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Background Evidence for the effects of exercise and dietary interventions on cognition from long-term randomized controlled trials (RCTs) in large general populations remains insufficient. Objective The objective of our study was to investigate the independent and combined effects of resistance and aerobic exercise and dietary interventions on cognition in a population sample of middle-aged and older individuals. Methods We conducted a 4-y RCT in 1401 men and women aged 57-78 y at baseline. The participants were randomly assigned to the resistance exercise, aerobic exercise, diet, combined resistance exercise and diet, combined aerobic exercise and diet, or control group. Exercise goals were at least moderate-intensity resistance exercise ≥2 times/wk and at least moderate-intensity aerobic exercise ≥5 times/wk. Dietary goals were ≥400 g/d of vegetables, fruit, and berries; ≥2 servings of fish/wk; ≥14 g fiber/1000 kcal; and ≤10% of energy of daily energy intake from SFAs. The primary outcome was the change in global cognition measured by the total score of the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological tests [CERAD total score (CERAD-TS)]. The data were analyzed using the intention-to-treat principle and linear mixed-effects models. Results There was a trend toward improved CERAD-TS over 4 y in the combined aerobic exercise and diet group compared with the control group (net increase: 1.4 points; 95% CI: 0.1, 2.7; P = 0.06) adjusted for age, sex, years of education, symptoms of depression, and waist circumference at baseline. No other differences in CERAD-TS changes were found across the 6 study groups. Diet did not potentiate the effect of aerobic or resistance exercise on CERAD-TS. Conclusions A combination of at least moderate-intensity aerobic exercise and a healthy diet may improve cognition in older individuals over 4 y, but there was no effect of either of these interventions alone, resistance training alone, or resistance exercise with a healthy diet on cognition.

Cardiovascular health scores have emerged as a simple way to assess the risk to suffer from a cardiovascular disease. The American Heart Association's Life's Simple 7 constitutes of modifiable lifestyle factors to reduce cardiovascular risk. Its association with carotid properties is yet inconclusive. The aim of this study is to determine the association between the adherence to Life's Simple 7 and carotid properties in middle-aged to elderly Finns.A representative sample of Finnish men and women aged 55-74 years was included in the present study. Carotid intima-media thickness (cIMT), lumen diameter (cLD), and carotid distensibility were measured by transcutaneous ultrasound using state-of-the-art wall contour detection techniques. The Life's Simple 7 cardiovascular health score was calculated using seven categories (body mass index, cholesterol, systolic blood pressure, fasting plasma glucose, smoking status, physical activity, and diet). In accordance to the American Heart Association, for each category, an ideal score was given 2 points, intermediate scores 1 point, and poor scores 0 points.In total, 1400 (49.4% male) subjects were included in the analyses. After adjusting for age and sex, we found that subjects with a an ideal cardiovascular health score had lower cLD than those with an intermediate score (-0.21 mm, 95% CI: 0.37 to -0.05 mm, p=0.005) and a poor score (-0.39 mm, 95% CI: 0.65 to -0.12 mm, p=0.001). Similarly, subjects with an ideal health score had higher carotid distensibility than those with an intermediate score (0.0032 1/kPa, 95% CI: 0.009-0.0055 1/kPa, p=0.002) and a poor score (0.0018 1/kPa, 95% CI: 0.0005-0.0032 1/kPa, p=0.004). We found no differences regarding cIMT.In middle-aged to elderly Finns, higher adherence to the Life's Simple 7 is associated with lower cLD and higher distensibility, but not with cIMT. Adherence to healthy lifestyle habits is therefore associated with better carotid structure and carotid function in middle-aged to elderly Finns.

