Abstract
Summary
Policy decisions about the allocation of current and future resources should be based on the most accurate predictions possible. A functional data analysis (FDA) approach improves the understanding of current trends and future incidence of injuries. FDA provides more valid and reliable long-term predictions than commonly used methods.
Introduction
Accurate information about predicted future injury rates is needed to inform public health investment decisions. It is critical that such predictions derived from the best available statistical models to minimise possible error in future injury incidence rates.
Methods
FDA approach was developed to improve long-term predictions but is yet to be widely applied to injury epidemiology or other epidemiological research. Using the specific example of modelling age-specific annual incidence of fall-related severe head injuries of older people during 1970–2004 and predicting rates up to 2024 in Finland, this paper explains the principles behind FDA and demonstrates their superiority in terms of prediction accuracy over the more commonly reported ordinary least squares (OLS) approach.
Results
Application of the FDA approach shows that the incidence of fall-related severe head injuries would increase by 2.3–2.6-fold by 2024 compared to 2004. The FDA predictions had 55% less prediction error than traditional OLS predictions when compared to actual data.
Conclusions
In summary, FDA provides more accurate predictions of long-term incidence trends than commonly used methods. The production of FDA prediction intervals for future injury incidence rates gives likely guidance as to the likely accuracy of these predictions.
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Acknowledgements
The authors wish to thank Professor Pekka Kannus, Chief Physician and Head, Injury & Osteoporosis Research Centre, UKK Institute for Health Promotion Research, Tampere, Finland for providing the data analysed in this study.
Dr Shahid Ullah was supported by an Injury Trauma and Rehabilitation (ITR) Research Fellowship funded through a National Health and Medical Research Council (NHMRC) Capacity Building Grant in Population Health. Professor Caroline Finch was supported by an NHMRC Principal Research Fellowship.
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Ullah, S., Finch, C.F. Functional data modelling approach for analysing and predicting trends in incidence rates—an application to falls injury. Osteoporos Int 21, 2125–2134 (2010). https://doi.org/10.1007/s00198-010-1189-2
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DOI: https://doi.org/10.1007/s00198-010-1189-2