1
|
Sizer A, Sacker A, Lacey R, Richards M. Non-employment over the working life: Implications for cognitive function and decline in later life. PUBLIC HEALTH IN PRACTICE 2025; 9:100563. [PMID: 39867295 PMCID: PMC11758421 DOI: 10.1016/j.puhip.2024.100563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 12/03/2024] [Accepted: 12/06/2024] [Indexed: 01/28/2025] Open
Abstract
Objectives Disuse theory predicts that cognitive function is vulnerable to transitions that remove factors that support cognitive skills. We sought to investigate whether non-employment over the working life was associated with cognitive function and decline in later life (≥60 years old), and possible gender differences in the association. Study design Longitudinal study. Method We used data from the MRC National Survey of Health and Development (NSHD). Cognitive function was measured by verbal memory and processing speed. Linear regression was used to test associations between non-employment duration and cognitive function at age 60-64, and conditional change models were used to examine associations between non-employment and cognitive decline from age 60-64 to 69. Gender specific models were adjusted for childhood factors and educational attainment, adult occupational features, and adult health and lifestyle indicators. Missing data was accounted for using multiple imputation by chained equations. Results In fully adjusted models >15 years non-employment was associated with lower cognitive function at age 60-64 in men (verbal memory: -0.72, 95%CI -1.18, -0.26; processing speed: -0.61, 95%CI -1.00, -0.28), but not women. Fully adjusted models also indicated that long-term and intermediate lengths of non-employment were associated with faster decline in verbal memory (-0.38, 95%CI -0.75, -0.02) and processing speed (-0.28, 95%CI -0.52, -0.03) in men. There was no association between non-employment and cognitive decline among women. Conclusion Long-term non-employment in men, but not women, is associated with accelerated cognitive ageing.
Collapse
Affiliation(s)
- A.J. Sizer
- Department of Epidemiology and Public Health, University College London, London, UK
| | - A. Sacker
- Department of Epidemiology and Public Health, University College London, London, UK
| | - R.E. Lacey
- Research Department of Epidemiology and Public Health, University College London, London, UK
| | - M. Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
2
|
Lu K, Baker J, Nicholas JM, Street RE, Keuss SE, Coath W, James SN, Keshavan A, Weston PSJ, Murray-Smith H, Cash DM, Malone IB, Wong A, Fox NC, Richards M, Crutch SJ, Schott JM. Associations between accelerated forgetting, amyloid deposition and brain atrophy in older adults. Brain 2025; 148:1302-1315. [PMID: 39423292 PMCID: PMC11969454 DOI: 10.1093/brain/awae316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 08/14/2024] [Accepted: 09/22/2024] [Indexed: 10/21/2024] Open
Abstract
Accelerated long-term forgetting (ALF) is the phenomenon whereby material is retained normally over short intervals (e.g. minutes) but forgotten abnormally rapidly over longer periods (days or weeks). ALF might be an early marker of cognitive decline, but little is known about its relationships with preclinical Alzheimer's disease pathology and how memory selectivity might influence which material is forgotten. We assessed ALF in 'Insight 46', a sub-study of the MRC National Survey of Health and Development (a population-based cohort born during the same week in 1946) (n = 429; 47% female; assessed at age ∼73 years). ALF assessment comprised visual and verbal memory tests: complex figure drawing and the face-name associative memory exam (FNAME). ALF scores were calculated as the percentage of material retained after 7 days, relative to 30 min. In 306 cognitively normal participants, we investigated effects on ALF of β-amyloid pathology (quantified using 18F-Florbetapir-PET, classified as positive/negative) and whole-brain and hippocampal atrophy rate (quantified from serial T1-MRI over ∼2.4 years preceding the ALF assessment), in addition to interactions between these pathologies. We categorized complex figure drawing items as 'outline' or 'detail', to test our hypothesis that forgetting the outline of the structure would be more sensitive to the effect of brain pathologies. We also investigated associations between ALF and subjective cognitive decline, measured with the MyCog questionnaire. Complex figure 'outline' items were better retained than 'detail' items (mean retention over 7 days = 94% versus 72%). Amyloid-positive participants showed greater forgetting of the complex figure outline compared with amyloid-negative participants (90% versus 95%; P < 0.01). There were interactions between amyloid pathology and cerebral atrophy, such that whole-brain and hippocampal atrophy predicted greater ALF on complex figure drawing among amyloid-positive participants only [e.g. 1.9 percentage-points lower retention per ml/year of whole-brain atrophy (95% confidence intervals 0.5, 3.7); P < 0.05]. Greater ALF on FNAME was associated with increased rate of hippocampal atrophy. ALF on complex figure drawing was also correlated with subjective cognitive decline [-0.45 percentage-points per MyCog point (-0.85, -0.05); P < 0.05]. These results provide evidence of associations between some measures of ALF and biomarkers of brain pathologies and subjective cognitive decline in cognitively normal older adults. On complex figure drawing, 'outline' items were better remembered than 'detail' items, illustrating the strategic role of memory selectivity, but 'outline' items were also relatively more vulnerable to ALF in individuals with amyloid pathology. Overall, our findings suggest that ALF might be a sensitive marker of cognitive changes in preclinical Alzheimer's disease.
Collapse
Affiliation(s)
- Kirsty Lu
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - John Baker
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| | - Rebecca E Street
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Sarah E Keuss
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - William Coath
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, WC1B 5JU, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Philip S J Weston
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
| | - Ian B Malone
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, WC1B 5JU, UK
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, WC1B 5JU, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| |
Collapse
|
3
|
Canning T, Richards M, Hansell AL, Gulliver J, Hardy R, Arias-de la Torre J, Hatch SL, Mudway IS, Khanolkar AR, Fisher HL, Bakolis I. Association of ambient air pollution exposure with psychological distress in mid and later adulthood: A 26-year prospective cohort study. PLoS One 2025; 20:e0320332. [PMID: 40138275 PMCID: PMC11940730 DOI: 10.1371/journal.pone.0320332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Accepted: 02/16/2025] [Indexed: 03/29/2025] Open
Abstract
BACKGROUND Existing evidence on associations between exposure to air pollution and psychological distress from middle to older age is limited by consideration of short exposure periods, poor historical covariates, exposures and outcomes, and cross-sectional study designs. We aimed to examine this association over a 26-year period between ages 43 and 69. METHODS We utilised data from the Medical Research Council National Survey of Health and Development Study (the 1946 British birth cohort). Land-use regression models estimated exposure to specific air pollutants using household addresses for 1991 (NO2), 2001 (PM10, NO2), and 2010 (NO2, NOx, PM10, PM2.5, PMcoarse, PM2.5abs). These were linked to the closest data collection wave at ages 43, 53 and 60-64, respectively. Psychological distress was assessed through the 28-item version of the General Health Questionnaire (GHQ-28), at ages 53, 60-64 and 69. Associations between each of the pollutants with psychological distress were analysed using generalised linear mixed models, adjusted for pollution exposure before age 43, assigned sex, social class, smoking status, neighbourhood deprivation, and previous mental health problems. We also examined effect modification by social class. RESULTS At age 69, 2125 participants completed the GHQ-28. In fully adjusted models, higher NO2 exposure was associated with higher GHQ-28 scores across a 26-year period (β=0.023, 95%CI:0.005, 0.040 per interquartile range increase in exposure), whereas higher exposure to PM10 was associated with lower GHQ-28 scores across a 16-year period (β=-0.021, 95%CI:-0.037, -0.006). There was no evidence of associations between exposure to other pollutants at age 60-64 and GHQ-28 at age 69. We found no effect modification by social class. CONCLUSIONS In this cohort there was some evidence of an association between higher cumulative exposure to NO2 and higher psychological distress, but mixed associations with other exposures. Policies to reduce pollutant exposure may help improve psychological symptoms in middle to late adulthood.
Collapse
Affiliation(s)
- Thomas Canning
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Centre for Mental Health Policy and Evaluation, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Anna L. Hansell
- Centre for Environmental Health and Sustainability, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Environmental Exposures and Health at the University of Leicester, Leicester, United Kingdom
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC), Leicester General Hospital, Leicester, United Kingdom
| | - John Gulliver
- Centre for Environmental Health and Sustainability, University of Leicester, Leicester, United Kingdom
- Population Health Research Institute, City St George’s, University of London, London, United Kingdom
| | - Rebecca Hardy
- Social Research Institute, University College London, London, United Kingdom
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - Jorge Arias-de la Torre
- Centre for Mental Health Policy and Evaluation, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Institute of Biomedicine (IBIOMED), University of Leon, Leon, Spain
- Care in Long Term Conditions Research Division, Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care, King’s College London, London, United Kingdom
| | - Stephani L. Hatch
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- ESRC Centre for Society and Mental Health, King’s College London, London, United Kingdom
- Population Health Improvement UK (PHI-UK), Population Mental Health Consortium, London, United Kingdom
| | - Ian S. Mudway
- MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom
- NIHR Health Protection Research Units in Environmental Exposures and Health, and Chemical and Radiation Threats and Hazards, Imperial College London, London, United Kingdom
| | - Amal R. Khanolkar
- Department of Population Health Sciences, School of Life Course & Population Sciences, King’s College London, London, United Kingdom
| | - Helen L. Fisher
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- ESRC Centre for Society and Mental Health, King’s College London, London, United Kingdom
| | - Ioannis Bakolis
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Centre for Mental Health Policy and Evaluation, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| |
Collapse
|
4
|
James SN, Sudre CH, Barnes J, Cash DM, Chiou YJ, Coath W, Keshavan A, Lu K, Malone I, Murray-Smith H, Nicholas JM, Orini M, Parker T, Almeida-Meza P, Fox NC, Richards M, Schott JM. The relationship between leisure time physical activity patterns, Alzheimer's disease markers and cognition. Brain Commun 2025; 7:fcae431. [PMID: 39898325 PMCID: PMC11781833 DOI: 10.1093/braincomms/fcae431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 10/11/2024] [Accepted: 11/27/2024] [Indexed: 02/04/2025] Open
Abstract
We assessed the association between leisure time physical activity patterns across 30 years of adulthood with a range of in vivo Alzheimer's disease-related neurodegenerative markers and cognition, and their interplay, at age 70. Participants from the 1946 British birth cohort study prospectively reported leisure time physical activity five times between ages 36 and 69 and were dichotomized into (i) not active (no participation/month) and (ii) active (participated once or more/month) and further derived into: (0) never active (not active); (1) active before 50's only (≤43 years); (2) active from 50's onwards only (≥53 years); (3) always active (active throughout). Participants underwent 18F-florbetapir Aβ and magnetic resonance imaging at age 70. Regression analyses were conducted to assess the direct and the moderating relationship between leisure time physical activity metrics, Alzheimer's disease-related neurodegeneration markers (including Aβ status, hippocampal and whole-brain volume, and cortical thickness in Alzheimer's disease signature regions) and cognition. All models were adjusted for childhood cognition, education and childhood socioeconomic position, and examined by sex. Findings drawn from 468 participants (49% female) demonstrated a direct association between being active before 50 years old (≤43 years) and throughout life (up to age 69 years), with larger hippocampal volume at age 70 (P < 0.05). There was little evidence that leisure time physical activity had direct effects on other brain health measures (all P > 0.05). However, leisure time physical activity patterns modified and attenuated the association between poorer cognitive functioning at age 70 and a range of Alzheimer's disease-related neurodegenerative markers (Aβ status; hippocampal and whole-brain volume; cortical thickness in Alzheimer's disease regions) (all P < 0.05). We found suggestive evidence that women with early markers of Alzheimer's disease-related neurodegeneration were most sensitive to leisure time physical activity patterns: a lifetime of inactivity in women exacerbated the manifestation of early Alzheimer's disease markers (Aβ and cortical thickness-related cognition), yet, if women were active across life or early in life, it mostly buffered these negative relationships. Engagement in leisure time physical activity in the life course is associated with better cognitive functioning at age 70, even in those with early markers of Alzheimer's disease. If causal, this is likely via multiple pathways, potentially through the preservation of hippocampal volume, as well as via cognitive resilience pathways delaying cognitive manifestations of early markers of Alzheimer's disease, particularly in women. Our findings warrant further research to shed light on the mechanisms of physical activity as a potential disease-modifying intervention of brain health and cognitive resilience.
