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Analysis of Individual Variations in Autonomic Responses to Urban and Forest Environments

Hindawi Publishing Corporation

Evidence-Based Complementary and Alternative Medicine

Volume 2015, Article ID 671094, 7 pages

http://dx.doi.org/10.1155/2015/671094

Research Article

Analysis of Individual Variations in Autonomic Responses to

Urban and Forest Environments

Hiromitsu Kobayashi,1 Chorong Song,2 Harumi Ikei,2,3

Takahide Kagawa,3 and Yoshifumi Miyazaki2

1Ishikawa Prefectural Nursing University, 1-1 Gakuendai, Kahoku, Ishikawa 929-1210, Japan

2Center for Environment, Health and Field Sciences, Chiba University, 6-2-1 Kashiwa-no-ha, Kashiwa-shi, Chiba 277-0882, Japan

3Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba, Ibaraki 305-8687, Japan

Correspondence should be addressed to Yoshifumi Miyazaki; ymiyazaki@faculty.chiba-u.jp

Received 29 July 2015; Accepted 20 September 2015

Academic Editor: Giuseppe Caminiti

License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly

cited.

Autonomic responses to urban and forest environments were studied in 625 young male subjects. The experimental sites were 57

forests and 57 urban areas across Japan. The subjects viewed the landscape (forest or urban environment) for a period of 15 min

while sitting on a chair. During this period, heart rate variability (HRV) was monitored continuously. The results were presented as

histograms and analyzed with special reference to individual variations. Approximately 80% of the subjects showed an increase in

the parasympathetic indicator of HRV (lnHF), whereas the remaining subjects showed a decrease in the parasympathetic activity.

Similarly, 64.0% of the subjects exhibited decreases in the sympathetic indicator of HRV (ln[LF/HF]), whereas the remaining

subjects showed opposite responses. Analysis of the distribution of HRV indices (lnHF and ln[LF/HF]) demonstrated the effect

of forest environments on autonomic activity more specifically than the conventional analysis based on the difference in mean

values.

1. Introduction

Recently, there has been growing interest in the effects of the

natural environment on human health. Beneficial effects may

include stress relief, improved cognition and physical activity,

better social cohesion, and promotion of overall health and

mental well-being [1]. The predisposition of humans to

responding positively to the natural environment may be a

result of past adaptation to natural environments for survival

or ongoing well-being during evolution [2].

The psychological effects of exposure to a forest envi-

ronment on emotions have been demonstrated by various

researchers. Bowler et al. [3] performed a meta-analysis of the

results of several studies on the effect of natural environments

and concluded that the natural environment has a consistent

effect of reducing negative emotions (anger, fatigue, or sad-

ness). In addition, exposure to a forest environment may have

a positive effect on psychiatric impairments, such as alcoholic

depression [4].

In recent years, along with psychological responses,

physiological responses to a forest environment have been

investigated. Studies have demonstrated that exposure to a

forest environment results in reduced physiological indi-

cators for stress. For example, lower fluctuation in skin

conductance, shorter pulse-transit time (suggesting lower

blood pressure), lower tension in frontalis muscles, and lower

heart rate were observed during exposure to a video of natural

settings [2]. Exposure to real forest environments decreased

salivary cortisol concentration [5, 6] and cerebral blood flow

(indicating a relaxation in brain activity) [6] and increased

natural killer (NK) cells (indicating an enhancement of the

immune system) [7–9]. Furthermore, Ohtsuka et al. [10]

reported that a long-term experience in forest environment

has significantly reduced blood glucose levels in patients with

diabetes.

The current study investigated the effects of forest envi-

ronments on autonomic nervous activity using heart rate

variability (HRV) as an indicator. The relationship between

Evidence-Based Complementary and Alternative Medicine

HRV and autonomic functions has been established by

previous studies [11–13]. Use of HRV as a physiological

indicator of stress is also well established. In addition, during

recent years within the field of alternative medicine, the effect

of acupuncture has been evaluated by HRV [14, 15].

Our previous studies have demonstrated an increase in

the high frequency (HF) component and/or a decrease in the

low frequency (LF)/HF ratio of HRV in forest environments

[16–19]. Similar results have been observed in parks in urban

areas [20, 21] or during exposure to indoor plants [22, 23]. The

HF component of HRV is considered a marker of parasym-

pathetic activity, whereas the LF component or LF/HF ratio

is considered a marker of sympathetic activity [24]. Thus,

the results of the abovementioned studies suggested a relative

activation of the parasympathetic function.

