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Datazone level Namibian Index of Multiple Deprivation 2001

Empowered lives.

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This report is the result of collaborative work between the Government of the Republic of Namibia (GRN), the United Nations Development programme (UNDp) and the centre for the analysis of South african Social policy at the Oxford Institute of Social policy at the University of Oxford.

n November 2009, the Khomas Regional 2011 Census becomes available and is subsequently Council requested UNDP to assist in designing used for carrying out a similar analysis. an objective criterion or set of criteria, devoid of political and other considerations, which the This report presents, using tables, charts and digital Council could use in allocating development maps, a profile of multiple deprivation in Hardap resources. Subsequent discussions led to an region at data zone level, which is a relatively new agreement that other stakeholders, especially the statistical geography developed for purposes of Central Bureau of Statistics needed to be involved measuring deprivation at a small area level. This and that the criterion or set of criteria needed to technique of profiling deprivation at datazone level, Igo beyond income poverty considerations. It was each with approximately 1000 people only, enables also agreed that rather than focus on Khomas the identification and targeting of pockets of region alone, the criterion or set of criteria needed deprivation within Hardap region for possible use to be applicable to, or cover the entire country. in panning for and implementation of development Specifically, it was agreed that a composite index of interventions. The aim of the exercise was to multiple deprivation, the Namibia Index of Multiple produce a profile of relative deprivation across Deprivation (NIMD), be constructed at both Hardap region in order for the most deprived areas national and regional levels. Since the scope and to be identified and clearly delineated. In this way, depth of analysis needed for the development of it would be possible for regional and constituency the NIMD required very detailed and reliable data level policy and decision makers, as well and information, it was agreed that the 2001 census development practitioners, to consider a particular data, though ‘outdated’, be used as the source of domain of deprivation, or to refer to the overarching inter alia information for preparing the NIMD. Accordingly, NIMD for each constituency or datazone, in the NIMD being presented in this report reflects the , allocating and applying development situation in Hardap region at the 2001 time-point resources and interventions. The NIMD can also only. UNDP and the GRN recognize that the report be used as a platform for effecting a paradigm shift does not speak to possible changes in relative in development planning towards increased focus deprivation that may have occurred in the Hardap on and targeting of deprived areas and sectors; region since 2001. Nevertheless the 2001 NIMD as well as interrogating the causes of inequality could serve as a benchmark against which change in access to basic services within the region. The over the last decade could be measured when the NIMD at datazone level should be viewed as adding

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 1 to the existing body of information and knowledge, the University of Oxford, under the leadership and including local knowledge systems, about poverty guidance a national steering committee chaired and deprivation in Hardap region and the large by Mr Sylvester Mbangu, Director of the Central family of existing planning and resource allocation Bureau of Statistics, with the participation of tools and methodologies already in use at the representatives of the thirteen Regional Councils. regional and constituency levels. In addition to providing the funds for carrying out the project, UNDP provided overall oversight This project was undertaken by Professor Michael and technical backstopping to the project through Noble, Dr Gemma Wright, Ms Joanna Davies, Dr Ojijo Odhiambo, Senior Economist and Johannes Helen Barnes and Dr Phakama Ntshongwana of Ashipala, National Economist. David Avenell is the Centre for the Analysis of South African Social thanked for his assistance with producing the Policy at the Oxford Institute of Social Policy at datazones.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 2 Table Of cONTeNTS

Section 1: Introduction 5

1.1 Background 5 1.2 Defining poverty and deprivation 6 1.3 The concept of multiple deprivation 6 Section 2: Datazones 7

Section 3: Methodology 8

3.1 An introduction to the domains and indicators 8 Domains 8 Indicators 8 3.2 Material Deprivation Domain 9 Purpose of the domain 9 Background 9 Indicators 10 Combining the indicators 10 3.3 Employment Deprivation Domain 10 Purpose of the domain 10 Background 10 Indicator 11 Combining the indicators 11 3.4 Health Deprivation Domain 11 Purpose of the domain 11 Background 11 Indicator 12 3.5 Education Deprivation Domain 12 Purpose of the domain 12 Background 12 Indicators 12 Combining the indicators 13 3.6 Living Environment Deprivation Domain 13 Purpose of the domain 13 Background 13 Indicators 14 Combining the indicators 14

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 3 3.7 Constructing the domain indices 15 3.8 Standardising and transforming the domain indices 15 3.9 Weights for the domain indices when combining into an overall Index of Multiple Deprivation 16 Section 4: Datazone level Namibian Index of Multiple Deprivation 2001: Kavango Region 17

4.1 Multiple Deprivation 17 4.2 Domains of deprivation 23 Section 5: conclusion and Some policy Recommendations 42

annex 1: Indicators included in the NIMD 2001 44

Material Deprivation Domain 44 Employment Deprivation Domain 44 Health Deprivation Domain 44 Education Deprivation Domain 44 Living Environment Deprivation Domain 44 appendix 2: Domain and overall NIMD scores and ranks 45

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 4 SecTION 1: INTRODUcTION

This report presents the datazone level Namibian Index of Multiple Deprivation 2001 (NIMD 2001) for the Hardap region. The NIMD is a composite index reflecting five dimensions of deprivation: income and material deprivation; employment deprivation; education deprivation; health deprivation; and living environment deprivation.

he NIMD and the component domains of members of UNDP. The objective of this phase of deprivation were produced at datazone the project was to construct measures of multiple level using data from the 2001 Population deprivation at constituency level in order to provide Census. Datazones are small areas containing a more detailed analysis of deprivation which approximately the same number of people (average would enable Khomas Regional Council, and other 1,000). The datazone level NIMD therefore provides regional councils across Namibia, to rank their areas a fine-grained picture of deprivation and enables in order of deprivation, and also to set them in the pockets of deprivation to be identified in Hardap context of all other areas in Namibia. The datazone region. level index presented in this report draws from the T previous constituency index, and covers, in detail, The report is structured as follows: The background the entire country including Hardap region. In information and the conceptual framework which underpins the model of multiple deprivation is described in this introductory section. In Section 2 the rationale for and process of constructing The NIMD and the datazones are described. Section 3 introduces the domains and indicators that were included component domains of in the NIMD and summarises the methodological deprivation were produced approach that was used in constructing the NIMD. In Section 4 datazone level results for Hardap at datazone level using data region are presented, while conclusions and some general policy recommendations are presented in from the 2001 Population Section 5. 1.1 background Census. As will be elaborated in Section 2, datazones