Recognizing correlates of low physical activity (PA) can help in targeting PA interventions for individuals who would benefit most from increasing their PA. We studied the associations of demographic, social, health, and lifestyle factors with low PA by sex in a population sample of 1,303 Finnish individuals aged 57–78 years. We defined low PA as no moderate or vigorous leisure-time PA reported in an interview. Altogether, 39% of men and 48% of women reported low PA. Satisfactory or poor perceived health and high BMI were independently associated with low PA in both sexes. In men, factors such as age, being divorced or separated, still working, having a weak social network, poor diet, and a health professional’s suggestion to increase PA were associated with low PA. In women, cardiovascular disease and depressive symptoms were associated with low PA. These results can be applied in targeting PA interventions.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery., The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (102318; 104781, 120315, 123885, 129619, 286284, 134309, 126925, 121584, 124282, 129378, 117787, 250207, 258753, 41071, 77299, 124243, 1114194, 24300796); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la Recherche; Agency for Health Care Policy Research (HS06516); Age UK Research into Ageing Fund; Åke Wiberg Foundation; ALF/LUA Research Grant in Gothenburg; ALFEDIAM; ALK-Abello´ A/S (Hørsholm, Denmark); American Heart Association (13POST16500011, 10SDG269004); Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; AstraZeneca; Australian Associated Brewers; Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 552485, 552498); Avera Research Institute; Bayer Diagnostics; Becton Dickinson; Biobanking and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007); Biocentrum Helsinki; Boston Obesity Nutrition Research Center (DK46200); British Heart Foundation (RG/10/12/28456, SP/04/002); Canada Foundation for Innovation; Canadian Institutes of Health Research (FRN-CCT-83028); Cancer Research UK; Cardionics; Center for Medical Systems Biology; Center of Excellence in Complex Disease Genetics and SALVECenter of Excellence in Genomics (EXCEGEN); Chief Scientist Office of the Scottish Government; City of Kuopio; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF–1333-00124, DFF–1331-007308); Danish Diabetes Academy; Danish Medical Research Council; Department of Psychology and Education of the VU University Amsterdam; Diabetes Hilfs- und Forschungsfonds Deutschland; Dutch Brain Foundation; Dutch Ministry of Justice; Emil Aaltonen Foundation; Erasmus Medical Center; Erasmus University; Estonian Government (IUT20-60, IUT24-6); Estonian Ministry of Education and Research (3.2.0304.11-0312); European Commission (230374, 284167, 323195, 692145, FP7 EurHEALTHAgeing-277849, FP7 BBMRI-LPC 313010, nr 602633, HEALTH-F2-2008-201865-GEFOS, HEALTH-F4-2007-201413, FP6 LSHM-CT-2004-005272, FP5 QLG2-CT-2002-01254, FP6 LSHG-CT-2006-01947, FP7 HEALTH-F4-2007-201413, FP7 279143, FP7 201668, FP7 305739, FP6 LSHG-CT-2006-018947, HEALTH-F4-2007-201413, QLG1-CT-2001-01252); European Regional Development Fund; European Science Foundation (EuroSTRESS project FP-006, ESF, EU/QLRT-2001-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, 01ZZ0403, 03ZIK012, 03IS2061A); Federal State of Mecklenburg - West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Food Standards Agency; Fondation de France; Fonds Santé; Genetic Association Information Network of the Foundation for the National Institutes of Health; German Diabetes Association; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); German Research Council (SFB-1052, SPP 1629 TO 718/2-1); GlaxoSmithKline; Göran Gustafssons Foundation; Göteborg Medical Society; Health and Safety Executive; Heart Foundation of Northern Sweden; Icelandic Heart Association; Icelandic Parliament; Imperial College Healthcare NHS Trust; INSERM, Réseaux en Santé Publique, Interactions entre les déterminants de la santé; Interreg IV Oberrhein Program (A28); Italian Ministry of Economy and Finance; Italian Ministry of Health (ICS110.1/RF97.71); John D and Catherine T MacArthur Foundation; Juho Vainio Foundation; King's College London; Kjell och Märta Beijers Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); Leiden University Medical Center; Lilly; LMUinnovativ; Lundbeck Foundation; Lundberg Foundation; Medical Research Council of Canada; MEKOS Laboratories (Denmark); Merck Santé; Mid-Atlantic Nutrition Obesity Research Center (P30 DK72488); Ministère de l’Économie, de l’Innovation et des Exportations; Ministry for Health, Welfare and Sports of the Netherlands; Ministry of Cultural Affairs of the Federal State of Mecklenburg-West Pomerania; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science of the Netherlands; MRC Human Genetics Unit; MRC-GlaxoSmithKline Pilot Programme Grant (G0701863); Municipality of Rotterdam; Netherlands Bioinformatics Centre (2008.024); Netherlands Consortium for Healthy Aging (050-060-810); Netherlands Genomics Initiative; Netherlands Organisation for Health Research and Development (904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192); Netherlands Organisation for Health Research and Development (2010/31471/ZONMW); Netherlands Organisation for Scientific Research (10-000-1002, GB-MW 940-38-011, 100-001-004, 60-60600-97-118, 261-98-710, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MaGW 452-04-314, GB-MaGW 452-06-004, 175.010.2003.005, 175.010.2005.011, 481-08-013, 480-05-003, 911-03-012); Neuroscience Campus Amsterdam; NHS Foundation Trust; Novartis Pharmaceuticals; Novo Nordisk; Office National Interprofessionel des Vins; Paavo Nurmi Foundation; Påhlssons Foundation; Päivikki and Sakari Sohlberg Foundation; Pierre Fabre; Republic of Croatia Ministry of Science, Education and Sport (108-1080315-0302); Research Centre for Prevention and Health, the Capital Region for Denmark; Research Institute for Diseases in the Elderly (014-93-015, RIDE2); Roche; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Executive Health Department (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du Diabète; State of Bavaria; Stroke Association; Swedish Diabetes Association; Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20140543); Swedish Research Council (2015-03657); Swedish Medical Research Council (K2007-66X-20270-01-3, 2011-2354); Swedish Society for Medical Research; Swiss National Science Foundation (33CSCO-122661, 33CS30-139468, 33CS30-148401); Tampere Tuberculosis Foundation; The Marcus Borgström Foundation; The Royal Society; The Wellcome Trust (084723/Z/08/Z, 088869/B/09/Z); Timber Merchant Vilhelm Bangs Foundation; Topcon; Torsten and Ragnar Söderberg's Foundation; UK Department of Health; UK Diabetes Association; UK Medical Research Council (MC_U106179471, G0500539, G0600705, G0601966, G0700931, G1002319, K013351, MC_UU_12019/1); UK National Institute for Health Research BioResource Clinical Research Facility and Biomedical Research Centre; UK National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre; UK National Institute for Health Research (RP-PG-0407-10371); Umeå University Career Development Award; United States – Israel Binational Science Foundation Grant (2011036); University Hospital Oulu (75617); University Medical Center Groningen; University of Tartu (SP1GVARENG); National Institutes of Health (AG13196, CA047988, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSC271201100004C, HHSN268200900041C, HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, HHSN268201500001I, HL36310, HG002651, HL034594, HL054457, HL054481, HL071981, HL084729, HL119443, HL126024, N01-AG12100, N01-AG12109, N01-HC25195, N01-HC55015, N01-HC55016, N01-HC55018, N01-HC55019, N01-HC55020, N01-HC55021, N01-HC55022, N01-HD95159, N01-HD95160, N01-HD95161, N01-HD95162, N01-HD95163, N01-HD95164, N01-HD95165, N01-HD95166, N01-HD95167, N01-HD95168, N01-HD95169, N01-HG65403, N02-HL64278, R01-HD057194, R01-HL087641, R01-HL59367, R01HL-086694, R01-HL088451, R24-HD050924, U01-HG-004402, HHSN268200625226C, UL1-RR025005, UL1-RR025005, UL1-TR-001079, UL1-TR-00040, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, DA12854, MH081802, MH66206, R01-D004215701A, R01-DK075787, R01-DK089256, R01-DK8925601, R01-HL088451, R01-HL117078, R01-DK062370, R01-DK072193, DK091718, DK100383, DK078616, 1Z01-HG000024, HL087660, HL100245, R01DK089256, 2T32HL007055-36, U01-HL072515-06, U01-HL84756, NIA-U01AG009740, RC2-AG036495, RC4-AG039029, R03 AG046389, 263-MA-410953, 263-MD-9164, 263-MD-821336, U01-HG004802, R37CA54281, R01CA63, P01CA33619, U01-CA136792, U01-CA98758, RC2-MH089951, MH085520, R01-D0042157-01A, MH081802, 1RC2-MH089951, 1RC2-MH089995, 1RL1MH08326801, U01-HG007376, 5R01-HL08767902, 5R01MH63706:02, HG004790, N01-WH22110, U01-HG007033, UM1CA182913, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, 44221); USDA National Institute of Food and Agriculture (2007-35205-17883); Västra Götaland Foundation; Velux Foundation; Veterans Affairs (1 IK2 BX001823); Vleugels Foundation; VU University’s Institute for Health and Care Research (EMGO+, HEALTH-F4-2007-201413) and Neuroscience Campus Amsterdam; Wellcome Trust (090532, 091551, 098051, 098381); Wissenschaftsoffensive TMO; and Yrjö Jahnsson Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution., A full list of acknowledgments appears in the Supplementary Note 4. Co-author A.J.M.d.C. recently passed away while this work was in process. This work was performed under the auspices of the Genetic Investigation of ANthropometric Traits (GIANT) consortium. We acknowledge the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium for encouraging CHARGE studies to participate in this effort and for the contributions of CHARGE members to the analyses conducted for this research. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (41071, 77299, 102318, 110413, 117787, 121584, 123885, 124243, 124282, 126925, 129378, 134309, 286284); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la 359 Recherche; Agency for Health Care Policy Research (HS06516); ALF/LUA research grant in Gothenburg; ALFEDIAM; ALK-Abelló A/S; Althingi; American Heart Association (13POST16500011); Amgen; Andrea and Charles Bronfman Philanthropies; Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; Australian National Health and Medical Research Council (241944, 339462, 389875, 389891, 389892, 389927, 389938, 442915, 442981, 496739, 552485, 552498); Avera Institute; Bayer Diagnostics; Becton Dickinson; BHF (RG/14/5/30893); Boston Obesity Nutrition Research Center (DK46200), Bristol-Myers Squibb; British Heart Foundation (RG/10/12/28456, RG2008/08, RG2008/014, SP/04/002); Medical Research Council of Canada; Canadian Institutes for Health Research (FRCN-CCT-83028); Cancer Research UK; Cardionics; Cavadis B.V., Center for Medical Systems Biology; Center of Excellence in Genomics; CFI; CIHR; City of Kuopio; CNAMTS; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF-1333-00124, DFF-1331-00730B); County Council of Dalarna; Dalarna University; Danish Council for Strategic Research; Danish Diabetes Academy; Danish Medical Research Council; Department of Health, UK; Development Fund from the University of Tartu (SP1GVARENG); Diabetes Hilfs- und Forschungsfonds Deutschland; Diabetes UK; Diabetes Research and Wellness Foundation Fellowship; Donald W. Reynolds Foundation; Dr Robert Pfleger-Stiftung; Dutch Brain Foundation; Dutch Diabetes Research Foundation; Dutch Inter University Cardiology Institute; Dutch Kidney Foundation (E033); Dutch Ministry of Justice; the DynaHEALTH action No. 633595, Economic Structure Enhancing Fund of the Dutch Government; Else Kröner-Fresenius-Stiftung (2012_A147, P48/08//A11/08); Emil Aaltonen Foundation; Erasmus University Medical Center Rotterdam; Erasmus MC and Erasmus University Rotterdam; the Municipality of Rotterdam; Estonian Government (IUT20-60, IUT24-6); Estonian Research Roadmap through the Estonian Ministry of Education and Research (3.2.0304.11-0312); European Research Council (ERC Starting Grant and 323195:SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC); European Regional Development Fund; European Science Foundation (EU/QLRT-2001-01254); European Commission (018947, 018996, 201668, 223004, 230374, 279143, 284167, 305739, BBMRI-LPC-313010, HEALTH-2011.2.4.2-2-EU-MASCARA, HEALTH-2011-278913, HEALTH-2011-294713-EPLORE, HEALTH-F2-2008-201865-GEFOS, HEALTH-F2-2013-601456, HEALTH-F4-2007-201413, HEALTH-F4-2007-201550-HYPERGENES, HEALTH-F7-305507 HOMAGE, IMI/115006, LSHG-CT-2006-018947, LSHG-CT-2006-01947, LSHM-CT-2004-005272, LSHM-CT-2006-037697, LSHM-CT-2007-037273, QLG1-CT-2002-00896, QLG2-CT-2002-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ0103, 01ZZ0403, 01ZZ9603, 03IS2061A, 03ZIK012); Federal State of Mecklenburg-West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Fondation Leducq; Food Standards Agency; Foundation for Strategic Research; French Ministry of Research; FRSQ; Genetic Association Information Network (GAIN) of the Foundation for the NIH; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); GlaxoSmithKline; Greek General Secretary of Research and Technology; Göteborg Medical Society; Health and Safety Executive; Healthcare NHS Trust; Healthway; Western Australia; Heart Foundation of Northern Sweden; Helmholtz Zentrum München—German Research Center for Environmental Health; Hjartavernd; Ingrid Thurings Foundation; INSERM; InterOmics (PB05 MIUR-CNR); INTERREG IV Oberrhein Program (A28); Interuniversity Cardiology Institute of the Netherlands (ICIN, 09.001); Italian Ministry of Health (ICS110.1/RF97.71); Italian Ministry of Economy and Finance (FaReBio di Qualità); Marianne and Marcus Wallenberg Foundation; the Ministry of Health, Welfare and Sports, the Netherlands; J.D.E. and Catherine T, MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health; Juho Vainio Foundation; Juvenile Diabetes Research Foundation International; KfH Stiftung Präventivmedizin e.V.; King's College London; Knut and Alice Wallenberg Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); La Fondation de France; Leenaards Foundation; Lilly; LMUinnovativ; Lundberg Foundation; Magnus Bergvall Foundation; MDEIE; Medical Research Council UK (G0000934, G0601966, G0700931, MC_U106179471, MC_UU_12019/1); MEKOS Laboratories; Merck Santé; Ministry for Health, Welfare and Sports, The Netherlands; Ministry of Cultural Affairs of Mecklenburg-West Pomerania; Ministry of Economic Affairs, The Netherlands; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science, The Netherlands; Ministry of Science, Education and Sport in the Republic of Croatia (108-1080315-0302); MRC centre for Causal Analyses in Translational Epidemiology; MRC Human Genetics Unit; MRC-GlaxoSmithKline pilot programme (G0701863); MSD Stipend Diabetes; National Institute for Health Research; Netherlands Brain Foundation (F2013(1)-28); Netherlands CardioVascular Research Initiative (CVON2011-19); Netherlands Genomics Initiative (050-060-810); Netherlands Heart Foundation (2001 D 032, NHS2010B280); Netherlands Organization for Scientific Research (NWO) and Netherlands Organisation for Health Research and Development (ZonMW) (56-464-14192, 60-60600-97-118, 100-001-004, 261-98-710, 400-05-717, 480-04-004, 480-05-003, 481-08-013, 904-61-090, 904-61-193, 911-11-025, 985-10-002, Addiction-31160008, BBMRI–NL 184.021.007, GB-MaGW 452-04-314, GB-MaGW 452-06-004, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MW 940-38-011, Middelgroot-911-09-032, NBIC/BioAssist/RK 2008.024, Spinozapremie 175.010.2003.005, 175.010.2007.006); Neuroscience Campus Amsterdam; NHS Foundation Trust; National Institutes of Health (1RC2MH089951, 1Z01HG000024, 24152, 263MD9164, 263MD821336, 2R01LM010098, 32100-2, 32122, 32108, 5K99HL130580-02, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, AG13196, CA047988, DA12854, DK56350, DK063491, DK078150, DK091718, DK100383, DK078616, ES10126, HG004790, HHSN268200625226C, HHSN268200800007C, HHSN268201200036C, HHSN268201500001I, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C, HL043851, HL45670, HL080467, HL085144, HL087660, HL054457, HL119443, HL118305, HL071981, HL034594, HL126024, HL130114, KL2TR001109, MH66206, MH081802, N01AG12100, N01HC55015, N01HC55016, N01C55018, N01HC55019, N01HC55020, N01HC55021, N01HC55022, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC95159, N01HC95160, N01HC95161, N01HC95162, N01HC95163, N01HC95164, N01HC95165, N01HC95166, N01HC95167, N01HC95168, N01HC95169, N01HG65403, N01WH22110, N02HL6‐4278, N01-HC-25195, P01CA33619, R01HD057194, R01HD057194, R01AG023629, R01CA63, R01D004215701A, R01DK075787, R01DK062370, R01DK072193, R01DK075787, R01DK089256, R01HL53353, R01HL59367, R01HL086694, R01HL087641, R01HL087652, R01HL103612, R01HL105756, R01HL117078, R01HL120393, R03 AG046389, R37CA54281, RC2AG036495, RC4AG039029, RPPG040710371, RR20649, TW008288, TW05596, U01AG009740, U01CA98758, U01CA136792, U01DK062418, U01HG004402, U01HG004802, U01HG007376, U01HL080295, UL1RR025005, UL1TR000040, UL1TR000124, UL1TR001079, 2T32HL007055-36, T32GM074905, HG002651, HL084729, N01-HC-25195, UM1CA182913); NIH, National Institute on Aging (Intramural funding, NO1-AG-1-2109); Northern Netherlands Collaboration of Provinces; Novartis Pharma; Novo Nordisk; Novo Nordisk Foundation; Nutricia Research Foundation (2016-T1); ONIVINS; Parnassia Bavo group; Pierre Fabre; Province of Groningen; Päivikki and Sakari Sohlberg Foundation; Påhlssons Foundation; Paavo Nurmi Foundation; Radboud Medical Center Nijmegen; Research Centre for Prevention and Health, the Capital Region of Denmark; the Research Institute for Diseases in the Elderly; Research into Ageing; Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center; Roche; Royal Society; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Government Health Directorates, Chief Scientist Office (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du 358 Diabète; State of Bavaria; Stiftelsen för Gamla Tjänarinnor; Stockholm County Council (560183, 592229); Strategic Cardiovascular and Diabetes Programmes of Karolinska Institutet and Stockholm County Council; Stroke Association; Swedish Diabetes Association; Swedish Diabetes Foundation (2013-024); Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20120197, 20150711); Swedish Research Council (0593, 8691, 2012-1397, 2012-1727, and 2012-2215); Swedish Society for Medical Research; Swiss Institute of Bioinformatics; Swiss National Science Foundation (3100AO-116323/1, 31003A-143914, 33CSCO-122661, 33CS30-139468, 33CS30-148401, 51RTP0_151019); Tampere Tuberculosis Foundation; Technology Foundation STW (11679); The Fonds voor Wetenschappelijk Onderzoek Vlaanderen, Ministry of the Flemish Community (G.0880.13, G.0881.13); The Great Wine Estates of the Margaret River Region of Western Australia; Timber Merchant Vilhelm Bangs Foundation; Topcon; Tore Nilsson Foundation; Torsten and Ragnar Söderberg's Foundation; United States – Israel Binational Science Foundation (Grant 2011036), Umeå University; University Hospital of Regensburg; University of Groningen; University Medical Center Groningen; University of Michigan; University of Utrecht; Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) (b2011036); Velux Foundation; VU University’s Institute for Health and Care Research; Västra Götaland Foundation; Wellcome Trust (068545, 076113, 079895, 084723, 088869, WT064890, WT086596, WT098017, WT090532, WT098051, 098381); Wissenschaftsoffensive TMO; Yrjö Jahnsson Foundation; and Åke Wiberg Foundation. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute (NHLBI); the National Institutes of Health (NIH); or the U.S. Department of Health and Human Services.