Use of HRV for evaluating stress provides some advan-

tages over alternative physiological measurements. HRV can

be recorded continuously in a noninvasive manner. Fur-

thermore, use of a portable heart rate monitor can provide

ambulatory recording of HRV. These advantages might be

maximized in field studies rather than experimental studies.

Thus, HRV can be the appropriate indicator of physiological

responses to forest environments.

One of the features of the current study is an analysis

with special reference to the distribution characteristics of

individual variations in the HRV response. Most previous

studies on physiological responses to environments have

focused on the differences in the mean value; individual

variations were considered an error or impurities. Individual

variations have been an underutilized resource in various

fields of life sciences. Bennett [25] described the tendency of

focusing on means as the “tyranny of the golden mean.” From

the viewpoint of adaptation, individual variations should

have biological and/or evolutionary significance and should

decidedly not be viewed as an error or impurity. The mean

value has certain significance as one of the representative

values of a population; however, it represents no more signif-

icance than any other aspect of the physiological responses of

a population.

Analysis of the physiological response focusing on indi-

vidual variations may be challenging compared with an

analysis focusing on the mean value because the analysis

of individual variations requires a larger sample size. The

current study investigated the frequency components of HRV

in 625 young Japanese males in urban and forest environ-

ments. The current study utilized a large sample size and

can therefore provide a new perspective on the physiological

responses to natural environments.

2. Materials and Methods

2.1. Study Sites and Subjects. The study sites were 57 forest

and 57 urban areas across Japan. The chosen urban sites were

downtown or nearby a Japan Railway (JR) station.

Although 684 young Japanese male university students

participated in the experiments, only 625 subjects with

complete data for both urban and forest sites were included

in the analysis. The demographic parameters of the subjects

are shown in Table 1.

Table 1: Demographic parameters of the subjects (𝑛 = 625).

Age (years)

Mean

21.6

1.6

Max

Min

∗SD: standard deviation.

Height (cm)

172.3

5.6

188

155

Weight (kg)

64.7

9.6

110

None of the subjects reported a history of physical or

psychiatric disorders. Consumption of alcohol and tobacco

was prohibited and consumption of caffeine was controlled

during the study period. The study was performed according

to the regulations of the Ethics Committee of the Center for

Environment, Health, and Field Sciences, Chiba University,

or the Institutional Ethics Committee of the Forestry and

Forest Products Research Institute in Japan.

2.2. Physiological Measurements. HRV was measured using

a portable electrocardiograph (Activtracer AC-301A, GMS,

Japan). Spectral analysis of HRV was conducted for 15

min recordings using HRV software (MemCalc/Win, GMS,

Tokyo, Japan) based on the maximum entropy method. The

HF and LF components were obtained by integration of

the power spectra at the respective ranges of 0.15–0.40 and

0.04–0.15 Hz. The natural logarithms of the HRV indices

(lnHF, ln[LF/HF]) were then calculated, considering that the

raw HRV components indicate skewed distributions [26]. In

the current study, HRV was measured during spontaneous

breathing, and paced breathing was not applied. The subjects

were instructed to avoid irregular breathing during the

measurements. A previous study has reported that paced

breathing has a negligible effect on interindividual variations

in the spectral components of HRV [27].

2.3. Experimental Design. The experiment was performed at

each experimental site over 2 consecutive days. Before the

experiment, the aim of the study and the experimental pro-

tocol was explained and general instructions were provided

to the subjects. The subjects ate lunch between 11:30 and

12:30, and the measurements were conducted between 13:30

and 15:30. All subjects were nonsmokers. Alcohol intake and

unusual physical activity on the day before the measurement

were forbidden.

The subjects at each site were randomly divided into two

groups, and the order of exposure to the experimental con-

ditions (urban or forest) differed among the two groups. One

group was exposed to the forest site prior to the urban site,

and the other group followed the reverse order. All subjects

remained in a waiting room before moving to the field site.

All subjects were instructed to rest on a chair for 5 min, which

mitigated the physiological effects of any possible physical

activity before the measurement period. HRV measurements

were obtained during 15 min when the subjects viewed the

landscape. On the second day, the subjects switched the field

sites. The experimental protocol on the second day was the

same as that on the first day.

