The coronavirus (COVID-19) pandemic has exposed vulnerable populations, including older adults, to experience the negative impacts associated with the global health crisis. According to Olding et al.,1 the COVID-19 pandemic has “exposed and intensified longstanding health and social inequalities”. Studies have shown that COVID-19 pandemic results in adverse health outcomes and higher mortality rates in older adults, including those with underlying cardiovascular disease, hypertension, chronic respiratory diseases, cancer and diabetes.2–4 Given that older adults are the most hit demographic group during the COVID-19 pandemic, many have been grappling with economic insecurity issues.5 They have also lost their source of livelihood. While the older population in many countries faces financial challenges, historically, older adults have struggled to earn incomes sufficient to cover their expenditure.6,7

COVID-19 has drastically changed older adults’ social lives and affected their care and various supports. Given that older adults are “functionally very dependent on family members or supports by community services”,8 they are more likely to receive fewer supports due to the associated financial and economic impacts of COVID-19. Globally, the socio-economic and financial implications of the COVID-19 crisis on older adults vary from one country to another and even within a country due to different political institutions and welfare support systems. Growing evidence suggests that more than half of all households in sub-Saharan Africa (SSA) reported reduced incomes during the outbreak of COVID-19.9 Consequently, this has become an obstacle in the fight against COVID-19 in SSA, given how financial assistance played a crucial role in controlling the previous outbreak of diseases such as the West African Ebola virus epidemic.10 To deal with financial impacts associated with COVID-19, many multilateral and non-governmental institutions such as the International Monetary Fund and the United Nations have committed to providing funds to low-and middle-income countries (LMICs), including those in SSA.11 However, it is still unclear how well relief funding and financial assistance have been provided for economically disadvantaged groups, particularly the older population.

In the sub-Saharan African context, limited studies have explored financial support for older adults during difficult times, while most have focused on the role of social support networks in healthcare services utilisation and the wellbeing of older adults.12 Previous studies also have shown the impact of financial support on health outcomes and healthcare services utilisation among older adults.13,14 For instance, Gyasi et al.15 found that the health financing schemes helped to improve healthcare access among older persons in Ghana. Another study that evaluated the impact of financial support for older adults in Ghana also showed a positive effect of financial aid on the health of noninstitutionalised older adults in Ghana.13 These findings give credence to earlier studies that confirmed the positive role of financial inclusion on health-seeking behaviour among older adults in Ghana.14

Despite these significant findings, there is a lack of evidence on the availability of financial support for older adults, inside and outside their household, during the COVID-19 crisis and the factors associated with such assistance in Ghana and other LMICs. This study, therefore, seeks to bridge this knowledge gap by ascertaining the prevalence of financial support services for older adults in Ghana and the demographic and socio-economic factors that predict access to such assistance. The findings of this study are crucial in guiding government and non-governmental financial policies that seek to improve the welfare of the older population during the COVID-19 pandemic. The study is also important because lack of financial support for vulnerable older adults, particularly the poor, can trigger mental health conditions for such groups and the increased risks of getting COVID-19. Moreover, the study provides intriguing findings to assist welfare institutions in Ghana in designing social welfare programs that target the health and wellbeing of the vulnerable populations who struggle to meet their basic needs during unprecedented health crises. Lastly, the study provides insights into the kinship care system through family relations and how older adults focus on their social support networks for financial resources in difficult situations like COVID-19.

METHODS

Sample and data

Data for this study were obtained from a survey on coronavirus-related health literacy (CHL) conducted between 12 September 2020 and 15 October 2020, in the Ashanti Region of Ghana. The CHL survey was carried out in Ashanti Region because the region houses the highest percentage (17.5%) of the older adults in Ghana coupled with their diverse cultural, social, and economic characteristics.13,16 The survey used a cross-sectional study design to understand CHL among older adults from the Ashanti Region of Ghana. Following the World Health Organization’s study on Global Ageing and Adult Health in 5 developing countries, including Ghana, we define an older adult as an individual who is 50 years or above.17

This paper reports aspects of the CHL survey by focusing on patterns and predictors of access to financial support among older adults during the COVID-19 pandemic in Ghana. We used the cluster sampling method to select five communities in the Ashanti Region of Ghana. To ensure some level of representation, a simple random sampling technique was used to recruit the respondents from the selected communities. We captured houses in some streets or townships of the communities selected with GPS devices with this sampling strategy. Subsequently, we wrote the location coordinates or information on pieces of paper which were put in a bowl for selection to interview older adults in the houses. In addition, we recruited the participants based on inclusion and exclusion criteria. First, participants who were sick during the survey were excluded from the study. Study participants who did not consent to the study were excluded. Second, participants aged below 50 years were not included in the study. We used a conservative prevalence of 40% (since most CHL was unknown in Ghana) among older adults in Ghana. Using Lwanga and Lemeshow18 formula for sample size calculation for health research with an alpha value of 0.05, minimum sample size was 369 was obtained but considering a 35% nonresponse rate, the final sample size was approximately 498. Out of the 498 participants contacted, 487 met the inclusion criteria. Of these eligible respondents, 13 (2.67%) refused to participate in the study yielding a sample size of 474, representing a response rate of 97.33%.

