Baker Heart and Diabetes Institute

A cluster of risk factors for cardiovascular disease and type 2 diabetes mellitus, which occur together more often than by chance alone, have become known as the metabolic syndrome. The risk factors include raised blood pressure, dyslipidemia (raised triglycerides and lowered high-density lipoprotein cholesterol), raised fasting glucose, and central obesity. Various diagnostic criteria have been proposed by different organizations over the past decade. Most recently, these have come from the International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute. The main difference concerns the measure for central obesity, with this being an obligatory component in the International Diabetes Federation definition, lower than in the American Heart Association/National Heart, Lung, and Blood Institute criteria, and ethnic specific. The present article represents the outcome of a meeting between several major organizations in an attempt to unify criteria. It was agreed that there should not be an obligatory component, but that waist measurement would continue to be a useful preliminary screening tool. Three abnormal findings out of 5 would qualify a person for the metabolic syndrome. A single set of cut points would be used for all components except waist circumference, for which further work is required. In the interim, national or regional cut points for waist circumference can be used.

Objectives To describe new WHO 2020 guidelines on physical activity and sedentary behaviour. Methods The guidelines were developed in accordance with WHO protocols. An expert Guideline Development Group reviewed evidence to assess associations between physical activity and sedentary behaviour for an agreed set of health outcomes and population groups. The assessment used and systematically updated recent relevant systematic reviews; new primary reviews addressed additional health outcomes or subpopulations. Results The new guidelines address children, adolescents, adults, older adults and include new specific recommendations for pregnant and postpartum women and people living with chronic conditions or disability. All adults should undertake 150–300 min of moderate-intensity, or 75–150 min of vigorous-intensity physical activity, or some equivalent combination of moderate-intensity and vigorous-intensity aerobic physical activity, per week. Among children and adolescents, an average of 60 min/day of moderate-to-vigorous intensity aerobic physical activity across the week provides health benefits. The guidelines recommend regular muscle-strengthening activity for all age groups. Additionally, reducing sedentary behaviours is recommended across all age groups and abilities, although evidence was insufficient to quantify a sedentary behaviour threshold. Conclusion These 2020 WHO guidelines update previous WHO recommendations released in 2010. They reaffirm messages that some physical activity is better than none, that more physical activity is better for optimal health outcomes and provide a new recommendation on reducing sedentary behaviours. These guidelines highlight the importance of regularly undertaking both aerobic and muscle strengthening activities and for the first time, there are specific recommendations for specific populations including for pregnant and postpartum women and people living with chronic conditions or disability. These guidelines should be used to inform national health policies aligned with the WHO Global Action Plan on Physical Activity 2018–2030 and to strengthen surveillance systems that track progress towards national and global targets.

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
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\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

OBJECTIVE: To examine the global prevalence and major risk factors for diabetic retinopathy (DR) and vision-threatening diabetic retinopathy (VTDR) among people with diabetes. RESEARCH DESIGN AND METHODS: A pooled analysis using individual participant data from population-based studies around the world was performed. A systematic literature review was conducted to identify all population-based studies in general populations or individuals with diabetes who had ascertained DR from retinal photographs. Studies provided data for DR end points, including any DR, proliferative DR, diabetic macular edema, and VTDR, and also major systemic risk factors. Pooled prevalence estimates were directly age-standardized to the 2010 World Diabetes Population aged 20-79 years. RESULTS: A total of 35 studies (1980-2008) provided data from 22,896 individuals with diabetes. The overall prevalence was 34.6% (95% CI 34.5-34.8) for any DR, 6.96% (6.87-7.04) for proliferative DR, 6.81% (6.74-6.89) for diabetic macular edema, and 10.2% (10.1-10.3) for VTDR. All DR prevalence end points increased with diabetes duration, hemoglobin A(1c), and blood pressure levels and were higher in people with type 1 compared with type 2 diabetes. CONCLUSIONS: There are approximately 93 million people with DR, 17 million with proliferative DR, 21 million with diabetic macular edema, and 28 million with VTDR worldwide. Longer diabetes duration and poorer glycemic and blood pressure control are strongly associated with DR. These data highlight the substantial worldwide public health burden of DR and the importance of modifiable risk factors in its occurrence. This study is limited by data pooled from studies at different time points, with different methodologies and population characteristics.

