1

Housing Correlates of Under-Five1 Mortality in Urban Ethiopia:

A Paper Presented at the XXVII IUSSP International Conference,

Busan , Korea, 26-31 August 2013

By: Hadgu Bariagaber (Ph.D/Associate Professor), University of Botswana ,

Faculty of social Sciences, Department of Population Studies, P/Bag UB

00705, Block 240, Office 241 : e-mail: hadgub84@gmail.com

Tel:(267) 355-2713, Mobile: 771-63-693

Abstract:

Little studies have been done to investigate the housing determinants of under-five mortality,

despite the fact that Ethiopia has collected abundant empirical housing data from the previous

national population and housing censuses (1984,1994 and 2007) and DHS studies (2000, 2005

and 2011 surveys).This is, therefore, to explore the extent of impacts of urban housing variables(

housing situations and facilities) on under-five mortality rates in consonance with MDG2

objectives and prepare some recommendations for awareness of the urban health planners of the

country in line with the perspectives of 2015 worldwide MDG.

The SPSS file of the 2005 Ethiopian Demographic and Health Survey covered a sample of

about 4420 households/housing units of urban Ethiopia, The number of children ever born and

living were collected based on the questionnaire “birth histories ” of the women in the age group

15-49. The number of under-five deaths is compiled by the author by subtracting the number of

children living from the everborn children and established the proportion dead by dividing deaths

by children everborn. The rationale and motivation of the Author is, therefore, to know how

housing components determine the quality of urban life through the health status of under-five

children.

The analytical techniques of the study are proposed to included simple descriptive frequency

distributions of univariate and bivariate cross tabulations as well as multivariate data analysis of

the proportional variations of childhood mortality patterns with respect to housing situations (

types of wall, roofing, floor, ceiling etc) and housing facilities ( toilet, water, bathing etc) as well

as household durables, namely communication media such as radio, telephone and TV.

Key Words: urbanization, primate city, urbanstructure/services, correlates, under-five

mortality, housing situation, housing facilities, household durables, frequency descriptive

statistics (univariate and bivariate) and proportions of multivariate data analysis.

1 Under-five: It is a summation consisting of Neonatal,(NN), Post-neonatal (PNN), Infant

and child mortality lrvel. 2 MDG: Goals 4 and 7( child mortality and environmental/urbanization) .

2

I. Introduction

1.1 Demographic Background of Ethiopia:

Ethiopia has so far undertaken three modern National Population and Housing Censuses. The

first census ever taken was in 1984, followed by 1994 and 2007, respectively. In terms

population size, the country stands second to Nigeria in the African continent. Summary of some

salient demographic features of the country are presented in Table 1.1.1

Table-1.1.1:Summary of Basic Demographic Indicators of Ethiopia:

Variables Basic demographic indicators corresponding to

Census Dates

1984 1994 2007

Population (million) 42.6 53.5 73.8

Level of urbanization (%) 11.4 13.7 16.1

Pop Growth Rate(%) 3.1 2.9 2.6

Total Fertility Rate (TFR) 6.5 6.0 5.5

Sex Ratio at Birth 104.0 103.0 103.0

Child mortality parameters

Demographic and Health Surveys (DHS)

2000 2005 2011

Infant Mortality Rate 97 77 59

Under-Five Mortality 166 123 88

Childhood Mortality 77 50 31

Life Expectancy: Male

Female

51.1

53.4

50.9

53.5

56.3

58.5

Source: (1) Compiled from 1984, 1994 and 2007 Population and Housing Census Reports

(2) Compiled from the 2000,2005 and 2011 Ethiopian Demographic and Health

Surveys (EDHS)

With the future prospective decline in mortality, particularly infant and childhood mortality

levels, patterns and trends (refer to Table 1.1.1), accompanied by probably persistent still high

fertility, the high population growth rate of Ethiopia would still remain to be worrisome to

planners of all development sectors and politicians of the country in the years to come.

