2017
The Kabwe Household Socioeconomic
Survey (KHSS) Report

Economics Team of
KAMPAI Project

The Kabwe Household Socioeconomic Survey (KHSS) Report
The Economics Team of the KAMPAI Project
Masato Hiwatari, Faculty of Economics and Business, Hokkaido University, Japan (1,5,8, Editing).
Daichi Yamada, Graduate School of Economics and Business, Hokkaido University, Japan (1,2,3,4,7,10).
Peter Hangoma, School of Public Health, The University of Zambia (6,9).
Daiju Narita, Graduate School of Arts and Sciences, University of Tokyo, Japan (Editing).
Chrispin Mphuka, School of Humanities and Social Sciences, The University of Zambia (2,3,4).
Bona Chitah, School of Humanities and Social Sciences, The University of Zambia (Editing).
* The chapters written by corresponding authors in parentheses.
Published by
Kabwe Mine Pollution Amelioration Initiative (KAMPAI)
July 2018

COPYRIGHTS RESERVED
Extracts may be published if source is duly acknowledged
Citation
Hiwatari, Masato, Daichi Yamada, Peter Hangoma, Daiju Narita, Chrispin Mphuka, and Bona Chitah.
2018. The Kabwe Household Socioeconomic Survey (KHSS) 2017 Report. Kabwe Mine Pollution
Amelioration Initiative (KAMPAI).

i

Acknowledgments
This report is the product of the Kabwe Household Socioeconomic Survey (KHSS) 2017. The survey is acomponent of the inter-disciplinary project “Kabwe Mine Pollution Amelioration Initiative (KAMPAI),”
formally referred to as the “Project for Visualization of Impact of Chronic/Latent Chemical Hazard andGeo-Ecological Remediation in Zambia,” funded by the Japan International Cooperation Agency (JICA)
and the Japan Science and Technology Agency (JST).
The fieldwork of the KHSS 2017 was an activity contracted by the KAMPAI Project to the joint project
team of the University of Zambia and the Central Statistical Office (CSO). The Economics Team of the
KAMPAI Project appreciates the effort and input of three statisticians from CSO, Frank Kakungu, Owen
Siyoto and Taonga Zulu, and thanks CSO for sharing the fieldwork training manual used in the previous
surveys, which was modified and used in the fieldwork training for the KHSS 2017. The Economics Teamalso extends its gratitude to two coordinators from the KAMPAI Project, Hisao Odagiri and MichikoNyanga, for their effort in finalising the outsourcing contract and their assistance in the fieldwork
preparation. The fieldwork preparation was conducted in cooperation with the medical sub-group membersof the KAMPAI Project: Mayumi Ishizuka, Kennedy Choongo, Yared Beyene, Andrew Kataba, Kaampwe
Muzandu, Shouta Nakayama, Hokuto Nakata, Haruya Toyomaki, John Yabe and Golden Zyambo. The
Economics Team appreciates their work. The efforts of the following 21 enumerators, including two fromCSO Kabwe, were vital for completing the fieldwork: Ntalasha Aggrey, Masiku Banda, Saidi Banda, Yvone
Chama, Jackson Chansa, Paul Chavula, Bornface Chuulu, Michael Kambwela, Norman Limwanya, Collins
Mapunga, Kashoba Mukwilima, Brian Munamunungu, Gabriel Mphuka, Paul Mwauluka, Tamika
Nakawala, Peter Njalaikadza, Joseph Njobvu, Kahilu Samuyachi, Matilda Sibongile, Nchimunya
Sichimbwe, and Gabriel Yali.
The six authors of the Economics Team of the KAMPAI Project conducted the data analysis and reportwriting. However, the report has benefited from a series of contributions. The authors appreciate the funding
by JICA and JST that allowed their work to come to fruition. They are also grateful to the medical subgroup of the KAMPAI Project for allowing them to use the blood lead level (BLL) data in this report.
Comments from the participants at the first KAMPAI Symposium held at Hokkaido University, Japan, in2017 were helpful in improving the contents of the report. The findings, analysis, and discussions containedin the report do not represent the views of the whole KAMPAI project or any institution listed above. Clearly,
the authors bear sole responsibility for any and all errors in the report.

ii

Table of Contents
Executive Summary ........................................................................................................... vi
Chapter 1. Survey Background and Sample Design ........................................................................1
1.1. Introduction ..............................................................................................................................1
1.2. Overview of the KAMPAI Project ..........................................................................................2
1.3. Objectives of KHSS 2017.........................................................................................................2
1.4. Sample Design and Coverage ..................................................................................................3
1.5. The Main Survey ......................................................................................................................6
1.6. Sample Weights ........................................................................................................................9
Appendix: Definition of a Household ............................................................................................9
Chapter 2. Demographic Characteristics ....................................................................................... 11
2.1. Introduction ............................................................................................................................ 112.2. Population Size and Distribution .......................................................................................... 11
2.3. Migration and Lengths of Residence in Kabwe .................................................................. 11
2.4. Death .......................................................................................................................................15
Chapter 3. Education ........................................................................................................................16
3.1. Introduction ............................................................................................................................16
3.2. School Attendance and Education Expenditure ..................................................................173.3. Absenteeism ............................................................................................................................19
3.4. Education Levels of population ............................................................................................19
Chapter 4. Health ..............................................................................................................................21
4.1. Introduction ............................................................................................................................21
4.2. Prevalence of Illness or Injury ..............................................................................................21
4.3. Main illness .............................................................................................................................23
4.4. Consultation for illness/ Injury and Medical Costs.............................................................23
4.5. Child Health (Age under 5 years) .........................................................................................24
Chapter 5. Economic Activity ..........................................................................................................26
5.1. Introduction ............................................................................................................................26
5.2. Economic Activity Status .......................................................................................................26
5.4. Labour Time ...........................................................................................................................31
Chapter 6. Household Crop and Livestock Production .................................................................32
6.1. Introduction ............................................................................................................................32
6.2. Agricultural Households ........................................................................................................32
6.3. Crop Production.....................................................................................................................32
6.4. Livestock and Poultry Production ........................................................................................34
6.5. Crop and Livestock Inputs ....................................................................................................35
6.6. Size of Farm and Home Gardens..........................................................................................36
Chapter 7. Household Income and Assets .......................................................................................37
7.1. Introduction ............................................................................................................................37iii

7.2. Household Income..................................................................................................................37
Chapter 8. Expenditure ....................................................................................................................428.1. Introduction ............................................................................................................................428.2. Average Monthly Expenditure ..............................................................................................428.3. Percentage Share of Household Expenditure by Expenditure Type..................................45
Chapter 9. Household Housing Condition ......................................................................................46
9.1. Introduction ............................................................................................................................46
9.2. Type of Housing Unit .............................................................................................................46
9.3. Tenancy Status of Housing Unit............................................................................................47
9.4. Main Source of Drinking Water ...........................................................................................49
9.5. Connection to Electricity .......................................................................................................49
Chapter 10. Blood Lead Levels ........................................................................................................52
10.1. Introduction ..........................................................................................................................52
Reference ...........................................................................................................................................57

The questionnaire of the KHSS 2017 attached at the end of the report.

iv

Abbreviations
BLL: Blood lead level
CSO: Central Statistical Office of Zambia
JICA: Japan International Cooperation Agency
JST: Japan Science and Technology Agency
LCMS: Living Condition Monitoring Survey
K: Kwacha
KAMPAI: Kabwe Mine Pollution Amelioration Initiative
KHSS: Kabwe Household Socioeconomic Survey
SAR: School attendance ratio
SEA: Standard Enumeration Areasv

Executive Summary
The Kabwe Household Socioeconomic Survey (KHSS) 2017 is a household survey
conducted from August to September in 2017 in Kabwe district, Zambia. The objectivesof the survey were to assess the socioeconomic and living conditions of residents of the
district and to provide information that could be used to examine the socioeconomic
causes and consequences of lead exposure in Kabwe. The KHSS 2017 is a component of
the “Kabwe Mine Pollution Amelioration Initiative (KAMPAI),” formally referred to as
the “Project for Visualization of Impact of Chronic/Latent Chemical Hazard and GeoEcological Remediation in Zambia,” which is an interdisciplinary research project carriedout by Hokkaido University, Japan, the University of Zambia, and other partners andfunded by the Japan International Cooperation Agency (JICA) and the Japan Science andTechnology Agency (JST). The KHSS is an interview survey with a similar (i.e.,comparable) design to that of the Zambia Living Conditions Monitoring Survey (LCMS),
and collects data on 895 households (4,900 individuals) in Kabwe district, randomly
chosen as a representative sample of the district.
The total population of Kabwe district is estimated at 270,389, an increase of 33.6 % fromthe 2010 national census figure, 202,360. The survey data shows that the population of
Kabwe district is concentrated among young individuals aged 25 years or below, whichclosely mirrors the national picture during 2015. The 5-9 year age group accounted forthe largest population share (15%) among all age groups.
The KHSS collected data on residents’ educational status and schooling conditions. The
number of students in any grade is estimated to be 92,699, 34.3% of the total population.
The proportion of students is higher than the national average of 30.4%. Despite being
largely urban, the school attendance ratio (SAR) in Kabwe is almost the same as theZambian average, although the SAR for male children in senior secondary and tertiary
school ages is slightly higher than the Zambian average. On average, households in
Kabwe pay 1,365.6 Kwacha (henceforth abbreviated as K) per year (i.e., K113.8 permonth) for each student in the family, and school fees constitute 87.4% of this amount.
The KHSS also collected data on health status, types of illnesses and medical costs.
Regarding health status, 19.1% of the population in Kabwe reported being ill or injuredin the two weeks preceding the survey. This amount is higher than the national averageof 14.2% and the urban average of 9.1% in 2015 identified by the LCMS. In line with thenational data, women are more likely to be ill or injured (20.3%) than men (17.8%).
vi

A number of questions regarding the economic activities of household members, such as
their jobs, wages and labour time were also included. The proportions of the economically
active population and those in paid employment in Kabwe district are estimated to be
57.7% and 39.6% respectively. These proportions are similar to the urban averages acrossall of Zambia (58.6% and 40.0%). Trade (20.2%), agriculture (19.8%), and construction(10.2%) constitute the top three sectors of employed persons. Regarding working status,
Kabwe district exhibits intermediate characteristics of total and urban Zambia. Among
those who have jobs in Kabwe, including unpaid ones, the proportion of those who
actually worked in the last seven days was 77.1%, and their average working hours were
44.4 hours.
The KHSS also gathered data on agricultural activities relating to the 2016–2017 farming
season. The percentage of households engaged in agricultural activities in Kabwe (41.7%)
is lower than the national average (58.7%) but higher than the average for the urban areasin the whole of Zambia (17.9%), as collected by the LCMS 2015. About half of all
agricultural households are engaged in hybrid maize production, which is the same as thenational average recorded by the LCMS 2015. The survey also finds that the average farm
size in the Kabwe district is 33.4 acres (13.2 hectares), and the average size of a homegarden is 2.6 acres.
The survey asked about monthly wage income and income from non-agricultural businessin the last month. The average total monthly household income is K3,492.7, translating
to K764.9 per capita. Compared to national averages as captured by the LCMS 2015,
these figures are similar to those of urban areas of Zambia. As for ownership of household
assets and durables, the items owned by more than 80% of households are beds,
mattresses, cellular phones, and braziers (mbaula). Ownership rates are lower forelectronic durables, such as televisions, electric stoves and refrigerators. Proportions ofownership of these items are close to the urban average in the LCMS 2015 data.
As the most commonly used measure for assessing living standards or poverty ofhouseholds in developing countries, household expenditure plays a vital role forhousehold welfare. The average monthly household total expenditure is estimated at
K3,532 in the Kabwe district, translating to K773 per capita. These values are
considerably higher than the averages at the national level, as estimated by the LCMS
2015. It is suggested that the residents of Kabwe enjoy relatively higher living standard
in Zambia, despite substantial differences in average household expenditure across areas(wards) within Kabwe, with the richest wards having over K5,000 of average expenditure
while the poorest have less than K2,000. The share of food expenditure to the total
expenditure in Kabwe accounts for 36%, which is not different from the urban average ofZambia (35%).
vii

The KHSS 2017 also surveyed the housing conditions of people in Kabwe district, namely,
the type of housing unit, the tenancy status, the main source of drinking water, and theelectricity connection. The findings show that the most common type of housing unit in
Kabwe is a detached house (53.9%), that most households in Kabwe occupied their own
housing units (64.4%) or rented them from private individuals (25.7%). The survey also
found that the proportion of households with a safe/improved water source in Kabwe(88.9%) reflects the average for that of urban areas in Zambia (89.1%).
The KHSS 2017 is a joint survey with the health assessment sub-group of the KAMPAI
project. The health assessment sub-group invited individuals―up to two children andtheir parents from each household―for blood sampling and measured the blood lead level(BLL) using the testing kit LeadCare II. (Note: We excluded BLL data in ORIGINALREPORT because of publishing regulations. The data will be published in otherpublications.)viii

Chapter 1
Survey Background and Sample Design
1.1. Introduction

relatively poor Makululu Compound―one of
the largest compounds in Africa―on thewestern side, and from the commercial areasin the centre to the farming areas in theoutskirts. Kabwe was also once one of themain mining sites in Zambia producing leadand zinc. The closure of the mine in 1994
made the city less dependent on mining.
However, lead pollution and human exposure
to lead remain critical problems. Leadcontaining mining wastes are left abandonedin the dumping site located at the centre of
Kabwe, which is the main source of lead
pollution.

Zambia is a land-locked Sub-Saharan Africancountry sharing boundaries with Malawi andMozambique to the east; Zimbabwe,
Botswana and Namibia to the south; Angola to
the west, and the Democratic Republic ofCongo and Tanzania to the north. According to
the Human Development Report (UNDP
2016), Zambia is a middle-human-developed
country, and its Human Development Indexranks 139th in the world and 8th amongst SubSaharan African countries. However, thecountry’s economy depends on primarycommodities. Copper and Cobalt exports are
the main source of foreign currency revenue.
58.2 per cent of the population lives in rural
areas and are dependent on agriculture for
their livelihood (CSO 2016). Inequality is an
important issue for the country with its GINI
coefficient reaching 55.6, fifth- highest
amongst Sub-Saharan African countries after
South Africa, Namibia, Botswana, and Central
African Republic in 2010-2015 (UNDP 2016).

Lead poisoning leads to various health andhuman developmental problems, such asneuronal, circulatory and reproductive
disorders, lack of concentration, fatigue andloss of IQ (Meyer et al. 2008). These problems
may further lead to poverty and othersocioeconomic problems by limiting theirlabour activities, productivity, and physicaland human capital accumulation (Zivin and
Neidell 2013). At the same time, poverty andother socioeconomic problems can be the risk
factors of lead exposure (Sargent et al. 1995).
In a deprived circumstance that lacks a meanof education, adequate shelter from leadcontaining dust, and access to lesscontaminated food and water, one may besubject to a relatively high risk of lead
exposure and poisoning. The direct healthproblems of lead poisoning may create a

Kabwe is the administrative capital of theCentral Province, one of ten provinces ofZambia. Despite being a medium-sizedmunicipality (the population was slightly
above 200,000 according to 2010 Census), thesocioeconomic conditions and living
standards in Kabwe demonstrate great
diversity; ranging from relatively wealthy
areas on the eastern side of the centre to the1vicious cycle of the abovementioned
interlocking problems that could put theeconomy into a poverty trap and undermine
the development potential of Kabwe andZambia.

issues of lead pollution and human exposure
to lead. The KAMPAI project is aninterdisciplinary research project that involves
a wide range of researchers from different
academic fields. The project aims to examine
multifaceted issues related to lead pollution
and exposure in Kabwe, including thegeographical, biomedical and socioeconomic
causes and consequences of lead exposure andthe potential remediation strategies. The
project is financed by the Japan International
Cooperation Agency (JICA) and the Japan
Science and Technology Agency (JST). It also
shares information with a project of the World
Bank, “Zambia – Mining and Environmental
Remediation and Improvement Project.”

The Kabwe Household Socioeconomic
Survey (KHSS) 2017 is a household survey
aiming to illustrate the socioeconomic andliving conditions of residents of the Kabwe
district and to provide information that could
be used to examine the socioeconomic causes
and consequences of lead exposure in further
research. The KHSS 2017 forms a componentof the “Kabwe Mine Pollution Amelioration
Initiative (KAMPAI),” formally referred to as
the “Project for Visualization of Impact ofChronic/Latent Chemical Hazard and GeoEcological Remediation in Zambia,” and isconducted in collaboration with the healthassessment sub-group of the KAMPAI project.

1.3. Objectives of KHSS 2017
The aim of the KHSS 2017 was to collectdetailed information on the socioeconomic
conditions of individuals and households in
Kabwe district that would allow us to:

In this report, from Chapter 2 onwards, we
present an overview of the KHSS 2017 anddata of key indicators to characterise thesocioeconomic and living conditions ofresidents in Kabwe. The remainder of thischapter provides basic information on the
KAMPAI project and the framework designs
and fieldwork results of the KHSS 2017.

1.

Assess the socioeconomic conditions of
the whole Kabwe district;2.

Examine the socioeconomic causes andconsequences of lead exposure.

The questionnaire design of the KHSS 2017
largely followed that of the Living Conditions
Monitoring Surveys (LCMSs), the nationwide
surveys conducted by Central Statistical
Office (CSO) of Zambia every 2-5 years since1996. Although we modified the structure of
the questionnaire and added various questions,
the KHSS 2017 provides data that allows us tomeasure the socioeconomic conditions ofindividuals and households in Kabwe districtin a way that is comparable to the results of the

1.2. Overview of the KAMPAI
Project
The “Kabwe Mine Pollution Amelioration
Initiative (KAMPAI),” formally referred to as
the “Project for Visualization of Impact ofChronic/Latent Chemical Hazard and GeoEcological Remediation in Zambia,” hasbegun to tackle those multi-dimensional2

1.4. Sample Design and Coverage

LCMSs. The structure of the questionnaire is
as follows:













The KHSS 2017 was designed to select 1,000
households from the whole Kabwe district,including both its centre and outskirts, so thatthe sample represents the population of theentire Kabwe district. It is also desirable thatthe sample is drawn from areas diverse in thelevels of lead contamination.

Section 1. Household roster
Section 2. Biological relationships ofhousehold members
Section 3. Health
Section 4. Education
Section 5. Economic activities andincome at the individual levels
Section 6. Agriculture
Section 7. Other income
Section 8. Household assets
Section 9. Household amenities andhousing conditions
Section 10. Household expenditure
Section 11. Child health and nutrition
Section 12. Deaths in household

The KHSS 2017 employed two-stage random
sampling to find the sample households using
the sampling frame of CSO. The sample frame
divides the whole Kabwe district into 384
Standard Enumeration Areas (SEAs). In thefirst stage, 40 SEAs are randomly selected.
The second stage randomly selected 25
households from each SEA. To ensure therepresentativeness of the sample, samplingweights were calculated (for details on
sampling weights, see Chapter 1.6). One
limitation is that we could not conduct asurvey in areas near military basements. Thus,
households in these areas were excluded in thesecond stage of the random sampling. Apartfrom this issue, our strategy provides areasonable sample representative of the whole
Kabwe district.

To accomplish its second objective, the KHSS
2017 was designed to be complementary withthe parallel surveys conducted by the healthassessment team of the KAMPAI project. The
health assessment team measured the bloodlead levels (BLLs)––a frequently usedbiomarker for lead exposure and poisoning––
to investigate health status of individuals fromthe biomedical aspect and conductedquestionnaire surveys on behavioural aspectsof lead exposure, the quality of life, etc. The
surveys of the health assessment sub-groupwere conducted separately from the KHSS
2017. However, the sample was designed sothat the data of each research component canbe used in the other analyses. This enables us
to examine the socioeconomic causes andconsequences of lead exposure although thisreport only describes the BLLs of the sample
individuals and leaves detailed analysis ofthese issues to further research.

1.4.1. Selecting SEAs
Table 1.1 shows the coverage of the chosen
SEAs at the ward level. A ward is the smallest
administrative unit and Kabwe district isdivided into 27 wards. As a naturalconsequence of random selection of SEAs, thechosen SEAs do not cover all 27 wards,
especially wards comprising a relatively small
number of SEAs. However, this would not be
a serious problem for making the sample
3

representative of the whole Kabwe district.
Figure 1.1 shows the maps of the whole
Kabwe district and its centre, where thechosen SEAs are coloured in green. They arewidely distributed across the whole Kabwe
district, including its centre and outskirts. Also,
the chosen SEAs cover diverse areas in termsof lead pollution. Areas far from the centre arethought to be least contaminated since the slag
dumping site is located close to the centre. The
level of lead pollution is also thought to vary
within the centre (Tembo, Sichilongo andCernak 2006): The Western side, containing
wards such as Makululu, Moomba and David
Ramushu, is considered to be the most
severely contaminated whereas the Easternside, such as Waya, Chirwa and Highridge, tobe less.

Table 1.1: Coverage of the Chosen SEAs
Total

ChosenSEAs

SEAs

Ben Kapufi

120Bwacha162

Chililalila

141Chimanimani

70Chinyanja

81

Chirwa51

6David Ramushu

17

5

Highridge

16

1

Justine Kabwe

100

Kalonga19

2

Kangomba

11

2

Kaputula

19

3

Kawama21

0Luangwa27

0Luansase

60Makululu

7

2

Moomba

21

6

Mpima

11

1

Munga

6

0

Munyama7

2

Muwowo80Muwowo East

12

3

Nakoli140Ngungu11

0

Njanji

8

0

Waya

10

1

Zambezi

15

2

Ward name1.4.2. Selecting Households
In each SEA chosen in the previous step, the
KHSS 2017 randomly located 25 households
plus a few replacement households. To do this,we conducted a household listing in July/
August 2017 in collaboration with the healthassessment sub-group of the KAMPAI project.
A standard method for the listing andhousehold selection, which was also followedby the LCMSs, is to visit all households ineach selected SEA, make a list of households,
and select 25 households randomly. However,this method turned out to be difficult for most
SEAs in the KHSS 2017 due to the logistical,
financial and time constraints. The household
lists obtained in this way were used only for a
few SEAs.

4

Figure 1.1: The map of Kabwe (chosen SEAs in deep green)5Instead, we sampled households in thefollowing alternative way utilising the satellite
maps of Google Earth, in cooperation with thehealth assessment sub-group of the KAMPAI
project. We first counted the number ofresidentialbuildings
orstructures
recognisable on the satellite maps (let us callthem houses). Then, we listed the houses in arandom order using the random numbers.
Ideally, if houses and households have one-toone correspondences, then we can obtain theset of randomly selected sample households
by selecting the 25 houses in the top of the list.
However, the list of houses could include
empty houses, detached rooms or nonresidential buildings (we made effort to avoid
counting these buildings, but it may not
perfectly eliminate these cases). Therefore, we
visited the houses in the list in a descendingorder to make the list of sample households. If
a house was inhabited by a household, then we
included it in the list of sample households.1
In cases where multiple households share thesame building, we chose one of themrandomly. In cases where some houses seemedinhabited but no individual was present, we
asked neighbours whether the houses were
inhabited. We continued visiting houses until
at least 25 households were listed as sample
households. In SEAs where we could list morethan 25 households, we reserved households
in the 26th or higher orders as replacement
households.

by single households and used as the main
residential buildings. This allowed us to use
the house counts to calculate the samplingweights, the details of which are explained in
Chapter 1.6.

