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Bradfeld JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernandez-Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga JJ, Íñiguez C, Kobes S, Leinonen J, Lowry E, Lyytikainen LP, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong C, Cruz M, Elliott P, Franks S, Frithiof-Bøjsøe C, Gauderman WJ, Glessner JT, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf H, Kelly A, Kindler J, Kähönen M, Lanca C, Lappe J, Lee NR, McCormack S, Mentch FD, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo YY, Baier LJ, van Beijsterveldt T, Adair LS, Boomsma DI, de Geus E, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Hansen T, Hardy R, Hivert MF, Holm JC, Jaddoe VWV, Järvelin MR, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfeld S, Pennell CE, Perry JRB, Raitakari O, Rivadeneira F, Saw SM, Sebert S, Shepherd JA, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hypponen E, Power C, McCarthy MI, Freathy RM, Widén E, Hakonarson H, Prokopenko I, Voight BF, Zemel BS, Grant SFA, Cousminer DL. Author Correction: Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes. Genome Biol 2024; 25:129. [PMID: 38773652 DOI: 10.1186/s13059-024-03276-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2024] Open
Affiliation(s)
- Jonathan P Bradfeld
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Rachel L Kember
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Anna Ulrich
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Zhanna Balkhiyarova
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- People-Centred Artifcial Intelligence Institute, University of Surrey, Guildford, UK
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Neil M Davies
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Ruby Fore
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Amitavo Ganguli
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, Valencia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Jaakko Leinonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Leo-Pekka Lyytikainen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Theresia M Schnurr
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Christian Theil Have
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK
| | - Elisabeth Thiering
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute, Newcastle, NSW, 2305, Australia
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Louise Aas Holm
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - Alessandra Chesi
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Catherine Choong
- Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA, Australia
| | - Miguel Cruz
- Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Paul Elliott
- MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Steve Franks
- Institute of Reproductive & Developmental Biology, Imperial College London, London, UK
| | - Christine Frithiof-Bøjsøe
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - W James Gauderman
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Joseph T Glessner
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Vicente Gilsanz
- Center for Endocrinology, Diabetes & Metabolism, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | | | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Marika Kaakinen
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Institute of Reproductive & Developmental Biology, Imperial College London, London, UK
| | - Heidi Kalkwarf
- Department of Pediatrics, Cincinnati Children's Hospital, University of Cincinnati, Cincinnati, OH, USA
| | - Andrea Kelly
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Joseph Kindler
- College of Family and Consumer Sciences, University of Georgia, Athens, GA, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
| | - Carla Lanca
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Joan Lappe
- Department of Medicine and College of Nursing, Creighton University School of Medicine, Omaha, NB, USA
| | - Nanette R Lee
- USC-Ofce of Population Studies Foundation, Inc, University of San Carlos, Cebu, Philippines
| | - Shana McCormack
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Frank D Mentch
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jonathan A Mitchell
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, 33014, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
| | - Harri Niinikoski
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Physiology, University of Turku, Turku, Finland
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
- Department of Nutrition, Harvard T.H Chan School of Public Health, Boston, MA, 02115, USA
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Paavo Nurmi Centre, Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Toos van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mònica Guxens
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Johan G Eriksson
- Institute of Clinical Medicine Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Department of Obstetrics & Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Frank D Gilliland
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Torben Hansen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Rebecca Hardy
- Cohort and Longitudinal Studies Enhancement Resources (CLOSER), UCL Institute of Education, London, UK
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Jens-Christian Holm
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
- The Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- Unit of Primary Health Care, Oulu University Hospital, OYS, Kajaanintie 50, 90220, Oulu, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, 33014, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
| | - David A Mackey
- Lions Eye Institute, Centre for Ophthalmology and Visual Science, Centre for Eye Research Australia, University of Western Australia, Perth, WA, Australia
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, Nancy, France
- Department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, Nancy, France
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Juha Mykkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Sharon Oberfeld
- Division of Pediatric Endocrinology, Columbia University Medical Center, New York, NY, USA
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute, Newcastle, NSW, 2305, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, NSW, 2305, Australia
| | - John R B Perry
- Metabolic Research Laboratory, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - John A Shepherd
- Department of Epidemiology and Population Science, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
| | - Thorkild I A Sørensen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Maties Torrent
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Fundació Institut d'Investigació Sanitària Illes Balears - IdISBa, Palma, Spain
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Elina Hypponen
- UCL Great Ormond Street Institute of Child Health, London, UK
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Chris Power
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Current Address: Genentech, 1 DNA Way, San Francisco, CA, 94080, USA
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, EX2 5DW, UK
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Inga Prokopenko
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- People-Centred Artifcial Intelligence Institute, University of Surrey, Guildford, UK
- UMR 8199 - EGID, Institut Pasteur de Lille, CNRS, University of Lille, 59000, Lille, France
| | - Benjamin F Voight
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Babette S Zemel
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
| | - Diana L Cousminer
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Currently Employed By GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA, 19426, USA.
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Li R, Jobson BT, Wen M, Li AL, Huangfu Y, Zhang W, Hardy R, O'Keeffe P, Simpson J, Fauci M, Paden N. Anthropogenic, biogenic, and photochemical influences on surface formaldehyde and its significant decadal (2006-2017) decrease in the Lewiston-Clarkston valley of the northwestern United States. Chemosphere 2024; 349:140962. [PMID: 38104739 DOI: 10.1016/j.chemosphere.2023.140962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/06/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023]
Abstract
Formaldehyde (HCHO) is a key carcinogen and plays an important role in atmospheric chemistry. Both field measurements and Positive Matrix Factorization (PMF) modeling have been employed to investigate the concentrations and sources of HCHO in the Lewiston-Clarkston (LC) valley of the mountainous northwestern U.S. Different instruments were deployed to measure surface formaldehyde and other related compounds in July of 2016 and 2017. The measurements reveal that the average HCHO concentrations have significantly decreased to 2-5 ppb in the LC valley in comparison to its levels (10-20 ppb) observed in July 2006. This discovery with surface measurements deserves attention given that satellite retrievals showed an increasing long-term trend from 2005 to 2014 in total vertical column density of HCHO in the region, suggesting that satellite instruments may not adequately resolve small valleys in the mountainous region. Our PMF modeling identified four major sources of HCHO in the valley: (1) emissions from a local paper mill, (2) secondary formation and background, (3) biogenic sources, and (4) traffic. This study reveals that the emissions from the paper mill cause high HCHO spikes (6-19 ppb) in the early morning. It is found that biogenic volatile organic compounds (VOCs) in the area are influenced by national forests surrounding the region (e.g., Nez Perce-Clearwater, Umatilla, Wallowa-Whitman, and Idaho Panhandle National Forests). The results provide useful information for developing strategies to control HCHO levels and have implications for future HCHO studies in atmospheric chemistry, which affects secondary aerosols and ozone formation.
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Affiliation(s)
- R Li
- Idaho Department of Environmental Quality, Boise, ID, USA.
| | - B T Jobson
- Laboratory for Atmospheric Research, Department of Civil & Environmental Engineering, Washington State University, Pullman, WA, USA
| | - M Wen
- Laboratory for Atmospheric Research, Department of Civil & Environmental Engineering, Washington State University, Pullman, WA, USA
| | - A L Li
- Boise High School, Boise, ID, USA
| | - Y Huangfu
- Laboratory for Atmospheric Research, Department of Civil & Environmental Engineering, Washington State University, Pullman, WA, USA
| | - W Zhang
- Idaho Department of Environmental Quality, Boise, ID, USA
| | - R Hardy
- Idaho Department of Environmental Quality, Boise, ID, USA
| | - P O'Keeffe
- Laboratory for Atmospheric Research, Department of Civil & Environmental Engineering, Washington State University, Pullman, WA, USA
| | - J Simpson
- Air Quality Program, Nez Perce Tribe, Lapwai, ID, USA
| | - M Fauci
- Air Quality Program, Nez Perce Tribe, Lapwai, ID, USA
| | - N Paden
- Idaho Department of Environmental Quality, Boise, ID, USA
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3
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Bradfield JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernandez-Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga JJ, Íñiguez C, Kobes S, Leinonen J, Lowry E, Lyytikainen LP, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong C, Cruz M, Elliott P, Franks S, Frithioff-Bøjsøe C, Gauderman WJ, Glessner JT, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf H, Kelly A, Kindler J, Kähönen M, Lanca C, Lappe J, Lee NR, McCormack S, Mentch FD, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo YY, Baier LJ, van Beijsterveldt T, Adair LS, Boomsma DI, de Geus E, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Biobank PM, Hansen T, Hardy R, Hivert MF, Holm JC, Jaddoe VWV, Järvelin MR, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfield S, Pennell CE, Perry JRB, Raitakari O, Rivadeneira F, Saw SM, Sebert S, Shepherd JA, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hypponen E, Power C, McCarthy MI, Freathy RM, Widén E, Hakonarson H, Prokopenko I, Voight BF, Zemel BS, Grant SFA, Cousminer DL. Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes. Genome Biol 2024; 25:22. [PMID: 38229171 PMCID: PMC10790528 DOI: 10.1186/s13059-023-03136-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 11/30/2023] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. RESULTS Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. CONCLUSION We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern.
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Affiliation(s)
- Jonathan P Bradfield
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Rachel L Kember
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Anna Ulrich
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Zhanna Balkhiyarova
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Neil M Davies
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Ruby Fore
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Amitavo Ganguli
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, Valencia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Jaakko Leinonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Leo-Pekka Lyytikainen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Theresia M Schnurr
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Christian Theil Have
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK
| | - Elisabeth Thiering
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute, Newcastle, NSW, 2305, Australia
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Louise Aas Holm
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - Alessandra Chesi
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Catherine Choong
- Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA, Australia
| | - Miguel Cruz
- Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Paul Elliott
- MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Steve Franks
- Institute of Reproductive & Developmental Biology, Imperial College London, London, UK
| | - Christine Frithioff-Bøjsøe
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - W James Gauderman
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Joseph T Glessner
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Vicente Gilsanz
- Center for Endocrinology, Diabetes & Metabolism, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | | | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Marika Kaakinen
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Institute of Reproductive & Developmental Biology, Imperial College London, London, UK
| | - Heidi Kalkwarf
- Department of Pediatrics, Cincinnati Children's Hospital, University of Cincinnati, Cincinnati, OH, USA
| | - Andrea Kelly
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Joseph Kindler
- College of Family and Consumer Sciences, University of Georgia, Athens, GA, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
| | - Carla Lanca
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Joan Lappe
- Department of Medicine and College of Nursing, Creighton University School of Medicine, Omaha, NB, USA
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc, University of San Carlos, Cebu, Philippines
| | - Shana McCormack
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Frank D Mentch
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jonathan A Mitchell
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, 33014, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
| | - Harri Niinikoski
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Physiology, University of Turku, Turku, Finland
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
- Department of Nutrition, Harvard T.H Chan School of Public Health, Boston, MA, 02115, USA
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Paavo Nurmi Centre, Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Toos van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mònica Guxens
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Johan G Eriksson
- Institute of Clinical Medicine Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Department of Obstetrics & Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Frank D Gilliland
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | | | - Torben Hansen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Rebecca Hardy
- Cohort and Longitudinal Studies Enhancement Resources (CLOSER), UCL Institute of Education, London, UK
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Jens-Christian Holm
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
- The Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- Unit of Primary Health Care, Oulu University Hospital, OYS, Kajaanintie 50, 90220, Oulu, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, 33014, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
| | - David A Mackey
- Lions Eye Institute, Centre for Ophthalmology and Visual Science, Centre for Eye Research Australia, University of Western Australia, Perth, WA, Australia
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, Nancy, France
- Department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, Nancy, France
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Juha Mykkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Sharon Oberfield
- Division of Pediatric Endocrinology, Columbia University Medical Center, New York, NY, USA
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute, Newcastle, NSW, 2305, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, NSW, 2305, Australia
| | - John R B Perry
- Metabolic Research Laboratory, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - John A Shepherd
- Department of Epidemiology and Population Science, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
| | - Thorkild I A Sørensen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Maties Torrent
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Fundació Institut d'Investigació Sanitària Illes Balears - IdISBa, Palma, Spain
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Elina Hypponen
- UCL Great Ormond Street Institute of Child Health, London, UK
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Chris Power
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Current Address: Genentech, 1 DNA Way, San Francisco, CA, 94080, USA
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, EX2 5DW, UK
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Inga Prokopenko
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
- UMR 8199 - EGID, Institut Pasteur de Lille, CNRS, University of Lille, 59000, Lille, France
| | - Benjamin F Voight
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Babette S Zemel
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
| | - Diana L Cousminer
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Currently Employed By GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA, 19426, USA.
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4
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Allen NE, Lacey B, Lawlor DA, Pell JP, Gallacher J, Smeeth L, Elliott P, Matthews PM, Lyons RA, Whetton AD, Lucassen A, Hurles ME, Chapman M, Roddam AW, Fitzpatrick NK, Hansell AL, Hardy R, Marioni RE, O'Donnell VB, Williams J, Lindgren CM, Effingham M, Sellors J, Danesh J, Collins R. Prospective study design and data analysis in UK Biobank. Sci Transl Med 2024; 16:eadf4428. [PMID: 38198570 DOI: 10.1126/scitranslmed.adf4428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/13/2023] [Indexed: 01/12/2024]
Abstract
Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.
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Affiliation(s)
- Naomi E Allen
- UK Biobank Ltd, Stockport, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ben Lacey
- UK Biobank Ltd, Stockport, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Deborah A Lawlor
- Population Health Science, Bristol Medical School University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Jill P Pell
- School of Health and Wellbeing, University of Glasgow, Scotland
| | - John Gallacher
- Department of Psychiatry, University of Oxford, Oxford, UK
- Dementias Platform UK, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Liam Smeeth
- London School of Hygiene and Tropical Medicine, London, UK
| | - Paul Elliott
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- NIHR Health Protection Research Unit in Chemical Radiation Threats and Hazards, Imperial College London, UK
| | - Paul M Matthews
- UK Dementia Research Centre Institute and Department of Brain Sciences, Imperial College London, London, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Swansea, Wales
| | - Anthony D Whetton
- Veterinary Health Innovation Engine, University of Surrey, Guildford, UK
| | - Anneke Lucassen
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Faculty of Medicine, Southampton University, Southampton, UK
| | - Matthew E Hurles
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | | | | | - Anna L Hansell
- Centre for Environmental Health and Sustainability, University of Leicester, Leicester, UK
| | - Rebecca Hardy
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, Scotland
| | | | - Julie Williams
- UK Dementia Research Institute, Cardiff University, Cardiff, Wales
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | | | | | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Rory Collins
- UK Biobank Ltd, Stockport, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
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5
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Bridger Staatz C, Kelly Y, Lacey RE, Hardy R. Investigating the factorial structure and measurement invariance of the parent-reported strengths and difficulties questionnaire at 11 years of age from the UK Millennium Cohort Study. Eur Child Adolesc Psychiatry 2024; 33:255-266. [PMID: 36773126 PMCID: PMC10806008 DOI: 10.1007/s00787-023-02156-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/26/2023] [Indexed: 02/12/2023]
Abstract
The strengths and difficulties questionnaire (SDQ) consist of five sub-scales that have been used to measure internalising and externalising symptoms in children, typically by combining sum scores of two sub-scales each, and pro-social behaviours. However, the different possible factorial structures that represent these symptoms have not been formally tested in a nationally representative sample of UK children. In addition, it is necessary to assess whether the SDQ is interpreted similarly across subgroups of the population. Exploratory and confirmatory factor analysis were used to test three competing structures for the parent-reported SDQ collected at age 11, the start of adolescence, in the UK Millennium Cohort Study (n = 11,519), and measurement invariance was assessed according to sex and a measure of deprivation of the area in which households lived. Internal consistency using ordinal alpha, internal convergent validity and external discriminant validity using average variance explained (AVE), and predictive validity were assessed. A five-factor model and a model with two second-order factors for internalising and externalising symptoms had better model fit than a three-factor model. For both structures, invariance was demonstrated across sex and area-level deprivation. AVE scores for the five-factor model indicated that peer and emotional problems factors were measuring a similar construct, as were the hyperactivity and conduct factors. In the second-order model, AVE scores indicated internalising and externalising symptoms were distinct constructs. A second-order model with two factors for internalising and externalising symptoms is appropriate for use in a cohort of UK children born in 2001/02, and our finding of invariance across sex and area-level deprivation indicate that the SDQ can be used in analysis investigating differences in symptoms across subgroups of the population.
