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Abstract Frailty is common and associated with poorer outcomes in the elderly, but its role as potential cardiovascular disease (CVD) risk factor requires clarification. We thus aimed to meta-analytically evaluate the evidence of frailty and pre-frailty as risk factors for CVD. Two reviewers selected all studies comparing data about CVD prevalence or incidence rates between frail/pre-frail vs. robust. The association between frailty status and CVD in cross-sectional studies was explored by calculating and pooling crude and adjusted odds ratios (ORs) ±95% confidence intervals (CIs); the data from longitudinal studies were pooled using the adjusted hazard ratios (HRs). Eighteen cohorts with a total of 31,343 participants were meta-analyzed. Using estimates from 10 cross-sectional cohorts, both frailty and pre-frailty were associated with higher odds of CVD than robust participants. Longitudinal data were obtained from 6 prospective cohort studies. After a median follow-up of 4.4 years, we identified an increased risk for faster onset of any-type CVD in the frail (HR = 1.70 [95%CI, 1.18–2.45]; I2 = 66%) and pre-frail (HR = 1.23 [95%CI, 1.07–1.36]; I2 = 67%) vs. robust groups. Similar results were apparent for time to CVD mortality in the frail and pre-frail groups. In conclusion, frailty and pre-frailty constitute addressable and independent risk factors for CVD in older adults.
Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.