CN108475542A - The method that remaining life is predicted by using biological age - Google Patents
The method that remaining life is predicted by using biological age Download PDFInfo
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- CN108475542A CN108475542A CN201680020966.9A CN201680020966A CN108475542A CN 108475542 A CN108475542 A CN 108475542A CN 201680020966 A CN201680020966 A CN 201680020966A CN 108475542 A CN108475542 A CN 108475542A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
Abstract
This disclosure relates to a kind of method measuring people's remaining life by using biological age and survival rate, and relate more specifically to it is a kind of by using by reflection health examination result biological age Measurement Algorithm measurement biological age come the method for measuring survival rate and a kind of method measuring remaining life by using biological age and the survival rate measured by the method.According to the disclosure, remaining life can be than not considering that the remaining life method of existing biological age is more accurately predicted.
Description
Technical field
This disclosure relates to the method that remaining life is measured by using biological age and survival rate, more particularly, to
The side of survival rate is predicted by using the biological age measured by the biological age Measurement Algorithm by reflection health examination result
Method, and method that remaining life is predicted by using the survival rate predicted by the method.
Background technology
Recently, although the cause of disease to human diseases has carried out multinomial research, the major part in them is considered emerging
The disposable information that interest is oriented to.Therefore, in fact they do not have special result in terms of preventing disease.For caused generation
The table prior art, each medical domain have the technology predicted and treat disease.Patent application No.2003-0067652 is
It is related to for diagnosing early liver cancer and its liver cancer forecasting system of control method and its technology of control method, these are designed to
The onset of liver cancer rate for estimating the onset of liver cancer rate of individual and generating the relative risk that liver cancer occurs, and being obtained by each individual
The relative risk occurred with liver cancer carries out the hierarchical classification of the high risk group in relation to liver cancer generation.The technology is designed to store
General information including patient, the information by carrying out ultrasonic generation and result when about patient's initial registration and it is diagnosed as liver
The clinical information of result when cancer and the high risk group information in database, and based on the clinical information and height stored
Danger community information measures the risk of liver cancer generation by calculating the regression coefficient corresponding to the contribution of each risk factors, from
And the prediction occurred according to liver cancer occurs to prevent individual liver cancer.What the liver cancer obtained by onset of liver cancer rate and by individual occurred
Relevant risk establishes customization liver cancer Occurrence forecast model by there is the high risk group by the way that liver cancer occurs to carry out hierarchical classification
The effect on basis.The family doctor of patient is received in the form of short message liver cancer prediction result by mobile communication terminal or passes through electricity
Sub- mail receives as a result, to make it possible the relative risk for continuing to monitor patient.In a damaged condition, having can be immediately
The effect taken action.
As described above, based on the information predicted, conventional Predicting Technique it is most of with specific disease on prospective medicine and
Treatment disease is related, and therefore it can not possibly measure how the service life of people changes according to current health status.
Therefore, the present inventor is it has been confirmed that when predicting residual useful life utility efficiency biological age and by from strong
When the large database in the Korean's service life for the DATA REASONING that sports is got carries out, remaining life can be reliably predicted, and
And complete the present invention.
Invention content
Purpose of this disclosure is to provide use to measure based on the biological age measured by the data obtained from health examination
The method of survival rate.
Another object of the present disclosure is to provide a kind of by using biological age and the survival rate measured by the method
Method to measure remaining life.
In order to realize the purpose, present disclose provides use following equation (1) and by using health examination result
Measured biological age is come the method for predicting survival rate：
Equation (1)
In above equation (1), S0(t) life after the current time-to-live point t away from national statistics office data is indicated
Rate is deposited, D indicates biological age (biological the age)-exact age (chronological age),Indicate being averaged for D
Value, a indicate influences of the D to survival rate, andIndicate the survival rate after adjusting t by using biological age.