For example, taking an average growth rate of 2.6 percent, the population is estimated to reach

about 86.3 million in 2013. Furthermore, if we assume a growth rate of 2.6% to persist for the

years to come, the population of the country could double itself in a matter of about every 27

years. This means that the population of Ethiopia would be about 147.6 million by the year 2031,

calling for all environmental, social and economic developmental efforts and relevant policy

actions to decrease the population growth and accelerate the socio-economic conditions in order

at least keep pace with the rapid population growth.

3

1.2 Preview of Urbanization and its problems in Sub-Saharan Africa

with Reference to Ethiopia:

Rural/urban distinction in many sub-Saharan African Countries has always been ambiguous. The

definition and delineation of urban from rural environment vary from country to country and

even from census to census of the same country.

In the majority of sub-Saharan countries, a minimum concentration of non-agricultural

population with 2000 and over inhabitants has generally been accepted as an urban locality.

Exceptions are Nigeria (with 20,000 and over), Ghana (with 5000 and over), Gabon and Tunisia

(with 1000 and over), Egypt (all administrative governorate centres regardless of population

size) and South Africa (with 500 and over non-agricultural settlements).

At International level, there are five main definitional and conceptual criteria, as follows:

Proper “urban population”, with 20,000 and over inhabitants;

“Metropolis”, with 50,000 and over ;

“City population”, with 100,000 and over ;

“Big city population”, with 500,000 and over; and

“Megalopolis”, with 10 million and over population.

The rationale of the minimum definition of 20,000 and over population is that in such

agglomeration of population, it is believed that there could be minimum agricultural activities,

more heterogeneous in ethnic composition, cultural diversity and multi-urban functional

variations such as demographic structure, social, economic, and political organizations,

lifestyles, values, perceptions and expectations, which all have been different from rural

hinterlands.

Even taking the minimum of 2000 and over, the size of urban population out of the national

population in each Sub-Saharan African country has been extremely low, ranging from as low as

10-22 percent for East and 25-33 percent for Middle Africa, with Ethiopia having had recorded

ranging from about 9 percent in 1970’s to about 16 percent as of the 2007 population and

housing census results out of the Total National Population(UN 1994, UNECA 1995, Ethiopia

1994 and 2007).

Contrary to the low level of urbanization , particularly for Ethiopia, the urban population growth

rate has been the highest in the world, ranging from 4.7 percent for Southern Africa to 5.6

percent for Eastern Sub-Region, giving about 5.3 percent for Sub-Saharan Africa, about 5

percent and 4 percent for Ethiopia urban sector and Addis Abeba city annual growth rate ,

respectively (UNECA 1995; Ethiopia 1984/1994//2007 population and housing censuses).

Besides being a low level of urbanization, the concentration of urbanization in one or two urban

area(s) in the African Continent has been worrisome. As observed by Sokona (1985) and

Sovani,N.V.(1964), the concentration of the urban population in a capital city, like Dakar in

4

Senegal, Bamako in Mali, Nairobi in Kenya etc., has been common characteristics in many other

Sub-Saharan African countries. As rightly stated by Hamden (1964), these concentration and

centralization of power and resources in a few urban settlements have been true since the

colonial and postcolonial era of the continent of Africa where the political capitals were emerged

by either being historical native significance or due to the colonial and postcolonial

administrative and economic phenomena, growing rapidly with all concomitant urbanization

problems, including housing situations and facilities.

Accordingly, UN(1976; ,1985,1986,1988) noted that adequate shelter, potable water and decent

sanitary facilities have been deplorably lacking and unhealthy overcrowding of accommodation

were apparently large cities emerged in many developing countries. For example, a study by

the UN in the late 1970’s showed that 50 percent of households in Calcutta, 33 percent in

Mexico city, 60 percent in Accra (Ghana) and about 50 percent in Monrovia (Liberia) of the

urban population were living in slum/squatter settlements and 35 percent of all urban localities

in Sub-Saharan Africa were living in overcrowded single–room houses (UN,!974, 1975).

