Nutrition Program Secondary 2014 DHS Analysis Reference: National - - PowerPoint PPT Presentation

Nutrition Program

“Secondary 2014 DHS Analysis”

Reference: National Nutrition Program, Nutrition secondary analysis 2014 CDHS, UNICEF/IRD/MOH, Phnom Penh, Cambodia, January 2016

Team

2

IRD MOH FiA UNICEF

Dr Frank Wieringa Dr Valerie Grefeuille Dr Jacques Berger Mr Ludovic Gauthier Dr Chhoun Chamnan Mr Khov Kuong Dr Prak Sophonneary

ICF

Mr Rathavuth Hong Dr Etienne Poirot Dr Rathmony Hong Mr Samoeurn Un Dr Arnaud Laillou

For the secondary analysis:

Special thanks to 1. WFP, ILSI, World Vision for their financial support to the micronutrient survey 2. FiA for the data collection

Economic Burden of malnutrition (I)

The impact of the indicators of malnutrition analyzed in the report represent a burden to the national economy of Cambodia estimated at more than 260 million USD annually -1.7% of GDP.

• Figure. Impact on the total economic

burden of malnutrition from each indicators

Economic Burden of malnutrition (II)

Depending on the discount rate, 0.9-1.7% of the GDP (145-266 million USD) are lost annually

Quantitative Practices during the 1,000 Days window

We analyzed the inequities between different groups

How to read the graphs?

Shows the difference in 2010 between rural and urban If * than the 2 prevalence are sig. different If letter different than the differences are significantly different

• therwise no sig. diff.

If letter different than the national prevalence in 2010 and 2014 are significantly different otherwise no sig. diff. If * on the line than the prevalence data in 2010 and 2014 for the different clusters (here urban and rural) are sig. different

• therwise no difference

Impact indicators

Health behavior and practices

Health behaviors and Practices

Urban vs Rural

0.0 5.0 10.0 15.0 20.0 25.0 2000 2005 2010 2014 Total Urban Rural

Prevalence of Diarrhea

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 2000 2005 2010 2014 seeking treatment/advice Total Urban Rural

Prevalence of mother seeking treatment

Diff: -5.3*a Diff: -0.4 a

* *

a a

Diff: -0.9 a Diff: -9.9*a

a a

Diff: 11.5*b

In 2014, no difference odds between rural and urban In 2014, Richest women are 1.5 significantly more likely to seek treatment than poorest women

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 2000 2005 2010 2014 Total Urban Rural

Prevalence of mother receiving ORT

Diff: -1.0 a Diff: -6.0 a

a a

Diff: 7.9* b

But zinc supplements given to only 5.4% in 2014 vs 2.4% in 2010:

• Urb: 1.4% to 3.3%
• Rur.: 2.5% to 5.8%

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 2000 2005 2010 2014 Total poorest richest 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 2000 2005 2010 2014 seeking treatment/advice Total poorest richest 0.0 5.0 10.0 15.0 20.0 25.0 2000 2005 2010 2014 Total poorest richest

Health behaviors and Practices

Poorest vs Richest

Prevalence of Diarrhea Prevalence of mother seeking treatment

Diff: -7.8*a Diff:-4.0*a

a a

Diff: 3.7a Diff:-16.8* a

a a

Diff: 13.5*b

In 2014, Poorest women are 1.4 significantly more likely to have diarrhea than richest women In 2014, Richest women are 2 significantly more likely to seek treatment than poorest women Prevalence of mother receiving ORT

a a

Diff:28.7*b

But zinc supplements given to only 5.4% in 2014 vs 2.4% in 2010:

• pooresr: 1.7% to 6.3%
• richest: 1.3% to 5.3%

* *

Diff: -0.3 a Diff:-15.4*a

In 2014, Richest women are 2 significantly less likely to receive ORT than poorest women

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 2005 2010 2014 seeking treatment/advice Total Urban Rural 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 2005 2010 2014 ARI Total Urban Rural