Context and Purpose of This Guideline
\nStatement of Remit
\nTo align with its mission to reduce the global burden of raised
\nblood pressure (BP), the International Society of Hypertension
\n(ISH) has developed worldwide practice guidelines for the
\nmanagement of hypertension in adults, aged 18 years and
\nolder.
\nThe ISH Guidelines Committee extracted evidence-based
\ncontent presented in recently published extensively reviewed
\nguidelines and tailored and standards
\nof care in a practical format that is easy-to-use particularly
\nin low, but also in high resource settings – by clinicians, but
\nalso nurses and community health workers, as appropriate.
\nAlthough distinction between low and high resource settings
\noften refers to high (HIC) and low- and middle-income countries (LMIC), it is well established that in HIC there are areas
\nwith low resource settings, and vice versa.
\nHerein optimal care refers to evidence-based standard of
\ncare articulated in recent guidelines1,2 and summarized here,
\nwhereas standards recognize that
\nstandards would not always be possible. Hence essential standards refer to minimum standards of care. To allow specification of essential standards of care for low resource settings,
\nthe Committee was often confronted with the limitation or
\nabsence in clinical evidence, and thus applied expert opinion

The adoption and maintenance of physical activity are critical foci for blood glucose management and overall health in individuals with diabetes and prediabetes. Recommendations and precautions vary depending on individual characteristics and health status. In this Position Statement, we provide a clinically oriented review and evidence-based recommendations regarding physical activity and exercise in people with type 1 diabetes, type 2 diabetes, gestational diabetes mellitus, and prediabetes. Physical activity includes all movement that increases energy use, whereas exercise is planned, structured physical activity. Exercise improves blood glucose control in type 2 diabetes, reduces cardiovascular risk factors, contributes to weight loss, and improves well-being (1,2). Regular exercise may prevent or delay type 2 diabetes development (3). Regular exercise also has considerable health benefits for people with type 1 diabetes (e.g., improved cardiovascular fitness, muscle strength, insulin sensitivity, etc.) (4). The challenges related to blood glucose management vary with diabetes type, activity type, and presence of diabetes-related complications (5,6). Physical activity and exercise recommendations, therefore, should be tailored to meet the specific needs of each individual.

It is increasingly apparent that not only is a cure for the current worldwide diabetes epidemic required, but also for its major complications, affecting both small and large blood vessels. These complications occur in the majority of individuals with both type 1 and type 2 diabetes. Among the most prevalent microvascular complications are kidney disease, blindness, and amputations, with current therapies only slowing disease progression. Impaired kidney function, exhibited as a reduced glomerular filtration rate, is also a major risk factor for macrovascular complications, such as heart attacks and strokes. There have been a large number of new therapies tested in clinical trials for diabetic complications, with, in general, rather disappointing results. Indeed, it remains to be fully defined as to which pathways in diabetic complications are essentially protective rather than pathological, in terms of their effects on the underlying disease process. Furthermore, seemingly independent pathways are also showing significant interactions with each other to exacerbate pathology. Interestingly, some of these pathways may not only play key roles in complications but also in the development of diabetes per se. This review aims to comprehensively discuss the well validated, as well as putative mechanisms involved in the development of diabetic complications. In addition, new fields of research, which warrant further investigation as potential therapeutic targets of the future, will be highlighted.

Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies. A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

Even when adults meet physical activity guidelines, sitting for prolonged periods can compromise metabolic health. Television (TV) time and objective measurement studies show deleterious associations, and breaking up sedentary time is beneficial. Sitting time, TV time, and time sitting in automobiles increase premature mortality risk. Further evidence from prospective studies, intervention trials, and population-based behavioral studies is required.

