food database

7/31/2019 Food Database

1/118

A Food Composition Database for

Bangladesh with Special reference to

Selected Ethnic Foods

Final Report PR #11/08

By

Sheikh Nazrul Islam, Principal Investigator

Md. Nazrul Islam Khan, Co-Investigator

M. Akhtaruzzaman, Co-Investigator

Institute of Nutrition and Food Science

University of Dhaka

November 2010

This study was carried out with the support of the

National Food Policy Capacity Strengthening Programme


2/118

1

This study was financed under the Research Grants Scheme (RGS) of the National Food

Policy Capacity Strengthening Programme (NFPCSP). The purpose of the RGS was to

assist in improving research and dialogue within civil society so as to inform and enrich

the implementation of the National Food Policy. The NFPCSP is being implemented by

the Food and Agriculture Organization of the United Nations (FAO) and the Food

Planning and Monitoring Unit (FPMU), Ministry of Food and Disaster Management with

the financial support of EU and USAID.

The designation and presentation of material in this publication do not imply the

expression of any opinion whatsoever on the part of FAO nor of the NFPCSP,

Government of Bangladesh, EU or USAID and reflects the sole opinions and views of the

authors who are fully responsible for the contents, findings and recommendations of this

report.


3/118

2

Executive Summary

A food composition database (FCD) provides essential information on the nutritive value

of foods for which updated data is available. FCD is required for formulating diets,

calculating the nutritive value of diets, quantitatively assessing diets for individuals or

different population groups and for diet therapy and management. FCD can also be used

as a guideline for food analysis in estimating nutrient levels of foods prior to actual

analysis. This is particularly useful in nutrition labeling. On the whole FCD provides the

basis for planning food, nutrition and health related policy tools. Bangladesh is in the

process of revisiting the existing FCD, with the purpose of updating and analyzing the

nutrient composition of general and ethnic foods. Presently, the nutrient values of many

of the foods have been obtained from food composition tables prepared by the Institute of

Nutrition and Food Science (INFS), University of Dhaka and Helen Keller International

(1988), wherein most of the nutrient data is based on the analysis that was car long ago,

and some that was drawn from the FCD of neighbouring countries, notably India. In the

ensuing decades, major changes have occurred in the nature and complexity of the food

chain as also in the environment, soil composition, cropping patterns and intensity. Little

is known about the nutrient composition of most of the new high yielding varieties of rice,

wheat, maize, potatoe s, fruits, vegetables, fish and livestock that have become part of

the nations production and consumption systems. Also, the nutrient composition of the

indigenous foods grown and consumed in the Chittagong Hill Tracts (CHT) and other

tribal areas is not known. To prepare dietary guidelines and determine standard dietary

intake, the true nutrient content of these foods needs to be known.

The present study has been undertaken to prepare a FCD with special reference to

general and ethnic foods. The study was designed to (i) conduct a comprehensive food

consumption survey (CFCS) among general and ethnic populations to identify the key

food items and (ii) carry out analysis for nutrient values of key food items. The survey

was conducted on a randomly selected sample of 2015 households covering 1210

general and 805 ethnic households. A total of 75 general and ethnic foods have been

selected for analysis of 22 nutrients and calorie. Validated standard and AOAC methods

have been employed for analysis of the nutrients in the selected 75 key foods. The


4/118

3

nutrient profiling comprised proximate principles such as protein, fat, carbohydrate,

dietary fiber, phytate, selected micronutrients and related compounds such as total

carotenoids, -carotene, vitamin C and minerals. Nutrient data obtained have been

compared with reported values published in different articles and books, most of whichare consistent with the reported value. The data has been compared with the FCT and

the Thai FCT. This food composition database would serve as an important primary

source for updating FCT in Bangladesh which is an essential tool in food policy planning

and program.

Keywords: Food Composition Database, General food, Ethnic food, Bangladesh


5/118

4

Contents

Executive summary 2

Chapers 4

Tables6

Figures 7

Abbreviations 8

Chapter 1 Introduction

1 Introduction 10

1.1 Background 10

1.2 Rationale of the study 11

1.3 Objectives and approach 14

Chapter 2 Materials and Methods

2 Materials and methods 16

2.1 Identification of key food items through CFCS 16

2.1.1 Comprehensive Food Consumption Survey (CFCS) 17

2.1.1.1 Sample size determination 18

2.1.1.2 Selection of general households 19

2.1.1.3 Selection of ethnic household 21

2.1.1.4 Questionnaire design, enumerator training and pre-testing 25

2.1.1.5 Comprehensive food consumption survey 26

2.1.1.5.1 Data collection, management and analysis 26

2.1.2 Focus group discussions (FGD) 27

2.1.3 Lifestyle characteristics of the general and ethnic population 28

2.1.4 Selection of key food items 28

2.2 Analysis of nutrients in key foods 35

2.2.1 Food sampling protocol 35

2.2.1.1 General food sampling protocol 37

2.2.1.2 Ethnic food sampling 39

2.2.2 Procedure for food sample collection 40

2.2.3 Identification of collected food samples 40

2.2.4 Sample preparation for analysis 41

2.2.5 Chemicals 43

2.2.6 Methods of nutrient analysis 43

2.2.6.1 Analysis of moisture 45

2.2.6.2 Estimation of protein 45


6/118

5

2.2.6.3 Estimation of total fat and fatty acids 45

2.2.6.4 Estimation of ash content 45

2.2.6.5 Analysis of crude fibre and dietary fibre 46

2.2.6.6 Analysis of phytic acid 46

2.2.6.7 Calculation of carbohydrate and energy 47

2.2.6.8 Analysis of vitamin C 47

2.2.6.9 Analysis of carotenoids 47

2.2.6.10 Analysis of-carotene 48

2.2.6.11 Analysis of mineral profile 48

2.2.7 Quality assurance programme (QAP) 48

Chapter 3 Results and Discussion

3 Results and Discussion 50

3.1 Key food identification 51

3.1.1 Comprehensive Food Survey (CFCS)51

3.1.2 Focus group discussions (FGDs) 60

3.1.3 Lifestyle characteristics of general and ethnic people 66

3.1.4 Identification of key foods 74

3.1.5 Selection of key food 76

3.2 Collection of food sample 82

3.3 Nutrient composition of key foods 85

3.3.1 Proximate Nutrients 86

3.3.2 Water in key Foods 87

3.3.3 Dietary fiber 87

3.3.4 -Phytate content 87

3.3.5 Vitamins and Minerals in key Foods 88

Key Findings 103

Policy Implications and Recommendations 105

Policy Recommendations 107

Future Research 109

Conclusion 109

Acknowledgements 110

References 112

Research team 116


7/118

6

Tables page

Table 2.1 Ethnic household selection representing 70% of ethnic population 22

Table 2.2 Focus group discussions 28

Table 2.3 Food items consumed by only general people (percent frequency 5%) 31

Table 2.4 Food items consumed by only ethnic households (percent frequency 5%) 32Table 2.5 Food items commonly consumed by both General and Ethnic people

(Percent frequency 5% households)

33

Table 2.6 Ethnic food items listed from ethnic CFCS and FGDs 34

Table 2.7. Nutrients analysed and the analytical techniques employed 44

Table 3.1 Location and descriptive of CFCS the data collection among the native

local/Indigenous population

54

Table 3.2 Location and descriptionof CFCS data collection among the ethnic population 55

Table 3.3 FGDs settings 60

Table 3.4 FGD outcome: Food consumption pattern of the Marma, Chakma, Tanchangaand

Tripura communities

61

Table 3.5 Socioeconomic profile of general households 68

Table 3.6 Food security by households type in general population 69

Table 3.7 Morbidity and its treatment by household type in general population 70

Table 3.8 Socioeconomic profile of ethnic households 71

Table 3.9 Food security of ethnic tribes 72

Table 3.10 Morbidity and its treatment by ethnic tribes 73

Table 3.11 Key food list consumed by both the native general and *ethnic people 78

Table 3.12 Exclusive ethnic food list 79

Table 3.13 Proximate nutrient composition of cereals and leafy vegetables 90Table 3.14 Vitamin C, carotenoids and micromineral composition of cereals and leafy

vegetables

91

Table 3.15 Macromineral composition of cereals and leafy vegetables 92

Table 3.16 Proximate composition of roots & tuber, non-leafy vegetables and fruits 93

Table 3.17 Vitamin C, carotenoids and micromineral composition of roots & tuber, non-leafy vegetables

94

Table 3.18 Macromineral composition of of roots & tuber, non-leafy vegetables 95

Table 3.19 Proximate composition of fish, egg and meat 96

Table 3.20 Micromineral composition of fish, egg and meat 97

Table 3.21 Macromineral composition of fish, egg and meat 98Table 3.22 -carotene content in general and ethnic foods 99

Table 3.23 Dietary fiber in key food items 100

Table 3.24 Phytic acid content in key food items 101

Table 3.25 Comparision of protein value in the present FCD with IFCT, DKPM, Thai

FCT

102


8/118

7

Figures page

Figure 2.1 Sampling plan of general households 20

Figure 2.2 Sampling plan for ethnic households 23

Figure 2.3 Geographical locations of ethnic CFCS 24

Figure 2.4 Multi-regions sampling plan for general food sample 38

Figure 2.5 Multi-regions sampling plan for ethnic food 39

CFCS activities 52

Figure 3.1 Distribution of general and ethnic households 56

Figure 3.2 Distribution of selected general households by division and household type 57