Health behaviors and Practices

Urban vs Rural

Prevalence of ARI Prevalence of mother seeking treatment In 2014, no difference odds between rural and urban Prevalence of mother receiving Antibiotic

Diff: -0.1 b

a a

Diff: -3.8*a

* * * *

a a

Diff: 3.9 a Diff: 1.0 a

In 2014, no difference odds between rural and urban

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 2005 2010 2014 Total Urban Rural

a b

Diff: 10.6* a Diff: -8.0* b

* * * *

Health behaviors and Practices

Poorest vs Richest

Prevalence of ARI Prevalence of mother seeking treatment Prevalence of mother receiving Antibiotic

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 2005 2010 2014 ARI Total poorest richest 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 2005 2010 2014 seeking treatment/advice Total poorest richest 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 2005 2010 2014 Total poorest richest

Diff: -4.6*a Diff: -2.1a

a a

Diff: 8.2 a Diff: -1.9a

a a

Diff: 21.3*a Diff: -13.2*b

a b

* *

In 2014, no difference odds between poorest and richest In 2014, Richest women are 2.5 significantly less likely to receive antibiotic than poorest women In 2014, Poorest women are 1.5 significantly more likely to have ARI than richest women

Health behavior and practices

Other inequities 2014 analysis shows that mothers are 2 times more likely to get advice or treatment for a girl than a boy during a ARI episode

Key Variables Gender (Boys vs Girls) in 2014 Trends among gender categories between 2010 and 2014 Diarrhoea No significant difference was

• bserved

The prevalence decreased significantly among boys (B: 15.9-13.4%) while no change among girls

Seeking treatment for diarrhoea

No significant difference was

• bserved

No significant difference was

• bserved

ARI No significant difference was

• bserved

No significant difference was

• bserved

Seeking treatment for ARI Significant difference was

• bserved (B: 62.2% vs G: 75.9%)

No significant difference was

• bserved

Impact indicators

Breastfeeding and Complementary feeding practices

Feeding practices

Birth 6mo 12mo 24mo Exclusive breastfeeding Partial breast and complementary feeding

Exclusive Breastfeeding (0-5.9 months)

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 2000 2005 2010 2014 % Total Urban Rural 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 2000 2005 2010 2014 % Total poorest richest

Diff:-11.2* a Diff:-30.9* b

a b

* *

Diff:-11.9* a Diff:-30.9* b

* *

In 2014, Rural children are 3.5 significantly more likely to be EBF than urban children In 2014, Poorest children are 5 significantly more likely to be EBF than richest children

I. Median duration of exclusive breastfeeding decreased from 4.9mo to 4.5mo II. Median duration of predominant breastfeeding decreased from 5.6mo to 5.4mo

Feeding practices

Birth 6mo 12mo 24mo Exclusive breastfeeding Partial breast and complementary feeding

Continuing Breastfeeding (6-23.9 months)

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

2000 2005 2010 2014

Total Urban Rural

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 2000 2005 2010 2014 Total poorest richest

a b b a

Diff:-21.9* a Diff:-27.9* b

* * * *

Diff:-28.7* a Diff:-22.5* a

* *

In 2014, Rural children are 3.3 significantly more likely to be PBF than urban children In 2014, Poorest children are 2.6 significantly more likely to be PBF than richest children

Feeding practices

Birth 6mo 12mo 24mo Exclusive breastfeeding Partial breast and complementary feeding

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 2000 2005 % Total Urban Rural

Minimum Acceptable Diet (6-23.9 months)

0.0 10.0 20.0 30.0 40.0 50.0 60.0 2000 2005 % Total poorest richest

Diff:0

a

Diff:19.4*b

a b

* *

Diff: 30.1* b Diff: 8.1* a

* *

In 2014, Urban children are 2.3 significantly more likely to receive the minimum acceptable diet than rural children In 2014, Richest children are 4.2 significantly more likely to receive the minimum acceptable diet than poorest children

a b

2010 2010 2014 2014

Feeding practices

Birth 6mo 12mo 24mo Exclusive breastfeeding Partial breast and complementary feeding