The case of Ethiopia has not been an exception where Addis Abeba has already become a

primate city, having similar urban primacy characteristics of many developing countries. It is

the National Capital, has become the leading primate city with all the privileges of

concentration of national investments, allocation of skilled human resources and being given

the national and international political attention, but still been experiencing all urban problems,

including housing (Ethiopian urbanization issues by different Authors, 1980-2000).

1.3 Source of Data:

In order to keep abreast with timely data requirements for short and long term development

planning, the Central Statistical Agency (CSA) of Ethiopia has been conducting series of

Demographic Sample Surveys in order to fill the intercensal gaps in population composition and

population dynamics. Among the demographic sample surveys include conducting series of

demographic and health surveys (DHS) with special reference to the incidence and prevalence of

HIV/AIDS pandemic and other opportunistic diseases such as Sexually Transmitted Infections

(STI’s) ,TB’s, and other non-HIV infectious diseases (EDHS: 2000,2005 and 2011).

However, the source of data of the study is the SPSS Data File of the 2005EDHS. The output of

this survey is found to be unique from other EDHS in that it covered about 14,000 women in the

productive and reproductive age segment of 15-49, for all classifications of urban setting in the

country with corresponding data on children everborn and surviving for each woman in the age

group 15-49. From the retrospective data of children evereborn (CEB) and surviving, the author

was able to construct the corresponding number of children dead, forming proportion of dead by

dividing number of children dead by corresponding CEB’s, covering 4420 households/housing

units (housing situation/structure: types of wall, floor, roof etc), housing facilities ( water, toilet,

kitchen etc) and housing communication (durables such as radio, telephone and TV).

5

1.4 Problem Statement:

There had been persistent high mortality condition in Sub-Saharan Africa in general and

Ethiopia in particular and this trend could be conjectured to continue for some decades before

coming down to acceptable levels. The main reasons could be noted to be largely due to the

widespread poverty conditions and low level of health services in urban/rural Sub-Saharan

Africa. In particular, it had been apparent that persistently high infant mortality induces high

fertility level, for women tend to increase their fertility performance in order to compensate the

loss of high infant mortality, which is termed as “ replacement effects”.

The reciprocal relationship between high infant mortality and high fertility levels has been such

that fertility tends to be superior to the level of infant mortality and follows by relatively high

survivors which results again having a youthful population, leading to high dependency ratio

(burden) on the productive. Eventually, the increase in the reproductive segments of the

population as well as producing high growth potentials, would subsequently result in significant

detrimental effects on developmental endeavours, aggravating poverty with concomitant effect

on health service provisions.

1.5 The Setting up of the Study:

1.5.1 Rationale of the Study: Little analysis has been done on the housing determinants of infant and childhood mortality,

despite the fact that Ethiopia has collected abundant empirical housing data from the previous

national population and housing censuses (1984,1994 and 2007) and EDHS studies (2000, 2005

and 2011 surveys).

1.5.2 Objective of the Study:

The focus of this paper is unique in the sense that examination of the variations of childhood

mortality are going to be explored in the urban structure of Ethiopia with respect to housing

characteristics, namely, housing situation, facilities and household durables using the SPSS Data

files of 2005 EDHS, which covered, among other data of interest, a sample of about 4400

households/ housing units.

1.5.3 Organization of the Study:

The study is organized under three main analytical levels , namely, frequency distribution of

housing situation and housing facilities along their respective categorical variables and

examination of the impact of housing categorical variables on under-five child mortality.

1.5.4 The Study Areas: With respect to area coverage, the study considers all urban areas of Ethiopia, being designed

and classified in the 2005EDHS questionnaire by the Central Statistical Agency of Ethiopia, as

follows:

Addis Abeba, the capital city of the country, with over 4 million population;

Large cities with population size of 100,000 and above;

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Medium cities with population size between 50,000 to 100,000.

Small Town with population size between2000 to 49,999.

Sub city which meets the administrative function or sub-division of an urban locality/

Kebele administration or Urban district/ Wereda with population size between 1000 to

1999.

