The COVID‐19 pandemic necessitated adaptations to standard operations and management of clinical studies, after lockdown measures put in place by several governments to reduce the spread of SARS‐COV‐2. In this paper, we describe our telehealth strategy developed for transitioning our dementia prevention clinical observational prospective study from face‐to‐face visits to virtual visits, to ensure the ongoing collection of longitudinal data. We share the lessons learned in terms of challenges experienced and solutions implemented to achieve successful administration of study assessments. Our methods will be useful for informing longitudinal observational or interventional studies that require a feasible model for remote data collection, in cognitively unimpaired adults.
Background: China is increasingly facing the challenge of control of the growing burden of non-communicable diseases. We assessed the epidemiology of Alzheimer's disease and other forms of dementia in China between 1990, and 2010, to improve estimates of the burden of disease, analyse time trends, and inform health policy decisions relevant to China's rapidly ageing population. Methods: In our systematic review we searched for reports of Alzheimer's disease or dementia in China, published in Chinese and English between 1990 and 2010. We searched China National Knowledge Infrastructure, Wanfang, and PubMed databases. Two investigators independently assessed case definitions of Alzheimer's disease and dementia: we excluded studies that did not use internationally accepted case definitions. We also excluded reviews and viewpoints, studies with no numerical estimates, and studies not done in mainland China. We used Poisson regression and UN demographic data to estimate the prevalence (in nine age groups), incidence, and standardised mortality ratio of dementia and its subtypes in China in 1990, 2000, and 2010. Findings: Our search returned 12 642 reports, of which 89 met the inclusion criteria (75 assessed prevalence, 13 incidence, and nine mortality). In total, the included studies had 340 247 participants, in which 6357 cases of Alzheimer's disease were recorded. 254 367 people were assessed for other forms of dementia, of whom 3543 had vascular dementia, frontotemporal dementia, or Lewy body dementia. In 1990 the prevalence of all forms of dementia was 1·8% (95% CI 0·0-44·4) at 65-69 years, and 42·1% (0·0-88·9) at age 95-99 years. In 2010 prevalence was 2·6% (0·0-28·2) at age 65-69 years and 60·5% (39·7-81·3) at age 95-99 years. The number of people with dementia in China was 3·68 million (95% CI 2·22-5·14) in 1990, 5·62 million (4·42-6·82) in 2000, and 9·19 million (5·92-12·48) in 2010. In the same period, the number of people with Alzheimer's disease was 1·93 million (1·15- 2·71) in 1990, 3·71 million (2·84-4·58) people in 2000, and 5·69 million (3·85-7·53) in 2010. The incidence of dementia was 9·87 cases per 1000 person-years, that of Alzheimer's disease was 6·25 cases per 1000 person-years, that of vascular dementia was 2·42 cases per 1000 person-years, and that of other rare forms of dementia was 0·46 cases per 1000 person-years. We retrieved mortality data for 1032 people with dementia and 20 157 healthy controls, who were followed up for 3-7 years. The median standardised mortality ratio was 1·94:1 (IQR 1·74-2·45). Interpretation: Our analysis suggests that previous estimates of dementia burden, based on smaller datasets, might have underestimated the burden of dementia in China. The burden of dementia seems to be increasing faster than is generally assumed by the international health community. Rapid and effective government responses are needed to tackle dementia in low-income and middle-income countries. Funding: Nossal Institute of Global Health (University of Melbourne, Australia), the National 12th Five-Year Major Projects of China, National Health and Medical Research Council Australia-China Exchange Fellowship, Importation and Development of High-Calibre Talents Project of Beijing Municipal Institutions, and the Bill & Melinda Gates Foundation.
