Social Indicators Research

, Volume 130, Issue 1, pp 71–86 | Cite as

Quality of Life in the Gauteng City-Region, South Africa

Article

Abstract

The core challenge facing South Africa after it became a democracy in 1994 was twofold: to meet the basic needs of (black) people denied these by apartheid, and simultaneously restoring dignity and undoing the psycho-social damage of racist white rule. This article analyses the first two in a planned long-term sequence of quality of life surveys in the Gauteng City-Region, the economic power-house of South Africa, with Johannesburg at its centre. The survey gathers data across multiple objective and subjective indicators. The key challenge is to try and understand the interplay between the two—and thus what impact, if any, meeting basic needs has on the psycho-social profile of residents of the city-region. The conclusion is that the impact is limited: objective indicators, which largely measure delivery of goods and services by government, drives the quality of life index up; but social, community and individuated indicators (such as anomie and alienation) pull scores down, and most particularly so for older, low educated black South Africans. The future may look positive for those born after apartheid; but for those who sacrificed their education in the struggle to topple the regime, the future looks like ‘more of the same’. Education emerges as the key asset that allows black South Africans to overcome the damage of apartheid; lack of (or low levels of) education do the reverse; this is true of both socio-economic advancement and social attitudes.

Keywords

South Africa Gauteng City-Region Quality of life Race Apartheid Marginalisation 

1 Introduction: The Gauteng City-Region and Quality of Life

The focus of this paper is the measurement of ‘Quality of Life’ in the Gauteng City-Region (GCR), South Africa. The article begins by briefly locating and describing the region, before turning to the methods and results of the first two Quality of Life surveys—in what is planned as an on-going, bi-annual set of surveys—conducted by the Gauteng City-Region Observatory (GCRO), which is charged with providing all actors in the GCR with the evidence base needed to make informed decisions.

The location matters: annually, the GCR generates over a third of national Gross Domestic Product, and has the largest labour force in the country. As such, if significant socio-economic improvements in the lives of black South Africans are to be identified and measured, the economic capital should be a good place to look. The purpose of using a quality of life approach—rather than, say, relying merely on census data to measure economic advancement—is to try and provide an holistic picture of post-apartheid development. The key challenge that faced South Africa is 1994 was twofold.

Firstly, after 400 years of white rule (and half a decade of apartheid), the vast majority of black South Africans—which under apartheid meant black Africans, those of Indian descent (many brought in under British rule as indentured labourers) and ‘coloured’ or people of mixed race—lacked many of the basic necessities of a decent life. Apartheid used a ‘divide and rule’ tactic to offer Indians slightly more benefits than coloureds, and coloureds slightly more than Africans, to (vainly, as it turned out) try and head off any chance of a united opposition movement. Africans, the majority of the population, were treated worst, with laws determining where they could live, who they could marry, what level of education was deemed suitable (and in which medium of instruction), what jobs they could take up, and so on. Blacks in general lived in spatially separate, racially discrete townships, often very far from their place of work, and formed a poor reserve army of labour with no rights and few socio-economic benefits.

Secondly, white rule had become increasingly violent as resistance had grown, leading to state-sponsored covert hit-squads as well as military attacks on neighbouring states suspected of hosting bases of the African National Congress (ANC) and its allies. This on top of mass detentions and the casual, everyday racism that afflicted every black South African (albeit in different ways) meant that apartheid bequeathed to democratic South Africa both a desperately poor black population where the majority lived under the poverty line and where psycho-social damage was widespread. To complicate matters further, the latter afflicted black and white (unequally, to be sure)—young conscripts sent into black townships or to invade foreign countries suffered (and still suffer) post-traumatic stress disorder, although their perpetrator status and white skins did not fit a neat narrative of universal black victimhood. That said, there was little debate that the preponderance of damage had been done to black South Africans.

Righting these wrongs was the primary challenge facing the first democratic government, elected in 1994 under the Presidency of Nelson Mandela. His government adopted The Reconstruction and Development Programme (ANC 1994) (commonly known by its acronym, the RDP), a basic needs blueprint that prioritised clean water, sanitation, formal housing, tarred roads, street lighting (and much more) and so on, in a deliberate attempt to provide the basic needs required to lift people out of poverty and offer them goods (such as free ‘RDP houses’) that could, over time, be marketized and allow entry into the economy. However, within the RDP was an unstated assumption, or perhaps more accurately, a hope: that meeting the basic needs of the mass of the population would restore their dignity and thereby enhance psychological healing. Dignity was a key facet of the Bill of Rights (adopted as part of the democratic Constitution in 1996) (Constitution of the Republic of South Africa 1996), but while governments can fund infrastructure programmes, they are far less equipped (if at all) to lead a national psycho-social rehabilitation programme.

