Demographic Determinants of Financial Stress and Well-Being in South Africa: Evidence from a Longitudinal Panel (2019–2021)

Demographic Determinants of Financial Stress and Well-Being in South Africa: Evidence from a Longitudinal Panel (2019–2021) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Demographic Determinants of Financial Stress and Well-Being in South Africa: Evidence from a Longitudinal Panel (2019–2021) Leon Steyn, Prof Surika Rooyen, Jaco Fouché, Morris Mensah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7571480/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Financial stress (FS) and financial well-being (FWB) are experienced unevenly across South Africa’s demographic and geographic groups, with the COVID-19 pandemic further deepening these disparities. This study investigates how FS and FWB changed over a three-year period (2019–2021) across five key demographic variables: age, income, gender, relationship status, and province of residence. It also examines the exacerbating effects of the COVID-19 pandemic on these trends. Using a longitudinal panel design, the study analysed data from the Old Mutual Rewards Program survey. In total, 6,713 individuals were assessed annually for FS and 2,923 for FWB. Statistical analyses, including ANOVA, Welch’s test, and post hoc comparisons, were used to assess group differences, which showed significant relationships between all five demographic variables and both FS and FWB scores. Younger adults, lower-income earners, women, single individuals, and residents of many economically marginalised provinces reported higher FS and lower FWB. The findings highlight the need for financial interventions and policy measures, such as youth-focused financial literacy programs, gender-equitable employment policies, and geographically tailored social protections. By incorporating longitudinal evidence, this study contributes to both the theoretical understanding and practical design of strategies aimed at improving financial resilience in the context of inequality and crises. Health sciences/Health care Biological sciences/Psychology Social science/Psychology financial stress financial well-being COVID-19 pandemic socioeconomic inequality demographic disparities South Africa 1. Introduction Financial stress (FS) and financial well-being (FWB) are increasingly recognised as central determinants of individual welfare, influencing not only household financial behaviour but also broader psychological and health outcomes (Kim et al. 2020 ; Netemeyer et al. 2018 ). FS reflects the psychological burden experienced when financial obligations exceed accessible resources, while FWB captures an individual’s perceived ability to manage day-to-day finances, absorb shocks, and feel secure about the future (CFPB 2015 ). While conceptually distinct, these constructs are interdependent and shaped by structural and demographic contexts. In South Africa, a country characterised by inequality and economic volatility, FS and FWB are shaped by structural determinants such as income level, gender, age, relationship status, and geographic location (Stats SA 2021 ; Burger et al. 2017). Younger individuals, for instance, face FS due to unemployment and educational debt, while older adults may benefit from accumulated savings and stable income (Collins & Urban 2019; Mantai & Marrone 2023 ). Income, in particular, remains one of the predictors of both FS and FWB, with low-income earners susceptible to financial insecurity and lacking access to financial tools and credit (Joo & Grable 2004 ; Cwynar et al. 2020 ). Gendered dimensions also compound financial vulnerability. South African women continue to face wage disparities, caregiving burdens, and overrepresentation in informal and low-paying sectors, all of which exacerbate FS and limit FWB (Mosomi 2019 ; Casale & Posel 2020 ). Similarly, marital status influences financial resilience, with married individuals more likely to benefit from income pooling and support systems compared to single, widowed, or divorced persons (Brown 2010; Falconier & Jackson 2020 ). Furthermore, provincial disparities reflect entrenched spatial inequalities: urbanised provinces such as Gauteng and Western Cape report better FS and FWB outcomes relative to economically marginalised areas such as Eastern Cape and Limpopo (Visagie & Turok 2021 ;Finscope 2019). The onset of COVID-19 has intensified pre-existing inequalities. Lockdowns, job losses, and informal sector disruptions disproportionately affect low-income earners, youth, and female populations already vulnerable to FS (UNISA 2022 ; Van der Berg et al. 2020). Despite temporary relief efforts, the crisis exposed weaknesses in South Africa’s social protection infrastructure, especially in rural and underserved areas (UN 2021). Although global studies have examined FS and FWB through various cross-sectional lenses (Lusardi & Mitchell 2014 ; Brüggen et al., 2017 ), few have tracked how these measures evolve over time, especially within emerging economies. In South Africa, the predominant use of one-off data collection hampers the ability to assess financial trajectories and resilience over time (Caruana et al. 2015 ). This study addresses these gaps by utilising a longitudinal dataset (2019–2021) to examine how FS and FWB have evolved across key demographic groups before and during the pandemic. Through a panel analysis of over 6,000 (FS) and 2,000 (FWB) respondents, this study explores how structural determinants shape individual responses to financial shocks and identifies the most affected groups. By linking empirical insights with theoretical frameworks such as the Social Determinants of Health (SDH) and Life-Cycle Theory, this research not only contributes to academic literature but also informs policy interventions aimed at enhancing financial resilience in both stable and crisis contexts. 2. Literature Review and Hypothesis Development 2.1 Financial Stress and Financial Well-being Financial stress (FS) occurs when individuals face difficulties in meeting their daily financial obligations such as paying bills, managing debt, or covering essential living expenses. This condition often leads to anxiety and emotional distress, impacting both mental and physical health (Kim et al. 2020 ; Consumer Financial Protection Bureau [CFPB] 2015 ). Financial stress is commonly triggered by factors such as income volatility, unexpected expenses, insufficient savings, or overwhelming debt burdens, which together can contribute to a state of financial insecurity (Lusardi & Mitchell 2014 ). In contrast, financial well-being (FWB) is understood as a holistic state reflecting an individual's ability to effectively manage their financial resources, maintain control over daily finances, and feel confident about their current and future financial situations (Netemeyer et al. 2018 ). The Consumer Financial Protection Bureau (2015) defines FWB as having sufficient financial resources to meet ongoing expenses, absorb financial shocks, make choices that allow enjoyment of life, and plan for long-term financial goals. The key components of FWB include a sense of financial security, the capacity to handle unexpected financial setbacks without severe hardship, and a positive outlook toward future financial stability (Brüggen et al. 2017 ). Research has highlighted the inverse relationship between FS and FWB, where higher levels of financial stress correlate with lower perceptions of financial well-being, and vice versa (Kim et al. 2020 ). Furthermore, fostering financial literacy, access to financial products, and supportive social policies can enhance FWB and reduce FS among various populations (Lusardi & Mitchell 2014 ; Xiao, Chen & Sun 2014). FS and FWB are shaped by various demographic factors, such as age, income, gender, relationship status, and residential province (Stats SA 2022 ). 2.1.1 Age and Financial Outcomes Younger individuals are more likely to experience financial stress (FS), particularly because they are early in their careers, often earn lower incomes, and have not yet accumulated substantial savings (Collins & Urban 2019; Kempson et al. 2017 ). Many also carry the additional burden of student debt and navigate the challenges of financial independence for the first time (Mantai & Marrone 2023 ). According to Collins and Urban (2019), financial well-being (FWB) tends to follow a lifecycle pattern, initially decreasing in early adulthood because of mounting financial responsibilities and constrained earning potential, and then gradually improving as individuals gain stability through work experience, career advancement, and asset accumulation. Kempson et al. ( 2017 ) similarly argue that older individuals generally experience higher FWB due to increased access to financial capital and more established saving habits. These findings are consistent with South African earnings data, where older individuals tend to earn more and exhibit higher financial resilience (Stats SA 2016 ; SAHRC 2017). Moreover, Mantai and Marrone ( 2023 ) described early career stages as marked by exploration and skill development, which, though important, may involve unstable income. In contrast, later stages offer more financial security due to accumulated assets, although challenges like age-based discrimination and career plateauing may arise (Coetzee & Stoltz 2015 ). This life-cycle view provides a meaningful framework to understand how age intersects with both FS and FWB over time. H1 There is a significant relationship between age and financial stress. H2 There is a significant relationship between age and financial well-being. 2.1.2 Income and Financial Outcomes Income is one of the strongest predictors of FS and FWB. Research has consistently shown that lower-income individuals are more likely to experience financial instability, limited access to credit, and difficulty in recovering from economic shocks (Kim & Garman 2003; Joo & Grable 2004 ; Cwynar et al. 2020 ). In contrast, higher-income individuals often benefit from financial buffers, including savings, insurance, and investment portfolios, which provide greater security and improve FWB. South Africa’s high-income inequality, reflected in a Gini coefficient of 0.63, underscores the structural disparities that shape financial outcomes (World Bank 2018 ). The COVID-19 pandemic intensified these disparities. Lower-income earners, many of whom worked in informal or vulnerable sectors, were disproportionately affected by job losses, reduced hours, and income instability (Rogan & Skinner 2020 ). Lacking sufficient savings or safety nets, these individuals experienced heightened FS and a decline in FWB (Kansiime et al. 2021 ). On the other hand, higher-income groups are often able to transition to remote work, maintain stable earnings, and draw on savings or investments to navigate crises (Sabri & Sakaria 2013). These patterns highlight the protective role of income in managing daily expenses and unexpected financial disruptions. H3 There is a significant relationship between income and financial stress. H4 There is a significant relationship between income and financial well-being. 2.1.3 Gender and Financial Outcomes Gender differences in FS and FWB are well documented in both South African and global research. Women consistently face greater financial vulnerability due to wage disparities, occupational segregation, and caregiving responsibilities (Mosomi 2019 ; Casale & Posel 2020 ). According to Stats SA ( 2023 ), women are overrepresented in precarious employment, have less access to paid benefits, and are less likely to be unionised. These factors contribute to the persistent gender gaps in earnings and financial security. The COVID-19 pandemic exacerbated these existing inequalities. Women, particularly those working in the retail, hospitality, and domestic sectors, are disproportionately affected by lockdown-related job losses (Stats SA 2021 ). Simultaneously, school closures and increased care needs place an additional burden on women, reducing their availability for paid work (UN 2021). Moreover, barriers to accessing credit and financial services further restrict women's financial resilience (Finscope South Africa 2019 ). These compounding challenges contribute to a higher FS and lower FWB among women, particularly during economic crises. H5 There is a significant relationship between gender and financial stress. H6 There is a significant relationship between gender and financial well-being. 2.1.4 Relationship Status and Financial Outcomes Relationship status plays a critical role in shaping financial outcomes. Married individuals tend to experience better FWB, and lower FS compared to single, divorced, or widowed individuals. This is often due to shared expenses, dual incomes, and mutual financial support, which enhance financial stability and reduce vulnerability during times of economic strain (Brown 2010; Addo & Lichter 2013 ; Joo 2008 ; Falconier & Jackson 2020 ). Conversely, single individuals frequently bear full financial responsibility and may lack the informal safety net provided by the partnership. Single-parent households, particularly those headed by women, are especially vulnerable because of the dual burden of caregiving and earning income (Posel & Rogan 2012 ; Adams-Prassl et al. 2020 ; Blundell et al. 2020 ). In South Africa, cultural practices such as lobola and extended family obligations further shape financial outcomes for married couples and may introduce additional pressure (IOL 2023 ; My Afrika Mag 2023 ; Yarbrough 2021 ). During crises such as COVID-19, these financial dynamics become even more pronounced, with partnered individuals more likely to access joint resources, while that alone face increased exposure to FS. H7 There is a significant relationship between relationship status and financial stress. H8 There is a significant relationship between relationship status and financial well-being. 2.1.5 Province and Financial Outcomes Geographic location also influences FS and FWB because of disparities in infrastructure, job availability, and access to services across South Africa’s provinces. Economically developed provinces, such as Gauteng and the Western Cape offer more employment opportunities and financial institutions, contributing to improved FWB and reduced FS among residents (Stats SA 2019 ; Visagie & Turok 2021 ). In contrast, provinces such as the Eastern Cape, Limpopo, and Free State struggle with higher unemployment, limited infrastructure, and weaker access to formal financial systems, resulting in more financial hardship (Burger et al. 2017; Finscope 2019). The urban-rural divide further complicates financial outcomes. Urban residents may benefit from better job prospects and services but also face higher living costs. Meanwhile, rural residents encounter lower costs of living but lack stable income opportunities, exacerbating FS (Tacoli et al. 2015 ). The pandemic has worsened these regional disparities, with some provinces experiencing delayed recovery and insufficient health and social service infrastructure (Rogerson & Rogerson 2020 ; Venter et al. 2020 ). These conditions demonstrate how spatial inequality in South Africa continues to shape divergent financial experiences across different geographic regions. H9 There is a significant relationship between province of residence and financial stress H10 There is a significant relationship between province of residence and financial well-being 3. Theoretical Framework 3.1 Social Determinants of Health (SDH) The SDH framework recognises that health and well-being outcomes are shaped by the environments in which people are born, grow, live, work, and age (WHO 2008). These determinants include income, education, employment, social support, and access to healthcare, factors that are not only relevant to health but also to financial stress and financial well-being (Braveman et al. 2011 ). FS, as a chronic source of stress, can have substantial mental and physical health consequences, including depression, anxiety, hypertension, and cardiovascular disease (Marmot et al. 2008 ). The American Psychological Association (APA 2021) highlights FS as one of the most commonly reported stressors affecting behaviour and lifestyle choices. Individuals experiencing FS are less likely to engage in preventive health behaviours and are more likely to resort to harmful coping mechanisms, such as substance use or poor dietary habits (Adler & Newman 2002 ). From an SDH perspective, FWB is not merely the absence of FS but also includes positive factors such as financial literacy, stable income, and access to financial tools that support effective decision-making and resilience (Lusardi & Mitchell 2014 ). Social capital and networks also play a critical buffering role in managing financial hardships (Umberson & Montes 2010 ; Kawachi & Berkman 2000 ). In communities with strong support systems, individuals are often better equipped to withstand financial shocks through informal lending, shared resources, or collective caregiving. Economic inequality, a core focus within the SDH framework, is particularly relevant in the South African context, where structural disparities in income, education, and employment persist. Individuals in lower socioeconomic groups face elevated FS due to limited access to financial resources and institutional support, reinforcing cycles of poverty and inequality (Braveman et al. 2011 ; Marmot et al. 2008 ). In line with the SDH model, FS is conceptualised as the psychological strain experienced when individuals are unable to meet their financial obligations, whereas FWB refers to having control over one’s finances and feeling confident about the financial future (Kim et al., 2020 ; Netemeyer et al., 2018 ). These constructs are influenced by intersecting demographic and structural factors such as age, income, gender, relationship status, and geographic location, all of which are empirically explored in this study. By integrating the SDH framework with these financial constructs, this study examines how systemic inequalities affect different demographic groups' experiences of FS and FWB, particularly during periods of economic disruption such as the COVID-19 pandemic. 