by using the Statistical Package for the
Social Science (SPSS version 15.0 software).
Statistical analysis involved a descriptive approach, cross-sectional design,
frequencies, and percentages for categorical variables, means and standard deviations for
continuous variables per group. Anthropometric status was described by means of
descriptive statistics. Adequacy of dietary intake was evaluated by comparing the average
from the 3-day food records of each student with the intakes recommended by Food Guide
Pyramid.
To determine the effect of food consumption patterns, dietary habits and body
weight, percent scores were compared with different categories of BMI. Energy,
macronutrient intakes and micronutrient intakes were analyzed by comparing the intake for
each student to the recommended ratio for total energy intake (TEE).
30
Chapter (4)
4. Results
The results are presented as socio-demographic factors, food consumption patterns,
dietary habits and body weight status of pharmacy students as well as the association
between the variables and body weight status in terms of body mass index (BMI).
4.1 Socio-demographic characteristics of the pharmacy students
Total number of population enrolled in the present study was 140 students. The age
range was 19 to 30 years old. According to the place of residence of pharmacy students,
46% of them were live in Gaza city, 40.3% from South Gaza and 13.7% from North Gaza
(Figure 2). Figure 3 shows personal information of the students sample that 20.7 % of the
sample from first year students, 15% from second year, 18.6% from third year, 20% from
fourth year, 16.4 % fifth year and 9.3% master students. The majority of the students were
single (91%) at the time of study. According to the educational level for parents, 49.5% of
student mother's and 61.5% of student father's has a university degree (Figure 4 and 5).
46%
17.30%
14.40%
13.70%
8.60%
North Gaza
gaza city
Central region
Khan Younis
Rafah
Figure 2: Permanent place of residence of male and female pharmacy students
20.70%
18.60%
20%
16.40%
15%
9.30%
First
level
Second
level
Third
level
Fourth
level
Fifth level
Figure 3: Academic level of male and female pharmacy
31
Master
61.50%
49.50%
37.00%
Figure 4: Mother's educational level
Postgraduate
University
Primary
Secondary
0%
14.10%
3.70%
Preparatory
0%
Illitrate/read
and write
Postgraduate
3.50%
University
Primary
6.00%
Secondary
2%
Preparatory
2%
Illitrate/read
and write
20.70%
Figure 5: Father's educational level
4.2 Economical characteristics of the sample
The collected data in table 5 demonstrated that most of the respondents had
moderate income with approximately 72.7% of the respondents had monthly income more
than 1000 NIS. On the other hand, most of participants were satisfied about their income
and reported that their income meet their needs of foods (87.9%).
Table 5: Economical characteristics of the sample
Personal information's
Monthly family income in NIS
Male
Female
No. % No.
5.8
Total
% No. %
Less than 1000 NIS
4
8
11.4 12 8.6
More than 1000 NIS
52 75.4 49
70 101 72.7
I do not know
13 18.8 13 18.6 26 18.7
sum
69 100 70
100 139 100
4.3 Mean physical characteristics of the sample
Table 6 shows anthropometric characteristics, body mass index and biochemical
analyses of the studied population. BMI was significantly different by gender and the mean
2
BMI was significantly lower in females than males (24.1 vs 21.6 kg/m ) (p<0.001). The
result was 66.5% (27.9% of male and 38.6% of female), that reflect a high incidence of
normal weight students among the respondents, the prevalence of overweight among the
subjects was 24.2% (17.1% of male and 7.1% of female), while that of obesity was 2.9%
among male students and the prevalence of underweight among subjects was 6.4% (2.1%
32
of male and 4.3% of female). Significant differences were found between males and
females regarding hematocrit, hemoglobin, and serum iron (p<0.001).
Table 6: Mean physical characteristics of the sample
Parameters
Male
Female
t
p-value
2.7
4.376
0.001*
84.2
15.7
4.451
0.001*
1.4
12.2
1.1
10.065
0.001*
41.9
3.5
36.2
2.8
10.698
0.001*
No.
%
No.
%
Ch
Normal weight
39
27.9
54
38.6
Overweight
24
17.1
10
7.1
Obesity
4
2.9
0
0.0
Underweight
3
2.1
6
* Means significance statistics (p-value < 0.05).
** Means significance statistics (p-value < 0.01).
4.3
Mean
SD
Mean
SD
BMI (kg/m )
24.1
3.8
21.6
Serum iron
99.6
24.2
Hemoglobin (g/dl)
14.3
Hematocrit (%)
2
BMI Categories
2
13.184
p-value
0.004**
66.50%
24.20%
6.40%
2.90%
Underweight Normal weight
Obesity
Overweight
Figure 6: BMI categories
4.4 Relationship between socio-demographic and BMI
The data in table 7 revealed that there is a statistical significance relationship
between BMI and marital status (P< 0.05) among male students it was found that 57% of
single students had normal BMI and 26% of single students had overweight. There were no
statistical significant difference between BMI and place of residence (P> 0.05), which 28%
of male students and 32% of female students who's living in Gaza city had normal weight
The collected data shows that there isn't a statistical significance relationship between BMI
33
and Mother's educational level (P>0.05). It was found that 23% of male students whose
mother's educational level are secondary level, 23% of male students whose mother's
educational level are university level and 44% of female students whose mother's
educational level are university level have normal weight. Similarly there was not a
statistical significance relationship between BMI and father's educational level (P>0.05).
29% of male students whose father's educational levels are university level and 20% of
female students whose father's are educational levels are university level have normal
weight.
Table 7: Relationship between marital status and BMI.
Marital
Normal
Gender
Overweight
status
weight
Married
0 0.0 5
7.5
Male
Single
38 56.7 17
25.4
Married
4 6.1 1
1.5
Female
Single
49 74.2 7
10.6
* Means significance statistics (p-value < 0.05).
Obesity Underweight
2
2
-
3.0
3.0
-
0
3
0
5
0.0
4.5
0.0
7.6
Chi
2
p
15.017 0.014*
1.687 0.678
4.5 Relationship between economical variables and BMI
The data regarding the economical status shown in table 8 didn‘t revealed a
statistical significance relationship between BMI and monthly income level (P>0.05). It
was found that 38% and 53% of the male and female students respectively with monthly
income rate more than 1000 NIS monthly had normal body weight
Table 8: Economical factors associated with overweight and obesity
Monthly income
level
Less than 1000 NIS
Gender
Normal
weight
Overweight
Obesity
Underweight
Chi
2
p
3
4.3
1
1.4
0
0.0
0
0.0
26
37.7 20
29.0
3
4.3
3
4.3 4.376 0.317
I do not know
10
14.5
3
4.3
0
0.0
0
0.0
Less than 1000 NIS
6
8.6
0
0.0
-
-
2
2.9
More than 1000 NIS Female 37
I do not know
11
52.9
15.7
9
1
12.9
1.4
-
-
3
1
4.3 5.099 0.314
1.4
More than 1000 NIS
Male
The data regarding the working status shown in table 9 that there is no a statistical
significance relationship between BMI and working parent's (P>0.05). 40% of male
students with working father and 62% of female students with working father have normal
weight. On similarity 45% of male students and 62% of female students whose mother's
didn't have any working have normal weight.
34
Table 9: Relationship between working parent's and BMI
Working
Father
Yes
No
Other
sources
Yes
No
Other
sources
Working
Mother
Yes
No
Other
sources
Yes
No
Other
sources
Gender
Normal weight
Overweight
Obesity
2
Underweight
Chi
Underweight
Chi
p
Male
Female
Normal weight
Overweight
-
-
-
-
-
-
Obesity
2
Male
Female
-
-
-
-
-
-
-
-
-
-
-
-
4.6 Macronutrient and micronutrient intake of the students
Data in table 10 shows the relationship between gender, macronutrient and
micronutrient intake variables among students. It has been found that there is a significant
difference between the carbohydrate intake and the participants gender (P< 0.05). The
mean intake of carbohydrates was 345 gm and 427 gm among males and females
respectively. Furthermore, it was found that average daily energy intake of pharmacy
students at Al-Azhar university was 1873 for males and 1834 kcal for females. The energy
requirements differ, but in general for ages 19-24, they need to be between 2200 kcal/day
for females and 2900 kcal/day for males (WHO, 1987).
Furthermore, data in table 10 shows that there is a statistical significance
relationship between the percentage of energy from fat, carbohydrate, protein and the
participants gender (P< 0.05). The mean intake of the percentage of energy was 66%
among male and 83% among female. Table 10 shows also a statistical significance
relationship between the percentage of carbohydrates and the participants gender (P< 0.05)
that the mean intake of the percentage of carbohydrates 59% among male and 71% among
female. Moreover there is a statistical significance relationship between the percentage of
sodium and the participants gender (P< 0.05) which the mean intake of the percentage of
sodium 86% among male and 66% among female. The collected data shown in table 10
35
p
demonstrates that there a statistical significance relationship between the percentage of
riboflavin (vitamin B2 and the participants gender (P< 0.05) that the mean intake of the
percentage of riboflavin 72% among male and 85% among female. On the other hand there
is no a statistical significance difference associated with gender and the remaining
variables. The mean intakes of nutrients varied between male and female respondents. A
comparison of mean dietary intakes of respondents is shown in Table 10. The mean intakes
of carbohydrate, energy, protein, calcium, phosphorus, thiamin, riboflavin and niacin were
higher in female compared with male students consumed more of total energy, fat (gm),
fat, iron, potassium, sodium, and vitamin A.
Table 10: Macronutrient and micronutrient intake from 3 day recalls
Parameters
Male
Female
t
p
-21.84
0.001*
43.7
0.667
0.506
83.2
31.4
-3.810
0.001*
18
71.1
24.9
-3.480
0.001*
10.06
6.71
15.75
6.41
Fat %
36.06
20.3
34.4
14.03
Calcium%
67.1
26.8
72.3
32.6
-1.020
0.310
Iron %
105.1
61
102.2
40.6
0.338
0.736
Phosphorus %
92.2
37.4
96.1
42.6
-0.579
0.564
Potassium%
66.2
21
62.5
23.8
1.003
0.318
Sodium%
86.2
58.2
65.9
37.1
2.458
0.015*
Vitamin A%
154.5
255.5
104.7
53
1.598
0.112
Thiamin (vitamin B1) %
81.2
28.8
91.4
37.7
-1.798
0.074
Riboflavin (vitamin B2)%
71.7
13.8
84.8
13.8
-5.606
0.001*
Niacin%
79.4
25.9
84.1
27
-1.045
0.298
Mean
SD
Mean
SD
1,873.415
749
1,834.963
565
Carbohydrate (gm)
345
115.2
426.6
149.4
Protein (gm)
84.6
37.1
87.7
38.8
Fat (gm)
89.3
40.3
84.5
66
20.9
Carbohydrate %
58.3
Protein %
Energy (kcal)
Energy %
-0.679
86
29.1
89.6
33.1
Vitamin C %
* Means significance statistics (p-value < 0.05).
4.7 The percentages of pharmacy students meeting RDA for nutrients
36
0.499
When nutrient content between genders was compared by using percentage of
RDA, there were some differences revealed that the percentage of energy, carbohydrate,
fat and vitamin B2 associated with gender are concerned (P< 0.05). There were no
significant differences associated with gender and the remaining factors (P> 0.05).
The percentages of the respondents meeting two thirds of the RDA for nutrients are
shown in Table 11. More than 50% of the respondents were meeting two thirds of the RDA
for energy (55.7%), protein (53.6%), fat (51.4.5%), iron (61.4%), phosphorus (62.1%),
vitamin A (52.1%), thiamin (69.3%), riboflavin (80 %) and niacin (67.9%). Whereby a
small percentages of the respondents met two thirds of the RDA for carbohydrates
(40.3%), calcium (46.4%), potassium (44.3%), sodium (37.1%) and vitamin C (10.7%).
