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Everyday good health:
the nutrient rich way
Lynley Drummond
Drummond Food Science Advisory Ltd
The Importance of Nutrient Balance
• Improved health outcomes are associated
with appropriate nutrition
– nutrient-rich, lower energy quality diets
– Variety of foods
• Ready access to low-cost, energy dense,
highly processed nutrient poor foods is
attributed to increasing rates of obesity &
associated comorbidities
• Overall nutritional quality of the diet is
assessed dietary indices looking at the
totality (balance) of the diet
• “Good nutrition”
Nutrient Profiling
• Is targeted to determining the nutrient quality of individual foods
– Ranks foods based on their composition
– Allows comparisons
– Enables consumers to make informed choice in food selection
– Provides a screening tool for authorities looking to make
recommendations on food selection, or screen for appropriate foods to
carry health claims
General Concepts
• Energy density
– Measure of the energy (calorific value) a specified quantity of food delivers
• Low energy density <1.5kcal/g
• Moderate energy density (1.6-3.0kcal/g)
• High energy density (>3.0kcla/g)
• Nutrient density
– Measure of the nutrient value of a food
• Weight
• Serve size
• Energy basis
• Multiple models have been developed
• Low energy dense fruit and vegetables consistently rank highly in
nutrient profiling systems.
Nutrient Density Standard for Fruit & Vegetables
• Developed specifically to enable comparison of nutrition properties
of fruits and vegetables to be made
• Based on key nutrients of interest in public health
• Reference value is 100g of the food of interest
• Consists of
1. Nutrient adequacy score = (Σ[Nutrienti/DVi] x 100)/16
2. Nutrient density (/100kcal) = (Nutrient Adequacy Score / Energy
Density) x 100
– Model further developed to consider cost (nutrient:price ratio)
Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for Vegetables and Fruits:
Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887. doi:doi:10.1016/j.jada.2005.09.005
Nutrient Adequacy
18.8
11.4
12.5
8.1 8
1.8
4.9
3.6
2.9 2.4 2.1 2.1
4.8
7
3.6
0
2
4
6
8
10
12
14
16
18
20
Based on the method of Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for
Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887.
doi:doi:10.1016/j.jada.2005.09.005
Nutrient Density
29.8
20 20.4
17.2
24.9
3.5
5.6
10.1
5.1
3.2 3.7
7.1
5.7
24
7.7
0
5
10
15
20
25
30
35
Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for Vegetables and Fruits:
Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887. doi:doi:10.1016/j.jada.2005.09.005
per100kcal
Based on the method of Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for
Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887.
doi:doi:10.1016/j.jada.2005.09.005
Nutrient Profiling Criteria Principles
• Based on accepted nutrition science
– Relevant (meaningful amounts of foods, labeling practices etc)
• Use published daily values and open-source data
• Publication of algorithms
• Use nutrients to be encouraged, and recognise those to be limited
• Be validated against measures of a healthy diet
• Consumer-driven to guide better food choice and more healthy diets
Drewnowski, A., & Fulgoni, V., 3rd. (2008). Nutrient profiling of foods: creating a nutrient-rich food index. Nutr Rev, 66(1),
23-39. doi:10.1111/j.1753-4887.2007.00003.x
Science-driven process recommended by
regulatory agencies around the world
Food
category
Across
the board
Encourage
Limit
100g or
100ml Algorithm:
Threshold
Testing and
validation
100kcal or
100kJ
Serving size
Algorithm:
x Score
Total fat
Saturated fat
trans fat
Sugars
Sodium
Protein
Fibre
Vitamin C
Vitamin A
Calcium
Iron
NZ & Australia NPSC
(FSANZ)
Used as a screening criteria for
foods with
• Health claims
• Certain nutrition content claims
(e.g. glycaemic index,
glycaemic load, “diet”)
3 Basic categories of food
1. Beverages
2. Any food other than those in
