Publisher's version (útgefin grein) ; Emerging evidence suggests that parents' preconception exposures may influence offspring health. We aimed to investigate maternal and paternal smoking onset in specific time windows in relation to offspring body mass index (BMI) and fat mass index (FMI). We investigated fathers (n = 2111) and mothers (n = 2569) aged 39–65 years, of the population based RHINE and ECRHS studies, and their offspring aged 18–49 years (n = 6487, mean age 29.6 years) who participated in the RHINESSA study. BMI was calculated from self-reported height and weight, and FMI was estimated from bioelectrical impedance measures in a subsample. Associations with parental smoking were analysed with generalized linear regression adjusting for parental education and clustering by study centre and family. Interactions between offspring sex were analysed, as was mediation by parental pack years, parental BMI, offspring smoking and offspring birthweight. Fathers' smoking onset before conception of the offspring (onset ≥15 years) was associated with higher BMI in the offspring when adult (β 0.551, 95%CI: 0.174–0.929, p = 0.004). Mothers' preconception and postnatal smoking onset was associated with higher offspring BMI (onset <15 years: β1.161, 95%CI 0.378–1.944; onset ≥15 years: β0.720, 95%CI 0.293–1.147; onset after offspring birth: β2.257, 95%CI 1.220–3.294). However, mediation analysis indicated that these effects were fully mediated by parents' postnatal pack years, and partially mediated by parents' BMI and offspring smoking. Regarding FMI, sons of smoking fathers also had higher fat mass (onset <15 years β1.604, 95%CI 0.269–2.939; onset ≥15 years β2.590, 95%CI 0.544–4.636; and onset after birth β2.736, 95%CI 0.621–4.851). There was no association between maternal smoking and offspring fat mass. We found that parents' smoking before conception was associated with higher BMI in offspring when they reached adulthood, but that these effects were mediated through parents' pack years, suggesting that cumulative smoking exposure during offspring's childhood may elicit long lasting effects on offspring BMI. ; Co-ordination of the RHINESSA study has received funding from the Research Council of Norway (Grants No. 274767, 214123, 228174, 230827 and 273838), ERC StG project BRuSH #804199, the European Union's Horizon 2020 research and innovation program under grant agreement No. 633212 (the ALEC Study WP2), the Bergen Medical Research Foundation, and the Western Norwegian Regional Health Authorities (Grants No. 912011, 911892 and 911631). Study centres have further received local funding from the following: Bergen: the above grants for study establishment and co-ordination, and, in addition, World University Network (RDF and Sustainability grant), Norwegian Labour Inspection, and the Norwegian Asthma and Allergy Association. Albacete and Huelva: SEPAR. Fondo de Investigación Sanitaria (FIS PS09). Gøteborg, Umeå and Uppsala: the Swedish Lung Foundation, the Swedish Asthma and Allergy Association. Reykjavik: Iceland University. Melbourne: NHMRC, Melbourne University, Tartu: the Estonian Research Council (Grant No. PUT562). Århus: The Danish Wood Foundation (Grant No. 444508795), the Danish Working Environment Authority (Grant No. 20150067134). The RHINE study received funding by Norwegian Research Council, Norwegian Asthma and Allergy Association, Danish Lung Association, Swedish Heart and Lung Foundation, Vårdal Foundation for Health Care Science and Allergy Research, Swedish Asthma and Allergy Association, Swedish Lung Foundation, Icelandic Research Council, and Estonian Science Foundation. The co-ordination of ECRHS was supported by European Union's Horizon 2020 research and innovation program under grant agreement No. 633212 (the ALEC Study), the European Commission frameworks 5 and 7 (ECRHS I and II) and the Medical Research Council (ECRHS III). ; Peer Reviewed