Minimum Acceptable Diet (6-23.9 months)

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 2010 2014 MAD Total 6-8 9-11 12-17 18-23

* * * *

Diff:9.3* a Diff: 12.4* a

In 2014, Children 18-23mo are 1.9 significantly more likely to receive the minimum acceptable diet than younger children 6-8mo

Feeding practices

Other inequities

Key Variables Gender (Boys vs Girls) in 2014 Trends among gender categories between 2010 and 2014 Exclusive breastfeeding Significant difference was observed (B: 60.1% vs G: 68.7%) The prevalence decreased significantly among boys (B: 74.7- 60.1%) while no change among girls Partial breastfeeding No significant difference was

• bserved

The prevalence decreased significantly among boys (B: 78.3- 69.6%) while no change among girls Minimum acceptable diet No significant difference was

• bserved

The prevalence increased significantly in both groups (B: 23.8-30.0%; G: 23.9-30.5%)

2014 analysis shows that a girl is 1.5 times more likely to be exclusively breastfed

Impact indicators

Nutritional status

Impact Indicators : Nutritional status

Child

• verweight/obese: rural < urban population

(17.3% vs 22.9%, p<0.05)

High disparity and inequities

Double burden of malnutrition in population Under-nutrition still dominant

Women

Impact Indicators : Nutritional status

Mothers

0.0 5.0 10.0 15.0 20.0 25.0 2000 2005 2010 2014 Total Urban Rural 0.0 5.0 10.0 15.0 20.0 25.0 30.0 2000 2005 2010 2014 Total poorest richest

Underweight Prevalence

Diff: 0.6a Diff: 2.9*a

* * * * * * * *

Diff: -5.8* a Diff: -2.6* a

In 2014, No significant difference between urban and rural children In 2014, Poorest children are 1.2 significantly more likely to be underweighted than the richest children

The multivariate analysis performed for the 2014 survey indicated that the significant factors contributing to thinness were the lowest age, having less than 3 children, belonging to the lowest wealth quintile and having anemia

Impact Indicators : Nutritional status

Mothers Underweight Prevalence

5 10 15 20 25 30 less 20yrs old 20-34 yrs 35-49 yrs 2000 2005 2010 2014

a b

• 4.4% pt
• 7% pt
• 19.4%pt between

younger and older women

The prevalence was significantly lower in low educated women than secondary+ (10.8 vs 16.9%)

a b a b

Impact Indicators : Nutritional status

Mothers

0.0 5.0 10.0 15.0 20.0 25.0 2000 2005 2010 2014 Overweight Total Urban Rural 0.0 5.0 10.0 15.0 20.0 25.0 2000 2005 2010 2014 Overweight Total poorest richest

Overweight Prevalence

Diff: 6.1* a Diff: 5.6* a

a b

* * * *

Diff: 11.5* a Diff: 11.5* a

* * * *

In 2014, Urban children are 1.4 significantly more likely to be overweighed than rural children In 2014, Richest children are 2.2 significantly more likely to be overweighed than the poorest children

Older women 35-49yrs old (30.6%) are 11.7 more likely to be over-weighted compared to younger women (<20yrs old: 3.6%)

Impact Indicators : Nutritional status

Mothers Overweight Prevalence

5 10 15 20 25 30 35 less 20yrs old 20-34 yrs 35-49 yrs 2000 2005 2010 2014

a b

+9.6% pt +27%pt between younger and older women : older are 11.7 more likely than youngest

Doubled in 4 years!

a b

The prevalence was significantly higher in low educated women than secondary+ (22.8 vs 14.2%)

a b

Impact Indicators : Nutritional status

10 20 30 40 50 60 2000 2005 2010 2014 % Total Urban Rural

Diff:-9* Diff:-10.6* Diff:-12.7*

a b

In 2014, Rural children are 1.7 significantly more likely to be stunted than urban children