3.2 Life-Cycle Theory of Financial Behaviour In addition to the SDH framework, this study draws on Life-Cycle Theory to account for differences in financial stress and financial well-being among various age groups. Formulated by Modigliani and Brumberg ( 1954 ), the life-cycle theory suggests that people's financial behaviours change in a predictable manner throughout their lives. In early adulthood, individuals typically have lower incomes and higher expenses (such as those related to education, housing, and raising children), which often results in increased financial strain. As individuals move through their careers, their income generally increases, allowing for asset accumulation and greater financial stability. In later years, many depend on savings and pensions to sustain their well-being in retirement. This theory is particularly pertinent for understanding generational variance in FS and FWB. Younger adults may experience heightened stress due to low income, student loans, or job insecurity, whereas older adults have the advantage of accumulated assets and financial experience. The longitudinal analysis in this study facilitates the examination of these life-cycle dynamics over time, offering a behavioural complement to the structural insights provided by the SDH framework. 4. Methodology This study employed a quantitative, longitudinal research design to explore changes in FS and FWB among South Africans over a three-year period from 2019 to 2021. The primary data source was the Old Mutual Rewards Program Survey, which provides consistent, standardised measures across time. Data were collected using structured survey instruments, including the CFPB Financial Well-Being Scale (CFPB 2015 a), ensuring the reliability and comparability of results across various demographic groups. The research design was informed by a structured, quantitative approach that focused on numerical data derived from a large respondent base. Specifically, 6,713 participants completed the FS assessments, while 2,923 individuals completed the FWB scale annually throughout the three-year period. Only participants who consistently responded across all three years were included in the final sample, facilitating the panel data analysis. This ensured internal validity by tracking changes within the same individuals rather than across different cohorts. The sampling frame was drawn from the Old Mutual Rewards Program database, which comprises over 1.3 million members. In 2019, South Africa's total population stood at approximately 58.5 million (Stats SA 2019 ), underscoring the broad but focused reach of the survey population. 4.1 Data Collection Data were collected as participants completed various surveys to earn points within the rewards program. If a participant completed multiple surveys within a year, only the initial submission for that year was used to maintain data consistency. The instruments were administered online via the Old Mutual Rewards Program’s webpage. Demographic variables analysed included age groups ranging from 18 to 65 years, income levels, marital status, residential province and gender. The data were analysed using the Statistical Package for the Social Sciences (SPSS) Version 25, with statistical consultation services from North-West University providing additional support. 4.2 Research Ethics The usage of data was also governed by Old Mutual’s overarching privacy policy with the following statement applying specifically with regards to the rewards program: As set out in the Privacy Policy, your responses to surveys may be used in our academic and/or market research and analytics unit to refine our propositions to customers. The data collected from the surveys will not be identifiable, thus ensuring anonymity of your responses and the responses published for academic and/or market research purposes will be aggregated and anonymised. The study was approved on 30 September 2022 by the Faculty of Economic and Management Sciences (North-West University) Research Ethics Committee under ethics number NWU − 01822–22 - A4 on 30 September 2022. 4.3 Measuring Instrument The FWB scale assesses respondents' financial health using nine items rated from 1 (poor) to 10 (excellent), producing a total score between 9 and 90. This was converted to a standardised FWB score based on age-specific CFPB ( 2015 a) guidelines, and then scaled back to a range of 1–10. For instance, a raw score of 20 for someone aged 18–61 equates to a scaled score of approximately 5.56. The FS scale measured perceived financial stress using eight items with responses ranging from "Overwhelming Stress" to "No Stress at All" (Prawitz et al., 2006 ). The FS score was calculated by averaging the item scores, resulting in a final value between 1.0 and 10.0, where higher scores indicated lower stress. For example, a total score of 28 yields an FS score of 3.5, indicating high financial distress. Table 1 Distribution of Sample Groups by Demographic Category for FS and FWB (2019–2021) Demographic Variable Category FWB Sample (n, %) FS Sample (n, %) Age 21–25 129 (4.41%) 253 (3.77%) 26–30 585 (20.00%) 1149 (17.12%) 31–35 833 (28.50%) 1781 (26.53%) 36–40 604 (20.66%) 1495 (22.27%) 41–45 354 (12.11%) 928 (13.82%) 46–50 179 (6.12%) 496 (7.39%) 51–55 116 (3.97%) 306 (4.56%) 56–60 66 (2.26%) 177 (2.64%) 60+ 57 (1.95%) 128 (1.91%) Income R0–R25,000 2,214 (75.74%) 4,803 (71.55%) R25,001-R100,000 607 (20.77%) 1,671 (24.89%) R100,000+ 36 (1.23%) 98 (1.48%) Unknown 66 (2.26%) 141 (2.10%) Gender Female 2002 (68.46%) 4627 (68.95%) Male 921 (31.54%) 2086 (31.05%) Relationship Status Single 1913 (65.45%) 4,255 (63.38%) In a relationship 785 (26.86%) 1,951 (29.06%) No Relationship 67 (2.29%) 181 (2.69%) Unknown 158 (5.40%) 326 (4.87%) Residential Province Eastern Cape 342 (11.70%) 844 (12.57%) Free State 107 (3.66%) 272 (4.05%) Gauteng 776 (26.55%) 1,720 (25.62%) KwaZulu-Natal 511 (17.48%) 1,199 (17.86%) Limpopo 144 (4.93%) 310 (4.62%) Mpumalanga 101 (3.46%) 250 (3.72%) Northwest 76 (2.60%) 201 (2.99%) Northern Cape 28 (0.96%) 82 (1.22%) Western Cape 535 (18.30%) 1,192 (17.76%) The study samples for FS (n = 6713) and FWB (n = 2923) were stratified across five key demographic variables (Table 1 ). The age group 31–35 was the most represented, with an income distribution skewed toward the R0-R25,000 range. More than two-thirds of the sample comprised female respondents. Single individuals formed the largest relationship group, and Gauteng had the highest provincial representation. These demographics as depicted in Table 1 reflect the socioeconomic diversity relevant to evaluating financial well-being and stress over time. 5. Data Analysis and Results Table 2 displays the statistically significant differences for age, income, gender, relationship status and residential province. Each of these differences is discussed in more detail below. Table 2 Summary Table: Financial Stress and Financial Well-being Tests by Demographics (2019–2021) Variable Test Type Years Statistical Significance (p) Findings Summary Age vs FS Welch's ANOVA 2019–2021 p < 0.001 (all years) Younger groups (21–30) showed significantly higher FS than older groups. Age vs FWB ANOVA 2019–2021 p < 0.001 (all years) Older individuals (60+) had significantly higher FWB scores across years. Income vs FS ANOVA 2019–2021 p < 0.001 (all years) FS improved with increasing income; lowest stress among R100,000 + group. Income vs FWB ANOVA (2019–20), Welch (2021) 2019–2021 p < 0.001 (all years) FWB scores significantly increased with income. Gender vs FS T-Test 2019–2021 p < 0.05 (all years) Females reported higher FS levels (notably in the pandemic period). Gender vs FWB T-Test 2021 p < 0.05 (2021 only) Males showed slightly higher FWB scores than females. Relationship vs FS ANOVA 2019–2021 p < 0.001 (all years) Individuals in relationships consistently had lower FS levels. Relationship vs FWB ANOVA (2019–20), Welch (2021) 2021 p = 0.004 (2021 only) FWB difference significant in 2021: people in relationships > single. Province vs FS ANOVA 2019–2021 p < 0.05 (all years) FS levels varied significantly; most rural provinces had higher FS. Province vs FWB Welch's ANOVA 2019–2021 p < 0.05 (all years) FWB scores higher in economically strong provinces like Gauteng. Age and Financial Outcomes The relationships between age and both FS and FWB were consistently significant across all three years (2019–2021), as revealed by Welch’s ANOVA and standard ANOVA tests, respectively. Younger respondents (especially those aged 21–30 years) reported markedly higher FS and lower FWB compared to older age groups. This aligns with the life-cycle hypothesis and findings from Collins and Urban (2019), who suggest that younger adults often enter the workforce with limited savings, lower incomes, and greater financial uncertainty. These conditions predispose them to heightened FS. Conversely, individuals aged 60 and above demonstrated the highest FWB and the lowest FS. This can be attributed to accumulated assets, stable income streams (e.g. pensions), and reduced dependents and debt obligations, as corroborated by Kempson et al. ( 2017 ) and Mantai and Marrone ( 2023 ). These results emphasise the critical importance of financial education and early career financial planning interventions targeted at younger demographics. The longitudinal nature of the data underscores persistent generational disparity, highlighting the structural need to support youth financial literacy and employment policies that enhance income stability and reduce early career financial stressors. Income and Economic Resilience The association between income and financial outcomes was the strongest among all demographic variables, with significant results across the FS and FWB for all years. Notably, income-related disparities in FWB were so pronounced in 2021 that the assumptions of variance equality were violated, necessitating the use of Welch's test. Respondents in higher income brackets consistently exhibited higher FWB and lower FS, a finding that mirrors empirical evidence from Joo and Grable ( 2004 ) and Cwynar et al. ( 2020 ). The COVID-19 pandemic exacerbated these disparities; low-income groups faced job losses, reduced hours, and lacked financial buffers (Rogan & Skinner 2020 ; Kansiime et al. 2021 ). Meanwhile, higher-income respondents were more likely to have continued employment (e.g. through remote work) and access to credit, insurance, and investments. These results support the call for income-targeted social protection programs, including unemployment insurance reform and emergency savings incentives for low-income earners. Gender and Financial Disparity Statistically significant gender differences were evident in both FS and FWB during the post-pandemic year (2021). Women reported higher levels of financial stress and lower financial well-being, reaffirming the global findings on gendered economic vulnerability. The observed disparities can be linked to gender pay gaps (Mosomi 2019 ), occupational segmentation, and women’s overrepresentation in precarious employment sectors, as documented by Casale and Posel ( 2020 ) and De Miquel et al. ( 2022 ). Moreover, the pandemic’s impact on caregiving responsibilities disproportionately affects women, amplifying their FS and hindering FWB (UN 2021). These results underline the necessity of a gender-sensitive policy design, especially in the domains of childcare support, workplace equity, and targeted financial literacy programs for women. Relationship Status and Economic Buffering Individuals in relationships consistently experienced lower FS and higher FWB compared to their single, divorced, or widowed counterparts. This trend, statistically significant in all FS tests and for FWB in 2021, aligns with the dual-income and resource-sharing advantages associated with marital unions (Brown 2010; Joo 2008 ). The buffering effect of a second income and mutual financial support within a marriage appears to have been especially critical during economic downturns. The role of cultural practices, such as lobola and extended familial financial obligations, is also noteworthy. These customs may place additional FS on married or soon-to-be-married individuals, particularly men (IOL 2023 ; Yarbrough 2021 ). The significance of 2021 in the FWB may reflect shifting economic pressures post-lockdown, where single households bore disproportionate burdens due to a lack of income sharing. These findings validate prior work (Addo & Lichter 2013 ; Falconier & Jackson 2020 ) and call for greater attention to the financial vulnerabilities of single and single-parent households in policymaking, especially regarding tax benefits, subsidies, and access to affordable credit. Residential Province and Geographic Inequality Regional disparities were prominent in both the FS and FWB analyses. Provinces with stronger economies, such as Gauteng and the Western Cape, demonstrated significantly higher FWB scores and lower FS, while underdeveloped or rural provinces, such as the Eastern Cape and Free State, showed the opposite trend. These differences, confirmed by ANOVA and Welch tests, are attributable to regional variations in job availability, infrastructure, and access to financial services, as noted by Burger et al. (2017) and Finscope (2019). COVID-19 has intensified these spatial inequalities. Provinces reliant on tourism (e.g. Western Cape) experienced sharp economic decline, but their relatively higher baseline FWB may have cushioned residents’ outcomes. Conversely, provinces with limited healthcare and social safety infrastructure have longer economic recovery periods (Venter et al. 2020 ). The results validate existing literature (Tacoli et al. 2015 ; Visagie & Turok 2021 ) and point toward a need for geographically targeted development policies, including digital financial access initiatives and employment stimulation in rural provinces. Post Hoc Tests Post hoc tests were conducted where the ANOVA indicated statistically significant differences between more than two groups. Table 3 displays the significant differences highlighted by the post hoc tests. Table 3 Post Hoc Analyses of Financial Stress and Well-being (2019–2021) Demographic Test Type Years Comparison Pairs Mean Difference p-value Age Tukey HSD (FS) 2019 21–25 vs. 51–60+; 26–30 vs. 51–60+; 31–35 vs. 46–60+ –0.576 to − 1.795 .048 to < .001 2020 21–25 vs. 46–60+; 26–30 vs. 36–60+; 31–35 vs. 46–60+ –0.413 to − 1.745 .014 to < .001 2021 21–25 vs. 46–60+; 26–30 vs. 41–60+; 31–35 vs. 41–60+ –0.376 to − 1.327 .015 to < .001 Tukey HSD (FWB) 2019 21–25, 26–30, 31–35, 36–45, 51–60 vs. 60+; 36–40 vs. 46–50 –2.549 to − 6.642 .009–<.001 2020 21–25, 26–30, 31–35, 36–45, 51–60 vs. 60+; 36–40 vs. 46–50 –4.339 to − 6.107 .001–<.001 2021 26–30, 31–35, 36–45 vs. 46–50 and 60+ –2.597 to − 5.471 .032–<.001 Income Tukey HSD (FS) 2019 <R25,000 vs. R25,001–R100,000; <R25,000 vs. R100,000+; R25,001–R100,000 vs. R100,000+ -0.546 -2.057 -1.510 1.672 < 0.001 < 0.001 < 0.001 < 0.001 2020 <R25,000 vs. R25,001-R100,000 <R25,000 vs. R100,000+ <R25,000 vs. Unknown R25,001-R100,000 vs. R100,000+ R100,000 + vs. Unknown -0.612 -1.905 -0.557 -1.292 1.348 < 0.001 < 0.001 0.026 < 0.001 < 0.001 2021 <R25,000 vs. R25,001-R100,000 <R25,000 vs. R100,000+ R25,001-R100,000 vs. R100,000+ R100,000 + vs. Unknown -0.602 -1.787 -1.185 1.574 < 0.001 < 0.001 < 0.001 < 0.001 Tukey HSD (FWB) 2019 <R25,000 vs. R25,001-R100,000 <R25,000 vs. R100,000+ R25,001-R100,000 vs. R100,000+ R100,000 + vs. Unknown -1.388 -8.022 -6.634 7.318 0.006 < 0.001 < 0.001 < 0.001 2020 <R25,000 vs. R25,001-R100,000 <R25,000 vs. R100,000+ -1.570 -4.911 < 0.001 0.002 Games-Howell (FWB) 2021 <R25,000 vs. R25,001-R100,000 <R25,000 vs. R100,000+ R25,001-R100,000 