The questionnaire was employed to take data from the respondents. The questionnaire was developed in the English Language. Still, it was read in the participant’s local language (Twi) to better understand the instrument and quality control. The translation of the instrument into Twi was done by considering the World Health Organization guidelines for assessments of data collection instruments.19 We established the validity of the questionnaire by undertaking a detailed review of related literature on the subject matter to check for language clarity, simplicity, and consulting experts in financial support services, which is consistent with previous studies.20,21 Five research assistants from the Department of Planning at the Kwame Nkrumah University of Science and Technology (KNUST) in Ghana were recruited and trained to assist in the data collection process. The training of the research assistants lasted a day. The data collection exercise was monitored and supervised to ensure quality control. The administration of each questionnaire lasted between 25 and 30 minutes. Informed consent (written and verbal) was sought from the participants before data collection began.

Since this study was conducted to assist welfare institutions and health authorities in improving older adults’ health during the COVID-19 pandemic, ethical issues were considered. First, the study was approved by the various municipal health directorates in which the study was conducted. In line with the ethical principles, after going through the research proposal and survey instruments, the municipal health research team granted permission for data collection in the study setting. Secondly, the research participants were briefed on the purpose of the study, and their informed consent (oral and written) was obtained. The research participation was voluntary; therefore, the study participants were free to opt-out when necessary. Confidentiality was ensured throughout the entire research process. More importantly, the research was conducted to provide empirical evidence to assist policymakers and planners in improving the wellbeing and welfare of older adults during the COVID-19 pandemic. However, to conduct further analysis of CHL among older adults during the pandemic, approval was granted by the Municipal Health directorates.22

Outcome variable

The outcome variable for this study was access to financial support. Access to financial support was defined as individuals aged 50+ who received cash from either a household member or someone outside the household. Access to financial support was measured as a dichotomous variable indicating "no access to financial support =0) or “access to financial support =1)” during the COVID-19 pandemic.

Exposure variables

The predictor variables were age (years) (1=50-69 years, 2= 70-79, 3= 80 or above), gender (1=Female, 2= Male ), marital status ( 1=Married, 2=Single), education ( 1=none, 2= basic, 3=secondary, 4=tertiary), wealth status (1=average, 2= poor, 3= rich), employment status (1=yes, 2= no), religion ( 1=Christian, 2= non-Christian), ethnicity (1= Akan, 2= non-Akan), health status (1=good, 2= poor), income (GH¢) (1=≤ 500, 2= >500). Gender, marital status, employment status, ethnicity, religion, health status and income were measured as dichotomous variables. Age was measured as ranked variable; wealth status and education were measured as nominal variables.

Analytical framework

Descriptive and inferential statistics were used to analyse the data. Descriptive statistics such as percentages and frequencies were used to describe the participants’ background characteristics and prevalence of financial support during the COVID-19 pandemic in Ghana. We used inferential statistics such as binary logistic regression embedded in the SPSS (version 20) software to find the factors influencing access to financial support services among older adults during the COVID-19 pandemic in Ghana. We employed multivariate logistic regression as an analytical framework to examine the demographic and socio-economic factors associated with access to financial support among older adults during the COVID-19 pandemic. With the aid of multivariate logistic regression, three independent models were built. Model 1 focused on demographic, socio-economic, and health-related factors associated with access to in-household financial support among the participants during the COVID-19 pandemic. Model 2 determined the demographic, socio-economic, and health-related variables that predict access to financial support outside their household during the COVID-19 pandemic. Model 3 determined the demographic, socio-economic and health-related factors to explain access to financial support at home and outside the household during the COVID-19 pandemic. Previous studies used the omnibus chi-square tests of model coefficients, Hosmer and Lemeshow Test, and proportion of correction classification to measure the fitness of the models.21