The disclosure additionally provides a kind of method of prediction remaining life, wherein is designated as expected remaining life in x-axis
(ER) and y-axis is designated as in the figure of the survival rate after T, the x-axis value quilt corresponding to y-axis examinate's survival rate value
It is appointed as carrying out the same day remaining remaining life of health examination from examinate.
Description of the drawings
The method that Fig. 1 briefly shows the prediction remaining life according to the disclosure.
Fig. 2 shows the average survival time rate based on the exact age after T according to national statistics office data in 2013.
Fig. 3 is according to national statistics office data in 2013 until the given age of South Korea for each person is expected the life of remaining life
Deposit rate figure.
Fig. 4 is 50 years old old man (D=biology years by being measured according to the method for measuring remaining life of the disclosure
Age-exact age=0) survival rate figure.
Fig. 5 is 50 years old old man (D=biology years by being measured according to the method for measuring remaining life of the disclosure
Age-exact age=5) survival rate figure.
Fig. 6 is 50 years old old man (D=biology years by being measured according to the method for measuring remaining life of the disclosure
Age-exact age=- 5) survival rate figure.
Fig. 7 is the figure for showing 10,000 Korean males and being distributed according to the estimation life expectancy of the disclosure.
Fig. 8 is the figure for showing 10,000 South Korea women and being distributed according to the estimation life expectancy of the disclosure.
Specific implementation mode
Unless otherwise stated, the technical and scientific term for this specification has and disclosure technical field
The normally understood identical meaning of technical specialist.The term for being commonly used for this specification is well known, and is commonly used in this skill
Art field.
In the disclosure, term " exact age (CA) " refers to the survival to the same day for carrying out health examination based on the date of birth
Year, and after term " biological age (BA) " refers to and is reflected in using health examination project as the statistic algorithm of input value
The age of calculated individual health situation.
In the disclosure, term " T survival rates (SR) " refers to based on the same day for carrying out health examination, from now to next year
Survival possibility, term " it is expected that remaining life (ER) " referred to based on the same day for carrying out health examination, the year that can survive of future,
And term " life expectancy (LE) " refers to when carrying out health examination, the exact age (CA)+expection remaining life (ER).
In the disclosure, term refers to x-axis " to the survival rate figure (SP2ER) of life expectancy " and is arranged to expected remaining life
(ER), and y-axis is arranged to the figure of the survival rate (SR) after T (by gender and character classification by age, data is by State Statistics Bureau's public affairs
Cloth).
In the disclosure, term is referred to " based on the survival rate (SPBA) after biological age T " by using in progress health
The survival rate of exact age (CA) that same day of physical examination calculates and biological age (BA) and T survival rates (SR) and calculating is biological
Survival rate.
In the disclosure, term is referred to " based on biological age (BA) to the survival rate figure (SP2ERBA) of expected remaining life "
The biological age (BA) of expection remaining life (ER) and y-axis based on x-axis be designated as T survival rates (SPBA) (by gender and
Character classification by age) figure.
In the disclosure, term " remaining life (RL) " refers to from the same day remaining survival year for carrying out health examination,
By using the survival rate figure (SP2ER) to expected remaining life and the life based on biological age (BA) until being expected remaining life
Rate figure (SP2ERBA) is deposited to calculate.
On the one hand, this disclosure relates to using by using the biological age and following equation measured by health examination result
Formula (1) is come the method that measures survival rate：
Equation (1)
In above equation (1), S0(t) life after the current time-to-live point t away from national statistics office data is indicated
Rate is deposited, D indicates biological age-exact age,Indicate that the average value of D, a indicate influences of the D to survival rate, andIt indicates
Survival rate after adjusting t by using biological age.
In above equation (1), S0(t) it is the survival rate provided every year for each male and female by State Statistics Bureau
It is worth (http://kosis.kr/statHtml/statHtml.doOrgId=101＆tblId=DT_1B42＆vw_cd=MT_
ZTITLE＆list_id=A5＆seqNo=＆lang_mode=ko＆language=kor＆obj_v ar_id=＆itm_id=＆
Conn_path=E1#).