The growing worldwide prevalence of type 2 diabetes mellitus in the young, as underlined by an earlier International Diabetes Federation (IDF) Consensus Statement 1, has highlighted a significant shortfall of data on the epidemiology of the disorder and the identification and treatment of children and adolescents at risk of progression to this disease. Urbanization, unhealthy diets, and increasingly sedentary lifestyles have contributed to increase the prevalence of childhood obesity, particularly in developing countries 2. Current treatment initiatives include school-based programs addressing physical activity and diet, which have been conducted with mixed success in reducing adiposity. There are limited safety data supporting the use of drugs for the treatment of obesity and related conditions such as type 2 diabetes in children and adolescents, and non-compliance in this population suggests that pharmacotherapy is unlikely to be effective long term 1. Although criteria have now been developed for bariatric surgery in teenagers 3, there are few evidence-based data available to support the increasing use of this modality in adolescents. Governments and society in general must be made more aware of the problems associated with obesity and the likelihood of progression to the metabolic syndrome in children and adolescents. Obesity, particularly in the central (abdominal) region, has been determined as a key factor in the etiology of type 2 diabetes 2. The prediction of health risks associated with obesity in youth is improved by the additional inclusion of waist circumference (WC) measure to the body mass index (BMI) percentile 4, 5. Such observations reinforce the importance of including WC in the assessment of childhood obesity to identify those at increased metabolic risk as a result of excess abdominal fat 5. The role of obesity can clearly be demonstrated in Japan, where a parallel increase in type 2 diabetes and obesity in children has occurred over the past few decades 6. Central (abdominal) obesity is also a key component in the IDF definition of metabolic syndrome in adults 2. The link between obesity, metabolic syndrome, and type 2 diabetes has already been characterized in adult populations 2. At present, 50–80% of almost 250 million adults worldwide with diabetes 7 are at risk of death from cardiovascular disease. Those with the metabolic syndrome are also at increased risk being twice as likely to die from, and three times as likely to have, cardiovascular complications as compared with those without the syndrome 8, 9. In addition, adults with the metabolic syndrome have a fivefold greater risk of developing type 2 diabetes 10. Already, one-quarter of the world’s adult population have metabolic syndrome 11, 12, and this condition is appearing with increasing frequency in children and adolescents, driven by the growing obesity epidemic in this young population 13-15. In 2004, the World Health Organization (WHO) reported that an estimated 22 million children younger than 5 yr of age and 10% of school-aged children, between 5 and 17 yr, were overweight or obese 16. WHO predicts that the prevalence of childhood obesity in developed and developing countries will continue to increase as has been seen in recent years. For example, from 1985 to 1997, in young Australians, the prevalence of overweight and obesity combined doubled and that of obesity trebled 17. In Thailand, the prevalence of obesity in those aged 5–12 yr increased from 12.2 to 15.6% in just 2 yr 18. In 2003–2004, 17.1% of children aged 2–19 yr in the USA were obese 19. Obesity is associated with an increase in cardiovascular risk factors (also indicators of metabolic syndrome) 20, and the persistence of these indicators from childhood and adolescence to young adulthood has been shown in several studies, including the Quebec Family Study 21, 22. Recently, the IDF released its guidelines for defining and diagnosing the metabolic syndrome in adults 2. The intention was to rationalize the existing multiple definitions of the syndrome and to avoid the confusion that arose as a result of conflicting opinions on the value of each set of criteria. The use of a single unified definition makes it possible to estimate the global prevalence of metabolic syndrome and make valid comparisons between nations. However, to date, there has not been a unified definition that can be used to assess risk in children and adolescents, and existing adult-based definitions of the metabolic syndrome may not be appropriate to address the problem in this age group. A study of adolescents using modified National Cholesterol Education Program (NCEP) [Adult Treatment Panel III (ATP III)] criteria 23 identified that 12% of the study group had the metabolic syndrome 24. When the ≥95th percentile of BMI was used as a cutoff point in the same study group, 31.3% were identified as having the syndrome, more than double of those previously found to be at risk. Duncan et al. 25 studied 991 adolescents (aged 12–19 yr) from National Health and Nutrition Examination Study (NHANES) 1999–2000 and used the ATP III definition modified for age. The overall prevalence of a metabolic syndrome phenotype among US adolescents increased from 4.2% in NHANES III (1988–1992) to 6.4% in NHANES 1999–2000. Based on population-weighted estimates, they estimated that more than 2 million US adolescents currently have a metabolic syndrome phenotype. In a population-based study of a Canadian Qji-Cree community involving 236 children aged 10–19 yr, Retnakaran et al. reported that 18.6% of the children met the criteria for the metabolic syndrome based on a pediatric metabolic syndrome definition based on the ATP III definition, and they used the ATP III definition modified for age and gender 26. Goodman et al. reported on a school-based, cross-sectional study of 1513 black, white, and Hispanic teenagers 27. Overall, the prevalence of ATP III-defined metabolic syndrome was 4.2% and that of the WHO-defined metabolic syndrome was 8.4%. The metabolic syndrome was found almost exclusively among obese teenagers in whom prevalence of the ATP III-defined metabolic syndrome was 19.5% and prevalence of WHO-defined metabolic syndrome 28 was 38.9%. No race or sex differences were present for ATP III definition. However, non-white teenagers were more likely to have metabolic syndrome by WHO criteria, and it was more common among girls if the WHO definition was used. Chi et al. have recently undertaken a literature review on definitions of the metabolic syndrome in children and adolescents published in the past decade 29. They noted that the prevalence of metabolic syndrome in pre-adolescent girls varies widely because of disagreement among proposed definitions of metabolic syndrome in pediatrics. They called