2 Approach and Theory

Although an initial flurry of activity focused on uncovering the truth of past torture, disappearances, assassinations and the like—the Truth and Reconciliation Commission—very little was put in place to deal with psycho-social damage that 400 years of white rule and settler colonialism had wrought. Mandela was a moral beacon in his capacity for forgiveness—but he was also far from being an everyman, and so our focus in this article is to try and understand the commingling of objective indicators—whether respondents have received their basic needs (a house, clean water, etc.)—and subjective indicators, such as social capital, alienation, extreme views (racial, towards foreigners, and so on).

In short, a quality of life approach is not a passive measuring instrument that tries to answer the question, ‘how far have we come?’ by bean-counting: it tries to find the right way to ask, and offer possible answers to the question, are South Africans attaining all-round quality of life? Does access to goods and services in any way correlate with good mental health, and thus holistic quality of life?

Thus this paper is located within the discipline and theoretical paradigm of social indicators research, using a positivist approach that relies on survey-generated data—with all the flaws and pitfalls that such reliance can generate (Babbie 1995: 273/4). In truth, it is closer to grounded theory, which searches for hypotheses by analysing data, rather than testing hypotheses through data analysis. These reverse-engineered hypotheses are usually generated through qualitative analysis, but this is a quantitative attempt to discover whether the South African approach of meeting basic needs has done anything for improving the overall well-being of South Africans, especially black South Africans, using a multivariate quality of life methodology. The hypothesis, it can be argued, was proposed by the first democratic government and its RDP—provide the basic requirements for human dignity, and healing will follow. This was never stated as a hypothesis, but is the foundation on which a basic needs approach (especially the RDP) rests; but how it might operate in a recently democratised, post-authoritarian, racially divided society, is entirely unknown. It is difficult to find comparable quality of life studies, given that no other society has recently democratised, after 400 years of settler colonialism and white supremacy, and legalised racial discrimination (and attendant violence) in every facet of life. The paper is one small contribution to uncovering what is happening ‘under the skin’ of the people living in post-apartheid South Africa.

3 The Gauteng City-Region

This article is situated in the Gauteng City-Region, a constellation of urban nodes within a radius of 175 km from the centre of Johannesburg. With a population of some 13 million people (StatsSA 2011), and contributing some 40 % of national Gross Domestic Product (the vast bulk of which comes from the province of Gauteng itself), the GCR is a major player nationally, regionally and continentally. These nodes are intimately linked through daily commuting, intense economic interaction, and shared bulk infrastructure and services. Some are linked through the social engineering of apartheid, which forcibly relocated urban workers to ‘homelands’ many scores of kilometres away, forcing them to make lengthy daily journeys to and from urban centres where they sold their labour. Although they live a long distance from urban centres, they are displaced urban workers and are included in our definition of the GCR, rather than opting only for vibrant economic hubs.

Most of this region of cities and towns falls within the boundaries of one of South Africa’s nine provinces, Gauteng, which was demarcated before the first democratic elections in 1994. The province includes the major cities of Johannesburg, South Africa’s primary economic centre, and Tshwane (formerly Pretoria), the national administrative capital, as well as smaller centres such as Germiston, Vereeniging and Krugersdorp. An even more extended urban region, stretching beyond the boundaries of Gauteng, includes Rustenburg (sitting on massive platinum reserves), Sasolburg (a huge chemical processing area), and the power generating towns of Witbank, Middelburg and Secunda. In this case study the focus will be primarily on the metropolitan region within Gauteng (Fig. 1).
Fig. 1

Map of the Gauteng City-Region (Source: GCRO)

Gauteng, which enjoys just 1.4 % of national land cover in South Africa, by 2011 was generating 36 % of national GDP while the broader Gauteng City-Region produced 43 % of national GDP (OECD 2011: 21). The province contains a fifth of South Africa’s population, which will rise to a quarter (16 million people) by 2020, if migration patterns remain at the level measured across censuses in 1996, 2001 and 2011. Given that services are provided to households not individuals, it is notable that there was an annual average growth in household numbers of 3.6 % between 2001 and 2011, with 2.9 million households in Gauteng by 2011.

As a result of apartheid, Gauteng’s settlements have been developed on the principle of a hard separation in space between the wealthy and the poor. All cities have some spatial separation between rich and poor areas, as the vicissitudes of property development drive the poor into lower value areas. But nowhere in the world are the distinctions as clearly marked as in South African cities, nor as starkly based on racial grounds. The wealthier parts of Gauteng’s cities provide a standard of urban infrastructure, and a quality of life (we return to this below), that easily matches that to be found in the world’s most developed cities. The poorer areas are located far from work and educational opportunities, often buffered by major highways, industrial parks and the like. Apartheid created literal, physical boundaries between races, and thus between classes, since race and class were so closely correlated under apartheid.