Division by total body weight is the usual way to standardise peak oxygen uptake (peak VO2) for body size. However, this method systematically underestimates cardiopulmonary fitness in obese individuals. Our aim was to analyse whether lean-mass is a better base for a body mass-independent standard of cardiopulmonary fitness.A population based sample of 578 men (body mass index (BMI) 19-47 kg/m(2)) and 592 women (BMI 16-49 kg/m(2)) 57-78 years of age. Peak VO2 was assessed by respiratory gas analysis during a maximal exercise test on a cycle ergometer. We studied the validity of the weight-ratio and the lean mass-ratio standards in a linear regression model.The weight-ratio standard implies an increase of peak VO2 per additional kg body weight with 20.7 ml/min (95% confidence interval (CI): 20.3-21.1) in women and 26.9 ml/min (95% CI: 26.4-27.5) in men. The observed increase per kg is only 8.5 ml/min (95% CI: 6.5-10.5) in men and 10.4 ml/min (95% CI: 7.5-13.4) in women. For the lean mass-ratio standard expected and observed increases in peak VO2 per kg lean mass were 32.3 (95% CI: 31.8-32.9) and 34.6 (95% CI: 30.0-39.1) ml/min for women and 36.2 (95% CI: 35.6-36.8) and 37.3 (95% CI: 32.1-42.4) ml/min in men. The lean mass-ratio standard is a body mass-independent measure of cardiopulmonary fitness in 100% of women and 58% of men; corresponding values for the weight-ratio standard were 11% and 16%.For comparisons of cardiopulmonary fitness across different categories of body mass, the lean mass-ratio standard should be used.

