The Living Conditions Monitoring Surveys (LCMS) evolved from the Social Dimensions of Adjustment Priority surveys conducted in 1991 (PSI) and 1993 (PSII), by the Central Statistical Office. So far, four Living Conditions Monitoring Surveys have been conducted and LCMS 1998 was the second in the series. The surveys are: -
(i) The Living Conditions Monitoring Survey I of 1996
(ii) The Living Conditions Monitoring Survey II of 1998
(iii) The Living Conditions Monitoring Survey III of 2002/2003 and
(iv) The Living Conditions Monitoring Survey IV of 2004
The Central Statistical Office carried out a Living Conditions Monitoring Survey in November-December, 1998. The survey was carried out nation-wide in all the 72 districts of Zambia on a sample basis. The main objectives of the survey are to:-
(i) Monitor the effects of government policies on households and individuals.
(ii) Measure and monitor poverty overtime in order for government to evaluate its poverty reduction programs.
(iii) To monitor the living conditions of households in Zambia in the form of access to various economic and social facilities and infrastructure and access to basic needs; food, shelter, clean water and sanitation, education and health, etc.
(iv) To identify vulnerable groups in society. The Living Conditions Monitoring Survey (LCMS 1998) collected data on the living standards of households and persons in the areas of education, health, income sources, income levels, food production and consumption, and access to various amenities.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The survey covered the following topics:-
· Demographic characteristics i.e. Age, sex , relationship, marital status and residence; Migration; Orphanhood; Deaths in households
· Economic Activities
· Under five Children Nutrition (Anthropometry)
· Access to various facilities & infrastructure
· Household Assets
· Community Developmental Issues
· Food production
The LCMS 1998 was conducted nation-wide on a sample basis and covered both rural and urban areas of all the 72 districts in the country. The eligible household population consisted of all households. Excluded from the sample were institutional populations in hospitals, boarding schools, colleges, universities, prisons, hotels, refugee camps, orphanages, military camps and bases and diplomats accredited to Zambia in embassies and high commissions. Private households living around these institutions and cooking separately were included such as teachers whose houses are within the premises of a school, doctors and other workers living on or around hospital premises, police living in police camps in separate houses, etc. Persons who were in hospitals, boarding schools, etc. but were usual members of households were included in their respective households. Ordinary workers other than diplomats working in embassies and high commissions were included in the survey also. Others with diplomatic status working in the UN, World Bank etc. were included. Also included were persons or households who live in institutionalized places such as hostels, lodges, etc. but cook separately. The major distinguishing factor between eligible and non eligible households in the survey is the cooking and eating separately versus food provided by an institution in a common/communal dining hall or eating place. The former cases were included while the latter were excluded.
Producers and sponsors
Central Statistical Office, Ministry of Finance and National Planning
Government of Republic of Zambia
Government of Republic of Zambia
Government of Norway
Social Recovery Project (SRP)
The World Bank
Managing the funds as a component of the overall Social Fund through the World Bank
The World Bank (ASIF 2000 Fund)
The World Bank
Contributing towards collection of data in some Micro-projects areas
The London School of Hygiene and Tropical Medicine
Contributing towards the collection of the health component of the survey
The World Bank Washington D.C and Lusaka
Sampling Frame and Stratification
The country is made up of 9 provinces comprising 72 districts delineated by the Local Government Administration. Previously there were 57 districts in Zambia. 15 new districts have been created. Central Statistical Office has delineated these districts into Census Supervisory Areas (CSAs) and then these into Standard Enumeration Areas (SEAs) for the purposes of conducting censuses and sampling for surveys. Each CSA is made up about 3 SEAs. The list of CSAs and SEAs by province & district constitute the sampling frame for CSO censuses and surveys. The sampling frame comprises 4,193 CSAs of which 3,231 are rural and 962 are urban and 12,999 SEAs. The frame of CSAs and SEAs is arranged by province, then by district within a province,then by rural/urban within a district, then by centrality within rural/urban, and finally by low, medium or high cost for urban SEAs. The frame also contains information on the number of households and the population size per SEA and this is what was used when selecting the sample using the probability proportional to size (PPS) method. The number of households and the population in the frame is based on the 1990 population census. To boost the data from the survey to 1998 population parameters the weights calculated were multiplied by a factor equal to the estimated population growth from 1990 to 1998. This was done at the district level.