Initially a NIMD was created at constituency level are small areas containing for the Khomas Region, but applicable to other approximately the same regions of the country as well, using data from the 2001 Population Census at constituency level after number of people a two-day consultative process on the domains and indicators with members of the Central Bureau of (average 1,000) Statistics, civil servants from the Council and staff

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 5 constructing the NIMD at datazone level however, multiple deprivation is underpinned by the idea it became necessary to make some small changes that there exists separate dimensions of deprivation to some of the domains and indicators initially which can be recognised and measured, and used in the constituency level study. These changes are experienced by individuals living in an area. are explained in detail in Section 3 of this report. Multiple deprivation is therefore conceptualised as As such, the constituency level index has also been a weighted combination of distinct dimensions or revised to give a comparable measure. The initial domains of deprivation. An area level score for each results of the work at the datazone level were domain is produced and these are then combined presented to, and validated by, representatives of to form an overall Index of Multiple Deprivation. all the 13 Regional Councils at a workshop held in relative Ondangwa in November 2011. Although the area itself is not deprived, it can 1.2 Defining poverty and deprivation nonetheless be characterised as deprived to other areas, in a particular dimension of deprivation, Townsend (1979) sets out the case for defining on the basis of the proportion of people in the area ‘Individuals, families and groups can be said to be in poverty in terms of relative deprivation as follows: experiencing the type of deprivation in question. poverty if they lack the resources to obtain the types In other words, the experiences of the people in an of diet, participate in the activities and have the living area give the area its deprivation characteristics. It conditions and amenities which are customary or at is important to emphasize that the area itself is not least widely encouraged or approved in the societies deprived, though the presence of a concentration to which they belong’ of people experiencing deprivation in an area may (Townsend, 1979, p31). give rise to a compounding deprivation effect, but this is still measured by reference to those Though ‘poverty’ and ‘deprivation’ have often individuals. Having attributed the aggregate of been used interchangeably, many have argued individual experience of deprivation to the area that a clear distinction should be made between however, it is possible to say that an area is deprived them (see for example the discussion in Nolan and in that particular dimension. And having measured Whelan, 1996). Based on this line of thought, it can specific dimensions of deprivation, these can be be argued that the condition of poverty means not understood as domains of multiple deprivation. In having enough financial resources to meet a need, his article ‘Deprivation’ Townsend also lays down whereas deprivation refers to an unmet need, the foundation for articulating multiple deprivation which is caused by a lack of resources of all kinds, as an aggregation of several types of deprivation not just financial. (Townsend, 1987). Townsend’s formulation of 1.3 The concept of multiple deprivation multiple deprivation is the starting point for the model of small area deprivation which is presented The starting point for the NIMD is a conceptual in this report. model of multiple deprivation. The model of

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 6 SecTION 2: DaTazONeS

Datazones are a new statistical geography for Namibia created especially for this version of the NIMD 2001. This section provides a non-technical overview of the process of creating the datazones and summarises their characteristics.

Internal homogeneity

The methodology adopted is based on a similar : It is important that process undertaken in South Africa (Avenell et al., datazones comprise EAs of similar characteristics. 2009) which in turn was adapted from techniques This helps to ensure that the datazone geography developed in the United Kingdom (see, for example, created is ‘meaningful’ in that, for example, in Martin et al., 2001). Datazones were built up urban areas housing of a similar type are grouped from Census Enumeration Areas (EAs) to create a together within one datazone and that those living standard uniform geography across Hardap region in EAs within a single datazone share similar socio- based on the existing EA geography which nest economic characteristics. In order to achieve this within the six constituency boundaries. Though all EAs were analysed using a technique known a datazone may be created from a single EA, it is as cluster analysis. This technique groups EAs usually created by merging one or more contiguous across the country and the region into a small EAs which share common characteristics in number of ‘families’ based on a variety of relevant accordance with a set of pre-defined rules. The characteristics. The datazones were checked actual creation of datazones was undertaken using and validated by obtaining aerial photography a variety of geographical programming techniques underlays for the mapping software and visually (see Avenell et al., 2009). A set of rules governing inspecting boundary positions. the merging process was drawn up to ensure that the datazones had, as close as was possible, the following characteristics: Population size Though a datazone : Datazones are designed to have may be created from a a similar resident population size - this allows comparability across the region. The target single EA, it is usually population size was 1,000 with a minimum of 500 and maximum of 1,500. A total 75 datazones were created by merging created for the Hardap region. Population density one or more contiguous : Datazones should comprise EAs of similar population density. This is important EAs which to ensure that urban areas become distinct from share common rural areas. The datazone algorithm incorporated thresholds to ensure that, wherever possible, urban characteristics in areas became tightly bounded. accordance with a set of pre-defined rules. Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 7 SecTION 3: MeTHODOlOGy

3.1 an introduction to the domains

and indicators was unemployed, had no qualifications and had no access to basic material goods they would be Domains captured in the Employment Deprivation, Education Deprivation and Material Deprivation domains. The NIMD was produced using the 2001 Namibian The indicators were chosen following an extensive Population Census which was supplied by the consultation process with representatives of the Central Bureau of Statistics, Khomas Regional Namibian Central Bureau of Statistics for the 2 purposes of this project. Whilst the intention Council and UNDP . should always to be concept-led rather than ‘data- driven’, the project team was restricted to selecting indicators from the range of questions included within the 2001 Census. The NIMD was produced The NIMD was at datazone level (and also at constituency level on a comparable basis). There are 75 datazones and produced using the six constituencies in Hardap region. The NIMD contains five domains of deprivation: 2001 Namibian • 1 Population Census • Material Deprivation • Employment Deprivation which was • Health Deprivation supplied by the • Education Deprivation Living Environment Deprivation Namibian Central

Each domain is presented as a separate domain Bureau of Statistics index reflecting a particular aspect of deprivation. for the purposes Each domain seeks to measure only one dimension of deprivation, avoiding overlaps between the of this project domains and providing a direct measure of the Indicators deprivation in question. Individuals can however, experience more than one type of deprivation at any given time and it is therefore conceivable Each domain index contains a number of indicators. that the same person can be captured in more There are 11 indicators in total in the NIMD. The than one domain. So, for example, if someone aim for each domain was to include a parsimonious

