Glycative Stress Research
Online edition : ISSN 2188-3610
Print edition : ISSN 2188-3602
Received : December 1, 2017
Accepted : January 10, 2018
Published online : March 31, 2018

Original article

Let’s aim at our healthy longevity with positive thinking (resilience)! :The results of 351 subjects enrolled in Anti-Aging Medical Survey
Takafumi Kusano 1), Kiyoshi Yasui 2)
1) Division of Anti-Aging Dock, Aeba Surgical Hospital, Osaka, Japan
2) Yotsubashi Clinic, Osaka, Japan

Abstract

Objectives: Wisconsin card sorting test (WCST) is known to be useful for evaluate prefrontal lobe function. 351 subjects
were examined for their brain functional age by WCST, and were also examined for the correlation between brain functional
age and mental stress symptoms. Here, we investigated rejuvenation of brain functional age for the effect of improvement ofnegative mental symptoms and resilience.
Methods: 351 subjects participated in our Anti-Aging medical survey, 179 men, average age 63.5 year and 172 women,
average age 65.7 year, between April 2006 and December 2016. We evaluated mental stress symptoms by use of Anti-Aging
Common QOL Questionnaire.
Results: The parameters of WCST were significant with aging. There is a gender difference for the correlation between
mental stress symptoms and aging. Young women have a lot of mental stress symptoms, but they decrease with age. On
the other hand, in men, mental stress symptoms increase with age. Increasing grip strength, quadriceps muscle, WBI,
basal metabolism, preventing sarcopenia, frailty is important to keep young brain age. In multivariate analysis Diabetes,
hypertension and obesity increased brain age, and decreased prefrontal function.
Conclusions: Elderly women exhibited younger brain age than men, Elderly women with strong resilience showed few
symptoms of mental stress and showed extended healthy life expectancy. To reduce symptoms of mental stress which
accelerate brain aging, it is important to maintain and increase thigh muscle mass, and avoid fraily. Maintaining a young
brain age prevents lifestyle diseases, and dementia, and increases healthy life expectancy.

KEY WORDS: Wisconsin card sorting test, Brain functional age, Prefrontal lobe function, Lifestyle disease, Frailty,		

Dementia, Healthy life expectancy

Introduction

An Anti-Aging Medical Checkup (AAMC) is forthe purpose of implementing guidance for lifestyle habit
improvements in order to aim at healthy longevity by
improving aging balance based upon the test results ofvascular age, muscle age, bone age, hormone age and neuralage 1-3). The Wisconsin card sorting test (WCST) is used
for the measurement of neural age 4, 5). This is often used inclinical sites because it is said to be useful for the examinationof functional disorders in the prefrontal cortex 6, 7). It is also
possible to download it from the Japan Stroke Data Bank forfree 8). In this research, we analyzed the data of the AAMC
examinees conducted in their hospital and discussed therelationship of brain age and mental stress with other physicalinformation.

Corresponding to: Takafumi Kusano MD. PhD
Division of Anti-Aging Dock, Aeba Surgical Hospital
4-6-5 Katsuyama Minami, Ikuno-ku, Osaka 544 - 0 021 Japan
TEL: + 81- 6 - 6715 - 0771 eMail: ugg86053@nifty.com
Co-author: Yasui K, mook@minos.ocn.ne.jp

Subjects and Method

The subjects were 179 males (average age: 63.5 years(95% confidence interval [CI]: 61.6 ~65.3)) and 172 females(average age: 65.7 (95% CI: 63.8 ~ 67.5)), 351 in total(including plural checkups), who received AAMC (called
Anti-Aging Dock in this hospital) from June 2006 to
December, 2016. The subjects received WCST for the purposeof age rating of neurological function.
The examinees received guidance for “positive thinking(resilience).” The main part of the resilience guidance inthis hospital consisted of individual image trainings leading
to positive thinking. For example, for a female examinee, adinner party or window-shopping with a friend with whom
she is at ease and can consult is arranged: and for a maleexaminee, events concerning music, sports or reading are_ 21 _