1.5. The Main Survey
1.5.1 General Description of Interviews
The fieldwork for the main survey of the
KHSS 2017 was conducted during three
weeks from late August to early September
2017, in the form of Computer Assisted
Personal Interviewing (CAPI) using theapplication Survey Solutions (version 5.22.20,
the latest version at the time of the survey),
developed by the World Bank. The fieldwork
involved five supervisors/trainers and 21
enumerators, including three Economics Team
members from the University of Zambia andfour CSO personnel.
Interviews were conducted mostly at thehouses of the sampled households, eachlasting two to three hours on average. In cases
where the knowledgeable persons were absent,
the enumerators stopped interviewing andrevisited these households when theknowledgeable persons were available.
Although the questionnaire is prepared in
English, interviews were also conducted inlocal languages, such as Bemba, Nyanja andTonga. Enumerators were required to speak atleast two local languages as well as English
and to be able to translate the questionnaire

It turned out that our house counts from thesatellite maps were relatively accurate. In
most cases, the visited houses were inhabited1

provided in Appendix of this chapter.

The details of the definition of a household is6

into these languages. The ability to conduct
interviews in local languages was also
examined in the pre-survey training session.

replacement households). The number oforiginally sampled households is fourhouseholds fewer than 1,000 because it turned
out when conducting the main survey that fourgroups of individuals listed as independent
households in the sampling procedure weremembers of other households according to ourdefinition.

1.5.2. The Response Rate and the Final
Sample Size
The main survey visited 1,015 households(996 originally sampled households and 19

Table 1.2: The Description of the Samples for Each Ward
The number of households
Replace

Total

ChosenOriginal

mentvisited

Not

Final

Response

SEAs

sampleusedhouseholds

available

Refusalsamplerate

Bwacha

2

50

2

52

4

1

47

90.4%

Chililalila

1

25

0

25

0

0

25

100.0%

Chinyanja

1

25

0

25

0

4

21

84.0%

Chirwa

6

149

0

149

17

7

117

78.5%

Ramushu

5

125

2

127

12

0

115

90.6%

Highridge

1

24

0

24

3

0

21

87.5%

Kalonga

2

50

8

58

7

2

44

75.9%

Kangomba

2

50

0

50

2

1

47

94.0%

Kaputula

3

75

1

76

3

0

72

94.7%

Makululu

2

50

0

50

5

1

44

88.0%

Moomba

6

150

0

150

19

0

131

87.3%

Mpima

1

23

0

23

2

0

21

91.3%

Munyama

2

50

1

51

1

0

50

98.0%

East

3

75

4

79

6

2

71

89.9%

Waya

1

25

1

26

4

0

22

84.6%

Zambezi

2

50

0

50

3

0

47

94.0%

Total

40

996

19

1,015

102

18

895

88.2%

Ward

David

Muwowo“Not available” includes the cases where the households turned out to be shifted and where we could not have any
contact.

7

Among the visited households, the overall
response rate was 88.2% and we could notconduct interviews with 11.8% of households(i.e. 120 households). For 17.5% of the 120
failed cases, we learnt, by asking neighbours
or making phone calls, that the sample
households had shifted during the period
between the listing and the main survey. These
cases include single student households who
were listed in the listing procedure but wereabsent at the time of the survey because ofsummer vacations. For 67.5% of the failed
cases, we could not make any contact evenafter repeated attempts to revisit them, perhaps
because either the households had shifted orwere temporarily absent. The explicit refusalof interviews was rare, constituting 15% of thefailed cases and 1.8% of the total cases.

The surveys of the health assessment team
were conducted over six weeks from July toAugust in 2017. Unlike the KHSS 2017,
where the enumerators visited sample
households, the health assessment teaminvited sample individuals to communal
clinics and conducted blood sampling and theother surveys there due to hygiene and ethicalreasons. Eleven clinics were chosen as thevenues for their surveys.
For each household, up to four persons―twoparents and two children―were invited to thenearest one of the chosen clinics. In SEAs withno nearby clinic, the health assessment teamprovided means of transportation. The dates ofblood sampling and interviews were preassigned since it was not feasible to allocate
the health assessment team members to all 11
clinics at once. Instead, the members formed
four groups, visited the clinics sequentially,
and requested the sample individuals to attend
the clinics while they were staying there. The
assigned dates had one-week windows so that
invited individuals could attend when they
were available during the week.

The final sample size in the main survey is 895
households (4,900 individuals). Table 1.2
summarises the sample sizes, the breakdownof the failed cases, and the response rate foreach ward, excluding wards from which no
SEA was chosen.

1.5.3. The Final Sample for the Surveys
by the Health Assessment TeamRegarding the final sample of the healthassessment team, there are two points to be
noted. First, in addition to the sample sharedwith the KHSS 2017, the health assessment
team invited additional households to partakein their surveys. However, the information onthese samples cannot be merged with the
KHSS 2017 data as no information is available
for these samples in the KHSS 2017 data.

The sample of the KHSS 2017 was designed
to be shared with the parallel surveys by thehealth assessment team of the KAMPAI
project, which, as earlier mentioned,
conducted blood sampling and questionnaire
surveys on aspects such as lead exposure andavoidance behaviours and the qualities of lives.
These data could be merged with the KHSS
2017 data at the individual and household
levels. This subsection briefly describes theirsurvey procedure.

Second, and unfortunately, the attendance rate
at the clinics was quite low. Some individuals
might not have been able to find time to visit
8the clinics despite one-week windows. Some
explicitly refused to visit the clinics because
the idea of blood sampling was not religiously
or ethically acceptable for them. Among thefinal sample of the KHSS 2017, blood
sampling was conducted for 827 out of 4,900
individuals (16.9%), or 372 out of 895
households (41.6%).

selections of 40 SEAs from 384 SEAs thatcover the entire Kabwe district at the firststage. P2i is calculated by dividing the final
sample size in the i th SEA by the total numberof households in the i th SEA. In SEAs where
the standard method of listing was feasible,
the total number of households is available. In
the other SEAs, we could reasonably use thenumber of houses counted from the satellite
maps as the estimated number of households
since it roughly matches the actual number ofhouseholds.

1.6. Sample Weights
To find estimates representative of the
population of the whole Kabwe district, theuse of sampling weights is essential. Since thesample size per SEA is fixed, mostly at 20-25
households, but each SEA differs in its
population size, differences in representationof the samples need to be corrected bysampling weights. The weights also correct
the differences in the response rates across the
SEAs.

Because this report aims to describe theinformation representative of the whole
residents in the Kabwe district, we use thesampling weights for most of the calculation.
Whenever we present a figure calculated
without using the sampling weights, weclearly state so.

Appendix: Definition of a
Household

Since we did not adopt stratified sampling, theweights of the sample are equal to the inverseof the product of the two selection
probabilities employed at each stage of
selection. The sample weight for a householdin the i th SEA, Wi, is calculated as follows:

𝑊𝑖 =The KHSS 2017 uses the same concept anddefinition of a household member as the
LCMSs. A household member is defined sothat it includes an individual who was
temporarily absent at the time of the survey,
but excludes an individual who usually lives
in other places but happened to stay in thehousehold.

1
𝑃1𝑖 𝑃2𝑖where:
P1i: the probability of selecting the i th SEA in
the first-stage selection, andP2i: the probability of selecting a household in
the i th SEA in the second-stage selection.

A more precise definition of a household
member is as follows: A household member isbasically defined as one who (i) has
continuously lived with the household for atleast six months, (ii) lives together with otherhousehold members in one house or closely
related premises and takes his/her meals from

In our sampling design, P1i is equal to 40/384
for any i, since we conducted random
9the same kitchen, and (iii) regards the person
who is regarded as head by other household
members as head. He/she may or may not be
related to the other household members byblood or marriage. A house helper or labourer(maid, nanny or house servant) is also ahousehold member as long as he/she meets thecriteria above. Conversely, there are situations
where people eat together and even sleep
under one roof, but have different persons
whom they regard as head. These persons are

considered as belonging to separate
households. The exceptional cases where
persons not meeting the criteria are regarded
as household members are newly married
couples, newly born babies, those who areaway for temporary basis and those attending
boarding schools, colleges and universities
within Zambia.

10Chapter 2
Demographic Characteristics
2.1. Introduction

LCMS 2015. The population is concentrated
among those below the age of 25 years, whichclosely mirrors the national picture during
2015. The age group with the largest
population is 5-9 years, accounting for 15.5%of the total population of Kabwe in 2017. This
percentage compares well with the national
population distribution in 2015 where that age
group accounted for 18.8%. There is nomarked difference in the population
distribution within a particular sex. Finally,
the total population of Kabwe district isestimated at 270,389 based on the KHSS data,
an increase of 33.6% from the 2010 national
census figure of 202,360.

The KHSS 2017 collected information on the
representative sample of the population of thewhole Kabwe district. Over seven years after
the census, the demography in Kabwe hasseemingly changed. New houses were built insuburban areas. New households may have
moved in from outside of the Kabwe district
while some households may have split into
several new households as children became
adults.
Under such circumstances, the demographic
characteristics would be interesting for theirown sake. They are also important inunderstanding the living conditions of thepeople because they would affect thesocioeconomic behaviour of individuals andhouseholds, and vice versa. In addition, thedemographic characteristics would also be
important factors regarding lead exposure.

2.3. Migration and Lengths of
Residence in Kabwe

2.2. Population Size andDistribution

Migration has implications on population
changes and has a close relationship withliving conditions. It would also be related tothe duration of individuals’ exposed to lead,which is one of the main focuses of the
KAMPAI project.

Table 2.1 shows the population distribution by
sex and age group. The population weights areused so that the distribution reflects that of thewhole Kabwe district. The first four columnsof the table refer to the population distributionof Kabwe as found in the KHSS 2017 while
the last two columns are the national
population distribution according to the

The term migration in the KHSS 2017 refers
to any change in residence, including
relocation within a township, a district, aprovince or a nation and international
immigration. Considering the objective of thewhole project, the KHSS 2017 modified andadded various questions about migration to thequestionnaire in the LCMS 2015.
11

Table 2.1: Population Estimates and Percentage Distribution by Age Group and Sex
Population estimates for Kabwe

Population estimates for Zambia(from the KHSS 2017)(from the LCMS 2015)

Population distribution
Both

Estimated

Population

Estimated

Age group

Male

Femalesexes

population

distribution

population

Total

100.0

100.0

100.0

270,389100.0

15,473,905

0-4

15.2

12.1

13.6

36,8939.9

1,536,048

5-9

17.0

14.0

15.5

41,88818.8

2,902,927

10-14

11.8

13.2

12.5

33,80014.2

2,201,329

15-19

13.0

12.3

12.6

34,18012.6

1,951,215

20-24

8.6

10.7

9.7

26,1409.6

1,483,666

25-29

6.8

8.3

7.5

20,4077.5

1,163,404

30-34

5.4

7.5

6.5

17,4576.2

960,741

35-39

5.6

5.7

5.7

15,357

5.6

868,372

40-44

4.9

3.5

4.2

11,2704.2

647,030

45-49

3.3

3.5

3.4

9,221

3.0

466,454

50-54

2.6

2.9

2.7

7,391

2.3

362,640

55-59

1.8

1.7

1.7

4,725

1.9

287,784

60-64

1.7

1.4

1.6

4,229

1.3

198,116

65+

2.4

3.1

2.7

7,433

2.9

444,177

Sample weights used.

A notable change from the LCMS 2015 is that
migration here is not restricted to the events ofresidential changes within one year. The
LCMS 2015 asked each household member
whether he/she had changed his/her residence
within one year prior to the survey. Meanwhile,
the KHSS 2017 asked whether he/she had everchanged his/her residence.

Table 2.2 shows the percentage distribution of
persons by area of the previous residence. Of
the total population of Kabwe, 71.8% had evermoved in their life. However, the previous
residence of 52.5% of the population was
located within the Kabwe district. Immigrants
from outside of the Kabwe district, including
other districts in Central Province, otherprovinces, or foreign countries, accounted for
19.2% of the population.

12

Table 2.2: Proportions of Individuals by Type of Migration (Past Residence); %Different

Different

Has

dwelling/

district/

never

same

Different

the same

Different

Different

know/

moved

townshiptownshipprovince

province

country

refusal

Total

Total Kabwe

28.2

33.4

19.1

3.2

15.7

0.3

0.1

100.0

Bwacha

30.3

20.9

17.9

3.5

27.0

0.0

0.3

100.0

Chililalila

28.1

21.5

26.4

4.1

13.2

6.6

0.0

100.0

Chinyanja

24.0

23.0

27.0

12.0

14.0

0.0

0.0

100.0

Chirwa

28.3

26.0

22.6

5.4

16.9

0.7

0.1

100.0

Ramushu

35.4

28.3

16.1

5.2

15.1

0.0

0.0

100.0

Highridge

36.4

23.4

15.0

2.8

21.5

0.0

0.9

100.0

Kalonga

22.2

35.7

15.5

1.1

25.4

0.0

0.0

100.0

Kangomba

38.5

21.4

24.6

3.5

12.3

0.0

0.0

100.0

Kaputula

30.6

38.8

15.0

2.1

13.2

0.2

0.0

100.0

Makululu

25.5

26.0

24.5

2.5

21.5

0.0

0.0

100.0

Moomba

39.4

31.4

12.2

4.1

12.9

0.0

0.0

100.0

Mpima

27.0

25.2

14.4

0.9

32.4

0.0

0.0

100.0

Munyama

33.7

25.0

15.4

5.1

19.8

1.0

0.0

100.0

Muwowo East

19.6

38.0

25.3

3.1

14.0

0.0

0.0

100.0

Waya

26.2

50.8

6.9

1.5

13.8

0.8

0.0

100.0

Zambezi

19.7

48.5

25.8

1.5

4.6

0.0

0.0

100.0

Don't

David

Sample weights used.

5

10

15

20

25

The survey also asked about the number ofyears each individual had stayed continuously
in the Kabwe district. Figure 2.1 shows thelengths of stay in the Kabwe district expressedin years. The chart shows that 23.8% had lived
in Kabwe for less than 5 years and 20.4% for
5-9 years, including young children and those
who had recently moved in to the Kabwe
district. However, more than 55% of
individuals had lived in Kabwe for more thana decade.

20.4

14.6

11.6

9.3

6.4

13.8

0

23.8

0-4 years
10-14 years
20-24 years
30+ years

5-9 years
15-19 years
25-29 years

Figure 2.1: Distribution of the Length of Stayin Kabwe District

13

The reasons for migration are diverse. Table
2.3 shows the distribution of reasons for
migrating. The most frequently reported
reason is the transfer of the household head
(36.7%). Schooling is a quite common reason
for young children, accounting for 8.9% of thecases. Among those aged 15 years or above,‘decided to resettle’ and ‘acquired new/different accommodation’ are commonly
observed. Marriage and ‘new household’ arealso common among adults.

Considering the possibility that some people
may migrate to avoid environmental pollution,
the KHSS 2017 added this answer as an option.
However, only 0.1% of the population chose
this as the main reason for migration. Either
people do not care about pollution or are notfully informed of pollution or its danger, or
those who care about pollution do not live inpolluted areas in the first place and do not needto migrate to avoid environmental pollution.

Table 2.3: Reasons of Migration (Proportions Among Those Who Have Ever Migrated)
Total

Aged 0-14 years

Both

Both

Aged 15 years or older
Both

sex

Male

Fem

sex

Male

Fem

sex

Male

Fem

For school

5.8

5.6

6.0

8.9

5.6

10.4

4.9

5.6

4.2

Back from school/studies

0.0

0.0

0.1

0.0

0.0

0.0

0.1

0.0

0.1

To seek work/ business

2.0

3.0

1.1

0.0

0.0

0.0

2.9

4.5

1.6

To start work/ business

2.2

3.1

1.3

0.0

0.0

0.1

3.1

4.7

1.7

36.7

35.0

38.2

57.3

63.7

50.1

27.8

20.1

33.7

not afford to keep him/her

2.8

2.9

2.7

4.0

3.3

4.7

2.3

2.7

2.0

Death of parent/guardian

3.7

3.2

4.1

3.7

2.1

5.5

3.7

3.8

3.5

Got married

5.6

1.6

9.5

0.0

0.0

0.0

8.1

2.4

13.1

New household

8.8

9.6

8.0

8.4

8.9

7.9

8.9

9.9

8.0

Retirement

0.5

0.7

0.4

0.0

0.0

0.0

0.8

1.0

0.5

Retrenchment

0.2

0.2

0.1

0.0

0.0

0.0

0.2

0.3

0.2

Decided to resettle

12.9

15.6

10.4

5.6

6.2

5.0

16.1

20.2

12.5

11.6

13.3

9.9

2.8

3.2

2.4

15.3

18.3

12.7

land

0.3

0.5

0.2

0.0

0.0

0.0

0.5

0.7

0.3

Environmental pollution

0.1

0.1

0.1

0.0

0.0

0.0

0.2

0.2

0.2

Other

6.6

5.5

7.6

10.2

6.8

13.9

5.0

4.8

5.2

Don’t know

0.2

0.1

0.4

0.1

0.1

0.0

0.3

0.1

0.5

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Transfer of head ofhousehold
Previous household could

Acquired own/different
accommodation
Found new agricultural

Sample weights used14

2.4. Death

Table 2.4: The Crude Death Rate (CDR)Per

The KHSS 2017 collected information on thedeaths of household members during theperiod 12 months prior to the survey.
Information collected included sex, age andthe main cause of death of the deceased.

Thousand

Persons,

andthe

Breakdowns of Deaths
CDR, %

Unlike the other sections of Chapter 2,
throughout this section, we do not intend toprovide a generalised, representative pictureof deaths in Kabwe mainly because thenumber of reported deaths is small―58
persons deceased within 12 months. Instead,
we focus on describing the details of thereported deaths. This figure itself is not
disproportionately low. We do not use thesampling weights, either.

Kabwe

11.7

Total Zambia*

15.8

Urban Zambia*

12.5

Rural Zambia*

18.1

Distribution of the ages at the time the persons
deceased (N= 55), %0-4 years

5 – 14 years

15 years or older

22.2

9.3

68.5

Causes of deaths

The crude death rate per thousand persons isof 11.7%, slightly lower than the rate in urban
Zambia in the LCMS 2015. Among 55
deceased persons whose ages at the time they
deceased are reported, 22.2% were 0-4 years
old, 9.3% were 5-14 years old, and 68.5%
were 15 years old or above.
The most frequent causes of deaths were
‘Other including natural deaths’ and‘hypertension.’ Deaths owing to malaria(‘Fever/malaria’ and ‘Cerebral malaria’) are
reported, but their proportion is smaller than
the national average in the LCMS 2015. Nonhealth-related deaths (suicide, murderer andaccident) are also reported.

Cases (proportion)

Fever/malaria

4(6.9%)

Cerebral malaria2(3.4%)

Cough/cold/chest infection

5(8.6%)

Tuberculosis

1(1.7%)

Pneumonia chest pain3

(5.2%)

Diarrhoea without blood2(3.4%)

Vomiting

2(3.4%)

Liver infection / side pain

1

(1.7%)

Lack of blood / aneamia

1(1.7%)

Suicide1(1.7%)

Murdered2(3.4%)

Accident

1(1.7%)

Hypertension

6(10.3%)

Diabetes / sugar disease1(1.7%)Headache2(3.4%)

Cancer1(1.7%)

Still birth2(3.4%)

Other (incl. Natural death)15(25.9%)

Don't know / Refusal

6(10.3%)

Sample weights not used. * Data from the LCMS
2015.

15

Chapter 3
Education
3.1. Introduction

grade, are as follows:•

Education is an important determinant ofpeople’s living conditions because it may
affect a household’s welfare throughemployment and health. Information collectedduring the survey includes questions seeking
to establish whether an individual was
attending school at the time of the survey. If
attending school, the individual was asked
about the grades they were attending andabsenteeism at school, based on how often one
missed school in the last term. Information
about education expenditure made in the last
12 months (2nd term, 1st term, and 3rd term in
the previous school year) was also collected.

Pre-primary/nursery level corresponds topersons aged 5-6 years•

Lower primary grades 1-4 correspond to
persons aged 7-10 years•

Upper primary grades 5-7 correspond to
persons aged 11-13 years•

Junior secondary grades 8-9 correspondto persons aged 14-15 years•

Seniorsecondarygrades10-12

correspond to persons aged 16-18 years•

Tertiary education level corresponds topersons aged 19-22 years

The survey also asked for the highest grade ofeducation an individual had attained. Data
collected on education is based on the current
formal education system. For those educatedunder the different education standards andforms in the past (Zambia has made threemajor changes to its education system in 1956,
1966 and 1980), their information on thehighest educational attainment is converted tothe current equivalent.

Note that the age information of the KHSS
2017 does not allow us to construct a complete
set of children whose ages correspond to theofficial school ages. To see this, let us takechildren aged 10 years as an example. Basedon their age, we treat them as children in theofficial lower primary school age group.
However, children aged 10 years at the time ofthe survey include children who became 10
years old in the 2017 school year (and werethus in the lower primary school ages) andthose who would have their birthday after thesurvey and become 11 years old by the end of
the 2017 school year (and were indeed in theupper primary school ages). This occurs
because the survey took place in August/
September, between the 2nd and 3rd terms, andThe current education system of Zambia
comprises pre-primary/nursery school, lower
and upper primary school, junior and seniorsecondary school, and tertiary school. The
official ages for these education levels, which
are the ages of students who start schooling at
the standard age and do not skip or repeat any
16

3.2. School Attendance
Education Expenditure

the ages were asked as of the time of thesurvey. Considering the timing of the survey,
roughly two-thirds of the children aged 10
years would fall into the former case and onethird into the latter.

and

The school attendance ratio (SAR) is thepercentage of children attending any school
grade among all children in a given age group.
Notably, the SAR is higher among children inupper primary education ages than among
those in lower primary education ages, and thesame tendency is also observed in the LCMS
2017 data. This suggests the possibility thatsome children start attending school at the ageof 8 years old or above. Despite being urban,
the SAR in Kabwe district is almost the sameas the Zambian average although the SAR for
male children in senior secondary and tertiary
school ages are slightly higher than the
Zambian average for male.

This is not a critical problem for analysing thedeterminants of education in further researchbecause whether a person becomes 10 years
old before or after the survey is basicallyexogenous to households. However, it would
be problematic for calculating somefrequently used measurements of school
attendance, such as the gross and net
attendance (enrolment) ratios, whose
estimation requires a complete and accurate
set of children in each official school age
group. Therefore, we avoid presenting thesemeasurements.

Table 3.1: School Attendance Rate (SAR) and Estimated Number of Students
Kabwe districtAge group

Total Zambia *

Total

Male

Female

Total

Male

FemalePre-school

5-6 years

40.9

37.7

44.5

29.8

28.2

31.4

Lower primary

7-10 years

79.1

76.4

82.2

77.2

75.5

78.9

Upper primary

11-13 years

89.4

89.4

89.4

90.9

88.9

92.8

Junior Secondary

14-15 years

82.5

79.1

85.9

85.7

86.1

85.3

Senior Secondary

16-18 years

70.0

78.7

61.3

65.3

70.9

60.9

All primary

7-13 years

83.1

81.0

85.2

83.1

81.3

84.8

All secondary

14-18 years

74.4

78.8

70.1

75.7

78.4

73.4

Higher education

19-22 years

30.8

40.1

22.2

29.4

36.3

22.5

92,69947,08145,6194,697,435

2,327,154

2,370,281

Estimated number of students

Sample weights used. * From LCMS 2015.

