Glycative Stress Research
Online edition : ISSN 2188-3610
Print edition : ISSN 2188-3602
Received : March 16, 2015
Accepted : April 22, 2016
Published online : June 30, 2016

Original Article

The Effects of Long-term Intake of Kale Juice on the Aging of Physical Functions- Cross Sectional Study Chie Tarumizu 1), Sayuri Matsuoka 1), Kei Yui 1), Motohiko Sugai 2), Umenoi Hamada 3),
Wakako Takabe 4), Yoshikazu Yonei 4)1) FANCL Research Institute, FANCL Corporation, Totsuka-ku, Yokohama, Japan2) Sakura Clinic, Mitaka, Tokyo
3) A-KIT. Co., Ltd, Kyotanabe, Kyoto, Japan4) Anti-Aging Medical Research Center and Glycative Stress Research Center, Graduate School of Life and Medical Sciences,
Doshisha University, Kyotanabe, Kyoto, Japan

Abstract

Objective: To verify the effects of kale juice on physical functional age by a cross sectional study.
Methods: An anti-aging medical checkup was performed on 110 females aged 50-69 years who had been consuming one
or more cups of kale juice (FANCL Corporation) daily for at least 1 year (hereinafter referred to as the “kale group”). The
subjects were examined once and the results were compared with a general, countrywide data group already accumulated
and age-adjusted (n = 1, 063). The study was only commenced once approved by the appropriate ethics committee.
Results: Concerning physical functional age, the results of the anti-aging medical checkup indicated a nervous system age of
53.5 ± 12.8 years (chronological age; -4.8 ± 12.0 years) and a muscle age of 48.7 ± 3.9 years (chronological age; -9.7 ± 4.7
years) in the kale group; both were significantly lower than the corresponding values in the control group. Blood biochemistryindicated significantly higher HDL cholesterol and significantly lower triglycerides, fasting blood glucose, HbA1c, insulin, andhomocysteine in the kale group than in the control group. Urine analysis showed a significantly lower isoprostane production
rate in the kale compared to control group. Finally, an anti-aging questionnaire measuring quality of life (QOL) showed lower
scores in the kale group for “palpitations,” “shortness of breath,” “thirst,” “anorexia,” “early satiety,” “coughing and sputum,”“diarrhea,” “constipation,” “memory lapse” and “inability to solve problems”, compared to control data.
Conclusion: These results suggested that long-term kale consumption could be effective for the prevention of physical andmental aging.

KEY WORDS: kale (Brassica oleracea var. acephala), aging, physical functional age, risk factor, quality of life (QOL)
Introduction

The recent and rapid aging in Japan is inducing increased
medical expenses and emerging problems associated withspecialized medical care. Anti-aging medicine falls underpreventive medicine and integrated medical care surpassing
specific clinical specialties 1), and aims to “enhance health,improve quality of life, and achieve long life in good health.”
Regressive changes associated with aging emerge as various
symptoms that can be expressed and understood as thefunctional age of organs, and which can be used to evaluate
the therapeutic effect of integrative medicine. For instance,
the Japanese Respiratory Society has already presented thenotion of lung age 2).

The Anti-Aging Medical Research Center, Doshisha
University is undertaking research into the development ofan aging evaluation system based on anti-aging clinical datacollected thus far 3, 4). Their system is defined as a “method
to evaluate aging with an anti-aging medical checkup andto present the results as functional age,” that is designed tomotivate users to enhance their health, and, for physicians
and researchers, is suitable for evaluating health promotion
programs. Data on approximately 10,000 persons across thecountry have already been accumulated. The reversal andprevention of functional age can be an indicator of healthenhancement and a motivator for the need to take healthfood.

*Address Correspondence to: Chie Tarumizu

FANCL Research Institute, FANCL Corporation
Address: 12-13 Kamishinano, Totsuka-ku, Yokohama, Kanagawa, 244 - 0806, Japan
Tel.: + 81- 45 - 820 -3443 Fax: + 81- 45 - 820 - 3526 E-mail: chie_0904@fancl.co.jp
Co-authors: Matsuoka S, matsuoka@fancl.co.jp ; Yui K, ke-yui@fancl.co.jp ;Sugai M, motohiko@pg7.so-net.ne.jp ; Hamada U, hamada@yonei-labo.com ;Takabe W, wtakabe@mail.doshisha.ac.jp ; Yonei Y, yyonei@mail.doshisha.ac.jp_ 81 _

Glycative Stress Research 2016; 3 (2): 81- 90(c) Society for Glycative Stress ResearchKale is a plant of the Brassicaceae family (the original
species of cabbage), which contains remarkably more vitamins,
antioxidative components and minerals such as calcium thanother vegetables, and there have been many reports about
its health benefits. We have reported various aspects of thefunctionality of kale such as its potential for the preventionof bone loss 5), palliation of knee joint pain 6), palliation of
cedar pollen allergy symptoms 7) and atopic dermatitis 8, 9),as well as improvement in alcohol metabolism 10). Other
possible effects of kale include cancer prevention, benefits
for intestinal health and immunity, reduction of bloodpressure and cholesterol, protection of the gastric mucosa,
and alleviating or reducing stress; however, there have been
no reports that investigated the effects on aging.
The present study therefore compared the effects on
aging of physical functions in persons who have consumed
kale juice for a long time compared to the general Japanese
population based on data already accumulated.

Study design

The study was designed as a cross-sectional study,
testing each person in the kale group 1 time, and was
performed at Tokyo Synergy Clinic (Chuo-ku, Tokyo) fromMay 2013 to May 2014.

Subject foodTable 1 shows a summary of the kale product (frozen
or powder, both equivalent to approximately 120 g of raw
leaves) corresponding to the inclusion criteria of subjects.

