Does stuntingoverweightness change our understanding of the - - PowerPoint PPT Presentation

SLIDE 1

Does stuntingoverweightness change our understanding of the socioeconomic gradient in child malnutrition?

Katie Bates (LSHTM), Arjan Gjonça (LSE), Tiziana Leone (LSE)

IPC2017 Cape Town 31/10/2017

SLIDE 2

Child Malnutrition

Overnutrition

• 41 children overweight
• 36 million in LMICs
• Short and long term health

consequences

UN Sustainable Development Goals #2 Zero Hunger #3 Good Health and Well-being #10 Reduced Inequality

Undernutrition

• Leading cause of death and

disability in children

• Implicated in 45% of child

deaths worldwide

• 155 million children (22.9%)

Tackling inequalities in child malnutrition crucial to reducing overall levels (Wagstaff & Wanatabe 2000)

SLIDE 3

Anthropometric Indicators for Malnutrition Status

Indicates:

• Overweight

Definition:

• >2SD

Indicates:

• Wasting

Definition:

• <-2SD (moderately)
• <-3SD (severely)

For most LMICs, national levels of child malnutrition(under-five) are created using anthropometric status indicators created from household survey data

Weight-for-Height (W/H) Indicates:

• Stunting

Definition:

• <-2SD (moderately)
• <-3SD (severely)

Height-for-Age (H/A)

SLIDE 4

Stata Macros:

• Zscore06
• Dm0004_1 (contains zanthro

and bmicat)

• igrowup

Other software:

• WHO Antho software package

No accompanying guidelines for concurrency Stuntingoverweight, stuntingwasting and the categorisation of continuous z-scores

Implicit assumption in the use of anthropometric indices: Children are only presenting with one form of malnutrition

UNICEF-WHO-The World Bank Joint Malnutrition Estimates ‘double count’ stuntedoverweight children, expect the same for stuntedwasted Stuntedoverweight

• Concurrently stunted and overweight

(stuntedoverweight)

• Found in all of 79 LMICs studied (Bates et al. 2017)
• 0.3% (Senegal) to 11.7% (Guinea-Bissau)

Stuntingwasting:

• Concurrently stunted and wasted
• Study of 84 countries rates from 0 to 8% (Khara et al.

2017)

Programmes create continuous z-scores

SLIDE 5

Socioeconomic inequality in malnutrition

Stunting

• Poorer children
• As NT progresses – stunting ↓
• Inequality doesn’t necessarily

change (Wagstaff & Wanatabe 2000; Van de Poel et al. 2008) Overweight

• Initially considered a problem of

the rich (Popkin & Gordon-Larsen 2004)

• Increasingly burden for the poor as

NT progresses (Monterio et al. 2004) Wasting

• Poor children (some studies have

shown no inequality)

• Levels decline as NT progresses

As LMICs progress in their Nutrition Transitions (NT), socioeconomic gradients in malnutrition change

No indication stuntedoverweight (or stuntedwasted) children are accounted for in research on socioeconomic inequality in malnutrition

SLIDE 6

20 40 60 80 100

20 40 60 80 100

Cumulative stunting %

Cumulative % of Children Ranked by Asset Scores

• Allows for binary health outcomes (e.g. stunted or not)
• Not dependent on mean
• Takes value between -1 and 1
• Cie=0 -no inequality in malnutrition
• C>0 if richer more affected
• C<0 if poorer more affected

Data and Methods

Erreygers’ Concentration Index (CIe)

Concen- tration curve Equality

line Concentration Index= 2*area between concentration curve and 45° line of equality

Data:

• Demographic and Health

Surveys

• Albania (2008-09)
• Azerbaijan (2006)
• Benin (2011)
• Egypt (2014)

Methods:

• 6 classifications of malnutrition

into all possible combinations

• f binary variables made from

continuous z-scores

• Socioeconomic status – wealth

index

• Analysed using Erreygers’

Concentration Index (CIe)

SLIDE 7

System 4

• Stunting (SW)
• Overweight (SO)
• Wasting

System 5UR

• Stunting
• Overweight
• Wasting
• Stuntingoverweight
• Stuntingwasting

System 6*

• Stunting (SO & SW)
• Overweight (SO)
• Wasting (SW)

Classification Systems

System 1

• Stunting (SO & SW)
• Overweight
• Wasting

System 2

• Stunting
• Overweight (SO)
• Wasting (SW)

System 3

• Stunting (SO)
• Overweight
• Wasting (SW)

KEY: SO: includes Stunting-overweight SW: includes Stuntingwasting

*As in UNICEF-WHO-WB Estimates UR also analysed by urban/rural

SLIDE 8

Results: System 5 Malnutrition Rates and GNI per capita 500 1000 1500 2000 2500 3000 3500 4000 4500

5 10 15 20 25 30 35 Albania Azerbaijan Benin Egypt

% children under-five

Stunting % Overweight % Wasting % Stuntedoverweight % Stuntedwasted % GNI per capita (Atlas Method)