17

Table 3.2: Education Expenditure (Kwacha)
Total in the last

2nd term, 2017

1st term, 2017

3rd term, 2016

three terms

school year

school year

school year

Total expenditure1365.6

417.2

601.6

346.8

School fees

1193.8

362.0

508.9

322.9

Private tuitions

36.7

19.6

10.4

6.7

Textbooks

44.0

16.4

19.0

8.6

School uniforms

91.1

19.2

63.3

8.6

Sample weights used.

Table 3.2 shows education expenditure foreach school-attending child. The KHSS asked
about expenditure on school fees, private
tuitions, textbooks and school uniforms foreach school-attending child―these items of
expenditure were asked separately from thegeneral household expenditure. Total
education expenditure is K1,365.6 per year

(K113.8 per month), and school fees constitute
87.4% of this expenditure. The remainingcolumns show the breakdown of education
expenditure by school terms. Expenditure is
the largest in the first term of a school year,
possibly because that is when the household
prepares school uniforms or when someparents pay the yearly education expenditure.

Table 3.3: The Frequency of Missing Classes; %A little
Never

Often

Very often(once or twice (3 to 10 times (more than 10
a month)a month)times a month)

Total Kabwe

53.2

34.5

9.8

2.5

Male

52.1

33.7

11.1

3.0

Female

54.3

35.3

8.5

1.9

Primary

49.8

35.6

11.4

2.9

Primary and junior secondary

49.9

36.4

10.7

3.0

Secondary

54.1

35.5

8.4

1.9

Sample weights used.

18

3.3. Absenteeism

education or lower is smaller but the
proportion above primary education is larger
than the Zambia’s average. Male education ishigher than female education. Note that the
proportion of those without any education,
14.6% for the Kabwe total, includes children
at pre-school ages. Note also that exclusion ofchildren currently attending school would also
underestimate the education levels of the
Kabwe residents.

The quality of education is partly affected by
the rate at which pupils attend school. The
KHSS 2017 asked how often children enrolled
in school had, on average, missed attendingclasses in the last term preceding the survey(i.e. the second term of the 2017 school year).
Table 3.3 presents the absence rate of students
by sex and age group. In any grade,approximately half of the students attend allclasses, and 85-90% of students missed onceor twice a month at most. Male children missschool more frequently than female children
did. The incidents of missing classes are lessfrequent among secondary school students
than among students in other grades, perhaps
because children having difficulty attendingclasses fail to advance to secondary school in
the first place.

Then, Panel B presents the distribution
including children attending school. For
children attending school, the grades they
were attending at the time of the survey istreated as their highest level of education. In
addition, since inclusion of very young
children would complicate the interpretation,
all calculations in Panel B focus on those aged
10 years or above. With this change, theproportion of individuals without education
decreased. For those aged 16-29 years, thelargest proportion has attained seniorsecondary education. For those aged 40-59
years, the proportion peaks at upper primaryeducation. For those aged 10-15 years, 82.2%of them have completed upper primaryeducation or lower―the majority of thosehaving not completed were attending primaryschool at the time of the survey, rather thanhaving left school without completing primaryeducation.

3.4. Education Levels of
population
In this section, we describe education levels
individuals have attained. Following the
LCMS 2015 report, which presents thepercentage distribution of the population five
years or older who were not attending schoolat the time of the survey, we present the same
distribution for the Kabwe population in Panel
A of Table 3.5. In Kabwe, the proportion ofindividuals having completed primary19

Table 3.4: Education Levels of Population
Primary education

Secondary

Grade 12 A-

educationlevel/
Certificate/

Post-

Grades

Diploma/

graduate

No

GradesGradesGrades10-12

Under-

andeducation

1-4

5-7

8-9

(O-level)

graduate

above

Panel A: 5 years or above who were not in education
Total Kabwe

14.6

7.3

20.7

19.5

24.9

12.2

0.8

Male

15.5

6.3

15.9

17.2

28.9

15.3

0.9

Female

13.8

8.3

24.9

21.6

21.4

9.4

0.6

Total Zambia*

27.0

10.8

24.0

16.3

15.7

4.7

1.4

Male*

25.2

9.0

21.8

16.6

19.5

5.9

2.0

Female*

28.7

12.5

26.1

16.1

12.1

3.7

0.8

Panel B: 10 years or above, including children in education
Total Kabwe

4.6

9.9

25.1

21.5

26.2

12.1

0.6

Male

3.5

9.4

21.9

20.3

30.1

14.1

0.7

Female

5.6

10.3

28.0

22.5

22.8

10.3

0.5

10-15

5.4

29.2

47.6

14.9

2.9

n/a

n/a

16-18

2.3

1.7

14.1

38.0

42.5

1.4

n/a

19-22

2.8

1.7

15.2

17.5

52.5

10.3

n/a

23-29

1.0

3.4

14.1

20.9

40.0

20.4

0.2

30-39

4.2

5.5

21.6

22.6

22.0

23.0

1.1

40-49

5.3

4.4

28.1

26.5

18.2

16.8

0.7

50-59

5.6

6.1

31.1

17.8

21.7

15.8

1.9

60+

18.3

18.1

16.5

12.9

18.8

12.7

2.7

Sample weights used. * Data from LCMS 2015.

20

Chapter 4
Health
4.1. Introduction

feeding status for children younger than 5
years old.

The KHSS 2017 collected data on the healthstatus of all persons. Health is directly related
to welfare for its own sake. It may also have
implications for economic activities, such as
labour activity, consumption and productivity,
which would ultimately affect welfare. In
addition, the health status could be a usefulmeasurement for assessing the causes andconsequences of lead exposure.

4.2. Prevalence of Illness or Injury
Table 4.1 shows the proportion of persons who
were ill or injured in the two weeks preceding
the survey by sex and ward. At the districtlevel, 19.1% of the population in Kabwe
reported being ill or injured in the two weeks
preceding the survey. This is higher than thenational average of 14.2% and the urban
average of 9.1% in the LCMS 2015. While thisresult could be a consequence of leadpoisoning, it could also be a consequence ofthe socioeconomic characteristics of Kabwe
residents. In line with the tendency in thenational data, women are more likely to be ill
or injured (20.3%) than men (17.8%).

In Chapter 4.2 to 4.4, we focus on the healthstatus of all individuals and summarise selfreported illness and injury and medical
expenditure. The reference period is the last
two weeks preceding the survey. Chapter 4.5
focuses on child health and presents
thebreastfeeding status and history and other

Table 4.1: The Proportion of the Ill or Injured Persons, %The KHSS 2017

The LCMS 2015

Total Kabwe

Male

Female

19.1

17.8

20.3

Total Zambia

Male

Female

Urban

Rural

14.2

13.4

15.0

9.1

17.9

Proportion reporting illness or injury for each ward
Bwacha19.9

Highridge

21.5

Moomba16.9

Chililalila

26.4

Kalonga

24.1

Mpima

11.7

Chinyanja

7.0

Kangomba

29.2

Munyama

17.7

Chirwa21.2

Kaputula

11.5

Muwowo East

7.0

David Ramushu

21.9

Makululu

22.0

Waya

15.4

Zambezi

31.6

Sample weights used.

21

Table 4.2: Breakdown of Sickness, %Age group (years)
Total

Male

Female

0-9

10-19

20-49

50+

Fever / malaria

17.6

16.7

18.5

19.0

18.2

17.2

16.2

Cough / cold / chest infection

50.9

55.3

47.3

65.0

52.9

46.2

38.0

Tuberculosis

0.1

0.1

0.1

n/a

n/a

0.3

n/a

Asthma

1.2

1.2

1.3

0.8

n/a

1.9

1.6

Bronchitis

0.8

1.0

0.6

2.3

0.4

0.2

0.3

Pneumonia / chest pain

1.7

1.9

1.5

0.2

1.4

1.9

4.0

Diarrhoea without blood

4.4

5.1

3.7

7.0

6.3

3.4

0.5

Diarrhoea with blood

0.7

1.1

0.3

2.0

n/a

0.3

n/a

Diarrhoea and vomiting

1.8

2.6

1.2

4.6

n/a

1.5

n/a

Vomiting

0.6

0.5

0.8

0.9

1.3

0.4

n/a

Abdominal pains

7.4

5.7

8.8

3.3

6.7

8.4

11.9

Constipations

1.2

1.0

1.3

1.3

2.0

1.2

0.3

Anaemia

0.3

n/a

0.5

n/a

0.3

0.2

0.8

Boils

0.4

0.8

n/a

1.3

n/a

n/a

n/a

Skin rash / skin infection

2.2

1.4

3.0

4.8

2.6

0.4

2.1

Shingles / herpes zoster

0.1

n/a

0.1

n/a

n/a

0.2

n/a

Paralysis

0.7

0.5

0.9

0.2

0.8

0.8

1.5

Stroke

0.1

0.1

1.4

n/a

n/a

n/a

0.8

Hypertension

4.6

3.3

5.7

n/a

n/a

4.2

17.3

Diabetes / sugar disease

0.7

0.7

0.7

n/a

n/a

n/a

4.0

Eye infection

3.0

3.1

2.9

2.7

1.9

4.1

2.0

Ear infection

0.1

n/a

0.1

0.2

n/a

n/a

n/a

Toothache / mouth infection

2.9

1.2

4.4

1.3

2.1

4.8

2.0

Headache

17.7

17.6

17.7

6.0

25.1

22.0

18.6

Measles

0.1

n/a

0.1

n/a

n/a

n/a

0.5

Backache

3.1

1.3

4.7

n/a

0.9

3.5

9.3

Cancer

0.4

n/a

0.8

0.3

n/a

n/a

1.9

Other

8.4

7.2

9.4

6.2

2.6

10.2

13.2

Total

133.2

129.4

137.8

129.4

125.5

133.3

146.8

Total percentage exceeds 100 since some persons report multiple sicknesses. Sample weights used.

At the ward level, Zambezi ward had thehighest proportion of population ill or injured
at 31.6%, followed by Kangomba (29.2%),
Chililalila (26.4%) and Kalonga (24.1%).

Wards with the lowest proportion of the
population ill or injured were Muwowo East
and Chinyanja (7.0%), followed by Kaputula(11.5%) and Mpima (11.7%).
22

4.3. Main illness

and/or medication by persons consulted. The
average amount spent on consultation and/or
medication was K161.2 for persons who
consulted medical doctors, K9.3 for persons
who consulted clinical officers, and K6.5 forpersons who consulted nurses/midwives. If we
restrict our focus to patients making any
payment, the average expenses become
K319.8, K49.4, and K38.5 for those
consulting medical doctors, clinical officers,
and nurses/midwives, respectively. One
person consulted a community health worker
but did not pay at all.

Table 4.2 shows the distribution of selfreported illnesses by cause over the last two
weeks prior to the survey. Overall, regardlessof sex and age, the most common cause wascough/cold/chest infection, followed byheadache and fever/ malaria. Some illnesses
are more common among young children thanamong adults, such as cough/ cold/chest
infection, and diarrhoea of any kind.

4.4. Consultation for illness/
Injury and Medical Costs

The bottom rows of Table 4.3 show thepayment methods. The majority did not pay atall. Excluding them, the majority covered the
medical expenses by themselves. The use of
pre-payment schemes and payments byemployers or insurance were also reported,
especially for patients who consulted medical
doctors.

All persons who reported illnesses or injuries
were asked to give the amount paid for
medical consultation or medication. Table 4.3
gives the proportions of those consulting
medical doctors, clinical officers, nurses or
midwives and community health workers, andthe average amount spent on consultations

Table 4.3: Medical Expenditure and Methods of Payment
MedicalClinicalNurses /Community

doctors

officers

midwives

health workers

Proportion of those consulting, %

23.4

53.7

22.6

0.2

Average expenses (Kwacha)

161.2

9.3

6.5

0

Among those who paid

319.8

49.4

38.5

n/a

Method for payment, %Pre-payment scheme (low cost)

3.2

0.8

n/a

n/a

Pre-payment scheme (high cost)

5.9

1.8

n/a

n/a

Paid by employer

8.6

0.4

0.7

n/a

paid by insurance

2.3

n/a

n/a

n/a

Paid directly

39.9

14.8

8.8

n/a

Paid by others

n/a

1.8

1.5

n/a

Did not pay

38.2

83.2

86.1

100

No information

6.3

3.7

2.9

n/a

Sample weights used.

23

4.5. Child Health (Age under 5
years)

sex and age group. Overall, the proportion of
infants aged 0-11 months who were breastfed
is similar to the national average in the LCMS
2015. Among young children aged 13-24
months, the proportion is higher in Kabwe
than the national average. The proportion ishigher for male than for female among those
aged 0 years (0-11 months old), but higher for
female than for male among those aged 1
years (12-23 months old). Note that the
sample size becomes small if we split the
sample by age and sex. Therefore, thesefigures do not necessarily point out a genderdifference in breastfeeding statuses.

In addition to the health measurements
described so far, the KHSS 2017 measured
breastfeeding and other dietary statuses andhistories for children younger than 5 years old.
Breastfeeding is closely related to infants’nutritional statuses and plays a significant rolein child development. However, it can also be
related to lead exposure if mothers are
exposed to high levels of lead.
Table 4.4 shows the proportion of children
under 5 years old who were being breastfed by

Table 4.4: Proportion of Infants Who Were Breastfed at the Time of the Survey
Age

Total

Male

FemaleTotal Zambia*

0 year

94.4

97

90.8

95.6

1 year

71.5

67.1

76

50.5

2 years

3.2

4.4

1.3

6.9

3 years

3.8

3.6

4.1

4 years

5.2

6.2

3.8

2.8**
Sample weights used. * Data from the LCMS 2015. ** The proportion among children aged 3 or 4 years.

Table 4.5: History on Breastfeeding and Other Foods
Lengths of
Neverbreastfeeding,breastfed, %monthsother than breastmilk

Total

1.3

15.8

5.5

Male

0.9

15.4

5.5

Female

1.7

16.4

5.5

Sample weights used.

24

Age in months when given any foodFinally, Table 4.6 shows how frequently
children were given solid food. For all sexes
and age groups, 45.2% of the children were
given solid food thrice a day. Females were
given solid foods less frequently than males,with the proportion of children given solid
food twice a day being higher for females andthe proportion of children given solid foodthrice a day being higher for males. Regarding
the age groups, the dietary characteristics ofchildren aged 1, 2 and 3 years old are similar.

In Table 4.5, we focus on children who were notbeing breastfed at the time of the survey. Amongthem, 1.3% had never breastfed. Children arebreastfed for 15.8 months on average and this isconsistent with the figures in Table 4.4 where
almost all children stop being breastfed by thetime they reach 2 years of age. Children start
consuming any food other than breastmilk at theage of 5.5 months on average. No significant
gender difference is found.

Table 4.6: The Distribution of the Numbers of Times Given Solid Food Per Day
More
Four

Five

than five Not yet started

Once

Twice

Thrice

times

times

times

on solids

Kabwe total

3.8

22.3

45.2

15.2

4.6

2.1

6.8

Male

3.4

19.3

48.4

15.3

4.2

2.1

7.1

Female

4.2

25.9

41.2

15.2

5.0

2.0

6.4

Aged 0 year

4.4

31.1

20.0

6.2

1.9

3.5

33.1

Aged 1 year

4.7

23.8

46.6

18.1

3.4

2.5

0.8

Aged 2 years

3.7

22.7

48.3

18.0

5.7

0.7

0.8

Aged 3 years

4.5

23.6

48.0

15.1

5.6

2.7

0.5

Aged 4 years

1.6

10.8

60.9

18.3

6.4

0.7

1.2

Zambia*

3.4

23.9

44.0

12.4

3.0

2.5

10.7

Sample weights used. * Data from the LCMS 2015.

25

Chapter 5
Economic Activity
5.1. Introduction

aggregated at ward levels are also presented.
The sample weights are applied in calculations.
The categorical classification follows thedefinition adopted by the LCMS 2015.
“Economically active population (labour
force)” consists of “paid employment(including self-employed)”, “un-paid family
worker,” and “not working”. The category of“not working” is constructed from two typesof status: “looking for work/means to dobusiness but available for work/business” and“not looking for work but available forwork/means to do business.” The percentages
for all Zambia and urban Zambia based on the
results of the LCMS 2015 are also listed forreference.

The KHSS 2017 collected detailed
information regarding the economic activities
of household members. The economic
participation of the population in various
economic activities can directly influence
households’ well-being. The topics covered by
the survey are as follows:

Economic activity status including labour
force participation, type of job and sectorof employment for the main economic
activity, second job, and other incomegenerating activities.
Wage income, which includes regularmonthly wages or salary, allowances,other income in-cash/in-kind.
Labour time, which includes actual
working hours in the last seven days,
usual working hours, missed working
days due to illness in the last 12 months.

The share/proportion of economically active
population and that of paid employment in
Kabwe are estimated at 57.7% and 39.6%,
respectively. These shares are similar to thoseof the urban averages in all Zambia (58.6%
and 40.0%, respectively). However, thebreakdown of the economically inactive
population in Kabwe district shows somedifferent features. The proportion of full-timestudents, accounting for 21.4%, is lower thanthat of Zambia or urban Zambia. Additionally,
the proportion of the population that is retired,
too old or too young to work in the Kabwe
district is 10.6%, which is more than two times
the averages for all Zambia and urban Zambia.

With regards to economic activity status andwage, the KHSS 2017 adopted a similar
format to that used by the LCMS 2015. The
topic of labour time was new.

5.2. Economic Activity Status
Table 5.1 shows the percentage distribution of
the main economic activity status for the
population aged 12 years or older in Kabwe
district. The percentage distributions

The regional variation of economic activity
26

within Kabwe district is recognizable in Table
5.1. The ratios of “not working” are relatively
low, less than 10%, in wards located in the
peripheral regions of the district such as
Chililalila, Chinyanja, Mpima, and Munyama

where a large proportion of households
engage in agricultural activities. Nevertheless,the worst ratio of “not working” is observed in
Makululu ward and reaches 25.5%.

Table 5.1: Percentage Distribution of the Population Aged 12 Years or Older by Main Economic
Activity, and Ward
Economically active population(Labour Force)

Total

Economically inactive population

UnpaidFull

Retired/Paid

Family

Not

Total

Time

Home-

Too Old/

Total

Total

Employment

WorkerWorking(active)

Student

Maker

Too YoungOther(inactive)

district

39.6

0.6

17.5

57.7

21.4

9.1

10.6

1.1

42.2

100

Zambia*

43.0

6.3

9.2

58.5

27

10.3

3.8

0.4

41.5

100

Urban*

40.0

1.2

14.2

55.4

27.8

12.3

4.3

0.2

44.6

100

Bwacha

37.1

0.6

20.4

58.1

19.9

6.1

14.0

1.9

41.9

100

Chililalila

40.3

0.0

4.2

44.5

20.8

19.4

15.3

0.0

55.6

100

Chinyanja

50.0

1.6

4.8

56.5

21.0

14.5

8.1

0.0

43.6

100

Chirwa

39.8

0.3

20.7

60.7

23.4

8.4

7.1

0.4

39.3

100

Ramushu

36.2

0.0

21.2

57.4

28.1

7.6

5.7

1.2

42.6

100

Highridge

34.2

0.0

21.5

55.7

26.6

7.6

8.9

1.3

44.3

100

Kalonga

39.4

0.0

16.6

56.0

25.8

5.3

10.1

2.8

44.0

100

Kangomba

48.0

2.9

11.4

62.3

20.8

5.3

9.1

2.5

37.7

100

Kaputula

33.0

0.0

19.2

52.2

15.9

12.9

18.1

0.9

47.8

100

Makululu

38.8

0.0

25.5

64.2

20.4

8.8

6.6

0.0

35.8

100

Moomba

39.1

1.0

15.8

56.0

22.8

9.7

11.3

0.2

44.0

100

Mpima

60.6

0.0

6.1

66.7

7.6

12.1

12.1

1.5

33.3

100

Munyama

40.2

3.8

8.7

52.7

24.6

15.2

7.0

0.5

47.3

100

East

40.2

0.0

16.8

56.9

22.8

10.9

8.4

1.0

43.1

100

Waya

33.3

1.1

17.8

52.2

16.7

6.7

21.1

3.3

47.8

100

Zambezi

46.2

1.3

17.0

64.5

15.7

9.0

10.3

0.4

35.5

100

Kabwe

WARD

David

MuwowoSample weights used. * Data from the LCMS 2015.

27

Figures 5.1 and 5.2 show distributions oflabour force participation rates by age group
among persons aged 12 years or older. Here,the labour force participation rate is the ratioof the “economically active population” asdefined above to the total population for eachage group. Figure 5.1 compares labour force

participation across age groups in Kabwe
district to those of Zambia total and urban
Zambia. The distribution for Kabwe shows asimilar tendency to that of urban Zambia, andthe participation rate starts declining rapidly
after age 50. Figure 5.2 shows the genderdifference of the distributions within Kabwe.

100

120.0

80

100.0
80.0

60

60.0

40

40.0

20

20.0

65+

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

12-19

Zambia total
Urban of all Zambia
Kabwe district

20-24

0.0

65+

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

12-19

0

Kabwe districtmale
femaleZambia total
Urban of all Zambia
Kabwe district

65+

60-64

12-19

65+

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

12-19

0

55-59

20

50-54

40

45-49

60

40-44

80

35-39

90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0

30-34

100

25-29

Figure 5.2: Labour Force Participation
Rates among Persons Aged 12 Years or
Older by Age Group and Gender.

20-24

Figure 5.1: Labour Force Participation
Rates among Persons Aged 12 Years or
Older by Age Group

Kabwe district
Male
FemaleFigure 5.3: Unemployment Rates among
Persons Aged 12 Years or older by Age
Group

Figure 5.4: Unemployment Rates among
Persons Aged 12 Years or older by Age
Group and Sex
28

Figures 5.3 and 5.4 present distributions of
unemployment rates by age group among
persons aged 12 years or older. Here, theunemployment rate is estimated as the ratio of“not working” to the “economically active
population”. The pattern of the distribution in
Kabwe district resembles that of the urban
average of Zambia more closely than that of
all Zambia, but the unemployment ratio in
Kabwe becomes slightly higher after age 30

than the Zambian urban average. In particular,a high ratio of unemployment is observed in
the 55–59 age group in Kabwe, at 17.3%. Thisappears to be a peculiar feature of employment
status. Figure 5.4 confirms that the high ratiosof unemployment in the 50–54 and 55–59 age
groups in Kabwe are more distinct in thefemale population, accounting for 23.7% and20.1%, respectively.

Table 5.2: Percentage Distribution of Employed Persons Aged 12 Years or Older by Industry

total*

Kabwe district
Urban of all Both
Zambia*sexes
male

femaleAgriculture, forestry and fisheries

58.7

11.2

19.8

21.4

17.7

Mining and quarrying

1.7

4.0

1.7

2.8

0.2

Manufacturing

4.2

8.2

1.9

2.8

0.8

Electricity, gas, steam and air condition

0.4

1.1

1.2

2.2

0.0

Water supply sewerage, waste management

0.1

0.2

0.3

0.2

0.3

Construction

3.7

8.1

10.2

17.5

0.7

Trade, wholesale and retail distribution

14.9

31.1

20.2

12.3

30.5

Transportation and storage

2.5

5.8

5.6

9.6

0.3

Accommodation and food service activities

1.0

2.3

4.5

1.4

8.6

Information and communication

0.4

1.1

0.3

0.3

0.3

Financial and insurance activities

0.8

2.0

1.1

1.3

0.9

Real estate activities

0.1

0.3

0.2

0.3

0.0

Professional, scientific and technical

0.3

0.8

0.9

1.0

0.7

Administrative and support services

1.1

2.4

0.6

0.3

1.1

Public administration and defense, comp

1.7

4.2

2.6

2.9

2.2

Education

3.3

6.4

6.5

5.1

8.4

Human health and social work

1.4

2.9

2.4

2.3

2.5

Arts, entertainment and recreation

0.1

0.3

1.3

1.2

1.3

Other service activities

1.5

3.5

7.7

7.3

8.3

Activities of household as employers

1.8

4.0

1.3

0.0

3.0

Activities of extraterritorial organization

0.0

0.0

0.7

0.8

0.6

Other / not stated

0.0

0.0

9.0

7.0

11.6

Total

100.0

100.0

100.0

100.0

100.0

ZambiaSample weights used. * Data from the LCMS 2015.