The robustness of each model was measured, and the results are as follows. In Model 1, the outcome (P>0.05) of the Hosmer and Lemeshow homogeneity test shows that the model is an excellent fit for the data. The Omnibus Tests of Model Coefficients demonstrate a significant difference between the based model (without explanatory variables) and the current model with explanatory variables (P<0.05). The proportion of correct classification is 74.3%. In Model 2, the outcome (P>0.05) of the Hosmer and Lemeshow homogeneity test shows that the model is an excellent fit for the data. The Omnibus Tests of Model Coefficients demonstrate a significant difference between the based model (without explanatory variables) and the current model with explanatory variables (P<0.05). In Model 2, the outcome (P>0.05) of the Hosmer and Lemeshow homogeneity test shows that the model is an excellent fit for the data. In Model 3, the Omnibus Tests of Model Coefficients demonstrate a significant difference between the based model (without explanatory variables) and the current model with explanatory variables (P<0.05). The proportion of correct classification is 70.9%. The tests were considered significant at a probability value of 0.05 or below.

RESULTS

Demographic, socio-economic, and medical characteristics of the respondents

Table 1 presents the respondents’ demographic, socio-economic, and medical characteristics. The majority (80.8%) of the respondents were aged 50-69 years, 66.7% were females, 58% were married, and 44.1% had primary education. When the respondents were asked to rate their wealth status, 61.6% rated themselves average. The majority (67.7%) of the respondents were employed, 83.1% professed Christian faith, 87.8% were Akans, and 86.1% rated their health status as good. About 87% of the respondents earned a monthly income of ˃ GH¢500.

Table 1.Demographic and socio-economic characteristics of the respondents (N=474)
Variables Category Frequency (n) Percentage (%)
Age (years) 50-69 383 80.8%
70-79 79 16.7%
80 or above 12 2.5%
Gender Female 316 66.7%
Male 158 33.3%
Marital status Married 275 58.0%
Single 199 42.0%
Educational level None 116 24.5%
Basic 209 44.1%
Tertiary 43 9.1%
Secondary 106 22.4%
Wealth status Average 292 61.6%
Poor 172 36.3%
Rich 10 2.1%
Employment Status Yes 321 67.7%
No 153 32.3%
Religion Christian 394 83.1%
Non-Christian 80 16.9%
Ethnicity Akan 416 87.8%
Non-Akan 58 12.2%
Health status Good 408 86.1%
Poor 66 13.9%
Monthly income (GH¢) ≤ 500 41 12.8%
˃500 280 87.2%

Prevalence of financial support services among older adults during the COVID-19 pandemic

The study revealed that 25.7% of the participants received financial support from someone in their household during the COVID-19 pandemic (see Table 2). Further, 18.6% of the participants received financial support from someone outside their home during the COVID-19 pandemic. Results show that older adults received more financial support from someone in their households than those outside their families. About 37.3% of the participants received financial support from someone in the home and outside the household during the COVID-19 pandemic (see Table 2).

Table 2.Prevalence of receiving financial support services at the household and outside the household levels
Variables Response Frequency (n) Percentage (%)
During the COVID-19 pandemic, have you received financial support from someone in your household? Yes 122 25.7%
No 352 74.3%
Total 474 100.0%
During the COVID-19 pandemic, have you received financial help from someone outside the household? Yes 88 18.6%
No 386 81.4%
Total 474 100.0%
During the COVID-19 pandemic, have you received financial support from someone in your household and outside your household Yes 177 37.3%
No 297 62.7%
Total 474 100%

Factors associated with access to financial support services among older adults during COVID-19 pandemic

Table 3 presents the results of multivariate logistic regression analysis of the factors associated with access to financial support services among older adults during the COVID-19 pandemic. In Model 1, education and employment status were significantly associated with receiving in-household financial support services among older adults during the COVID-19 pandemic. Older adults with secondary education had lower odds of receiving financial support from the household compared with those with no formal education (adjusted odds ratio, aOR=0.38, 95% confidence interval, CI=0.15-0.93, P=0.034). Expectedly, older unemployed adults had higher odds of receiving financial support services from households than their employment counterparts (2.63 [1.53-4.51], P<0.001). In Model 2, only education was associated with access to financial support services from someone outside their households. Older adults with secondary education had lower odds of receiving financial support services from someone outside their home (0.21 [0.09-0.50], P<0.001). In Model 3, education, age, and employment status were significantly associated with access to financial support services from someone in and outside the household during the COVID-19 pandemic. Older adults aged 70-79 years had lower odds of receiving financial support from the family and outside the household during the COVID-19 pandemic than those aged 50-69 years (0.23 [0.12-0.43], P<0.001). We found that having secondary education significantly decreases the odds of receiving financial support from the household and outside household during the COVID-19 pandemic (0.34 [0.14-0.82], P=0.016). Also, employed older adults had lower odds of receiving financial support from the household and outside household during the COVID-19 pandemic (0.51 [0.31-0.85], P=0.009).