Table 11: The percentages of pharmacy students meeting RDA for nutrients
Parameters
Energy%
Carbohydrate%
Protein%
Fat%
Insufficient Sufficient
Gender
(%)
(%)
Over
sufficient
(%)
Male
25.7%
24.3%
0.0%
Female
15.7%
31.4%
2.9%
Total
41.4%
55.7%
2.9%
Male
37.4%
12.2%
0.0%
Female
21.6%
28.1%
0.7%
Total
59.0%
40.3%
0.7%
Male
18.6%
25.0%
6.4%
Female
10.7%
28.6%
10.7%
Total
29.3%
53.6%
17.1%
Male
16.4%
26.4%
7.1%
Female
10.0%
25.0%
15.0%
Total
27.4%
51.4%
22.2%
Male
25.7%
24.3%
0.0%
Female
25.0%
22.1%
2.9%
Total
50.7%
46.4%
2.9%
Chi
2
p
8.661
0.013*
15.539
0.000*
4.785
0.091
6.148
0.046*
4.153
0.125
Calcium%
37
Iron%
Phosphorus %
Potassium%
Sodium%
Male
7.9%
31.4%
10.7%
Female
10.0%
30.0%
10.0%
Total
17.9%
61.4%
20.7%
Male
10.7%
32.1%
7.1%
Female
10.0%
30.0%
10.0%
Total
20.7%
62.1%
17.1%
Male
26.4%
23.6%
-
Female
29.3%
20.7%
-
Total
55.7%
44.3%
-
Male
22.9%
20.0%
7.1%
Female
28.6%
17.1%
4.3%
Total
51.4%
37.1%
11.4%
Male
15.0%
21.4%
13.6%
Female
8.6%
30.7%
10.7%
Total
23.6%
52.1%
24.3%
9.3%
38.6%
2.1%
12.1%
30.7%
7.1%
Total
21.4%
69.3%
9.3%
Male
17.1%
32.9%
0.0%
Female
1.4%
47.1%
1.4%
Total
18.6%
80.0%
1.4%
Male
15.7%
30.7%
3.6%
Female
9.3%
37.1%
3.6%
Total
25.0%
67.9%
7.1%
0.441
0.802
0.805
0.669
0.463
0.496
2.197
0.333
5.24
0.073
5.55
0.062
24.187
0.000*
3.167
0.205
Vitamin A%
Male
Thiamin
(vitamin B1) % Female
Riboflavin
(vitamin B2)%
Niacin%
38
Vitamin C %
Male
15.0%
5.7%
29.3%
Female
12.1%
5.0%
32.9%
27.1%
10.7%
Total
* Means significance statistics (p-value < 0.05).
0.775
0.679
62.1%
4. 8 Relationship between dietary habits and BMI
4.8.1 Relationship between BMI and breakfast at home
The collected data shows that there isn't any statistical significance relationship
between BMI and having breakfast at home (P>0.05). It was found that 20% of male
students and 30% of female students who rarely take breakfast at home have normal BMI
(Table 12).
Table 12: Relationship between BMI and breakfast at home
Normal
Overweight Obesity
weight
Dietary habits
Gender
Do you take breakfast
at home?
Daily
Male
(3-4) times/week
<2 times/week
Rarely
Daily
(3-4) times/week
Female
<2 times/week
Rarely
No.
7
11
7
14
12
14
7
21
%
No.
10.0 10
15.7 5
10.0 4
20.0 5
17.1 3
20.0 1
10.0 1
30.0 5
%
14.3
7.1
5.7
7.1
4.3
1.4
1.4
7.1
Underweight
No. % No.
1
1
1
1
-
1.4
1.4
1.4
1.4
-
0
1
1
1
1
3
1
1
%
0.0
1.4
1.4
1.4
1.4
4.3
1.4
1.4
Chi
2
6.112
p
0.729
3.889 0.692
4.8.2 Relationship between BMI and number of daily meals
Table 13 shows that there isn't any statistical significance relationship between
BMI and number of daily meals variable (P>0.05). It was found that 27% of male students
and 44% of female students who takes two meals daily had normal BMI.
39
Table 13: Relationship between BMI and number of daily meals
Normal
Overweight Obesity
weight
Dietary habits
Gender
How many meals do
No.
you eat each day?
One meal
1
Male
Two meals
19
Three meals
17
More than three meals
2
One meal
3
Two meals
Female 31
Three meals
16
More than three meals
4
%
No.
1.4 1
27.1 9
24.3 11
2.9 3
4.3 0
44.3 8
22.9 2
5.7 0
%
Underweight
No. % No.
1.4
12.9
15.7
4.3
0.0
11.4
2.9
0.0
0
2
2
0
-
0.0
2.9
2.9
0.0
-
0
2
1
0
0
3
3
0
%
0.0
2.9
1.4
0.0
0.0
4.3
4.3
0.0
Chi
2
p
2.905 0.968
4.037 0.672
4.8.3 Relationship between BMI and eating out-home
The data revealed that there isn't any statistical significance relationship between
BMI and eating out home variable (P>0.05). It was found that 23% of male students and
32% of female students who eat out home more than one time weekly had normal BMI
(Table 14).
Table 14: Relationship between BMI and eating out home
Dietary habits
Normal
Overweight Obesity Underweight
Gender weight
2
No. % No. % No. % No.
%
p
Chi
5
7.1 2
2.9
0 0.0 0
0.0
16 22.9 11 15.7 3 4.3 2
2.9
12 17.1 6
8.6
0 0.0 0
0.0
16.358 0.175
Male
1
1.4 0
0.0
0 0.0 1
1.4
Eating out of home
Almost every day
(1-2) times/week
(3-5) times/week
> 5 times/week
I do not take the food
5
outside the home
Almost every day
6
(1-2) times/week
22
(3-5) times/week
7
Female
> 5 times/week
3
I do not take the food
16
outside the home
7.1
5
7.1
1
1.4
0
0.0
8.6
31.4
10.0
4.3
0
6
0
0
0.0
8.6
0.0
0.0
-
-
0
3
1
0
0.0
4.3
1.4
0.0
22.9
4
5.7
-
-
2
2.9
40
5.116 0.745
4.8.4 Relationship between BMI and skipped meal
There was no statistical significance relationship between BMI and skipped meal
variable (P>0.05). It was found that 34% of male students and 42% of female students who
skipped breakfast meal had normal BMI (Table 15).
Table 15: Relationship between BMI and skipped meal
Dietary habits
Skipped meal:
breakfast
Lunch
Dinner
breakfast
Lunch
Dinner
Normal
Overweight Obesity Underweight
Gender weight
2
No. % No. % No. % No.
%
p
Chi
21 33.9 10 16.1 4 6.5 3
4.8
3
4.8 4
6.5
0 0.0 0
0.0
7.791 0.254
Male
8 12.9 9 14.5 0 0.0 0
0.0
28 41.8 4
6.0
3
4.5
7.5 0
0.0
0
0.0
Female 5
2.421 0.659
19 28.4 5
7.5
3
4.5
4.8.5 Relationship between BMI and diet salt
The data revealed that there is a statistical significance relationship between BMI
and medium intake of salt among male (P< 0.05). It was found that 51% of male students
and 63% of female students who take medium salt in their food had normal BMI (Table
16).
Table 16: Relationship between BMI and diet salt
Dietary habits
Normal
Overweight Obesity Underweight
weight
Gender
you like the food that
No. % No. % No. % No.
is:
Without salt
0
0.0 0
0.0
1 1.4 0
Medium salt
Male 35 50.7 21 30.4 3 4.3 2
Salt Plus
3
4.3 3
4.3
0 0.0 1
Without salt
2
2.9 1
1.4
0
Medium salt
6
Female 44 62.9 7 10.0 Salt Plus
8 11.4 2
2.9
0
* Means significance statistics (p-value < 0.05).
41
%
0.0
2.9
1.4
0.0
8.6
0.0
Chi
2
p
18.869 0.004*
2.573 0.632
4.8.6 Relationship between BMI and physical activity
The collected data in table 17 illustrates that there isn't any statistical significance
relationship between BMI and physical activity exercised by students (P>0.05). Data
revealed that 23% of male students who was practicing twice a week activity and 48% of
female students who was decreasing their physical activity had normal BMI.
Table 17: Relationship between BMI and physical activity
Dietary habits
Normal
Overweight Obesity Underweight
weight
Gender
Do you have exercise
No.
routine?
Daily
1
Twice a week
Male 16
>4 times/week
7
No physical activity
15
Daily
3
Twice a week
Female 15
>4 times/week
3
No physical activity
33
%
No.
1.4 3
22.9 11
10.0 2
21.4 8
4.3 0
21.7 1
4.3 2
47.8 7
%
4.3
15.7
2.9
11.4
0.0
1.4
2.9
10.1
No. % No.
0
2
1
1
-
0.0
2.9
1.4
1.4
-
0
1
0
2
1
1
1
2
%
0.0
1.4
0.0
2.9
1.4
1.4
1.4
2.9
Chi
2
p
5.889 0.751
6.766 0.343
4.8.7 Relationship between BMI and smoking habit
The relationship between BMI and smoking habit variables among pharmacy
students was studied and the result showed that there isn't any statistical significance
relationship between BMI and smoking habit variables by students (P>0.05). It was found
that 49% of male students and 77% of female students who don't smoke cigarettes had
normal BMI (Table 18). Table 18 shows that 30% of male students smoke less than 10
cigarettes, had normal BMI and 30% of male students smoke more than 10 cigarettes had
overweight.
42
Table 18: Relationship between BMI and smoking habit
Dietary habits
Gender
Are you a smoker?
Yes
Male
No
How many cigarettes
you smoke per day?
10 cigarettes
<10 cigarettes
>10 cigarettes
<10 cigarettes
>10 cigarettes
Male
Normal
Overweight Obesity Underweight
weight
No.
%
No.
%
5
7.1
4
5.7
0
0.0
1
1.4
34
48.6 20
28.6
4
5.7
2
2.9
No.
%
No.
%
1
3
2
-
10.0
30.0
20.0
-
0
1
3
1
0.0
10.0
30.0
0.01
No. % No.
No. % No.
-
-
-
%
%
-
Chi
2
p
1.735 0.629
Chi
2
p
1.875 0.392
4.9 Basic food group consumption as stated in frequency per week among the
included pharmacy students associated with their BMI classification
4.9.1 Relationship between BMI and protein rich food consumption
Table 19 demonstrates the relationship between the BMI and protein rich food
consumption among students. The data shows that there isn't any statistical significance
relationship between BMI and the consumption of any of the protein rich foods. According
of 37% of male students and 47% of female students who eating red or white meat more
than one time weekly had normal BMI. The table also shows that 40% of female students
who was drinking milk or eating dairy products more than one times weekly had normal
BMI. And there isn't any statistical significance relationship between BMI and legumes
consumption (P> 0.05). It was found that 33% of male students and 50% of female
students who eating legumes one time weekly, had normal BMI.
43
Table 19: Relationship between BMI and protein rich food consumption
Variables
Gender
How many times a week
eat red meat or white?
Rarely
Once a week
Male
(2-4) times/week
>5 times/week
Rarely
Once a week
Female
(2-4) times/week
>5 times/week
Normal
weight
No.
Overweight Obesity Underweight
% No. % No. % No.
3 4.3 0 0.0
6 8.6 1 1.4
26 37.1 19 27.1
4 5.7 4 5.7
3 4.3 0 0.0
13 18.6 3 4.3
33 47.1 6 8.6
5 7.1 1 1.4
How many times a week
is covered by milk or
No.
dairy products?
Rarely
24
Once a week
Male 5
(2-4) times/week
10
Rarely
22
Once a week
Female 4
(2-4) times/week
28
How often do you eat
legumes such as peas or
No.
lentils or beans each
week?
Once a week
23
(2-4) times/week
Male 16
>5 times/week
0
Once a week
35
Female 17
(2-4) times/week
>5 times/week
2
%
0.0
2.9
2.9
0.0
-
0
0
3
0
0
0
4
2
No. % No. % No.
34.3 10 14.3
7.1 4 5.7
14.3 10 14.3
31.4 5 7.2
5.7 0 0.0
40.0 5 7.1
%
0
2
2
0
-
3
0
1
-
4.3
0.0
1.4
-
3
0
0
1
1
3
No. % No. % No.
32.9 7 10.0
22.9 15 21.4
0.0 2 2.9
50.0 6 8.6
24.3 4 5.7
2.9 0 0.0
1
3
0
-
1.4
4.3
0.0
-
2
1
0
3
3
0
%
Chi
2
p
0.0
0.0
11.05 0.275
4.3
0.0
0.0
0.0
5.309 0.504
5.7
2.9
%
4.3
0.0
0.0
1.4
1.4
4.3
%
2.9
1.4
0.0
4.3
4.3
0.0
Chi
2
p
8.844 0.451
1.961 0.923
Chi
2
p
9.340 0.155
1.448 0.836
4.9.2 Relationship between BMI and fruits and vegetables consumption
Concerning the relationship between the BMI and fresh fruits or juice consumption
the collected results illustrate that there isn't any statistical significance relationship
between BMI and the consumption of fresh fruits or juice (P>0.05), thus 32% of male
students and 44% of female students who eating fresh fruits or juice more than one time
weekly had normal BMI. Similarity there isn't any statistical significance relationship
between BMI and fresh vegetables (green salad) consumption (P> 0.05). It was found that
28% of male students and 35% of female students who eating fresh vegetables (green
44
salad) more than one time weekly had normal BMI. Furthermore table 20 also shows that
there isn't any statistical significance relationship between BMI and cooked vegetables
consumption (P> 0.05). It was found that 26% of male students and 44% of female
students who cooked vegetables more than one time weekly had normal BMI
Table 20: Relationship between BMI and fruits and vegetables consumption
Normal
weight
Variables
Overweight Obesity Underweight
Gender
How many times a week
No. % No. % No. % No.
eat fresh fruits or juice?
