SAGE Wave 1 was undertaken in Ghana in a partnership between the University of Ghana’s Department of Community Health, the Ministry of Health and WHO, as part of a multi-country longitudinal study to complement existing aging data sources and to inform policy and programmes [17, 18]. A nationally representative sample of respondents ≥ 50 years were interviewed on socio-demographic background, health risk factors, chronic conditions, well-being and health insurance coverage. Face-to-face interviews and data entry were undertaken between May 2007 and June 2008. Ethical approval for SAGE Wave 1 in Ghana was given by WHO’s Ethical Review Board and the University of Ghana Medical School Ethics and Protocol Review Committee. All study participants provided informed consent [17, 18].
Measures
Demographic and socioeconomic variables included sex, age, marital status, highest educational level completed, health insurance status and household income levels. Access to health care in Ghana is through the National Health Insurance Scheme (NHIS), introduced in 2003 and operationalized in most public and private health facilities in 2005. Basic eye care services including cataract surgery is covered by the NHIS. Assessment of health insurance status of older persons was based on this[19]. Educational level was categorized as low (primary or basic school completed or less) and high (at least secondary school completed or higher).
Chronic diseases
SAGE collected data on prevalent chronic diseases in older persons in Ghana. Data on four of these chronic conditions (cataract, diabetes mellitus, hypertension and stroke) were used in this analysis. For cataract, the question asked was: “ In the last 5 years, were you diagnosed with a cataract in one or both of your eyes (a cloudiness in the lens of the eye) by a health care professional?” Diagnosis of cataract in Ghana is done by a doctor or nurse trained in ophthalmology. SAGE Wave 1 in Ghana included operated and unoperated cataract within the self-reported diagnosis of cataract in the last 5 years.
The prevalence rates for the other chronic diseases were obtained through responses to the question “Has a health care professional ever told you, you have…?". Though SAGE Wave 1 measured blood pressure, the analysis considered only self-reported hypertension due to the focus on self-reported ill-health among older persons in Ghana [17, 18].
Tobacco use
Lifetime tobacco use was assessed with the question ‘Have you ever smoked tobacco or used smokeless tobacco?’ SAGE considered tobacco products such as cigarettes, cigars, pipes, chewing tobacco, or snuff. Details on how tobacco use was assessed is provided in published elsewhere [17, 18, 20].
Alcohol use
Lifetime alcohol use was assessed from responses to the question ‘Have you ever consumed a drink that contains alcohol (such as beer, wine, spirits, etc.)?’ SAGE Wave 1 quantified alcohol (commercially available and home-brewed beverages) in "standard drink" units as recommended by the World Health Organization [17, 18, 20].
Body mass index (BMI)
Was obtained from measured weight and height of respondents.
Subjective wellbeing (SWB)
Well-being or life satisfaction was assessed through a multi-dimensional scale, the WHO Disability Assessment Schedule 2.0, including a question about satisfaction with life overall [17, 18]. SWB as a single item measure was based on the overall life satisfaction question. As in a similar analysis by Yawson et al., 2013, the responses to this question were categorized into satisfied (very satisfied and satisfied), indifferent (neither satisfied nor dissatisfied) and not satisfied (dissatisfied and very dissatisfied) [21].
Wealth or income quintiles
Were derived from the household ownership of durable goods, dwelling characteristics and access to services (improved water, sanitation and cooking fuel) for a total of 21 assets. Wealth levels were generated through a multi-step process, where asset ownership was converted to an asset ladder, Bayesian post-estimation method used to generate raw continuous income estimates, and then income transformed into quintiles [17, 18, 20].
Data analysis
Demographic and socio-economic variables such as age, location (urban/ rural), educational level, marital status (due to its relevance in social support and health access), and income levels were described using proportions. Chi-square tests of significance were used to compare distribution of cataract and demographic, socioeconomic, health risk and life satisfaction indices.
Binary logistic regression analysis was done to determine factors associated with cataract in the older persons. Ever been diagnosed with cataract was the binary dependent variable in the regression model. Independent variables used included age, sex, location (urban/rural), educational level, marital status, income quintile, health insurance status, self-reported chronic conditions (diabetes, hypertension and stroke), alcohol use, tobacco use, and subjective wellbeing. Decisions were based on adjusted odds ratio [AOR] and p-values at 95% confidence level. Data were analysed using SPSS version 21.