| ObjectiveAging can be defined as a degenerative process of biological system, the accumulation of the body irreversible degenerative changes increased vulnerability to disease and eventually leaded to death. Strehler proposed four characteristics of aging, namely, universal, progressive, intrinsic and harmfu. Aging is universal, none of animals could escape the aging process; aging is gradual in nature, aging are ongoing in various periods of life; aging is inherent, biological aging process and its speed have inherent characteristics of species; Aging is harmful, molecular and cellular senescence declined the functional reserve and reduced ability to adapt to the stress. Aging is not a disease, but it can reduce the threshold of aging-related diseases and thus increased chance of illness.At present, most of the countries in the world must face the problems of the population aging which were serious challenges to a country's social and economic long-term development. From the early 90s of last century, many developed countries such as Europe, the United States and Japan have implemented a series of longitudinal studies of aging. Representative studies were American Baltimore study, the Health ABC Longitudinal Study,Canada's VLS study Japan's seven-year longitudinal study,the Italian ILSA study and so on. The trends seen from these studies were: (1) emphasis on the individual assessment of aging; (2) the reliable, easily measured biomarkers of aging is an important topic in aging research; (3) research focus to healthy aging transfer; (4) the use of systems biology approach to establish the overall aging network is the direction of future research; (5) genetic background, lifestyle and dietary habits are important factors affecting the aging individual.Because the organization aged at different speeds, the differences among human individuals increased with increasing age. Chronological age (CA) can not provide the exact instructions for the aging process In medicine and prevention perspective, researchers concerned with aging changes in the individuals. The purposes of them were screening high risk individuals and providing timely intervention. Therefore, to solve the above problems, the researchers proposed the "biological age (BA)" which defined as the fuctional status of individuals relative to their chronological peers on the basement of the biological indicators or parameters Different rates of individual aging leads to the differences in chronological age and biological age so at any given age, biological age of individuals would be showing great differences and ultimately can be expected to be consistent with the time&magnitude of the differences of longevity and results of the aging process. Biological age study was the premise and foundation of quantitative analysis of individual aging and will help identifying the high risk individualsThe human body is a complex organism, aging of the individual evaluation of use to the multi-level, multi-system physiological indicators. This selection and evaluation were more comprehensive, their combined ability to predict the better end of the event. In the body, the system is extracted from the whole of the abstractions (latent variables), the reaction of the human body, a comprehensive functional status, by itself, can not be directly measured, using a single indicator is unscientific to evaluate the need to use other various indicators to be expressed. Structural equation modeling (SEM) for the latent variable expression and measurement accuracy provides a method of testing. It belongs to multi-dimensional three-dimensional network structure, the structure of the elements involved in not only vertically between the left and right spatial relations, but also was the time before and after, so this method is suitable for longitudinal observational studies and in the logical nature of the information with a horizontal longitudinal information, such as aging research.This study was population-based multi-center cross-sectional study. On the basis of 108 indicators including blood routine, urine routine, blood biochemistry, cardiovascular ultrasound and endocrine factors of healthy people in China, the biomarkers of aging were screened, individual biological evaluation indicators biological age points were constructed, the law of biological aging process in healthy people in China was quantitative analyzed. And on this basis, to expand the scope of the variable selected to establish the structural equation model of biological aging. This study provided the important theoretical basis for our aging individual evaluation studies.Methods1. Establishment of biological aging score(1) Subjects2876 independently living and apparently healthy community-dwelling participants between 30 and 98 years of age were recruited from Beijing, Shenyang, and Dalian cities in China in 2003. Consequently, a total of 852 participants (392 men and 460 women) were enrolled. They were classified as young (< 45 yr), middle-aged (45-59 yr), old (60-74 yr), and very-old (≥75 yr). Informed consent was obtained from all participants.(2) Detection indicatorsa total of 108 indicators were examined including blood pressure, blood routine, urine routine, blood biochemistry, echocardiography, carotid artery ultrasound, endocrine, inflammation and nutrition.