Glycative Stress Research 2018; 5 (1): 021-029(c) Society for Glycative Stress ResearchSurvey of 351 Caces in Anti-Aging Medical Checkup

arranged, where he can enjoy his habit and receive training.
The evaluations of the functional ages of muscles,
vascular system, nerves, hormones and bones were conductedby AAMC, and the evaluation was carried out using an AntiAging Quality of Life Common Questionnaire (AAQOL) 9).
Muscles were measured using bioelectrical impedancemuscle mass measurement (Phyion-MD: Nippon Shooter Ltd.,Tokyo). The masses of upper and lower limbs, weight bearing
index (WBI), body fat percentage (%), basal metabolism (kcal/day), water volume (kg), muscle rate (%) and bone mass (kg)were measured. WBI is defined as quadriceps muscle/bodyweight ratio. Muscle age was evaluated using these indexes.
Higher brain function was measured using WCST.
WCST is a test to observe the reactions of an examinee by
showing cards with graphics of triangles, stars, crosses andcircles in red, green, yellow and blue, a kind of card game.
The examinee analogizes to which category a new cardshould be classified to between color, figure and number.
The frontal cortex function and neural age (called “brainage” in this hospital) of the examinees were evaluated using
the parameters of categories achieved (CA), numbers of
response cards used until the first category achieved (NUCA),
total errors (TE), percentage of perseverative errors of theMilner type (%PEM), percentage of perseverative errors of
the Nelson type (%PEN) and reaction time which means card
selection total time.
Dehydroepiandrosterone-sulfate (DHEA-s), insulin-likegrowth factor-I (IGF-I) and cortisol were measured for theevaluation of hormone age.
The relationships between neural age related indexes andother items were analyzed.

Ethical Standards
Before the start of this research, written letters ofconsent were obtained from the subjects and this research
was conducted with the approval of the ethics committee ofDoshisha University (Application Nos. #0832 and #14089).

Results

WCST and Aging

The results of WCST are shown in Fig. 1. Significant
relationships of real ages with categories achieved (CA),numbers of response cards used until the first category
achieved (NUCA), total error (TE), percentage preservative
errors of the Nelson type (%PEN) and reaction time wereobserved.

Mental Symptoms and Aging

The results of 21 factors of mental symptoms of the
AAQOL recommended by the Japanese Society of AntiAging Medicine are shown. The relationships between
the total score of mental symptoms and neural age wereanalyzed. The mental symptoms become severe with aging
in males and, on the contrary, it was improved with aging infemales (Fig. 2). It was at the age of 65, and when the total
score of mental symptoms was 50, that the regression linesof males and females were crossed. There were many males

who were older than 65 and had severe mental symptoms(total score > 50) and there were many young females who
had severe mental symptoms (total score > 50).
The correlation analysis between mental symptom andreal age is shown in Table 1. In the case of males, the scoreof “Depressed,” a mental symptom, increased with aging,and on the contrary, it decreased with aging (Fig. 3 ) in
females. Similar differences between males and females canbe recognized in other factors. The scores of “No feelingof happiness,” “Nothing to look forward to in life,” “ Daily
life is not enjoyable” and “ Loss of confidence” increased
with aging in males, and on the contrary, the scores of these
symptoms decreased in females. The scores of “Lapseof memory,” “Inability to sleep because of worries” and“Difficulty in falling asleep” increased with aging in bothmales and females.

Correlation between body composition changes
and neural age

Table 2 shows the correlation analysis between bodycomposition changes and neural age.
In the case of males, grip strength, muscle mass, basal
metabolic rate, brachial muscle and femoral muscle showednegative correlations with neural age, and it was found thatthe amount of muscle mass greatly affected neural age.
Increasing femoral muscle and brachial muscle mass, inparticular, greatly related to the rejuvenation of neural age.
In the case of females, it was recognized that increases
in BMI, body fat and waist circumference have a positive
correlation with neural aging and that grip strength and
WBI have negative correlations with neural aging. It can besaid that increasing grip strength and WBI is important for
maintaining a young neural age.
It was shown that increasing grip strength wasrecognized to relate to the rejuvenation of neural age for bothmales and females.
The relationships of neural age with cortisol, which isa stress hormone, and DHEA-s /Cortisol ratio (D/C ratio),which is an indicator of resistance, are shown in Fig. 4. No
significant relationship between cortisol and neural age
was observed in males, but a very weak relationship (R2 =0.025) was observed in females. The D/C ratio showed very
weak negative correlation with neural age in both males andfemales (male: R2 = 0.116, female: R2 = 0.070), and the more
the D/C ratio rose, the more neural age was rejuvenated.
A multivariate analysis of the relationships between
lifestyle diseases and neural age was conducted (Table 3).
There were diabetes, hypertension and obesity as the risk
factors involved in neural aging in males and only obesity
was a risk factor involved in neural aging in females.

