Predictors of subjective well-being among older Ghanaians

Abstract

Background: Later years of life are accompanied by many physical, emotional and environmental changes which may impact on the well-being of the individual. Many factors are known to influence the subjective well-being of older adults, but most, if not all of this information was the result of studies in the Western world. This study aimed at obtaining and documenting the predictors of subjective well-being (SWB) among older Ghanaians. Methods: Data for the study was obtained from the WHO SAGE study. The single item measure of life satisfaction was used to determine subjective wellbeing. Descriptive statistics as well as logistic regression analysis were carried out to determine the predictors of SWB. Results: A total of 4724 individuals aged 50 years and above responded to the questionnaires. Of these 50.4% were males. Following multivariate logistic regression analysis, age, sex, educational level, income and ethnic background were found to significantly affect the SWB of older Ghanaians. Being male was associated with higher level of SWB (OR=1.68; CI: 1.39 -2.03). For those 50 years and above, being younger (50-59 years) was also associated with a high level of SWB (OR=17.72; CI: 10.13-30.98). Earning a low income and having low educational level were both associated with low levels of SWB (OR=0.304; and OR=0.47; CI: 0.37-0.60 respectively). Ewes (p=0.027), Grumas (p=0.002) and Mole-Dagbons (p=0.04) had significantly higher SWB compared to the other ethnic groups. Conclusion: Among older Ghanaians, factors that positively influence SWB are younger age, male sex, high educational level and high income.

Subjective Happiness, Health and Quality of Life and Their Sociocultural Correlates among Younger Population in Malawi

“…Currently, there are no other studies showing the predictors of subjective health, happiness, and life satisfaction among healthy adolescent populations in an African context. A cross-sectional study involving elderly people in Ghana reported that age, sex, educational level, income, and ethnic background were significantly associated with subjective well-being (Calys-Tagoe et al 2014). A similar study on the elderly population in Nigeria found that socioeconomic status was the biggest indicator of quality of life (Gureje et al 2008).…”

“…Previous studies have shown subjective health and quality of life outcomes among older population and people living with disease conditions (Bishwajit et al 2017;Klotz et al 2018;Matsuguma et al 2018;Calys-Tagoe et al 2014;Ryan et al 2007). Currently, there are no other studies showing the predictors of subjective health, happiness, and life satisfaction among healthy adolescent populations in an African context.…”

Getting Old Well in Sub Saharan Africa: Exploring the Social and Structural Drivers of Subjective Wellbeing among Elderly Men and Women in Uganda

“…That said, despite the importance of SWB in old age, its analysis remains limited in low-middle income countries (LMICs) [47]. The few studies exploring SWB among elderly in SSA (i.e., South Africa, Nigeria, Ghana), reveal that seniors with low socioeconomic status, few social supports and/or identify as a woman, are more likely to report poor SWB compared to their economically advantaged, socially connected, male counterparts [48][49][50][51]. An important point from these investigations is that more work needs to tease out the role of particular determinants in the relationship between SWB and aging across a wider range of geographic contexts [50,51].…”

“…The few studies exploring SWB among elderly in SSA (i.e., South Africa, Nigeria, Ghana), reveal that seniors with low socioeconomic status, few social supports and/or identify as a woman, are more likely to report poor SWB compared to their economically advantaged, socially connected, male counterparts [48][49][50][51]. An important point from these investigations is that more work needs to tease out the role of particular determinants in the relationship between SWB and aging across a wider range of geographic contexts [50,51]. These statements are buttressed by recent academic and systematic reviews calling for more work to investigate the possible moderating factors and pathways that shape SWB in old age, particularly in under-resourced contexts where substantive gaps in knowledge exist [13,52].…”

Relative Association of Multi-Level Supportive Environments on Poor Health among Older Adults

“…Personal factors found to be associated with health in older adults are age [12,13], gender [12,13,14,15,16], race/ethnicity [12,13], education attainment [13,17,18,19]; and employment [12]. Research conducted in Europe, Asia, Africa, and Latin America with aging populations found several economic and social factors associated with broad health and independence outcomes, including: reduced retirement pensions [20]; community involvement and social support [21,22,23]; housing conditions [22,24,25]; income level [17,22,26,27,28]; forced retirement [29]; and feeling discriminated [24].…”