Geography of contentment: Life satisfaction across wards in Gauteng

Introduction

The Gauteng City-Region Observatory (GCRO) has previously produced analyses examining the overall quality of life for residents within the province (Naidoo, et al. 2024). A Quality of Life Index has been developed based on 33 objective and subjective indicators across seven dimensions: health, life satisfaction, government satisfaction, participation, safety, services, and socioeconomic status (Katumba et al., 2022). The Quality of Life Index score – measured on a 100 point scale – has declined from 64 to 60 between 2017/18 and 2023/24 (Naidoo et al., 2024).

Quality of life can broadly be divided into two components: objective well-being (material conditions and access to services) and subjective well-being (how people evaluate their lives). This Map of the Month narrows its focus to subjective factors, and specifically a set of indicators that make up the ‘life satisfaction’ dimension of the Quality of Life Index.

Literature emphasizes that it is important to not only focus on the objective measures of quality of life. Subjective factors must also be considered. Individuals' subjective assessment of their lives – how they perceive themselves and regard themselves in relation to others – is often referred to as ‘life satisfaction’. Research has shown that how satisfied people are with their lives, or their level of happiness, is essential for their success in life (De Neve et al., 2013). Globally, analyses of subjective Quality of Life measures have indicated that most people report being happy, but that levels of life satisfaction are not equal (Veenhoven, 1996). We observe similar patterns in Gauteng.

Life satisfaction index

This Map of the Month used data from the GCRO’s Quality of Life Survey 7 (2023/24) (QoL 7), in comparison to Quality of Life 6 (2020/21) (QoL 6) results. In the Quality of Life Survey, life satisfaction is derived from responses to five questions:

The survey asks four questions that relate to personal time and relations with loved ones who might be expected to provide emotional connection and support, as follow: How satisfied or dissatisfied are you with:

(1) Time – the amount of time you have to do the things you want to?

(2) Family life – the time you spend with them and the things you do with them?

(3) Friends – how satisfied are you with your friends?

(4) Leisure time – recreation, relaxation, etc.?

In the ‘life satisfaction’ dimension of the QoL Index these are then combined with another broad question: (5) How satisfied are you with your standard of living?

For each question, respondents rated their satisfaction on a five-point Likert scale, where 1 indicated ‘very satisfied’ and 5 indicated ‘very dissatisfied’. To ensure that higher scores reflect higher levels of satisfaction, the scale was reversed and recoded so that 0 means very dissatisfied to 4 means very satisfied. Each of the five question scores was multiplied by five (contributing up to 20 points to the overall life satisfaction score), and the values were then summed to produce a life satisfaction score out of 100. The average (mean) life satisfaction was then calculated for each ward in Gauteng.

Figure 1: Life satisfaction variables over time (ranging from 0 to 20 points).

Figure 1 above shows the results over time for the five variables that make up the life satisfaction index. The lowest-performing variables in the index are satisfaction with standard of living (11.1 points in 2017/18), time (11.6 points) and leisure time (12.4 points), while the best-performing variables are satisfaction with friends (13.5 points) and family time (13.2).

The figure makes it clear that subjective well being as measured by all five variables declined between 2015/16 and 2023/24. Overall, the largest decline from 2015/16 to 2023/24 was in satisfaction with family time (-2.1 points), followed by standard of living (-1.6 points) and leisure time (-1.3 points). Across the entire period, only three instances of increases in life satisfaction variables were observed: in 2017/18, where both leisure time and time saw an improvement; and in 2023/24 where satisfaction with friends improved by 0.1 points compared to 2020/21. The largest decline in satisfaction with family occurred between 2015/16 and 2017/18, decreasing by 1.4 points. For both time and leisure time, the biggest declines were recorded between 2017/18 and 2020/21, decreasing by 0.9 and 0.7 respectively. Satisfaction with friends and standard of living declined the most between 2015/16 and 2017/18 with decreases of 0.7 and 1.3 respectively.

These results show that the decline in overall life satisfaction is not driven by a single variable but sustained decreases across all aspects of this well-being index.

Figure 2: Average life satisfaction over time by population group

The QoL data can also be disaggregated to show how life satisfaction has shifted over time across different population groups. As seen in Figure 2, with all five variable scores added together, the Gauteng average declined from a high of 68.4 in 2015/16 to a low of 61.8 in 2023/24. All population groups experienced a sharp decline between QoL 4 (2015/16) and QoL 5 (2017/18), and continued a downward trajectory for the next two surveys in 2020/21 and 2023/24.