1 2 This refers to material goods, that is, assets or possessions. During the consultation process a number of other domains were discussed. These included: access to recreation facilities, level of participation in community activities, crime, food security, provision of emergency services, and availability of affordable transport. Unfortunately data relating to these issues were not available within the Census. These issues could be incorporated into further iterations of the NIMD if appropriate administrative or geographical data becomes available. Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 8 (i.e. economical in number) collection of indicators In the following sub-sections the domains and that comprehensively captured the deprivation for indicators which make up the NIMD 2001 are each domain, but within the constraints of the data described. 3.2 Material Deprivation Domain available from the 2001 Census. When identifying indicators for the domains, it was important to purpose of the domain ensure that they are direct measures of the domain of deprivation in question and specific to that domain. This domain measures the proportion of the population experiencing material deprivation In the construction of that index the indicators were in an area by reference to the percentage of the discussed at length during the consultation process population who are deprived of access to basic and every effort was made to ensure that they material possessions. background were appropriate for the Namibian context. The domains need to allow different geographical areas to be distinguished from one another; therefore it In other indices that have followed this model would be unhelpful to identify a deprivation which (e.g. UK indices), an Income Deprivation Domain is experienced by most people in most areas as this was created. However, there is an argument that would not enable the areas to be ranked relative to such a domain is inappropriate within an Index of each other in terms of deprivation. Multiple Deprivation, because - as explained above - deprivation can be regarded as the outcome of lack of income rather than the lack of income itself. With the exception To follow Townsend, within a multiple deprivation measure, only the deprivations resulting from a of changes to three low income would be included so low income itself would not be a component, but lack of material indicators in the newly possessions would be included. In any event, the constituted Living 2001 Census did not have an income question and so an income poverty indicator, if included, would Environment need to be modelled from a different data source Deprivation Domain, such as the Namibian Household Income and Expenditure Survey. Such modelling work is being the indicators are undertaken separately for the Central Bureau of Statistics (now Namibia Statistics Agency) by Lux the same as those used Development and will provide a complementary in the previous small area measure of income poverty. For these reasons, a material deprivation domain was constituency level index.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 9 •

Number of people living in a household with In any event, the no access to a telephone/cell phone. combining the indicators 2001 Census did not have an income question A simple proportion of people living in households experiencing either one or both of the deprivations and so an income poverty was calculated (i.e. the number of people living in indicator, if included, a household with no access to a television/radio and/or with no access to a telephone/cell phone would need to be modelled divided by the total population). 3.3 employment Deprivation from a different data source Domain such as the Namibian purpose of the domain Household Income and Expenditure Survey This domain measures employment deprivation conceptualised as involuntary exclusion of the produced. A lack of access to basic material goods working age population from the world of work can be understood as a proxy for low income. The by reference to the percentage of the working age 2001 Census included questions about access to population who are unemployed. background material goods (e.g. television, radio, newspaper, telephone and computer) which are internationally accepted and widely used as measures of variations The 2001 Census recorded employment status in in living standards. line with the International Labour Organisation (ILO) ‘labour force framework’ and the ‘priority ‘regardless of the amount of time Of the possible material goods that could be rules’ which give precedence to employment over devoted to it, which in extreme cases may be only one included as indicators, access to a television/radio all other activities hour’ and telephone/cell phone were selected as they represent important modes of communication (Hussmanns, 2007, p6). Therefore a person and a means of accessing information crucial to was considered to be employed if during the seven one’s life and livelihood. The quality of the services days prior to the Census night they worked for provided however, were not be taken into account. at least one hour for pay, profit or family gain. It Indicators follows that unemployment was defined as a • situation of a total lack of work. The definition of th Number of people living in a household with unemployment adopted by the 13 International no access to a television or a radio; or Conference of Labour Statistics (ICLS) stipulates

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 10 combining the indicators three criteria which must be simultaneously met for a person to be considered unemployed. According The domain was calculated as those identified as to this official definition, the unemployed are those unemployed and aged 15 to 59 inclusive divided by persons within the economically active population the number of people who are economically active (aged 15-65 inclusive) who during the reference in that age group. period (for the 2001 Census this is the seven days 3.4 Health Deprivation Domain prior to Census night) were: 1. Without work, i.e. in a situation of total lack purpose of the domain of work; and 2. Currently available for work, i.e. not a student This domain identifies areas with relatively high or homemaker or otherwise unavailable for rates of people who die prematurely. The domain work; and measures premature mortality but not aspects of forthcoming 3. Seeking work, i.e. taking steps to seek behaviour or environment that may be predictive employment or self-employment. of health deprivation. background

Using the 2001 Census however, it was not possible to measure whether unemployed people were Although the consultation process raised the available for work and seeking work. Though importance of measuring people’s health status; other indices have also included people of and access to health facilities and healthcare, working age who cannot work because of illness these issues could not be measured using the 2001 or disability, as they are involuntarily excluded Census data. It was therefore not possible to include from the world of work and internationally are any measures of morbidity or access to health regarded as the ‘hidden unemployed’ (Beatty et services. Instead a form of standardised mortality al., 2000), the consultation group wanted to limit ratio known as Years of Potential Life Lost (YPLL) this domain to the economically active population was used. An internationally recognised measure and therefore disabled or long-term sick people of poor health, the YPLL measure is the level of were not included. The age band was modified to unexpected mortality weighted by the age of the 15-59 inclusive to reflect a concept of working age individual who has died (for details about how this relevant to Namibia. indicator was constructed see Blane and Drever, Indicator 1998). An area with a relatively high death rate in a • ceteris paribus young age group (including areas with high levels

Number of people aged 15-59 inclusive who of infant mortality) will therefore , are unemployed. have a higher overall YPLL score than an area with a similarly relatively high death rate for an older age group.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 11 3.5 education Deprivation Domain

The YPLL measure is purpose of the domain

related to life expectancy This domain measures deprivation in educational in an area. Areas with low attainment for people aged 15 to 59 inclusive. background life expectancy will have high YPLL scores Elsewhere in the Southern Africa Development Community (SADC) region it has been shown that the level of educational attainment in the The YPLL indicator is a directly age and gender working age adult population is closely linked standardised measure of premature death (i.e. 3 to an individual’s employment status and future death under the age of 75) . The YPLL measure opportunities for those individuals and their is related to life expectancy in an area. Areas dependants (Bhorat et al., 2004). with low life expectancy will have high YPLL scores. Equally high levels of infant mortality and The 2001 Census includes a record of the level perinatal mortality as well as high levels of serious of education completed and a record of illiteracy. illness such as HIV/AIDS and tuberculosis will all These two questions provide the best available contribute to reduced life expectancy in an area measures of educational attainment and make up and therefore high YPLL scores. Thus, although the indicators for this domain. The consultation the YPLL is a mortality measure, it does, implicitly, process additionally raised the importance of reflect the extent of serious ill-health in an area. affordable education and availability of tertiary And although it would have been possible to use education opportunities, but again, these could not infant mortality, under-five mortality, and life be adequately captured using the 2001 Census. expectancy as indicators, YPLL in effect combines Indicators all these issues into a single indicator and is • therefore a broader and more useful overview of Number of 15-59 year olds inclusive with no health deprivation in an area. Indicator schooling completed at secondary level or • • above; or Number of 15-59 year olds inclusive who are Years of potential life lost illiterate.

