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Return to Ch 3 Test Yourself

Question #1:

Given the following data for two districts the prevalence of underweight for the region overall is given in each table for each example.

 

 

Child Population

Prevalence Underweight (%)

# Underweight Children*

District A

200,000

20

40,000

District B

50,000

40

20,000

Region  

24

60,000

* estimate that 20% of child population is underweight.

 

Prevalence Underweight (%)

Total Population (million)

District A

15

2.468

District B

30

1.234

Region

20

 

If you have any questions about how these numbers were calculated, see page 2, Chapter 3

Question #2:

Area Profile

Table 1 gives an overview of the Rift Valley region of Kenya by summarizing some important descriptive statistics. The ratio of female to male children is roughly equal, and the overall prevalence of malnutrition in this region is 20.5%. Compared to average levels of malnutrition of 27.2% (Average 1985 to 1995) for Sub-Saharan Africa, this level of underweight prevalence is below average. The percent of people without access to toilet is not too bad, while the percent with poor roofing (a proxy indicator for SES) is higher. The level respondents with low education is greater than half and literacy rates are not much better. The coverage rate of measles vaccination for children 9 months is not far from the ideal coverage rate of 90%. A very high percentage of people in this region have a health card, whether this means that they take advantage of health services or not is unclear. The percent of women who deliver in a home is fairly high at 62.2%. Only half of the residents of this region have access to a good water source.

Table 1: Rift Valley Area Profile
Descriptive
% Female Child

49.8 (1276)

% Underweight (<-2SDs)

20.5 (806)

Socioeconomic
% Without Toilet/Latrine Access

21.2 (1746)

% With Poor Housing (thatched or other type of roof)

41.6 (1739)

% Illiterate Respondents

44.9 (1750)

% Respondents with Low education (incomplete 1o or none)

64.0 (1754)

Health Services
% Received Measles Vaccine (children >= 9 months)

81.0 (699)

% Respondents With Health Card

94.9 (953)

% Home Delivery Location

62.2 (953)

Environmental Characteristics
% Bad Drinking Water Source (surface or other)

50.1 (1737)

% Bad Household Water Source (surface or other)

50.0 (1749)

% Time to Water Source >30 min

16.9 (1327)

 

Question #3:

By compiling district level area profile data we can rank districts by malnutrition prevalence and then add other indicators to see if they are in line with the malnutrition ranking. Table 2 ranks districts based on malnutrition and compares this with the contribution each area makes to the total number of malnourished. This ranking shows that Kericho and Other rural districts have the highest prevalence of malnutrition in kids under five. It is also important to note that in Nandi, although the prevalence of malnutrition is not among the highest, as this region is the largest (population), it contributes the second highest number of malnourished children and should also be targeted.

 

Table 2: Targeting Districts by Prevalence of Malnutrition
District

Population

# Children <5 years

% Underweight (<-2 SDs)

% of All Malnourished Children

% Received Measles Vaccine

% Without Access to Toilet/Latrine

% Low Education of Mother

Kericho (rural)

322

152

26.3

24.2

88.1

28.3

69.3

Other rural

300

132

25.0

20.0

74.6

36.4

75.0

Uasin Gishu (rural)

315

142

19.7

17.0

81.3

17.6

66.7

Nakuru (rural)

252

125

19.2

14.5

88.2

1.6

56.3

Nandi (rural)

403

204

16.7

20.6

73.8

28.4

67.7

Other urban

162

51

11.8

3.6

85.2

2.0

30.2

Total

1754

806

20.5

99.9

81.0

22.0

64.0

 

Question #4:

Current Program Coverage and Targeting

The current program coverage for several health access variables and education is summarized in Table 5. Table 3 gives the coverage, coverage of the malnourished and focusing over population prevalence for each of these associations. From these results we can see that none of the current programs are particularly well targeted to the malnourished. This is evidenced by the ratio of prevalence in the program to population prevalence being < 1.00. In an ideal situation, where a program is well targeted to the malnourished this ratio would be > 1.00.

It would be smart to look at all current interventions and those that are not targeted to the malnourished should be re-targeted to the worse-off.