vs. R100,000+ R100,000 + vs. Unknown -1.821 -7.652 -5.831 7.750 < 0.001 0.001 0.021 0.003 Relationship Status Tukey HSD (FS) 2019 In Relationship vs. Unknown In relationship vs. Single Unknown vs. Single 0.623 0.205 -0.412 < 0.0001 0.015 0.021 2020 In Relationship vs. Unknown In Relationship vs. Single 0.627 0.316 < 0.001 < 0.001 2021 In Relationship vs. Unknown In Relationship vs. Single 0.525 0.245 0.002 0.002 Games-Howel (FWB) 2021 In Relationship vs. Unknown 2.430 0.009 Province Tukey HSD (FS) 2019 KZN vs. Western Cape Limpopo vs. Western Cape 0.470 0.556 < 0.001 0.019 2020 Eastern Cape vs. KZN KZN vs. Western Cape -0.335 0.366 0.047 0.005 2021 Gauteng vs. KZN KZN vs. Northern Cape KZN vs. Western Cape Limpopo vs. Northern Cape -0.340 0.953 0.438 1.0064 0.010 0.026 0.001 0.035 Games- Howell (FWB) 2019 Eastern Cape vs. Western Cape Gauteng vs. Western Cape KZN vs. Western cape 2.248 1.711 1.937 0.014 0.024 0.026 2021 KZN vs, Mpumalanga Limpopo vs. Mpumalanga 0.778 0.928 0.007 0.001 Post hoc tests for both FS and FWB revealed consistent age-related differences across 2019–2021. Younger respondents, particularly those aged 21–30, reported significantly lower FS and FWB scores compared with older age groups, especially those aged 51 years and above. The largest and most consistent gaps were observed between the youngest cohort (21–25) and the 60 + group, with mean differences ranging from − 1.3 to − 1.8 for FS (indicating higher stress among the youngest) and − 5.0 to − 6.6 for FWB (indicating lowers FWB for the youngest) (all p < .001). Similar but smaller differences were also evident for those aged 26–40 compared with the 51–60 + categories. In contrast, differences between adjacent younger groups (e.g., 21–25 vs. 26–30) were not significant. Overall, the results highlight a systematic pattern in which both financial stress decreases and financial well-being increase with age, with respondents aged 60 and older consistently reporting the most favourable outcomes across all three survey years. Post hoc comparisons revealed strong and consistent income effects for both FS and FWB across 2019–2021. Respondents earning less than R25,000 per month reported significantly lower FS and FWB scores than those in higher income brackets. The largest differences were consistently observed between the lowest-income group (< R25,000) and the highest-income group (R100,000+), with mean gaps of − 1.8 to − 2.1 for FS (indicating higher stress among lower earners) and − 4.9 to − 8.0 for FWB (all p < .01). Middle-income respondents (R25,001–R100,000) also scored lower than those earning above R100,000, with mean differences of − 1.2 to − 1.5 for FS and − 5.8 to − 6.6 for FWB (all p < .01). Overall, the findings underscore a systematic pattern in which higher income is associated with lower financial stress and higher financial well-being, while lower-income groups consistently face the most adverse outcomes. Descriptive statistics indicated that women consistently reported higher FS and lower FWB than men across all three years of the study. Post hoc tests indicated consistent differences in financial stress (FS) by relationship status across all years (2019–2021). Respondents in a relationship reported significantly higher FS scores (indicating lower stress) than both single individuals and those with unknown status. Mean differences ranged from + 0.21 to + 0.63 (all p ≤ .015). Conversely, singles generally scored lower than those in relationships, reflecting greater stress levels. In 2021, a similar pattern extended to financial well-being (FWB), where those in a relationship scored significantly higher than respondents with unknown status (mean difference + 2.43, p = .009). Overall, the results suggest that being in a relationship is associated with reduced financial stress and, to a lesser extent, higher well-being, whereas being single or having an unknown relationship status is linked to less favourable financial outcomes. Significant provincial differences emerged in both financial stress (FS) and financial well-being (FWB). For FS, respondents from KwaZulu-Natal (KZN) consistently differed from those in other provinces: in 2019, KZN residents reported higher FS scores (lower financial stress) than those in the Western Cape (+ 0.47, p < .001), while Limpopo respondents also scored higher than the Western Cape (+ 0.56, p = .019). In 2020, FS scores were lower in the Eastern Cape compared with KZN (–0.34, p = .047), but higher in KZN relative to the Western Cape (+ 0.37, p = .005) and Northern Cape (+ 0.43, p = 0.001). In 2021, notable contrasts included lower FS scores in Gauteng compared with KZN (–0.34, p = .010), and higher FS scores in KZN and Limpopo relative to the Northern Cape (+ 0.95 to + 1.01, p < .05), as well as higher FS scores in KZN versus the Western Cape (+ 0.44, p = .001). For FWB, differences were also observed. In 2019, respondents in the Eastern Cape, Gauteng, and KZN all reported significantly higher FWB scores than those in the Western Cape (+ 1.71 to + 2.25, p ≤ .026). By 2021, KZN and Limpopo reported higher FWB compared with Mpumalanga (+ 0.78 to + 0.93, p ≤ .007). Overall, the results suggest regional variation in both stress and well-being, with the Western Cape often scoring less favourably in comparison with other provinces, while Gauteng, KZN and Limpopo tended to report more positive outcomes. 5.1 Hypothesis Testing H1: There is a significant relationship between age and financial stress. Statistical testing using Welch’s ANOVA revealed a significant relationship between age and FS across all three years (2019–2021), with p-values less than 0.001 in each year. The largest and most consistent gaps were observed between the youngest cohort (21–25) and the 60 + group, with mean differences ranging from − 1.3 to − 1.8 for FS (indicating higher stress among the youngest). These findings align with the life-cycle hypothesis and support H1. H2: There is a significant relationship between age and financial well-being. Standard ANOVA tests indicated that age significantly influenced FWB during 2019–2021 (p < 0.001). Older respondents, especially those aged 60 + years, consistently reported higher FWB scores. The largest and most consistent gaps were observed between the youngest cohort (21–25) and the 60 + group, with mean differences ranging from − 5.0 to − 6.6 for FWB (indicating lowers FWB for the youngest) (all p < .001). Therefore, H2 is supported. H3: There is a significant relationship between income and financial stress. Income was significantly associated with FS across all years (p < 0.001, ANOVA). Participants earning higher incomes (R100000+) experienced a substantially lower FS than those earning less. For instance, the largest differences were consistently observed between the lowest-income group (< R25,000) and the highest-income group (R100,000+), with mean gaps of − 1.8 to − 2.1 for FS (indicating higher stress among lower earners). These results confirm H3. H4: There is a significant relationship between income and financial well-being. The FWB scores increased with income, as shown by the significant ANOVA and Welch’s test results (p < 0.001 across years). Post hoc comparisons indicated that the largest differences were consistently observed between the lowest-income group (< R25,000) and the highest-income group (R100,000+), with mean gaps of − 4.9 to − 8.0 for FWB (all p < .01). Accordingly, H4 is accepted. H5: There is a significant relationship between gender and financial stress. An independent-sample t-test for 2019–2021 revealed that females reported significantly higher FS levels than males (p < 0.05). This finding supports H5, suggesting that gender differences meaningfully influence financial stress, particularly in the pandemic context. H6: There is a significant relationship between gender and financial well-being. Similarly, males demonstrated significantly higher FWB scores than females in 2021 (p < 0.05, t-test), a finding consistent with gender-based disparities in employment and income security. Therefore, H6 is partially supported. H7: There is a significant relationship between the relationship status and financial stress. Relationship status significantly affected FS across all three years (p < 0.001, ANOVA). Respondents in relationships reported a consistently lower FS than those who were single. Post hoc tests confirmed this difference, with people in relationships experiencing significantly less stress than single individuals (Mean differences ranged from 0.21 to 0.63, all p ≤ .021). Thus, H7 is confirmed. H8: There is a significant relationship between relationship status and financial well-being. Although FWB did not vary significantly by relationship status in 2019–2020, a significant difference emerged in 2021 (p = 0.004, Welch’s ANOVA). Post hoc tests revealed people in relationships reported higher FWB scores than single individuals (mean difference + 2.43, p = .009). Consequently, H8 is partially supported, with significance observed in the pandemic recovery period. H9: There is a significant relationship between province of residence and financial stress. The ANOVA results indicated significant provincial differences in FS during 2019–2021 (p < 0.05). Residents in KZN and Gauteng experienced less FS compared to those in the Eastern Cape and Northern Cape. Therefore, H9 is supported. H10: There is a significant relationship between province of residence and financial well-being. Welch’s ANOVA also revealed significant differences in FWB by province (p < 0.05) in all years. Respondents in the KZN and Gauteng reported higher FWB scores than those in the Western Cape and Mpumalanga. These findings affirm H10. 6. Discussion and Implications The results of the hypothesis testing affirm that demographic variables such as age, income, gender, relationship status, and province of residence significantly influence FS and FWB among South Africans, particularly during and after the COVID-19 pandemic. These findings validate the theoretical and empirical frameworks and reinforce the structural nature of financial vulnerability. The age-related differences observed in this study reaffirm the life-cycle theory of financial well-being. Younger adults aged 21–25 years experienced significantly more FS and lower FWB compared to older individuals, supporting H1 and H2. This trend is consistent with the findings of Collins and Urban (2019) and Kempson et al. ( 2017 ), who linked youth financial vulnerability to limited job experience, unstable income, and lower savings. It also underscores the importance of early financial education and targeted support for youth entering the labour market. Income was confirmed as a predictor of FS and FWB (H3 and H4), with low-income earners (particularly those below R25,000 per month) experiencing heightened stress and reduced well-being. The widening gap in 2021, especially during the pandemic, echoes the findings of Rogan and Skinner ( 2020 ) and Kansiime et al. ( 2021 ) and highlights how economic shocks disproportionately impact already vulnerable groups. These outcomes call for stronger income protection policies such as emergency grants, wage support, and inclusive financial tools. Gender-based disparities (H5 and H6) were also statistically significant, with women experiencing more FS and less FWB than men, particularly in 2021. This aligns with the findings of Mosomi ( 2019 ) and Casale and Posel ( 2020 ), who argue that wage gaps, caregiving roles, and occupational segmentation disadvantage women financially. The results highlight a pressing need for gender-responsive budgeting and equitable access to formal employment, childcare support, and financial products. Regarding relationship status, individuals in relationships experienced significantly lower FS and higher FWB than single individuals (H7 and H8). These findings are consistent with Brown (2010) and Falconier and Jackson ( 2020 ), confirming that income pooling and financial collaboration within marriages provide buffers against economic shocks. These implications are particularly relevant for single-parent households and previously married individuals, who may require additional social and financial support mechanisms. Finally, the findings on geographic variation (H9 and H10) revealed entrenched spatial inequalities. Provinces such as Gauteng and KZN consistently exhibited better FS and FWB outcomes compared to more rural provinces such as the Eastern Cape, Northern Cape and Mpumalanga. These results reflect disparities in infrastructure, employment opportunities, and access to financial services, as noted by Burger et al. (2017) and the Finscope (2019). Policymakers must address these disparities through geographically targeted interventions such as rural employment schemes, digital financial access, and provincial infrastructure development. Collectively, these results offer a case for an intersectional understanding of financial vulnerability in South Africa. They also support the application of the Social Determinants of Health framework by demonstrating how demographic, geographic, and socioeconomic factors jointly shape financial stress and well-being. As future economic disruptions are likely, these insights should inform more equitable and resilient policy interventions. 7. Conclusion and Recommendation This study examined how (FS and FWB varied across key demographic dimensions, age, income, gender, relationship status, and province of residence, over a three-year period (2019–2021), using longitudinal data from the Old Mutual Rewards Program. The statistical analysis confirmed all ten hypotheses, revealing significant associations between these demographic variables and both FS and FWB. The findings demonstrate that younger adults, low-income individuals, women, those who are single, and residents of underdeveloped or rural provinces are most at risk of financial vulnerability. The COVID-19 pandemic has further amplified these disparities, especially among low-income earners, females and singles. In contrast, older adults, higher-income individuals, men, persons in relationships, and residents in certain provinces, often with stronger economies, consistently reported better financial outcomes. These insights not only extend the current scholarship on financial well-being but also highlight the layered nature of financial vulnerability in South Africa. They reveal how intersecting identities and geographic realities shape individuals' capacity to manage financial obligations and plan for their future. In response, several practical and policy recommendations are offered. First, financial education programs should begin at the school level and continue into adulthood with a special focus on young adults and women. Second, income support mechanisms, including basic income grants and targeted relief, should be expanded to cushion low-income households during economic downturn. Third, infrastructure investment in rural and underserved provinces is essential for bridging the regional disparities in FS and FWB. Fourth, gender equity policies must address both labour market access and caregiving responsibilities. This study is limited by its reliance on self-reported measures and digital-only survey access, which may underrepresent individuals without consistent internet access. Future research should explore the long-term trajectory of financial recovery beyond 2021 and include qualitative methods to capture the lived experiences behind quantitative trends. Doing so will offer a richer and more nuanced understanding of the financial realities faced by different demographic groups. Ultimately, a multidimensional strategy that integrates financial, social, and health considerations is vital to build a financially resilient and equitable South African society. Declarations Acknowledgements The authors are very grateful to the reviewers and editors for their very insightful comments and suggestions on the paper. Funding: No funding was received for the research. Competing Interests: None to declare. Author information: Leon Steyn [email protected] http://orcid.org/0009-0006-2448-3192 Faculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa Prof Surika van Rooyen [email protected] https://orcid.org/0000-0002-0601-1371 Faculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa Prof Jaco Fouché [email protected] https://orcid.org/0000-0002-7791-5669 Faculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa Dr Morris Mensah [email protected] https://orcid.org/0000-0008-5130-3032 Faculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa Correspondence: Prof Jaco Fouché [email protected] Authors' contributions: Leon Steyn is the MCom candidate responsible for conceptualising the paper, conducting the literature review, implementing the research methodology, and interpreting the research findings. Prof Surika van Rooyen is the supervisor, and Prof JP Fouché is the co-supervisor (who also designed the study as part of