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, 2016Acting Assistant Professor of Global Health

Policy Formulation

PolicyAdoption

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

PolicyAdoption

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 problemStatistical Power No food composition data needed Between-food interactionsSupplementation Use in dietary advice

Defining diet

7

Absolute Intake

Relative IntakeHealth outcomeDisease 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

(Num

ber)

RCTs

with

sign

ifica

nt e

ffect

in

the

oppo

site

dire

ctio

n (%

)

RCTs

with

nul

l fin

ding

s (%

)

Pros

pect

ive

obse

rvat

iona

l st

udie

s (Nu

mbe

r)

Pros

pect

ive

obse

rvat

iona

l st

udie

s with

sign

ifica

nt

Low

er li

mit

of R

R >

1.5

Dose

-res

pons

e re

latio

nshi

p

Biol

ogic

pla

usib

ility

Anal

ogy

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 vegetablesDiet low in vegetablesDiet low in vegetablesDiet low in whole grains

Diet low in whole grains

Diet low in nuts and seeds

Diet low in fruits

Diet low in fruitsDiet low in fruitsDiet low in fruitsDiet low in fruits

Diet low in vegetablesDiet low in fruits

Diet low in fruits

Diet low in fruitsDiet low in fruitsDiet low in fruits

Diet low in whole grainsDiet low in whole grains

Epidemiologic evidence supporting causality between dietary risk-outcome pairs

GBD 2015

Outcome RCTs

(Num

ber)

RCTs

with

sign

ifica

nt e

ffect

in

the

oppo

site

dire

ctio

n (%

)

RCTs

with

nul

l fin

ding

s (%

)

Pros

pect

ive

obse

rvat

iona

l st

udie

s (Nu

mbe

r)

Pros

pect

ive

obse

rvat

iona

l st

udie

s with

sign

ifica

nt

Low

er li

mit

of R

R >

1.5

Dose

-res

pons

e re

latio

nshi

p

Biol

ogic

pla

usib

ility

Anal

ogy

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 acidsDiet low in polyunsaturated fatty acidsDiet high in trans fatty acids

Diet low in milkDiet high in red meatsDiet high in red meatsDiet high in processed meatsDiet high in processed meatsDiet high in processed meatsDiet high in sugar sweetened beverages

Diet high in sodiumDiet high in sodium

Epidemiologic evidence supporting causality between dietary risk-outcome pairs

GBD 2015

Policy Formulation

PolicyAdoption

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

Com

para

tive

Ris

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sses

smen

t

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 Liuadded branadded wheat germbagelsbranbreakfast cerealsbrown ricebrown rice flourbuckwheatbulgurcooked cerealcooked oatmealcorn meal dumplingscorn meal flat cakescorn meal porridgecorn meal steamed breadnon-white breadoatsother grainspancakespizzapopcornpsyllium Aune (2016)

Covariates

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Age

Sex

Race

Educ

atio

n

Mer

ital S

tatu

s

Smok

ing

Alco

hol

Phys

ical

Exc

eris

e

Enge

ry

Frui

t and

Veg

etab

les

SFA

Fish

/ Se

afoo

d

PUFA

MU

FA

Tran

s- F

A

Red

Mea

t

Sucr

ose

Coffe

e

Sodi

um

Soy

Dairy

BMI

Wai

st/h

ip

Vita

min

Sup

plem

ents

Ora

l Con

trac

eptiv

es

HRT

Diab

etes

Hyp

erte

nsio

n

Hyp

erch

oles

tero

lem

ia

Men

tal S

tres

s

Men

opau

sal S

tatu

s

Slee

p Du

ratio

n

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 DiseaseAune (2016)

Correlation between dietary factors

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Veg

Frui

t

Proc

Mea

t

Red

Mea

t

Nut

s/se

eds

Who

le g

rain

s

SSB

Milk

Sodi

um

Om

ega-

3

PUFA

SFA

Fibe

r

Calc

ium

Veg 1.00Fruit 0.19 1.00Proc Meat -0.13 -0.04 1.00Red Meat -0.02 -0.11 -0.08 1.00Nuts/seeds 0.10 0.13 -0.07 -0.08 1.00Whole grains 0.08 0.17 -0.07 -0.11 0.12 1.00SSB -0.21 -0.22 0.03 0.07 -0.13 -0.18 1.00Milk -0.04 0.04 -0.02 -0.02 -0.03 0.09 -0.12 1.00Sodium 0.29 -0.12 0.31 0.08 -0.13 -0.03 -0.13 -0.05 1.00Omega-3 0.12 0.05 -0.10 -0.06 0.07 0.03 -0.07 -0.04 0.14 1.00PUFA 0.08 -0.03 0.06 -0.13 0.21 0.00 -0.15 -0.14 0.02 0.07 1.00SFA -0.14 -0.12 0.18 0.14 -0.07 -0.18 -0.14 0.10 0.00 -0.11 0.09 1.00Fiber 0.61 0.48 -0.15 -0.17 0.25 0.44 -0.34 0.04 0.07 0.05 0.04 -0.25 1.00Calcium 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

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GBD 2015 Fruits 200-300 gr/dayVegetables 340-500 gr/dayWhole grains 100-150 gr/dayNuts 16-25 gr/dayRed meats 18-27 gr/dayProcessed meats 0-4 gr/dayMilk 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%EDietary fiber 19-28 gr/dayDietary calcium 1-1.5 gr/day

New approach to determine TMREL

Healthy diet fact sheet (WHO)

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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

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Acknowledgment

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1700+ GBD Collaborators