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Background & aims: Low muscle mass is associated with increased falls, medical complications, length of hospital stay and loss of independence. An increasing number of studies has also shown the association between sarcopenia and health care expenditure. The following narrative review summarizes the current evidence on the economic relevance of low muscle mass (MM) or sarcopenia. Methods: An extensive search of the literature in Medline identified twelve studies in English, which evaluated direct and indirect health care expenditure in patients with low muscle mass or sarcopenia (low MM and strength or mobility). Results: Three studies analysed the cost of age-related loss of MM or strength in large surveys of the general, older population. Six retrospective analyses evaluated perioperative medical costs related to low MM in primarily older patients from different medical areas. One prospective study presented hospital costs related to sarcopenia in patients with gastric cancer. Two studies presented data from general hospital patients. Despite the difference in diagnostic criteria, study population and statistical design, low MM and sarcopenia were consistently identified as predictors of increased health care expenditure in community, perioperative and general hospital settings. Conclusions: Low MM and sarcopenia are prevalent and associated with significantly higher health care costs. Considering the demographic change, which will lead to an increasing number of patients with sarcopenia, every effort should be made to identify and treat patients with sarcopenia. The use of a unified definition and diagnostic criteria would allow a better comparison of data. (C) 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.
Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.