1.6. Methodological Issues:

1.6.1 General Conceptual Framework:

Housing conditions are covariates of the level of living conditions which influence the status of

mortality in general and infant and childhood mortality in particular. A simplified web is hereby

presented in Figure-1, demonstrating the complex reciprocal interaction among Socio-economic,

housing, demographic variables and general mortality conditions. In-built in the general

mortality box, we conceptualize the levels and patterns of infant and childhood mortality in

relation to the housing variables.

Fig-1: Conceptual framework manifesting the antecedent and proximate

determinant of Infant and Childhood mortality

The housing conditions, therefore, can reflect the levels of the living conditions and also

indirectly influence the status of mortality in general and infant and childhood mortality in

particular.

1.6.2)Analytical Methods of the Study: The analytical methods would be done at three stages:

(i) univariate; (ii) bivariate and (iii) multivariate data analysis. Simple descriptive and

proportionality of variation among the categories of each housing characteristic (for example,

type of floor, toilet facility etc.) with respect to relative infant and childhood mortality level be

applied where the univariate and bivariate analysis would deal with the types, levels and

characteristics of urban services whereas the latter would focus on the housing determinants of

infant and childhood mortality levels and patterns. From the analysis, we would be able to

identify the most critical categorical variables of the housing situations, housing facilities and

household service durables which would likely appear influence childhood mortality.

Socio-economic

variables

Housing Variables

:Proximate Variables

Childhood

Mortality

Demographic

Variables

7

II. Housing Situation and Housing Facilities in Urban Ethiopia:

2.1 General Housing Situation and Facility of Addis Abeba:

As presented in Table-2.1.1, despite the fact that Addis Abeba has been receiving the lion’s

share of the national human and material resources, the city has been characterized by a number

unhealthy conditions,:

Table-2.1.1:Summary indicators of housing facilities and situations, Addis Abeba

Housing Facility: Percent out

of total

Housing situation: Percent out

of total

Kitchen facility:

Traditional

modern

Rooms used as kitchen

No kitchen

67.8

6.0

46.9

26.2

Wood/mud /thatched walls

Floor of earth/mud

Cooking: fire wood/ dung

using kerosene for lighting

Renting households

84.4

53-56

53.4

10.3

60.6

Water supply:

Private tap

No bathing

Using well/river/spring

27-29

85.8

19-22

Overcrowding Indicators:

3+ persons per room

Doubled up households

41.7

19.3

Toilet facility:

Flush toilet:

Dry pits

No toilets

12.0

73-77

24-30

Source: Compiled from different data sources: (i) 1990 HFF; 1994 Population and Housing

Census (ii) 1998 and 2000 EDHS

In order to upgrade and renew the existing situation of the city to acceptable standard, it calls for

huge human and material resources. On top of that, the city’s population has been growing

rapidly due to rural and other urban migration which would compound the city’s problems.

2.2 Frequency Distribution of Housing Structure of Urban Ethiopia:

The housing situations of urban Ethiopia, expressed in terms of the quality of types of wall ,

floor and roofing, are summarized in Tables 2.2.1, -2.2.2 and 2.2.3, respectively

As shown in Table-2,2,1, more than 60 percent of the walls of the houses in urban Ethiopia are

made of bamboo trees or woods with mud. With respect to types of flooring, Table 2.2,2

manifests that exhibits that about 32 percent and 24 percent are made of Vinyl (plastic tiles) and

either cements or bricks. Regarding roofing materials, more than 90 percent of the houses are

covered by corrugated iron sheets.