3. Because the direct method of standardisation makes use of individual age/gender death rates it is often associated with small numbers. An empirical Bayes or ‘shrinkage’ technique is therefore used to smooth the individual age/gender death rates in order to reduce the impact of small number problems on the YPLL.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 12 combining the indicators

and therefore provides a more valid measure of A simple proportion of the working age population deprivation in terms of access to energy for lighting (aged 15 to 59 years old inclusive) who had not (Bhorat et al., 2004). This was the measure used in completed schooling at secondary level or who the previous constituency level index. However, at are illiterate was calculated (i.e. the number of datazone level, all individuals in a high proportion people with no schooling completed at secondary of datazones were found to lack electricity for level or above or who are illiterate divided by the lighting. These datazones would all be given population aged 15 to 59 inclusive). the same overall score for this domain, and so it 3.6 living environment Deprivation would not be possible to discriminate between Domain datazones in terms of their level of deprivation. For this reason the indicator was altered slightly purpose of the domain to include paraffin alongside electricity (and solar power) as the measure of access to energy for This domain measures both inadequacy in housing lighting. The inclusion of paraffin however, does conditions and a lack of basic services to the not imply any judgement about its suitability for home. lighting purposes, but is rather a means of enabling background datazones to be properly ranked on this domain.

The 2001 Census questionnaire provides indicators Access to clean drinking water and sanitation on households’ access to basic amenities. These facilities is essential for the good health of the aspects of the immediate environment in which population and thus an important indicator to people live impact on the quality of their life and provide good measures of deprivation in terms of access to services. Access to clean

Measuring access to electricity as a basic amenity is drinking water and a useful indicator of living environment deprivation. sanitation facilities Three Census indicators were considered: main source of energy for cooking, lighting and heating. is essential for the Although cost, availability and effectiveness are factors in the consumption of all energy supplies, good health of the it has been argued that in certain instances, the population and thus choice of fuel for cooking may be influenced by cultural preference rather than availability alone, an important indicator whereas the use of electricity for lighting would to include in generally be the preferred choice, if available, this domain Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 13 include in this domain. An indicator of no access to kitchens, stoops and verandas. Different versions piped water within the home or within 200 metres of the crowding indicator were considered. It was of the home was included. The threshold of 200 felt that the most appropriate measure of crowding metres was regarded by the consultation group as was to classify three or more people per room as a preferable to a threshold of 400 metres (the MDG deprivation. Setting the capacity cut-off at two or measure). Though in the previous (constituency) more people per room was considered. However, it index people without flush toilets or ventilated pit was felt that this lower capacity would capture too latrines were regarded as deprived, investigation of many non-deprived people, for example relatively this indicator at datazone level revealed that again, well-off couples sharing a one room urban a high proportion of datazones scored 100 percent. apartment. Indicators Therefore, as with the access to energy indicator, an additional criterion was added: long drop pit • latrines were included alongside flush toilets and Number of people living in a household without ventilated pit latrines. Again, the inclusion of long the use of electricity, paraffin or solar power drop pit latrines does not imply adequacy, but • for lighting; or is included simply as a means of discriminating Number of people living in a household without between datazones. access to a flush toilet or pit latrine (ventilated • or long drop); or The quality of housing construction provides an Number of people living in a household without important indicator for the quality of day-to-day piped water/borehole/borehole with covered life and vulnerability to shocks such as adverse tank (but not open tank)/protected well inside weather conditions (Bhorat et al., 2004; Programme their dwelling or yard or within 200 metres; of Action Chapter 2 World Summit for Social • or Development Copenhagen 1995). There was much Number of people living in a household that is discussion during the consultation process about • a shack; or traditional dwellings and their adequacy. Though Number of people living in a household with the 2001 Census contains fairly precise information three or more people per room. combining the indicators about materials used in the construction process, there is no way of identifying whether the resultant buildings were of a high quality or not. It was A simple proportion of people living in households therefore agreed that only shacks could be reliably experiencing one or more of the deprivations was identified as constituting inadequate housing. calculated (i.e. the number of people living in a household without electricity, paraffin or solar The crowding indicator is calculated by dividing power for lighting and/or without adequate toilet the number of people in the household by the facilities and/or without adequate water provision number of rooms excluding bathrooms, toilets, and/or living in a shack and/or in overcrowded conditions divided by the total population). Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 14 3.7 constructing the domain indices

As Censuses can be In all domains apart from the Health Deprivation regarded as a sample Domain, the overall score is a simple proportion of the relevant population, and so can be easily from a super-population, interpreted. As Censuses can be regarded as a it is important to sample from a super-population, it is important to consider and deal with large standard errors. A consider and deal with technique that takes standard errors into account but still enables one to then combine the domains large standard errors. into an overall index of multiple deprivation is A technique that takes called Bayesian shrinkage estimation. Specifically, the scores for datazones can be unreliable when the standard errors into deprived population is small and so the shrinkage account but still enables technique was applied to each of the domains. The ‘shrunk’ estimate is the weighted average of the one to then combine original datazone level estimate and an appropriate larger spatial unit. The weight is based on the the domains into an standard error of the original datazone estimate overall index of multiple and the amount of variation within the constituency. For further details about this technique see Annex deprivation is called 2 of the 2001 NIMD National Report available at Bayesian shrinkage http://www.undp.org.na/publications.aspx and also Noble et al. (2006b). estimation 3.8 Standardising and transforming the domain indices criteria. First it must ensure that each domain has a common distribution; second, it must not be scale dependent (i.e. conflate size with level of

