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Prediction of Biological Age

Buslova, Anastasiia (2017) MASM01 20171
Mathematical Statistics
Abstract
The biological age (BA) equation is a prediction model that utilizes an algorithm to combine various biological
markers of ageing. This model has been used to assess the ageing process in a more precise way and may predict
possible diseases better as compared with the chronological age (CA). Here study focus on predicting BA as deviation
from healthy state of aging and treats CA as known and unkown value. The multiple linear regression (MLR),
principal component analysis (PCA) and Klemera and Doubal method (KDM) are applied on data set from Research
Laboratories, Russia. Thesis summarize the up-to-date knowledge about the BA formula construction and discuss the
influential factors, so as to give an overview of BA estimate by PCA,... (More)
The biological age (BA) equation is a prediction model that utilizes an algorithm to combine various biological
markers of ageing. This model has been used to assess the ageing process in a more precise way and may predict
possible diseases better as compared with the chronological age (CA). Here study focus on predicting BA as deviation
from healthy state of aging and treats CA as known and unkown value. The multiple linear regression (MLR),
principal component analysis (PCA) and Klemera and Doubal method (KDM) are applied on data set from Research
Laboratories, Russia. Thesis summarize the up-to-date knowledge about the BA formula construction and discuss the
influential factors, so as to give an overview of BA estimate by PCA, MLR, KDM and group miltiple linear regression,
choices of test items, and selection of ageing biomarkers. It is also discussed the advantages and disadvantages of
every method with reference to the construction mechanism, accuracy, and practicability of several common methods
in the construction of the BA formula. (Less)
Popular Abstract
It is obvious that the estimation of the person's rate of aging does not always correspond to the calendar age (CA). To obtain more appropriate estimates, the concept of biological age (BA) was proposed as an indicator of body's condition, reflecting the degree of age related frailty. Here study focus on predicting BA as deviation from healhy state of aging. This work looks at female population of Russia (3.326 participants for healthy and 12.280 for unhealthy population), and try to estimate what factors are relevant for prediction of age related problems and how important factors change over the life span. Also this study compare several methods of calculating BA and concludes what method gives the best accuracy. Given the potential of... (More)
It is obvious that the estimation of the person's rate of aging does not always correspond to the calendar age (CA). To obtain more appropriate estimates, the concept of biological age (BA) was proposed as an indicator of body's condition, reflecting the degree of age related frailty. Here study focus on predicting BA as deviation from healhy state of aging. This work looks at female population of Russia (3.326 participants for healthy and 12.280 for unhealthy population), and try to estimate what factors are relevant for prediction of age related problems and how important factors change over the life span. Also this study compare several methods of calculating BA and concludes what method gives the best accuracy. Given the potential of BA to highlight heterogeneity, the Klemera and Doubal method algorithm as well as group miltiple linear regression may be useful for studying a number of questions regarding the biology of aging. Estimation of BA could help identifying people who need medical attention, choose a health care plan and measure effectiveness of medication and way of life. (Less)
Please use this url to cite or link to this publication:
author
Buslova, Anastasiia
supervisor
organization
course
MASM01 20171
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8917091
date added to LUP
2017-06-21 10:02:08
date last changed
2017-06-21 10:02:08
@misc{8917091,
  abstract     = {{The biological age (BA) equation is a prediction model that utilizes an algorithm to combine various biological
markers of ageing. This model has been used to assess the ageing process in a more precise way and may predict
possible diseases better as compared with the chronological age (CA). Here study focus on predicting BA as deviation
from healthy state of aging and treats CA as known and unkown value. The multiple linear regression (MLR),
principal component analysis (PCA) and Klemera and Doubal method (KDM) are applied on data set from Research
Laboratories, Russia. Thesis summarize the up-to-date knowledge about the BA formula construction and discuss the
influential factors, so as to give an overview of BA estimate by PCA, MLR, KDM and group miltiple linear regression,
choices of test items, and selection of ageing biomarkers. It is also discussed the advantages and disadvantages of
every method with reference to the construction mechanism, accuracy, and practicability of several common methods
in the construction of the BA formula.}},
  author       = {{Buslova, Anastasiia}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Prediction of Biological Age}},
  year         = {{2017}},
}