a larger study). Both supervisors acted as critical readers and provided guidance throughout the study. Dr Morris Mensa was responsible for quality review and adjusting the paper to the requirements of the journal. Consent for Publication: Confirmed with all authors. Ethics declarations: Ethical approval statement Ethical approval was obtained from the Faculty of Economic and Management Sciences Research Ethics Committee (EMS-REC) of the North-West University, South Africa (Approval No. NWU-01822-22-A4). EMS-REC operates under the authority of the Senate Committee on Research Ethics (SCRE) and functions independently in accordance with internationally recognized standards for ethical oversight. Its role includes evaluating and confirming ethical compliance in commerce-related research, as well as providing advisory and training capacity in research ethics. The first approval was granted on 30 September 2022, following the conclusion of a Non-Disclosure Agreement between Old Mutual and the North-West University in April 2022. Approval was subsequently extended on 30 July 2024 to include the work of master’s students making use of the same dataset. The study was identified as low risk, and only secondary data were used. All conditions of approval, including the requirement to notify EMS-REC without delay of any adverse events or ethical concerns, and the need to seek prior approval for any amendments to the research protocol, were strictly adhered to. Informed consent statement This study employed a quantitative, longitudinal design to examine changes in financial stress (FS) and financial well-being (FWB) among South Africans from January 2019 to December 2021. The primary data source was the Old Mutual Rewards Program Surveys. Participation in these surveys was governed by Old Mutual’s overarching privacy policy, which was communicated to all participants. Specifically, the Rewards Program informed participants that: “As set out in the Privacy Policy, your responses to surveys may be used in our academic and/or market research and analytics unit to refine our propositions to customers. The data collected from the surveys will not be identifiable, thus ensuring anonymity of your responses and the responses published for academic and/or market research purposes will be aggregated and anonymised.” All participants voluntarily agreed to participate in the Rewards Program surveys, and by doing so, consented to the use of their anonymised responses for academic research purposes. No vulnerable individuals were included in the study. Participants received points for completing surveys, which could be redeemed with rewards partners. As part of Old Mutual Rewards’ objective to promote good financial behaviour and education, participants could also earn points for a variety of qualifying financial wellness activities that included the completion of these surveys. Points were not transferable, could not be exchanged, sold, or redeemed for cash, and had no cash value. Participants were free to withdraw from a survey at any time, though in such cases, the corresponding points would not be awarded. All data were anonymised by Old Mutual before being made available to the North-West University, ensuring the privacy and confidentiality of participants. The anonymised data are stored in digital format on an official North-West University OneDrive, with access strictly limited to the principal investigator, the statistician, and authorized members of the research team. 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Stats SA (2021) Quantifying SA’s economic performance in 2020. Statistics South Africa. https://www.statssa.gov.sa/?p=13601 Stats SA (2021) Quarterly labour force survey quarter 2: 2021. Stats SA. https://www.statssa.gov.za/publications/P0211/P02112ndQuarter2021.pdf Stats SA (2022) Gender series volume IX: Women empowerment, 2017–2022. Statistics South Africa. https://www.statssa.gov.sa/?p=17597 Stats SA (2023) Income dynamics of female-headed households: Shifts between salaries and grants, 2014 to 2023. Stats SA. https://www.statssa.gov.za/?p=17597 Tacoli C, McGranahan G, Satterthwaite D (2015) Urbanisation, rural-urban migration, and urban poverty. Human Settlements Group, International Institute for Environment and Development. https://www.jstor.org/stable/pdf/resrep01308 Umberson D, Montes A (2010) Social support and its role in mitigating financial stress. Journal of Social Issues 66(3):489–506. https://doi.org/10.1111/j.1540-4560.2010.01652.x UNISA (2022) Consumer finances crumble under the pressures of rising prices and interest rates. Consumer Financial Vulnerability Index. https://www.momentum.co.sa UN (United Nations). 2021. COVID-19 and human rights: We are all in this together. UN Policy Briefs. https://unsdg.un.org/resources/covid-19-and-human-rights-we-are-all-together. Date of access: 1 Apr. 2024.U.S. Census Bureau. 2025. Work from home inequalities. https://www.census.gov/library/stories/2025/01/work-from-home-inequalities.html Accessed 3 Mar. 2025. Van der Berg S, Patel L, Bridgman G (2022) Food insecurity in South Africa: Evidence from NIDS-CRAM wave 5. Development Southern Africa 39(5):722–737. https://www.tandfonline.com/doi/abs/10.1080/0376835X.2022.2062299 Vancea M, Utset M (2016) The unequal financial impacts of remote work: Challenges for young adults in unstable economies. Journal of Economic Studies 43(1):45–62. https://doi.org/10.1007/s12110-2016-0045-6 Venter ZS, Aunan K, Chowdhury S, Lelieveld J (2020) COVID-19 lockdowns cause global air pollution declines. Proceedings of the National Academy of Sciences 117(32):18984–18990. https://www.pnas.org/doi/abs/10.1073/pnas.2006853117 Visagie J, Turok I (2021) Rural-urban inequalities amplified by COVID-19: Evidence from South Africa. Area Development and Policy 6(1):50–62. https://www.tandfonline.com/doi/full/10.1080/23792949.2020.1851143 World Bank (2018) Overcoming poverty and inequality in South Africa: An assessment of drivers, constraints, and opportunities. Washington, D.C.: World Bank. https://openknowledge.worldbank.org/handle/10986/29614 WHO (World Health Organisation) (2008) Closing the gap in a generation: Health equity through action on the social determinants of health. Final report of the Commission on Social Determinants of Health. https://www.who.int Xiao JJ, Chen C, Chen F (2014). Consumer financial capability and financial satisfaction. Social indicators research, 118(1), 415-432. Yarbrough MW (2021) Very long engagements: The persistent authority of bridewealth in a post-apartheid South African community. Law & Social Inquiry 46(4):944–970. https://www.cambridge.org/core/journals/law-and-social-inquiry/article/very-long-engagements-the-persistent-authority-of-bridewealth-in-a-postapartheid-south-african-community/D839A712784A82946BC05567B62FA9B3 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7571480","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":531352660,"identity":"0069280d-7a60-4af6-8cfc-bf1d2f5058ed","order_by":0,"name":"Leon Steyn","email":"","orcid":"","institution":"North-West University","correspondingAuthor":false,"prefix":"","firstName":"Leon","middleName":"","lastName":"Steyn","suffix":""},{"id":531352662,"identity":"9e8c86ec-ecdd-49b4-b627-9a6bfdde8b88","order_by":1,"name":"Prof Surika Rooyen","email":"","orcid":"","institution":"North-West 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Introduction","content":"\u003cp\u003eFinancial stress (FS) and financial well-being (FWB) are increasingly recognised as central determinants of individual welfare, influencing not only household financial behaviour but also broader psychological and health outcomes (Kim et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Netemeyer et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). FS reflects the psychological burden experienced when financial obligations exceed accessible resources, while FWB captures an individual\u0026rsquo;s perceived ability to manage day-to-day finances, absorb shocks, and feel secure about the future (CFPB \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While conceptually distinct, these constructs are interdependent and shaped by structural and demographic contexts.\u003c/p\u003e\u003cp\u003eIn South Africa, a country characterised by inequality and economic volatility, FS and FWB are shaped by structural determinants such as income level, gender, age, relationship status, and geographic location (Stats SA \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Burger et al. 2017). Younger individuals, for instance, face FS due to unemployment and educational debt, while older adults may benefit from accumulated savings and stable income (Collins \u0026amp; Urban 2019; Mantai \u0026amp; Marrone \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Income, in particular, remains one of the predictors of both FS and FWB, with low-income earners susceptible to financial insecurity and lacking access to financial tools and credit (Joo \u0026amp; Grable \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Cwynar et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGendered dimensions also compound financial vulnerability. South African women continue to face wage disparities, caregiving burdens, and overrepresentation in informal and low-paying sectors, all of which exacerbate FS and limit FWB (Mosomi \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Casale \u0026amp; Posel \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, marital status influences financial resilience, with married individuals more likely to benefit from income pooling and support systems compared to single, widowed, or divorced persons (Brown 2010; Falconier \u0026amp; Jackson \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, provincial disparities reflect entrenched spatial inequalities: urbanised provinces such as Gauteng and Western Cape report better FS and FWB outcomes relative to economically marginalised areas such as Eastern Cape and Limpopo (Visagie \u0026amp; Turok \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e;Finscope 2019).\u003c/p\u003e\u003cp\u003eThe onset of COVID-19 has intensified pre-existing inequalities. Lockdowns, job losses, and informal sector disruptions disproportionately affect low-income earners, youth, and female populations already vulnerable to FS (UNISA \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Van der Berg et al. 2020). Despite temporary relief efforts, the crisis exposed weaknesses in South Africa\u0026rsquo;s social protection infrastructure, especially in rural and underserved areas (UN 2021).\u003c/p\u003e\u003cp\u003eAlthough global studies have examined FS and FWB through various cross-sectional lenses (Lusardi \u0026amp; Mitchell \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Br\u0026uuml;ggen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), few have tracked how these measures evolve over time, especially within emerging economies. In South Africa, the predominant use of one-off data collection hampers the ability to assess financial trajectories and resilience over time (Caruana et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This study addresses these gaps by utilising a longitudinal dataset (2019\u0026ndash;2021) to examine how FS and FWB have evolved across key demographic groups before and during the pandemic. Through a panel analysis of over 6,000 (FS) and 2,000 (FWB) respondents, this study explores how structural determinants shape individual responses to financial shocks and identifies the most affected groups. By linking empirical insights with theoretical frameworks such as the Social Determinants of Health (SDH) and Life-Cycle Theory, this research not only contributes to academic literature but also informs policy interventions aimed at enhancing financial resilience in both stable and crisis contexts.\u003c/p\u003e"},{"header":"2. Literature Review and Hypothesis Development","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Financial Stress and Financial Well-being\u003c/h2\u003e\u003cp\u003eFinancial stress (FS) occurs when individuals face difficulties in meeting their daily financial obligations such as paying bills, managing debt, or covering essential living expenses. This condition often leads to anxiety and emotional distress, impacting both mental and physical health (Kim et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Consumer Financial Protection Bureau [CFPB] \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Financial stress is commonly triggered by factors such as income volatility, unexpected expenses, insufficient savings, or overwhelming debt burdens, which together can contribute to a state of financial insecurity (Lusardi \u0026amp; Mitchell \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn contrast, financial well-being (FWB) is understood as a holistic state reflecting an individual's ability to effectively manage their financial resources, maintain control over daily finances, and feel confident about their current and future financial situations (Netemeyer et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The Consumer Financial Protection Bureau (2015) defines FWB as having sufficient financial resources to meet ongoing expenses, absorb financial shocks, make choices that allow enjoyment of life, and plan for long-term financial goals. The key components of FWB include a sense of financial security, the capacity to handle unexpected financial setbacks without severe hardship, and a positive outlook toward future financial stability (Br\u0026uuml;ggen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eResearch has highlighted the inverse relationship between FS and FWB, where higher levels of financial stress correlate with lower perceptions of financial well-being, and vice versa (Kim et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, fostering financial literacy, access to financial products, and supportive social policies can enhance FWB and reduce FS among various populations (Lusardi \u0026amp; Mitchell \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Xiao, Chen \u0026amp; Sun 2014). FS and FWB are shaped by various demographic factors, such as age, income, gender, relationship status, and residential province (Stats SA \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e2.1.1 Age and Financial Outcomes\u003c/h2\u003e\u003cp\u003eYounger individuals are more likely to experience financial stress (FS), particularly because they are early in their careers, often earn lower incomes, and have not yet accumulated substantial savings (Collins \u0026amp; Urban 2019; Kempson et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Many also carry the additional burden of student debt and navigate the challenges of financial independence for the first time (Mantai \u0026amp; Marrone \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to Collins and Urban (2019), financial well-being (FWB) tends to follow a lifecycle pattern, initially decreasing in early adulthood because of mounting financial responsibilities and constrained earning potential, and then gradually improving as individuals gain stability through work experience, career advancement, and asset accumulation. Kempson et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) similarly argue that older individuals generally experience higher FWB due to increased access to financial capital and more established saving habits. These findings are consistent with South African earnings data, where older individuals tend to earn more and exhibit higher financial resilience (Stats SA \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; SAHRC 2017).\u003c/p\u003e\u003cp\u003eMoreover, Mantai and Marrone (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) described early career stages as marked by exploration and skill development, which, though important, may involve unstable income. In contrast, later stages offer more financial security due to accumulated assets, although challenges like age-based discrimination and career plateauing may arise (Coetzee \u0026amp; Stoltz \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This life-cycle view provides a meaningful framework to understand how age intersects with both FS and FWB over time.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between age and financial stress.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between age and financial well-being.