8

Table-2.2.1: Summary of Housing situations by Urban Classifications:

Housing Structure

Classification of urban areas

Capital,

large city

Medium

city

Small

Town Column

Total (%)

Types of

Wall

Modern 22.8 46.2 15.6 30.2

Bamboo /wood/ mud 69.8 45.3 74.6 61.5

Others 7.4 8.5 9.8 8.3

Total 100.0(1812) 100.0(1663) 100.0(948) 4423

Row total (%) 41.0 37.6 21.4 100.0

Types of

Floor

Vinyl/ cement bricks 67.9 66.2 26.3 58.4

Carpet/earth/dung 27.3 30.3 71.0 37.7

Others 4.8 3.5 2.7 3.9

Total 100.0(1812) 100.0(1663) 100.0(948) 4423

Row total (%) 41.0 37.6 21.4 100.0

Types of

Roof

Corrugated iron sheets 94.3 92.5 75.7 88.8

Thatch / leaf/reed/ 0.4 2.5 15.9 5.1

Others 5.3 4.9 8.4 6.1

Total 100.0(1812) 100.0(1660) 100.0(948) 4420

Row total (%) 41.0 37.6 21.4 100.0

2.3 Frequency Distribution of Housing Facilities:

The percentage distributions of availability of water , toilets, cooking facilities and types of

lightning are presented in Tables 2.3.1 to 2.3.5. From these Tables, we can observe that urban

Ethiopia has generally been facilitated by poor water supply, unhealthy toilet facility,

environmentally unacceptable cooking materials and very traditional household lightnings.

9

Table-2.3.1 Summary of frequency distribution of Housing Facilities

Housing facilities

Classification of urban areas

Capital,

large city

Medium

city

Small

Town

Column

Total %

Types

of

Water

Supply

Pipe in dwelling /compound 71.0 49.0 25.3 51.1

Pipe outside compound 24.0 43.6 42.8 36.9

Unprotected well / spring 5.0 7.4 31.9 12.0

Total 100.0(1812) 100.0(1663) 100.0(948) 4423

Row Total (%) 41.0 37.6 21.4 100.0

Type of

toilet

facility

Pit latrine with open pit 69.3 75.0 69.3 71.5

Flush to sewer / septic tank 19.7 8.5 6.5 12.8

Others ( bucket, bush etc) 11.0 3.5 24.2 15.7

Total 100.0(1812) 100.0(1663) 100.0(948) 4423

Row total (%) 41.0 37.6 21.4 100.0

Toilet

facilities

shared

No 34.1 42.9 53.3 43.0

Yes 60.7 53.3 43.5 57.5

Not de jure 5.1 3.8 3.2 4.5

Total 100.0 (1755) 100.0(1531) 100.0(758) 100.0(4044)

Row total (%) 43.4 37.9 18.7 100.0

Cooking

Fuel

Kerosene 69.0 29.9 4.2 40.5

Firewood/straw/Charcoal 21.2 60.7 92.1 51.3

Other (elect+ natural gas..) 9.8 9.4 3.7 8.2

Total 100.0(1812) 100.0(1663) 100.0(944) 4419

Row Total (%) 41.0 37.6 21.4 100.0

Has

electrici

ty

No 2.6 1.9 31.8 8.7

Yes 92.4 94.6 65.7 87.2

Other 5.0 3.5 2.5 4.1

Total 100.0(1812) 100.0(1663) 100.0(948) 100.0(4423)

Row Total (%) 41.0 37.6 21.4 100.0

3.4 Communication facilities-durables:

The types of household communication durables are summarized in Table 3.4.1. While about 83

percent of the total urban household own radios, the case of small urban localities has been still

low where about 68 percent of the household own radios.

10

Regarding the availability of household TV, although about 51 percent of the total own TV, it is

only about 17 percent of the households in small towns appear to have access to national TV

media. The households’ access to Telephone ownership is also deplorably low where about

only 41 percent of urban Ethiopia could own individual household telephone apparatus.