for a consensus definition for the metabolic syndrome in children, which would allow researchers to make better temporal, biological, environmental, and social comparisons between data sets. The American College of Endocrinology definition 30 is not ideal in pediatric subjects as WC is rarely measured in children, and nomograms have only recently become available 31 for some ethnic groups but are not available for all. A recent paper has suggested yet another set of criteria with age- and gender-specific cutoff points 32. The variety of cutoff points used for the different components in this paper underlines the need for a single consistent definition with easily measurable components. Therefore, to date, no formal definition for the diagnosis of the metabolic syndrome in children and adolescents has been developed. The rapid increase in obesity highlights the urgency for a definition that could be used to further understand who is at high risk and to distinguish them from those with ‘simple’ uncomplicated obesity. The metabolic syndrome in adults is defined as a cluster of cardiovascular and diabetes risk factors including abdominal obesity, dyslipidemia, glucose intolerance, and hypertension 2. While the danger associated with clustering of components of the metabolic syndrome has been demonstrated in adults, where the presence of three or more components significantly increases the risk for coronary heart disease death/non-fatal myocardial infarction and the onset of new diabetes 33, few, if any, outcome data in children exist. While one definition, although with gender- and ethnicity-specific cutoff points, is suitable for use in the at-risk adult population 2, transposing a single definition to children and adolescents is problematic. Blood pressure, lipid levels, and anthropometric variables change with age and pubertal development. Puberty impacts on fat distribution and is known to cause a decrease both in insulin sensitivity, of approximately 30% with a complementary increase in insulin secretion 34, and in adiponectin levels 35. Therefore, single cutoff points cannot be used to define abnormalities in children. Instead, values above the 90th, 95th, or 97th percentile for gender and age are used. However, there has not been universal agreement as to which level to use for the criteria for the metabolic syndrome. The importance of the early identification of children at risk of developing the metabolic syndrome and subsequently progressing to type 2 diabetes and cardiovascular disease in later life must not be underestimated. From birth and before, circumstances can predispose a child to conditions such as obesity or dysglycemia. The presence of maternal gestational diabetes 36, low birth weight 37, infant feeding practices 38, early adiposity rebound 39, and genetic factors may all contribute to a child’s future level of risk. Being raised in an ‘obesogenic’ environment can also have a strong impact, as can the influence of socioeconomic factors 40, with weight gain often being observed as a positive correlate to affluence in developing countries. Longitudinal outcome studies and further research on the progression and etiology of the metabolic syndrome are urgently required to ascertain the long-term outcomes of abdominal obesity and clustering of the components of metabolic syndrome in at-risk children and to help improve future definitions of the syndrome. This new IDF definition of metabolic syndrome in children and adolescents was developed during a consensus workshop that brought together experts in the field of the metabolic syndrome and pediatrics. The purpose of the new definition of metabolic syndrome in children and adolescents is to expand on the IDF recommendations for managing type 2 diabetes in the young 1 and to provide a useful and unified tool for identifying those at risk. A clinically accessible diagnostic tool, avoiding measurements that may only be available in research settings, is needed to identify the metabolic syndrome in children and adolescents globally. This need has prompted the IDF to develop a definition that has used the limited data available from existing studies in youth. As with the adult criteria, we look on these new criteria as a starting point. As new information emerges, they can be modified. Inspired, in part, by the IDF worldwide definition of metabolic syndrome in adults 2, this new definition builds on previous studies investigating the prevalence of metabolic syndrome in children and adolescents, which have used modified adult criteria with varying cutoff points 12-14, 41, 42 (Table 1). The wide variety of cutoff points used has emphasized the need for a single consistent set of criteria, which is easily measurable and can be used as the basis for future work 29. Because of the developmental challenges presented by the age-related differences in children and adolescents, the new IDF definition of metabolic syndrome has been divided according to the following age groups: 6 to <10, 10 to <16, and ≥16 yr (Table 2). In all the three age groups, abdominal obesity is the ‘sine qua non’. We suggest that below the age of 10 yr, the metabolic syndrome as an entity is not diagnosed, although a strong message for weight reduction will be made for these children. At the age of 10 yr and more, a diagnosis of metabolic syndrome can be made. It requires the presence of abdominal obesity plus the presence of two or more of the other components (elevated triglycerides, low high-density lipoprotein (HDL)-cholesterol, high blood pressure, and elevated plasma glucose). The IDF adult criteria 2 can be used for adolescents aged ≥16 yr, while a modified version of these criteria will be applied to those aged 10 to <16 yr (use 90th percentile cutoff point for waist and <40 mg/dL of HDL for both sexes). On the basis of emerging new data, these criteria may change in the future. In adults, insulin resistance and abdominal obesity are considered to be significant causative factors in the development of the metabolic syndrome 9, 43, 44. The link between obesity, insulin resistance, and the risk of developing the metabolic syndrome has also been described in children 22, 27. With measurement of insulin resistance considered to be impractical for clinical use, abdominal adiposity was positioned as the ‘sine qua non’ in the IDF definition of metabolic syndrome in adults 2 and is recognized to be an independent risk factor for the development of cardiovascular disease in adults 45. Abdominal obesity can be easily assessed using the simple measure of WC, which is known to correlate more strongly with visceral adipose tissue (VAT) than BMI in adults 46 and is a strong predictor of cardiovascular disease risk factors in children 47. The correlation between WC and VAT has also been more recently demonstrated in children 48, further strengthening the existing evidence that WC is an effective measure of abdominal obesity 49 in the youth population. In children and adolescents, a number of studies have demonstrated a similar link between childhood obesity and elevated cardiovascular risk in later life. The Bogalusa Heart study showed that childhood overweight is related to the development of adverse risk factors (BMI, lipids, insulin, diabetes mellitus, and blood pressure) in adulthood and is attributable to the strong persistence of weight status from childhood to adulthood 50. Of the overweight children in the Bogalusa Heart study (BMI ≥95th percentile), 77% remained obese in adulthood. Furthermore, the Muscatine study demonstrated that in young adults, excess weight was the earliest predictor of coronary artery calcification 51. The ATP III definition, applied to a cohort of individuals aged 12–19 yr (NHANES III), identified that 4% of those studied were found to have the metabolic syndrome, with 80% of those meeting the criteria of being overweight 13. Using a modified version of the ATP III definition, metabolic syndrome in adolescents has also been linked to high levels of C-reactive protein, a pro-inflammatory marker. Of the five components of metabolic syndrome, C-reactive protein was higher only among those with abdominal obesity 41. Waist circumference in children is an independent predictor of insulin resistance, lipid levels, and blood pressure 4, 52-54– all components of metabolic syndrome. Moreover, in obese youth with similar BMI, insulin sensitivity is lower in those with high VAT and high waist/hip ratio 53, 54. Furthermore, insulin sensitivity decreases and insulin levels increase with increasing WC percentiles 3. These data, combined with the unequivocal evidence of the dangers of abdominal obesity in adulthood, support the use of abdominal obesity as the ‘sine qua non’ for the diagnosis of metabolic syndrome in children and adolescents. Percentiles rather than absolute values of WC have been used in the new criteria to compensate for varying degrees of development and ethnicity in the youth population. WC percentile data are becoming increasingly available worldwide 31, 55-58. Children with a WC >90th percentile are more likely to have multiple risk factors than those with a WC below this level 59. Several studies attempting to estimate the prevalence of metabolic syndrome in children and adolescents have already used the 90th percentile as a cutoff point for WC 13, 14, 41. We have also chosen to use the 90th percentile as a cutoff point for WC based on this existing evidence and aim to reassess criteria and cutoff points in 5 yr and modify the guidelines, if necessary, based on the new outcome data. Previous studies investigating the metabolic syndrome in children and adolescents have used a range of cutoff points primarily based on ATP III criteria for categorizing additional components of the syndrome, i.e., triglycerides, HDL-cholesterol, blood pressure, and fasting glucose (Table 1) 12-14, 41, 42. Other definitive sources include the National High Blood Pressure Education Program, which recommends blood pressure cutoff points of >90th or >95th percentile adjusted for height, age, and gender to identify ‘high normal’ blood pressure or prehypertension and high blood pressure or hypertension in children and adolescents 60. Cutoff points for impaired fasting glucose have previously followed recommendations by the American Diabetes Association (ADA) [100–125 mg/dL (≥5.6–6.9 mmol/L)] 61 and the NCEP/ATP III in adults [≥110 mg/dL (6.1 mmol/L)] 23, although the latter has recently changed to the lower ADA recommended levels 62. Criteria for defining lipid (triglyceride and HDL-cholesterol) imbalances are even less consistent in the youth population, with recommendations by the NCEP/ATP III (age specific), NHANES III (age and gender specific), and the National Growth and Health Study (age, gender, and ethnic specific), employing either absolute value or percentile cutoff points. In view of this lack of consistency, we believe that use of the adult levels for the present is wise until further information is available. We recommend the following topics as priorities for future research: Develop a better understanding of the relationship between body fat and its distribution in children and adolescents, e.g., dual energy X-ray absorptiometry (DEXA), WC, BMI, and height and weight percentiles; a) Explore whether early growth patterns predict future adiposity and features of the metabolic syndrome, diabetes, and cardiovascular disease and b) explore whether low birth weight predicts future metabolic syndrome, diabetes, and cardiovascular disease; Perform factor analysis in children and adolescents to establish grouping of metabolic characteristics – adiposity, dyslipidemia, hyperinsulinemia, hypoadiponectinemia, and insulin resistance; Investigate how should obesity in children could be better defined, e.g., weight/height, WC etc.; Develop ethnic-specific normal ranges for WC, ideally based on healthy values; Perform ethnic-specific studies of WC etc. vs. abdominal (truncal) fat based on magnetic resonance imaging and DEXA; Support studies of adiponectin, leptin, etc. in children and adolescents to determine if they may be predictors of metabolic syndrome in adulthood; Initiate long-term studies of multi-ethnic cohorts followed into adulthood to determine the natural history and effectiveness of intervention strategies, particularly lifestyle. In conclusion, to combat any conflict that could arise from these multiple interpretations of the metabolic syndrome in children and adolescents, the IDF consensus group has aimed primarily at developing a simple, easy-to-apply definition to begin using in the clinical setting. In the absence of definitive research findings at this time, the proposed IDF definition of the metabolic syndrome in children and adolescents (Table 2) adheres to the absolute values presented in the adult definition 2, with the exception of WC. As described previously, until such time that outcome data from studies in children and adolescents indicate otherwise, WC percentiles are recommended for use. Early detection, followed by treatment in the form of lifestyle intervention and possibly pharmacotherapy, if its safety has been clearly demonstrated, is vital in halting the progression of this syndrome pathway in the adolescent population. It is likely that this will reduce morbidity and mortality in adulthood, as well as minimize the global socioeconomic burden of cardiovascular disease and type 2 diabetes. The workshop was sponsored by an unrestricted educational grant to the IDF Task Force on Epidemiology and Prevention from sanofi-aventis.