Methods
Subjects

for at least 1 year (hereafter referred to as kale group). Subjects
were excluded under the following criteria: 1) serious kidney,
liver, heart, brain, blood or immune disease; 2) contraindicatedfor the use of the test apparatus; 3) blood not able to becollected from the cubital fossa vein; and 4) judged as
unsuitable by the principal investigator.
The significance of the study, test method, andparticipants’ rights were properly explained to the candidate
participants, and their participation thereafter was determinedby signing a consent form.

The study group comprised 110 females aged 50 to 69
years who had been consuming one or more cups of kale asjuice produced by FANCL Corporation (Honshibori-aojiru;
Premium-Reito or Premium (frozen or powder), both equatedto approximately 120 g of raw leaves), daily and continuously

Test method

Subjects were prohibited from performing more exercise
than daily activities necessitated and from drinking alcohol
beverages on the day before testing, and were instructed toTable 1. Kale Component（/a pack）
Honshibori-aojiru
Premium-Reito(frozen100 g)

Honshibori-aojiru
Premium(powder10 g )Energy11 〜 30 kcal

25 〜 44 kcal

Dietary fiber

0.10 〜 0.60 g

0.81 〜 2.0 g−

18 〜 44 mg

Sodium
Sodium chloride equivalent

0.06 〜 0.15 g−

Potassium

138 〜 349 mg

161 〜 445 mg

Calcium

73 〜 226 mg

91 〜 215 mg

Magnesium

19 〜 33 mg

17 〜 48 mg

Iron

0.14 〜 0.78 mg

0.19 〜 0.36 mg

β-Carotene

935 〜 2,378 μg

555 〜 2,029 μg

Vitamin C

200 mg76 〜 229 mg

Vitamin E

0.32 〜 2.1 mg

0.46 〜 1.6 mg

Vitamin K

92 〜 209 μg

98 〜 222 μg

Folic acid38 〜 127 μg

39 〜 93 μg

Total chlorophyll

16 〜 35 mg

14 〜 44 mg

49,000 〜 110,000 unit

27,000 〜 78,000 unit

1.3 〜 3.1 mg

0.97 〜 2.7 mg

500 mg

500 mg

SOD activity
LuteinDFA Ⅲ (Difructose anhydride Ⅲ)
SOD, superoxide dismutase; DFA, difructose anhydride.

_ 82 _Glycative Stress Researchfinish dinner before 21:00 and to sleep for an appropriate
time. Urine was collected and analyzed in the morning on thetest day. Patients were prohibited from eating, drinking
except for water, or smoking from rising until after completionof the tests. In addition, oral drugs were only administeredunder the direction of the attending physician. Testing was
performed during the morning sequentially after checking
the health condition on the day. Test parameters included
anthropometry, blood pressure after resting, anti-aging
medical checkup (functional age evaluation: muscle age,bone age, hormonal age, nervous system age and vascularage), blood biochemistry, urine analysis, and subjective
symptoms, in reference to previous reports 11-13).
(1) Anti-aging medical checkup (functional age evaluation)
Relative functional age of muscles, bones, hormones,
nerves, and blood vessels was calculated for each subject
using the system database of the population by the AgeManagement Check R system (Ginga Kobo, Naka-ku, Nagoya,Japan). To determine muscle age, weight bearing index,
basal metabolic rate, body mass index (BMI), and body fat
percentage were measured using a bioelectrical impedance
body composition meter (Physion MD; Physion, Shimogyoku, Kyoto). For bone age, the stiffness was measured byultrasonic bone densitometry (A-1000; GE Yokogawa
Medical Systems Ltd., Hino, Tokyo). For hormonal age, blood
somatomedin-C (insulin-like growth factor-I; IGF-I ) anddehydroepiandrosterone-sulfate (DHEA-s) were analyzed.
For nervous system age, the Wisconsin card-sorting test
(WCST) 14) was performed to test higher brain function.
Vascular age was measured with a blood pressure/pulse wave
meter (Cardio Ankle Vascular Index (CAVI); Fukuda
Denshi Co., Ltd., Bunkyo-ku, Tokyo) and accelerated
plethysmography (Dyna Pulse SDP-100; Fukuda Denshi Co.,
Ltd., Bunkyo-ku, Tokyo) as indicators of arteriosclerosis.
(2) Blood biochemistry
Hematology measurements included leukocyte count,erythrocyte count, hemoglobin (Hb), hematocrit, and platelet
count. Biochemistry measurements included total bilirubin,
aspartate aminotransferase (AST), alanine transaminase(ALT ), γ -glutamyl transpeptidase ( γ - GTP), lactate
dehydrogenase (LDH), blood urea nitrogen (BUN), andcreatinine. Lipid metabolism was investigated by measuring
total cholesterol (TC), HDL cholesterol (HDL-C), LDL
cholesterol (LDL-C), and triglycerides (TG), while sugar
metabolism was investigated by measuring fasting plasma
glucose (FPG). HbA1c [NGSP] and insulin (immune reactive
insulin; IRI), and protein metabolism was investigated bymeasuring the total protein (TP). The measured electrolytes
were sodium (Na), potassium (K), chloride (C l), calcium(Ca) and iron (Fe). Endocrine function was assessed bymeasuring cortisol, DHEA-s, IGF-I, progesterone, andestradiol (E 2), while glycative stress index was measured
based on pentosidine. Finally, levels of highly sensitive
C-reactive protein (hsCRP) and total homocysteine werealso measured. These analyses were contracted out to LSI
Medience Corporation (Minato-ku, Tokyo). The LDLcholesterol/HDL cholesterol (L/H) ratio as the arteriosclerosis
index and insulin resistance index (HOMA-R) were also
calculated.
(3) Urine analysis
The first morning urine was used to measure the oxidative
stress indices of 8-OHdG (8-hydroxydeoxyguanosine) andisoprostane (1, 5-isoprostane F2t: 8-epi-PGF2α/ 8-isoPGF2α)
production rates as well as creatinine levels. Analysis wascontracted out to LSI Medience Corporation (Minato-ku,
Tokyo).
(4) Subjective symptoms
Subjective symptoms were evaluated using the AntiAging QOL Common Questionnaire (AAQol) 15) that consistedof 56 questions on complaints concerning “physicalsymptoms” and “mental symptoms” at 5 grades, as follows:“1. Not at all”, “ 2. Almost not”, “ 3. Slightly”, “4. Moderately”,“5. Severe.” For lifestyle-related behavior, an interview was
conducted regarding smoking, alcohol consumption, exercise,sleeping hours, water intake, and visual display terminal(VDT) working hours.
(5) Diet survey
The current status of nutrient and food consumption
was investigated as consumption frequency using a brief
self-administered diet history questionnaire (BDHQ) 16, 17).
(6) Skin AGEs measurement
The skin deposition of advanced glycation endproducts(AGEs) was evaluated non-invasively by the AGE reader TM(DiagnOptics, Groningen, The Netherlands) 18).
(7) General data
For the control group, females aged 50 to 69 years andmatched to the subject group were selected from the first
visit data of anti-aging examinees (6,016 cases as of November2012) owned by the Anti-Aging Medical Research Center,
Doshisha University, and 1,063 individuals who had undergonebone densitometry and WCST required for the calculationof functional age were extracted from them. There were nodifferences in chronological age distribution between thecontrol group and the kale group.