Current US$

SLIDE 9

Results: CIe by Country and System Albania

S 1 S 2 S 3 S 4 S 5 S 6

Stunting

• 0.074*
• 0.03
• 0.073*
• 0.03
• 0.03
• 0.074*

Overweight

0.02

• 0.03

0.022

• 0.03

0.02

• 0.03

Wasting

0.03 0.03 0.027 0.03 0.03 0.027

Stunting-

• verweight
• 0.047*
• Stunting-

wasting

• 0.001
• Azerbaijan

S 1 S 2 S 3 S 4 S 5 S 6

Stunting

• 0.165*** -0.144***
• 0.158*
• 0.147*** -0.144***
• 0.165***

Overweight

0.047* 0.03 0.047* 0.032 0.047* 0.03

Wasting

• 0.046**
• 0.052**
• 0.052**
• 0.046**
• 0.046**
• 0.052**

Stunting-

• verweight
• 0.014
• Stunting-

wasting

• 0.007
• Benin

S 1 S 2 S 3 S 4 S 5 S 6

Stunting

• 0.096*** -0.071*** -0.090*** -0.078*** -0.071*** -0.096***

Overweight

0.003

• 0.016

0.003 0.016 0.003

• 0.016

Wasting

• 0.032** -0.039**
• 0.039**

0.032**

• 0.032** -0.039**

Stunting-

• verweight
• 0.019
• Stunting-

wasting

• 0.007*
• Pro-poor

Pro-rich Not sig Not created

• Egypt

S 1 S 2 S 3 S 4 S 5 S 6

Stunting

• 0.017
• 0.021*
• 0.019
• 0.019
• 0.021*
• 0.017

Overweight

0.016* 0.018 0.016* 0.018 0.016* 0.018

Wasting

• 0.008
• 0.008
• 0.008

0.006 0.006

• 0.008

Stunting-

• verweight
• 0.002
• Stunting-

wasting

• 0.002
• *p<0.05 **p<0.01 ***p<0.001

Key:

SLIDE 10

Results: Cross-country comparison of system 5

Albania Azerbaijan Benin Egypt

Stunting (SE)

• 0.026

(0.024)

• 0.144***

(0.031)

• 0.071***

(0.014)

• 0.021*

(0.010)

Overweight (SE)

0.022 (0.027) 0.047* (0.018) 0.003 (0.008) 0.016* (0.007)

Wasting (SE)

0.028 (0.031)

• 0.046**

(0.017)

• 0.032**

(0.012) 0.006 (0.008)

Stuntingoverweight (SE)

• 0.047*

(0.022)

• 0.014

(0.023)

• 0.019

(0.012) 0.002 (0.008)

Stuntingwasting (SE)

• 0.001

(0.001)

• 0.007

(0.004)

• 0.007*

(0.003) 0.002 (0.008)

*p<0.05 **p<0.01 ***p<0.001

SLIDE 11

Results: Rural/Urban inequality for System 5

Albania Azerbaijan Benin Egypt U R U R U R U R

Stunting

• 0.041
• 0.061* -0.111** -0.089*
• 0.080**
• 0.030

0.005

• 0.049***

(SE) (0.029) (0.027)

(0.035) (0.044) (0.023) (0.016) (0.014) (0.010)

Overweight 0.082*

• 0.026

0.080**

• 0.002

0.004 0.002 0.030** 0.010

(SE) (0.034) (0.040)

(0.024) (0.011) (0.014) (0.008) (0.010)

• 0.008

Wasting

0.022

• 0.002

0.034

• 0.047*
• 0.012**
• 0.040**
• 0.014

0.013

(SE) (0.048) (0.021)

(0.018) (0.020) (0.015) (0.013) (0.012) (0.009)

Stuntingoverweight -0.081* -0.040

• 0.024

0.009

• 0.007
• 0.024

0.007 0.016

(SE) (0.036) (0.030)

(0.029) (0.024) (0.017) (0.013) (0.012) (0.009)

Stuntingwasting

• 0.000
• 0.002

0.001

• 0.012*
• 0.001
• 0.002

0.000

(SE)

(0.002) (0.002) (0.008) (0.005) (0.004) (0.003) (0.001)

N

590 701 892 1050 2808 4828 5488 8194

*p<0.05 **p<0.01 ***p<0.001

SLIDE 12

Conclusions

• 1. Concurrency in malnutrition needs to be accounted for
• Stuntingoverweight, in particular, challenges our current

understanding of inequality in both stunting and overweight

• 2. Increased transparency in binary indicator construction is required
• 3. Spatial differences in inequality exist and need to be accounted for
• Results here show rural/urban differentials
• Regional differentials also exist (not presented)

‘Evidence that the social gradient in health can be reduced should make us

• ptimistic that reducing health inequalities is a realistic goal for all societies.’

(Marmot & Bell 2016)

Malnutrition in LMICs is changing, for efficient targeted malnutrition interventions: