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Liu W, Song J, Yu L, Lai X, Shi D, Fan L, Wang H, Yang Y, Liang R, Wan S, Zhang Y, Wang B. Exposure to ambient air pollutants during circadian syndrome and subsequent cardiovascular disease and its subtypes and death: A trajectory analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 944:173777. [PMID: 38844213 DOI: 10.1016/j.scitotenv.2024.173777] [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: 12/08/2023] [Revised: 05/09/2024] [Accepted: 06/03/2024] [Indexed: 06/17/2024]
Abstract
BACKGROUND The association between exposure to air pollutants and cardiovascular disease (CVD) trajectory in individuals with circadian syndrome remains inconclusive. METHODS The individual exposure levels of air pollutants, including particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM2.5), PM with aerodynamic diameter ≤ 10 μm (PM10), PM2.5 absorbance, PM with aerodynamic diameter between 2.5 μm and 10 μm, nitrogen dioxide (NO2), nitrogen oxides (NOx), and air pollution score (overall air pollutants exposure), were estimated for 48,850 participants with circadian syndrome from the UK Biobank. Multistate regression models were employed to estimate associations between exposure to air pollutants and trajectories from circadian syndrome to CVD/CVD subtypes (including coronary heart disease [CHD], atrial fibrillation [AF], heart failure [HF], and stroke) and death. Mediation roles of CVD/CVD subtypes in the associations between air pollutants and death were evaluated. RESULTS After a mean follow-up time over 12 years, 12,570 cases of CVD occurred, including 8192 CHD, 1693 AF, 1085 HF, and 1600 stroke cases. In multistate model, per-interquartile range increment in PM2.5 (hazard ratio: 1.08; 95 % confidence interval: 1.06, 1.10), PM10 (1.04; 1.01, 1.06), PM2.5 absorbance (1.04; 1.02, 1.06), NO2 (1.07; 1.03, 1.11), NOx (1.08; 1.04, 1.12), or air pollution score (1.06; 1.03, 1.08) was associated with trajectory from circadian syndrome to CVD. Significant associations between the above-mentioned air pollutants and trajectories from circadian syndrome and CVD to death were observed. CVD, particularly CHD, significantly mediated the associations of PM2.5, NO2, NOx, and air pollution score with death. CONCLUSIONS Long-term exposure to air pollutants during circadian syndrome was associated with subsequent CVD and death. CHD emerged as the most prominent CVD subtype in CVD progression driven by exposure to air pollutants during circadian syndrome. Our study highlights the importance of controlling air pollutants exposure and preventing CHD in people with circadian syndrome.
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Affiliation(s)
- Wei Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou 341000, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
| | - Jiahao Song
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Linling Yu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xuefeng Lai
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Da Shi
- Agricultural, Food and Nutritional Science, Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alberta T6G 2P5, Canada
| | - Lieyang Fan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Hao Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yueru Yang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ruyi Liang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shuhui Wan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yongfang Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Bin Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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Chen Y, Bandosz P, Stoye G, Liu Y, Wu Y, Lobanov-Rostovsky S, French E, Kivimaki M, Livingston G, Liao J, Brunner EJ. Dementia incidence trend in England and Wales, 2002-19, and projection for dementia burden to 2040: analysis of data from the English Longitudinal Study of Ageing. Lancet Public Health 2023; 8:e859-e867. [PMID: 37898518 PMCID: PMC10958989 DOI: 10.1016/s2468-2667(23)00214-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 08/25/2023] [Accepted: 09/06/2023] [Indexed: 10/30/2023]
Abstract
BACKGROUND Dementia incidence declined in many high-income countries in the 2000s, but evidence on the post-2010 trend is scarce. We aimed to analyse the temporal trend in England and Wales between 2002 and 2019, considering bias and non-linearity. METHODS Population-based panel data representing adults aged 50 years and older from the English Longitudinal Study of Ageing were linked to the mortality register across wave 1 (2002-03) to wave 9 (2018-19) (90 073 person observations). Standard criteria based on cognitive and functional impairment were used to ascertain incident dementia. Crude incidence rates were determined in seven overlapping initially dementia-free subcohorts each followed up for 4 years (ie, 2002-06, 2004-08, 2006-10, 2008-12, 2010-14, 2012-16, and 