Ethics

The study was performed in compliance with the ethics
principles that have their origin in the Declaration of Helsinki,
the Law for the Protection of Computer - Processed Personal
Data Held by Administrative Organs, and the “Ethical
Guidelines for Epidemiological Research” of the Ministry of
Health, Labour and Welfare and the Ministry of Education,
Culture, Sports, Science and Technology. The present study
was also performed with the approval of the clinical research
ethics board of FANCL Corporation (Approval No. F12-031),
the ethics board of Tokyo Synergy Clinic, and the ethics
board of Doshisha University (Approval No. #1318).

Statistical analysis

Results are shown as mean ± standard deviation (SD).
For the functional age of the control group, there aredifferences in the number n, because the data were obtainedwith different models of analysis and thus only data using
the same model as used for the kale group were includedin the present study for some parameters. Comparison
between groups was performed using an independent t
test for parametric data and the Mann-Whitney U-test for
nonparametric data. The statistical analysis software used
was SPSS 21.0 for windows (SPSS Japan, Shibuya-ku,
Tokyo), with a two-tailed significance level of 5%.

_ 83 _

Results(1) Subjects

All collected data of 110 persons in total (mean age
58.4 ± 5.6 years) were used for analysis of the kale group.
The control group was set as 1,063 females aged 50 to 69
years of matching age, sex, and ethnicity (Japanese) as
the general data, and it was confirmed that there were nodifferences in chronological age distribution from the kalegroup.
Table 2 shows lifestyle-related behaviors, and Table 3
shows the status of kale intake in the kale group as subject
background. Among the lifestyle-related behaviors, alcohol
consumption and frequency of alcohol drinking weresignificantly higher in the kale group compared to controls.
The kale intake status in the kale group confirmed that
almost all had consumed 1 cup of frozen juice daily for
3 years. The combined use of supplements containing
functional components that overlap with those of kale wasreflected in high percentages of vitamin C (15%) and calcium(15%) in the kale group, but most (~ 73%) did not use any
supplements. The daily food consumption status of the kalegroup was generally the standard for Japanese people. As forthe glycative stress index, blood pentosidine in the kale group
was 0.0453 ± 0.0147 μg/mL, which was slightly higher
than the standard range according to the kit manufacturer(0.00915 to 0.0431 μg/mL [ELISA]). AGEs accumulation(AF) in the kale group was 2.2 ± 0.3, which was similar to
the mean value (2.09 ± 0.36 at age 50 to 60 years, and 2.46
± 0.57 at age 60 to 70 years) supplied by the manufacturerof the AGEs Reader.

(2) Functional age

Table 4 represents the comparison of functional age;muscle age in kale group was younger than that in control
group ( p < 0.001), bone age in kale group older than incontrol group ( p = 0.024), hormonal age in kale group older
in control group ( p = 0.005), nervous system age in kalegroup younger than in control group ( p < 0.001), and vascular
age in kale group was not significantly different from that incontrol group ( p = 0.244).

(3) Functional age calculation factors

Table 5 represents the comparison of functional age
factors. Among muscle age factors, the basal metabolic rate
was significantly higher while BMI and body fat percentage
were significantly lower in the kale group than in controls.
As for the bone age factor, stiffness was significantly lower
in the kale group. Among vascular age factors, estimatedvascular age by accelerated plethysmography was higher

Table 2. Lifestyle-related behaviors.
Control group (CON)Smoking
Alcohol consumption
Frequency of alcohol drinking
Exercise
Sleeping hours
Water consumption
VDT working hours

Cigatettes/day
mL/daytimes/weekdays/week
hours/dayL/dayhours/day

n

mean

1,063
1,063
1,050
1,063
1,063
1,063
1,023

1.25
0.45
1.49
1.76
6.21
1.21
3.61

±
±
±
±
±
±
±

Kale intake group (KL)

SD

n

mean

5.09
0.76
2.29
2.08
1.13
0.51
2.50

110
102
108
109
108
100
107

0.65
0.72
2.46
1.68
6.21
1.24
4.30

±
±
±
±
±
±
±

p-valueSD(CON vs KL)

3.22
0.90
2.57
2.18
0.93
0.48
3.31

0.154
0.000 **
0.000 **
0.319
0.590
0.456
0.184

**p<0.01, Mann -Whitney U test. SD, standard deviation; VDT, visual display terminals.

Table 3. Kale intake background (KL).
Ingestion history
Kale type

Over 3 years
More than 1 year less than 3 years
Honshiboriaojiru
Honshiboriaojiru