Collapse
Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London WC1E 7HB, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London WC1E 7HB, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
- Biomedical Computing, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- UK Dementia Research Institute at UCL, University College London, London NW1 3BT, UK
| | - Yu-Jie Chiou
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 833401, Taiwan
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Ian Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London WC1E 7HT, UK
| | - Michele Orini
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London WC1E 7HB, UK
| | - Thomas Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- UK Dementia Research Institute, Centre for Care Research and Technology, Imperial College London, London W12 0BZ, UK
- Department of Medicine, Division of Brain Sciences, Imperial College London, London W12 0NN, UK
| | - Pamela Almeida-Meza
- Department of Behavioural Science and Health, University College London, London WC1E 6BT, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London WC1E 7HB, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London WC1E 7HB, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| |
Collapse
|
5
|
Budin-Ljøsne I, Fredheim NAG, Jevne CA, Kleven BM, Charles MA, Felix JF, Flaig R, García MP, Havdahl A, Islam S, Kerr SM, Meder IK, Molloy L, Morton SMB, Pizzi C, Rahman A, Willemsen G, Wood D, Harris JR. Participant engagement and involvement in longitudinal cohort studies: qualitative insights from a selection of pregnancy and birth, twin, and family-based population cohort studies. BMC Med Res Methodol 2024; 24:297. [PMID: 39623293 PMCID: PMC11613753 DOI: 10.1186/s12874-024-02419-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 11/25/2024] [Indexed: 12/06/2024] Open
Abstract
BACKGROUND Longitudinal cohort studies are pivotal to understand how socioeconomic, environmental, biological, and lifestyle factors influence health and disease. The added value of cohort studies increases as they accumulate life course data and expand across generations. Ensuring that participants stay motivated to contribute over decades of follow-up is, however, challenging. Participant engagement and involvement (PEI) aims to secure the long-term commitment of participants and promote researcher-participant interaction. This study explored PEI practices in a selection of pregnancy and birth, twin, and family-based population cohort studies. METHODS Purposive sampling was used to identify cohorts in Europe, Australia and New Zealand. Fourteen semi-structured digital interviews were conducted with cohort study representatives to explore strategies for participant recruitment, informed consent, communication of general and individual information to participants, data collection, and participant involvement. Experiences, resources allocated to PEI, and reflections on future PEI, were discussed. The interview data were analyzed using a content analysis approach and summary results were reviewed and discussed by the representatives. RESULTS The cohort studies used various strategies to recruit participants including support from health professionals and organizations combined with information on the studies' web sites and social media. New approaches such as intra-cohort recruitment, were being investigated. Most cohorts transitioned from paper-based to digital solutions to collect the participants' consent and data. While digital solutions increased efficiency, they also brought new challenges. The studies experimented with the use of participant advisory panels and focus groups to involve participants in making decisions, although their success varied across age and socio-economic background. Most representatives reported PEI resources to be limited and called for more human, technical, educational and financial resources to maximize the positive effects of PEI. CONCLUSIONS This study of PEI among well-established cohort studies underscores the importance of PEI for project sustainability and highlights key factors to consider in developing PEI. Our analysis shows that knowledge gaps exist regarding which approaches have highest impact on retention rates and are best suited for different participant groups. Research is needed to support the development of best practices for PEI as well as knowledge exchange between cohorts through network building.
Collapse
Affiliation(s)
- Isabelle Budin-Ljøsne
- Department of Food Safety, Norwegian Institute of Public Health, P.O. Box 222, Skøyen, Oslo, NO-0213, Norway.
| | | | | | | | | | - 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
| | - Robin Flaig
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - María Paz García
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Alexandra Havdahl
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Psychology, PROMENTA Research Centre, University of Oslo, Oslo, Norway
| | - Shahid Islam
- Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, UK
| | | | - Lynn Molloy
- Population Health Sciences, Bristol Medical School, ALSPAC (Children of the 90s), University of Bristol, Bristol, UK
| | - Susan M B Morton
- Research Institute for Innovative Solutions for Well-Being and Health (INSIGHT), Faculty of Health, University of Technology, Sydney, Australia
| | - Costanza Pizzi
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Aamnah Rahman
- Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Diane Wood
- The Raine Study, School of Population and Global Health, The University of Western Australia, Perth, Australia
| | - Jennifer R Harris
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| |
Collapse
|
6
|
Deng R, Victoria G, Ucci M. Associations between residential daytime indoor temperature and self-reported sleep disturbances in UK adults: A cross-sectional study. ENVIRONMENTAL RESEARCH 2024; 257:119281. [PMID: 38821464 DOI: 10.1016/j.envres.2024.119281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/12/2024] [Accepted: 05/29/2024] [Indexed: 06/02/2024]
Abstract
BACKGROUND In the past few decades, research on the association between indoor temperature and sleep has primarily used laboratory rather than field data collected in epidemiological cohorts. METHODS Secondary data on 2493 individuals aged 43 years was obtained from the National Survey of Health and Development (NSHD). Logistic regression models were used to investigate the associations between temperatures (indoor at home, spot measurement when the nurses visited during the day; and outdoor, monthly average) and self-reported sleep disturbances, adjusting for socio-demographics, health variables, housing variables, and temperature-related variables. RESULTS Associations were found between daytime indoor temperature with difficulty initiating (OR: 0.95, 95%CI: 0.91-0.98) and maintaining sleep (OR: 0.96, 95%CI: 0.93-0.99). Compared with neutral indoor temperatures (17-28 °C), low indoor temperature (≤17 °C) was associated with difficulty initiating sleep (OR: 1.79, 95%CI: 1.21-2.65). Stratified analysis results across tertiles showed that associations with difficulty initiating (OR: 0.87, 95%CI: 0.77-0.99) and maintaining sleep (OR: 0.88, 95%CI: 0.79-0.98) were observed respectively in the lowest (≤20 °C) and highest tertile (≥23 °C) of indoor temperature. There was no association between outdoor temperature and self-reported sleep disturbances in this study. CONCLUSION In this first UK-based epidemiology study investigating temperature and sleep, self-reported sleep disturbances were associated with residential daytime indoor temperatures. Low indoor temperature had significantly higher odds ratio for difficulty initiating sleep compared with the neutral indoor temperature. A warmer indoor environment might be more suitable for sleep maintenance than sleep initiation. Indoor temperature in this study was a superior indicator of sleep disturbances than outdoor temperature. Although these findings are based on a UK sample, they may be relevant to other high-income settings with similar housing stock and climatic conditions.
Collapse
Affiliation(s)
- Ruiwen Deng
- Institute of Environmental Design and Engineering, The Bartlett School of Environment, Energy and Resources, University College London, London, United Kingdom.
| | - Garfield Victoria
- Department of Pharmacology & Therapeutics, Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Marcella Ucci
- Institute of Environmental Design and Engineering, The Bartlett School of Environment, Energy and Resources, University College London, London, United Kingdom
| |
Collapse
|
7
|
Bundil I, Baltruschat S, Zhang J. Characterising and differentiating cognitive and motor speed in older adults: structural equation modelling on a UK longitudinal birth cohort. BMJ Open 2024; 14:e083968. [PMID: 39160108 PMCID: PMC11337668 DOI: 10.1136/bmjopen-2024-083968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 07/29/2024] [Indexed: 08/21/2024] Open
Abstract
OBJECTIVES Information processing speed (IPS) has been proposed to be a key component in healthy ageing and cognitive functioning. Yet, current studies lack a consistent definition and specific influential characteristics. This study aimed to investigate IPS as a multifaceted concept by differentiating cognitive and motor IPS. DESIGN, SETTING AND PARTICIPANTS A retrospective data analysis using data from the Medical Research Council National Survey of Health and Development (a population-based cohort of UK adults born in 1946) at childhood (ages 8, 11 and 15) and adulthood (ages 60-64 and 68-70). Using structural equation modelling, we constructed two models of IPS with 2124 and 1776 participants, respectively. OUTCOME MEASURES Measures of interest included IPS (ie, letter cancellation, simple and choice reaction time), intelligence (ie, childhood intelligence and National Adult Reading Test), verbal memory, socioeconomic status (SES) and cognitive functions measured by the Addenbrooke's Cognitive Examination III, as well as a variety of health indexes. RESULTS We found distinct predictors for cognitive and motor IPS and how they relate to other cognitive functions in old age. In our first model, SES and antipsychotic medication usage emerged as significant predictors for cognitive IPS, intelligence and smoking as predictors for motor IPS while both share sex, memory and antiepileptic medication usage as common predictors. Notably, all differences between both IPS types ran in the same direction except for sex differences, with women performing better than men in cognitive IPS and vice versa in motor IPS. The second model showed that both IPS measures, as well as intelligence, memory, antipsychotic and sedative medication usage, explain cognitive functions later in life. CONCLUSION Taken together, these results shed further light on IPS as a whole by showing there are distinct types and that these measures directly relate to other cognitive functions.
Collapse
Affiliation(s)
- Indra Bundil
- School of Psychology, Cardiff University, Cardiff, UK
| | | | - Jiaxiang Zhang
- School of Psychology, Cardiff University, Cardiff, UK
- Department of Computer Science, Swansea University, Swansea, UK
| |
Collapse
|
8
|
Rawle MJ, Lau WCY, Gonzalez-Izquierdo A, Patalay P, Richards M, Davis D. Associations Between Midlife Anticholinergic Medication Use and Subsequent Cognitive Decline: A British Birth Cohort Study. Drugs Aging 2024; 41:543-554. [PMID: 38740716 DOI: 10.1007/s40266-024-01116-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/03/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND Anticholinergic medication use is associated with cognitive decline and incident dementia. Our study, a prospective birth cohort analysis, aimed to determine if repeated exposure to anticholinergic medications was associated with greater decline, and whether decline was reversed with medication reduction. METHODS From the Medical Research Council (MRC) National Survey of Health and Development, a British birth cohort with all participants born in a single week of March 1946, we quantified anticholinergic exposure between ages 53 and 69 years using the Anticholinergic Cognitive Burden Scale (ACBS). We used multinomial regression to estimate associations with global cognition, quantified by the Addenbrooke's Cognitive Examination, 3rd Edition (ACE-III). Longitudinal associations between ACBS and cognitive test results (Verbal memory quantified by the Word Learning Test [WLT], and processing speed quantified by the Timed Letter Search Task [TLST]) at three time points (age 53, 60-64 and 69) were assessed using mixed and fixed effects linear regression models. Analyses were adjusted for sex, childhood cognition, education, chronic disease count and severity, and mental health symptoms. RESULTS Anticholinergic exposure was associated cross-sectionally with lower ACE-III scores at age 69, with the greatest effects in those with high exposure at ages 60-64 (mean difference - 2.34, 95% confidence interval [CI] - 3.51 to - 1.17). Longitudinally, both mild-moderate and high ACBS scores were linked to lower WLT scores, again with high exposure showing larger effects (mean difference with contemporaneous exposure - 0.90, 95% CI - 1.63 to - 0.17; mean difference with lagged exposure - 1.53, 95% CI - 2.43 to - 0.64). Associations remained in fixed effects models (mean difference with contemporaneous exposure -1.78, 95% CI -2.85 to - 0.71; mean difference with lagged exposure - 2.23, 95% CI - 3.33 to - 1.13). Associations with TLST were noted only in isolated contemporaneous exposure (mean difference - 13.14, 95% CI - 19.04 to - 7.23; p < 0.01). CONCLUSIONS Anticholinergic exposure throughout mid and later life was associated with lower cognitive function. Reduced processing speed was associated only with contemporaneous anticholinergic medication use, and not historical use. Associations with lower verbal recall were evident with both historical and contemporaneous use of anticholinergic medication, and associations with historical use persisted in individuals even when their anticholinergic medication use decreased over the course of the study.
Collapse
Affiliation(s)
- Mark J Rawle
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK.
