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What makes a healthy diet a healthy diet?
Challenges and opportunities for defining, measuring, and evaluating the health impact of diet at the population level
Ashkan Afshin, MD MPH MSc ScD November 15, 2016
Acting Assistant Professor of Global Health
Policy
Formulation
Policy
Adoption
Policy
Implementation
Policy
Evaluation
Agenda Setting1. Defining optimal nutrition
2. Quantifying the burden of disease due to malnutrition
3. Evaluating the effectiveness of policies to improve nutrition
4. Evaluating the cost-effectiveness of nutrition policies
5. Evaluating the political/legal feasibility of nutrition policies
6. Evaluating the intensity of implementation of nutrition policies
7. Evaluating the short/long term effects of nutrition policies
Policy
Formulation
Policy
Adoption
Policy
Implementation
Policy
Evaluation
Agenda Setting1. Defining optimal nutrition
2. Quantifying the burden of disease due to malnutrition
3. Evaluating the effectiveness of policies to improve nutrition
4. Evaluating the cost-effectiveness of nutrition policies
5. Evaluating the political/legal feasibility of nutrition policies
6. Evaluating the intensity of implementation of nutrition policies
7. Evaluating the short/long term effects of nutrition policies
4
Malnutrition
5
GBD 2015
1943 1992 2005 2011
1989 2002 2015
Nutrients Foods Dietary patterns
Biological mechanism No biological knowledge Intercorrelations not a problem
Statistical Power No food composition data needed Between-food interactions
Supplementation Use in dietary advice
Defining diet
7
Absolute Intake
Relative IntakeHealth outcome
Disease endpoints
(CVD, diabetes, cancer)
Intermediate outcomes
(obesity, blood pressure)
8
Evidence Description
RCTs of disease endpoint Number of independent RCTs evaluating the effect of the risk on the disease endpoint
% of independent RCTs showing significant effect in the opposite direction
% of independent RCTs showing no effect
Prospective observational studies of
disease endpoint
Number of independent prospective observational studies evaluating the association of the
risk with the disease endpoint
% of independent prospective observational studies with significant association in the
opposite direction
Strength Lower Limit of RR in observational studies> 1.5 (Yes/No)
Dose response Evidence of the dose-response relationship between the risk and the outcome(Yes/No)
Biologic plausibility
Potential biologic mechanism that could explain the effect of the risk on the disease endpoint
(Yes/No)
Analogy
Evidence on the relationship between the risk factor and a disease endpoint from the same
category (Yes/No)
Outcome
RCTs(Number)
RCTswithsignificanteffectin
theoppositedirection(%)
RCTswithnullfindings(%)
Prospectiveobservational
studies(Number)
Prospectiveobservational
studieswithsignificant
LowerlimitofRR>1.5
Dose-responserelationship
Biologicplausibility
Analogy
Lip and oral cavity cancer 0 - - 2 0
Nasopharynx cancer 0 - - 2 0
Other pharynx cancer 0 - - 2 0
Larynx cancer 0 - - 2 0
Oesophageal cancer 0 - - 5 0
Tracheal, bronchus, and lung cancer 0 - - 22 0
Ischaemic heart disease 0 - - 9 0
Ischaemic stroke 0 - - 9 0
Hemorrhagic stroke 0 - - 5 0
Diabetes mellitus 0 - - 9 0
Oesophageal cancer 0 - - 5 0
Ischaemic heart disease 0 - - 9 0
Ischaemic stroke 0 - - 8 0
Hemorrhagic stroke 0 - - 5 0
Ischaemic heart disease 0 - - 7 0
Ischemic stroke 0 - - 6 0
Hemorrhagic stroke 0 - - 6 0
Diabetes mellitus 0 - - 10 0
Diet low in nuts and seeds Ischaemic heart disease 1 0 100 6 0
Diabetes mellitus 1 0 100 5 0