In equation (1), a be by using use survival data as input value cox proportional hazard models algorithm from
The dynamic value calculated, and the business or free analysis software such as SPSS or SAS, R program of execution conventional statistical analysis can be passed through
The realizations such as packet.Here, survival data refers to containing the examinate for each having already passed through health examination when observing particular point in time
Whether the data of dead or existence information.
In one preferred embodiment, a values and can be had according to the age according to the value in the equation (1) of the disclosure
Such as the value in table 1, but not limited to this.
[table 1]
In the disclosure, biological age is measured by following equation (2)~(3)：
Equation (2)
Equation (3)
Wherein, preBA is indicated through the preceding biological age (pre-biological age) before equation (3) modification, BA
It indicates to be based on the modified biological age of the preceding biological age (preBA), xjIndicate the jth item inspection item of examinate
Check numerical value,Indicate the average value of all samples of jth item inspection item, sd (xj) indicate all of jth item inspection item
The standard deviation of sample, βijExpression is examined using principal component analysis (principal component analysis) by jth item
I-th of factor value of project is looked into explain that the degree of each sample actual age, m expressions obtain by carrying out principal component analysis
Factor quantity, PiIndicate that the weighted value calculated preBA by i-th of factor value, y indicate the exact age of each individual
(CA),Indicate that the average value for establishing the individual exact age (CA) of each of biological age (BA) model, sd (y) indicate y
Standard deviation, andIt indicates to constitute and be generated as the actual age of each sample and the Regression Analysis Result of preBA
Regression equationCoefficient.
In the disclosure, βijCan be two or more variable (X by will be measured by health examinationj) it is input to use
The value of gained is calculated in the principal component analysis statistic algorithm of SPSS, SAS and R program bag (package) and m represents principal component
The quantity of factor, and be automatically true when characteristic value (eigen value) is arranged to 1 when executing Principal Component Analysis Algorithm
Fixed value.
In an embodiment of the disclosure, in the side described in Korean Patent Publication text No.2014-0126229
Method can be used for measuring biological age.
In the disclosure, feature can be, when examinate is male, x is health examination item selected from the following
Purpose result value：Waistline (WC), forced expiratory volume in 1 second (FEV1), liver enzyme (G-GTP), blood urea nitrogen (BUN), high density fat
Albumen (HDL), low-density lipoprotein (LDL), triglycerides (TG), fasting blood-glucose (FBS), body fat percent (FBR), muscle
The number of results of rate (BMR), A/G albunin globuline ratio example (AGR) and systolic pressure (SBP) or health examination project selected from the following
Value：Waistline (WC), systolic pressure (SBP), liver enzyme (G-GTP), high-density lipoprotein (HDL), triglycerides (TG), fasting blood-glucose
(FBS), hemoglobin (Hemoglobin), low-density lipoprotein (LDL), body mass index (BMI) and pulse pressure (PP).
In the disclosure, feature can be, when examinate is women, x is health examination item selected from the following
Purpose result value：Waistline (WC), forced expiratory volume in 1 second (FEV1), γ-GTP (G-GTP), blood urea nitrogen (BUN), high density
Lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), fasting blood-glucose (FBS), body fat percent (FBR), flesh
Meat rate (BMR), A/G albunin globuline ratio example (AGR), diastolic pressure (DBP), erythrocyte sedimentation rate (ESR) (ESR) and body mass index
(BMI) or the result value of health examination project selected from the following：It is waistline (WC), diastolic pressure (DBP), liver enzyme (AST), highly dense
Spend lipoprotein (HDL), triglycerides (TG), fasting blood-glucose (FBS), hemoglobin, low-density lipoprotein (LDL), body mass index
(BMI) and pulse pressure (PP).