Figure 3.3 Distribution of ethnic households by districts 58

Figure 3.4 Distribution of ethnic households by tribes 59

FGDs activities 62

Figure 3.5 Number of food itemconsumed by population type 74

Figure 3.6: Distribution of common food item consumed by 5% HH 75

Figure 3.7 Distribution of ethnic food of food items consumed by 5% HH 75

Figure 3.8 Distribution of general food items consumed by 5% HH 75

General key foods 80

Ethnic key food 81

Ethnic food collection activities 82


9/118

8

Abbreviations

AOAC Association of Official Analytical Chemists

CFCS Comprehensive Food Consumption Survey

CHT Chittagong Hill Tracts

CV Co-efficient of Variance

DAE Department of Agricultural Extension

DKPM

EP

Dhesio Khadder Pustiman

Edible Portion

EU European Union

ES External StandardFAO Food and Agriculture Organization of the United Nations

FCDB Food Composition Database

FCT Food Composition Tables

FGDs Focus group discussions

HKI Helen Keller International

HYV High Yielding Varieties

IFCT Indian Food Composition Tables

INFS Institute of Nutrition and Food Science

IS Internal Standard

NFCD National Food Composition Database

SRM Standard Reference material

SEM Standard Error of Mean

TAT Technical Advisory Team

TDF Total Dietary Fiber

USAID United States Agency for International Development


10/118

9

Chapter 1

Introduction


11/118

10

1 Introduction

A food composition database (FCDB) provides detailed information on the nutrient

composition of foods. FCDBs provide values for energy and nutrients (e.g. protein,

vitamins and minerals) and other important food components or bioactive compoundsthat are important for human nutrition. This includes the nutrient profile of key foods

commonly taken by the population. The key food list comprises the local staples,

cereals, fish, meat, vegetables, fruits, milk and others. The nutritive values are either

based on chemical analysis which are carried out in analytical laboratories or are

estimated from other appropriate data. The earliest known food composition table

was produced in 1818 (Somogyi, 1974). The current knowledge of nutrition is still

incomplete, and studies are still required, often at ever increasing level of

sophistication, into the composition of foods and the role of these components and

their interactions in health diseases (Greenfield and Southgate, 2003a). Food

composition database will serve to address the basic need for nutrient information,

public health problems in the country, the current knowledge in nutrition, and for food

safety and toxicity.

1.1 Background

Food is one of the essential components for human survival. Good health needs a

balanced diet. In order to achieve this, the nutrient composition of most frequently

consumed foods has to be made well-known and available to the mass population.

Food composition database is of great importance in health and nutrition. It is used in

research studies dealing with the effects of diets on health, reproduction and

development. There is a significant relationship between diet and health and

diseases. Lack of proper dietary habits contributes to the development of many

diseases. In this regard, there is a worldwide call for updating or establishing the

Food Composition Database. Many countries, particularly in the developing world,

lack the resources needed for setting up a national food composition programme.


12/118

11

Some countries are collaborating on food composition analyses among the

institutions in their own country and in the region. Accordingly Bangladesh has

undertaken steps in generating its own FCD.

Bangladesh is an agriculture based country. Agriculture produces around 90% of its

food need including cereals and vegetables (FAO/WFP CFSAM 2008; WFP, 2010). It

has been blessed with high yielding varieties (HYV) of rice, and plenty of vegetables

and fruits. There are 141 varieties of leafy vegetables (commonly known as shak)

and 25 varieties of non-leafy vegetables in Bangladesh (Maksuda, 2010). Among the

leafy vegetables, 97 items are identified as ethnic varieties, and the rest are

consumed by both the general and ethnic people. A good number of shaksgrow asweeds or during cultivation of other crops. Many of the poor and landless people

depend on these indigenous foods (SANFEC, 2005). Several the indigenous fruits

and vegetables are known to be nutritionally rich with vitamins and minerals. The

biologically rich open water bodies include 260-500 species of inland fish, and some

seventy five of these species are regularly consumed by poor communities (Minkin et

al, 1997; Rahman and Minkin, 2003; Rahman, 2005; FAO/CINE, 2009 ). The nutrient

content of these foods should be incorporated into the food composition table as a

valuable source of information on nutrition and food diversity. The nutritive values of

these abundantly produced foods as well as the ethnic foods needs to be analyzed

and incorporated in the Food Composition Database.

1.2 Rationale of the study

The national food intake pattern in Bangladesh is dominated by cereals contributing

up to 74-76% of total dietary energy as against the internationally accepted value 54-

55% for developing countries (WHO/FAO, 2003; WHO/FAO, 2004; Murshid et al.,

2008; Yusuf et al, 2009). Vegetables comprise one-fifth of total diet for rural people.

Protein and micronutrient rich foods account for less than 10 percent of the rural


13/118

12

persons diet. Intake of vegetables and fruits has increased considerably. It is still

very low, although their consumption is vital for a diversified and nutritious diet (BBS,

2007). The high intake of cereal based food and low intake of micronutrient rich foods

results in an unmbalanced diet and causes different health disorders. Diets rich in

vegetables and fruits contribute to micronutrients that have specific antioxidant

functions and many of which reduce the risk of many health disorders including

cardiovascular complications, diabetes related damage, cancers (Connealy, 2008;

Liu, 2003; Kaur and Kapoor, 2001), even HIV infection (Oguntibeju, 2009; Baeten et al,

2001). Additionally they provide phytochemicals that have marked health significance.

Therefore, it is important to identify the food sources of various nutrients that are

required for the maintenance of good health.

Over the last decade, food composition activities have increasingly been undertaken

by several agencies and programmes for its ever growing importance. Many national,

regional and international organizations recognize its significance. The food

composition data are used primarily for the planning, assessment and establishment

of human energy and nutrient requirements and intakes. Its importance is versatile.

It is required for nutrition planning and in agriculture, health and nutrition assessment;

formulation of national; institutional and therapeutic diets; nutrition education and

training; formulation of food based dietary guidelines; research on nutrition,

agriculture and epidemiology; product development; nutrition labeling; setting food

standards and establishing food safety regulations.

Until now, data on nutrient values have been obtained from food composition tables

(FCT) prepared for Bangladesh by the Institute of Nutrition and Food Science,

University of Dhaka (INFS, DU, 1986) and Helen Keller International (HKI, 1988).

Most of the nutrient data in these FCT were analyzed long ago with uch of the data

borrowed from neighboring countries. Moreover, the nutrient composition of ethnic

foods is not available in the Bangladesh food composition table. With the increasing


14/118

13

concern of the relationships between diet, food habits and degenerative lifestyle

diseases, there is increased interest in food composition data. At the same time,

there is a call for attention to the major limitations in the available data and to support

a variety of research activities in this area (Greenfield and Southgate, 2003a),

particularly in food security mapping. This would help to bridge the lack of

information on the nutrient and non-nutrient content of different foodstuffs consumed

by different populations and subgroups including ethnic populations.

Further, changes in the food chain due to emergence of high yielding varieties (HYV)

newer foods and changes in soil composition (due to environmental changes,

increased use of fertilizers and crop intensity) have resulted in possible changes inthe composition of nutrient in the foods now being grown. The food chain of the

country has been modified during the last decades. Nutritive values of these local

food items need to be analyzed and incorporated in the food composition database.

All these facts call for a renewed look and analysis of the most frequently consumed

foods.

It is time to prepare a Food Composition Database with nutrient data through

analysis of general, ethnic and relatively newer foods. Such a Food Composition

Database will help in formulating dietary guidelines for different people to meet their

nutrient requirements. This is also in line with one of the key areas of intervention of

the National Food Policy Plan of Action (2008-2015).


15/118

14

1.3 Objectives and approach

Considering the importance of having a National Nutrient Database, this study aimed

to prepare a Food Composition Database with reference to general and ethnic

foods. To this end, the study was designed to:

identify the most frequently consumed foods of the general and ethnic

people of Bangladesh through a comprehensive food consumption

survey(CFCS);

prepare a key foods list that contributes 75% of any one nutrient need

(key food list);

analyse macronutrients, micronutrients, and anti-nutrients in the selected

key foods (nutrient value of food);

develop a comprehensive National Food Composition Database (NFCD)

with the analytical results obtained; and

provide recommendations for food policy planning and program.


16/118

15

Chapter 3

Materials and Methods


17/118


18/118

17

that some food source as those consumed by specific population contribute

substantially to the nutrient of their diets. Therefore, alternative methods of collecting

information, such as small localized surveys and interviews were carried out.

Key food items were indentified through a Comprehensive Food Consumption

Survey (CFCS) among the general and ethnic population of Bangladesh.

General and Ethnic Foods

In this study, general foodsare referred to those foods which are consumed by local

general people (Rahman et al, 2001; Rashid et al, 2007) who constitute the majority

of the Bangladeshi population. Ethnic foodsare those foods which are consumed by

ethnic tribal people who are the inhabitants of the Chittagong Hill Tracts (CHT) region

and other specific locations in Bangladesh.