- Academic Centre for Healthy Ageing (ACHA) @ Whipps Cross University Hospital, Barts Health NHS Trust, Whipps Cross Road, London, E11 1NR, UK.
| | - Wallis C Y Lau
- Research Department of Practice and Policy, School of Pharmacy, UCL, London, UK
- Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Pak Shek Kok, Hong Kong
| | - Arturo Gonzalez-Izquierdo
- Institute of Health Informatics and Health Data Research UK, UCL, London, UK
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | | | | | - Daniel Davis
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| |
Collapse
|
9
|
Murray-Smith H, Barker S, Barkhof F, Barnes J, Brown TM, Captur G, R E Cartlidge M, Cash DM, Coath W, Davis D, Dickson JC, Groves J, Hughes AD, James SN, Keshavan A, Keuss SE, King-Robson J, Lu K, Malone IB, Nicholas JM, Rapala A, Scott CJ, Street R, Sudre CH, Thomas DL, Wong A, Wray S, Zetterberg H, Chaturvedi N, Fox NC, Crutch SJ, Richards M, Schott JM. Updating the study protocol: Insight 46 - a longitudinal neuroscience sub-study of the MRC National Survey of Health and Development - phases 2 and 3. BMC Neurol 2024; 24:40. [PMID: 38263061 PMCID: PMC10804658 DOI: 10.1186/s12883-023-03465-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/13/2023] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Although age is the biggest known risk factor for dementia, there remains uncertainty about other factors over the life course that contribute to a person's risk for cognitive decline later in life. Furthermore, the pathological processes leading to dementia are not fully understood. The main goals of Insight 46-a multi-phase longitudinal observational study-are to collect detailed cognitive, neurological, physical, cardiovascular, and sensory data; to combine those data with genetic and life-course information collected from the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort); and thereby contribute to a better understanding of healthy ageing and dementia. METHODS/DESIGN Phase 1 of Insight 46 (2015-2018) involved the recruitment of 502 members of the NSHD (median age = 70.7 years; 49% female) and has been described in detail by Lane and Parker et al. 2017. The present paper describes phase 2 (2018-2021) and phase 3 (2021-ongoing). Of the 502 phase 1 study members who were invited to a phase 2 research visit, 413 were willing to return for a clinic visit in London and 29 participated in a remote research assessment due to COVID-19 restrictions. Phase 3 aims to recruit 250 study members who previously participated in both phases 1 and 2 of Insight 46 (providing a third data time point) and 500 additional members of the NSHD who have not previously participated in Insight 46. DISCUSSION The NSHD is the oldest and longest continuously running British birth cohort. Members of the NSHD are now at a critical point in their lives for us to investigate successful ageing and key age-related brain morbidities. Data collected from Insight 46 have the potential to greatly contribute to and impact the field of healthy ageing and dementia by combining unique life course data with longitudinal multiparametric clinical, imaging, and biomarker measurements. Further protocol enhancements are planned, including in-home sleep measurements and the engagement of participants through remote online cognitive testing. Data collected are and will continue to be made available to the scientific community.
Collapse
Affiliation(s)
- Heidi Murray-Smith
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK.
| | - Suzie Barker
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Centre for Medical Image Computing, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Thomas M Brown
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Gabriella Captur
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Molly R E Cartlidge
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - David M Cash
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - William Coath
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Daniel Davis
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - John C Dickson
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - James Groves
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Josh King-Robson
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Kirsty Lu
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Ian B Malone
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Alicja Rapala
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Catherine J Scott
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Rebecca Street
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Carole H Sudre
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
- Centre for Medical Image Computing, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Selina Wray
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Hong, Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| |
Collapse
|
10
|
Liu Y, Patalay P, Stafford J, Schott JM, Richards M. Lifecourse investigation of the cumulative impact of adversity on cognitive function in old age and the mediating role of mental health: longitudinal birth cohort study. BMJ Open 2023; 13:e074105. [PMID: 37940163 PMCID: PMC10632868 DOI: 10.1136/bmjopen-2023-074105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 10/23/2023] [Indexed: 11/10/2023] Open
Abstract
OBJECTIVE To investigate the accumulation of adversities (duration of exposure to any, economic, psychosocial) across the lifecourse (birth to 63 years) on cognitive function in older age, and the mediating role of mental health. DESIGN National birth cohort study. SETTING Great Britain. PARTICIPANTS 5362 singleton births within marriage in England, Wales and Scotland born within 1 week of March 1946, of which 2131 completed at least 1 cognitive assessment. MAIN OUTCOME MEASURES Cognitive assessments included the Addenbrooke's Cognitive Examination-III, as a measure of cognitive state, processing speed (timed-letter search task), and verbal memory (word learning task) at 69 years. Scores were standardised to the analytical sample. Mental health at 60-64 years was assessed using the 28-item General Health Questionnaire, with scores standardised to the analytical sample. RESULTS After adjusting for sex, increased duration of exposure to any adversity was associated with decreased performance on cognitive state (β=-0.39; 95% CI -0.59 to -0.20) and verbal memory (β=-0.45; 95% CI -0.63 to -0.27) at 69 years, although these effects were attenuated after adjusting for further covariates (childhood cognition and emotional problems, educational attainment). Analyses by type of adversity revealed stronger associations from economic adversity to verbal memory (β=-0.54; 95% CI -0.70 to -0.39), with a small effect remaining even after adjusting for all covariates (β=-0.18; 95% CI -0.32 to -0.03), and weaker associations from psychosocial adversity. Causal mediation analyses found that mental health mediated all associations between duration of exposure to adversity (any, economic, psychosocial) and cognitive function, with around 15% of the total effect of economic adversity on verbal memory attributable to mental health. CONCLUSIONS Improving mental health among older adults has the potential to reduce cognitive impairments, as well as mitigate against some of the effect of lifecourse accumulation of adversity on cognitive performance in older age.
Collapse
Affiliation(s)
- Yiwen Liu
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Jean Stafford
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| |
Collapse
|
11
|
Liu Y, Hatch SL, Patalay P, Schott JM, Richards M. A lifecourse approach in examining the association between accumulation of adversity and mental health in older adulthood. J Affect Disord 2023; 339:211-218. [PMID: 37442442 DOI: 10.1016/j.jad.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 06/01/2023] [Accepted: 07/08/2023] [Indexed: 07/15/2023]
Abstract
BACKGROUND There is evidence for a cumulative effect of adversities on mental health, however, less is known on the accumulating duration of exposure to adversity across the lifecourse on mental health in older adults. METHODS Using data from the 1946 British birth cohort study (N = 2745), we examined associations between the accumulation of adversity (birth-63 years) and mental health (emotional symptom, life satisfaction, affective wellbeing) in older adults (63-69 years). Accumulation of adversity was assessed as the number of adversities and duration of exposure (number of lifecourse stages exposed to any, economic, psychosocial, or physical adversity). Linear regression tested their association with mental health, adjusted for sex, childhood cognition and emotional problems, and educational attainment. RESULTS Increased number of adversities was associated with increased emotional symptoms (β = 0.08 [0.06, 0.10]), decreased life satisfaction (β = -0.14 [-0.16, -0.12]) and decreased affective wellbeing (β = -0.08 [-0.10, -0.06]). Each additional duration of exposure was associated with a 0.38 [0.12, 0.65] standard deviation (SD) increase in emotional symptoms, and a - 0.68 [-0.96, -0.39] and -0.43 SD [-0.68, -0.18] decrease in life satisfaction and affective wellbeing, respectively. Life satisfaction showed stronger associations with economic and psychosocial compared to physical adversity. LIMITATIONS Some limitations include selective drop-out and lack of ethnic diversity. CONCLUSIONS Efforts to improve mental health in older adults should focus on reducing the number of adversities, as well as considering previous exposure across different lifecourse stages, to prevent adversities from becoming chronic. Future research should also consider the clustering and co-occurrence of different adversities across the lifecourse.
Collapse
Affiliation(s)
- Yiwen Liu
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK.
| | - Stephani L Hatch
- Department of Psychological Medicine, King's College London, London, UK; ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK; Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
12
|
James SN, Chiou YJ, Fatih N, Needham LP, Schott JM, Richards M. Timing of physical activity across adulthood on later-life cognition: 30 years follow-up in the 1946 British birth cohort. J Neurol Neurosurg Psychiatry 2023; 94:349-356. [PMID: 36810321 PMCID: PMC10176405 DOI: 10.1136/jnnp-2022-329955] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 12/16/2022] [Indexed: 02/23/2023]
Abstract
BACKGROUND To assess how timing, frequency and maintenance of being physically active, spanning over 30 years in adulthood, is associated with later-life cognitive function. METHODS Participants (n=1417, 53% female) were from the prospective longitudinal cohort study, 1946 British birth cohort. Participation in leisure time physical activity was reported five times between ages 36 and 69, categorised into: not active (no participation in physical activity/month); moderately active (participated 1-4 times/month); most active (participated 5 or more times/month). Cognition at age 69 was assessed by tests of cognitive state (Addenbrooke's Cognitive Examination-III), verbal memory (word learning test) and processing speed (visual search speed). RESULTS Being physically active, at all assessments in adulthood, was associated with higher cognition at age 69. For cognitive state and verbal memory, the effect sizes were similar across all adult ages, and between those who were moderately and most physically active. The strongest association was between sustained cumulative physical activity and later-life cognitive state, in a dose-response manner. Adjusting for childhood cognition, childhood socioeconomic position and education largely attenuated these associations but results mainly remained significant at the 5% level. CONCLUSIONS Being physically active at any time in adulthood, and to any extent, is linked with higher later-life cognitive state, but lifelong maintenance of physical activity was most optimal. These relationships were partly explained by childhood cognition and education, but independent of cardiovascular and mental health and APOE-E4, suggestive of the importance of education on the lifelong impacts of physical activity.
Collapse
Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Yu-Jie Chiou
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Department of Psychiatry, Chang Gung Memorial Hospital Kaohsiung Branch, Kaohsiung, Taiwan
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Nasri Fatih
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Louisa P Needham
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
13
|
Norris T, Johnson W, Cooper R, Pereira SMP. Associations between diabetes status and grip strength trajectory sub-groups in adulthood: findings from over 16 years of follow-up in the MRC National Survey of Health and Development. BMC Geriatr 2023; 23:213. [PMID: 37016329 PMCID: PMC10074704 DOI: 10.1186/s12877-023-03871-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/03/2023] [Indexed: 04/06/2023] Open
Abstract
BACKGROUND Cross-sectional studies suggest a relationship between diabetes status and weaker grip strength (GS) in adulthood and limited evidence from longitudinal studies has focussed on the association with average change in GS. We aimed to investigate whether diabetes status was related to membership of distinct GS trajectories in mid-to-late adulthood in 2,263 participants in the Medical Research Council National Survey of Health and Development. METHODS Grip strength (kg) was measured at 53, 60-64 and 69 years. Pre-/diabetes was defined at 53 years based on HbA1c > 5.6% and/or doctor-diagnosis of diabetes. Sex-specific latent class trajectory models were developed and multinomial logistic regression was used to investigate the association between pre-/diabetes status and membership into GS trajectory classes. RESULTS For both males and females, a 3-class solution ('High', 'Intermediate', 'Low') provided the best representation of the GS data and the most plausible solution. There was no evidence that pre-/diabetes status was associated with class membership in either sex: e.g., adjusted odds ratios of being in the 'Low' class (vs. 'High') for males with pre-/diabetes (vs. no-diabetes) was 1.07 (95% CI:0.45,2.55). CONCLUSION Using a flexible data-driven approach to identify GS trajectories between 53 and 69 years, we observed three distinct GS trajectories, all declining, in both sexes. There was no association between pre-/diabetes status at 53 years and membership into these GS trajectories. Understanding the diabetes status-GS trajectories association is vital to ascertain the consequences that projected increases in pre-/diabetes prevalence's are likely to have.
Collapse
Affiliation(s)
- T Norris
- Institute of Sport, Exercise and Health, Division of Surgery & Interventional Science, University College London, London, UK
| | - W Johnson
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - R Cooper
- AGE Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne NHS Foundation Trust, Newcastle, UK
| | - S M Pinto Pereira
- Institute of Sport, Exercise and Health, Division of Surgery & Interventional Science, University College London, London, UK.
| |
Collapse
|
14
|
Chandrasekar R, Lacey RE, Chaturvedi N, Hughes AD, Patalay P, Khanolkar AR. Adverse childhood experiences and the development of multimorbidity across adulthood-a national 70-year cohort study. Age Ageing 2023; 52:afad062. [PMID: 37104379 PMCID: PMC10137110 DOI: 10.1093/ageing/afad062] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 02/16/2023] [Indexed: 04/28/2023] Open
Abstract
AIM To examine impact of adverse childhood experiences (ACE) on rates and development of multimorbidity across three decades in adulthood. METHODS Sample: Participants from the 1946 National Survey of Health and Development, who attended the age 36 assessment in 1982 and follow-up assessments (ages 43, 53, 63, 69; N = 3,264, 51% males). Prospectively collected data on nine ACEs was grouped into (i) psychosocial, (ii) parental health and (iii) childhood health. For each group, we calculated cumulative ACE scores, categorised into 0, 1 and ≥2 ACEs. Multimorbidity was estimated as the total score of 18 health disorders.Serial cross-sectional linear regression was used to estimate associations between grouped ACEs and multimorbidity during follow-up. Longitudinal analysis of ACE-associated changes in multimorbidity trajectories across follow-up was estimated using linear mixed-effects modelling for ACE groups (adjusted for sex and childhood socioeconomic circumstances). FINDINGS Accumulation of psychosocial and childhood health ACEs were associated with progressively higher multimorbidity scores throughout follow-up. For example, those with ≥2 psychosocial ACEs experienced 0.20(95% CI 0.07, 0.34) more disorders at age 36 than those with none, rising to 0.61(0.18, 1.04) disorders at age 69.All three grouped ACEs were associated with greater rates of accumulation and higher multimorbidity trajectories across adulthood. For example, individuals with ≥2 psychosocial ACEs developed 0.13(-0.09, 0.34) more disorders between ages 36 and 43, 0.29(0.06, 0.52) disorders between ages 53 and 63, and 0.30(0.09, 0.52) disorders between ages 63 and 69 compared with no psychosocial ACEs. INTERPRETATIONS ACEs are associated with widening inequalities in multimorbidity development in adulthood and early old age. Public health policies should aim to reduce these disparities through individual and population-level interventions.
