Burden of hip fracture using disability-adjusted life-years: a pooled analysis of prospective cohorts in the CHANCES consortium.

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.

Does Commuting Affect Health?

This paper analyzes the relation between commuting time and health in the UK. I focus on four different types of health outcomes: subjective health measures, objective health measures, health behavior, and healthcare utilization. Fixed effect models are estimated with British Household Panel Survey data. I find that whereas objective health and health behavior are barely affected by commuting time, subjective health measures are clearly lower for people who commute longer. A longer commuting time is, moreover, related to more visits to the general practitioner. Effects turn out to be more pronounced for women and for commuters driving a car. For women, commuting time is also negatively related to regular exercise and positively to calling in sick. Copyright © 2015 John Wiley & Sons, Ltd.