Life satisfaction in adults in rural and urban regions of Canada - the Canadian Longitudinal Study on Aging

Introduction: Understanding rural-urban differences, and understanding levels of life satisfaction in rural populations, is important in planning social and healthcare services for rural populations. The objectives of this study were to determine patterns of life satisfaction in Canadian rural populations aged 45-85 years, to determine rural-urban differences in life satisfaction across a rural-urban continuum after accounting for potential confounding factors and to determine if related social and health factors of life satisfaction differ in rural and urban populations. Methods: A secondary analysis was conducted using data from an ongoing population-based cohort study, the Canadian Longitudinal Study on Aging. A cross-sectional sample from the baseline wave of the tracking cohort was used, which was intended to be as generalizable as possible to the Canadian population. Four geographic areas were compared on a rural-urban continuum: rural, mixed (indicating some rural, but could also include some peri-urban areas), peri-urban, and urban. Life satisfaction was measured using the Satisfaction with Life Scale and dichotomized as satisfied versus dissatisfied. Other factors considered were province of residence, age, sex, education, marital status, living arrangement, household income, and chronic conditions. These factors were self-reported. Bivariate analyses using χ2 tests were conducted for categorical variables. Logistic regression models were constructed with the outcome of life satisfaction, after which a series of models were constructed, adjusting for province of residence, age, and sex, for sociodemographic factors, and for health-related factors. To report on differences in the factors associated with life satisfaction in the different areas, logistic regression models were constructed, including main effects for the variable of interest, for the variable rurality, and for the interaction term between these two variables. Results: Individuals living in rural areas were more satisfied with life than their urban counterparts (odds ratio (OR)=1.23; 95% confidence interval (CI): 1.13-1.35), even after accounting for the effect of confounding sociodemographic and health-related factors (OR=1.32, 95%CI: 1.19-1.45). Those living in mixed (OR=1.30, 95%CI: 1.14-1.49) and peri-urban (OR=1.21, 95%CI: 1.07-1.36) areas also reported being more satisfied than those living in urban areas. In addition, a positive association was found between life satisfaction and age, as well as between life satisfaction and being female. A strong graded association was noted between income and life satisfaction. Most chronic conditions were associated with lower life satisfaction. Finally, no major interaction was noted between rurality and each of the previously mentioned different factors associated with life satisfaction. Conclusion: Rural-urban differences in life satisfaction were found, with higher levels of life satisfaction in rural populations compared to urban populations. Preventing and treating common chronic illness, and also reducing inequalities in income, may prove useful to improving life satisfaction in both rural and urban areas. Studies of life satisfaction should consider rurality as a potential confounding factor in analyses of life satisfaction within and across societies