Category 1 or 2
3. Specific fat based foods
(cheese & processed cheese;
edible oil; edible oil spreads;
margarine; butter)
Development and validation of NRF9.3
• Identified (9) nutrients to encourage
– Protein, Fibre, Vitamin A, Vitamin C, Vitamin E, Calcium, Iron,
Magnesium, Potassium
• Identified (3) nutrients to limit
– Saturated fat, Added sugar, Sodium
• Selected reference Daily Values (DV)
– US reference values
• Nutrient values capped to 100%DV to avoid overvaluing foods that
provide very large quantities of a single nutrient
Fulgoni, V. L., 3rd, Keast, D. R., & Drewnowski, A. (2009). Development and validation of the nutrient-rich foods index: a tool
to measure nutritional quality of foods. J Nutr, 139(8), 1549-1554. doi:10.3945/jn.108.101360
Development and validation of NRF9.3
• Considered basis for calculations
– 100g vs. 100kcal vs. serve size (government mandated)
– Determined per 100kcal basis most appropriate
• Accepted unit/base for nutrient density
• Standard measure for comparison of all foods
• Relevant to food packaging / labeling systems internationally
• Validated against a number of variables
– Nutrients to encourage and limit
– Against serve size (RACC reference amounts customarily consumed
per eating occasion (21CFR101.12))
• Validated against other diet quality measures and systems
Fulgoni, V. L., 3rd, Keast, D. R., & Drewnowski, A. (2009). Development and validation of the nutrient-rich foods index: a tool
to measure nutritional quality of foods. J Nutr, 139(8), 1549-1554. doi:10.3945/jn.108.101360
NRF9.3 Algorithm
NRF9.3100kcal= Σi=9 (%DVi/100kcal) - Σi=3 (%MRVi/100kcal)
NRF9.3RACC = Σi=9 (%DVi/RACC) - Σi=3 (%MRVi/RACC)
DV = Daily Value
MRV= Maximum Recommended Value
9 nutrients to encourage 3 nutrients to
limit
Protein Fibre Iron
Saturated
fat
Calcium
Vitamin A
Magnesium Potassium
Vitamin C Vitamin E
Added
sugars
Sodium
Median Nutrient Rich Foods (NRF9.3) Index scores for each major US Department of Agriculture food group
plotted against median cost per 100 kcal.
Adam Drewnowski Am J Clin Nutr 2010;91:1095S-1101S
©2010 by American Society for Nutrition
NRF9.3 and Nutrient Model Development
• NRF9.3 widely used as the reference or validated comparator for the
evaluation of dietary patterns in different regions
– Developed in the USA
• In China development and validation of a new model of desirable dietary
patterns score (N-DDP)
• In the Netherlands to evaluate the Dutch Healthy Diet (DHD) Index
• In France to evaluate the contribution of fruit and vegetable juices to overall
quality of diet in terms of nutrient density
• Assessment of diets in obese Australian adolescents
• Nutrient profiling of the diets of Egyptian youths
Nutrient Rich Food Index NRF9.3100kcal
147.3
160.6 165.3
153.8
169.5
46.7 51.8
122.8
63.1
28.5
48.7
86.7
61.9
189
111.3
0
20
40
60
80
100
120
140
160
180
200
NRF9.3
Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of
Clinical Nutrition, 91(4), 1095S-1101S. doi:10.3945/ajcn.2010.28450D
Nutrient Rich Food Index NRF9.3RACC
138.7
147.3
153.8
135.4 131.1
27
56.5 61.9
50.4
18.6
38.9
72.8 71.9
62.8
18.2
0
20
40
60
80
100
120
140
160
180
NRF9.3
Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of
Clinical Nutrition, 91(4), 1095S-1101S. doi:10.3945/ajcn.2010.28450D
RACC (21CFR101.12)
Comparison of NRF 9.3 models
0
40
80
120
160
200
Chart Title
100kcal
RACC
Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of
Clinical Nutrition, 91(4), 1095S-1101S. doi:10.3945/ajcn.2010.28450D
NRF9.3
Future Trends in in Nutrient Profiling
• Current models target individual foods
– NRF9.3 most widely used reference model
– Continued use if nutrient profiling models for dietary analysis and planning
– Simplified concepts are more appropriate for consumer use
• Many labeling schemes developed with limited success
• Consumer insights showed beyond a “5-point scale” profiling systems were to
complex for “daily food choice use”
• Future models will target total diets