In the biological age prediction model for the disclosure, one or more can be inputted as existing inspection data
Sample.In biological age computation model, all samples can be inputted, no matter whether sample is included in biological age computation model
In variable (inspection item) inspection numerical value, it is preferred that only input is included in the institute of variable in biological age computation model
There is the sample for checking numerical value.For example, will only have all BMI to check numerical value, pulmonary function test numerical value and forced expiratory volume in 1 second
It checks that the sample of numerical value is input to first biological age computation model, and will only have all BMI to check numerical value, lung function
Check that numerical value and PSA check that the sample of numerical value is input to second biological age computation model.
After one or more samples are input to biological age computation model, principal component analysis can be on the input data
It carries out.By principal component analysis, one or more can enter data into can be obtained and be construed to biological age computation model
Factor.The quantity of obtained factor can be less than the quantity of biological age computation model variable.Hereinafter, the quantity of factor is described
Quantity for m, and biological age computation model variable is described as n.
In accordance with one embodiment of the present disclosure, by principal component analysis, it is included in input biological age computation model
I-th of factor value in j-th of variate-value of each sample can calculate weight (βij), refer to the degree for explaining actual age.βij
Value is the value calculated by Principal Component Analysis commonly known in statistical analysis.That is, βijIt is when progress principal component analysis process
The ingredient of the factor loading matrix of the calculated each variables of Shi Zidong.
In accordance with one embodiment of the present disclosure, the weight (P that the biological age of i-th of factor value calculates is giveni) can be with
It is calculated by principal component analysis.Hereinafter, the method for calculating weighted value (Pi) will be explained.
Weighted value (Pi) can by using actual age and from the calculated each sample of principal component analysis it is each because
Determination coefficient (R between several factor scores2) calculate.It is carried as follows using the computational methods of the weighted value (Pi) of determining coefficient
For.
First, calculate the factor score for each factor of each sample of analysis by principal component analysis.For example, such as
Fruit has 100 samples and m factor, will calculate 100 factor scores for each of m factor.
Then, the factor score of each sample and the actual age of each sample are analyzed using returning to calculate determining system
Several m numbers Ri 2, i=1,2,3 ..., m.Assuming that determining that the m number summations of coefficient are S, biological age meter is given by i-th of factor
Weighted value (the P of calculationi) following mathematical equation 1 can be used to calculate.
[mathematical equation 1]
Weighted value (Pi) can be calculated by using the characteristic value from the calculated each factor of principal component analysis.This
When, weighted value (Pi) following mathematical equation (2) can be used to calculate.
[mathematical equation 2]
In the above mathematical equation (2), eiIt is the characteristic value of factor i, and m is the quantity of factor.
It, can be by using according to the biological age calculation formula of biological age computation model when completing principal component analysis
Factor generates.
According to one embodiment, biological age can be calculated according to the mathematical equation (3) based on equation (2).
Equation (2)
(wherein, preBA indicates preceding biological age, xjIndicate the inspection numerical value of the jth item inspection item of examinate,Table
Show the average value of all samples of jth item inspection item, sd (xj) indicate jth item inspection item all samples standard deviation
Difference, βijI-th of factor value of the jth item inspection item by being used as principal component analysis result is indicated to explain that each sample is practical
The degree at age, m are denoted as the result for carrying out principal component analysis and the factor quantity and P that obtainiExpression is given as
The weighted value that the BA of i factor value is calculated.)
[mathematical equation 3]
(in the above mathematical equation 3, BA indicates that biological age, preBA and preBA' indicate preceding biological age, xjTable
Show the inspection numerical value of the jth item inspection item of examinate,Indicate the average value of all samples of jth item inspection item, sd
(xj) indicate jth item inspection item all samples standard deviation, βijIndicate the jth item by being used as principal component analysis result
I-th of factor value of inspection item explains the degree of the actual age of each sample, and m is denoted as carrying out principal component analysis
As a result the quantity of the factor obtained, Pi indicate that the weighted value that the preBA for giving i-th of factor value is calculated, y indicate each individual
Exact age (CA),Indicate exact age (CA) average value for establishing the exact age each of (BA) model individual,
Sd (y) indicates the standard deviation of y, andWithIt indicates to constitute as the actual age of each sample and the regression analysis of preBA
As a result the regression equation generatedCoefficient.)