Collapse
Affiliation(s)
| | - Rebecca E Lacey
- Research Department of Epidemiology and Public Health, University College London, London WC1E 7HB, UK
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing at University College London, London WC1E 7HB, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at University College London, London WC1E 7HB, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing at University College London, London WC1E 7HB, UK
- Centre for Longitudinal Studies, University College London Social Research Institute, London WC1H 0AL, UK
| | - Amal R Khanolkar
- MRC Unit for Lifelong Health and Ageing at University College London, London WC1E 7HB, UK
- Department of Population Health Sciences, King’s College London, London SE1 1UL, UK
| |
Collapse
|
15
|
Milk intake across adulthood and muscle strength decline from mid- to late life: the MRC National Survey of Health and Development. Br J Nutr 2023; 129:820-831. [PMID: 35795912 PMCID: PMC9975781 DOI: 10.1017/s0007114522001799] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Milk is a source of several nutrients which may be beneficial for skeletal muscle. Evidence that links lower milk intake with declines in muscle strength from midlife to old age is lacking. We used data from the Medical Research Council National Survey of Health and Development to test sex-specific associations between milk consumption from age 36 to 60-64 years, low grip strength (GS) or probable sarcopenia, and GS decline from age 53 to 69 years. We included 1340 men and 1383 women with at least one measure of both milk intake and GS. Milk intake was recorded in 5-d food diaries (aged 36, 43, 53 and 60-64 years), and grand mean of total, reduced-fat and full-fat milk each categorised in thirds (T1 (lowest) to T3 (highest), g/d). GS was assessed at ages 53, 60-64, and 69 years, and probable sarcopenia classified at the age of 69 years. We employed logistic regression to examine the odds of probable sarcopenia and multilevel models to investigate decline in GS in relation to milk intake thirds. Compared with T1, only T2 (58·76-145·25 g/d) of reduced-fat milk was associated with lower odds of sex-specific low GS at the age of 69 years (OR (95 % CI): 0·59 (0·37, 0·94), P = 0·03). In multilevel models, only T3 of total milk (≥ 237·52 g/d) was associated with stronger GS in midlife in men (β (95 % CI) = 1·82 (0·18, 3·45) kg, P = 0·03) compared with T1 (≤ 152·0 g/d), but not with GS decline over time. A higher milk intake across adulthood may promote muscle strength in midlife in men. Its role in muscle health in late life needs further examination.
Collapse
|
16
|
James SN, Nicholas JM, Lu K, Keshavan A, Lane CA, Parker T, Buchanan SM, Keuss SE, Murray-Smith H, Wong A, Cash DM, Malone IB, Barnes J, Sudre CH, Coath W, Modat M, Ourselin S, Crutch SJ, Kuh D, Fox NC, Schott JM, Richards M. Adulthood cognitive trajectories over 26 years and brain health at 70 years of age: findings from the 1946 British Birth Cohort. Neurobiol Aging 2023; 122:22-32. [PMID: 36470133 PMCID: PMC10564626 DOI: 10.1016/j.neurobiolaging.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 10/06/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022]
Abstract
Few studies can address how adulthood cognitive trajectories relate to brain health in 70-year-olds. Participants (n = 468, 49% female) from the 1946 British birth cohort underwent 18F-Florbetapir PET/MRI. Cognitive function was measured in childhood (age 8 years) and across adulthood (ages 43, 53, 60-64 and 69 years) and was examined in relation to brain health markers of β-amyloid (Aβ) status, whole brain and hippocampal volume, and white matter hyperintensity volume (WMHV). Taking into account key contributors of adult cognitive decline including childhood cognition, those with greater Aβ and WMHV at age 70 years had greater decline in word-list learning memory in the preceding 26 years, particularly after age 60. In contrast, those with smaller whole brain and hippocampal volume at age 70 years had greater decline in processing search speed, subtly manifest from age 50 years. Subtle changes in memory and processing speed spanning 26 years of adulthood were associated with markers of brain health at 70 years of age, consistent with detectable prodromal cognitive effects in early older age.
Collapse
Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK.
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, UK; Department of Medicine, Division of Brain Sciences, Imperial College London
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastien Ourselin
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
17
|
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] [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.
Collapse
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
| |
Collapse
|
18
|
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: 1.0] [Reference Citation Analysis] [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.
Collapse
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
| |
Collapse
|
19
|
Richards M. The Power of Birth Cohorts to Study Risk Factors for Cognitive Impairment. Curr Neurol Neurosci Rep 2022; 22:847-854. [PMID: 36350423 PMCID: PMC9643995 DOI: 10.1007/s11910-022-01244-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/16/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE OF REVIEW Birth cohorts are studies of people the same time; some of which have continuously followed participants across the life course. These are powerful designs for studying predictors of age-related outcomes, especially when information on predictors is collected before these outcomes are known. This article reviews recent findings from these cohorts for the outcomes of cognitive function, cognitive impairment, and risk of dementia, in relation to prior cognitive function, and social and biological predictors. RECENT FINDINGS Cognitive function and impairment are predicted by a wide range of factors, including childhood cognition, education, occupational status and complexity, and biological factors, including genetic and epigenetic. The particular importance of high and rising blood pressure in midlife is highlighted, with some insight into brain mechanisms involved. Some limitations are noted, including sources of bias in the data. Despite these limitations, birth cohorts have provided valuable insights into factors across the life course associated with cognitive impairment.
Collapse
Affiliation(s)
- Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
| |
Collapse
|
20
|
Almeida-Meza P, Richards M, Cadar D. Moderating Role of Cognitive Reserve Markers Between Childhood Cognition and Cognitive Aging: Evidence From the 1946 British Birth Cohort. Neurology 2022; 99:e1239-e1250. [PMID: 35922143 PMCID: PMC9576292 DOI: 10.1212/wnl.0000000000200928] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/19/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES As the population ages, differences in cognitive abilities become more evident. We investigated key genetic and life course influences on cognitive state at age 69 years, building on previous work using the longitudinal Medical Research Council National Survey of Health and Development (the British 1946 birth cohort). METHODS Multivariable regressions investigated the association between 4 factors: (1) childhood cognition at age 8 years; (2) a Cognitive Reserve Index (CRI) composed of 3 markers: (i) educational attainment by age 26 years, (ii) engagement in leisure activities at age 43 years, and (iii) occupation up to age 53 years; (3) reading ability assessed by the National Adult Reading Test (NART) at age 53 years; and (4) APOE genotype in relation to cognitive state measured at age 69 years with Addenbrooke's Cognitive Examination, third edition (ACE-III). We then investigated the modifying role of the CRI, NART, and APOE in the association between childhood cognition and the ACE-III. RESULTS The analytical sample comprised 1,184 participants. Higher scores in childhood cognition, CRI, and NART were associated with higher scores in the ACE-III. We found that the CRI and NART modified the association between childhood cognition and the ACE-III: for 30 additional points in the CRI or 20 additional points in the NART, the simple slope of childhood cognition decreased by approximately 0.10 points (CRI = 70: marginal effects (MEs) 0.22, 95% CI 0.12-0.32, p < 0.001 vs CRI = 100: MEs 0.12, 95% CI 0.06-0.17, p < 0.001; NART = 15: MEs 0.22, 95% CI 0.09-0.35, p = 0.001, vs NART = 35: MEs 0.11, 95% CI 0.05-0.17, p < 0.001). The association between childhood cognition and the ACE-III was nonsignificant at high levels of the CRI or NART. Furthermore, the e4 allele of the APOE gene was associated with lower scores in the ACE-III (β = -0.71, 95% CI -1.36 to -0.06, p = 0.03) but did not modify the association between childhood cognition and cognitive state in later life. DISCUSSION The CRI and NART are independent measures of cognitive reserve because both modify the association between childhood cognition and cognitive state.
Collapse
Affiliation(s)
- Pamela Almeida-Meza
- From the Department of Behavioural Science and Health (P.A.-M., D.C.), University College London; MRC Unit for Lifelong Health and Ageing, University College London; and Centre for Dementia Studies (D.C.), Department of Neuroscience, Brighton and Sussex Medical School, UK.
| | - Marcus Richards
- From the Department of Behavioural Science and Health (P.A.-M., D.C.), University College London; MRC Unit for Lifelong Health and Ageing, University College London; and Centre for Dementia Studies (D.C.), Department of Neuroscience, Brighton and Sussex Medical School, UK
| | - Dorina Cadar
- From the Department of Behavioural Science and Health (P.A.-M., D.C.), University College London; MRC Unit for Lifelong Health and Ageing, University College London; and Centre for Dementia Studies (D.C.), Department of Neuroscience, Brighton and Sussex Medical School, UK
| |
Collapse
|
21
|
Hostettler IC, Seiffge D, Wong A, Ambler G, Wilson D, Shakeshaft C, Banerjee G, Sharma N, Jäger HR, Cohen H, Yousry TA, Al-Shahi Salman R, Lip GYH, Brown MM, Muir K, Houlden H, Werring DJ. APOE and Cerebral Small Vessel Disease Markers in Patients With Intracerebral Hemorrhage. Neurology 2022; 99:e1290-e1298. [PMID: 36123141 PMCID: PMC9576291 DOI: 10.1212/wnl.0000000000200851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 04/28/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE We investigated the associations between the APOE genotype, intracerebral hemorrhage (ICH), and neuroimaging markers of cerebral amyloid angiopathy (CAA). METHODS We included patients from a prospective, multicenter UK observational cohort study of patients with ICH and representative UK population controls. First, we assessed the association of the APOE genotype with ICH (compared with controls without ICH). Second, among patients with ICH, we assessed the association of APOE status with the hematoma location (lobar or deep) and brain CT markers of CAA (finger-like projections [FLP] and subarachnoid extension [SAE]). RESULTS We included 907 patients with ICH and 2,636 controls. The mean age was 73.2 (12.4 SD) years for ICH cases vs 69.6 (0.2 SD) for population controls; 50.3% of cases and 42.1% of controls were female. Compared with controls, any APOE ε2 allele was associated with all ICH (lobar and nonlobar) and lobar ICH on its own in the dominant model (OR 1.38, 95% CI 1.13-1.7, p = 0.002 and OR 1.50, 95% CI 1.1-2.04, p = 0.01, respectively) but not deep ICH in an age-adjusted analyses (OR 1.26, 95% CI 0.97-1.63, p = 0.08). In the cases-only analysis, the APOE ε4 allele was associated with lobar compared with deep ICH in an age-adjusted analyses (OR 1.56, 95% CI 1.1-2.2, p = 0.01). When assessing CAA markers, APOE alleles were independently associated with FLP (ε4: OR 1.74, 95% CI 1.04-2.93, p = 0.04 and ε2/ε4: 2.56, 95% CI 0.99-6.61, p = 0.05). We did not find an association between APOE alleles and SAE. DISCUSSION We confirmed associations between APOE alleles and ICH including lobar ICH. Our analysis shows selective associations between APOE ε2 and ε4 alleles with FLP, a CT marker of CAA. Our findings suggest that different APOE alleles might have diverging influences on individual neuroimaging biomarkers of CAA-associated ICH.
Collapse
Affiliation(s)
- Isabel Charlotte Hostettler
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - David Seiffge
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Andrew Wong
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Gareth Ambler
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Duncan Wilson
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Clare Shakeshaft
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Gargi Banerjee
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Nikhil Sharma
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Hans Rolf Jäger
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Hannah Cohen
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Tarek A Yousry
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Rustam Al-Shahi Salman
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Gregory Y H Lip
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Martin M Brown
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Keith Muir
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - Henry Houlden
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK
| | - David J Werring
- From the Stroke Research Centre (I.C.H., D.S., Duncan Wilson, C.S., G.B., M.M.B., David Werring), University College London, Institute of Neurology; Neurogenetics Laboratory (I.C.H., H.H.), The National Hospital of Neurology and Neurosurgery, London, UK; Department of Neurosurgery (I.C.H.), Cantonal Hospital St. Gallen, Switzerland; Stroke Centre (D.S.), Department of Neurology and Department of Clinical Research, University of Basel and University Hospital Basel; Department of Neurology and Stroke Centre (D.S.), University Hospital Berne; MRC Unit for Lifelong Health and Ageing at UCL (A.W.), London; Department of Statistical Science (G.A.), UCL, London; Department of Clinical and Movement Neuroscience (N.S.), Institute of Neurology, London; Neuroradiological Academic Unit (H.R.J., T.A.Y.), Department of Brain Repair & Rehabilitation, University College London, Institute of Neurology; Haemostasis Research Unit (H.C.), Department of Haematology, University College London; Centre for Clinical Brain Sciences (R.A.-S.S.), School of Clinical Sciences, University of Edinburgh; Liverpool Centre for Cardiovascular Science (G.Y.H.L.), University of Liverpool and Liverpool Heart & Chest Hospital; Department of Clinical Medicine (G.Y.H.L.), Aalborg University, Denmark; and Institute of Neuroscience & Psychology (K.M.), University of Glasgow, Queen Elizabeth University Hospital, UK.
| |
Collapse
|
22
|
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: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [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.