Factors affecting the changes in neural age

The repeat examinees who received AAMC multiple
times were 64 males and 40 females, 104 in total. They
received guidance in “positive thinking (resilience)”. Thechange in the condition of mental symptoms before and after
the guidance, and its effect on neural aging, were analyzed
by a one-way analysis of variance (AVOVA)In the case of males, the improvement of the score of“Depressed” was connected to the rejuvenation of neuralage, and its exacerbation led to neural aging (Fig. 5). The
exacerbation of the score for the symptom of “Nothing to_ 22 _Glycative Stress Research

14
12
10

4

8

3
2

6

5

0
20

30

40

50

60

Age (year)

70

80

90

20

30

40

50

60

Age (year)

70

80

90

b)

50

40

40

30

30

%PEN

50

20

10

0

0
30

40

50

60

Age (year)

70

80

90

d)

30

40

20

30

40

50

60

70

80

90

50

60

70

80

90

Age (year)

600

20

10

20

20

c)

Reaction time (second)

a)

15
10

4
2

1

%PEN

20

TE

5

NUCA

CA

6

20

30

40

50

60

Age (year)

70

80

90

e)

500
400
300
200
100
0

Age (year)f)Fig. 1. Relationship between WCST parameter and aging.

a) CA, y = −0.01x + 5.59, R2 = 0.027, p = 0.002. b) NUCA, y = −0.02x + 3.02, R2 = 0.019, p = 0.009. c) TE, y = 0.04x + 12.17, R2 = 0.079,
p = 0.010. d) %PEM, y = 0.04x + 7.18, R2 = 0.002, p = 0.391. e) %PEN, y = 0.16x + 9.19, R2 = 0.024, p = 0.004. f) Reaction time, y = 4.54x−109.18, R2 = 0.357, p < 0.001. n = 351. WCST, Wisconsin Card Sorting Test; CA, categories achieved; NUCA, numbers of response cards
used until the first category achieved; TE, total errors; %PEM, percentage perseverative errors of Milner; %PEN, percentage perseverative
errors of Nelson.

100
90

80

Mental symptom score

Mental symptom score

90

70
60
50
40
30

70
60
50
40
30
20

20
20

30

40

50

60

70

20

80

Age (year)

a)

80

30

40

50

60

70

80

90

Age (year)b)

Fig. 2. Relationship between mental symptoms in AAQOL and aging.

a) Male, y = 0.26x + 30.75, R2 = 0.059, p = 0.001, n = 179. b) Female, y = −0.10x + 55.6, R2 = 0.008, p = 0.245, n = 172. Y axis shows the total
score of mental symptoms in AAQOL. AAQOL, Anti-Aging Quality of Life Common Questionnaire; AAQOL; CI, confidence interval.

_ 23 _

Survey of 351 Caces in Anti-Aging Medical Checkup

Table 1. Correlation analysis between neural age and “Mental symptom” score in AAQOL.

Mental symptoms
Depressed
Lapse of memory
No feeling of happinessFeeling of uselessness
Nothing to look forward to in life
Loss of motivation
Daily life is not enjoyable
Loss of confidence
Inability to sleep because of worries
Difficulty in falling asleep

Male

R2

p value

FemaleR2

p value

0.01x + 1.13

0.032

0.017

− 0.01x + 2.77

0. 0370.011

0.02x + 2.32

0.036

0.011

0.02x + 2.17

0.046

0.005

0.02x + 0.96

0.028

0.006

− 0.01x + 2.77

0.025

0.040

0.01x + 1.09

0.048

0.026

− 0.01x + 2.56

0. 0140.12 70.02x + 0.81

0.034

0.006

− 0.01x + 2.58

0.005

0.198

0.01x + 1.41

0.034

0.013

− 0.01x + 2.30

0.001

0.090

0.02x + 0.74

0.080

< 0.001− 0.01x + 2.74

0.001

0.073

0.01x + 1.35

0.023

0.045

− 0.01x + 2.91

0. 021

0.056

0.02x + 0.94

0.083

< 0.001

0.003x + 2.35

0. 001

0.616

0.03x + 0.85

0.069

< 0.001

0.01x + 1.95

0.023

0.045

Male; 63.5 years (95% CI: 61.6 ~ 65.3), n = 179. Female; 65.7 years (95% CI：63.8 ~ 67.5), n = 172. AAQOL, Anti-Aging Quality of Life Common
Questionnaire; AAQOL; CI, confidence interval.

