Transcript Low Birth Weight MICS3 Data Analysis and Report Writing Background • Low birth weight carries a range of grave health risks for children.

Low Birth Weight
MICS3 Data Analysis and Report Writing
Background
•
Low birth weight carries a range of grave health
risks for children. Low birthweight babies face a
greatly increased risk of dying during their early
months and years.
•
Those who survive have impaired immune
function and increased risk of disease; are likely
to remain malnourished, with reduced muscle
strength, throughout their lives, and suffer a
higher incidence of diabetes and heart disease
in later life.
Background
•
Children born underweight also tend to have a
lower IQ and cognitive disabilities that affect
their performance in school and their job
opportunities as adults.
International Goals & Targets
Reduction in the rate of low
birth weight by at least
one-third of the current rate
Definition of Indicator
% of infants who weigh
less than 2,500 grams
(2.5 kg) at birth
Numerator:
Number of last live births in the 2 years preceding
the survey weighing below 2,500 grams (2.5 kg)
Denominator:
Total number of last live births in the 2 years
preceding the survey
Methodological Issues
•
Prior to about 1990, estimates of low birth
weight were based primarily on data from health
facilities. These data are often biased.
•
Since about 1990, birth weight information has
been collected systematically from mothers
participating in national HH surveys.
•
Early assessments of survey data showed that
mothers are often unable to provide numerical
birth weights, mostly because they are not
weighed at birth.
Methodological Issues
Percentage of births NOT weighed
100
80
74
65
60
58
60
40
30
21
20
17
0
South Asia
SubSaharan
Africa
Middle East/
North Africa
East Asia/
Pacific
CEE/CIS
Latin America/
Caribbean
Developing
Countries
Methodological Issues
Comparison of births weighed and not weighed
Urban
No education
Secondary education
First births
Delivered with medical
assistance
Delivered in a medical facility
0
20
40
60
Percent
Not weighed
Weighed
80
100
Methodological Issues
Adjustment Procedure
• An adjustment procedure was proposed by Boerma
and colleagues (1996) that uses additional
information on the mother’s assessment of the
child’s size at birth.
• MICS and DHS surveys collect information on
mother’s assessment of birth size. Three questions:
–When [child’s name] was born, was he/she very large, larger
than average, average, smaller than average, or very small?
–Was [child’s name] weighed at birth?
–If yes, what did [child’s name] weigh?
Methodological Issues
Adjustment Procedure
Numerical
birth weight
100% of
survey
sample
Mothers’
assessments
of birth size
Methodological Issues
Heaping of Birth Weight, Tanzania 1999
300
250
Number of births
200
150
100
50
0
1000
1500
2000
2500
3000
3500
4000
Birth weight in grams
4500
5000
5500
6000
Methodological Issues
Effect of Adjustment
18.0
15.6
16.0
14.0
% low birth weight
12.5
12.0
11.2
10.0
8.0
6.0
4.0
2.0
0.0
Unweighted average (62 surveys)
Based on weight only
Adjusted for underreporting
Adjusted for heaping
Methodological Issues
Note that updated
estimates are
available in The
State of the World’s
Children 2006
Methodological Issues
In MICS, 2 items in the questionnaire are
used to estimate low birth weight.