Obese children are usually less active than their normal-weight counterparts, although the reasons for this remain unclear. The objective of the present study was to determine how a long-term program (3 years of intervention and 6 months of follow-up detraining) of physical exercise with or without a low calorie diet influenced sedentary obese children's intention to be physically active. The participants were 27 children, ages from 8 to 11 years, who formed two groups according to the program that they followed. One group followed an exercise program (three 90-min sessions per week), and the other this same exercise program together with a hypocaloric diet. The intention to be physically active was assessed via the Measurement of Intention to be Physically Active (MIFA) questionnaire. The subjects' scores at different times of the program (baseline, Year 3, and detraining) were compared using a repeated-measures ANOVA, and a post-hoc Tukey's test was applied to confirm the differences. After both the intervention and detraining, both groups showed greater intention to be physically active. This suggests the suitability of long-term physical exercise to generate greater intention to be physically active and thus establish healthy life habits including increased levels of physical activity. ; This study was funded by European Regional Development Fund (FEDER FUNDS) ("Una manera de hacer Europa") and the Autonomous Government of Extremadura (Junta de Extremadura-Consejeria de Infraestructura y Desarrollo Tecnologico) (PRI07B092, PO10012, GR10171, PRE08060). We also gratefully acknowledge the collaboration of M.D. (recruiting the sample), F.A. (prescription of the diet), F.R. (statistical advice), R.C. (checking the English), and of all the subjects and their parents who participated in the study. ; Peer reviewed
To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files ; Life course data on obesity may enrich the quality of epidemiologic studies analysing health consequences of obesity. However, achieving such data may require substantial resources. We investigated the use of body silhouettes in adults as a tool to reflect obesity in the past. We used large population-based samples to analyse to what extent self-reported body silhouettes correlated with the previously measured (9-23 years) body mass index (BMI) from both measured (European Community Respiratory Health Survey, N = 3 041) and self-reported (Respiratory Health In Northern Europe study, N = 3 410) height and weight. We calculated Spearman correlation between BMI and body silhouettes and ROC-curve analyses for identifying obesity (BMI ≥30) at ages 30 and 45 years. Spearman correlations between measured BMI age 30 (±2y) or 45 (±2y) and body silhouettes in women and men were between 0.62-0.66 and correlations for self-reported BMI were between 0.58-0.70. The area under the curve for identification of obesity at age 30 using body silhouettes vs previously measured BMI at age 30 (±2y) was 0.92 (95% CI 0.87, 0.97) and 0.85 (95% CI 0.75, 0.95) in women and men, respectively; for previously self-reported BMI, 0.92 (95% CI 0.88, 0.95) and 0.90 (95% CI 0.85, 0.96). Our study suggests that body silhouettes are a useful epidemiological tool, enabling retrospective differentiation of obesity and non-obesity in adult women and men. ; European Union Medical Research Council European Commission
Publisher's version (útgefin grein) ; Background: Previous studies have reported an association between weight increase and excess lung function decline in young adults followed for short periods. We aimed to estimate lung function trajectories during adulthood from 20-year weight change profiles using data from the population-based European Community Respiratory Health Survey (ECRHS). Methods: We included 3673 participants recruited at age 20-44 years with repeated measurements of weight and lung function (forced vital capacity (FVC), forced expiratory volume in 1 s (FEV 1)) in three study waves (1991-93, 1999-2003, 2010-14) until they were 39-67 years of age. We classified subjects into weight change profiles according to baseline body mass index (BMI) categories and weight change over 20 years. We estimated trajectories of lung function over time as a function of weight change profiles using population-averaged generalised estimating equations. Results: In individuals with normal BMI, overweight and obesity at baseline, moderate (0.25-1 kg/year) and high weight gain (>1 kg/year) during follow-up were associated with accelerated FVC and FEV 1 declines. Compared with participants with baseline normal BMI and stable weight (±0.25 kg/year), obese individuals with high weight gain during follow-up had -1011 mL (95% CI -1.259 to -763) lower estimated FVC at 65 years despite similar estimated FVC levels at 25 years. Obese individuals at baseline who lost weight (<-0.25 kg/year) exhibited an attenuation of FVC and FEV 1 declines. We found no association between weight change profiles and FEV 1 /FVC decline. Conclusion: Moderate and high weight gain over 20 years was associated with accelerated lung function decline, while weight loss was related to its attenuation. Control of weight gain is important for maintaining good lung function in adult life. ; Funding The present analyses are part of the ageing lungs in european cohorts (alec) study (www.alecstudy.org), which has received funding from the european Union's horizon 2020 research and innovation programme under grant agreement no. 633212. The local investigators and funding agencies for the european community respiratory health survey are reported in the online supplement. isglobal is a member of the cerca Programme, generalitat de catalunya. ; Peer Reviewed