In the above mathematical equation (3), according to one embodiment, y average values are the actual age of all samples
Average value and sd (y) can be the standard deviations of the actual age of all samples.According to another embodiment, y average values
It is reality of the data with each inspection item being included in biological age computation model as all samples of virtual value
The average value and sd (y) at age can be the data with each inspection item being included in biological age computation model
The standard deviation of the actual age of all samples as virtual value.
In conclusion one or more factors are by entering data into biological age computation model and by inputting number
According to principal component analysis and obtain, and biological age calculation formula can be obtained by using principal component analysis result and factor
.It, can preferred equation (2) or mathematical equation 3 as the example of biological age calculation formula.
When the inspection item being included in the inspection result data of the examinate is added to biology one by one as variable
When age computation model, it is construed as finding to constitute one group of variable of the biological age computation model of extraction optimum
Process.That is, using so-called stepwise forward selection (step-by-step forward selection) method, wherein choosing
The original collection of best one inspection item is selected, and selected inspection item is as the biological age calculating for being initially sky
The variable of model is added.
Hereinafter, stepwise forward selection method will be explained.Assuming that original collection includes BMI, lung capacity, one second forced expiration
The total of five inspection item of amount, albumin (albumin) and PSA is as element.
As the first step, generation includes the test model of unitary variant.Then, by the sample of the value including relevant variable,
The inspection numerical value of i.e. corresponding inspection item is input to generated test model, and carries out principal component point in input sample
Analysis is to obtain factor.Biological age calculation formula is generated by using the result of the factor and principal component analysis that are obtained.With
Under, it is experiment inspection item by the new variable description that test model is added.Then, each input sample is inputted into biological age meter
Formula is calculated to calculate the biological age of each sample.
Then, simple regression equation BA=a+by passes through the regression analysis generation to sample distribution.Therefore, it can obtain
Obtain the tropic of sampleDetermination coefficient (the R of (BA=y) between actual age2).Display is used as first
The result of step and the determination coefficient value of each inspection item obtained.As the first step as a result, selection is had maximum value
Lung capacity.It includes that breathing checks numerical value that this, which refers in biological age computation model,.Breathing inspection item is removed from original collection,
Because it is added in biological age model.Second, selection is included in second in biological age computation model
Inspection item.The test model of second step is with two changes in total for including one of breathing inspection item and other inspection items
The model of amount.Therefore, in second step, total of four experiment (lung capacity, BMI), (lung capacity, one second forced expiration will be carried out
Amount), (lung capacity, albumin), (lung capacity, PSA).
Then, by the value including relevant variable, i.e., the sample of the inspection numerical value of corresponding inspection item is input to generated
In biological age computation model, and principal component analysis is carried out to obtain factor to input sample.Biological age calculation formula is logical
It crosses and the result of obtained factor and principal component analysis is used to generate.
Then, each input sample is input to calculate the biological age of each sample in biological age computation model,
And simple regression equationPass through the regression analysis generation to sample distribution.Thus, it is possible to obtain sample
This tropicDetermination coefficient (R between actual age (BA=y)2)。
It is to increase model compared with existing determining coefficient 0.4 and determine coefficient as second step as a result, BMI will be selected
The maximum inspection project of amplification of value.It includes BMI values and breathing value that this, which refers in biological age computation model,.BMI inspection items
It is removed from original collection, because it has been added to biological age computation model.Third, selection are included in biological age
Third inspection item in computation model.Third step test model be have include breathing inspection item, BMI and other examine
Look into the model of the total of three variable of one of project.Therefore, in second step, will carry out total of three experiment (lung capacity, BMI,
Forced expiratory volume in 1 second), (lung capacity, BMI, albumin), (lung capacity, BMI, PSA).Third walks also with similar with second step
Method carries out.The determination coefficient value of forced expiratory volume in 1 second is only the increased value compared with existing determining coefficient value 0.5, and because
This selects forced expiratory volume in 1 second as the third inspection item being included in biological age computation model.One second forced expiration
Amount is removed from original collection.