– Account for the role of nearly all foods in improving overall dietary quality
(“balance”) in meals and total diets
– Account for cultural differences in dietary patterns
Vitamin C Content
161.3
85.1
92.7
53.2 58.8
4.6 8.7
18.0
9.7
3.2 4.2 8.1 10.2
53.0
14.0
0
20
40
60
80
100
120
140
160
180
USDA National Nutrient Database for Standard Reference (2016) Release 28
*NZ FOODfiles 2014 Version 01
EU RDA
15% EU RDA
mg/100g
Potassium Content
315 301 312
181
153
107
358
228
77
191
116 112
236
138
80
0
50
100
150
200
250
300
350
400
15% EU RDA
mg/100g
Fibre Content
2.1
3.0 3.0
2.4
2.0
2.4
2.6
0.8
2.4
0.9
3.1
0.4
4.0
2.8
3.6
0
1
2
3
4
5
g/100g
Phytonutrients
• Diverse range of complex compounds that naturally occur in plant-
based foods
• Absorption and metabolism still to be fully understood
• Contribute to the overall health benefits of fruits, vegetables, & other
plant foods
– Research looks at specific effects
• Flavanols in cocoa
• Lutein in tomatoes
• Carotenoids in yellow/orange fruits
• No established recommended intakes
• Not included in nutrient rich models
Phytonutrients
Phenolic
compoundsGlucosinolates
• Isothiocyante
precursors
• Aglycone
derivatives
• Organosulphur
compounds
• Indoles
Betalains
Chlorophylls
Organic acids
Enzymes
Enzyme
Inhibitors
Terpenoids Carotenoids
• Carotenes
• Lutein
• Zeaxanthin
Monoterpenes
Triterpenoids
Steroids
• Phytosterols
• Tocopherol
Aromatic acids
• Phenolic acids
• Hydroxycinnamic
acids
Polyphenols
Flavonoids
Natural
monophenols
Phenylethanoids
& others
Isoflavonoids
Flavonolignans
Lignans
Stilbenoids
Curcuminoids
Tannins
Flavanols
Flavonols
Anthocyanins,
Flavones,
Flavanones
Isoflavones
Proanthocyanidins
Procyanidins Prodelphinidin
Catechin &
Epicatechins
Phytonutrients and Health
Phytonutrient Food Source Potential Benefit
Anthocyanins Strawberries, Red Wine, Blueberries Neuroprotection, improvement of vision, reduction in
platelet aggregation, induction of apoptosis, inhibition
of nitric oxide production
Flavanols and proanthocyanins Cocoa, Grapes and Grape Extracts,
Red Wine
Endothelial function, inhibition of LDL cholesterol
oxidation, inhibition of cellular oxygenases, inhibition
of pro-inflammatory responses in arterial walls
Carotenoids Tomatoes & tomato products, Fruits
and Vegetables
Eye health, prevention of cell damage from free
radicals
Isothiocyanates (sulphorane) Broccoli and other cruciferous
vegetables (e.g. kale)
Prevention of cell damage from free radicals,
chemoprotection / chemoprevention
Sulphides, thiols Garlic, onions, leeks, olives Reduction in LDL cholesterol
Isoflavones (genistein, daidzen) Soy and soy products Endothelial function, reduction in blood pressure
Everyday good health:
the nutrient rich way
• Good health is supported by the consumption of a balanced diet
– Adequate energy intake for lifestyle
– Appropriate range of food groups
– Wide range of nutrients
• Diets high in nutrient-rich, low energy-dense fruit and vegetables are
pivotal to improving health outcomes driven by dietary factors
– Role of fresh/ minimally processed fruit and vegetables with their
complement of naturally occurring phytonutrients cannot be
underestimated
Everyday good health:
the nutrient rich kiwi way
• Fruit consistently scores highly in nutrient profiling systems
• Kiwifruit consistently scores amongst the highest of fruits in nutrient
scoring systems
– Key driver is its high vitamin C content
– Other nutrients also contribute to its high nutrient rich value
– The range of phytonutrients in kiwifruit undoubtedly contribute to the
health benefits if kiwifruit as a part of a healthy balanced diet and
lifestyle
Everyday Good Health: The Nutrient Rich Way by Lynley Drummond

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Everyday Good Health: The Nutrient Rich Way by Lynley Drummond

  • 1. Everyday good health: the nutrient rich way Lynley Drummond Drummond Food Science Advisory Ltd