The classification of centrality is shown below:-
1. Areas within Lusaka city.
2. Areas within Ndola city.
3. Areas within Kitwe city.
4. Areas within 50 Kms radius outside Lusaka, or Ndola, or Kitwe cities.
5. Areas within provincial capitals.
6. Areas along Southern to Copperbelt line of Rail (within 30 Kms radius).
7. Areas along Northern line of Rail (within 30 Kms radius).
8. Areas within 30kms radius outside provincial capitals.
9. Areas within district centres.
10.Areas within 30 Kms radius outside district centres
Areas within cities, provincial capitals and district centres is equivalent to the urban part of the town.Within the rural SEAs households have been classified on the basis of the scale of agricultural activities into small scale, medium scale, large scale, and non-agricultural households.The urban SEAs have been classified into low cost, medium cost or high cost depending on the type of housing in the area.The local government administration has classified localities into low, medium and high cost based on the required housing standard. The urban SEAs were classified into low, medium and high cost areas based on a combination of the local government and CSO criteria. All urban SEAs were physically visited by CSO mapping staff with locality classification from local government and determined whether the SEA was low, medium or high cost based on the local government definition and the actual observation of the mapper. The mappers were trained on how to make this determination. Households within rural SEAs were classified into small scale, medium scale, large scale, and non agricultural households after the listing operation.
Sample Size: Out of a total of 12,999 SEAs in the frame, a sample of 820 SEAs were selected for the Living Conditions Monitoring Survey (1998) representing about 6% of the total. The urban stratum was allocated 328 SEAs and the rural stratum was allocated 492 SEAs. The total number of households enumerated were 8520 in rural areas and 8220 in the urban areas.The total number of persons who fell in the sample were 45989 in rural areas and 47480 in urban areas.All the 72 districts in Zambia were covered in the survey on a sample basis.
Sample Allocation: Sample allocation was done using the "Probability Proportional to size" (PPS) method. This entailed allocating the total sample (820) proportionately to each province according to its population share.Thereafter, allocation of the provincial sample was done proportionately to each district according to the population share from the provincial population. Similarly allocation was done by centrality within a district. For example, Mkushi district was allocated 10 SEAs by the PPS method. The district has four centrality classifications (9, 7, 10, and11). The number of SEAs under each centrality classification in the frame were summed up. The next step was to determine the share of each centrality group of SEAs from the total number of SEAs in the frame under Mkushi district. The corresponding proportions were used to allocate the sample to each centrality category. However, the final allocation was plus or minus depending on what was obtaining in the frame. For example if 1 SEA was to be allocated to centrality 9 (District centre) by using PPS and yet there is low, medium & high cost SEAs under centrality 9 in that district, the number of SEAs selected was 3 (one from low, and the other two from the medium & high cost SEAs). Not all centrality classifications obtain in all districts, for example, Lusaka district had all the SEAs fall under centrality 1 (Lusaka city) in the frame. Therefore the entire number of SEAs allocated to Lusaka district was selected from this category. The minimum size for each district sample was 7 SEAs, meaning that even the smallest district was allocated at least 7 SEAs.
Sample Selection: Sample selection was done in two stages. In the first stage, a sample of SEAs was selected within each stratum (centrality) according to the number allocated to that stratum. The second stage comprised selection of households from each sample SEA according to the number of households recommended after a complete listing of all households in the sample SEAs. Thus SEAs formed primary sampling units. The unit of analysis was the household.
Selection of SEAS: After sample allocation was done, selection of the sample SEAs from the frame followed. The allocated number of SEAs were selected at centrality level using the PPS method.
Selection of Households:In each selected SEA, households were listed and each household given a unique sampling serial number. A circular systematic sample of households was then selected. Vacant residential housing units and noncontact households were not assigned sampling serial numbers. Selection of sample households was done by supervisors in the field and they were required to select the following numbers of households:
30 households from SEAs with sample Micro-projects (whether rural or urban).
25 households from urban SEAs (without sample micro-projects)
15 households from rural SEAs (without sample micro-projects). This number increased in rural SEAs where large scale farmers were identified.