29

Table 5.3 shows the proportion of employedpersons by occupation type. In Kabwe,occupation types such as service and sales
workers (24.5%), skilled agricultural (16.4%)
or craft and related trades workers (11.7%) are
the most common. When compared with thoseof averages in all Zambia and urban Zambia,

the proportions of these occupation types in
Kabwe fall in the middle. It is also found that
more females in Kabwe are employed asservice and sales workers (33.1%), and moremales are employed as craft and related trades
workers (18.2%) in Kabwe.

Table5.3: Percentage Distribution of Employed Persons Aged 12 Years or Older by Occupationand Sex
Kabwe District
Zambia*

Both
sexes

Male

Female

1.8

3.6

2.1

1.8

2.4

5.2

9.9

10.8

9.4

12.6

Technicians and associate professionals 1.7

4.1

2.1

3.1

0.7

Clerical support workers

0.9

2.3

2.3

1.8

2.8

Service and sales workers

16.9

36.9

24.5

18.0

33.1

51.8

9.6

16.4

17.8

14.7

6.4

13.0

11.7

18.2

3.2

Plant and machine operators, andassembly
3.4

7.5

1.2

2.1

0.0

Collecting
mountain

-

-

0.3

0.5

0.0

Other elementary occupations

11.6

12.6

10.9

11.5

10.1

Armed forces

0.2

0.5

2.7

3.5

1.7

Other / Not stated

0.0

0.0

15.1

12.3

18.8

Total

100.0

100.0

100.0

100.0

100.0

ZambiaUrban of all

total*

Managers
Professionals

Skilledfishery

agricultural,

forestry

andCraft and related trades workers

minerals

from

black

Sample weights used. * Data from the LCMS 2015.

30

5.4. Labour Timewas 44.4 hours. However, 14.3% of those who
worked claimed that they worked shorter
hours than usual. Regarding the last 12 months,
18.2% of those who had jobs reported missing
more than five days owing to illness or injury.
Table 5.4 also illustrates the regional
differences of those data.

Table 5.4 summarises the results of labour
time data. Among those in Kabwe who havejobs (paid or unpaid), the proportion of those
who actually worked in the last seven days
was 77.1%, and their average working time

Table 5.4: Labour Time (Aged 12 Years or Older)
For those who have jobs (paid or unpaid) aged 12 years or older
Last 7 days

Kabwe district

Last 12 months

Average% who missed more than

% who actually working% who worked 5 days due to illness andworkedshorter than usualhours

injuries

77.1

44.4

14.3

18.2

Bwacha

78.9

44.4

24.6

16.9

Chililalila

79.3

47.1

17.4

6.9

Chinyanja

56.3

40.1

44.4

12.5

Chirwa

82.8

44.9

11.4

13.2

David Ramushu

85.2

44.8

5.2

15.9

Highridge

74.1

39.4

10.0

7.4

Kalonga

66.8

42.7

9.2

34.0

Kangomba

54.3

42.7

17.4

28.9

Kaputula

68.9

41.6

17.1

22.5

Makululu

83.0

53.7

9.1

18.9

Moomba

83.9

45.7

6.3

21.1

Mpima

72.5

30.1

51.7

12.5

Munyama

81.5

45.2

19.9

16.2

Muwowo East

86.7

44.2

24.7

19.1

Waya

61.3

46.5

5.3

25.8

Zambezi

81.4

46.7

7.2

3.7

Sample weights used.

31

Chapter 6
Household Crop and Livestock Production
6.1. Introduction
Rates of participation showed a heterogeneous
picture by ward (Figure 6.1). Wards with thehighest participation in agriculture were
Chinyanja (95%), Munyama (88%), Mpima(81%), Kangomba (75.5%), and Chililalila(68%). The remaining wards had lower than
average (41.7%) participation rates with
Moomba (11.7%), Makululu (20.4%), andDavid Ramushu (20.6%) showing the lowest
participation rates.

The KHSS 2017 collected information on
agricultural activities relating to the
2016/2017 farming season. The collected data
include the following: Household participation in agriculturalactivities
 Production of crops such as maize, sweet
potatoes, potatoes, and soya beans among
agricultural households
 Livestock and poultry ownership Use and cost of various crop andlivestock inputs
 Size of farms and home gardens

6.3. Crop Production
About half of all agricultural households were
engaged in hybrid maize production, which isthe same as the national average recorded by
the LCMS 2015 (Figure 6.2). However, theshare of agricultural households growing local
maize in Kabwe was higher (44.1%) than thenational average (35.9%) but close to theaverage for the urban areas in Zambia (46.4%).
A higher share of households in Kabwe grew
sweet potatoes and soya beans than in thewhol e count r y ( 22.8% vs. 8.2 % and6.2. Agricultural Households
The percentage of households engaged inagricultural activities in Kabwe (41.7%) was
lower than the national average (58.7%), as
reported in the LCMS 2015 (Table 6.1).
However, the percentage was higher than the
average of the urban areas in the wholecountry (17.9%).

Table 6.1: Proportion of Households Engaged in Agricultural Activities
Allhouseholds

Agricultural households
Number

Per cent

Whole Kabwe district

49,056

20,456

41.7

Zambia total*

30,15,000

1,769,805

58.7

Urban area of all Zambia*

12,97,000

232,163

17.9

Sample weights used. * Data from the LCMS 2015.

32

Chinyanja
Munyama
Mpima
Kangomba
Chililalila
Muwowo East
Kaputula
Waya
BwachaKalonga
ChirwaZambezi
Highridge
David Ramushu
Makululu
Moomba

0

10

20

30

40

50

60

70

80

90

100

Zambia

0.4
0.2
0.7

3.7
10.1

4.9

7.5
2.3
4.5

8.3

22.1

Zambia Urban

8.7
6
11.2

12.2

22.8
8.2
12.8

13.7
21.4
31.1

Kabwe

44.1
35.9
46.4

49.9
49.6
44.5

Figure 6.1: Percentage of Households Engaged in Agricultural Activities by Ward

Figure 6.2: Proportion of Agricultural Households Producing Each Crop in Kabwe, Urban
Areas of Zambia, and the whole Zambia

33

6.4. Livestock and Poultry
Production

7.5% vs. 2.3%, respectively). Nonetheless, theproportion of households growing groundnuts
and cassava was lower in Kabwe than thenational or urban averages.
On average, each household produced 57 bagsof hybrid maize (Table 6.2). The average
production of soya beans was 31 bags (90 kg
per bag) per household. A typical agricultural
household in Kabwe produced about 11 bags
(25 kg per bag) of sweet potatoes. The
quantity produced for fruit vegetables (e.g.,
tomatoes) was 106 bags (25 kg per bag) per
household.

At the time of the survey, most households in
Kabwe district owned chickens (86.7%) andeach household owned an average of 66 birds.
Goats were the second most owned type of
livestock (25.1%), followed by cattle (23%).
Each household kept an average of 13 goatsand 26 cows.

Table 6.2: Agricultural Households Producing Each Crop
and Quantity Produced

Crop

Proportion of Average household
agricultural production
households
Units
Quantity
growing thecrop, %

Table 6.3: Livestock and Poultry
Owned by Agricultural Households
Livestock Percentage oforhouseholds
poultryowninglivestock andpoultry

Averagenumbersowned
perhousehold

Maize (all types)

88.4

50kg Bag

57.0

Cattle23.0

26

Hybrid Maize

50.0

50kg Bag

77.0

Chicken

86.7

66

Local Maize

44.1

50kg Bag

25.0

14.4

6

groundnuts

13.7

90kg Bag

4.4

Ducks
and Geese

Mixed Beans

8.7

90kg Bag

0.4

Goats

25.1

13

Soya Beans

7.5

90kg Bag

31.0

6.0

17

leaf vegetables(e.g. cabbage)

Guineafowls

12.2

50kg Bag

17.5

Pigs

9.1

18

Quails

1.7

19

Rabbits

1.8

9

Sheep

1.2

7

Root vegetables(e.g carrots)

4.9

10kg Bag

2.8

fruit vegetables(e.g. tomatoes)

8.3

25 kg Bag

106.0

Turkeys

3.1

7

cassava

3.7

90kg Bag

0.2

Pigeons

1.0

12

Irish potatoes

0.4

10kg Bag

10.0

Sample weights used.

Sweet Potatoes

22.7

25 kg Bag

11.0

Sunflower

1.4

90kg Bag

2.4

Sample weights used.

34

6.5. Crop and Livestock Inputs

farmers used the input, the costliest crop
inputs were fuel (K5,888), irrigationequipment (K4,518), repair and maintenanceof
agriculturalequipment(K1,458),
insecticides (K1,369), and transport (K723).
Hand tools were the cheapest crop input.

Among the crop inputs used by more than
40% of households, the costliest were
inorganic fertilizer (K1,834), hired labour(K1,437), and seeds/seedlings (K810) (Table
6.4). In general, regardless of how many

Table 6.4: Percentage Using Different Crop and Livestock Inputs and Average Cost
Percentageofagri- Average

cost

cultural households using input (ZMW)
input by type
Crop Inputs
Transport

23.3

722.6

Sack or bags/containers

50.1

245

Fertilizer (Inorganic)

60.8

1,834

Fertilizer (organic)

24.0

1,857

Herbicides

9.8

1,773.6

Hired animals

13.0

402

Hired equipment

6.9

602

Hired labour

48.9

1,437

Imported hand tools

1.6

109.3

Storage facility

14.0

196.2

Local hand tools

41.6

104.4

Insecticides

28.0

1,369

Irrigation Equipment

2.5

4,518

Fuel

5.3

5,888

Seed, seedling, etc.,

64.6

810

Repair/maintenance of agricultural equipment

6.6

1,458

Transport

14.3

1,004

Animal Feed

48.3

4,784

Hired labour

11.9

2,926

Maintenance of pens/stables

15.5

321

Veterinary services

41.4

667

Penalties for damage caused by animals

6.7

323

Animal sales agents

4.1

357

Other livestock related inputs

7.0

3,157

Livestock Inputs

Sample weights used.

35ofFor livestock inputs, animal feed was the mostexpensive (K4,784) and most commonly used
input (48.3% of all agricultural households).
About 11.9% of households used hired labour,
costing them an average of K2,926.
Agricultural households that used transport
services for their livestock (14.3%) spent
K1,004 on average. Veterinary services wereused by about 41.4% of households and it cost
K667 on average.

Table 6.5: Average Size of Farm Landand Home Garden by Ward (Acres)
RegionFarmHome garden

33.4

2.6

Bwacha11

0.3

Chililalila

10

1.1

Chinyanja

48.1

1.5

Chirwa

44

0.35

David
Ramushu

50.62Highridge

00Kalonga8

0.39

Kangomba

14

11.88

Kaputula

6

0.242

Makululu

3

0.46

Moomba

96

0.62

Mpima

8.98

2.11

Munyama134

1.88

Muwowo East

16

0.397

Waya

4

0.453

Zambezi47

4.19

Whole Kabwe
districtWards

6.6. Size of Farm and Home
Gardens
The average farm size in Kabwe district was
33.4 acres (13.2 hectares), and home gardens
were 2.6 acres on average.
Households in Munyama had the largest farmsizes (134 acres), followed by Moomba (96acres), Chinyanja (48.1 acres), and Zambezi(47 acres). Households in Highridge had nofarms while those in the Makululu area hadtiny farms.

Sample weights used.

Households in Kangomba had the biggest
home gardens (11.9 acres) followed by thosefrom Zambezi (4.2 acres), Mpima (2.1 acres),Munyama (1.8 acres), Chinyanja (1.5 acres),and Chililalila (1.1 acres). The remaining
wards had gardens smaller than one acre.

36

Chapter 7
Household Income and Assets
7.1. Introduction

and income from non-agricultural business in
the last month prior to the survey. Income
from the other sources listed above was asked
in the yearly basis in the survey but is rescaled
to a monthly equivalent here. Throughout thissection, we focus on 860 households thatreported positive household incomes ― 35
households (3.9% of the total sample
households) are dropped from calculation. All
the monetary terms are expressed in Kwacha,
the national currency of Zambia abbreviatedto K. All the calculations here use samplingweights.

The KHSS 2017 collected data on income for
persons aged five years or older. The
calculation of household income includes thefollowing income sources:









Wage income of all household members,
including both cash and in-kind payments
Income from non-agricultural business of
all household members
Profit from agricultural production,
including the foregone profit of domestic
consumption
Rental income from properties owned
Income from interest or dividends onshares, bonds, securities, etc.
Income from pensions and grants
Income from remittances, gifts, and otherexternal sources

Table 7.1 first shows the monthly householdincome and per capita household income. The
means of total monthly household income andits per capita variation are K3,492.7 andK764.9, respectively. These figures are larger
than the Zambian average but are similar to
the average of urban Zambia in the LCMS
2015 data.

While income captures monetary flow,
ownership of assets and durable goods is also
useful for measuring the cumulative wealthlevels of households. Asset ownership also
provides information on the ability ofhouseholds to produce further income andbuffer against income shocks. The survey
asked whether a household owns each of 63
items. Borrowed or permanently broken items
were not counted.

The remainder of Table 7.1 shows thebreakdown of the mean household income.
The two largest income sources are wage
income and non-farm business income,constituting 53.6% and 25.5% of the total
income, respectively. The share of agricultural
profit is small, constituting only 4.6% of thetotal income, partly because Kabwe district isbasically an urban area. Although 41.7% ofhouseholds engage in farming (see Chapter 6),
most of them do their farming in home

7.2. Household Income
The survey asked about monthly wage income37

gardens and small-scale farms. The shares ofpension, rental income and remittances receipt
are not very large, either, although thesesources of income would be crucial forhouseholds that do not have labour income.

partly because incomes of temporarily
unemployed persons and persons whosebusinesses were in off season were recorded
as zero. However, quite a large proportion ofhouseholds had total household income larger
than K10,000 and per capita householdincome larger than K2,000 (both are roughly
three times larger than the means and six times
larger than the medians). Thus, income
inequality seems severe within Kabwe district.

Figure 7.1 shows the distributions of total andper capita household incomes. For both total
and per capita household incomes, a large
proportion of households are concentrated at
the tail end. This uneven distribution would be

Table 7.1: Average Monthly Household Income and its Breakdown (In Kwacha)
Total Household Income

Per Capita Household Income

Total Kabwe

3,492.7

764.9

Zambia total*

1,801.3

444.2

Urban area of all Zambia*

3,152.4

796.4

Breakdown of Total Household Income in Kabwe
Labour income
Wage income

2,998.0 Pension

50.7

1,871.3 Grants

12.7

Irregular allowances

188.4 Rental income

100.3

Non-farm business income

889.0 Interests

13.9

In-kind labour income

49.2 Dividends of shares, bonds,
160.4 securities, etc.

17.9

Sales

283.9 Remittances receipt

92.0

Domestic consumption

36.1 Gifts receipt

13.6

Costs

159.6 Income from any other source

33.2

Agricultural profit

Sample weights used. * Data from the LCMS 2015.

38

25.0%

Total Household Income

20.0%
15.0%
10.0%
5.0%
0.0%

25.0%

Per Capita Household Income

20.0%
15.0%
10.0%
5.0%
0.0%

Figure 7.1: Distributions of Monthly Total and Per Capita Household Income (Weights Used)

Table 7.2 shows heterogeneity in householdincome and per capita household income withrespect to gender of the household head andward. As it may be expected, both total and per
capita household incomes are larger in maleheaded households than in female-headedhouseholds. Total and per capita householdincomes also show substantial variation acrosswards. The wards with the highest mean
incomes are located east and within a shortkilometre distance from Kabwe town centre.
Meanwhile, in wards located in Makululu
compound, west of the city centre, which

include Makululu, Moomba and Zambezi
wards, household income is less than half ofthe entire Kabwe mean.

7.3. Ownership of Household
Assets and Durables
Table 7.3 shows the proportion of households
owning each of 63 items of assets anddurable goods, where the sampling weights
are used. Items owned by more than 80% ofhouseholds include beds, mattresses, cellular
phones, and braziers (mbaula). Electronic
39

Table 7.2: Total and Per Capita Monthly Average Household Income by Gender of Headof Household and Ward
Total household income
All

Male

households headed

Per capita household income
FemaleAll

Maleheadedhouseholds headed

FemaleheadedTotal Kabwe

3,492.7

3,901.9

2,179.1

764.9

827.6

563.5

Bwacha5,513.3

6,159.2

4,245.8

1,174.2

1,090.3

1,338.9

Chililalila

1,452.5

1,552.3

355.4

506.3

538.7

150.1

Chinyanja

1,071.1

1,174.1

710.5

291.7

334.9

140.5

Chirwa6,343.1

7,235.4

3,247.0

1,577.3

1,784.6

857.8

David Ramushu

3,888.5

4,142.2

3,157.5

835.3

745.8

1,093.3

Highridge

11,449.2

11,649.6

10,313.9

3,376.5

3,682.6

1,641.7

Kalonga

3,903.6

4,218.2

3,124.2

815.1

805.4

839.1

Kangomba

2,171.0

2,379.6

1,307.6

441.3

495.4

217.2

Kaputula

3,022.5

3,287.4

1,779.4

596.3

604.0

559.7

Makululu

1,500.6

1,655.6

1,167.3

342.3

372.7

276.9

Moomba1,556.7

1,912.5

832.0

282.5

337.4

170.8

Mpima

581.7

636.4

344.6

124.7

139.8

59.6

Munyama

2,648.4

2,657.2

2,575.1

557.6

574.5

415.7

Muwowo East

2,914.8

3,640.9

648.7

473.8

583.0

132.7

Zambezi

1,237.7

1,422.2

481.3

218.7

242.0

122.9

Waya

6,241.1

6,548.3

5,319.6

1,319.8

1,417.4

1,027.0

Sample weights used.

durables, such as televisions, electric stovesand refrigerators were owned less. Proportionsof ownership of these items are close to theurban averages in the LCMS 2015 data.
Ownership of cars is limited, and its
ownership rate is lower than the urban averagein the LCMS 2015 data. Meanwhile, bicycle
ownership is almost twice the urban averagein the LCMS 2015 data. Ownership ofagricultural production instruments is limited
basically because few households engage in
middle to large-scale farming. Among all
items, no households own boats and donkeys(indicated as n/a in table).

40

Table 7.3: The Ownership Rates of Various Assets and Durables
Assets / durables

The

Assets / durables

The

Assets / durables

The

rate

rate

rate

(%)

(%)

(%)

Bed

87.9

Electric stove

34.4

Fishing net

2.7

Mattress

91.8

Refrigerator

24.0

Hunting gun

1.2

Mosquito net

68.1

Deep freezer

33.4

Plough6.0

Table (dinning)

53.6

Washing machine

1.5

Crop sprayer

7.6

Lounge suit / sofa

63.6

Dish washer

4.8

Knitting machine

0.9Radio / Stereo

62.4

Air

Lawn mowers

0.7

Generator

3.0

Television
Satellite

58.9
dish

/

decoder (free to air)Satellite

dishdecoder (DSTV)/

conditioner/

ventilator

2.2

Electric iron

38.8

Small / hand-drivenNon-electric iron

28.0

tractorPrivate water pump

4.0

4-wheel tractor

0.9

Sewing machine

3.9

Wheel barrow

18.0

2.9

Scotch cart

2.2

Bicycle39.5

Motor cycle

1.9

Large truck

0.7

21.9

0.5

31.6

Other pay TV

20.0

Hand hammer mill

DVD / VCR

37.6

Grinding / hammer millHome theater

25.9(powered)Land phone

1.9

Sheller

Cellular phone

84.5

Ramp

1.3
1.2

presses

/

oil

0.5

Small

/

pick-up

14.1

expellers

Watch

26.6

Hand saw

4.5

Van / minibus

1.8

Clock

33.8

Carpentry plane

3.7

Car

10.1

Residential building

48.8

Axe

50.7

Canoe

0.7

Pick

45.2

Boat

n/a

Hoe

77.6

Oxen

3.0

Donkeyn/aNon-residentialbuilding

truck

1.4

Computer

8.5

Brazier / Mbaula

92.8

Hammer

37.3

Gas stove

1.9

Shovel / spade

48.2

Sample weights used.

41

Chapter 8
Expenditure
8.1. Introductionin the marketplace, self-produced food, fooditems received as gifts, relief food or food-forwork, and food taken or eaten outside thehome. These items were asked for two recall
periods: the last two weeks and the last fourweeks prior to the survey, depending onwhether the items were frequently or
infrequently purchased. In this section, allitems were converted into monthly values.

Household expenditure, which plays a vitalrole in household welfare, is the mostcommonly used measure for assessing living
standards or poverty of households indeveloping countries. The KHSS 2017
collected data on the following household
consumption expenditures:












Expenditure on food, which includes
expenses for cereals, crop products,
meats, dairy, fish, and domestic
consumption on self-produced foods.
Educational expenditure, which includes
expenses on fees, tuition, textbooks anduniforms.
Medical expenses, which include
expenses for medicine, fees for doctors,
and fees for hospital stays.
Expenditure on housing and utility, which
includes expenses on rents of dwelling,
electricity, water.
Remittances, which include cash and inkind remittances sent to inside andoutside Zambia.
Other expenditure, which includes
expenses for consumer goods, transport,
mobile phones, etc.

The estimated expenditure on housing
services was based on the data for the rental
value of the dwelling. Even if the household
occupies their own dwelling, we asked themto estimate how much it would earn per monthif they were to rent out that house. Theirestimate was imputed to be the rental value of
their dwelling.

8.2. Average Monthly
Expenditure
Table 8.1 shows means of monthly household
expenditures, food and non-food expenditures,and per capita expenditure. We calculated
mean values for the entire Kabwe district andfor each ward investigated by the KHSS 2017using the sample weights. The values for all
Zambia and urban Zambia derive from theresults of the LCMS 2015.

Food expenditure consists of food purchased

42

Table 8.1: Average Monthly Household Expenditure
Household Expenditure
Total

Food

%
of NonFood/Total Food

Per capita
expenditure

Whole Kabwe district

3,532

1,264

36

2,268

773

Zambia total*

1,588

645

41

943

388

Urban area of all Zambia*

2,680

930

35

1,750

675

Bwacha

4,284

1,291

30

2,993

918

Chililalila

1,389

566

41

823

329

Chinyanja

2,214

840

38

1,374

673

Chirwa

5,413

1,649

30

3,763

1,313

David Ramushu

3,052

1,043

34

2,010

658

Highridge

9,995

2,207

22

7,788

2,688

Kalonga

3,653

1,194

33

2,459

817

Kangomba

3,670

2,024

55

1,646

849

Kaputula

4,138

2,015

49

2,122

719

Makululu

1,793

921

51

872

424

Moomba

1,559

694

44

865

294

Mpima

866

499

58

367

177

Munyama

3,719

860

23

2,859

798

Muwowo East

3,673

1,291

35

2,383

761

Waya

5,495

1,768

32

3,727

1,106

Zambezi

1,447

596

41

851

286

WARD

Sample weights used. * Data from the LCMS 2015.