The majority of the foods that have been analysed for the nutrient content are

commonly consumed by both the general and ethnic people of Bangladesh. Some

foods which are uncommon in the food consumption list have also been included for

analysis of their nutrient profile.

2.1.1 Comprehensive Food Consumption Survey (CFCS)

Food consumption surveys form the basis for food intake surveys or dietary surveys.

The aim of the CFCS was to collect food consumption data of the general and ethnic

population that included the types and amounts of food intake, frequency of intake

and dietary practices. CFCS was also conducted to prepare a comprehensive

database that would be useful for food safety risk assessmen. It would also provide a

valuable resource for health protection and public health policy planning.

In this study, the comprehensive food consumption survey (CFCS) was conducted to

collect data on the diversity of food items that are most frequently consumed by

general and ethnic people in Bangladesh. The aim of this survey was to obtain a key


19/118

18

food list that includes the most frequently and commonly consumed foods by both

groups of population. In addition, the CFCS also collected information on the lifestyle,

socioeconomic information, food security and health related knowledge of the

general and ethnic people.

The CFCS was conducted among a cross-sectional population of adults and older

groups of population of general and ethnic origins (Kuhnlein et al, 2006). A pretested

questionnaire was used to conduct the survey. Pretesting was performed by trained

enumerators in cluster mapping locations.

2.1.1.1 Sample size determination

In the study, households were taken as the sampling unit. This is based on the

principle that in most cases, food is first purchased in the household and then

consumed by the members of the household. To determine the sample size required

the following statistical formula was used:

n = {Z2P(1-P)}/ d2 where,

n = Minimum sample size

P = Expected proportion of the household consuming the diversified food items

Z = Standard error corresponding to a given confidence level

d = Precision of the estimate which is considered to be 0.05 at 95% confidence level.

Considering the prevalence of diversity in food consumption by the households and

by the individuals at 0.15% and the standard scores of the estimate at 95%

confidence level with precision of 0.05, the above equation gave a value of sample

size of 196 households equivalent to 200 households as minimum sample size fromeach of the six divisions of Bangladesh. Thus, it comprised a total of 1200 general

households. It was selected to get the percentage of households consuming the

specific food items throughout the year by the general population in Bangladesh.


20/118

19

2.1.1.2 Selection of general households

In selecting the 1200 general representative households, a three stage sampling

technique was used.

Bangladesh, administratively, is divided into six divisions. In selecting the 1200households, 200 households were selected from each of the six divisions in the first

stage. To select the 200 households from each division in the second stage, two

districts were randomly selected from each of the six divisions and then 100

households were selected from each of the selected 12 districts. Finally in the third

stage, 50 households from urban setting (district city) and 50 households from

multiple rural settings under the same district were randomly selected. The

household sampling plan is presented in the following diagram.


21/118

20

Figure 2.1: Sampling plan of general households

Chittagong

HH # 200

Rajshahi

HH # 200

D1

Dhaka

HH # 200

Khulna

HH # 200

Sylhet

HH # 200

D1 D2 D1 D2D2 D2 D1 D2D1

BangladeshHH # 1200

R U R U R U R U R U R U R U R U R U R


22/118


23/118

22

was, therefore, conducted on another 300 ethnic households in Khagrachari and

Rangamati districts of CHT. It was undertaken among Marma, Chakma, Tripura and

Tangchagaethnic community during March and April, 2010. Thus the CFCS on ethnic

households was carried out on a total of 805 households. The selection criteria

employed to recruit the ethnic households are described in table 2.1 and figure 2.2 and

2.3.

Table 2.1: Ethnic household selection representing 70% of ethnic population

Tribe name No. of household in

respective tribe

PPS-Households in

respective tribe

Projected PPS-

Households in

respective tribe

Targeted

Households

selected in the

study

Chakma 44730 108 136 238

Marma 29137 71 88 171

Tanchanga 4043 10 12 51

Tripura 15220 37 46 87

Bam 2681 7 8 30

Murong 4273 10 13 30

Monipuri 3559 9 11 25

Khasia 7500 19 23 25

Santal 36406 88 111 89

Garo 12867 31 39 31

Hajong 4251 10 13 28

Total households 1,64,667 (>70%) 400 500 805


24/118

23

Figure 2.2: Sampling plan for ethnic households


25/118

24

Figure 2.3: Geographical locations of ethnic CFCS

Moulavi Bazar

Mymensingh

Rajshahi

Khagrachari

Rangamati

Bandarban


26/118

25

2.1.1.4 Questionnaire design, enumerator training and pre-testing

Questionnaire design:The major components included in the questionnaire were- types

of food consumed by the households throughout the year, socioeconomic profile, family

food security, nutritional knowledge, knowledge on nutritional deficiency diseases etc of

the projected households. This stand that whole process of collecting information on

food items commonly consumed by the household throughout the year, socioeconomic

condition and other lifestyle factors related to questionnaire. It was conducted through

direct interview to the households respondent during the survey. A semi precode

formatted questionnaire was used as the basic data collection tool to get the household

information. Considering the importance of the study in the national context and its

objectives, information on the variable collected were meticulously included in the

questionnaire, discussed with the Technical Advisory Team (TAT) members and

carefully examined so that all the relevant information were taken and recorded during

the comprehensive consumption survey.

The questionnaire was designed in the light of experience achieved from the National

Nutrition Survey and various other large scale surveys conducted in Bangladesh

focusing on the required variables to answer the objectives as well as purpose of the

study. The questionnaire was field tested prior to actual use and was modified on the

basis of the feed-back received from the field tests.

The questionnaire and selection of survey site were finalized and approved in

consultation with Technical Advisory Team (TAT) members of this Programme.

Enumerator recruitment and training: A team consisting of four enumerators with one

supervisor were recruited and trained to conduct the field survey. All the enumerators

recruited were university graduates and postgraduates. In the five members team, two

enumerators belonged to general community and three were ethnic who were fluent in

speaking and understanding the general peoples language as well as the tribal peoples

language. More ethnic members were recruited because they were familiar with the


27/118

26

difficulties in tribal locations where the ethnic people are mostly concentrated as well as

to facilitate the data collection within the stipulated time. Initially, all field staffs received 7

days orientation training consisting of familiarization of the questionnaire through guided

readings and field trials.

Pretesting questionnaire: The enumerator team spent a considerable time in the office

and at the field-testing sites in practicing the techniques of recording types of food

consumed by the household throughout the year and the other related variables included

in the questionnaire as well as the related data collection activity. Fifty households

comprising general and ethnic people were interviewed in pretesting the questionnaire.

2.1.1.5 Comprehensive food consumption survey

To identify the most common food items consumed by the general and ethnic people,

2015 households was selected comprising 1210 general and 805 ethnic households that

were interviewed with a precoded and pretested questionnaire. Though there is

disproportionate distribution of general population in rural and urban locations, in order

to obtain the maximum diversity in consumption of different food items, an equal number

of households were selected from both the urban and rural locations. Further, to get the

factual data on food consumption in the rural and urban population, a weighted food

frequency was calculated giving the actual weighted representation of the rural urban

population proportion in the country.

2.1.1.5.1 Data collection, management and analysis

Data collection: Data were collected from the selected locations and households

through home visits during the period January to May 2009 and during April to May,

2010. To get the information related to food purchase, consumption and other variables,

the household head (male) and the spouse were interviewed. Every day, the collected

information/data was checked, coded and cross checked by the interviewers and finally


28/118

27

by the supervisor at the field sites in order to avoid any misreporting. Any confusion

arising out of this matter was settled on the following day during subsequent home visits.

This process of scrutinizing the data was performed during the entire period of CFCS.

Data management and analysis: The questionnaire was edited and entered into

SPSS program. Data entry was done by the computer data entry personnel of INFS, DU

and this was followed by an extensive period of logical checking to identify any error in

data entry, which were then corrected by consulting the original questionnaires.

2.1.2 Focus group discussions (FGDs)

The focus group is a type of group interview (http://www.extension.iastate.edu/publications/

pm1969b.pdf). It provides qualitative approaches to research aiming to obtain in-depth

information on concepts, perceptions and ideas of a group on certain specific topic in

short time at relatively low cost. The FGD supplements the survey data. In case of

health and nutrition, it is primarily done to get information regarding the lifestyle, food

consumption, food security, health and nutrition knowledge of a community. The

activities of conducting a focus group include- identification of the objectives of the focus

group discussions, preparation of questions, selection of participants, selection of

location and facilitator, note-taker and planning of session. It produces high quality data

if it is employed for the right purposes using the right procedures.

The FGD comprises a group of approximately 6-12 participants with key informants such

as community leaders and a critique, and the discussion may last for one hour to one

and half hour (IDRC, http://www.idrc.ca/en/ev-56615-201-1-DO_TOPIC.html). It is an important tool for

acquiring feedback regarding the topic, and it facilitates the enumerators to talk to the

people in a more natural setting than a one-to-one interview. In presence of the critique,

the participants and key informants are directly asked about their perceptions, opinions,

beliefs and attitudes towards a particular topic. Their responses are discussed, criticized

and recorded.


