Abstract
Background
As South Africa’s population rapidly ages, the burden of non-communicable diseases and the challenges of performing daily care activities among older individuals are increasing. This study investigates trends in self-reported difficulties with daily care activities among older adults in South Africa and examines the association between these difficulties, sociodemographic factors, and chronic conditions.
Methods
The study used cross-sectional data from ten rounds of South Africa General Household Survey (2012–2021). Sample population included 26,362 men and 42,400 women aged 60 years and above. The outcome measure was assessed by self-reported difficulty in performing basic care activities such as washing or dressing.
Results
Between 2012 and 2021, the percentage of participants reporting “A lot of difficulty” increased by 79.75%, “Some difficulty” increased by 112.11%, while “Unable to do” decreased by 8.97%. The risk of self-care difficulties was higher for men (RR = 1.11, 95% CI = 1.02, 1.20) and increased with age: RR = 1.24 (95% CI = 1.08, 1.42) for ages 65–69; RR = 2.27 (95% CI = 2.00, 2.58) for ages 70–74; and RR = 5.65 (95% CI = 5.08, 6.28) for ages 75+. Not being currently married (RR = 1.65, 95% CI = 1.51, 1.79), being of African/Black (RR = 1.21, 95% CI = 1.06, 1.38) or Coloured race (RR = 1.41, 95% CI = 1.21, 1.65), and having diabetes (RR = 1.44, 95% CI = 1.34, 1.55), hypertension (RR = 1.35, 95% CI = 1.26, 1.45), or asthma (RR = 1.30, 95% CI = 1.14, 1.48) were also associated with a higher risk of self-care difficulties.
Conclusion
There was a notable increase in the proportion of participants reporting significant difficulty and some difficulty in performing self-care tasks, while a decrease was observed in the category of participants unable to do such tasks. Health policies should prioritize the specific needs of vulnerable sociodemographic and health groups, considering their increased risk of self-care difficulties.
Keywords: Health inequality, Elderly health, Self-care, South Africa, Global health
Background
The growing demand for elderly care in resource-poor countries is an important public health concern, notably in the case of South Africa, where the elderly population is expanding at a rapid rate. Life expectancy in South Africa is relatively low (59.3 years for men and 64.6 years for women in 2021) [1] riven by factors such as widespread poverty, socioeconomic inequality, and high rates of life-threatening diseases like tuberculosis and HIV/AIDS [2]. Nonetheless, South Africa has the second largest population aged 60 years or above among the sub-Saharan African nations [3], and the proportion of older adults are expected to account for 9.1% of the population in 2022 compared with 7.7% in 2012 [4].
The disease profile in South Africa is traditionally characterized by a higher burden of infectious diseases [5–8]. However, with increased urbanization and lifestyle changes, non-communicable diseases (NCDs) such as diabetes and heart disease have rapidly expanded, leading to a greater demand for care and monitoring. This rapid shift from a disproportionate burden of infectious diseases to NCDs can overwhelm healthcare systems as age-related physical decline makes it more common for older people to require assistance even with the daily tasks including eating, dressing, and bathing. As people age, the growing need for care impacts not only their physical health but also their mental health and social well-being [9, 10]. Intuitively, difficulties in performing daily living and self-care activities can significantly reduce the opportunities for social gathering and lead to feeling of isolation, which can further intensify the struggle with physical difficulties, depression, and related mental health challenges, leading to a decline in overall well-being.
However, the challenges of aging and the rise of NCDs are not experienced equally across sociodemographic groups [11]. Research has shown considerable gender and racial disparities in the prevalence of NCDs, physical and mental disability and difficulty in performing the activities of daily living [12, 13]. In particular, older women, especially those from disadvantaged backgrounds, are more likely to report difficulties with activities of daily living compared to men [14, 15]. This can be due to a range of factors, including differences in biology, lifestyle behaviours, social roles and expectations, and access to healthcare and social support [16].
Current research on gender and racial disparities on functional limitations for difficulties in performing activities of daily living are lacking in the context of South Africa, however, a large number of studies have documented the racial differences in physical and mental health status and access to basic healthcare services [17–21]. In general, individuals of Black and coloured background are more likely to experience poorer health status and lower quality of life than those from white or other communities [22–24]. Addressing these gender and racial disparities in health status, especially among older adults is crucial for promoting healthy aging and ensuring that individuals suffering from NCDs can live as fully and independently as possible during old age. Given the critical importance of the issue, this study will fill an important gap in the existing literature and can have important implications for healthcare and social policy.
