Life satisfaction in adults in rural and urban regions of Canada - the Canadian Longitudinal Study on Aging
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».