29/118

28

It has a high apparent validity - since it is easy to understand, and the results are

believable. FGD is relatively easy to assemble, good for getting rich data in participants'

own words and developing deeper insights, good for obtaining data from children and/or

people with low levels of literacy, identifying factual errors or extreme views. Its

limitations are -the responses of each participant are not independent, a few dominant

focus group members can skew the session. Focus groups require a skilled and

experienced moderator and the data analysis requires expertise and experience.

In the present study, FGD was conducted among the ethnic communities of Marma,

Chakma, Tripura and Tangchagaliving in Khagrachari and Rangamati during March and

April, 2010 (table 2.2). It was carried out to obtain information on their food consumption

pattern.

Table 2.2: Focus group discussions

Division District Upazilla Time of visit Location Type of HHs

Chittagong

Khagrachari Khagracharisadar

31/03/2010 Marma palli Marma

Rangamati Rangamatisadar

03/04/2010 Chakma palli Chakma

Rangamati Rangamatisadar 08/04/2010 Tanchangapara, TanchangaKhagrachari Khagrachari

sadar21/04/2010 Tripura para Tripura

2.1.3 Lifestyle characteristics of the general and ethnic population

Although the primary aim of the CFCS was to obtain the information on the food

consumption pattern of the general and ethnic people, information on their lifestyle such

as socioeconomic profile, food security and morbidity and care taken for it were also

collected, analysed and addressed.

2.1.4 Selection of key food items

It is documented that the key foods contribute up to 80 percent of any nutrient, but the

total nutrient contribution of key foods in a diet accounts for approximately 90 percent of


30/118

29

the nutrient contents of the diet. In selecting the key foods, priority was given to those

foods that contribute primarily to the energy anf key nutrients of the diet. In addition,

considerations were given to- the basic need for nutrient composition, public health

problems in the country, current knowledge on nutrition and toxicity, availability of

existing data, existence of adequate analytical methods, and feasibility of analytical

works. Special focuswas given to the distribution of nutrients in foods with emphasis on

-carotene, vitamin C, calcium and iron content. Importance of food trading was also

considered in making the key food list (Greenfield and Southgate, 2003e).

Analysis of CFCS data indicated that food items consumed by the 5% households

included a list of 120 foods comprising 20 foods consumed only by the general people

(table 2.2), 46 foods consumed only by ethnic people (table 2.3) and 54 common food

items consumed by both the general and ethnic population (table 2.4).

The study undertook preparation of a database with nutrient composition of 50 key food

items. In preparation of the list of 50 food items out of 120 items, the following criteria

were used:

food items that were consumed by15% of the households were included in thekey food list.

some of the ethnic foods were excluded though consumed by >15% households

of the ethnic population on the basis that these are being consumed by a very

minor group of population. The above exclusion criteria condensed the food list

to 70 food items.

further to make the list to 50 items, the foods containing poor micronutrients (less

or no-carotene) were excluded.

thus the key food list included 50 food items.

The 50 key food items were initially selected in consultation with Technical Assistance

Team (TAT) members. Later in compliance with the recommendation made by some

ethnic participants at Rangamati workshop for inclusion of more ethnic tribal foods, a


31/118

30

critical review and discussion were made with TAT members, and it was decided to

survey on additional 300 ethnic households to include an adequate number of ethnic

foods for nutrient analysis.

Inclusion of additional ethnic foods made the key food list of 75 food items. This revised

key food list comprised 53 general food items (most of which are consumed by ethnic

people) and 22 ethnic foods.


32/118

31

Table 2.3: Food items consumed by only general people (percent frequency 5%)

Sl no English name Bengali name Scientific name Urban Rural weighted% frequency

Leafy vegetables

1 Spleen Amaranth Data shak Amaranthus dubius 14

2 Jute Pat shak Corchorus capsularis 11

3 Swamp Morning-glory Kalmi shak Ipomoea aquatica 174 Coco-yam Sobuj kochu shak Colocasia esculenta 5

Non-Leafy vegetables

5 Spleen Amaranth Data Amaranthus dubius 13

6 Bean Broad Makhon shim Canavalia gladiata 5

7 Drumstick Shajna data Moringa olefera 7

Fruits

8 Apple Apel Pyrus malus 7

9 Bullocks Heart Atafol Annona reticulata 5

10 Water melon Tormuz Citrullus vulgaricus 22

Fish and Meat

11 Sunfish Mola mach Mola mola 14

12 Taki fish Taki mach Channa puncpatus 10

13 Bailla Bele mach Awaous guamensis 17

14 Ganges River Gizzard Shad Chapila mach Gonialosa manmina 6

15 Zig-zag eel/Tire track eel Baim mach Mastacembelus armatus 5

16 Hilsha Fish Ilish mach Tenualosa ilisha 7

17 Chingri mach Shrimp Macrobrachium rosenberghii 29

18 Striped dwarf catfish Tengra Fish (Taja) Mystus vittatus 23

19 Beef Garor mangsha Beef cattle 26

20 Chicken egg (farm) Murgir dim (farm) Gallus bankiva murghi 45


33/118

32

Table 2.4: Food items consumed by only ethnic households (percent frequency 5%)

Sl. no English name Bengali/Localname

Scientific name Urban Rural weighted% frequency native

general people

% frequency ofEthnic people food

consumption

CEREALS1 Rice parboiled (Brri-29) Sidhoy chal Oryza sativa 99 342 Lentil (deshi) Masur dal Lens culinaris 78 35

LEAFY VEGETABLES3 Josephs Coat Lalshak Amaranthus gangeticus 84 494 Bottle Gourd Lau shak Lagenaria siceraria 47 425 Indian spinach Pui shak Basella alba 64 286 Radish Mula shak Raphanus sativus7 Spinach Palong sag Spinacea oleracea 41 178 Coco-yam Sobuj kochu shak Colocasia esculenta 18 179 Bathua Pigweed Chenopodium album 13 7

ROOTS & TUBERS10 Potato Gol Alu Solanum tuberosum 93 9311 Radish Mula Raphanus sativus 44 4012 Coco-yam Sobuj kochu Colocasia esculenta 33 37

NON-LEAFY VEGETABLES

13 Egg plant Begun Solanum melongena 81 8014 Bean Shim Dolichos lablab 70 75

15 Cabbage Badha KopiBrassica oleracea var. capitata

80 5816 Cauliflower Foolkopi Brassica oleraceavar. botrytis 90 7417 Cow pea Borboti Vigna catjang 38 818 Cucumber Shasha Cucumis sativus 20 2119 Folwal Potol Trichosanthes dioica 49 1620 Gourd (Ash) Chal kumra Benincasa cerifera 31 2121 Bitter Gourd Karola Momordica charantia 43 4222 Sweet pumpkin Misti kumra Cucurbita maxima 40 3923 Kakrol Kakrol Momordicacochinchinensis 20 824 Ladies finger Dherosh Abelmoschus esculentus 43 2425 Bottle gourd Lau Lagenaria siceraria 68 5626 Snake gourd Chichinga Trichosanthes anguina 53 1927 Jackfruit (immature) Kacha kathal Artocarpus heterophyllus 8 2328 Green papaya Kacha papay Carica papaya 30 2729 Plantan (green) Kacha kola Musa paradisiaca 12 18

30 Tomato (green) Kacha tomato Lycopersicon lycopersicum 21 3331 Yam Stem Kachur data/loti Colocasia esculenta 28 12

FRUITS

32 Mango ripe(deshi) Paka Am Mangifera indica 66 5633 Black berry (deshi) Kalojam Syzygium cumini 17 834 Jackfruit (ripe) Paka Kathal Artocarpus heterophyllus 60 5635 Banana (ripe) Paka kala Musa sapientum 29 1736 Bitter Plum Boroi Zizyphus mauritiana 38 3637 Pine Apple (Jaldugi) Anarash (Jaldugi) Ananas comosus 12 538 Tomato (ripe) Tomato paka Lycopersicon lycopersicum 61 52

FISH

39 Carp Katol mach Labeo rohita 21 740 Tilapia Tilapia mach Anabus testudineus 20 2541 Dragon Fish Pangash Pangasius pangasius 44 2642 Fry (very small) Choto puti Puntius ticho 56 27

43 Sunfish Mola mach Mola mola 11 944 Shrimp(dry) Chingri (shukna) Heterocarpus ensifer 7 2245 Rohu Rui Labeo ruhita 45 3546 Shrimp Chingri Heterocarpus ensifer 30 6


34/118


35/118


36/118

35

2.2. Analysis of nutrients in key foods

In generation of nutrient data for food composition database, designing and executing

sampling protocol, preparation of analytical samples and portions, selection of analytical

method, execution of analytical procedures with appropriate number of analytes and

analytical replicates, involvement of skilled lab personnel, evaluation of analytical values

and documentation of data are of utmost important (Greenfield and Southgate, 2003b).

Lapse in any of the process would result in error in the representative nutrient data. The

basic principles of producing quality data should give attention on-

the collection and preparation of food sample

the selection of the analytical method and its validation within the

laboratory carrying out the analysis of a particular food

proper execution of methods, and

review of the values obtained.

Therefore, adequate and appropriate care and precaution were taken in designing and

addressing these approaches.

2.2.1. Food sampling protocol

A sampling plan is the predetermined procedure for selection, collection, preservation,

transportation and preparation of the analytical portion to be used from a lot as samples.

A sampling plan should be a well organized document for program objectives (Proctor et

al, 2003).

Foods are biological materials and exhibit variation in composition, particularly prone to

variation in water, carbohydrate and vitamin contents. This variation is related to a

number of factors such as cultivation place (cultivated, wild, garden), geographical

location, seasons, state of maturity, cultivar and breed, etc. Therefore, collection of food

sample needs to be specific in terms of timing and frequency to reflect these variations.


37/118


38/118

37

nutrient composion in the food composition database, food items, particularly the

vegetables, fruits and fishes were collected during their peak available period.

2.2.1.1 General food sampling protocol

In this study a multi-regions sampling plan was used to collect representative food

samples. The identified and selected key food items were collected from four different

wholesale markets located at the four entry points to Dhaka city, and from two

cultivation fields (figure 2.4). Every two samples were pooled together to make a single

analyte (test sample), thus made three analytes for each food item, which were then

analyzed for their nutrient profile (figure 2.4). Sampling of general food item was started

at June 2009, particularly cereals and it was continued upto March, 2010.


39/118

38

Figure 2.4: Multi-regions sampling plan for general food sample


40/118

39

2.2.1.2 Ethnic food sampling

Ethnic food items were collected from local weekly markets at Rangamati and

Khagrachari. Three food samples for each food item were collected from each market.

Every two food samples were pooled together to make three analytes (test sample),

which were analyzed for their nutrient profile. The ethnic food sampling plan is depicted

in figure 2.5. A few ethnic foods were collected during September through December,

2009, but most of the ethnic foods were collected during April-May, 2010.

A CAnalyte-I

Rangamati

Bnorupa bazar

Sample A Sample B Sample C Sample FSample ESample D

D FAnalyte-IB E

Analyte-I

Khargrachari

Bazar

Figure 2.5: Multi-regions sampling plan for ethnic food


41/118

40

2.2.2 Procedure for food sample collection

Representative food samples were collected from the selected wholesale markets

where food items come from all over the country and from cultivation fields. Attempt was

taken to collect tender fresh sample. Collection was made in new clean plastic poly

bags. In case of field sample collection, some water was sprayed on the vegetable

samples during packing into the poly bag, and thus kept it moistened during

transportation from the field to the lab.

For collection of general food items, particularly the vegetable items, replicate samples

of approximately 2.0kg of each food was purchased from each of the four selected

wholesale markets and from the two cultivation fields. These replicate samples weremixed together to make a single sample for each collection point, and thus made six

samples for six collection sites. Two samples were then pooled to make a single analyte

and thus made three analytes for each food item.

Ethnic food samples were collected from weekly wholesale markets at Rangamati and

Khagrachari. Three samples for each food items of approximately 1.5kg were purchased

from each market. The samples were water sprayed and packed into new clean plasticpoly bags for transportation to the lab.

2.2.3 Identification of collected food samples

Nutrient profile in food composition database needs to be representative of the foods-

what the mass people consume and from where they collect it? To minimize the

compositional variations that may arised by geographical locations, timing of collection,

sample preparation; the food samples, particularly vegetables, fruits and fishes, were

collected from the wholesale markets where the foods arrive from four geographical

regions of the country. It thus ensured the representative consumable food items of all

geographical locations. Samples were collected at very early morning from the collection


42/118

41

points, taken to the lab and immediately processed for analyte preparation at adequate

required lab environment with trained and skilled lab personnel.

Rice, maize and lentil

A market survey was conducted in different wholesale and local rice markets in and

around the Dhaka City to find out the rice varieties which were consumed by the

majority of population. It was then identified and certified by an expert at the Grain

Quality and Nutrition Division, Bangladesh Rice Research Institute, Gazipur. It was the

BRRI -29 variety. The lentil deshi and maize deshi varieties were also indentified and

certified by BRRI.

Vegetables and fruits

The vegetable and fruit items were categorically identified and certified by personnel of

Department of Agricultural Extension (DAE) and the taxonomist of the Department of

Botany, Dhaka University. In case of ethnic foods, food samples were purchased from

the weekly wholesale markets with the help of local ethnic DAE staff, who confirmed its

identity. After taking the food sample to the lab, the taxonomic expert further identified it

for its scientific and English name.

Fish, meat and eggs

The identified fresh fish samples were purchased from wholesale and local markets at

Dhaka city. Meat and egg samples were also purchased from the local market. They

were then rapidly processed for estimation of moisture content. The dried samples were

used for analysis of proximate nutrients and mineral contents.

2.2.4 Sample preparation for analysis

Generation of nutrient values employs a range of analytical procedures and it requires a

number of analytical sample portions. Taking of analytical portions and size depend on

the analytical method to be used. When food samples are used for analysis of a range

of nutrients, it is convenient to store some analytical portions (at least 3 portions) at -40


43/118

42

or -70oC (Greenfield and Southgate, 2003c). Care should be taken to separate the

edible portion and inedible portion. When analytical portions are taken repetitively from

stored samples for analysis of different nutrients, it is convenient to store multiple

identical sample units in the freeze.

In this study, the properly collected food items were first rinsed with tape water followed

by washing with distilled water, then gently swabbed with tissue paper and air dried. The

cleaned air-dried sample was diced or cut into small pieces (peeled where needed)

using a cleaned stainless knife on a cleaned plastic cutting surface. Hand gloves were

used throughout the process. The diced food sample was taken to a stainless steel bowl

and mixed with a plastic spatula. Adequate precautions were taken to avoid any metalcontamination. In case of vitamin analysis, these operations were performed very fast in

dim light to avoid any degradation by oxygen and light, and for some food items,

portions of fresh process sample(s) were kept frozen. Where required, the clean air

dried sample was homogenated with a lab blender, and the required portion of the

sample analyte was taken from the homogenated material.

Vegetable and fruit analytical sampling

The vegetables and fruits were subjected to multiple nutrient analyses. Accordingly, they

were processed for analytical samplings and stored in multiple portions as

(a) 3x5g taken for carotenoid analysis, (b) 3x5g taken for vitamin C analysis, (c) 3x20g for B-

vitamins analysis, (d) 3x10g for sugar analysis (for fruits), (d) 3x10g for dietary fiber analysis, (e)

3x10g for crude fiber analysis, (f) 3x10g taken for nitrogen analysis, (g) 3x10g taken for mineral

analysis, (h) 3x25g taken for moisture analysis, and (i) remaining portion in multiple units frozen

and stored at -20oC & -40oC depending on nutrient to be analysed.

Fish, meat and egg analytical sampling

Fish:Approximately 1.0-1.5kg fish of consuming size of each variety was collected from

3 wholesale and from 3 local markets located at Dhaka and its peripheries from where


44/118

43

people purchased fish for their consumption. The fish samples were brought to lab

quickly to avoid any spoilage during transport. Ice box was used during collection of fish

from the peripheral points. Taking the sample in lab, it was cleaned and processed for

edible portion. Small fish was taken as a whole.

Meat: About 20-25 meat cuts at least 2-3 pieces from each of five regions of the

slaughted animal were purchased from butcher shop at two markets and brought in

clean plastic poly bags to the lab, where it was processed for analytical sampling.

Egg:Twelve eggs of each variety were collected from the local markets from where

mass people taken for their consumption. Each 4 eggs were pooled together to process

to make a single analyte, and thus prepared three analytes for each variety.

2.2.5 Chemicals

All chemicals and reagents used in the analysis of the nutrient profile were of analytical

grade and were purchased from Merck (Darmstadt, Germany, BDH (UK), Sigma

Chemical Co (St. Louis, MO, USA). Ascorbic acid, -carotene, and B-vitamins, were

procured from Sigma Chemical Co. (St. Louis, MO, USA).

2.2.6 Methods of nutrient analysis

Use of appropriate and accurate methods employing skilled analysts can only ensure

reliable data for preparation of a food composition database. However, the choice of

analytical methods is limited to equipment facilities and technical staffs available.

The original project proposition was aimed to analyse 50 food items for their nutrientprofile comprising proximate composition, minerals, vitamin C, total carotenoids,

carotene profile and B-vitamins. Because of the fund constraint and time limitation,

arising out of the inclusion of additional 25 food items in the analysis, the number of

nutrients to be analyzed was reduced to proximate nutrients, minerals, vitamin C and


45/118

44

carotenoid for the 75 food items. Analysis of -carotene was limited to 20 vegetables

and fruits of both general and ethnic origin. The nutrients analysed and the analytical

techniques employed are summarized in the table 2.7.

Table 2.7: Nutrients analysed and the analytical techniques employed

Nutrient class Nutrients AOAC and Standards methods

Macronutrients Moisture Drying in Air oven at 100-105oC (AOAC, 1998a)

Protein Micro-Kjeldahl method (AOAC, 1998b)

Fat Soxhlet extraction (Raghuramulu et al, 2003a)

Fatty acids By calculation (Greenfield & Southgate, 2003)

Crude fiber Gravimetric (Raghuramulu et al, 2003b)

Ash Muffle furnace (AOAC, 199c)

Dietary Fiber Sigma Kit (AOAC, 1998d; Sigma TDF-100A)

Carbohydrate By Calculation (Rand et al, 1991)

Micronutrients

Vitamin Carotenoids Spectrophotometry (Roriguez-Amaya and Kimura, 2004;

Rahman et al, 1990)

-carotene HPLC (Roriguez-Amaya and Kimura, 2004)

Vitamin C Spectrophotometry (AOAC, 1998e)

Mineral Cu, Zn, Fe, Mn, Ca,

Mg, Na, K, P

Atomic Absorption Spectrophotometry (Petersen, 2002)

Antinutrients Phytate Spectrophotometry (Wheefer and Ferral, 1971)


46/118

45

2.2.6.1 Analysis of moisture

Moisture content is one of the most variable components, particularly in the plant foods.