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Affiliation(s)
- Charis Bridger Staatz
- Social Research Institute, Institute of Education, University College London, London, UK.
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.
| | - Yvonne Kelly
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, UK
| | - Rebecca E Lacey
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, UK
| | - Rebecca Hardy
- Social Research Institute, Institute of Education, University College London, London, UK
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
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6
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Lessof C, Cooper R, Wong A, Bendayan R, Caleyachetty R, Cheshire H, Cosco T, Elhakeem A, Hansell AL, Kaushal A, Kuh D, Martin D, Minelli C, Muthuri S, Popham M, Shaheen SO, Sturgis P, Hardy R. Comparison of devices used to measure blood pressure, grip strength and lung function: A randomised cross-over study. PLoS One 2023; 18:e0289052. [PMID: 38150442 PMCID: PMC10752545 DOI: 10.1371/journal.pone.0289052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 07/11/2023] [Indexed: 12/29/2023] Open
Abstract
BACKGROUND Blood pressure, grip strength and lung function are frequently assessed in longitudinal population studies, but the measurement devices used differ between studies and within studies over time. We aimed to compare measurements ascertained from different commonly used devices. METHODS We used a randomised cross-over study. Participants were 118 men and women aged 45-74 years whose blood pressure, grip strength and lung function were assessed using two sphygmomanometers (Omron 705-CP and Omron HEM-907), four handheld dynamometers (Jamar Hydraulic, Jamar Plus+ Digital, Nottingham Electronic and Smedley) and two spirometers (Micro Medical Plus turbine and ndd Easy on-PC ultrasonic flow-sensor) with multiple measurements taken on each device. Mean differences between pairs of devices were estimated along with limits of agreement from Bland-Altman plots. Sensitivity analyses were carried out using alternative exclusion criteria and summary measures, and using multilevel models to estimate mean differences. RESULTS The mean difference between sphygmomanometers was 3.9mmHg for systolic blood pressure (95% Confidence Interval (CI):2.5,5.2) and 1.4mmHg for diastolic blood pressure (95% CI:0.3,2.4), with the Omron HEM-907 measuring higher. For maximum grip strength, the mean difference when either one of the electronic dynamometers was compared with either the hydraulic or spring-gauge device was 4-5kg, with the electronic devices measuring higher. The differences were small when comparing the two electronic devices (difference = 0.3kg, 95% CI:-0.9,1.4), and when comparing the hydraulic and spring-gauge devices (difference = 0.2kg, 95% CI:-0.8,1.3). In all cases limits of agreement were wide. The mean difference in FEV1 between spirometers was close to zero (95% CI:-0.03,0.03), limits of agreement were reasonably narrow, but a difference of 0.47l was observed for FVC (95% CI:0.53,0.42), with the ndd Easy on-PC measuring higher. CONCLUSION Our study highlights potentially important differences in measurement of key functions when different devices are used. These differences need to be considered when interpreting results from modelling intra-individual changes in function and when carrying out cross-study comparisons, and sensitivity analyses using correction factors may be helpful.
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Affiliation(s)
- Carli Lessof
- National Centre for Research Methods, University of Southampton, Southampton, United Kingdom
| | - Rachel Cooper
- Faculty of Medical Sciences, Translational and Clinical Research Institute, AGE Research Group, Newcastle University, Newcastle upon Tyne, United Kingdom
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Rebecca Bendayan
- Department of Biostatistics and Health Informatics of the Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- NIHR Biomedical Research Centre at South London and Maudsley, NHS Foundation Trust and King’s College London, London, United Kingdom
| | - Rishi Caleyachetty
- Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- Warwick Medical School, University of Warwick, Warwick, United Kingdom
| | | | - Theodore Cosco
- Department of Gerontology, Simon Fraser University, Vancouver, Canada and Oxford Institute of Population Ageing, University of Oxford, Oxford, United Kingdom
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
| | - Anna L. Hansell
- Centre for Environmental Health and Sustainability, University of Leicester, United Kingdom
| | - Aradhna Kaushal
- Research Department of Behavioural Science and Health, UCL, London, United Kingdom
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - David Martin
- National Centre for Research Methods, University of Southampton, Southampton, United Kingdom
| | - Cosetta Minelli
- National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Stella Muthuri
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Maria Popham
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Seif O. Shaheen
- Institute of Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Patrick Sturgis
- Department of Methodology, London School of Economics, United Kingdom
| | - Rebecca Hardy
- Social Research Institute, UCL, London, United Kingdom
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
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Allinson JP, Chaturvedi N, Wong A, Shah I, Wedzicha JA, Hardy R. Lower respiratory tract infections in early childhood - Authors' reply. Lancet 2023; 402:2195-2196. [PMID: 38070946 DOI: 10.1016/s0140-6736(23)01620-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/02/2023] [Indexed: 12/18/2023]
Affiliation(s)
- James Peter Allinson
- Department of Respiratory Medicine, Royal Brompton Hospital, London, UK; National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK.
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Imran Shah
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | | | - Rebecca Hardy
- School of Sport, Exercise, and Health Sciences, Loughborough University, Loughborough, UK; Social Research Institute, University College London, London, UK
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8
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Chung HF, Dobson AJ, Hayashi K, Hardy R, Kuh D, Anderson DJ, van der Schouw YT, Greenwood DC, Cade JE, Demakakos P, Brunner EJ, Eastwood SV, Sandin S, Weiderpass E, Mishra GD. Ethnic Differences in the Association Between Age at Natural Menopause and Risk of Type 2 Diabetes Among Postmenopausal Women: A Pooled Analysis of Individual Data From 13 Cohort Studies. Diabetes Care 2023; 46:2024-2034. [PMID: 37747341 PMCID: PMC10696407 DOI: 10.2337/dc23-1209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/19/2023] [Indexed: 09/26/2023]
Abstract
OBJECTIVE To investigate associations between age at natural menopause, particularly premature ovarian insufficiency (POI) (natural menopause before age 40 years), and incident type 2 diabetes (T2D) and identify any variations by ethnicity. RESEARCH DESIGN AND METHODS We pooled individual-level data of 338,059 women from 13 cohort studies without T2D before menopause from six ethnic groups: White (n = 177,674), Chinese (n = 146,008), Japanese (n = 9,061), South/Southeast Asian (n = 2,228), Black (n = 1,838), and mixed/other (n = 1,250). Hazard ratios (HRs) of T2D associated with age at menopause were estimated in the overall sample and by ethnicity, with study as a random effect. For each ethnic group, we further stratified the association by birth year, education level, and BMI. RESULTS Over 9 years of follow-up, 20,064 (5.9%) women developed T2D. Overall, POI (vs. menopause at age 50-51 years) was associated with an increased risk of T2D (HR 1.31; 95% CI 1.20-1.44), and there was an interaction between age at menopause and ethnicity (P < 0.0001). T2D risk associated with POI was higher in White (1.53; 1.36-1.73), Japanese (4.04; 1.97-8.27), and Chinese women born in 1950 or later (2.79; 2.11-3.70); although less precise, the risk estimates were consistent in women of South/Southeast Asian (1.46; 0.89-2.40), Black (1.72; 0.95-3.12), and mixed/other (2.16; 0.83-5.57) ethnic groups. A similar pattern, but with a smaller increased risk of T2D, was observed with early menopause overall (1.16; 1.10-1.23) and for White, Japanese, and Chinese women born in 1950 or later. CONCLUSIONS POI and early menopause are risk factors for T2D in postmenopausal women, with considerable variation across ethnic groups, and may need to be considered in risk assessments of T2D among women.
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Affiliation(s)
- Hsin-Fang Chung
- School of Public Health, University of Queensland, Brisbane, Queensland, Australia
| | - Annette J. Dobson
- School of Public Health, University of Queensland, Brisbane, Queensland, Australia
| | - Kunihiko Hayashi
- School of Health Sciences, Gunma University, Maebashi City, Gunma, Japan
| | - Rebecca Hardy
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, U.K
| | - Diana Kuh
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, U.K
| | - Debra J. Anderson
- Faculty of Health, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Darren C. Greenwood
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, U.K
| | - Janet E. Cade
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, U.K
| | - Panayotes Demakakos
- Department of Epidemiology and Public Health, University College London, London, U.K
| | - Eric J. Brunner
- Department of Epidemiology and Public Health, University College London, London, U.K
| | - Sophie V. Eastwood
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, U.K
| | - Sven Sandin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Gita D. Mishra
- School of Public Health, University of Queensland, Brisbane, Queensland, Australia
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9
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Goodwin MV, Hogervorst E, Hardy R, Stephan BCM, Maidment DW. How are hearing loss and physical activity related? Analysis from the English longitudinal study of ageing. Prev Med 2023; 173:107609. [PMID: 37423474 DOI: 10.1016/j.ypmed.2023.107609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 07/02/2023] [Accepted: 07/06/2023] [Indexed: 07/11/2023]
Abstract
Although cross-sectional studies suggest that hearing loss in middle- and older-aged adults is associated with lower physical activity, longitudinal evidence is limited. This study aimed to investigate the potential bi-directional association between hearing loss and physical activity over time. Participants were from the English Longitudinal Study of Ageing (N = 11,292) who were 50-years or older at baseline assessment (1998-2000). Individuals were followed-up biannually for up to 20-years (2018-2019) and were classified as ever reporting hearing loss (n = 4946) or not reporting hearing loss (n = 6346). Data were analysed with Cox-proportional hazard ratios and multilevel logistic regression. The results showed that baseline physical activity was not associated with hearing loss over the follow-up. Time (i.e., wave of assessment) by hearing loss interactions showed that physical activity declined more rapidly over time in those with hearing loss, compared to those without (Odds Ratios = 0.94, 95% Confidence Intervals; 0.92-0.96, p < .001). These findings highlight the importance of addressing physical activity in middle- and older-aged adults with hearing loss. As physical activity is a modifiable behaviour that can reduce the risk of developing chronic health conditions, individuals with hearing loss may need additional, tailored support to be more physically active. Mitigating the decline in physical activity could be essential to support healthy ageing for adults with hearing loss.
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Affiliation(s)
- Maria V Goodwin
- School of Sport, Exercise and Health Sciences, Loughborough University, UK.
| | - Eef Hogervorst
- School of Sport, Exercise and Health Sciences, Loughborough University, UK
| | - Rebecca Hardy
- School of Sport, Exercise and Health Sciences, Loughborough University, UK
| | | | - David W Maidment
- School of Sport, Exercise and Health Sciences, Loughborough University, UK
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10
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Villicaña S, Castillo-Fernandez J, Hannon E, Christiansen C, Tsai PC, Maddock J, Kuh D, Suderman M, Power C, Relton C, Ploubidis G, Wong A, Hardy R, Goodman A, Ong KK, Bell JT. Genetic impacts on DNA methylation help elucidate regulatory genomic processes. Genome Biol 2023; 24:176. [PMID: 37525248 PMCID: PMC10391992 DOI: 10.1186/s13059-023-03011-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). CONCLUSIONS Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .
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Affiliation(s)
- Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | | | | | - Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Christine Power
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - George Ploubidis
- Centre for Longitudinal Studies, Institute of Education, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca Hardy
- School of Sport, Exercise & Health Sciences, Loughborough University, Loughborough, UK
- UCL Social Research Institute, University College London, London, UK
| | - Alissa Goodman
- Centre for Longitudinal Studies, Institute of Education, University College London, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit and Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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11
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Liang C, Chung HF, Dobson AJ, Cade JE, Greenwood DC, Hayashi K, Hardy R, Kuh D, Schouw YTVD, Sandin S, Weiderpass E, Mishra GD. Is there a link between infertility, miscarriage, stillbirth, and premature or early menopause? Results from pooled analyses of 9 cohort studies. Am J Obstet Gynecol 2023; 229:47.e1-47.e9. [PMID: 37059411 DOI: 10.1016/j.ajog.2023.04.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/14/2023] [Accepted: 04/02/2023] [Indexed: 04/16/2023]
Abstract
BACKGROUND Some reproductive factors (such as age at menarche and parity) have been shown to be associated with age at natural menopause, but there has been little quantitative analysis of the association between infertility, miscarriage, stillbirth, and premature (<40 years) or early menopause (40-44 years). In addition, it has been unknown whether the association differs between Asian and non-Asian women, although the age at natural menopause is younger among Asian women. OBJECTIVE This study aimed to investigate the association of infertility, miscarriage, and stillbirth with age at natural menopause, and whether the association differed by race (Asian and non-Asian). STUDY DESIGN This was a pooled individual participant data analysis from 9 observational studies contributing to the InterLACE consortium. Naturally postmenopausal women with data on at least 1 of the reproductive factors (ie, infertility, miscarriage, and stillbirth), age at menopause, and confounders (ie, race, education level, age at menarche, body mass index, and smoking status) were included. A multinomial logistic regression model was used to estimate relative risk ratios and 95% confidence intervals for the association of infertility, miscarriage, and stillbirth with premature or early menopause, adjusting for confounders. Between-study difference and within-study correlation were taken into account by including study as a fixed effect and indicating study as a cluster variable. We also examined the association with number of miscarriages (0, 1, 2, ≥3) and stillbirths (0, 1, ≥2), and tested whether the strength of association differed between Asian and non-Asian women. RESULTS A total of 303,594 postmenopausal women were included. Their median age at natural menopause was 50.0 years (interquartile range, 47.0-52.0). The percentages of women with premature and early menopause were 2.1% and 8.4%, respectively. The relative risk ratios (95% confidence intervals) of premature and early menopause were 2.72 (1.77-4.17) and 1.42 (1.15-1.74) for women with infertility; 1.31 (1.08-1.59) and 1.37 (1.14-1.65) for women with recurrent miscarriages; and 1.54 (1.52-1.56) and 1.39 (1.35-1.43) for women with recurrent stillbirths. Asian women with infertility, recurrent miscarriages (≥3), or recurrent stillbirths (≥2) had higher risk of premature and early menopause compared with non-Asian women with the same reproductive history. CONCLUSION Histories of infertility and recurrent miscarriages and stillbirths were associated with higher risk of premature and early menopause, and the associations differed by race, with stronger associations for Asian women with such reproductive history.
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12
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Bakolis I, Murray ET, Hardy R, Hatch SL, Richards M. Area disadvantage and mental health over the life course: a 69-year prospective birth cohort study. Soc Psychiatry Psychiatr Epidemiol 2023; 58:735-744. [PMID: 36757437 PMCID: PMC10097760 DOI: 10.1007/s00127-023-02427-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 01/12/2023] [Indexed: 02/10/2023]
Abstract
PURPOSE Existing evidence on the mental health consequences of disadvantaged areas uses cross-sectional or longitudinal studies with short observation periods. The objective of this research was to investigate this association over a 69-year period. METHODS Data were obtained from the MRC National Survey of Health and Development (NSHD; the British 1946 birth cohort), which consisted of 2125 participants at 69 years. We assessed longitudinal associations between area disadvantage and mental health symptoms at adolescence and adulthood with use of multilevel modelling framework. RESULTS After adjustment for father's social class, for each one percentage increase in area disadvantage at age 4, there was a 0.02 (95% CI 0.001, 0.04) mean increase in the total score of the neuroticism scale at age 13-15. After adjustment for father's social class, adult socio-economic position, cognitive ability and educational attainment, a one percentage increase in change score of area disadvantage between age 4 and 26 was associated with a mean increase in the total Psychiatric Symptom Frequency score (MD 0.06; 95% CI 0.007, 0.11). Similar associations were observed with change scores between ages 4, 53, 60 and total General Health Questionnaire-28 score at age 53 (MD 0.05; 95% CI 0.01, 0.11) and 60-64 (MD 0.06; 95% CI 0.009, 0.11). CONCLUSIONS Cohort members who experienced increasing area disadvantage from childhood were at increased risk of poor mental health over the life course. Population-wide interventions aiming at improving social and physical aspects of the early neighbourhood environment could reduce the socio-economic burden of poor mental health.