Once a week
4 5.7 1 1.4 0 0.0 0
(2-4) times/week
Male 22 31.4 13 18.6 2 2.9 3
>5 times/week
13 18.6 10 14.3 2 2.9 0
Once a week
9 13.0 0 0.0 1
(2-4) times/week
Female 30 43.5 5 7.2
2
>5 times/week
14 20.3 5 7.2 3
How often do you eat
fresh vegetables (green
salad)?
Once a week
(2-4) times/week
>5 times/week
Once a week
(2-4) times/week
>5 times/week
How often do you eat
cooked vegetables per
week?
Once a week
(2-4) times/week
>5 times/week
Once a week
(2-4) times/week
>5 times/week
No.
7
Male 19
12
16
Female 24
14
No.
17
Male 18
3
22
Female 30
2
%
No. % No. % No.
10.1 5 7.2
27.5 9 13.0
17.4 10 14.5
22.9 2 2.9
34.3 5 7.1
20.0 3 4.3
%
0
3
1
-
0.0
4.3
1.4
-
2
1
0
3
1
2
No. % No. % No.
24.6 10 14.5
26.1 14 20.3
4.3 0 0.0
31.9 2 2.9
43.5 8 11.6
2.9 0 0.0
0
3
1
-
0.0
4.3
1.4
-
1
2
0
2
3
0
%
0.0
4.3
0.0
1.4
2.9
4.3
%
2.9
1.4
0.0
4.3
1.4
2.9
%
1.4
2.9
0.0
2.9
4.3
0.0
Chi
2
p
3.968 0.681
4.412 0.353
Chi
2
p
7.011 0.319
2.391 0.664
Chi
2
p
7.041 0.317
2.375 0.667
4.9.3 Relationship between BMI and the grains consumption
The study results show that there isn't any statistical significance relationship
between BMI and bread consumption (P> 0.05) that 52% of male students and 67% of
female students who eat white bread had normal BMI. Table 21 also shows that there is a
statistical significant relationship between BMI and the rice consumption (P< 0.05).
45
Regarding the pasta consumption there isn't any statistical significant relationship between
BMI and the pasta consumption (P> 0.05) as 50% of male students and 72% of female
students who eat pasta had normal BMI.
Table 21: Relationship between BMI and the grains consumption
Variables
Gender
What is the type of bread
you eat in your food
each week?
White bread
Black bread
Male
I do not know the type
White bread
Black bread
Female
I do not know the type
Normal
weight
No.
%
Overweight
%
Underweight
No. % No. % No.
36 51.4 19 27.1
3 4.3 4 5.7
0 0.0 1 1.4
46 66.7 9 13.0
7 10.1 1 1.4
-
How often eat rice each
No.
week?
Once a
week
10
(2-4) times/week
Male 24
>5 times/week
5
Once a
week
21
(2-4) times/week
Female 33
>5 times/week
0
Obesity
4
0
0
-
5.7
0.0
0.0
-
3
0
0
6
0
-
No. % No. % No.
14.3 6 8.6
34.3 16 22.9
7.1 2 2.9
30.0 2 2.9
47.1 7 10.0
0.0 1 1.4
How many times you eat
No. % No.
pasta every week?
Once a week
35 50.7 22
(2-4) times/week
Male 3 4.3 1
>5 times/week
1 1.4 0
Once a week
50 71.4 10
Female 3
(2-4) times/week
4.3 0
>5 times/week
1 1.4 0
* Means significance statistics (p-value < 0.05).
46
3
1
0
-
4.3
1.4
0.0
-
0
1
2
2
3
1
% No. % No.
31.9
1.4
0.0
14.3
0.0
0.0
4
0
0
-
5.8
0.0
0.0
-
3
0
0
6
0
0
%
Chi
2
p
4.3
0.0 4.295 0.637
0.0
8.7
0.0 0.946 0.623
%
Chi
2
p
0.0
1.4 13.280 0.039*
2.9
2.9
4.3 8.435 0.077
1.4
%
4.3
0.0
0.0
8.6
0.0
0.0
Chi
2
p
1.599 0.953
1.257 0.869
4.9.4 Association between flour source and the range of serum iron among healthy
students.
Table 22 shows that there is a statistical significant relationship between flour source and
serum iron (P< 0.05).
Table 22: ANOVA - flour source
No
1.
2.
Dimension
t. Test Value
Sig.
SERUM IRON
2.786
1.876
0.043*
0.137
Fe
* The mean difference is significant at 0. 05 level.
Sig means significance
Table 23 shows that the mean respondents between UNRWA and NGOs are
statistically significant (P< 0.05). Since the mean difference is negative, then we conclude
that the mean of NGOs respondents is statistically greater than that of UNRWA
respondents. There were some significance differences revealed that there was association
between eating bread made of flour donated from NGOs and the normal range of serum
iron among healthy students.
Table 23: Association between flour source and serum iron level among healthy
students.
(I) Flour source (J) Flour source
UNRWA
CHF
Serum iron
Bakeries
NGOs
CHF
Bakeries
NGOs
UNRWA
Bakeries
NGOs
UNRWA
CHF
NGOs
UNRWA
CHF
Bakeries
CHF
Bakeries
*The mean difference is significant at the0 .05 level.
Sig means significance
47
Mean Difference
(I-J)
-0.453
-3.628
-20.671
0.453
-3.175
-20.218
3.628
3.175
-17.043
20.671
20.218
17.043
-29.596
4.364
Sig.
1.000
1.000
0.035*
1.000
1.000
0.109
1.000
1.000
0.084
0.035*
0.109
0.084
0.884
1.000
4.10 Obesogenic food consumption as stated in frequency per week among the
included pharmacy students associated with their BMI classification
4.10.1 Relationship between BMI and soft and hot drinks consumption variables
Table 24 shows the relationship between BMI and soft and hot drinks consumption
among students. It was found that there isn't any statistical significance relationship
between BMI and the consumption of any of the hot or soft drinks (P> 0.05), thus about
35% of male students and 47% of female students who were consuming soft drinks or
juices manufactured one time weekly or more had normal BMI. Regarding tea, coffee and
cocoa, there isn't any statistical significant relationship between BMI and the tea, coffee
and cocoa drinking consumption (P> 0.05), as 37% of male students and 44% of female
students who were consuming tea, coffee and cocoa one or more daily had normal BMI.
Table 24: Relationship between BMI and soft and hot drinks consumption variables
Dietary habits
How often do you
take soft drinks or
juices?
(1-2) times/week
(3-6) times/week
Once or more a day
(1-2) times/week
(3-6) times/week
Once or more a day
Gender
No.
Once or more a day
%
19 35.2
Male
5 9.3
7
13
27 46.6
Female 14 24.1
3 5.2
How many times
dealing with tea,
coffee and cocoa in a
day?
(1-2) times/week
(3-6) times/week
Normal
weight
Male
Overweight
No.
%
13 24.1
3 5.6
1 1.9
7 12.1
1 1.7
0
0
Obesity
Underweight
No.
%
No.
%
4
0
0
-
7.4
0
0
-
1
1
0
4
1
1
1.9
1.9
0
6.9
1.7
1.7
No.
%
No.
%
No.
%
No.
%
3
4.5
3
4.5
1
1.5
0
0
11 16.7
8
12.1
0
0
1
1.5
24 36.4
11 16.7
2
3
2
3
I do not take
-
-
-
-
-
-
-
-
(1-2) times/week
9
13.4
2
3
-
-
0
0
9
13.4
5
7.5
-
-
2
3
29 43.3
3
4.5
-
-
3
4.5
5
0
0
-
-
0
0
(3-6) times/week
Once or more a day
I do not take
Female
7.5
48
Chi
2
p
6.154 0.406
3.295 0.509
Chi
2
p
3.913 0.688
7.836 0.250
4.10.2 Relationship between BMI and chocolates, and dessert consumption variables
The collected data was presented in table 25 shows that there isn't any statistical
significance relationship between BMI and the consumption of any of the chocolates (P>
0.05). It was found that about 29% of male students and 37% of female students who were
consuming chocolates one time weekly or more had normal BMI. Regarding the dessert
there isn't any statistical significant relationship between BMI and the dessert (P> 0.05), as
50% of male students and 58% of female students who were consuming dessert one time
weekly or more had normal BMI.
Table 25: Relationship between BMI and chocolates and dessert consumption
variables
Dietary habits
Gender
How often do you eat
chocolates?
(1-2) times/week
Normal
weight
Overweight
No.
%
18 26.1
2
2.9
1
1.4
13 18.8
6
8.7
2
2.9
2
2.9
Once or more a day
5
7.2
0
0
0
0
0
0
(1-2) times/week
26 37.1
7
10
-
-
2
2.9
19 27.1
3
4.3
-
-
2
2.9
-
2
2.9
%
No.
%
Chi
5.7
0
3
0
4.3
0
3.678 0.720
0
-
0
6
0
0
0
8.7
0
0
(3-6) times/week
Female
No.
20
29
%
2
%
Male
%
Underweight
No.
(3-6) times/week
No.
Obesity
Once or more a day
9 12.9 0
0
How often do you eat
No. % No. % No.
dessert?
(1-2) times/week
35 50 19 27.1 4
Male
(3-6) times/week
4 5.7
4 5.7
0
Once or more a day
(1-2) times/week
(3-6) times/week
Once or more a day
0
40
Female 9
4
0
58
13
5.8
1
8
1
1
1.4
11.6
1.4
1.4
0
-
Chi
p
7.599 0.268
4.026 0.402
2
2.2
p
0.698
4.10.3 Relationship between BMI and chips and popcorn consumption variables
The collected data was presented in table 26 shows that there is a statistical
significance relationship between eating chips, and popcorn and BMI (P<0.01) among
female students, as 30.4% of female students and 24.3% of male students who were
consuming chips, and popcorn 3-6 times weekly had normal BMI.
49
Table 26: Relationship between BMI and chips and popcorn consumption variables
Variable
Gender
How often do you eat
chips and popcorn?
(1-2) times/week
Normal
weight
No.
%
Overweight
No.
%
Obesity
Underweight
No.
%
No.
%
17 24.3
13 18.6
2
2.9
0
0
11 15.7
4
5.7
0
0
3
4.3
7
10
2
2.9
0
0
0
0
I do not take
4
5.7
5
7.1
2
2.9
0
0
(1-2) times/week
20
29
3
4.3
-
-
1
1.4
21 30.4
1
1.4
-
3
4.3
11 15.9
3
4.3
-
-
2
2.9
I do not take
1 1.4
3 4.3
* Means significance statistics (p-value < 0.05
-
-
0
0
(3-6) times/week
Once or more a day
(3-6) times/week
Once or more a day
Male
Female
Chi
2
p
16.797 0.052
15.598 0.016*
4.10.4 Relationship between BMI and pizza and fast food consumption variables
Table 27 shows that there isn't any statistical significance relationship between
BMI and the consumption of any of the pizza consumption (P> 0.05), thus about 29% of
male students and 42% of female students who were consuming pizza one time weekly or
more had normal BMI. Regarding fast food consumption there isn't any statistical
significant relationship between BMI and eating fast food (P> 0.05). It was found that 12%
of male students and 49% of female students who was consuming fast food one time
weekly or more had normal BMI.
50
Table 27: Relationship between BMI and pizza and fast food consumption variables
Variable
How many times a
week eat pizza?
(1-2) times/week
(3-6) times/week
Once or more a day
I do not take
Gender
Normal
Overweight
weight
Obesity Underweight
2
No. % No.
%
No.
%
No.
%
Chi
29 41.4 14
3 4.3 1
0
0
1
7 10 8
20
1.4
1.4
11.4
1
0
0
3
1.4
0
0
4.3
2
0
0
1
2.9
0
0
1.4
9.307 0.409
10
0
0
4.3
-
-
5
0
1
0
7.1
0
1.4
0
8.417 0.209
%
No.