The means of monthly household expenditureand per capita expenditure in the Kabwe
district are estimated as K3,532 and K773,
respectively. These values are considerably
higher than the averages of all Zambia, whichsuggests that the residents in Kabwe enjoy arelatively higher living standard compared toother locations in Zambia. The share of foodexpenditure to the total expenditure in Kabwe
accounts for 36% and shows a similar ratio tothat of the urban average in Zambia (35%).

levels across wards within Kabwe are large.
Overall, wards with highest expenditure levels
are concentrated in the city centre, locatednortheast from the mining site, including
wards such as Highridge, Chirwa, or Waya.
The average monthly household expendituresin these wards exceeds K5,000. Conversely,
most of the wards with lowest expenditurelevels spread toward the northwest from themining site, such as Moomba, Makululu,
Zambezi, and Chililalila. Their averagemonthly household expenditure does notreach K2,000. In the outer southern rural areas,

However, the regional gap of expenditure
43

such as Munyama, the expenditure level
equals the average level of Kabwe.

Compared to the income distributions(Figures 7.1 and 7.2), the expenditure
distributions show slightly more moderatevariation. Nevertheless, substantial inequality
is confirmed in terms of expenditure levels in
Kabwe.

Figures 8.1 and 8.2 show the distributions ofmonthly household expenditure and monthly
per capita household expenditure, respectively.

20.0%
15.0%
10.0%
5.0%
0.0%

Figure 8.1: Distribution of Monthly Household Expenditure (total household)
20.0%
15.0%
10.0%
5.0%
0.0%

Figure 8.2: Distribution of Monthly Household Expenditure (per capita)44

8.3. Percentage Share ofHousehold Expenditure by
Expenditure Typeare similar to those of the urban average in
Zambia. However, the breakdown of non-food
expenditure indicates some peculiar features.
In Kabwe, the expenditure share for housing,which includes expenses on rental of
dwellings and fees for electricity or water, isrelatively low, while the share for healthexpenditure is relatively high compared withthe averages in all Zambia and urban Zambia.

Table 8.2 shows the expenditure pattern ofhouseholds in Kabwe. The values in all
Zambia and urban Zambia derive from theresults of the LCMS 2015. The average sharesof food and non-food expenditures in Kabwe

Table 8.2: Percentage Expenditure Share by Expenditure Type
Expenditure Share

Zambia*Urban*

Kabwe District

Total

100

100

100.0

Food

40.3

34.2

35.8

Non-food

59.7

65.8

64.2

Education

6.3

6.7

6.1

Housing

26.9

30.4

20.3

Health

0.3

0.3

0.8

Other

26.2

28.4

36.7

Sample weights used. * Data from the LCMS 2015.

45

Chapter 9
Household Housing Condition
9.1. Introduction
The KHSS 2017 collected information on the
housing conditions of people in the Kabwe
district. Housing conditions have a direct
bearing on well-being. For example, poor
housing conditions such as lack of access toclean drinking water or undeveloped housing
units may increase exposure to environmental
aspects that could be harmful to health. The
KHSS 2017 collected the following
information:








Type of housing unit: This was as definedin the LCMS 2015, broken down into
traditional huts, improved traditional huts,
detached houses, flat/apartment/multiunits, semi-detached houses, and other. A
traditional hut referred to a housing
structure usually made of mud walls witha thatched roof. If some material used for
either the wall or roof is improved (e.g.,burnt bricks for walls or iron sheets forroofing), then the housing unit is said tobe an improved traditional hut. Detachedhouse refers to a housing unit that stands
on its own, unconnected to another house.
A flat/apartment/multi-unit is defined as“a housing unit that had a set of rooms
and its accessories in a permanentbuilding”. A semi-detached house isreferred to as a housing structure orbuilding that is split into two or more
housing units, which do not standindependently but are separated by a wall.
The “other” category refers to a housing
unit not captured in the above definitions.
Tenancy Status: this was determined byasking the head of household the basis onwhich the household occupied the
housing unit in which they lived.
Main source of drinking water: the main
source of drinking water was categorized
as safe (improved) and unsafe(unimproved), consistent with the 2015
LCMS.
Electricity
connection:
thiswasdetermined by whether a housing unit
was connected to electricity via the grid.

9.2. Type of Housing Unit
The most common type of housing unit in
Kabwe is a detached house (53.9%) (Table
9.1), which reflects the results for all urban
areas of Zambia, as captured in the LCMS
2015. However, Kabwe district has a muchhigher share of households with improved
traditional huts (22.7%) compared to theaverage of all urban areas in Zambia (10.2%).
The third most common housing type in the
district is a flat/apartment/multi-unit (14.6%).
By ward, Highridge, Bwacha, and Waya werethe most urbanized with most households (90100%) living in either detached houses or flats,
and with few or no households living in
traditional or improved traditional huts (046

4.5%). Kalonga, Chirwa, and Kaputula werenext in terms of households living in either
detached houses or flats (70-80%). Thesewards also had a good share of households
living in improved traditional huts (9-23%).
Although located close to Kabwe town centre,
a substantial share of households living in
Makululu area, namely, Moomba, Makululu,
and David Ramushu wards, lived in improved
traditional huts (24%-46%). Although this
could also be said of wards like Mpima,
Chililalila, Chinyanja, Kangomba, Munyama,

and Zambezi, these wards are mainly
agricultural and located a little further, on
average, from the town centre.

9.3. Tenancy Status of Housing
Unit
Most households in Kabwe occupied theirown housing units (64.4%) or rented themfrom private individuals (25.7%), reflecting
the national picture obtained in the LCMS
2015 (Table 9.2). Ownership levels wereTable 9.1: Percentage Distribution of Households by Type of Housing Unit by Ward
Improved
Flat/
SemiTraditional
traditional Detached apartment/ detached
hut
hut
house
multi-unit house
Other

RegionWhole Kabwe district

5.8

22.7

53.9

14.6

2.0

0.0

Zambia total*

32.0

21.5

28.5

10.4

5.5

0.8

4.3

10.2

47.4

22.5

11.4

1.4

Bwacha

0

2.4

62.1

29.5

6.0

0

Chililalila

4

28

52.0

16

0.0

0

Chinyanja

9.5

38.09

47.6

4.76

0.0

0

Chirwa

1

23.3

52.2

18.54

4.1

1.2

David Ramushu

0

45.67

38.1

15.5

0.7

0

Highridge

0

0

80.9

19.05

0.0

0

Kalonga

0

12.97

53.8

26.71

3.2

3.24

Kangomba

4

27.45

46.4

13.07

6.9

2.29

Kaputula

1

9.56

72.1

14.23

3.4

0

Makululu

9

22.68

49.9

18.26

0.0

0

Moomba

2

34.49

43.8

17.95

1.8

0

Mpima

14.28

38.09

14.3

33.3

0.0

0

Munyama

18

23.95

46.4

9.875

2.0

0

Muwowo East

6

16.5

77.0

0.44

0.0

0

Waya

0

4.5

63.6

22.7

0.0

9.09

Zambezi

29

35.03

34.93

1.41

0

0

Urban

area

of

all

Zambia*Wards

Sample weights used. * Data from the LCMS 2015.

47

generally higher than the average rates forurban Zambia, which may be explained by thefact that Kabwe district has a higher thannational urban average of traditional andimproved traditional huts; these are thepredominant housing units in rural areas that
tend to have higher ownership rates.

Mpima, Munyama, Muwowo East, andZambezi. In general, households in more
urban wards, e.g., Bwacha, Chirwa, Kalonga,
and Waya, occupy housing units on a rental
basis (more than 35%) from either individuals
or institutions. However, some wards, such as
Chinyanja and Makululu, have a substantial
share of households occupying either
traditional or improved traditional huts on arental basis, which might indicate the depth ofpoverty in these areas.

Ownership rates are highest (more than 70%)
in wards with more traditional or improved
traditional housing, e.g., Kangomba, Moomba,

Table 9.2: Percentage Distribution of Households by Tenancy Status by WardRegionOwner

RentedRented fromfrom
PrivateInstitution
PersonFree
Housing

Other

Whole Kabwe district

64.4

1.7

25.7

8.2

0.0

Zambia total*

69.5

1.8

22.2

5.9

0.5

Urban area of all Zambia*

41.4

2.8

49.0

6.1

0.8

Bwacha

51

7.25

27.7

14.5

0.0

Chililalila

40

0

0.0

60

0.0

Chinyanja

52.38

0

47.6

0

0.0

Chirwa

54

2.67

36.88

6.05

0.0

David Ramushu

63

0

30.7

6.42

0.0

Highridge

62

9.52

23.8

4.76

0.0

Kalonga

49

0

41.7

9.73

0.0

Kangomba

78

0

16.0

6.21

0.0

Kaputula

57

0

34.5

8.01

0.0

Makululu

55

2.26

38.7

4.52

0.0

Moomba

71

0.84

27.0

1.26

0.0

Mpima

76.19

0

0.0

23.81

0.0

Munyama

74

1.98

2.0

21.87

0.0

Muwowo East

80

3.4

8.0

8.43

0.0

Waya

63

0

36.4

0

0.0

Zambezi

75

0.71

22.3

2.12

0.0

Wards

Sample weights used. * Data from the LCMS 2015.

48

9.4. Main Source of Drinking
Water

Wards with a large share of households using
protected wells were Mpima (71.42%),
Muwowo East (56.6%), Kaputula (47.7%),
and Kangomba (32%). More than 12% ofhouseholds did not have access to safe water,
mostly depending on unprotected wells in
Chinyanja (14.2%), Kangomba (13.7%), andKalonga (12.9%).

The proportion of households with asafe/improved water source in Kabwe (88.9%)
is the same as the average for urban Zambia(89.1%), which is much higher than thenational average (67.7%). Nevertheless, thesources of water between these areas differ
somewhat. For example, fewer people use
their own faucets in Kabwe (28.8%) comparedto urban areas of Zambia (37.5%), with more
people in Kabwe depending on protected
wells (17.8% vs 10.3%) and rain water (2.5%
vs. 1.1%).

9.5. Connection to Electricity
The proportion of households connected toelectricity in Kabwe (52.3%) was higher thanthat in the rest of Zambia as captured in the
LCMS 2015 (31.4%), although lower than theurban areas in the whole of Zambia (67.3%).

By ward, all households in Highridge, David
Ramushu, Moomba, and Zambezi have accessto an improved water source. However, unlike
Highridge, where the source of water for all
households was their own faucet, the sourcefor Moomba and Zambezi was a public spigot
or water kiosk, and most households in David
Ramushu depended on public facilities andtheir own faucets. Other wards with a highproportion of households depending on theirown faucets are Bwacha (83.7%), Chirwa(58.6%), Waya (59%), and Kalonga (34.3%).

By ward, more than 95 per cent of households
in Bwacha, Highridge, and Waya wereconnected to electricity. The proportion
connected to electricity was also high in David
Ramushu (72.1%), Chirwa (70.1%), andKalonga (67.6%). Electricity connection in
Chililalila, Chinyanja, Mpima, Kangomba,
Munyama, Moomba, Makululu, and Zambezi
was below the Kabwe average (52.3%).

49

Rain
Water
Whole Kabwe district
2.5
Zambia total*
0.5
Urban area of all Zambia* 1.1
Wards
Bwacha0
7.19
Chililalila
00Chinyanja
0
19.04
Chirwa0
3.58
David Ramushu
2
1.77
Highridge
00Kalonga7
9.7
Kangomba
0
32.02
Kaputula047.77
Makululu
0
2.28
Moomba
14
0
Mpima
0
71.42
Munyama0
8.1
Muwowo East
0
56.63
Waya
9
Zambezi00
Sample weights used. * Data from the LCMS 2015.

RegionUnsafe

0.0
40.0
52.4
4.83
2.0
0.0
0.0
2.0
3.9
0.0
2.7
0.0
28.1
1.9
13.6
8.39

0
0
0
0
0
0
0
1.96
0.73
0
0
0
0
0
0
0

2.4
44.0
0.0
17.8
35.3
0.0
3.2
9.2
2.7
47.7
24.8
0.0
5.9
0.0
4.5
69.21
11.85
6.8
59.09
0

83.75
0
9.52
58.59
42.35
100
34.35
34.31
32.27
0
1.43

4.22
12
4.76
5.38
11.62
0
29.19
6.86
3.42
9.04
5.82
0
1.975
0
4.54
14.66

0
0
0
0
4.95
0
3.24
0
0
38.7
51.31
0
0
0
0
7.733

0
0
0
1.2
0
0
0
0
0
0
0
0
1.975
0
0
0

97.6
96.0
85.7
91.4
100.0
100.0
87.0
86.3
90.7
97.7
100.0
71.4
57.9
65.3
90.8
100.0

0
0
0
0.7
0
0
0
0
0
2.26
0
0
0
0
0
0

2.42
4
14.28
7.86
0
0
12.97
13.73
9.26
0
0
28.57
40.05
34.66
9.09
0

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
0
0
0
0
0
0
0
2.02
0
0
0

Directly
Other
from
tap(e.g.,river/lake/
Unprotec
Protect
Protected Publicfrom nearby Water Bottled Total safe- stream/da Unprotec ted
well Borehole spring
tap Own tap building) Kiosk Water Improvedm
ted well spring Other
17.8
4.8
0.2
18.8
28.8
7.92
7.97
0.23
88.9
0.18
10.8
0
0
10.4
23.5
0.4
9.8
16.9
3.5
2.6
0.1
67.7
10.7
19.6
1.2
0.7
10.3
8.0
0.2
18.5
37.5
7.5
5.8
0.2
89.1
0.7
8.6
0.3
1.2

Table 9.3: Percentage Distribution of Households by Main Source of Drinking Water by Ward
Safe-Improved

50

2.42
4
14.28
8.56
0
0
12.97
13.73
9.26
2.26
0
0
0
0
0
0

Total
unsafe
10.98
32.2
10.8

Total
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

Table 9.4: Percentage Distribution of Households by Electricity Connection by WardRegion

Proportion
connected toelectricity

Proportion notconnected toelectricity

Total

Total
number ofhouseholds

Whole Kabwe district

52.3

47.7

100

49,056

Zambia total*

31.4

68.6

100

30,14,965

Urban area of all Zambia*

67.3

32.7

100

12,97,000

Wards

100
Bwacha

95.8

4.2

100

2,256

Chililalila

20.0

80.0

100

710

Chinyanja

14.3

85.7

100

624

Chirwa

70.1

29.9

100

6,490

David Ramushu

72.1

27.9

100

3,677

Highridge

95.2

4.8

100

1,209

Kalonga

67.6

32.4

100

4,234

Kangomba

43.5

56.5

100

2,448

Kaputula

57.6

42.4

100

4,483

Makululu

43.2

56.8

100

1,920

Moomba

44.5

55.5

100

4,762

Mpima

0

100

100

998

Munyama

31.9

68.2

100

1,536

Muwowo East

52.4

47.6

100

6,442

Waya

95.5

4.6

100

2,016

97.2

100

5,252

Zambezi
2.8
Sample weights used. * Data from the LCMS 2015.

51

Chapter 10
Blood Lead Levels
10.1. Introduction

BLL below that level must not be overlooked.
Figure 10.1 summarises the major health risks
associated with BLL.

The KHSS 2017 is a joint survey with thesurveys by the health assessment sub-group of
the KAMPAI project. The health assessment
sub-group invited individuals―up to twochildren and their parents from eachhousehold―for blood sampling and measured
the blood lead level (BLL) using the testing kit
LeadCare II.

Previously, three major sets of surveys haveexamined the BLL of Kabwe residents: theCopperbelt Environment Project, the Pure Earth
Projects, and the projects conducted by the
University of Zambia in collaboration with
Hokkaido University. These surveys primarily
focusedBLL is a useful biomarker for measuring theextent of lead exposure, which is frequently
used to examine lead poisoning around theworld. Generally, 10μg/dL has been regarded
as the level of concern: BLL higher than thislevel is associated with significant health risks,such as metabolic, neuronal, reproductive andcirculatory disorders and death (The Centers
for Disease Control and Prevention, CDC,
2002). However, recent researches show that
individuals, especially children, with a BLL
less than 10μg/dL still face certain risks oflead poisoning, such as decreased IQ levels(Canfield et al. 2003). Some experts begansetting the level of concern at 5μg/dL, whilethe very concept of the level of concern has
been recently questioned because nomeasurable level of blood lead is known to besafe (CDC 2012). For convenience, thischapter treats 10μg/dL BLL as the reference
level, rather than as the level of concern, to
describe the current situation in Kabwe,
although the possibility of health risks foronchildrenlivinginhighlycontaminated areas and illustrated severe lead
exposure among these children (results are
summarisedbyBose-O’Reilly

et

al.,

forthcoming). Meanwhile, the BLL data of the
KAMPAI project aims to describe a general
picture of lead exposure in the entire Kabwe
district. The sample includes children fromlowly contaminated areas and adults from any
area. Regarding the use of BLL, note thefollowing two cautions. First, as discussed in
Chapter 1, BLLs are not available for all thesampled individuals in the KHSS 2017.
Therefore, this chapter focuses on the subsampleof the KHSS 2017 main sample for whom the
BLL data are available. Since the sample set here
differs from the main samples of the KHSS 2017,
we do not use the sample weights throughout
Chapter 10. Secondly, because the detection
limit of the LeadCare II is 3.3μg/dL, the precise
values of BLLs cannot be determined forindividuals with true BLLs below this detection
limit. We conventionally treat the BLLs of suchindividuals as 1.65μg/dL, a mean of 0 and 3.3.
52

Health risks for children

BLL(𝛍𝐠/𝐝𝐋) Health risks for adults
150

Death
Encephalopathy
Nephropathy
Frank anaemia
Colic
Decreased hemoglobin synthesis
Decreased vitamin D metabolism

100

50
40
30
20

Decreased nerve conduction velocity
Increased erythrocyte protoporphyrin
Decreased IQ level, hearing, growth

Encephalopathy
Nephropathy

Frank anaemia
Male Reproductive effects
Decreased hemoglobin synthesis
Female Reproductive effects
Decreased nerve conduction velocity
Elevated blood pressure
Increased erythrocyte protoporphyrin (men)Increased erythrocyte protoporphyrin (women)

10

Transplacental transfer

Figure 10.1: The BLL and Associated Health Risk (Authors’ Creation Following Meyer Et Al.
(2008)).

NOTE:
We excluded BLL data (pp 53-56 in ORIGINAL REPORT) in this report because of
publishing regulations. The data will be published in other publications.

53

NOTE:We excluded BLL data (pp 53-56 in ORIGINAL REPORT) in this report because of
publishing regulations. The data will be published in other publications.

54

NOTE:We excluded BLL data (pp 53-56 in ORIGINAL REPORT) in this report because of
publishing regulations. The data will be published in other publications.

55

NOTE:We excluded BLL data (pp 53-56 in ORIGINAL REPORT) in this report because of
publishing regulations. The data will be published in other publications.

56

Reference
Bose-O’Reilly, S., J. Yabe, J. Makumba, et al. (forthcoming): “Lead intoxicated children in
Kabwe, Zambia.” Environmental Research, Article in press.
Canfield, R. L., C. R. Henderson, D. A. Cory-Slechta, et al. (2003): “Intellectual Impairment inChildren with Blood Lead Concentrations below 10 μg per Deciliter.” The New England
Journal of Medicine 348 (16): 1517-1526.
Centers for Disease Control and Prevention. Managing Elevated Blood Lead Levels Among YoungChildren: Recommendations from the Advisory Committee on Childhood Lead Poisoning
Prevention. Atlanta, GA.
Centers for Disease Control and Prevention (2012): Low level lead exposure harms children: arenewed call for primary prevention. Report of the Advisory Committee on Childhood Lead
Poisoning Prevention of the Centers for Disease Control and Prevention. Atlanta, GA.
Central Statistical Office of Zambia, CSO, (2016): 2015 Living conditions monitoring survey(LCMS) report. Lusaka, Zambia.
Meyer, P. A., M. J. Brown, and H. Falk (2008): “Global approach to reducing lead exposure andpoisoning.” Mutation Research 659: 166-175.
Sargent, J. D., M. J. Brown, J. L. Freeman, A. Bailey, D. Goodman, and D. H. Freeman Jr. (1995):“Childhood Lead Poisoning in Massachusetts Communities: Its Association with
Sociodemographic and Housing Characteristics.” American Journal of Public Health 85 (4):528-534.
Tembo, B. D., K. Sichilongo and J. Cernak (2006): “Distribution of copper, lead, cadmium andzinc concentrations in soils around Kabwe town in Zambia.” Chemosphere 63, 497-501.
United Nations Development Programme. UNDP, (2016): Human Development Report 2016. NY.
WHO (2010): Childhood lead poisoning. WHO Press, Geneva, Switzerland.
Yabe, J., S. M. M. Nakayama, Y. Ikenaka, et al. (2015): “Lead poisoning in children fromtownships in the vicinity of a lead–zinc mine in Kabwe, Zambia.” Chemosphere 119: 941947.
Zivin, J. G. and M. Neidell (2013): “Environment, Health, and Human Capital.” Journal of
Economic Literature 51 (3): 689-730.

57

Kabwe Household Socioeconomic Survey 2017
Questionnaire
Notes
This is the printable version of the questionnaire. The interviews were conducted in the form ofComputer Assisted Personal Interviewing (CAPI) using the application Survey Solutions (version
5.22.20) developed by the World Bank.

Contents
Household identification
Section 1. Household roster
Section 2. Biological relationships
Section 3. Health
Section 4. Education
Section 5. Economic activity and non-farm income
Section 6. Agricultural production
Section 7. Other income
Section 8. Household assets and durables
Section 9. Household amenities and housing conditions
Section 10. Household expenditure
Section 11. Child health and nutrition
Section 12. Deaths in Household
Concluding remarks

HOUSEHOLD IDENTIFICATION
HHID

HHID

SEA
HEAD_NAMESEA CODETHE NAME OF THE HOUSEHOLD HEAD

TEL

Telephone number (if available)

DATE_BDATE OF THE BEGINNING OF THE INTERVIEWGPSGPS coordinate

PROVIDED BY SUPERVISOR

For all persons. Answer cells omitted.

SECTION 1: HOUSEHOLD ROSTERINTRODUCTION: I would like to start the interview by asking you questions about yourself and other usual members of the household
SERIAL
Please give me the names of 1A
1B
For children aged 2A
2B
2C
NUMBER OF all persons who usually live How
oldis Record exact age 5-9 years, ask The date of birth for
HOUSEHOL
with
thishousehold [NAME] now?
their children aged 0-4 years
incompleted about
D MEMBERS (START
WITH
THE
and old
months for those birthdays(personID)
HEAD
OF
THE [RECORD
whether
0-59 months old check
HOUSEHOLD).
they were born Asked if Q1A<5AGE
IN (0-4 years old).
BEFORECOMPLETED[Preferred order: HEAD, YEARS.
[USE
UNDER AUGUST 2011.
SPOUSEofhead, RECORD
0 FIVE CLINIC
CHILDREN of head FOR THOSE 0- CARD
note
IF This(eldertoyounger), 11
appears
if
MONTHS AVAILABLE.
OTHER
MEMBERS. OLD.]
Q1A=5,6,7,8,9.
RECORD 99 IF
Include visitors who have
DON’T KNOW]
lived with the householdfor sixmonths or more.
DAY MON
YEAR
Asked if Q1A<5
Include usual members,TH
who are away visiting, in
hospital, at boarding
schools or college oruniversity, etc.]