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Affiliation(s)
- Ioannis Bakolis
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Centre for Implementation Science, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Emily T Murray
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rebecca Hardy
- Social Research Institute, University College London, London, UK
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Stephani L Hatch
- Department of Psychological Medicine, King's College London, IOPPN and South London and Maudsley NHS Foundation Trust, London, UK
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
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13
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Borra C, Hardy R. Differences in chronic pain prevalence between men and women at mid-life: a systematic review protocol. BMJ Open 2023; 13:e065497. [PMID: 37116997 PMCID: PMC10151927 DOI: 10.1136/bmjopen-2022-065497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/30/2023] Open
Abstract
INTRODUCTION Epidemiological literature shows differences in chronic pain (CP) prevalence in men and women. Women are more likely to develop CP at different points of the life course, such as adolescence and old age. Less is known about the prevalence of CP by sex and the difference in prevalence during mid-life, when changes may predispose to an earlier differentiation in CP distribution. The aim of this study is to describe the difference in prevalence of CP at mid-life (ages 40-60) in men and women in the general population. METHODS AND ANALYSIS This systematic review follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Appropriate studies will be identified in the following databases: MEDLINE, EMBASE, AMED and PsycINFO. Two reviewers will independently screen each title and abstract. Studies eligible for data extraction will report estimates of CP prevalence for each sex, and/or a measure of the difference in prevalence between sexes. The findings will be reported in a narrative synthesis following the Social Research Council Methods Programme guidelines. A random effects meta-analysis will be conducted where the reviewers can justify combining results. ETHICS AND DISSEMINATION This review will summarise the prevalence of CP in men and women at mid-life, based on existing evidence. It is expected that the results will identify gaps in knowledge and areas for further research. The review will be submitted for publication in topic specific journals and disseminated to professional networks. Individual patient data are not included, so ethical approval is not required. PROSPERO REGISTRATION NUMBER CRD42021295895.
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Affiliation(s)
- Catherine Borra
- Social Research Institute, University College London, London, UK
| | - Rebecca Hardy
- Social Research Institute, University College London, London, UK
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
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14
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Allinson JP, Chaturvedi N, Wong A, Shah I, Donaldson GC, Wedzicha JA, Hardy R. Early childhood lower respiratory tract infection and premature adult death from respiratory disease in Great Britain: a national birth cohort study. Lancet 2023; 401:1183-1193. [PMID: 36898396 DOI: 10.1016/s0140-6736(23)00131-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/13/2023] [Accepted: 01/17/2023] [Indexed: 03/09/2023]
Abstract
BACKGROUND Lower respiratory tract infections (LRTIs) in early childhood are known to influence lung development and lifelong lung health, but their link to premature adult death from respiratory disease is unclear. We aimed to estimate the association between early childhood LRTI and the risk and burden of premature adult mortality from respiratory disease. METHODS This longitudinal observational cohort study used data collected prospectively by the Medical Research Council National Survey of Health and Development in a nationally representative cohort recruited at birth in March, 1946, in England, Scotland, and Wales. We evaluated the association between LRTI during early childhood (age <2 years) and death from respiratory disease from age 26 through 73 years. Early childhood LRTI occurrence was reported by parents or guardians. Cause and date of death were obtained from the National Health Service Central Register. Hazard ratios (HRs) and population attributable risk associated with early childhood LRTI were estimated using competing risks Cox proportional hazards models, adjusted for childhood socioeconomic position, childhood home overcrowding, birthweight, sex, and smoking at age 20-25 years. We compared mortality within the cohort studied with national mortality patterns and estimated corresponding excess deaths occurring nationally during the study period. FINDINGS 5362 participants were enrolled in March, 1946, and 4032 (75%) continued participating in the study at age 20-25 years. 443 participants with incomplete data on early childhood (368 [9%] of 4032), smoking (57 [1%]), or mortality (18 [<1%]) were excluded. 3589 participants aged 26 years (1840 [51%] male and 1749 [49%] female) were included in the survival analyses from 1972 onwards. The maximum follow-up time was 47·9 years. Among 3589 participants, 913 (25%) who had an LRTI during early childhood were at greater risk of dying from respiratory disease by age 73 years than those with no LRTI during early childhood (HR 1·93, 95% CI 1·10-3·37; p=0·021), after adjustment for childhood socioeconomic position, childhood home overcrowding, birthweight, sex, and adult smoking. This finding corresponded to a population attributable risk of 20·4% (95% CI 3·8-29·8) and 179 188 (95% CI 33 806-261 519) excess deaths across England and Wales between 1972 and 2019. INTERPRETATION In this prospective, life-spanning, nationally representative cohort study, LRTI during early childhood was associated with almost a two times increased risk of premature adult death from respiratory disease, and accounted for one-fifth of these deaths. FUNDING National Institute for Health and Care Research Imperial Biomedical Research Centre, Royal Brompton and Harefield National Health Service (NHS) Foundation Trust, Royal Brompton and Harefield Hospitals Charity and Imperial College Healthcare NHS Trust, UK Medical Research Council.
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Affiliation(s)
- James Peter Allinson
- Royal Brompton Hospital, London, UK; National Heart and Lung Institute, Imperial College London, London, UK.
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Imran Shah
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | | | | | - Rebecca Hardy
- Social Research Institute, University College London, London, UK; School of Sport, Exercise, and Health Sciences, Loughborough University, Loughborough, UK
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Blodgett JM, Hardy R, Davis DHJ, Peeters G, Hamer M, Kuh D, Cooper R. Prognostic accuracy of the one-legged balance test in predicting falls: 15-years of midlife follow-up in a British birth cohort study. Front Sports Act Living 2023; 4:1066913. [PMID: 36699981 PMCID: PMC9869374 DOI: 10.3389/fspor.2022.1066913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 12/06/2022] [Indexed: 01/11/2023] Open
Abstract
Introduction The one-legged balance test is a common screening tool for fall risk. Yet, there is little empirical evidence assessing its prognostic ability. The study aims were to assess the prognostic accuracy of one-legged balance performance in predicting falls and identify optimal cut-points to classify those at greater risk. Methods Data from up to 2,000 participants from a British birth cohort born in 1,946 were used. The times an individual could stand on one leg with their eyes open and closed were recorded (max: 30 s) at ages 53 and 60-64. Number of falls in the past year was self-reported at ages 53, 60-64 and 68; recurrent falls (0-1 vs. 2+) and any fall (0 vs. 1+) were considered binary outcomes. Four longitudinal associations between balance times and subsequent falls were investigated (age 53 → 60-64; age 53 → 68; age 60-64 → 68; age 53 & 60-64 → 68). For each temporal association, areas under the curve (AUC) were calculated and compared for a base sex-only model, a sex and balance model, a sex and fall history model and a combined model of sex, balance and fall history. The Liu method was used to identify optimal cut-points and sensitivity, specificity, and AUC at corresponding cut-points. Results Median eyes open balance time was 30 s at ages 53 and 60-64; median eyes closed balance times were 5 s and 3 s, respectively. The predictive ability of balance tests in predicting either fall outcome was poor (AUC range for sex and balance models: 0.577-0.600). Prognostic accuracy consistently improved by adding fall history to the model (range: 0.604-0.634). Optimal cut-points ranged from 27 s to 29 s for eyes open and 3 s to 5 s for eyes closed; AUC consistently indicated that using "optimal" cut-points to dichotomise balance time provided no discriminatory ability (AUC range:0.42-0.47), poor sensitivity (0.38-0.61) and poor specificity (0.23-0.56). Discussion Despite previous observational evidence showing associations between better one-legged balance performance and reduced fall risk, the one-legged balance test had limited prognostic accuracy in predicting recurrent falls. This contradicts ongoing translation of this test into clinical screening tools for falls and highlights the need to consider new and existing screening tools that can reliably predict fall risk.
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Affiliation(s)
- Joanna M. Blodgett
- Institute of Sport, Exercise & Health, Division of Surgery & Interventional Science, University College London, London, UK
| | - Rebecca Hardy
- School of Sport, Exercise and Health Sciences,Loughborough University, Loughborough, UK
- Social Research Institute, University College London, London, UK
| | | | - Geeske Peeters
- Department of Geriatric Medicine, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Mark Hamer
- Institute of Sport, Exercise & Health, Division of Surgery & Interventional Science, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, UCL, London, UK
| | - Rachel Cooper
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University Institute of Sport, Manchester, UK
- AGE Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
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16
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Blodgett JM, Hardy R, Davis D, Peeters G, Kuh D, Cooper R. One-Legged Balance Performance and Fall Risk in Mid and Later Life: Longitudinal Evidence From a British Birth Cohort. Am J Prev Med 2022; 63:997-1006. [PMID: 35995713 PMCID: PMC10499759 DOI: 10.1016/j.amepre.2022.07.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION The one-legged balance test is widely used as a fall risk screening tool in both clinical and research settings. Despite rising fall prevalence in midlife, there is little evidence examining balance and fall risk in those aged <65 years. This study investigated the longitudinal associations between one-legged balance and the number of falls between ages 53 and 68 years. METHODS The study included 2,046 individuals from the Medical Research Council National Survey of Health & Development, a British birth cohort study. One-legged balance times (eyes open, maximum: 30 seconds) were assessed at ages 53 years (1999) and 60-64 years (2006-2010). Fall history within the last year (none, 1, ≥2) was self-reported at ages 60-64 years and 68 years (2014). Multinomial logistic regressions assessed the associations between balance and change in balance with subsequent falls. Models adjusted for anthropometric, socioeconomic, behavioral, health status, and cognitive indicators. Analysis occurred between 2019 and 2022. RESULTS Balance performance was not associated with single falls. Better balance performance at age 53 years was associated with decreased risk of recurrent falls at ages 60-64 years and 68 years, with similar associations between balance at age 60-64 years and recurrent falls at age 68 years. Those with consistently lower balance times (<15 seconds) were at greater risk (RRR=3.33, 95% CI=1.91, 5.80) of recurrent falls at age 68 years in adjusted models than those who could balance for 30 seconds at ages 53 years and 60-64 years. CONCLUSIONS Lower balance and consistently low or declining performance were associated with a greater subsequent risk of recurrent falls. Earlier identification and intervention of those with poor balance ability can help to minimize the risk of recurrent falls in aging adults.
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Affiliation(s)
- Joanna M Blodgett
- Division of Surgery & Interventional Science, Institute of Sport, Exercise & Health, University College London, London, United Kingdom; MRC Unit for Lifelong Health and Ageing at UCL, UCL Institute of Cardiovascular Science, London, United Kingdom.
| | - Rebecca Hardy
- Cohort and Longitudinal Studies Enhancement Resources, Social Research Institute, University College London, London, United Kingdom
| | - Daniel Davis
- MRC Unit for Lifelong Health and Ageing at UCL, UCL Institute of Cardiovascular Science, London, United Kingdom
| | - Geeske Peeters
- Department of Geriatric Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, UCL Institute of Cardiovascular Science, London, United Kingdom
| | - Rachel Cooper
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University Institute of Sport, Manchester, United Kingdom; AGE Research Group, NIHR Newcastle Biomedical Research Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom; NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
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17
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Peycheva D, Sullivan A, Hardy R, Bryson A, Conti G, Ploubidis G. Risk factors for natural menopause before the age of 45: evidence from two British population-based birth cohort studies. BMC Womens Health 2022; 22:438. [DOI: 10.1186/s12905-022-02021-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 10/22/2022] [Indexed: 11/09/2022] Open
Abstract
Abstract
Background
Menopause that occurs before the age of 45 and is not medically induced (referred to here as ‘early natural menopause’) affects around one in 10 women and has serious health consequences. These consequences include increased risk of all-cause mortality, cardiovascular disease, osteoporosis, and type 2 diabetes.
Methods
We investigate risk factors for the onset of natural menopause before the age of 45 in two population-based prospective cohort studies in Britain: the 1958 cohort following 8959 women and the 1970 cohort following 8655 women. These studies follow women from birth to adulthood, and we use harmonized data on birth and early life characteristics, reproductive health, health behaviour, and socioeconomic characteristics for 6805 women who were pre-menopausal, peri-menopausal or had undergone natural menopause. Of these 6805 women, 3614 participated in the 1958 cohort (of which 368 had early menopause) and 3191 participated in the 1970 cohort (of which 206 had early menopause). Taking a life course approach, we focus on three distinct life stages - birth/early life, childhood, and early adulthood - to understand when risk factors are most harmful. Respecting the temporal sequence of exposures, we use a series of multivariable logistic regression models to estimate associations between early menopause and each potential risk factor adjusted for confounders.
Results
We find that early menopause is influenced by circumstances at birth. Women born in lower social class families, whose mother smoked during the pregnancy or who were breastfed 1 month or less were more likely to undergo early menopause. Early menopause is also associated with poorer cognitive ability and smoking in childhood. Adult health behaviour also matters. Smoking is positively correlated with early menopause, while regular exercise and moderate frequency of alcohol drinking in women’s early thirties are associated with reduced risk of early menopause. The occurrence of gynaecological problems by women’s early thirties is also linked to early menopause.
Conclusions
We demonstrate that characteristics at different periods of life are associated with early menopause. Some of these associations relate to modifiable behaviours and thus the risks of early menopause and the adverse health outcomes associated with it may be preventable.
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18
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Mason SA, Al Saikhan L, Jones S, James SN, Murray-Smith H, Rapala A, Williams S, Sudre C, Wong B, Richards M, Fox NC, Hardy R, Schott JM, Chaturvedi N, Hughes AD. Association between carotid atherosclerosis and brain activation patterns during the Stroop task in older adults: An fNIRS investigation. Neuroimage 2022; 257:119302. [PMID: 35595200 PMCID: PMC10466022 DOI: 10.1016/j.neuroimage.2022.119302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 11/17/2022] Open
Abstract
There is an increasing body of evidence suggesting that vascular disease could contribute to cognitive decline and overt dementia. Of particular interest is atherosclerosis, as it is not only associated with dementia, but could be a potential mechanism through which cardiovascular disease directly impacts brain health. In this work, we evaluated the differences in functional near infrared spectroscopy (fNIRS)-based measures of brain activation, task performance, and the change in central hemodynamics (mean arterial pressure (MAP) and heart rate (HR)) during a Stroop color-word task in individuals with atherosclerosis, defined as bilateral carotid plaques (n = 33) and healthy age-matched controls (n = 33). In the healthy control group, the left prefrontal cortex (LPFC) was the only region showing evidence of activation when comparing the incongruous with the nominal Stroop test. A smaller extent of brain activation was observed in the Plaque group compared with the healthy controls (1) globally, as measured by oxygenated hemoglobin (p = 0.036) and (2) in the LPFC (p = 0.02) and left sensorimotor cortices (LMC)(p = 0.008) as measured by deoxygenated hemoglobin. There were no significant differences in HR, MAP, or task performance (both in terms of the time required to complete the task and number of errors made) between Plaque and control groups. These results suggest that carotid atherosclerosis is associated with altered functional brain activation patterns despite no evidence of impaired performance of the Stroop task or central hemodynamic changes.
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Affiliation(s)
- Sarah A Mason
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom.
| | - Lamia Al Saikhan
- Department of Cardiac Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, 2835 King Faisal Street, Damman, Kingdom of Saudi Arabia
| | - Siana Jones
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom; Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Centre for Medical Image Computing, Department of Computer Science, University College London, London UK
| | - Alicja Rapala
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Suzanne Williams
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Carole Sudre
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom; Centre for Medical Image Computing, Department of Computer Science, University College London, London UK; School of Biomedical Engineering, King's College, London UK
| | - Brian Wong
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom; Centre for Medical Image Computing, Department of Computer Science, University College London, London UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom.