We validated the metabolic syndrome (MetS) score by confirmatory factor analysis (CFA) in children, middle-aged men, and older women and men and by investigating the relationships of the MetS score to incident type 2 diabetes, myocardial infarction, and cardiovascular and overall death in middle-aged men.We assessed the core features of MetS, calculated the MetS score using z scores for waist circumference, insulin, glucose, triacylglycerols, HDL-cholesterol and blood pressure, and carried out CFA to investigate whether MetS represents a single entity in population samples of 491 children, 1,900 middle-aged men, 614 older women and 555 older men from Finland. We also followed-up incident type 2 diabetes for 11 years and other outcomes for 17-18 years in middle-aged men.We carried out second-order CFAs in which the MetS was represented by a second-order latent variable underlying four latent variables characterised by abdominal obesity, insulin resistance, dyslipidaemia and raised blood pressure in different age groups. These second-order factors and factors derived from first-order CFA using previously proposed models were strongly associated with a composite MetS score in all age groups (r = 0.84-0.94) and similarly predicted type 2 diabetes, cardiovascular outcomes and mortality in middle-aged men. The risk of type 2 diabetes, myocardial infarction, cardiovascular death and overall death increased 3.67-, 1.38-, 1.56- and 1.44-fold, respectively, for a 1 SD increase in the MetS score.The MetS can be described as a single entity in all age groups. The MetS score is a valid tool for research evaluating cardiometabolic risk in different age groups. Further research is needed to define cut-off points for risk estimation in clinical practice.

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways., published version, peerReviewed

To dissect the genetic architecture of blood pressure (BP) and assess how its elevation promotes downstream cardiovascular diseases, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry. Genotypes from an additional 140,886 individuals of European ancestry were used as validation for loci reaching genome-wide significance but without prior support in the literature. We identified 66 BP loci, of which 17 were novel and 15 harbored multiple distinct association signals, and which together explain up to 3.5% of BP variation. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in BP control through modulating blood vessel tone and fluid filtration across multiple tissues, not solely the kidney. Importantly, the 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent (South-Asian, East-Asian and African), confirming that these are ancestral physiological effects that arose prior to human migration out of Africa. The 66-SNP BP risk score was significantly associated with target-organ damage in multiple tissues, with minor effects in the kidney. Our data expand current knowledge of BP pathways, and also, highlight that BP regulation and its effects may occur in multiple organs and tissues beyond the classic renal system.

ObjectiveTo examine 21-year longitudinal changes in dietary habits and their associations with age and marital status among women aged 50–60 years at baseline.DesignProspective, longitudinal study of a cohort in the FINMONICA population-based risk factor survey with clinical assessments in 1982, 1992 and 2003. Dietary habits were assessed via self-reported consumption of foods typically contributing to SFA, cholesterol and sugar intakes in the Finnish diet. A dietary risk score based upon five items was used.SettingKuopio region, Finland.SubjectsComplete data from all three assessments for 103 women of the original cohort of 299 were included for two age groups: 50–54 and 55–60 years at baseline.ResultsDietary habits improved between 1982 and 1992 and showed continued but less pronounced improvement between 1992 and 2003: within the younger age group, 78 % of the women reduced the number of dietary risk points from the 1982 to 2003 scores, whereas 3 % increased them and 19 % reported no change. In the older age group these percentages were 61 %, 23 % and 16 %, respectively. Women who remained married showed a steadier decline in dietary risk points than single women or women who were widows at the beginning of the follow-up.ConclusionsOlder women make positive changes to their dietary habits but the consistency of these changes may be affected by the ageing process, marital status and changes in the latter.