Methods
Data source and study population
This study utilized data from the South Africa General Household Survey conducted by Statistics South Africa (Stats SA) [25]. The survey collects information on a range of topics including demographics, education, employment, health, and access to basic services. The dataset used in this study included data from the years 2012 to 2021, which were the most recent years with publicly available data at the time of analysis. The survey employs a multistage stratified random sampling design to select households and individuals for inclusion, and oversampled certain population groups, such as individuals living in informal dwellings and individuals living in the former homelands. Data were collected through face-to-face interviews with household members, using computer-assisted personal interviewing (CAPI) technology. Data were processed to ensure consistency and accuracy, including checks for missing or out-of-range values, before being combined into a single dataset for analysis. Ethical approval was not required, as the datasets are secondary and publicly available.
Measurement of variables
The outcome variable for this study was self-reported difficulty in performing daily activities. Participants were asked to rate their level of difficulty using the following response options: (1) No difficulty, (2) Some difficulty, (3) A lot of difficulty, and (4) Unable to do. The one-item measure of Self-reported activities of daily living has been used in previous studies as it can help identify a wide spectrum of disabilities [26, 27]. Selection of the explanatory variables were guided by a literature review in PubMed: ((“self-care” OR “self-care”) AND (“gender” OR “sex”) AND (“racial disparities” OR “ethnic disparities” OR “racial inequality” OR “ethnic inequality”) AND (“aging” OR “older individuals” OR “elderly” OR “geriatric”)). Based on the insights from the review, and availability of the variables in the dataset, the following were included in the analysis:
Gender: Male, Female.
Race: African, Black, Coloured, Indian/Asian, White.
Age: 60-, 65–69, 70–74, 75+.
Marital status: Married, Divorced, Widowed, Other.
Area: Urban, Rural.
Province: Western Cape, Eastern Cape, Northern Cape, Free State, KwaZulu Natal, Northwest, Gauteng, Mpumalanga, Limpopo.
Diabetes: No, Yes.
Hypertension: No, Yes.
Asthma: No, Yes.
Year: 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021.
Statistical analysis
The data were analyzed using statistical software including Stata 16 (Stata Statistical Software. College Station, TX: StataCorp LLC) and R Studio (Posit Software, PBC, Boston, MA). Datasets from the ten rounds of survey were first checked for the target variables, and then renamed and recoded before merging into one dataset. Descriptive statistics (percentage) were used to summarize variables by the level of the outcome variable with chi-square tests to assess group differences. The trend in the proportion of participants with any level of difficulty in self-care by sex and race was presented as line charts. The association between difficulty in self-care and the explanatory variables was measured using binary logistic regression methods. We ran five different models to determine the adjusted effects of various demographic, geographic, and health-related factors. Results were reported as odds ratios with corresponding 95% confidence intervals. Multicollinearity test was then performed using the VIF statistic to make sure no explanatory variable was strongly correlated with the others. We also reported area under the ROC curve for each of the regression models which gives an idea about how well the given model can distinguish between the cases and non-cases. As sensitivity tests, we calculated the Predicted probabilities to show the actual probability of the outcome for different age groups by sex, area, race, diabetes, hypertension, and asthma.
Results
Table 1 presents the percentage of participants with varying levels of self-care needs by demographic characteristics and health conditions. The percentage reporting unable to do in self-care generally increases with age, ranging from 12.40% in the 60–64 age group to 64.1% in the 75 + age group. Women have a higher percentage of reporting unable to do (68.4%) compared to men (31.6%). The percentage of reporting no difficulty (72.4%) was comparatively higher among the African/Black participants. Among the provinces, the Eastern Cape and Gauteng have the highest percentage reporting no difficulty in self-care (16.2%). The percentage of individuals reporting significant self-care difficulties varied slightly over the years, decreasing from 12.8% in 2012 to 5.6% in 2021.
Table 1.
