Regional Technical Working Group Meeting on Developing Nutrition

Information Systems

Nairobi, 1-3 Feb 2007

Aims of Nutrition

Information

John B Mason, Tulane SPHTM

Inadequate dietary intake Disease

Malnutrition and death

Inadequate access to food

Inadequate care for mothers and children

Insufficient health services and un- healthy environ-

ment

I na d e q u a t e e d u c a t i o n

Potential resources

Political and ideological superstructure

Economic structure

Formal and non- formal institutions

Outcomes

Immediate causes

Underlying causes

Basic causes

Source: Redrawn from UNICEF, 1990 [39]

Conceptual framework for the causes of malnutrition in society

Surveillance: “to watch over ... to make decisions that will lead to improvements in populations ...”

Data Observation

Decide on action

Take action (‘Implement’)

Monitor Evaluate

Detect new problems

Surveillance cycle

National Trends in Underweight Prevalence

0

5

10

15

20

25

30

35

Date

Prev (%)

Lesotho

Malawi

Mozambique (6Provinces)Zambia

Zambia (S.Prov.)Zimbabwe

Figure 2.1. Trends in national prevalences of children underweight.

0

5

10

15

20

25

30

35

40

45

50

1994 1996 1998 2000 2002 2004 2006

%

Eritrea

Ethiopia

Kenya

Uganda

Note: child ages are 6-59 months for Kenya and Uganda, 3-59 months for Ethiopia, and 0-36 months for Eritrea. Underweight is < - 2SDs by WHO/NCHS standards.

0

5

10

15

20

25

30

35

40

Coast

Eastern

North East

Rift Valley

Area level survey results, Kenya: GAM % by season

0

5

10

15

20

25

30

Area level survey results, pooled & smoothed: Kenya, GAM%, by season

0

5

10

15

20

25

30

Area level survey results, pooled & smoothed: Ethiopia, GAM%, by season

Uses of information can be distinguished into:

• long-term planning and policy-making

• programme monitoring and evaluation

• timely warning to pre-empt and mitigate crises

Usual sources of data are:

• repeated large-scale surveys (e.g. natl, DHS, MICS)

• area level surveys (e.g. 30 by 30)

• reporting systems using data from clinics, screeening, programmes

• sentinels systems, from sites (e.g. clinics) or special surveys

Source

Long-term planning

Program monitoring and evaluation

Timely warning to prevent crises

A. Repeated national surveys

Yes, main use Possible but rare as process data limited and design not ideal

No, too infrequent and too long lag

B. Area level surveys

Not usually, but some potential with further analysis

Possible but rare as process data limited, design not ideal, and external validity may be unclear.

Main use, together with other data (e.g. prices)

C. Reporting systems

Not usually, as less reliable than A.

Potential use for process monitoring if lag can be reduced.

Potential main use if lag can be minimized.

D. Sentinel systems

Potential: e.g. Zimbabwe

Potential for evaluation if carefully designed.

Potentially important use

• Trends give the most useful information

• Note: evaluation only really works with before-after + with-without data

Technical issues for surveys

• sampling procedures

• mortality estimates

• indicators

Sampling procedures

• PPS, then issue is at last stage

• Options: spin-the-bottle; segmentation-full enumeration; segmentation then sample

• Consider bias; re-estimating pop numbers (for weights)

• Depends on feasibility (incl. habitation features: e.g. along road/river vs round); and use

• Compare results with norms, use for targeting, get trends

Child mortality estimates from area level surveys

Issues are

• Estimate and state confidence intervals, which will be wide with 30*30 design, and calculate design effect

• Care in interpreting these -- e.g. what does 0.5-2.0/10,000/day over last 3 months mean?

Indicators

• Malnutrition can worsen without showing in wasting -- see Srn Africa 02-3: use wt/age if possible

• Evidence suggests: interpret wasting WITHIN populations, not across, because of different growth patterns and relations to mortality

• More focus on getting ages?

Kenya

0

5

10

15

20

25

30

35

40

K: NE K: Nyanza

Pre

vale

nce

%

Stunting

Wasting

Underweight

Differences in stunting and wasting in two regions of Kenya

0

10

20

30

40

50

60

m0-6 m6-12 m12-24

m24-36

m36-48

m48-60

Age group

%

Somalia-W

Somalia-St

Uganda-W

Uganda-St

Differential growth patterns in Uganda and Somalia

Low birth weight, %

Maternal mortality

ratio

Prevalence BMI <18.5 in women

Kenya 11% 1000 12%

Uganda 12% 880 9%

Ethiopia 15% 850 26%

Somalia 16% 1100 -

Eritrea 21% 630 41%

Sudan 31% 590 -

India 30% 540 41%

Maternal and new born data

Birth weight relates to maternal BMI, but that is not directly related to MMR as indicator of health care ...

overall GAM Prevalence

50403020100

U5M

R2

7

6

5

4

3

2

1

0

- 1

Country Code

Uganda

Ethiopia

Sudan

Somalia

Kenya

Mortality

Different relations between GAM% and child mortality in different populations

Hence interpret GAM within populations, not across ...

Nutrition Surveillance Information Flow & Decision Making Process

Sentinel sites Data Collection, Decision-Making

Food & Nutrition Sub-Division MHSS

Data entry, Analysis and Reporting

Monthly Nutrition and Health Data

MHSS

Review Reports & Make Decisions

VAC

Prepare Food Security & Nutrition Bulletin and Make Recommendations for Action

Nutrition Surveillance Bulletin

Internal Nutrition Surveillance Report

National Emergency Management

Committee

Review VAC Recommendations & Decision-Making

Decisions for MHSS Action/Intervention

EMU, Line Ministries, UN, NGOs, Donors

Intervention

Food Secu./ Nut. Bulletin & Recommendations

Decisions for Intervention

Regions (MHSS, REMU) Decision-making

District (MHSS) Decision-making

Internal Nut. Surveillance Report

Internal Nut. Surveillance Report

Internal Nut. Surveillance Report

System/ Data source

Eth

Ken

Som

Uga

Bots

Les

Mal

Moz

Nam

S A

Zam

Zim

A. Repeated natl surveys (# 90 on)

Y (6 )

Y (4)

?

Y (2)

Y (1)

Y (3)

Y (4)

Y (3)

Y (2)

?

Y (3)

Y (4)

B. Area level Surveys (ad hoc) # 2000 on

399

163

107

100

-

-

2/~30

N

-

2/32

N

C. Reporting systems Clinics

(Y) Chanis

Thru HMIS

Y (food distrn points)

Y?

Selected clinics

Proposed

Thru DHIS

Screening

EOS twice yrly

Progs CBNP D. Sentinel Systems

Survey

F-up asst surveys

ALRMP In FSAU Y

Site

Proposed

In FSAU Proposed

Fitting systems together and deciding priorities

Capacity

• Enough people?

• Is this useful for them?

• Needed skills?

• Resources and priorities?

• How to meet these needs…?