Bangladesh Food Composition table 2013
Upcoming SlideShare
Loading in...5
×
 

Bangladesh Food Composition table 2013

on

  • 1,801 views

 

Statistics

Views

Total Views
1,801
Slideshare-icon Views on SlideShare
1,773
Embed Views
28

Actions

Likes
0
Downloads
36
Comments
0

1 Embed 28

http://www.asianfoodreg.com 28

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Bangladesh Food Composition table 2013 Bangladesh Food Composition table 2013 Presentation Transcript

    • Food Composition Table for Bangladesh Centre for Advanced Research in Sciences (CARS) Principal Investigator Prof. Nazma Shaheen, PhD Institute of Nutrition and Food Science Co-Principal Investigators Prof. Abu Torab MA Rahim, PhD University of Dhaka Prof. M. Mohiduzzaman Prof. S.M. Mizanur Rahman Dr. Latiful Bari National Consultant Prof. Amir Hussain Khan, PhD International Consultant T. Longvah, PhD Research Assistants Cadi Parvin Banu Avonti Basak Tukun
    • Background What is the problem with the existing FCT? Food Composition Table for Bangladesh   New high yielding varieties and non local foods are constantly being introduced in the food production/supply chain   With increasing urbanization food consumption behavior is shifting with towards more commercialized foods and processed foods   The nutrient value of these foods is yet to be evaluated though sporadic analytical work has been conducted   Moreover, existing FCTs contain a number of missing nutrient values
    • Methodological Differences Food Composition Table for Bangladesh Nutrients Existing FCT Updated FCT Dietary fibre Crude fibre Total dietary fibre Vitamin C Titrimetric methods Analyzed by HPLC Beta-carotene Analyzed as total carotene Analyzed as Beta- carotene by HPLC Vitamin B1 & B2 Borrowed value Analyzed by HPLC Retinol Borrowed value Analyzed by HPLC Sum of proximate Not within range 95-105 %
    • Objectives Food Composition Table for Bangladesh   Identify Key Foods (KFs) and critical nutrients for FCDB   Analyze 20 sampled foods under AOAC laboratory procedures from the list of KFs   Evaluate existing secondary data for scientific quality and compile all available (new & old) data to construct a food composition database for Bangladesh   Estimate a single value for each nutrient of each food from all data records   Adapt, estimate, borrow and compile values for missing nutrients for a complete & comprehensive FCDB
    • Methodology Food Composition Table for Bangladesh   HIES 2010 & INFS’ NNS 1996 for Food Consumption Data g consumed each ingredient for all foods g consumed X nutrient value of each ingredient DKF & HKI’s FCT for Food Composition Data Ranked list of % contribution of food to total nutrient intake Repeat      for      all  nutrients   Top 75% Intake KEY FOODS The KF Identification Approach Key Foods are those foods, that in aggregate, contribute >75% of the nutrient intake for selected nutrients of public health importance from the diet The Key Foods process uses food composition and food consumption data to identify and prioritize foods and nutrients for analysis (Haytowitz, et al., 2000)
    • Findings Food Composition Table for Bangladesh Sl No. Food Item* % of Total Citation** Sl No. Food Item* % of Total Citation** 1 Rice (6) 7.06 17 Shrimp (2) 2.35 2 Tomato (6) 7.06 18 Rohu (2) 2.35 3 Green Chili (6) 7.06 19 Cooking oil (1) 1.18 4 Egg Plant (5) 5.88 20 Hilsha fish (1) 1.18 5 Banana (5) 5.88 21 Amaranth stem (1) 1.18 6 Onion (5) 5.88 22 Pointed gourd (1) 1.18 7 Tilapia fish (4) 4.71 23 Bitter gourd (1) 1.18 8 Wheat Flour (4) 4.71 24 Bean (1) 1.18 9 Potato (4) 4.71 25 Pumpkin (1) 1.18 10 Pond Pangas (4) 4.71 26 Indian spinach (1) 1.18 11 Silver carp (4) 4.71 27 Lady s finger (10 1.18 12 Hen's egg (4) 4.71 28 Puti (1) 1.18 13 Rooti (4) 4.71 29 Mrigal fish (1) 1.18 14 Lentils (3) 3.53 30 Jute leaves (1) 1.18 15 Jack fruit (3) 3.53 In parentheses: * # appeared in nutrient group; ** # of total citation of all foods = 87 16 Mango (3) 3.53 The Key Food List (KFs having >1% of citation are presented)