Having obtained a set of domain indices, these deprivation); third, it must have an appropriate needed to be combined into an overall Namibia degree of cancellation built into it; and fourth, it must Index of Multiple Deprivation and in order to facilitate the identification of the most deprived combine domain indices which are each based on datazones. The exponential transformation of the different metrics there needed to be some way to ranks best meets these criteria and was applied standardise the scores before any combination in the NIMD 2001. For further details about this could take place. A form of standardisation and technique see Annex 3 of the 2001 NIMD National transformation is required that meets the following Report available at http://www.undp.org.na/

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 15 publications.aspx and also Noble et al. (2006b). 3.9 Weights for the domain indices A form of standardisation when combining into an overall Index of Multiple Deprivation and transformation is required that meets the following criteria. First it Domains are conceived as independent dimensions of multiple deprivation, each with their own must ensure that each additive impact on multiple deprivation. The strength of this impact, though, may vary between domain has a common domains depending on their relative importance. distribution; second, it must As a starting point, equal weights for the domains were recommended and this was supported by the not be scale dependent (i.e. consultation group. Each domain was therefore conflate size with level of assigned a weight of 1. The NIMD was therefore constructed by adding the standardised and deprivation); third, it must transformed domain indices with equal weights. have an appropriate degree of cancellation built into it; and fourth, it must facilitate the identification of the most deprived datazones. The exponential transformation of the ranks best meets these criteria and was applied in the NIMD 2001. For further details see Annex 3 and Noble et al. (2006b)

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 16 SecTION 4: DaTazONe level NaMIbIaN INDex Of MUlTIple DepRIvaTION 2001: HaRDap ReGION

4.1 Multiple Deprivation

combined together). The lightest shading relates to the least deprived datazones. Maps 2 and 3 In this section a profile of multiple deprivation in are zoom-ins of Map 1, showing the datazones Hardap region, at both constituency and datazone within the Mariental and Rehoboth areas (as these levels, is presented. Using the data from the NIMD are small in physical size and therefore hard to it is possible to compare the 74 datazones and six distinguish on Map 1). These maps provide an constituencies within Hardap region. Map 1 shows easy to interpret picture of the pattern of multiple the datazones in Hardap in relation to the overall deprivation in the Hardap Region. NIMD (i.e. the five separate domains of deprivation

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 17

18 Map 1

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 18

Map 2

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 19 Map 3

Datazone level Namibian Index of Multiple21 Deprivation 2001 - Hardap Region 20 Table 1 below shows some of the data underlying given a rank of 1 among the datazones in Hardap. these maps. The NIMD 2001 score, national rank If ranked alongside all datazones in Namibia, (where 1=most deprived and 1,871=least deprived) it ranks at 48. Therefore this datazone and one and Hardap rank (where 1=most deprived and other, in Mariental Urban, are in the most deprived 75=least deprived) for the 20 most deprived 10 percent of datazones in Namibia in terms of datazones in Hardap are shown. Appendix 2 multiple deprivation (the cut-off for the 10 percent provides this information for all of the datazones most deprived is a rank of 187). The least deprived in Hardap. datazone in Hardap is located in Rehoboth West Urban and is ranked at 1,803 in Namibia as a The most deprived datazone in Hardap is in whole.

TableMariental 1: The Rural 20 most constituency, deprived anddatazones is therefore in the Hardap Region NIMD rank – NIMD rank – within Datazone constituency NIMD score national Hardap

226 Mariental Rural 307.8 48 1 237 Mariental Urban 265.4 182 2 253 Rehoboth East Urban 258.0 220 3 200 Gibeon 246.0 295 4 228 Mariental Rural 244.2 308 5 211 Gibeon 223.3 472 6 234 Mariental Urban 213.6 551 7 264 Rehoboth East Urban 208.2 596 8 235 Mariental Urban 206.3 612 9 201 Gibeon 200.3 654 10 208 Gibeon 198.9 669 11 210 Gibeon 195.0 702 12 225 Mariental Rural 194.9 704 13 209 Gibeon 193.5 713 14 262 Rehoboth East Urban 192.4 726 15 224 Mariental Rural 191.8 731 16 202 Gibeon 191.1 736 17 248 Rehoboth Rural 190.0 749 18 213 Gibeon 186.4 776 19 227 Mariental Rural 185.1 783 20

national The six constituencies in Hardap vary in terms of interquartile range for the overall NIMD. This is the range of deprivation of their datazones. Chart based on the ranks (i.e. where the most 1 shows the minimum, maximum and median deprived datazone in Namibia is ranked 1, and the rank of datazones in each constituency, and the least deprived datazone is ranked 1,871).

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 21

Interpreting the Charts: For details on how to interpret the chart please see the ‘How to interpret interquartile range charts’ description in section 4.1 of the national report available at http://www.undp.org.na/publications.aspx Interpreting the Charts: For details on how to interquartile range charts’ description in section interpret the chart please see the ‘How to interpret 4.1 of the national report available at http://www. undp.org.na/publications.aspx

The vertical green line for each constituency shows the range of the ranks of the The vertical green line for each constituency datazone within that constituency. The median datazonesshows in thea constituency range of the ranks (including of the datazones the dots in whichrank in forRehoboth some West constituencies Urban is the highest, like (least Gibeon and Rehobotha constituency West (including Urban ,the appear dots which at either for some end ofdeprived) the line). in the Marientalregion, while GibeonRural, has Mariental the lowest Urban andconstituencies, Rehoboth like East Gibeon Urban and Rehobothall have Westa relatively (most deprived)wide range median of rank. deprivation. If the box is relatively Urban, appear at either end of the line). Mariental short this indicates that datazones are ranked Rural,The greenMariental box Urban for and each Rehoboth constituency East Urban shows in a the narrow range range, of with the similarNIMD NIMD ranks ranks of (and the middle all50 have percent a relatively of datazones wide range of in deprivation. the constituencytherefore (the interquartile similar levels of range). multiple deprivation).The horizontal line within the box for each constituency representsRehoboth the rankRural, Rehobothof the median West Urban datazone and Gibeon, within The green box for each constituency shows the have a narrow range for the middle 50 percent. that constituency.range of the NIMD The ranks median of the rankmiddle in 50 Rehoboth percent MarientalWest Urban Rural, is Mariental the highest Urban and(least Rehoboth deprived) in the region,of datazones while inGibeon the constituency has the (the lowest interquartile (most deprived)East Urban median on the other rank. hand If have the a bmuchox is wider relatively short thisrange). indicates The horizontal that datazones line within the are box ranked for each in arange narrow for the rang middlee, 50with percent. similar NIMD ranks (and thereforeconstituency similar represents levels the of rank multiple of the median deprivation). Rehoboth Rural, Rehoboth West Urban and Gibeon, have a narrow range for the middle 50 percent. Mariental Rural, Mariental Urban and RehobothDatazone East level Urban Namibian on Indexthe other of Multiple hand Deprivation have a much 2001 -wider Hardap range Region for the middle 22 50 percent.

