Modelling the Cost of Nutrient Adequacy over the Life Cycle: - PowerPoint Presentation

Slide1

Modelling the Cost of Nutrient Adequacy over the Life Cycle: How do methods matter?

Yan Bai, Ph.D. CandidateFriedman School of Nutrition Science & PolicyTufts UniversitySeminar at International Food Policy Research InstituteWashington DC, November 13, 2019

Slide2

Introduction

Methodology and Data

Modelling for Different Age-Sex Groups

Conclusions and The Future

2

Photo:

Stevier Kaiyatsa

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

OUTLINE

Slide3

introduction

3

Slide4

WHY MODEL DIETS?

Identify foods or whole diets to meet nutrient gaps in the population

For advocacy, nutrition education or behavioral change

Diet recommendations for key populations (e.g. pregnant women or infants)

Measuring diet costs/affordability for targeting & designing social transfers

Measuring poverty (Allen 2017 AER)

Identifying critical nutrient gaps and deficienciesEvaluating impacts of (bio)fortification, reformulation and supplementsEvaluating impacts of agriculture, economic, and nutrition policiesEvaluating food systems

How efficient is a given food system for delivering nutrients?4

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide5

THE COST OF NUTRIENT ADEQUACY

CANDASA developed Cost of Nutrient Adequacy (

CoNA

):

Use least-cost way to meet nutrient needs for

an adult woman of 19-30 y/o

35 upper & lower bounds of energy + 21 nutrients for a balanced dietCan be measured in any time and location in the world But concerns about internal & external validity of CoNA

:We know requirements vary by age and sexCoNA produce diets heavy in plant-based foods, but major bioavailability concernsInfants/toddlers have additional constraints: small stomachs, chewable, palatable, ….In short, methodological assumptions could matter a lot

5

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide6

Methodology and data

6

Slide7

Methodology AND DATA

Optimization: linear programming

Widely applied in both Economics and Nutrition since Stigler (1945)

Measuring poverty, tracking and comparing nutritious diets, making recommendations

The Cost of Nutrient Adequacy (

CoNA

) :CoNA: min. Ck =

Σipiqi subject to relevant dietary reference intake requirements

Food price data collected for other purposes:Food retail prices collected by national statistical agenciesChoice of items aims to represent all good & services consumed

Underlying data are typically confidential7

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide8

Dietary Reference Intakes (DRIs)

Estimated Average Requirements (EARs)

meet needs for 50% of a healthy population

Recommended Dietary Allowances (RDAs)

and

Adequate Intake (AI): meet needs for 97.5% of a healthy populationUpper Levels: eliminating risk for toxicity of over intakes

DIETARY REFERENCE INTAKES

Incorporated DRIs for long-term health

Acceptable Macronutrient Distribution Ranges (

AMDRs

) and Chronic Disease Risk Reduction Intakes (

CDRR)

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide9

DIETARY REFERENCE INTAKES (CONT’D)

The DRIs specify min. & max. levels for energy and up to 21 nutrients

9

Source: Dietary Reference Intakes (DRI) values for the US & Canada, last revised 2011. Available online at https://www.nal.usda.gov/fnic/dietary-reference-intakes

Energy

balance

1 calorie constraint

Macronutrient

ranges

For

protein

, fat and carbohydrates

3 lower bounds

3

upper bounds

2 average requirements

Micronutrient requirements

For 8 minerals (calcium, copper, iron, magnesium, phosphorous, selenium, zinc and sodium) and also for 10 vitamins (niacin, riboflavin, thiamin, folate, and Vitamin A, retinol, B6, B12, C, E)

16 average requirements

10 upper limits for toxicity

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide10

Dri

will vary across age-sex groups

Nutrient requirements vary by age, sex over life courses

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide11

DRI will vary by individual status

Nutrient bioavailability may alter nutrient requirements and lead to the need for adjustments

Multiple factors may affect

WHO and FAO provide DRIs (RDA equivalent) of Zinc and Iron for all gender-age groups assuming lower bioavailability

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide12

MODELING FOR DIFFERENT SEX-AGE GROUPS

12

Slide13

Nutrition cases

Four methodological variations considered:

EAR only – meet needs of 1/2 population, recommended for population assessments;

The traditional way of making the least-cost diet constraints;

EAR plus upper limits (UL) and Acceptable Macronutrient Distribution Range (AMDR)

“default case” for the current

CoNA applications

Using Recommended Dietary Allowance (RDA) or Adequate Intake (AI) to replace EARTargeting almost entire healthy population’s needs;RDAs for Indispensable Amino-Acids – “protein quality” impacts the least cost?

