Food Consumption Patterns and Dietary Habits Associated with

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‫ 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.

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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.

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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.

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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

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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).

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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.

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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

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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).

.

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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.

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Song WO, Chun OK, Obayashi S, Cho S and Chung CE (2005): Is consumption of breakfast associated with body mass index in US adults? J Am Diet Assoc; 105:1373– 82. Spencer L (2002): Results of a heart disease risk-factor screening among traditional college students. J Am Coll Health; 50:291-296. Stanton JL and Keast DR (1989): Serum cholesterol, fat intake, and breakfast consumption in the United States adult population. J Am Coll Nutr; 8:567–72. Stea TH, Wandel M, Mansoor MA, Uglem S and Frølich W (2009): BMI, lipid profile, physical fitness and smoking habits of young male adults and the association with parental education. Eur J Public Health. Jan; 19(1):46-51. Steffen LM, Jacobs DR, Murtaugh MA, Moran A, Steinberger J, Hong CP and Sinaiko AR (2003): Whole grain intake is associated with lower body mass and greater insulin sensitivity among adolescents. Am J Epidemiol; 58:243-250. Steyn NP, Myburgh NG and Nel JH (2003): Evidence of support of food-based dietary guideline on sugar consumption in South Africa. Bulletin of World Heath Organization; vol. 81, no. 8, pp. 599-608. Story M, Neumark-Sztainer D and French S (2002): Individual and environmental influences on adolescent eating behaviours. J. Am. Diet. Assoc. 102 (Suppl), S40–S51. Stunkard, AJ and Wadden TA (1993): Obesity: Theory and Therapy. 2nd Edn. Raven Press, New York. Subar AF, Krebs-Smith SM, Cook A and Kahle LL (1998): Dietary sources of nutrients among US children, 1989-1991. Pediatrics, 102: 913-923. Summerbell CD, Moody RC, Shanks J, Stock MJ and Geissler C. (1996): Relationship between feeding pattern and body mass index in 220 free-living people in four age groups. Eur J Clin Nutr; 50:513–19

85

Sundquist J, and Johansson SE (1998): The influence of socioeconomic status, ethnicity and lifestyle on body mass index in a longitudinal study. International Journal of Epidemiology; vol. 27, pp. 57-63. Telama R and Yang X (2000): Decline of physical activity from youth to young adulthood in Finland. Med Sci Sports Exerc; 32: 1617–1622. Temple NJ, Steyn K, Hoffman M, Levitt NS and Lombard CJ (2001): The epidemic of obesity in South Africa: a study in disadvantaged community. Ethnicity and Disease; vol.11, No. 3, pp. 431-437. Tietz NW (1987). Fundamentals of Clinical Chemistry, p.940. W.B. Saunders Co., Philadelphia. Togo P, Osler M, Sorensen TIA and Heitmann BL (2001): Food intake patterns and body mass index in observational studies. Int J Obes; 25:1741-1751. Troiano RP, Briefel RR, Carroll MD and Bialostosky K (2000): Energy and fat intakes of children and adolescents in the United States: data from the national health and nutrition examination surveys. Am. J. Clin. Nutr., 72: 1343S-1353S. US Department of Agriculture (2005): Nutrition and your health: Dietary Guidelines for Americans. 6th ed. Washington, DC: US Department of Health and Human Services. Van den Brandt PA, Spiegelman D and Yaun SS (2000): Pooled analysis of prospective cohort studies on height, weight and breast cancer risk. Am J Epidemiol; 152:514-27. Van Mechelen W, Twisk JW, Post GB, Snel J and Kemper HC (2000): Physical activity of young people: the Amsterdam Longitudinal Growth and Health Study. Med Sci Sports Exerc; 32:1610–1616. Wang Y (2001): Cross-national comparison of childhood obesity: the epidemic and the relationship between obesity and socioeconomic status. Int J Epidemiol 30:1129–1136. Weinberg LG, Berner LA and Groves JE (2004): Nutrient contributions of dairy foods in the UnitedStates, Continuing Survey of Food Intakes by Individuals, 1994-1996,1998. J Am diet Assoc; 104:895-902. 86