If this box sits towards the bottom of the chart it tells us that datazones in the constituency are concentrated in the most deprived part of the national distribution of the NIMD. If the box sits towards the top of the chart it tells us that the datazones in the

If this box sits towards the bottom of the chart it In terms of material deprivation, the most deprived tells us that datazones in the constituency are constituency in Hardap is Rehoboth Rural (with 58 concentrated in the most deprived part of the percent of the population experiencing material national distribution of the NIMD. If the box sits deprivation), followed by Gibeon (53 percent) towards the top of the chart it tells us that the and Mariental Rural (49 percent). In relation datazones in the constituency are concentrated in to employment deprivation, the most deprived the least deprived part of the national distribution. constituency is Gibeon (with 38 percent of the For most constituencies the datazones are relevant population being employment deprived), concentrated towards the middle of the national followed closely by Rehoboth East Urban (also 38 distribution. However, the datazones in Rehoboth percent) and Rehoboth Rural (37 percent). West Urban are concentrated at the least deprived end of the distribution. In terms of education deprivation, the most deprived constituency is Rehoboth Rural (with 77 percent of Further analysis shows that four constituencies the relevant population being education deprived). within Hardap have datazones in the most deprived 10 percent In Gibeon and Mariental Rural also, over 70 percent of datazones on the overall NIMD. of the relevant population experience education These four constituencies and the number of deprivation. These same three constituencies are datazones that are in the most deprived 10 percent also the three most deprived in Hardap in terms of datazones within Hardap are as follows: Gibeon of living environment deprivation. Mariental (2 of 14), Mariental Rural (2 of 17), Mariental Urban Rural is the most deprived (with 79 percent of the (2 of 11) and Rehoboth East Urban (1 of 14). total population experiencing living environment 4.2 Domains of deprivation deprivation), followed by Gibeon (78 percent) and Rehoboth Rural (77 percent). Gibeon constituency Although it is not possible to calculate multiple has the highest or second highest scores for all four deprivation rates as such, each of the individual domains. domains of deprivation can be presented at constituency level, and for all domains except The domain scores and ranks for each of the health the domain scores can be compared. datazones in Hardap are presented in Appendix Table 2 provides the domain scores for each 2. As in Table 2, four of the five domains are constituency in Hardap, excluding health as the expressed as rates. Health deprivation is expressed health score is not calculated as a rate. The other as the years of potential life lost in that datazone. four domains are in the form of simple deprivation A datazone with a relatively high death rate in a rates. So for example, 34.9 percent of the population young age group (including areas with high levels in Mariental Urban constituency experienced of infant mortality) will have a higher score than material deprivation in 2001. The within Hardap an area with a similarly relatively high death rate ranks are shown as well as the domain scores, for an older age group, all else being equal. The for each constituency in Hardap (where 1= most measure is related to life expectancy in an area, so deprived). datazones with low life expectancy will have high scores on this domain.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 23 6 3 5 4 1 2 rank iving l iving (within Hardap) deprivation deprivation environment environment 31.97 76.60 59.45 64.11 78.61 78.33 iving l iving rate (%) rate deprivation deprivation environment environment 6 1 5 4 3 2 rank (within ducation Hardap) e deprivation 56.5 77.2 67.1 67.5 74.3 74.8 ducation rate (%) rate e deprivation deprivation 6 3 2 4 5 1 rank (within Hardap) deprivation mployment e mployment 24.0 37.2 37.6 34.2 31.4 38.2 rate (%) rate deprivation deprivation mployment e mployment 6 1 4 5 3 2 rank (within Hardap) Material Material deprivation 25.2 58.0 39.5 34.9 48.9 52.8 rate (%) rate Material Material deprivation deprivation onstituency Rehoboth West Urban West Rehoboth Rehoboth Rural Rehoboth Rehoboth East Urban Rehoboth Mariental Urban Mariental Rural c Gibeon Table 2: Domain scores and ranks for each constituency in the Hardap Region in the Hardap for each constituency and ranks 2: Domain scores Table

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 24 Table 3 shows the percentage of each constituency’s in terms of employment deprivation (7 percent of nationally datazones that are in the most deprived 10 percent datazones). Four constituencies have datazones in of datazones for each domain. Five of the most deprived 10 percent in terms of education the six constituencies in Hardap have datazones deprivation (Gibeon, Mariental Rural, Mariental that feature amongst the most deprived 10 percent Urban and Rehoboth Rural) and health deprivation of datazones nationally on one or more domains (Gibeon, Mariental Rural, Mariental Urban and (Rehoboth West Urban is the constituency that does Rehoboth East Urban). None of the constituencies not). Only Gibeon has datazones that fall within the have datazones which feature in the most deprived most deprived 10 percent of datazones nationally 10 percent of datazones nationally for material deprivation or living environment deprivation. Table 3: percentage of datazones in most deprived 10 percent of datazones in Namibia Number of Material employment Health education living env. constituency datazones deprivation deprivation deprivation deprivation deprivation

Gibeon 14 0.0 7.1 14.3 42.9 0.0 Mariental Rural 17 0.0 0.0 11.8 29.4 0.0 Mariental Urban 11 0.0 0.0 9.1 18.2 0.0 Rehoboth East Urban 14 0.0 0.0 14.3 0.0 0.0 Rehoboth Rural 9 0.0 0.0 0.0 33.3 0.0 Rehoboth West Urban 10 0.0 0.0 0.0 0.0 0.0

Table 4 shows the percentage of each constituency’s 10 percent for each domain. Mariental Urban within Hardap datazones that are in the most deprived 10 percent and Rehoboth East Urban have datazones which of datazones for each domain. Gibeon feature in the most deprived 10 percent on four and Mariental Rural are the only constituencies that of the five domains. Rehoboth West Urban has just have at least one datazone in the most deprived one datazone in the most deprived 10 percent for material deprivation only.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 25 Table 4: percentage of datazones in most deprived 10 percent of datazones in the Hardap Region Number of Material employment Health education living env. constituency datazones deprivation deprivation deprivation deprivation deprivation