%
No.
%
Chi
18
25.7
1
1.4
1
1.4
8 11.4
0
0
1
1.4
1
1.4
2
2.9
1
1.4
0
0
0
0
I do not take
8 11.4
5
7.1
2
2.9
1
1.4
(1-2) times/week
34 49.3
5
7.2
-
-
4
5.8
6
8.7
1
1.4
-
-
0
0
3
4.3
0
0
-
-
0
0
11 15.9
3
4.3
-
-
2
2.9
Male
(1-2) times/week
42 60
(3-6) times/week
4 5.7
Female
Once or more a day
1 1.4
I do not take
7 10
How many times per
week eat fast food
like burgers or
shawarma and
others?
(1-2) times/week
(3-6) times/week
Once or more a day
(3-6) times/week
Once or more a day
I do not take
7
0
0
3
No. % No.
21
Male
Female
30
51
2
p
p
9.857 0.362
2.439 0.875
Chapter (5)
5. Discussion
The main objective of the current study is to provide data on food consumption
patterns and dietary habits associated with weight status in healthy young adult students. In
this study 140 young adult students (70 male and 70 female) were selected randomly from
faculty of pharmacy at Al Azhar University. The present study shows important result
regarding the food consumption patterns and dietary habits of young adults. The results
will be discussed and compared with available literature in context with the aim of the
study.
5.1 Relationship between socio-demographic characteristics and BMI
The study results revealed that there is a statistical significance relationship
between BMI and marital status (P< 0.05). Among male students it was found that 57% of
single students had normal BMI and 26% of single students had overweight in agreement
with that observed by Al-Mannai et al., 1996. According to Janghorbani et al (2008) the
married men and women were more likely to be overweight and obese than those never
married. The positive relationship between marital status and overweight, obesity, or abdominal
obesity can be explained by the fact that people, after marriage have less physical activities, change
their dietary pattern, may be less focused on being attractive, have more social support, or may be
exposed to other environmental factors. Unmarried subjects may intentionally manage their
weight in an effort to be more attractive to potential marital partner.
The results of the present study revealed that 24.2% of the students were
overweight while 2.8% were obese indicating however, that their abilities to translate these
health messages into health-promoting behaviors are somewhat questionable. Furthermore,
these differences in the level of overweight and obesity may be attributable to be eating in
a group not eating alone or in couples. In most cases, faculty of pharmacy students eat in
large groups which may encourage overeating; students tend sometimes to compete among
each other in the amount of food they can eat. Moreover, the majority of faculty of
pharmacy students live at home and eat with their families in groups. Theoretically,
pharmacy students, being highly educated and potentially of higher socio-economic status,
are often exposed to some forms of the mass media which may provide health-promoting
messages put forward by health agencies. Their level of education should enable them to
grasp these messages better than those in society who are less educated (Patterson et al.,
52
1995). In the same context, well educated students had the knowledge regarding the risks
of the obesity and the associated chronic diseases that lead to decrease the level of
overweight or obesity among university students.
Many studies have shown that educational achievement of parents, associated with
their children‘s nutritional status (De Vito et al., 1999 and Wang, 2001). The educational
attainment of parents could lead to higher income and may imply a higher availability of
food and household resources (Giuoglino and Carneiro, 2004). On the other hand, it
might be positively associated with higher nutritional awareness as well as better caring of
children (Crockett and Sims, 1995). In the present study, however, we found that 50% of
student mother's and 62% of student father's has academic degree and there isn't any
statistical relationship between parents' educational levels and BMI. However Stea et al.,
2009 stated that high paternal educational level was associated with a lower BMI and a
better lipid profile among young adult men.
5.2 Relationship between economical variables and BMI
The results of the present study revealed that the majority of the mothers were
housewives or were unemployed and there isn't any statistical relationship between
parents‘ work and BMI status, similar to the findings reported by Lamerz et al., 2005.
The present study shows important results regarding the economical status of the
pharmacy students and reflects the current economical status of the students. However the
majority of the sample population have monthly income rate more than 1000 NIS and most
of them agreed that their monthly income rate meet their needs of food.
5.3 Mean physical characteristics of the sample
Body weight status was assessed by using body mass index. Based on the BMI
2
classification of weight status, the average BMI of the male students was 24.1 Kg/m , and
2
for female students were 21.6 Kg/m . Using the classification of BMI ranges, there were
significant differences between genders (p<0.004). The findings of this study indicate a
high incidence of normal weight students among the respondents about 67% (28% of male
and 39% of female). Normal weight was more prevalent among female (39 %) as
compared to male (28 %). In contrast, 2.1% male students compared to 4.3% of the
females were underweight. In contrast with the present study, Yahia et al (2007) found
that the prevalence of normal weight to be more common among females (76.8 %)
compared to males (49 %) in Lebanese University students. Puoane et al. (2002) found
53
that underweight rarely occurs in South African adults; however it was much higher in men
(12.2 %) than women (5.6 %). The finding from this study also indicated that the
prevalence of overweight about 24.2% (7.1% in females as compared to 17.1 % in males),
while the prevalence of obesity about 2.9% found among male students. In contrast to
study of Zabut and habiby, 2005 that conducted at nursing students at Islamic universityGaza Strip (IUG) showed that 66.1% of male students and 73% of female students had
normal weight. The study also showed that 28.5% of males and 27% of females were
overweight. He also indicated that, more than 25% of these students in the college might
be at risk of diabetes, hypertension, cardiovascular disease, and other chronic diseases. The
observed prevalence in the studied population of overweight (24.2%) and obesity (2.9 %)
indicated that 27.1% of the students might be at risk for serious diet-related chronic
diseases, according to the WHO (2003) criteria. In other countries, similar findings have
been reported. In Lebanon, the prevalence of overweight and obesity among university
students was common among males compared to females (37.5 % and 13.6 % versus 12.5
% and 3.2 % respectively (Yahia et al., 2008). In Pakistan the prevalence of overweight
(20.5 %) and obesity (6.2 %) was shown in medical students (Zafar et al., 2007). In Japan,
5.8 % of female students were overweight while none was obese (Sakamaki et al., 2005).
5.4 The percentages of pharmacy students meeting RDA for nutrients
The mean energy, protein, carbohydrate, fat, minerals and vitamins were calculated
and compared with the international standards. Anthropometric reference data for
assessing the nutrition of pharmacy students are limited. In summary, physical activity data
do not affect BMI of the pharmacy students studied here, whose energy intake meets the
recommended level for their age and sex. In this study females were more likely to meet
the mean intakes for both micro and macro nutrients.
According to Mann, 2001 adults should consume enough high quality protein from
meat, milk and milk products as well as carbohydrates from a variety of food sources such
as cereal grains (wheat, maize, rice, barley and oats) for adequate growth and development.
Fats and oils however should be consumed sparingly. Fat is essential for absorption
and transport of fat soluble vitamins (Wildman and Miller, 2004). When people consume
too little or too much fat or a large amount of a certain type of fat, health can be affected.
According to Whitney et al. (2007), consumption of fats and oils below 20 % of kJ intake
increases the risk of inadequate essential fatty acid intake.
54
The energy requirements differ, but in general for ages 19-24, they need to be
between 2200 kcal/day for females and 2900 kcal/day for males (WHO, 1987). Energy
should come from various foods. It is recommended that 55-60% of total calories should
come from carbohydrates, 10-20% from protein and less than 30% from fats (DRI, 2002).
The pharmacy male students consumed about 84.6 g proteins, 345g carbohydrates
and 89.3 g lipids that contributed to the total daily energy intake by 10%, 59% and 36%,
respectively. On the other hand, female students consumed about 88 g proteins, 427 g
carbohydrates, and 85 g lipids that contributed to the total daily energy intake by 16%,
71% and 35% respectively. The energy contribution by macronutrients was calculated and
compared accordingly with the recommended dietary intake of 15, 55 and 30% protein,
carbohydrates and fat respectively (Health and Welfare Canada, 1990). According to
Zabut and Elhabiby (2007), average daily energy intakes of nursing students at Islamic
University-Gaza (IUG) were 2310 Kcal (males) and 1740 Kcal (females). The male
students had 12.2% lower energy intake than the reference value reported by WHO, 1987,
whereas the female students exactly met the reference value. In comparison with Palestine
College of Nursing (PCN), the average daily energy intakes were 2250 and 1545 Kcal for
males and females respectively. These values were 14.3% and 10.7%, respectively lower
than the reference values. The Nursing male students at IUG consumed about 90 g
proteins, 321g carbohydrates, and 71 g lipids that contribute to the total daily energy intake
by 15.8%, 56.4% and 27.8%, respectively. On the other hand, female students consumed
about 68 g proteins, 231g carbohydrates, and 59g lipids that contribute to the total daily
energy intake by 15.6%, 53.6% and 30.7%, respectively. In comparison with PCN
students, male students consume about 87 g proteins, 327g carbohydrates, and 62 g lipids
that contribute to the total daily energy intake by 15.7%, 59.0% and 25.4%, respectively.
On the other hand, female students consume about 66 g proteins, 218 g carbohydrates, and
44 g lipids that contribute to the total daily energy intake by 17.1%, 57.1% and 25.7%,
respectively.
When comparing with females, male respondents have appropriate carbohydrate
and fat intakes. Mean percent of total calories from fat for female and male group were
34.4% and 36%, respectively. This percentage is greater than the recommended 30% as
mentioned by NRC, 1989.
55
When the mean intake of vitamins of respondents was compared with RDA, our
respondents consumed inadequate vitamin C. In this study respondents consumed adequate
thiamine, riboflavin and niacin that are essential for carbohydrate use. Vitamins A taken
are sufficiently consumed by the respondents. Vitamin A and C are vital for healthy
immune systems and act as an antioxidant that participates in oxidation-reduction reactions
(Shapiro and Saliou, 2001). The reason for low intake of vitamin C may due to
inadequate consumption of fruits and vegetables by the respondents. Lowered intake often
is associated with chronic disease including atherosclerosis, cancer, senile cataracts, lung
diseases, cognitive decline, and organ degenerative diseases (Institute of Medicine, 2000).
Vitamin C is relatively easy to replenish by consuming fruits, and vegetables, or through
vitamin supplementation (Chernoff, 2005). The food Pyramid suggests 3 to 5 servings of
vegetables each day and 2 to 4 servings of fruits each day.
On average 50.7% of the respondents have inadequate calcium intake. Calcium
intake of female students was lower than that of males. On the other hand 62.1% of the
respondents have adequate phosphorus. The reason for lower intake of calcium may be due
to inadequate consumption of milk and milk products by the respondents (Sanlier and
Unusan, 2007). An intake of more than two portions of milk per day is important for
achieving bone mineral density (Basabe et al., 2004). According to RDA, 1200 mg of
calcium and phosphorus for 19-24 year old provide adequate levels (Sanlier and Unusan,
2007).
In our study, 61.4% of the respondents have adequate iron intake. Iron intake of
female students was lower than that of males. NHANES III data (1988-1991) show that the
mean iron intake of adolescent girls is less than 12 mg (Alajma et al., 1994). According to
the National Academy of Science (2001), the RDA for iron for the adult male is 10
mg/day, while that for the adult woman is 15 mg/day. In our study although males
consume adequate amounts of iron (10 mg RDA), females do not (15 mg RDA). Dietary
factors such as low consumption of red meat, vegetables, cereals and fruits have been
reported to be associated with iron deficiency anemia (Galan et al., 1998). In this study
respondents consumed more than one time weekly of red meat and vegetables. Iron is
relatively easy to replenish by consuming red meat, poultry, beans, leaf of vegetables,
fortified bread, or through iron supplementation., e.g. in the form of ferrous sulfate, ferrous
gluconate, or amino acid chelate tablets. Recent research suggests the replacement dose of
56
iron, at least in the elderly with iron deficiency, may be as little as 15 mg per day of
elemental iron (Rimon et al., 2005).
5.5 dietary habits as stated by the included pharmacy students associated with their
BMI classification
Healthy dietary patterns are associated with healthy lifestyle factors such as being
more physically active (Brodney et al., 2001 and Sjoberg et al., 2003) and regular
consumption of main meals including breakfast (Sjoberg et al., 2003). Adults who skip
breakfast are at higher risk for weight gain and are more likely to have less healthy
behaviors such as increased snacking, sedentary lifestyle, smoking and high BMI (KeskiRahkonen et al., 2003). It is considered important that young adult have regular daily
meals with special attention to breakfast, which is often referred to as the most important
meal of the day (Nicklas et al., 1993a). Our study showed that rarely intake of breakfast at
home were found in 20% of male students and 30% of female students who had normal
BMI (Table 12). The usual number of daily meals in the palestinian context is three;
breakfast, lunch and dinner. Lunch is considered the main meal, and is shared by family
members at home. The findings showed that breakfast was the meal most often skipped;
42% of the female and 34% of the male who skipped breakfast meal had normal BMI.
