The key reference guide to rural crime and rural justice, this encyclopedia includes 85 concise and informative entries covering rural crime theories, offences and control. It is divided into five complementary sections: • theories of rural crime; • rural crime studies; • rural criminal justice studies; • rural people and groups; • rural criminological research. With contributions from established and emerging international scholars, this authoritative guide offers state-of-the-art synopses of the key issues in rural crime, criminology, offending and victimisation, and both institutional and informal responses to rural crime
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From a collection of pamphlets and offprints donated by Fred Newton Scott (1860-1931), Instructor of English at the University of Michigan. ; Mode of access: Internet.
In: Klein , R A , Vianello , M , Hasselman , F , Adams , B G , Adams , R B , Alper , S , Aveyard , M , Axt , J R , Babalola , M T , Bahník , Š , Batra , R , Berkics , M , Bernstein , M J , Berry , D R , Bialobrzeska , O , Binan , E D , Bocian , K , Brandt , M J , Busching , R , Rédei , A C , Cai , H , Cambier , F , Cantarero , K , Carmichael , C L , Ceric , F , Chandler , J , Chang , J-H , Chatard , A , Chen , E E , Cheong , W , Cicero , D C , Coen , S , Coleman , J A , Collisson , B , Conway , M A , Corker , K S , Curran , P G , Cushman , F , Dagona , Z K , Dalgar , I , Dalla Rosa , A , Davis , W E , de Bruijn , M , De Schutter , L , Devos , T , de Vries , M , Doğulu , C , Dozo , N , Dukes , K N , Dunham , Y , Durrheim , K , Ebersole , C R , Edlund , J E , Eller , A , English , A S , Finck , C , Frankowska , N , Freyre , M , Friedman , M , Galliani , E M , Gandi , J C , Ghoshal , T , Giessner , S R , Gill , T , Gnambs , T , Gómez , Á , González , R , Graham , J , Grahe , J E , Grahek , I , Green , E G T , Hai , K , Haigh , M , Haines , E L , Hall , M P , Heffernan , M E , Hicks , J A , Houdek , P , Huntsinger , J R , Huynh , H P , Ijzerman , H , Inbar , Y , Innes-ker , Å H , Jiménez-leal , W , John , M , Joy-gaba , J A , Kamiloğlu , R G , Kappes , H B , Karabati , S , Karick , H , Keller , V N , Kende , A , Kervyn , N , Knežević , G , Kovacs , C , Krueger , L E , Kurapov , G , Kurtz , J , Lakens , D , Lazarević , L B , Levitan , C A , Lewis , N A , Lins , S , Lipsey , N P , Losee , J E , Maassen , E , Maitner , A T , Malingumu , W , Mallett , R K , Marotta , S A , Međedović , J , Mena-pacheco , F , Milfont , T L , Morris , W L , Murphy , S C , Myachykov , A , Neave , N , Neijenhuijs , K , Nelson , A J , Neto , F , Lee Nichols , A , Ocampo , A , O'donnell , S L , Oikawa , H , Oikawa , M , Ong , E , Orosz , G , Osowiecka , M , Packard , G , Pérez-sánchez , R , Petrović , B , Pilati , R , Pinter , B , Podesta , L , Pogge , G , Pollmann , M M H , Rutchick , A M , Saavedra , P , Saeri , A K , Salomon , E , Schmidt , K , Schönbrodt , F D , Sekerdej , M B , Sirlopú , D , Skorinko , J L M , Smith , M A , Smith-castro , V , Smolders , K C H J , Sobkow , A , Sowden , W , Spachtholz , P , Srivastava , M , Steiner , T G , Stouten , J , Street , C N H , Sundfelt , O K , Szeto , S , Szumowska , E , Tang , A C W , Tanzer , N , Tear , M J , Theriault , J , Thomae , M , Torres , D , Traczyk , J , Tybur , J M , Ujhelyi , A , Van Aert , R C M , Van Assen , M A L M , Van Der Hulst , M , Van Lange , P A M , Van 't Veer , A E , Vásquez- Echeverría , A , Ann Vaughn , L , Vázquez , A , Vega , L D , Verniers , C , Verschoor , M , Voermans , I P J , Vranka , M A , Welch , C , Wichman , A L , Williams , L A , Wood , M , Woodzicka , J A , Wronska , M K , Young , L , Zelenski , J M , Zhijia , Z & Nosek , B A 2018 , ' Many Labs 2: Investigating Variation in Replicability Across Samples and Settings ' , Advances in Methods and Practices in Psychological Science , vol. 1 , no. 4 , pp. 443-490 . https://doi.org/10.1177/2515245918810225
We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen's ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.