3B
What
is
ethnicity?

[NAME]’s

1: BEMBA
2: TONGA
3: CHEWA
4: LOZI
5: NSENGA
6: TUMBUKA
7: NGONI
8: LENJE
9: LAMBA
10: WHITE
11: OTHER ETHNICITY
Asked if Q3A=1

7Is[NAME].analbino
1: YES
2: NO

8A
Does
[NAME]
haveany
disability?
1: YES
2: NO

SECTION 1: HOUSEHOLD ROSTER (Continued)
4
5
6A
What is the relationship of [NAME] to Is[NAME] What is [NAME]’s
the head of the household?
Maleor primary language?
Female?
1: HEAD
1: BEMBA
2: SPOUSE
1: MALE
2: NYANJA
3: OWN CHILD
2: FEMALE
3: TONGA
4: STEP CHILD
4: LOZI
5: ADOPTED CHILD
5: KAONDE
6: GRAND CHILD
6: LUVALE
7: BROTHER/SISTER
7: LUNDA
8: COUSIN
8: LENJE
9: NIECE/NEPHEW
9: LAMBA
10: BROTHER/SISTER-IN LAW
10: ENGLISH
11: PARENT
11: OTHER
12: PARENT-IN-LAW
13: OTHER RELATIVE[THE LANGUAGE
14: MAID / NANNY /MAINLY USED AT
HOUSE-SERVANTHOME.]
15: OTHERSECTION 1: HOUSEHOLD ROSTER (Continued)
8B
9Is [NAME] blind, partially sighted, deaf, Where was [NAME] born?
dumb, crippled, mentally retarded, mentallyill, ex-mental?
1: KABWE DIST
2: CENTRAL PROV. OTHER
1: BLIND
THAN KABWE
2: PARTIALLY SIGHTED
3: COPPERBELT PROVINCE
3: DEAF
4: EASTERN PROV
4: DUMB
5: LUAPULA PROV
5: PHYSICALLY DISABLED
6: LUSAKA PROV
6: MENTALLY RETARDED
7: MUCHINGA PROV
7: MENTALLY ILL
8: NORTHERN PROV
8: EX-MENTAL
9: NORTH WESTERN PROV
10: SOUTHERN PROV[RECORDUP
TO
THREE 11: WESTERN PROVDISABILITIES]
12: OTHER COUNTRIES
Asked if Q8A=1.

3A
Is [NAME] a
Zambiannational?
1: YES
2: NO

6B
Please state [NAME]’s level ofEnglish proficiency.
1: EXCELLENT (he/she speaks
English like his/her primary language)
2: GOOD (he/she speaks English
without any problem in most cases)
3: FAIR (he/she speaks English
without any problem in daily
conversation)
4: POOR (he/she understands simple
conversation)
5: DOES NOT SPEAK AT ALL
Asked if Q6A is not English AND
Q1A≥5.

10A
How many years
has [NAME] been
living in Kabwe
district?
[GIVE TOTAL
YEARS
IN
LIFE]

10B
How many years has[NAME] been livingin this dwelling?
[GIVE LENGTH
YEAR]

11A
Where was [NAME] residing before?
1: HAS NEVER MOVED
2: DIFFERENT DWELLING/ SAME
WARD
3: DIFFERENT WARD/KABWE DIST
4: DIFFERENT DISTRICT/ CENTRALPROVINCE
5: DIFFERENT PROVINCE
6: DIFFERENT COUNTRY
7: DON’T KNOW/ REFUSEDSECTION 1: HOUSEHOLD ROSTER (Continued)
11B
12
Was the previous residence Why did [NAME] move from his/her previous
rural or urban?
residence?
1: RURAL
2: URBAN
3: DIFFICULT TO SAY /DON’T KNOW
Asked if Q11A=3,4,5,6.

1: FOR SCHOOL
2: BACK FROM SCHOOL/STUDIES
3: TO SEEK WORK/ BUSINESS
4: TO START WORK/ BUSINESS
5: TRANSFER OF HEAD OF HOUSEHOLD
6: PREVIOUS HOUSEHOLD COULD NOT
AFFORD TO KEEP HIM/HER
7: DEATH OF PARENT/GUARDIAN
8: GOT MARRIED
9: NEW HOUSEHOLD
10: RETIREMENT
11: RETRENCHMENT
12: DECIDED TO RESETTLE
13: ACQUIRED OWN/DIFFERENTACCOMODATION
14: FOUND NEW AGRICULTURAL LAND
15: REFUGEE/ASYLUM SEEKER
16: ENVIRONMENTAL POLLUTION
17: OTHER
18: DON’T KNOW

13What is the marital status of[NAME]?
1: NEVER MARRIED
2: MARRIED
3: SEPARATED
4: DIVORCED
5: WIDOWED
6: CO-HABITING
ASKED IF Q1A>=12[CHOOSE THE MAIN OR THE MOSTIMPORTANT REASON.]
Asked only if Q11A==2,3,4,5,6.

For all persons aged 0-20 years. Answer cells omitted.
SECTION 2: BIOLOGICAL RELATIONSHIP
1
Is the biological motherof [NAME] in thishousehold?
1: YES
2: NO

2
Who is the biologicalmother of [NAME]?

3
Is the biological motherof [NAME] still alive?

LIST
OF
HOUSEHOLD
MEMBERS TO BE
AUTOMATICALLY
MADE.

1: YES
2: NO
3: DON’T KNOW

Asked if Q1=1

Asked if Q1=2

4
Is the biological fatherof [NAME] in thishousehold?
1: YES
2: NO

5
Who is the biologicalfather of [NAME]?

6
Is the biological fatherof [NAME] still alive?

LIST
OF
HOUSEHOLD
MEMBERS TO BE
AUTOMATICALLY
MADE.

1: YES
2: NO
3: DON’T KNOW

Asked if Q4=1

Asked if Q4=2

For all persons. Answer cells omitted.

SECTION 3: HEALTH - FOR ALL PERSONSINTRODUCTION: I am now going to ask about the health status of each member of your household.
1
2
Has [NAME] been sick or What was [NAME] mainly suffering from? [MULTIPLE ANSWERS ALLOWED.
injured during the last two RECORD UP TO THREE ILLNESSES.] Asked if Q1=1 or 3
weeks?
1: FEVER/MALARIA
17: PILES/HAEMOROIDS
2: COUGH/COLD/CHEST INFECTION
18: SHINGLES/HERPES ZOSTER
1: YES SICK
3: TUBERCULOSIS (TB)
19: PARALYSIS OF ANY KIND
2: YES INJURED
4: ASTHMA
20: STROKE
3: YES BOTH
5: BRONCHITIS
21: HYPERTENSION
4: NO
6: PNEUMONIA/CHEST PAIN
22: DIABETES/SUGAR DISEASE
5: DON’T KNOW
7: DIARRHOEA WITHOUT BLOOD
23: EYE INFECTION
8: DIARRHOEA WITH BLOOD
24: EAR INFECTION
9: DIARRHOEA AND VOMITTING
25: TOOTHACHE/MOUTH
10: VOMITINGINFECTION
11: ABDOMINAL PAINS
26: HEADACHE
12: CONSTIPATION/STOMACH UPSET
27: MEASLES
13: LIVER INFECTION/SIDE PAIN
28: JAUNDICE/YELLOWNESS
14: LACK OF BLOOD/ANEAMIA
29: BACKACHE
15 : BOILS
30: CANCER OF ANY KIND
16 : SKIN RASH/SKIN INFECTION
31: MENINGITIS
32: OTHER

4
How much in total was
spent on [NAME]’s
medication/
consultation in the last
two weeks?
[GIVE AMOUNT INKWACHA]
Asked if Q3=1,2.

5
Where did [NAME] get the
medicine from?
1: GOVT INSTITUTION
2: MISSION INSTITUTION
3: INDUSTRIAL INST.
4: PRIVATE INSTITUTION
5: PHARMACY/ CHEMIST
6: RELATIVES
7: NEIGHBOURS
8: FRIENDS
9:TRADITIONALHEALERS
10: OTHER
Asked if Q3=1,2.

SECTION 3: HEALTH (CONT’D)
6
7
Which
healthorother Who attended to [NAME]
institution/personnel
did during this visit?
[NAME] visit first for thisillness/injury?
1: MEDICAL DOCTOR
2: CLINICAL OFFICER
1: GOVT HOSPITAL
3: NURSE/MIDWIFE
2:
GOVT
HEALTH 4:
COMMUNITY
CENTRE/CLINICHEALTH WORKER
3: GOVT HEALTH POST
5:
TRADITIONAL
4: MISSION INSTHEALER
5: INDUSTRIAL INST
6: FAITH HEALER
6: PRIVATE INST
7: SPIRITUAL HEALER
7:
INSTITUTION 8: CHURCH HEALER
9: OTHEROUTSIDE ZAMBIA

8: MEDICAL PERSONNEL
9: TRADITIONAL HEALER
10: FAITH / SPIRITUAL /CHURCH HEALER
11: OTHER
Asked if Q3=1.

9
Has [NAME] been
continuously ill, for atleast 3 months in thelast 12 months?

1: YES
2: NO

Asked if Q3=1.

3
Did [NAME] consult any health orother institution/personnel for thisillness/injury or did he/she only
use self-administered medicine?
1: CONSULTED
2: USED SELF
ADMINISTEREDMEDICINE ONLY
3: NONE OF THE ABOVE
ASKED IF Q1=1, 2, 3

8What was the method used forpaying for the services of the facilityon this visit?
1: PRE-PAYMENT SCHEME(LOW COST)
2: PRE-PAYMENT SCHEME(HIGH COST)
3: PAID FOR BY EMPLOYER
4: PAID BY INSURANCE
5: PAID PART AND THE
OTHER PART BY OTHER;(e.g. EMPLOYER, FRIENDS,
INSURANCE)
6: PAID DIRECTLY
7: PAID FOR BY OTHER
8: DIDN’T PAY
9: NOT APPLICABLE[Multiple answers allowed]
Asked if Q3=1.

SECTION 3: HEALTH (CONT’D)
10
What was [NAME] mainly suffering from? [MULTIPLE ANSWERS ALLOWED. RECORD UP TO
THREE ILLNESSES.] Asked if Q9=1
1: FEVER/MALARIA
17: PILES/HAEMOROIDS
2: COUGH/COLD/CHEST INFECTION
18: SHINGLES/HERPES ZOSTER
3: TUBERCULOSIS (TB)
19: PARALYSIS OF ANY KIND
4: ASTHMA
20: STROKE
5: BRONCHITIS
21: HYPERTENSION
6: PNEUMONIA/CHEST PAIN
22: DIABETES/SUGAR DISEASE
7: DIARRHOEA WITHOUT BLOOD
23: EYE INFECTION
8: DIARRHOEA WITH BLOOD
24: EAR INFECTION
9: DIARRHOEA AND VOMITTING
25: TOOTHACHE/MOUTH INFECTION
10: VOMITING
26: HEADACHE
11: ABDOMINAL PAINS
27: MEASLES
12: CONSTIPATION/STOMACH UPSET
28: JAUNDICE/YELLOWNESS
13: LIVER INFECTION/SIDE PAIN
29: BACKACHE
14: LACK OF BLOOD/ANEAMIA
30: CANCER OF ANY KIND
15 : BOILS
31: MENINGITIS
16 : SKIN RASH/SKIN INFECTION
32: OTHER

11
Has [NAME] been able
to carry out his/hernormal activities during
the period of the illness?
1: YES
2: NO
Asked if Q9=1

For all persons. Answer cells omitted.

SECTION 4: EDUCATION – FOR ALL PERSONSINTRODUCTION: I am now going to ask about the educational status of each member of your household
123A
Is [NAME] currently attending school?
What grade / level of education is Is the school [NAME] is currently[NAME] currently attending?
attending, a Central Government,
1: YES, NURSERY/ PRE-SCHOOL
Local Government (council),
2: YES, OTHER GRADES FULL TIME
1 to 11: Grade 1 to 11
Mission/Religious, Industrial or
3: YES, OTHER GRADES PART TIME
12: Grade 12 GCE (O-level)
private school?
4: YES, COMM. SCHOOL FULL TIME
13: Grade 12 GCE(A-level)
5: YES, CORRESPONDENCE
14: College students
1: CENTRAL GOVT
6: YES, ADULT LITERACY CLASS
15:
Undergraduate
University 2: LOCAL GOVT (council)
7: YES, TERTIARY SCHOOL
students
3: MISSION/RELIGIOUS
8: OTHER
16: Post-graduate Certificate / 4: INDUSTRIAL
9: NO
Diploma students
5: PRIVATE
17: Master Degree students
6: OTHER[INCLUDING THOSE IN COLLEGES AND 18: Doctoral level and above
UNIVERSITIES. ASK ABOUT THE PREVIOUS students
Asked if Q1=1,2,3,4,5,7,8
SCHOOL TERM (OR THE PREVIOUS SCHOOL
YEAR) IF IT IS TIME FOR VACATIONS.]
Asked if Q1=2,3,4,5,7,8
SECTION 4: EDUCATION (CONT’D)
45
How often did [NAME] miss classes (on average in the last term)?
Has [NAME] everattended school?
1: NEVER
2: A LITTLE (ONE DAY OR TWO PER MONTH)
1: YES
3: OFTEN (THREE TO TEN DAYS PER MONTH)
2: NO
4: VERY OFTEN (MORE THAN TEN DAYS PER MONTH)
Asked if Q1=6,9
In case of part time students:
A LITTLE: ONE DAY OR TWO OUT OF 20 SCHOOL DAYS.
OFTEN: THREE TO TEN DAYS OUT OF 20 SCHOOL DAYS.
VERY OFTEN: MORE THAN TEN DAYS OUT OF 20 SCHOOL DAYS.

3B
Please give the nameof the school
Asked
if
Q1=1,2,3,4,5,7,8

6
What is the highest grade [NAME] attained?
1 to 11: Grade 1 to 11
12: Grade 12 GCE (O-level)
13: Grade 12 GCE (A-level)
14: CERTIFICATE
15: DIPLOMA
16: DEGREE
17: MASTER DEGREE
18: DOCTORAL DEGREE
19: NONE (went to school but did not complete any
grade)

Asked if Q1=1,2,3,4,5,7,8
Asked if Q5=1
SECTION 4: EDUCATION (CONT’D)
7
What was the main reason for [NAME] leaving school at the time?
Asked if Q5=1
1: STARTED WORKING / BUSINESS
2: EXPENSIVE
3: TOO FAR
4: NOT SELECTED/FAILED
5: PREGNANCY
6: MADE GIRL PREGNANT
7: COMPLETED STUDIES / SCHOOL
8: GOT MARRIED
9: NO NEED TO CONTINUE SCHOOL

10: SCHOOL NOT IMPORTANT
11: UNSAFE TO TRAVEL TO SCHOOL
12: EXPELLED
13: LACK OF FINANCIAL SUPPORT
14: NEEDED TO HELP OUT AT HOME
15: ILLNESS/INJURY/DISABLED
16: OTHER
17: DON’T KNOW

8
Why has [NAME] never attended school?
1: UNDER-AGE
2: COULDN’T GET A PLACE
3: EXPENSIVE
4: NO FINANCIAL SUPPORT
5: NO SCHOOL / SCHOOL TOO FAR
6: ILLNESS/INJURY
7: SCHOOL NOT IMPORTANT
8: UNSAFE TO TRAVEL TO SCHOOL
9: OTHER
10: DON’T KNOW
Asked if Q5=2

SECTION 4: EDUCATION (CONT’D)
From now on I would like to ask about the expenditure to various school items in the LAST 12 MONTHS.
9A
9B
9C
10A
10B
10C
11A
11B
11C
How much did your household spend How much did your household spend How much did your household spend
on SCHOOL FEES for [NAME] on PRIVATE TUITIONS for on TEXTBOOKS for [NAME]
during…
[NAME] during…
during…

12A
12B
12C
How much did your household spend
on SCHOOL UNIFORMS for[NAME] during…

[INCLUDE
EXAMINATIONFEES AND BOARDING FEES.
ENTER 0 IF NOT SPENDING
ANY MONEY][INCLUDE
SOCKS,TIES,
MATERIALS,TAILORINGCHARGES. ENTER 0 IF NOTSPENDING ANY MONEY]

Asked if Q1=1,2,3,4,5,6,7,8
2nd term 1st term 3rd term
this year
this year
the last
year[ENTER 0 IF NOT SPENDING
ANY MONEY][ENTER 0 IF NOT SPENDING
ANY MONEY]

Asked if Q1=1,2,3,4,5,6,7,8

Asked if Q1=1,2,3,4,5,6,7,8

2nd term
this year

2nd term
this year

1st term
this year

3rd term
the lastyear

1st term
this year

3rd term
the lastyear

Asked if Q1=1,2,3,4,5,6,7,8
2nd term 1st term 3rd term
this year
this year
the lastyear

For all persons aged 5 years or above. Answer cells omitted.

SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME
INTRODUCTION: I am now going to ask about the economic activity status of each member aged 5 or above of your household.
1
2
What is [NAME]’s main current economic activity status?
What type of job/business is [NAME] doing?
[FOR THOSE ENGAGING IN FARMING, FISHING and FORESTRY: If
he/she works for non-household members and receives wages, choose IN
WAGE EMPLOYMENT.
IF HE/SHE IS MAID/NANNY/HOUSE-SERVANT IN THIS HOUSEHOLD:
Record OTHER even if he/she receives wages.]

Asked if Q1=1,2,6,7

1: IN WAGE EMPLOYMENT
2: RUNNING A BUSINESS/ SELF
EMPLOYED BUT NON FARM
3: FARMING
4: FISHING
5: FORESTRY
6: PIECEWORK
7: UNPAID FAMILY WORKER /ASSISTING
NON-FARM
FAMILY
BUSINESS WITHOUT WAGE
8: NOT WORKING BUT LOOKING FOR
WORK/MEANS TO DO BUSINESS

1: MANAGERS
2: PROFESSIONALS
3:
TECHNICIANSANDASSOCIATE PROFESSIONALS
4:
CLERICALSUPPORT
WORKERS
5: SERVICE AND SALESWORKERS
6: SKILLED AGRICULTURAL,
FORESTRY AND FISHERYWORKERS

9: NOT WORKING AND NOTLOOKING FOR WORK/MEANS
TO DO BUSINESS (BUT
AVAILABLE TO DO SO)
10: FULL TIME STUDENT
11:
HOME
MAKER
/
HOUSEWIFE
12: RETIRED / TOO OLD TO
WORK
13: TOO YOUNG TO WORK
14: OTHER

7: CRAFT AND RELATEDTRADES WORKERS
8: PLANT AND MACHINEOPERATORS,ANDASSEMBLERS
9: COLLECTING MINERALSFROM BLACK MOUNTAIN
10:
OTHER
ELEMENTARYOCCUPATIONS
11: ARMED FORCES
12: OTHER/ NOT STATEDSECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)INTRODUCTION: I am now going to ask about the economic activity status of each member aged 5 or above of your household.
3
4
What sort of business/service is carried out by [NAME]’s employer / establishment What is [NAME]’s employment status?
/ business?
Asked if Q1=1,2,6,7
1: CENTRAL GOVT EMPLOYEE2:
LOCAL
GOVT/COUNCILEMPLOYEE
1: AGRICULTURE, FORESTRY & 12: REAL ESTATE ACTIVITIESPARASTATAL/QUASI-GOVT
FISHERIES
13: PROFESSIONAL, SCIENTIFIC 3:EMPLOYEE
2: MINING AND QUARRYING
AND TECHNICAL ACTIVITIES
3: MANUFACTURING14:
ADMINISTRATIVE
AND 4: PRIVATE SECTOR EMPLOYEE
5: NGO EMPLOYEE
4: ELECTRICITY, GAS, STREAM SUPPORT SERVICES
AND AIR CONDITIONING SUPPLY
15: PUBLIC ADMINISTRATION 6: INT’L ORGANISATION/
5: WATER SUPPLY, SEWERAGE, AND DEFENSE, COMPULSORY EMBASSY EMPLOYEE
7: HOUSEHOLD EMPLOYEEWASTEMANAGEMENT
AND SOCIAL SECURITY
8: OTHERREMEDIATION ACTIVITIES
16: EDUCATION
6: CONSTRUCTION
17: HUMAN HEALTH AND SOCIAL
Asked if Q1=1
7: TRADE, WHOLESALE, AND WORKRETAIL DISTRIBUTION
18: ARTS, ENTERTAINMENT AND
8:
TRANSPORTATION
AND RECREATIONSTORAGE
19: OTHER SERVICE ACTIVITIES
9: ACCOMMODATION AND FOOD 20: ACTIVITIES OF HOUSEHOLDSERVICE ACTIVITIESAS EMPLOYERS10:
INFORMATION
AND 21:
ACTIVITIESOFCOMMUNICATIONEXTRATERRITORIAL
11: FINANCIAL AND INSURANCE ORGANIZATION AND BODIESACTIVITIES
22: OTHER / NOT STATED

5
How much is [NAME]’sregular gross monthly
salary/wage from this job?
[INCLUDE REGULAR
ALLOWANCES(HOUSING,
TRANSPORT,ETC)
AND
REGULAR
OVERTIME
RETENTION
ALLOWANCE.]
Asked if Q1=1

SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)
6
How much non regular allowances did[NAME] receive last month from thisjob?
[E.g. OVERTIME PAYMENTS,
SUBSISTENCE ALLOWANCES,
BONUSES, ETC.]
Asked if Q1=1

7
How much income
did [NAME] receivefrom this business in
the last one month?

8
How much income in-kind do[NAME] receive per month (e.g.
bags of mealie meal, charcoal) fromthis job / business?

9
In this job/business, is[NAME]
entitled
topension, gratuity or social
security?

Asked if Q1=2, 6[CONVERTTOEQUIVALENT]

1: YES
2: NO

Asked if Q1=1, 2, 6

KWACHA

Asked if Q1=1,2,3,4,5,6

10
Is [NAME] entitledto paid leave in thisjob / business?
1: YES
2: NO
Asked
Q1=1,2,3,4,5,6

if

SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)
11A
Does [NAME] employ
any worker in thisbusiness?
1: YES
2: NO

11B
Are there five (5) or more
people working in thiscompany/business including
the owner?

12
Does[NAME]
haveanother
job/business?
1: YES
2: NO

1: YES
2: NO[DO NOT COUNTFAMILY MEMBERSASSISTINGTHE
BUSINESS WITHOUTPAYMENT.][INCLUDING
ALL
WORKERS
IN
ALL
BRANCHES OF THE SAMECOMPANY/BUSINESS]

Asked if Q1=1-7

Asked if Q1=2

Asked if Q1=1,6 OR Q11A=1

13
In this job/business, is [NAME] …?
1: IN WAGE EMPLOYMENT
2: RUNNING A BUSINESS/ SELF
EMPLOYED BUT NON FARM
3: FARMING
4: FISHING
5: FORESTRY
6: PIECEWORK
7: UNPAID FAMILY WORKER /ASSISTING NON-FARM FAMILY
BUSINESS WITHOUT WAGE
14: OTHER

14
What type ofjob/business is
this?
The
same
answer options
as in Q2
Asked
if
Q13=1,2,6,7

15
What sort ofbusiness/servic
e is carried out
by [NAME]’s
employer/establishment/
business in thisjob/ business?
Thesame
answer options
as in Q3
Asked
if
Q13=1,2,6,7

Asked if Q12=1
SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)
16
What
is
[NAME]’s
employment
status in this job?
The same answer
options as in Q4.
Asked if Q13=1

17
How much is [NAME]’sregulargross
monthlysalary/wage from this job?

18
How much non regularallowances did [NAME]
receive last month fromthis job?

19
How much income
did [NAME] receivefrom this business in
the last one month?

[INCLUDE
REGULAR
ALLOWANCES (HOUSING,
TRANSPORT, ETC) AND
REGULAR
OVERTIME
RETENTION
ALLOWANCE.][E.g.
OVERTIMEPAYMENTS,SUBSISTENCEALLOWANCES,
BONUSES, ETC.]