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19
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Bann D, Wright L, Hardy R, Williams DM, Davies NM. Polygenic and socioeconomic risk for high body mass index: 69 years of follow-up across life. PLoS Genet 2022; 18:e1010233. [PMID: 35834443 PMCID: PMC9282556 DOI: 10.1371/journal.pgen.1010233] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 05/03/2022] [Indexed: 11/29/2022] Open
Abstract
Genetic influences on body mass index (BMI) appear to markedly differ across life, yet existing research is equivocal and limited by a paucity of life course data. We thus used a birth cohort study to investigate differences in association and explained variance in polygenic risk for high BMI across infancy to old age (2-69 years). A secondary aim was to investigate how the association between BMI and a key purported environmental determinant (childhood socioeconomic position) differed across life, and whether this operated independently and/or multiplicatively of genetic influences. Data were from up to 2677 participants in the MRC National Survey of Health and Development, with measured BMI at 12 timepoints from 2-69 years. We used multiple polygenic indices from GWAS of adult and childhood BMI, and investigated their associations with BMI at each age. For polygenic liability to higher adult BMI, the trajectories of effect size (β) and explained variance (R2) diverged: explained variance peaked in early adulthood and plateaued thereafter, while absolute effect sizes increased throughout adulthood. For polygenic liability to higher childhood BMI, explained variance was largest in adolescence and early adulthood; effect sizes were marginally smaller in absolute terms from adolescence to adulthood. All polygenic indices were related to higher variation in BMI; quantile regression analyses showed that effect sizes were sizably larger at the upper end of the BMI distribution. Socioeconomic and polygenic risk for higher BMI across life appear to operate additively; we found little evidence of interaction. Our findings highlight the likely independent influences of polygenic and socioeconomic factors on BMI across life. Despite sizable associations, the BMI variance explained by each plateaued or declined across adulthood while BMI variance itself increased. This is suggestive of the increasing importance of chance ('non-shared') environmental influences on BMI across life.
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Affiliation(s)
- David Bann
- Centre for Longitudinal Studies, Social Research Institute, UCL, London, United Kingdom
- * E-mail: (DB); (LW)
| | - Liam Wright
- Centre for Longitudinal Studies, Social Research Institute, UCL, London, United Kingdom
- * E-mail: (DB); (LW)
| | - Rebecca Hardy
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
- Social Research Institute, UCL, London, United Kingdom
| | - Dylan M. Williams
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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20
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Liang C, Chung HF, Dobson AJ, Hayashi K, van der Schouw YT, Kuh D, Hardy R, Derby CA, El Khoudary SR, Janssen I, Sandin S, Weiderpass E, Mishra GD. Infertility, recurrent pregnancy loss, and risk of stroke: pooled analysis of individual patient data of 618 851 women. BMJ 2022; 377:e070603. [PMID: 35732311 PMCID: PMC9214882 DOI: 10.1136/bmj-2022-070603] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/04/2022] [Indexed: 11/05/2022]
Abstract
OBJECTIVE To examine the associations of infertility, recurrent miscarriage, and stillbirth with the risk of first non-fatal and fatal stroke, further stratified by stroke subtypes. DESIGN Individual participant pooled analysis of eight prospective cohort studies. SETTING Cohort studies across seven countries (Australia, China, Japan, Netherlands, Sweden, the United Kingdom, and the United States) participating in the InterLACE (International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events) consortium, which was established in June 2012. PARTICIPANTS 618 851 women aged 32.0-73.0 years at baseline with data on infertility, miscarriage, or stillbirth, at least one outcome event (non-fatal or fatal stroke), and information on covariates were included; 93 119 women were excluded. Of the participants, 275 863 had data on non-fatal and fatal stroke, 54 716 only had data on non-fatal stroke, and 288 272 only had data on fatal stroke. MAIN OUTCOME AND MEASURES Non-fatal strokes were identified through self-reported questionnaires, linked hospital data, or national patient registers. Fatal strokes were identified through death registry data. RESULTS The median follow-up for non-fatal stroke and fatal stroke was 13.0 years (interquartile range 12.0-14.0) and 9.4 years (7.6-13.0), respectively. A first non-fatal stroke was experienced by 9265 (2.8%) women and 4003 (0.7%) experienced a fatal stroke. Hazard ratios for non-fatal or fatal stroke were stratified by hypertension and adjusted for race or ethnicity, body mass index, smoking status, education level, and study. Infertility was associated with an increased risk of non-fatal stroke (hazard ratio 1.14, 95% confidence interval 1.08 to 1.20). Recurrent miscarriage (at least three) was associated with higher risk of non-fatal and fatal stroke (1.35, 1.27 to 1.44, and 1.82, 1.58 to 2.10, respectively). Women with stillbirth were at 31% higher risk of non-fatal stroke (1.31, 1.10 to 1.57) and women with recurrent stillbirth were at 26% higher risk of fatal stroke (1.26, 1.15 to 1.39). The increased risk of stroke (non-fatal or fatal) associated with infertility or recurrent stillbirths was mainly driven by a single stroke subtype (non-fatal ischaemic stroke and fatal haemorrhagic stroke), while the increased risk of stroke (non-fatal or fatal) associated with recurrent miscarriages was driven by both subtypes. CONCLUSION A history of recurrent miscarriages and death or loss of a baby before or during birth could be considered a female specific risk factor for stroke, with differences in risk according to stroke subtypes. These findings could contribute to improved monitoring and stroke prevention for women with such a history.
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Affiliation(s)
- Chen Liang
- University of Queensland, School of Public Health, Queensland, Australia
| | - Hsin-Fang Chung
- University of Queensland, School of Public Health, Queensland, Australia
| | - Annette J Dobson
- University of Queensland, School of Public Health, Queensland, Australia
| | | | - Yvonne T van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, Utrecht, Netherlands
| | - Diana Kuh
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, London, UK
| | | | - Carol A Derby
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Samar R El Khoudary
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, PA, USA
| | - Imke Janssen
- Department of Preventive Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Sven Sandin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Gita D Mishra
- University of Queensland, School of Public Health, Queensland, Australia
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21
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Anbar R, Sultan SR, Al Saikhan L, Alkharaiji M, Chaturvedi N, Hardy R, Richards M, Hughes A. Is carotid artery atherosclerosis associated with poor cognitive function assessed using the Mini-Mental State Examination? A systematic review and meta-analysis. BMJ Open 2022; 12:e055131. [PMID: 35440451 PMCID: PMC9020283 DOI: 10.1136/bmjopen-2021-055131] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 03/29/2022] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVES To determine associations between carotid atherosclerosis assessed by ultrasound and the Mini-Mental State Examination (MMSE), a measure of global cognitive function. DESIGN Systematic review and meta-analysis. METHODS MEDLINE and EMBASE databases were searched up to 1 May 2020 to identify studies assessed the associations between asymptomatic carotid atherosclerosis and the MMSE. Studies reporting OR for associations between carotid plaque or intima-media thickness (cIMT) and dichotomised MMSE were meta-analysed. Publication bias of included studies was assessed. RESULTS A total of 31 of 378 reviewed articles met the inclusion criteria; together they included 27 738 participants (age 35-95 years). Fifteen studies reported some evidence of a positive association between measures of atherosclerosis and poorer cognitive performance in either cross-sectional or longitudinal studies. The remaining 16 studies found no evidence of an association. Seven cross-sectional studies provided data suitable for meta-analysis. Meta-analysis of three studies that assessed carotid plaque (n=3549) showed an association between the presence of plaque and impaired MMSE with pooled estimate for the OR (95% CI) being 2.72 (0.85 to 4.59). An association between cIMT and impaired MMSE was reported in six studies (n=4443) with a pooled estimate for the OR (95% CI) being 1.13 (1.04 to 1.22). Heterogeneity across studies was moderate to small (carotid plaque with MMSE, I2=40.9%; cIMT with MMSE, I2=4.9%). There was evidence of publication bias for carotid plaque studies (p=0.02), but not cIMT studies (p=0.2). CONCLUSIONS There is some, limited cross-sectional evidence indicating an association between cIMT and poorer global cognitive function assessed with MMSE. Estimates of the association between plaques and poor cognition are too imprecise to draw firm conclusions and evidence from studies of longitudinal associations between carotid atherosclerosis and MMSE is limited. PROSPERO REGISTRATION NUMBER CRD42021240077.
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Affiliation(s)
- Rayan Anbar
- Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Makkah, Saudi Arabia
- MRC Unit for Lifelong Health and Aging, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Salahaden R Sultan
- Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Makkah, Saudi Arabia
| | - Lamia Al Saikhan
- College of Applied Medial Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Mohammed Alkharaiji
- Department of Public Health, Saudi Electronic University, Riyadh, Saudi Arabia
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Aging, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca Hardy
- Social Research Institute, UCL Institute of Education, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Aging, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Alun Hughes
- MRC Unit for Lifelong Health and Aging, UCL Institute of Cardiovascular Science, University College London, London, UK
- Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
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22
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Blodgett JM, Cooper R, Davis DHJ, Kuh D, Hardy R. Associations of Word Memory, Verbal Fluency, Processing Speed, and Crystallized Cognitive Ability With One-Legged Balance Performance in Mid- and Later Life. J Gerontol A Biol Sci Med Sci 2022; 77:807-816. [PMID: 34125203 PMCID: PMC8974350 DOI: 10.1093/gerona/glab168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Cognitive integration of sensory input and motor output plays an important role in balance. Despite this, it is not clear if specific cognitive processes are associated with balance and how these associations change with age. We examined longitudinal associations of word memory, verbal fluency, search speed, and reading ability with repeated measures of one-legged balance performance. METHOD Up to 2 934 participants in the MRC National Survey of Health and Development, a British birth cohort study, were included. At age 53, word memory, verbal fluency, search speed, and reading ability were assessed. One-legged balance times (eyes closed) were measured at ages 53, 60-64, and 69 years. Associations between each cognitive measure and balance time were assessed using random-effects models. Adjustments were made for sex, death, attrition, height, body mass index, health conditions, health behaviors, education, and occupational class. RESULTS In sex-adjusted models, 1 SD higher scores in word memory, search speed, and verbal fluency were associated with 14.1% (95% CI: 11.3, 16.8), 7.2% (4.4, 9.9), and 10.3% (7.5, 13.0) better balance times at age 53, respectively. Higher reading scores were associated with better balance, although this association plateaued. Associations were partially attenuated in mutually adjusted models and effect sizes were smaller at ages 60-64 and 69. In fully adjusted models, associations were largely explained by education, although remained for word memory and search speed. CONCLUSIONS Higher cognitive performance across all measures was independently associated with better balance performance in midlife. Identification of individual cognitive mechanisms involved in balance could lead to opportunities for targeted interventions in midlife.
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Affiliation(s)
| | - Rachel Cooper
- Musculoskeletal Science and Sports Medicine Research Centre, Department of Sport and Exercise Sciences, Manchester Metropolitan University, UK
| | | | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
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23
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Webber M, Falconer D, AlFarih M, Joy G, Chan F, Davie C, Hamill Howes L, Wong A, Rapala A, Bhuva A, Davies RH, Morton C, Aguado-Sierra J, Vazquez M, Tao X, Krausz G, Tanackovic S, Guger C, Xue H, Kellman P, Pierce I, Schott J, Hardy R, Chaturvedi N, Rudy Y, Moon JC, Lambiase PD, Orini M, Hughes AD, Captur G. Study protocol: MyoFit46-the cardiac sub-study of the MRC National Survey of Health and Development. BMC Cardiovasc Disord 2022; 22:140. [PMID: 35365075 PMCID: PMC8972905 DOI: 10.1186/s12872-022-02582-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 03/23/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world's longest running continued surveillance birth cohort providing a unique opportunity to understand life course determinants of myocardial dysfunction as part of MyoFit46-the cardiac sub-study of the NSHD. METHODS We aim to recruit 550 NSHD participants of approximately 75 years+ to undertake high-density surface electrocardiographic imaging (ECGI) and stress perfusion cardiovascular magnetic resonance (CMR). Through comprehensive myocardial tissue characterization and 4-dimensional flow we hope to better understand the burden of clinical and subclinical cardiovascular disease. Supercomputers will be used to combine the multi-scale ECGI and CMR datasets per participant. Rarely available, prospectively collected whole-of-life data on exposures, traditional risk factors and multimorbidity will be studied to identify risk trajectories, critical change periods, mediators and cumulative impacts on the myocardium. DISCUSSION By combining well curated, prospectively acquired longitudinal data of the NSHD with novel CMR-ECGI data and sharing these results and associated pipelines with the CMR community, MyoFit46 seeks to transform our understanding of how early, mid and later-life risk factor trajectories interact to determine the state of cardiovascular health in older age. TRIAL REGISTRATION Prospectively registered on ClinicalTrials.gov with trial ID: 19/LO/1774 Multimorbidity Life-Course Approach to Myocardial Health- A Cardiac Sub-Study of the MCRC National Survey of Health and Development (NSHD).
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Affiliation(s)
- Matthew Webber
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Debbie Falconer
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK
| | - Mashael AlFarih
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - George Joy
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Fiona Chan
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Clare Davie
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Lee Hamill Howes
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Alicja Rapala
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Anish Bhuva
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Institute of Health Informatics, UCL, Euston Road, London, UK
| | - Rhodri H Davies
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | | | - Jazmin Aguado-Sierra
- ELEM Biotech, S.L, Bristol, BS1 6QH, UK
- Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
| | - Mariano Vazquez
- ELEM Biotech, S.L, Bristol, BS1 6QH, UK
- Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
| | - Xuyuan Tao
- École Nationale Supérieure Des Arts Et Industries Textiles, 2 allée Louise et Victor Champier, 59056, Roubaix Cedex 1, France
| | - Gunther Krausz
- g.Tec Medical Engineering GmbH, Siernigtrabe 14, 4521, Schiedlberg, Austria
| | | | - Christoph Guger
- g.Tec Medical Engineering GmbH, Siernigtrabe 14, 4521, Schiedlberg, Austria
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Iain Pierce
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Jonathan Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | | | - Nishi Chaturvedi
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Yoram Rudy
- Cardiac Bioelectricity and Arrhythmia Center, Washington University, St. Louis, MO, 63130, USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO, 63130, USA
| | - James C Moon
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Pier D Lambiase
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Alun D Hughes
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Gabriella Captur
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK.
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK.
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK.
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Blodgett JM, Ventre JP, Mills R, Hardy R, Cooper R. A systematic review of one-legged balance performance and falls risk in community-dwelling adults. Ageing Res Rev 2022; 73:101501. [PMID: 34748974 DOI: 10.1016/j.arr.2021.101501] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/20/2021] [Accepted: 10/20/2021] [Indexed: 01/11/2023]
Abstract
OBJECTIVE The aim of this systematic review was to synthesise all published evidence on associations between one-legged balance performance and falls. METHODS Medline, EMBASE, CINAHL and Web of Science were systematically searched (to January 2021) to identify peer-reviewed, English language journal articles examining the association between one-legged balance performance and falls in community-dwelling adults. RESULTS Of 4310 records screened, 55 papers were included (n = 36954 participants). There was considerable heterogeneity between studies including differences in study characteristics, ascertainment of balance and falls, and analytical approaches. A meta-analysis of the time that individuals could maintain the one-legged balance position indicated that fallers had worse balance times than non-fallers (standardised mean difference: -0.29 (95%CI:-0.38,-0.20) in cross-sectional analyses; -0.19 (-0.28, -0.09) in longitudinal analyses), although there was no difference in the pooled median difference. Due to between-study heterogeneity, regression estimates between balance and fall outcomes could not be synthesised. Where assessed, prognostic accuracy indicators suggested that one-legged balance was a poor discriminator of fall risk; for example, 5 of 7 studies demonstrated poor prognostic accuracy (Area Under the Curve <0.6), with most studies demonstrating poor sensitivity. CONCLUSIONS This systematic review identified 55 papers that examined associations between balance and fall risk, the majority in older aged adults. However, the evidence was commonly of low quality and results were inconsistent. This contradicts previous perceptions of one-legged balance as a useful fall risk tool and highlights crucial gaps that must be addressed in order to translate such assessments to clinical settings.
