Eye Care Utilization by Older Adults in Different Countries
Eye Care Utilization by Older Adults in Different Countries
Study Population The WHS was coordinated by the World Health Organization (WHO) to collect population-based, nationally representative, high quality cross-sectional data from 70 countries within 6 world regions. This paper focuses on the 52 countries that asked about eye care utilization including 18 African countries, 13 European countries, 7 countries from Central and South America, 4 Middle Eastern countries, 5 from Southeast Asia, and 5 from the Western Pacific in 2002–2003. Survey institutions were selected by WHO in each country and these institutions carried out the survey according to WHS procedures. Informed consent was obtained from all participants and ethics approval was obtained from every institution that was involved in the study.
A multi-stage stratified random cluster sampling strategy was used to identify the participants to be contacted in each country. All sampling plans were reviewed by WHO before implementation. Strata were created based on 3 factors: region, socioeconomic status, and presence of a healthcare facility. Lists of households were obtained from population registries, voter lists, manual enumeration, or other methods. Households within the sampling units were randomly selected from these lists. Each member of the household was listed by the household informant. Within each household, an adult 18 years or older was randomly selected using a Kish table to complete the survey. Non-response was carefully documented. Response rates were very good with an average household response rate of 87% and an average individual response rate of 97%.
All surveys were interviewer-administered in person in local languages. Questionnaires were translated into 68 local languages using standard techniques. Briefly, forward translation was done locally by a bilingual multidisciplinary group. Back-translation was then done by an independent group. A review of the back-translation was also done at WHO. Any discrepancies were resolved. A review of the translated instrument was then done by a panel of experts. Detailed background information was obtained on the age, gender, urban versus rural dwelling, and education of the participant. Participants were asked to rate their general health status and whether they wore eyeglasses or contact lenses. Participants who were aged 60 years and older were asked "When was the last time you had your eyes examined by a medical professional?".
The wealth of the participant was estimated by measuring asset ownership using the widely used method of Filmer and Pritchett. This asset index had good internal coherence and robustness to the selection of variables used. This measure is considered to represent the household's long-run economic status rather than its current economic status. WHS participants were asked about their ownership of various items (i.e. bicycle, television, computer).
We also obtained data on the income status of the 52 countries from the World Bank website using data from 2003. According to the website, gross national income was converted to U.S. dollars using the Atlas method and was divided by the mid-year population. The Atlas method of conversion is used by the World Bank to smooth fluctuations in prices and exchange rates. We categorized this variable into 4 categories using World Bank classifications. The 4 categories were low (<$766), lower middle ($766–$3035), upper middle ($3036–$9385), and high income (> $9385).
There were 46,209 people who reported their age to be 60 years or older. We limited our analyses to the 35,839 respondents from the 52 countries who answered the question on the time of their last eye exam who reported their age to be 60 years or older (78% of the total). Means, standard deviations, and percentages were estimated. Prevalence rates were adjusted for the complex survey design although 3 countries (Slovenia, Guatamala, Zambia) did not report survey design information and therefore unweighted estimates are given for these 3 countries. Logistic regression analyses were performed to identify factors associated with having an eye exam in the last year. A random effects model with an exchangeable correlation structure was used to account for the multi-level nature of the data (people within countries). Principal components analysis was used to determine the weights for the index of the asset variables according to the method of Filmer and Pritchett. The index was divided into tertiles for use in the regression model. Stata Version 11 was used for the analyses (StataCorp, College Station Texas, USA) while the map was created in SAS Version 9.2 (Cary, North Carolina, USA).
Methods
World Health Survey
Study Population The WHS was coordinated by the World Health Organization (WHO) to collect population-based, nationally representative, high quality cross-sectional data from 70 countries within 6 world regions. This paper focuses on the 52 countries that asked about eye care utilization including 18 African countries, 13 European countries, 7 countries from Central and South America, 4 Middle Eastern countries, 5 from Southeast Asia, and 5 from the Western Pacific in 2002–2003. Survey institutions were selected by WHO in each country and these institutions carried out the survey according to WHS procedures. Informed consent was obtained from all participants and ethics approval was obtained from every institution that was involved in the study.
Sampling Strategy
A multi-stage stratified random cluster sampling strategy was used to identify the participants to be contacted in each country. All sampling plans were reviewed by WHO before implementation. Strata were created based on 3 factors: region, socioeconomic status, and presence of a healthcare facility. Lists of households were obtained from population registries, voter lists, manual enumeration, or other methods. Households within the sampling units were randomly selected from these lists. Each member of the household was listed by the household informant. Within each household, an adult 18 years or older was randomly selected using a Kish table to complete the survey. Non-response was carefully documented. Response rates were very good with an average household response rate of 87% and an average individual response rate of 97%.
Survey
All surveys were interviewer-administered in person in local languages. Questionnaires were translated into 68 local languages using standard techniques. Briefly, forward translation was done locally by a bilingual multidisciplinary group. Back-translation was then done by an independent group. A review of the back-translation was also done at WHO. Any discrepancies were resolved. A review of the translated instrument was then done by a panel of experts. Detailed background information was obtained on the age, gender, urban versus rural dwelling, and education of the participant. Participants were asked to rate their general health status and whether they wore eyeglasses or contact lenses. Participants who were aged 60 years and older were asked "When was the last time you had your eyes examined by a medical professional?".
The wealth of the participant was estimated by measuring asset ownership using the widely used method of Filmer and Pritchett. This asset index had good internal coherence and robustness to the selection of variables used. This measure is considered to represent the household's long-run economic status rather than its current economic status. WHS participants were asked about their ownership of various items (i.e. bicycle, television, computer).
Income Status of Country
We also obtained data on the income status of the 52 countries from the World Bank website using data from 2003. According to the website, gross national income was converted to U.S. dollars using the Atlas method and was divided by the mid-year population. The Atlas method of conversion is used by the World Bank to smooth fluctuations in prices and exchange rates. We categorized this variable into 4 categories using World Bank classifications. The 4 categories were low (<$766), lower middle ($766–$3035), upper middle ($3036–$9385), and high income (> $9385).
Data Analysis
There were 46,209 people who reported their age to be 60 years or older. We limited our analyses to the 35,839 respondents from the 52 countries who answered the question on the time of their last eye exam who reported their age to be 60 years or older (78% of the total). Means, standard deviations, and percentages were estimated. Prevalence rates were adjusted for the complex survey design although 3 countries (Slovenia, Guatamala, Zambia) did not report survey design information and therefore unweighted estimates are given for these 3 countries. Logistic regression analyses were performed to identify factors associated with having an eye exam in the last year. A random effects model with an exchangeable correlation structure was used to account for the multi-level nature of the data (people within countries). Principal components analysis was used to determine the weights for the index of the asset variables according to the method of Filmer and Pritchett. The index was divided into tertiles for use in the regression model. Stata Version 11 was used for the analyses (StataCorp, College Station Texas, USA) while the map was created in SAS Version 9.2 (Cary, North Carolina, USA).
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