5

Depressed score

Depressed score

5
4
3
2
1

4
3
2
1

20

30

40

50

60

70

80

20

Age (year)

a)

30

40

50

60

70

80

90

Age (year)b)

Fig. 3. Relationship between mental symptom “depression” and aging.

a) Male, y = 0.01x + 1.13, R2 = 0.032, p = 0.017, n = 179. b) Female, y = −0.01x + 2.77, R2 = 0.037, p = 0.011, n = 172. Y axis shows scores ofmental symptom “depression” in AAQOL. AAQOL, Anti-Aging Quality of Life Common Questionnaire; AAQOL; CI, confidence interval.

_ 24 _Glycative Stress Research

Table 2. Correlation analysis between neural age and physical information.

Male

R2

p value

FemaleR2

p value− 0.61x + 73.56

0.011

0.160

1.64x + 23.73

0.083< 0.001

0.45x + 47.70

0.017

0.081

1.30x + 24.78

0.16 6< 0.001

0.04x + 55.20

0.000

0.828

0.64x + 11.57

0.133< 0.001− 0.88x + 88.48

0.122< 0.001− 0.69x + 75.22

0.066< 0.001− 5.45x + 62.82

0.000

0.688

− 44.6x + 93.25

0.046

0.005

0.69x + 31.9 0

0.019

0.036

− 0.67x + 81.99

0.014

0.122

− 0.03x + 96.53

0.083< 0.001− 0.02x + 82.46

0.017

0.093

−16.97x + 71.63

0.032

0.017

11.37x + 56.50

0.004

0.428

− 5.42x + 78.80

0.049

0.003

− 5.36x + 75.31

0.017

0.088

BMI [kg/m 2]
Body Fat [%]Waist [cm]Grip strength (right) [kg]WBI
Muscle mass [%]Basal metaboric rate [kcal]
Brachial muscle[kg]

Femoral muscle [kg]

100

100

90

90

80

80

Neural age (year)

Neural age (year)

Male; 63.5 years (95% CI: 61.6 ~ 65.3), n = 179. Female; 65.7 years (95% CI：63.8 ~ 67.5), n = 172. BMI, body mass index; WBI, weight bearing index = leg
extension strength ÷ body weight; CI, confidence interval.

70
60
50
40
30

70
60
50
40
30

20

20
0

5

10

15

20

25

0

10

20

30

40

50

DHEA-s/cortisol ratio

Cortisol (ng/dL)

b)
100

100

90

90

80

80

Neural age (year)

Neural age (year)

a)

70
60
50
40
30

70
60
50
40
30

20

20
0

5

10

15

20

25

30

0

c)

5

10

15

20

25

30

35

DHEA-s/cortisol ratio

Cortisol (ng/dL)

d)Fig. 4. Stress-related hormones and neural age.

a) Cortisol in male, b) DHEA-s/Cortisol ratio in male, c) Cortisol in female, d) DHEA-s/Cortisol ratio in female. Y axis shows neural age.
Serum cortisol concentration shows positive correlation to neural age in male (a); y = 0.70x + 5.04, R2 = 0.037, p = 0.091, n = 179 and in female(c); y = 0.60x + 54.74, R2 = 0.025, p = 0.039, n = 172. DHEA-s/Cortisol ratio shows negative correlation in male (b); y = −0.66x + 67.43, R2 =0.116, p < 0.001, n = 179 and in female (d); y = −0.64x + 66.82, R2 = 0.070, p < 0.001, n = 172. DHEA-s, dehydroepiandrosterone-sulfate.

_ 25 _

Survey of 351 Caces in Anti-Aging Medical Checkup

Table 3. Multiple logistic regression analysis by using the neurological age as the target variable.

Male
95% CI

Odds ratio
Hypertension
Diabetes
Dyslipidemia
Metabolic syndrome
Obesityp value

Odds ratio

Female95% CI

p value

1.02

1.00

1.05

< 0.051.01

0.99 1.04

0.21

1.03

1.01

1.06

< 0.05

1.03

0.99

1.07

0.12

0.99

0.97

1.01

0.52

0.99

0.97

1.01

0.52

1.00

0.95

1.05

0.90

1.00

0.95

1.05

0.90

1.04

1.01

1.07

< 0.05

1.04

1.01

1.07

< 0.05

No changeover 5%

Male; 63.5 years (95% CI: 61.6 ~ 65.3), n = 179. Female; 65.7 years (95% CI：63.8 ~ 67.5), n = 172. CI, confidence interval.