Cardiorespiratory fitness is currently estimated by dividing maximal oxygen consumption (VO(2max)) by body weight (per-weight standard). However, the statistically correct way to neutralize the effect of weight on VO(2max) in a given population is adjustment for body weight by regression techniques (adjusted standard). Our objective is to quantify the bias introduced by the per-weight standard in a population distributed across different categories of body mass.This is a cross-sectional study.Baseline measures from participants of the Dose-Responses to Exercise Training Study (DR's EXTRA), 635 men (body mass index (BMI): 19-47 kg m⁻²) and 638 women (BMI: 16-49 kg m⁻²) aged 57-78 years who performed oral glucose tolerance tests and maximal exercise stress tests with direct measurement of VO(2max). We compare the increase in VO(2max) implied by the per-weight standard with the real increase of VO(2max) per kg body weight. A linear logistic regression model estimates odds for abnormal glucose metabolism (either impaired fasting glycemia or impaired glucose tolerance or Type 2 diabetes) of the least-fit versus most-fit quartile according to both per-weight standard and adjusted standard.The per-weight standard implies an increase of VO(2max) with 20.9 ml min⁻¹ in women and 26.4 ml min⁻¹ in men per additional kg body weight. The true increase per kg is only 7.0 ml min⁻¹ (95% confidence interval: 5.3-8.8) and 8.0 ml min⁻¹ (95% confidence interval: 5.3-10.7), respectively. Risk for abnormal glucose metabolism in the least-fit quartile of the population is overestimated by 52% if the per-weight standard is used.In comparisons across different categories of body mass, the per-weight standard systematically underestimates cardiorespiratory fitness in obese subjects. Use of the per-weight standard markedly inflates associations between poor fitness and co-morbidities of obesity.

Vascular endothelium is a key determinant of circulatory homeostasis because it coordinates tissue perfusion and modulates arterial compliance. Endothelial dysfunction is considered to be a very early indication of atherosclerosis, being detectable even in childhood. Later on in life, endothelial dysfunction in large conduit arteries has been consistently shown to be a significant predictor of cardiovascular events. Elegantly conducted innovative studies have demonstrated the efficacy of physical exercise in improving endothelial dysfunction. Randomized controlled trials with parallel group design with adequate statistical power have consistently shown the therapeutic efficacy of both aerobic and resistance exercise training as physiologic means to improve, and even normalize, vascular endothelial function in patients with cardiovascular diseases. On the contrary, few data of comparable quality are available from randomized controlled trials among asymptomatic subjects or in those with metabolic disturbances. In addition, female participants are clearly under-represented in exercise training studies with vascular function as the key outcome measure.

The associations of different components of diet with metabolic syndrome (MetS) are largely unknown. We therefore studied the associations of intakes of selected food items and nutrients with the risk of having MetS.The participants were a representative population sample of 1334 individuals (671 women, 663 men) 57-78 years of age. Dietary intake was assessed by a 4-day food record. MetS was defined by the National Cholesterol Education Program criteria.Consumption of vegetables, non-root vegetables, legumes and nuts berries and fish had an inverse and consumption of sausage had a direct association with the risk of having MetS in men after adjustment for age, smoking and alcohol consumption. Consumption of vegetables and non-root vegetables had an inverse and consumption of sausage had a direct association with the risk of having MetS in women after these adjustments. However, after further adjustment for maximal oxygen uptake (VO₂(max)) most of these associations vanished. Men in the highest third of consumption of berries, fish, and legumes and nuts had 49, 37 and 44% lower risk of having MetS, respectively, than those in the lowest third after further adjustment for VO₂(max). Women in the highest third of sausage consumption had a 72% higher risk of having MetS than non-consumers.Consumption of legumes and nuts, berries and fish was inversely associated with MetS in men. Consumption of sausage was directly associated with MetS in women. VO₂(max) seems to be a strong confounding factor between food consumption and MetS.

Background Observational studies suggest that higher levels of physical activity and cardiorespiratory fitness associate with improved cognition. However, evidence from randomised controlled trials (RCT) is limited. We hypothesised that increased regular exercise improves cognition in older individuals. The trial is registered: ISRCTN45977199 (http://isrctn.org). Methods A population sample of 1335 men and women aged 57–78 years was randomised into aerobic exercise, resistance exercise, diet, combined aerobic exercise and diet, combined resistance exercise and diet or reference group for a 4-year intervention. Here, we report 2-year interim data. Exercise was assessed by a questionnaire and by maximal oxygen uptake (VO 2max ), an objective measure of exercise, and cognition using Consortium to establish a registry for Alzheimer's disease (CERAD) neuropsychological tests. Findings In the intention to treat analyses, regular exercise increased in exercise groups, but remained unchanged in reference and diet only groups ( P 2max remained unchanged in exercise groups, but decreased in reference and diet only groups ( P 2max to cognition during the first 2 years of intervention. In secondary analyses, improved VO 2max was associated with improved immediate memory in aerobic (β=0.11, P =0.001), resistance (β=0.08, P =0.018), diet (β=0.09, P =0.029) and combined aerobic and diet groups (β=0.09, P =0.013), with improved delayed memory in diet group (β=0.08, P =0.015) and with verbal performance in aerobic group (β=0.14, P =0.044). Those who were in the upper gender-specific VO 2max tertile had a 66.0% (95% confidence interval [CI] 34.2–82.4%, P =0.001) lower, and those in the middle tertile a 56.4% (95% CI 22.6–75.4%, P =0.005) lower risk of developing impaired delayed memory compared to those in the lower VO 2max tertile, after adjusting for potential confounders. Conclusions Present data from a large RCT among older individuals failed to show between group differences on the effects of regular exercise on cognition. However, secondary analyses suggest that higher levels of fitness may potentially mitigate memory impairment.

The aim of the study was to describe the levels and to create reference values of cardiorespiratory fitness, expressed as maximal oxygen consumption (VO(2max) ), maximal metabolic equivalents (METs) and maximal workload in aging men and women. We measured VO(2max) directly by a breath-by-breath method during a maximal exercise stress test on a bicycle ergometer with a linear workload increase of 20 W/min in a representative population sample of 672 men and 677 women aged 57-78 years. We presented the age and sex-specific categories of cardiorespiratory fitness (very low, low, medium, high and very high) based on variable distribution and non-linear regression models of VO(2max) , maximal METs and maximal workload. The linear age-related decrement of VO(2max) was -0.047 L/min/year (-2.3%) and -0.404 mL/kg/min/year (-1.6%) in men and -0.027 L/min/year (-1.9%) and -0.328 mL/kg/min/year (-1.6%) in women. After exclusion of diseased individuals, the rate of VO(2max) decrement remained similar. The number of chronic diseases (0, 1, 2 or ≥3) was inversely associated with VO(2max) in men (P

OBJECTIVE—We studied the associations of cardiorespiratory fitness with metabolic syndrome in older men and women, because such data are limited in representative population samples. RESEARCH DESIGN AND METHODS—We studied a population sample of 671 men and 676 women aged 57–79 years at baseline of a randomized controlled intervention study. We assessed maximal oxygen uptake (Vo2max) by respiratory gas analysis during a maximal bicycle exercise test. RESULTS—Vo2max had a strong, inverse, and graded association with the risk of having metabolic syndrome as defined by the National Cholesterol Education Program criteria. Men and women in the lowest third of Vo2max had 10.2- and 10.8-fold higher risks and those in the middle third had 2.9- and 4.7-fold higher risks (P < 0.001 all) of metabolic syndrome than those with the highest Vo2max after multivariable adjustments. Factor analysis generated a principal factor that was strongly loaded by the main components of metabolic syndrome and Vo2max (−0.68 in men and −0.70 in women). CONCLUSIONS—Low cardiorespiratory fitness is associated with metabolic syndrome in older men and women. Our findings suggest that low cardiorespiratory fitness could be considered a feature of metabolic syndrome.