(3) Data processingwe excluded the binary variablesand observed the changes of variableswith aging. We performed correlation analysis and choose those variables that were significantly correlated with age and the correlation coefficient> 0.25 of the variables for the next redundancy analysis and principal component analysis in order to screen the biomarkers of aging. Then we performed exploratory factor analysis and use factor scores weighting the biomarkers of aging for building the formula to calculate an individual biological age scores and analyzed the laws of biological aging in healthy population.2. Individual aging evaluation by structural equation modeling(1) Subjects2876 independently living and apparently healthy community-dwelling participants between 30 and 98 years of age were recruited from Beijing, Shenyang, and Dalian cities in China in 2003. Consequently, a total of 852 participants (392 men and 460 women) were enrolled. They were classified as young (< 45 yr), middle-aged (45-59 yr), old (60-74 yr), and very-old (≥75 yr). Informed consent was obtained from all participants.(2) Detection indicatorsA total of 108 indicators were examined including blood pressure, blood routine, urine routine, blood biochemistry, echocardiography, carotid artery ultrasound, endocrine, inflammation and nutrition.(3) Data processingFirst we choose those variables that were significantly correlated with age and correlation coefficient was greater than or equal to 0.15 for redundancy analysis (excluding the highly collinear variables). For those variables with the correlation coefficient greater than 0.65, we selected the one with the highest correlation coefficient with age. Then we developed various systems and organs markers to determine the latent variables and observed variables, draw the road map, construct theoretical models, carry out model and estimate the fitting index, make amendment and re-validation by a variety of fit indices of the model to do the whole evaluation, while the significance of test parameters to evaluate the significance and reasonableness of the parameters to calculate the coefficient of determination, the evaluation equation interpretation of the data capacity, model updating. Finalize the biology of aging structural equation model to explain the model, analysis of various organs and systems biology of aging pattern.Results1. The establishment of biological aging scoreA total of 108 variables including physical characteristics, cardiovascular function, blood and urine biochemical properties, and the state of the inflammation, hormonal and nutritional data, were measured and derived. After having excluded all binary variables and the variables not correlated with CA well (i.e., P>0.05 or r<0.25) or the redundant variables for men and women,12 age-related variables were selected for the analysis of the correlation with CA. At last,8 variables:CA, IMT, EDV, E/A, MVEL, PP, FIB and CYSC, were selected as biomarkers to evaluate BA. The contribution of each variable to the variance of BAS were as follows:CA (20.59%), followed by EDV (12.9%), IMT (12.74%), CYSC (12.47%), PP (11.78%), FIB (11.05%), E/A ratio (9.3%). MVEL variable had the lowest contribution (9.17%). Using the associated factor score coefficients, a weighted composite BAS using 8 age-related variables including CA was created for each individual as follows:BAS= 0.248(CA)+0.195(IMT)-0.196(EDV)-0.167(E/A)-0.166(MVEL)+ 0.188(PP)+0.182(FIB)+0.193(CYSC).We calculate individual BAS for 852 healthy individuals plotted against CA with the predicted line and its 95% confidence interval (r=0.893, P<0.001). Biological aging rate predicted by BAS was accelerated with increases in CA and peaked when healthy men and women reached>75 years old.2. The establishment of structural equation modeling of aging A total of 108 variables including physical characteristics, cardiovascular function, blood and urine biochemical properties, and the state of the inflammation, hormonal and nutritional data, were measured and derived. After having excluded all binary variables and the variables not correlated with CA well (i.e., P>0.05 or r≤0.15) or the redundant variables for men and women,27 age-related variables were selected for the next analysis, however, estradiol and progesterone in male and female age because of changes in in a different direction are excluded. The establishment of the structural equation model of biological aging, aging-related changes of expression in the vascular structure and function (IMT, EDV, PP), cardiac structure (D, LAAPD, LALRD, AD, MVEDT), cardiac function (E/A, MVEL, MVAS, MVAA), inflammatory factors (CRP, IL6, FIB), renal function (BUN, CYSC), liver function (GPT, PRE), nutrition (ALB, HDL, TC, GLU), and blood and endothelial function (MCV, TM, TRF), of which the relationship between vascular factors and aging was greatest (r= 0.90), followed by cardiac function (r= 0.69).Conclusion1. The establishment of biological aging scoreEstablished the integral formula for calculating biological aging score:BAS= 0.248 (timing of age)+0.195 (IMT)-0.196 (EDV)-0.167 (E/A)-0.166 (MVEL)+ 0.188 (PP)+0.182 (FIB)+0.193 (CYSC). Healthy aging rate increases with age to> 75 year-old group then reached its peak.2. The establishment of the individual aging structural equation modelingAging associated changes in expression in the vascular structure and function, cardiac structure, cardiac function, inflammatory factors, renal function, liver function, nutrition, and blood and endothelial function related to vascular factors which most closely with aging (r= 0.90), followed by for the cardiac function (r= 0.69)。...
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