The present study is in agreement with Sakamaki et al., (2005a) who reported that
the majority of Japanese university students (81.0 %) ate three meals but were also more
likely to skip breakfast. However in Korea 58.9 % of university students ate twice a day
and the most frequently skipped meal was breakfast. The present findings are also in
agreement with Baric et al., (2003), who also found breakfast to be the most frequently
skipped meal in Croatian university students
Table 16 revealed that there is a statistical significance relationship between BMI
and medium intake of salt among male (P< 0.05), it was found that 51% of male students
and 63% of female students who take medium salt in his food had normal BMI. Salted
food may be an addictive substance that stimulates opiate and dopamine receptors in the
brain's reward and pleasure center more than it is "tasty", while salted food preference,
urge, craving and hunger may be manifestations of opiate withdrawal. Salted food and
opiate withdrawal stimulate appetite, increases calorie consumption, augments the
incidence of overeating, overweight, obesity and related illnesses. Obesity and related
illnesses may be symptoms of salted food addiction. (Cocores and Gold, 2009).
57
Few subjects smoke, smoking habit appeared to be of no importance. Several
epidemiological studies indicate that smoker's weight less than nonsmokers. Weight gain is
a likely outcome of smoking cessation. Years ago, it was thought that smokers consumed
less food than nonsmokers owing to the effects of smoking to inhibit the hunger drive
arising from gastric contractions. Studies have reported an increased metabolic rate
immediately following cigarette smoke inhalation and a decreased metabolic rate following
30 days of smoking cessation (Bryant et al., 1986). Table 18 shows that 49% of male
students and 77% of female students who don't smoke cigarettes had normal BMI. Table
18 also shows that 30% of male students smoke less than 10 cigarettes had normal BMI
and 30% of male student's smoke more than 10 cigarettes had overweight.
5.6 Basic food group consumption as stated in frequency per week among the
included pharmacy students associated with their BMI classification
Guidelines for healthy eating practice encourage the consumption of fruits,
vegetables, milk and milk products and whole grain (Wildman and Miller, 2004). The
United States (US) Food Guide Pyramid recommended the number of daily servings of
each group: the food group with the highest number of recommended daily servings
(bread, cereal, and pasta group) form the base of the pyramid; the group with the lowest
recommended number of servings (fats, oils, and sweets) form the apex of the pyramid.
The number of servings per day of different foods included in the questionnaire
revealed that students consumed more servings of grains, vegetables, fruits, milk, meat and
beans had normal weight. However, these servings were consumed less among the students
in the overweight and obese groups. In general, the present study shows that the majority
of students eat either less than or more than the recommended daily servings for most food
groups.
Other studies have shown that the food choices of adolescents and young adults are
not consistent with the dietary guidelines for Americans (Story et al., 2002). A study
conducted by King et al., (2007) revealed that one of each of three university students eat
at least three servings of vegetables a day and less than half (42.2 %) eat at least two
servings of fruits a day. In another study in the USA, Huang et al., (2002) also found a low
intake of fruit and vegetables in most college students. In agreement with the present study,
King et al., (2007) reported that 65.5 % of university students in the USA consume at least
two servings of dairy a day, the minimum amount recommended for this age. In contrast to
the present study, Sakamaki et al., (2005b) found 80 % of university students in China eat
58
fruit and vegetables twice daily. In our study it was found that only 32% of male students
and 44% of female students who eat fresh fruits or juice more than one time weekly have
normal BMI and 28% of male students and 35% of female students who eat fresh
vegetables (green salad) more than one time weekly have normal BMI, but their intakes
were still below the recommended levels.
In the present study, 52% of male students and 67% of female students who intake
within the recommended daily servings of white bread had normal BMI. In contrast,
Anding et al., (2001) reported that breads and grain consumption are less than the
minimum number of servings in most American students. According to Brunt et al.,
(2008), one or few grains are consumed by US college students per day indicating a lack of
diversity for this category. The practice of eating bread and cereals within the
recommended daily intake ought to be encouraged because breads and cereals are an
economical source of carbohydrates. The carbohydrates are a preferred energy source for
body functions (Whitney et al., 2007), and the human brain depends exclusively on
carbohydrate as an energy source.
The low intake of milk, fruits and vegetables, as well as the over-consumption of
meat and meat alternates, sweets and sugar, fats and oils in the present study could be
considered unhealthy according to Wildman and Miller (2004). Low intakes of fruits and
vegetables are a concern because fruits and vegetables are good sources of vitamin C and
β-corotene which act as anti-oxidants protecting the body cells from damage due to
oxidation (Gallagher, 2004). In this way vitamin C and β-carotene can for example, help
in prevention of diseases and infections therefore contributing to good health. According to
Mathai (2004), an inadequate consumption of fruits and vegetables may result in a low
intake of antioxidants and phytochemicals, which are thought to play a role in preventing
cancer and heart disease.
Our study shows that there isn't any statistical significance relationship between
BMI and the consumption of any of the protein rich foods, which 37% of male students
and 47% of female students who eat red or white meat more than one time weekly have
normal BMI. The table 19 also shows that 40% of female students who eat milk or dairy
products more than one times weekly have normal BMI. Although there is no statistical
significance relationship between BMI and legumes consumption (P> 0.05), thus 33% of
male students and 50% of female students who eating legumes one time weekly had
normal BMI.
59
5.7 Association between flour source and the range of serum iron among healthy
students.
An association was found between eating bread made of flour, obtained from
NGOs and the normal range of serum iron among healthy students, because NGOs flour is
fortified by iron.
5.8 Obesogenic food consumption as stated in frequency per week among the included
pharmacy students associated with their BMI classification
Foods, such as chips/crisps are low nutrient but high in fats which provide 38 kJ per
one gram consumed (Okeyo, 2009). Potato chips also contain large amounts of sodium in
the form of salt. The salt gives these chips the flavor and taste which many people find
addictive in potato chips. High sodium intake have also been linked to an increase in blood
pressure. Our study shows that there is a statistical significance relationship between BMI
(P<0.01) and eating chips/crisps among female students that 30.4% of female students and
24.3% of male students who was consuming chips/crisps 3-6 times weekly had normal
BMI. Okeyo (2009) found that there was a statistical significant difference between all
categories of BMI in terms of their daily chips (crisps) consumption. Normal weight (67.6
%) and overweight/obese (72.5 %) nursing students at the university of Fort Hare consumed
more chips/crisps on a daily basis than underweight (28.6 %) nursing students which were
significantly different. This high chips/crisps intake may probably explain the high energy
intake which may have influenced BMI of overweight/obese individuals.
Soft drinks, which are usually high in ―empty‖ calories, contribute the most calories
to the daily diet (Bowman, 2002). Some studies have shown that between 12% and 16% of
the daily caloric intake for children and adolescent comes from soft drinks alone (Subar et
al., 1998 and Forshee et al., 2004). Troiano et al., (2000) found that soft drinks
contributed a significantly higher proportion of daily energy intake in overweight
adolescents than in adolescents who were not overweight. In our study there isn't any
statistical significance relationship between BMI and the consumption of any of the hot or
soft drinks (P> 0.05), whereas about 35% of male students and 47% of female students
who was consuming soft drinks or manufactured juices one time weekly or more had
normal BMI. Regarding the tea, coffee and cocoa there isn't any statistical significant
relationship between BMI and the tea, coffee and cocoa (P> 0.05), where 37% of male
60
students and 44% of female students who was consuming tea, coffee and cocoa one or
more daily had normal BMI.
Karabudak and Kiziltan (2008) found that there isn't a significant association
between the intake of carbonated soft drinks, fruit drinks, 100% fruit juices, sugarsweetened iced tea or coffee or energy drinks and BMI in the subjects.
Our study shows that there isn't any statistical significance relationship between
BMI and the consumption of any of the chocolates (P> 0.05). About 29% of male students
and 37% of female students who was consuming chocolates one time weekly or more had
normal BMI. Regarding the dessert there isn't any statistical significant relationship
between BMI and the dessert (P> 0.05), that 50% of male students and 58% of female
students who was consuming dessert one time weekly or more had normal BMI. Okeyo
(2009) found that there was a statistical significant difference between underweight and
overweight/obese nursing students in terms of their frequency of dessert and chocolate
consumption. The percentage of underweight students who ate dessert and chocolate on a
daily basis was less than overweight/obese individuals at 57 % and 90.0 % respectively.
Our finding are also in agreement with Aranceta et al (2001) who reported a high
prevalence of overweight and obesity among people having a high fat/ sugar ratio.
Generally, it can be concluded that fats, sweets, chocolate and crisps intake played a role in
the prevalence of overweight/obesity seen in this group of students, Okeyo (2009).
.
61
CHAPTER (6)
6. CONCLUSION AND RECOMMENDATIONS
The following conclusions and recommendations can be made regarding the food
consumption patterns, dietary habits of pharmacy Students at Al azhar university and their
influence on body weight status.
6.1 Conclusions
The obtained data provided a general picture of the typical aspects related to food
consumption patterns, dietary habits and body weight status characterizing pharmacy
students.
-
The results showed that, about quarter (24.2%) of the pharmacy students had
overweight which is a key risk factors in the development of numerous chronic health
related conditions such as cancer, cardiovascular disease, hypertension, diabetes, and
other chronic diseases and therefore should be discouraged.
-
The data revealed that there is a statistical significance relationship between BMI and
marital status (P< 0.05) among male students, it was found that 57% of single students
had normal BMI and 26% of single students had overweight.
-
In this study females were more likely to meet the mean intakes for both micro and
macro nutrients
-
These results indicated that, most of pharmacy students at Gaza Strip had normal
energy requirements.
-
The study showed that energy derived from fat which is greater than the recommended
30% or less of kilocalories from fat, and was significantly different between the two
groups.
-
In this study respondents consumed inadequate vitamin C, who were consumed more
than one time weekly of fresh vegetables (green salad), fresh fruit or juice.
-
In our study only male respondents consumed enough phosphorus and iron intakes of
female students were lower than that of males.
-
The findings showed that breakfast were the meal most often skipped; 42% of the
female and 34% of the male who skipped breakfast meal had normal BMI.
-
Our study revealed that there is a statistical significance relationship between BMI and
medium intake of salt among male (P< 0.05), it was found that 51% of male students
and 63% of female students who take medium salt in their food had normal BMI.
62
-
Association between eating bread made of flour originating from NGOs and the normal
range of serum iron among healthy students because flour originating from NGOs
fortified by iron.
-
Our study showed that there is statistical significance relationship between BMI
(P<0.01) and eating chips, and popcorn among female students that 30.4% of female
students and 24.3% of male students who was consuming chips, and popcorn 3-6 times
weekly had normal BMI.
6.2 Recommendations:
Assessments of nutritional status for adults in any population are considered a very
important predictor of health status of this important group. Gaza Strip is very crowded
area, and most people undergo of social economical and political problems affecting their
nutritional status. Accordingly, many adults have high risk of chronic diseases. The present
study used representative samples and gave an indication about the risk of such diseases
between young adult students in Gaza Strip.
Results from food consumption patterns and dietary habits showed that a high
percentage of the students have unhealthy eating habits with less than or more than
recommended daily allowance (RDA) for most food groups therefore major changes in
eating habits of this sample are required.
-
The 3 day food records are regarded as reproducible and provide a useful scale for
categorizing individuals according to their intake of energy and nutrients.
-
Macro and micronutrients intake of pharmacy students is poor. Further research is
needed of the apparent low dietary intake of carbohydrates, calcium, potassium,
sodium and vitamin C in pharmacy students with exploration of potential effects on
health and academic performance.
-
The recommendation is that nutritional education should be targeted at students
entering their first year at faculty of pharmacy and should motivate more healthy food
choices such as increasing daily consumption of fruits and non-fried vegetables, milk,
low-fat dairy, whole grains, a variety in food choices as well as the eating of breakfast
and small changes in physical activity patterns. Breakfast meals should include fruits
and other sources of dietary fibers.
-
Health professional should also be involved in developing and implementing nutrition
education intervention and strategies aimed at improving the nutritional well-being of
individuals and develop messages to raise awareness and develop greater intolerance of
63
the dangers of overweight, obesity and underweight and maintain adequate nutrient
intake as well as regular physical activity among young adults.
