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Bone. 2007 Nov;41(5):896-900. Epub 2007 Jul 10.

A seventy percent overestimation of the burden of hip fractures in women aged 85 and over.

Author information

1
Hospices Civils de Lyon, Pole Information Medicale Evaluation recherche, Lyon, France. chantal.couris@chu-lyon.fr

Abstract

BACKGROUND:

Hip fractures are the most devastating result of osteoporosis and are common worldwide. Based on an exponential increase in incidence with age, many studies in the 1990s forecasted an epidemic of hip fracture in women in the next 15 years which is not currently being observed. Despite the ageing of the populations, accurate description of hip fracture incidence in women aged 85 or older are scarce.

METHODS:

All women aged 60 to 95, living in the Rhône-Alpes area of France, who were admitted to hospitals during 2001-2004 for treatment of hip fracture were selected from the French claims databases. An exponential model was tested to describe the increase in hip fracture incidence in women aged 60-84 and 60-95. The first model was used to predict annual hip fracture incidence in women aged 85-95 in the Rhône-Alpes area, in France and in Europe.

RESULTS:

An exponential model was adequate to describe the increase in incidence in women aged 60-84. Assuming an exponential increase in incidence in women aged 85-95, the predicted number of cases was overestimated by 70% in the Rhône-Alpes. In France and in Europe, the excess number of incident cases is believed to be respectively 16,000 and 85,965 a year.

INTERPRETATION:

The age-specific incidence estimates an average risk although the individual risks are heterogeneous throughout the population. The slower increase in incidence after age 85 might not be related to a decreasing individual risk with age but rather might indicate that women at higher risk have already experienced hip fracture or have died. After age 85, women who are still at risk may represent a population with a lower risk of hip fracture. Models adapted to the elderly population should be developed to improve the accuracy of predictions and optimise the health care system.

PMID:
17715006
DOI:
10.1016/j.bone.2007.06.020
[Indexed for MEDLINE]
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