Risk
Diet low in vegetables
Diet low in vegetables
Diet low in vegetables
Diet low in whole grains
Diet low in whole grains
Diet low in nuts and seeds
Diet low in fruits
Diet low in fruits
Diet low in fruits
Diet low in fruits
Diet low in fruits
Diet low in vegetables
Diet low in fruits
Diet low in fruits
Diet low in fruits
Diet low in fruits
Diet low in fruits
Diet low in whole grains
Diet low in whole grains
Epidemiologic evidence supporting causality between dietary risk-outcome pairs
GBD 2015
Outcome
RCTs(Number)
RCTswithsignificanteffectin
theoppositedirection(%)
RCTswithnullfindings(%)
Prospectiveobservational
studies(Number)
Prospectiveobservational
studieswithsignificant
LowerlimitofRR>1.5
Dose-responserelationship
Biologicplausibility
Analogy
Colon and rectum cancer cancer 0 - - 7 0
Colon and rectum cancer cancer 0 - - 8 0
Diabetes mellitus 0 - - 9 11
Colon and rectum cancer cancer 0 - - 9 11
Ischaemic heart disease 0 - - 5 0
Diabetes mellitus 0 - - 8 0
Body mass index 10 0 60 22 0 - -
Colon and rectum cancer cancer 0 - - 15 0
Diet low in fibre Ischaemic heart disease 0 - - 12 0
Colon and rectum cancer cancer 0 - - 13 0
Ischaemic heart disease 17 0 94 16 0
Ischaemic heart disease 8 0 75 11 0
Ischaemic heart disease 0 - - 4 0
Systolic blood pressure 45 0 73 - - - -
Stomach cancer 0 - - 3 0
Risk
Diet low in fibre
Diet low in calcium
Diet low in seafood omega-3 fatty acids
Diet low in polyunsaturated fatty acids
Diet high in trans fatty acids
Diet low in milk
Diet high in red meats
Diet high in red meats
Diet high in processed meats
Diet high in processed meats
Diet high in processed meats
Diet high in sugar sweetened beverages
Diet high in sodium
Diet high in sodium
Epidemiologic evidence supporting causality between dietary risk-outcome pairs
GBD 2015
Policy
Formulation
Policy
Adoption
Policy
Implementation
Policy
Evaluation
Agenda Setting1. Defining optimal nutrition
2. Quantifying the burden of disease due to malnutrition
3. Evaluating the effectiveness of policies to improve nutrition
4. Evaluating the cost-effectiveness of nutrition policies
5. Evaluating the political/legal feasibility of nutrition policies
6. Evaluating the intensity of implementation of nutrition policies
7. Evaluating the short/long term effects of nutrition policies
12
ComparativeRiskAssessment
Measurement Error
13
Subar (2001)
Publication Bias
14
Nuts & IHD
Red meat & Diabetes Processed meat & Diabetes
Trans fat & IHD
SSBs & Diabetes
Definition of dietary factors
15
Wang Huang Johnsen Wu Jacobs Jensen Steffen Liu
added bran
added wheat germ
bagels
bran
breakfast cereals
brown rice
brown rice flour
buckwheat
bulgur
cooked cereal
cooked oatmeal
corn meal dumplings
corn meal flat cakes
corn meal porridge
corn meal steamed bread
non-white bread
oats
other grains
pancakes
pizza
popcorn
psyllium Aune (2016)
Covariates
16
Age
Sex
Race
Education
MeritalStatus
Smoking
Alcohol
PhysicalExcerise
Engery
FruitandVegetables
SFA
Fish/Seafood
PUFA
MUFA
Trans-FA
RedMeat
Sucrose
Coffee
Sodium
Soy
Dairy
BMI
Waist/hip
VitaminSupplements
OralContraceptives
HRT
Diabetes
Hypertension
Hypercholesterolemia
MentalStress
MenopausalStatus
SleepDuration
Atkins (2014)
Eshak(2011)
Eshak (2014)
Jacobs(2001)
Jensen(2004)
Johnsen (2015)
Liu (1999)
Mink (2007)
Muraki (2014)
Muraki (2014)
Pietinen (1996)
Rautiainen (2012)
Steffen(2003)
Tognon (2014)
Wang(2016)
Yu (2013)
Whole grains and Ischemic Heart Disease
Aune (2016)
Correlation between dietary factors
17
Veg
Fruit
ProcMeat
RedMeat
Nuts/seeds
Wholegrains
SSB
Milk
Sodium
Omega-3
PUFA
SFA
Fiber