When apartheid barriers to movement began to crumble in the 1980s, and were formally eradicated in the 1990s, a pent-up demand for urban lives and opportunities saw a massive wave of urbanisation. This process of inevitable, and essential, correction in national population distribution continues today. For Gauteng, huge inflows of largely poor people has been difficult to manage. The new in-migrants add daily to the pre-existing challenge of addressing service backlogs for the African residents who were already living in underserviced townships in the city region. The result was a burgeoning of large informal settlements, the growth informal dwellings in the backyards of formal houses, and overcrowding of historical points of first access into the city such as inner city areas.

Both provincial and local government in Gauteng moved quickly to address service backlogs and accommodate new arrivals. Significant progress has been made in housing provision, but often with perverse outcomes: the price of land and a limited government budget meant that hundreds of thousands of ‘RDP’ houses have been built predominantly in large housing estates on peripheral sites. Because of the speed of housing delivery, urban amenities such as schools, crèches, libraries and clinics were often only added later. The implications for variation in quality of life—even if it is ‘better than apartheid’—are self-evident.

That said, in many ways, delivery in Gauteng since 1994 has been a success story. According to the 2011 census produced by Statistics South Africa (StatsSA 2011), the proportion of people with no formal education has dropped from 10 % in 1996 to 4 % in 2011, and half of those migrated into the province from elsewhere. Census 2011 tells us that where 75 % of Gautengers lived in formal dwellings in 1996, that figure has now risen—despite the massive population growth shown above—to 80 %; 11 % still live in informal dwellings. 98 % of people now have access to piped water, 96 % have access to a flush toilet, and 87 % access the national grid for lighting energy. The basic needs approach, based on the need to restore dignity, seems to have been very successful—though it simultaneously, through its very success, continues to draw in thousands and thousands of migrants (South African, African, European and others) who join the queue of those needing their basic needs to be met. However, this should be tempered by the fact that the province of Gauteng has witnessed more social protest—often referred to as ‘service delivery protests’—than any other province in South Africa. Relative deprivation—having received some services but the desire for more—seems to be widespread.1

If poor (overwhelmingly African) people have been housed in large estates, the same has happened at the other end of the scale. Many suburbs formerly zoned for whites have become near-impenetrable life-style estates, gated communities and the like, with booms barring entry, backed up by armed guards. Apartheid social geography has effortlessly adapted to class—black middle class families now live in those same estates, cheek by jowl with white middle class families, all safely walled off from ‘the poor’—and as such, apartheid geography has proved remarkably difficult to eradicate or even ameliorate.

The GCR, generating 43 % of national Gross Domestic Product (GDP) and Value Add (GVA), emerges, unsurprisingly, as a major magnet, and Gauteng includes the largest population (12.3 million in 2011) squeezed into the smallest landmass of all nine provinces in South Africa. So while the GCR includes pockets of severe poverty, the region—and Johannesburg in particular—are among the best-off (and best-serviced) parts of South Africa. Thus the results of quality of life measurement provided below need to be seen in context: they are measurements taken in the wealthiest province-cum-city-region in the country, and cannot be extrapolated to other parts of South Africa.

4 Quality of Life

Quality of life is a concept often used by policy-makers or planners, but less often tightly defined or unpacked. Take, for example, the following headline from an article on the South Africa: The Good News website: “Quality of life improves, but inequality widens”. The ensuing article makes no further mention of quality of life, but does go on to report on issues such as income, poverty, housing, basic services, inequality and national pride. Quality of life is thus merely adjectival, and not at all analytic.

The term quality of life is typically used to evaluate—or merely describe from afar—the general well-being of individuals and societies, actual or imputed. The term is used in a wide range of contexts, including the fields of international development, health care, psycho-social services and political science. Quality of life and national (or regional or local) well-being had emerged before the move away from ‘standard of living’, and has become far more popular since the much stronger resistance to ‘Gross Domestic Product’ as the best measure of how well a society is performing. Where the former approaches only included economic indicators—and thus only measured economic performance (but for example ignored the environmental damage caused by that economic performance)—standard indicators of the quality of life include not only wealth and employment, but also the built environment, physical and mental health, education, recreation and leisure time, and social belonging.

