Analysis of article using Artificial Intelligence tools
Id | 116 | |
Author | Hyyppä, M. T.; Mäki, J.; Impivaara, O.; Aromaa, A | |
Title | Leisure participation predicts survival: a population-based study in Finland. | |
Reference | Hyyppä, M. T.; Mäki, J.; Impivaara, O.; Aromaa, A. (2006). Leisure participation predicts survival: A population‑based study in Finland. Health Promotion International, 21(1): 5–12. |
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Keywords | leisure participation; survival; longitudinal survey |
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Link to article | https://doi.org/10.1093/heapro/dai027 |
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Abstract | The authors study whether leisure participation is an independent predictor of survival over 20 years. Of the nationally representative sample of 8000 adult Finns (Mini-Finland Health Survey), aged >30 years, the cohort of 30–59 years (n 5087) was chosen for the Cox proportional survival analyses. The sum score of leisure participation was divided in quartiles (the lowest quartile = scarce = 0–6), two intermediate quartiles = 7–11 and the highest quartile = abundant = 12–21). Adjusted for statistically significant covariates (age, tobacco smoking, alcohol consumption, obesity, self-rated health and diagnosed chronic diseases), and with scarce participation as the reference, the hazard ratios and 95% confidence intervals (CIs) for the risk of death were 0.80, 0.67–0.95 (intermediate) and 0.66, 0.52–0.84 (abundant) for men. The association was insignificant in women with good health. The results show that leisure participation predicts survival in middle-aged Finnish men and its effect is independent of demographic features, of health status and of several other health-related factors. The beneficial effect emphasizes the significance of leisure activities for the promotion of men’s health. |
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Metodology | First, we divided the population in three groups according to the quartiles of sum score in leisure participation (the lowest quartile = scarce = 0–6), two intermediate quartiles = 7–11 and the highest quartile = abundant = 12–21). Secondly, we applied multivariate Cox proportional hazard models for survival to identify and to control for relevant health-related covariates and their interactions with leisure participation measures. Thirdly, controlling for the health-related variables that significantly predicted survival and/or confounded the relationship between leisure participation scores and survival, we calculated hazard ratios with 95% confidence intervals (CIs). The SAS procedures (PHREG, LIFETEST) were applied for statistical calculations. |
Technique | Multivariate Cox proportional Hazard; PHREG; LIFETEST; statistical calculation; General Health Questionaire of Finland; |