3
2
1
0
-1
below 5%

No change

4
3
2
1
0
-1

over 5%

below 5%

Neural age (year)a)Nothing of lookforward to in life score

Feeling of uselessness
score

Depressed score

4

No changeover 5%2
10-1
below 5%

Neural age (year)b)

3

Neural age (year)c)Fig. 5. Mental symptoms and neural age in male.

a) “Depressed”, b) “Feeling of uselessness”, c) “Nothing to look forward to in life”. Y axis shows the Score change of mental symptoms
in AAQOL (n = 351). Improvement in “Depressed” tends to rejuvenate neural age (Difference 0.38, 95% CI: − 0.10 ~ 0.87, p = 0.09).
Deterioration in “Depressed” proceed ageing neural age (Difference 0.39, 95% CI: 0.002 ~ 0.78, p < 0.05). Deterioration in “Feeling ofuselessness” ages neural age (Difference 0.39, 95% CI: 63.8 ~ 67.5, p < 0.05). Deterioration in “Nothing to look forward to in life” ages
neural age (Difference 0.56, 95% CI: 0.13 ~ 0.99, p < 0.01). AAQOL, Anti-Aging QOL Common Questionnaire; Difference, different values
from “No change”; CI, confident interval.

look forward to in life” was recognized to relate to neural
aging. The exacerbation of the score for the symptom of“Feeling of uselessness” was recognized to relate to neural
aging.
In the case of females, no significant relationshipbetween the changes of these scores and neural aging wasrecognized.

Discussion

Based on a paper “Happy People Live Longer” by Frey
BS, Professor Kazuo Tsubota, Department of Ophthalmology,
Keio University, and former chief of the Japanese Societyof Anti-Aging Medicine, advocates the concept of “positive
thinking.” The things relating to “food,” “exercise” and“healthy longevity” are being acknowledged among thepeople who are concerned about anti-aging, but the effects
that mental symptoms bring about such as such “positive