There is an unexpectedly strong history of exploring quality of life in the South African context, stretching back into the apartheid era. The South African Quality of Life Trends Study has data that goes back to the early 1980s (Møller 1998). While the focus of the study (and the reports emanating from it) has shifted across time, this study has focused on the issue of quality of life across a number of different areas: global satisfaction, family life, personal life, food, health, socio-political issues, housing, education, community facilities, work and income and social security. The data, as with the data reported below, are generated through surveys that asks respondents for their level of satisfaction across a variety of indicators within each of these areas, relying on subjective responses to gauge quality of life. To that extent, there is a convergence of approaches.

However, as we argue below, the key challenge in most South African work in this area has been the failure to create a compelling composite index that speaks to multiple audiences, from citizens to policy-makers. This requires restraint on the part of quality of life researchers, who in the past valorised have one variable above others—such as, say, the importance of the democratic transition in 1994 to black South Africans—and provides rather a holistic and longitudinal understanding of quality of life. The ‘South African miracle’ saw some selecting single indicators—such as black attitudes to freedom and democracy—at the expense of other variables, not least because of their contextual significance as well as the large ‘jump’ in the data. As we show below, this can lead to rather facile conclusions, such as positive black attitudes to the attainment of freedom may be an insufficient basis for broader quality of life—a brief ‘headline’ that took the place of analysing what those other conditions may be are that are required to attain quality of life after freedom.

If quality of life researchers, in a society undergoing a fundamental transition, such as occurred in South Africa between 1990 and 1994, face the (understandably seductive) danger of selecting one or two variables because of the exigencies and global fascination of the historical moment, quality of life studies located in cities and city-regions face other dangers. For example, Boddy and Parkinson (2004: 242) argue that quality of life—more or less clearly defined—is merely a tool that contributes to the competitiveness (or not) of large cities, used in making investment decisions or marketing locations for future investment. Ranking ‘world cities’ is a global fad, often based on entrenched developed world prejudices, but one that easily absorbs quality of life studies into a broader marketing exercise for those seeking to influence investment decisions. In this approach, city-regions are not ‘real’—they are simply marketing exercises to better leverage investment based on arguments about agglomeration and competitive advantage. By the same token, quality of life studies are merely a flag to wave so as to garner attention and investment as a ‘natural’ part of globalisation, with little value to the citizens being studies, or those seeking to govern them.

Worse, quality of life can be seen as separating the worthy from their less worthy brethren in the cut-and-thrust world of globalised capitalism. With globalisation seen as a modern form of social Darwinism, the logic is fairly simple: the better educated and well-off citizens of a city or city-region will do well, and those less well-off will inevitably fall by the way-side, the unavoidable victims of market forces. The positive and negative impacts of globalisation on quality of life is regarded by some authors as “two sides of the same coin” rather than the trade offs and negative social costs of ‘progress’ (Hack et al.: 2). They further call for strong and effective governance of these city regions—and of course a large role for the private sector. Thus, we are warned that governments must guard against avoiding “unpopular political decisions by focusing [limited local resources] on local services [as this strategy] may only be postponing the inevitable impact of globalization, including its potentially long-term beneficial effects” (ibid.). The notion of actually changing the status quo to benefit the poor immediately seems not to enter the debate.

Thus we are in a strange situation where city-region discourse is predominantly focused on economic indicators, co-opts the language of ‘quality of life’ as part of its discourse, but uses it for economic reasons. Quality of life deliberately veers away from economic reductionism to try and understand far more complex and subtle nuances of life in city-regions. There remains an inherent tension, which is not automatically a bad thing, unless either side claims supremacy. The rise of quality of life indicators beyond the economic, in tandem with the rise in studies of well being, does assist in the formulation of global economic investment considerations and related non-economic issues such as social cohesion and governance. These latter variables or categories are self-evidently critical in a society such as South Africa, but are primarily related to the image and marketability of global city-regions—the ‘liveability’ of cities and their ability to attract and retain high-skill and high-worth individuals and institutions. Mercer for example in their city rankings use 39 key quality of living determinants, grouped in categories that include consumer goods costs, currency exchange regulation and banking services, availability of international schools and so on, alongside more predictable indicators such as the political and social environment, crime, housing and so on (Mercer 2009).

A good ranking could have positive economic consequences for the recipient city or city-region, in terms of investment opportunities and ultimately economic growth, by boosting its image. The irrelevance of many of the indicators to the poor, seeking to survive in the same space, is equally evident. This brief detour is meant to emphasise to the reader that the study being analysed here is not a city-region marketing exercise. It is, as we stated earlier, an attempt to study a society undergoing fundamental transformation, and understand the interplay between subjective and objective indicators used to measure transformation.