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Affiliation(s)
- Joanna M Blodgett
- Institute of Sport, Exercise & Health, Division of Surgery & Interventional Science, University College London, 170 Tottenham Court Road, W1T 7HA, London, UK.
| | - Jodi P Ventre
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University, Oxford Road, M15 6BH, Manchester, UK; Department of Psychology, Health, Psychology and Communities Research Centre, Manchester Metropolitan University, Bonsall Street, M15 6GX, Manchester, UK
| | - Richard Mills
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University, Oxford Road, M15 6BH, Manchester, UK
| | - Rebecca Hardy
- CLOSER, Social Research Institute, University College London, 55-59 Gordon Square, WC1H 0NU, London, UK
| | - Rachel Cooper
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University, Oxford Road, M15 6BH, Manchester, UK
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25
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Bryson A, Conti G, Hardy R, Peycheva D, Sullivan A. The consequences of early menopause and menopause symptoms for labour market participation. Soc Sci Med 2021; 293:114676. [PMID: 34953416 DOI: 10.1016/j.socscimed.2021.114676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 12/06/2021] [Accepted: 12/20/2021] [Indexed: 10/19/2022]
Abstract
Using a difference-in-difference estimator we identify the causal impact of early menopause and menopause symptoms on the time women spend in employment through to their mid-50s. We find the onset of early natural menopause (before age 45) reduces months spent in employment by 9 percentage points once women enter their 50s compared with women who do not experience early menopause. Early menopause is not associated with a difference in full-time employment rates. The number of menopause symptoms women face at age 50 is associated with lower employment rates: each additional symptom lowers employment rates and full-time employment rates by around half a percentage point. But not all symptoms have the same effects. Vasomotor symptoms tend not to be associated with lower employment rates, whereas the employment of women who suffer psychological problems due to menopause is adversely affected. Every additional psychological problem associated with menopause reduces employment and full-time employment rates by 1-2 percentage points, rising to 2-4 percentage points when those symptoms are reported as particularly bothersome.
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Affiliation(s)
| | - Gabriella Conti
- UCL Social Research Institute, UK; UCL's Department of Economics, UK
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26
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Cooper R, Lessof C, Wong A, Hardy R. The impact of variation in the device used to measure grip strength on the identification of low muscle strength: Findings from a randomised cross-over study. J Frailty Sarcopenia Falls 2021; 6:225-230. [PMID: 34950813 PMCID: PMC8649858 DOI: 10.22540/jfsf-06-225] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/17/2021] [Indexed: 11/23/2022] Open
Abstract
Grip strength is commonly used to identify people with low muscle strength. It is unclear what impact the type of dynamometer used to measure grip strength has on the identification of low muscle strength so we aimed to assess this. Study participants were 118 men and women aged 45-74y from a randomised, repeated measurements cross-over study. Maximum grip strength was assessed using four hand-held dynamometers (Jamar Hydraulic; Jamar Plus+ Digital; Nottingham Electronic; Smedley) in a randomly allocated order. EWGSOP2 cut-points were applied to estimate prevalence of low muscle strength for each device. Agreement between devices was compared. Prevalence of low muscle strength varied by dynamometer ranging between 3% and 22% for men and, 3% and 15% for women. Of the 13 men identified as having low muscle strength by at least one of the four dynamometers, only 8% were identified by all four and 54% by just one. Of the 15 women classified as having low muscle strength by at least one of the four dynamometers, only 7% were identified by all four and 67% by only one. Variation in the measures of grip strength acquired by different hand-held dynamometers has potentially important implications when identifying low muscle strength.
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Affiliation(s)
- Rachel Cooper
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University, Manchester, UK
| | - Carli Lessof
- National Centre for Research Methods, University of Southampton, Southampton, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Rebecca Hardy
- Cohort and Longitudinal Studies Enhancement Resources (CLOSER), UCL Social Research Institute, London, UK
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27
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Bann D, Scholes S, Hardy R, O'Neill D. Changes in the body mass index and blood pressure association across time: Evidence from multiple cross-sectional and cohort studies. Prev Med 2021; 153:106825. [PMID: 34599929 PMCID: PMC8633761 DOI: 10.1016/j.ypmed.2021.106825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/15/2021] [Accepted: 09/26/2021] [Indexed: 11/26/2022]
Abstract
Although body mass index (BMI) is considered a key determinant of high blood pressure, its importance may differ over time and by age group. We utilised separate data sources to investigate temporal changes in this association: 23 independent (newly sampled), repeated cross-sectional studies (Health Survey for England (HSE)) at ≥25 years (1994-2018; N = 126,742); and three British birth cohorts at 43-46 years (born 1946, 1958, and 1970; N = 18,657). In HSE, associations were weaker in more recent years, with this trend most pronounced amongst older adults. After adjustment for sex, anti-hypertensive treatment and education, the mean difference in systolic blood pressure (SBP) per 1 kg/m2 increase in BMI amongst adults ≥55 years was 0.75 mmHg (95%CI: 0.60-0.90) in 1994, 0.66 mmHg (0.46-0.85) in 2003, and 0.53 mmHg (0.35-0.71) in 2018. In the 1958 and 1970 cohorts, BMI and SBP associations were of similar magnitude yet weaker in the 1946 cohort, potentially due to differences in blood pressure measurement device. Quantile regression analyses suggested that associations between BMI and SBP were present both below and above the hypertension threshold. A weaker association between BMI and blood pressure may partly offset the public health impacts of increasing obesity prevalence. However, despite sizable increases in use of antihypertensive medication, BMI remains positively associated with SBP in all ages. Our findings highlight the need to tackle non-medical factors such as population diet which influence both BMI and blood pressure, and the utility of using multiple datasets to obtain robust inferences on trends in risk factor-outcome associations across time.
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Affiliation(s)
- David Bann
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK.
| | - Shaun Scholes
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rebecca Hardy
- CLOSER, Social Research Institute, University College London, London, UK
| | - Dara O'Neill
- CLOSER, Social Research Institute, University College London, London, UK
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28
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Bridger Staatz C, Kelly Y, Lacey RE, Blodgett JM, George A, Arnot M, Walker E, Hardy R. Socioeconomic position and body composition in childhood in high- and middle-income countries: a systematic review and narrative synthesis. Int J Obes (Lond) 2021; 45:2316-2334. [PMID: 34315999 PMCID: PMC8528703 DOI: 10.1038/s41366-021-00899-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 05/24/2021] [Accepted: 06/30/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND The relation between socioeconomic position (SEP) and obesity measured by body mass index (BMI), a measure of weight for height, has been extensively reviewed in children, showing consistent associations between disadvantaged SEP and higher BMI in high-income countries (HICs) and lower BMI in middle-income countries (MICs). Fat mass (FM), a more accurate measure of adiposity, and fat-free mass (FFM) are not captured by BMI, but have been shown to track from childhood to adulthood, and be important for cardiovascular health and functional outcomes in later life. It is not clear whether body composition is associated with SEP. We systematically reviewed the association between SEP and body composition in childhood. METHODS A systematic review was carried out following PRISMA guidelines. The protocol was pre-registered with PROSPERO (CRD42019119937). Original studies in the English language, which examined the association between SEP and body composition in childhood, were included. An electronic search of three databases was conducted. Two independent reviewers carried out screening, data extraction and quality assessment. Due to heterogeneity in results, a narrative synthesis was conducted. Heterogeneity in findings according to SEP, sex, body composition measure and country income level was investigated. RESULTS 50 papers were included, the majority from HICs. No papers were from low-income countries. Disadvantage in childhood was associated with greater FM and lower FFM in HICs, but with lower FM and lower FFM in MICs. When measures of FFM indexed to height were used there was no evidence of associations with SEP. In HICs, more studies reported associations between disadvantaged SEP and higher FM among girls comparative to boys. CONCLUSIONS Inequalities in FM are evident in HICs and, in the opposite direction, in MICs and follow similar trends to inequalities for BMI. Inequalities in height are likely important in understanding inequalities in FFM.
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Affiliation(s)
- Charis Bridger Staatz
- Social Research Institute, Institute of Education, University College London, London, UK.
| | - Yvonne Kelly
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rebecca E Lacey
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Joanna M Blodgett
- Institute of Sport Exercise and Health, Division of Surgery and Interventional Science, Faculty of Medical Sciences, University College London, London, UK
| | - Anitha George
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Megan Arnot
- Department of Anthropology, University College London, London, UK
| | - Emma Walker
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rebecca Hardy
- Social Research Institute, Institute of Education, University College London, London, UK
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29
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Topriceanu C, Moon JC, Hardy R, Hughes AD, Captur G. Childhood bradycardia associates with atrioventricular conduction defects in older age: a longitudinal birth cohort study. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
A high resting heart rate (RHR) has been associated with cardiovascular morbidity and mortality. However, little is known about the long-term effects of childhood bradycardia.
Purpose
This study aimed to explore the association between childhood bradycardia and later-life cardiac phenotype using longitudinal data from the 1946 Medical Research Council National Survey of Health and Development (NSHD) birth cohort.
Methods
RHR was recorded at ages 6 and 7 to provide the bradycardia exposure defined as a childhood RHR<75. Three outcomes were studied: i) echocardiographic data at 60–64 consisting of ejection fraction (EF), left ventricular mass index (LVmassi), myocardial contraction fraction index (MCFi) and E/e'; ii) electrocardiographic (ECG) evidence of atrio-ventricular (AV) conduction defects (Minnesota categories: 6-1, 6-2-1, 6-2-2, 6-2-3, 6-3, 6-8, 8-5-1, 8-5-2, 8-6-1, 8-6-2, 8-6-3 and 8-6-4) or ventricular conduction defects (any Minnesota group 7) by age 60–64; and iii) all-cause and cardiovascular mortality. Generalized linear models (glm) with gamma distribution were used for echocardiographic analyses, glms with binomial distribution for ECG analyses and Cox proportional hazards models for mortality. Adjustment was made for relevant demographic and health-related covariates, and for multiple testing. In order to account for within-subject correlated repeated measures at 6 and 7 years of age, mixed glms (glmms) were used as a sensitivity analysis. To explore any nonlinear relationships, we modeled each outcome as a sum of best fitting fractional polynomials of RHR at 6 and 7 (as continuous variables) and covariates using a “closed test procedure” with backward elimination.
Results
The number of participants included was: 4381 for mortality, 1631 for ECG and 1617 for echocardiography analyses. Childhood bradycardia was associated with male sex (p<0.0001) and higher BMI (p=0.009). In fully adjusted models, childhood bradycardia was associated with 2.91 higher odds of AV conduction defects (95% confidence interval [CI] 1.59–5.31, p=0.0005), even at a false discovery rate of 0.05. Associations persisted in random coefficients glmm models (odds ratio 2.50, 95% CI 1.01–4.31). The fractional polynomials analyses revealed that the log odds of AV conduction defects at 60–64 years of age were linearly associated with RHR at 7 years. There was no association between bradycardia in childhood and ventricular conduction defects, echocardiographic parameters or mortality outcomes.
Conclusions
Longitudinal data indicate that childhood bradycardia trebles the odds of having AV conduction defects, but does not influence mortality or heart size and function in older age. As one in three older adults with AV conduction defects will have been bradycardic in childhood, future research should concentrate on identifying children at risk, the potential mechanisms involved and whether AV blocking drugs accelerate nodal dysfunction.
Funding Acknowledgement
Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): British Heart Foundation (MyoFit46 Special Programme Grant SP/20/2/34841)
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Affiliation(s)
- C Topriceanu
- University College London, UCL MRC Unit of Lifelong Health and Ageing, London, United Kingdom
| | - J C Moon
- University College London, UCL Institute of Cardiovascular Science, London, United Kingdom
| | - R Hardy
- University College London, CLOSER, UCL Institute of Education, London, United Kingdom
| | - A D Hughes
- University College London, UCL MRC Unit of Lifelong Health and Ageing, London, United Kingdom
| | - G Captur
- University College London, UCL MRC Unit of Lifelong Health and Ageing, London, United Kingdom
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30
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Akasaki M, Nicholas O, Abell J, Valencia-Hernández CA, Hardy R, Steptoe A. Adverse childhood experiences and incident coronary heart disease: a counterfactual analysis in the Whitehall II prospective cohort study. Am J Prev Cardiol 2021; 7:100220. [PMID: 34611646 PMCID: PMC8387301 DOI: 10.1016/j.ajpc.2021.100220] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 06/14/2021] [Accepted: 06/19/2021] [Indexed: 11/17/2022] Open
Abstract
Objectives Adverse childhood experience is thought to be associated with risk of coronary heart disease, but it is not clear which experiences are cardiotoxic, and whether risk increases with the accumulation of adverse childhood experiences. Methods Participants were 5149 adults (72.6% men) in the Whitehall II cohort study. Parental death was recorded at phase 1 (median age in years 44.3), and 13 other adverse childhood experiences at phase 5 (55.3). We applied Cox proportional hazards regression with person-time from phase 5 to examine associations of adverse childhood experiences with incident coronary heart disease. We predicted hazard ratios according to count of the experiences, and examined dose-response effect. We finally estimated reduction of coronary heart disease in a hypothetical scenario, the absence of adverse childhood experiences. Results Among study participants, 62.9% had at least one adversity, with "financial problems" having the highest prevalence (26.1%). There were 509 first episodes of coronary heart disease during an average 12.9 years follow-up. Among 14 adverse childhood experiences in a multiply adjusted model, "parental unemployment" showed the highest hazard of coronary heart disease incidence (hazard ratio; 95% confidence interval: 1.53; 1.16 to 2.02). No dose-response effect was observed (constant for proportionality in hazard ratio: 1.05, 0.99 to 1.11). Based on the estimates of final model, in the absence of childhood adversities, we estimated a 6.0% reduction in coronary heart disease (0.94; 0.87 to 1.01), but the confidence interval includes one. Conclusion Although individual adverse childhood experiences show some association with coronary heart disease, there is no clear relationship with the number of adverse experiences. Further research is required to quantify effects of multiple and combinations of adverse childhood experiences considering timing, duration, and severity.
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Affiliation(s)
- Mifuyu Akasaki
- Social Research Institute, Institute of Education, University College London, London, UK.,Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Owen Nicholas
- Department of Statistical Science, Faculty of Mathematical and Physical Sciences, University College London, London, UK
| | - Jessica Abell
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Carlos A Valencia-Hernández
- Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Rebecca Hardy
- Social Research Institute, Institute of Education, University College London, London, UK
| | - Andrew Steptoe
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
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31
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Topriceanu CC, Moon JC, Hardy R, Hughes AD, Captur G. Childhood Bradycardia Associates With Atrioventricular Conduction Defects in Older Age: A Longitudinal Birth Cohort Study. J Am Heart Assoc 2021; 10:e021877. [PMID: 34569262 PMCID: PMC8649134 DOI: 10.1161/jaha.121.021877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background This study explored the association between childhood bradycardia and later‐life cardiac phenotype using longitudinal data from the 1946 National Survey of Health and Development (NSHD) birth cohort. Methods and Results Resting heart rate was recorded at 6 and 7 years of age to provide the bradycardia exposure defined as a childhood resting heart rate <75 bpm. Three outcomes were studied: (1) echocardiographic data at 60 to 64 years of age, consisting of ejection fraction, left ventricular mass index, myocardial contraction fraction index, and E/e′; (2) electrocardiographic evidence of atrioventricular or ventricular conduction defects by 60 to 64 years of age; and (3) all‐cause and cardiovascular mortality. Generalized linear models or Cox regression models were used, and adjustment was made for relevant demographic and health‐related covariates, and for multiple testing. Mixed generalized linear models and fractional polynomials were used as sensitivity analyses. One in 3 older adults with atrioventricular conduction defects had been bradycardic in childhood, with defects being serious (Mobitz type II second‐degree atrioventricular block or higher) in 12%. In fully adjusted models, childhood bradycardia was associated with 2.91 higher odds of atrioventricular conduction defects (95% CI, 1.59–5.31; P=0.0005). Associations persisted in random coefficients mixed generalized linear models (odds ratio, 2.50; 95% CI, 1.01–4.31). Fractional polynomials confirmed a linear association between the log odds of atrioventricular conduction defects at 60 to 64 years of age and resting heart rate at 7 years of age. There was no association between bradycardia in childhood and mortality outcomes or with echocardiographic parameters and ventricular conduction defects in older age. Conclusions Longitudinal birth cohort data indicate that childhood bradycardia trebles the odds of having atrioventricular conduction defects in older age, 88% of which are benign. In addition, it does not influence mortality or heart size and function. Future research should concentrate on identifying children at risk.