-
Nutritional education for male and female students especially related to weight
management and maintains adequate nutrient is recommended. Interventions for the
prevention and control of obesity must go much further than simply prompting
nutrition knowledge.
-
Therefore, the recommendation is studying the relationship between nutritional
knowledge and practices with weight status among healthy young adult students in
Gaza Strip.
-
These messages should be extensive, beamed through the mass media, especially
television, and should project that fatness is a risk factor for a variety of health
problems.
64
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Appendix A
90
Appendix B
91
‫‪Appendix C‬‬
‫)‪(First-day food intake record‬‬
‫الىجبة‬
‫األطعمة الذي جم جناولها وطزيقة‬
‫جحضيزها‬
‫طعام اإلفطار‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بين الىجبات‬
‫أو وجبات خفيفة أو سزيعة‬
‫طعام الغداء‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بين الىجبات‬
‫أو وجبات خفيفة أو سزيعة‬
‫طعام العشاء‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بعد طعام العشاء‬
‫أو وجبات خفيفة أو سزيعة‬
‫‪92‬‬
‫الكمية‬
‫)‪(Second-day food intake record‬‬
‫الىجبة‬
‫األطعمة الذي جم جناولها وطزيقة‬
‫جحضيزها‬
‫طعام اإلفطار‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بين الىجبات‬
‫أو وجبات خفيفة أو سزيعة‬
‫طعام الغداء‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بين الىجبات‬
‫أو وجبات خفيفة أو سزيعة‬
‫طعام العشاء‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بعد طعام العشاء‬
‫أو وجبات خفيفة أو سزيعة‬
‫‪93‬‬
‫الكمية‬
‫)‪(Third-day food intake record‬‬
‫الىجبة‬
‫األطعمة الذي جم جناولها وطزيقة‬
‫جحضيزها‬
‫طعام اإلفطار‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بين الىجبات‬
‫أو وجبات خفيفة أو سزيعة‬
‫طعام الغداء‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بين الىجبات‬
‫أو وجبات خفيفة أو سزيعة‬
‫طعام العشاء‬
‫الىقث‪--------‬‬
‫طعام أو شزاب جم جناوله‬
‫بعد طعام العشاء‬
‫أو وجبات خفيفة أو سزيعة‬
‫‪94‬‬
‫الكمية‬
‫‪Appendix D‬‬
‫اؼزقصبء ىج‪ٞ‬بُ‬
‫أَّبط االؼزٖالك اىغصائ‪ٗ ٜ‬اىؼبزاد اىغصائ‪ٞ‬خ اىَطرجغخ ثبى٘ظُ ػْس اىغالة األصحبء‬
‫‪Food Consumption Patterns and Dietary Habits Associated with‬‬
‫‪Weight Status in Healthy Young Adult Students‬‬
‫األخ اىنط‪ٌٝ‬‬
‫حفظٔ اهلل‬
‫تهدف هرٍ االستببًت إلى التعسف على أًوبط استهالك الطعبم والعبداث الغرائٍت ذاث‬
‫الصلت ببلىشى عٌد طالة كلٍت الصٍدلت بجبهعت األشهس‪ -‬غصة‪.‬‬
‫بهدف الوعسفت والىقىف على الىضع التغروي والسلىكٍبث الغرائٍت ذاث الصلت عٌد‬
‫هؤالء الطلبت‪ .‬هع العلن أى هرٍ االستببًت هىجهت للطالة فً جبهعت األشهس‪-‬كلٍت‬
‫الصٍدلت‪.‬‬
‫الوشبزكت فً هرٍ االستببًت طىعٍت والوعلىهبث التً ٌتن تعبئتهب فً االستببًت سىف‬
‫تبقى سسٌت لي ٌطلع علٍهب أحد ببستثٌبء الببحث والوشسفٍي على الدزاست‪.‬‬
‫فبلسجبء تعبئت هرٍ االستوبزة بدقت هع العلن أى البٍبًبث الىازدة فٍهب هً ألغساض‬
‫البحث العلوً ولي ٌتن ًشسهب أو إعالًهب لغٍس هرا الغسض‪.‬‬
‫شبمط‪ ِٝ‬ىنٌ حؽِ رؼبّٗنٌ‬
‫ٗثبضك اهلل ف‪ٞ‬نٌ‬
‫اىجبحش‬
‫ر٘ف‪ٞ‬ق ىجس‬
‫‪95‬‬
‫ؼجو االؼزجبّخ‬
‫‪1‬‬
‫‪2‬‬
‫‪3‬‬
‫‪4‬‬
‫‪5‬‬
‫‪6‬‬
‫‪7‬‬
‫‪8‬‬
‫ضقٌ االؼزجبّخ‬
‫ربض‪ٝ‬د رؼجئخ االؼزجبّخ‬
‫اؼٌ اىني‪ٞ‬خ‬
‫اىرصبئص اىس‪َ٘ٝ‬غطاف‪ٞ‬خ ٗاالجزَبػ‪ٜ‬ح شاد اىصيخ‬
‫‪----------------‬‬‫اىؼَط‬
‫‪ .....‬شمط‬
‫اىجْػ‬
‫‪ .....‬أّض‪ٚ‬‬
‫ٍنبُ اىؽنِ‬
‫‪ ....‬ضفح ‪ ....‬ذبّ‪ّ٘ٞ‬ػ ‪ ....‬اىَْغقخ اى٘ؼغ‪ٚ‬‬
‫‪ ....‬غعح ‪ ....‬شَبه غعح‬
‫اىَؽز٘‪ ٙ‬األمبز‪ .... َٜٝ‬األٗه ‪ ....‬اىضبّ‪ .... ٜ‬اىضبىش ‪ ....‬اىطاثغ ‪ ....‬اىربٍػ ‪ٍ ....‬بجؽز‪ٞ‬ط‬
‫اىحبىخ االجزَبػ‪ٞ‬خ‬
‫‪ٍ ....‬زعٗط ‪ ....‬أػعة ‪ٍ ....‬غيق‬
‫‪.... .... ....‬‬
‫‪ .... .... / .... .... / .... .... .... ....‬اىزؼجئخ ٍِ اى‪ٞ‬ؽبض‬
‫‪-----------------‬‬
‫‪ 9‬إشا مْذ ٍزعٗجب أٗ ٍغيق فَب ٕ٘ ػسز‬
‫أفطاز أؼطرل؟‬
‫‪ 10‬إشا مْذ أػعثب فَب ٕ٘ ػسز أفطاز األؼطح؟ ‪-----------------‬‬
‫‪-----------------‬‬
‫‪ 11‬ػَط األً‬
‫‪ 12‬اىَؽز٘‪ ٙ‬اىزؼي‪ َٜٞ‬ىألً‬
‫‪ 13‬ػَط األة‬
‫‪ 14‬اىَؽز٘‪ ٙ‬اىزؼي‪ َٜٞ‬ىألة‬
‫‪ٕ 15‬و األة ‪ٝ‬ؼَو؟‬
‫‪ٕ 16‬و األً رؼَو؟‬
‫‪ 17‬زذو اىؼبئيخ اىشٖط‪ ٛ‬ثبىش‪ٞ‬نو‬
‫‪----------------‬‬‫‪ ....‬ثسُٗ رؼي‪ .... ٌٞ‬اثزسائ‪ .... ٜ‬إػساز‪ٛ‬‬
‫‪ ....‬جبٍؼ‪ .... ٜ‬زضاؼبد ػي‪ٞ‬ب‬
‫‪ ....‬صبّ٘‪ٛ‬‬
‫‪----------------‬‬‫‪ ....‬ثسُٗ رؼي‪ .... ٌٞ‬اثزسائ‪ .... ٜ‬إػساز‪ٛ‬‬
‫‪ ....‬جبٍؼ‪ .... ٜ‬زضاؼبد ػي‪ٞ‬ب‬
‫‪ ....‬صبّ٘‪ٛ‬‬
‫‪ٍ ....‬صبزض أذط‪ ٙ‬ىيسذو‬
‫‪ّ ....‬ؼٌ ‪ ....‬ال‬
‫‪ٍ ....‬صبزض أذط‪ ٙ‬ىيسذو‬
‫‪ّ ....‬ؼٌ ‪ ....‬ال‬
‫‪ ....‬أقو ٍِ ‪ 1000‬ش‪ٞ‬نو ‪ ....‬أمضط ٍِ ‪ 1000‬ش‪ٞ‬نو‬
‫‪ ....‬ال أػطف‬
‫‪ ....‬ال أػطف‬
‫‪ ....‬ال‬
‫‪ّ ....‬ؼٌ‬
‫‪ٕ 18‬و زذو األؼطح اىشٖط‪٘ٝ ٛ‬فط‬
‫احز‪ٞ‬بجبد اىؼبئيخ اىغصائ‪ٞ‬خ؟‬
‫‪ّ ....‬ؼٌ‬
‫‪ٕ 19‬و أّذ رؼَو ثجبّت اىسضاؼخ ؟‬
‫‪ 20‬إشا مْذ رؼَو فَب ٕ‪ ٜ‬عج‪ٞ‬ؼخ ػَيل؟ ‪ٍْٜٖ ....‬‬
‫‪ ....‬ال‬
‫‪ٍ ....‬نزج‪ٜ‬‬
‫‪ ....‬أذط‪ٙ‬‬
‫اىؼبزاد اىغصائ‪ٞ‬خ ٗاىََبضؼبد ػْس اىغبىت‪/‬ح شاد اىصيخ‬
‫‪ٍ )4-3 ( ....‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪ٍٞ٘ٝ ....‬ب‬
‫‪ٕ 21‬و رزْبٗه عؼبً اإلفغبض ف‪ ٜ‬اىج‪ٞ‬ذ؟‬
‫‪ ....‬أقو ٍِ ٍطر‪ ِٞ‬ف‪ ٜ‬األؼج٘ع‬
‫‪ٗ ....‬ججخ ٗاحسح‬
‫‪ 22‬مٌ ػسز اى٘ججبد اىز‪ ٜ‬رزْبٗىٖب ‪ٍٞ٘ٝ‬ب؟‬
‫‪ّ ....‬بزضا‬
‫‪ٗ ....‬ججذاُ‬
‫‪ ....‬صالس ٗججبد ‪ ....‬أمضط ٍِ صالس ٗججبد‬
‫‪96‬‬
‫‪ٗ ....‬ججذاُ‬
‫‪ٗ ....‬ججخ ٗاحسح‬
‫‪ّ ....‬بزضا‬
