{"type":"survey","study_desc":{"title_statement":{"idno":"NAM_2000_DHS_v01_M","title":"Demographic and Health Survey 2000","alt_title":"DHS 2000"},"authoring_entity":[{"name":"Ministry of Health and Social Services (MOHSS)","affiliation":""}],"production_statement":{"producers":[{"name":"Central Bureau of Statistics of the National Planning Commission","affiliation":"","role":"Collaboration"},{"name":"ORC Macro","affiliation":"","role":"Technical assistance"}],"funding_agencies":[{"name":"Ministry of Health - Namibia","abbreviation":"","role":"Funding"},{"name":"Health and Social Sector Support Programme","abbreviation":"HSSSP","role":"Funding"},{"name":"National Social Marketing Programme","abbreviation":"NaSoMa","role":"Funding"},{"name":"United Nations Children's Fund","abbreviation":"UNICEF","role":"Funding"},{"name":"United Nations Population Fund","abbreviation":"UNFPA","role":"Funding"},{"name":"French Cooperation","abbreviation":"","role":"Funding"},{"name":"European Union","abbreviation":"EU","role":"Funding"},{"name":"Deutsche Gesellschaft f\u00fcr Internationale Zusammenarbeit","abbreviation":"GTZ","role":"Funding"},{"name":"World Health Organization","abbreviation":"WHO","role":"Funding"},{"name":"Spanish Agency for International Development Cooperation","abbreviation":"AECID","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"General Inquiries","affiliation":"","email":"info@measuredhs.com","uri":"www.measuredhs.com"},{"name":"Data and Data Related Resources","affiliation":"","email":"archive@measuredhs.com","uri":"www.measuredhs.com"},{"name":"Ministry of Health and Social Services (MoHSS)","affiliation":"","email":"doccentre@mhss.gov.na","uri":"http:\/\/www.healthnet.org.na\/"}]},"series_statement":{"series_name":"Demographic and Health Survey (standard) - DHS IV","series_info":"The Namibia Demographic and Health Survey 2000 is the second survey of its kind to be conducted in Namibia after the first one in 1992."},"study_info":{"abstract":"The 2000 Namibia Demographic and Health Survey (NDHS) was implemented to assess the progress made in the health sector since the 1992 NDHS. It therefore focused on measuring achievements related to the same indicators as in 1992, but also included new aspects, e.g. HIV\/AIDS. Furthermore, the 2000 NDHS was designed to obtain reliable data for all 13 administrative regions, which had not been established at the time of the 1992 NDHS. In addition, data for the four MOHSS Regional Directorates are included, which provide comparison to the 1992 NDHS results at the sub-national level. \n\nA nationally representative sample of 6,755 women age 15-49 and a sub-sample of about 2,954 men age 15-59 were interviewed in the 2000 NDHS. Twenty mobile teams conducted the interviews from late September to mid-December 2000. \n\nThe primary objective of the 2000 NDHS was to provide up-to-date information on fertility and mortality, family planning, fertility preferences, maternal and child health, and knowledge and behaviour regarding HIV\/AIDS. The 2000 NDHS was patterned after the 1992 NDHS so as to maximise the ability to measure trends on similar indicators between 1992 and 2000. The ultimate intent is to use this information to evaluate existing programmes and design new strategies in order to ensure delivery of health and social welfare services to the population in a cost effective and efficient manner.","coll_dates":[{"start":"2000-09","end":"2000-12","cycle":""}],"nation":[{"name":"Namibia","abbreviation":"NAM"}],"geog_coverage":"The 2000 NDHS sample was designed to produce reliable estimates of most of the major survey variables for the country as whole; for urban and rural areas separately; and for each of the 13 regions.","analysis_unit":"- Household\n- Women age 15-49\n- Men age 15-59\n- Children under five","universe":"The population covered by the 2000 NDHS is defined as the universe of all women age 15\u00ad-49 in Namibia and all men age 15-54 living in the household.","data_kind":"Sample survey data","notes":"The Namibia Demographic and Health Survey 2000 covers the following topics:\n- Anthropometry\n- Birth Registration\n- Breastfeeding\n- Fertility preferences \n- Knowledge and use of contraception \n- Health services\n- Marriage \n- Maternal and child Mortality\n- Reproductive behaviour\n- Reproductive Calendar\n- Vaccination\n- Woman's work","study_scope":"The Namibia Demographic and Health Survey 2000 covers the following topics:\n- Anthropometry\n- Birth Registration\n- Breastfeeding\n- Fertility preferences \n- Knowledge and use of contraception \n- Health services\n- Marriage \n- Maternal and child Mortality\n- Reproductive behaviour\n- Reproductive Calendar\n- Vaccination\n- Woman's work"},"method":{"data_collection":{"data_collectors":[{"name":"Ministry of Health and Social Services (MOHSS)","abbreviation":"","affiliation":""},{"name":"Central Bureau of Statistics of the National Planning Commission","abbreviation":"","affiliation":""}],"sampling_procedure":"The 2000 NDHS sample was designed to produce reliable estimates of most of the major survey variables for the country as whole; for urban and rural areas separately; and for each of the 13 regions. The design called for a nationally representative probability sample of 6,500 women age 15-49 and a subsample of about 3,000 men age 15-59.  \n\nThe 2000 NDHS sample was largely based on the Central Bureau of Statistics' master sample, drawn from the list of enumeration areas (EAs) created for the 1991 census. In 1997, new EAs were demarcated in Walvis Bay, which was not part of Namibia at the time of the 1991 census. The new EAs were incorporated into the 1991 census frame and the number of primary sampling units (PSUs) in the master sample was increased. A PSU corresponds to an entire EA or a group of EAs. \n\nDue to considerable rural-urban migration, extensive peripheral development and intensive development of previously rural areas has taken place since 1991, particularly in Windhoek. At the time of the 2000 NDHS sample design, new EAs were being demarcated for the upcoming population census. A list of the new EAs in the urban areas of Caprivi, Hardap, Kunene, Omaheke, Oshana, and Otjozondjupa Regions was made available for the sample selection. Finally, in Khomas Region, a quick count of dwellings both in the old EAs within Windhoek and in the newly demarcated EAs in the informal settlement zones on the outskirts of Windhoek was implemented in order to get an up-to-date measure of size for the capital city. \n\nThe sampling frame for the 2000 NDHS was obtained by supplementing the master sample with the list of the new EAs in urban areas in selected regions and the updated EAs in Khomas Region. It should also be noted that the urban-rural classification of EAs was changed in the master sample so as to reflect the recent proclamation of municipalities, towns and villages. Some of the EAs were also shifted from one region to another following changes in regional boundaries. \n\nThe 2000 NDHS sample was selected in two stages. In the first stage, 260 PSUs (106 urban and 154 rural) were selected with probability proportional to the number of households within the PSU. Each selected PSU was divided into segments, one of which was retained in the sample. All households residing in the selected segment were included in the sample and all women age 15-49 listed in these households were eligible for individual interview. In one-half of the households, all men age 15-59 were also eligible.","coll_mode":"Face-to-face","research_instrument":"The 2000 NDHS involved three questionnaires: a) a household questionnaire, b) a questionnaire for individual women 15-49, and c) a questionnaire for individual men 15-59. These instruments were based on the model questionnaires developed for the international DHS program, as well as on the questionnaires used in the 1992 NDHS.  \n\nThe questionnaires were developed in English and translated into six local languages-Afrikaans, Damara\/Nama, Herero, Kwangali, Lozi, and Oshiwambo. People other than the initial translators did back translations into English with the goal of verifying the accuracy of the translations.  \n\na) The household questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including his\/her age, sex, education, and relationship to the head of the household. The main purpose of the household questionnaire was to identify women and men eligible for individual interview and children under five who were to be weighed and measured. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, ownership of various consumer goods, use of iodised salt, and household expenditures on health care. \n\nb) The Woman's Questionnaire was used to collect information from all women aged 15-49 and covered the following topics: \n- Background characteristics (age, education, religion, etc.); \n- Reproductive history; \n- Knowledge and use of contraceptive methods; \n- Antenatal, delivery, and postnatal care (including tetanus toxoid testing); \n- Breastfeeding and weaning practices; \n- Child health and immunisation; \n- Marriage and recent sexual activity; \n- Fertility preferences; \n- Knowledge of HIV\/AIDS (condom use, number of partners, etc.); \n- Maternal mortality; \n- Husband's background and respondent's work. \n\nc) In every second household, in addition to the women, all men age 15-59 were eligible to be interviewed with the Man's Questionnaire, which covered: \n- Background characteristics (age, education, religion, etc.); \n- Knowledge and use of contraceptive methods; \n- Marriage and recent sexual activity; \n- Fertility preferences; \n- Knowledge of HIV\/AIDS (condom use, number of partners, etc.); \n- Respondent's work. \n\nThe survey instruments were pretested in three areas (one urban and two rural) outside the segments drawn in the sample. About 200 women and 200 men were interviewed in the pretest, the results of which were used to modify the survey instruments as necessary.","coll_situation":"Training for the main survey took place from 21st August to 20th September 2000 at the University of Namibia. Fieldwork was organised in 20 teams, each composed of a supervisor (team leader), a field editor (nurse), three female interviewers, one male interviewer, and a driver. Candidates for field positions were recruited on the basis of maturity, friendliness, education, language ability, and willingness to work away from home for up to four months.  \n\nThe training program included a detailed description of the content of the questionnaires, how to fill the questionnaires, interviewing techniques, contraceptive methods, and how to use the anthropometric measuring equipment and the salt-testing kits. Due to the inclusion of tetanus toxoid blood testing, field editors received training on how to collect and store blood spots from recent mothers. Supervisors received training on mapping, segmentation, household listing and use of global positioning system units. Fieldwork started on 22 September and was completed on 15 December 2000. Field teams were supervised frequently by senior staff from headquarters.","cleaning_operations":"After field editing and correction in the field, all completed questionnaires were sent to the Multisdisciplinary Research Centre at the University of Namibia in Windhoek for logging in and supplementary editing prior to data entry. The processing operation consisted of office editing, coding of open-ended questions, initial data entry and subsequent re-entry (verification) of all questionnaires to ensure correct capturing of data, and editing of inconsistencies found by the computer programs. ORC Macro staff provided assistance in developing the programs for data entry, training of data processing personnel and editing in the Integrated System for Survey Analysis (ISSA) computer package. A team of two supervisors and 16 data entry operators, working in two six-hour shifts, completed data processing activities in February 2001."