In urban areas the required sample number of households were selected straight forwardly using the circular systematic sampling method. In the rural areas, 7 households were selected from the stratum of small scale farmers, 5 from medium scale farmers, 3 from non-agricultural households, and all large scale farmers if any were found in the SEA. Therefore, the number of selected households from a rural SEA was more than 15 where there were large scale farmers. In Micro-project areas the number of households to select was double, 14 in the small scale category, 10 in the medium, 6 in the non-agric, and all large scale farmers.
The circular systematic sample selection method was used in both rural and urban SEAs.The circular systematic sampling method assumes that the households are arranged in a circle and the following relationship applies (Kalton G., 1983):-
were, N=Total number of households assigned sampling serial numbers in a stratum.
n=Total sample required from a stratum.
K=The sampling interval in a given stratum calculated as K=N/n.
Therefore, for urban strata K=N/25 or K=N/30 (for micro-projects areas).
And for rural strata, K=N/7 in the small scale stratum, K=N/5 in the medium scale stratum, and K=N/3 in the non-agric stratum. K was not calculated in the large scale stratum as all large scale households identified in an SEA were enumerated. In most cases there were no large scale farmers in an SEA and in a few cases there was no more than one. In the case of micro-projects areas the corresponding K'S were N/14, N/10 and N/6 respectively. The N in the rural SEAs differed from stratum to stratum within an SEA.
The steps in selecting households were as follows:-
(i) A random number was obtained using a table of random numbers. This number was between 1 and N (both inclusive). The urban SEAs had one random start per SEA while the rural SEAs had three random starts per SEA (one for each stratum except the large scale stratum).
(ii) The sampling interval (K=N/n) was calculated for each urban SEA and for each stratum in the rural SEAs.
(iii) The sample number of households required was then selected using the circular systematic method. The household whose sampling serial number corresponded to the random start was the first to be selected. Then K, the sampling interval was added to the sampling serial number of each selected household in the respective strata until the required n (sample size) was achieved. All in all 8220 urban households and 8520 rural households were selected.
After enumeration was completed, weights were calculated and sample statistics were used to estimate population parameters. In the rural areas weights were calculated for each of the four strata separately, that is, for the small scale, medium scale, and large scale agricultural households and nonagricultural households. In the urban areas, weights were calculated for each of the three urban strata also and these are, low cost, medium cost, and high cost areas. The information used for calculating weights was obtained from the listing form as well as from the sampling frame. The information used to calculate weights included the following; Number of households listed per stratum, number of households enumerated per stratum, and stratum populations (from the frame). The weights were calculated based on the 1990 census population. In order to get population totals which are consistent with projected ones, the calculated weights were multiplied by a factor which is equal to the ratio of the projected population proportion in 1998 and the total 1990 population from the frame. This adjustment was done at district level.
Dates of Data Collection
Listing, Enumeration and Editing
Data Collection Mode
Supervisors were generally responsible for the following functions :
(i) Assisting Master Trainers and Provincial heads to train enumerators.
(ii) Organizing the enumerators to successfully complete their assignments;
(iii) Ensuring that the work completed by the field staff meets the standards of quality which are required.
(iv) Communicating with the Master trainer and Provincial head on a regular basis to report the status of the Survey, relay problems encountered in the field, and receive directives on Survey operations and resolutions to problems raised, allocating areas (SEAs), showing enumerator his/her SEA boundaries on the ground, issuing Survey Forms and other equipment.
(v) Providing routine supervision with regard to administrative and personnel matters. To supervise the enumerators under him/her on a daily basis and rotating between enumerators. Supervisors will lead and supervise on the average 5 enumerators.
(vi) Selecting the sample of households.
(vii) Editing completed listing sheets and questionnaires for consistency, legibility, completion, etc.
Data Collection Notes
The duties of the survey staff in conducting the Living Conditions Monitoring Survey (1998) were:
- Ensuring effective planning and timely execution of the survey.
- Developing and finalizing survey questionnaires.
- Writing of enumerators' and supervisors’ instruction manuals.
- Conducting and analyzing a pre-test.
- Training of field staff.
- Designing of quality control instructions and procedures.
- Preparing field materials, equipment and other logistical aspects of field work
- Organizing and supervising data entry..