  • 2. The Importance of Nutrient Balance • Improved health outcomes are associated with appropriate nutrition – nutrient-rich, lower energy quality diets – Variety of foods • Ready access to low-cost, energy dense, highly processed nutrient poor foods is attributed to increasing rates of obesity & associated comorbidities • Overall nutritional quality of the diet is assessed dietary indices looking at the totality (balance) of the diet • “Good nutrition”
  • 3. Nutrient Profiling • Is targeted to determining the nutrient quality of individual foods – Ranks foods based on their composition – Allows comparisons – Enables consumers to make informed choice in food selection – Provides a screening tool for authorities looking to make recommendations on food selection, or screen for appropriate foods to carry health claims
  • 4. General Concepts • Energy density – Measure of the energy (calorific value) a specified quantity of food delivers • Low energy density <1.5kcal/g • Moderate energy density (1.6-3.0kcal/g) • High energy density (>3.0kcla/g) • Nutrient density – Measure of the nutrient value of a food • Weight • Serve size • Energy basis • Multiple models have been developed • Low energy dense fruit and vegetables consistently rank highly in nutrient profiling systems.
  • 5. Nutrient Density Standard for Fruit & Vegetables • Developed specifically to enable comparison of nutrition properties of fruits and vegetables to be made • Based on key nutrients of interest in public health • Reference value is 100g of the food of interest • Consists of 1. Nutrient adequacy score = (Σ[Nutrienti/DVi] x 100)/16 2. Nutrient density (/100kcal) = (Nutrient Adequacy Score / Energy Density) x 100 – Model further developed to consider cost (nutrient:price ratio) Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887. doi:doi:10.1016/j.jada.2005.09.005
  • 6. Nutrient Adequacy 18.8 11.4 12.5 8.1 8 1.8 4.9 3.6 2.9 2.4 2.1 2.1 4.8 7 3.6 0 2 4 6 8 10 12 14 16 18 20 Based on the method of Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887. doi:doi:10.1016/j.jada.2005.09.005
  • 7. Nutrient Density 29.8 20 20.4 17.2 24.9 3.5 5.6 10.1 5.1 3.2 3.7 7.1 5.7 24 7.7 0 5 10 15 20 25 30 35 Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887. doi:doi:10.1016/j.jada.2005.09.005 per100kcal Based on the method of Darmon, N., Darmon, M., Maillot, M., & Drewnowski, A. (2005). A Nutrient Density Standard for Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost. J Am Diet Assoc, 105(12), 1881-1887. doi:doi:10.1016/j.jada.2005.09.005
  • 8. Nutrient Profiling Criteria Principles • Based on accepted nutrition science – Relevant (meaningful amounts of foods, labeling practices etc) • Use published daily values and open-source data • Publication of algorithms • Use nutrients to be encouraged, and recognise those to be limited • Be validated against measures of a healthy diet • Consumer-driven to guide better food choice and more healthy diets Drewnowski, A., & Fulgoni, V., 3rd. (2008). Nutrient profiling of foods: creating a nutrient-rich food index. Nutr Rev, 66(1), 23-39. doi:10.1111/j.1753-4887.2007.00003.x
  • 9. Science-driven process recommended by regulatory agencies around the world Food category Across the board Encourage Limit 100g or 100ml Algorithm: Threshold Testing and validation 100kcal or 100kJ Serving size Algorithm: x Score Total fat Saturated fat trans fat Sugars Sodium Protein Fibre Vitamin C Vitamin A Calcium Iron
  • 10. NZ & Australia NPSC (FSANZ) Used as a screening criteria for foods with • Health claims • Certain nutrition content claims (e.g. glycaemic index, glycaemic load, “diet”) 3 Basic categories of food 1. Beverages 2. Any food other than those in Category 1 or 2 3. Specific fat based foods (cheese & processed cheese; edible oil; edible oil spreads; margarine; butter)