Calcium
Veg 1.00
Fruit 0.19 1.00
Proc Meat -0.13 -0.04 1.00
Red Meat -0.02 -0.11 -0.08 1.00
Nuts/seeds 0.10 0.13 -0.07 -0.08 1.00
Whole grains 0.08 0.17 -0.07 -0.11 0.12 1.00
SSB -0.21 -0.22 0.03 0.07 -0.13 -0.18 1.00
Milk -0.04 0.04 -0.02 -0.02 -0.03 0.09 -0.12 1.00
Sodium 0.29 -0.12 0.31 0.08 -0.13 -0.03 -0.13 -0.05 1.00
Omega-3 0.12 0.05 -0.10 -0.06 0.07 0.03 -0.07 -0.04 0.14 1.00
PUFA 0.08 -0.03 0.06 -0.13 0.21 0.00 -0.15 -0.14 0.02 0.07 1.00
SFA -0.14 -0.12 0.18 0.14 -0.07 -0.18 -0.14 0.10 0.00 -0.11 0.09 1.00
Fiber 0.61 0.48 -0.15 -0.17 0.25 0.44 -0.34 0.04 0.07 0.05 0.04 -0.25 1.00
Calcium 0.10 0.11 0.02 -0.10 0.11 0.16 -0.27 0.54 0.11 -0.02 -0.17 0.18 0.23 1.00
NHANES 2011-2012
RR for CHD per 1 serving (28.4g)/week of nuts
Afshin (AJCN, 2014)
Luo (AJCN, 2014)
Zhou (AJCN, 2014)
19
ComparativeRiskAssessment
20
GBD 2015
Fruits 200-300 gr/day
Vegetables 340-500 gr/day
Whole grains 100-150 gr/day
Nuts 16-25 gr/day
Red meats 18-27 gr/day
Processed meats 0-4 gr/day
Milk 350-520 gr/day
Sugar sweetened beverages 0-5 gr/day
Polyunsaturated fatty acids 9-13% of total daily energy
Seafood omega-3 fatty acids 200-300 mg/day
Trans fatty acids 0-1%E
Dietary fiber 19-28 gr/day
Dietary calcium 1-1.5 gr/day
New approach to determine TMREL
Healthy diet fact sheet (WHO)
21
Free sugars<10% E/d Salt <5 g/d | Sodium< 2g/d Total Fat < 30% E/d
Adiposity Cardiovascular disease Cardiovascular disease
Mente (Lancet 2016)
Sodium excretion and risk of cardiovascular disease
Mozaffarian (NEJM 2014)
Sodium<5 g/d Sodium<2 g/d
Citation network graph
with 269 reports and 2165
citations.
Ludovic Trinquart et al.
Int. J. Epidemiol. 2016
Co-authorship network graph with 643
authors.
Ludovic Trinquart et al.
Int. J. Epidemiol. 2016
Reducing intake of free sugars and body fatness Increasing intake of free sugars and body fatness
Adults
Children
Morenga (BMJ, 2012)
Isoenergetic exchanges of free sugars with other carbohydrates
Free sugars<10% E/d
Morenga (BMJ, 2012)
Total Fat
< 30% E/d
Howard (2006)
28
ComparativeRiskAssessment
Acknowledgment
29
1700+ GBD Collaborators

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What makes a healthy diet a healthy diet

  • 1. What makes a healthy diet a healthy diet? Challenges and opportunities for defining, measuring, and evaluating the health impact of diet at the population level Ashkan Afshin, MD MPH MSc ScD November 15, 2016 Acting Assistant Professor of Global Health
  • 2. Policy Formulation Policy Adoption Policy Implementation Policy Evaluation Agenda Setting1. Defining optimal nutrition 2. Quantifying the burden of disease due to malnutrition 3. Evaluating the effectiveness of policies to improve nutrition 4. Evaluating the cost-effectiveness of nutrition policies 5. Evaluating the political/legal feasibility of nutrition policies 6. Evaluating the intensity of implementation of nutrition policies 7. Evaluating the short/long term effects of nutrition policies
  • 3. Policy Formulation Policy Adoption Policy Implementation Policy Evaluation Agenda Setting1. Defining optimal nutrition 2. Quantifying the burden of disease due to malnutrition 3. Evaluating the effectiveness of policies to improve nutrition 4. Evaluating the cost-effectiveness of nutrition policies 5. Evaluating the political/legal feasibility of nutrition policies 6. Evaluating the intensity of implementation of nutrition policies 7. Evaluating the short/long term effects of nutrition policies
  • 6. 1943 1992 2005 2011 1989 2002 2015
