Quantification of biological age as a determinant of age-related diseases in the Rotterdam Study: a structural equation modeling approach

被引:0
作者
Reem Waziry
Luuk Gras
Sanaz Sedaghat
Henning Tiemeier
Gerrit J. Weverling
Mohsen Ghanbari
Jaco Klap
Frank de Wolf
Albert Hofman
M. Arfan Ikram
Jaap Goudsmit
机构
[1] Harvard T.H. Chan School of Public Health,Department of Epidemiology
[2] Erasmus Medical Center,Department of Epidemiology
[3] Janssen Prevention Center,Department of Preventive Medicine
[4] Janssen Pharmaceutical Companies of Johnson & Johnson,Department of Social and Behavioral Science
[5] Northwestern University Feinberg School of Medicine,Department of Neurology
[6] Harvard T.H. Chan School of Public Health,Amsterdam Neuroscience
[7] Erasmus Medical Center,Department of Infectious Disease Epidemiology
[8] Academic Medical Center of the University of Amsterdam,undefined
[9] School of Public Health,undefined
[10] Imperial College,undefined
来源
European Journal of Epidemiology | 2019年 / 34卷
关键词
Biological age; Morbidity; Mortality; Biologically young; Elderly;
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学科分类号
摘要
Chronological age alone is not a sufficient measure of the true physiological state of the body. The aims of the present study were to: (1) quantify biological age based on a physiological biomarker composite model; (2) and evaluate its association with death and age-related disease onset in the setting of an elderly population. Using structural equation modeling we computed biological age for 1699 individuals recruited from the first and second waves of the Rotterdam study. The algorithm included nine physiological parameters (c-reactive protein, creatinine, albumin, total cholesterol, cytomegalovirus optical density, urea nitrogen, alkaline phosphatase, forced expiratory volume and systolic blood pressure). We assessed the association between biological age, all-cause mortality, all-cause morbidity and specific age-related diseases over a median follow-up of 11 years. Biological age, compared to chronological age or the traditional biomarkers of age-related diseases, showed a stronger association with all-cause mortality (HR 1.15 vs. 1.13 and 1.10), all-cause morbidity (HR 1.06 vs. 1.05 and 1.03), stroke (HR 1.17 vs. 1.08 and 1.04), cancer (HR 1.07 vs. 1.04 and 1.02) and diabetes mellitus (HR 1.12 vs. 1.01 and 0.98). Individuals who were biologically younger exhibited a healthier life-style as reflected in their lower BMI (P < 0.001) and lower incidence of stroke (P < 0.001), cancer (P < 0.01) and diabetes mellitus (P = 0.02). Collectively, our findings suggest that biological age based on the biomarker composite model of nine physiological parameters is a useful construct to assess individuals 65 years and older at increased risk for specific age-related diseases.
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页码:793 / 799
页数:6
相关论文
共 93 条
[1]  
Hayflick L(2000)The future of ageing Nature 408 267-269
[2]  
Sebastiani P(2017)Biomarker signatures of aging Aging Cell 16 329-338
[3]  
Thyagarajan B(2013)The state of US health, 1990-2010: burden of diseases, injuries, and risk factors JAMA 310 591-608
[4]  
Sun F(2014)Advances in geroscience: impact on healthspan and chronic disease J Gerontol Ser A, Biol Sci Med Sci 69 S1-S3
[5]  
Murray CJ(1969)Test-battery to measure ageing-rate in man Lancet 294 1411-1415
[6]  
Atkinson C(2006)A new approach to the concept and computation of biological age Mech Ageing Dev 127 240-248
[7]  
Bhalla K(2012)Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol Ser A: Biomed Sci Med Sci 68 667-674
[8]  
Burch JB(2017)The Rotterdam Study: 2018 update on objectives, design and main results Eur J Epidemiol 32 807-850
[9]  
Augustine AD(2013)Response to Dr. Mitnitski’s and Dr. Rockwood’s letter to the editor: biological age revisited J Gerontol Ser A: Biomed Sci Med Sci 69 297-298
[10]  
Frieden LA(2015)Quantification of biological aging in young adults Proc Natl Acad Sci USA 112 E4104-E4110