10 20 30 40 50 60 2000 2005 2010 2014 % Total poorest richest

Stunting Prevalence (0-59 months)

a a

Diff:-25.2* Diff:-20.4* Diff:-26.8*

Child

a a

a b

In 2014, Poorest children are 2.7 significantly more likely to be stunted than richest children

* * * * * *

In 2014, there is a significant difference between non educate and secondary+ (37.8% vs 27.1%, p<0.05)

Impact Indicators : Nutritional status

In 2014, Rural children are 1.3 significantly more likely to be wasted than urban children

Wasting Prevalence (0-59 months) Child

In 2014, Poorest children are 1.7 significantly more likely to be wasted than richest children

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 2000 2005 2010 2014 % Total Urban Rural 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 2000 2005 2010 2014 % Total poorest richest

Diff:0.9a Diff:-2.2*a

a a

* *

a a

Diff:-4.3* a Diff:-2.2 a

Impact Indicators : Nutritional status

In 2014, Rural children are 1.7 significantly more likely to be underweighted than urban children

Underweight Prevalence (0-59 months) Child

In 2014, Poorest children are 2.7 significantly more likely to be underweighted than richest children

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 2000 2005 2010 2014 % Total Urban Rural 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 2000 2005 2010 2014 % Total poorest richest

Diff:-9.4* a Diff:-12.4*a

* *

Diff:-16.2* a Diff:-19.3* a

a b a b

Impact Indicators : Nutritional status

Child The multivariate analysis indicated that in the 2014 survey:  The risk of being stunted, wasted and underweight was higher in children who had a low birth weight, a mother with low BMI and belonging to the lowest category of wealth.  Age was a contributing factor for stunting and underweight with higher risk in older children.  Being younger, living in urban settings as well as higher BMI of mother were risk factors for overweight in children.  Being younger, living in rural area, having a mother with low BMI, and belonging to the poorest wealth quintile were associated with anemia.  Wasting and stunting were risk factors of having anemia.

Impact Indicators : Nutritional status

Other inequities Child

Key Variables Gender (Boys vs Girls) in 2014 Trends among gender categories between 2010 and 2014 Stunting No significant difference was

• bserved

The prevalence decreased significantly in both groups (B: 40.2-32.9%; G: 38.1-32.2%) Wasting No significant difference was

• bserved

No significant difference was

• bserved

Underweight No significant difference was

• bserved

The prevalence decreased significantly in both groups (B: 27.3-23.3%; G: 28.9-25.1%) Overweight Significant difference was

• bserved (B: 8.3% vs G: 6.5%)

No significant difference was

• bserved

2014 analysis shows that a boy is 1.3 times more likely to be overweight

Micronutrient status

Micronutrients status of women

Women

CDC/IRD/WFP/UNICEF analysis 2012 data

Vitamin A def.

Low - Medium

• High -

0.6% of the women with VAD (marginal vitamin A status: rural vs urban : 6.5% vs 2.9%, P=0.003)

Not a public health issue

Iron Def.

Low - Medium

• High -

The prevalence of low iron stores status was 8.1% but 37.9% have marginal status.

Mild issue

Mothers

DHS 2014 data

Vitamin A def.

Low - Medium

• High -

3.2% of the mothers with VAD (marginal vitamin A status (rural vs urban : 9.8% vs 8.6%, P=0.05)

Not a public health issue

Zinc Def.

Low - Medium

• High -

62.8% of the mother with zinc deficiencies (rural vs urban: 60.3% vs 72.0%; p<0.01) – severe deficiency: 26.1%

Severe public health issue

Mothers

DHS 2014 data

30.9% of the mothers were considered to be vitamin D deficient (<50 nmol/L) and 4.1% severely deficient

Iodine

Low - Medium

• High -

Median UIC is 63µg/l (IUC rural vs urban: 58 vs 78µg/l; p<0.001)

Severe public health issue

Vitamin D Def.