This variability affects the food composition as a whole. Therefore, the moisture value

remains as an essential component in food composition database.

The moisture content in the food items was determined by measuring the amount of

water removed from the food (AOAC, 1998a). It was done by direct heating the food in

an Air oven at 100-105oC to constant weight.

2.2.6.2 Estimation of protein

Protein content in the food items was determined by indirect method estimating total

nitrogen in the food. It was calculated by multiplying the total nitrogen using the

respective factor as estimated by Micro-Kjeldahl method (AOAC, 1998b).

2.2.6.3 Estimation of total fat and fatty acids

The most frequently used method for fat estimation in food is the continuous extraction

of fat with petroleum ether or diethyl ether. For some specific foods, mixture of

chloroform and methanol is also used to extract fat.

In this study, dried food was subjected to continuous extraction with petroleum ether in a

Soxhlet extractor (AOAC, 1998c). Chloroform-methanol extraction was also used in

isolation of fat in some particular food items such as meat and eggs (Raghuramulu et al,

2003).

Total fatty acid content in the foods was estimated by calculation and by multiplication of

total fat content by a factor (Greenfield and Southgate, 2003d).

2.2.6.4 Estimation of ash content

In ash estimation, dried food sample is ignited at 600oC to burn out all organic materials.

The inorganic material which is ignited at this temperature is the ash.


47/118

46

In this study, ash in the food sample was estimated by heating the dried sample in a

Muffle furnace at 600oC for 3h (AOAC, 1998d). Ash content was calculated from weight

difference.

2.2.6.5 Analysis of crude fibre and dietary fibre

Crude fibre was estimated by gravimetric method as described by Raghuramulu et al

(2003). The dried and fat free food sample was treated with boiling sulphuric acid at

constant volume, cooled, filtered, washed with hot water, made alkaline, boiled, filtered

and washed with water followed by ethanol and ether wash. The residue was then

heated in a Muffle furnace at 600oC for 3h. Crude fibre was finally calculated from the

weight difference.

Dietary fibre was analysed by AOAC method (1998d) using total dietary fibre assay kit

(TDF-100, Sigma Chemical Co., Saint Louis, Missouri, USA). In this method, a

combination of enzymatic and gravimetric techniques was used. Dried fat free sample

was gelatinized with heat stable -amylase, then enzymatically digested with protease

and amyl glycosidase to remove the protein and starch present in the food sample.

Ethanol was added to precipitate the soluble dietary fibre. The residue was filtered and

washed with ethanol and acetone. After drying, half of the residue was analysed for

protein and half for ash. Total dietary fibre was the weight of the residue minus the

weight of the protein and ash.

2.2.6.6 Analysis of phytatic acid

Phytic acid was determined by spectrophotometric method (Wheeler and Ferrat, 1971).

Phytic acid in the food sample reacting with ferric chloride developed red colour with

potassium thiocyanate. This colour difference was read in the spectrophotometer at

485nm against the water blank. Intensity of the colour is proportional to ferric ion

concentration, which was used in the calculation of phytic acid content in the food

sample.


48/118


49/118

48

2.2.6.10 Analysis of-carotene

Reverse phase HPLC (Shimadzu PC based Binary Gradient HPLC Prominence System

with PDA Detector, SPD-M20A; Solvent delivery System, LC-20AT; LC Solution Multi

Workstation Software) was used to determine the -carotene (Roriguez-Amaya and

Kimura, 2004). The nitrogen dried carotenoid was reconstituted with mobile phase

(acetonitrile: methanol: 2-propanol-) and 50l reconstituted sample was injected into the

VYDAC reverse phase C18 column (5m particle size). The column was re-equilibrated

with the mobile phase for at least five minutes before the next injection. -carotene was

purchased from Sigma Chemical Co. USA and was used as standard analytes.

2.2.6.11 Analysis of mineral profile

Mineral content in the food sample was analysed by Atomic absorption

spectrophotometric method (Petersen, 2002). Dried food sample was subjected to wet

digestion with nitric acid and perchloric acid in an auto- digestor at 325oC. The digested

sample after appropriate dilution was aspirated into the spectrophotometer where it was

burned into atomic components and it was read at their respective wavelength.

Sigma standard elements were used as standard analytes.

2.2.7 Quality assurance programme (QAP)

Method standardization and validation were carried out with internal standard (IS),

external standard (ES), intra and inter lab analysis of particular food and percent

recovery. Data quality was maintained by precision (co-efficient of variance, CV),

accuracy (Standard Reference material, SRM) and well documented foods, standard

error of mean (SEM).


50/118

49

Chapter 3

Results and Discussion


51/118

50

3 Results and Discussions

Healthy well-nourished people are the outcome of successful social and economic

development and constitute an essential input into the development process. Good

health needs balanced diets, which could be obtained and designed from nutrientcomposition of key foods. Therefore, nutrient composition of key foods is to be well-

known and available to the mass population.

Public health nutrition activities, nutrition, agricultural, health and epidemiological

research, food industries and trade decision and government policy planning concerning

nutrition and agriculture, all depend on an accurate knowledge of what is in food. It is the

nutrient composition of food that can provide this information. Currently these data are

not adequate to meet the existing needs of planners, practioners, and professionals in

Bangladesh. Often the data are incomplete, inconsistent and inaccessible.

There is a worldwide call for updating food composition databases. The third world

countries are far behind to address this attempt. Like most of the developing countries,

Bangladesh does not have food composition database. The current food composition

table (FCT) - Deshio Khadder Pustimanprepared by the Institute of Nutrition and Food

Science (INFS), University of Dhaka, later edited by Helen Keller International (HKI) in

english version- Tables of Nutrient Composition of Bangladeshi Foods was prepared

long back; most of the nutrient data used were analyzed long ago, and some were

assumed to be borrowed from neighboring countries, and did not have the nutrient data

of ethnic foods.

Over the last decade food composition activities have increasingly been addressed by

many agencies. As an effort to contribute to this need, this study has been undertaken

with an aim to prepare a food composition database with reference to general and ethnic

foods of Bangladesh.


52/118

51

3.1 Key food identification

Nutrient profiling of a food is expensive in term of its identification, collection, processing

and analysis. Therefore, analyzing every food item for every nutrient and meeting all

user requirements is difficult. Consequently, priorities must be determined. Key foods

have been identified as those foods that contribute up to 75% of any one nutrient to the

dietary intake (Haytowitz et al, 1996; 2000; 2002). Key foods can be documented by

food consumption survey.

In this study, the key foods was indentified through CFCS and FGDs and priorities made

in consultation with TAT members.

3.1.1 Comprehensive Food Consumption Survey (CFCS)

Food consumption survey comprises collection of information about food intake

frequency and amount of food consumed (Brussaard et al, 2002). It is performed by

household survey. The aim of CFCS is to generate food consumption statistics. Food

consumption data and nutrient values help to generate Key Foodslist. In identifying the

key foods, nutrient contribution of the food and public health significance of nutrients are

taken into consideration.

The proposal was to conduct CFCS on 1700 households comprising 1200 general

households and 500 ethnic tribal households. Later on as per recommendation received

from the 5th dissemination workshop at Rangamati on the 18th March 2010, more ethnic

households were included in the CFCS to make a total 805 ethnic households

CFCS activities

To select the key food items to be investigated for their nutrient profiling, CFCS was

carried out to collect food consumption data of the general and ethnic tribal population.

Before starting it, survey locations were mapped out, a questionnaire was developed

and pretested and sample size was determined. These activities were finalized and


53/118

52

approved in consultation with FAO Technical Advisory Team members. CFCS sampling

plan of the general and ethnic households are described in the table 3.1 and 3.2, and

some CFCS activities in ethnic tribes are highlighted in the photographs.