The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry. The Catalog contains variant-trait associations and supporting metadata for >45 000 published GWAS across >5000 human traits, and >40 000 full P-value summary statistics datasets. Content is curated from publications or acquired via author submission of prepublication summary statistics through a new submission portal and validation tool. GWAS data volume has vastly increased in recent years. We have updated our software to meet this scaling challenge and to enable rapid release of submitted summary statistics. The scope of the repository has expanded to include additional data types of high interest to the community, including sequencing-based GWAS, gene-based analyses and copy number variation analyses. Community outreach has increased the number of shared datasets from under-represented traits, e.g. cancer, and we continue to contribute to awareness of the lack of population diversity in GWAS. Interoperability of the Catalog has been enhanced through links to other resources including the Polygenic Score Catalog and the International Mouse Phenotyping Consortium, refinements to GWAS trait annotation, and the development of a standard format for GWAS data.

Parametric mapping techniques provide a non-invasive tool for quantifying tissue alterations in myocardial disease in those eligible for cardiovascular magnetic resonance (CMR). Parametric mapping with CMR now permits the routine spatial visualization and quantification of changes in myocardial composition based on changes in T1, T2, and T2*(star) relaxation times and extracellular volume (ECV). These changes include specific disease pathways related to mainly intracellular disturbances of the cardiomyocyte (e.g., iron overload, or glycosphingolipid accumulation in Anderson-Fabry disease); extracellular disturbances in the myocardial interstitium (e.g., myocardial fibrosis or cardiac amyloidosis from accumulation of collagen or amyloid proteins, respectively); or both (myocardial edema with increased intracellular and/or extracellular water). Parametric mapping promises improvements in patient care through advances in quantitative diagnostics, inter- and intra-patient comparability, and relatedly improvements in treatment. There is a multitude of technical approaches and potential applications. This document provides a summary of the existing evidence for the clinical value of parametric mapping in the heart as of mid 2017, and gives recommendations for practical use in different clinical scenarios for scientists, clinicians, and CMR manufacturers.