thinking” and “happy” have not been well known.
In the area of psychology, resilience is defined as theindividual’s ability to adapt their own life tasks to social
disadvantageous and hostile conditions. Both concepts of “ina good mood” and “resilience” can be positioned as measuresagainst mental stress. The measures against mental stressare very important for healthy longevity as well as “food”
and “exercise.” The clinic, which we belong to, also focuses
on measures against mental stress and is giving guidance of“positive thinking (resilience)” to examinees in a positive way.
For excess calories causing glycative stress 11-15) andoxidative stress, there is much evidence indicating they are
aging promoting factors. Furthermore, mental stress also
affects the endocrine system, autonomic nervous system
and immune system through the functions of hypothalamus,
pituitary and adrenal systems, and as a result, it promotes
aging. A strong mental stress load for a long period of time
becomes a factor of depression. It is reported that in thecondition of depression, it is possible that hypercortisolemia
exists at higher rate and that neurotrophic factors decrease_ 26 _Glycative Stress Researchwhich harms hippocampal neurons 16). Furthermore, the study
on mental stress by brain function analysis using functional
MRI, and the study on neural circuit for emotion control areprogressing. Recently, Konishi et al. pointed out that brain
aging and cognitive impairment are related to the prefrontal
cortex ventral 6), and Monchi et al. noted that these are
related to the caudate nuclei 7). There are reports that the left
prefrontal cortex is involved with agreeable stimuli 17, 18).
WCST that was used for the evaluation of neural age issaid mainly to reflect the degree of functional impairment of
the prefrontal cortex 4, 5). Each index of WCST has a strong
correlation with aging and it is recognized to be clinicallyuseful as the index of neural age. It was also shown that there
is a difference in the correlation between mental symptom
and aging between the sexes. Young females’ total score ofmental symptoms was high, and it was suggested that young
females need mental health care. This is matched with theresults of recent research by Foster 19). Even though social
participation by women has been progressing recently inJapan, the problem of difference in the terms and conditionsof employment between males and females still remain. The
above result probably reflects the situation where females
are in need of mental elbowroom or they are under a lot of
emotional pressure.
In the scattering diagram of real ages and total scoresof mental symptoms, it was approximately at the age of 65
and when the total score of mental symptom was 50 that the
regression lines of males and females were crossed. Depressed
symptoms, in particular, increased with aging in males andon the contrary, it decreased in females. There were manyother males with the symptoms of “Nothing to look forward
to in life” and “Feeling of uselessness.” From the analysis ofstress-related hormones in the blood, it was shown that thelevel of cortisol rises with aging and the D/C ratio lowers inmales. If they are exposed to stress, corticotropin-releasing
hormone: (CRH) is released from hypothalamus and acts on
the pituitary gland, and then adrenocorticotropic hormone(ACTH) is released from the pituitary gland and it stimulates
the adrenal cortex, and as a result, cortisol and DHEA are
released. However, the release of cortisol is predominant.
From these facts, it is assumed that mental stress affected theheart-brain interaction and hypothalamus-pituitary-adrenal
axis (HPA-axis), increased cortisol and decreased DHEA and,as a result, it acted in the direction of neural aging.
As a result of the analysis of the conditions before andafter the guidance of resilience in males, the rejuvenationof neural age was observed as a result of the improvementof the symptoms of “Nothing to look forward to in life,”“Depressed” and “Feeling of uselessness” that had been
exacerbated. Cortisol is involved with resilience and, in thecase of depression, the concentration of cortisol in the bloodincrease. Meanwhile, DHEA is involved with the responseto stress and mental diseases, and it was shown that the D/C
ratio can be an important parameter showing the vulnerability
to stress. The prevention of aging is said to be a measureagainst mental stress, oxidative stress and glycative stress.
The results obtained in this research do not contradict theseconcepts.
Frailty is defined as the conditions showing thephysiological reserve lowered with aging and the vulnerability
against stress to the body 20). Frailty is reversible and theprevention against a state requiring long-term care, lack of
independence, tumbling, fractures, and death is possible
through early and appropriate intervention. Sarcopenia isdiagnosed by decreases of grip strength, walking speed andmuscle mass. The decreases of grip strength and walking
speed are overlapped in both diagnostic criterions of frailty
and sarcopenia, so that frailty and sarcopenia are overlapping
concepts.
Frailty and sarcopenia have a significant impact on
the independence of the elderly. In a report analyzing therelationship between the level of independence and theneural age of the elderly, the differences in neural age among
the elderly living an independent life 21), those requiringsupport attending daycare 22) and those requiring long-termcare admitted in a medical care facility for the elderly 23) are
discussed. As a result, neural aging had an impact on the
degree of independence more remarkably than the muscle
age directly related to frailty and sarcopenia had 24).
In this research, the indexes relating to frailty andsarcopenia were also focused on, and the relationships
between each index and neural age were analyzed. As theresults of body composition tests, in the case of males, thelower BMI was, the higher neural age was and the higher
grip strength, quadriceps muscles, WBI and basal metabolic
rate were. This suggests that in order to keep neural age
young, it is important to prevent frailty and sarcopenia 25). It isinteresting that, in the case of females, the higher BMI was,the higher neural age was; the higher body fat percentage andwaist circumference were, the higher neural age was; and thehigher grip strength, quadriceps muscle and WBI are, thelower neural age was. In this research, obesity made neuralage high in both males and females. However, the differences
between the sexes in BMI became salient with age: a lower
BMI caused higher neural age in males, but it caused alower neural age in females. It is reported that the higher
obesity and BMI are, the lower the mortality rate from heart
failure is. This is discussed as the “obesity paradox,” andit is interesting that males become physically weaker thanfemales through age and their incidence rates of cancer andlifestyle diseases become higher 26-28).
It was found that diabetes, hypertension and obesity
caused aging in the nervous system and prefrontal cortex
functions through a multivariate analysis between lifestylediseases and neural ages. There are several papers concerning
the relationship between diabetes and dementia 29-31) and it has
been discussed that insulin resistance, high insulin level andinsulin-degrading enzymes are also involved in the degradationof amyloid-beta, and that high blood glucose accumulatesamyloid-beta 32, 33). Diabetes and obesity are typical diseases
involved in strong glycative stress. Glycative stress is a seriesof reactions where blood glucose, triglyceride and the riseof triglyceride form the intermediates of glycation reaction
having aldehyde group (3-deoxyglucosone: 3DG, glyoxal,
methylglyoxal, glyceraldehyde, etc.), they Amadori-modify
protein in vivo, and it causes carbonyl modification andforms advanced glycation end products (AGEs). The increaseof toxicity caused by glycation of amyloid-beta and theacceleration of neurodegenerative fibril change are involvedin the progression of Alzheimer’s type dementia 34, 35). Diabetes
and obesity were identified as risk factors involved in the
aging of the nervous system by multivariate analysis. Therefore,
it is supported that glycative stress is an aging risk factor of
the nervous system. The relationship between hypertension
and cerebrovascular disorders also is discussed 36, 37).
It was presumed that females have more “positive
thinking” and are younger in neural age than males due totheir strength of resilience, and they are preventing diseases
and extending their healthy longevity.