Low - Medium

• High -

Moderate public health issue

Iron Def.

Low - Medium

• High -

The prevalence of low iron stores status was 2.9%

Not a public health issue

folate Def.

Low - Medium

• High -

17.0% of the mothers were considered folate deficient

Severe public health issue

And 3.3% of mothers surveyed were Vitamin B1 deficient* and an additional 6% marginal

*erythrocyte thiamin<70nmol/l: deficient

Mothers

DHS 2014 data

Anemia

Parasites

Zinc deficiencies Folate deficiencies

Other vitamins and factors

Genetic disorders Iron deficiency

Mother assessed

58% non-anemic

42% anemic

94.8% due to

• ther factors

5.2% due to iron deficiency 2.2% of the mothers assessed were iron deficient anemia +0.7% iron deficient without anemia (see ferritin data) TOTAL iron deficient: 2.9%

Anemia versus Iron Deficiency

Mothers

DHS 2014 data

Anemia

10 20 30 40 50 60 70 Total 2000 2005 2010 2014

a b b b

• 8% points
• 1. In 2014, Rural women are 1.4

significantly more likely to be anemic than urban women

• 2. In 2014, poorest women are 1.8

significantly more likely to be anemic than richest women

Mothers

DHS 2014 data

29.9 28.3 10.2 2.7 28.9

Hemoglobin disorders contribution to overall anemia

Normal Hb pattern HbE heterozygote HbE homozygote HbE_beta thallassemia Beta thalassemia heterozygote Other forms Hb.pathy

Anemia and Hemoglobinopathies

Association of Anemia

Mothers

DHS 2014 data Anemia

Parasites

Zinc deficiencies Folate deficiencies

Other vitamins and factors

Genetic disorders Iron deficiency

Only iron deficiency, and none of the other factors was significantly associated with anemia in the women.

B (95% CI) P Hemoglobinopathy (any) 0.08 (-0.03 - 0.19) 0.16 Inflammation

• 0.06 (-0.17 – 0.05)

0.29 ID (ferritin <15 mg/L) 0.45 (0.14 – 0.76) 0.005 Vitamin A deficiency (<0.70 mmol/L)

• 0.13 (-0.41 – 0.15)

0.36 Zinc deficiency (<9.95)

• 0.01 (-0.11 – 0.10)

0.90 Hookworm infection 0.01 (-0.13 – 0.14) 0.9 Vitamin B12 deficiency (<150 pmol/L)

• 0.15 (-0.64 – 0.34)

0.55 Women

Etiology of Anemia

Mothers

DHS 2014 data Anemia

Parasites

Zinc deficiencies Folate deficiencies

Other vitamins and factors

Genetic disorders Iron deficiency

10 20 30 40 50 60 70 80 90 100

Anemia in women

no anemia anemia

43.6%

24.8% of anemia could be corrected through conventional activities

10 20 30 40 50 60 70 80 90 100 iron deficiency anemia folate deficiency vitamin A deficiency hemoglobinopathy vitamin B12 deficiency unknown

29.4% 45.9% 17.0% 4.8% 2.5% 0.5%

Child

DHS 2014 data (use less 6-24 months only)

MNP targeted population

Vitamin A def.

Low - Medium

• High -

4.4% of the children 6- 23mo with VAD (marginal vitamin A status : 8.9% and no difference between residence)

Not a public health issue

Zinc Def.

Low - Medium

• High -

64.4% of the children 6-23mo with zinc deficiencies (no diff. between residence) – severe deficiency: 24.4%

Severe public health issue

Iodine

Low - Medium

• High -

Median UIC is 72µg/l (IUC rural vs urban: 112 vs 64µg/l; p<0.001)

Severe public health issue Deficiency among children (<50 nmol/L) were detected for 7.3%

• f children aged 6-11mo

and 11.3% for children aged 12-23.9mo

Vitamin D Def.