Gibeon 14 14.3 21.4 14.3 7.1 7.1 Mariental Rural 17 5.9 5.9 11.8 17.6 5.9 Mariental Urban 11 0.0 9.1 9.1 18.2 18.2 Rehoboth East Urban 14 7.1 7.1 14.3 0.0 14.3 Rehoboth Rural 9 22.2 11.1 0.0 11.1 0.0 Rehoboth West Urban 10 10.0 0.0 0.0 0.0 10.0

The following maps present each of the five 2 and 3, the lightest shading relates to the least domains at datazone level for Hardap and for the deprived datazones. It is intended that these maps Mariental and Rehoboth areas. As with Maps 1, should provide accessible profiles of the domains of deprivation in the Hardap Region.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 26

Map 4

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 27

Map 5

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 28 Map 6

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 32 29

Map 7

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 30

Map 8

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 31 Map 9

Datazone level Namibian Index of Multiple36 Deprivation 2001 - Hardap Region 32

Map 10

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 33

Map 11

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 34 Map 12

Datazone level Namibian Index of Multiple40 Deprivation 2001 - Hardap Region 35

Map 13

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 36

Map 14

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 37 Map 15

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 44 38

Map 16

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 39

Map 17

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 40 Map 18

Datazone level Namibian Index of Multiple48 Deprivation 2001 - Hardap Region 41 SecTION 5: cONclUSIONS aND SOMe pOlIcy RecOMMeNDaTIONS

The analysis presented in this report has identified particular areas – both datazones and constituencies – where deprivation is high relative to other areas in Hardap region. This analysis can support pro-poor policy formulation processes and programmatic interventions in many ways.

y providing reliable and objective information on, and profiling the distribution of, multiple deprivation By providing reliable and the distribution of the individual domains and objective information of deprivation across the region, the analysis presented in this report can provide planners; policy on, and profiling the and decision makers at the regional level with the distribution of multiple evidence base on which to plan and make decisions regarding resource allocation and the geographic deprivation and the individual areasB (constituencies and datazones) and sectors in which to prioritise public investments, government domains of deprivation support and service delivery. Specifically, the across the country, the NIMD analysis can be useful in the following ways: Temporal analysis of nature, scope and effects of can provide policy and poverty reduction programmes decision makers with the : By describing the geographical distribution and extent of individual evidence base on which to dimensions of deprivation and overall multiple deprivation at constituency and datazone levels, make decisions regarding this report provides a baseline map of deprivation resource allocation and the against which progress in poverty reduction in these areas can be measured over time, that is geographic areas and sectors between successive censuses (2001 and 2011 in which to prioritise public censusses). The NIMD is based on data relating to 2001 time- line and significant changes may have investments, government taken place since then. It will thus be necessary to support and service conduct further analyses using the 2011 Census data and information in order to shed light on the delivery relating to the extent to which changes have occurred in the region and possible reasons for any noted changes. various domains of deprivation Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 42 Interrogating the causes of inequality

: The report constituencies and datazones characterised by could be used by the regional authorities to initiate severe multiple deprivation could be targeted for the process of interrogating the causal factors of integrated development projects and programmes. such wide inter- and intra-constituency (datazone The most deprived areas vary by domain, and not all level) variations with respect to specific domains areas show a uniform degree of deprivation across and the overall combined and weighted index of the domains. This should be taken into account deprivation. when selecting a measure of deprivation to use Better planning and targeting of development as it is important to choose the most appropriate resources: measure for the particular policy purpose. Regional Councils have two distinct sources of development revenue – transfers It should be noted however, that the NIMD, as relative from central government and locally generated presented in this report, provides a profile of resources. The NIMD allows for better planning deprivation in Hardap region and even the for and targeting of such resources on the basis of least deprived areas, such as Rehoboth West Urban relative deprivation to the datazone level. Priorities constituency, contain pockets of deprivation. They can then be identified at the constituency and are simply less deprived than other areas with datazone levels that could be addressed through higher levels of deprivation such as Gibeon and integrated development approaches. Importantly, Mariental Urban constituencies. As such, spatially funds could be targeted to and ring-fenced for those targeted policy initiatives should be regarded as sectors/domains in which specific constituencies a complement to, rather than a substitution for, and datazones are particularly deprived or to mainstream pro-poor policies and strategies that the most deprived constituencies and datazones the Regional Council and National Government are within a constituency. It is also conceivable that already implementing in Hardap region.

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 43 aNNex 1: INDIcaTORS INclUDeD IN THe NIMD 2001

Material Deprivation Domain •

Number of 15-59 year olds (inclusive) who Numerator are illiterate • Denominator Number of people living in a household with • no access to a television or a radio; or Population aged 15-59 (inclusive) Number of people living in a household with living environment Deprivation Domain no access to a telephone/cell phone Denominator Numerator •

Total population Number of people living in a household employment Deprivation Domain without the use of electricity, paraffin or solar • power for lighting; or Numerator Number of people living in a household • without access to a flush toilet or pit latrine Number of people aged 15-59 who are • (ventilated or long drop); or unemployed Number of people living in a household Denominator without piped water/borehole/borehole with covered tank (but not open tank)/protected Total economically active population aged 15-59 well inside their dwelling or yard or within inclusive • 200 metres; or Health Deprivation Domain Number of people living in a household that is • Numerator a shack; or • Number of people living in a household with three or more people per room Years of potential life lost Denominator education Deprivation Domain

Numerator Total population •

Number of 15-59 year olds (inclusive) with no schooling completed at secondary level or above; or