Consumption and frequency of Kale juice

1 cup/day
1 ~ 2 cups/day
over 2 cups/day

Supplement combination(The main components that overlap with kale juice)

Vitamin C
Vitamin E
Calcium
No combination_ 84 _

Premium-Reito (frozen 100 g)
Premium (powder 10 g)

n

%

107
3

97
3

107
1
2

97
1
2

16
3
16
80

15
3
15
73

100
10

91
9

Glycative Stress Researchin the kale group than in controls, while no difference wasobserved in pressure/pulse wave measurement (CAVI)
between the groups. As for nervous system age factors,
categories achieved (CA) was significantly higher whilenumbers of response cards used until the first category

achieved (NUCA) and Time were significantly lower in the
kale group than in controls by the higher brain function test.
Among hormonal age factors, IGF-I was significantly lower
in the kale group than in controls, while no difference wasobserved in DHEA-s between the groups.

Table 4. Functional age by Anti-aging check system.
Control group (CON)nmean

Kale intake group (KL)

SD

n

mean

SD

p-value(CON vs KL)

Age

years

1,063

59.4 ± 5.5

11058.4 ± 5.6

Muscle age

years

1,063

53.7 ± 11.4

11048.7 ± 3.9< 0.001 **Bone age

years

1,063

56.7 ± 14.3

110

60.4 ± 16.2

0.024 *

Hormonal age

years

1,063

61.5 ± 9.9

11064.3 ± 9.9

0.005 **

Nervous system age

years

1,063

60.9 ± 14.4

110

53.5 ± 12.8

< 0.001 **Vascular age

years

1,063

65.2 ± 13.0

11064.1 ± 8.90.244**p<0.01, *p<0.05, independent t-test. SD, standard deviation; Functional age is estimated by Age Management Check (Ginga Kobo).

Table 5. Anti-aging medical checkup.

Anthropometry

HeightWeightSystolic blood pressure
Diastolic blood pressure
Muscle age
R-WBI
L-WBI
BMR
BMI

Body fat percentage
Bone age

Stiffness value
Hormonal age
IGF-I

DHEA-sNervous system age
CA
NUCA

Control group (CON)
n
mean
SD
cm
kg
mmHg
mmHg

kcal/daykg/m 2
%

ng/mL
μg/dL

secondSDPTG-estimated vascular age
R-CAVI

year

L-CAVI

1,063
1,063
1,063
79

Response time
Vascular age

1,063

79

142

Kale intake group (KL)
n
mean
SD

156.1 ± 5.3
54.0 ± 8.2
122.6 ± 18.6

108

0.7 ± 0.1
0.7 ± 0.1
1,098.4 ± 166.4

108

74.9 ± 11.0

108
110
110

157.9 ± 5.5
53.0 ± 6.7
120.4 ± 15.7

76.4 ± 10.6

0.7 ± 0.1
0.7 ± 0.1
108 1,144.6 ± 106.2
108p-value(CON vs KL)
0.001 **
0.152

0.230
0.181

0.085
0.189

0.008 **

1,046

22.1 ± 3.1
28.5 ± 6.598580.1 ± 15.2

11076.1 ± 16.7

0.009 **

1,063

128.9 ± 40.8
835.7 ± 446.0

110111.1 ± 27.5
862.8 ± 425.4< 0.001 **1,063

4.8 ± 1.4
4.5 ± 8.2
154.2 ± 120.0

110

5.5 ± 0.7
1.3 ± 1.5
109.8 ± 39.3

< 0.001 **60.7 ± 7.1
8.0 ± 0.9
7.9 ± 0.9

109

64.5 ± 9.3
7.9 ± 0.9
7.8 ± 0.9

0.032 *

1,063

1,063

1,063
1,063
24
69
69

108
108

21.3 ± 2.6
25.1 ± 4.8

0.001 **
< 0.001 **

110

110
110

110
110

0.542

< 0.001 **< 0.001 **

0.304
0.394

**p<0.01, *p<0.05, independent t-test. WBI, weight bearing index measured by Physion MD; BMR, basal metabolic rate; BMI, body mass index; IGF-I,
insulin-like growth factor-I; DHEA-s, dehydroepiandrosterone-sufate; CA, categories achieved; NUCA, numbers of response cards used until the first category
achieved. CA, NUCA and response time are measured by Wisconsin card sorting test. SDPTG-estimated vascular age is measured by Dyna Pulse SDP-100;
CAVI, cardio ankle vascular index.

_ 85 _

(4) Blood biochemistry and urine analysis

Table 6 data compares the blood chemistry and urine
analysis. Regarding lipid metabolism, HDL cholesterol was
significantly higher, while triglycerides and L/H ratio weresignificantly lower in the kale group than in the control group,and of the sugar metabolism factors, FPG, HbA1c, insulin,and HOMA-R were significantly lower in the kale group.
Hormonal status showed significantly higher estradiol levelsin the kale group compared to controls, while progesterone
and cortisol were significantly lower in the kale group.
Homocysteine as an index of arteriosclerosis was significantly
lower in the kale group. In addition, although the leukocyte
count, hemoglobin, hematocrit, protein, and LDH weresignificantly lower, and the bilirubin, Cl and creatinine weresignificantly higher in the kale group than in controls, alldata were within the range of standard values. Urine analysis
showed that the isoprostane production rate (ng/kg/hr) was
significantly lower in the kale group compared to the control
group.

(5) Subjective symptoms

Table 7 shows the comparison of subjective symptoms.
Among physical symptoms, the eight items of palpitations,shortness of breath, thirst, anorexia, early satiety, coughing
and sputum, diarrhea, and constipation showed a significantly
lower score (milder symptoms) in the kale group than thecontrol group; conversely, the three items of skin problems,
gray hair, and easily breaking into a sweat showed asignificantly higher score in the kale group. As for mental
symptoms, the two items of memory lapse, and inability tosolve problems showed a significantly lower score in the
kale group than the control group.