Percentage of participants with different degrees of self-care needs
| No difficulty | Some difficulty | A lot of difficulty | Unable to do | p | |
|---|---|---|---|---|---|
| N | 65,491 (95.2%) | 2,025 (2.9%) | 736 (1.1%) | 510 (0.7%) | |
| age | |||||
| 60–64 | 22,792 (34.8%) | 256 (12.6%) | 98 (13.3%) | 63 (12.4%) | < 0.001 |
| 65–69 | 16,642 (25.4%) | 254 (12.5%) | 82 (11.1%) | 55 (10.8%) | |
| 70–74 | 11,387 (17.4%) | 351 (17.3%) | 106 (14.4%) | 65 (12.7%) | |
| 75+ | 14,670 (22.4%) | 1,164 (57.5%) | 450 (61.1%) | 327 (64.1%) | |
| Gender | |||||
| Male | 25,364 (38.7%) | 601 (29.7%) | 236 (32.1%) | 161 (31.6%) | < 0.001 |
| Female | 40,127 (61.3%) | 1,424 (70.3%) | 500 (67.9%) | 349 (68.4%) | |
| Population group | |||||
| African/Black | 47,398 (72.4%) | 1,567 (77.4%) | 559 (76.0%) | 373 (73.1%) | < 0.001 |
| Coloured | 6,721 (10.3%) | 181 (8.9%) | 91 (12.4%) | 80 (15.7%) | |
| Indian/Asian | 1,746 (2.7%) | 66 (3.3%) | 24 (3.3%) | 4 (0.8%) | |
| White | 9,626 (14.7%) | 211 (10.4%) | 62 (8.4%) | 53 (10.4%) | |
| Currently married | |||||
| Yes | 31,149 (47.6%) | 541 (26.7%) | 196 (26.6%) | 148 (29.0%) | < 0.001 |
| No | 34,342 (52.4%) | 1,484 (73.3%) | 540 (73.4%) | 362 (71.0%) | |
| Province | |||||
| Western Cape | 7,592 (11.6%) | 174 (8.6%) | 83 (11.3%) | 67 (13.1%) | < 0.001 |
| Eastern Cape | 10,595 (16.2%) | 287 (14.2%) | 115 (15.6%) | 90 (17.6%) | |
| Northern Cape | 3,507 (5.4%) | 113 (5.6%) | 41 (5.6%) | 44 (8.6%) | |
| Free State | 4,538 (6.9%) | 95 (4.7%) | 41 (5.6%) | 28 (5.5%) | |
| KwaZulu-Natal | 10,142 (15.5%) | 631 (31.2%) | 195 (26.5%) | 86 (16.9%) | |
| North West | 4,981 (7.6%) | 94 (4.6%) | 34 (4.6%) | 45 (8.8%) | |
| Gauteng | 10,602 (16.2%) | 240 (11.9%) | 63 (8.6%) | 58 (11.4%) | |
| Mpumalanga | 5,130 (7.8%) | 144 (7.1%) | 55 (7.5%) | 32 (6.3%) | |
| Limpopo | 8,404 (12.8%) | 247 (12.2%) | 109 (14.8%) | 60 (11.8%) | |
| Area | |||||
| Urban | 38,610 (59.0%) | 1,098 (54.2%) | 373 (50.7%) | 265 (52.0%) | < 0.001 |
| Rural | 26,881 (41.0%) | 927 (45.8%) | 363 (49.3%) | 245 (48.0%) | |
| Diabetes | |||||
| No | 55,209 (84.4%) | 1,511 (74.7%) | 525 (71.3%) | 387 (76.0%) | < 0.001 |
| Yes | 10,218 (15.6%) | 512 (25.3%) | 211 (28.7%) | 122 (24.0%) | |
| Hypertension | |||||
| No | 37,773 (57.7%) | 879 (43.5%) | 319 (43.3%) | 228 (44.8%) | < 0.001 |
| Yes | 27,651 (42.3%) | 1,144 (56.5%) | 417 (56.7%) | 281 (55.2%) | |
| Asthma | |||||
| No | 62,667 (95.8%) | 1,909 (94.4%) | 683 (92.8%) | 479 (94.1%) | < 0.001 |
| Yes | 2,757 (4.2%) | 114 (5.6%) | 53 (7.2%) | 30 (5.9%) | |
| Year | |||||
| 2012 | 8,368 (12.8%) | 194 (9.6%) | 69 (9.4%) | 68 (13.3%) | < 0.001 |
| 2013 | 8,603 (13.1%) | 236 (11.7%) | 87 (11.8%) | 74 (14.5%) | |
| 2014 | 8,767 (13.4%) | 186 (9.2%) | 81 (11.0%) | 79 (15.5%) | |
| 2015 | 6,457 (9.9%) | 173 (8.5%) | 80 (10.9%) | 51 (10.0%) | |
| 2016 | 6,407 (9.8%) | 161 (8.0%) | 49 (6.7%) | 51 (10.0%) | |
| 2017 | 6,613 (10.1%) | 158 (7.8%) | 59 (8.0%) | 43 (8.4%) | |
| 2018 | 6,727 (10.3%) | 169 (8.3%) | 76 (10.3%) | 39 (7.6%) | |
| 2019 | 6,495 (9.9%) | 389 (19.2%) | 131 (17.8%) | 59 (11.6%) | |
| 2020 | 3,394 (5.2%) | 173 (8.5%) | 48 (6.5%) | 18 (3.5%) | |
| 2021 | 3,660 (5.6%) | 186 (9.2%) | 56 (7.6%) | 28 (5.5%) |