},"analysis_info":{"response_rate":"In all, 6,849 households were selected for the 2000 NDHS, of which 6,594 were reported occupied at the time of the interview. The primary reasons for the difference were households that were away for an extended period of time and dwellings that were vacant. \n\nInterviews were completed in 6,392 households or 97 percent of the occupied households. In the interviewed households, 7,308 women were identified as eligible for the individual interview, of which 6,755 (92 percent) were successfully interviewed. Of the 3,551 men identified as eligible in every second household, 2,954 (83 percent) were interviewed. The principal reason for non-responses among eligible women and men was the failure to find them at home despite repeated visits to the household.","sampling_error_estimates":"Sampling errors, on the other hand, can be evaluated statistically.  The sample of respondents selected in the 2000 NDHS is only one of many samples that could have been selected from the same population, using the same design and expected size.  Each of these samples would yield results that differ somewhat from the results of the actual sample selected.  Sampling errors are a measure of the variability between all possible samples.  Although the degree of variability is not known exactly, it can be estimated from the survey results. \n\nA sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance.  The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall.  For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design. \n\nIf the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors.  However, the 2000 NDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae.  The computer software used to calculate sampling errors for the 2000 NDHS is the ISSA Sampling Error Module. This module used the Taylor linearisation method of variance estimation for survey estimates that are means or proportions.  The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. \n\nThe Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one clusters in the calculation of the estimates.  Pseudo-independent replications are thus created. In the 2000 NDHS, there were 260 non-empty clusters. Hence, 260 replications were created. \n\nIn addition to the standard error, ISSA computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used.  A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design.  ISSA also computes the relative error and confidence limits for the estimates. \n\nSampling errors for the NDHS are calculated for selected variables considered to be of primary interest. The results are presented in an appendix of the Final Report for the country as a whole, urban and rural area separately, and for each region and group of regions.  For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1 of the Final Report. Tables B.2 to B.21 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE\/R), and the 95 percent confidence limits (R\u00b12SE), for each variable. The DEFT is considered undefined when the standard error considering simple random sample is zero (when the estimate is close to 0 or 1). In the case of the total fertility rate, the number of unweighted cases is not relevant, as there is no known unweighted value for woman-years of exposure to child-bearing.  Sampling errors for fertility and childhood mortality rates are presented only for the whole country, urban and rural areas, and for groups of regions (Northwest, Northeast, Central and South). \n\nThe confidence interval (e.g., as calculated for Children ever born to women aged 15-49) can be interpreted as follows: the overall average from the national sample is 2.148 and its standard error is 0.037. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 2.148 \u00b1 2 \u00d7 0.037.  There is a high probability (95 percent) that the true average number of children ever born to all women aged 15 to 49 is between 2.074 and 2.221. \n\nSampling errors are analysed for the national woman sample and for two separate groups of estimates: (1) means and proportions, and (2) complex demographic rates.  The relative standard errors (SE\/R) for the means and proportions range between 0.4 percent and 76.5 percent with an average of 8.6 percent; the highest relative standard errors are for estimates of very low values (e.g., Women currently using withdrawal). If estimates of very low values (less than 10 percent) were removed, then the average would drop to 3.2 percent. So in general, the relative standard errors for most estimates for the country as a whole is small, except for estimates of very small proportions.   The relative standard error for the total fertility rate is small, 3.5 percent. However, for the mortality rates, the average relative standard error is much higher, 12.7 percent. \n\nThere are differentials in the relative standard error for the estimates of sub-populations. For example, for the variable Currently married, the relative standard errors as a percent of the estimated mean for the whole country, and for Ohangwena Region and the Northwestern Directorate are 2.9 percent, 15.1 percent, and 6 percent, respectively. \n\nFor the total sample, the value of the design effect (DEFT), averaged over all variables, is 1.57 which means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.57 over that in an equivalent simple random sample.","data_appraisal":"Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors.  Although numerous efforts were made during the implementation of the 2000 Namibia Demographic and Health Survey to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically."}},"data_access":{"dataset_use":{"contact":[{"name":"MEASURE DHS","affiliation":"ICF International","email":"archive@measuredhs.com","uri":"www.measuredhs.com"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such 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