‫‪ ....‬أضثغ ٗججبد‬
‫‪ ....‬صالس ٗججبد‬
‫‪ ....‬ال‬
‫‪ّ ....‬ؼٌ‬
‫‪ 23‬مٌ ٗججخ رزْبٗه ث‪ ِٞ‬اى٘ججبد اىطئ‪ٞ‬ؽ‪ٞ‬خ؟‬
‫‪ٕ 24‬و رزْبٗه ٗججبرل ف‪ٗ ٜ‬قزٖب ثبّزظبً؟‬
‫‪ٕ 25‬و رأذص اى٘قذ اىنبف‪ ٜ‬ىزأمو ٗججبرل‬
‫اىطئ‪ٞ‬ؽ‪ٞ‬خ ‪ٍٞ٘ٝ‬ب؟‬
‫‪ 26‬ػسز اىَطاد اىز‪ ٜ‬رزْبٗه ثٖب عؼبٍل‬
‫‪....‬‬
‫ّؼٌ‬
‫‪....‬‬
‫‪ ....‬رقط‪ٝ‬جب ‪ٍٞ٘ٝ‬ب‬
‫ذبضط اىج‪ٞ‬ذ‪.‬‬
‫ال‬
‫‪ٍ )2-1( ....‬طح اؼج٘ػ‪ٞ‬ب‬
‫‪ٍ )5-3( ....‬طاد أؼج٘ػ‪ٞ‬ب ‪ ....‬أمضط ٍِ ‪ٍ 5‬طاد‬
‫أؼج٘ػ‪ٞ‬ب‬
‫‪ 27‬اى٘ججبد اىطئ‪ٞ‬ؽ‪ٞ‬خ اىز‪ ٜ‬ال رزْبٗىٖب ٕ‪:ٜ‬‬
‫‪ ....‬ال أرْبٗه اىغؼبً ذبضط اىَْعه‬
‫‪ٗ ....‬ججخ اىغصاء‬
‫‪ٗ ....‬ججخ اإلفغبض‬
‫‪ٗ ....‬ججخ اىؼشبء‬
‫‪ ....‬إرجبع حَ‪ٞ‬خ غصائ‪ٞ‬خ (ضج‪)ٌٞ‬‬
‫‪ 28‬اىؽجت ف‪ ٜ‬ػسً رْبٗىل ألحس‪ ٙ‬اى٘ججبد‬
‫‪ ....‬ى‪ٞ‬ػ ىس‪ٝ‬ل ٗقذ‬
‫اىطئ‪ٞ‬ؽ‪ٞ‬خ ٕ٘‪:‬‬
‫‪ ....‬فقساُ اىشٖ‪ٞ‬خ ىيغؼبً ‪ ....‬أؼجبة أذط‪ٙ‬‬
‫‪ٕ 29‬و رحت أُ ‪ٝ‬نُ٘ اىغؼبً ‪-------‬؟‬
‫‪ ....‬ثسُٗ ٍيح ‪ٍ ....‬يح ٍز٘ؼظ ‪ٍ ....‬يح ظائس‬
‫‪ٕ 30‬و رحت أُ ‪ٝ‬نُ٘ اىغؼبً ‪-------‬؟‬
‫‪ ....‬ثسُٗ ثٖبضاد ‪ ....‬ثٖبضاد ٍز٘ؼغخ‬
‫‪ ....‬ثٖبضاد ظائسح‬
‫‪ٍٞ٘ٝ ....‬ب‬
‫‪ٕ 31‬و رَبضغ اىط‪ٝ‬بضخ؟‬
‫‪ٍ ....‬طر‪ ِٞ‬أؼج٘ػ‪ٞ‬ب‬
‫‪ ....‬أمضط ٍِ أضثغ ٍطاد أؼج٘ػ‪ٞ‬ب‬
‫‪ ....‬ال‬
‫‪ٕ 32‬و أّذ ٍسذِ؟‬
‫‪ّ ....‬ؼٌ‬
‫‪ 33‬إشا مبّذ اإلجبثخ ثْؼٌ ف‪ ٜ‬اىؽؤاه اىؽبثق‬
‫‪....‬‬
‫فمٌ ؼ‪ٞ‬جبضح رسذِ ثبى‪ً٘ٞ‬؟‬
‫‪ 10‬ؼجبئط‬
‫‪ ....‬ال‬
‫‪....‬‬
‫أقو ٍِ ‪ 10‬ؼجبئط‬
‫‪ ....‬أمضط ٍِ ‪ 10‬ؼجبئط‬
‫‪ّ ....‬ؼٌ‬
‫‪ٕ 34‬و رزْبٗه اىش‪ٞ‬شخ؟‬
‫أَّبط اؼزٖالك اىغؼبً ػْس اىغبىت شاد اىصيخ‬
‫‪ّ ....‬بزضا‬
‫‪ 35‬مٌ رأمو ىحٍ٘ب ث‪ٞ‬ضبء أٗ حَطاء؟‬
‫‪ ....‬ال‬
‫‪ٍ ....‬طح ٗاحسح أؼج٘ػ‪ٞ‬ب‬
‫‪ٍ )4-2( ....‬طاد أؼج٘ػ‪ٞ‬ب‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد أؼج٘ػ‪ٞ‬ب‬
‫‪97‬‬
‫‪ّ ....‬بزضا‬
‫‪ 36‬مٌ ٍطح رزْبٗه اىحي‪ٞ‬ت أٗ ٍْزجبد‬
‫األىجبُ؟‬
‫‪ٍ ....‬طح ٗاحسح أؼج٘ػ‪ٞ‬ب‬
‫‪ٍ )4-2( ....‬طاد أؼج٘ػ‪ٞ‬ب‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد أؼج٘ػ‪ٞ‬ب‬
‫‪ٍ ....‬طح ٗاحسح أؼج٘ػ‪ٞ‬ب‬
‫‪ 37‬مٌ ٍطح رزْبٗه اىف٘امٔ اىغبظجخ أٗ‬
‫ػص‪ٞ‬طٕب ؟‬
‫‪ٍ )4-2( ....‬طاد أؼج٘ػ‪ٞ‬ب‬
‫‪( ....‬أمضط ٍِ ذَػ ٍطاد أؼج٘ػ‪ٞ‬ب‬
‫‪ٍ ....‬طح ٗاحسح أؼج٘ػ‪ٞ‬ب‬
‫‪ 38‬مٌ ٍطح رزْبٗه اهذضطٗاد اىغبظجخ‬
‫(ؼيغخ ذضبض)؟‬
‫‪ٍ )4-2( ....‬طاد أؼج٘ػ‪ٞ‬ب‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد أؼج٘ػ‪ٞ‬ب‬
‫‪ ....‬ذجع أث‪ٞ‬ض‬
‫‪ٍ 39‬ب ٕ٘ ّ٘ع اىرجع اىص‪ ٛ‬رزْبٗىٔ ف‪ٜ‬‬
‫عؼبٍل أؼج٘ػ‪ٞ‬ب؟‬
‫‪ ....‬ذجع أؼ٘ز‬
‫‪ ....‬ال أػطف اىْ٘ع‬
‫‪ ٍِ .. CHF ... UNRWA ....‬اىَربثع‬
‫‪ 40‬اىرجع اىص‪ ٛ‬رزْبٗىٔ ٍصْ٘ع ٍِ عح‪ِٞ‬‬
‫ٍصسضٓ ٍِ‪-:‬‬
‫‪ٍ ..‬ؤؼؽبد أذط‪NGOs ٙ‬‬
‫‪ٍ ....‬طح ٗاحسح‬
‫‪ 41‬مٌ ٍطح رأمو األضظ أؼج٘ػ‪ٞ‬ب ؟‬
‫‪ 42‬مٌ ٍطح رأمو اىجق٘ى‪ٞ‬بد ٍضو اىجبظ‪ٝ‬الء أٗ‬
‫اىؼسغ أٗ اىف٘ه أؼج٘ػ‪ٞ‬ب ؟‬
‫‪ 43‬مٌ ٍطح رأمو اىَؼنطّٗخ أؼج٘ػ‪ٞ‬ب ؟‬
‫‪ 44‬مٌ ٍطح رزْبٗه اىرضطٗاد اىَغج٘ذخ‬
‫أؼج٘ػ‪ٞ‬ب ؟‬
‫‪ٍ )4-2( ....‬طاد‬
‫ّبزضا‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد‬
‫‪....‬‬
‫‪ٍ ....‬طح ٗاحسح‬
‫‪ٍ )4-2( ....‬طاد‬
‫ّبزضا‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد‬
‫‪....‬‬
‫‪ٍ ....‬طح ٗاحسح‬
‫‪ٍ )4-2( ....‬طاد‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد‬
‫‪....‬‬
‫‪ٍ ....‬طح ٗاحسح‬
‫‪ٍ )4-2( ....‬طاد‬
‫‪ ....‬أمضط ٍِ ذَػ ٍطاد‬
‫‪....‬‬
‫ّبزضا‬
‫ّبزضا‬
‫أَّبط اؼزٖالك اىغؼبً اىز‪ ٜ‬رؤز‪ ٛ‬إى‪ ٚ‬اىؽَْخ ػْس اىغبىت شاد اىصيخ‬
‫‪ّ ....‬ؼٌ‬
‫‪ٕ 45‬و رزْبٗه اىَشطٗثبد اىغبظ‪ٝ‬خ أٗ اىؼصبئط اىصْبػ‪ٞ‬خ؟‬
‫‪ 46‬إشا مبّذ اإلجبثخ ثْؼٌ ف‪ ٜ‬اىؽؤاه‬
‫‪ ....‬ال‬
‫‪ٍ )2-1( ....‬طح ف‪ ٜ‬األؼج٘ع‬
‫اىؽبثق‪ :‬فمٌ ٍطح رزْبٗه اىَشطٗثبد‬
‫‪....‬‬
‫(‪ٍ )6-3‬طاد ف‪ ٜ‬األؼج٘ع‬
‫اىغبظ‪ٝ‬خ أٗ اىؼصبئط اىصْبػ‪ٞ‬خ؟‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪ٍ )2-1( ....‬طح ف‪ ٜ‬األؼج٘ع‬
‫‪ 47‬مٌ ٍطح رزْبٗه اىش٘م٘الرخ؟‬
‫‪98‬‬
‫‪....‬‬
‫ّبزضا‬
‫‪ 48‬مٌ ٍطح رزْبٗه اىحي٘‪ٝ‬بد؟‬
‫‪....‬‬
‫(‪ٍ )6-3‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪....‬‬
‫ّبزضا‬
‫‪ٍ )2-1( ....‬طح ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫(‪ٍ )6-3‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪ٕ 49‬و رزْبٗه اىشب‪ٗ ٛ‬اىقٖ٘ح ٗاىنبمبٗ؟‬
‫‪....‬‬
‫ّؼٌ‬
‫‪ 50‬ف‪ ٜ‬اىؽؤاه اىؽبثق إشا مبّذ اإلجبثخ‬
‫ثْؼٌ‪:‬‬
‫مٌ ٍطح رزْبٗه اىشب‪ٗ ٛ‬اىقٖ٘ح ٗاىنبمبٗ ؟‬
‫‪ٍ )2-1( ....‬طح ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫‪....‬‬
‫ّبزضا‬
‫ال‬
‫‪....‬‬
‫(‪ٍ )6-3‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪ ....‬ال أرْبٗه‬
‫‪ ....‬ثؼس األمو ٍجبشطح‬
‫‪ 51‬رزْبٗه اىشب‪ٗ ٛ‬اىقٖ٘ح‪:‬‬
‫‪....‬‬
‫ثؼس األمو ثؽبػخ‬
‫‪ ....‬ال أرْبٗه اىشب‪ ٛ‬أٗ اىقٖ٘ح‬
‫‪ٍ )2-1( ....‬طح ف‪ ٜ‬األؼج٘ع‬
‫‪ 52‬مٌ ٍطح رزْبٗه ضقبئق اىجغبعب (ش‪ٞ‬جػ)‪,‬‬
‫شضح فشبض ٗاىَؽي‪ٞ‬بد؟‬
‫‪....‬‬
‫(‪ٍ )6-3‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪ ....‬ال أرْبٗه‬
‫‪ٍ )2-1( ....‬طح ف‪ ٜ‬األؼج٘ع‬
‫‪ 53‬مٌ ٍطح رزْبٗه اىج‪ٞ‬زعا أٗ اىَؼجْبد؟‬
‫‪....‬‬
‫(‪ٍ )6-3‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪ ....‬ال أرْبٗه‬
‫‪ 54‬مٌ ٍطح رزْبٗه اىؽْسٗرشبد اىؽط‪ٝ‬ؼخ ٍضو ‪ٍ )2-1( ....‬طاد ف‪ ٜ‬األؼج٘ع‬
‫اىَٖج٘ضجط أٗاىشبٗضٍب ٗغ‪ٞ‬طٓ؟‬
‫‪ٍ )6-3( ....‬طاد ف‪ ٜ‬األؼج٘ع‬
‫‪....‬‬
‫ٍطح أٗ أمضط ‪ٍٞ٘ٝ‬ب‬
‫‪ ....‬ال أرْبٗه‬
‫اىزبض‪ٝ‬د اىغج‪ ٜ‬ىيغبىت‬
‫‪ ....‬أة‬
‫‪ 55‬أحس أفطاز ػبئيزل ٍصبة ثبىؽَْخ‪:‬‬
‫‪....‬‬
‫‪99‬‬
‫جس‬
‫‪ ...‬أً‬
‫‪ ...‬جسح‬
‫‪ ...‬مال ٍِ األة ٗاألً‬
‫‪...‬‬
‫ال أحس‬
‫‪56‬‬
‫‪57‬‬
‫‪58‬‬
‫‪59‬‬
‫إشا مبّذ اإلجبثخ ثْؼٌ ف‪ ٜ‬اىؽؤاه اىؽبثق‬