Table 2 shows the risk ratios of reporting difficulties in performing self-care activities based on various demographic, geographic, and health-related factors. Model 5 results indicate that men initially had a lower risk of self-care difficulties compared to women; however, this association became insignificant after adjusting for race, marital status, and geographic factors, and reversed (RR = 1.11, 95% CI = 1.02, 1.20) after further adjustments for diabetes, hypertension, and asthma. Older age was strongly associated with an increased risk of reporting difficulties in self-care activities. Compared to the reference age group of 60–64 years, the risk ratios for reporting difficulties in self-care activities increased to 1.24 (95%CI = 1.08, 1.42) for ages 65–69, 2.27 (95%CI = 2.00, 2.58) for ages 70–74, and 5.65 (95%CI = 5.08, 6.28) for ages 75 and above. Those who were not currently married had a higher risk of reporting difficulties in self-care activities, with a risk ratio of 1.65 (95%CI = 1.51, 1.79) compared to those who are currently married. Regarding race, African/Black (RR = 1.21, 95%CI = 1.06,1.38) and Colored (RR = 1.41, 95%CI = 1.21,1.65) participants had higher risk of reporting difficulties in self-care activities.
Table 2.
Risk ratios of the factors associated with difficulties in performing self-care
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | |
|---|---|---|---|---|---|
| Sex (Female) | ref | ref | ref | ref | ref |
| Male |
0.71*** [0.66,0.76] |
0.81*** [0.76,0.88] |
1.04 [0.96,1.13] |
1.03 [0.95,1.12] |
1.11* [1.02,1.20] |
| Age (60–64) | ref | ref | ref | ref | |
| 65–69 |
1.27*** [1.11,1.46] |
1.28*** [1.11,1.46] |
1.27*** [1.11,1.45] |
1.24** [1.08,1.42] |
|
| 70–74 |
2.42*** [2.13,2.75] |
2.36*** [2.08,2.68] |
2.38*** [2.10,2.70] |
2.27*** [2.00,2.58] |
|
| 75+ |
6.37*** [5.74,7.07] |
5.87*** [5.29,6.52] |
6.00*** [5.40,6.67] |
5.65*** [5.08,6.28] |
|
| Currently married (Yes) | ref | ref | ref | ||
| No |
1.69*** [1.55,1.84] |
1.64*** [1.51,1.79] |
1.65*** [1.51,1.79] |
||
| Race (White) | ref | ref | ref | ||
| African/Black |
1.33*** [1.19,1.49] |
1.29*** [1.13,1.46] |
1.21** [1.06,1.38] |
||
| Coloured |
1.56*** [1.35,1.81] |
1.51*** [1.30,1.77] |
1.41*** [1.21,1.65] |
||
| Indian/Asian |
1.64*** [1.31,2.04] |
0.98 [0.78,1.23] |
0.90 [0.71,1.13] |
||
| Province (Western Cape) | ref | ref | |||
| Eastern Cape |
0.92 [0.78,1.09] |
0.89 [0.76,1.05] |
|||
| Northern Cape |
1.20* [1.01,1.42] |
1.19* [1.00,1.41] |
|||
| Free State |
0.80* [0.66,0.99] |
0.79* [0.65,0.97] |
|||
| KwaZulu-Natal |
1.86*** [1.59,2.18] |
1.80*** [1.54,2.10] |
|||
| North West |
0.75** [0.61,0.92] |
0.75** [0.61,0.92] |
|||
| Gauteng |
0.84* [0.71,1.00] |
0.84* [0.71,1.00] |
|||
| Mpumalanga |
0.94 [0.77,1.13] |
0.96 [0.79,1.16] |
|||
| Limpopo |
0.90 [0.75,1.07] |
1.00 [0.83,1.19] |
|||
| Area (Urban) | ref | ref | |||
| Rural |
0.94 [0.86,1.02] |
0.98 [0.90,1.07] |
|||
| Year (2012) | ref | ref | |||
| 2013 |
1.16* [1.01,1.33] |
1.15* [1.00,1.32] |
|||
| 2014 |
0.99 [0.86,1.15] |
0.98 [0.85,1.13] |
|||
| 2015 |
1.17* [1.01,1.36] |
1.15 [0.99,1.33] |
|||
| 2016 |
1.02 [0.88,1.19] |
1.01 [0.86,1.18] |
|||
| 2017 | [0.85,1.16] |
0.99 [0.85,1.16] |
|||
| 2018 |
1.06 [0.91,1.23] |
1.05 [0.90,1.23] |
|||
| 2019 |
2.14*** [1.88,2.43] |
2.04*** [1.80,2.32] |
|||
| 2020 |
1.80*** [1.54,2.10] |
1.73*** [1.48,2.02] |
|||
| 2021 |