  • 11. Development and validation of NRF9.3 • Identified (9) nutrients to encourage – Protein, Fibre, Vitamin A, Vitamin C, Vitamin E, Calcium, Iron, Magnesium, Potassium • Identified (3) nutrients to limit – Saturated fat, Added sugar, Sodium • Selected reference Daily Values (DV) – US reference values • Nutrient values capped to 100%DV to avoid overvaluing foods that provide very large quantities of a single nutrient Fulgoni, V. L., 3rd, Keast, D. R., & Drewnowski, A. (2009). Development and validation of the nutrient-rich foods index: a tool to measure nutritional quality of foods. J Nutr, 139(8), 1549-1554. doi:10.3945/jn.108.101360
  • 12. Development and validation of NRF9.3 • Considered basis for calculations – 100g vs. 100kcal vs. serve size (government mandated) – Determined per 100kcal basis most appropriate • Accepted unit/base for nutrient density • Standard measure for comparison of all foods • Relevant to food packaging / labeling systems internationally • Validated against a number of variables – Nutrients to encourage and limit – Against serve size (RACC reference amounts customarily consumed per eating occasion (21CFR101.12)) • Validated against other diet quality measures and systems Fulgoni, V. L., 3rd, Keast, D. R., & Drewnowski, A. (2009). Development and validation of the nutrient-rich foods index: a tool to measure nutritional quality of foods. J Nutr, 139(8), 1549-1554. doi:10.3945/jn.108.101360
  • 13. NRF9.3 Algorithm NRF9.3100kcal= Σi=9 (%DVi/100kcal) - Σi=3 (%MRVi/100kcal) NRF9.3RACC = Σi=9 (%DVi/RACC) - Σi=3 (%MRVi/RACC) DV = Daily Value MRV= Maximum Recommended Value 9 nutrients to encourage 3 nutrients to limit Protein Fibre Iron Saturated fat Calcium Vitamin A Magnesium Potassium Vitamin C Vitamin E Added sugars Sodium
  • 14. Median Nutrient Rich Foods (NRF9.3) Index scores for each major US Department of Agriculture food group plotted against median cost per 100 kcal. Adam Drewnowski Am J Clin Nutr 2010;91:1095S-1101S ©2010 by American Society for Nutrition
  • 15. NRF9.3 and Nutrient Model Development • NRF9.3 widely used as the reference or validated comparator for the evaluation of dietary patterns in different regions – Developed in the USA • In China development and validation of a new model of desirable dietary patterns score (N-DDP) • In the Netherlands to evaluate the Dutch Healthy Diet (DHD) Index • In France to evaluate the contribution of fruit and vegetable juices to overall quality of diet in terms of nutrient density • Assessment of diets in obese Australian adolescents • Nutrient profiling of the diets of Egyptian youths
  • 16. Nutrient Rich Food Index NRF9.3100kcal 147.3 160.6 165.3 153.8 169.5 46.7 51.8 122.8 63.1 28.5 48.7 86.7 61.9 189 111.3 0 20 40 60 80 100 120 140 160 180 200 NRF9.3 Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of Clinical Nutrition, 91(4), 1095S-1101S. doi:10.3945/ajcn.2010.28450D
  • 17. Nutrient Rich Food Index NRF9.3RACC 138.7 147.3 153.8 135.4 131.1 27 56.5 61.9 50.4 18.6 38.9 72.8 71.9 62.8 18.2 0 20 40 60 80 100 120 140 160 180 NRF9.3 Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of Clinical Nutrition, 91(4), 1095S-1101S. doi:10.3945/ajcn.2010.28450D RACC (21CFR101.12)
  • 18. Comparison of NRF 9.3 models 0 40 80 120 160 200 Chart Title 100kcal RACC Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of Clinical Nutrition, 91(4), 1095S-1101S. doi:10.3945/ajcn.2010.28450D NRF9.3
  • 19. Future Trends in in Nutrient Profiling • Current models target individual foods – NRF9.3 most widely used reference model – Continued use if nutrient profiling models for dietary analysis and planning – Simplified concepts are more appropriate for consumer use • Many labeling schemes developed with limited success • Consumer insights showed beyond a “5-point scale” profiling systems were to complex for “daily food choice use” • Future models will target total diets – Account for the role of nearly all foods in improving overall dietary quality (“balance”) in meals and total diets – Account for cultural differences in dietary patterns