Table-3.4.1: Availability of Radio, Telephone and TV in the Households ::

Household Durables

Classification of urban areas

Capital, large

city

Medium

city

Small

Town Column

Total (%)

Has Radio

No 6.5 12.1 29.7 13.6

Yes 88.5 84.4 67.7 82.5

Not de jure 5.0 3.5 2.5 3.9

Total 100.0(1812) 100.0(1663) 100.0(948) 4423

Row Total %) 41.0 37.6 21.4 100.0

Has

Television

No 28.0 43.3 80.2 44.9

Yes 67.0 53.2 17.3 51.2

Not de jure 5.0 3.5 2.5 3.9

Total 100.0(1812) 100.0(1663) 100.0(948) 4423

Row total (%) 41.0 37.6 21.4 100.0

Has

Telephone

No 38.1 58.9 83.0 55.5

Yes 57.0 37.7 14.5 40.6

Not de jure nt 5.0 3.5 2.5 3.9

Total 100.0(1812) 100.0(1660) 100.0(948) 4420

Row total (%) 41.0 37.6 21.4 100.0

III. Impact of Housing Variables on Under-Five Mortality

Mortality is one of the components of the demographic dynamics. It plays important role in the

determination of population growth and demographic transition concept3, for it is the outcome

of the interplay among various biological , environmental, economic and socio-cultural factors.

This section, therefore, deals with the influence of housing conditions on the mortality levels of

under-five children of urban Ethiopia. From the SPSS data file of 2005 EDHS, the proportions

of children dead are computed from the difference between children everborn and children

living, controlled for urban areas, housing conditions and establish proportion of dead against

the categorical variables of housing situation, facilities and household durables under sections-

3.1, 3.2 and 3.4 , respectively . The details are shown in tabular forms in the subsequent different

tables.

3 The demographic Transition Theory :

11

3.1 Impact of Housing Structure on Under-Five Mortality Level:

This sub-section examines the correlates of the housing situation, comprising mainly the material

of construction of walls, floor and roofing of under-five childhood mortality of urban Ethiopia.

The results are summarized in the following Tables and with their respective graphical

representations.

Table-3.1.1: construction material of floors

Types of Floor

CEB

Total Alive

Deaths

(absolute)

Proportion

dead

Earth / sand 1977 1684 293 0.1482

Animal Dung 494 409 85 0.1721

Wood planks/reed 90 85 7 0.0778

polished wood 204 193 11 0.0539

Vinyl 1998 1773 225 0.1126

Ceramic tiles 124 118 6 0.0484

Cement / bricks 1457 1324 133 0.0913

Carpet 252 225 27 0.1071

Not dejure resident 158 137 21 0.1329

Total 6754 5948 808 0.1196

0.1482

0.1721

0.0778

0.0539

0.1126

0.0484

0.0913 0.1071

0.1329

0.0000 0.0200 0.0400 0.0600 0.0800 0.1000 0.1200 0.1400 0.1600 0.1800 0.2000

Pro

po

rtio

n d

ead

Type of floor

Proportion Dead By Type Of Floor

12

Table-3.1.2 construction material of wall:

Wall Material

CEB

Alive

Dead

(absolute)

Proportion

dead

Unconventional walls 433 293 140 0.3233

Bamboo / wood with mud 4404 3853 551 0.1251

Stone with mud 630 552 78 0.1238

Cement 177 159 18 0.1017

Stone with lime / cement 435 395 40 0.0920

Cement blocks 622 568 54 0.0868

Not dejure resident 158 137 21 0.1329

Total 6859 5957 902 0.1315

0.3233

0.1251 0.1238 0.1017 0.0920 0.0868

0.1329

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

0.3000

0.3500

Pro

port

ion

dea

d

Type of wall

Proportion Dead By Type Of Wall

13

Table-3.1.3 construction material of roofing

3.2. Impact of Housing Facilities on Under-Five Mortality:

The housing facilities under this sub-section include water supply, toilets, Cooking Fuel

and power.