4th, the third inspection item being optionally comprised in biological age computation model.
Remaining two inspection items all make biological age calculate the determination coefficient having less than existing determining coefficient 0.6.
As proceeding to the 4th step as a result, being the situation that a kind of not additional inspection item is present in original collection.Therefore, exist
4th step is gradually carried forward step and terminates.It is therefore preferable that only three kinds of BMI in five kinds of inspection items, lung capacity, one second firmly
Expiration amount is included in the biological age computation model of the examinate.Gradually it is carried forward the biological age at the end of step
Computation model is confirmed as the biological age computation model for being applied to check data.
Then, the inspection data received can be input to the biological year according to identified biological age computation model
Age calculation formula is to calculate the biological age of examinate.
According to one embodiment, next examinate can be used as by adding inspection data to sample data
Sample.
Stepwise forward selection step according to the present disclosure is the inspection in the inspection data for being included in examinate
The process for the inspection item that at least part is included in biological age computation model is added in project one by one.According to the number
According to due to carrying out stepwise forward selection step, the case where continuing to increase with determining coefficient value.It is understood, therefore, that being included in
All inspection items in the inspection data of examinate can be included in biological age computation model.
At the same time, it is using the advantages of can showing sample similar with the figure of inspection data of examinate, it is raw
At more accurate biological age computation model.Therefore, the sample inputted in the test model of stepwise forward selection step can be with
It is restricted to the sample with personal information similar with the examinate for checking data.For example, defeated in test model
The sample entered is identical as the gender of examinate, and can be restricted to have predetermined model based on the actual age of examinate
The actual age enclosed.
In stepwise forward selection step, additional selection criteria can be used, and is determined and existing test model
It determines that coefficient is compared, determines whether coefficient is added to maximum.
According to one embodiment, the case where the sample size with experiment inspection item data is less than predetermined threshold
Under, it may be excluded and test except inspection item.According to another embodiment, with being included in test model
In the case that the sample size of all inspection numerical value of inspection item is less than predetermined threshold, it may be excluded in experiment check item
Except mesh.Because if the quantity of sample is less than threshold value, it is difficult to provide reliability as statistical data.
In addition, according to one embodiment, the phase relation at least one inspection item being included in test model
Number (R) may be excluded more than the experiment inspection item of predetermined threshold and test except inspection item.This be in order to prevent, when with
Being included in the inspection item in test model, there is the inspection item of high correlation to be included in test model again
When, it reduces existing inspection item and enjoys negative effect affected in test model.In addition, when the inspection with high correlation
When the project of looking into is included in test model, matrix calculating process phase that singularity problem carries out during principal component analysis process
Between occur, the problem of to prevent from not calculating characteristic value suitably.
In order to which related coefficient calculates accurate, related coefficient can be used whole to be checked be included in test model
The sample data of the inspection numerical value of project calculates.
In an embodiment of the disclosure, according to after current time-to-live point (national statistics office data) T
Survival rate can use the expection remaining life table of such as table 2 and Fig. 2.
In addition, the age specific survival rate of an embodiment of the disclosure is shown in table 3.
[table 2]
[table 3]
On the other hand, this disclosure relates to the method for being used to measure remaining life, which is characterized in that be designated as in x-axis
It is expected that remaining life (ER) and y-axis be designated as by using measured by health examination result biological age and by by making
After the T measured with the method for equation (1) measurement survival rate in the figure of survival rate, correspond to the x-axis of the survival rate of y-axis
Value is designated as from the progress health examination same day remaining remaining life.