  • 7. Nutrients Foods Dietary patterns Biological mechanism No biological knowledge Intercorrelations not a problem Statistical Power No food composition data needed Between-food interactions Supplementation Use in dietary advice Defining diet 7 Absolute Intake Relative IntakeHealth outcome Disease endpoints (CVD, diabetes, cancer) Intermediate outcomes (obesity, blood pressure)
  • 8. 8 Evidence Description RCTs of disease endpoint Number of independent RCTs evaluating the effect of the risk on the disease endpoint % of independent RCTs showing significant effect in the opposite direction % of independent RCTs showing no effect Prospective observational studies of disease endpoint Number of independent prospective observational studies evaluating the association of the risk with the disease endpoint % of independent prospective observational studies with significant association in the opposite direction Strength Lower Limit of RR in observational studies> 1.5 (Yes/No) Dose response Evidence of the dose-response relationship between the risk and the outcome(Yes/No) Biologic plausibility Potential biologic mechanism that could explain the effect of the risk on the disease endpoint (Yes/No) Analogy Evidence on the relationship between the risk factor and a disease endpoint from the same category (Yes/No)
  • 9. Outcome RCTs(Number) RCTswithsignificanteffectin theoppositedirection(%) RCTswithnullfindings(%) Prospectiveobservational studies(Number) Prospectiveobservational studieswithsignificant LowerlimitofRR>1.5 Dose-responserelationship Biologicplausibility Analogy Lip and oral cavity cancer 0 - - 2 0 Nasopharynx cancer 0 - - 2 0 Other pharynx cancer 0 - - 2 0 Larynx cancer 0 - - 2 0 Oesophageal cancer 0 - - 5 0 Tracheal, bronchus, and lung cancer 0 - - 22 0 Ischaemic heart disease 0 - - 9 0 Ischaemic stroke 0 - - 9 0 Hemorrhagic stroke 0 - - 5 0 Diabetes mellitus 0 - - 9 0 Oesophageal cancer 0 - - 5 0 Ischaemic heart disease 0 - - 9 0 Ischaemic stroke 0 - - 8 0 Hemorrhagic stroke 0 - - 5 0 Ischaemic heart disease 0 - - 7 0 Ischemic stroke 0 - - 6 0 Hemorrhagic stroke 0 - - 6 0 Diabetes mellitus 0 - - 10 0 Diet low in nuts and seeds Ischaemic heart disease 1 0 100 6 0 Diabetes mellitus 1 0 100 5 0 Risk Diet low in vegetables Diet low in vegetables Diet low in vegetables Diet low in whole grains Diet low in whole grains Diet low in nuts and seeds Diet low in fruits Diet low in fruits Diet low in fruits Diet low in fruits Diet low in fruits Diet low in vegetables Diet low in fruits Diet low in fruits Diet low in fruits Diet low in fruits Diet low in fruits Diet low in whole grains Diet low in whole grains Epidemiologic evidence supporting causality between dietary risk-outcome pairs GBD 2015
  • 10. Outcome RCTs(Number) RCTswithsignificanteffectin theoppositedirection(%) RCTswithnullfindings(%) Prospectiveobservational studies(Number) Prospectiveobservational studieswithsignificant LowerlimitofRR>1.5 Dose-responserelationship Biologicplausibility Analogy Colon and rectum cancer cancer 0 - - 7 0 Colon and rectum cancer cancer 0 - - 8 0 Diabetes mellitus 0 - - 9 11 Colon and rectum cancer cancer 0 - - 9 11 Ischaemic heart disease 0 - - 5 0 Diabetes mellitus 0 - - 8 0 Body mass index 10 0 60 22 0 - - Colon and rectum cancer cancer 0 - - 15 0 Diet low in fibre Ischaemic heart disease 0 - - 12 0 Colon and rectum cancer cancer 0 - - 13 0 Ischaemic heart disease 17 0 94 16 0 Ischaemic heart disease 8 0 75 11 0 Ischaemic heart disease 0 - - 4 0 Systolic blood pressure 45 0 73 - - - - Stomach cancer 0 - - 3 0 Risk Diet low in fibre Diet low in calcium Diet low in seafood omega-3 fatty acids Diet low in polyunsaturated fatty acids Diet high in trans fatty acids Diet low in milk Diet high in red meats Diet high in red meats Diet high in processed meats Diet high in processed meats Diet high in processed meats Diet high in sugar sweetened beverages Diet high in sodium Diet high in sodium Epidemiologic evidence supporting causality between dietary risk-outcome pairs GBD 2015