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.1.2 Income and Financial Outcomes\u003c/h2\u003e\u003cp\u003eIncome is one of the strongest predictors of FS and FWB. Research has consistently shown that lower-income individuals are more likely to experience financial instability, limited access to credit, and difficulty in recovering from economic shocks (Kim \u0026amp; Garman 2003; Joo \u0026amp; Grable \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Cwynar et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, higher-income individuals often benefit from financial buffers, including savings, insurance, and investment portfolios, which provide greater security and improve FWB. South Africa\u0026rsquo;s high-income inequality, reflected in a Gini coefficient of 0.63, underscores the structural disparities that shape financial outcomes (World Bank \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic intensified these disparities. Lower-income earners, many of whom worked in informal or vulnerable sectors, were disproportionately affected by job losses, reduced hours, and income instability (Rogan \u0026amp; Skinner \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Lacking sufficient savings or safety nets, these individuals experienced heightened FS and a decline in FWB (Kansiime et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On the other hand, higher-income groups are often able to transition to remote work, maintain stable earnings, and draw on savings or investments to navigate crises (Sabri \u0026amp; Sakaria 2013). These patterns highlight the protective role of income in managing daily expenses and unexpected financial disruptions.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH3\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between income and financial stress.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH4\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between income and financial well-being.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.1.3 Gender and Financial Outcomes\u003c/h2\u003e\u003cp\u003eGender differences in FS and FWB are well documented in both South African and global research. Women consistently face greater financial vulnerability due to wage disparities, occupational segregation, and caregiving responsibilities (Mosomi \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Casale \u0026amp; Posel \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to Stats SA (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), women are overrepresented in precarious employment, have less access to paid benefits, and are less likely to be unionised. These factors contribute to the persistent gender gaps in earnings and financial security.\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic exacerbated these existing inequalities. Women, particularly those working in the retail, hospitality, and domestic sectors, are disproportionately affected by lockdown-related job losses (Stats SA \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Simultaneously, school closures and increased care needs place an additional burden on women, reducing their availability for paid work (UN 2021). Moreover, barriers to accessing credit and financial services further restrict women's financial resilience (Finscope South Africa \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These compounding challenges contribute to a higher FS and lower FWB among women, particularly during economic crises.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH5\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between gender and financial stress.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH6\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between gender and financial well-being.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.1.4 Relationship Status and Financial Outcomes\u003c/h2\u003e\u003cp\u003eRelationship status plays a critical role in shaping financial outcomes. Married individuals tend to experience better FWB, and lower FS compared to single, divorced, or widowed individuals. This is often due to shared expenses, dual incomes, and mutual financial support, which enhance financial stability and reduce vulnerability during times of economic strain (Brown 2010; Addo \u0026amp; Lichter \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Joo \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Falconier \u0026amp; Jackson \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConversely, single individuals frequently bear full financial responsibility and may lack the informal safety net provided by the partnership. Single-parent households, particularly those headed by women, are especially vulnerable because of the dual burden of caregiving and earning income (Posel \u0026amp; Rogan \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Adams-Prassl et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Blundell et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In South Africa, cultural practices such as lobola and extended family obligations further shape financial outcomes for married couples and may introduce additional pressure (IOL \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; My Afrika Mag \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yarbrough \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). During crises such as COVID-19, these financial dynamics become even more pronounced, with partnered individuals more likely to access joint resources, while that alone face increased exposure to FS.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH7\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between relationship status and financial stress.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH8\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between relationship status and financial well-being.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.1.5 Province and Financial Outcomes\u003c/h2\u003e\u003cp\u003eGeographic location also influences FS and FWB because of disparities in infrastructure, job availability, and access to services across South Africa\u0026rsquo;s provinces. Economically developed provinces, such as Gauteng and the Western Cape offer more employment opportunities and financial institutions, contributing to improved FWB and reduced FS among residents (Stats SA \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Visagie \u0026amp; Turok \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In contrast, provinces such as the Eastern Cape, Limpopo, and Free State struggle with higher unemployment, limited infrastructure, and weaker access to formal financial systems, resulting in more financial hardship (Burger et al. 2017; Finscope 2019). The urban-rural divide further complicates financial outcomes. Urban residents may benefit from better job prospects and services but also face higher living costs. Meanwhile, rural residents encounter lower costs of living but lack stable income opportunities, exacerbating FS (Tacoli et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The pandemic has worsened these regional disparities, with some provinces experiencing delayed recovery and insufficient health and social service infrastructure (Rogerson \u0026amp; Rogerson \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Venter et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These conditions demonstrate how spatial inequality in South Africa continues to shape divergent financial experiences across different geographic regions.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH9\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between province of residence and financial stress\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH10\u003c/strong\u003e\u003cp\u003eThere is a significant relationship between province of residence and financial well-being\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Theoretical Framework","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Social Determinants of Health (SDH)\u003c/h2\u003e\u003cp\u003eThe SDH framework recognises that health and well-being outcomes are shaped by the environments in which people are born, grow, live, work, and age (WHO 2008). These determinants include income, education, employment, social support, and access to healthcare, factors that are not only relevant to health but also to financial stress and financial well-being (Braveman et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFS, as a chronic source of stress, can have substantial mental and physical health consequences, including depression, anxiety, hypertension, and cardiovascular disease (Marmot et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The American Psychological Association (APA 2021) highlights FS as one of the most commonly reported stressors affecting behaviour and lifestyle choices. Individuals experiencing FS are less likely to engage in preventive health behaviours and are more likely to resort to harmful coping mechanisms, such as substance use or poor dietary habits (Adler \u0026amp; Newman \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFrom an SDH perspective, FWB is not merely the absence of FS but also includes positive factors such as financial literacy, stable income, and access to financial tools that support effective decision-making and resilience (Lusardi \u0026amp; Mitchell \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Social capital and networks also play a critical buffering role in managing financial hardships (Umberson \u0026amp; Montes \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kawachi \u0026amp; Berkman \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In communities with strong support systems, individuals are often better equipped to withstand financial shocks through informal lending, shared resources, or collective caregiving.\u003c/p\u003e\u003cp\u003eEconomic inequality, a core focus within the SDH framework, is particularly relevant in the South African context, where structural disparities in income, education, and employment persist. Individuals in lower socioeconomic groups face elevated FS due to limited access to financial resources and institutional support, reinforcing cycles of poverty and inequality (Braveman et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Marmot et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn line with the SDH model, FS is conceptualised as the psychological strain experienced when individuals are unable to meet their financial obligations, whereas FWB refers to having control over one\u0026rsquo;s finances and feeling confident about the financial future (Kim et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Netemeyer et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These constructs are influenced by intersecting demographic and structural factors such as age, income, gender, relationship status, and geographic location, all of which are empirically explored in this study.\u003c/p\u003e\u003cp\u003eBy integrating the SDH framework with these financial constructs, this study examines how systemic inequalities affect different demographic groups' experiences of FS and FWB, particularly during periods of economic disruption such as the COVID-19 pandemic.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Life-Cycle Theory of Financial Behaviour\u003c/h2\u003e\u003cp\u003eIn addition to the SDH framework, this study draws on Life-Cycle Theory to account for differences in financial stress and financial well-being among various age groups. Formulated by Modigliani and Brumberg (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1954\u003c/span\u003e), the life-cycle theory suggests that people's financial behaviours change in a predictable manner throughout their lives. In early adulthood, individuals typically have lower incomes and higher expenses (such as those related to education, housing, and raising children), which often results in increased financial strain. As individuals move through their careers, their income generally increases, allowing for asset accumulation and greater financial stability. In later years, many depend on savings and pensions to sustain their well-being in retirement. This theory is particularly pertinent for understanding generational variance in FS and FWB. Younger adults may experience heightened stress due to low income, student loans, or job insecurity, whereas older adults have the advantage of accumulated assets and financial experience. The longitudinal analysis in this study facilitates the examination of these life-cycle dynamics over time, offering a behavioural complement to the structural insights provided by the SDH framework.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Methodology","content":"\u003cp\u003eThis study employed a quantitative, longitudinal research design to explore changes in FS and FWB among South Africans over a three-year period from 2019 to 2021. The primary data source was the Old Mutual Rewards Program Survey, which provides consistent, standardised measures across time. Data were collected using structured survey instruments, including the CFPB Financial Well-Being Scale (CFPB \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003ea), ensuring the reliability and comparability of results across various demographic groups. The research design was informed by a structured, quantitative approach that focused on numerical data derived from a large respondent base. Specifically, 6,713 participants completed the FS assessments, while 2,923 individuals completed the FWB scale annually throughout the three-year period. Only participants who consistently responded across all three years were included in the final sample, facilitating the panel data analysis. This ensured internal validity by tracking changes within the same individuals rather than across different cohorts. The sampling frame was drawn from the Old Mutual Rewards Program database, which comprises over 1.3\u0026nbsp;million members. In 2019, South Africa's total population stood at approximately 58.5\u0026nbsp;million (Stats SA \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), underscoring the broad but focused reach of the survey population.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Data Collection\u003c/h2\u003e\u003cp\u003eData were collected as participants completed various surveys to earn points within the rewards program. If a participant completed multiple surveys within a year, only the initial submission for that year was used to maintain data consistency. The instruments were administered online via the Old Mutual Rewards Program\u0026rsquo;s webpage. Demographic variables analysed included age groups ranging from 18 to 65 years, income levels, marital status, residential province and gender. The data were analysed using the Statistical Package for the Social Sciences (SPSS) Version 25, with statistical consultation services from North-West University providing additional support.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Research Ethics\u003c/h2\u003e\u003cp\u003eThe usage of data was also governed by Old Mutual\u0026rsquo;s overarching privacy policy with the following statement applying specifically with regards to the rewards program:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAs set out in the Privacy Policy, your responses to surveys may be used in our academic and/or market research and analytics unit to refine our propositions to customers. The data collected from the surveys will not be identifiable, thus ensuring anonymity of your responses and the responses published for academic and/or market research purposes will be aggregated and anonymised.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e The study was approved on 30 September 2022 by the Faculty of Economic and Management Sciences (North-West University) Research Ethics Committee under ethics number NWU \u0026minus;\u0026thinsp;01822\u0026ndash;22 - A4 on 30 September 2022.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Measuring Instrument\u003c/h2\u003e\u003cp\u003eThe FWB scale assesses respondents' financial health using nine items rated from 1 (poor) to 10 (excellent), producing a total score between 9 and 90. This was converted to a standardised FWB score based on age-specific CFPB (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003ea) guidelines, and then scaled back to a range of 1\u0026ndash;10. For instance, a raw score of 20 for someone aged 18\u0026ndash;61 equates to a scaled score of approximately 5.56. The FS scale measured perceived financial stress using eight items with responses ranging from \"Overwhelming Stress\" to \"No Stress at All\" (Prawitz et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The FS score was calculated by averaging the item scores, resulting in a final value between 1.0 and 10.0, where higher scores indicated lower stress. For example, a total score of 28 yields an FS score of 3.5, indicating high financial distress.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of Sample Groups by Demographic Category for FS and FWB (2019\u0026ndash;2021)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFWB Sample (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFS Sample (n, %)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u0026ndash;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e129 (4.