    • 20 Key Foods Selected for Analysis Food Composition Table for Bangladesh Sl No. Food Item Sl No. Food Item 1. Rice 11. Hen's egg 2. Tomato 12. Lentils 3. Green Chili 13. Jack fruit 4. Egg Plant 14. Mango 5. Banana 15. Rohu 6. Onion 16. Bean 7. Tilapia fish 17. Cooking oil 8 Wheat Flour 18. Chicken 9. Potato 19. Carrot 10. Pond Pangas 20. Milk
    • Methodology Food Composition Table for Bangladesh Sample frame and sampling protocol   Level 1: List of population regions (7 divisions of Bangladesh) Level 2: List of Haats in each division for food collection (rural) Level 4: Random sampling from stock lots Level 5: Composite sampling for analysis Level 3: List of Wholesale/Retail Markets in each selected city corporation areas for food collection (urban) Stratified sampling (National Population Census model) The sampling frame, interestingly, covered a l l m a j o r a g r o - ecological zones of Bangladesh
    • Preparation of composite sample Food Composition Table for Bangladesh Sample collected from seven divisions Weighing Washing Air dryingDressingComposite sample
    • Analytical methods Food Composition Table for Bangladesh I. Methods AOAC and other standard methods of food analysis. II. Parameters i.  Proximate analysis: Protein, (by Micro-level digestion-distillation system) Fat, CHO, Water, Ash i.  Macro-minerals: Na, K, Ca, Mg (by AAS, & FP) ii.  Heavy metals: As, Cd, Pb, Sb (by ICPMS) iii.  Trace elements : Cu, Zn, Fe, Se, Cr, Mo, Mn, V, Ni (by ICPMS) iv.  Amino acid (by AA auto-analyzer) v.  Total Phenol (by Spectrophotometer) vi.  Antioxidant activity: DPPH & ORAC (by Spectrophotometry) vii.  Antinutrients: Phytate & Oxalate (by Open column & High performance liquid chromatography ) i.  Fatty acid profile (by Gas liquid chromatography) ii.  Total dietary fiber (TDF) (by Enzymatic-gravimetric method) iii.  Total sugar (TS) (by titrimetric method) iv.  Total free sugar (TFS) (by titrimetric method) v.  Retinol ( High performance liquid chromatography) vi.  β-Carotene ( High performance liquid chromatography) vii.  Vitamin C, B1, B2, ( High performance liquid chromatography) viii.  Vitamin B6 ( Microbial assay)
    • Quality Assurance P r o g r a m (QAP) √  Method Standardization √  Method Validation: Internal standard (IS), External standard (ES), % of recovery √  Data Quality: Precision (CV), Accuracy (In-house reference material – IHRM, Certified reference material and well documented food), SEM √  Meticulous Documentation QC protocol
    • New components in this FCTs 87 components including   Total dietary fibre   Vitamin B1, B2, B6   Retinol, beta-carotene   Amino acids   Fatty acids   Minerals: Mg, Na, K, P, Zn, Cu   Antinutrient: Phytate & Oxalate   Total phenol content, antioxidant capacity (DPPH, ORAC)   Total sugar
    • Proximate Nutrients Name Water (%) Protein Fat TDF CHO (available) Ash Energy g/100g EP Kcal Cereals Rice 12.35 6.51 0.41 3.43 76.80 0.55 344.0 Wheat flour 12.21 10.61 1.64 4.4 70.3 0.8 347.0 Pulses Lentil 12.16 27.73 0.79 13.2 43.2 2.92 317.38 Root & tubers Potato 81.71 1.19 0.16 2.11 13.96 0.87 66.260 Onion 83.73 1.37 0.07 1.89 12.26 0.68 58.930 Carrot 89.71 0.92 0.26 2.55 5.96 0.60 34.960 Vegetables Bean 90.02 2.41 0.11 4.3 2.5 0.65 29.0 Brinjal 91.35 1.9 0.06 4.073 1.957 0.66 24.110 Green chili 85.51 2.77 0.13 8.371 2.179 1.04 37.710 Fruits Banana 75.22 1.26 0.84 2.6 19.2 0.84 95.0 Jackfruit 76.99 1.19 0.2 7.2 13.3 1.08 74.0 Mango 78.44 0.79 0.41 1.56 18.04 0.76 82.130 Tomato 95.01 1.11 0.25 1.65 1.44 0.54 15.750 Fish Pangas fish 70.84 15.9 10.96 NA 0.0 0.96 162.24 Rohu fish 76.25 20.56 2.55 NA 0.0 0.90 105.19 Tilapia fish 76.21 20.8 3.02 NA 0.0 1.08 110.38 Meat Chicken breast 72.86 22.29 1.82 NA 0.0 1.08 105.54 Chicken leg 71.94 19.19 5.69 NA 0.0 0.96 127.97 Egg Egg 72.31 14.49 8.34 NA 0.0 0.81 134.62 Milk Milk 88.27 3.10 3.74 NA 4.30 0.64 63.060 NA, Not applicable