5 The South African Context

In South Africa, measuring quality of life of citizens has been a subject of robust debate among policy makers and academics alike. Different writers, following different theoretical traditions, have deployed a range of factors as indicators of life satisfaction and happiness. Broadly speaking, literature on measuring quality of life for the citizens of South Africa have followed two theoretical trajectories, namely: (a) that life satisfaction and happiness are a function of material conditions linked to the individual, or (b) that expression of life satisfaction or dissatisfaction is the projected expression of personal wellbeing. This article rejects this as a false distinction, and argues that only by admixing ‘interior’ variables with material measurements will we open a window on quality of life.

Research on the material aspect of quality of life commands more appeal. Beginning from the early 1980s, the academics that initiated the Quality-of-Life Trends Project argued that they were developing “cross-cultural quality of life methodologies” for a socially heterogeneous society (Møller 2007). To date, a corpus of literature generated by this project contains many important insights on quality of life. Valerie Møller is one of the leading academics working in the field, and a founder member of the project. Her work has focused principally on tracking the satisfaction and happiness of South Africans against the background of changing socio-economic and political circumstances before and after 1994. However, she reflects a more common tendency to single out individual variables for attention, at the expense of a broader, integrated index.

For example, in examining what she terms “trendiness” for subjective life satisfaction indicators versus objective quality of life indicators (at a national level), Møller (2007) firstly reviewed the contrasting interpretations of approaches to quality of life in black and white communities in South Africa over different periods of time both before and after the dawn of democratic rule. Her principal observation was that “post-election” “trendiness” has shown that attaining freedom in 1994 was not the only determinant of happiness and satisfaction among South Africans. A shift of focus is evident, once the afterglow of 1994 faded, to a closer examination of the impact of different phenomena impacting on substantive democracy such as service delivery, crime and unemployment, as differentially experienced by South Africa’s different racial groups. South Africa offers researchers a racial fixation, given the massive material and attitudinal differences between races; the danger is that issues such as gender, age (a more recent focus of the project) and other key social variables may be submerged in the drama of racial differentiation.

South Africa is known inter alia for racial division and inequality—so many researchers go looking for, and find, that these matter. Thus some researchers suggest that there is a large gap between the life satisfaction of black and white South Africans because (they argue, not wrongly) race is a reasonable proxy for income and access to resources—a single factor which explains the highest proportion of variance of satisfaction with life and domain satisfaction. At one level, this is both true and obvious. At another, however, it is reductionist and misleading—the burgeoning black middle class (probably the most important social change occurring in the society) is swallowed by macro-level black/white differences, as well as other intra-racial differences (both subjective and objective). The real question is what is happening beneath the surface?

Some post-apartheid governments have embraced quality of life measurements. For example, the eThekwini Metropolitan Municipality (including the port city of Durban) in 1998 began conducting annual surveys to monitor the changes in the quality of life of Durban’s people. The available reports reflect on areas including service delivery, individual sense of well-being, crime, HIV prevalence, and the like. The hypothesis we are seeking to either test or develop—the interrelationship between objective and subjective indicators, between meeting basic needs and enhancing psycho-social health—would not be adequately serviced by this (otherwise robust) model, which is heavily loaded with objective and rather light on subjective indicators, designed as it is for policy makers. Moreover, the eThekwini study makes no attempt to create an aggregate score within each broad area (of which there are nine), nor, more importantly, across the different areas, in order to generate an overall quality of life index. Data are merely reported for each indicator and, on occasion, disaggregated by variables such as race.

This paper argues strongly for the creation of a quality of life index and using it to look beneath the surface of society, rather than pick ‘easy’ variables such as race and make judgements accordingly. Higgs proposed one such model, which he called ‘Everyday Quality of Life’ (EQL) (Higgs 2003: 11). His EQL model operates across 15 broad areas ranging from genetics to diet to socio-economic status and so on. Although it appears to be a fairly comprehensive model, it is unclear whether the resultant survey instrument adequately covers each area within the model or how the model is put together—as the paper ends before an overall EQL score is computed.

In short, many South African academics and researchers have been working in the broad domain of quality of life, but few if any seem to have taken the key step: moving beyond a description of key variables or analytic categories (many of which, such as race, politics and inequality, are deeply alluring) to creating and analysing a composite index. The drivers behind the overall scores must of course be analysed—but as drivers behind an index, not substitutes for it. As has been argued elsewhere, any adequate measure of quality of life must be a plural measure, recognising a number of distinct components that are irreducible to one another (Nussbaum and Sen 1993: 3).

6 Quality of Life in the Gauteng City-Region

The Gauteng City-Region Observatory (GCRO) completed its second ‘Quality of Life’ survey in 2011 (the first took place in 2009), with a sample of almost 17,000 respondents (the first had a sample of 6600). This allows some sense of change over time, which will be more evident when the third (2013) survey is analysed (it is under way at the time of writing).