International audience ; Background: Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic.Methods: In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed.Findings: 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 837 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By contrast, no significant changes in the incidence of invasive S agalactiae infections were observed. Similar trends were observed across most countries and territories despite differing stringency in COVID-19 control policies. The incidence of reported S pneumoniae infections decreased by 68% at 4 weeks (incidence rate ratio 0·32 [95% CI 0·27-0·37]) and 82% at 8 weeks (0·18 [0·14-0·23]) following the week in which significant changes in population movements were recorded. Interpretation: The introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of S pneumoniae, H influenzae, and N meningitidis, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide
The authors have read the journal's policy and the authors of this manuscript have the following competing interests: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. OHF is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Terho Lehtimäki (TL) is employed by Fimlab Ltd. Ozren Polašek (OP) is employed by Gen‐info Ltd. There are no patents, products in development, or marked products to declare. All the other authors have declared no competing interests exist. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials. ; International audience ; Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
The authors have read the journal's policy and the authors of this manuscript have the following competing interests: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. OHF is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Terho Lehtimäki (TL) is employed by Fimlab Ltd. Ozren Polašek (OP) is employed by Gen‐info Ltd. There are no patents, products in development, or marked products to declare. All the other authors have declared no competing interests exist. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials. ; International audience ; Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
The authors have read the journal's policy and the authors of this manuscript have the following competing interests: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. OHF is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Terho Lehtimäki (TL) is employed by Fimlab Ltd. Ozren Polašek (OP) is employed by Gen‐info Ltd. There are no patents, products in development, or marked products to declare. All the other authors have declared no competing interests exist. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials. ; International audience ; Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
On January 2020, the WHO Director General declared that the outbreak constitutes a Public Health Emergency of International Concern. The world has faced a worldwide spread crisis and is still dealing with it. The present paper represents a white paper concerning the tough lessons we have learned from the COVID-19 pandemic. Thus, an international and heterogenous multidisciplinary panel of very differentiated people would like to share global experiences and lessons with all interested and especially those responsible for future healthcare decision making. With the present paper, international and heterogenous multidisciplinary panel of very differentiated people would like to share global experiences and lessons with all interested and especially those responsible for future healthcare decision making.
Publisher's version (útgefin grein). ; Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3, 514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 × 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2, 159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 × 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 × 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension. ; The following authors declare commercial private and/or governmental affiliations: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. Oscar H Franco (OHF) is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Fimlab LTD provided support in the form of salaries for author Terho Lehtimäki (TL) but did not have any additional role in the study design to publish, or preparation of the manuscript. Gen‐info Ltd provided support in the form of salaries for author Ozren Polašek (OP) but did not have any additional role in the study design to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the 'author contributions' section. There are no patents, products in development, or marked products to declare. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer Reviewed
Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding: Bill & Melinda Gates Foundation.