To access publisher's full text version of this article click on the hyperlink at the bottom of the page We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease. cademy of Finland 77299 102318 10493 118065 123885 124243 129293 129680 136895 139635 211119 213506 251217 263836 Agence National de la Recherche Association de Langue Francaise pour l'Etude du Diabete et des Maladies Metaboliques Association Diabeete Risque Vasculaire Association Francaise des Diabetiques Association of Danish Pharmacies Augustinus Foundation Becket Foundation British Diabetes Association (BDA) Research British Heart Foundation Central Norway Health Authority Central Finland Hospital District Center for Inherited Disease Research (CIDR) City of Kuopio City of Leutkirch Copenhagen County Danish Centre for Evaluation and Health Technology Assessment Danish Council for Independent Research Danish Heart Foundation Danish Research Councils Deutsche Forschungsgemeinschaft ER 155/6-2 Diabetes Research Foundation Diabetes UK Doris Duke Charitable Foundation Erasmus Medical Center Erasmus University Estonian government SF0180142s08 European Commission ENGAGE HEALTH-F4-2007-201413 FP7-201413 FP7-245536 EXGENESIS LSHM-CT-2004-005272 FP6 LSHM_CT_2006_037197 LSHM-CT-2007-037273 C-Public Health 2004310 European Regional Development Fund Federal Ministry of Education and Research, Germany FKZ 01GI1128 FKZ 01EO1001 Federal Ministry of Health, Germany Finnish Diabetes Association Finnish Diabetes Research Foundation Finnish Foundation for Cardiovascular Research Finnish Medical Society Folkhalsan Research Foundation Foundation for Life and Health in Finland Foundation for Old Servants Fredrick och Ingrid Thuring Foundation French region of Nord-Pas-de-Calais (Contrat de Projets Etat-Region) German Center for Diabetes Research German Research Council GRK1041 German National Genome Research Network Groupe d'Etude des Maladies Metaboliques et Systemiques Health Care Centers in Vasa, Narpes and Korsholm, Finland Health Foundation Heinz Nixdorf Foundation Helmholtz Zentrum Munchen Helsinki University Central Hospital Research Foundation Hospital District of Southwest Finland Ib Henriksens Foundation IngaBritt and Arne Lundberg's Research Foundation 359 Karolinska Institutet Knut and Alice Wallenberg Foundation KAW 2009.0243 Kuopio University Hospital Lundbeck Foundation Magnus Bergvall Foundation Medical Faculty of University Duisburg-Essen Medical Research Council, UK G0000649 G0601261 Ministry for Health, Welfare and Sports, the Netherlands Ministry of Education and Culture, Finland 722 627 Ministry of Education, Culture and Science, the Netherlands Ministry of Health and Prevention, Denmark Ministry of Social Affairs and Health, Finland Ministry of Innovation, Science, Research and Technology of North Rhine-Westphalia, Germany Munich Center of Health Sciences Municipal Health Care Center and Hospital in Jakobstad, Finland municipality of Rotterdam, the Netherlands Narpes Health Care Foundation National Health Screening Service of Norway National Heart, Lung, and Blood Institute, USA HHSN268201100005C HHSN268201100006C HHSN268201100007C HHSN268201100008C HHSN268201100009C HHSN268201100010C HHSN268201100011C HHSN268201100012C N01HC25195 N02HL64278 R01HL087641 R01HL59367 R01HL086694 National Human Genome Research Institute, USA U01HG004402 N01HG65403 National Institute for Diabetes and Digestive and Kidney Diseases, USA R01DK078616 U01DK085526 K24DK080140 R01DK073490 National Institute for Health and Welfare, Finland National Institutes of Health, USA HHSN268200625226C UL1RR025005 R01DK062370 R01DK072193 1Z01HG000024 AG028555 AG08724 AG04563 AG10175 AG08861 U01HG004399 DK58845 CA055075 DK085545 DK098032 Netherlands Genomics Initiative Netherlands Organisation for Health Research and Development Netherlands Organisation of Scientific Research NOW Investments 175.010.2005.011 911-03-012 050-060-810 Nord-Trondelag County Council Nordic Center of Excellence in Disease Genetics Norwegian Institute of Public Health Norwegian Research Council Novo Nordisk Foundation Ollquist Foundation Oxford National Institute for Health Research (NIHR) Biomedical Research Centre Paavo Nurmi Foundation Paivikki and Sakari Sohlberg Foundation Perklen Foundation Pirkanmaa Hospital District, Finland Programme Hospitalier de Recherche Clinique Programme National de Recherche sur la Diabete Research Institute for Diseases in the Elderly 014-93-015 Robert Dawson Evans Endowment, Department of Medicine, Boston University School of Medicine and Boston Medical Center Royal Swedish Academy of Sciences Sarstedt, Germany Signe and Ane Gyllenberg Foundation Sigrid Juselius Foundation Slottery Machine Association, Finland Social Insurance Institution of Finland South OstroBothnia Hospital District state of Baden-Wurttemberg, Germany Stockholm County Council 560183 Swedish Cultural Foundation, Finland Swedish Diabetes Foundation Swedish e-science Research Center Swedish Foundation for Strategic Research Swedish Heart-Lung Foundation Swedish Research Council SFO EXODIAB 2009-1039 521-2010-3490 521-2007-4037 521-2008-2974 ANDIS 825-2010-5983 LUDC 349-2008-6589 8691 Swedish Society of Medicine Tore Nilsson Foundation Torsten and Ragnar Soderbergs Stiftelser MT33/09 University Hospital Essen University of Tromso University College London NIHR Biomedical Research Centre UK NIHR Cambridge Biomedical Research Centre Uppsala University Uppsala University Hospital Vaasa Hospital District Velux Foundation Wellcome Trust GR072960 076113 083948 090367 090532 083270 086596 098017 095101 098051 098381

Cardiorespiratory fitness as a prognostic factor in heart failure needs to be standardized for body composition

Background:Little is known about factors that modify the effectiveness of exercise interventions in increasing exercise. We aimed to identify moderators of the effectiveness of aerobic exercise intervention in maintaining increased aerobic exercise among older individuals.Methods:The participants of a 4-year randomized controlled trial were a population sample of 1410 men and women aged 57 to 78 years. The aerobic exercise group included 185 individuals and the control group included 169 individuals who reported low aerobic exercise at baseline. Maintained increase in aerobic exercise was defined as at least 60-minute increase in moderate-to-heavy aerobic exercise per week from baseline to 2- and 4-year assessments.Results:Individuals in the aerobic exercise group were 2.5 (95% CI 1.5 to 3.9) times more likely to maintain increased aerobic exercise than those in the control group. Individuals aged < 68.5 years but not older individuals succeeded in maintaining increased aerobic exercise in the intervention group (P = .02 for interaction). Individuals who were past smokers (P = .02 for interaction), were working (P = .05 for interaction), or had symptoms of depression (P = .05 for interaction) succeeded better in maintaining increased aerobic exercise in the intervention group than other individuals.Conclusions:These findings help in more precise targeting of future exercise interventions among older individuals.

