UNLABELLED: The study determined the spatial temporal characteristics of fall-related hip fractures in the elderly using routinely collected injury hospitalization and sociodemographic data. There was significant spatial temporal variation in hospitalized hip fracture rates in New South Wales, Australia. INTRODUCTION: The study determined the spatial temporal characteristics of fall-related hip fractures in the elderly using routinely collected injury hospitalization data. METHODS: All New South Wales (NSW), Australia residents aged 65+ years who were hospitalized for a fall-related hip fracture between 1 July 1998 and 30 June 2004 were included. Bayesian Poisson regression was used to model rates in local government areas (LGAs), allowing for the incorporation of spatial, temporal, and covariate effects. RESULTS: Hip fracture rates were significantly decreasing in one LGA, and there were no significant increases in any LGAs. The proportion of the population in residential aged care facilities was significantly associated with the rate of hospitalized hip fractures with a relative risk (RR) of 1.003 (95% credible interval 1.002, 1.004). Socioeconomic status was also related to hospitalized hip fractures with those in the third and fourth quintiles being at decreased risk of hip fracture compared to those in the least disadvantaged (fifth) quintile [RR = 0.837 (0.717, 0.972) and RR = 0.855 (0.743, 0.989) respectively]. CONCLUSIONS: There was significant spatial temporal variation in hospitalized hip fracture rates in NSW, Australia. The use of Bayesian methods was crucial to allow for spatial correlation, covariate effects, and LGA boundary changes.
UNLABELLED: The study determined the spatial temporal characteristics of fall-related hip fractures in the elderly using routinely collected injury hospitalization and sociodemographic data. There was significant spatial temporal variation in hospitalized hip fracture rates in New South Wales, Australia. INTRODUCTION: The study determined the spatial temporal characteristics of fall-related hip fractures in the elderly using routinely collected injury hospitalization data. METHODS: All New South Wales (NSW), Australia residents aged 65+ years who were hospitalized for a fall-related hip fracture between 1 July 1998 and 30 June 2004 were included. Bayesian Poisson regression was used to model rates in local government areas (LGAs), allowing for the incorporation of spatial, temporal, and covariate effects. RESULTS:Hip fracture rates were significantly decreasing in one LGA, and there were no significant increases in any LGAs. The proportion of the population in residential aged care facilities was significantly associated with the rate of hospitalized hip fractures with a relative risk (RR) of 1.003 (95% credible interval 1.002, 1.004). Socioeconomic status was also related to hospitalized hip fractures with those in the third and fourth quintiles being at decreased risk of hip fracture compared to those in the least disadvantaged (fifth) quintile [RR = 0.837 (0.717, 0.972) and RR = 0.855 (0.743, 0.989) respectively]. CONCLUSIONS: There was significant spatial temporal variation in hospitalized hip fracture rates in NSW, Australia. The use of Bayesian methods was crucial to allow for spatial correlation, covariate effects, and LGA boundary changes.
Authors: Julieann Brennan nee Saunders; Antony Johansen; John Butler; Mike Stone; Peter Richmond; Sarah Jones; Ronan A Lyons Journal: Osteoporos Int Date: 2003-04-30 Impact factor: 4.507
Authors: Jonathan R Sugarman; Frederick A Connell; Amy Hansen; Steven D Helgerson; Michael C Jessup; Helan Lee Journal: J Am Geriatr Soc Date: 2002-10 Impact factor: 5.562
Authors: Lesley Day; Caroline F Finch; Keith D Hill; Terry P Haines; Lindy Clemson; Margaret Thomas; Catherine Thompson Journal: Inj Prev Date: 2010-12-24 Impact factor: 2.399