The development of these updated guidelines was commissioned by the AACE, TOS, and ASMBS Board of Directors and adheres to the AACE 2010 protocol for standardized production of clinical practice guidelines (CPG). Each recommendation was re-evaluated and updated based on the evidence and subjective factors per protocol. Examples of expanded topics in this update include: the roles of sleeve gastrectomy, bariatric surgery in patients with type-2 diabetes, bariatric surgery for patients with mild obesity, copper deficiency, informed consent, and behavioral issues. There are 74 recommendations (of which 56 are revised and 2 are new) in this 2013 update, compared with 164 original recommendations in 2008. There are 403 citations, of which 33 (8.2%) are EL 1, 131 (32.5%) are EL 2, 170 (42.2%) are EL 3, and 69 (17.1%) are EL 4. There is a relatively high proportion (40.4%) of strong (EL 1 and 2) studies, compared with only 16.5% in the 2008 AACE-TOS-ASMBS CPG. These updated guidelines reflect recent additions to the evidence base. Bariatric surgery remains a safe and effective intervention for select patients with obesity. A team approach to perioperative care is mandatory with special attention to nutritional and metabolic issues.

The EACVI/ASE/Industry Task Force to standardize deformation imaging prepared this consensus document to standardize definitions and techniques for using two-dimensional (2D) speckle tracking echocardiography (STE) to assess left atrial, right ventricular, and right atrial myocardial deformation. This document is intended for both the technical engineering community and the clinical community at large to provide guidance on selecting the functional parameters to measure and how to measure them using 2D STE.This document aims to represent a significant step forward in the collaboration between the scientific societies and the industry since technical specifications of the software packages designed to post-process echocardiographic datasets have been agreed and shared before their actual development. Hopefully, this will lead to more clinically oriented software packages which will be better tailored to clinical needs and will allow industry to save time and resources in their development.

OBJECTIVE: Total sedentary (absence of whole-body movement) time is associated with obesity, abnormal glucose metabolism, and the metabolic syndrome. In addition to the effects of total sedentary time, the manner in which it is accumulated may also be important. We examined the association of breaks in objectively measured sedentary time with biological markers of metabolic risk. RESEARCH DESIGN AND METHODS: Participants (n = 168, mean age 53.4 years) for this cross-sectional study were recruited from the 2004-2005 Australian Diabetes, Obesity and Lifestyle study. Sedentary time was measured by an accelerometer (counts/minute(-1) < 100) worn during waking hours for seven consecutive days. Each interruption in sedentary time (counts/min > or = 100) was considered a break. Fasting plasma glucose, 2-h plasma glucose, serum triglycerides, HDL cholesterol, weight, height, waist circumference, and resting blood pressure were measured. MatLab was used to derive the breaks variable; SPSS was used for the statistical analysis. RESULTS: Independent of total sedentary time and moderate-to-vigorous intensity activity time, increased breaks in sedentary time were beneficially associated with waist circumference (standardized beta = -0.16, 95% CI -0.31 to -0.02, P = 0.026), BMI (beta = -0.19, -0.35 to -0.02, P = 0.026), triglycerides (beta = -0.18, -0.34 to -0.02, P = 0.029), and 2-h plasma glucose (beta = -0.18, -0.34 to -0.02, P = 0.025). CONCLUSIONS: This study provides evidence of the importance of avoiding prolonged uninterrupted periods of sedentary (primarily sitting) time. These findings suggest new public health recommendations regarding breaking up sedentary time that are complementary to those for physical activity.

AIMS: Prolonged sedentary time is ubiquitous in developed economies and is associated with an adverse cardio-metabolic risk profile and premature mortality. This study examined the associations of objectively assessed sedentary time and breaks (interruptions) in sedentary time with continuous cardio-metabolic and inflammatory risk biomarkers, and whether these associations varied by sex, age, and/or race/ethnicity. METHODS AND RESULTS: Cross-sectional analyses with 4757 participants (≥ 20 years) from the 2003/04 and 2005/06 US National Health and Nutrition Examination Survey (NHANES). An Actigraph accelerometer was used to derive sedentary time [< 100 counts per minute (cpm)] and breaks in sedentary time. Independent of potential confounders, including moderate-to-vigorous exercise, detrimental linear associations (P for trends < 0.05) of sedentary time with waist circumference, HDL-cholesterol, C-reactive protein, triglycerides, insulin, HOMA-%B, and HOMA-%S were observed. Independent of potential confounders and sedentary time, breaks were beneficially associated with waist circumference and C-reactive protein (P for trends <0.05). There was limited evidence of meaningful differences in associations with biomarkers by age, sex, or race/ethnicity. Notable exceptions were sex-differences in the associations of sedentary time and breaks with HDL-cholesterol, and race/ethnicity differences in the association of sedentary time with waist circumference with associations detrimental in non-Hispanic whites, null in Mexican Americans, and beneficial in non-Hispanic blacks. CONCLUSION: These are the first population-representative findings on the deleterious associations of prolonged sedentary time with cardio-metabolic and inflammatory biomarkers. The findings suggest that clinical communications and preventive health messages on reducing and breaking up sedentary time may be beneficial for cardiovascular disease risk.