- Tabulation, analysis, report writing and dissemination.
Training of field staff took place in three phases. The first stage was the training of Master trainers and heads of provincial CSO offices. Copperbelt and Northern provinces had two master trainers each while Lusaka province had three because of the magnitude of the sample in those provinces while the other provinces had one Master trainer each. Thirteen (13) Master trainers and thirteen (13) provincial heads were trained in total. The training was done in Lusaka and lasted one week. This was followed by another week of supervisors training in Lusaka. The total number of supervisors were 84. The third phase was the training of enumerators. The enumerators were trained for ten days in the provinces where they worked. A total of 420 enumerators were trained. The data entry operators and data entry supervisors also attended the enumerators training to familiarize them with the questionnaire. The enumerators training covered:
- Map reading (identification of SEA boundaries).
- Listing procedures.
- Enumeration procedures.
- Translation of questionnaire into major local languages spoken in that province.
- Supervisors manual.
- Field practice.
Central Statistical Office
Government of Republic of Zambia
The survey used two types of questionnaires to collect data from the field. The listing form was used to list all households in the sample enumeration areas, and the main questionnaire was used to obtain information on the household and each member of the household.The questionnaires were designed by the LCMU staff taking into account the various user needs and also comparability with the previous surveys.
The main questionnaire has sections with the following topics:
- Section 0 Geographic identification/localization of household
- Section 1 Household roster & migration
- Section 2 Demography
- Section 3 Health
- Section 4 Education
- Section 5 Economic Activities
- Section 6 Household income & individual incomes
- Section 7 Anthropometry & Child Nutrition
- Section 8 Household Amenities and Housing Conditions
- Section 9 Household Access to Facilities
- Section 10 Household Ownership of Assets
- Section 11 Household Self Assessed Poverty & Coping Strategies
- Section 12 Household Expenses
- Section 13 Developmental Issues
- Section 14 Household Food Production
- Section 15 Deaths in Households
Computer data processing began with the training of the data entry operators. Their training took one week and was done jointly by LCMU staff and data entry supervisors. A total of 30 data entry operators were trained. The data entry was done in provincial centers using the IMPS (Integrated Microcomputer Processing System) Software - version 3.2. This software was developed by the United States Census Bureau. It has three components; CENTRY - for data entry and verification, CONCOR - for range, skip and consistency checks in the data, and CENTS - for tabulation. Cents was not used. Data entry lasted for two months.
The SAS (Statistical Analysis System) for windows (Release 6.12) software was used for more sophisticated cleaning of the data, analysis and for producing all statistical tables. This software was also developed in the USA. The software, EPI - INFO was used to produce the Anthropometry (nutrition) tables. The EPI - INFO software was developed by the Centre for Diseases Control in the USA. The report was typed using the Microsoft WORD (97) software.
Director-Central Statistical Office
Ministry of Finance and National Planning
Director - Central Statistical Office
Ministry of Finance and National Planning
Confidentiality of respondents is guaranteed under the provisions of the Census and Statistics Act, CAP 127 of the laws of Zambia.
The Director of the Central Statistical Office has to authorise access to information. Before being granted access to the dataset or any other information produced by CSO, all users have to formally agree to the following:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the Central statistical Office.
2. Not to use any technique in an attempt to learn the identity of any person, establishment or sampling unit not identified on public use data files
3. To hold in the strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion or analysis. Such inadvertent identification revealed in the user's analysis will be immediately brought to the attention of the Central Statistical office.
4. The data will be used for statistical and scientific research purposes only.
5. The data and other materials will not be redistributed or sold to other individuals, institutions, or organization without the written agreement of the CSO.
Central Statistical Office, Priority Survey II 1993 (PSII 1993),Version 1.1 of the public use dataset (September 2009),provided by the Central Statistical office.
Disclaimer and copyrights
All CSO products are protected by copyright. Users may apply the information as they wish, provided that they acknowledge CSO as the source of the basic data whenever they process, apply, utilize, publish or distribute the data, and also that they specify that the relevant application and analysis (where applicable) result from their own processing of the data .CSO and the relevant funding agency bear no responsibility for use of the data for interpretations or inferences based upon such uses.