2014-18). We examined the temporal trend of dementia incidence according to age, sex, and educational attainment. We estimated the trend of dementia incidence adjusted by age and sex with Cox proportional hazards and multistate models. Restricted cubic splines allowed for potential non-linearity in the time trend. A Markov model was used to project future dementia burden considering the estimated incidence trend. FINDINGS Incidence rate standardised by age and sex declined from 2002 to 2010 (from 10·7 to 8·6 per 1000 person-years), then increased from 2010 to 2019 (from 8·6 to 11·3 per 1000 person-years). Adjusting for age and sex, and accounting for missing dementia cases due to death, estimated dementia incidence declined by 28·8% from 2002 to 2008 (incidence rate ratio 0·71, 95% CI 0·58-0·88), and increased by 25·2% from 2008 to 2016 (1·25, 1·03-1·54). The group with lower educational attainment had a smaller decline in dementia incidence from 2002 to 2008 and a greater increase after 2008. If the upward incidence trend continued, there would be 1·7 million (1·62-1·75) dementia cases in England and Wales by 2040, 70% more than previously forecast. INTERPRETATION Dementia incidence might no longer be declining in England and Wales. If the upward trend since 2008 continues, along with population ageing, the burden on health and social care will be large. FUNDING UK Economic and Social Research Council.
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Affiliation(s)
- Yuntao Chen
- Department of Epidemiology and Public Health, University College London, London, UK.
| | - Piotr Bandosz
- Division of Prevention Medicine & Education, Medical University of Gdansk, Gdansk, Poland
| | | | - Yuyang Liu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yanjuan Wu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | | | - Eric French
- Faculty of Economics, University of Cambridge, Cambridge, UK
| | - Mika Kivimaki
- Division of Psychiatry, University College London, London, UK
| | - Gill Livingston
- Division of Psychiatry, University College London, London, UK
| | - Jing Liao
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Eric J Brunner
- Department of Epidemiology and Public Health, University College London, London, UK
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Zhang S, Qian ZM, Chen L, Zhao X, Cai M, Wang C, Zou H, Wu Y, Zhang Z, Li H, Lin H. Exposure to Air Pollution during Pre-Hypertension and Subsequent Hypertension, Cardiovascular Disease, and Death: A Trajectory Analysis of the UK Biobank Cohort. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:17008. [PMID: 36696106 PMCID: PMC9875843 DOI: 10.1289/ehp10967] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 11/27/2022] [Accepted: 12/15/2022] [Indexed: 05/28/2023]
Abstract
BACKGROUND The associations between air pollution exposure and morbidity and mortality of cardiovascular diseases (CVDs) have been widely reported; however, evidence on such associations across different dynamic disease trajectories remain unknown. OBJECTIVE We examined whether ambient air pollution during the prehypertension (pre-HTN) stage could aggravate the progression from hypertension (HTN) to CVD, and consequent death. METHODS A total of 168,010 adults with pre-HTN (120 - 139 mmHg systolic blood pressure or 80 - 89 mmHg diastolic blood pressure) from the UK Biobank were included in this analysis. We used a multistate model to explore the associations between five air pollutants (PM 2.5 , PM 2.5 absorbance, PM 10 , NO 2 , and NO x ) and the risk of six disease transitions (from pre-HTN to HTN, from pre-HTN to CVD, from pre-HTN to death, from HTN to CVD, from HTN to death, and from CVD to death). Mediation analyses were further conducted to explore the role of intermediate diseases in the dynamic progression of CVDs. RESULTS During a median follow-up of 12 y, 13,743 (8.18%) of participants with pre-HTN developed HTN, whereas 12,825 (7.63%) and 4,467 (2.66%) directly developed CVD or died, respectively. Air pollution was positively associated with the dynamic disease progression. For example, a per-interquartile range increase of PM 2.5 was significantly associated with the hazard ratios (HRs) of 1.105 [95% confidence intervals (CI): 1.083, 1.127], 1.045 (95% CI: 1.022, 1.068), and 1.086 (95% CI: 1.047, 1.126) in the transition from pre-HTN to HTN, CVD, and death, respectively. Higher levels of air pollution were associated with increased transition probability of disease progression. Mediation analyses indicated that intermediate diseases subsequently significantly mediated air pollutant-associated risk to develop more serious disease. CONCLUSIONS This study provides evidence that air pollution might play a role in the early stages of CVD progression. Controlling air pollution might be an effective measure to prevent CVD progression and reduce the disease burden of CVD. https://doi.org/10.1289/EHP10967.