  • 20. Vitamin C Content 161.3 85.1 92.7 53.2 58.8 4.6 8.7 18.0 9.7 3.2 4.2 8.1 10.2 53.0 14.0 0 20 40 60 80 100 120 140 160 180 USDA National Nutrient Database for Standard Reference (2016) Release 28 *NZ FOODfiles 2014 Version 01 EU RDA 15% EU RDA mg/100g
  • 21. Potassium Content 315 301 312 181 153 107 358 228 77 191 116 112 236 138 80 0 50 100 150 200 250 300 350 400 15% EU RDA mg/100g
  • 23. Phytonutrients • Diverse range of complex compounds that naturally occur in plant- based foods • Absorption and metabolism still to be fully understood • Contribute to the overall health benefits of fruits, vegetables, & other plant foods – Research looks at specific effects • Flavanols in cocoa • Lutein in tomatoes • Carotenoids in yellow/orange fruits • No established recommended intakes • Not included in nutrient rich models
  • 24. Phytonutrients Phenolic compoundsGlucosinolates • Isothiocyante precursors • Aglycone derivatives • Organosulphur compounds • Indoles Betalains Chlorophylls Organic acids Enzymes Enzyme Inhibitors Terpenoids Carotenoids • Carotenes • Lutein • Zeaxanthin Monoterpenes Triterpenoids Steroids • Phytosterols • Tocopherol Aromatic acids • Phenolic acids • Hydroxycinnamic acids Polyphenols Flavonoids Natural monophenols Phenylethanoids & others Isoflavonoids Flavonolignans Lignans Stilbenoids Curcuminoids Tannins Flavanols Flavonols Anthocyanins, Flavones, Flavanones Isoflavones Proanthocyanidins Procyanidins Prodelphinidin Catechin & Epicatechins
  • 25. Phytonutrients and Health Phytonutrient Food Source Potential Benefit Anthocyanins Strawberries, Red Wine, Blueberries Neuroprotection, improvement of vision, reduction in platelet aggregation, induction of apoptosis, inhibition of nitric oxide production Flavanols and proanthocyanins Cocoa, Grapes and Grape Extracts, Red Wine Endothelial function, inhibition of LDL cholesterol oxidation, inhibition of cellular oxygenases, inhibition of pro-inflammatory responses in arterial walls Carotenoids Tomatoes & tomato products, Fruits and Vegetables Eye health, prevention of cell damage from free radicals Isothiocyanates (sulphorane) Broccoli and other cruciferous vegetables (e.g. kale) Prevention of cell damage from free radicals, chemoprotection / chemoprevention Sulphides, thiols Garlic, onions, leeks, olives Reduction in LDL cholesterol Isoflavones (genistein, daidzen) Soy and soy products Endothelial function, reduction in blood pressure
  • 26. Everyday good health: the nutrient rich way • Good health is supported by the consumption of a balanced diet – Adequate energy intake for lifestyle – Appropriate range of food groups – Wide range of nutrients • Diets high in nutrient-rich, low energy-dense fruit and vegetables are pivotal to improving health outcomes driven by dietary factors – Role of fresh/ minimally processed fruit and vegetables with their complement of naturally occurring phytonutrients cannot be underestimated
  • 27. Everyday good health: the nutrient rich kiwi way • Fruit consistently scores highly in nutrient profiling systems • Kiwifruit consistently scores amongst the highest of fruits in nutrient scoring systems – Key driver is its high vitamin C content – Other nutrients also contribute to its high nutrient rich value – The range of phytonutrients in kiwifruit undoubtedly contribute to the health benefits if kiwifruit as a part of a healthy balanced diet and lifestyle

Editor's Notes

  1. Validation is an important factor
  2. Model developed in France – used French National food Composition Database NUTRIENT DENSITY Low – most fruit and veg and low fat unsweetened dairy Moderate – lean meats, breads, fish & salmon High – fried foods, cheese, nuts, oils, fast food, chocolate
  3. U.S. Department of Agriculture, Agricultural Research Service(2016) USDA National Nutrient Database for Standard Reference, Release 28.
  4. Exercise & lifetsyle cannot be underestimated Socioeconomic status