Collapse
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.
| |
Collapse
|
23
|
Keuss SE, Coath W, Nicholas JM, Poole T, Barnes J, Cash DM, Lane CA, Parker TD, Keshavan A, Buchanan SM, Wagen AZ, Storey M, Harris M, Malone IB, Sudre CH, Lu K, James SN, Street R, Thomas DL, Dickson JC, Murray-Smith H, Wong A, Freiberger T, Crutch S, Richards M, Fox NC, Schott JM. Associations of β-Amyloid and Vascular Burden With Rates of Neurodegeneration in Cognitively Normal Members of the 1946 British Birth Cohort. Neurology 2022; 99:e129-e141. [PMID: 35410910 PMCID: PMC9280996 DOI: 10.1212/wnl.0000000000200524] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 03/01/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The goals of this work were to quantify the independent and interactive associations of β-amyloid (Aβ) and white matter hyperintensity volume (WMHV), a marker of presumed cerebrovascular disease (CVD), with rates of neurodegeneration and to examine the contributions of APOE ε4 and vascular risk measured at different stages of adulthood in cognitively normal members of the 1946 British Birth Cohort. METHODS Participants underwent brain MRI and florbetapir-Aβ PET as part of Insight 46, an observational population-based study. Changes in whole-brain, ventricular, and hippocampal volume were directly measured from baseline and repeat volumetric T1 MRI with the boundary shift integral. Linear regression was used to test associations with baseline Aβ deposition, baseline WMHV, APOE ε4, and office-based Framingham Heart Study Cardiovascular Risk Score (FHS-CVS) and systolic blood pressure (BP) at ages 36, 53, and 69 years. RESULTS Three hundred forty-six cognitively normal participants (mean [SD] age at baseline scan 70.5 [0.6] years; 48% female) had high-quality T1 MRI data from both time points (mean [SD] scan interval 2.4 [0.2] years). Being Aβ positive at baseline was associated with 0.87-mL/y faster whole-brain atrophy (95% CI 0.03, 1.72), 0.39-mL/y greater ventricular expansion (95% CI 0.16, 0.64), and 0.016-mL/y faster hippocampal atrophy (95% CI 0.004, 0.027), while each 10-mL additional WMHV at baseline was associated with 1.07-mL/y faster whole-brain atrophy (95% CI 0.47, 1.67), 0.31-mL/y greater ventricular expansion (95% CI 0.13, 0.60), and 0.014-mL/y faster hippocampal atrophy (95% CI 0.006, 0.022). These contributions were independent, and there was no evidence that Aβ and WMHV interacted in their effects. There were no independent associations of APOE ε4 with rates of neurodegeneration after adjustment for Aβ status and WMHV, no clear relationships between FHS-CVS or systolic BP and rates of neurodegeneration when assessed across the whole sample, and no evidence that FHS-CVS or systolic BP acted synergistically with Aβ. DISCUSSION Aβ and presumed CVD have distinct and additive effects on rates of neurodegeneration in cognitively normal elderly. These findings have implications for the use of MRI measures as biomarkers of neurodegeneration and emphasize the importance of risk management and early intervention targeting both pathways.
Collapse
Affiliation(s)
- Sarah E Keuss
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - William Coath
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Jennifer M Nicholas
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Teresa Poole
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Josephine Barnes
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - David M Cash
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Christopher A Lane
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Thomas D Parker
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Ashvini Keshavan
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sarah M Buchanan
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Aaron Z Wagen
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Mathew Storey
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Matthew Harris
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Ian B Malone
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Carole H Sudre
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Kirsty Lu
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sarah-Naomi James
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Rebecca Street
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - David L Thomas
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - John C Dickson
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Heidi Murray-Smith
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Andrew Wong
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Tamar Freiberger
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sebastian Crutch
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Marcus Richards
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Nick C Fox
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Jonathan M Schott
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK.
| |
Collapse
|
24
|
Thompson EJ, Ploubidis GB, Richards M, Gaysina D. Life course trajectories of affective symptoms and their early life predictors. LONGITUDINAL AND LIFE COURSE STUDIES : INTERNATIONAL JOURNAL 2022; 13:412-431. [PMID: 35920619 DOI: 10.1332/175795921x16487298020502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND Life course trajectories of affective symptoms (depression and anxiety) are heterogenous. However, few studies have investigated the role of early life risk factors in the development of these trajectories. The present study aimed to: (1) derive latent trajectories of affective symptoms over a period of more than 50 years (ages 13-69), and (2) examine early life risk factors for associations with specific life course trajectories of affective symptoms. METHOD Participants are from the MRC National Survey of Health and Development (NSHD) (n = 5,362). Affective symptoms were measured prospectively at ages 13, 15, 36, 43, 53, 60-64 and 69. A latent variable modelling framework was implemented to model longitudinal profiles of affective symptoms. Twenty-four prospectively measured early life predictors were tested for associations with different symptom profiles using multinomial logistic regression. RESULTS Four life course profiles of affective symptoms were identified: (1) absence of symptoms (66.6% of the sample); (2) adolescent symptoms with good adult outcome (15.2%); (3) adult symptoms only (with no symptoms in adolescence and late life) (12.9%); (4) symptoms in adolescence and mid adulthood (5.2%). Of the 24 early life predictors observed, only four were associated with life course trajectories, with small effect sizes observed. CONCLUSIONS People differ in their life course trajectories of anxiety and depression symptoms and that these differences are not largely influenced by early life factors tested in this study.
Collapse
|
25
|
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] [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.
Collapse
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
| | | |
Collapse
|
26
|
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: 1.3] [Reference Citation Analysis] [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).
Collapse
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.
| |
Collapse
|
27
|
Fatih N, Chaturvedi N, Lane CA, Parker TD, Lu K, Cash DM, Malone IB, Silverwood R, Wong A, Barnes J, Sudre CH, Richards M, Fox NC, Schott JM, Hughes A, James SN. Sex-related differences in whole brain volumes at age 70 in association with hyperglycemia during adult life. Neurobiol Aging 2022; 112:161-169. [PMID: 35183802 DOI: 10.1016/j.neurobiolaging.2021.09.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 09/01/2021] [Accepted: 09/04/2021] [Indexed: 01/19/2023]
Abstract
Longitudinal studies of the relationship between hyperglycemia and brain health are rare and there is limited information on sex differences in associations. We investigated whether glycosylated hemoglobin (HbA1c) measured at ages of 53, 60-64 and 69 years, and cumulative glycemic index (CGI), a measure of cumulative glycemic burden, were associated with metrics of brain health in later life. Participants were from Insight 46, a substudy of the Medical Research Council National Survey of Health and Development (NSHD) who undertook volumetric MRI, florbetapir amyloid-PET imaging and cognitive assessments at ages of 69-71. Analyses were performed using linear and logistic regression as appropriate, with adjustment for potential confounders. We observed a sex interaction between HbA1c and whole brain volume (WBV) at all 3 time points. Following stratification of our sample, we observed that HbA1c at all ages, and CGI were positively associated with lower WBV exclusively in females. HbA1c (or CGI) was not associated with amyloid status, white matter hyperintensities (WMHs), hippocampal volumes (HV) or cognitive outcomes in either sex. Higher HbA1c in adulthood is associated with smaller WBV at 69-71 years in females but not in males. This suggests that there may be preferential target organ damage in the brain for females with hyperglycemia.
Collapse
Affiliation(s)
- Nasrtullah Fatih
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom.
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Christopher A Lane
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Thomas D Parker
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Kirsty Lu
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - David M Cash
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Ian B Malone
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Richard Silverwood
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Josephine Barnes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Nick C Fox
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Alun Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| |
Collapse
|
28
|
Elizabeth HJ, Payling D. From cohort to community: The emotional work of birthday cards in the Medical Research Council National Survey of Health and Development, 1946-2018. HISTORY OF THE HUMAN SCIENCES 2022; 35:158-188. [PMID: 35103037 PMCID: PMC8795233 DOI: 10.1177/0952695121999283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The Medical Research Council National Survey of Health and Development (NSHD) is Britain's longest-running birth cohort study. From their birth in 1946 until the present day, its research participants, or study members, have filled out questionnaires and completed cognitive or physical examinations every few years. Among other outcomes, the findings of these studies have framed how we understand health inequalities. Throughout the decades and multiple follow-up studies, each year the study members have received a birthday card from the survey staff. Although the birthday cards were originally produced in 1962 as a method to record changes of address at a time when the adolescent study members were potentially leaving school and home, they have become more than that with time. The cards mark, and have helped create, an ongoing evolving relationship between the NSHD and the surveyed study members, eventually coming to represent a relationship between the study members themselves. This article uses the birthday cards alongside archival material from the NSHD and oral history interviews with survey staff to trace the history of the growing awareness of importance of emotion within British social science research communities over the course of the 20th and early 21st centuries. It documents changing attitudes to science's dependence on research participants, their well-being, and the collaborative nature of scientific research. The article deploys an intertextual approach to reading these texts alongside an attention to emotional communities drawing on the work of Barbara Rosenwein.
Collapse
|
29
|
Kaushal A, Stafford M, Cadar D, Richards M. Bi-directional associations between religious attendance and mental health: findings from a British birth cohort study. J Epidemiol Community Health 2022; 76:190-195. [PMID: 34353867 PMCID: PMC8762020 DOI: 10.1136/jech-2021-216943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/16/2021] [Indexed: 11/03/2022]
Abstract
BACKGROUND There is evidence that religious attendance is associated with positive outcomes for mental health; however, there are few longitudinal studies, and even fewer, which take into account the possibility of bi-directional associations. This study aimed to investigate bi-directional associations between religious attendance and mental health. METHODS Participants were 2125 study members who provided data at age 68-69 from the Medical Research Council National Survey of Health and Development (1946 British birth cohort study). Mental health was assessed using the 28-item General Health Questionnaire at ages 53, 60-64 and 68-69. Religious attendance was measured using a 4-point scale (weekly=3, monthly=2, less than monthly=1 or never=0) at ages 43, 60-64 and 68-69. Cross-lagged path analysis was used to assess reciprocal associations between mental health and religious attendance, adjusting for gender and education. RESULTS Previous religious attendance was strongly related to later attendance (r=0.62-0.74). Similarly, mental health at baseline was strongly associated with subsequent mental health scores (r=0.46-0.54). Poor mental health at age 53 and 60-64 was associated with more frequent religious attendance at age 60-64 (b=0.04; 95% CI: 0.02 to 0.06; p<0.05), and 68-69 (b=0.03; 95% CI: 0.02 to 0.06; p<0.05), respectively. There was no evidence that religious attendance at age 43, 60-64 or 68-69 was associated with later or concurrent mental health. CONCLUSION Using birth cohort data from the UK, it was found that poor mental health was associated with later religious attendance but not vice versa. Future research should confirm these novel findings and explore the underlying mechanisms between religious attendance and mental health.