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Affiliation(s)
- Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, Missouri, USA
| | - Lan Chen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Hongtao Zou
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yinglin Wu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Haitao Li
- Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
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4
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Hayes-Larson E, Shaw C, Ackley SF, Zimmerman SC, Glymour MM, Graff RE, Witte JS, Kobayashi L, Mayeda ER. The role of dementia diagnostic delay in the inverse cancer-dementia association. J Gerontol A Biol Sci Med Sci 2021; 77:1254-1260. [PMID: 34788817 DOI: 10.1093/gerona/glab341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Cancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history. METHODS We used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to US population and cohort data. We varied the average lapse between dementia onset and diagnosis, including non-differential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis. RESULTS Non-differential dementia diagnosis delay introduced minimal bias (IRRs=0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR=0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias. CONCLUSIONS Delays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.
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Affiliation(s)
- Eleanor Hayes-Larson
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Crystal Shaw
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA.,Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Sarah F Ackley
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Scott C Zimmerman
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - John S Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Lindsay Kobayashi
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Elizabeth Rose Mayeda
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
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5
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Mitra S, Gera R, Linderoth B, Lind G, Wahlberg L, Almqvist P, Behbahani H, Eriksdotter M. A Review of Techniques for Biodelivery of Nerve Growth Factor (NGF) to the Brain in Relation to Alzheimer's Disease. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1331:167-191. [PMID: 34453298 DOI: 10.1007/978-3-030-74046-7_11] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Age-dependent progressive neurodegeneration and associated cognitive dysfunction represent a serious concern worldwide. Currently, dementia accounts for the fifth highest cause of death, among which Alzheimer's disease (AD) represents more than 60% of the cases. AD is associated with progressive cognitive dysfunction which affects daily life of the affected individual and associated family. The cognitive dysfunctions are at least partially due to the degeneration of a specific set of neurons (cholinergic neurons) whose cell bodies are situated in the basal forebrain region (basal forebrain cholinergic neurons, BFCNs) but innervate wide areas of the brain. It has been explicitly shown that the delivery of the neurotrophic protein nerve growth factor (NGF) can rescue BFCNs and restore cognitive dysfunction, making NGF interesting as a potential therapeutic substance for AD. Unfortunately, NGF cannot pass through the blood-brain barrier (BBB) and thus peripheral administration of NGF protein is not viable therapeutically. NGF must be delivered in a way which will allow its brain penetration and availability to the BFCNs to modulate BFCN activity and viability. Over the past few decades, various methodologies have been developed to deliver NGF to the brain tissue. In this chapter, NGF delivery methods are discussed in the context of AD.
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Affiliation(s)
- Sumonto Mitra
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Stockholm, Sweden.
| | - Ruchi Gera
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Stockholm, Sweden
| | - Bengt Linderoth
- Section of Neurosurgery, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Göran Lind
- Section of Neurosurgery, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | | | - Per Almqvist
- Section of Neurosurgery, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Homira Behbahani
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Stockholm, Sweden.,Karolinska Universitets laboratoriet (LNP5), Karolinska University Hospital, Stockholm, Sweden
| | - Maria Eriksdotter
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Huddinge, Sweden
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6
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Milan V, Fetzer S, Hagist C. Healing, surviving, or dying? - projecting the German future disease burden using a Markov illness-death model. BMC Public Health 2021; 21:123. [PMID: 33430836 PMCID: PMC7799167 DOI: 10.1186/s12889-020-09941-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 11/19/2020] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND In view of the upcoming demographic transition, there is still no clear evidence on how increasing life expectancy will affect future disease burden, especially regarding specific diseases. In our study, we project the future development of Germany's ten most common non-infectious diseases (arthrosis, coronary heart disease, pulmonary, bronchial and tracheal cancer, chronic obstructive pulmonary disease, cerebrovascular diseases, dementia, depression, diabetes, dorsal pain and heart failure) in a Markov illness-death model with recovery until 2060. METHODS The disease-specific input data stem from a consistent data set of a major sickness fund covering about four million people, the demographic components from official population statistics. Using six different scenarios concerning an expansion and a compression of morbidity as well as increasing recovery and effective prevention, we can show the possible future range of disease burden and, by disentangling the effects, reveal the significant differences between the various diseases in interaction with the demographic components. RESULTS Our results indicate that, although strongly age-related diseases like dementia or heart failure show the highest relative increase rates, diseases of the musculoskeletal system, such as dorsal pain and arthrosis, still will be responsible for the majority of the German population's future disease burden in 2060, with about 25-27 and 13-15 million patients, respectively. Most importantly, for almost all considered diseases a significant increase in burden of disease can be expected even in case of a compression of morbidity. CONCLUSION A massive case-load is emerging on the German health care system, which can only be alleviated by more effective prevention. Immediate action by policy makers and health care managers is needed, as otherwise the prevalence of widespread diseases will become unsustainable from a capacity point-of-view.