The scores for the different population groups are aligned to their commonly understood socioeconomic status, with whites being the only group to maintain scores at 70 and above. Indian/Asians started with scores close to those for whites at 76.9 and 77.1 respectively, but despite this almost identical starting position, experienced a greater decline in subsequent iterations of the survey, dropping to 2 points lower than whites in 2023/24. Average life satisfaction for coloureds and Africans declined to the low-60s, at 63.7 and 60.4 respectively.

Average life satisfaction per ward

Figure 3 below illustrates the spatial distribution of average life satisfaction scores across wards in Gauteng. Darker shades of green indicate higher life satisfaction scores, based on a maximum index score of 100.

Life satisfaction varies quite substantially across wards in Gauteng. A total of 214 wards (40%) scored above 63.4 points. Many of these higher-scoring wards are located in central areas such as Irene, Laudium and Jukskei Park, in southern areas such as Ratanda, and in peripheral areas such as Bronkhurstspruit and Rayton.

The picture in Gauteng’s urban core is relatively even, but lower scores are seen in certain centrally located townships and inner city spaces. Wards in predominantly African townships and low-income settlements show lower levels of life satisfaction at a score <57. Examples include Stinkwater and Hammanskraal in the far north-west, Orange Farm and Vosloorus in the south, and Riverlea (a coloured township)1. Wards in suburbs such as Irene, Hillshaven, and Southdene as well as Ladium (an Indian township) experience very high life satisfaction.

Figure 3: Life satisfaction across wards in Gauteng, mapped using the average life satisfaction score per ward (ranging from 0 to 100 points).

Spatial patterns of changes in life satisfaction scores within wards

Figure 4 below illustrates the spatial variability of changes to life satisfaction scores between 2020/21 (the COVID-19 period) and 2023/24 (post-COVID). Darker shades of blue indicate magnitudes of increased life satisfaction between the two periods, while shades of orange indicate magnitudes of decreased life satisfaction between the two periods.

Large declines in life satisfaction can be seen in parts of all municipalities in Gauteng. Notable clusters appear in north-western parts of Tshwane, the south-western parts of the West Rand District, the central areas of the Sedibeng District, central Johannesburg, and various parts of Ekurhuleni. The Emfuleni Local Municipality experienced the most dramatic decline in life satisfaction between 2020/21 and 2023/24, with many wards showing greater than -8.3 point changes. Emfuleni also records the lowest levels of satisfaction with local, provincial and national government, the lowest proportion of residents who perceive their water to always be clean, the highest proportion experiencing water interruptions, and high levels of dissatisfaction with basic services (Tshuma et al., 2025). In this case, poor life satisfaction may be driven by the dire conditions caused by extremely poor delivery of basic services.

A similar decline in life satisfaction is evident in areas of the far north-west. These include Hammanskraal and Stinkwater and the adjacent areas of Mabopane, Garankuwa and Winterveld. Some areas such as Aracdia and Olivenhoutbos experienced very little change in life satisfaction scores.

The largest increase in life satisfaction between 2020/21 and 2023/24 was in the large rural wards of Gauteng’s periphery (around Magaliesburg, Rayton and Bronkhorstspruit). Particular white and Indian areas also recorded an improvement in life satisfaction over the period, notably Laudium and Pretoria East.

Figure 4: Spatial variability in changing life satisfaction across wards in Gauteng between 2020/21 and 2023/24

Figure 5: Average life satisfaction score by different variables

The QoL data enables a more nuanced understanding of life satisfaction when the mean score is cross-tabulated by variables reflecting demographics, economic status and other subjective well-being indicators, as shown in Figure 5 above.

Again, as seen above in figures 2 and 3 above, the score for life satisfaction for whites is 70.0, while the score for Africans is just under ten points lower at 60.4.

Individuals who are not economically active (this includes those who do not need or want to work, are disabled, homemakers, unpaid caregivers, students, or retired/pensioners) have the highest average life satisfaction score of 67.5, while unemployed individuals displayed the lowest score of 59.7. In the same vein, those individuals with household incomes of R51 201 or more scored on average higher (68.5), while the lowest income (R1- R1 600) group had the lowest average score (57.0). People who find it easy to save money displayed a higher life satisfaction score (74.1), which is 15.2 points higher than those who find it impossible to save (58.9).