Table 3.Factors associated with access to financial support services among older adults during COVID-19 pandemic
Variables In-household financial support (Model 1) AOR [95% CI]
P‑value
Outside household financial Support (Model 2) AOR [95% CI]
P‑value
In-household and outside household financial support (Model 3) AOR [95% CI]
P‑value
Age (years)
50-69 Reference Reference Reference
70-79 1.35 [0.35‑5.28] 0.662 n/a 0.999 0.23 [0.12‑0.43] <0.001
80 or above 0.38 [0.10‑1.47] 0.161 n/a 0.999 1.06 [0.28‑4.10] 0.930
Gender
Female Reference Reference Reference
Male 1.21 [0.73‑2.01] 0.548 1.38 [0.80‑2.39] 0.246 0.82 [0.52‑1.30] 0.406
Marital Status
Married Reference Reference Reference
Single 1.14 [0.70‑1.88] 0.596 1.22 [0.70‑2.12] 0.478 0.74 [0.47‑1.16] 0.194
Education
None Reference Reference Reference
Basic 0.89 [0.43‑1.83] 0.743 1.25 [0.54‑2.85] 0.605 1.06 [0.61‑1.86] 0.830
Secondary 0.38 [0.15‑0.93] 0.034 0.21 [0.09‑0.50] <0.001 0.34 [0.14‑0.82] 0.016
Tertiary 0.90 [0.48‑1.70] 0.753 1.15 [0.58‑2.28] 0.690 1.07 [0.55‑2.09] 0.834
Wealth Status
Average Reference Reference Reference
Poor 0.96 [0.21‑4.41] 0.955 1.54 [0.33‑7.10] 0.580 0.66 [0.41‑1.08] 0.096
Rich 0.79 [0.16‑3.84] 0.767 1.14 [0.23‑5.76] 0.872 0.44 [0.09‑2.06] 0.296
Employment Status
Employed Reference Reference Reference
Unemployed 2.63 [1.53‑4.51] <0.001 1.01 [0.55‑1.88] 0.971 0.51 [0.31‑0.85] 0.009
Religion
Christian Reference Reference Reference
Non-Christian 0.57 [0.20‑1.60] 0.284 1.26 [0.45‑3.53] 0.658 1.11 [0.45‑2.74] 0.820
Ethnicity
Akan Reference Reference Reference
Non-Akan 2.43 [0.80‑7.45] 0.119 1.16 [0.38‑3.52] 0.793 0.43 [0.16‑1.19] 0.105
Health Status
Good Reference Reference Reference
Poor 1.42 [0.71‑2.84] 0.324 2.34 [0.94‑5.82] 0.067 1.67 [0.85‑3.28] 0.136
Income (GH¢)
≤ 500 Reference Reference Reference
˃500 0.94 [0.38‑2.32] 0.898 1.74 [0.61‑4.92] 0.300 1.25 [0.56‑2.80] 0.585
Model Fitting Information
Omnibus Chi-Square Tests of Model Coefficients (P-value) 64.488 (<0.001) 44.819 (<0.001) 80.693 (<0.001)
Hosmer and Lemeshow Test (P-value) 3.173 (0.923) 6.108 (0.635) 7.511 (0.483)
The proportion of Correct classification 74.3% 81.9% 70.9%

AOR: adjusted odds ratio. 95% CI: 95% confidence interval. Significant P-values are written in bold.

DISCUSSION

Older adults have been especially hard hit by COVID-19 either directly due to exposure to the virus or indirectly due to measures taken to mitigate the health and economic effects.23 Using a cross-sectional survey, this is the first study investigating the access to financial support amid the COVID-19 pandemic among older adults in Ghana. Our first aim was to determine the prevalence of access to financial support among older adults during the COVID-19 pandemic in Ghana. Less than half (37.3%) of older adults in this study had received financial support from their households and/or outside their homes during the COVID-19 pandemic. The majority of the older adults interviewed received financial support from their families during the pandemic. Our finding suggests that most older adults were not receiving financial aid regardless of the economic and financial hardships that accompanied the pandemic.5,24,25 The majority of older adults in Ghana are already financially vulnerable and struggle to meet basic needs even in regular times, mostly due to lack of social security and pension services, frailty and lack of jobs.14,26–28 In the wake of the pandemic and associated economic conditions, the financial vulnerability of older adults could worsen as these individuals have little control over their immediate financial situations.29