    • Qualitative Differences Foods Water (g) Protein (g) Fat (g) Available CHO (g) TDF (g) Crude fiber (g) Ash (g) Energy (kcal) Rice, parboiled 13.3 6.4 0.4 79.0 - 1.9 0.7 356 (345.2) Rice, BR-28, parboiled 12.4 6.5 0.4 76.8 3.4 - 0.5 344 Wheat flour (coarse) 12.2 12.1 1.7 69.4 - 1.9 2.7 341 Wheat flour, white 12.2 10.6 1.6 70.3 4.4 - 0.8 347 Lentil 12.4 25.1 0.7 59.0 - 0.7 2.1 343 Lentil 12.2 27.7 0.8 43.2 13.2 - 2.9 317 Black values – Existing FCT Red values_ updated FCT
    • Overestimation of Energy & Protein Energy:   Previously used formula CHO = 100-(moisture + protein + fat + ash + crude fiber )   Corrected formula Available CHO= 100-(moisture + protein + fat + ash + TDF + alcohol) Protein:   Previously used formula: Protein= Nitrogen x 6.25   Corrected formula: Protein= Nitrogen x Jone s factor for different food e.g. for rice 5.95 for wheat 5.70
    • Minerals Content (mg/100g)
    • Heavy metals Name Elements with unknown food toxicity Potentially toxic elements (µg/100 g EP) (µg/100 g EP) Sb Ba V Ni Ag Cd As Pb Cereals Rice 0.519 12.248 10.173 39.116 0.081 1.064 5.845 NA Wheat flour 0.097 394.851 3.271 15.249 0.122 1.957 0.618 2.42 Pulses Lentil 0.338 17.069 7.823 90.701 NA 0.082 0.405 NA Root & tubers Potato 0.326 28.303 7.335 32.288 0.092 1.011 0.284 NA Onion 0.106 45.885 6.340 23.163 0.024 1.598 0.242 NA Carrot 0.339 348.39 2.800 04.014 0.028 0.965 0.250 NA Vegetables Bean 0.141 111.97 14.544 75.695 0.046 0.335 0.399 2.558 Brinjal 0.176 23.688 5.149 39.410 0.141 2.532 0.280 NA Green Chili 0.342 19.552 4.004 82.653 0.026 1.351 0.207 NA Fruits Banana 0.050 17.045 0.156 0.838 NA 0.008 0.006 0.108 Jackfruit 0.157 276.077 1.056 33.219 0.118 1.366 0.278 0.95 Mango 0.142 26.303 0.292 6.317 0.009 0.109 0.275 20.606 Tomato NA 16.801 6.137 20.972 0.036 1.756 0.220 0.056 Fish Pangas fish 0.064 0.667 0.478 NA NA 0.015 2.756 0.614 Rohu fish 0.202 6.460 1.974 0.326 0.030 0.014 2.750 0.504 Tilapia fish 0.071 17.785 3.531 1.426 0.003 0.075 34.221 2.140 Meat Chicken breast 0.029 1.913 0.395 0.183 NA 0.008 1.010 NA Chicken leg 0.044 2.450 0.491 0.545 0.001 0.022 1.055 0.279 Egg Egg 0.012 132.609 0.522 1.647 0.004 0.031 0.328 1.107 Milk Milk 0.014 33.543 0.529 3.501 0.005 0.03 0.860 0.984 NA, Not available
    • Water soluble vitamins (mg/100 g EP)
    • β-Carotene & Retinol Name Retinol β-carotene µg/100 g EP Cereals Rice NA NA Wheat flour NA NA Pulses Lentil NA 33.984 Root & tubers Potato NA 27.15 Onion NA 22.776 Carrot NA 3945.956 Vegetables Bean NA 202.592 Brinjal NA 45.438 Green Chili NA 114.828 Fruits Banana NA 21.442 Jackfruit NA 28.178 Mango NA 299.543 Tomato NA 103.853 Fish Pangas fish 5.143 NA Rohu fish 3.193 NA Tilapia fish 2.033 NA Meat Chicken breast 25.152 ± 1.5 NA Chicken leg 22.802 ± 1.4 NA Egg Egg 165.246 ± 1.1 NA Milk Milk 30.177 ± 0.2 NA NA, Not applicable
    • Anti-nutrient: Oxalate & Phytate
    • Selected nutrient content of three cultured fishes (g/100g EP) 20.6 2.6 3.2 20.8 3 2 15.9 11 5.1 0 5 10 15 20 25 Protein  (g)   Fat  (g) Retinol  (mcg) Rui Telapia Pangas
    • Fatty acid content of three cultured fishes (g/100g EP)
    • Iron rich fishes (selected) Name   Fe (mg/100g)   Silver carp, kata chara   1.5   Taki, kata chara   1.5   Chital, kata chara   1.6   Fesha   1.8   Mrigal, chokh soho   1.8   Chela, Fulchela   1.9   Meni   1.9   Punti, Vadi punti, kata chara   2.0   Chanda, Ranga, chokh soho   2.0   Chompa   2.0   Name   Fe (mg/ 100g)   Parshe   2.1   Shing mach, kata chara   2.1   Tatkini   2.2   Fesha, Teli   2.3   Kachki, bivinno projati   2.4   Punti, Vadi punti, chokh soho   2.6   Tengra, bivinno projati   2.8   Mola, chokh soho   3.8   Olua   4.5   Chapila   4.8   Chela, Narkeli   5.4  