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e253 (3.77%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e585 (20.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1149 (17.12%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31\u0026ndash;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e833 (28.50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1781 (26.53%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e604 (20.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1495 (22.27%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41\u0026ndash;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e354 (12.11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e928 (13.82%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e179 (6.12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e496 (7.39%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51\u0026ndash;55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e116 (3.97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e306 (4.56%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56\u0026ndash;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66 (2.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e177 (2.64%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57 (1.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e128 (1.91%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR0\u0026ndash;R25,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,214 (75.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4,803 (71.55%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR25,001-R100,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e607 (20.77%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1,671 (24.89%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR100,000+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36 (1.23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98 (1.48%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66 (2.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e141 (2.10%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2002 (68.46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4627 (68.95%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e921 (31.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2086 (31.05%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1913 (65.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4,255 (63.38%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIn a relationship\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e785 (26.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1,951 (29.06%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Relationship\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67 (2.29%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e181 (2.69%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e158 (5.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e326 (4.87%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidential Province\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEastern Cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e342 (11.70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e844 (12.57%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFree State\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e107 (3.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e272 (4.05%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGauteng\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e776 (26.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1,720 (25.62%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKwaZulu-Natal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e511 (17.48%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1,199 (17.86%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLimpopo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144 (4.93%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e310 (4.62%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMpumalanga\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e101 (3.46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e250 (3.72%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNorthwest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e76 (2.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e201 (2.99%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNorthern Cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28 (0.96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e82 (1.22%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWestern Cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e535 (18.30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1,192 (17.76%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe study samples for FS (n\u0026thinsp;=\u0026thinsp;6713) and FWB (n\u0026thinsp;=\u0026thinsp;2923) were stratified across five key demographic variables (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The age group 31\u0026ndash;35 was the most represented, with an income distribution skewed toward the R0-R25,000 range. More than two-thirds of the sample comprised female respondents. Single individuals formed the largest relationship group, and Gauteng had the highest provincial representation. These demographics as depicted in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reflect the socioeconomic diversity relevant to evaluating financial well-being and stress over time.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Data Analysis and Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays the statistically significant differences for age, income, gender, relationship status and residential province. Each of these differences is discussed in more detail below.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary Table: Financial Stress and Financial Well-being Tests by Demographics (2019\u0026ndash;2021)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTest Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYears\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStatistical Significance (p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFindings Summary\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge vs FS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWelch's ANOVA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYounger groups (21\u0026ndash;30) showed significantly higher FS than older groups.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge vs FWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANOVA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOlder individuals (60+) had significantly higher FWB scores across years.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome vs FS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANOVA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFS improved with increasing income; lowest stress among R100,000\u0026thinsp;+\u0026thinsp;group.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome vs FWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANOVA (2019\u0026ndash;20), Welch (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFWB scores significantly increased with income.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender vs FS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT-Test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFemales reported higher FS levels (notably in the pandemic period).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender vs FWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT-Test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (2021 only)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMales showed slightly higher FWB scores than females.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship vs FS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANOVA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIndividuals in relationships consistently had lower FS levels.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship vs FWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANOVA (2019\u0026ndash;20), Welch (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.004 (2021 only)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFWB difference significant in 2021: people in relationships\u0026thinsp;\u0026gt;\u0026thinsp;single.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProvince vs FS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANOVA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFS levels varied significantly; most rural provinces had higher FS.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProvince vs FWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWelch's ANOVA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (all years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFWB scores higher in economically strong provinces like Gauteng.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAge and Financial Outcomes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe relationships between age and both FS and FWB were consistently significant across all three years (2019\u0026ndash;2021), as revealed by Welch\u0026rsquo;s ANOVA and standard ANOVA tests, respectively. Younger respondents (especially those aged 21\u0026ndash;30 years) reported markedly higher FS and lower FWB compared to older age groups. This aligns with the life-cycle hypothesis and findings from Collins and Urban (2019), who suggest that younger adults often enter the workforce with limited savings, lower incomes, and greater financial uncertainty. These conditions predispose them to heightened FS. Conversely, individuals aged 60 and above demonstrated the highest FWB and the lowest FS. This can be attributed to accumulated assets, stable income streams (e.g. pensions), and reduced dependents and debt obligations, as corroborated by Kempson et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Mantai and Marrone (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese results emphasise the critical importance of financial education and early career financial planning interventions targeted at younger demographics. The longitudinal nature of the data underscores persistent generational disparity, highlighting the structural need to support youth financial literacy and employment policies that enhance income stability and reduce early career financial stressors.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIncome and Economic Resilience\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe association between income and financial outcomes was the strongest among all demographic variables, with significant results across the FS and FWB for all years. Notably, income-related disparities in FWB were so pronounced in 2021 that the assumptions of variance equality were violated, necessitating the use of Welch's test. Respondents in higher income brackets consistently exhibited higher FWB and lower FS, a finding that mirrors empirical evidence from Joo and Grable (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and Cwynar et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic exacerbated these disparities; low-income groups faced job losses, reduced hours, and lacked financial buffers (Rogan \u0026amp; Skinner \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kansiime et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Meanwhile, higher-income respondents were more likely to have continued employment (e.g. through remote work) and access to credit, insurance, and investments. These results support the call for income-targeted social protection programs, including unemployment insurance reform and emergency savings incentives for low-income earners.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGender and Financial Disparity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStatistically significant gender differences were evident in both FS and FWB during the post-pandemic year (2021). Women reported higher levels of financial stress and lower financial well-being, reaffirming the global findings on gendered economic vulnerability. The observed disparities can be linked to gender pay gaps (Mosomi \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), occupational segmentation, and women\u0026rsquo;s overrepresentation in precarious employment sectors, as documented by Casale and Posel (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and De Miquel et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, the pandemic\u0026rsquo;s impact on caregiving responsibilities disproportionately affects women, amplifying their FS and hindering FWB (UN 2021). These results underline the necessity of a gender-sensitive policy design, especially in the domains of childcare support, workplace equity, and targeted financial literacy programs for women.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRelationship Status and Economic Buffering\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIndividuals in relationships consistently experienced lower FS and higher FWB compared to their single, divorced, or widowed counterparts. This trend, statistically significant in all FS tests and for FWB in 2021, aligns with the dual-income and resource-sharing advantages associated with marital unions (Brown 2010; Joo \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The buffering effect of a second income and mutual financial support within a marriage appears to have been especially critical during economic downturns.\u003c/p\u003e\u003cp\u003eThe role of cultural practices, such as lobola and extended familial financial obligations, is also noteworthy. These customs may place additional FS on married or soon-to-be-married individuals, particularly men (IOL \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yarbrough \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The significance of 2021 in the FWB may reflect shifting economic pressures post-lockdown, where single households bore disproportionate burdens due to a lack of income sharing.\u003c/p\u003e\u003cp\u003eThese findings validate prior work (Addo \u0026amp; Lichter \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Falconier \u0026amp; Jackson \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and call for greater attention to the financial vulnerabilities of single and single-parent households in policymaking, especially regarding tax benefits, subsidies, and access to affordable credit.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResidential Province and Geographic Inequality\u003c/b\u003e\u003c/p\u003e\u003cp\u003e Regional disparities were prominent in both the FS and FWB analyses. Provinces with stronger economies, such as Gauteng and the Western Cape, demonstrated significantly higher FWB scores and lower FS, while underdeveloped or rural provinces, such as the Eastern Cape and Free State, showed the opposite trend. These differences, confirmed by ANOVA and Welch tests, are attributable to regional variations in job availability, infrastructure, and access to financial services, as noted by Burger et al. (2017) and Finscope (2019).\u003c/p\u003e\u003cp\u003eCOVID-19 has intensified these spatial inequalities. Provinces reliant on tourism (e.g. Western Cape) experienced sharp economic decline, but their relatively higher baseline FWB may have cushioned residents\u0026rsquo; outcomes. Conversely, provinces with limited healthcare and social safety infrastructure have longer economic recovery periods (Venter et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results validate existing literature (Tacoli et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Visagie \u0026amp; Turok \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and point toward a need for geographically targeted development policies, including digital financial access initiatives and employment stimulation in rural provinces.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePost Hoc Tests\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePost hoc tests were conducted where the ANOVA indicated statistically significant differences between more than two groups. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the significant differences highlighted by the post hoc tests.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePost Hoc Analyses of Financial Stress and Well-being (2019\u0026ndash;2021)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTest Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYears\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eComparison Pairs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean Difference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTukey HSD (FS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u0026ndash;25 vs. 51\u0026ndash;60+; 26\u0026ndash;30 vs. 51\u0026ndash;60+; 31\u0026ndash;35 vs. 46\u0026ndash;60+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;0.576 to \u0026minus;\u0026thinsp;1.795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.048 to \u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u0026ndash;25 vs. 46\u0026ndash;60+; 26\u0026ndash;30 vs. 36\u0026ndash;60+; 31\u0026ndash;35 vs. 46\u0026ndash;60+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;0.413 to \u0026minus;\u0026thinsp;1.