  • 11. Policy Formulation Policy Adoption Policy Implementation Policy Evaluation Agenda Setting1. Defining optimal nutrition 2. Quantifying the burden of disease due to malnutrition 3. Evaluating the effectiveness of policies to improve nutrition 4. Evaluating the cost-effectiveness of nutrition policies 5. Evaluating the political/legal feasibility of nutrition policies 6. Evaluating the intensity of implementation of nutrition policies 7. Evaluating the short/long term effects of nutrition policies
  • 14. Publication Bias 14 Nuts & IHD Red meat & Diabetes Processed meat & Diabetes Trans fat & IHD SSBs & Diabetes
  • 15. Definition of dietary factors 15 Wang Huang Johnsen Wu Jacobs Jensen Steffen Liu added bran added wheat germ bagels bran breakfast cereals brown rice brown rice flour buckwheat bulgur cooked cereal cooked oatmeal corn meal dumplings corn meal flat cakes corn meal porridge corn meal steamed bread non-white bread oats other grains pancakes pizza popcorn psyllium Aune (2016)
  • 17. Correlation between dietary factors 17 Veg Fruit ProcMeat RedMeat Nuts/seeds Wholegrains SSB Milk Sodium Omega-3 PUFA SFA Fiber Calcium Veg 1.00 Fruit 0.19 1.00 Proc Meat -0.13 -0.04 1.00 Red Meat -0.02 -0.11 -0.08 1.00 Nuts/seeds 0.10 0.13 -0.07 -0.08 1.00 Whole grains 0.08 0.17 -0.07 -0.11 0.12 1.00 SSB -0.21 -0.22 0.03 0.07 -0.13 -0.18 1.00 Milk -0.04 0.04 -0.02 -0.02 -0.03 0.09 -0.12 1.00 Sodium 0.29 -0.12 0.31 0.08 -0.13 -0.03 -0.13 -0.05 1.00 Omega-3 0.12 0.05 -0.10 -0.06 0.07 0.03 -0.07 -0.04 0.14 1.00 PUFA 0.08 -0.03 0.06 -0.13 0.21 0.00 -0.15 -0.14 0.02 0.07 1.00 SFA -0.14 -0.12 0.18 0.14 -0.07 -0.18 -0.14 0.10 0.00 -0.11 0.09 1.00 Fiber 0.61 0.48 -0.15 -0.17 0.25 0.44 -0.34 0.04 0.07 0.05 0.04 -0.25 1.00 Calcium 0.10 0.11 0.02 -0.10 0.11 0.16 -0.27 0.54 0.11 -0.02 -0.17 0.18 0.23 1.00 NHANES 2011-2012
  • 18. RR for CHD per 1 serving (28.4g)/week of nuts Afshin (AJCN, 2014) Luo (AJCN, 2014) Zhou (AJCN, 2014)
  • 20. 20 GBD 2015 Fruits 200-300 gr/day Vegetables 340-500 gr/day Whole grains 100-150 gr/day Nuts 16-25 gr/day Red meats 18-27 gr/day Processed meats 0-4 gr/day Milk 350-520 gr/day Sugar sweetened beverages 0-5 gr/day Polyunsaturated fatty acids 9-13% of total daily energy Seafood omega-3 fatty acids 200-300 mg/day Trans fatty acids 0-1%E Dietary fiber 19-28 gr/day Dietary calcium 1-1.5 gr/day New approach to determine TMREL
  • 21. Healthy diet fact sheet (WHO) 21 Free sugars<10% E/d Salt <5 g/d | Sodium< 2g/d Total Fat < 30% E/d Adiposity Cardiovascular disease Cardiovascular disease
  • 22. Mente (Lancet 2016) Sodium excretion and risk of cardiovascular disease Mozaffarian (NEJM 2014) Sodium<5 g/d Sodium<2 g/d
  • 23. Citation network graph with 269 reports and 2165 citations. Ludovic Trinquart et al. Int. J. Epidemiol. 2016
  • 24. Co-authorship network graph with 643 authors. Ludovic Trinquart et al. Int. J. Epidemiol. 2016
  • 25. Reducing intake of free sugars and body fatness Increasing intake of free sugars and body fatness Adults Children Morenga (BMJ, 2012)
  • 26. Isoenergetic exchanges of free sugars with other carbohydrates Free sugars<10% E/d Morenga (BMJ, 2012)
  • 27. Total Fat < 30% E/d Howard (2006)