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Affiliation(s)
- Valeska Milan
- AOK Baden-Württemberg, Stuttgart / WHU Otto Beisheim School of Management, Burgplatz 2, 56179, Vallendar, Germany.
| | - Stefan Fetzer
- Hochschule Aalen - Technik und Wirtschaft, Aalen, Germany
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7
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Hayes-Larson E, Ackley SF, Zimmerman SC, Ospina-Romero M, Glymour MM, Graff RE, Witte JS, Kobayashi LC, Mayeda ER. The competing risk of death and selective survival cannot fully explain the inverse cancer-dementia association. Alzheimers Dement 2020; 16:1696-1703. [PMID: 32881307 DOI: 10.1002/alz.12168] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 06/16/2020] [Accepted: 07/09/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION We evaluated whether competing risk of death or selective survival could explain the reported inverse association between cancer history and dementia incidence (incidence rate ratio [IRR] ≈ 0.62-0.85). METHODS A multistate simulation model of a cancer- and dementia-free cohort of 65-year-olds was parameterized with real-world data (cancer and dementia incidence, mortality), assuming no effect of cancer on dementia (true IRR = 1.00). To introduce competing risk of death, cancer history increased mortality. To introduce selective survival, we included a factor (prevalence ranging from 10% to 50%) that reduced cancer mortality and dementia incidence (IRRs ranged from 0.30 to 0.90). We calculated IRRs for cancer history on dementia incidence in the simulated cohorts. RESULTS Competing risk of death yielded unbiased cancer-dementia IRRs. With selective survival, bias was small (IRRs = 0.89 to 0.99), even under extreme scenarios. DISCUSSION The bias induced by selective survival in simulations was too small to explain the observed inverse cancer-dementia link, suggesting other mechanisms drive this association.
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Affiliation(s)
- Eleanor Hayes-Larson
- Department of Epidemiology, University of California, Los Angeles Fielding School of Public Health, Los Angeles, California, USA
| | - Sarah F Ackley
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - Scott C Zimmerman
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - Monica Ospina-Romero
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - John S Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - Lindsay C Kobayashi
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Elizabeth Rose Mayeda
- Department of Epidemiology, University of California, Los Angeles Fielding School of Public Health, Los Angeles, California, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
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Ikram MA, Brusselle G, Ghanbari M, Goedegebure A, Ikram MK, Kavousi M, Kieboom BCT, Klaver CCW, de Knegt RJ, Luik AI, Nijsten TEC, Peeters RP, van Rooij FJA, Stricker BH, Uitterlinden AG, Vernooij MW, Voortman T. Objectives, design and main findings until 2020 from the Rotterdam Study. Eur J Epidemiol 2020; 35:483-517. [PMID: 32367290 PMCID: PMC7250962 DOI: 10.1007/s10654-020-00640-5] [Citation(s) in RCA: 298] [Impact Index Per Article: 74.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/23/2020] [Indexed: 12/19/2022]
Abstract
The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.
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Affiliation(s)
- M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.
| | - Guy Brusselle
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - André Goedegebure
- Department of Otorhinolaryngology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Kamran Ikram
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Brenda C T Kieboom
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Caroline C W Klaver
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robert J de Knegt
- Department of Gastroenterology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Tamar E C Nijsten
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robin P Peeters
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Bruno H Stricker
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
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