Low - Medium

• High -

Mild public health issue

Iron Def.

Low - Medium

• High -

The prevalence of IDA was 11.1% for children 6-11mo and 15.2% for 12-23mo

Mild public health issue

+11.4% of children Vitamin B12 deficient and 8.4% of children folate deficient among children 6- 11 months

Micronutrients status of children

Child

DHS 2014 data

Micronutrients status of children

5 10 15 20 25 30 <12months 12-24 months 24-36 months 36-48 months >48months

Vitamin B1 deficiency 8.7% of children 6- 59.9months are thiamin deficient and another 3.4% as marginal

Main source of thiamine animal source food

!

DHS 2014 data

Anemia

Child

50 52 54 56 58 60 62 64 66 Total 2000 2005 2010 2014

a c b c

• 11.7% points
• 1. In 2014, poorest children are 2.3

significantly more likely to be anemic than richest children

• 2. In 2014, Rural children are 1.7

significantly more likely to be anemic than urban children

Child

Anemia

Parasites

Zinc deficiencies Folate deficiencies

Other vitamins and factors

Genetic disorders Iron deficiency

Children assessed

50.9% non- anemic

49.1% anemic

88.4% due to

• ther factors

11.6% due to iron deficiency 5.7% of the children assessed were iron deficient anemia +1.6% iron deficient without anemia (see ferritin data) TOTAL iron deficient: 7.3%

DHS 2014 data

Anemia versus Iron Deficiency

Child

Anemia

Parasites

Zinc deficiencies Folate deficiencies

Other vitamins and factors

Genetic disorders Iron deficiency

DHS 2014 data

10 20 30 40 50 60 70 Not anemic IDA Anemic but not ID

Prevalence of anemia and iron deficiency anemia by age group

6-11mo 12-23mo 24-36mo 36-48mo >48mo

a a a a a a,b b a a a a,b b c c a,c 6-23mo

Anemia versus Iron Deficiency

Child

DHS 2014 data

19.1 27.3 7.2 0.5 1.9 44

Hemoglobinopathy disorders contribution to

• verall anemia

Normal Hb pattern HbE heterozygote HbE homozygote HbE_beta thallassemia Beta thalassemia heterozygote Other forms Hb.pathy

Anemia and Hemoglobinopathies

Anemia

Parasites

Zinc deficiencies Folate deficiencies

Other vitamins and factors

Genetic disorders Iron deficiency

In children, anemia was associated with iron deficiency. Zinc deficiency, hemo-globinopathy, hookworm were also associated with anemia.

Child

DHS 2014 data

B (95% CI) P Hemoglobinopathy (any) 0.16 (0.03 - 0.29) 0.006 Inflammation

• 0.03 (-0.15 – 0.08)

0.56 ID (ferritin <15 mg/L) 0.36 (0.15 - 0.57) 0.001 Vitamin A deficiency (<0.70 mmol/L) 0.01 (- 0.21 – 0.22) 0.94 Zinc deficiency (<9.95) 0.14 (0.03 - 0.26) 0.015 Hookworm infection 0.30 (0.11 – 0.49) 0.003 Vitamin B12 deficiency (<150 pmol/L) 0.12 (-0.25 – 0.49) 0.52 Children

Association of Anemia

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% no anemia anemia

Etiology of Anemia

Child 74.1%

10 20 30 40 50 60 70 80 90 100 iron deficiency anemia folate deficiency vitamin A deficiency hemoglobinopathy vitamin B12 deficiency unknown

49.9% 30.8% 12.1% 1.5% 3.5% 2.2%

19.3% of anemia could be corrected through conventional activities

6-24 months

10 20 30 40 50 60 70 80 90 100 no anemia anemia 10 20 30 40 50 60 70 80 90 100 iron deficiency anemia folate deficiency vitamin A deficiency hemoglobinopathy vitamin B12 deficiency unknown