    • Sample Protein Trp Thr Val Met Ile Leu Phe His Lys TEAA Rice, BR-28, parboiled, milled 6.51 8 34 57 32 35 77 53 23 36 354 Wheat, flour, white 10.6 12 28 42 21 29 65 45 22 26 290 Lentil, dried 27.7 9 37 49 5 38 73 52 23 76 362 Pangas, without bones, 15.9 15 43 48 35 39 72 39 20 79 390 Rohu, without bones 20.6 15 42 48 31 37 70 40 26 77 386 Tilapia, without bones 20.8 14 43 45 32 37 72 39 23 77 383 Chicken breast, without skin 22.3 13 44 52 36 44 75 38 36 72 411 Chicken leg, without skin 19.2 12 43 51 34 42 77 39 27 73 399 Eggs, chicken, farmed 14.5 15 31 63 31 63 72 85 14 43 417 Milk, cow, whole fat (pasteurised, UHT )* 3.08 11 40 61 22 42 87 44 25 73 406  Protein  content  (g%),  essen0al  amino  acid  profile  (mg/g  protein)and     total  essen0al  amino  acid  (mg/g  protein)  of  food  samples.
    • Name Chemical Score Limiting Amino Acid Egg 100 Milk, cow, whole fat (pasteurised, UTH) 51 SAA Chicken leg, without skin 67 Ile Chicken breast, without skin 66 AAA Pangas, without bones 62 Ile Rohu, without bones 59 Ile Tilapia, without bones 58 AAA Rice, BR-28, parboiled, milled 50 Trp Wheat, flour, white 46 Ile Lentil, dried 23 SAA Chemical  score  and  predicted  first-­‐  limi0ng  amino  acid  according  to     reference  Protein  (egg)
    • Summary of data compilation steps with FAO data compilation tool 1.2.1 Food Composition Table for Bangladesh Data source •  Collection of compositional data Archival record •  Compilation of information from data sources Reference database •  Compilation of archival data records for each food User database •  Selection and compilation of series of values for each food item in database
    • Different Stages Employed in Preparing FCDB
    • Single Ingredient Recipe (55) Foods Water (g) Protein (g) Fat (g) Available CHO (g) TDF (g) Ash (g) Energy Kcal Rice, BR-28, parboiled 12.4 6.5 0.4 76.8 3.4 0.5 344 Rice, BR-28, Parboiled, boiled 71.4 2.1 0.1 24.3 1.1 0.2 109 Potato, Diamond, raw 81.7 1.2 0.2 14.0 2.1 0.9 66 Potato, Diamond, raw Boiled (with out salt) 81.5 1.2 0.2 14.2 2.1 0.9 67 Potato, Diamond, raw Boiled (with salt) 77.0 1.4 0.8 16.6 2.5 1.8 84
    • Multi Ingredient Recipe (11) Foods Water (g) Protein (g) Fat (g) Available CHO (g) TDF (g) Ash (g) Energy Kcal Plain khichuri 65.7 4.1 7.4 17.7 2.5 1.6 163 Analytical value* 4.7 7.3 21.0 - - 168 Analytical value** 65.77 6.18 6.83 20.3 4.21 0.92 176 *Some Common Indian Recipes and their Nutritive Value, NIN **Rahim et.al, Institute of Nutrition and Food Science, DU
    • Key Findings *Key foods for Bangladesh have been identified using consumption-composition and consumption frequency database (HIES, 2010). *Nutrient values of mostly consumed KFs (high yielding variety) currently are dominant in production and consumption in Bangladesh. *Some of the nutrients e.g. Amino Acid profile, Fatty Acid profile, vitamin B profile, heavy metals etc. have been analyzed for the first time in FCDB *All the analysis has been done by AOAC and FAO recommended methods and using certified reference material (RM) and in house RM, as appropriate). *A complete archival databank for food composition has been constructed, which contains approximately 2575 entries from all secondary data sources. * A food composition database from the archival databank has been developed using the INFOOD compilation tool 1.2.1. * Secondary data collection, compilation, management and archiving has been done using FAO recommended compilation guideline for the 1st time. * A comprehensive FCT for Bangladesh with least missing nutrient values has been developed.