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Affiliation(s)
- Constantin-Cristian Topriceanu
- University College London (UCL) Medical Research Council (MRC) Unit for Lifelong Health and AgeingUniversity College London London United Kingdom
| | - James C Moon
- UCL Institute of Cardiovascular Science University College London London United Kingdom.,Cardiac MRI Unit Barts Heart Centre London United Kingdom
| | - Rebecca Hardy
- CLOSER Social Research Institute London United Kingdom
| | - Alun D Hughes
- University College London (UCL) Medical Research Council (MRC) Unit for Lifelong Health and AgeingUniversity College London London United Kingdom.,UCL Institute of Cardiovascular Science University College London London United Kingdom
| | - Gabriella Captur
- University College London (UCL) Medical Research Council (MRC) Unit for Lifelong Health and AgeingUniversity College London London United Kingdom.,UCL Institute of Cardiovascular Science University College London London United Kingdom.,Cardiology Department Centre for Inherited Heart Muscle Conditions Royal Free Hospital London United Kingdom
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32
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Whitton AE, Hardy R, Cope K, Gieng C, Gow L, MacKinnon A, Gale N, O'Moore K, Anderson J, Proudfoot J, Cockayne N, O'Dea B, Christensen H, Newby JM. Mental Health Screening in General Practices as a Means for Enhancing Uptake of Digital Mental Health Interventions: Observational Cohort Study. J Med Internet Res 2021; 23:e28369. [PMID: 34528896 PMCID: PMC8485187 DOI: 10.2196/28369] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 07/07/2021] [Accepted: 07/27/2021] [Indexed: 01/30/2023] Open
Abstract
Background Digital mental health interventions stand to play a critical role in managing the mental health impact of the COVID-19 pandemic. Thus, enhancing their uptake is a key priority. General practitioners (GPs) are well positioned to facilitate access to digital interventions, but tools that assist GPs in identifying suitable patients are lacking. Objective This study aims to evaluate the suitability of a web-based mental health screening and treatment recommendation tool (StepCare) for improving the identification of anxiety and depression in general practice and, subsequently, uptake of digital mental health interventions. Methods StepCare screens patients for symptoms of depression (9-item Patient Health Questionnaire) and anxiety (7-item Generalized Anxiety Disorder scale) in the GP waiting room. It provides GPs with stepped treatment recommendations that include digital mental health interventions for patients with mild to moderate symptoms. Patients (N=5138) from 85 general practices across Australia were invited to participate in screening. Results Screening identified depressive or anxious symptoms in 43.09% (1428/3314) of patients (one-quarter were previously unidentified or untreated). The majority (300/335, 89.6%) of previously unidentified or untreated patients had mild to moderate symptoms and were candidates for digital mental health interventions. Although less than half were prescribed a digital intervention by their GP, when a digital intervention was prescribed, more than two-thirds of patients reported using it. Conclusions Implementing web-based mental health screening in general practices can provide important opportunities for GPs to improve the identification of symptoms of mental illness and increase patient access to digital mental health interventions. Although GPs prescribed digital interventions less frequently than in-person psychotherapy or medication, the promising rates of uptake by GP-referred patients suggest that GPs can play a critical role in championing digital interventions and maximizing the associated benefits.
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Affiliation(s)
- Alexis E Whitton
- Black Dog Institute, Randwick, Australia.,University of New South Wales, Randwick, Australia
| | | | - Kate Cope
- Black Dog Institute, Randwick, Australia
| | | | - Leanne Gow
- Black Dog Institute, Randwick, Australia
| | | | - Nyree Gale
- Black Dog Institute, Randwick, Australia
| | | | - Josephine Anderson
- Black Dog Institute, Randwick, Australia.,University of New South Wales, Randwick, Australia
| | - Judith Proudfoot
- Black Dog Institute, Randwick, Australia.,University of New South Wales, Randwick, Australia
| | | | - Bridianne O'Dea
- Black Dog Institute, Randwick, Australia.,University of New South Wales, Randwick, Australia
| | - Helen Christensen
- Black Dog Institute, Randwick, Australia.,University of New South Wales, Randwick, Australia
| | - Jill Maree Newby
- Black Dog Institute, Randwick, Australia.,University of New South Wales, Randwick, Australia
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Akasaki M, Hardy R, Steptoe A. 1348Childhood adversities and diurnal patterns of salivary cortisol in adulthood: two UK-based prospective cohort studies. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Dysregulation of diurnal cortisol patterns may mediate between chronic stress and health problems. Findings on the association of childhood adversities with adult cortisol, however, are equivocal, mainly due to low statistical power, sample selection, and unstandardised indices of cortisol.
Methods
Participants were from Whitehall II study (n = 3434), and National Child Development Study (NCDS) (n = 2072). In Whitehall II, multilevel models were used to examine associations of retrospectively measured childhood adversities with two indices of diurnal cortisol patterns (awakening response and diurnal slope) at a median age of 65. In NCDS, regression was used to investigate associations of prospectively measured adversities with two measures of morning cortisol at the age of 44/45. We then regressed predicted values of cortisol from these models against count of adversities to examine dose-response effects.
Results
The prevalence of reporting at least one adversity was 67.8% in Whitehall II, and 47.8% in NCDS. None of the individual adversities were associated with overall cortisol levels in either study. However, for each additional adversity, there was a 1% elevated awakening response (95%CI: 0.8% to 1.19%), and, among men only, a 1.2% lower cortisol level at awakening (-1.98 to -0.40) with flatter diurnal slope (0.1 to 0.1) in Whitehall II; and a 1.3% lower cortisol level (-1.78 to -0.70) at 3.75 hrs after awakening in NCDS.
Conclusions
Experience of multiple childhood adversities may be associated with dysregulated salivary cortisol patterns later in life.
Key messages
Accumulation of childhood adversities might be associated with dysregulated diurnal cortisol patterns in adulthood.
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Norris T, Mansukoski L, Gilthorpe MS, Hamer M, Hardy R, Howe LD, Li L, Ong KK, Ploubidis GB, Viner RM, Johnson W. Early childhood weight gain: Latent patterns and body composition outcomes. Paediatr Perinat Epidemiol 2021; 35:557-568. [PMID: 33960515 DOI: 10.1111/ppe.12754] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 11/26/2020] [Accepted: 01/03/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Despite early childhood weight gain being a key indicator of obesity risk, we do not have a good understanding of the different patterns that exist. OBJECTIVES To identify and characterise distinct groups of children displaying similar early-life weight trajectories. METHODS A growth mixture model captured heterogeneity in weight trajectories between 0 and 60 months in 1390 children in the Avon Longitudinal Study of Parents and Children. Differences between the classes in characteristics and body size/composition at 9 years were investigated. RESULTS The best model had five classes. The "Normal" (45%) and "Normal after initial catch-down" (24%) classes were close to the 50th centile of a growth standard between 24 and 60 months. The "High-decreasing" (21%) and "Stable-high" (7%) classes peaked at the ~91st centile at 12-18 months, but while the former declined to the ~75th centile and comprised constitutionally big children, the latter did not. The "Rapidly increasing" (3%) class gained weight from below the 50th centile at 4 months to above the 91st centile at 60 months. By 9 years, their mean body mass index (BMI) placed them at the 98th centile. This class was characterised by the highest maternal BMI; highest parity; highest levels of gestational hypertension and diabetes; and the lowest socio-economic position. At 9 years, the "Rapidly increasing" class was estimated to have 68.2% (95% confidence interval [CI] 48.3, 88.1) more fat mass than the "Normal" class, but only 14.0% (95% CI 9.1, 18.9) more lean mass. CONCLUSIONS Criteria used in growth monitoring practice are unlikely to consistently distinguish between the different patterns of weight gain reported here.
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Affiliation(s)
- Tom Norris
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Liina Mansukoski
- Centre for Global Child Health, The Hospital for Sick Children, Toronto, ON, Canada
| | - Mark S Gilthorpe
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.,Faculty of Medicine and Health, University of Leeds, Leeds, UK.,Alan Turing Institute, British Library, London, UK
| | - Mark Hamer
- Division of Surgery and Interventional Sciences, Faculty Medical Sciences, University College London, London, UK
| | - Rebecca Hardy
- CLOSER, Department of Social Science, University College London, London, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit at the University of Bristol, Population Health Sciences, University of Bristol, Bristol, UK
| | - Leah Li
- Population, Policy and Practice Programme, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit and Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - George B Ploubidis
- Centre for Longitudinal Studies, Department of Social Science, University College London, London, UK
| | - Russell M Viner
- Population, Policy and Practice Programme, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - William Johnson
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
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Maddock J, Castillo-Fernandez J, Wong A, Ploubidis GB, Kuh D, Bell JT, Hardy R. Childhood growth and development and DNA methylation age in mid-life. Clin Epigenetics 2021; 13:155. [PMID: 34372922 PMCID: PMC8351141 DOI: 10.1186/s13148-021-01138-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 07/20/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND In the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life. METHODS Participants were from the Medical Research Council National Survey of Health and Development (n = 1376). Four DNAm age acceleration (AgeAccel) biomarkers were measured when participants were aged 53 years: AgeAccelHannum; AgeAccelHorvath; AgeAccelLevine; and AgeAccelGrim. Exposure variables included: relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores); and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2 years, weight gain only), early childhood (2-4 years), middle childhood (4-7 years) and late childhood to adolescence (7-15 years); age at menarche; and pubertal stage for men at 14-15 years. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study (NCDS). RESULTS A 1SD increase in relative weight gain in late childhood to adolescence was associated with 0.50 years (95% CI 0.20, 0.79) higher AgeAccelGrim. Although the CI includes the null, the estimate was similar in NCDS [0.57 years (95% CI - 0.01, 1.16)] There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥ 12 years had 1.20 years (95% CI 0.15, 2.24) higher AgeAccelGrim on average than women who reached menarche < 12 years; however, this was not replicated in NCDS and was not statistically significant after Bonferroni correction. CONCLUSIONS Our findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, we found rapid weight gain during pubertal development, previously related to higher cardiovascular disease risk, to be associated with older AgeAccelGrim. Given this is an exploratory study, this finding requires replication.
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Affiliation(s)
- Jane Maddock
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
| | | | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - George B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Rebecca Hardy
- CLOSER, UCL Institute of Education, University College London, London, WC1H 0NU, UK
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36
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Winpenny EM, Howe LD, van Sluijs EMF, Hardy R, Tilling K. Early adulthood socioeconomic trajectories contribute to inequalities in adult cardiovascular health, independently of childhood and adulthood socioeconomic position. J Epidemiol Community Health 2021; 75:1172-1180. [PMID: 34362821 PMCID: PMC8588297 DOI: 10.1136/jech-2021-216611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 05/27/2021] [Indexed: 11/03/2022]
Abstract
BACKGROUND Cardiovascular health shows significant socioeconomic inequalities, however there is little understanding of the role of early adulthood in generation of these inequalities. We assessed the contribution of socioeconomic trajectories during early adulthood (16-24 years) to cardiovascular health in mid-adulthood (46 years). METHODS Participants from the 1970 British Cohort Study with socioeconomic data available in early adulthood were included (n=12 423). Longitudinal latent class analysis identified socioeconomic trajectories, based on patterns of economic activity throughout early adulthood. Cardiometabolic risk factors (46 years) were regressed on socioeconomic trajectory class (16-24 years), testing mediation by adult socioeconomic position (46 years). Models were stratified by sex and adjusted for childhood socioeconomic position (SEP) and adolescent health. RESULTS Six early adulthood socioeconomic trajectories were identified: (1) Continued Education (20.2%), (2) Managerial Employment (16.0%), (3) Skilled Non-manual Employment (20.9%), (4) Skilled Manual Employment (18.9%), (5) Partly Skilled Employment (15.8%) and (6) Economically Inactive (8.1%). The 'Continued Education' trajectory class showed the best cardiovascular health at age 46 years, with the lowest levels of cardiometabolic risk factors. For example, systolic blood pressure was 128.9 mm Hg (95% CI 127.8 to 130.0) among men in the 'Continued Education' class, compared with 131.3 mm Hg (95% CI 130.4 to 132.2) among men in the 'Skilled Manual' class. Patterns across classes 2-6 differed by risk factor and sex. The observed associations were largely not mediated by SEP at age 46 years. CONCLUSION Findings suggest an independent contribution of early adulthood socioeconomic trajectories to development of later life cardiovascular inequalities. Further work is needed to understand mediators of this relationship and potential for interventions to mitigate these pathways.
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Affiliation(s)
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | | | | | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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37
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Staatz CB, Kelly Y, Lacey RE, Hardy R. Area-level and family-level socioeconomic position and body composition trajectories: longitudinal analysis of the UK Millennium Cohort Study. Lancet Public Health 2021; 6:e598-e607. [PMID: 34332672 PMCID: PMC8342403 DOI: 10.1016/s2468-2667(21)00134-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/28/2021] [Accepted: 06/02/2021] [Indexed: 01/22/2023]
Abstract
BACKGROUND Inequalities in the trajectories of body composition in childhood and adolescence have been infrequently studied. Despite the importance of environmental factors in obesity development, little research has looked at area-level socioeconomic position, independent of family socioeconomic position. We aimed to assess how inequalities in body composition develop with age. METHODS The Millennium Cohort Study is a longitudinal study of 19 243 families who had a child born between 2000 and 2002 in the UK. Multilevel growth curve models were applied to examine change in fat mass index (FMI), fat free mass index (FFMI; using the Benn index), and fat mass to fat free mass ratio (FM:FFM), measured using Bioelectrical Impedance Analysis, from ages 7 years to 17 years by the Index of Multiple Deprivation (IMD) and household income at baseline. FINDINGS Inequalities in FMI and FM:FFM ratio are evident at age 7 years and widen with age. At age 17 years, adolescents in the most disadvantaged IMD group had FMI 0·57 kg/mB (B=Benn parameter; 95% CI 0·43 to 0·70) higher and FM:FFM ratio 0·037 (95% CI 0·026 to 0·047) higher compared with the most advantaged group. Disadvantaged socioeconomic position is associated with higher FFMI but is reversed in adolescence after adjustment for FMI. Inequalities were greater in girls at age 7 years (mean FMI 0·22 kg/mB; 95% CI 0·13 to 0·32) compared with boys of the same age (0·05 kg/mB; -0·04 to 0·15, p=0·3), but widen fastest in boys, especially for FMI, in which there was over an 11 times increase in the inequality from age 7 years of 0·05kg/mB (95% CI -0·04 to 0·15) to 0·62 kg/mB at 17 years (0·42 to 0·82). Inequalities for the IMD were similar to income, and persisted at age 17 years independent of family socioeconomic position. INTERPRETATION Childhood and adolescence is an important period to address inequalities in body composition, as they emerge and widen. Policies should consider FFM as well as FM, and inequalities in the environment. FUNDING Medical Research Council, Economic and Social Research Council.
