‘Optifood’ – A tool based on linear programming analysis to inform

nutrition programme planning and policy decisions

Elaine FergusonLondon School of Hygiene & Tropical

Medicine

Improving health worldwide

www.lshtm.ac.uk

Introduction

• Dietary survey data is important for describing food patterns, intakes of energy and nutrients and estimating the % at risk of inadequate nutrient intakes; however, there are important programme and policy uses of dietary data

• I will describe how dietary data together with a tool based on linear programming analyses (Optifood), can be used to inform decisions regarding the use of food-based strategies to improve nutrition of high risk target population

• I will present an illustrative example from SE Asia

Why a food-based intervention?

• Dietary approaches are more sustainable and will likely provide benefits across a wide range of age groups

• Avoids unintentional/unexpected adverse effects from providing high or unbalanced levels of nutrients

• However questions remain – is a food-based approach alone a cost-effective approach for ensuring dietary adequacy?

• → Culturally acceptable, affordable & nutritionally adequate

• What nutrient requirements are easy to meet using locally available foods and which are more difficult?

What Optifood can do.... Formulate food-based recommendations (FBR) for a

specific target group

Test & compare FBRs → cost & nutrient adequacy

Identify nutrients whose requirements are difficult to achieve using local foods → “problem nutrients”

Identify the lowest cost nutritionally best diet, and the most expensive food sources of nutrients in this diet as well as the most expensive nutrient requirements to achieve

Types of issues it can address

• FOOD AVAILABILITY/ ACCESSIBILITY: Can locally available food provide all nutrients needed by a target population? → Policy & programme decisions and advocacy.

• FOOD AFFORDABILITY: How much will the nutritionally best diet cost ? → Cost transfer programme decisions.

• BEHAVIOUR CHANGE: What food-based recommendations are best to promote for improving the nutritional status of the target population? → Programme decisions and research

Optifood ….

• Tool based on linear programming analyses (LP)

• LP is mathematical optimisation which selects the best option from amongst all possible options given specified criteria

• In Optifood, its diet modeling , so its quickly selects the best diet from hundreds/thousands of modeled diets that are run in each analysis to inform decisions

Data Requirements

• Dietary Surveys– Quantitative (recalls,

records)– Food frequency data

• Market surveys– Food cost per 100 g edible

portion

• Food composition tables

Food Composition TableEnergyProteinWaterFatCarbohydrateVitamin AVitamin CB1B2B3CaFeZnB6B12Folate

Select Fe and Zn bioavailabilitySelect Fe and Zn bioavailability

Optifood Analysis StructureModel Constraints

Food listMin & max g/wk

Food Patterns Min & max serves/wkMain food groupsStaples & snacksFood sub-groups

Energy content

Maximum cost (optional)

Food-based recommendations (FBRs)

Nutrient content

Module#1

Module#2

Module#3

Module#4

Module Outputs Check parameters

Create food-based recommendations; ‘Problem nutrients’

Test & compare alternative FBRs

Type of ‘problem nutrient’

Cost analysis: Lowest cost

nutritionally best diet

Module III: models tails of the nutrient intake distribution to test FBRs

Baseline Food-based recommendation

>65% or 70% RNI=adequate

Vitamin A intakes

• Test 11 micronutrients• Test alternative sets of FBRs

Define “problem nutrients”Upper tail < 100% RNI/AI

Formulate and Test Food-based Recommendations:

• What food-based recommendations are best to promote for this target group?

• Module 2 results are used = “best diet” → potential food-based recommendations– Best food and food sub-group sources of nutrients– Food group patterns

Food-based RecommendationsTest and compare in Module 3

“lower tail of intake distributions”

Dairy 14 serves / weekVegetables 21 serves / weekMeat, fish or eggs 5 serves / weekLegumes 7 serves/weekFruits 7 serves/weekLiver 2 serves/weekGreen leafy vegetables 5 serves/weekVitamin C rich fruits 5 serves/weekPotatoes 3 serves/weekTofu/tempeh 7 serves/weekAnchovies 3 serves/week

Minimised nutrient content analysis from Module 3 Count number of “lower tails” >65% or 70% RNI and cost

Research in SE Asia

Countries and Target groups

• Up to 6 target groups representative at national or district level in each country– 6-8 month olds– 9-11 month olds– 12-23 month olds– Pregnant women– Lactating women or adolescent girls– Non-pregnant, non-lactating women

• In all countries but Laos, dietary data were collected using a 24-hour recall at the national level; in Thailand FFQ

• in Laos, a 7-day qualitative 24-hour recall at a district level

Define “Problem nutrients”

1. Can a nutritionally adequate diet be promoted given local foods & food patterns?

Numbers of “Problem Nutrients”

Cambodia Indonesia Lao PDR Thailand VietnamChildren:6-8 m9-11 m12-23 m

664

420

330

330

210

Women:PregnantLactatingNPNL

754

Not analysed

321

Not analysed

442

For children: Ca, Fe & Zn; sometimes folate, B1, B2 & B3For women: Ca & Fe; often folate, B2, B6 & vitamin A

Food-based Recommendations

2. To what extent can food-based recommendations ensure dietary adequacy for these target groups?

Number of nutrients –lower tails of their intake distributions >70% RNI

when FBRs were tested(11 micronutrients)

% target groups where nutrient adequacy was not ensured

Testing Alternative Interventions -children

What is the minimum of sachets/w of multiple micronutrient powders that would ensure dietary adequacy?