CFCS Team

Co-Investigator and DAE enumerator with ethnic people

Enumerator taking interview


54/118

53

Enumerator with ethnics

PI and enumerator with ethnics taking interview

Co- Investigator and enumerator with ethnics taking interview


55/118

54

Table 3.1: Location and description of CFCS data collection among the general po

Division District Upazilla Date of visit Location No of

intervie

Dhaka Netrokona Netrokona

sadar

31.01.09 to 02.02.09 West chakpara 50

Mohandrapur 54Manikgonj Saturia 08.02.09 to 11.02.09 Sawdagar para &

Uttarkaunna

50

12.02.09 to 16.02.09 Char saturia 50

Sylhet Moulavibazar Moulavibazar

Sadar

21.02.09 to 22.02.09 Suvro 52

23.02.09 to 25.02.09 Kodupur 50

Habigonj Madhobpur 25.02.09 to 27.02.09 Godampara &

Krishnanagar

51

28.02.09 to 02.03.09 West madhobpur 50

Chittagong Feni Feni Sadar 16.03.09 to 17.03.09 North Charipur 50

18.03.09 to 19.03.09 Nagarkandi, Mathiara 50

Comilla Comilla Sadar 20.03.09 to 21.03.09 Gabindapur 50

22.03.09 to 24.03.09 Kashinathpur 50

Rajshahi Natore Natore Sadar 03.04.09 to 04.04.09 Uttar Patua para 51Ulupur 49

Rajshahi Rajpara 01.04.09 to 02.04.09 Terkhadia 52

Kashia danga 52

Khulna Jessore Jessore

Kotoali

04.04.09 to 06.04.09 Shangkarpur 50

Mubarak Kathi 49

Jhenaidah Kaligonj 08.04.09 to 09.04.09 Arpara Nadir par 50

Mithapukur 50

Barisal Barisal Barisal Kotoali 11.04.09 to 14.04.09 Ganopara 50

Rupatoli 50

Jhalokathi Jhalokathi

Sadar

13.04.09 to 14.04.09 Krishnakathi 50

Rajapremhar 50

Total 121


56/118

55

Table 3.2: Location and description of CFCS data collection among the ethnic popula

Division District Upazilla Time of visit Location No o

interv

Dhaka Netrokona Durgapur 03.02.09 to 07.02.09 Gopalpur, Nolua 2

Debdul 3

Sylhet Moulavi Bazar Kamolgonj 18.02.09 to 20.02.09 Tilokpur 2

Magurchara & Kashiapunji 2

Chittagong Khagrachari Khagrachari

sadar

31.03.10 to 15.04.10

17.04.10 to 23.04.10

Nilkantipara 7

Dewanpara 6

Soyanundarpara 5

Rangamati Rangamati

sadar

03.04.10 to 10.04.10 Haja Chara, Diglibak, ShapChari,

6

Naraichari, Vhulu Chari, 2

Tanchanga para, Banna Chari 3

Bandarban Bandarban

sadar

06.03.09 to 07.03.09 Raicha Senior para 3

07.03.09 to 08.03.09 Kalaghata 3

09.03.09 to 12.03.09 Balaghata Biddopara,Painchara, Parjatan Chakmapara, Pain para, Nadir par,Balaghata bazar

1

13.03.09 to 14.03.09 Bameri para 3

Faruk para 3

Puratan and nutun choroi para 7

Rajshahi Rajshahi Godagari 29.03.09 to 31.03.09 Nimghat para, Nobai bottala,Dangapara, Nimghatu para

8

Total 8


57/118

56

Figure 3.1: Distribution of general and ethnic households by number

1210

805

General Ethnic


58/118


59/118

58

Figure 3.3: Distribution of ethnic households by district

0

50

100

150

200

250

300

350

59 50

180

120

307

89

Number

of

households


60/118

59


61/118

60

Figure 3.4: Distribution of ethnic households by tribe and number

238

171

51

8730

30

25

2589

31

28

Chakma Marma Tanchanga Tripura

Bam Murong Monipuri Khashia

Shantal Garo Hajong


62/118

61

3.1.2 Focus group discussions (FGDs)

In the present study, FGDs were conducted to enrich and supplement the CFCS food

consumption data. It carried out among the ethnic community of Marma, Chakma,

Tripura and Tangchagatribes living in Khagrachari and Rangamati. It was done during

March and April, 2010. The FGD composed of 8-12 community participants, 2 key

informants- one from the community NGO person and one was DAE block supervisor,

and a critique- the agriculture officer. The composition, characteristics and activities of

the FGDs are depicted in the table 3.3 and photographs.

The key question was the type of foods that the ethnic people consume throughout the

year. Their response to this issue was discussed, criticized and recorded carefully. In

the CFCS it is indicated that ethnic people consumed about 46 food items, most of

which are also consumed by the general people; therefore, these are not absolutely

ethnic. To explore the true ethnic foods, the FGDs were conducted among the ethnic

communities. FGDs showed that aboutt 47 foods comprising leafy vegetables, non-

leafy vegetables, fruits, fish and meat of wild origin are consumed by the ethnic

people. The outcome of the FGDs is listed in the table 3.4.

Table 3.3: FGDs settings

FGDcommunity

Objective Location No. ofparticipants

Duration ofdiscussion

Marma Type of foodintakethroughoutthe year

Pankhaiya para, Khagrachari, CHT 12 90 minutes

Chakma South Rangapani, BidhadhanChakma Bari, Chakma palli,Rangamati, CHT

8 60 minutes

Tanchanga Tanchaga para, Dharmaraj BabuBari, Kotoali, Rangamati, CHT

8 75 minutes

Tripura Ghasbhan no 2 project Gram,

Jagonnath Mandir, Khagrachari, CHT

10 90 minutes


63/118

62

Table 3.4: FGD outcome: Food consumption pattern of the Marma, Chakma, Tanchangaand Tripura comm

na: not available * ethnic food

Sl no English name Bengali name Scientific name Sl no English name Bengali name Scientific

LEAFY VEGETABLES 25 na Banchalta* na1 Rashun Leaves Rashun shak na 26 na Fakong na2 Dheki leaves Dheki shak na 27 na Hahnagulu na3 Jarul Khambang na 28 Yam Pan/jhum alu* na4 Dumurshomi Leaves Dumurshumi shak na FRUITS5 Seneya Leaves Seneha shak na 29 Pamelo (red) Jambura (Lal) na6 Lelom Leaves Lelom shak na 30 Pineapple (wild ) Anarash (bonno) na7 na Sabarang* Ajuga macrosperma 31 Wild Melon Sindera* Cumis melo8 Roselle Amila pata* Hibiscus sabdariffa 32 na Roshko* Syzygium balsa9 na Lalam pata* Premna obtusifolia 33 Bead tree kusumgulu* Elaeocarpus an10 Indian Ivy-rue Baruna Shak* Xanthoxylum rhetsa FISH AND MEAT11 na Ojan shak* Spilanthes calva 34 Lota Fish Lota mach Na12 na Ghanda batali* Paederia foetida 35 Churi Fish (Dried) Churi mach na13 na Orai balai Premna esculenta 36 Nappi paste Nappi na

14 Purslane Bat slai* Portulaca oleracea 37 Zhinuk Shell Mollusk shell15 Yellow saraca Maytraba Saraca thaipingensis 38 Crabs Kakra Liocarcinus ver16 Yellow Flower Holud fool na 39 Shark Hangar Carcharhinus amb

17 Ginger Flower Ada shak na 40 Shark (dried) Hangar shutki Carcharhinus amb

18 Sime Flower Sime fool na 41 Kuchia fish Kuchia Monopterus cucNON LEAFY VEGETABLES 42 Snails (small) Shamuk (choto) Helix pomatia

19 Pea eggplant Mistti begun* Solanum spinosa 43 Snails (large) Shamuk (Boro) Helix pomati20 Solanum Tak begun* Solanum virginianum 44 Rat Idur Rattus norvegic21 Sigon data Sigon data* Lasia spinosa 45 Frog Beng Litoria caerulea22 Tara (Like Kochu data) Tara data na 46 na Gobar poka na23 Basher Korol Basher korol na 47 Pork Shukurer mangsha Sus scrofa dom24 Wild mushroom Edur kan na


64/118

63

FGDs activities

FGD in Marma community in Marma palli, Khagrachari

FGD in Marma community in Marma palli, Khagrachari


65/118

64

FGD in Chakma community in Chakma palli, Rangamati

FGD in Chakma community in Chakma palli, Rangamati


66/118

65

FGD in Tanchanga community in tanchanga palli in Rangamati

FGD in Tanchanga community in tanchanga palli in Rangamati


67/118

66

FGD in Tripura community in Tripura palli, Khagrachari

FGD in Tripura community in Tripura palli, Khagrachari


68/118

67

3.1.3Lifestyle characteristics of general and ethnic people

The key objective of the CFCS was to obtain food consumption information of the

general and ethnic population of Bangladesh. In addition to collecting the food

consumption data, the lifestyle profile of this population was also addressed.

Analysis of socioeconomic data showed that amongst the 1210 general households

(table 3.1) only 65 households were female headed and the rest were the male headed.

The male-headed urban household heads were more educated in numbers than their

counter part in rural locations (tables 3.5). Their main occupation was found to be earth

cutting. It may be because of their low educational level as well as currently running

road and civil works in the rural and semi urban areas. Female headed householdheads were mostly engaged in household works. Mean age of the male headed

household heads were similar in rural and urban areas. Female headed household

heads were comparatively older than the male head. The monthly income and

expenditure of both the urban and rural households were found similar.

Prevalence of illiteracy was high among the Marma and Shaontalwhile Chakmaand

Tripura were more educated, and consequently Chakma and Tripura people were

employed in services (table 3.8). The monthly family income was found to be highest

among the Tripura followed by Chakma, and lowest income was found in the Marma

and Shaontaltribes.

Food security data indicated that almost 3% households frequently experienced food

shortage, while 12% percent reported to have food shortage infrequently (tables 3.6,

3.9). Food insecurity was high in February of the year. Rural (46%) and Urban (54%)

households reported to have infrequent balanced diet. Almost 9% household ate less

than three times a day. In food shortage, adult women had to eat less and it was higher

among the rural than the urban households. Compared to the general population, food

insecurity was high among the ethnic people. It was found higher among Marmaand


69/118

68

Shaontal while food security was comparatively better among the Tripura, Tanchanga

and Chakmatribes.