INTRODUCTION: Due to demographic change, an increase in the frequency of Parkinson's disease (PD) patients is expected in the future and, thus, the identification of modifiable risk factors is urgently needed. We aimed to examine the associations of body mass index (BMI) and waist circumference (WC) with incident PD. METHODS: In 13 of the 23 centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a total of 734 incident cases of PD were identified between 1992 and 2012 with a mean follow-up of 12 years. Cox proportional hazards regression was used to calculate hazard ratios (HR) with 95% confidence intervals (CI). We modelled anthropometric variables as continuous and categorical exposures and performed subgroup analyses by potential effect modifiers including sex and smoking. RESULTS: We found no association between BMI, WC and incident PD, neither among men nor among women. Among never and former smokers, BMI and waist circumference were also not associated with PD risk. For male smokers, however, we observed a statistically significant inverse association between BMI and PD risk (HR 0.51, 95%CI: 0.30, 0.84) and the opposite for women, i.e. a significant direct association of BMI (HR 1.79, 95%CI: 1.04, 3.08) and waist circumference (HR 1.64, 95%CI: 1.03, 2.61) with risk of PD. CONCLUSION: Our data revealed no association between excess weight and PD risk but a possible interaction between anthropometry, sex and smoking. ; This research has been made possible thanks to a grant of the European Community (5th Framework Programme) to Prof. Paolo Vineis (grant QLK4CT199900927); and a grant of the Compagnia di San Paolo to the ISI Foundation. All authors are independent from founders. Mortality data from the Netherlands are obtained from "Statistics Netherlands". The centers contributing to the NeuroEPIC4PD study are financially supported by: Europe Against Cancer Program of the European Commission (SANCO); ISCIII, Red de Centros RCESP, C03/09; Spanish Ministry of Health (ISCIII RETICC RD06/0020); German Cancer Aid; German Cancer Research Center (DKFZ); German Federal Ministry of Education and Research (BMBF); Danish Cancer Society; Health Research Fund (FIS) of the Spanish Ministry of Health; Spanish Regional Governments of Andalucia, Asturias, Basque Country, Murcia and Navarra; Spanish Ministry of Health (ISCIII RETICC RD06/0020) Cancer Research U.K.; Medical Research Council, United Kingdom; Stroke Association, United Kingdom; British Heart Foundation; Department of Health, United Kingdom; Food Standards Agency, United Kingdom; Welcome Trust, United Kingdom Greek Ministry of Health; Greek Ministry of Education; Italian Association for Research on Cancer (AIRC); Italian National Research Council; Dutch Ministry of Public Health, Welfare and Sports (VWS); Netherlands Cancer Registry (NKR); LK Research Funds; Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland); World Cancer Research Fund (WCRF); Statistics Netherlands (The Netherlands); Swedish Cancer Foundation; Swedish Scientific Council; Regional Governments of Skåne and Västerbotten Counties, Sweden; Norwegian Cancer Society; Research Council of Norway; French League against cancer, Inserm, Mutuelle Generale l'Education National and IGR; the Hellenic Health Foundation.
BACKGROUND: The aim of this paper is to investigate the causality of the inverse association between cigarette smoking and Parkinson's disease (PD). The main suggested alternatives include a delaying effect of smoking, reverse causality or an unmeasured confounding related to a low-risk-taking personality trait. METHODS: A total of 715 incident PD cases were ascertained in a cohort of 220 494 individuals from NeuroEPIC4PD, a prospective European population-based cohort study including 13 centres in eight countries. Smoking habits were recorded at recruitment. We analysed smoking status, duration, and intensity and exposure to passive smoking in relation to PD onset. RESULTS: Former smokers had a 20% decreased risk and current smokers a halved risk of developing PD compared with never smokers. Strong dose-response relationships with smoking intensity and duration were found. Hazard ratios (HRs) for smoking 30 years 0.54 (95% CI 0.43-0.36) compared with never smokers. The proportional hazard assumption was verified, showing no change of risk over time, arguing against a delaying effect. Reverse causality was disproved by the consistency of dose-response relationships among former and current smokers. The inverse association between passive smoking and PD, HR 0.70 (95% CI 0.49-0.99) ruled out the effect of unmeasured confounding. CONCLUSIONS: These results are highly suggestive of a true causal link between smoking and PD, although it is not clear which is the chemical compound in cigarette smoking responsible for the biological effect. ; Mortality data from the Netherlands are obtained from "Statistics Netherlands". In addition we would like to thank for their financial support: Europe Against cancer Program of the European Commission (SANCO); ISCIII, Red de Centros RCESP, C03/09; Spanish Ministry of Health (ISCIII RETICC RD06/0020); Deutsche Krebshilfe; Deutsches Krebsforschungszentrum; German Federal Ministry of Education and Research; Danish Cancer Society; Health Research Fund (FIS) of the Spanish Ministry of Health; Spanish Regional Governments of Andalucia, Asturias, Basque Country, Murcia and Navarra; Spanish Ministry of Health (ISCIII RETICC RD06/0020)Cancer Research U.K.; Medical Research Council, United Kingdom; Stroke Association, United Kingdom; National Institute of Health Research funding of a Biomedical Research Centre in Cambridge ; British Heart Foundation; Department of Health, United Kingdom; Food Standards Agency, United Kingdom; Wellcome Trust, United Kingdom Greek Ministry of Health; Greek Ministry of Education; Italian Association for Research on Cancer (AIRC); Italian National Research Council; Dutch Ministry of Public Health, Welfare and Sports (VWS); Netherlands Cancer Registry (NKR); LK Research Funds; Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland); World Cancer Research Fund (WCRF); Statistics Netherlands (The Netherlands); Swedish Cancer; Swedish Research Council; European Research Council, Regional Government of Skåne and Västerbotten, Sweden; Norwegian Cancer Society; Research Council of Norway; French League against cancer, Inserm, Mutuelle Generale l'Education National and IGR. Claudio Ruffmann received funding from 'Fondazione Grigioni per la lotta al Morbo di Parkinson
The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.
