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Sökning: WFRF:(Johansson A) > Johansson L

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  • 2017
  • swepub:Mat__t
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  • Gakidou, E., et al. (författare)
  • Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
  • 2017
  • Ingår i: Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 390:10100, s. 1345-1422
  • Tidskriftsartikel (refereegranskat)abstract
    • Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined. Findings Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124.1 million DALYs [95% UI 111.2 million to 137.0 million]), high systolic blood pressure (122.2 million DALYs [110.3 million to 133.3 million], and low birthweight and short gestation (83.0 million DALYs [78.3 million to 87.7 million]), and for women, were high systolic blood pressure (89.9 million DALYs [80.9 million to 98.2 million]), high body-mass index (64.8 million DALYs [44.4 million to 87.6 million]), and high fasting plasma glucose (63.8 million DALYs [53.2 million to 76.3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9.3% (6.9-11.6) decline in deaths and a 10.8% (8.3-13.1) decrease in DALYs at the global level, while population ageing accounts for 14.9% (12.7-17.5) of deaths and 6.2% (3.9-8.7) of DALYs, and population growth for 12.4% (10.1-14.9) of deaths and 12.4% (10.1-14.9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27.3% (24.9-29.7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks. Interpretation Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade. Copyright (C) The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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  • Burgess, S., et al. (författare)
  • Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables
  • 2010
  • Ingår i: Statistics in medicine. - : Wiley. - 1097-0258 .- 0277-6715. ; 29:12, s. 1298-311
  • Tidskriftsartikel (refereegranskat)abstract
    • Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.
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  • Knudsen, A. K., et al. (författare)
  • Life expectancy and disease burden in the Nordic countries: results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017
  • 2019
  • Ingår i: Lancet Public Health. - : Elsevier BV. - 2468-2667. ; 4:12
  • Tidskriftsartikel (refereegranskat)abstract
    • Background The Nordic countries have commonalities in gender equality, economy, welfare, and health care, but differ in culture and lifestyle, which might create country-wise health differences. This study compared life expectancy, disease burden, and risk factors in the Nordic region. Methods Life expectancy in years and age-standardised rates of overall, cause-specific, and risk factor-specific estimates of disability-adjusted life-years (DALYs) were analysed in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. Data were extracted for Denmark, Finland, Iceland, Norway, and Sweden (ie, the Nordic countries), and Greenland, an autonomous area of Denmark. Estimates were compared with global, high-income region, and Nordic regional estimates, including Greenland. Findings All Nordic countries exceeded the global life expectancy; in 2017, the highest life expectancy was in Iceland among females (85.9 years [95% uncertainty interval [UI] 85.5-86.4] vs 75.6 years [75.3-75.9] globally) and Sweden among males (80.8 years [80.2-81.4] vs 70.5 years [70.1-70.8] globally). Females (82.7 years [81.9-83.4]) and males (78.8 years [78.1-79.5]) in Denmark and males in Finland (78.6 years [77.8-79.2]) had lower life expectancy than in the other Nordic countries. The lowest life expectancy in the Nordic region was in Greenland (females 77.2 years [76.2-78.0], males 70.8 years [70.3-71.4]). Overall disease burden was lower in the Nordic countries than globally, with the lowest age-standardised DALY rates among Swedish males (18 555.7 DALYs [95% UI 15 968.6-21 426.8] per 100 000 population vs 35 834.3 DALYs [33 218.2-38 740.7] globally) and Icelandic females (16 074.1 DALYs [13 216.4-19 240.8] vs 29 934.6 DALYs [26 981.9-33 211.2] globally). Greenland had substantially higher DALY rates (26 666.6 DALYs [23 478.4-30 218.8] among females, 33 101.3 DALYs [30 182.3-36 218.6] among males) than the Nordic countries. Country variation was primarily due to differences in causes that largely contributed to DALYs through mortality, such as ischaemic heart disease. These causes dominated male disease burden, whereas non-fatal causes such as low back pain were important for female disease burden. Smoking and metabolic risk factors were high-ranking risk factors across all countries. DALYs attributable to alcohol use and smoking were particularly high among the Danes, as was alcohol use among Finnish males. Interpretation Risk factor differences might drive differences in life expectancy and disease burden that merit attention also in high-income settings such as the Nordic countries. Special attention should be given to the high disease burden in Greenland. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd.
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