Publisher's version (útgefin grein) ; Life course data on obesity may enrich the quality of epidemiologic studies analysing health consequences of obesity. However, achieving such data may require substantial resources. We investigated the use of body silhouettes in adults as a tool to reflect obesity in the past. We used large population-based samples to analyse to what extent self-reported body silhouettes correlated with the previously measured (9–23 years) body mass index (BMI) from both measured (European Community Respiratory Health Survey, N = 3 041) and self-reported (Respiratory Health In Northern Europe study, N = 3 410) height and weight. We calculated Spearman correlation between BMI and body silhouettes and ROC-curve analyses for identifying obesity (BMI ≥30) at ages 30 and 45 years. Spearman correlations between measured BMI age 30 (±2y) or 45 (±2y) and body silhouettes in women and men were between 0.62–0.66 and correlations for self-reported BMI were between 0.58–0.70. The area under the curve for identification of obesity at age 30 using body silhouettes vs previously measured BMI at age 30 (±2y) was 0.92 (95% CI 0.87, 0.97) and 0.85 (95% CI 0.75, 0.95) in women and men, respectively; for previously self-reported BMI, 0.92 (95% CI 0.88, 0.95) and 0.90 (95% CI 0.85, 0.96). Our study suggests that body silhouettes are a useful epidemiological tool, enabling retrospective differentiation of obesity and non-obesity in adult women and men. ; The project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 633212. The co-ordination of ECRHS I and ECRHS I was supported by the European Commission. The co-ordination of ECRHS III was supported by the Medical Research Council (Grant Number 92091). The co-ordination of the RHINE study is led by Professor C. Janson at the Uppsala University. The funding sources for the local ECRHS and RHINE studies are provided in the on-line supplement. ; Peer Reviewed
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. ; Peer Reviewed
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. ; Peer Reviewed
To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files ; Introduction Sleep length has been associated with obesity and various adverse health outcomes. The possible association of sleep length and respiratory symptoms has not been previously described. The aim of this study was to investigate the association between sleep length and respiratory symptoms and whether such an association existed independent of obesity. Methods This is a multicentre, cross-sectional, population-based study performed in 23 centres in 10 different countries. Participants (n=5079, 52.3% males) were adults in the third follow-up of the European Community Respiratory Health Survey III. The mean +/- SD age was 54.2 +/- 7.1 (age range 39-67 years). Information was collected on general and respiratory health and sleep characteristics. Results The mean reported nighttime sleep duration was 6.9 +/- 1.0 hours. Short sleepers (= 9 hours per night) were n=271 (4.3%). Short sleepers were significantly more likely to report all respiratory symptoms (wheezing, waking up with chest tightness, shortness of breath, coughing, phlegm and bronchitis) except asthma after adjusting for age, gender, body mass index (BMI), centre, marital status, exercise and smoking. Excluding BMI from the model covariates did not affect the results. Short sleep was related to 11 out of 16 respiratory and nasal symptoms among subjects with BMI >= 30 and 9 out of 16 symptoms among subjects with BMI = 30. Conclusions Our results show that short sleep duration is associated with many common respiratory symptoms, and this relationship is independent of obesity. ; European Union
