| 1. |
- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 2. |
- Fransson, Eleonor I, et al.
(author)
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Job strain and the risk of stroke : an individual-participant data meta-analysis
- 2015
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In: Stroke. - 0039-2499 .- 1524-4628. ; 46:2, s. 557-559
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Journal article (peer-reviewed)abstract
- BACKGROUND AND PURPOSE: Psychosocial stress at work has been proposed to be a risk factor for cardiovascular disease. However, its role as a risk factor for stroke is uncertain.METHODS: We conducted an individual-participant-data meta-analysis of 196 380 males and females from 14 European cohort studies to investigate the association between job strain, a measure of work-related stress, and incident stroke.RESULTS: In 1.8 million person-years at risk (mean follow-up 9.2 years), 2023 first-time stroke events were recorded. The age- and sex-adjusted hazard ratio for job strain relative to no job strain was 1.24 (95% confidence interval, 1.05;1.47) for ischemic stroke, 1.01 (95% confidence interval, 0.75;1.36) for hemorrhagic stroke, and 1.09 (95% confidence interval, 0.94;1.26) for overall stroke. The association with ischemic stroke was robust to further adjustment for socioeconomic status.CONCLUSION: Job strain may be associated with an increased risk of ischemic stroke, but further research is needed to determine whether interventions targeting job strain would reduce stroke risk beyond existing preventive strategies.
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| 3. |
- Kivimäki, Mika, et al.
(author)
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Long working hours, socioeconomic status, and the risk of incident type 2 diabetes : a meta-analysis of published and unpublished data from 222 120 individuals.
- 2015
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In: The Lancet Diabetes and Endocrinology. - 2213-8587 .- 2213-8595. ; 3:1, s. 27-34
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Journal article (peer-reviewed)abstract
- BACKGROUND: Working long hours might have adverse health effects, but whether this is true for all socioeconomic status groups is unclear. In this meta-analysis stratified by socioeconomic status, we investigated the role of long working hours as a risk factor for type 2 diabetes.METHODS: We identified four published studies through a systematic literature search of PubMed and Embase up to April 30, 2014. Study inclusion criteria were English-language publication; prospective design (cohort study); investigation of the effect of working hours or overtime work; incident diabetes as an outcome; and relative risks, odds ratios, or hazard ratios (HRs) with 95% CIs, or sufficient information to calculate these estimates. Additionally, we used unpublished individual-level data from 19 cohort studies from the Individual-Participant-Data Meta-analysis in Working-Populations Consortium and international open-access data archives. Effect estimates from published and unpublished data from 222 120 men and women from the USA, Europe, Japan, and Australia were pooled with random-effects meta-analysis.FINDINGS: During 1·7 million person-years at risk, 4963 individuals developed diabetes (incidence 29 per 10 000 person-years). The minimally adjusted summary risk ratio for long (≥55 h per week) compared with standard working hours (35-40 h) was 1·07 (95% CI 0·89-1·27, difference in incidence three cases per 10 000 person-years) with significant heterogeneity in study-specific estimates (I(2)=53%, p=0·0016). In an analysis stratified by socioeconomic status, the association between long working hours and diabetes was evident in the low socioeconomic status group (risk ratio 1·29, 95% CI 1·06-1·57, difference in incidence 13 per 10 000 person-years, I(2)=0%, p=0·4662), but was null in the high socioeconomic status group (1·00, 95% CI 0·80-1·25, incidence difference zero per 10 000 person-years, I(2)=15%, p=0·2464). The association in the low socioeconomic status group was robust to adjustment for age, sex, obesity, and physical activity, and remained after exclusion of shift workers.INTERPRETATION: In this meta-analysis, the link between longer working hours and type 2 diabetes was apparent only in individuals in the low socioeconomic status groups.FUNDING: Medical Research Council, European Union New and Emerging Risks in Occupational Safety and Health research programme, Finnish Work Environment Fund, Swedish Research Council for Working Life and Social Research, German Social Accident Insurance, Danish National Research Centre for the Working Environment, Academy of Finland, Ministry of Social Affairs and Employment (Netherlands), Economic and Social Research Council, US National Institutes of Health, and British Heart Foundation.
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| 4. |
- Kivimäki, Mika, et al.
(author)
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Overweight, obesity, and risk of cardiometabolic multimorbidity : pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe
- 2017
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In: The Lancet Public Health. - : The Lancet Publishing Group. - 2468-2667. ; 2:6, s. e277-e285
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Journal article (peer-reviewed)abstract
- BACKGROUND: Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight.METHODS: ) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis.FINDINGS: Participants were 120 813 adults (mean age 51·4 years, range 35-103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973-2012). During a mean follow-up of 10·7 years (1995-2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7-2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5-5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1-21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9-2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1-17·9) for vascular disease followed by diabetes, 18·6 (16·6-20·9) for diabetes only, and 29·8 (21·7-40·8) for diabetes followed by vascular disease.INTERPRETATION: The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes.FUNDING: NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.
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