Etiology of Anemia

Child 52.4%

41.0% 38.0% 8.8% 4.8% 6.3% 1.1%

21% of anemia will be solved through conventional activities

All children 6-59.9 months

Policies and future actions needed

Breastfeeding

• Signif. Urban

decrease Signif. Decrease in wealthiest quintile Increase of Breastmilk substitute promotion Increase of prelacteal feeding practices Limited accreditation tools for health facilities

Stop the decline

• f breastfeeding

Pre-lacteal feeding practices has significantly increased in urban (25.8 vs 50.2) and rural area (17.8 vs 24.2) between 2010 and 2014

Need strong control

As already shown by HKI and WVI, many BMS producers or their wholesalers are breaking the code

Need Enforcement of sub- decree 133

Our actual campaign does not target those population and rural population might mimic the urban mothers in the coming years

Develop new C4D materials

BFHI should be integrated in more health systematic accreditation system

See potential interaction with health partners

Complementary feeding

The actual strategy and Campaign has had limited impact Policy level

• Develop the new

2015-2020 Complementary feeding strategy

• Support legal

framework including sub- decree 133

Adapt current messaging

• Ensure that the

solution proposed are possible to implement (not

• n paper but in

real life)

Monitoring system

• If consistency is

still one of the indicator, we need to have the tools to test the improvement

Management of Acute Malnutrition

No improvement of the prevalence

• f SAM and MAM

Need to update the current guidelines to ensure that more SAM children are treated Need to have a local guidelines for MAM in case that NGOs are willing to work on this targeted population Need to increase the government contribution for the treatment of SAM

Severe Acute Malnutrition

Moderate Acute Malnutrition Increase Monitoring system for OPT and IPT and on- going screening

1 2 3

If any screening ensure that the children is referred if needed Need to test the system

Supplementation and fortification (I)

Data shows the need for MNP and other alternatives

But we need to reduce from 270 sachets to 180 sachets for 18 months (10 sachets a month): UPDATE GUIDELINES

MN P

Strategy 1: Highly subsidized Strategy 2: Market based approach

1

Support the development of innovative snacks to prevent malnutrition and increase micronutrient intakes of young children: Develop BUSINESS MODEL

2 Child

Provide several micronutrient lacking todate: Zc, Iode, B1, vitamin D… Provide several micronutrient BUT also Animal Protein and Energy

Both are complementary

Supplementation and fortification (IIa)

Women

Which supplementation for women?

Pregnant women Women of reproductive Age It is a possibility to increase the number of IFA tablets from 90 to 180 but it has to be a government decision to know if it is a priority intervention

It will be an increased of 500k USD per year

Women weekly Iron Folate could be a solution to prevent folate deficiencies.

If not a government priority, we should look at possibility for social marketing

53

Cost of the inputs

To date If guidelines are adapted 2016-2020: HSP costing Discussion on the government contribution should be engaged to ensure that the potential funds are invested in the most efficient strategies (short and long term impact)

Supplementation and fortification (IIb)

Women

Fish and soy Fortification

More than 37% of the women had marginal iron stores (CDC data)

Folate could be supported by fortification as 17% of the anemia is do to folate

NaFeEDTA in sauces has proven to be an effective strategy for prevention of ID…..not for anemia in Cambodia any more

• 1. Support enforcement
• 2. Promote through media on the benefit for

prevention and not treatment

NEED ATTENTION With our new findings on ID and anemia, we should question the results and the efficiency of several projects promoted in international media.

Supplementation and fortification (III)

Low Median Urinary Concentration among mothers

2

Support MOP, MOI, MOC to: 1. Enforce legislation on iodized salt 2. Update standard according to new WHO guidelines to reduce cost of iodization 3. Promote good behaving industries

3 1

Assess the need of iodized capsule supplement for pregnant women until salt is properly iodized Advocate and monitor the use of iodized salt for the production of local fish and soya sauces

THANK YOU

57