Prevalence and risk factors of osteosarcopenia: a systematic review and meta-analysis.

BACKGROUND: Osteosarcopenia is a syndrome with a concomitant presence of both sarcopenia and osteopenia/osteoporosis. It increases the risk of frailty, falls, fractures, hospitalization, and death. Not only does it burden the lives of older adults, but it also increases the economic burden on health systems around the world. This study aimed to review the prevalence and risk factors of osteosarcopenia to generate important references for clinical work in this area. METHODS: Pubmed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, CBM, and VIP databases were searched from inception until April 24th, 2022. The quality of studies included in the review was evaluated using the NOS and AHRQ Scale. Pooled effects of the prevalence and associated factors were calculated using random or fixed effects models. Egger's test, Begg's test, and funnel plots were used to test the publication bias. Sensitivity analysis and subgroup analysis were conducted to identify the sources of heterogeneity. Statistical analysis was performed using Stata 14.0 and Review Manager 5.4. RESULTS: A total of 31 studies involving 15,062 patients were included in this meta-analysis. The prevalence of osteosarcopenia ranged from 1.5 to 65.7%, with an overall prevalence of 21% (95% CI: 0.16-0.26). The risk factors for osteosarcopenia were female (OR 5.10, 95% CI: 2.37-10.98), older age (OR 1.12, 95% CI: 1.03-1.21), and fracture (OR 2.92, 95% CI: 1.62-5.25). CONCLUSION: The prevalence of osteosarcopenia was high. Females, advanced age, and history of fracture were independently associated with osteosarcopenia. It is necessary to adopt integrated multidisciplinary management.

A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat-GLAS Footprints.

We present in this paper a polynomial fitting method applicable to segments of footprints measured by the Geoscience Laser Altimeter System (GLAS) to estimate glacier thickness change. Our modification makes the method applicable to complex topography, such as a large mountain glacier. After a full analysis of the planar fitting method to characterize errors of estimates due to complex topography, we developed an improved fitting method by adjusting a binary polynomial surface to local topography. The improved method and the planar fitting method were tested on the accumulation areas of the Naimona'nyi glacier and Yanong glacier on along-track facets with lengths of 1000 m, 1500 m, 2000 m, and 2500 m, respectively. The results show that the improved method gives more reliable estimates of changes in elevation than planar fitting. The improved method was also tested on Guliya glacier with a large and relatively flat area and the Chasku Muba glacier with very complex topography. The results in these test sites demonstrate that the improved method can give estimates of glacier thickness change on glaciers with a large area and a complex topography. Additionally, the improved method based on GLAS Data and Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) can give estimates of glacier thickness change from 2000 to 2008/2009, since it takes the 2000 SRTM-DEM as a reference, which is a longer period than 2004 to 2008/2009, when using the GLAS data only and the planar fitting method.