Evidence-Based Complementary and Alternative Medicine

Table 2: Descriptive statistics of the distribution of heart rate variability (𝑛 = 625).

ln HF

ln(LF/HF)

Urban

Forest

Urban-forest

Urban

Forest

Urban-forest

Mean

5.54

6.02

−0.48

1.48

1.32

0.16

Median

5.66

6.14

−0.45

1.51

1.31

0.16

0.92

1.01

0.70

0.77

0.82

0.71

5th percentile

3.81

4.41

−1.57

0.16

0.00

−0.92

95th percentile

6.9

7.29

0.56

2.70

2.66

1.19

Skewness

−1.20

−1.10

−0.92

−0.21

0.32

−0.46

Kurtosis

3.42

2.97

8.21

0.47

0.97

4.24

∗SD: standard deviation; skewness: a measure of symmetry of distribution; Kurtosis: a measure of whether the distribution curve is peaked (positive) or flat

(negative) relative to the normal distribution.

Among the experiments at 57 sites, the experimental

design used at 44 sites was the “Stay-in Forest Therapy”

design, where arrangements were made for all subjects to

reside in a hotel with identical single rooms. At the remaining

13 sites, the experimental design of “One-Day Forest Therapy”

was used, where the subjects were allowed to return home

after the first day. To reduce inconvenience to subjects and

to limit research expenses, we switched to the simplified

experimental design of One-Day Forest Therapy.

2.4. Data Analysis. Mean, median, standard deviation (SD),

5th and 95th percentile values, skewness, and kurtosis were

calculated for each HRV index. Skewness is a measure of

symmetry of distribution. Negative or positive skewness is

indicated when the left or right tail of the research data

fitted to a histogram is longer, respectively. The skewness of a

normal distribution is zero. Kurtosis is a measure of whether

the distribution curve is peaked (positive) or flat (negative)

relative to the normal distribution. The kurtosis of a normally

distributed data set is zero. Statistical analysis was performed

using IBM SPSS statistics ver. 21 (IBM, New York, US).

3. Results and Discussion

3.1. Individual Variations in Autonomic Responses to a Forest

Environment. The descriptive statistics of the distribution

of the HRV indices are summarized in Table 2. The mean

lnHF in urban and forest environments was 5.54 and 6.02

[ln(ms2)], respectively. A larger lnHF value was observed in

forest environments, suggesting activation of the parasym-

pathetic function. The histograms for lnHF are shown in

Figure 1. Although the mean values were different, the dis-

tribution curves were almost identical between urban and

forest environments. In both environments, the distributions

indicated slightly left skewed and peaked curves compared

with the normal distribution (Figures 1(a) and 1(b)). Dif-

ferences in lnHF between urban and forest environments

were calculated individually and depicted as a histogram

(Figure 1(c)). Negative values in the difference imply that

lnHF was larger in forest than in urban environments,

whereas the positive values in the difference imply that

lnHF was smaller in forest than in urban environments. A

histogram showing the difference indicated a slightly left-

skewed and markedly peaked distribution. In the results of

the current study, 495 out of 625 (79.2%) subjects exhibited

an increase in lnHF in forest environments.

The results of ln(LF/HF) were analyzed in a similar way to

lnHF. The mean ln(LF/HF) in urban and forest environments

was 1.48 and 1.32, respectively. Lower ln(LF/HF) values were

observed in forest environments, suggesting suppression of

the sympathetic function. The histograms for ln(LF/HF)

are shown in Figure 2. A histogram for the difference in

ln(LF/HF) between urban and forest environments indicated

an almost symmetrical distribution (Figures 2(a) and 2(b)).

Furthermore, 397 out of 625 (63.5%) subjects exhibited a

decrease in ln(LF/HF) in forest environments (Figure 2(c)).

In summary, approximately 80% of the subjects showed

an increase in the parasympathetic activity in forest environ-

ments, whereas the remaining subjects exhibited a negative

effect of the forest environments. The mean lnHF in urban

and forest environments was 5.54 and 6.02 [ln(ms2)], respec-

tively; thus, the change was approximately 9%. Although the

difference in the mean values was statistically significant,

the difference appeared marginal. On the other hand, the

ratio of positive and negative responders (80 : 20) was a more

conclusive result as compared with the changes in the mean

values. Similar results were obtained for the sympathetic

indicator [ln(LF/HF)]. Thus, histograms are considered to be

an efficient tool for the analysis of physiological responses

to natural environments in which larger individual variation

exists.

3.2. Effect of Respiration and Air Pollution. It has been

known that HRV is closely related with respiratory rate.

Slower respiratory rate produces larger HF power in the

HRV spectrum. Increased HF in a forest environment may

relate with slower and/or deeper respiration. Gladwell et al.