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.014 to \u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u0026ndash;25 vs. 46\u0026ndash;60+; 26\u0026ndash;30 vs. 41\u0026ndash;60+; 31\u0026ndash;35 vs. 41\u0026ndash;60+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;0.376 to \u0026minus;\u0026thinsp;1.327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.015 to \u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTukey HSD (FWB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u0026ndash;25, 26\u0026ndash;30, 31\u0026ndash;35, 36\u0026ndash;45, 51\u0026ndash;60 vs. 60+; 36\u0026ndash;40 vs. 46\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;2.549 to \u0026minus;\u0026thinsp;6.642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.009\u0026ndash;\u0026lt;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u0026ndash;25, 26\u0026ndash;30, 31\u0026ndash;35, 36\u0026ndash;45, 51\u0026ndash;60 vs. 60+; 36\u0026ndash;40 vs. 46\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;4.339 to \u0026minus;\u0026thinsp;6.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u0026ndash;\u0026lt;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u0026ndash;30, 31\u0026ndash;35, 36\u0026ndash;45 vs. 46\u0026ndash;50 and 60+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;2.597 to \u0026minus;\u0026thinsp;5.471\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.032\u0026ndash;\u0026lt;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTukey HSD (FS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;R25,000 vs. R25,001\u0026ndash;R100,000; \u0026lt;R25,000 vs. R100,000+; R25,001\u0026ndash;R100,000 vs. R100,000+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.546\u003c/p\u003e\u003cp\u003e-2.057\u003c/p\u003e\u003cp\u003e-1.510\u003c/p\u003e\u003cp\u003e1.672\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;R25,000 vs. R25,001-R100,000\u003c/p\u003e\u003cp\u003e\u0026lt;R25,000 vs. R100,000+\u003c/p\u003e\u003cp\u003e\u0026lt;R25,000 vs. Unknown\u003c/p\u003e\u003cp\u003eR25,001-R100,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR100,000\u0026thinsp;+\u0026thinsp;vs. Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.612\u003c/p\u003e\u003cp\u003e-1.905\u003c/p\u003e\u003cp\u003e-0.557\u003c/p\u003e\u003cp\u003e-1.292\u003c/p\u003e\u003cp\u003e1.348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e0.026\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;R25,000 vs. R25,001-R100,000\u003c/p\u003e\u003cp\u003e\u0026lt;R25,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR25,001-R100,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR100,000\u0026thinsp;+\u0026thinsp;vs. Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.602\u003c/p\u003e\u003cp\u003e-1.787\u003c/p\u003e\u003cp\u003e-1.185\u003c/p\u003e\u003cp\u003e1.574\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTukey HSD (FWB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;R25,000 vs. R25,001-R100,000\u003c/p\u003e\u003cp\u003e\u0026lt;R25,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR25,001-R100,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR100,000\u0026thinsp;+\u0026thinsp;vs. Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.388\u003c/p\u003e\u003cp\u003e-8.022\u003c/p\u003e\u003cp\u003e-6.634\u003c/p\u003e\u003cp\u003e7.318\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;R25,000 vs. R25,001-R100,000\u003c/p\u003e\u003cp\u003e\u0026lt;R25,000 vs. R100,000+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.570\u003c/p\u003e\u003cp\u003e-4.911\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGames-Howell (FWB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;R25,000 vs. R25,001-R100,000\u003c/p\u003e\u003cp\u003e\u0026lt;R25,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR25,001-R100,000 vs. R100,000+\u003c/p\u003e\u003cp\u003eR100,000\u0026thinsp;+\u0026thinsp;vs. Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.821\u003c/p\u003e\u003cp\u003e-7.652\u003c/p\u003e\u003cp\u003e-5.831\u003c/p\u003e\u003cp\u003e7.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e0.021\u003c/p\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTukey HSD (FS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIn Relationship vs. Unknown\u003c/p\u003e\u003cp\u003eIn relationship vs. Single\u003c/p\u003e\u003cp\u003eUnknown vs. Single\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.623\u003c/p\u003e\u003cp\u003e0.205\u003c/p\u003e\u003cp\u003e-0.412\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003cp\u003e0.015\u003c/p\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIn Relationship vs. Unknown\u003c/p\u003e\u003cp\u003eIn Relationship vs. Single\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.627\u003c/p\u003e\u003cp\u003e0.316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIn Relationship vs. Unknown\u003c/p\u003e\u003cp\u003eIn Relationship vs. Single\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.525\u003c/p\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGames-Howel (FWB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIn Relationship vs. Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.430\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProvince\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTukey HSD (FS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKZN vs. Western Cape\u003c/p\u003e\u003cp\u003eLimpopo vs. Western Cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.470\u003c/p\u003e\u003cp\u003e0.556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEastern Cape vs. KZN\u003c/p\u003e\u003cp\u003eKZN vs. Western Cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.335\u003c/p\u003e\u003cp\u003e0.366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGauteng vs. KZN\u003c/p\u003e\u003cp\u003eKZN vs. Northern Cape\u003c/p\u003e\u003cp\u003eKZN vs. Western Cape\u003c/p\u003e\u003cp\u003eLimpopo vs. Northern Cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.340\u003c/p\u003e\u003cp\u003e0.953\u003c/p\u003e\u003cp\u003e0.438\u003c/p\u003e\u003cp\u003e1.0064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003cp\u003e0.026\u003c/p\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGames- Howell\u003c/p\u003e\u003cp\u003e(FWB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEastern Cape vs. Western Cape\u003c/p\u003e\u003cp\u003eGauteng vs. Western Cape\u003c/p\u003e\u003cp\u003eKZN vs. Western cape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.248\u003c/p\u003e\u003cp\u003e1.711\u003c/p\u003e\u003cp\u003e1.937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003cp\u003e0.024\u003c/p\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKZN vs, Mpumalanga\u003c/p\u003e\u003cp\u003eLimpopo vs. Mpumalanga\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.778\u003c/p\u003e\u003cp\u003e0.928\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePost hoc tests for both FS and FWB revealed consistent age-related differences across 2019\u0026ndash;2021. Younger respondents, particularly those aged 21\u0026ndash;30, reported significantly lower FS and FWB scores compared with older age groups, especially those aged 51 years and above. The largest and most consistent gaps were observed between the youngest cohort (21\u0026ndash;25) and the 60\u0026thinsp;+\u0026thinsp;group, with mean differences ranging from \u0026minus;\u0026thinsp;1.3 to \u0026minus;\u0026thinsp;1.8 for FS (indicating higher stress among the youngest) and \u0026minus;\u0026thinsp;5.0 to \u0026minus;\u0026thinsp;6.6 for FWB (indicating lowers FWB for the youngest) (all p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Similar but smaller differences were also evident for those aged 26\u0026ndash;40 compared with the 51\u0026ndash;60\u0026thinsp;+\u0026thinsp;categories. In contrast, differences between adjacent younger groups (e.g., 21\u0026ndash;25 vs. 26\u0026ndash;30) were not significant. Overall, the results highlight a systematic pattern in which both financial stress decreases and financial well-being increase with age, with respondents aged 60 and older consistently reporting the most favourable outcomes across all three survey years.\u003c/p\u003e\u003cp\u003ePost hoc comparisons revealed strong and consistent income effects for both FS and FWB across 2019\u0026ndash;2021. Respondents earning less than R25,000 per month reported significantly lower FS and FWB scores than those in higher income brackets. The largest differences were consistently observed between the lowest-income group (\u0026lt;\u0026thinsp;R25,000) and the highest-income group (R100,000+), with mean gaps of \u0026minus;\u0026thinsp;1.8 to \u0026minus;\u0026thinsp;2.1 for FS (indicating higher stress among lower earners) and \u0026minus;\u0026thinsp;4.9 to \u0026minus;\u0026thinsp;8.0 for FWB (all p\u0026thinsp;\u0026lt;\u0026thinsp;.01). Middle-income respondents (R25,001\u0026ndash;R100,000) also scored lower than those earning above R100,000, with mean differences of \u0026minus;\u0026thinsp;1.2 to \u0026minus;\u0026thinsp;1.5 for FS and \u0026minus;\u0026thinsp;5.8 to \u0026minus;\u0026thinsp;6.6 for FWB (all p\u0026thinsp;\u0026lt;\u0026thinsp;.01). Overall, the findings underscore a systematic pattern in which higher income is associated with lower financial stress and higher financial well-being, while lower-income groups consistently face the most adverse outcomes.\u003c/p\u003e\u003cp\u003eDescriptive statistics indicated that women consistently reported higher FS and lower FWB than men across all three years of the study.\u003c/p\u003e\u003cp\u003ePost hoc tests indicated consistent differences in financial stress (FS) by relationship status across all years (2019\u0026ndash;2021). Respondents in a relationship reported significantly higher FS scores (indicating lower stress) than both single individuals and those with unknown status. Mean differences ranged from +\u0026thinsp;0.21 to +\u0026thinsp;0.63 (all p\u0026thinsp;\u0026le;\u0026thinsp;.015). Conversely, singles generally scored lower than those in relationships, reflecting greater stress levels. In 2021, a similar pattern extended to financial well-being (FWB), where those in a relationship scored significantly higher than respondents with unknown status (mean difference\u0026thinsp;+\u0026thinsp;2.43, p\u0026thinsp;=\u0026thinsp;.009). Overall, the results suggest that being in a relationship is associated with reduced financial stress and, to a lesser extent, higher well-being, whereas being single or having an unknown relationship status is linked to less favourable financial outcomes.\u003c/p\u003e\u003cp\u003eSignificant provincial differences emerged in both financial stress (FS) and financial well-being (FWB). For FS, respondents from KwaZulu-Natal (KZN) consistently differed from those in other provinces: in 2019, KZN residents reported higher FS scores (lower financial stress) than those in the Western Cape (+\u0026thinsp;0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), while Limpopo respondents also scored higher than the Western Cape (+\u0026thinsp;0.56, p\u0026thinsp;=\u0026thinsp;.019). In 2020, FS scores were lower in the Eastern Cape compared with KZN (\u0026ndash;0.34, p\u0026thinsp;=\u0026thinsp;.047), but higher in KZN relative to the Western Cape (+\u0026thinsp;0.37, p\u0026thinsp;=\u0026thinsp;.005) and Northern Cape (+\u0026thinsp;0.43, p\u0026thinsp;=\u0026thinsp;0.001). In 2021, notable contrasts included lower FS scores in Gauteng compared with KZN (\u0026ndash;0.34, p\u0026thinsp;=\u0026thinsp;.010), and higher FS scores in KZN and Limpopo relative to the Northern Cape (+\u0026thinsp;0.95 to +\u0026thinsp;1.01, p\u0026thinsp;\u0026lt;\u0026thinsp;.05), as well as higher FS scores in KZN versus the Western Cape (+\u0026thinsp;0.44, p\u0026thinsp;=\u0026thinsp;.001). For FWB, differences were also observed. In 2019, respondents in the Eastern Cape, Gauteng, and KZN all reported significantly higher FWB scores than those in the Western Cape (+\u0026thinsp;1.71 to +\u0026thinsp;2.25, p\u0026thinsp;\u0026le;\u0026thinsp;.026). By 2021, KZN and Limpopo reported higher FWB compared with Mpumalanga (+\u0026thinsp;0.78 to +\u0026thinsp;0.93, p\u0026thinsp;\u0026le;\u0026thinsp;.007). Overall, the results suggest regional variation in both stress and well-being, with the Western Cape often scoring less favourably in comparison with other provinces, while Gauteng, KZN and Limpopo tended to report more positive outcomes.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Hypothesis Testing\u003c/h2\u003e\u003cp\u003eH1: There is a significant relationship between age and financial stress.\u003c/p\u003e\u003cp\u003eStatistical testing using Welch\u0026rsquo;s ANOVA revealed a significant relationship between age and FS across all three years (2019\u0026ndash;2021), with p-values less than 0.001 in each year. The largest and most consistent gaps were observed between the youngest cohort (21\u0026ndash;25) and the 60\u0026thinsp;+\u0026thinsp;group, with mean differences ranging from \u0026minus;\u0026thinsp;1.3 to \u0026minus;\u0026thinsp;1.8 for FS (indicating higher stress among the youngest). These findings align with the life-cycle hypothesis and support H1.\u003c/p\u003e\u003cp\u003eH2: There is a significant relationship between age and financial well-being.\u003c/p\u003e\u003cp\u003eStandard ANOVA tests indicated that age significantly influenced FWB during 2019\u0026ndash;2021 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Older respondents, especially those aged 60\u0026thinsp;+\u0026thinsp;years, consistently reported higher FWB scores. The largest and most consistent gaps were observed between the youngest cohort (21\u0026ndash;25) and the 60\u0026thinsp;+\u0026thinsp;group, with mean differences ranging from \u0026minus;\u0026thinsp;5.0 to \u0026minus;\u0026thinsp;6.6 for FWB (indicating lowers FWB for the youngest) (all p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Therefore, H2 is supported.\u003c/p\u003e\u003cp\u003eH3: There is a significant relationship between income and financial stress.\u003c/p\u003e\u003cp\u003eIncome was significantly associated with FS across all years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ANOVA). Participants earning higher incomes (R100000+) experienced a substantially lower FS than those earning less. For instance, the largest differences were consistently observed between the lowest-income group (\u0026lt;\u0026thinsp;R25,000) and the highest-income group (R100,000+), with mean gaps of \u0026minus;\u0026thinsp;1.8 to \u0026minus;\u0026thinsp;2.1 for FS (indicating higher stress among lower earners). These results confirm H3.\u003c/p\u003e\u003cp\u003eH4: There is a significant relationship between income and financial well-being.\u003c/p\u003e\u003cp\u003eThe FWB scores increased with income, as shown by the significant ANOVA and Welch\u0026rsquo;s test results (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 across years). Post hoc comparisons indicated that the largest differences were consistently observed between the lowest-income group (\u0026lt;\u0026thinsp;R25,000) and the highest-income group (R100,000+), with mean gaps of \u0026minus;\u0026thinsp;4.9 to \u0026minus;\u0026thinsp;8.0 for FWB (all p\u0026thinsp;\u0026lt;\u0026thinsp;.01). Accordingly, H4 is accepted.\u003c/p\u003e\u003cp\u003eH5: There is a significant relationship between gender and financial stress.\u003c/p\u003e\u003cp\u003eAn independent-sample t-test for 2019\u0026ndash;2021 revealed that females reported significantly higher FS levels than males (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This finding supports H5, suggesting that gender differences meaningfully influence financial stress, particularly in the pandemic context.\u003c/p\u003e\u003cp\u003eH6: There is a significant relationship between gender and financial well-being.\u003c/p\u003e\u003cp\u003eSimilarly, males demonstrated significantly higher FWB scores than females in 2021 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, t-test), a finding consistent with gender-based disparities in employment and income security. Therefore, H6 is partially supported.\u003c/p\u003e\u003cp\u003eH7: There is a significant relationship between the relationship status and financial stress.\u003c/p\u003e\u003cp\u003eRelationship status significantly affected FS across all three years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ANOVA). Respondents in relationships reported a consistently lower FS than those who were single. Post hoc tests confirmed this difference, with people in relationships experiencing significantly less stress than single individuals (Mean differences ranged from 0.21 to 0.63, all p\u0026thinsp;\u0026le;\u0026thinsp;.021). Thus, H7 is confirmed.