_ 27 _

Survey of 351 Caces in Anti-Aging Medical Checkup

Summary1) WCST can examine the functional disorder of prefrontal
cortex and each index is clinically significant as an index ofneural age.
2) Mental stress affected heart-brain interaction and HPAaxis and was involved in the aging of the nervous system byincreasing cortisol and decreasing DHEA.
3) The cases of mental symptoms including “Depressed”
increased with age in males, and on the contrary, they
decreased in females. There were many males, in particular,
who were suffering exacerbated metal symptoms such as“Nothing to look forward to in life,” “Depressed” and“Feeling of uselessness” and the improvement of these
symptoms was effective in the prevention of the aging of thenervous system.
4) In order to maintain a young neural age, it was importantto prevent frailty and sarcopenia by increasing grip strength,
quadriceps muscle, WBI and basal metabolic rate.
5) Diabetes, hypertension and obesity were extracted as thefactors lowering the functions of the prefrontal cortex.
6) It was shown that elderly females have better “positive
thinking,” are younger in neural age and stronger inresilience than elderly males and it was suggested thatthese characteristics of the elderly females possibly prevent
diseases and extend their healthy longevity.

Conclusion

Elderly females were younger in neural age and had
better “positive thinking” than elderly males. It is important
to improve mental symptoms, increase and maintain thequadriceps muscle mass, prevent frailty and aging of
nervous system and improve “positive thinking” in order toprevent lifestyle diseases and dementia and extend healthy
longevity. Let’s aim at our healthy longevity!

Conflict of interest

The authors declare no conflict of interest in this study.

Acknowledgement

The outline of this research was presented at the 17th
meeting of Japanese Society of Anti-Aging Medicine on
June 2nd-4th, 2017 (Tokyo) and the 31st meeting of Japan
Physicians Association on October 8, 2017 (Osaka).

Reference
1) Yonei Y. Anti-Aging Medical Chekup. Modern Physician.

2007; 27: 1057-1060. (in Japanese)2) Ito H. A support system for Anti-Aging Medical Chekup:
Aging Check®. Modern Physician. 2006; 26: 605-608. (inJapanese)3) Yonei Y, Miuno Y. The human dock of tomorrow: Annual
health check-up for antiaging. Ningen Dock. 2005; 19: 5-8.
4) Berman KF, Ostrem JL, Randolph C, et al. Physiologicalactivation of a cortical network during performance ofthe Wisconsin Card Sorting Test: A positron emission
tomography study. Neuropsychologia. 1995; 33: 1027-1046.
5) Cabeza R, Nyberg L. Imaging cognition II: An empiricalreview of 275 PET and fMRI studies. J Cogn Neurosci.
2000; 12: 1-47.
6) Konishi S, Nakajima K, Uchida I, et al. Transient
activation of inferior prefrontal cortex during cognitive set
shifting. Nat Neurosci. 1998; 1: 80-84.
7) Monchi O, Petrides M, Petre V, et al. Wisconsin Card
Sorting revisited: distinct neural circuits participating
in different stages of the task identified by event-related
functional magnetic resonance imaging. J Neurosci. 2001;
21: 7733-7741. 2.0
8) Japan Stroke Data Bank. Wisconsin Card Sorting Test
Ver.2.0. http://strokedatabank.ncvc.go.jp/archive (inJapanese)9) Oguma Y, Iida K, Yonei Y, et al. Significance evaluationof Anti-Aging QOL Common Questionnaire. Glycative
Stress Res. 2016; 3: 177-185.
10) Frey BS. Psychology: Happy people live longer. Science.
2011; 331: 542-543.

11) Colman RJ, Beasley TM, Kemnitz JW, et al. Caloric

restriction reduces age-related and all-cause mortality inrhesus monkeys. Nat Commun. 2014; 5: 3557.
12) Colman RJ, Anderson RM, Johnson SC, et al. Caloric
restriction delays disease onset and mortality in rhesus
monkeys. Science. 2009; 325: 201-204.
13) Lane MA, Black A, Handy A, et al. Caloric restriction inprimates. Ann N Y Acad Sci. 2001; 928: 287-295.
14) Mattison JA, Roth GS, Beasley TM, et al. Impact
of caloric restriction on health and survival in rhesus
monkeys from the NIA study. Nature. 2012; 489: 318-321.
15) Mattison JA, Colman RJ, Beasley TM, et al. Caloric
restriction improves health and survival of rhesus
monkeys. Nat Commun. 2017; 8: 14063.
16) Demuyser T, Bentea E, Deneyer L, et al. Disruption of the
HPA-axis through corticosterone-release pellets induces
robust depressive-like behavior and reduced BDNF levels
in mice. Neurosci Lett. 2016; 626: 119-125.
17) Suardi A, Sotgiu I, Costa T, et al. The neural correlatesof happiness: A review of PET and fMRI studies using
autobiographical recall methods. Cogn Affect Behav
Neurosci. 2016; 16: 383-392.
18) Luo Y, Kong F, Qi S, et al. Resting-state functional
connectivity of the default mode network associated withhappiness. Soc Cogn Affect Neurosci. 2016; 11: 516-524.
19) Foster SN, Hansen SL, Capener DC, et al. Genderdifferences in sleep disorders in the US military. Sleep
Health. 2017; 3: 336-341.
20) Kusunoki H, Shinmura K. Association between glycative
stress, frailty, and sarcopenia. Glycative Stress Res. 2017;
4: 292-298.