[28] studied the effects of natural and urban landscapes on

heart rate, blood pressure, and respiration. In their results,

no significant changes were observed in the respiratory rate

and depth, although a parasympathetic indicator of HRV

increased in natural landscape similar to the present results.

Thus, the change in the respiratory rate is not considered to

be a major cause of the increased HF in forest.

lnHF

Evidence-Based Complementary and Alternative Medicine

(a) Urban environment

Increase

at forest site

79.2%

(b) Forest environment

Decrease

at forest site

20.8%

Figure 1: Histograms showing the high frequency component (lnHF) of heart rate variability in urban and forest environments. (a) lnHF at

urban sites, (b) lnHF at forest sites, and (c) difference in lnHF between urban and forest sites.

In recent years, the effect of air pollution on human HRV

has been attracting attention in the field of environmental

medicine. A relationship between increased PM2.5 (par-

ticulate matter with an aerodynamic diameter of <2.5 𝜇m)

and decreased parasympathetic indicator of HRV has been

reported [29, 30]. Because the effect of PM2.5 was considered

to be acute rather than chronic [31], the difference in air

pollution between urban and forest environments may be an

explanation of the present results.

3.3. Biophilia and Biophobia. The biophilia hypothesis was

proposed by the distinguished biologist Wilson [32]. Bio-

philia is defined as the “innate tendency to focus on life and

life-like processes” [33]. This tendency could be explained

from an evolutionary perspective. For millions of years,

human beings (or their recent ancestors) lived in the savannas

of Africa. Within this environment, natural features such as

trees or forests could provide food, water, or shelter, thereby

increasing the probability of survival. Thus, biophilia can be

regarded as an adaptive characteristic of human evolution.

On the other hand, it has been known that certain people

show a strong dislike for natural settings. This tendency is

called biophobia [34]. Biophobia includes certain specific

phobias, such as arachnophobia (irrational fear of spiders)

or entomophobia (fear of insects). Previous studies have

reported that patients displaying arachnophobia showed

Evidence-Based Complementary and Alternative Medicine

ln(LF/HF)

(a) Urban environment

Increase

at forest site

36.5%

(b) Forest environment

Decrease

at forest site

63.5%

Figure 2: Histograms showing the low frequency/high frequency ratio (ln[LF/HF]) of heart rate variability in urban and forest environments.

(a) ln(LF/HF) at urban sites, (b) ln(LF/HF) at forest sites, and (c) difference in ln(LF/HF) between urban and forest sites.

increased HR or HRV during presentation of images of spi-

ders [35, 36]. Without actually perceiving spiders or insects,

people exhibiting these phobias manifested phobic reactions

even if they merely imagined spiders or insects in their

immediate environment. Therefore, the negative responders

in the results of the current study could be explained by these

specific phobias to living things. Further consideration of

the relationship between physiological responses to the forest

environment and biophobia is expected in future studies.

4. Conclusion

Autonomic responses to a forest environment were studied

in 625 young male subjects. The results were demonstrated

using histograms and were analyzed with special reference

to individual variations. An increase in the parasympathetic

indicator of HRV (lnHF) was observed in approximately

80% of the subjects. Analysis of the distribution of HRV

indices (lnHF and ln[LF/HF]) demonstrated the effect of

forest environments on autonomic activity more specifically

than the conventional analysis based on mean values.

Conflict of Interests

The authors declare that there is no conflict of interests

regarding the publication of this paper.

Acknowledgments

The authors thank Dr. Yuko Tsunetsugu, Mr. Takeshi

Morikawa of Forestry and Forest Products Research Institute,

Dr. Bum-Jin Park of Chungnam National University, and Dr.

Juyoung Lee of Korea Forest Service for their assistance in

the experiments. This study was supported by the 2015 Strate-

gic Innovation Promotion (SIP) Program of the National

Agriculture and Food Research Organization (NARO) in

Japan.

Evidence-Based Complementary and Alternative Medicine

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Computational and

Mathematical Methods

in Medicine

Hindawi Publishing Corporation

http://www.hindawi.com

Volume 2014

Behavioural

Neurology

Hindawi Publishing Corporation

http://www.hindawi.com

Volume 2014

Hindawi Publishing Corporation

http://www.hindawi.com

Volume 2014

AIDS

Research and Treatment

Hindawi Publishing Corporation

http://www.hindawi.com

Volume 2014

Oxidative Medicine and

Cellular Longevity

Hindawi Publishing Corporation

http://www.hindawi.com

Volume 2014