The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.
In: Bauermeister , S , Orton , C , Thompson , S , Barker , R A , Bauermeister , J R , Ben-Shlomo , Y , Brayne , C , Burn , D , Campbell , A , Calvin , C , Chandran , S , Chaturvedi , N , Chêne , G , Chessell , I P , Corbett , A , Davis , D H J , Denis , M , Dufouil , C , Elliott , P , Fox , N , Hill , D , Hofer , S M , Hu , M T , Jindra , C , Kee , F , Kim , C H , Kim , C , Kivimaki , M , Koychev , I , Lawson , R A , Linden , G J , Lyons , R A , Mackay , C , Matthews , P M , McGuiness , B , Middleton , L , Moody , C , Moore , K , Na , D L , O'Brien , J T , Ourselin , S , Paranjothy , S , Park , K S , Porteous , D J , Richards , M , Ritchie , C W , Rohrer , J D , Rossor , M N , Rowe , J B , Scahill , R , Schnier , C , Schott , J M , Seo , S W , South , M , Steptoe , M , Tabrizi , S J , Tales , A , Tillin , T , Timpson , N J , Toga , A W , Visser , P J , Wade-Martins , R , Wilkinson , T , Williams , J , Wong , A & Gallacher , J E J 2020 , ' The Dementias Platform UK (DPUK) Data Portal ' , European Journal of Epidemiology , vol. 35 , no. 6 , pp. 601-611 . https://doi.org/10.1007/s10654-020-00633-4
The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.
In: Bauermeister , S , Orton , C , Thompson , S , Barker , R A , Bauermeister , J R , Ben-Shlomo , Y , Brayne , C , Burn , D , Campbell , A , Calvin , C , Chandran , S , Chaturvedi , N , Chêne , G , Chessell , I P , Corbett , A , Davis , D H J , Denis , M , Dufouil , C , Elliott , P , Fox , N , Hill , D , Hofer , S M , Hu , M T , Jindra , C , Kee , F , Kim , C H , Kim , C , Kivimaki , M , Koychev , I , Lawson , R A , Linden , G J , Lyons , R A , Mackay , C , Matthews , P M , McGuiness , B , Middleton , L , Moody , C , Moore , K , Na , D L , O'Brien , J T , Ourselin , S , Paranjothy , S , Park , K S , Porteous , D J , Richards , M , Ritchie , C W , Rohrer , J D , Rossor , M N , Rowe , J B , Scahill , R , Schnier , C , Schott , J M , Seo , S W , South , M , Steptoe , M , Tabrizi , S J , Tales , A , Tillin , T , Timpson , N J , Toga , A W , Visser , P J , Wade-Martins , R , Wilkinson , T , Williams , J , Wong , A & Gallacher , J E J 2020 , ' The Dementias Platform UK (DPUK) Data Portal ' , European Journal of Epidemiology , vol. 35 , no. 6 , pp. 601-611 . https://doi.org/10.1007/s10654-020-00633-4
The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.