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 of residents within the province. The Quality of Life Index is 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 has declined from 64 to 60 on a 100-point index 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). It is important to not only focus on the objective measures of quality of life, but also focus on the subjective measures, such as life satisfaction. Research shows that happiness (life satisfaction) is associated with factors that are essential for success in life (De Neve et al., 2013). This Map of the Month narrows its focus to the subjective dimension, and specifically, life satisfaction.

Life satisfaction, often used interchangeably with happiness, reflects individuals' subjective assessment of their lives. In this context, life satisfaction serves as an indicator of subjective quality of life. Literature reveals that even though most people report being satisfied, levels of life satisfaction are not equal (Veenhoven, 1996). We observe similar patterns in Gauteng, discussed below.

Life satisfaction index

Data from the GCRO Quality of Life Survey 7 (2023/24), or QoL 7, was used for this Map of the Month. Here, life satisfaction is derived from responses to five questions:

‘How satisfied or dissatisfied are you with the following parts of your life?’:

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. How satisfied are you with your standard of living?
5. Leisure time - recreation, relaxation, etc.?

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 and 4 means very satisfied. Scores across the five questions were summed and multiplied by five to produce a total score out of 100. The average (mean) life satisfaction was then calculated for each ward in Gauteng. Each of the five variables contributes a total of 20 points to the overall life satisfaction index.

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

Figure 1 above shows that all variables that make up the life satisfaction index 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 deceases of 0.7 and 1.3, respectively. The lowest-performing variables in the index are satisfaction with satisfaction of living (11.1 points), time (11.6 points) and leisure time (12.4 points), while the best-performing variables include satisfaction with friends (13.5 points) and family time (13.2). These results show that the decline in the overall life satisfaction index is not driven by a single variable but sustained decreases across both satisfaction with material conditions (standard of living) and satisfaction with relational or time-related aspects of life.

Figure 2: Average life satisfaction over time by population group

The QoL data highlights how life satisfaction has shifted over time across different population groups, as seen in Figure 2 above. 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 Gauteng average thus declined from a high of 68.4 in 2015/16 to a low of 61.8 in 2023/24.

The scores for the different population groups are aligned to their socioeconomic status and average standards of living (Modiba et al., 2024), with whites being the only group to maintain their scores at 70 and above. Indian/Asians started at very close scores with whites at 76.9 and 77.1, respectively, but experienced a greater decline in subsequent iterations of the survey. Their final score for 2023/24 was 67.8, meaning that their average life satisfaction was 2 points lower than that of white in 2023/24, despite being almost identical in 2015/16. Average life satisfaction for coloureds and black Africans declined to the low-60s, at 63.7 and 60.4, respectively, which indicated moderate life satisfaction that was tempered by comparatively lower socioeconomic positions.

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 average life satisfaction scores.

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 central townships and inner city spaces. wards in predominantly black African townships and low-income settlements such as Stinkwater and Hammanskraal in the far north-west, Orange Farm and Vosloorus in the south, and Riverlea (a coloured township) show lower levels of life satisfaction at a score <57.1. While wards in suburbs such as Irene, Hillshaven, and Southdene, as well as Ladium (an indian township), experience high life satisfaction by a combination of a subjective view of their standard of living, social interaction, and leisure time.

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 (COVID-19 period) and 2023/24 (post-COVID). Dark blue indicates magnitudes of increased life satisfaction between the two periods, while orange indicates magnitudes of decreased life satisfaction between the two periods.

Large declines in life satisfaction (greater -8.3) can be seen across all municipalities. 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 at < -8.3. 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, Ga-Rankuwa and Winterveld. While, some areas such as those near Pretoria, Olivenhoutbos and Little Falls 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). Moreover, mainly white and Indian areas also recorded an improvement in life satisfaction in the period under review (like Laudium and Pretoria East).

Figure 4: Difference in life satisfaction across wards in Gauteng

Figure 5: Average life satisfaction score by different variables

The QoL data enables a more nuanced understanding of life satisfaction when the score is averaged (mean) by variables such as demographics, economic status and subjective experiences, as shown in Figure 5 above.

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. This demonstrates profound despair at being unemployed. 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).

Residents who were satisfied with the performance of their local municipality scored on average higher (65.9) compared to those who were dissatisfied (60.3). Those who felt a sense of belonging in their area displayed a higher average life satisfaction score (64.4), which is 10.1 points higher than those who did not (54.3). 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).

Conclusion

The level of life satisfaction across Gauteng is not evenly distributed. It varies according to location, socioeconomic conditions, demographic characteristics and subjective experiences. While the overall quality of life in the province has declined in recent years, this Map of the Month highlights how specific locations might have still experienced an increase in life satisfaction. This also offers a more personal lens into residents’ subjective experiences, which shows that material conditions alone do not determine how people evaluate their lives.

Spatially, these findings reveal that residents in rural peripheral wards and suburban areas with higher standards of living reported higher levels of satisfaction. At the same time, townships and poorer settlements reflect deeper levels of dissatisfaction. 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.

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.

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

De Neve, J., Diener, E., Tay, L., & Xuereb, C. (2013). The objective benefits of subjective well-being. In J. Helliwell, R. Layard, & J. Sachs (Eds.), World happiness report 2013 (pp.54–79). UN Sustainable Development Solutions Network.

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GCRO (Gauteng City-Region Observatory). (2019). Quality of Life Survey V (2017/18) [Dataset]. Version 1.1. Johannesburg and Cape Town: GCRO & DataFirst. https://doi.org/10.25828/8yf7-9261

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

GCRO (Gauteng City-Region Observatory). (2024). Quality of Life Survey 7 (2023/24) [Dataset]. Version 1. Johannesburg and Cape Town: GCRO & DataFirst. https://doi.org/10.25828/v2ky-v879

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

Modiba, M., Hassen, E.–K., Labuschagne, H., Masinga, K., Radebe, M., Tladi, M., Erasmus, L., Nemavunde, M., Fani, N., Masango, B., & Machika, C. (2024, October). Inclusive economies: Findings from the GCRO’s Quality of Life Survey 7 (2023/24). Gauteng City-Region Observatory. https://doi.org/10.36634/BNCK6336

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