Article, The rapid increase in the prevalence of dementia associated with ageing populations has stimulated interest in identifying modifiable lifestyle factors that could prevent cognitive impairment. One such potential preventive lifestyle factor is the Nordic diet that has been shown to reduce the risk of CVD; however, its effect on cognition has not been studied. The aim of the present study was to estimate the cross-sectional and longitudinal associations of the baseline Nordic diet with cognitive function at baseline and after a 4-year follow-up in a population-based random sample (n 1140 women and men, age 57–78 years) as secondary analyses of the Finnish Dose-Responses to Exercise Training study. The Nordic diet score was created based on reported dietary components in 4-d food records. Cognition was assessed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery and the Mini-mental State Examination (MMSE). The baseline Nordic diet score had been positively associated with Verbal Fluency (β 0·08 (95 % CI 0·00, 0·16), P= 0·039) and Word List Learning (β 0·06 (95 % CI 0·01, 0·10), P= 0·022) at 4 years but not with the Consortium to Establish a Registry for Alzheimer's Disease total score (CERAD-TS) or MMSE at 4 years, after adjustment for baseline cognitive scores, demographic factors and health-related factors. After excluding individuals with impaired cognition at baseline, the baseline Nordic diet score had also been positively associated with the CERAD-TS (β 0·10 (95 % CI 0·00, 0·20), P= 0·042) and MMSE (β 0·03 (95 % CI 0·00, 0·06), P= 0·039) at 4 years. These associations disappeared after further adjustment for energy intake. In conclusion, the Nordic diet might have a positive association with cognition in individuals with normal cognition., final draft, http://purl.org/eprint/status/PeerReviewed

Objective: To test the hypothesis that metabolic syndrome predicts cognitive impairment, and to examine the association of single metabolic risk factors with cognitive functioning. Methods: Weperformed a 12-year follow-up study in a population-based sample of 101 women aged 60–70 years at baseline. Metabolic syndrome wasdefined by the National Cholesterol Education Program criteria (≧3 out of 5 risk factors). Global cognitive function was measured by the Mini-Mental State Examination both at baseline and follow-up. A detailed neuropsychological evaluation for memory and cognitive speed was performed at follow-up. Results: The prevalence of metabolic syndrome increased from 13% at baseline to 49% at follow-up (p < 0.001). Women with metabolic syndrome at baseline had a 4.27 (95% confidence interval: 1.02–17.90; p = 0.047) times higher risk of poor memory at follow-up after adjustment for age, education and depression. The increasing number of metabolic risk factors was associated with worsening of memory at follow-up (p = 0.034 for linear trend). Women with low baseline levels of high-density lipoprotein (HDL) cholesterol were more likely to have poor memory at follow-up than those with higher HDL levels (p = 0.028). The risk of having poor memory increased by 46.5% (95% confidence interval: 15–66%; p = 0.008) with 1 SD decrease in HDL cholesterol level. Conclusion: In elderly women, metabolic syndrome may be an important contributor to worsening of memory, which is an essential part of mild cognitive impairment.

Background:The epidemic of sedentary lifestyle and obesity increases the risk of disability with aging. We studied the relationships of body composition, physical activity, and muscular fitness with balance and walking ability.Methods:Men and women, age 70 to 74 y (n = 146), were randomly selected from the Finnish population register. Body composition [body weight, body-mass index (BMI), waist circumference], physical activity (questionnaire), muscular fitness (hand-grip strength), balance (commonly used field tests), and walking ability (20 m walking test) were assessed.Results:BMI (r = –0.287, P < 0.001), waist circumference (r = –0.260, P = 0.002), physical activity (r = 0.206, P = 0.013), and hand-grip strength (r = 0.244, P = 0.003) correlated with balance. BMI (r = 0.330, P < 0.001), waist circumference (r = 0.237, P = 0.004), physical activity (r = –0.252, P = 0.002), and hand-grip strength (r = –0.307, P < 0.001) also correlated with walking time.Conclusions:Overweight and central obesity as well as low muscular fitness associate with impaired balance and walking ability in the elderly.

OBJECTIVE We studied the association of maximum oxygen uptake (Vo2max) with the development and resolution of metabolic syndrome (MetS) for 2 years in older individuals. RESEARCH DESIGN AND METHODS Subjects were a population sample of 1,226 men and women aged 57–78 years. We assessed Vo2max directly by respiratory gas analysis during maximum exercise testing and used dichotomous and continuous variables for MetS. RESULTS One SD increase in baseline Vo2max associated with 44% (95% CI 24–58) decreased risk of developing MetS. Individuals in the highest third of baseline Vo2max were 68% (37–84) less likely to develop MetS than those in the lowest third. One SD increase in Vo2max increased the likelihood to resolve MetS 1.8 (1.2–2.8) times. Individuals in the highest Vo2max third were 3.9 (1.5–9.9) times more likely to resolve MetS than those in the lowest third. CONCLUSIONS Higher levels of cardiorespiratory fitness protect against MetS and may resolve it in older individuals.

We report associations of saturated fat (SF) intake with impaired fasting glucose (IFG), impaired glucose tolerance (IGT), concurrent IFG+IGT and type 2 diabetes (T2DM) at different levels of cardiorespiratory fitness and body mass index (BMI). In a population-based sample (n=1261, age 58-78 years), oral glucose tolerance, 4-day food intake and maximal oxygen uptake were measured. High intake of SF (11.4 E%) was associated with elevated risk for IFG (4.36; 1.93-9.88), concurrent IFG+IGT (6.03; 1.25-29.20) and T2DM (4.77; 1.93-11.82) in the category of high BMI (26.5) and high fitness, whereas there was no significantly elevated risk in individuals reporting low intake of SF. Concurrent high BMI and low fitness were associated with elevated risks. In general, SF intake and fitness did not differentiate the risk of abnormal glucose metabolism among subjects with low BMI. Limited intake of SF may protect from diabetogenic effects of adiposity, but only in individuals with high level of fitness.

When the motivation for exercise is high and people are retired, the cost of time used for physical exercise may be lower and individuals may exercise more compared to individuals with a low motivational level and in working life. The aim was to study the effect of time cost of physical exercise on the amount of physical exercise and on health-related quality of life. We used 2-year data (n = 1,292) from a 4-year randomised controlled trial in a population-based sample of Eastern Finnish men and women, 57-78 years of age at baseline, in 2005-2006. In the statistical analysis, physical exercise and health outcomes were assumed to be endogenous variables explained with a set of exogenous variables. The statistical modelling was done by panel data instrumental variable regressions. Health-related quality of life was evaluated by the RAND 36-item survey and motives for exercise with a questionnaire. Joy as the motivation for physical exercise and retirement increased the amount of physical exercise per week (p < 0.001). A higher amount of exercise was associated with physical (p < 0.001) and mental (p < 0.001) components of quality of life. Moreover, a higher amount of physical exercise decreased the metabolic risk factor score (p < 0.001). The motivation and extra time, i.e. retirement, have a significant impact on the time spent on physical exercise (p < 0.001). Our data agree with the theory that high motivation and retirement lower the time cost of physical exercise. The results emphasise that motivation and the labour market position are important in determining the cost of physical exercise.