\u003c/p\u003e\u003cp\u003eH8: There is a significant relationship between relationship status and financial well-being.\u003c/p\u003e\u003cp\u003eAlthough FWB did not vary significantly by relationship status in 2019\u0026ndash;2020, a significant difference emerged in 2021 (p\u0026thinsp;=\u0026thinsp;0.004, Welch\u0026rsquo;s ANOVA). Post hoc tests revealed people in relationships reported higher FWB scores than single individuals (mean difference\u0026thinsp;+\u0026thinsp;2.43, p\u0026thinsp;=\u0026thinsp;.009). Consequently, H8 is partially supported, with significance observed in the pandemic recovery period.\u003c/p\u003e\u003cp\u003eH9: There is a significant relationship between province of residence and financial stress.\u003c/p\u003e\u003cp\u003eThe ANOVA results indicated significant provincial differences in FS during 2019\u0026ndash;2021 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Residents in KZN and Gauteng experienced less FS compared to those in the Eastern Cape and Northern Cape. Therefore, H9 is supported.\u003c/p\u003e\u003cp\u003eH10: There is a significant relationship between province of residence and financial well-being.\u003c/p\u003e\u003cp\u003eWelch\u0026rsquo;s ANOVA also revealed significant differences in FWB by province (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in all years. Respondents in the KZN and Gauteng reported higher FWB scores than those in the Western Cape and Mpumalanga. These findings affirm H10.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Discussion and Implications","content":"\u003cp\u003eThe results of the hypothesis testing affirm that demographic variables such as age, income, gender, relationship status, and province of residence significantly influence FS and FWB among South Africans, particularly during and after the COVID-19 pandemic. These findings validate the theoretical and empirical frameworks and reinforce the structural nature of financial vulnerability.\u003c/p\u003e\u003cp\u003eThe age-related differences observed in this study reaffirm the life-cycle theory of financial well-being. Younger adults aged 21\u0026ndash;25 years experienced significantly more FS and lower FWB compared to older individuals, supporting H1 and H2. This trend is consistent with the findings of Collins and Urban (2019) and Kempson et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who linked youth financial vulnerability to limited job experience, unstable income, and lower savings. It also underscores the importance of early financial education and targeted support for youth entering the labour market.\u003c/p\u003e\u003cp\u003eIncome was confirmed as a predictor of FS and FWB (H3 and H4), with low-income earners (particularly those below R25,000 per month) experiencing heightened stress and reduced well-being. The widening gap in 2021, especially during the pandemic, echoes the findings of Rogan and Skinner (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Kansiime et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and highlights how economic shocks disproportionately impact already vulnerable groups. These outcomes call for stronger income protection policies such as emergency grants, wage support, and inclusive financial tools.\u003c/p\u003e\u003cp\u003eGender-based disparities (H5 and H6) were also statistically significant, with women experiencing more FS and less FWB than men, particularly in 2021. This aligns with the findings of Mosomi (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Casale and Posel (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who argue that wage gaps, caregiving roles, and occupational segmentation disadvantage women financially. The results highlight a pressing need for gender-responsive budgeting and equitable access to formal employment, childcare support, and financial products.\u003c/p\u003e\u003cp\u003eRegarding relationship status, individuals in relationships experienced significantly lower FS and higher FWB than single individuals (H7 and H8). These findings are consistent with Brown (2010) and Falconier and Jackson (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), confirming that income pooling and financial collaboration within marriages provide buffers against economic shocks. These implications are particularly relevant for single-parent households and previously married individuals, who may require additional social and financial support mechanisms.\u003c/p\u003e\u003cp\u003eFinally, the findings on geographic variation (H9 and H10) revealed entrenched spatial inequalities. Provinces such as Gauteng and KZN consistently exhibited better FS and FWB outcomes compared to more rural provinces such as the Eastern Cape, Northern Cape and Mpumalanga. These results reflect disparities in infrastructure, employment opportunities, and access to financial services, as noted by Burger et al. (2017) and the Finscope (2019). Policymakers must address these disparities through geographically targeted interventions such as rural employment schemes, digital financial access, and provincial infrastructure development.\u003c/p\u003e\u003cp\u003eCollectively, these results offer a case for an intersectional understanding of financial vulnerability in South Africa. They also support the application of the Social Determinants of Health framework by demonstrating how demographic, geographic, and socioeconomic factors jointly shape financial stress and well-being. As future economic disruptions are likely, these insights should inform more equitable and resilient policy interventions.\u003c/p\u003e"},{"header":"7. Conclusion and Recommendation","content":"\u003cp\u003eThis study examined how (FS and FWB varied across key demographic dimensions, age, income, gender, relationship status, and province of residence, over a three-year period (2019\u0026ndash;2021), using longitudinal data from the Old Mutual Rewards Program. The statistical analysis confirmed all ten hypotheses, revealing significant associations between these demographic variables and both FS and FWB.\u003c/p\u003e\u003cp\u003eThe findings demonstrate that younger adults, low-income individuals, women, those who are single, and residents of underdeveloped or rural provinces are most at risk of financial vulnerability. The COVID-19 pandemic has further amplified these disparities, especially among low-income earners, females and singles. In contrast, older adults, higher-income individuals, men, persons in relationships, and residents in certain provinces, often with stronger economies, consistently reported better financial outcomes. These insights not only extend the current scholarship on financial well-being but also highlight the layered nature of financial vulnerability in South Africa. They reveal how intersecting identities and geographic realities shape individuals' capacity to manage financial obligations and plan for their future.\u003c/p\u003e\u003cp\u003eIn response, several practical and policy recommendations are offered. First, financial education programs should begin at the school level and continue into adulthood with a special focus on young adults and women. Second, income support mechanisms, including basic income grants and targeted relief, should be expanded to cushion low-income households during economic downturn. Third, infrastructure investment in rural and underserved provinces is essential for bridging the regional disparities in FS and FWB. Fourth, gender equity policies must address both labour market access and caregiving responsibilities. This study is limited by its reliance on self-reported measures and digital-only survey access, which may underrepresent individuals without consistent internet access. Future research should explore the long-term trajectory of financial recovery beyond 2021 and include qualitative methods to capture the lived experiences behind quantitative trends. Doing so will offer a richer and more nuanced understanding of the financial realities faced by different demographic groups. Ultimately, a multidimensional strategy that integrates financial, social, and health considerations is vital to build a financially resilient and equitable South African society.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are very grateful to the reviewers and editors for their very insightful comments and suggestions on the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLeon Steyn\u003c/p\u003e\n\u003cp\[email protected] \u003c/p\u003e\n\u003cp\u003ehttp://orcid.org/0009-0006-2448-3192 \u003c/p\u003e\n\u003cp\u003eFaculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa\u003c/p\u003e\n\u003cp\u003eProf Surika van Rooyen\u003c/p\u003e\n\u003cp\[email protected]\u003c/p\u003e\n\u003cp\u003ehttps://orcid.org/0000-0002-0601-1371\u003c/p\u003e\n\u003cp\u003eFaculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa\u003c/p\u003e\n\u003cp\u003eProf Jaco Fouché\u003c/p\u003e\n\u003cp\[email protected]\u003c/p\u003e\n\u003cp\u003ehttps://orcid.org/0000-0002-7791-5669 \u003c/p\u003e\n\u003cp\u003eFaculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa\u003c/p\u003e\n\u003cp\u003eDr Morris Mensah\u003c/p\u003e\n\u003cp\[email protected]\u003c/p\u003e\n\u003cp\u003ehttps://orcid.org/0000-0008-5130-3032\u003c/p\u003e\n\u003cp\u003eFaculty of Economic and Management Sciences, North-West University, School of Accounting Sciences and WorkWell Research Unit, Potchefstroom, South Africa\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCorrespondence:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eProf Jaco Fouché\u003c/p\u003e\n\u003cp\[email protected] \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLeon Steyn is the MCom candidate responsible for conceptualising the paper, conducting the literature review, implementing the research methodology, and interpreting the research findings. Prof Surika van Rooyen is the supervisor, and Prof JP Fouché is the co-supervisor (who also designed the study as part of a larger study). Both supervisors acted as critical readers and provided guidance throughout the study. Dr Morris Mensa was responsible for quality review and adjusting the paper to the requirements of the journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConfirmed with all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Faculty of Economic and Management Sciences Research Ethics Committee (EMS-REC) of the North-West University, South Africa (Approval No. NWU-01822-22-A4). EMS-REC operates under the authority of the Senate Committee on Research Ethics (SCRE) and functions independently in accordance with internationally recognized standards for ethical oversight. Its role includes evaluating and confirming ethical compliance in commerce-related research, as well as providing advisory and training capacity in research ethics. The first approval was granted on 30 September 2022, following the conclusion of a Non-Disclosure Agreement between Old Mutual and the North-West University in April 2022. Approval was subsequently extended on 30 July 2024 to include the work of master’s students making use of the same dataset.\u003c/p\u003e\n\u003cp\u003eThe study was identified as low risk, and only secondary data were used. All conditions of approval, including the requirement to notify EMS-REC without delay of any adverse events or ethical concerns, and the need to seek prior approval for any amendments to the research protocol, were strictly adhered to.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a quantitative, longitudinal design to examine changes in financial stress (FS) and financial well-being (FWB) among South Africans from January 2019 to December 2021. The primary data source was the Old Mutual Rewards Program Surveys. Participation in these surveys was governed by Old Mutual’s overarching privacy policy, which was communicated to all participants. Specifically, the Rewards Program informed participants that:\u003c/p\u003e\n\u003cp\u003e“As set out in the Privacy Policy, your responses to surveys may be used in our academic and/or market research and analytics unit to refine our propositions to customers. The data collected from the surveys will not be identifiable, thus ensuring anonymity of your responses and the responses published for academic and/or market research purposes will be aggregated and anonymised.”\u003c/p\u003e\n\u003cp\u003eAll participants voluntarily agreed to participate in the Rewards Program surveys, and by doing so, consented to the use of their anonymised responses for academic research purposes. No vulnerable individuals were included in the study. Participants received points for completing surveys, which could be redeemed with rewards partners. As part of Old Mutual Rewards’ objective to promote good financial behaviour and education, participants could also earn points for a variety of qualifying financial wellness activities that included the completion of these surveys. Points were not transferable, could not be exchanged, sold, or redeemed for cash, and had no cash value. Participants were free to withdraw from a survey at any time, though in such cases, the corresponding points would not be awarded.\u003c/p\u003e\n\u003cp\u003eAll data were anonymised by Old Mutual before being made available to the North-West University, ensuring the privacy and confidentiality of participants. The anonymised data are stored in digital format on an official North-West University OneDrive, with access strictly limited to the principal investigator, the statistician, and authorized members of the research team.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is governed by a non-disclosure agreement between the North-West university and Old Mutual. Available on request. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdams-Prassl A, Boneva T, Golin M, Rauh C (2020) Inequality in the impact of the coronavirus shock: Evidence from real-time surveys. 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Law \u0026amp; Social Inquiry 46(4):944\u0026ndash;970. https://www.cambridge.org/core/journals/law-and-social-inquiry/article/very-long-engagements-the-persistent-authority-of-bridewealth-in-a-postapartheid-south-african-community/D839A712784A82946BC05567B62FA9B3\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"financial stress, financial well-being, COVID-19 pandemic, socioeconomic inequality, demographic disparities, South Africa","lastPublishedDoi":"10.21203/rs.3.rs-7571480/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7571480/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFinancial stress (FS) and financial well-being (FWB) are experienced unevenly across South Africa\u0026rsquo;s demographic and geographic groups, with the COVID-19 pandemic further deepening these disparities. This study investigates how FS and FWB changed over a three-year period (2019\u0026ndash;2021) across five key demographic variables: age, income, gender, relationship status, and province of residence. It also examines the exacerbating effects of the COVID-19 pandemic on these trends. Using a longitudinal panel design, the study analysed data from the Old Mutual Rewards Program survey. In total, 6,713 individuals were assessed annually for FS and 2,923 for FWB. Statistical analyses, including ANOVA, Welch\u0026rsquo;s test, and post hoc comparisons, were used to assess group differences, which showed significant relationships between all five demographic variables and both FS and FWB scores. Younger adults, lower-income earners, women, single individuals, and residents of many economically marginalised provinces reported higher FS and lower FWB. The findings highlight the need for financial interventions and policy measures, such as youth-focused financial literacy programs, gender-equitable employment policies, and geographically tailored social protections. By incorporating longitudinal evidence, this study contributes to both the theoretical understanding and practical design of strategies aimed at improving financial resilience in the context of inequality and crises.\u003c/p\u003e","manuscriptTitle":"Demographic Determinants of Financial Stress and Well-Being in South Africa: Evidence from a Longitudinal Panel (2019–2021)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-20 07:57:27","doi":"10.21203/rs.3.rs-7571480/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"81a8a5b5-0cef-423d-9ca8-9333ff53fe7d","owner":[],"postedDate":"October 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56491558,"name":"Health sciences/Health care"},{"id":56491559,"name":"Biological sciences/Psychology"},{"id":56491560,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-02-03T08:27:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-20 07:57:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7571480","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7571480","identity":"rs-7571480","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}