Wellens RI, Roche AF, Khamis HJ, Jackson AS, Pollock ML and Siervogel RM (1996): Relationships between the body mass index and body composition. Obes Res; 4:35–44. Whitney E, DeBruyne LK, Pinna K and Rolfes SR (2007): Nutrition for Health and Healthcare; 3rd ed. Thompson Wadsworth, Belmore, California, USA. Wildman REC and Miller BS (2004): Sports and Fitness Nutrition. Australia: Wadsworth Inc. Willett WC (1990): Nutritional epidemiology. Oxford, United Kingdom: Oxford University Press. Williams BM (2008): Association of Breakfast Consumption Patterns with Weight Status, Nutrient Intake, and Dietary Adequacy in African American Children 1-12 Years of Age and Adolescents 13-18 Years of Age. Human Ecology-LSU-masters -11-04 World Health Organization (WHO) (1987): Measuring Obesity Classification and Description of Anthropometric Data. Report on WHO consultation on the Epidemiology of Obesity, Warsaw; pp: 21- 23. World Health Organization (WHO) (1995): Physical status: the use and interpretation of anthropometry: report of a WHO Expert Committee. Geneva. World Health Organization; WHO Technical Report Series 854. World Health Organization (WHO) (1997). International Obesity Task Force. Managing the global epidemic of obesity. Report of the WHO Consultation on Obesity, Geneva, June 5-7, 1997. World Health Organization: Geneva. World Health Organization (WHO) (1998): Global prevalence and secular trends in obesity. In: Obesity preventing and Managing the Global Epidemic, Report of a WHO Consultation on Obesity. Geneva: WHO; p. 17 World Health Organization (WHO) (2000): Obesity: preventing and managing the global epidemic: report of a WHO consultation. World Health Organ Tech Rep Ser; 894: 1–253. 87

World Health Organization (WHO) (2002): Diet, nutrition, and the prevention of chronic diseases. Report of a WHO Study Group. Geneva, World Health Organization; WHO Technical Report Series 916. World Health Organization (WHO) (2002): Reducing risks, promoting healthy life. Geneva, World Health Report. World Health Organization (WHO) (2003): Diet, nutrition and the prevention of chronic diseases. Report of a Joint FAO/WHO Expert Consultation. Geneva, World Health Organization; (WHO Technical Report Series, No. 916). World Health Organization (WHO) (2004): ―Obesity and overweight‖. World Health Organization (WHO); Geneva, Austria. Yahia N, Achkar A, Abdallas A and Rizk S (2008): Eating habits and obesity among Lebanese university student. Nutr J 2008, 7:32. Yang RJ, Wang EK, Hsieh YS and Chen MY (2006): Irregular breakfast eating and health status among adolescents in Taiwan. BMC Public Health; 6: 295. Yao M and Roberts SB (2001): Dietary energy density and weight regulation. Nutr Rev; 59:247–58 York DA, Rossner S, Caterson I, Chen CM, James WPT, Kumanyika S, Martorell R and Vorster HH (2004): Obesity, a worldwide epidemic related to heart disease and stroke: Group 1 - worldwide demographics of obesity. American Heart Association, Inc; vol. 110, pp. 463-470. Yunsheng M, Bertone ER, Stanek EJ, Reed GW, Hebert JR, Cohen NL, Merriam PA and Ockene IS (2003): Association between eating patterns and obesity in free-living US adult population. Am J Epidemiol; 158:85-92. Zabut BM (2005): Energy requirements, prediction of body fat and weight status analysis of nursing students in Gaza Strip. Pakistan journal of nutrition 4(4): 202-207, ISSN 16805194.

88

Zabut BM. and Habiby MI (2007): Energy consumption and energy yielding nutrients among nursing students in Gaza strip. Al-Najah J., Nablus, West Bank. Zafar S, ul Haque I, Butt AR, Mirza HG, Shafiq F, ur Rehman A and Ullah Ch N (2007): Relationship of body mass index and waist to hip ration measurements with hypertension in young adult medical students. Pakistan Journal of Medical Sciences, 23, pp. 1-9. Zemel MB (2002): Regulation of adiposity and obesity risk by dietary calcium: mechanisms and implications.J Am Coll Nutr21:146S –151S. Zemel MB and Gottlieb B (2004): The calcium key. Hoboken (NJ): John Wiley and Sons, Inc. Zemel MB and Miller SL (2004): Dietary calcium and dairy modulation of adiposity and obesity risk. Nutr Rev; 62:125-131. Zemel MB, Thompson W and Milstead A (2004): Dietary calcium and dairy products accelerate weight and fat loss during energy restriction in obese adults. Obes Res. Zemel MB, Shi H, Greer B, Dirienzo D and Zemel PC (2000): Regulation of adiposity by dietary calcium.FASEB J14:1132 –1138. Zino S, Skeaff M, Williams S and Mann J (1997): Randomized controlled trial of effect of fruit and vegetable consumption on plasma concentrations of lipids and antioxidants. BMJ; 314:1787-1791.

89

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

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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 الصيد...

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