Adverse events

There was one case of edema of the right lower leg due
to blood pressure/pulse wave measurement (self-reported),
but the symptom was mild and did not require any specifictreatment.

Discussion
The kale group showed better results than the control
group for many parameters analyzed in this cross-sectional
study, with the main differences showing in memory,
intelligence and gastrointestinal symptoms such as constipation
among the subjective physical and mental symptoms. The
risk factor analysis showed good results for markers oflipid metabolism and sugar metabolism in addition to bodycomposition, and this could explain the lower muscle age andnervous system age in the kale group compared to control
data among functional age parameters measured.
Nervous system age was lower in the kale group in thisstudy than in controls. This is notable because for the control
group, results from multiple centers using different analyzers
were mixed to determine muscle age, bone age, hormonal
age, and vascular age, but nervous system age was tested by
the same test (PC version: Wisconsin card sorting test) inall persons, and thus the results are more valid in terms ofstatistical significance. In addition, blood cortisol (stress),
homocysteine (Alzheimer risk factor 19) ), urine isoplastane(oxidative stress), and mental symptom scores (memory lapse,
and inability to solve problems) were lower in the kale groupthan the control group, supporting the results for nervous
system parameters.
Plant species of the Brassicaceae family have organic
sulfur compounds (such as sulforaphane) in common, andthere have been reports on the neuroprotective effect of extractsof broccoli sprouts, which also belong to the Brassicaceae
family in the Alzheimer cell model (SH-SY5Y cells) 20),and on the protective effect of Brussels sprouts and thephytochemicals they contain on amyloid β (Aβ) peptideinduced neurotoxicity in ICR mice 21). Since kale is also
considered to contain antioxidative polyphenols such as
sulforaphane, and the SOD activity of kale is also high (inhouse analysis: 49,000 to 110,000 units), it is likely to also
have an anti-oxidative effect on cranial nerves.
Muscle age was lower in the kale group mainly becauseof the body composition (being thin), and it can be assumed
based on the blood biochemistry results that it is possible thatthe long-term effects on sugar metabolism and lipid metabolism
indirectly contributed to weight loss. The general benefits ofBrassicaceae plants including kale on health have been widelyreported in relation to cancer, inflammation, cardiovasculardisease, and metabolic diseases including diabetes 22, 23).
Reports have also implicated kale consumption in theprevention of blood sugar elevation (in-house data), a decrease
in LDL-C, an increase in HDL-C, and increased glutathione
peroxidase activity in males with hyperlipidemia 24), and it
can be said that these data support the present results. In
addition, findings that kale supernatant promoted the in vitro
growth of Bifidobacterium longum 25), effects on intestinal
flora and beneficial effects on bowel movements due to thecontained dietary fiber are also expected, and it is possiblethat kale could help to control obesity. In fact, users of thetarget products gave the highest rating for improvement inconstipation.
The overall comparison herein also indicated that bone
age was significantly higher in the kale group than thecontrol group, namely by + 2.0 years compared with thechronological age. Bone age reflects the bone mineraldensity, and the physical constitution (being thin) of the kalegroup is considered to be a contributing factor in these results.
However, it is unlikely that the bone mineral density decreased
due to kale consumption, because factors that maintain bone
substance including sugar metabolism and homocysteine levels
were good in the kale group, and kale contains abundantvitamin K and Ca. Thus, it is possible that the bone mineraldensity results were more reflective of the subject age and thelikelihood of bone loss inhibition in postmenopausal females 5).
Moreover, while the glycative stress index markers wereslightly higher in the kale group in the present study, theglycation suppression effect of kale has been shown in an
in vitro study (in-house data), and the suppression of glycatedprotein has been reported for leaf mustard of the same
Brassicaceae family 26), and thus it is unlikely that thecomponents of kale promote glycation. Since the consumptionof alcoholic beverages, confectionery, and fruit (fructose)
was higher in the kale group than the results of a national
nutrition survey, it is possible that glycation progressed eventhough sugar metabolism-related markers were low. Since_ 86 _Glycative Stress Research

Table 6. Blood biochemistry and urine analysis.
Control group (CON)Blood biochemistry
Leukocyte count

Erythrocyte countHemoglobin
Hematocrit

Platelet countTotal bilirubin
AST

ALT
γ -GTP
LDH

×

n

mean

/μL

23

g/dL

22

5,731.3 ± 1,123.7
432.1 ± 25.5
13.2 ± 0.7

10 4 /μL%

10 4 /μL

×
mg/dL
U/L
U/L
U/L
U/L

BUN

mg/dL

Total cholesterol (TC)mg/dL

Creatinine
HDL-C
LDL-C

Triglyceride (TG)
FPG

HbA1c

mg/dL

mg/dL
%

Cl

mEq/L

Cortisol

g/dL

mEq/L
mg/dL
μg/dL

mg/dL

HOMA-R

8-OHdG production rate

Isoprostane production rate

20
22

174

1,058
1,053
1,041
193
20
29
28
13
13
64

130

nmol/mL

Urine analysis

19

pg/mL

Homocysteine
LH ratio

27

1,061

ng/mL

hsCRP

26

μg/dL

Progesterone

Estradiol (E2)

26

1,056

mEq/L

Fe

19

mg/dL

mg/dL

Na

Ca

22

1,043

μU/mL

K

21

mg/dL

Insulin (IRI)

Total protein (TP)

25

71

133
998

1,043
191

ng/kg/hr
ng/kg/hr

67
64

SD

41.0 ± 2.5
23.3 ± 5.8
0.6 ± 0.2

22.0 ± 5.7
19.5 ± 7.8
28.3 ± 21.1

209.4 ± 62.4
13.6 ± 3.8
0.6 ± 0.1
222.5 ± 36.8
64.8 ± 15.5
124.9 ± 30.9
93.4 ± 48.4
97.6 ± 16.8
5.3 ± 0.6
5.8 ± 4.2