Background and Aims To study the independent and combined associations of diet and cardiorespiratory fitness with the prevalence of the metabolic syndrome (MetS). Methods and Results We studied a population-based random sample of 663 men and 671 women 57–78 years of age at baseline of an ongoing randomised controlled trial. Based on a 4-day food record a diet score was created according to goals achieved (vegetables ≥400 g/day, fish ≥2 servings/week, fibre ≥14 g/1000 kcal, saturated fat 2 max ) in a maximal symptom-limited bicycle ergometer test. MetS was defined by the National Cholesterol Education Program criteria. The lowest prevalence of MetS (5%) was observed among individuals in the highest VO 2 max tertile and achieving 3–4 dietary goals. The highest prevalence (55%) was observed among those in the lowest VO 2 max tertile and achieving none of the dietary goals. Among individuals in the highest VO 2 max tertile, the odds ratio of having MetS was 0.04 (95% CI 0.02–0.10) for those achieving 3–4 dietary goals, 0.07 (0.04–0.14) for those achieving 1–2 dietary goals, and 0.16 (0.07–0.37) for those achieving none of the dietary goals compared with individuals in the lowest VO 2 max tertile and achieving none of the goals after adjustment for confounding factors. Conclusion Healthy diet and higher levels of cardiorespiratory fitness are associated with a reduced risk of having MetS. However, fitness seems to have a stronger association with MetS than diet. Clinical Trial Registry No.: ISRCTN45977199, September 13 2006.

Brain-derived neurotrophic factor (BDNF) is one of the key molecules modulating brain plasticity. While low circulating levels of BDNF have been suggested to predispose to Alzheimer's disease, very little data are available on its association with cognitive function in general population. We evaluated the association between plasma BDNF levels and cognition in a representative population sample of ageing men and women. The subjects (n=1389) were participants of the Dose-Responses to Exercise Training (DR's EXTRA) Study and represent a random sample of Eastern Finnish people (684 men and 705 women), 57-79 years of age at baseline of the study. Plasma BDNF levels were measured by enzyme-linked immunosorbent assay (ELISA). Cognitive function was evaluated using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological test battery. Women had a higher mean (+/-SEM) plasma BDNF level than men (1721+/-55vs. 1495+/-54pg/ml, P

Objective: Several vascular risk factors have been linked to cognitive decline. However, little is known about the association between the atherosclerotic process and cognitive impairment. We investigated whether carotid intima-media thickness (IMT) predicts the risk of cognitive impairment and whether the putative impairment is specific for some cognitive domains. Methods: A 12-year population-based follow-up study was performed for a total of 91 women, aged 60–70 years at baseline. Ultrasonographically assessed carotid artery IMT and the Mini-Mental State Examination test were performed at baseline and 12-year follow-up. A detailed cognitive evaluation for memory and cognitive speed was performed in 2003. The mean of left and right carotid bifurcation IMT was used in the analyses for association with the risk for poor cognitive speed and memory. Results: Increased IMT at baseline was an independent predictor for poor memory (β = –5.004, 95% confidence interval = –7.74 to –2.27; p = 0.001) and cognitive speed (β = 2.562, 95% confidence interval = 1.19–4.94; p = 0.035) at 12-year follow-up after adjustment for age, education, depression, plasma LDL cholesterol, systolic blood pressure, cardiovascular disease, hormone replacement therapy, smoking, alcohol consumption and physical activity. The risk for poor memory (p = 0.023 for linear trend) and cognitive speed (p = 0.070 for linear trend) increased with increasing IMT tertiles. Conclusions: Carotid IMT predicts an increased risk for cognitive impairment, particularly poor memory and cognitive speed, in elderly women.

Background: inflammation has been linked to cognitive impairment. However, limited data are available on the association between inflammatory markers and cognitive function. Objectives: we tested the hypothesis that elevated serum concentration of high sensitivity C-reactive protein (hs-CRP), an established marker of low-grade inflammation, predicts cognitive impairment in elderly women. Design: a 12-year population-based follow-up study. Participants: a total of 97 women between 60 and 70 years of age at baseline. Methods: serum hs-CRP concentration was measured by a high sensitivity assay. Global cognitive function was measured with the Mini-Mental State Examination (MMSE), and memory and cognitive speed were measured with a detailed cognitive test battery. Results: higher baseline hs-CRP was associated with poorer memory at 12-year follow-up without adjustment and after adjustment for age, education and depression (standardised regression coefficient β −0.842, 95% confidence interval −1.602 to −0.083,P = 0.030),andfurtheradjustmentforthe useofhormone replacementtherapy,smoking,serumLDLcholesterol and body mass index (standardised regression coefficient β −0.817, 95% confidence interval −1.630 to −0.004, P = 0.049). Memory at 12-year follow-up worsened linearly with increasing hs-CRP at baseline (P = 0.048 for linear trend). There was no association between hs-CRP at baseline and cognitive speed or MMSE score at 12-year follow-up. Conclusions: high serum hs-CRP concentration predicts poorer memory 12 years later in elderly women. Hs-CRP may be a useful biomarker to identify individuals at an increased risk for cognitive decline.

To test the hypothesis that waist and hip circumferences together provide additional information on the progression of preclinical atherosclerosis beyond either of them alone in elderly women. A 12-year follow-up study. A population-based sample of 102 women 60–70 years of age at baseline. Waist and hip circumferences and body mass index (BMI) were assessed and carotid intima-media thickness (IMT) was quantified noninvasively by ultrasonography. There was a significant increase in the 12-year carotid IMT progression across the thirds of waist circumference (0.080, 0.277, 0.279 mm, P=0.02 for difference) and hip circumference (0.030, 0.342, 0.260 mm, P=0.001 for difference) adjusted for conventional risk factors (age, smoking, systolic blood pressure, serum low-density lipoprotein and high-density lipoprotein cholesterol, blood glucose). The association of waist circumference with IMT progression was not significant after further adjustment for hip circumference or BMI. Further adjustment for waist circumference and BMI did not change the association of hip circumference with IMT progression. The IMT progression was greatest in women with waist circumference >83 cm and hip circumference ⩽98 cm adjusted for conventional risk factors (P=0.003 for interaction). Not only waist circumference but also hip circumference is associated with the progression of carotid atherosclerosis during 12 years in elderly women. Women with both a larger waist circumference and a smaller hip circumference had the greatest progression of carotid atherosclerosis.

BACKGROUND: Although the metabolic syndrome can predict cardiovascular events in middle-aged individuals, data on its association with the progression of subclinical atherosclerosis, particularly in elderly women, are limited. We investigated the association of the metabolic syndrome with the progression of carotid intima-media thickness (IMT) in elderly women. METHODS: We performed a 12-year follow-up study in a population-based sample of 101 women (age range at baseline, 60-70 years). All study variables were measured at baseline and 12 years later. We used the National Cholesterol Education Program definition for metabolic syndrome (> or =3 of 5 risk factors) and quantified carotid IMT noninvasively by ultrasonography. RESULTS: The prevalence of metabolic syndrome increased from 13% at baseline to 46% after 12 years of follow-up (P