Collapse
Affiliation(s)
- Aradhna Kaushal
- Research Department of Behavioural Science and Health, University College London, London, UK
| | | | - Dorina Cadar
- Research Department of Behavioural Science and Health, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
30
|
Richards M, James SN, Lu K, Livingston G, Schott JM, Lane CA, Barnes J, Parker TD, Sudre CH, Cash DM, Coath W, Fox N, Davis DHJ. Straight and Divergent Pathways to Cognitive State: Seven Decades of Follow-Up in the British 1946 Birth Cohort. J Alzheimers Dis 2022; 89:659-667. [PMID: 35964185 DOI: 10.3233/jad-220296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Using the British 1946 birth cohort we previously estimated life course paths to the Addenbrooke's Cognitive Examination (ACE-III). OBJECTIVE We now compared those whose ACE-III scores were expected, worse and better than predicted from the path model on a range of independent variables including clinical ratings of cognitive impairment and neuroimaging measures. METHODS Predicted ACE-III scores were categorized into three groups: those with Expected (between -1.5 and 1.5 standard deviation; SD); Worse (&lt; -1.5 SD); and Better (&gt;1.5 SD) scores. Differences in the independent variables were then tested between these three groups. RESULTS Compared with the Expected group, those in the Worse group showed independent evidence of progressive cognitive impairment: faster memory decline, more self-reported memory difficulties, more functional difficulties, greater likelihood of being independently rated by experienced specialist clinicians as having a progressive cognitive impairment, and a cortical thinning pattern suggestive of preclinical Alzheimer's disease. Those in the Better group showed slower verbal memory decline and absence of independently rated progressive cognitive impairment compared to the Expected group, but no differences in any of the other independent variables including the neuroimaging variables. CONCLUSION The residual approach shows that life course features can map directly to clinical diagnoses. One future challenge is to translate this into a readily usable algorithm to identify high-risk individuals in preclinical state, when preventive strategies and therapeutic interventions may be most effective.
Collapse
Affiliation(s)
- Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Sarah N James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, University College London, London, UK
| | - Gill Livingston
- Division of Psychiatry, University College London, London, UK
| | | | | | | | - Thomas D Parker
- Dementia Research Centre, University College London, London, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK.,Dementia Research Centre, University College London, London, UK.,Centre for Medical Image Computing, University College London, London, UK.,School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - David M Cash
- Dementia Research Centre, University College London, London, UK
| | - William Coath
- Dementia Research Centre, University College London, London, UK
| | - Nicholas Fox
- Dementia Research Centre, University College London, London, UK
| | - Daniel H J Davis
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
31
|
Green R, Lord J, Xu J, Maddock J, Kim M, Dobson R, Legido-Quigley C, Wong A, Richards M, Proitsi P. Metabolic correlates of late midlife cognitive outcomes: findings from the 1946 British Birth Cohort. Brain Commun 2021; 4:fcab291. [PMID: 35187482 PMCID: PMC8853724 DOI: 10.1093/braincomms/fcab291] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 09/17/2021] [Accepted: 12/10/2021] [Indexed: 11/14/2022] Open
Abstract
Investigating associations between metabolites and late midlife cognitive function could reveal potential markers and mechanisms relevant to early dementia. Here, we systematically explored the metabolic correlates of cognitive outcomes measured across the seventh decade of life, while untangling influencing life course factors. Using levels of 1019 metabolites profiled by liquid chromatography-mass spectrometry (age 60-64), we evaluated relationships between metabolites and cognitive outcomes in the British 1946 Birth Cohort (N = 1740). We additionally conducted pathway and network analyses to allow for greater insight into potential mechanisms, and sequentially adjusted for life course factors across four models, including sex and blood collection (Model 1), Model 1 + body mass index and lipid medication (Model 2), Model 2 + social factors and childhood cognition (Model 3) and Model 3 + lifestyle influences (Model 4). After adjusting for multiple tests, 155 metabolites, 10 pathways and 5 network modules were associated with cognitive outcomes. Of the 155, 35 metabolites were highly connected in their network module (termed 'hub' metabolites), presenting as promising marker candidates. Notably, we report relationships between a module comprised of acylcarnitines and processing speed which remained robust to life course adjustment, revealing palmitoylcarnitine (C16) as a hub (Model 4: β = -0.10, 95% confidence interval = -0.15 to -0.052, P = 5.99 × 10-5). Most associations were sensitive to adjustment for social factors and childhood cognition; in the final model, four metabolites remained after multiple testing correction, and 80 at P < 0.05. Two modules demonstrated associations that were partly or largely attenuated by life course factors: one enriched in modified nucleosides and amino acids (overall attenuation = 39.2-55.5%), and another in vitamin A and C metabolites (overall attenuation = 68.6-92.6%). Our other findings, including a module enriched in sphingolipid pathways, were entirely explained by life course factors, particularly childhood cognition and education. Using a large birth cohort study with information across the life course, we highlighted potential metabolic mechanisms associated with cognitive function in late midlife, suggesting marker candidates and life course relationships for further study.
Collapse
Affiliation(s)
- Rebecca Green
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
| | - Jodie Lord
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Jin Xu
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Institute of Pharmaceutical Science, King’s College London, London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | - Min Kim
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
- Health Data Research UK London, University College London, London, UK
- NIHR Biomedical Research Centre at University College London, Hospitals NHS Foundation Trust, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King’s College London, London, UK
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| |
Collapse
|
32
|
Lu K, Nicholas JM, Pertzov Y, Grogan J, Husain M, Pavisic IM, James SN, Parker TD, Lane CA, Keshavan A, Keuss SE, Buchanan SM, Murray-Smith H, Cash DM, Malone IB, Sudre CH, Coath W, Wong A, Henley SM, Fox NC, Richards M, Schott JM, Crutch SJ. Dissociable effects of APOE-ε4 and β-amyloid pathology on visual working memory. NATURE AGING 2021; 1:1002-1009. [PMID: 34806027 PMCID: PMC7612005 DOI: 10.1038/s43587-021-00117-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 08/17/2021] [Indexed: 01/21/2023]
Abstract
Although APOE-ε4 carriers are at significantly higher risk of developing Alzheimer's disease than non-carriers1, controversial evidence suggests that APOE-ε4 might confer some advantages, explaining the survival of this gene (antagonistic pleiotropy)2,3. In a population-based cohort born in one week in 1946 (assessed aged 69-71), we assessed differential effects of APOE-ε4 and β-amyloid pathology (quantified using 18F-Florbetapir-PET) on visual working memory (object-location binding). In 398 cognitively normal participants, APOE-ε4 and β-amyloid had opposing effects on object identification, predicting better and poorer recall respectively. ε4-carriers also recalled locations more precisely, with a greater advantage at higher β-amyloid burden. These results provide evidence of superior visual working memory in ε4-carriers, showing that some benefits of this genotype are demonstrable in older age, even in the preclinical stages of Alzheimer's disease.
Collapse
Affiliation(s)
- Kirsty Lu
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jennifer M. Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Yoni Pertzov
- Department of Psychology, The Hebrew University of Jerusalem, Israel
| | - John Grogan
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK
- Department of Experimental Psychology, University of Oxford, UK
| | - Ivanna M. Pavisic
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Thomas D. Parker
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher A. Lane
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E. Keuss
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah M. Buchanan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David M. Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B. Malone
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H. Sudre
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - William Coath
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Susie M.D. Henley
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Nick C. Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Jonathan M. Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sebastian J. Crutch
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| |
Collapse
|
33
|
Pavisic IM, Lu K, Keuss SE, James SN, Lane CA, Parker TD, Keshavan A, Buchanan SM, Murray-Smith H, Cash DM, Coath W, Wong A, Fox NC, Crutch SJ, Richards M, Schott JM. Subjective cognitive complaints at age 70: associations with amyloid and mental health. J Neurol Neurosurg Psychiatry 2021; 92:1215-1221. [PMID: 34035132 PMCID: PMC8522456 DOI: 10.1136/jnnp-2020-325620] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/08/2021] [Accepted: 04/28/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To investigate subjective cognitive decline (SCD) in relation to β-amyloid pathology and to test for associations with anxiety, depression, objective cognition and family history of dementia in the Insight 46 study. METHODS Cognitively unimpaired ~70-year-old participants, all born in the same week in 1946 (n=460, 49% female, 18% amyloid-positive), underwent assessments including the SCD-Questionnaire (MyCog). MyCog scores were evaluated with respect to 18F-Florbetapir-PET amyloid status (positive/negative). Associations with anxiety, depression, objective cognition (measured by the Preclinical Alzheimer Cognitive Composite, PACC) and family history of dementia were also investigated. The informant's perspective on SCD was evaluated in relation to MyCog score. RESULTS Anxiety (mean (SD) trait anxiety score: 4.4 (3.9)) was associated with higher MyCog scores, especially in women. MyCog scores were higher in amyloid-positive compared with amyloid-negative individuals (adjusted means (95% CIs): 5.3 (4.4 to 6.1) vs 4.3 (3.9 to 4.7), p=0.044), after accounting for differences in anxiety. PACC (mean (SD) -0.05 (0.68)) and family history of dementia (prevalence: 23.9%) were not independently associated with MyCog scores. The informant's perception of SCD was generally in accordance with that of the participant. CONCLUSIONS This cross-sectional study demonstrates that symptoms of SCD are associated with both β-amyloid pathology, and more consistently, trait anxiety in a population-based cohort of older adults, at an age when those who are destined to develop dementia are still likely to be some years away from symptoms. This highlights the necessity of considering anxiety symptoms when assessing Alzheimer's disease pathology and SCD.
Collapse
Affiliation(s)
- Ivanna M Pavisic
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah-Naomi James
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - William Coath
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| |
Collapse
|
34
|
John A, Rusted J, Richards M, Gaysina D. Bidirectional relation between affective symptoms and cognitive function from middle to late adulthood: a population-based birth cohort study. Aging Ment Health 2021; 25:1642-1648. [PMID: 32363904 DOI: 10.1080/13607863.2020.1758916] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 04/13/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVES There is an association between affective symptoms and cognition. However, the direction of this association remains unclear. This study aimed to test bidirectional relationships between affective symptoms and cognition from middle to late adulthood. METHOD Data were available from the MRC National Survey of Health and Development (NSHD), a prospective birth cohort of 5362 people born in 1946. Affective symptoms and cognition were measured at ages 53, 60-64, and 69. Latent scores of affective symptoms were derived and cross-lagged models were fitted for affective symptoms with verbal memory and processing speed. RESULTS Results revealed an inverse cross-sectional association between affective symptoms and verbal memory (β=-0.18, SE=0.04, p<.001) and processing speed (β=-0.13, SE=0.06, p=.05) at age 53, but not at ages 60-64 or 69. Affective symptoms at age 53 predicted lower verbal memory at age 60-64 (β=-0.58, SE=0.27, p=.03), and affective symptoms at age 60-64 predicted lower verbal memory (β=-0.64, SE=0.29, p=.03) and processing speed (β=-1.27, SE=0.41, p=.002) at age 69. Verbal memory and processing speed did not predict subsequent affective symptoms. CONCLUSION Affective symptoms predict poorer verbal memory and processing speed over a period of 16 years, but not vice versa.
Collapse
Affiliation(s)
- Amber John
- EDGE Lab, School of Psychology, University of Sussex, Brighton, UK
| | | | | | - Darya Gaysina
- EDGE Lab, School of Psychology, University of Sussex, Brighton, UK
| |
Collapse
|
35
|
Dercon Q, Nicholas JM, James SN, Schott JM, Richards M. Grip strength from midlife as an indicator of later-life brain health and cognition: evidence from a British birth cohort. BMC Geriatr 2021; 21:475. [PMID: 34465287 PMCID: PMC8406895 DOI: 10.1186/s12877-021-02411-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/10/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Grip strength is an indicator of physical function with potential predictive value for health in ageing populations. We assessed whether trends in grip strength from midlife predicted later-life brain health and cognition. METHODS 446 participants in an ongoing British birth cohort study, the National Survey of Health and Development (NSHD), had their maximum grip strength measured at ages 53, 60-64, and 69, and subsequently underwent neuroimaging as part of a neuroscience sub-study, referred to as "Insight 46", at age 69-71. A group-based trajectory model identified latent groups of individuals in the whole NSHD cohort with below- or above-average grip strength over time, plus a reference group. Group assignment, plus standardised grip strength levels and change from midlife were each related to measures of whole-brain volume (WBV) and white matter hyperintensity volume (WMHV), plus several cognitive tests. Models were adjusted for sex, body size, head size (where appropriate), sociodemographics, and behavioural and vascular risk factors. RESULTS Lower grip strength from midlife was associated with smaller WBV and lower matrix reasoning scores at age 69-71, with findings consistent between analysis of individual time points and analysis of trajectory groups. There was little evidence of an association between grip strength and other cognitive test scores. Although greater declines in grip strength showed a weak association with higher WMHV at age 69-71, trends in the opposite direction were seen at individual time points with higher grip strength at ages 60-64, and 69 associated with higher WMHV. CONCLUSIONS This study provides preliminary evidence that maximum grip strength may have value in predicting brain health. Future work should assess to what extent age-related declines in grip strength from midlife reflect concurrent changes in brain structure.
Collapse
Affiliation(s)
- Quentin Dercon
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.
| | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| |
Collapse
|
36
|
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: 0.5] [Reference Citation Analysis] [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.