In term of morbidity, most of the rural and urban household heads reported the suffering

of their under five children from diarrhea in the last one month (tables 3.7, 3.10). Most of

them did not take any specific care for the treatment of diarrhea. Comparing the

prevalence of diarrhea among the general population, prevalence of diarrhoea among

the ethnic under five children was found too high. It was found to be lowest among the

Tanchangaand highest among the Tripurachildren.

The lifestyle data reveal that the ethnic people are far behind the general population in

terms of socioeconomic situation, food security and health care access facilities.

Special care should be taken to address these problems.


70/118

69

Table 3.5: Socioeconomic profile of general households

ParametersUrban Rural

Frequency Percent Frequency Percent

Type of household (HH) 606 50.1 604 49.9

Gender of household headMaleFemale

575

31

94.9

5.1

570

34

94.4

5.6Education of male headed HH head

Below primaryBelow SSCBelow HSCHSC to Below BScBSc to MScIlliteratecan sign onlyCan read and signTotal

Education of female headed HH headBelow primaryBelow SSCBelow HSCIlliteratecan sign onlyCan read and signTotal

10616237394

6175121606

1633

126

31

17.526.86.16.50.7

10.112.3020.0100.0

3.417.210.310.139.020.0100.0

12915634322

22228-

604

710129534

21.325.95.75.30.436.74.7-

100.0

20.03.3-

36.725.015.0

100.0

Occupation of male headed HH headAgri (work)Earth cuttingRickshaw / van driverOthersTotal

205742

10606

3.394.70.41.6

100.0

135838-

604

2.196.51.4-

100.0

Occupation of female headed HH headAgri (work)Earth cuttingHousehold workNGO workerOthersTotal

16

1842

31

3.417.258.613.96.9

100.0

-23020-

34

-6.786.66.7-

100.0Mean Sd Percent Mean Sd Percent

Age of male headed HH head (Year)15-3030-4545-6060-75Total

26.683.4038.674.3551.903.8766.103.5340.731.42

23.345.925.45.4

100.0

27.30 2.9538.37 4.2853.11 4.7667.15 3.49

41.23 11.64

21.348.923.95.9

100.0Age of female headed HH head (Year)

15-3030-4545-6060-75Total

27.253.2040.08 3.7752.78 4.2466.67 2.8945.00 11.79

13.8%44.8%31.0%10.3%

100.0%

26.00 0.0039.23 4.0255.00 4.8870.00 0.00

48.20 11.21

3.343.346.76.7

100.0

Monthly total income (Tk.)14000Total

4093.82 926.686673.87 827.449653.40 749.35

12520.00 699.5518976.00 5949.647837.54 4556.45

30.6936.6317.00

7.438.25100.0

4058.38 931.656714.47 843.559493.94 745.71

12411.36 790.4120924.00 7222.358006.99 5075.75

28.6439.4016.40

7.288.28100.0

Monthly average total expenditure (Tk.)6259.28 3148.04 100.0 6169.38 3324.94 100.0


71/118

70

Table 3.6: Food security by households type in general population

ParametersUrban Rural

Frequency Percent FrequencyPercent

Experience food shortage in familyNever everSome timesOften/alwaysTotal

5177415

606

85.312.22.5

100.0

5226418

604

86.510.63.0

100.0Time of food shortage

JanuaryFebruaryWhole yearTotal

21644

89

23.6071.914.49

100.0

22582

82

26.8370.732.44

100.0Status of getting balance food

AlwaysNever eversome timesTotal

24238326606

39.96.353.8

100.0

28242280604

46.77.046.4

100.0HH head ate < 3 times a day

YesNoTotal

54552606

8.991.1

100.0

57547604

9.490.6

100.0

Children ate


72/118

71

Table 3.7: Morbidity and its treatment by household type in general population

ResponseUrban Rural

Frequency Percent Frequency Percent

Eating adequately but not gaining weightYesNoDont understandTotal

2353053

606

3.887.58.7

100.0

1952461

604

3.186.810.1

100.0Member suffers from stomachache

YesNoDont knowTotal

29575

2606

4.894.90.3

100.0

28576

-604

4.695.4

-100.0

Knowledge about reasons of diarrhoeaAnswered rightlyAnswer partly rightWrongly answeredTotal

44611743

606

73.719.37.1

100.0

39716245

604

65.626.87.5

100.0Diarrhoea in any


73/118

72

Table 3.8: Socioeconomic profile of ethnic households

Parameters CHAKMA MARMA SHAONTAL TRIPURA

Type of household Frequency % Frequency % Frequency % Frequency %Education Level HH Head

Below primaryBelow SSCBelow HSCHSC and aboveIlliteratecan sign onlyCan read and signTotal

204826518292

238

8.320.411.121.334.33.70.9

100.0

9-18-

1277-

161

5.6-11.3

-78.94.2-

100.0

22741

504-

88

2.310.24.51.156.84.5-

100.0

-19339242-

87

-21.637.810.827.02.7-

100.0

Occupation of HH headAgri (work) (1)Earth cutting (2)Rickshaw / van driver (5)Business (7)Jobless (9)Service (11)Others (12)Total

7927

11-

7960238

33.30.92.84.6-

33.325.0100.0

63-7

119-

70161

39.4-

3.27.05.6-

43.7100.0

38-4-5

122988

43.2-

4.5-

5.713.633.0

100.0

---7-

71987

---

8.1-

81.110.8100.0

n Meansd n Meansd n Meansd n Meansd Age (y) distribution of HH Head

15-3030-4545-6060-75Total

31145539

238

26.53.0138.33.8253.14.5769.54.2041.210.50

20635720161

28.12.5238.53.9653.54.2766.43.0946.212.4

1442284

88

27.62.4137.24.2752.83.5066.04.2442.011.1

124916987

27.44.2239.73.8851.63.6966.32.9943.111.3

Family monthly income (taka)14000Total

1455718117

238

309094969658849375694126008941667288753063462

13820---

161

278010886444846

---

32651635

8251--

88

23431268610054810000.0

--

26431704

24192491287

364014186875991950066712375478

23200113495107292

Family monthly expenditure 238 65744392 161 37681754 88 3125998 87 105121189


74/118

73

Table 3.9: Food security of ethnic tribes

Parameters CHAKMA MARMA SHAONTAL TRIPURA TFreq. % Freq. % Freq. % Freq. % Fr

Experience food shortage in familyNever ever

Some timesOften/alwaysTotal

163

6411

238

68.5

26.94.6

100.0

98

612

161

60.6

38.01.4

100.0

30

362288

34.1

40.925.0

100.0

73

14-

87

83.8

16.2-

100.0Time of food shortage

JanuaryFebruaryWhole yearTotal

1626411

237

68.326.94.8

100.0

984221

161

61.125.913.0

100.0

31451288

35.051.014.0

100.0

85-2

87

97.3-

2.7100.0

Status of getting balance foodAlwaysNever eversome timesTotal

9513

130238

39.85.6

54.6100.0

41-

120161

25.4-

74.6100.0

123

7388

14.03.0

83.0100.0

54-

3387

62.2-

37.8100.0

HH head ate < 3 times a dayYesNoTotal

68170238

28.771.3

100.0

25136161

15.584.5

100.0

464288

52.347.7

100.0

-8787

-100.0100.0

Children ate


75/118

74

Table 3.10: Morbidity and its treatment by ethnic tribes

Parameters CHAKMA MARMA SHAONTAL TRIPURA

Freq. % Freq. % Freq. % Freq. % Eating adequately but not gaining weight

Not respond

YesNoDont understandTotal

15

1513771

238

6.5

6.557.429.6

100.0

-

-9368

161

-

-57.742.3

100.0

-

1711688

-

1.180.718.2

100.0

-

5802

87

-

5.491.92.7

100.0Member suffers from stomach ache

YesNoDont knowTotal

92209

238

3.792.63.7

100.0

2159

-161

1.498.6

-100.0

-88-

88

-100.0

-100.0

-87-

87

-100.0

-100.0

Knowledge about reasons of diarrheaAnswered rightlyAnswer partly rightWrongly answeredTotal

1347133

238

56.529.613.9

100.0

687320

161

42.245.112.7

100.0

32431288

36.849.413.8

100.0

87--

87

100.0--

100.0Diarrhea in any 5 children in last month

Didnt experiencedLast weekOne month agoMore than one month agoCannot remember

Total

1172-

8633

238

49.10.9-

36.113.9

100.0

603-

4949

161

37.11.6-

30.630.6

100.0

48132115

88

54.01.13.424.117.2

100.0

40-2

1628

87

28251619

70Measures taken to get relief of diarrhoea

Didnt experiencedFed packet salineMedicineMedicine and oral salineTotal

152481324

238

63.920.45.610.2

100.0

12612186

161

78.27.310.93.6

100.0

63153788

71.317.23.48.0

100.0

68927

87

78.410.82.78.1

100.0Giving anti helminthics regularly to


76/118

75

3.1.4 Identification of Key foods

The key food approach is used t

food database

Documents