 

Table 3: Current Program Coverage and Targeting

Weight for Age Prevalence (<-2SDs of ref. Median)

Health Card
Coverage

0.97

% Malnourished in program

0.98

F/PP

1.00

Tetanus Toxoid
Coverage

0.89

% Malnourished in program

0.85

F/PP

0.96

Measles Vaccination
Coverage

0.81

% Malnourished in program

0.82

F/PP

1.01

Delivery Location
Coverage

0.38

% Malnourished in program

0.27

F/PP

0.70

 

These results are taken from Table 4 which shows the prevalence of underweight receiving or not receiving the program. From that we can calculate the ratio of prevalence among program participants to population prevalence to see how well current programs are targeted.

Table 4: Targeting and Coverage of Current Programs and Interventions
Weight for age Prevalence (<-2 SDs) Weight for age Prevalence (<-2 SDs)
Health Card

Mean

N

# maln

# not maln

Delivery Location

Mean

N

# maln

# not maln

Has health card (pgm)

0.2006

783

157

626

Public or private sector (pgm)

0.1433

307

44

263

No health card (no pgm)

0.1739

23

4

19

Homes or other (no pgm)

0.243

498

121

377

Total

0.2047

806

165

641

Total

0.205

805

165

640

Coverage

0.97

Coverage

0.38

% of malnourished rec. pgm

0.98

% of malnourished rec. pgm

0.27

Focusing

0.20

Focusing

0.14

Population prevalence

0.20

Population prevalence

0.20

F/PP

1.00

F/PP

0.70

Weight for age Prevalence (<-2 SDs) Weight for age Prevalence (<-2 SDs)
Tetanus Toxoid

Mean

N

# maln

# not maln

Measles Vaccine

Mean

N

# maln

# not maln

Rec'd injection (pgm)

0.1972

710

140

570

Rec'd Vaccine (pgm)

0.2485

495

123

372

No injection (no pgm)

0.2697

89

24

65

No Vaccine (no pgm)

0.2348

115

27

88

Total

0.2053

799

164

635

Total

0.2459

610

150

460

Coverage

0.89

Coverage

0.81

% of malnourished rec. pgm

0.85

% of malnourished rec. pgm

0.82

Focusing

0.20

Focusing

0.25

Population prevalence

0.21

Population prevalence

0.25

F/PP

0.96

F/PP

1.01

Question #5:

Associations with Nutritional Status

The one-way analysis looks at the associations between important variables and mean weight for age z score as well as underweight prevalence. This is summarized in Table 4, showing that toilet access, roof (proxy for SES), educational attainment and delivery location are all significantly associated with both mean WAZ and underweight prevalence.

Table 4: One-Way Analysis

Mean WAZ

Underweight Prevalence (%)

n

Toilet Access

p = 0.035

p = 0.025

No access to toilet

-1.11

26.6

177

Access to toilet

-0.87

18.9

626

Difference (b/n worse and best off)

-0.2

7.7

Total

-0.93

20.6

803

Roof

p = 0.000

p = 0.001

Thatched or other roof

-1.12

25.9

359

Corrugated iron or tiles

-0.76

16.3

443

Difference (b/n worse and best off)

-0.4

9.7

Total

-0.92

20.6

802

Drinking water source

p = 0.064

p = 0.292

Surface

-1.00

22.0

396

pub. Tap and well w/o pump

-0.91

21.4

262

piped to res. And well w/ pump

-0.68

15.4

117

Difference (b/n worse and best off)

-0.3

6.6

Total

-0.95

20.8

775

Educational attainment

p = 0.006

p = 0.005

none or incomplete 1o

-1.02

23.5

511

complete 1o or more

-0.76

15.3

295

Difference (b/n worse and best off)

-0.3

8.2

Total

0.92

20.5

806

Delivery location

p = 0.000

p = 0.001

Homes or other

-1.09

24.3

498

Public or private sector

-0.66

14.3

307

Difference (b/n worse and best off)

-0.4

10.0

Total

-0.93

20.5

805