0.1902

0.2461

0.1266 0.1146

0.0000

0.1329

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

0.3000

Pro

port

ion

Dea

d

Type of Roof

Proportion Dead By Type Of Roof

Roofing material

CEB

Alive

Dead

(absolute)

Proportion

dead

Unconventional roofing 184 149 35 0.1902

Thatch / leaf / reed 447 337 110 0.2461

Wood planks 79 69 10 0.1266

Corrugated iron 5915 5237 678 0.1146

Cement / concrete 21 21 0 0.0000

Not dejure resident 158 137 21 0.1329

Total 6804 5950 854 0.1255

14

Table-3.2.1 water supply

Source of drinking water

CEB

Alive

Dead

(absolute)

Proportion

dead

Piped in dwelling 145 130 15 0.1034

Piped into compound 2712 2485 227 0.0837

Piped outside compound 2878 2457 421 0.1463

Unprotected well/ spring 438 372 66 0.1507

Protected well / spring 428 369 59 0.1379

Not dejure resident 158 137 21 0.1329

Total 6759 5950 809 0.1197

0.1034

0.0837

0.1463 0.1507 0.1379 0.1329

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

0.1600

Pro

po

rtio

n D

ead

Water Supply

Proportion Dead By Water Supply Facility

15

Table-3.2.1 Toilet Facility

Type of toilet facility

CEB

Alive

Dead

(absolute)

proportion

dead

Flush to sewer / septic tank 166 160 6 0.0361

Flush to pit latrine 175 157 18 0.1029

Ventilated improved pit latrine 314 275 39 0.1242

Pit latrine with slab 2840 2549 291 0.1025

Pit latrine without slab / open pit 1971 1719 252 0.1279

Composting toilet 228 196 32 0.1404

Bucket toilet 36 28 8 0.2222

No facility / bush / field 871 729 142 0.1630

Not de jure resident 158 137 21 0.1329

Total 6759 5950 809 0.1197

0.0361

0.1029

0.1242

0.1025

0.1279 0.1404

0.2222

0.1630

0.1329

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

Pro

port

ion

Dea

d

Type of Toilet Facilty

Proportion Dead By Toilet Facility

16

Table- 3.2.2 Toilet sharing facility

Toilet facility shared CEB Alive dead (absolute) proportion dead

No 2682 2408 274 0.1022

Yes 3052 2679 373 0.1222

Not dejure resident 158 137 21 0.1329

Total 5892 5224 668 0.1134

Table 3.2.3 Cooking Fuel

Type of cooking fuel

CEB

Alive

Dead

(absolute)

proportion

dead

Electricity 82 77 5 0.0610

LPG, natural gas 84 81 3 0.0357

Kerosene 2083 1891 192 0.0922

Charcoal 1191 1065 126 0.1058

Firewood, straw 3102 2651 451 0.1454

Animal Dung 57 47 10 0.1754

Not dejure member 158 137 21 0.1329

Total 6757 5949 808 0.1196

0.1022

0.1222

0.1329

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

No Yes Not dejure resident

Pro

port

ion

Dea

d

Shared Toilet

Proportion Dead y Toilet Facility Sharing

17

Table- 3.2.4 Type of lighting

Has electricity

CEB

Alive

Dead

(absolute)

Proportion

dead

No 1058 878 180 0.1701

Yes 5543 4935 608 0.1097

Not dejure resident 158 137 21 0.1329

Total 6759 5950 809 0.1197

0.0610

0.0357

0.0922 0.1058

0.1454

0.1754

0.1329

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

0.1600

0.1800

0.2000

Pro

port

ion

Dea

d

Cooking Fuel

Proportion Dead By Type Of Cooking Fuel

18

3.3 Impact of Housing Durables on Under-Five Mortality:

Table-3.3.1 Under-five mortality variations with respect to radio availability in a

household:

Has Radio

CEB

Alive

Dead

(absolute)

Proportion

dead

No 1382 1144 238 0.1722

Yes 5219 4669 550 0.1054

Not dejure resident 158 137 21 0.1329

Total 6759 5950 809 0.1197

0.1701

0.1097

0.1329

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

0.1600

0.1800

No Yes Not dejure resident

Pro

port

ion

Dea

d

Availability of Electricity

Proportion Dead By Availability of Electric Lighting

19

Table-3.3.2 Under-five mortality variations with respect to telephone availability in a

household:

Has telephone

CEB

Alive

Dead

(absolute)