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 44 aNNex 2: DOMaIN aND OveRall NIMD ScOReS aND RaNKS 95.7 59.2 98.8 97.9 95.1 93.3 89.2 246.0 200.3 191.1 137.6 172.3 167.2 198.9 193.5 195.0 223.3 152.9 186.4 114.9 132.4 117.5 score NIMD 7 9 10 16 23 22 56 42 11 36 20 58 53 13 32 52 26 39 31 21 49 40 rank iving l iving deprivation deprivation environment environment 96.0 94.9 91.5 86.1 96.0 86.3 52.0 70.9 94.3 75.9 86.9 48.2 57.5 93.9 77.6 57.5 81.1 71.6 78.4 86.7 64.9 71.5 score iving l iving deprivation deprivation environment environment 6 9 8 10 25 13 16 17 55 62 45 21 22 56 40 65 53 52 46 43 66 47 rank ducation e deprivation 80.5 75.5 79.7 81.9 79.0 78.5 66.9 62.2 80.6 71.1 77.8 76.5 66.9 80.7 72.7 60.6 69.0 69.4 70.8 71.7 59.5 70.6 score ducation e deprivation deprivation 9 2 3 8 44 18 63 13 46 51 59 21 28 33 52 23 10 50 37 73 15 64 rank Health deprivation deprivation 39.0 921.4 323.9 655.1 140.2 787.9 291.8 270.5 216.4 587.3 488.2 951.8 423.9 255.5 569.5 842.6 271.7 411.2 700.4 119.9 1427.4 1325.0 score Health deprivation deprivation 3 1 2 8 34 71 66 30 32 74 27 18 25 38 65 29 68 55 42 60 56 67 rank deprivation mployment e mployment 59.6 67.6 32.7 15.7 19.2 35.6 34.8 12.3 39.3 46.8 61.7 54.6 43.1 31.4 19.6 36.7 17.3 23.5 29.0 22.1 23.4 17.4 score deprivation deprivation mployment e mployment 9 4 3 28 13 29 60 30 38 17 56 45 20 27 10 46 23 26 36 43 40 22 rank Material Material deprivation 51.2 64.9 68.2 50.7 25.2 76.5 50.7 44.3 60.7 32.5 41.8 55.7 52.0 76.9 68.0 41.6 54.8 52.1 47.0 42.2 43.0 55.1 score Material Material deprivation deprivation onstituency Gibeon c Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Gibeon Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. This table presents the scores and ranks for every datazone in Hardap for the five domains and the NIMD. overall For all deprivation domains material except health experienced constituency Gibeon in 200 datazone in population the of 51.2% example, for So rate. a as calculated is score the in 2001. Health is expressed as the years of potential life lost (a measure of premature mortality) in that datazone, and a higher score indicates 1=most deprived). each datazone (where for shown are ranks The within Hardap health deprivation. greater

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 45 97.3 95.3 81.4 26.0 57.7 86.5 191.8 194.9 307.8 185.1 244.2 102.0 110.0 113.6 158.7 213.6 206.3 265.4 157.6 108.1 178.7 171.1 135.3 152.0 131.1 138.1 190.0 139.9 160.0 165.8 177.0 3 2 4 8 27 33 24 17 29 34 25 30 47 60 63 12 70 65 45 51 48 15 41 37 35 43 54 19 38 14 46 79.3 76.8 83.5 89.1 98.9 78.6 76.6 82.5 78.5 66.3 47.1 40.6 94.0 99.4 25.0 98.9 35.8 68.8 62.8 65.4 92.1 71.1 73.7 76.5 70.8 57.2 88.5 72.1 92.5 68.6 96.0 1 4 2 5 3 7 35 28 15 12 30 48 38 37 58 32 75 72 41 49 54 18 20 24 44 31 19 14 11 27 23 74.2 74.6 86.7 82.8 84.0 79.2 79.9 74.4 70.3 73.1 73.1 64.2 82.4 74.3 35.5 83.5 46.4 72.4 70.0 68.6 81.1 78.5 78.3 75.6 71.7 74.3 78.4 79.3 80.2 75.2 76.0 1 4 5 68 74 41 29 26 72 36 24 39 35 20 17 62 30 19 57 22 40 56 43 25 38 54 53 69 49 16 32 83.0 31.2 41.8 72.4 373.7 452.8 510.4 411.8 560.6 381.4 412.4 601.9 658.9 165.4 439.0 620.1 219.5 581.7 376.2 238.6 342.1 513.4 383.3 243.3 248.4 276.5 665.1 427.3 1692.6 1275.6 1238.3 5 6 9 4 70 72 19 15 10 11 73 58 57 35 13 22 75 17 51 62 63 41 23 59 40 24 20 33 50 14 28 16.0 13.9 46.7 49.0 52.2 52.0 57.3 13.8 22.9 23.1 56.7 31.9 51.7 44.3 11.5 47.0 24.7 52.3 20.7 19.8 29.2 44.2 22.8 29.4 43.8 46.0 57.8 33.3 24.9 49.2 37.1 5 7 2 8 6 41 39 49 50 47 32 21 35 75 16 61 37 25 69 55 71 58 48 31 33 52 34 11 18 15 65 5.9 42.9 43.3 39.9 36.6 74.8 41.4 50.4 55.7 47.3 60.9 24.2 45.6 53.0 16.3 33.4 14.2 30.4 40.5 50.6 74.4 78.8 49.3 69.0 34.7 49.2 67.9 60.1 62.8 20.6 74.7 Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental R. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Mariental U. Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth R. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 46 50.4 76.7 62.3 59.4 52.9 37.6 96.6 69.1 80.5 25.5 34.2 31.8 46.8 258.0 139.8 133.5 108.1 192.4 119.2 208.2 116.4 178.3 1 5 6 69 61 55 44 57 67 66 64 28 18 74 59 62 68 50 75 72 73 71 9.6 99.8 26.9 46.2 55.7 69.5 48.5 31.4 32.2 36.6 97.4 79.1 88.9 12.3 47.5 44.8 29.9 63.7 24.1 14.3 96.5 24.2 36 68 57 50 51 64 61 60 67 39 34 33 71 42 59 63 26 74 70 73 29 69 73.6 56.8 64.7 69.8 69.4 60.9 62.6 63.1 58.9 73.0 74.3 74.3 47.9 72.2 63.8 61.2 75.4 37.7 52.0 44.8 74.4 54.5 7 6 55 12 60 34 14 48 71 67 11 70 66 47 42 27 45 65 75 61 31 58 46.8 83.5 60.4 86.3 13.6 241.0 809.8 189.0 414.3 764.8 288.5 809.9 291.7 345.7 502.3 313.9 119.6 177.3 437.8 218.0 1229.7 1231.4 7 12 47 54 21 31 49 37 39 16 43 26 48 53 45 44 36 69 61 64 52 46 51.8 26.8 56.0 23.8 45.0 35.0 25.8 31.8 30.8 47.6 28.2 41.6 26.3 23.9 27.6 27.7 31.8 16.2 21.8 19.8 24.3 26.9 1 14 66 64 73 24 44 62 51 54 53 12 19 63 57 67 42 72 70 59 74 68 63.2 19.0 22.1 11.6 53.2 42.2 23.9 36.2 33.8 34.3 67.3 59.1 23.5 31.6 19.0 42.5 14.2 14.3 26.3 10.8 92.3 18.0 Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth E. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth Rehoboth W. Rehoboth

Datazone level Namibian Index of Multiple Deprivation 2001 - Hardap Region 47 RefeReNceS

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