Asked if Q13=2, 6

Asked if Q13=1

Asked if Q13=1

20
How much income inkind do you receive permonth (e.g. bags ofmealie meal, charcoal,etc) from this job /business?

21
In this job/business,is [NAME] entitledto pension, gratuity
or social security?
1: YES
2: NO

Asked if Q13=1, 2, 6
Asked
Q13=1,2,3,4,5,6

if

SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)
22Is[NAME]
entitled to paid
leave in thisjob/business?
1: YES
2: NO
Asked
if
Q13=1,2,3,4,5,6

23A
Does [NAME] employ any
worker in this business?
1: YES
2: NO
[DO
NOT
COUNT
FAMILYMEMBERSASSISTINGTHE
BUSINESSWITHOUTPAYMENT.]

23B
Are there five (5) or more people
working in this company/businessincluding the owner?
1: YES
2: NO[INCLUDING ALL WORKERSIN ALL BRANCHES OF THE
SAME COMPANY/BUSINESS]

1: YES
2: NO
Asked if Q12=1

Asked if Q13=1,6 OR Q23A=1
Asked if Q13=2

24
Is[NAME]
currently engaged
in
any
other
income generating
activities
orfarming?

25
What type of job/business is [NAME] doing as
the other income generating activities or
farming?
1: IN WAGE EMPLOYMENT
2: RUNNING A BUSINESS/ SELF
EMPLOYED BUT NON FARM
3: FARMING
4: FISHING
5: FORESTRY
6: PIECEWORK
7: UNPAID FAMILY WORKER / ASSISTING
NON-FARM FAMILY BUSINESS WITHOUTWAGE
14: OTHER
Asked if Q24=1

SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)
28
29
30

26

27

During the last 7 days, did[NAME] engage in any of
the following economic
activities?
-WAGE
LABOUR -A BUSINESS/SELFEMPLOYEDWORK -FARMING FISHING -FORESTRY PIECEWORK -UNPAIDFAMILY WORK

How
many
hours
did
[NAME] work
for
those
economic
activities during
the last 7 days?

1: YES
2: NO[INCLUDE THE MAIN,
SECOND AND THIRDJOBS / BUSINESSES (IFANY).]
Asked if Q1=1-7.

[RECORDTHE
NUMBER OF
HOURSINTOTAL]

Are the hours
worked during
the last 7 days…?
1:
LONGER
THAN USUAL
2: THE SAMEAS USUAL
3: SHORTER
THAN USUAL4:NOTAPPLICABLE /DON’T KNOW

Asked if Q26=1
Asked if Q26=1

(FOR
THOSE
NOT WORKINGOR WORKING
LESS
THAN
USUAL DURING
THE LAST 7
DAYS) How many
hours per week
would [NAME]
usually work?
[[RECORD THE
NUMBEROF
HOURSIN
TOTAL.]
Asked if Q26=2
OR Q28A=3

What was the main reason that [NAME] did
fewer hours than usual/away from the economic
activities in the last 7 days?
1: NUMBER OF HOURS WORKED VARIESBY THE NATURE OF THE WORK
2: STUDY, TRAINING
3: HOUSEWORK
4: PREGNANCY
5: OWN ILLNESS(PHYSICALLY/MENTALLY)
6: FATIGUE, EXHAUSTION, LACK OFCONCENTRATION
7: INJURY, DISABILITY
8: CARING FOR (PHYSICALLY /MENTALLY) ILL MEMBERS
9: CARING FOR INJURED OR DISABLED
MEMBERS
10: CARING FOR OTHER ELDERLY /CHILDREN
11: OFF-SEASON
12: OTHER REASONS
13: DON’T KNOW

31
In the last 12
months,how
many days ofthe economic
activities
did[NAME] missowing to his/herown or family
members’
illness
andinjuries?
1: 0 days
2: 1–2 days
3: 3–5 days
4: 6–10 days
5: 11–15 days
6: 16+ days
Asked
Q1=01-07.

if

Asked if Q26=2 OR Q28A=3

32
During the last 12
months,did[NAME] change
employment/
businesses?
1: YES
2: NO
Asked if Q1=1-7.

SECTION 5: ECONOMIC ACTIVITY AND NON-FARM INCOME (CONT’D)
33
34
35
36
What was the main reason for Did you have a What was the main reason for How much did you
leaving that job/business?
job or business leaving that job/business?
receive as pension
1: LOW WAGE./SALARY
in the last 12 1: LOW WAGE./SALARY
payment
per
2: FIRED/DISMISSED
months?
2: FIRED/DISMISSED
month?
3: ENTERPRISE CLOSED
3: ENTERPRISE CLOSED
4: ENTERPRISE PRIVATISED
1: YES
4: ENTERPRISE PRIVATISED[TYPE 0 IF NOT
5: ENTERPRISE LIQUIDATED
2: NO
5: ENTERPRISE LIQUIDATEDRECEIVING
6:RETRENCHED/DECLARED
6: RETRENCHED/DECLARED ANY PENSION.]
REDUNDANT
Asked if Q1=8- REDUNDANT
7: GOT ANOTHER JOB
14.
7: GOT ANOTHER JOB
8: BANKRUPTCY
8: BANKRUPTCY
9: LACK OF PROFIT
9: LACK OF PROFIT
10: WAS A TEMPORARY JOB
10: WAS A TEMPORARY JOB
11: RETIRED
11: RETIRED
12: CONTRACT EXPIRED
12: CONTRACT EXPIRED
13:
POOR
WORKING
13:
POOR
WORKING
CONDITIONSCONDITIONS
14: ILNESS/ DISABILITY
14: ILNESS/ DISABILITY
15: PREGNANCY
15: PREGNANCY
16: OTHER
16: BECAME A STUDENT
Asked if Q32=1
17: OTHER
Asked if Q34=1

37
How much income
in form of grants
do you receive permonth (both cash
and in-kind)?
[CONVERT INKIND TO CASH.
TYPE 0 IF NOTRECEIVING
ANY GRANT.]SECTION 6: AGRICULTURAL PRODUCTION
Q1A
Q1B
Q1C

Did any member of this household grow or anybody grow on their behalf any food crops in the last twelve (12) months?
Did any member of this household own any livestock or poultry in the last twelve (12) months?
Did any member of this household engage in fish farming, forestry, or any other income generating activity related to agriculture in the last twelve (12) months?

1: YES / 2: NO
1: YES / 2: NO
1: YES / 2: NO

SUB-SECTION 6A: FOOD CROP PRODUCTION (asked if Q1A==1)

CROPS

AQ1
Did any memberof this household
or anybody growon their behalf any[ITEM] in the lasttwelve months?
1: YES
2: NO

AQ 2
Is
[ITEM]
planted in

AQ 3A
AQ 3B
What was the area
planted under [ITEM]?

1: Home garden
2: Farm land

UNIT
1: LIMA
2: ACRE
3: HECTARE
Asked if AQ1=1

Asked
AQ1=1

if

AREA

UNIT

AQ 4A
AQ 4B
From what you planted,
what quantity of [ITEM]
did all the members of thehousehold harvest?

AQ 5A
AQ 5B
What quantity of [ITEM]
did all the members of thehousehold sell in the lasttwelve (12) months?

AQ 6
How much wasrealisedfromthe sale of[ITEM]?

[Unit codes from the list
below]
Asked if AQ1=1[Unit codes from the list
below]
Asked if AQ1=1[Total value in
KWACHA]
Asked
if
AQ1=1

AmountAmountUnit

AQ 7
Did your household
consumeownproduced [ITEM] inthelast
twelvemonths?
1: YES
2: NO
Asked if AQ1=1

Unit

1 Local Maize
2 Hybrid Maize
3 Cassava
4 Millet
5 Sorghum
6 Rice7 Mixed beans
8 Soya beans
9 Sweet potatoes
10 Irish Potatoes
11Groundnuts
12 Root vegetable (e.g. carrot)
13 Fruit Vegetable (e.g. tomato)
14 Leaf vegetable (e.g. cabbage)
15 Cotton
16 Tobacco
17 Sunflower
18 Paprika
19 Flowers
20 Other crops[UNIT CODES]

KG…1

20 Ltr Tin…2

25KG Bag...350KG Bag…490KG Bag...5

AQ 8
How much would
you receive forown-consumed[ITEM] if you
were to sell them?
[Total value in
KWACHA]
Asked if AQ7=1

SUBSECTION 6B: LIVESTOCK AND POULTRY (asked if Q1B==1)
Livestock and poultry

BQ 1
Did any memberof your household
own / produce[ITEM] in the lasttwelve months?
1: YES2: NO

BQ 2
How many [ITEM]
does your household
own NOW?

BQ 3
Did your household
sell any [ITEM] inthelast
twelvemonths?

Asked if BQ1=1

BQ 4
How many [ITEM] did
your household sell in thelast twelve months?
Asked if BQ3=1

1: YES
2: NO
Asked if BQ1=1

BQ 5
How much income did yourhousehold receive from the saleof [ITEM] in the last twelve (12)months[VALUE IN KWACHA]
Asked if BQ3=1

BQ 6
Did your household
consume own-produced[ITEM] in the last twelve(12) months?

BQ 7
Hou much would you
receive for own- consumed[ITEM] if you were to sellthem?

1: YES
2: NO
Asked if BQ1=1[VALUE IN KWACHA]
Asked if BQ6=1

1 Cattle
2 Goats
3 Sheep
4 Pigs5 Chickens
6 Guinea fowls
7 Ducks and geese
8 Turkeys
9 Rabbits
10 Pigeons
11 quails
12 Other livestocks and poultry
13 Eggs
14 Other livestock products (e.g.
milk, yoghurt, fat, cheese, hides)

SUBSECTION 6C: FISH FARMING, FORESTRY, AND OTHER FARMING PRODUCTION (asked if Q1C==1)
CQ 1
CQ 2
CQ 3
CQ 4
CQ 5
CQ 6
CQ 7
CQ 8
CQ 9
CQ 10
CQ 11
CQ 12

Did your household harvest or collect in FISH FARMING in the last twelve months?
How much did your household harvest or collect in FISH FARMING in the last twelve months? [in KG] [VALUE IN KWACHA] Asked if CQ1=1
How many fish did your household sell in the last twelve months? [in KG] Asked if CQ1=1
How much did your household receive from the sale of FISH? [VALUE IN KWACHA] Asked if CQ1=1
Did your household consume own-harvested (collected) FISH in the last twelve months? Asked if CQ1=1
How much would you pay for own-consumed FISH if you were to buy them? [VALUE IN KWACHA] Asked if CQ5=1
Did your household harvest or collect in FORESTRY in the last twelve months?
How much did your household receive from the sale of FORESTRY PRODUCT? [VALUE IN KWACHA] Asked if CQ7=1
Did your household consume own-harvested (collected) FORESTRY PRODUCTS in the last twelve months? Asked if CQ7=1
How much would you pay for own-consumed FORESTRY PRODUCTS if you were to buy them? [VALUE IN KWACHA] Asked if CQ9=1
In the last twelve months, did your household receive any other source of farming income (lease of tractor, agricultural land, scotch cart, lease of transport for produce, hiring outof draught animals, etc.)
How much income did your household receive from those activities? [VALUE IN KWACHA] Asked if CQ11==1

1: YES / 2: NO

1: YES / 2: NO
1: YES / 2: NO
1: YES / 2: NO
1: YES / 2: NO

SUBSECTION 6D: FARMING COSTS & EXPENSES [ASKED IF Q1A=1]
ITEMS

DQ 1
Did you use /incur[ITEM] during the lasttwelve months?

DQ 2
How much was spent in cash
and in kind on [ITEM] in thelast twelve months?

1: YES
2: NO[VALUE IN KWACHA.
CONVERT IN KIND TO
CASH EQUIVALENT]

DQ 3What was the source of the [ITEM]?
1: PRIVATE SECTOR
2: COOPERATIVES
3: MIN OF AGRICULTURE
4: MIN COMMUNITY DEVT
5: NGOs
6: OTHER

Asked if DQ1=1
Asked if DQ1=1
1. Fertilizer (Inorganic)
2. Organic Fertilizer
3. Insecticides
4. Herbicides
5. Any crop storage facility
6. Purchased seed, seedlings etc
7. Irrigation equipment
8. Bags, containers, strings
9. Petrol/ diesel/ oil
10. Repairs/ maintenance of agriculturalequipment including purchase of spare parts
11. Hired labour
12. Any transport costs
13. Hired animals
14. Hired equipment
15. Local hand tools
16. Imported hand tools
17. Any other crop production related costs

DQ 4
Was/were the [ITEM] obtainable/ available during the last twelve
months when needed?
1: YES SOMETIMES
2: YES ALL THE TIME
3: NO
4: NOT APPLICABLE / DON’T
KNOW

DQ 5
Why was the [ITEM] unobtainable?
1: INPUT MARKET TOO FAR
2: INPUTS WERE NOT ENOUGH
3: LATE DELIVERY OF INPUTS
4: TOO EXPENSIVE
5: OTHER
Asked if DQ4=1, 3

SUBSECTION 6E: LIVESTOCK & POULTRY COSTS [ASKED IF Q1B=1]
EQ 1
Did you use /incur[ITEM] during thelast twelve months?

ITEMS

1: YES2: NO

EQ 2
How much was spent incash and in kind on[ITEM] during the lasttwelve months?
[CONVERT IN KINDTO
CASH
EQUIVALENT]
Asked if EQ1=1

EQ 3
What was the source of the [ITEM]?
1: PRIVATE SECTOR
2: COOPERATIVES
3: MIN OF AGRICULTURE
4: MIN COMMUNITY DEVT
5: NGOs
6: OTHER
Asked if EQ1=1

EQ 4
Was/were
the[ITEM]
obtainable/available during
the last twelve months whenneeded?
1: YES SOMETIMES
2: YES ALL THE TIME
3: NO
4: NOT APPLICABLE /DON’T KNOW

EQ 5
Why was the [ITEM] unobtainable?
1: INPUT MARKET TOO FAR
2: INPUTS WERE NOT ENOUGH
3: LATE DELIVERY OF INPUTS
4: TOO EXPENSIVE
5: OTHER
Asked if EQ4=1,3

1. Animal Feed including salt
2. Veterinary services (incl vaccination & medicine)
3. Any hired labour
4. Maintenance of pens, stables
5. Transport costs
6. Commission on sale of animals
7. Compensation for damage caused by animals
8. Any other livestock production related costs

SUBSECTION 6F: FISH FARMING & FORESTRY COSTS [ASKED IF Q1C=1]
ITEMS

FQ 1
Did you use /incur[ITEM] during thelast twelve months?
1: YES2: NO

FQ 2
How much was spent incash and in kind on[ITEM] during the lasttwelve months?
[CONVERT IN KINDTO
CASH
EQUIVALENT]
Asked if FQ1=1

1. Purchase of fingerlings
2. Feed3. Hired labour
4. Repairs & Maintenance of fish ponds
5. Repairs & Maintenance of fish pond related equipment
6. Medicines for fish
7. Transport costs
8. Hand tools
9. Other fish farming production related costs
10. Forestry costs

FQ 3
What was the source of the [ITEM]?
1: PRIVATE SECTOR
2: COOPERATIVES
3: MIN OF AGRICULTURE
4: MIN COMMUNITY DEVT
5: NGOs
6: OTHER
Asked if FQ1=1

FQ 4
Was/were
the[ITEM]
obtainable/available during
the last twelve months whenneeded?
1: YES SOMETIMES
2: YES ALL THE TIME
3: NO
4: NOT APPLICABLE /DON’T KNOW

FQ 5
Why was the [ITEM] unobtainable?
1: INPUT MARKET TOO FAR
2: INPUTS WERE NOT ENOUGH
3: LATE DELIVERY OF INPUTS
4: TOO EXPENSIVE
5: OTHER
Asked if FQ4=1,3

SECTION 7: OTHER INCOME
INTRODUCTION: I would like to ask about income from other sources in the last twelve months.
1

RENT: What was the value of rent your household received in the twelve months? [Rent for houses, other buildings, non-agricultural equipment and non-agricultural land you own]
[VALUE IN KWACHA. ENTER 0 IF NO INCOME FROM THIS SOURCE]

2

SAVING INTEREST: What was the value of interest on savings your household received in the last twelve months?
[VALUE IN KWACHA. ENTER 0 IF NO INCOME FROM THIS SOURCE]

3

SHARES, SECURITIES, BONDS: What was the value of interest or dividends on shares, securities, bonds, treasury bills, etc your household received in the last twelve months?
[VALUE IN KWACHA. ENTER 0 IF NO INCOME FROM THIS SOURCE]

4

REMITTANCES: What was the value of remittances your household received in the last twelve months?
[VALUE IN KWACHA. ENTER 0 IF NO INCOME FROM THIS SOURCE]

5

GIFT: What was the value of gifts your household received in the last twelve months? (E.g. Ceremony gifts, small food gifts from neighbors, relief food. DO NOT include in-kind payment from jobs)[VALUE IN KWACHA. CONVERT IN-KIND GIFTS INTO KWACHA EQUIVALENT. ENTER 0 IF NOT RECEIVE THIS SOURCE OF INCOME]

6

Does your household receive income from any other source? If so, how much was it in the last twelve months?
[VALUE IN KWACHA. ENTER 0 IF NOT RECEIVE THIS SOURCE OF INCOME]

7(CHANGE IN REFERENCE PERIOD) Did you borrow in cash or in kind in the LAST MONTH? If so, how much did your household borrow, including both CASH and IN-KIND?
[VALUE IN KWACHA. CONVERT IN-KIND BORROWING TO KWACHA EQUIVALENT. INCLUDE BORROWING THAT WAS ALREADY REPAID. TYPE 0 IF NOT BORROWING.]

Section 8: HOUSEHOLD ASSETS & DURABLES
I would like to ask you about whether your household owns the following assets or durable goods. Does your household own ...?
[DO NOT COUNT PERMANENTLY BROKEN ITEMS OR ITEMS BORROWED FROM SOMEONE]
1: YES
2: NO
GENERAL ITEMSTOOLS & MACHINES
1
Bed
31
Sewing machine2
Mattress
32
Hand hammer mill
3
Mosquito net
33
Grinding / hammer mill (powered)
4
Table (dinning)
34
Sheller
5
Lounge suit / sofa
35
Ramp presses / oil expellers
6Radio / Stereo
36
Hand saw
7
Television37
Carpentry plane
8
Satellite dish / decoder (free to air)
38
Axe
9
Satellite dish / decoder (DSTV)
39
Pick
10 Other pay TV
40
Hoe
11
DVD / VCR
41
Hammer12 Home theater
42
Shovel / spade
13 Land phone
43
Fishing net
14 Cellular phone
44
Hunting gun
15 Computer
45
Plough16 Watch
46
Crop sprayer
17 Clock
47
Knitting machine48
Lawn mowers
KITCHEN / HOUSEHOLD
49
Generator
18 Residential building
19 Non-residential building
TRANSPORT
20 Brazier / Mbaula
50
Small / hand-driven tractor
21 Gas stove51
4 wheel tractor
22 Electric stove52
Wheel barrow
23 Refrigerator
53
Scotch cart
24 Deep freezer
54
Bicycle25 Washing machine
55
Motor cycle
26 Dish washer
56
Large truck
27 Air conditioner / ventilator
57
Small / pick-up truck
28 Electric iron58
Van / minibus
29 Non-electric iron59
Car
30 Private water pump
60
Canoe
61
Boat
ANIMALS62
Oxen
63
donkeySECTION 9: HOUSEHOLD AMENITIES AND HOUSING CONDITIONSINTRODUCTION: I am now going to ask you about various amenities and housing conditionsNo.
QUESTION
CATEGORY AND CODE
1
What kind of dwelling does your 1: TRADITIONAL HUT
9: HOUSE ATTACHED TO/ ON TOP OF SHOP ETC
household live in?
2: IMPROVED TRADITIONAL HOUSE
10: HOSTEL
3: DETACHED HOUSE
11: NON-RESIDENTIAL BUILDING (EG SCHOOL
4: FLAT/APARTMENT/MULTI-UNIT
CLASSROOM, ETC)
5: SEMI-DETACHED HOUSE
12: UNCONVENTIONAL (EG KANTEMBA,
6: SERVANTS QUARTERS
STORAGE CONTAINER, ETC)
7: GUEST WING
13: OTHER
8: COTTAGE
2
How many rooms are occupied by this household excluding bathrooms and toilets?
(For rural areas count the number of rooms in each hut belonging to the household collectively)
3
On what basis does your 1: Owner-occupied
5: Rented from Parastatal (e.g. ZSIC, NAPSA, NHA,
household occupy the dwelling 2: Rented from local Government
ZIMCO, etc)
you live in?
(District council)
6: Rented from private persons (landlord)
Is it […]?
3: Rented from Central Government
7: House owned and provided free by employer
4: Rented from Private Company
8: Other free housing
9: Other4
How is the rent paid?
1: Deducted from salary but paid in full
4: Paid by employer
Is it […]?
2: Deducted from salary and subsidized by 5: Other
employer
6: Not applicable
Asked if Q3=2-6
3: Paid directly by the household
7: Don’t know
5A
In what installments or period do Monthly
Every six (6) months
you pay your rent?
Every two (2) months
Other
Asked if Q4=1-3
Every three (3) months
Not applicable
5B
How much rent do you pay per month?
Asked if Q4=1-3
AMOUNT IN KWACHA
5C
Does this rent include charges for electricity? 1: YES / 2: NO
Asked if Q4=1-3
5D
Does this rent include charges for water? 1: YES / 2: NO Asked if Q4=1-3
6
If you were to rent out this house, how much would it fetch per month (excl water AMOUNT IN KWACHA
and electricity)?
7A
How much do you pay for ground rates per year? Asked if Q3=1
AMOUNT IN KWACHA
7B
How much do you pay for property rates per six months? Asked if Q3=1
AMOUNT IN KWACHA
7C
Do you pay mortgage for your dwelling? 1: YES / 2: NO Asked if Q3=1
7D
How much do you pay for mortgage per month? Asked if Q3=1
AMOUNT IN KWACHA
8A
What kind of building materials is 1: ASBESTOS SHEETS
6: CONCRETE
the ROOF of this dwelling made 2: ASBESTOS TILES
7: OTHER
of?
3: OTHER/ NON-ASBESTOS TILES
8: NOT APPLICABLE
4: IRON SHEETS
9: DON’T KNOW
5: GRASS/STRAW/THATCH
8B
What kind of building materials 1: PAN BRICK
9: IRON SHEETS
is/are the WALLS of this dwelling 2: CONCRETE BRICK
10: STEEL
made of?
3: MUD BRICK
11: HARDBOARD
4: BURNT BRICK
12: A MIXTURE OF HARDBOARD, TIN
5: POLESHEET, PLASTIC, ETC
6: POLE & DAGGA
13: OTHER
7: MUD
14: NOT APPLICABLE
8: GRASS/STRAW
15: DON’T KNOW
8C
What kind of building materials is 1: CONCRETE ONLY
5: OTHER
the FLOOR of this dwelling made 2: COVERED CONCRETE
6: NOT APPLICABLE
of?
3: MUD
7: DON’T KNOW
4: WOOD ONLY
9What is the main source of water 1: DIRECTLY FROM RIVER/ LAKE/ 7: PROTECTED SPRING
supply for this household?
STREAM/DAM
8: PUBLIC TAP
[ASK
ABOUT
NON- 2: RAINWATER
9: OWN TAPDRINKING WATER.]
3: UNPROTECTED WELL
10: OTHER TAP (EG FROM NEARBY BUILDING)
4: PROTECTED WELL
11: WATER KIOSK
5: BOREHOLE
12: BOUGHT FROM OTHER VENDORS
6: UNPROTECTED SPRING
13: OTHER
10
How far is this source of water 1: LESS THAN 1 KM
4: ABOUT 3 KM (45-MINUTE WALK)
from this house?
(LESS THAN 15-MINUTE WALK)
5: ABOUT 4 KM (1-HOUR WALK)[RECORD 'LESS THAN 1 KM' 2: ABOUT 1 KM (15-MINUTE WALK)
6: GREATER THAN 4 KM
IF OWN TAP]
3: ABOUT 2 KM (30-MINUTE WALK)(GREATER THAN 1-HOUR WALK)
7: NOT APPLICABLE / DON’T KNOWANSWER