While measures of life satisfaction clearly correlate with socio-economic circumstances, material conditions are not the only consideration. Indeed it is noteworthy that the unemployed (both those still looking for work and those discouraged) did not have dramatically worse life satisfaction scores than those working. There are in fact larger differences in measured life satisfaction between those showing positive and negative outcomes on other indicators of subjective well-being.

Those who felt a sense of belonging in their area displayed a higher average life satisfaction score (64.4) – more than 10 points higher – than those who did not (54.3) feel like they belonged. People who felt they could express their feelings and confide in their families displayed higher average life satisfaction scores (62.9 and 63.0, respectively), compared to those who felt they could not (54.4 and 45.9). Residents who felt satisfied with the performance of their local municipality scored on average higher (65.9) compared to those who were dissatisfied (60.3). These variations are fascinating. While an analysis that traces causal co-determination is beyond the scope here, the difference may suggest that material conditions are not the only determinants of personal life satisfaction.

Conclusion

By focusing on life satisfaction, this Map of the Month provides a view into the subjective well-being of Gauteng’s residents. It reminds policymakers and planners that improving the lives of residents requires more than a focus on objective measures.

The analysis has shown that the level of life satisfaction across Gauteng is not evenly distributed. It varies according to location, socioeconomic conditions, demographic characteristics and also subjective experiences.

Seen spatially, the data indicates that residents in rural peripheral wards and suburban areas with higher standards of living reported higher levels of life satisfaction. At the same time, townships and poorer settlements reflect deeper levels of dissatisfaction. While there has been an overall decline in measured life satisfaction over the last decade, this Map of the Month also highlights how specific locations have experienced greater than average decreases, while others – not only those known to be wealthier – have seen unexpected gains.

The data also shows that mean scores on our life satisfaction vary considerably by positive and negative outcomes on other indicators of subjective well-being, more so even than on objective factors such as employment. Put simply, material conditions alone do not determine how people evaluate their lives. These findings underline the importance of not only addressing service delivery and economic challenges but also subjective measures such as community belonging and emotional support.

Note of methods

This analysis is based on data from the QoL 7 (2023/24), QoL 6 (2020/21), QoL 5 (2017/18) and QoL 4 (2015/16). All analyses were conducted in SPSS Version 30.0.0.0 and results were exported to Datawrapper for mapping and line graphs. Datawrapper is an online-based data visualisation tool that interactively presents information in the form of maps, charts and tables.

References

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GCRO (Gauteng City-Region Observatory). (2021). Quality of Life Survey 6 (2020/21) [Dataset]. Version 1. Johannesburg and Cape Town: GCRO & DataFirst. https://doi.org/10.25828/wemz-vf31

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Katumba, S., de Kadt, J., Orkin, M., & Fatti, P. (2022). Construction of a reflective quality of life index for Gauteng Province in South Africa. Social Indicators Research, 164(1), 373–408. https://doi.org/10.1007/s11205-022-02945-2

Naidoo, Y., Mahamuza, P. and Naidoo, L. (2024). Quality of life and wellbeing: Findings from the GCRO's Quality of Life Survey 7 (2023/24). GCRO Data Brief 25, October 2024 https://doi.org/10.36634/PJCA9220

Tshuma, N., Simelane, X., Hamann, C., Miles-Timotheus, S., & Naidoo, Y. (2025, June). Municipal benchmarking report: Findings from the GCRO’s Quality of Life Survey 7 (2023/24). Gauteng City-Region Observatory. https://doi.org/10.36634/RFNO2431

Veenhoven, R. (1996). The study of life satisfaction. In W. E. Saris, R. Veenhoven, A. C. Scherpenzeel, & B. Bunting (Eds.), A comparative study of satisfaction with life in Europe (pp. 11–48). Eötvös University Press.

Cartography/mapping: Shamsunisaa Miles-Timotheus and Christian Hamann

Inputs, edits, and comments: Christian Hamann, Graeme Götz, Dr Laven Naidoo and Dr Samkelisiwe Khanyile

Suggested citation: Seedat, R., & Miles-Timothues, S. (2025). Geography of contentment: Life satisfaction across wards in Gauteng. GCRO Map of the Month, November 2025. Gauteng City-Region Observatory, Johannesburg. https://doi.org/10.36634/BAVH7282