_ 28 _Glycative Stress Research21) Miyazaki R, Ishii K, Ichikawa H, et al. Community

medicine and anti-aging: Effects of combining a longterm pedometer-based physical activity program with antiaging medical checkups on health and anti-aging medical
indicators in community-dwelling older adults (Yurin
study 1). Anti-Aging Med. 2010; 7: 143-152.
22) Yabukita H, Miyazaki R, Nomoto K, et al. Characteristicsof physical functions in elderly people requiring support.
Anti-Aging Med. 2013; 10: 16-20.
23) Ishikawa M, Ishikawa S, Kamata H, et al. Efficacy of ahealth promotion program with facial mimetic muscle
training in residents of a medical care facility for theelderly. Anti-Aging Med. 2010; 7: 120-128.
24) Yonei Y, Takabe W, Yagi M. What does the Anti-Aging
Medical Checkup show? : Data presentation. Health
Evaluation and Promotion. 2017; 44: 600-605.
25) Dye L, Boyle NB, Champ C, et al. The relationshipbetween obesity and cognitive health and decline. Proc
Nutr Soc. 2017; 76: 443-454.
26) Sharma A, Lavie CJ, Borer JS, et al. Meta-analysisof the relation of body mass index to all-cause andcardiovascular mortality and hospitalization in patientswith chronic heart failure. Am J Cardiol. 2015; 115: 14281434.
27) Costanzo P, Cleland JG, Pellicori P, et al. The obesity
paradox in type 2 diabetes mellitus: Relationship of bodymass index to prognosis: A cohort study. Ann Intern Med.
2015; 162: 610-618.
28) Gupta T, Kolte D, Mohananey D, et al. Relation of obesity
to survival after in-hospital cardiac arrest. Am J Cardiol.
2016; 118: 662-667.
29) Ohara T. Epidemiology of diabetes and risk of dementia.
Brain Nerve. 2016; 68: 719-727. (in Japanese)30) Espeland MA, Carmichael O, Hayden K, et al. Long-term
impact of weight loss intervention on changes in cognitive
function: Exploratory analyses from the Action for Healthin Diabetes Randomized Controlled Clinical Trial. J
Gerontol A Biol Sci Med Sci. 2017; Aug 25.
31) Kiyohara Y. Alteration of lifestyle-related diseases inJapanese: Current status and challenges: The Hisayama
Study. Rinsho Byori. 2015; 63: 623-630. (in Japanese)
32) Su F, Shu H, Ye Q, et al. Brain insulin resistancedeteriorates cognition by altering the topologica featuresof brain networks. Neuroimage Clin. 2016; 13: 280-287.
33) Leal MC, Fernandez Gamba A, Morelli L, et al. Cerebral
proteolysis of amyloid-b peptide: Relevance of insulindegrading enzyme in Alzheimer's disease. Medicina (BAires). 2009; 69: 466-472. (in Spanish)34) Barić N. Role of advanced glycation end products in
Alzheimer's disease. Glycative Stress Res. 2014; 1: 68-83.
35) Barić N. Role of advanced glycation end products (AGEs)
on the reactive oxygen species (ROS) generation in
Alzheimer’s disease amyloid plaque. Glycative Stress Res.
2015; 2: 140-155.
36) Ninomiya T, Kiyohara Y. Hypertension and dementia.
Nihon Rinsho. 2011; 69: 2064-2070. (in Japanese)37) Gottesman RF, Albert MS, Alonso A, et al. Associations
between midlife vascular risk factors and 25-year incident
dementia in the atherosclerosis risk in Communities(ARIC) Cohort. JAMA Neurol. 2017; 74: 1246-1254.

_ 29 _