And for Adult Groups: check if dietary zinc and iron sufficient given predicted bioavailability

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide14

CONA Cost ($) by age & sex

Lactating women and adolescent men are facing the highest CoNARDA substantially raises the cost, with CoNA in most age-sex groups greater than the national poverty line

METHODOLOGY AND DATA

INTRODUCTION

MODELING FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide15

CONA Cost ($) per calorie by age & sex

Per 1,000kcal, females are consistently facing higher CoNA than male groups, and the CoNA density is increasing as people are aging

METHODOLOGY AND DATA

INTRODUCTION

MODELING FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide16

Change in

cona from % change in CALCIUM EAR/RDACalcium has most expensive for the adolescent boys and girls

METHODOLOGY AND DATA

INTRODUCTION

MODELING FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide17

Cona

food composition in adult groupsHigh contribution of plant foods due to missing bioavailability assumptions?

METHODOLOGY AND DATA

INTRODUCTION

MODELING FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide18

Zinc/iron absorption at lower levels

Dietary zinc in

CoNA

food selections always above WHO standard:

Almost no zinc deficiencyDietary iron is far below the WHO DRIs: 5% absorption of many food selections,

Lots of deficiency

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide19

Using higher requirements for iron

Malabsorption of Iron leads to a much higher CoNA in adult women

Implausible pulse/nut/seed diet: iron fortification for women?

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide20

Modeling

for infants and toddlers

Current approach underestimates costs for young children?

Food selection and preparation

Is the food item suitable for infant/toddler feeding?

Do cooking methods relate to nutrient retention and food volumes?

Maximum daily feeding volumes? (small stomach problem)Need to consider additional nutrients and estimated energy requirements Breast feeding assumptionsBioavailability and health challenges like persistent diarrhea, infections, etc.

At least make adjustment for protein digestibility?

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide21

PRELIMINARY Analysis strategy

We are using the ICP price data for 25 low-income countries

Model for infants from 7-12 months, and toddlers from 13-36 months

First step focuses on food selection and preparation assumptions:

Certain foods are excluded for the infant group, such as red/white meat?

Food preparation assumptions from the West African Food Composition Table

Nutrient loss during food preparation (nutrient retention rates)Food volumes will change during preparation (food yield factors)Make different yield factors of cereals for infant and toddler groups (~7 vs ~2.5)

Assume functional gastric capacity: 30 g/kg reference BW and ~4 meals for infants and ~5 meals for toddlers (WHO, 2003) Reference BW: average of the median BW at each month

METHODOLOGY AND DATA

INTRODUCTION

MODELING FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide22

PRELIMINARY Results

Average

CoNA

for the infant group is USD0.52 for male, and USD0.75 for female;

For the toddler group, it is USD1.12 for male and USD1.13 for female

METHODOLOGY AND DATA

INTRODUCTION

MODELING FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide23

Top 5 foods being selected - NEPAL

Infant MaleInfant FemaleToddler Male

Toddler Female

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide24

Top 5 foods being selected - Malawi

METHODOLOGY AND DATAINTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTUREInfant Male

Infant Female

Toddler Male

Toddler Female

Slide25

CONCLUSIONS AND THE FUTURE

25

Slide26

CONCLUSIONS AND THE FUTURE

Rigorous & realistic costing of nutritious diets has many applications

However, relatively little previous work explores how much methods matter

Our future goals in this project are:

Establish how methods matter (methodological study)

Create a user-friendly dietary modelling tool (open access)

Apply these methods to different types of data & different populations

METHODOLOGY AND DATA

INTRODUCTION

MODELING

FOR DIFFERENT AGE-SEX GROUPS

CONCLUSIONS AND THE FUTURE

Slide27

Thank you! Q&A

27