‫فَب ٕ٘ ٗظُ شىل اىشرص؟‬
‫ٕو ىس‪ٝ‬ل حؽبؼ‪ٞ‬خ ألحس األعؼَخ؟‬
‫إشا مبّذ اإلجبثخ ثْؼٌ أشمط اؼٌ اىغؼبً‬
‫اىَؽجت ىيحؽبؼ‪ٞ‬خ‪.‬‬
‫ٕو رزْبٗه أزٗ‪ٝ‬خ ٍؼ‪ْٞ‬خ؟‬
‫إشا مبّذ اإلجبثخ ف‪ ٜ‬اىؽؤاه اىؽبثق ثْؼٌ‬
‫أشمط اؼٌ اىسٗاء‬
‫‪-------------------‬‬‫‪....‬‬
‫ّؼٌ‬
‫‪ ...‬ال‬
‫‪-------------------‬‬‫‪ ...‬ال‬
‫‪ّ ....‬ؼٌ‬
‫‪------------------------------------------‬‬‫‪-------------------------------------------‬‬
‫ّشبط اىغبىت اىجؽَبّ‪ ٜ‬اى‪ٍٜ٘ٞ‬‬
‫‪ّ ....‬شبط ٍطرفغ‬
‫‪ّ . ..‬شبط ٍطرفغ جسا‬
‫‪ ....‬مض‪ٞ‬ط اىجي٘غ‬
‫‪ّ ....‬شبط ذف‪ٞ‬ف‬
‫‪ّ ....‬شبط ٍؼزسه‬
‫ٍؤشط مزيخ اىجؽٌ ػْس اىغبىت‬
‫‪ .... ....‬ؼْخ‬
‫‪ 60‬ػَط اىغبىت ‪ ً٘ٝ‬رؼجئخ االؼزج‪ٞ‬بُ‬
‫‪ .... .... .... .... ....‬م‪ٞ‬ي٘جطاً‬
‫‪ٗ 61‬ظُ اىغبىت ‪ ً٘ٝ‬االؼزج‪ٞ‬بُ‬
‫‪ .... .... .... ....‬ؼْز‪َٞ‬زطا‬
‫‪ 62‬ع٘ه اىغبىت ‪ ً٘ٝ‬االؼزج‪ٞ‬بُ‬
‫شنطا‬
‫‪/‬‬
‫‪Signed‬‬
‫‪Date /‬‬
‫‪100‬‬
Appendix E
101
102
103
‫‪Appendix F‬‬
‫‪Daily of Food Intake Records‬‬
‫ذعهًٍاخ ٌدة أٌ ٌرثعها انطانة‬
‫ ين فضهك ال جنسى جسجٍم انٍىو وانحارٌخ وانىقث انذي جقىو فٍه بحسجٍم يعهىيات األطعًة‬‫وانًشزوبات التي جى جناونها وكًٍحها أٌضا‪.‬‬
‫ أكحب كم شًء جشزبه أو جأكهه عهى يدار انٍىو و طزٌقة انطبخ يثم يقهٍة أو يطبىخة أو‬‫يشىٌة‪.‬‬
‫ سجم يححىٌات انىجبة كم صنف بشكم ينفزد يثال ساندوٌحش سًك انحىنا جسجم يححىٌاجه‬‫كانحانً ‪ -:‬رغٍف بٍحا ويعهقحٍن بحجى يعهقة انشاي سٌث و‪ 50‬جزاو سًك جىنا ‪.‬‬
‫تعض األيثهح عهى كٍفٍح كراتح حدى وكًٍح انطعاو انًرُاونح كانرانً‪:‬‬
‫انًادج انغزائٍح‬
‫خثض أتٍض ‪ +‬خثض أعًش‬
‫كٍك تانشكىالذه يغطى تكشًٌح‬
‫انشكىالذح‬
‫كٍك اتٍض‬
‫تاٌ كٍك‬
‫أسص ( يطثىخ )‬
‫يعكشوَح يطثىخح‬
‫فشاونح‬
‫ذفاذ‬
‫تشذمال‬
‫يىص‬
‫عُة‬
‫أفىكادو‬
‫نًٍىٌ‬
‫خٍاس‬
‫خضس‬
‫تطاطظ‬
‫تطاطا حهىج ( فُذال )‬
‫تارَداٌ‬
‫تايٍح‬
‫تصم‬
‫ثىو‬
‫فدم‬
‫لشع‬
‫طًاطى‬
‫فهفم أخضش حاس‬
‫فهفم أخضش تاسد‬
‫لشَثٍط‬
‫يهفىف (حدى كثٍش)‬
‫انحدى‬
‫(تانرمشٌة)‬
‫ششٌحح واحذج‬
‫انىصٌ‬
‫(خى)‬
‫‪25‬‬
‫ششٌحح واحذج‬
‫‪64‬‬
‫ششٌحح واحذج‬
‫ششٌحح واحذج‬
‫كىب واحذ‬
‫كىب واحذ‬
‫كىب واحذ‬
‫واحذج يرىعطح‬
‫واحذج يرىعطح‬
‫واحذج يرىعطح‬
‫كىب واحذ‬
‫واحذج يرىعطح‬
‫واحذج يرىعطح‬
‫َصف كىب‬
‫واحذج يرىعطح‬
‫واحذج يرىعطح‬
‫كىب واحذ‬
‫َصف كىب‬
‫كىب واحذ‬
‫كىب واحذ‬
‫فص واحذ‬
‫َصف كىب‬
‫َصف كىب‬
‫واحذج يرىعطح‬
‫لطعح واحذج‬
‫واحذج يرىعطح‬
‫َصف كىب‬
‫كىب واحذ‬
‫‪74‬‬
‫‪28.35‬‬
‫‪158‬‬
‫‪140‬‬
‫‪146‬‬
‫‪138‬‬
‫‪131‬‬
‫‪114‬‬
‫‪92‬‬
‫‪201‬‬
‫‪58‬‬
‫‪104‬‬
‫‪60‬‬
‫‪202‬‬
‫‪328‬‬
‫‪82‬‬
‫‪160‬‬
‫‪159.87‬‬
‫‪3‬‬
‫‪116‬‬
‫‪130‬‬
‫‪123‬‬
‫‪45‬‬
‫‪74‬‬
‫‪100‬‬
‫‪70‬‬
‫‪104‬‬
‫يهفىف (حدى صغٍش)‬
‫خظ‬
‫فاصىنٍا خضشاء طاصخح‬
‫تاصالء يع خضس يثهح‬
‫نىتٍا‬
‫رسج يحهى ويعهة‬
‫خٍاس يخهم حايض‬
‫ذثىنح‬
‫حهٍة كايم انذعى‬
‫حهٍة لهٍم انذعى‬
‫يخفىق انحهٍة تانشكىالذه‬
‫نثٍ‬
‫خثٍ شذس‬
‫خثٍ كشٌى (كايم انذعى )‬
‫خثٍ كشٌى(لهٍم انذعى)‬
‫خثُح تٍضاء (فٍرا )‬
‫خثٍ يثهثاخ‬
‫نحى تمش يمهً (يطحىٌ)‬
‫نحى تمش يغهىق (يطحىٌ)‬
‫كثذج نحى يطثىخح‬
‫نحى عدم يطثىخ‬
‫صذس دخاج يمهً‬
‫فخذ دخاج يمهً‬
‫كثذ دخاج‬
‫تٍض يمهً‬
‫تٍض يغهىق‬
‫تٍض اويٍهٍد‬
‫عًك ذىَا يعهة‬
‫عًك يمهً تانثفصًاخ ( فٍهٍه )‬
‫حـًــــص‬
‫عــذط‬
‫عصٍش تشذمال‬
‫عصٍش أَاَاط‬
‫عصٍش خضس‬
‫شاي يع عكش‬
‫لهىج خاهضج‬
‫لهىج كثرشٍُى‬
‫كىال( عادي )‬
‫صتذج ياسخشٌٍ ( يًهحح )‬
‫صٌد انضٌرىٌ‬
‫فغرك يحًص‬
‫نىص (تٍذاٌ )‬
‫خىص‬
‫حهٍة تانشكىالذح‬
‫شثظ‬
‫كٍد كاخ‬
‫تغكىٌد تانشكىالذح‬
‫تغكىٌد وٌفش( عادي )‬
‫كىب واحذ‬
‫كىب واحذ‬
‫َصف كىب‬
‫َصف كىب‬
‫َصف كىب‬
‫كىب واحذ‬
‫ششٌحح واحذج‬
‫يهعمرٍٍ طعاو‬
‫كىب واحذ‬
‫كىب واحذ‬
‫كىب وَصف‬
‫كىب واحذ‬
‫‪ 3‬يالعك طعاو‬
‫يهعمرٍٍ طعاو‬
‫يهعمرٍٍ طعاو‬
‫‪ 3‬يالعك طعاو‬
‫لطعح وَصف‬
‫يهعمرٍٍ طعاو‬
‫يهعمرٍٍ طعاو‬
‫‪ 4‬لطع يرىعطح‬
‫‪ 3‬لطع صغٍشج‬
‫½ صذس دخاخح صغٍشج‬
‫فخذ دخاخح يرىعطح‬
‫‪ 3‬لطع يرىعطح‬
‫واحذج كثٍشج‬
‫واحذج كثٍشج‬
‫واحذج كثٍشج‬
‫ساحح انٍذ‬
‫ساحح انٍذ‬
‫َصف كىب‬
‫َصف كىب‬
‫ثالثح أستاع انكىب‬
‫كىب واحذ‬
‫ثالثح أستاع انكىب‬
‫ثالثح أستاع انكىب‬
‫كىب وَصف‬
‫كىب وَصف‬
‫كىب وَصف‬
‫يهعمح صغٍشج‬
‫يهعمح صغٍشج‬
‫َصف كىب‬
‫َصف كىب‬
‫َصف كىب‬
‫عهثح واحذج‬
‫كٍظ صغٍش‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫‪105‬‬
‫‪156‬‬
‫‪56‬‬
‫‪110‬‬
‫‪160‬‬
‫‪256‬‬
‫‪164‬‬
‫‪7‬‬
‫‪28.35‬‬
‫‪244‬‬
‫‪244‬‬
‫‪345.44‬‬
‫‪245‬‬
‫‪28.35‬‬
‫‪28.35‬‬
‫‪16.01‬‬
‫‪28.35‬‬
‫‪28.35‬‬
‫‪85‬‬
‫‪85‬‬
‫‪85‬‬
‫‪85‬‬
‫‪85‬‬
‫‪85‬‬
‫‪85‬‬
‫‪46‬‬
‫‪50‬‬
‫‪59‬‬
‫‪85‬‬
‫‪85‬‬
‫‪60‬‬
‫‪56‬‬
‫‪248‬‬
‫‪250.17‬‬
‫‪246‬‬
‫‪236‬‬
‫‪29.86‬‬
‫‪29.3‬‬
‫‪369‬‬
‫‪4.7‬‬
‫‪13.51‬‬
‫‪112‬‬
‫‪112‬‬
‫‪120‬‬
‫‪44‬‬
‫‪25‬‬
‫‪46‬‬
‫‪7‬‬
‫‪25‬‬
‫وٌفش تانشكىالذح‬
‫عُكشط‬
‫ذىفً‬
‫ذىكظ‬
‫خهً‬
‫عغم‬
‫عكش أتٍض‬
‫عُذوٌش تشخش تاندثٍ‬
‫عُذوٌش تشخش عادي‬
‫عُذوٌش تانذخاج‬
‫عُذوٌش دخاج فٍهٍح‬
‫تٍرضا تاندثٍ‬
‫تطاطظ يمهٍح‬
‫يشق نحى‬
‫دخاج تانفشٌ‬
‫يشق دخاج‬
‫عًك يشىي‬
‫خشٌش‬
‫يشق عذط‬
‫يكشوَه تانثشايٍم‬
‫كفره‬
‫يحشً كىعا‬
‫يحشً وسق عُة‬
‫شىستح انذخاج تانخضشواخ‬
‫خثض سلاق‬
‫عهطح خضشاواخ‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫َصف كىب‬
‫يهعمح طعاو‬
‫يهعمح شاي‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫لطعح واحذج‬
‫ششٌحح واحذج‬
‫حدى كثٍش‬
‫َصف كىب‬
‫ستع دخاخح‬
‫َصف كىب‬
‫َصف كىب‬
‫َصف كىب‬
‫َصف كىب‬
‫َصف كىب‬
‫‪ 3‬حثاخ‬
‫حثح واحذج‬
‫‪ 4‬حثاخ‬
‫كىب واحذ‬
‫سغٍف واحذ‬
‫َصف كىب‬
‫‪106‬‬
‫‪6‬‬
‫‪61‬‬
‫‪12‬‬
‫‪57‬‬
‫‪140‬‬
‫‪21‬‬
‫‪4‬‬
‫‪138‬‬
‫‪102‬‬
‫‪229‬‬
‫‪182‬‬
‫‪63‬‬
‫‪115‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪100‬‬
‫‪241‬‬
‫‪100‬‬
‫‪100‬‬