As shown in Figure 1, the method for predicting remaining life described in the disclosure is designed to by using measurement target
Gender, age data, health examination data and biological age computational algorithm (equation (2) to (3)) come calculate individual life
The object age, and after calculating by using biological age and equation (1) the age specific survival rate after t, x-axis is defined as
It is expected that remaining life (ER), and y-axis is defined as the survival rate after the t measured by the method, with by using aobvious
Show the figure of survival rate after the t measured by the method to calculate the remaining life of gender and age.
The computing system of the remaining life of the disclosure uses the age specific existence based on national statistics office data in 2013
Rate value (is shown in Table 2 and Fig. 4), and but not limited to this.To those of ordinary skill in the art it is evident that accuracy can pass through
Improve using by State Statistics Bureau is annual or each fixed time period announces again value.
The method of prediction remaining life according to the present disclosure will be explained by specific embodiment.50 years old Korean males
The average remaining lifetime of (exact age 50) is 30.57 years old (being shown in Table 1).The survival rate of 50 years old males is about 0.5595 (to be shown in Table
2)。
Hereafter, x-axis is designated as expected remaining life (ER), and y-axis is designated as the t measured by the method
Survival rate afterwards.After the t that display is measured by the method in the figure of survival rate, survival rate value is located at y-axis, and thus sets
Set the dotted line for being parallel to x-axis.Meet the x-axis value of the point of 50 years old man's survival rate figure as according to the very remaining life of the disclosure
(Fig. 4).
At the same time, in 50 years old Korean male, if measuring biological age than full year by using survival rate figure
The remaining life of the people in old 5 years old of age (D=biological ages-exact age=5), then can determine that remaining life is substantially less than 30.5
Year (Fig. 5).
In addition, 5 years old younger than the exact age as biological age in 50 years old Korean male is measured by using survival rate figure
The result of the remaining life of the people of (D=biological ages-exact age=- 5), it may be determined that remaining life is significantly higher than 30.5 years old
(Fig. 6).
In a specific embodiment, as by using the side according to the present disclosure for predicting remaining life
Method, as a result, when determining the life expectancy of the male with 50 years old exact age, is found when (biological age-is full by D calculating
Age) when being -4.5 years old, it is contemplated that the service life is 91.9 years old, when D=0 Sui, it is contemplated that the service life is 80.8 years old (Korean's average value), and
And when D=4.5 Sui, it is contemplated that the service life 69.3.
In another embodiment, as the life expectancy for determining the women with 50 years old exact age as a result, hair
When D=-4.3 Sui existing, it is contemplated that the service life 94.3, when D=0 Sui, it is contemplated that the service life is 86.3 (Korean's average values), and works as D
At=4.2 years old, it is contemplated that the service life 79.1.
In the another embodiment of the disclosure, by using the side for measuring remaining life according to the disclosure
Method by age divides 10,000 Korean male/women to measure remaining life, and its result is shown in Fig. 7 and 8.
As described above, having been described in the specific part of present disclosure.Therefore, there is ordinary skill to related field
Personnel it is readily apparent that the special technique is only preferred embodiment, and the scope of the present disclosure is without being limited thereto.
Therefore, the essential scope of the disclosure is defined by the following claims and their equivalents.
Industrial applicibility
According to the disclosure, remaining life can be than not considering that the remaining life prediction method of existing biological age is more accurately pre-
It surveys.
Claims (8)
1. predicting the side of survival rate using following equation (1) and by using the biological age measured by health examination result
Method：
Equation (1)
In above equation (1),
S0(t) survival rate after the current time-to-live point t away from national statistics office data is indicated,
D indicates biological age-exact age,
Indicate the average value of D,
A indicates influences of the D to survival rate, and
Indicate the survival rate after calibrating by using biological age and calculating t.