In order to measure quality of life, the GCRO surveys include some 200 indicator questions across a wide range of areas, and 54 of those are variables (see Table 1) used to construct the quality of life index. These include subjective and objective indicator questions. Both are combined into 10 ‘dimensions’ of quality of life—again to try and measure both overall quality of life, and the ‘drivers’ behind quality of life either rising or falling.
Table 1

Objective and subjective indicators used to construct the Quality of Life index

Broad areas

Subjective indicators (level of satisfaction)

Objective indicators (measured to RDP standard)a

1. Global/‘headspace’

Life satisfaction

Alienation

Anomie

Country going in right direction

 

2. Family

Marriage/relationship

Family life

Time available for family

Leisure time

Ability to feed children/self in year prior to interview

3. Community

Trust community (social capital)

Friends

Important to look after environment

Membership of clubs, organisations, societies (across 21 civil society organisations)

4. Health

Health affects work

Health affects social activities

 

5. Housing

Rating of dwelling

Rating of area/place

Dwelling structure (RDP standard)

Dwelling ownership

Overcrowding (more than two households sharing one room excluding kitchen/bathroom)

6. Infrastructure

Perceived improvement in community

Water cleanliness (self-reported)

Sanitation access (RDP standard)

Water access (RDP standard)

Electricity (RDP standard)

Refuse removal (RDP standard)

Cut offs/evictions for non-payment of bills

7. Education and connectivity

Press is free (Likert item)

Highest level of education attained

Telephone/cell phone ownership

Radio/television ownership

Internet connection

8. Work

Amount of money available

Household status (self-described class position)

Standard of living

Working conditions (decent work index)

Employment status

Household income

Absence of debt

9. Security

Safety in area during day

Safety in area during night

Safety at home

Crime situation improved

Victim of crime (self-reported)

10. Socio-political

Politics is waste of time (Likert)

Elections are free and fair (Likert)

Judiciary is free (Likert)

Trust between races (Likert)

Foreigners are taking benefits meant for locals

Government performance rating

Government officials live up to Batho Pele principles (i.e. ‘People First’ principles of the South African public service)

Public participation (in a range of government/community initiatives such as local development fora, school governing bodies, etc.)

Voted in most recent election

Have been asked for a bribe by officials/police

aThe RDP set standards for service delivery, such as clean water piped into dwellings, into their yards, or being available within 200 m; acceptable types of sanitation; and so on

The history of the current quality of life index began with a multivariate index created in 1991 to try and understand the impact of apartheid and resistance to it, on youth—the ‘marginalised youth’ project. (Everatt and Orkin 1993) This was a survey that collected data on subjective and objective indicators, used factor analysis to identify typologies, and correspondence analysis to identify correlations between categories and variables such as age cohort, race, sex and so on. The emphasis in this early outing was more on subjective than objective indicators, given that apartheid laws were still in place and the survey took place in 1991, one year after the transition to democracy began. The focus was on trying to understand and measure youth marginalisation; the subjective components remain key to current quality of life measurement in South Africa. It was further developed into a 2001 quality of life index used to assess the impact of service delivery on deep rural communities, including the use of control areas where no delivery had occurred, to assess whether quality of life rose because of service delivery (Everatt and Jennings 2001). The conclusion was that objective indicators rose—predictably—driving the overall index higher, but with little impact on psycho-social issues.

These early attempts at defining quality of life have been developed and refined, resulting in an index comprising the following broad dimensions: life satisfaction/‘headspace’, family, community and socio-political, all of which are heavily loaded (see below) with subjective indicators as well as objective; and then connectivity, health, housing, infrastructure, education, security and work. The purpose at one level is to balance service delivery with subjective indicators, so that government programmes.

These 10 dimensions comprise a series of subjective indicators and—except in the life satisfaction/‘headspace’ area (which includes alienation, anomie, extreme racial views, and so on)—objective indicators. The use of objective indicators is important as it seeks to limit (although not negate) the influence that a bad experience or event in the preceding hours, days or months before being interviewed may have on the attitudes of the interviewees. The indicators used are set out below (please note that some indicators are themselves derived from multiple individual questions—thus ‘decent work’ for example is one variable in the ‘work dimension’ but is itself a score derived from a 12-part index of questions about conditions of service). In all, there are 54 indicators, across the 10 ‘dimensions’ of quality of life.