7.2 ± 0.5
142.2 ± 1.9
4.0 ± 0.3
104.5 ± 1.8
9.4 ± 0.3

93.2 ± 30.8
9.3 ± 3.8
0.4 ± 1.1
16.9 ± 30.4
9.5 ± 2.7
6.5 ± 39.0
2.1 ± 0.8
1.3 ± 1.0
6.9 ± 3.5
2.0 ± 1.4

Kale intake group (KL)
n

mean

SD

p-value(CON vs KL)

110 4,378.2 ± 1,208.2
110 421.9 ± 31.0
11012.8 ± 0.9< 0.001 **

110

0.517

110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110
110

39.6 ± 2.5
22.5 ± 4.9
0.8 ± 0.2

21.0 ± 4.6
17.0 ± 6.1
22.2 ± 13.7

177.2 ± 28.3
13.9 ± 3.6
0.6 ± 0.1
216.7 ± 33.1
72.6 ± 15.3
126.0 ± 29.6
77.9 ± 36.0
84.6 ± 10.3
5.2 ± 0.3
3.7 ± 4.4

6.8 ± 0.4
141.6 ± 1.8
4.1 ± 0.3
105.9 ± 1.5
9.6 ± 0.4

99.7 ± 24.4
7.7 ± 2.8
0.1 ± 0.0
25.2 ± 51.0
6.4 ± 1.6
0.0 ± 0.1
1.8 ± 0.7
0.8 ± 1.5
6.7 ± 3.3
1.2 ± 0.9

0.128

0.040 *
0.019 *
0.001 **
0.332
0.081
0.069

0.039 *
0.740

0.032 *
0.180

< 0.001 **0.721< 0.001 **< 0.001 **< 0.001 **< 0.001 **< 0.001 **
0.126
0.368

0.002 **
0.126
0.130

< 0.001 **< 0.001 **0.001 **

< 0.001 **< 0.001 **0.001 **
0.003 **
0.721

< 0.001 ****p<0.01, *p<0.05, independent t-test or Mann-Whitney U test. FPG, fasting plasma glucose; IRI, immuno reactive insulin; hsCRP, high-sensitive C-reactive
protein; LH ratio, LDL-C : HDL-C ; HOMA-R, homeostasis model assessment insulin resistance; 8-OHdG, 8-hydroxydeoxyguanosine.

_ 87 _

Table 7. Physical symptom and Mental symptom score in AAQolControl group (CON)Physical symptoms
Tired eyes
Blurry eyes
Eye pain
Stiff shoulders
Muscular pains/stiffness
Palpitations
Shortness of breath
Tendency to gain weight
Weight loss, thin
Lethargy
Lack of sense of wellness
ThirstSkin problems
Anorexia
Early satiety
Epigastralgia
Liability to catch colds
Coughing and sputum
Diarrhea
Constipation
Hair loss
Gray hair
HeadacheDizziness
Tinnitus
LumbagoArthralgia
Edematous
Easily breaking into a sweat
Frequent urination
Hot flashes
Cold skin

1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063

Mental symptoms
Irritability
Easily angered
Loss of motivation
Unhappy
Nothing to look forward to in my life
Daily life is not enjoyable
No confidence
Reluctance to talk with others
Depressed
Feeling useless
Shallow sleep
Difficulty falling asleep
Pessimism
Memory lapse
Inability to concentrate
Inability to solve problems
Inability to readily make judgments
Inability to sleep due to worries
Felling tense
Felling anxious for no particular reason
Vague feeling of fear

1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063
1,063

n

mean

SD

3.19
2.63
2.01
3.64
3.07
2.09
2.07
3.00
1.56
2.48
2.35
2.14
2.28
1.72
2.06
2.00
2.08
2.13
1.90
2.44
2.47
3.68
2.35
1.99
1.93
2.89
2.50
2.32
2.56
2.31
2.08
2.82

±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±

0.98
1.04
0.97
1.13
1.14
0.93
0.93
1.27
0.79
0.96
0.97
0.98
0.90
0.72
0.92
0.89
0.89
0.94
0.82
1.15
0.93
0.95
1.01
0.88
1.01
1.16
1.13
1.04
1.19
1.02
0.98
1.21

2.51
2.37
2.29
1.91
1.91
1.90
2.09
1.85
1.90
1.88
2.52
2.36
2.29
3.12
2.46
2.17
2.15
2.21
2.46
1.98
1.76

±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±

0.85
0.81
0.88
0.85
0.87
0.83
0.85
0.81
0.81
0.78
1.12
1.11
0.92
0.84
0.85
0.77
0.77
0.87
0.86
0.85
0.78

Control group (CON)
n
mean
SD

Kale intake group (KL)
n

110
110
108
109
110
110
110
110
109
110
109
110
110
110
110
110
110
110
109
110
109
110
110
110
109
110
110
110
110
110
110
110

mean
3.33
2.72
1.92
3.50
2.89
1.76
1.70
2.94
1.56
2.50
2.31
1.92
2.51
1.56
1.84
1.90
2.05
1.87
1.66
2.15
2.50
3.95
2.33
1.85
1.85
2.75
2.55
2.42
2.81
2.25
1.95
2.59

±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±

1.01
1.07
0.99
1.24
1.21
0.87
0.81
1.37
0.85
1.06
0.95
0.98
1.00
0.74
0.80
0.86
0.91
0.92
0.81
1.21
0.91
0.81
1.08
0.90
1.01
1.06
1.12
1.05
1.22
1.10
0.93
1.12