    • Limitations   There is a serious lack of secondary data on total dietary fiber, niacin equivalents, phosphorous and folate.   Therefore, most of these data were imputed from other sources (e.g. Indian FCT (IND), Thai FCT (TH), Vietnam FCT (VIN), Pakistan (PAK), USDA (US25), UK (UK6), Danish (DK7),FAO/INFOODS analytical Food Composition Database (ADB), FAO/INFOODS and Food Composition Database for Biodiversity (BID).   Iodine content of the foods is highly dependent on soil and has regional variation which cannot be captured by composite analysis. Therefore, these values were omitted.   Only L-Ascorbic acid was estimated for KFs by HPLC which may not give the total Vitamin C content   Calcium content in milk, pasteurized and fresh milk (cow) was noted to be low. This has been confirmed by repeated analysis. SW388R7 Data Analysis & Computers II Slide 32
    • Policy Implications  Detailed information on nutrient composition of local foods serves as a basic tool for planning and assessment of food, nutrition and health programmes  Formulation of national food and nutrition policy through the setting goals for agricultural, aqua cultural, animal and poultry production.  Designing guidelines for consumption and particular policies such as trade, assistance, food fortification or supplementation, increased subsidy or promotion of certain foods.  Determination of gross per capita nutrient availability to assess gross adequacy or inadequacy of the national food supply/ shortfall or excess.   Preliminary checking of nutritional label information or claims.  Nutritional regulation of food supply and compliance with CODEX standards
    • Recommendations   Further work is necessary for which allocation of funding is required in order to generate primary analytical data for the rest of the key foods as determined in present project.   To develop a comprehensive FCDB in response to long-term change in the food chain, efforts have been made to increase the quality of data by the generation of data of 20 KFs and including as many analytical data of Bangladeshi foods, generated by the food scientists of Bangladesh and aboard. Nutrient values presented with 3rd bracket, [ ] would need to be reconfirmed by re-analysis of the foods.   Further revision should include numerous foods of archival database as it was not possible to incorporate these into reference database due to lack of reference values to fill up the missing nutrients.   SW388R7 Data Analysis & Computers II Slide 34
    • Recommendations (contd.)   As the reference values become available at the regional level, especially in the case of fish, those foods should be incorporated into the user database.   Only selected mixed recipes were included in the current FCT due to time constraints.   The future edition of the database should include traditional and frequently consumed recipes.   It is necessary to develop a list of all the ingredients, cooking methods, yield factors for the majority of foods and nutrient retention factors. Weights, measures and serving sizes also need to be standardized as part of the recipe calculations and analysis. SW388R7 Data Analysis & Computers II Slide 35
    • Recommendations (contd.)   Since the FCDB has been constructed with rigorous and meticulous analytical and compilation methodology, its wide dissemination should be undertaken.   Biodiversity and varietal species of foods other than rice could not be considered in the current due limited funding resources and lack of available data.   Future funding should be directed toward adequate generation of food composition data that capture elements of biodiversity and variety.   At the same time, adequate training should be made available for food scientists and analysts to generate and manage food composition data according to INFOODS Guidelines.   E-learning tools as available from FAO should be widely disseminated for use. SW388R7 Data Analysis & Computers II Slide 36
    • We appreciate the active contribution of various academic, research and government organizations as well as authors of published papers, reports, scientific proceedings and theses providing analytical food composition data (contributors names have been cited in bibliography)