– Mother’s recall of the child’s size at birth
(i.e. very small, smaller than average, larger
than average, very large)
– Mother’s recall of the child’s weight or the
weight recorded on a health card if the child
was weighed at birth
Tabulation Plan
Table NU.8: Low Birth Weight
Methodological Issues
•
Tabulate children’s size by their weight for those
weighed at birth to obtain proportion of births in each
size category who weighed less than 2,500 grams
•
Multiply this proportion by the total number of
children in size category to obtain estimated number
of children by size category with low birth weight
•
Sum the estimated number of children in each size
category with low birth weight in order to obtain the
total number of low birth weight children
•
Divide by the total number of live births to obtain the
percentage with low birth weight
Tabulation Plan
Table NU.8E: Low Birth Weight Estimation
co
un
tri
es
9
lo
pi
ng
IS
ci
fic
EE
/C
ib
be
an
C
ic
a/
Ca
r
a
9
Ea
st
As
ia
/P
a
m
er
14
ev
e
A
Af
ric
15
D
in
er
n
ic
a
ic
a
15
La
t
ou
th
st
/S
fr
Af
r
A
si
a
20
Ea
h
or
t
en
tra
l
st
/N
t/C
Ea
A
40
W
es
M
id
dl
e
So
ut
h
% of infants with low birth weight
Regional Data
Low Birth Weight
100
80
60
31
17
7
0
Low Birthweight (CEE/CIS)
Turkey
Tajikistan
Azerbaijan
Bulgaria
Romania
Kazakhstan
Uzbekistan
Kyrgyzstan
Georgia
Armenia
Turkmenistan
Macedonia TFYR
Russian Federation
Croatia
Ukraine
Moldova, Rep of
Belarus
Serbia/Montenegro
Bosnia/Herzegovina
Albania
16
15
11
10
9
8
7
7
7
7
6
6
6
6
5
5
5
4
4
3
9
CEE/CIS
0
20
40
60
% infants with low birth weight
80
100
A
si
a
20
ut
h
19
So
ta
n
21
Bh
u
22
Pa
ki
st
an
al
22
Ne
p
an
ka
30
Sr
iL
iv
es
al
d
36
M
di
a
sh
40
In
Ba
ng
la
de
% of infants with low birth weight
Low Birthweight (ROSA)
Low Birth Weight
100
80
60
31
15
0
Low Birthweight (TACRO)
Trinidad/Tobago
Haiti
Ecuador
Honduras
Suriname
Nicaragua
Guyana
Guatemala
Peru
DR
Saint Vincent/Grenadines
Panama
Jamaica
Dominica
Brazil
Barbados
Venezuela
Saint Kitts/Nevis
Paraguay
Grenada
Colombia
Uruguay
Saint Lucia
Mexico
Argentina
Antigua/Barbuda
El Salvador
Costa Rica
Bolivia
Bahamas
Cuba
Belize
Chile
23
21
16
14
13
12
12
12
11
11
10
10
10
10
10
10
9
9
9
9
9
8
8
8
8
8
7
7
7
7
6
6
5
Latin America/Caribbean
9
0
20
40
60
% infants with low birth weight
80
100
Low Birthweight (MENA)
Yemen
Sudan
UAE
Iraq
Egypt
Saudi Arabia
Morocco
Qatar
Jordan
OPT
Oman
Bahrain
Tunisia
Libya
Kuwait
Iran
Algeria
Syria
Lebanon
32
31
15
15
12
11
11
10
10
9
8
8
7
7
7
7
7
6
6
Middle East/North Africa
15
0
20
40
60
80
% infants with low birth weight
100
Low Birthweight (EAPRO)
Philippines
Micronesia
Myanmar
Lao PDR
Solomon
Timor-Leste
Marshall
PNG
Cambodia
Fiji
Brunei
Viet Nam
Thailand
Palau
Malaysia
Indonesia
Singapore
Mongolia
Korea, Dem Rep
Vanuatu
Tuvalu
Kiribati
Samoa
Korea, Rep of
China
Cook Islands
Tonga
Niue
20
18
15
14
13
12
12
11
11
10
10
9
9
9
9
9
8
7
7
6
5
5
4
4
4
3
0
0
East Asia/Pacific
7
0
20
40
60
% infants with low birth weight
80
100
Low Birthweight (ESARO)
25
Comoros
Eritrea
Madagascar
Malawi
Burundi
South Africa
Mozambique
Ethiopia
Namibia
Mauritius
Lesotho
Tanzania
Zambia
Uganda
Angola
Zimbabwe
Kenya
Botswana
Swaziland
Rwanda
21
17
16
16
15
15
15
14
14
14
13
12
12
12
11
10
10
9
9
14
East/Southern Africa
0
20
40
60
% infants with low birth weight
80
100
Low Birthweight (WCARO)
Sierra Leone
Mali
Guinea-Bissau
Sao Tome/Principe
Burkina Faso
Togo
Senegal
Gambia
Côte d'Ivoire
Guinea
Ghana
Benin
Nigeria
Gabon
CAR
Niger
Eq. Guinea
Cape Verde
Congo, Dem Rep
Cameroon
Chad
23
23
22
20
19
18
18
17
17
16
16
16
14
14
14
13
13
13
12
11
10
West/Central Africa
15
0
20
40
60
80
% infants with low birth weight
100