2. the method as described in claim 1, the biological age is measured by following equation (2)~(3)：
Equation (2)
Equation (3)
Wherein,
PreBA indicates the preceding biological age before being changed by equation (3),
BA expressions are based on the modified biological age of the preceding biological age (preBA),
xjIndicate the inspection numerical value of the jth item inspection item of examinate,
Indicate the average value of all samples of jth item inspection item,
sd(xj) indicate jth item inspection item all samples standard deviation,
βijIt indicates to explain each sample actual age by i-th of factor value of jth item inspection item using principal component analysis
Degree,
M indicates the quantity of the factor obtained by carrying out principal component analysis,
PiIndicate the weighted value calculated preBA by i-th of factor value,
Y indicates the exact age (CA) of each individual,
Indicate the average value for establishing the individual exact age (CA) of each of biological age (BA) model,
Sd (y) indicates the standard deviation of y, and
It indicates to constitute the regression equation generated as the actual age of each sample and the Regression Analysis Result of preBACoefficient.
3. method as claimed in claim 2, βijIt is two or more variable (X by will be measured by health examinationj) input
To the value being calculated in principal component analysis statistic algorithm.
4. method as claimed in claim 2, when examinate is male, x is the knot of health examination project selected from the following
Fruit numerical value：Waistline (WC), forced expiratory volume in 1 second (FEV1), liver enzyme (G-GTP), blood urea nitrogen (BUN), high-density lipoprotein
(HDL), low-density lipoprotein (LDL), triglycerides (TG), fasting blood-glucose (FBS), body fat percent (FBR), muscle rate
(BMR), A/G albunin globuline ratio example (AGR) and systolic pressure (SBP).
5. method as claimed in claim 2, when examinate is male, x is the knot of health examination project selected from the following
Fruit numerical value：Waistline (WC), systolic pressure (SBP), liver enzyme (G-GTP), high-density lipoprotein (HDL), triglycerides (TG), fasting blood
Sugared (FBS), hemoglobin, low-density lipoprotein (LDL), body mass index (BMI) and pulse pressure (PP).
6. method as claimed in claim 2, when examinate is women, x is the knot of health examination project selected from the following
Fruit numerical value：Waistline (WC), forced expiratory volume in 1 second (FEV1), γ-GTP (G-GTP), blood urea nitrogen (BUN), high-density lipoprotein
(HDL), low-density lipoprotein (LDL), triglycerides (TG), fasting blood-glucose (FBS), body fat percent (FBR), muscle rate
(BMR), A/G albunin globuline ratio example (AGR), diastolic pressure (DBP), erythrocyte sedimentation rate (ESR) (ESR) and body mass index (BMI).
7. method as claimed in claim 2, when examinate is women, x is the knot of health examination project selected from the following
Fruit numerical value：Waistline (WC), diastolic pressure (DBP), liver enzyme (AST), high-density lipoprotein (HDL), triglycerides (TG), fasting blood-glucose
(FBS), hemoglobin, low-density lipoprotein (LDL), body mass index (BMI) and pulse pressure (PP).
8. a kind of method of prediction remaining life, wherein be designated as expected remaining life (ER) in x-axis and y-axis is referred to
It is set in the figure of the survival rate after the T as measured by selected from the method described in claim 1 to 7, y-axis examinate life
The x-axis value corresponding to rate value is deposited to be designated as carrying out the same day remaining remaining life of health examination from examinate.
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| KR10-2015-0030331 | 2015-03-04 | ||
| KR1020150030331A KR101669526B1 (en) | 2015-03-04 | 2015-03-04 | Method for Assessinging Residual Life Using Biological Age |
| PCT/KR2016/000353 WO2016140432A2 (en) | 2015-03-04 | 2016-01-13 | Method for predicting residual life using biological age |
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| KR (1) | KR101669526B1 (en) |
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| JP2018512659A (en) | 2018-05-17 |
| HK1256728A1 (en) | 2019-10-04 |
| JP6640868B2 (en) | 2020-02-05 |
| KR20160107508A (en) | 2016-09-19 |
| KR101669526B1 (en) | 2016-10-26 |
| WO2016140432A2 (en) | 2016-09-09 |
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