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Affiliation(s)
- Charis Bridger Staatz
- Social Research Institute, Institute of Education, University College London, London, UK.
| | - Yvonne Kelly
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rebecca E Lacey
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rebecca Hardy
- Social Research Institute, Institute of Education, University College London, London, UK
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38
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Caleyachetty R, Barber TM, Mohammed NI, Cappuccio FP, Hardy R, Mathur R, Banerjee A, Gill P. Ethnicity-specific BMI cutoffs for obesity based on type 2 diabetes risk in England: a population-based cohort study. Lancet Diabetes Endocrinol 2021; 9:419-426. [PMID: 33989535 PMCID: PMC8208895 DOI: 10.1016/s2213-8587(21)00088-7] [Citation(s) in RCA: 126] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/23/2021] [Accepted: 03/24/2021] [Indexed: 01/05/2023]
Abstract
BACKGROUND National and global recommendations for BMI cutoffs to trigger action to prevent obesity-related complications like type 2 diabetes among non-White populations are questionable. We aimed to prospectively identify ethnicity-specific BMI cutoffs for obesity based on the risk of type 2 diabetes that are risk-equivalent to the BMI cutoff for obesity among White populations (≥30 kg/m2). METHODS In this population-based cohort study, we used electronic health records across primary care (Clinical Practice Research Datalink) linked to secondary care records (Hospital Episodes Statistics) from a network of general practitioner practices in England. Eligible participants were aged 18 years or older, without any past or current diagnosis of type 2 diabetes, had a BMI of 15·0-50·0 kg/m2 and complete ethnicity data, were registered with a general practitioner practice in England at any point between Sept 1, 1990, and Dec 1, 2018, and had at least 1 year of follow-up data. Patients with type 2 diabetes were identified by use of a CALIBER phenotyping algorithm. Self-reported ethnicity was collapsed into five main categories. Age-adjusted and sex-adjusted negative binomial regression models, with fractional polynomials for BMI, were fitted with incident type 2 diabetes and ethnicity data. FINDINGS 1 472 819 people were included in our study, of whom 1 333 816 (90·6%) were White, 75 956 (5·2%) were south Asian, 49 349 (3·4%) were Black, 10 934 (0·7%) were Chinese, and 2764 (0·2%) were Arab. After a median follow-up of 6·5 years (IQR 3·2-11·2), 97 823 (6·6%) of 1 472 819 individuals were diagnosed with type 2 diabetes. For the equivalent age-adjusted and sex-adjusted incidence of type 2 diabetes at a BMI of 30·0 kg/m2 in White populations, the BMI cutoffs were 23·9 kg/m2 (95% CI 23·6-24·0) in south Asian populations, 28·1 kg/m2 (28·0-28·4) in Black populations, 26·9 kg/m2 (26·7-27·2) in Chinese populations, and 26·6 kg/m2 (26·5-27·0) in Arab populations. INTERPRETATION Revisions of ethnicity-specific BMI cutoffs are needed to ensure that minority ethnic populations are provided with appropriate clinical surveillance to optimise the prevention, early diagnosis, and timely management of type 2 diabetes. FUNDING National Institute for Health Research.
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Affiliation(s)
- Rishi Caleyachetty
- Nuffield Department of Population Health, University of Oxford, Oxford, UK; Warwick Medical School, University of Warwick, Coventry, UK.
| | - Thomas M Barber
- Warwick Medical School, University of Warwick, Coventry, UK; Warwickshire Institute for the Study of Diabetes, Endocrinology and Metabolism, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK
| | | | | | - Rebecca Hardy
- Social Research Institute, University College London, London, UK
| | - Rohini Mathur
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
| | - Paramjit Gill
- Warwick Medical School, University of Warwick, Coventry, UK
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Lane CA, Barnes J, Nicholas JM, Baker JW, Sudre CH, Cash DM, Parker TD, Malone IB, Lu K, James SN, Keshavan A, Buchanan S, Keuss S, Murray-Smith H, Wong A, Gordon E, Coath W, Modat M, Thomas D, Hardy R, Richards M, Fox NC, Schott JM. Investigating the relationship between BMI across adulthood and late life brain pathologies. Alzheimers Res Ther 2021; 13:91. [PMID: 33941254 PMCID: PMC8091727 DOI: 10.1186/s13195-021-00830-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 04/12/2021] [Indexed: 01/01/2023]
Abstract
Background In view of reported associations between high adiposity, particularly in midlife and late-life dementia risk, we aimed to determine associations between body mass index (BMI), and BMI changes across adulthood and brain structure and pathology at age 69–71 years. Methods Four hundred sixty-five dementia-free participants from Insight 46, a sub-study of the British 1946 birth cohort, who had cross-sectional T1/FLAIR volumetric MRI, and florbetapir amyloid-PET imaging at age 69–71 years, were included in analyses. We quantified white matter hyperintensity volume (WMHV) using T1 and FLAIR 3D-MRI; β-amyloid (Aβ) positivity/negativity using a SUVR approach; and whole brain (WBV) and hippocampal volumes (HV) using 3D T1-MRI. We investigated the influence of BMI, and BMI changes at and between 36, 43, 53, 60–64, 69 and 71 years, on late-life WMHV, Aβ-status, WBV and mean HV. Analyses were repeated using overweight and obese status. Results At no time-point was BMI, change in BMI or overweight/obese status associated with WMHV or WBV at age 69–71 years. Decreasing BMI in the 1–2 years before imaging was associated with an increased odds of being β-amyloid positive (OR 1.45, 95% confidence interval 1.09, 1.92). There were associations between being overweight and larger mean HV at ages 60–64 (β = 0.073 ml, 95% CI 0.009, 0.137), 69 (β = 0.076 ml, 95% CI 0.012, 0.140) and 71 years (β = 0.101 ml, 95% CI 0.037, 0.165). A similar, albeit weaker, trend was seen with obese status. Conclusions Using WMHV, β-amyloid status and brain volumes as indicators of brain health, we do not find evidence to explain reported associations between midlife obesity and late-life dementia risk. Declining BMI in later life may reflect preclinical Alzheimer’s disease. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00830-7.
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Affiliation(s)
- Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,Hoffmann-La Roche UK Ltd, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK
| | - John W Baker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Carole H Sudre
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | | | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Sarah Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Sarah Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Elizabeth Gordon
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David Thomas
- Leonard Wolfson Experimental Neurology Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | | | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at UCL, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK. .,UK Dementia Research Institute at UCL, University College London, London, UK.
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40
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George A, Hardy R, Castillo Fernandez J, Kelly Y, Maddock J. Life course socioeconomic position and DNA methylation age acceleration in mid-life. J Epidemiol Community Health 2021; 75:1084-1090. [PMID: 33906906 PMCID: PMC8515099 DOI: 10.1136/jech-2020-215608] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 03/01/2021] [Accepted: 04/18/2021] [Indexed: 12/17/2022]
Abstract
Background Ageing biomarkers can help us better understand how well-established socioeconomic position (SEP) disparities in ageing occur. A promising new set of DNAm methylation (DNAm)-based ageing biomarkers indicate through their age acceleration (AA) measures if biological ageing is slower or faster than chronological ageing. Few studies have investigated the association between SEP and DNAm AA. Methods We used linear regression to examine the sex-adjusted relationships between childhood social class, adult social class, intergenerational social class change, education and adult household earnings with first (Horvath AA and Hannum AA) and second generation (PhenoAge AA and GrimAge AA) DNAm AA markers using data from the MRC National Survey of Health and Development. Results In the first-generation biomarkers, there was little evidence of any associations with Horvath AA but associations of childhood social class and income with Hannum AA were observed. Strong associations were seen between greater disadvantage in childhood and adult SEP and greater AA in the second generation biomarkers. For example, those with fathers in an unskilled occupational social class in childhood had 3.6 years greater PhenoAge AA (95% CI 1.8 to 5.4) than those with fathers from a professional social class. Individuals without qualifications had higher AA compared with those with higher education (4.1 years greater GrimAge AA (95% CI 3.1 to 5.0)). Conclusion Our findings highlight the importance of exposure to social disadvantage in childhood to the biological ageing process. The second generation clocks appear to be more sensitive to the accumulation of social disadvantage across the life course.
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Affiliation(s)
- Anitha George
- Department of Epidemiology & Public Health, UCL, London, UK
| | | | | | - Yvonne Kelly
- Department of Epidemiology & Public Health, UCL, London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing, Faculty of Population Health, UCL, London, UK
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41
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Caleyachetty R, Stafford M, Cooper R, Anderson EL, Howe LD, Cosco TD, Kuh D, Hardy R. Exposure to multiple childhood social risk factors and adult body mass index trajectories from ages 20 to 64 years. Eur J Public Health 2021; 31:385-390. [PMID: 33462607 PMCID: PMC8599879 DOI: 10.1093/eurpub/ckaa237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND While childhood social risk factors appear to be associated with adult obesity, it is unclear whether exposure to multiple childhood social risk factors is associated with accelerated weight gain during adulthood. METHODS We used the Medical Research Council National Survey of Health and Development, a British population-based birth cohort study of participants born in 1946, height and weight were measured by nurses at ages 36, 43, 53 and 60-64 and self-reported at 20 and 26 years. The 9 childhood socioeconomic risk factors and 8 binary childhood psychosocial risk factors were measured, with 13 prospectively measured at age 4 years (or at 7 or 11 years if missing) and 3 were recalled when participants were age 43. Multilevel modelling was used to examine the association between the number of childhood social risk factors and changes in body mass index (BMI) with age. RESULTS Increasing exposure to a higher number of childhood socioeconomic risk factors was associated with higher mean BMI across adulthood for both sexes and with a faster increase in BMI from 20 to 64 years, among women but not men. Associations remained after adjustment for adult social class. There was no evidence of an association between exposure to childhood psychosocial risk factors and mean BMI in either sex at any age. CONCLUSIONS Strategies for the prevention and management of weight gain across adulthood may need to tailor interventions in consideration of past exposure to multiple socioeconomic disadvantages experienced during childhood.
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Affiliation(s)
- Rishi Caleyachetty
- Nuffield Department of Population Health (NDPH), University of Oxford, Oxford, UK
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- Correspondence: Rishi Caleyachetty, Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford OX3 7LF, UK. Tel: +44 (0)1865 743660, e-mail:
| | - Mai Stafford
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- The Health Foundation, London, UK
| | - Rachel Cooper
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- Department of Sport and Exercise Sciences, Manchester Metropolitan University, Manchester, UK
| | - Emma L Anderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Theodore D Cosco
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- Department of Gerontology, Simon Fraser University, Vancouver, BC, Canada
- Oxford Institute of Population Ageing, University of Oxford, Oxford, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- UCL Institute of Education, London, UK
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Norris T, Hamer M, Hardy R, Li L, Ong KK, Ploubidis GB, Viner R, Johnson W. Changes over time in latent patterns of childhood-to-adulthood BMI development in Great Britain: evidence from three cohorts born in 1946, 1958, and 1970. BMC Med 2021; 19:96. [PMID: 33879138 PMCID: PMC8059270 DOI: 10.1186/s12916-021-01969-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/22/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Most studies on secular trends in body mass index (BMI) are cross-sectional and the few longitudinal studies have typically only investigated changes over time in mean BMI trajectories. We aimed to describe how the evolution of the obesity epidemic in Great Britain reflects shifts in the proportion of the population demonstrating different latent patterns of childhood-to-adulthood BMI development. METHODS We used pooled serial BMI data from 25,655 participants in three British cohorts: the 1946 National Survey of Health and Development (NSHD), 1958 National Child Development Study (NCDS), and 1970 British Cohort Study (BCS). Sex-specific growth mixture models captured latent patterns of BMI development between 11 and 42 years. The classes were characterised in terms of their birth cohort composition. RESULTS The best models had four classes, broadly similar for both sexes. The 'lowest' class (57% of males; 47% of females) represents the normal weight sub-population, the 'middle' class (16%; 15%) represents the sub-population who likely develop overweight in early/mid-adulthood, and the 'highest' class (6%; 9%) represents those who likely develop obesity in early/mid-adulthood. The remaining class (21%; 29%) reflects a sub-population with rapidly 'increasing' BMI between 11 and 42 years. Both sexes in the 1958 NCDS had greater odds of being in the 'highest' class compared to their peers in the 1946 NSHD but did not have greater odds of being in the 'increasing' class. Conversely, males and females in the 1970 BCS had 2.78 (2.15, 3.60) and 1.87 (1.53, 2.28), respectively, times higher odds of being in the 'increasing' class. CONCLUSIONS Our results suggest that the obesity epidemic in Great Britain reflects not only an upward shift in BMI trajectories but also a more recent increase in the number of individuals demonstrating more rapid weight gain, from normal weight to overweight, across the second, third, and fourth decades of life.
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Affiliation(s)
- T Norris
- School of Sport Exercise and Health Sciences, Loughborough University, Loughborough, UK.
| | - M Hamer
- UCL Institute Sport Exercise Health , Division Surgery Interventional Science, London, UK
| | - R Hardy
- UCL Institute of Education, London, UK
| | - L Li
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - K K Ong
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - G B Ploubidis
- Centre for Longitudinal Studies, Department of Social Science, University College London, London, UK
| | - R Viner
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - W Johnson
- School of Sport Exercise and Health Sciences, Loughborough University, Loughborough, UK
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Pinto Pereira SM, De Stavola BL, Rogers NT, Hardy R, Cooper R, Power C. Adult obesity and mid-life physical functioning in two British birth cohorts: investigating the mediating role of physical inactivity. Int J Epidemiol 2021; 49:845-856. [PMID: 32142119 PMCID: PMC7394955 DOI: 10.1093/ije/dyaa014] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 01/17/2020] [Indexed: 12/31/2022] Open
Abstract
Background Associations between obesity and physical inactivity are bi-directional. Both are associated with physical functioning (PF, ability to perform physical tasks of daily living) but whether obesity influences PF via inactivity is unknown. We investigated whether mid-adult obesity trajectories were associated with subsequent PF and mediated by inactivity. Methods Body mass index (BMI; kg/m²) and inactivity were recorded at: 36, 43, 53 and 60–64 years in the 1946 Medical Research Council (MRC) National Survey of Health and Development (1946-NSHD; n = 2427), and at 33, 42 and 50 years in the 1958 National Child Development Study (1958-NCDS; n = 8674). Poor PF was defined as the lowest (gender and cohort-specific) 10% on the Short-form 36 Physical Component Summary subscale at 60–64 years (1946-NSHD) and 50 years (1958-NCDS). Estimated randomized-interventional-analogue natural direct (rNDE) and indirect (rNIE) effects of obesity trajectories on PF via inactivity are expressed as risk ratios [overall total effect (rTE) is rNDE multiplied by rNIE]. Results In both cohorts, most individuals (∼68%) were never obese in adulthood, 16–30% became obese and ≤11% were always obese. In 1946-NSHD, rTE of incident obesity at 43 years (vs never) on poor PF was 2.32 (1.13, 3.51); at 53 years it was 1.53 (0.91, 2.15). rNIEs via inactivity were 1.02 (0.97, 1.07) and 1.02 (0.99, 1.04), respectively. Estimated rTE of persistent obesity from 36 years was 2.91 (1.14, 4.69), with rNIE of 1.03 (0.96, 1.10). In 1958-NCDS, patterns of association were similar, albeit weaker. Conclusions Longer duration of obesity was associated with increased risk of poor PF. Inactivity played a small mediating role. Findings reinforce the importance of preventing and delaying obesity onset to protect against poor PF.