Thus, vulnerable older adults need to be supported financially through these difficult and uncertain times as they still have bills to pay and families to feed. A small proportion of older adults who received financial support during the pandemic could be explained by loss of jobs, reduced income remittances from family members, and inadequate local and national support. Meanwhile, previous studies have suggested that access to financial support, even in the absence of a pandemic, has significant implications for older adults’ health, wellbeing, and quality of life.14 For instance, Adams et al.30 reported that access to financial support reduces stigma and stereotypes among older adults. Gyasi et al.13 also asserted that financial aid could reduce mental ill-health among older adults. Similarly, financial support reduces stress and anxiety that promote the psychological health and wellbeing of older adults regardless of their income statuses.31 This suggests that government and non-governmental institutions, besides family members need to provide older adults with financial support during the pandemic to help minimise any psychological and health impacts that economic challenges can cause. Supporting older adults financially in these uncertain times is an important mechanism to offer a safety net and empower older adults to maintain their general health and wellbeing during and after the pandemic.

This study found that education, age and employment status were associated with access to financial support services among older adults sampled. Older adults aged 70-79 years had lower odds of receiving financial support during the pandemic than those aged 50-69 years. Those with secondary education had decreased financial support odds than those with no formal, essential, and tertiary education. Older unemployed adults had lower odds of receiving financial support during the COVID-19 pandemic than those with employment. These findings appear somewhat surprising and challenging to explain, as one would expect that older adults aged 70-79 years and without work will instead be more likely to receive financial support, due to their vulnerability and economic conditions.25 However, one possible explanation for these findings could be that older adults aged 70-79 years with secondary education and no employment may have limited social networks (including friends and schoolmates) that they can rely on in difficult situations, in this case, the COVID-19 pandemic. Another explanation could be the effect of perception and assumption concerning older adults within 70-79 age cohorts. This group of older adults might be pensioners people perceive as within the middle or rich wealth category in Ghanaian societies. As a result, financial support may not be extended to them during this pandemic. Overall, our findings suggest that education, age, and employment status rather than other demographic and socio-economic factors play crucial roles in accessing financial support and services among older adults in Ghana.

It is important to understand that due to the financial impact on older adults resulting from COVID-19, older adults are more likely to experience hunger, which will subsequently worsen their health conditions. Gyasi et al.32 explain that inadequate financial support limits older persons from purchasing essential services, including medicines and food, during the COVID-19 pandemic, which puts them in a depressed mood. Therefore, the poor, vulnerable older population needs financial support to access essential services during the pandemic to avoid worsening health conditions.

Despite the timeliness and contributions of this study, some limitations need to be highlighted. Significant limitations of this study include the cross-sectional design and sample size. First, due to the study’s cross-sectional nature, a causal relationship between the primary variable of interest — access to financial support—and exposure variables such as age, education, and employment status cannot be established. However, a longitudinal study that demonstrates a causal relationship is required. Second, our sample included only 474 older adults residing in Kumasi and its environs, suggesting that the results cannot necessarily generalise to Ghana’s broader ageing population. Further, the accuracy of the results is limited to the self-report of the participants. Lastly, unmeasured confounding factors may be relevant to older adults’ access to financial support.

CONCLUSIONS

This study investigated access to financial support among older adults and the factors influencing their access to financial support during the COVID-19 pandemic in Ghana. The majority of older adults sampled were not receiving financial support despite the pandemic’s financial hardship. Access to financial support among older adults was associated with demographic and economic characteristics, particularly education, age, and employment status. Considering the general and mental health impact of financial vulnerability, this study recommends that the government, non-governmental organisations, and civil societies (such as religious denominations) support older adults financially during the pandemic. Also, responses to older adults’ financial issues during the pandemic should consider demographic and economic variables such as age, education, and employment status.


Acknowledgments

We acknowledge our study participants for providing the study data and the authors and publishers whose works were consulted.

Funding

None.

Authorship contributions

All authors contributed to the manuscript.

Competing interests

The authors completed the Unified Competing Interest form at http://www.icmje.org/disclosure-of-interest/ (available upon request from the corresponding author), and declare no conflicts of interest.

Correspondence to:

Shadrack Osei Frimpong: Department of Public Health and Primary Care, University of Cambridge, Forvie Site, Robinson Way, Cambridge CB2 0SR, United Kingdom; Email: [email protected]; [email protected].