Publisher's version (útgefin grein). ; Background: Overweight status and asthma have increased during the last decades. Being overweight is a known risk factor for asthma, but it is not known whether it might also increase asthma risk in the next generation. Objective: We aimed to examine whether parents being overweight in childhood, adolescence, or adulthood is associated with asthma in their offspring. Methods: We included 6347 adult offspring (age, 18-52 years) investigated in the Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) multigeneration study of 2044 fathers and 2549 mothers (age, 37-66 years) investigated in the European Community Respiratory Health Survey (ECRHS) study. Associations of parental overweight status at age 8 years, puberty, and age 30 years with offspring's childhood overweight status (potential mediator) and offspring's asthma with or without nasal allergies (outcomes) was analyzed by using 2-level logistic regression and 2-level multinomial logistic regression, respectively. Counterfactual-based mediation analysis was performed to establish whether observed associations were direct or indirect effects mediated through the offspring's own overweight status. Results: We found statistically significant associations between both fathers' and mothers' childhood overweight status and offspring's childhood overweight status (odds ratio, 2.23 [95% CI, 1.45-3.42] and 2.45 [95% CI, 1.86-3.22], respectively). We also found a statistically significant effect of fathers' onset of being overweight in puberty on offspring's asthma without nasal allergies (relative risk ratio, 2.31 [95% CI, 1.23-4.33]). This effect was direct and not mediated through the offspring's own overweight status. No effect on offspring's asthma with nasal allergies was found. Conclusion: Our findings suggest that metabolic factors long before conception can increase asthma risk and that male puberty is a time window of particular importance for offspring's health. ; This study was funded by the European Union's Horizon 2020 research and innovation program as part of the ALEC study (Ageing Lungs in European Cohorts study, grant no. 633212). The RHINESSA generation study also received funding by the Research Council of Norway (grant nos. 214123 and 228174), the Bergen Medical Research Foundation (Norway), the Western Norwegian Regional Health Authorities (grant nos. 912011, 911892, and 911631), the Norwegian Labour Inspection, the Norwegian Asthma and Allergy Association, the Danish Woods Foundation (grant no. 444508795), the Danish Working Environment Authority (grant no. 20150067134), the Swedish Lung Foundation, the Swedish Asthma and Allergy Association, and the Estonian Research Council (grant no. PUT562). The funding agencies had no direct role in the conduct of the study; the collection, management, statistical analysis, and interpretation of the data; and the preparation or approval of the manuscript. ; Peer Reviewed
To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files ; Multiple sclerosis (MS) is an autoimmune disease with both genetic and environmental risk factors. Recent studies indicate that childhood and adolescent obesity double the risk of MS, but this association may reflect unmeasured confounders rather than causal effects of obesity. We used separate-sample Mendelian randomization to estimate the causal effect of body mass index (BMI) on susceptibility to MS. Using data from non-Hispanic white members of the Kaiser Permanente Medical Care Plan of Northern California (KPNC) (2006-2014; 1,104 cases of MS and 10,536 controls) and a replication data set from Sweden (the Epidemiological Investigation of MS (EIMS) and the Genes and Environment in MS (GEMS) studies, 2005-2013; 5,133 MS cases and 4,718 controls), we constructed a weighted genetic risk score using 97 variants previously established to predict BMI. Results were adjusted for birth year, sex, education, smoking status, ancestry, and genetic predictors of MS. Estimates in KPNC and Swedish data sets suggested that higher genetically induced BMI predicted greater susceptibility to MS (odds ratio = 1.13, 95% confidence interval: 1.04, 1.22 for the KPNC sample; odds ratio = 1.09, 95% confidence interval: 1.03, 1.15 for the Swedish sample). Although the mechanism remains unclear, to our knowledge, these findings support a causal effect of increased BMI on susceptibility to MS for the first time, and they suggest a role for inflammatory pathways that characterize both obesity and the MS disease process. ; National Institute of Neurological Disorders and Stroke National Institute of Allergy and Infectious Diseases Robert Wood Johnson Foundation Wayne and Gladys Valley Foundation Ellison Medical Foundation AFA Foundation Knut and Alice Wallenberg Foundation Swedish Brain Foundation Margareta af Ugglas Foundation European Union Seventh Framework ...