Proportion

dead

No 4321 3708 613 0.1419

Yes 2274 2100 174 0.0765

Not dejure resident 158 137 21 0.1329

Total 6753 5945 808 0.1197

0.1722

0.1054

0.1329

0.0000

0.0500

0.1000

0.1500

0.2000

No Yes Not dejure resident

Pro

port

ion

Dea

d

Radio Availability

Proportion Dead By Radio Availability

20

Table-3.3.3 Under-five mortality variations with respect to TV availability in a

household:

Has TV CEB Alive

Dead

(absolute)

Proportion

dead

No 3697 3143 554 0.1499

Yes 2904 2670 234 0.0806

Not dejure resident 158 137 21 0.1329

Total 6759 5950 809 0.1197

0.1419

0.0765

0.1329

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

0.1600

No Yes Not dejure resident

Pro

port

ion

Dea

d

Telephone Availabity

Proportion Dead By Telephone Availability

21

IV Summary, Conclusion and Recommendations:

4.1 Summary and Conclusion of the frequency distribution Tables:

The frequency distribution Tables of the housing structure, facilities and household durables can

be summarized as follows:

most of the materials of floor are made of Carpet/earth/dung (specially with small

towns) which are full of dusts, detrimental to child health;

material construction of walls are mostly bamboos/woods/mud in all urban

areas;

materials for roofing are mostly corrugated iron sheets, though some thatched

/leave/reed roofs in small towns

water supply facilities are mostly outside compound, being shared among households

but unprotected well/spring, specially in small towns;

toilets are mostly shared pit latrine, use of buckets and bush:

cooking facilities are kerosene, firewood straw, charcoal

power is available with significant coverage in big and medium cities but about only

one-third of households in small towns have electric power;.

durables: availability of radio is significantly high in large, but having low proportions

in telephone and TV in medium and very low in small towns.

In general, from the frequency distribution tables of the housing situation, facilities, and

household communication durables, we can conclude as follows:

0.1499

0.0806

0.1329

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

0.1600

No Yes Not dejure resident

Pro

port

ion

Dea

d

Television Availability

Proportion Dead By Television Availability

22

Prevalence of deplorable housing shortages, poor environmental sanitation, unhealthy

overcrowding in terms of person/room ratios;

Congestion with high rate of household tenancy and unacceptable waste disposal

practices

, unhealthy housing conditions with doubled up households, sharing the same facilities;

inadequate and qualitatively inefficient water supply system;

sub-standard unacceptable toilet facilities; and

serious lack of modern kitchen facilities associated with poor cooking fuel facilities.

4.2 Summary of the analysis of housing correlation of proportion of infant and

childhood mortality levels:

Among the categorical variables of the housing structures, facilities and household

durables, which manifested highest proportions of the prevalence of proportion of under-five

mortality levels, are summarized in the following Table:

Housing Characteristics Highest proportion

Dead

Housing Structure:

Floor: animal dung---------------------------

Wall: unconventional material------------ l

Roofing: thatched leave/reed--------------

0.1721

0.3233

0.2461

Housing Facilities:

Water: Unprotected well/spring--------------

Toilet: shared pit latrine, use of bucket/ bush

Lightning: no electric power: ---------------

Cooking: kerosene, fire wood/straw, charcoal

0.1507

0.2222

0.17o1

0.1754

Household Durables:

No household radio----------------------------

No household telephone----------------------

No household TV-----------------------------

0.1722

0.1419

0.1499

4.3 Recommendation:

It is believed that this study provides basic inputs for urban planners and policy makers to be

engaged in ameliorating the current urban housing conditions ,which could contribute to the

evaluation of the attainment for the 2015 MDG4 expected target and also for future

improvements of urban quality of life.

The remaining task is further to undertake analysis by cross-tabulating among the housing

characteristics, being controlled for proportion of under-five mortality levels. For example, types

of floor cross-tabulating by types of wall, controlled for proportion dead, could help focus in

upgrading existing housing conditions and also for future urban and housing planning,

monitoring and evaluation programmes.

23

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24

Paper Presented at the workshop on “Urban Poverty in Southern and Eastern Africa”,

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