6-8 months 9-11 months 12-23 monthsAlone With

FBRAlone With

FBRAlone With

FBRCambodia 5* 4* 4* 4* 4* 3Indonesia 5* 3* 5* 3* 4* 4*Lao PDR 5* 4* 5* 4* 5* 3*Vietnam 5* 3 5* 3 4* 3

*Ca adequacy not ensuredFBR – food-based recommendations

Choose an iron-folate or a multi-micronutrient supplement for pregnant Cambodian women?

Daily Fe – folate Supplement Daily Multiple Micronutrient Supplement

Number per week

Only supplement#Nutrients≥70% RNI

Supplement + FBR

#Nutrients≥70% RNI

Number per week

Only supplement#Nutrients≥70% RNI

Supplement + FBR

#Nutrients≥70% RNI

1 day2 days3 days4 days5 days6 days7 days

112222

3*

667778

8#

1 day2 days3 days4 days5 days6 days7 days

234699

10**

66789

1010**

*Achieved only Fe, folate & niacin#Did not achieve Ca, riboflavin & vitamin A**Did not achieve Ca

Will the proposed national sets of Complementary Feeding Recommendations ensure dietary adequacy?

CF Recommendations for 6-8 m olds in ThailandOriginal Tested#1 Tested#2 Tested#3 Tested#4 Optifood

Rice -14MFE – 14Egg – 7

Veg – 14Fruit-14

Oil-7

““““

Fruit -7“

“““““

No oil

““““

Fruit-7Oil-3

““““““

F- rice-14

Not feasible Not feasible 4 low nutrients*

4 low nutrients

2 low nutrients

Problem nutrients

Ca Fe ZnB3

CaFeZnB3

FeB3

Ca Fe Zn

*low nutrients defined as worst-case scenarios <65% RNI

Did intervention foods ensure dietary adequacy?from Cambodia (6-8 months)

FoodsWinfoodWinfood-liteCSB+CSB++

Skau et al, AJCN 99:130-8, 2014

Dietary Adequacy not ensured: “worst-case scenario” <65% RNI

Baseline Winfood Winfood-lite CSB+ CSB++

6-8m 6-8m 6-8m 6-8m 6-8m

B1*B2

B3*B6*B9*

B12*Ca*Fe*Zn*

B1*B2

B9*Fe*

B1*B9Fe*

B1*B9CaFe*

B1*B9Fe*

Skau at al, AJCN 99:130-8, 2014*worst-case scenario <50% RNI

Conclusions• Food-based approaches can improve the micronutrient content of

diets in SE Asian countries but they may not ensure dietary adequacy for all nutrients especially – Ca, Fe, and Zn for children; and perhaps also folate, thiamin, riboflavin & niacin– Ca, Fe and folate for women; and perhaps also thiamin, riboflavin, niacin, B6, VA

• Alternative strategies are needed to ensure dietary adequacy in these SE Asian populations (advocacy)

• Food-based recommendations plus an alternative strategy, such as multiple micronutrient powders/supplements or tailored fortified foods, can ensure dietary adequacy for most micronutrients if successfully adopted (programmes/policy – need evaluations )

The SMILLING TeamLao – National Institute of

Public Health– Dr Sengchanh Kownnavong– Dr Manithong Vonglokham– Dr Daovieng Douangvichith

Thailand – Mahidol University– Dr Uraiporn Chittchang– Dr Nipa Rojroongwasiukul– Dr Pattanee Winnichagoon

Indonesia – SEAMEO TROPMED RCCN– Dr Umi Fahmida– Mr Otte Santika

Cambodia – Ministry of Health; Ministry of Agriculture, Forestry & Fisheries– Dr Mary Chea– Mr Seyha Sok– Ms Daream Sok– Mr Kuong Khov– Dr Jutta Skau

Vietnam – National Institute of Nutrition– Prof Le Bach Mai– Dr Tran Thaan Do– Dr Tran Lua-NIN

Thank-you!

FBRs – number servings/wChildren- breastfeed Women

C I* L T V C L V

MFE Pork Liver Eggs

217

7 14

1, 3

14, 21

3

14, 21 2173

21

3

21717

Dairy (12-23 m) 7 14 14 7

Legumes 7 7 7

Fruits 7 7 7 7, 14 7 14 7 7

Vegetables GLV

7 74

72

1414

21 4914

35

Fortified Products

7

*Indonesia – day-based servings not meal-basedMFE – meat, fish, eggs

Nutrients not adequate (<70% RNI)

Cambodia Indonesia Lao PDR Thailand Vietnam

6-8 m Ca, Fe, Zn, folate

Fe, Zn, B3 Ca, Fe, Zn, B1, B3

Ca, Fe, Zn Ca, Fe, Zn

9-11 m Ca, Fe, Zn, folate

Ca, Fe, Zn, B3

Ca, Fe, Zn, B1, B3

Ca, Fe, Zn Fe

12-23 m Fe, folate Ca, B2, B3 Fe, Zn, B1, B3, folate

Fe, B3, folate

Ca, Fe, B1

Pregnant Ca, Fe, folate, B2,

VA

Ca, Fe, B1, B3, B6, folate

Ca, Fe, folate, B2,

B3, B6

Lactating Ca, Fe, folate, B2,

VA

Ca, Fe, B1, B3, B6, folate

Ca, folate, B2

NPNL Ca, Fe, folate, B2,

VA

Ca, Fe, B1, folate

Ca, Fe, B2, B3