For each indicator, a score of 0 or 1 was allocated to each individual respondent in order to compute an overall score for the area. For each dimension, the score was then scaled out of 1. For each dimension, a maximum score of 1 was possible (working on the same 0–1 basis as the Gini co-efficient). A score of 1 would reflect extremely high levels of quality of life, a score of 0 the reverse. When the dimensions are added, perfect quality of life would be represented by 10 (out of 10), where a respondent scores 1 out 1 on every dimension: this is a simple matter of adding the scores from the 10 dimensions together. Therefore, the higher the score the higher the level of quality of life. The mean scores for each dimension, for 2009 and 2011, are shown in Fig. 2 below, and immediately reflect quite significant changes.
Fig. 2

Scores for all dimensions of quality of life, 2009 and 2011

No variables or dimensions in the index were weighted, a questionable approach in a deeply divided society. It is reasonable to ask, should specific variables (or even entire dimensions) be weighted above others? Given the extended unemployment crisis that has beset South Africa for decades (and mainly affected black South Africans), for example, should unemployment—part of the ‘work’ dimension—not be weighted more than, say, membership of a civil society organisation, or satisfaction with respondent’s dwelling, and so on.

These are legitimate questions, and GCRO commissioned an economist from the University of Johannesburg to use Principal Component Analysis (PCA) on both the 2009 and 2011 surveys to see whether or not PCA—which applies weights to key variables as they emerge from the analysis—generated results that were significantly different from the unweighted approach. (Greyling 2011). The simple answer was ‘no’, although the nuance emerging from her analysis added value to our understanding of the quality of life index.

It is notable that ‘work’—which includes un/employment status, a decent work index as well as satisfaction with work indicators, remains the weakest area in the GCR in both 2009 and 2011. With a strict unemployment rate (which only measures ‘active work-seekers’ as unemployed) of 29 % and a broader rate (which includes all people who can work but are out of work) closer to 36 % in Gauteng, this is not surprising. This dimension was also impacted by the global recession, which hit South Africa later than much of the developed world, but which during 2009–2011 saw South Africa lose approximately 1 million jobs (mainly in the informal sector and among domestic workers)—thus while ‘work’ is the lowest dimension, it is positive to see that it made a tiny incremental gain from 0.43 to 0.44.

Looking at the index more broadly, what pushes scores up between 2009 and 2011 seem to be infrastructural and other delivery projects driven primarily by government: ‘infrastructure’ stayed constant as the highest scoring dimension at 0.78, but ‘dwelling’ rose (as the housing programme gathered momentum) from 0.7 to 0.78, ‘connectivity’ rose by 0.02, and even security improved, despite South Africa’s poor global reputation in this area. Some of these improvements may have been triggered by the massive government investments around the 2010 FIFA World Cup (which included, for example, ‘World Cup courts to ensure instant ‘justice’ for anyone caught committing crime), given that the GCR had three stadia hosting games including the opening and final matches, and the requisite infrastructure had to be provided. Whatever the case, it is important to note that while these primarily ‘hard’ delivery areas rose, they include both objective and subjective indicators—infrastructure includes self-reported responses on water cleanliness and a perceived improvement in locale, for example—and so the index is not measuring merely ‘bricks and mortar’, but also respondents’ perceptions of what those deliverables mean in their lives.

It is notable that ‘global’—which refers to an all-round sense of well-being and includes alienation and anomie measures, as well as a sense of whether the country is heading in the wrong or right direction—also dropped, quite significantly, reflecting the general findings of this survey, namely a very low mood in the GCR. This is reflected in slightly lower scores for both family and community as well. Generally, psycho-social and work-related variables pulled the scores down. What the index suggests is that many of the areas in which local, provincial and national government work, have improved; but many of the less development-oriented issues, such as psycho-social and ‘headspace’ areas, deteriorated. This strongly suggests that the hoped-for transformative power of meeting basic needs providing dignity, and in turn psycho-social healing, is misplaced. People are receiving goods and services, and are happy about them; but they remain deeply scarred about race, deeply alienated and anomic, and without direct intervention in these more complex areas—the provision of psychological services at a mass scale (or at least at community level)—we may well find this dichotomous situation is true (or worse) in the 2013 iteration of this survey.

This is important to bear in mind, because when the quality of life is tabulated as an overall score, the Gauteng City-Region fares pretty well. Once the 10 dimensions were added together, the mean or average score across all respondents and all dimensions was 6.24 in 2009, but dropped to 6.1 in 2011 (some of the possible reasons for this were explained above).

In both instances, it is immediately apparent that very few respondents score very badly—no-one scored below 1.75 (out of 10) at all, suggesting that while there are indeed challenges in the social domain, they are balanced against important tangible benefits. Put simply, delivery of services may not be transforming the mind-sets of respondents, but is nonetheless having a positive impact on their overall quality of life. However, it is also apparent that there is enormous inequality in the GCR, given that there are respondents scoring just below 10 on the index.

