Nikos Papadimitriou1, Konstantinos K Tsilidis2, Philippos Orfanos3, Vassiliki Benetou4, Evangelia E Ntzani5, Isabelle Soerjomataram6, Annemarie Künn-Nelen7, Ulrika Pettersson-Kymmer8, Sture Eriksson9, Hermann Brenner10, Ben Schöttker11, Kai-Uwe Saum12, Bernd Holleczek13, Francine D Grodstein14, Diane Feskanich14, Nicola Orsini15, Alicja Wolk15, Andrea Bellavia15, Tom Wilsgaard16, Lone Jørgensen17, Paolo Boffetta18, Dimitrios Trichopoulos19, Antonia Trichopoulou3. 1. Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. 2. Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece; Hellenic Health Foundation, Athens, Greece; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. Electronic address: ktsilidi@cc.uoi.gr. 3. Hellenic Health Foundation, Athens, Greece; WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece. 4. WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece. 5. Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece; Center for Evidence-Based Medicine, Department of Health Services, Policy and Practice, School of Public Health, Brown University, RI, USA. 6. International Agency for Research on Cancer (IARC-WHO), Lyon, France. 7. Department of Health Economics and Management, University of Wuppertal, Wuppertal, Germany; Research Centre for Education and the Labour Market, Maastricht University, Maastricht, Netherlands. 8. Department of Pharmacology and Clinical Neurosciences, Umeå University, Umeå, Sweden. 9. Department of Biobank Research, Umeå University, Umeå, Sweden. 10. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, National Center for Tumor Diseases, German Cancer Research Center (DKFZ), Heidelberg, Germany; German Cancer Consortium, German Cancer Research Center (DKFZ), Heidelberg, Germany. 11. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Network Aging Research, University of Heidelberg, Heidelberg, Germany; Institute of Health Care and Social Management, FOM University of Applied Sciences, Essen, Germany. 12. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany. 13. Saarland Cancer Registry, Saarbrücken, Germany. 14. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston MA, USA. 15. Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. 16. Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway. 17. Department of Health and Care Sciences, UiT The Arctic University of Norway, Tromsø, Norway; Department of Clinical Therapeutic Services, University Hospital of Northern Norway, Tromsø, Norway. 18. Hellenic Health Foundation, Athens, Greece; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 19. Hellenic Health Foundation, Athens, Greece; Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece.
Abstract
BACKGROUND: No studies have estimated disability-adjusted life-years (DALYs) lost due to hip fractures using real-life follow-up cohort data. We aimed to quantify the burden of disease due to incident hip fracture using DALYs in prospective cohorts in the CHANCES consortium, and to calculate population attributable fractions based on DALYs for specific risk factors. METHODS: We used data from six cohorts of participants aged 50 years or older at recruitment to calculate DALYs. We applied disability weights proposed by the National Osteoporosis Foundation and did a series of sensitivity analyses to examine the robustness of DALY estimates. We calculated population attributable fractions for smoking, body-mass index (BMI), physical activity, alcohol intake, type 2 diabetes and parity, use of hormone replacement therapy, and oral contraceptives in women. We calculated summary risk estimates across cohorts with pooled analysis and random-effects meta-analysis methods. FINDINGS: 223 880 men and women were followed up for a mean of 13 years (SD 6). 7724 (3·5%) participants developed an incident hip fracture, of whom 413 (5·3%) died as a result. 5964 DALYs (27 per 1000 individuals) were lost due to hip fractures, 1230 (20·6%) of which were in the group aged 75-79 years. 4150 (69·6%) DALYs were attributed to disability. Current smoking was the risk factor responsible for the greatest hip fracture burden (7·5%, 95% CI 5·2-9·7) followed by physical inactivity (5·5%, 2·1-8·5), history of diabetes (2·8%, 2·1-4·0), and low to average BMI (2·0%, 1·4-2·7), whereas low alcohol consumption (0·01-2·5 g per day) and high BMI had a protective effect. INTERPRETATION: Hip fracture can lead to a substantial loss of healthy life-years in elderly people. National public health policies should be strengthened to reduce hip fracture incidence and mortality. Primary prevention measures should be strengthened to prevent falls, and reduce smoking and a sedentary lifestyle. FUNDING: European Community's Seventh Framework Programme.
BACKGROUND: No studies have estimated disability-adjusted life-years (DALYs) lost due to hip fractures using real-life follow-up cohort data. We aimed to quantify the burden of disease due to incident hip fracture using DALYs in prospective cohorts in the CHANCES consortium, and to calculate population attributable fractions based on DALYs for specific risk factors. METHODS: We used data from six cohorts of participants aged 50 years or older at recruitment to calculate DALYs. We applied disability weights proposed by the National Osteoporosis Foundation and did a series of sensitivity analyses to examine the robustness of DALY estimates. We calculated population attributable fractions for smoking, body-mass index (BMI), physical activity, alcohol intake, type 2 diabetes and parity, use of hormone replacement therapy, and oral contraceptives in women. We calculated summary risk estimates across cohorts with pooled analysis and random-effects meta-analysis methods. FINDINGS: 223 880 men and women were followed up for a mean of 13 years (SD 6). 7724 (3·5%) participants developed an incident hip fracture, of whom 413 (5·3%) died as a result. 5964 DALYs (27 per 1000 individuals) were lost due to hip fractures, 1230 (20·6%) of which were in the group aged 75-79 years. 4150 (69·6%) DALYs were attributed to disability. Current smoking was the risk factor responsible for the greatest hip fracture burden (7·5%, 95% CI 5·2-9·7) followed by physical inactivity (5·5%, 2·1-8·5), history of diabetes (2·8%, 2·1-4·0), and low to average BMI (2·0%, 1·4-2·7), whereas low alcohol consumption (0·01-2·5 g per day) and high BMI had a protective effect. INTERPRETATION:Hip fracture can lead to a substantial loss of healthy life-years in elderly people. National public health policies should be strengthened to reduce hip fracture incidence and mortality. Primary prevention measures should be strengthened to prevent falls, and reduce smoking and a sedentary lifestyle. FUNDING: European Community's Seventh Framework Programme.
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