Document reviewers: Hind Beheiry (Sudan), Irina Chazova (Russia), Albertino Damasceno (Mozambique), Anna Dominiczak (UK), Anastase Dzudie (Cameroon), Stephen Harrap (Australia), Hiroshi Itoh (Japan), Tazeen Jafar (Singapore), Marc Jaffe (USA), Patricio Jaramillo-Lopez (Colombia), Kazuomi Kario (Japan), Giuseppe Mancia (Italy), Ana Mocumbi (Mozambique), Sanjeevi N.Narasingan (India), Elijah Ogola (Kenya), Srinath Reddy (India), Ernesto Schiffrin (Canada), Ann Soenarta (Indonesia), Rhian Touyz (UK), Yudah Turana (Indonesia), Michael Weber (USA), Paul Whelton (USA), Xin Hua Zhang, (Australia), Yuqing Zhang (China).

It is postulated that localized tissue oxidative stress is a key component in the development of diabetic nephropathy. There remains controversy, however, as to whether this is an early link between hyperglycemia and renal disease or develops as a consequence of other primary pathogenic mechanisms. In the kidney, a number of pathways that generate reactive oxygen species (ROS) such as glycolysis, specific defects in the polyol pathway, uncoupling of nitric oxide synthase, xanthine oxidase, NAD(P)H oxidase, and advanced glycation have been identified as potentially major contributors to the pathogenesis of diabetic kidney disease. In addition, a unifying hypothesis has been proposed whereby mitochondrial production of ROS in response to chronic hyperglycemia may be the key initiator for each of these pathogenic pathways. This postulate emphasizes the importance of mitochondrial dysfunction in the progression and development of diabetes complications including nephropathy. A mystery remains, however, as to why antioxidants per se have demonstrated minimal renoprotection in humans despite positive preclinical research findings. It is likely that the utility of current study approaches, such as vitamin use, may not be the ideal antioxidant strategy in human diabetic nephropathy. There is now an increasing body of data to suggest that strategies involving a more targeted antioxidant approach, using agents that penetrate specific cellular compartments, may be the elusive additive therapy required to further optimize renoprotection in diabetes.

OBJECTIVE: Observational studies show breaking up prolonged sitting has beneficial associations with cardiometabolic risk markers, but intervention studies are required to investigate causality. We examined the acute effects on postprandial glucose and insulin levels of uninterrupted sitting compared with sitting interrupted by brief bouts of light- or moderate-intensity walking. RESEARCH DESIGN AND METHODS: Overweight/obese adults (n = 19), aged 45-65 years, were recruited for a randomized three-period, three-treatment acute crossover trial: 1) uninterrupted sitting; 2) seated with 2-min bouts of light-intensity walking every 20 min; and 3) seated with 2-min bouts of moderate-intensity walking every 20 min. A standardized test drink was provided after an initial 2-h period of uninterrupted sitting. The positive incremental area under curves (iAUC) for glucose and insulin (mean [95% CI]) for the 5 h after the test drink (75 g glucose, 50 g fat) were calculated for the respective treatments. RESULTS: The glucose iAUC (mmol/L) · h after both activity-break conditions was reduced (light: 5.2 [4.1-6.6]; moderate: 4.9 [3.8-6.1]; both P < 0.01) compared with uninterrupted sitting (6.9 [5.5-8.7]). Insulin iAUC (pmol/L) · h was also reduced with both activity-break conditions (light: 633.6 [552.4-727.1]; moderate: 637.6 [555.5-731.9], P < 0.0001) compared with uninterrupted sitting (828.6 [722.0-950.9]). CONCLUSIONS: Interrupting sitting time with short bouts of light- or moderate-intensity walking lowers postprandial glucose and insulin levels in overweight/obese adults. This may improve glucose metabolism and potentially be an important public health and clinical intervention strategy for reducing cardiovascular risk.

BACKGROUND: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease. METHODS: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th-95th percentile 1·04-13·5]) from 71 011 participants from 37 studies. FINDINGS: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1·14, 95% CI, 1·10-1·17), coronary disease excluding myocardial infarction (1·06, 1·00-1·11), heart failure (1·09, 1·03-1·15), fatal hypertensive disease (1·24, 1·15-1·33); and fatal aortic aneurysm (1·15, 1·03-1·28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0·94, 0·91-0·97). In comparison to those who reported drinking >0-≤100 g per week, those who reported drinking >100-≤200 g per week, >200-≤350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively. INTERPRETATION: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines. FUNDING: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council.