Collapse
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
| |
Collapse
|
37
|
Stewart S, Robertson C, Kennedy S, Kavanagh K, Haahr L, Manoukian S, Mason H, Dancer S, Cook B, Reilly J. Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection. J Hosp Infect 2021; 114:32-42. [PMID: 34301394 DOI: 10.1016/j.jhin.2021.03.032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 02/22/2021] [Accepted: 03/25/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND Few healthcare-associated infection (HAI) studies focus on risk of HAI at the point of admission. Understanding this will enable planning and management of care with infection prevention at the heart of the patient journey from the point of admission. AIM To determine intrinsic characteristics of patients at hospital admission and extrinsic events, during the two years preceding admission, that increase risk of developing HAI. METHODS An incidence survey of adults within two hospitals in NHS Scotland was undertaken for one year in 2018/19 as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. The primary outcome measure was developing any HAI using recognized case definitions. The cohort was derived from routine hospital episode data and linkage to community dispensed prescribing data. FINDINGS The risk factors present on admission observed as being the most significant for the acquisition of HAI were: being treated in a teaching hospital, increasing age, comorbidities of cancer, cardiovascular disease, chronic renal failure and diabetes; and emergency admission. Relative risk of developing HAI increased with intensive care unit, high-dependency unit, and surgical specialties, and surgery <30 days before admission and a total length of stay of >30 days in the two years to admission. CONCLUSION Targeting patients at risk of HAI from the point of admission maximizes the potential for prevention, especially when extrinsic risk factors are known and managed. This study proposes a new approach to infection prevention and control (IPC), identifying those patients at greatest risk of developing a particular type of HAI who might be potential candidates for personalized IPC interventions.
Collapse
Affiliation(s)
- S Stewart
- Safeguarding Health through Infection Prevention Research Group, Research Centre for Health (ReaCH), Glasgow Caledonian University, Glasgow, UK.
| | - C Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
| | | | - K Kavanagh
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
| | - L Haahr
- Safeguarding Health through Infection Prevention Research Group, Research Centre for Health (ReaCH), Glasgow Caledonian University, Glasgow, UK
| | - S Manoukian
- Yunus Centre for Social Business and Health, Glasgow Caledonian University, Glasgow, UK
| | - H Mason
- Yunus Centre for Social Business and Health, Glasgow Caledonian University, Glasgow, UK
| | - S Dancer
- Department of Microbiology, Hairmyres Hospital, NHS Lanarkshire, UK; School of Applied Science, Edinburgh Napier University, Edinburgh, UK
| | - B Cook
- Departments of Anaesthesia and Critical Care, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - J Reilly
- Safeguarding Health through Infection Prevention Research Group, Research Centre for Health (ReaCH), Glasgow Caledonian University, Glasgow, UK; National Services Scotland (NSS), UK
| |
Collapse
|
38
|
Jacobsen E, Ran X, Liu A, Chang CCH, Ganguli M. Predictors of attrition in a longitudinal population-based study of aging. Int Psychogeriatr 2021; 33:767-778. [PMID: 32301414 PMCID: PMC7572515 DOI: 10.1017/s1041610220000447] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Longitudinal studies predictably experience non-random attrition over time. Among older adults, risk factors for attrition may be similar to risk factors for outcomes such as cognitive decline and dementia, potentially biasing study results. OBJECTIVE To characterize participants lost to follow-up which can be useful in the study design and interpretation of results. METHODS In a longitudinal aging population study with 10 years of annual follow-up, we characterized the attrited participants (77%) compared to those who remained in the study. We used multivariable logistic regression models to identify attrition predictors. We then implemented four machine learning approaches to predict attrition status from one wave to the next and compared the results of all five approaches. RESULTS Multivariable logistic regression identified those more likely to drop out as older, male, not living with another study participant, having lower cognitive test scores and higher clinical dementia ratings, lower functional ability, fewer subjective memory complaints, no physical activity, reported hobbies, or engagement in social activities, worse self-rated health, and leaving the house less often. The four machine learning approaches using areas under the receiver operating characteristic curves produced similar discrimination results to the multivariable logistic regression model. CONCLUSIONS Attrition was most likely to occur in participants who were older, male, inactive, socially isolated, and cognitively impaired. Ignoring attrition would bias study results especially when the missing data might be related to the outcome (e.g. cognitive impairment or dementia). We discuss possible solutions including oversampling and other statistical modeling approaches.
Collapse
Affiliation(s)
- Erin Jacobsen
- University of Pittsburgh, School of Medicine, Department of Psychiatry
| | - Xinhui Ran
- University of Pittsburgh, Graduate School of Public Health, Department of Biostatistics
| | - Anran Liu
- University of Pittsburgh, Graduate School of Public Health, Department of Biostatistics
| | - Chung-Chou H Chang
- University of Pittsburgh, Graduate School of Public Health, Department of Biostatistics
- University of Pittsburgh, School of Medicine, Department of Medicine
| | - Mary Ganguli
- University of Pittsburgh, School of Medicine, Department of Psychiatry
- University of Pittsburgh, Graduate School of Public Health, Department of Epidemiology
- University of Pittsburgh, School of Medicine, Department of Neurology
| |
Collapse
|
39
|
Intrauterine Exposures and Maternal Health Status during Pregnancy in Relation to Later Child Health: A Review of Pregnancy Cohort Studies in Europe. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18147702. [PMID: 34300152 PMCID: PMC8307645 DOI: 10.3390/ijerph18147702] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 07/16/2021] [Accepted: 07/18/2021] [Indexed: 12/18/2022]
Abstract
We show a description of pregnancy cohorts in the European region. Our investigation identified 66 pregnancy cohorts, mostly hosted in Western Central Europe. Among these 66 cohorts, 24 began recruitment before the year 2000, while six cohorts are still enrolling. The most common topics were lifestyle, environment and nutrition with allergies and neurodevelopment being a minority. We observed a pattern of positive correlations between data collected using medical records, structured interviews, and the collection of biological samples. Objectively assessed data were negatively correlated with self-administered questionnaires. Eight cohorts addressed intrauterine exposure, focusing on environmental pollutants such as endocrine-disrupting chemicals. The effects of these compounds on the developing foetus have been studied greatly, but more research on their effects is still needed. Many cohorts investigated genetics through the collection of biological samples from the mothers and children, to improve knowledge on the mother-to-child transmission of genetic information, antibodies, microbiota, etc. Paediatric epidemiology represents an important field of research since preserving healthy lives from conception onwards is the most efficient way to improve population health. According to our report, it seems that this field of research is well developed in Europe, where numerous high profile studies are currently ongoing.
Collapse
|
40
|
John A, Stott J, Richards M. Childhood reading problems and cognitive ageing across mid to later life. J Epidemiol Community Health 2021; 76:67-74. [PMID: 34230218 PMCID: PMC8666812 DOI: 10.1136/jech-2020-215735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 06/07/2021] [Indexed: 11/25/2022]
Abstract
Background Little research has investigated long-term associations of childhood reading with cognitive ageing. The aim of this study was to test longitudinal associations between childhood reading problems and cognitive function from mid-adulthood (age 43) to early old age (age 69), and whether associations were mediated by education. Methods Data were from the MRC National Survey of Health and Development, a prospective population-based birth cohort. Reading problems were measured at age 11 using a reading test. Verbal memory and processing speed were measured at ages 43, 53, 60–64 and 69 and Addenbrooke’s Cognitive Examination (ACE) was administered at age 69. Linear mixed models and path analyses were used to test: (1) associations between reading problems and verbal memory and processing speed trajectories; (2) associations between reading problems and ACE-III scores; (3) whether associations were mediated by education. Results Reading problems were associated with poorer verbal memory at intercept but not rate of decline (N=1726), and were not associated with processing speed intercept or decline (N=1730). There were higher rates of scores below ACE-III clinical thresholds (<82 and <88) in people with reading problems compared with those without. Reading problems were associated with poorer total ACE-III scores and all domain scores at age 69 (N=1699). Associations were partly mediated by education. Conclusion Reading problems in childhood were associated with poorer cognitive function in early old age, and associations were partly mediated by education.
Collapse
Affiliation(s)
- Amber John
- ADAPT Lab, Research Department of Clinical, Educational, and Health Psychology, UCL, London, UK
| | - Josh Stott
- ADAPT Lab, Research Department of Clinical, Educational, and Health Psychology, UCL, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, UCL, London, UK
| |
Collapse
|
41
|
Fattore G, Federici C, Drummond M, Mazzocchi M, Detzel P, Hutton ZV, Shankar B. Economic evaluation of nutrition interventions: Does one size fit all? Health Policy 2021; 125:1238-1246. [PMID: 34243979 DOI: 10.1016/j.healthpol.2021.06.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 06/14/2021] [Accepted: 06/24/2021] [Indexed: 11/19/2022]
Abstract
BACKGROUND Nutrition interventions have specific features that might warrant modifications to the methods used for economic evaluations of healthcare interventions. AIM The aim of the article is to identify these features and when they challenge the use of cost-utility analysis (CUA). METHODS A critical review of the literature is conducted and a 2 by 2 classification matrix for nutrition interventions is proposed based on 1) who the main party responsible for the implementation and funding of the intervention is; and 2) who the target recipient of the intervention is. The challenges of conducting economic evaluations for each group of nutrition interventions are then analysed according to four main aspects: attribution of effects, measuring and valuing outcomes, inter-sectorial costs and consequences and equity considerations. RESULTS AND CONCLUSIONS CUA is appropriate for nutrition interventions when they are funded from the healthcare sector, have no (or modest) spill-overs to other sectors of the economy and have only (or mainly) health consequences. For other interventions, typically involving different government agencies, with cost implications for the private sector, with important wellbeing consequences outside health and with heterogeneous welfare effects across socio-economic groups, other economic evaluation methods need to be developed in order to offer valid guidance to policy making. For these interventions, checklists for critical appraisal of economic evaluations may require some substantial changes.
Collapse
Affiliation(s)
- Giovanni Fattore
- CeRGAS-SDA, Università Bocconi, Milano, Italy; Department of Social and Political Sciences, Università Bocconi, Milano, Italy.
| | - Carlo Federici
- Department of Social and Political Sciences, Università Bocconi, Milano, Italy
| | - Michael Drummond
- Department of Social and Political Sciences, Università Bocconi, Milano, Italy; Centre for Health Economics, York University, United Kingdom
| | - Mario Mazzocchi
- Department of Statistical Sciences, Bologna University, Bologna, Italy
| | | | | | - Bhavani Shankar
- Institute of Sustainable Food and Department of Geography, Sheffield University, United Kingdom
| |
Collapse
|
42
|
Salzmann A, James SN, Williams DM, Richards M, Cadar D, Schott JM, Coath W, Sudre CH, Chaturvedi N, Garfield V. Investigating the Relationship Between IGF-I, IGF-II, and IGFBP-3 Concentrations and Later-Life Cognition and Brain Volume. J Clin Endocrinol Metab 2021; 106:1617-1629. [PMID: 33631000 PMCID: PMC8118585 DOI: 10.1210/clinem/dgab121] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Indexed: 01/18/2023]
Abstract
BACKGROUND The insulin/insulin-like signaling (IIS) pathways, including insulin-like growth factors (IGFs), vary with age. However, their association with late-life cognition and neuroimaging parameters is not well characterized. METHODS Using data from the British 1946 birth cohort, we investigated associations of IGF-I, IGF-II and IGF binding protein 3 (IGFBP-3; measured at 53 and 60-64 years of age) with cognitive performance [word-learning test (WLT) and visual letter search (VLS) at 60-64 years and 69 years of age] and cognitive state [Addenbrooke's Cognitive Exam III (ACE-III) at 69-71 years of age], and in a proportion, quantified neuroimaging measures [whole brain volume (WBV), white matter hyperintensity volume (WMHV), hippocampal volume (HV)]. Regression models included adjustments for demographic, lifestyle, and health factors. RESULTS Higher IGF-I and IGF-II at 53 years of age was associated with higher ACE-III scores [ß 0.07 95% confidence interval (CI) (0.02, 0.12); scoreACE-III 89.48 (88.86, 90.1), respectively). IGF-II at 53 years of age was additionally associated with higher WLT scores [scoreWLT 20 (19.35, 20.65)]. IGFBP-3 at 60 to 64 years of age was associated with favorable VLS score at 60 to 64 and 69 years of age [ß 0.07 (0.01, 0.12); ß 0.07 (0.02, 0.12), respectively], higher memory and cognitive state at 69 years of age [ß 0.07 (0.01, 0.12); ß 0.07 (0.01, 0.13), respectively], and reduced WMHV [ß -0.1 (-0.21, -0.00)]. IGF-I/IGFBP-3 at 60 to 64 years of was associated with lower VLS scores at 69 years of age [ß -0.08 (-0.15, -0.02)]. CONCLUSIONS Increased measure in IIS parameters (IGF-I, IGF-II, and IGFBP-3) relate to better cognitive state in later life. There were apparent associations with specific cognitive domains (IGF-II relating to memory; IGFBP-3 relating to memory, processing speed, and WMHV; and IGF-I/IGFBP-3 molar ratio related to slower processing speed). IGFs and IGFBP-3 are associated with favorable cognitive function outcomes.