By analysing the data spatially, at sub-provincial level, it is also clear that the overall scores mask significant differences. The overall trend was downwards, almost across the board—only smaller, and generally poorer municipalities (such as Westonaria and Randfontein) saw their scores rise. In large part, the recession and low mood seem to have lowered scores across the GCR. What is apparent is that two of the three cities—Johannesburg and Tshwane—started high, and with the drop in scores, stayed towards the upper end of the scale. Ekurhuleni, the third metropolitan municipality, started low, unsurprising, given the impact of the global recession on this manufacturing heart of the GCR. Two points in time do not allow for any attempt at trend analysis, but the key question to ask once the 2013 data are ready will be: are the cities able to consolidate themselves as offering the highest overall quality of life, or will the peripheral municipalities take their place? (Fig. 3).
Fig. 3

Quality of Life by municipality, 2009 and 2011 (Source: GCRO Quality of Life surveys)

Finally, there are wide variations across the respondents who fell between the highest (at 9.55 out of 10) and lowest (1.75 out of 10), in both years. To make some sense of the data, we followed the natural breaks in the data, providing four categories. Respondents scoring 8 out of 10 or above were taken to have “high” quality of life. Although an important part of the GCR, this ‘high’ category comprised just 5.8 % of the sample in 2011—meaning one in twenty people then enjoyed high quality of life. The second highest category included the largest proportion of respondents, namely 46.9 % who had what we labelled “good” quality of life in 2011—this was taken to be from immediately above the sample mean (6.11—the mean was 6.1) to immediately below the 8/10 cut off for high, so they fell between 6.11 and 7.99 out of 10. Taken overall, therefore, the GCR can reflect positively on the fact that despite the global crisis and its domestic aftershocks, 53 % of respondents in 2011 were enjoying high or good quality of life.

At the other end of the scale, using 2011 scores (simply because they are the most recent) we find another dichotomy, between those with ‘below average’ quality of life and those with ‘poor’ quality of life. The first category are those scoring 6.0 (i.e. immediately below the mean score) down to those scoring half, or 5 out of 10. This category accounted a third (32.5 %) of respondents, leaving 14.8 % to score in the ‘poor’ category—i.e. everyone below 5 out of 10. Anywhere from 1.75 out of 10 (the lowest score in the sample) to 4.99 out of 10. The extremes of the scale see more people with “poor” than “high” quality of life—perhaps not surprising, given the fact that South African democracy is just 20 years old. The positive point—assuming over time the trend continues—is, as noted above, the fact that taken as a whole, the majority of respondents enjoy “high” or “good” quality of life.

Given our post-apartheid context, it is important to note that when the data are analysed by race, three times as many whites (13 % of white respondents) enjoy high quality of life as do Africans (4 %). In the middle, slightly more coloureds (8 %) enjoy high quality of life than Indians (7 %). Whites, coloureds and Indians are also more likely to have ‘”good” quality of life. The divide and rule strategy of the apartheid regime has left deep roots in the South African fabric.

Sex also makes a difference. More men (7 %) enjoy high (5 %) and good quality life than women (45 and 35 % respectively). Quality of life is as gendered as the society in which it is located. Most telling perhaps is the sad finding that while money may not buy you love, it does buy quality of life. Just 3 respondents had no regular source of income but high quality of life, while 75 % had poor or below average quality of life. At the other extreme, no-one with a monthly average household income of R102 401 (at the time of writing, equivalent to US$9 600) and above had poor quality of life, while 85 % had good or high quality of life.

7 Conclusion

Quality of life as measured by the GCRO seeks to provide holistic reflection of society. It does so by combining objective and subjective indicators, in the belief that real quality of life must include both access to goods and services and robust psycho-social values and attitudes.

While the majority of respondents in both 2009 and 2011 surveys enjoyed “good” or “high” quality of life, but whites, coloureds, Indians; and men, were over-represented in these categories. At the Bad” and “poor” end of the scale, Africans and women were over-represented.

Finally, the data strongly suggest that service delivery will not, in and of itself, knit together a rent social fabric. Scores on the quality of lie matrix are pushed up by the welcome delivery of services to people formerly denied them because of their race; but they do not magically transform the psycho-social damage of apartheid, and knit together non-racial communities. Rather, dimensions dealing with ‘headspace’, social capital and life satisfaction pull the overall scores downwards. As such, there is a clear message for the governments in the GCR: service delivery cannot be restricted to bricks and mortar. Interventions are urgently needed to provide individual and communal support and healing, in order to ensure that holistic quality of life is available equally to all in the Gauteng City-Region.

Footnotes

  1. 1.

    According to a recent South African Press Association release quoting police figures: "Gauteng police had dealt with 569 protest marches in the last 3 months, of which 122 were violent." (Quintal 2014).

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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.School of GovernanceJohannesburgSouth Africa

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