(CON vs KL)
0.162
0.516
0.257
0.318
0.097
< 0.001 **< 0.001 **
0.626
0.692
0.966
0.705
0.011 *
0.025 *
0.010 *
0.021 *
0.264
0.675
0.003 **
0.001 **
0.004 **
0.608
0.009 **
0.737
0.078
0.383
0.200
0.464
0.222
0.029 *
0.436
0.201
0.113

2.41
2.25
2.22
2.02
2.00
2.01
2.17
1.90
1.94
1.89
2.33
2.18
2.45
2.92
2.32
1.95
2.03
2.12
2.45
1.90
1.65

±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±

0.86
0.81
0.86
0.81
0.90
0.86
0.89
0.82
0.88
0.82
1.11
1.09
1.01
0.86
0.78
0.71
0.75
0.90
0.81
0.85
0.71

0.212
0.092
0.521
0.124
0.295
0.210
0.262
0.569
0.802
0.937
0.063
0.087
0.118
0.007 **
0.129
0.008 **
0.123
0.232
0.668
0.329
0.168

Kale intake group (KL)
n
mean
SD
110
110
110
110
110
110
110
110
110
110
109
110
110
110
109
110
109
110
110
110
110

**p<0.01, *p<0.05, Mann-Whitney U test. SD, standard deviation; AAQol, Anti-Aging QOL Common Questionnaire.

_ 88 _

SD

p-valuep-value(CON vs KL)

Glycative Stress Researchglycation is also a cause of osteoporosis 27), it may also be acontributor to the higher bone age in the kale group.
Interestingly, the control group used for comparison in
the present study consisted of anti-aging examinees, andmay be a population that is more health-conscious andcontinues more physical activity than the average person.
This assumption is also supported by a comparison between
executives who had an anti-aging medical checkup andordinary males in the same age group in a major iron andsteel company, showing 7.1% higher bone mineral densityand 5.3 years younger bone age in the former group 28).
Moreover, mixed testing was performed using X-rays (dualenergy X-ray absorptiometry; DEXA) and ultrasonic method
using different models of analyzers, thus the test method is aproblem to be addressed in future studies.
Hormonal age was significantly higher in the kale groupthan the control group and was +5.9 years older than thechronological age. This could be related to the IGF-I level
being significantly lower in the kale group. IGF-I is a hormonethat repairs damaged cell tissues by cell proliferation andgrowth promotion via growth hormone, it is known to decrease
with increasing age and is used as an index of aging, and thereported factors of higher IGF-I include cancer, obesity,
metabolic syndrome-related factors 29), exercise 30), and milk(casein) consumption 31). Thus, the hormonal index is complex
and has at least two aspects of relevance to this study. Since
milk consumption was high and insulin was low in the kalegroup, it is assumed that BMI is a factor of the low IGF-I.
It is also possible that a large amount of soybean products(estrogen-like product rich ) 32), which inhibit the effectof IGF-I, were consumed in the kale group based on the
consumption of beans, and soybean product consumption may
also have a greater or lesser effect. However, because the
IGF-I value in the kale group is within the normal range, it isassumed that there is hardly any effect of kale consumption.
The above-mentioned comparison between executives
and ordinary males of the same age group also showed 15%
higher IGF-I in the former group 28). It is therefore possiblethat IGF-I was higher in the anti-aging examinees (formergroup) than the general health checkup examinees (lattergroup) due to differences in lifestyle-related behavior, andthe same can be said of the overall control group.

Conclusion

The present study compared aging of physical functions
between persons who consumed kale for at least 1 year
and a control group representing the general population.
Functional ages, particularly muscle and nervous systemage, were significantly lower in the kale group than incontrols, and the kale group was functionally better based onlaboratory test values and a comprehensive anti-aging QOL
questionnaire. These data suggest that kale consumption
could have a beneficial and preventative effect on mental
and physical aging.

Statement of Conflict of Interest

The present study was partly supported by FANCL
Corporation. FANCL Corporation was not involved in thestatistical analysis of the results.

Acknowledgment

This study was partially supported by the JapaneseCouncil for Science, Technology and Innovation, SIP(Project ID 14533567 ), “Technologies for creating nextgeneration agriculture, forestry and fisheries” (funding
agency: Bio-oriented Technology Research Advancement
Institution, NARO).

Functional age is one of the developing evaluation
method, and discussions are therefore ongoing regarding theobtained laboratory test values as valid risk factors and qualityof life (QOL) indicators regardless of the results. Notably,
the kale group tested herein showed good laboratory test
values and QOL in general.
The limitations of the present study are that the survey
region of both groups could not be unified and thus thedifference in background information of subjects such as
lifestyle-related behaviors and consumption status of meals
and health food cannot be estimated or analyzed, and that asufficient number of cases for analysis considering the kaleconsumption status could not be found in the kale group.
Despite these limitations, the result of nervous system age
can particularly be appreciated among the present findings.
There has been generally been limited efficacy of Brassicaceae
plants including kale on the neuronal function, and theevaluation in humans in particular is very difficult. We will
therefore verify the effects of kale in this field in the future.

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Reference16) Kobayashi S, Murakami K, Sasaki S, et al. Comparison

1) Yonei Y. Introduction to Anti-Aging Medicine, 2nd ed,

Keio University Publication, Tokyo, 2011. (in Japanese)

