Background: The COVID-19 outbreak caused by the SARS-Cov-2 virus has been sustained in China

Background Previous cohort studies investigating the association between sarcopenic obesity (SO) and all-cause mortality among adult people have been inconsistent. We performed a meta-analysis to determine if SO is a predictor of all-cause mortality. Methods Prospective cohort studies that evaluated the association between SO and mortality in older people were identified via a systematic search of three electronic databases (PubMed, EMBASE, and the Cochrane Library). A random-effects model was applied to combine the results. We considered the methods recommeded by consensuses (dual X-ray absorptiometry,bio-impedancemetry, anthropometric measures or CT scan) to assess sarcopenic obesity. Results Of the 603 studies identified through the systematic review, 23 (Participants: 50866) were included in the meta-analysis. The mean age ranged from 50 to 82.5 years.SO was significantly associated with a higher risk of all-cause mortality among adult people (pooled HR = 1.21, 95% confidence interval [95% CI] = 1.10–1.32, p < 0.001, I 2 = 64.3%). Furthermore, the subgroup analysis of participants showed that SO was associated with all-cause mortality (pooled HR = 1.14, 95% CI: 1.06–1.23) among community-dwelling adult people; similarly, this association was found in hospitalized patients (pooled HR = 1.65, 95% CI: 1.17–2.33). Moreover, the subgroup analysis demonstrated that SO was associated with all-cause mortality when using skeletal muscle mass (SMM) criteria, muscle strength criteria, and skeletal muscle index (SMI) criteria (HR = 1.12, 95% CI: 1.01–1.23; HR = 1.18, 95% CI: 1.05–1.33; and HR = 1.53, 95% CI: 1.13–2.07, respectively). In addition, we analyzed SO on the basis of obesity definition and demonstrated that participants with a SO diagnosis based on waist circumference (WC) (HR = 1.24, 95% CI: 1.09–1.40), body mass index (BMI) (HR = 1.29, 95% CI: 1.04–1.59), or visceral fat area (HR = 2.54, 95% CI: 1.83–3.53) have a significantly increase mortality risk compared with those without SO. Conclusion Based on our update of existing scientific researches, SO is a significant predictor of all-cause mortality among older people, particularly hospitalized patients. Therefore, it is important to diagnose SO and to treat the condition to reduce mortality rates among older people. Electronic supplementary material The online version of this article (10.1186/s12877-019-1195-y) contains supplementary material, which is available to authorized users.

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Purpose This paper aims to attempt to explore the influence of network position on innovation performance, specifically for companies from a less-developed area in China. Design/methodology/approach The paper uses a social network analysis method based on the data of high and new tech companies from Jiangxi province, China. It relies on Ucinet 6.212 software for data processing. Findings The present work, on the one hand, reveals that a high and new tech company from Jiangxi province tends to achieve better innovation performances if it is in the central position of its social network. On the other hand, it indicates that the same type of company from the same area does not always accomplish better innovation performance, even it possesses more structural holes. Originality/value The conclusions of this paper suggest that a high and new tech company from a less-developed area in China should build up its position closer to the center when constructing a social network. Meanwhile, the company should also exert more effort into managing its networks, as only building structural holes offers little help with operations besides showing that it has a broad social network.

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