Publisher´s version (útgefin grein). ; Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders.Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach.Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable).Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. ; ROA is funded by the National Institutes of Health (U01HG010273). SMA acknowledges the International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia and Department of Health Policy and Management, Faculty of Public Health, Kuwait University for the approval and support to participate in this research project. AAw acknowledges funding support from Department of Science and Technology, Government of India, New Delhi, through INSPIRE Faculty scheme. TBA acknowledges partial funding from the Institute of Medical Research and Medicinal Plant Studies. ABa is supported by the Public Health Agency of Canada. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor Award, funded by the Federal Ministry of Education and Research. MSBS acknowledges support from the Australian Government Research and Training Program scholarship for a PhD degree at the Australian National University, Australia. JJC is supported by the Swedish Heart and Lung Foundation. FCar is supported by the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundacao para a Ciencia e a Tecnologia and Ministerio da Educacao e Ciencia) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020UID/QUI/50006/2013. EC is supported by an Australian Research Council Future Fellowship (FT3 140100085). KD is supported by a Wellcome Trust [Grant Number 201900] as part of his International Intermediate Fellowship. EF is supported by the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundacao para a Ciencia e a Tecnologia and Ministerio da Educacao e Ciencia) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020UID/QUI/50006/2013. SMSI is funded by the Institute for Physical Activity and Nutrition (IPAN), Deakin University and received funding from High Blood Pressure Research Council of Australia. YKa is a DBT/Wellcome Trust India Alliance Fellow in Public Health. YJK is supported by the Office of Research and Innovation at Xiamen University Malaysia. BL acknowledges funding from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. WDL is supported in part by U10NS086484 NINDS. SLo is funded by the German Federal Ministry of Education and Research (nutriCARD, grant agreement number 01EA1411A). RML is supported by a National Health and Medical Research Council (NHMRC) of Australia Senior Research Fellowship. AMa and the Imperial College London are grateful for support from the NW London NIHR Collaboration for Leadership in Applied Health Research and Care. JJM is supported by the Danish National Research Foundation (Niels Bohr Professorship), and the John Cade Fellowship (APP1056929) from NHMRC. TMei acknowledges additional institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD), Jena-Halle-Leipzig. IMV is supported by the Sistema Nacional de Investigacion (Panama). MOO is supported by SIREN U54 U54HG007479 and SIBS Genomics R01NS107900 grants. AMS was supported by a fellowship from the Egyptian Fulbright Mission Program. MMSM acknowledges the support from the Ministry of Education, Science and Technological Development, Republic of Serbia (contract no 175087). AShe is supported by Health Data Research UK. MBS' work on traumatic brain injury is supported by grants NIH U01 NS086090 (PI G Manley) from the National Institutes of Health (NIH) and DoD W81XWH-14-2-0176 (PI G Manley) from the United States Department of Defense. RTS is supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIIIFEDER. AGT was supported by a Fellowship from the NHMRC (Australia; 1042600. KBT acknowledges funding supports from the Maurice Wilkins Centre for Biodiscovery, Cancer Society of New Zealand, Health Research Council, Gut Cancer Foundation, and the University of Auckland. CY acknowledges support from the National Natural Science Foundation of China (grant number 81773552) and the Chinese NSFC International Cooperation and Exchange Program (grant number 71661167007). ; "Peer Reviewed"
BACKGROUND: Traumatic brain injury (TBI) and spinal cord injury (SCI) are increasingly recognised as global health priorities in view of the preventability of most injuries and the complex and expensive medical care they necessitate. We aimed to measure the incidence, prevalence, and years of life lived with disability (YLDs) for TBI and SCI from all causes of injury in every country, to describe how these measures have changed between 1990 and 2016, and to estimate the proportion of TBI and SCI cases caused by different types of injury. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 to measure the global, regional, and national burden of TBI and SCI by age and sex. We measured the incidence and prevalence of all causes of injury requiring medical care in inpatient and outpatient records, literature studies, and survey data. By use of clinical record data, we estimated the proportion of each cause of injury that required medical care that would result in TBI or SCI being considered as the nature of injury. We used literature studies to establish standardised mortality ratios and applied differential equations to convert incidence to prevalence of long-term disability. Finally, we applied GBD disability weights to calculate YLDs. We used a Bayesian meta-regression tool for epidemiological modelling, used cause-specific mortality rates for non-fatal estimation, and adjusted our results for disability experienced with comorbid conditions. We also analysed results on the basis of the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, there were 27·08 million (95% uncertainty interval [UI] 24·30-30·30 million) new cases of TBI and 0·93 million (0·78-1·16 million) new cases of SCI, with age-standardised incidence rates of 369 (331-412) per 100 000 population for TBI and 13 (11-16) per 100 000 for SCI. In 2016, the number of prevalent cases of TBI was 55·50 million (53·40-57·62 million) and of SCI was 27·04 million (24·98-30·15 million). From 1990 to 2016, the age-standardised prevalence of TBI increased by 8·4% (95% UI 7·7 to 9·2), whereas that of SCI did not change significantly (-0·2% [-2·1 to 2·7]). Age-standardised incidence rates increased by 3·6% (1·8 to 5·5) for TBI, but did not change significantly for SCI (-3·6% [-7·4 to 4·0]). TBI caused 8·1 million (95% UI 6·0-10·4 million) YLDs and SCI caused 9·5 million (6·7-12·4 million) YLDs in 2016, corresponding to age-standardised rates of 111 (82-141) per 100 000 for TBI and 130 (90-170) per 100 000 for SCI. Falls and road injuries were the leading causes of new cases of TBI and SCI in most regions. INTERPRETATION: TBI and SCI constitute a considerable portion of the global injury burden and are caused primarily by falls and road injuries. The increase in incidence of TBI over time might continue in view of increases in population density, population ageing, and increasing use of motor vehicles, motorcycles, and bicycles. The number of individuals living with SCI is expected to increase in view of population growth, which is concerning because of the specialised care that people with SCI can require. Our study was limited by data sparsity in some regions, and it will be important to invest greater resources in collection of data for TBI and SCI to improve the accuracy of future assessments. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation ; We acknowledge the funding and support of the Bill & Melinda Gates Foundation. AK was supported by the Miguel Servet contract, which was financed by the CP13/00150 and PI15/00862 projects integrated into the National Research, Development, and Implementation,and funded by the Instituto de Salud Carlos III General Branch Evaluation and Promotion of Health Research and the European Regional Development Fund (ERDF-FEDER). AMS is supported by the Egyptian Fulbright Mission Program. AF acknowledges the Federal University of Sergipe (Sergipe, Brazil). AA received financial assistance from the Indian Department of Science and Technology (New Delhi, India) through the INSPIRE faculty programme. AS is supported by Health Data Research UK. DJS is supported by the South African Medical Research Council. AB is supported by the Public Health Agency of Canada. SMSI received a senior research fellowship from the Institute for Physical Activity and Nutrition, Deakin University (Waurn Ponds, VIC, Australia), and a career transition grant from the High Blood Pressure Research Council of Australia. FP and CF acknowledge support from the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e a Tecnologia, and Ministério da Educação e Ciência) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020 UID/QUI/50006/2013. TB acknowledges financial support from the Institute of Medical Research and Medicinal Plant Studies, Yaoundé, Cameroon. AM of Imperial College London is grateful for support from the Northwest London National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research andCare and the Imperial NIHR Biomedical Research Centre. KD is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (grant number 201900). PSA is supported by an Australian National Health and Medical Research Council Early Career Fellowship. RT-S was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. The Serbian part of this contribution (by MJ) has been co-financed with grant OI175014 from the Serbian Ministry of Education, Science and Technological Development; publication of results was not contingent upon the Ministry's approval. MMMSM acknowledges support from the Serbian Ministry of Education, Science and Technological Development (contract 175087). MM's research was supported by the NIHR Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust (London, UK) and King's College London. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the UK Department of Health. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt professor award, which was funded by the German Federal Ministry of Education and Research ; Sí
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types.