Collapse
Affiliation(s)
- Antoine Salzmann
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Dylan M Williams
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Dorina Cadar
- Department of Behavioural Science and Health, University College London, London, UK
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, The Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - William Coath
- Department of Neurodegenerative Disease, The Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Carole H Sudre
- Department of Neurodegenerative Disease, The Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Victoria Garfield
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| |
Collapse
|
43
|
Lord J, Jermy B, Green R, Wong A, Xu J, Legido-Quigley C, Dobson R, Richards M, Proitsi P. Mendelian randomization identifies blood metabolites previously linked to midlife cognition as causal candidates in Alzheimer's disease. Proc Natl Acad Sci U S A 2021; 118:e2009808118. [PMID: 33879569 PMCID: PMC8072203 DOI: 10.1073/pnas.2009808118] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 02/23/2021] [Indexed: 12/29/2022] Open
Abstract
There are currently no disease-modifying treatments for Alzheimer's disease (AD), and an understanding of preclinical causal biomarkers to help target disease pathogenesis in the earliest phases remains elusive. Here, we investigated whether 19 metabolites previously associated with midlife cognition-a preclinical predictor of AD-translate to later clinical risk, using Mendelian randomization (MR) to tease out AD-specific causal relationships. Summary statistics from the largest genome-wide association studies (GWASs) for AD and metabolites were used to perform bidirectional univariable MR. Bayesian model averaging (BMA) was additionally performed to address high correlation between metabolites and identify metabolite combinations that may be on the AD causal pathway. Univariable MR indicated four extra-large high-density lipoproteins (XL.HDL) on the causal pathway to AD: free cholesterol (XL.HDL.FC: 95% CI = 0.78 to 0.94), total lipids (XL.HDL.L: 95% CI = 0.80 to 0.97), phospholipids (XL.HDL.PL: 95% CI = 0.81 to 0.97), and concentration of XL.HDL particles (95% CI = 0.79 to 0.96), significant at an adjusted P < 0.009. MR-BMA corroborated XL.HDL.FC to be among the top three causal metabolites, in addition to total cholesterol in XL.HDL (XL.HDL.C) and glycoprotein acetyls (GP). Both XL.HDL.C and GP demonstrated suggestive univariable evidence of causality (P < 0.05), and GP successfully replicated within an independent dataset. This study offers insight into the causal relationship between metabolites demonstrating association with midlife cognition and AD. It highlights GP in addition to several XL.HDLs-particularly XL.HDL.FC-as causal candidates warranting further investigation. As AD pathology is thought to develop decades prior to symptom onset, expanding on these findings could inform risk reduction strategies.
Collapse
Affiliation(s)
- Jodie Lord
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 5AF, United Kingdom
| | - Bradley Jermy
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, United Kingdom
- National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, SE5 8AF, United Kingdom
| | - Rebecca Green
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 5AF, United Kingdom
- National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, SE5 8AF, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, WC1E 7HB, United Kingdom
| | - Jin Xu
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 5AF, United Kingdom
- Institute of Pharmaceutical Science, King's College London, London, SE1 9NH, United Kingdom
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, SE1 9NH, United Kingdom
- Systems Medicine, Steno Diabetes Centre Copenhagen, 2820 Gentofte, Denmark
| | - Richard Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, United Kingdom
- National Institute for Health Research Biomedical Research at South London and Maudsley NHS Foundation Trust and King's College London, London, SE5 8AF, United Kingdom
- Health Data Research UK London, University College London, London, NW1 2DA, United Kingdom
- Institute of Health Informatics, University College London, London, NW1 2DA, United Kingdom
- National Institute for Health Research Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, NW1 2DA, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, WC1E 7HB, United Kingdom;
| | - Petroula Proitsi
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 5AF, United Kingdom;
| |
Collapse
|
44
|
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: 1.0] [Reference Citation Analysis] [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.
Collapse
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
| |
Collapse
|
45
|
John A, Stott J, Richards M. Associations between childhood reading problems and affective symptoms across the life course: Evidence from the 1946 British Birth Cohort. J Affect Disord 2021; 282:284-288. [PMID: 33418380 DOI: 10.1016/j.jad.2020.12.054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 12/11/2020] [Accepted: 12/14/2020] [Indexed: 11/27/2022]
Abstract
BACKGROUND Little is known about long-term outcomes of reading problems in childhood on affective symptoms across the life course. The aim of this research was to test longitudinal associations between reading problems in childhood and affective symptoms from adolescence to early old age. METHODS Data were from the National Survey of Health and Development (British 1946 birth cohort). A measure of reading problems was available at age 11. Affective symptoms were assessed at ages 13, 15, 35, 43, 53, 60-64 and 69. Path analyses tested longitudinal associations between reading problems and affective symptoms from adolescence to early old age. Linear regressions tested associations between reading problems in childhood and accumulation of affective symptoms across the life course (age 13 to 69). Models were adjusted for sex, education, conduct problems, and socioeconomic position in childhood and adulthood. RESULTS After full adjustment, reading problems were significantly associated with higher affective symptoms in adolescence (ages 13 and 15) but not affective symptoms in adulthood (ages 36, 43, 53, 60-64, and 69). Reading problems were not associated with accumulation of affective symptoms across the life course. LIMITATIONS Attrition was limitation of this study, due to the long follow-up period. In order to account for missing data, full information maximum likelihood (FIML) was used. CONCLUSIONS Childhood reading problems are associated with higher affective symptoms in adolescence, but this does not persist into adulthood. These results highlight an important period in adolescence when reading problems may exert a particularly strong effect on affective symptoms.
Collapse
Affiliation(s)
| | | | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, UCL, London, United Kingdom
| |
Collapse
|
46
|
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: 1.0] [Reference Citation Analysis] [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.
Collapse
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
| | | |
Collapse
|
47
|
Fluharty ME, Hardy R, Ploubidis G, Pongiglione B, Bann D. Socioeconomic inequalities across life and premature mortality from 1971 to 2016: findings from three British birth cohorts born in 1946, 1958 and 1970. J Epidemiol Community Health 2021; 75:193-196. [PMID: 33023969 PMCID: PMC7815902 DOI: 10.1136/jech-2020-214423] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 08/31/2020] [Accepted: 09/18/2020] [Indexed: 12/28/2022]
Abstract
INTRODUCTION Disadvantaged socioeconomic position (SEP) in early and adult life has been repeatedly associated with premature mortality. However, it is unclear whether these inequalities differ across time, nor if they are consistent across different SEP indicators. METHODS British birth cohorts born in 1946, 1958 and 1970 were used, and multiple SEP indicators in early and adult life were examined. Deaths were identified via national statistics or notifications. Cox proportional hazard models were used to estimate associations between ridit scored SEP indicators and all-cause mortality risk-from 26 to 43 years (n=40 784), 26 to 58 years (n=35 431) and 26 to 70 years (n=5353). RESULTS More disadvantaged SEP was associated with higher mortality risk-magnitudes of association were similar across cohort and each SEP indicator. For example, HRs (95% CI) from 26 to 43 years comparing lowest to highest paternal social class were 2.74 (1.02 to 7.32) in 1946c, 1.66 (1.03 to 2.69) in 1958c, and 1.94 (1.20 to 3.15) in 1970c. Paternal social class, adult social class and housing tenure were each independently associated with mortality risk. CONCLUSIONS Socioeconomic circumstances in early and adult life show persisting associations with premature mortality from 1971 to 2016, reaffirming the need to address socioeconomic factors across life to reduce inequalities in survival to older age.
Collapse
Affiliation(s)
- Meg E Fluharty
- UCL Institute of Education, Centre for Longitudinal Studies, London, UK
| | - Rebecca Hardy
- UCL Institute of Education, Cohort and Longitudinal Studies Enhancement Resources, London, UK
| | - George Ploubidis
- UCL Institute of Education, Centre for Longitudinal Studies, London, UK
| | - Benedetta Pongiglione
- Bocconi University, Centre for Research on Health and Social Care Management, Milano, Italy
| | - David Bann
- UCL Institute of Education, Centre for Longitudinal Studies, London, UK
| |
Collapse
|
48
|
Wehrle FM, Caflisch J, Eichelberger DA, Haller G, Latal B, Largo RH, Kakebeeke TH, Jenni OG. The Importance of Childhood for Adult Health and Development-Study Protocol of the Zurich Longitudinal Studies. Front Hum Neurosci 2021; 14:612453. [PMID: 33633550 PMCID: PMC7901945 DOI: 10.3389/fnhum.2020.612453] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/23/2020] [Indexed: 11/13/2022] Open
Abstract
Evidence is accumulating that individual and environmental factors in childhood and adolescence should be considered when investigating adult health and aging-related processes. The data required for this is gathered by comprehensive long-term longitudinal studies. This article describes the protocol of the Zurich Longitudinal Studies (ZLS), a set of three comprehensive cohort studies on child growth, health, and development that are currently expanding into adulthood. Between 1954 and 1961, 445 healthy infants were enrolled in the first ZLS cohort. Their physical, motor, cognitive, and social development and their environment were assessed comprehensively across childhood, adolescence, and into young adulthood. In the 1970s, two further cohorts were added to the ZLS and assessed with largely matched study protocols: Between 1974 and 1979, the second ZLS cohort included 265 infants (103 term-born and 162 preterm infants), and between 1970 and 2002, the third ZLS cohort included 327 children of participants of the first ZLS cohort. Since 2019, the participants of the three ZLS cohorts have been traced and invited to participate in a first wave of assessments in adulthood to investigate their current health and development. This article describes the ZLS study protocol and discusses opportunities, methodological and conceptual challenges, and limitations arising from a long-term longitudinal cohort recruited from a study about development in early life. In the future, the ZLS will provide data to investigate childhood antecedents of adult health outcomes and, ultimately, will help respond to the frequent call of scientists to shift the focus of aging research into the first decades of life and, thus, to take a lifespan perspective on aging.
Collapse
Affiliation(s)
- Flavia M. Wehrle
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Jon Caflisch
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | | | - Giulia Haller
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Beatrice Latal
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Remo H. Largo
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Tanja H. Kakebeeke
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Oskar G. Jenni
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
| |
Collapse
|
49
|
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: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [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.
Collapse
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
| | | |
Collapse
|
50
|
Mason SA, Al Saikhan L, Jones S, Bale G, James SN, Murray-Smith H, Rapala A, Williams S, Wong B, Richards M, Fox NC, Hardy R, Schott JM, Chaturvedi N, Hughes AD. Study Protocol - Insight 46 Cardiovascular: A Sub-study of the MRC National Survey of Health and Development. Artery Res 2020; 26:170-179. [PMID: 32879639 DOI: 10.2991/artres.k.200417.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The commonest causes of dementia are Alzheimer's disease and vascular cognitive impairment. Although these conditions have been viewed as distinct entities, there is increasing evidence that neurodegenerative and vascular pathologies interact or overlap to cause cognitive decline, and that at least in some cases individuals at risk of cognitive decline exhibit abnormal cardiovascular physiology long before emergence of disease. However, the mechanisms linking haemodynamic disturbances with cognitive impairment and the various pathologies that cause dementia are poorly understood. A sub-sample of 502 participants from the Medical Research Council National Survey of Health and Development (NSHD) have participated in the first visit of a neuroscience sub-study referred to as Insight 46, where clinical, cognitive, imaging, and lifestyle data have been collected for the purpose of elucidating the pathological changes preceding dementia. This paper outlines the cardiovascular phenotyping performed in the follow-up visit of Insight 46, with the study participants now aged 74. In addition to standard cardiovascular assessments such as blood pressure measurements, echocardiography, and electrocardiography (ECG), functional Near Infrared Spectroscopy (fNIRS) has been included to provide an assessment of cerebrovascular function. A detailed description of the fNIRS protocol along with preliminary results from pilot data is presented. The combination of lifestyle data, brain structure/function, cognitive performance, and cardiovascular health obtained not only from Insight 46, but also from the whole NSHD provides an exciting opportunity to advance our understanding of the cardiovascular mechanisms underlying dementia and cognitive decline, and identify novel targets for intervention.
Collapse
Affiliation(s)
- Sarah Ann Mason
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Lamia Al Saikhan
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiac Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, 2835 King Faisal Street, Dammam, Kingdom of Saudi Arabia
| | - Siana Jones
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Gemma Bale
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Alicja Rapala
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Suzanne Williams
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Brian Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| |
Collapse
|