Introduction: Understanding urban-rural differences, and understanding levels of life satisfaction (LS) in rural populations, is important in planning social and health care services for rural populations. The objectives of this study were to determine patterns of LS in Canadian rural populations aged 45 to 85; to determine rural-urban differences in LS across a rural-urban continuum after accounting for potential confounding factors; and to determine if related social and health factors of LS 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 chi-square tests were conducted for categorical variables. Logistic regression models were constructed with the outcome of LS, 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 LS 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 (OR=1.23; 95% 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 LS and age, as well as between LS and being female. A strong graded association was noted between income and LS. Most chronic conditions were associated with lower LS. Finally, no major interaction was noted between rurality and each of the previously mentioned different factors associated with LS.
Conclusion: Rural-urban differences in LS were found, with higher levels of LS in rural populations compared to urban populations. Preventing and treating common chronic illness, and also reducing inequalities in income may prove useful to improving LS in both rural and urban areas. Studies of LS should consider rurality as a potential confounding factor in analyses of LS within and across societies.