Blindness registrations and socioeconomic factors in Canada: An ecologic study

PURPOSE: To investigate the socioeconomic factors associated with blindness registration in Canada and its regions using an ecologic approach. METHODS: Canadian National Institute for the Blind (CNIB) blindness registration data for 1996 were divided into units of analysis using postal codes and correlated with demographic and socioeconomic information collected by the 1996 Census of Canada. A total of 1250 units were analyzed representing 28,429,519 persons (98.55% of the population of Canada). Six socioeconomic factors were examined using weighted linear multivariate regression analysis: 1) Percentage of the population aged 65 years and over; 2) Median household income; 3) Percentage of the population with university education; 4) Percentage of income derived from government transfer payments; 5) Recent immigrants; and 6) Visible minorities (blacks, Chinese, South Asians). Regression models were created for Canada as well as five geographic regions within Canada. RESULTS: For Canada as a whole, blindness registration prevalence was positively correlated with age distribution and percentage of recent immigrants, and negatively correlated with level of government assistance income and percentage ethnic Chinese population. For five regional regression models, the common predictor variables were age distribution, median household income and percentage of the population who are black. None of the regional models produced an identical set of correlations. CONCLUSIONS: Socioeconomic factors associated with blindness registration prevalence varied across different regions. Median household income was the second most common factor after age distribution, suggesting that areas with lower incomes tend to utilize more blind services. Higher blindness registration rates were associated with areas that had a higher percentage of the population who were black. Differences in blindness registration rates may reflect under-utilization of blind services and/or variations in disease and treatment rates in different populations.