2) Hamada M, Aizawa H. Lung age: New conception forunderstanding respiratory function easily. Respiration
and Circulation. 2008; 56: 609-616. (in Japanese)3) Yonei Y, Mizuno Y. The human dock of tomorrow: Annual
health check-up for anti-aging. Ningen Dock. 2005; 19:
5-8.
4) Yonei Y, Takabe W. Aging assessment by anti-aging
medical checkup. Health Evaluation and Promotion.
2015; 42: 459-464.
5) Yamamoto N, Endo N. Effects of Kale supplementation
on bone mineral density and bone metabolic markers inpostmenopausal women. The American Society for Boneand Mineral Research (ASBMR) 2011 Annual Meeting,
San Diego, California, USA, September 16-20, 2011.
(abstract)6) Tarumizu C, Shin M, Teramo S, et al. Effect of Kale intake
on pain with knee osteoarthritis. The 33th Meeting ofJapanese Society of Clinical Nutrition, Tokyo, Japan,
October 28-29, 2011. (abstract in Japanese)7) Oono T, Shin M, Shigematsu N. Effect of Kale leaf
juice on cedar pollen allergy. The 123th Meeting ofPharmaceutical Society of Japan, Nagasaki, Japan, March
27-29, 2003. (abstract in Japanese)
8) Ishii Y, Matsuoka S, Hayamizu K, et al. Relation of Kale
leaf juice intake to blood immunology examination andskin conditions. The 58th Meeting of Japan Society of
Nutrition and Food Science, Sendai, Japan, May 21-23,
2004. (abstract in Japanese)
9) Tsuji T. To overcome the disease in a functional food Kale
physiology elucidation research. Pharmacometrics (ŌyōYakuri). 2005; 69: 52-55. (in Japanese)10) Ishii Y, Manji A, Hayamizu K et al. Effect of Kale on
alcohol metabolism: A clinical study on the flushers andmicroarray analysis. The 31th Meeting of Japanese Societyof Clinical Nutrition, Kobe, Japan, September 18-20, 2009.
(abstract in Japanese)11) Yabukita H, Miyazaki R, Nomoto K, et al. Characteristicsof physical functions in elderly people requiring support.
Anti-Aging Medicine. 2013; 10: 16-20.
12) Nomoto K, Miyazaki R, Hasegawa T, et al. Efficacy of ahealth promotion with anti-aging medical checkup andinstructions for walking under pedometer management infactory workers. Anti-Aging Medicine. 2010; 7: 73-84.
13) 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 Medicine. 2010; 7: 120-128.
14) Grant DA, Berg EA. A behavioral analysis of degree ofreinforcement and ease of shifting to new responses in a
Weigl-type card-sorting problem. J Exp Psychol. 1948;
38: 404-411.
15) Yonei Y, Takahashi Y, Watanabe M, et al. Effects on thehuman body of a dietary supplement containing l-carnitine
and Garcinia cambogia extract: A study using double-blind
tests. J Clin Biochem Nutr. 2008; 42: 89-103.

of relative validity of food group intakes estimated bycomprehensive and brief-type self-administered diet history
questionnaires against 16 d dietary records in Japanese
adults. Public Health Nutr. 2011; 14: 1200-1211.
17) Kobayashi S, Honda S, Murakami K, et al. Both
comprehensive and brief self-administered diet history
questionnaires satisfactorily rank nutrient intakes inJapanese adults. J Epidemiol. 2012; 22: 151-159.
18) Meerwaldt R, Links T, Graaff R, et al. Simple noninva
sive measurement of skin autofluorescence. Ann N Y Acad
Sci. 2005; 1043: 290-298.
19) Beydoun MA, Beydoun HA, Gamaldo AA, et al.
Epidemiologic studies of modifiable factors associatedwith cognition and dementia: Systematic review and metaanalysis. BMC Public Health. 2014 Jun 24; 14: 643.
20) Masci A, Mattioli R, Costantino P, et al. Neuroprotective
effect of Brassica oleracea sprouts crude juice in a cellularmodel of Alzheimer's disease. Oxid Med Cell Longev.
2015; 2015: 781938.
21) Kim JK, Shin EC, Kim CR, et al. Effects of brussels sprouts
and their phytochemical components on oxidative stressinduced neuronal damages in PC12 cells and ICR mice. J
Med Food. 2013; 16: 1057-1061.
22) Manchali S, Murthy KNC, Patil BS. Crucial facts about
health benefits of popular cruciferous vegetables. Journalof Functional Foods. 2012; 4: 94 -106.
23) Mohamed S. Functional foods against metabolic syndrome(obesity, diabetes, hypertension and dyslipidemia) andcardiovasular disease. Trends in Food Science & Technology.
2014; 35: 114-128.
24) Kim SY, Yoon S, Kwon SM, et al. Kale juice improves
coronary artery disease risk factors in hypercholesterolemicmen. Biomed Environ Sci. 2008; 21: 91-97.
25) Suido H, Miyao M. Bifidobacterium longum-fermented
broccoli supernatant inhibited the growth of Candida
albicans and some pathogenic bacteria in vitro. Biocontrol
Science. 2008; 13: 41-48.
26) Yokozawa T, Kim HY, Cho EJ, et al. Protective effects ofmustard leaf (Brassica juncea) against diabetic oxidative
stress. J Nutr Sci Vitaminol (Tokyo). 2003; 49: 87-93.
27) Hein G, Wiegand R, Lehmann G, et al. Advanced
glycation end-products pentosidine and N epsiloncarboxymethyllysine are elevated in serum of patients withosteoporosis. Rheumatology (Oxford). 2003; 42: 1242-1246.
28) Yonei Y, Iwaita Y, Muramatsu K, et al. The anti-aging
secrets of Japanese executives. Anti-Aging Medical
Research. 2005; 2: 61-69.
29) Ungefroren H, Gieseler F, Lehnert H. Obesity and cancer.
Internist (Berl). 2015; 56: 127-128, 130-136. (in German)30) Gregory SM, Spiering BA, Alemany JA, et al. Exerciseinduced insulin-like growth factor I system concentrations
after training in women. Med Sci Sports Exerc. 2013; 45:
420-428.
31) Qin LQ, He K, Xu JY. Milk consumption and circulating
insulin-like growth factor-I level: A systematic literature
review. Int J Food Sci Nutr. 2009; 60: 330-340.
32) Takata Y, Maskarinec G, Rinaldi S, et al. Serum insulinlike growth factor-I levels among women in Hawaii andJapan with different levels of tofu intake. Nutr Cancer.
2006; 56: 136-142.

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