1.83*** [1.57,2.13] |
1.77*** [1.52,2.05] |
|||
| Diabetes (No) | ref | ||||
| Yes |
1.44*** [1.34,1.55] |
||||
| HBP (No) | ref | ||||
| Yes |
1.35*** [1.26,1.45] |
||||
| Asthma (No) | ref | ||||
| Yes |
1.30*** [1.14,1.48] |
Cells display risk ratios with 95% confidence intervals in brackets. Significance level: *p < 0.05, **p < 0.01, ***p < < 0.001. Model 1 = adjusted for Sex, Model 2 = adjusted for model 1 + Age, Model 3 = Model 2 + Marital Status + Race, Model 4 = model 3 + Area + Province, Model 5 = model 4 + Year + Diabetes + HBP + Asthma
Individuals living in the Northern Cape have a 19% higher risk (RR = 1.19, 95% CI = 1.00, 1.41) of reporting difficulties in self-care compared to those living in the Western Cape, as shown in Table 2, risk ratios of reporting difficulties in performing in self-care. Similarly, individuals living in KwaZulu-Natal have 80% higher risk (RR = 1.80, 95% CI = 1.54, 2.10) of reporting difficulties in self-care compared to those living in the Western Cape, while those in the Free State have a 21% lower risk (RR = 0.79, 95% CI = 0.65, 0.97). The risk ratios for the Northwest and Gauteng provinces were 0.75 (95% CI = 0.61, 0.92) and 0.84 (95% CI = 0.71, 1.00), respectively, indicating a lower risk of reporting difficulties in self-care compared to the Western Cape, although the effect was only statistically significant for the Northwest province. Regarding year, the results indicate significant differences in the risk of reporting difficulties in self-care activities across years. For instance, the risk ratios were significantly higher for 2020 (RR = 1.73, 95%CI = 1.48, 2.02), and 2021 (RR = 1.77, 95%CI = 1.52, 2.05). Participants with diabetes, HBP, and asthma had respectively 44% (RR = 1.44, 95%CI = 1.34,1.55), 35% (RR = 1.35, 95%CI = 1.26,1.45), and 30% (RR = 1.30, 95%CI = 1.14,1.48) higher risk of reporting difficulties in self-care compared to those without the respective condition.
Discussion
South Africa, like many countries, is experiencing population aging. The increasing burden of self-care difficulties aligns with the aging population trend, as older individuals generally face higher risks of health conditions and functional limitations. This suggests that the healthcare system may face additional demands due to the aging population, requiring appropriate strategies to address the evolving healthcare needs of older adults. Our findings show a gradual increase in the percentage of individuals reporting significant difficulty or being unable to perform self-care tasks between 2012 and 2021. The percent increase in “A lot of difficulty” between 2012 and 2021 is approximately 79.75%, while for “Some difficulty” the percentage has increased by 112.11%. Of note, the percentage of ‘Unable to do’ decreased by approximately 8.97% between the same period. This decrease suggests that although the overall burden of self-care difficulties has increased, there has been a slight improvement in certain aspects of self-care capabilities among the surveyed population. Nevertheless, the overall upward trend in self-care difficulties emphasizes the importance of continued efforts to enhance healthcare services, promote healthy aging, and ensure adequate support for older adults in managing their self-care needs.
