2012
DOI: 10.1016/j.archger.2012.02.006
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Prevalence and predictors of healthcare utilization among older people (60+): Focusing on ADL dependency and risk of depression

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Cited by 21 publications
(13 citation statements)
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References 63 publications
(65 reference statements)
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“…However, the model in our study explained 11% of the variance, meaning that depressed mood explained 11% of the total use of outpatient services. This indicates that it is difficult to predict health care consumption for frail older people who often have multiple illnesses and needs, which also has been shown in previous research (31).…”
Section: Discussionmentioning
confidence: 74%
“…However, the model in our study explained 11% of the variance, meaning that depressed mood explained 11% of the total use of outpatient services. This indicates that it is difficult to predict health care consumption for frail older people who often have multiple illnesses and needs, which also has been shown in previous research (31).…”
Section: Discussionmentioning
confidence: 74%
“…Also, counties that show lower proportions of elderly individuals with shorter distances to basic services (grocery stores, ATM, health care center, and post office), tend to have lower fall rates. Moreover, some studies suggest that the presence of adequate and proper access to health care and social services may result in longer lifespans (Andersen 2008;Landi et al 2001;Sandberg et al 2012).…”
Section: Discussion Of the Resultsmentioning
confidence: 99%
“…Internationally, previous studies show that demographic and socio-economic characteristics affect the prevalence of the elderly fall (Andersen 2008;Cakar et al 2011;Cauley 2011;Dhanwal et al 2011;Galizia et al 2008;Graham et al 2008;Haan et al 1987;Hokby et al 2003;Jacobsen et al 1992;Kannus et al 1999;Landi et al 2001;Lopata 1982;Luukinen et al 1996;Megyesi et al 2011;Nguyen-Oghalai et al 2009;Penrod et al 2008;Reimers and Laflamme 2007;Sandberg et al 2012;Tinetti et al 1988;Trujillo et al 2011;Van Rossum et al 2000). Based on this literature, it is suggested that counties that have higher rates of falls are expected to be associated with one or more of these factors: lower proportion of nonSwedes, greater proportion of non-active population, larger share of low income earners, and single individuals.…”
Section: Theoretical Background and Hypothesesmentioning
confidence: 91%
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