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Affiliation(s)
- Snehal M Pinto Pereira
- UCL Research Department of Epidemiology & Public Health, London WC1E 7HB, UK.,MRC Unit for Lifelong Health and Ageing at UCL, London WC1E 7HB, UK
| | - Bianca L De Stavola
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK
| | - Nina T Rogers
- UCL Research Department of Epidemiology & Public Health, London WC1E 7HB, UK.,MRC Unit for Lifelong Health and Ageing at UCL, London WC1E 7HB, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, London WC1E 7HB, UK.,CLOSER, Department of Social Science, UCL Institute of Education, London WC1H 0AL, UK
| | - Rachel Cooper
- Musculoskeletal Science and Sports Medicine Research Centre, Department of Sport and Exercise Sciences, Faculty of Science and Engineering, Manchester Metropolitan University, Manchester M15 6BH, UK
| | - Chris Power
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK
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44
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Norris T, Mansukoski L, Gilthorpe MS, Hamer M, Hardy R, Howe LD, Hughes AD, Li L, O'Donnell E, Ong KK, Ploubidis GB, Silverwood RJ, Viner RM, Johnson W. Distinct Body Mass Index Trajectories to Young-Adulthood Obesity and Their Different Cardiometabolic Consequences. Arterioscler Thromb Vasc Biol 2021; 41:1580-1593. [PMID: 33657884 DOI: 10.1161/atvbaha.120.315782] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Tom Norris
- School of Sport, Exercise and Health Sciences, Loughborough University, United Kingdom (T.N., E.O., W.J.)
| | - Liina Mansukoski
- Centre for Global Child Health, The Hospital for Sick Children, Toronto, Canada (L.M.)
| | - Mark S Gilthorpe
- Leeds Institute for Data Analytics (M.S.G.), University of Leeds, United Kingdom.,Faculty of Medicine and Health (M.S.G.), University of Leeds, United Kingdom.,Alan Turing Institute, British Library, London, United Kingdom (M.S.G.)
| | - Mark Hamer
- Division of Surgery and Interventional Sciences, Faculty of Medical Sciences (M.H.), University College London, United Kingdom
| | - Rebecca Hardy
- CLOSER (Cohort and Longitudinal Studies Enhancement Resources), Department of Social Science (R.H.), University College London, United Kingdom
| | - Laura D Howe
- MRC (Medical Research Council) Integrative Epidemiology Unit at the University of Bristol, Department of Population Health Sciences, University of Bristol, United Kingdom (L.D.H.)
| | - Alun D Hughes
- Institute of Cardiovascular Science (A.D.H.), University College London, United Kingdom
| | - Leah Li
- Population, Policy and Practice Programme, Great Ormond Street Institute of Child Health (L.L., R.M.V.), University College London, United Kingdom
| | - Emma O'Donnell
- School of Sport, Exercise and Health Sciences, Loughborough University, United Kingdom (T.N., E.O., W.J.)
| | - Ken K Ong
- Department of Social Science, Centre for Longitudinal Studies (G.B.P., R.J.S.), University College London, United Kingdom.,MRC Epidemiology Unit and Department of Paediatrics, University of Cambridge, United Kingdom (K.K.O.)
| | | | - Richard J Silverwood
- Department of Social Science, Centre for Longitudinal Studies (G.B.P., R.J.S.), University College London, United Kingdom
| | - Russell M Viner
- Population, Policy and Practice Programme, Great Ormond Street Institute of Child Health (L.L., R.M.V.), University College London, United Kingdom
| | - William Johnson
- School of Sport, Exercise and Health Sciences, Loughborough University, United Kingdom (T.N., E.O., W.J.)
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45
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Staines KA, Hardy R, Samvelyan HJ, Ward KA, Cooper R. Life course longitudinal growth and risk of knee osteoarthritis at age 53 years: evidence from the 1946 British birth cohort study. Osteoarthritis Cartilage 2021; 29:335-340. [PMID: 33383179 PMCID: PMC7955286 DOI: 10.1016/j.joca.2020.12.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 12/01/2020] [Accepted: 12/21/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To examine the relationship between height gain across childhood and adolescence with knee osteoarthritis in the MRC National Survey of Health and Development (NSHD). MATERIALS AND METHODS Data are from 3035 male and female participants of the NSHD. Height was measured at ages 2, 4, 6, 7, 11 and 15 years, and self-reported at ages 20 years. Associations between (1) height at each age (2) height gain during specific life periods (3) Super-Imposition by Translation And Rotation (SITAR) growth curve variables of height size, tempo and velocity, and knee osteoarthritis at 53 years were tested. RESULTS In sex-adjusted models, estimated associations between taller height and decreased odds of knee osteoarthritis at age 53 years were small at all ages - the largest associations were an OR of knee osteoarthritis of 0.9 per 5 cm increase in height at age 4, (95% CI 0.7-1.1) and an OR of 0.9 per 5 cm increase in height, (95% CI 0.8-1.0) at age 6. No associations were found between height gain during specific life periods or the SITAR growth curve variables and odds of knee osteoarthritis. CONCLUSIONS There was limited evidence to suggest that taller height in childhood is associated with decreased odds of knee osteoarthritis at age 53 years in this cohort. This work enhances our understanding of osteoarthritis predisposition and the contribution of life course height to this.
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Affiliation(s)
- K A Staines
- School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, UK; School of Applied Sciences, Edinburgh Napier University, Edinburgh UK.
| | - R Hardy
- Cohort and Longitudinal Studies Enhancement Resources (CLOSER), UCL Institute of Education, London, UK.
| | - H J Samvelyan
- School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, UK.
| | - K A Ward
- MRC Lifecourse Epidemiology, Human Development and Health, University of Southampton, Southampton, UK.
| | - R Cooper
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University, Manchester, UK.
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46
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Christiansen C, Castillo-Fernandez JE, Domingo-Relloso A, Zhao W, El-Sayed Moustafa JS, Tsai PC, Maddock J, Haack K, Cole SA, Kardia SLR, Molokhia M, Suderman M, Power C, Relton C, Wong A, Kuh D, Goodman A, Small KS, Smith JA, Tellez-Plaza M, Navas-Acien A, Ploubidis GB, Hardy R, Bell JT. Novel DNA methylation signatures of tobacco smoking with trans-ethnic effects. Clin Epigenetics 2021; 13:36. [PMID: 33593402 PMCID: PMC7888173 DOI: 10.1186/s13148-021-01018-4] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/24/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Smoking remains one of the leading preventable causes of death. Smoking leaves a strong signature on the blood methylome as shown in multiple studies using the Infinium HumanMethylation450 BeadChip. Here, we explore novel blood methylation smoking signals on the Illumina MethylationEPIC BeadChip (EPIC) array, which also targets novel CpG-sites in enhancers. METHOD A smoking-methylation meta-analysis was carried out using EPIC DNA methylation profiles in 1407 blood samples from four UK population-based cohorts, including the MRC National Survey for Health and Development (NSHD) or 1946 British birth cohort, the National Child Development Study (NCDS) or 1958 birth cohort, the 1970 British Cohort Study (BCS70), and the TwinsUK cohort (TwinsUK). The overall discovery sample included 269 current, 497 former, and 643 never smokers. Replication was pursued in 3425 trans-ethnic samples, including 2325 American Indian individuals participating in the Strong Heart Study (SHS) in 1989-1991 and 1100 African-American participants in the Genetic Epidemiology Network of Arteriopathy Study (GENOA). RESULTS Altogether 952 CpG-sites in 500 genes were differentially methylated between smokers and never smokers after Bonferroni correction. There were 526 novel smoking-associated CpG-sites only profiled by the EPIC array, of which 486 (92%) replicated in a meta-analysis of the American Indian and African-American samples. Novel CpG sites mapped both to genes containing previously identified smoking-methylation signals and to 80 novel genes not previously linked to smoking, with the strongest novel signal in SLAMF7. Comparison of former versus never smokers identified that 37 of these sites were persistently differentially methylated after cessation, where 16 represented novel signals only profiled by the EPIC array. We observed a depletion of smoking-associated signals in CpG islands and an enrichment in enhancer regions, consistent with previous results. CONCLUSION This study identified novel smoking-associated signals as possible biomarkers of exposure to smoking and may help improve our understanding of smoking-related disease risk.
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Affiliation(s)
- C Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - A Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
- Department of Statistics and Operative Research, University of Valencia, Valencia, Spain
| | - W Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - J S El-Sayed Moustafa
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - P-C Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - J Maddock
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - K Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, USA
| | - S A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, USA
| | - S L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - M Molokhia
- School of Population Health and Environmental Sciences, King's College London, London, UK
| | - M Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - C Power
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - C Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - A Wong
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - D Kuh
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - A Goodman
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - K S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - J A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - M Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - A Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
| | - G B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - R Hardy
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - J T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Blodgett JM, Cooper R, Davis DHJ, Kuh D, Hardy R. Bidirectional associations between word memory and one-legged balance performance in mid and later life. Exp Gerontol 2021; 144:111176. [PMID: 33279666 PMCID: PMC7840581 DOI: 10.1016/j.exger.2020.111176] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 11/24/2020] [Accepted: 11/30/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND Age-related changes in cognitive and balance capabilities are well-established, as is their correlation with one another. Given limited evidence regarding the directionality of associations, we aimed to explore the direction and potential explanations of associations between word memory and one-legged balance performance in mid-later life. METHODS A total of 3062 participants in the Medical Research Council National Survey of Health and Development, a British birth cohort study, were included. One-legged balance times (eyes closed) were measured at ages 53, 60-64 and 69 years. Word memory was assessed at ages 43, 53, 60-64 and 69 with three 15-item word-recall trials. Autoregressive cross-lagged and dual change score models assessed bidirectional associations between word memory and balance. Random-effects models quantified the extent to which these associations were explained by adjustment for anthropometric, socioeconomic, behavioural and health status indicators. RESULTS Autoregressive cross-lagged and dual change score models suggested a unidirectional association between word memory and subsequent balance performance. In a sex-adjusted random-effects model, 1 standard deviation increase in word memory was associated with 9% (7,12%) higher balance performance at age 53. This association decreased with age (-0.4% /year (-0.6,-0.1%). Education partially attenuated the association, although it remained in the fully-adjusted model (3% (0.1,6%)). CONCLUSIONS There was consistent evidence that word memory is associated with subsequent balance performance but no evidence of the reverse association. Cognitive processing plays an important role in the balance process, with educational attainment providing some contribution. These findings have important implications for understanding cognitive-motor associations and for interventions aimed at improving cognitive and physical capability in the ageing population.
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Affiliation(s)
| | - Rachel Cooper
- Musculoskeletal Science and Sports Medicine Research Centre, Department of Sport and Exercise Sciences, Manchester Metropolitan University, Manchester, UK
| | | | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
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48
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Wood N, Hardy R, Bann D, Gale C, Stafford M. Childhood correlates of adult positive mental well-being in three British longitudinal studies. J Epidemiol Community Health 2021; 75:177-184. [PMID: 32967893 DOI: 10.1136/jech-2019-213709] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 09/01/2020] [Accepted: 09/08/2020] [Indexed: 11/04/2022]
Abstract
BACKGROUND Previous evidence has shown how experiences within childhood, such as parenting and socioeconomic conditions, are associated later on in life with adult mental well-being. However, these studies tend to focus on childhood experiences in isolation, and fewer studies have investigated how multiple aspects of the childhood environment, including both socioeconomic and psychosocial aspects, are associated with adult positive mental well-being. Using data from three British birth cohort studies, we investigated how prospective measures of the childhood environment up to the age of 16 years were associated with midlife adult mental well-being and whether similar associations were replicated across different generations. METHODS Childhood environment comprised socioeconomic circumstances, psychosocial factors (child-rearing and parenting, family instability) and parental health. The Warwick-Edinburgh Mental Wellbeing Scale, a validated instrument measuring both hedonic and eudaemonic aspects of well-being, was administered in mid-life. We modelled associations between childhood environment domains and well-being. RESULTS Despite changes in social context in all three studies, poorer quality parent-child relationships and poor parental mental health were strongly and independently associated with poorer adult mental well-being. Socioeconomic circumstances were also associated with adult mental well-being, but the association was weaker than for the measures of parenting or parental mental health. CONCLUSION These findings confirm that parenting and parental mental health, as well as socioeconomic circumstances, are important for adult mental well-being. Interventions in early childhood aimed at reducing socioeconomic adversity and offering support to parents might be warranted, to enhance adult mental well-being later on in the life course.
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Affiliation(s)
- Natasha Wood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - David Bann
- Centre for Longitudinal Studies, UCL, London, UK
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49
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Muthuri S, Cooper R, Kuh D, Hardy R. Do the associations of body mass index and waist circumference with back pain change as people age? 32 years of follow-up in a British birth cohort. BMJ Open 2020; 10:e039197. [PMID: 33310796 PMCID: PMC7735102 DOI: 10.1136/bmjopen-2020-039197] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES To investigate whether cross-sectional and longitudinal associations of body mass index (BMI) and waist circumference (WC) with back pain change with age and extend into later life. DESIGN British birth cohort study. SETTING England, Scotland and Wales. PARTICIPANTS Up to 3426 men and women from the MRC National Survey of Health and Development. PRIMARY OUTCOME MEASURES Back pain (sciatica, lumbago or recurring/severe backache all or most of the time) was self-reported during nurse interviews at ages 36, 43, 53 and 60-64 years and in a postal questionnaire using a body manikin at age 68. RESULTS Findings from mixed-effects logistic regression models indicated that higher BMI was consistently associated with increased odds of back pain across adulthood. Sex-adjusted ORs of back pain per 1 SD increase in BMI were: 1.13 (95% CI: 1.01 to 1.26), 1.11 (95% CI: 1.00 to 1.23), 1.17 (95% CI: 1.05 to 1.30), 1.31 (95% CI: 1.15 to 1.48) and 1.08 (95% CI: 0.95 to 1.24) at ages 36, 43, 53, 60-64 and 68-69, respectively. Similar patterns of associations were observed for WC. These associations were maintained when potential confounders, including education, occupational class, height, cigarette smoking status, physical activity and symptoms of anxiety and depression were accounted for. BMI showed stronger associations than WC in models including both measures. CONCLUSIONS These findings demonstrate that higher BMI is a persistent risk factor for back pain across adulthood. This highlights the potential lifelong consequences on back pain of the rising prevalence of obesity within the population.
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Affiliation(s)
- Stella Muthuri
- MRC Unit for Lifelong Health and Ageing, UCL, London, UK
| | - Rachel Cooper
- Department of Sport and Exercise Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Manchester Metropolitan University, Manchester, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, UCL, London, UK
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50
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Zhu D, Chung HF, Dobson AJ, Pandeya N, Anderson DJ, Kuh D, Hardy R, Brunner EJ, Avis NE, Gold EB, El Khoudary SR, Crawford SL, Mishra GD. Vasomotor menopausal symptoms and risk of cardiovascular disease: a pooled analysis of six prospective studies. Am J Obstet Gynecol 2020; 223:898.e1-898.e16. [PMID: 32585222 DOI: 10.1016/j.ajog.2020.06.039] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/18/2020] [Accepted: 06/18/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND Menopausal vasomotor symptoms (ie, hot flashes and night sweats) have been associated with unfavorable risk factors and surrogate markers of cardiovascular disease, but their association with clinical cardiovascular disease events is unclear. OBJECTIVE To examine the associations between different components of vasomotor symptoms, timing of vasomotor symptoms, and risk of cardiovascular disease. STUDY DESIGN We harmonized and pooled individual-level data from 23,365 women in 6 prospective studies that contributed to the International Collaboration for a Life Course Approach to Women's Reproductive Health and Chronic Disease Events consortium. Women who experienced cardiovascular disease events before baseline were excluded. The associations between frequency (never, rarely, sometimes, and often), severity (never, mild, moderate, and severe), and timing (before or after age of menopause; ie, early or late onset) of vasomotor symptoms and incident cardiovascular disease were analyzed. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals. RESULTS In the adjusted model, no evidence of association was found between the frequency of hot flashes and incident cardiovascular disease, whereas women who reported night sweats "sometimes" (hazard ratio, 1.22; 95% confidence interval, 1.02-1.45) or "often" (hazard ratio, 1.29; 95% confidence interval, 1.05-1.58) had higher risk for cardiovascular disease. Increased severity of either hot flashes or night sweats was associated with higher risk of cardiovascular disease. The hazards ratios of cardiovascular disease in women with severe hot flashes, night sweats, and any vasomotor symptoms were 1.83 (95% confidence interval, 1.22-2.73), 1.59 (95% confidence interval, 1.07-2.37), and 2.11 (95% confidence interval, 1.62-2.76), respectively. Women who reported severity of both hot flashes and night sweats had a higher risk for cardiovascular disease (hazard ratio, 1.55; 95% confidence interval, 1.24-1.94) than those with hot flashes alone (hazard ratio, 1.33; 95% confidence interval, 0.94-1.88) and night sweats alone (hazard ratio, 1.32; 95% confidence interval, 0.84-2.07). Women with either early-onset (hazard ratio, 1.38; 95% confidence interval, 1.10-1.75) or late-onset (hazard ratio, 1.69; 95% confidence interval, 1.32-2.16) vasomotor symptoms had an increased risk for incident cardiovascular disease compared with women who did not experience vasomotor symptoms. CONCLUSION Severity rather than frequency of vasomotor symptoms (hot flashes and night sweats) was associated with increased risk of cardiovascular disease. Vasomotor symptoms with onset before or after menopause were also associated with increased risk of cardiovascular disease.
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