The results of multivariate analysis showed that men had a higher risk of reporting difficulties in self-care activities than women. One possible explanation for the sex difference in self-care difficulties is health-seeking behaviors and help-seeking behaviour between men and women. Men are less likely to seek medical attention or express health concerns, often leading to delayed diagnosis and treatment [28, 29]. Consequently, men may experience a higher burden of self-care difficulties due to insufficient care of their health conditions. Consistent with previous studies, older age was strongly associated with an increased risk of reporting difficulties in self-care activities [30]. The risk ratios for reporting difficulties in self-care activities increased with age, from 1.24 for ages 65–69 to 5.65 for ages 75 and above. These findings highlight the importance of promoting healthy aging and preventing disability among older adults in South Africa. Being unmarried was also associated with a higher risk of reporting difficulties in self-care activities. This finding is consistent with previous research on the social determinants of health, which suggests that social support and social connections are important for maintaining health and well-being [31–33]. Regarding race, being of Indian/Asian or White race was associated with a lower risk of reporting difficulties in self-care activities, while being of African/Black and Coloured background was associated with a higher risk. This finding is consistent with previous research on racial disparities in health outcomes, which suggests that African/Black and Coloured individuals have higher rates of chronic diseases and disabilities than other racial groups [34]. The results also highlighted a notable increase in the risk of self-care difficulties across the years. These changes suggest that factors beyond aging alone may have contributed to the worsening self-care capabilities. The onset of the COVID-19 pandemic during this period likely exacerbated physical and mental health challenges, as well as access to healthcare services, leading to increased difficulties in managing self-care among vulnerable populations.
Regarding geographic disparities, the odds of having difficulties in self-care were significantly higher in KwaZulu-Natal compared to the Western Cape. Finally, we found that participants with diabetes, hypertension, and asthma had a higher risk of reporting difficulties in self-care activities, which is consistent with previous literature on the negative impact of chronic conditions on daily living activities [35–37]. These conditions are among the leading causes of morbidity and mortality globally and are becoming increasingly prevalent in South Africa, particularly among the aging population. The higher risk of reporting difficulties in self-care among individuals with these conditions can be attributed to the burden of symptoms, such as pain, fatigue, and breathlessness, which can limit their ability to carry out activities of daily living independently. In addition, the management of these conditions, which often involves complex medication regimens and lifestyle modifications, can also be challenging and may require additional support from healthcare providers and family members.
This study has several strengths, including a large and nationally representative sample size, which enhances the generalizability of the findings to the South African population. The study also employed rigorous statistical methods, including multivariable logistic regression analysis, to identify the factors associated with higher dependence on care. These results could offer valuable knowledge for developing future research and policies focused on the increasing number of older adults in South Africa who struggle with self-care, with a particular emphasis on addressing the higher burden faced by certain racial groups. However, this study also has some limitations to consider. Firstly, the cross-sectional design means that it is not possible to establish causality between the variables examined, as the data collected represents a single point in time. This study was also reliant on a single indicator of difficulties of difficulties in performing self-care, which may not capture the full scope of self-care needs. Additionally, the study is based on self-reported data, which may be subject to recall bias and may not always accurately reflect the true health status of the participants. The data also cannot indicate whether the population with self-care difficulties were care dependent. Future research could explore the relationship between self-reported self-care difficulties and care dependency to provide a more comprehensive understanding of the care needs among older adults.
Conclusion
This study revealed significant associations between demographic, health, and social factors and the increased risk of self-care difficulties among older South Africans. Specifically, the risk of self-care difficulties increased with age, with the highest risk observed among those aged 75 and above. Marital status was also identified as a key factor, with divorced, widowed, and single individuals showing higher risks of self-care difficulties compared to those who were married. African/Black and Coloured individuals had a higher risk of self-care difficulties compared to White individuals. Additionally, certain provinces in South Africa demonstrated higher risks of self-care difficulties than others. The presence of diabetes, hypertension, and asthma was also associated with an elevated risk of self-care difficulties. These findings provide valuable insights for future research and policy development, particularly in addressing the growing self-care challenges among South Africa’s older adults, with an emphasis on racial disparities.
Acknowledgements
The authors thank Statistics South Africa (Stats SA) for their support and for free access to the original data.
Author contributions
SY and GB contributed to the study design, the review of literature, and analysis of literature, manuscript conceptualization, preparation, and data analysis. SY had final responsibility to submit for publication. All authors read and approved the final manuscript.
Funding
The authors have no support or funding to report.
Data availability
Data for this study were sourced from South Africa General Household Survey conducted by Statistics South Africa (Stats SA) and available here: https://www.statssa.gov.za/?p=15482.
Declarations
Ethics approval and consent to participate
Ethics approval for this study was not required since the data is secondary and is available in the public domain.
Consent for publication
No consent to publish was needed for this study as we did not use any details, images or videos related to individual participants. In addition, data used is available in the public domain.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data for this study were sourced from South Africa General Household Survey conducted by Statistics South Africa (Stats SA) and available here: https://www.statssa.gov.za/?p=15482.