No.
11

12
13
14

SECTION 9: HOUSEHOLD AMENITIES AND HOUSING CONDITIONS (cont’d)
QUESTION
CATEGORY AND CODE
What is the main source of 1: DIRECTLY FROM RIVER/ LAKE/ 8: PUBLIC TAP
drinking
waterforthis STREAM/DAM
9: OWN TAP
household?
2: RAINWATER
10: OTHER TAP (EG FROM NEARBY BUILDING)
3: UNPROTECTED WELL
11: WATER KIOSK
4: PROTECTED WELL
12: BOUGHT FROM OTHER VENDORS
5: BOREHOLE
13: BOTTLED WATER
6: UNPROTECTED SPRING
14: OTHER
7: PROTECTED SPRING
Do you treat your drinking water? 1: YES / 2: NO [YES ONLY IF TREATMENT IS DONE BY HOUSEHOLD.]
How do you treat your drinking water? 1: BOIL / 2: ADD CHLORINE / 3: OTHER Asked if Q12=1

23

How much on average are you charged for water per month?
AMOUNT IN KWACHA[ENTER “0” IF HOUSEHOLD IS PROVIDED WITH WATER FOR FREE]
Asked if Q5D is not YES
What is the main type of energy 1: KEROSINE/PARAFFIN
4: CANDLE
7: TORCH
used for lighting in your 2: ELECTRICITY
5: DIESEL
8: NONEhousehold?
3: SOLAR PANEL
6: OPEN FIRE
9: OTHER
What is the main type of energy 1: COLLECTED FIREWOOD
5: COAL
9: SOLAR
that your household uses for 2: PURCHASED FIREWOOD
6: KEROSINE/PARAFFIN
10: CROP/LIVESTOCK
cooking?
3: CHARCOAL OWN PRODUCED
7: GASRESIDUES
4: CHARCOAL PURCHASED
8: ELECTRICITY
11: OTHER
What is the main type of cooking 1: STOVE/COOKER…1
4: BRICK/STONE STAND ON 7: HOT PLATE WITHOUT STAND
device used by your household?
2: BRAZIER (MBAULA)
OPEN FIRE
8: HOT PLATE ON WELDED
3:CLAY
STOVE 5: METAL STAND ON OPEN STAND(MBAULA)FIRE
9: OTHER
6: VEHICLE TYRE RIM
Is your house connected to electricity? 1: YES / 2: NO
How much on average are you charged for electricity per month?
AMOUNT IN KWACHA[ENTER “0” IF HOUSEHOLD IS PROVIDED WITH ELECTRICITY FOR FREE]
Asked if Q18 is YES but Q5D is not YES
What is the main type of toilet 1: OWN FLUSH TOILET INSIDE THE 7: COMMUNAL PIT LATRINE WITHOUT SLAB
facility used by this household?
HOUSEHOLD
8: NEIGHBOUR’S/ ANOTHER HOUSEHOLD’S
2: OWN FLUSH TOILET OUTSIDE THE PIT LATRINE WITHOUT SLAB
HOUSEHOLD
9: BUCKET/ OTHER CONTAINER
3: OWN PIT LATRINE WITH SLAB
10: AQUA PRIVY
4: COMMUNAL PIT LATRINE WITH SLAB
11: NONE
5:
NEIGHBOUR’S/
ANOTHER 12: OTHER
HOUSEHOLD’S PIT LATRINE WITH SLAB
6: OWN PIT LATRINE WITHOUT SLAB
If flush/ pour flush: Where is the 1: PIPED SEWER SYSTEM
4: OTHER
sewerage piped into?
2: SEPTIC TANK
5: DON’T KNOW
Asked if Q20=1,2
3: PIT LATRINE
What is the main method of 1: REFUSE COLLECTED
4: BURNING
garbage disposal that this 2: PIT
5: OTHER
household uses?
3: DUMPING
Is there a farm land where any member of this household can cultivate any food crops on their behalf? 1: YES / 2: NO

24AWhat is the total size of the farm land?

[AREA]

24B

Asked if Q23=1[UNIT] 1: LIMA / 2: ACRE / 3: HECTARE

25

Is there a home garden where any member of this household can cultivate any food crops on their behalf?

26A

What is the total size of home garden?

[AREA]

26B

Asked if Q25=1[UNIT] 1: LIMA / 2: ACRE / 3: HECTARE

15
16

17

18
19
20

21
22

1: YES / 2: NO

ANSWERSECTION 10 HOUSEHOLD EXPENDITURE
Cereals DURING LAST 4 WEEKS
ITEMS

Q1
Did your household
purchase / consume[ITEM] during thelast 4 weeks?
1: YES
2: NO

1
2
3
4
5
6

Q2A
Q2B
How many (much) [ITEM] did
your household purchase?
Asked if Q1=1

QUANTITY

UNIT
CODE

Q3
How much did yourhousehold spend on[ITEM]? (IN TOTAL)
Asked if Q1=1

VALUE IN KWACHA

Q4
When
purchasing,was[ITEM] shelled or unshelled?
1: SHELLED
2: UNSHELLED
3: BOTH
4: DON’T KNOW
Asked if Q1=1

Maize grain
breakfast mealie meal
Roller meal
Hammer mealie meal
Pounded maize meal
Cost of milling
SECTION 10 HOUSEHOLD EXPENDITURE (Cont.)

Crops & Crop Products DURING LAST 2 WEEKS
ITEMS

Q5
Did your household
purchase / consume[ITEM] during thelast 2 weeks?
1: YES
2: NO

7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37

MilletSorghum
Rice
Wheat / Flour
Bread / Breadrolls
Buns / scones
Fritters
Other cereal / bread items
Sweet potatoes
Potatoes
Cassava (tubers)
Cassava (flour)
Other roots / tubers
Fresh beans (excl green beans)
Sunflower
Soya beans
Dried beans
Groundnuts
BambaraCowpeasPeas
Other pulses, legumes
OnionsTomatoes
Cabbages
Rape
Okra
Pumpkin leaves (chibwabwa)
Cassava leaves
Kalem bula
Bondwe

Q6A
Q6B
How many (much) [ITEM]
did
yourhouseholdpurchase?
Asked if Q5=1
QUANTITY

UNIT
CODE

Q7
How much did yourhousehold spend on[ITEM]? (IN TOTAL)
Asked if Q5=1
VALUE IN KWACHA

Q8When purchasing, was [ITEM]
shelled or unshelled (unpeeled or
peeled)?
1: SHELLED/UNPEELED
2: UNSHELLED/PEELED
3: BOTH
4: DON’T KNOW
Asked if Q5=1

ITEMSSECTION 10 HOUSEHOLD EXPENDITURE (cont.)
Crops & Crop Products DURING LAST 2 WEEKS (cont.)
Q5
Q6A
Q6B
Q7
Did your household How many (much) [ITEM] How much did yourpurchase / consume did
yourhousehold household
spend
on[ITEM] during the purchase for these amounts? [ITEM]? (IN TOTAL)
last 2 weeks?
Asked if Q5=1
Asked if Q5=1
1: YES
2: NO

38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56

QUANTITY

UNIT
CODE

VALUE IN KWACHA

Q8When purchasing, was [ITEM]
shelled or unshelled (unpeeled or
peeled)?
1: SHELLED/UNPEELED
2: UNSHELLED/PEELED
3: BOTH
4: DON’T KNOW
Asked if Q5=1

Impwa
CucumberGreen beans
CarrotPumpkinGreen maize
Other vegetables
Oranges
ApplesMangoesBananasPawpaws
Water melons
LemonsPinapples
Pears
Guavas
Avocados
Other fruits
SECTION 10 HOUSEHOLD EXPENDITURE (cont.)

Meat, Dairy & Fish DURING LAST 2 WEEKS
ITEMS

Q9
Did your household
purchase / consume[ITEM] during thelast 2 weeks?
1: YES
2: NO

57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74

KapentaBream
Buka Buka
Other fish
Fish products
Chicken
Other Poultry
Beef
Pork
Goat meat
Sheep meat
Game meat
Other meat
Fresh milk
Powdered milk (excl baby milk)
Eggs
CheeseOther dairy products

Q10A
Q10B
How many [UNITS] of[ITEM]
did
yourhousehold purchase forthese amounts?
Asked if Q9=1

Q11
How much did yourhouseholdspend
on[ITEM]? (IN TOTAL)
Asked if Q9=1

QUANTITYVALUE IN KWACHA

UNIT
CODE

Q12
When purchasing, was [ITEM]
fresh, frozen, dried or smoked?
1: FRESH
2: FROZEN
3: DRIED / SMOKED
4: DON’T KNOW
Asked if Q9=1

SECTION 10 HOUSEHOLD EXPENDITURE (cont.)

MICELLANEOUS DURING LAST 2 WEEKSQ13
Did your household purchase/ consume [ITEM] during thelast 2 weeks?
1: YES
2: NO

ITEMS

75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105

Q14A
Q14B
How many [UNITS] of [ITEM]
did your household purchase forthese amounts?

Q15
How much did your household spend
on [ITEM]? (IN TOTAL)
Asked if Q13=1

Asked if Q13=1
QUANTITY

UNIT CODEVALUE IN KWACHA

ButterMargarine
Peanut butter
Other fats (excl cooking oil)
Sugar
Honey
Jam
Cocoa and chocolate
CremoraOther sweets
Tea leaves / tea bags
Coffee (fresh, blend or instant)
Drinking chocolate / Milo / cocoa
JuiceSoft drinks
Mineral water
Munkoyo
Maheu
Other non-alcoholic beverages
Spirits
Wines
CidersClear beer
Opaque beer
Traditional brews
Other alcoholic beverages
Baby foods (e.g. Cerelac, vitaso, baby
milk)
Food from kiosks, cafes, restaurants
Other foods & beverages
Cigarettes
TobaccoUNIT CODES
B90
B50
B25
B10
T20
T10
T5
P
KG
GR
LT
ML

UNITS
90 KG BAG
50 KG BAG
25 KG BAG
10 KG BAG
20 LITRE TIN
10 LITRE TIN
5 LITRE TIN
PIECE/NUMBER
KILOGRAMS
GRAM
LITRE
MILLILITER

UNIT CODES
BOT500
BOT750
BOT2.5
BP
HP
PL
CU
GAL
BK
BD
MD
OT

UNITS
BOTTLE 500 ML
BOTTLE 750 ML
BOTTLE 2.5 LT
BP
HEAP
PLATE
CUP
GALLON
BUCKET
BUNDLEMEDAOTHER

SECTION 10 HOUSEHOLD EXPENDITURE (cont.)

MICELLANEOUS DURING LAST 4 WEEKSQ16
Did your household
purchase / consume[ITEM] during thelast 4 weeks?
1: YES
2: NO

ITEMS

106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130

Salt
SpicesCooking Oil
Charcoal
Firewood
Paraffin
Diesel (for lighting and cooking only)Home repairs (plumbing, painting, stove
repaires etc)
Cable/pay TV (DSTV, My TV, SATELITE,
ZNBC, etc)
Garbage collection (solid waste)
Gas
Kerosene / fuel for cooking / lighting
Coal, excl charcoal
Batteries, lightbulbs, lighters, matches, candles
Other housing expenses
Bath / hand-washing soap
Laundry detergent
Toothpaste & toothbrushes
Sanitary towels
Toilet paper and other tissues
Cosmetics (eg. lotion, creams, glycerin, makeup, petroleum jellies etc)
Hair care (eg perming, braiding hair,conditioning, shampooing, haircuts, etc)
Laundry service (eg dry cleaning, washing at thelaundry, etc)
Baby diapers
Cleaning agents, excl soap and laundry
detergents (eg ajax, dish washing liquids or
pastes, toilet cleansers, handy andy, air
freshners, cobra/polish, etc)

Q17
How much did yourhousehold spend on[ITEM]? (IN TOTAL)VALUE IN KWACHA
Asked if Q16=1

ITEMS

131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150

SECTION 10 HOUSEHOLD EXPENDITURE (cont.)
MICELLANEOUS DURING LAST 4 WEEKS (cont.)
Q16
Q17
Did your household How much did yourpurchase / consume household spend on[ITEM] during the [ITEM]? (IN TOTAL)
last 4 weeks?
VALUE IN KWACHA
1: YES
2: NO
Asked if Q16=1
Insecticides
Other hygiene expenses
Public transport to/from work
Public transport to/from school incl boarding
school and abroad
Other public transport
Petrol / diesel / oil
Vehicle maintenance & repairs
Motorbike repairs (tyres, tubes, oil, etc)
Bicycle repairs (tyres, tubes, oil, etc)
Boat / canoe repairs
Other private transport
Mobile phones (connection fees. air time
excluding cost of phone)
Landline phones (connection fees, prepaid &postpaid)Internet (connection and subscription fees)
Postal expenses
Other communication expenses
Entertainment excl alcohol (eg cinema, disco,watching soccer/boxing, video hire, visits toentertainment centres)
Domestic servants
Stationary (eg copies, printing paper, envelopes.
excl stationary for education)
Typing services, filling in official forms

SECTION 10 HOUSEHOLD EXPENDITURE (cont.)

SECTION 10 HOUSEHOLD EXPENDITURE (cont.)

MICELLANEOUS LAST TWELVE MONTHSREMITTANCES LAST TWELVE MONTHS

Q18
During the lasttwelve months, did
yourhouseholdpurchase / pay for[ITEM]?
1: YES
2: NO

ITEMS

151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177

Purchase of medicines
Fees for doctors
Fees for nurses, midwives
Fees for dentists
Fees for hospital stays
Fees for health assistantFees for traditional healers
Payment to hospital / health centre / surgery
Pre-payment scheme
Other health expenses
Water Treatment tablets, chemical etc
Other water treatment
Chitenges
Children’s clothing
Men’s clothing
Women’s clothing (excl chitenges)
Fabric / material
Tailoring chitenges
Footwear (eg shoes, sandals, pata pata, sofias)
Loan payments
Contributions to church, mosques, etc
Insurance (car, life, health)
Funerals, gifts, dowries
Contribution to school / PTA
School stationary (exercise books, pens, pencils,
rulers, rubbers, math sets, paper)
Purchase of other school requisites (for boarders
snacks, mazoe, biscuits, tinned foods)
Other
education
expenses(graduation
ceremonies, tuck shop money, pocket money forstudents, boarding and lodging for students,
remittances to students outside of house)

Q19
How much did yourhousehold spend on[ITEM]? (IN TOTAL)VALUE IN KWACHA

Q20A
Q20B

Asked if Q18=1
Q20C

Q21A
Q21B

Q21C

Q22A
Q22B

Q22C

During the last twelve months, did your household send remittances in cash or in kind to person
in rural area of Zambia (excluding any member of your household)?
1: YES / 2: NO
What is the value of CASH REMITTANCES to person in rural area of Zambia?
[VALUE IN KWACHA.
ENTER 0 IF NO CASH REMITTANCES]
Asked if Q22A=1
What is the value of IN-KIND REMITTANCES to person in rural area of Zambia?
[VALUE IN KWACHA.
CONVERT TO KWACHA EQUIVALENT.
ENTER 0 IF NO IN-KIND REMITTANCES]
Asked if Q22A=1
During the last twelve months, did your household send remittances in cash or in kind to person
in urban area of Zambia (excluding any member of your household)?
1: YES / 2: NO
What is the value of CASH REMITTANCES to person in urban area of Zambia?
[VALUE IN KWACHA.
ENTER 0 IF NO CASH REMITTANCES]
Asked if Q23A=1
What is the value of IN-KIND REMITTANCES to person in urban area of Zambia?
[VALUE IN KWACHA.
CONVERT TO KWACHA EQUIVALENT.
ENTER 0 IF NO IN-KIND REMITTANCES]
Asked if Q23A=1
During the last twelve months, did your household send remittances in cash or in kind to person
outside of Zambia (excluding any member of your household)?
1: YES / 2: NO
What is the value of CASH REMITTANCES to person outside of Zambia?
[VALUE IN KWACHA.
ENTER 0 IF NO CASH REMITTANCES]
Asked if Q24A=1
What is the value of IN-KIND REMITTANCES to person outside of Zambia?
[VALUE IN KWACHA.
CONVERT TO KWACHA EQUIVALENT.
ENTER 0 IF NO IN-KIND REMITTANCES]
Asked if Q24A=1

For children aged 0-59 months only. Answer cells omitted.

SECTION 11: CHILD HEALTH AND NUTRITION [FOR CHILDREN AGED 0 - 59 MONTHS ONLY]
1
Is [NAME]
being
breastfed
now?
1: YES
2: NO

2A
How long after birth
did you put [NAME] tothe breast? (IN DAYS)[IF LESS THAN 24
HOURS, RECORD 0.
IF DON’T KNOW,
RECORD 99.]

2B
(IF LESS THAN 24
HOURS TO THE
PREVIOUSQUESTION) How
long IN HOURS?
[IF LESS THAN 24
HOURS, RECORD
0.]

Asked if Q1=1
Asked if Q2A=0

3A
3B
3C
3D
In addition to breast milk is [NAME] fed on any of the following? Asked if Q1=1
Any other milk other thanbreast milk[e.g. S26, lactogen,promil or other baby
formula, Fresh milk,
Soya milk, Goat milk]
1: YES
2: NO

Water

Other fluids

Solids[e.g. custard, cerelac orothercereal,vitaso,porridge, nshima]

1: YES
2: NO
1: YES
2: NO

1: YES
2: NO

4Has [NAME] ever beenbreastfed?

SECTION 13: CHILD HEALTH AND NUTRITION [Cont’d]56
7
For how many months At what age did you first give [NAME] How many times is [NAME] currently given solids foods in
did you breastfeed water or other fluids or food? (IN a day (nshima, rice, potatoes, porridge, cerelac, other[NAME]?
MONTHS)
cereals, vitaso, custard, etc)?

1: YES
2: NO
3: DON’T KNOW

Asked if Q6=1

Asked if Q1=2

ENTER 0 IF LESS THAN ONE
MONTH.
ENTER 88 IF NOT STARTED ON
WATER, OTHER FLUIDS OR FOOD.
ENTER 99 IF DON'T KNOW.

1: ONCE
2: TWICE
3: THRICE
4: FOUR TIMES
5: FIVE TIMES
6: MORE THAN FIVE TIMES
7: NOT YET STARTED ON SOLIDSSECTION 12: DEATHS in HOUSEHOLD
1
2

Have there been any deaths in the household (OF USUAL MEMBERS) in the last 12 months?
1: YES / 2: NO / 3: REFUSEDHow many people died in the last 12 months?

I am going to ask about the first deceased person. Asked if Q2≥1
3
4How old was he/she?
[RECORD AGE IN COMPLETED YEARS. RECORD 0 IF LESS THAN 1 YEAR. RECORD 888 IF NO RESPONSE]
Wat was his/her sex? 1: MALE / 2: FEMALE / 8: REFUSED

5

What was the main cause of death? [CHOOSE FROM THE LIST BELOW]

I am going to ask about the second deceased person. Asked if Q2≥2
6
7How old was he/she?
[RECORD AGE IN COMPLETED YEARS. RECORD 0 IF LESS THAN 1 YEAR. RECORD 888 IF NO RESPONSE]
Wat was his/her sex? 1: MALE / 2: FEMALE / 8: REFUSED

8

What was the main cause of death? [CHOOSE FROM THE LIST BELOW]

I am going to ask about the third deceased person. Asked if Q2≥3
910How old was he/she?
[RECORD AGE IN COMPLETED YEARS. RECORD 0 IF LESS THAN 1 YEAR. RECORD 888 IF NO RESPONSE]
Wat was his/her sex? 1: MALE / 2: FEMALE / 8: REFUSED

11

What was the main cause of death? [CHOOSE FROM THE LIST BELOW]

I am going to ask about the fourth deceased person. Asked if Q2≥412
13How old was he/she?
[RECORD AGE IN COMPLETED YEARS. RECORD 0 IF LESS THAN 1 YEAR. RECORD 888 IF NO RESPONSE]
Wat was his/her sex? 1: MALE / 2: FEMALE / 8: REFUSED

14

What was the main cause of death? [CHOOSE FROM THE LIST BELOW]

I am going to ask about the fifth deceased person. Asked if Q2≥5
15
16How old was he/she?
[RECORD AGE IN COMPLETED YEARS. RECORD 0 IF LESS THAN 1 YEAR. RECORD 888 IF NO RESPONSE]
Wat was his/her sex? 1: MALE / 2: FEMALE / 8: REFUSED

17

What was the main cause of death? [CHOOSE FROM THE LIST BELOW]

I am going to ask about the sixth deceased person. Asked if Q2≥6
18
19

How old was he/she?
[RECORD AGE IN COMPLETED YEARS. RECORD 0 IF LESS THAN 1 YEAR. RECORD 888 IF NO RESPONSE]
Wat was his/her sex? 1: MALE / 2: FEMALE / 8: REFUSED

20

What was the main cause of death? [CHOOSE FROM THE LIST BELOW]
THE LIST OF THE CAUSES OF DEATH

1

FEVER/MALARIA

13

2
3
4
5
6
7
8
9
10
11
12

CEREBRAL MALARIACOUGH/COLD/CHEST INFECTION
TUBERCULOSISASTHMA
BRONCHITISPNEUMONIA/CHEST PAIN
DIARRHOEA WITHOUT BLOOD
DIARRHOEA WITH BLOOD
DIARRHOEA AND VOMITTINGVOMITTING
ABDOMINAL PAINS

14
15
16
17
18
19
20
21
22
23

CONSTIPATION/STOMACHUPSETLIVER INFECTION/SIDE PAINLACK OF BLOOD/ANEAMIABOILSSKIN RASH/SKIN INFECTIONPILES/HAEMOROIDS
SHINGLES/HERPES ZOSTERPARALYSIS OF ANY KINDSUICIDE
MURDERED
ACCIDENT24

STROKE

25
26
27
28
29
30
31
32
33
34

HYPERTENSIONDIABETES/SUGAR DISEASEHEADACHE
MEASLESJAUNDICE/YELLOWNESSCANCER OF ANY KINDMENINGITISSTILL BIRTH
OTHER (INCL NATURAL DEATH)
DON’T KNOW / REFUSEDCONCLUDING REMARKDATE_EDATE OF THE END OF THE INTERVIEWINTERVIEWER

NAME OF THE INTERVIEWER