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Forest Walking Affects Autonomic Nervous Activity: A Population-Based Study

ORIGINAL RESEARCH

published: 01 October 2018

doi: 10.3389/fpubh.2018.00278

Forest Walking Affects Autonomic

Nervous Activity: A Population-Based

Study

Hiromitsu Kobayashi 1, Chorong Song 2, Harumi Ikei 2,3, Bum-Jin Park 4, Juyoung Lee 5,

Takahide Kagawa 3 and Yoshifumi Miyazaki 2*

1 Department of Nursing, Ishikawa Prefectural Nursing University, Ishikawa, Japan, 2 Center for Environment, Health and Field

Sciences, Chiba University, Kashiwa, Japan, 3 Forestry and Forest Products Research Institute, Tsukuba, Japan,

4 Department of Environment and Forest Resources, Chungnam National University, Daejeon, South Korea, 5 Department of

Landscape Architecture, Hankyong National University, Anseong-si, South Korea

Edited by:

Mohiuddin Md. Taimur Khan,

Washington State University,

United States

Reviewed by:

Jean Challacombe,

Colorado State University,

United States

Ellie Abdi,

Montclair State University,

United States

*Correspondence:

Yoshifumi Miyazaki

ymiyazaki@faculty.chiba-u.jp

Specialty section:

This article was submitted to

Environmental Health,

a section of the journal

Frontiers in Public Health

Received: 17 April 2018

Accepted: 10 September 2018

Published: 01 October 2018

Citation:

Kobayashi H, Song C, Ikei H,

Park B-J, Lee J, Kagawa T and

Miyazaki Y (2018) Forest Walking

Affects Autonomic Nervous Activity:

A Population-Based Study.

Front. Public Health 6:278.

doi: 10.3389/fpubh.2018.00278

The present study aimed to evaluate the effect of walking in forest environments on

autonomic nervous activity with special reference to its distribution characteristics. Heart

rate variability (HRV) of 485 male participants while walking for ∼15 min in a forest and

an urban area was analyzed. The experimental sites were 57 forests and 57 urban

areas across Japan. Parasympathetic and sympathetic indicators [lnHF and ln(LF/HF),

respectively] of HRV were calculated based on ∼15-min heart rate recordings. Skewness

and kurtosis of the distributions of lnHF and ln(LF/HF) were almost the same between

the two environments, although the means and medians of the indicators differed

signiﬁcantly. Percentages of positive responders [presenting an increase in lnHF or a

decrease in ln(LF/HF) in forest environments] were 65.2 and 67.0%, respectively. The

percentage of lnHF was signiﬁcantly smaller than our previous results on HRV during

the viewing of urban or forest landscapes, whereas the percentage of ln(LF/HF) was

not signiﬁcantly different. The results suggest that walking in a forest environment has a

different effect on autonomic nervous activity than viewing a forest landscape.

Keywords: forest therapy, walking, heart rate variability (HRV), skewness, kurtosis, population approach

INTRODUCTION

“Shinrin-yoku” is a Japanese term for “forest bathing,” which was coined by the Director of the

Japanese Forestry Agency, Tomohide Akiyama, in 1982 (1). This term is now increasingly being

used internationally (1–3). Various studies on the psychological eﬀects of natural environments

have been conducted, with consistent eﬀects of reducing negative emotions, such as anger, fatigue,

or sadness, being demonstrated in previous studies (4). In addition to psychological eﬀects,

beneﬁcial eﬀects of a forest environment in terms of physiological responses have also been

investigated (5). Decreases in blood pressure (6–8), in serum or salivary cortisol concentration

(6, 9, 10), and enhancements in immune system functioning (11–13) have been reported.

Heart rate variability (HRV) measurement is a method for evaluating autonomic nervous

functions. HRV measurement is the most frequently used physiological indicator in studies

on the eﬀect of forest environments and demonstrates better results than other physiological

measurements, such as salivary cortisol concentration (10). The power spectrum of the heartbeat

interval sequence generally exhibits two spectral components: a high-frequency (HF; 0.15–0.40 Hz)

component and a low-frequency (LF; 0.04–0.15 Hz) component. The HF component of HRV is

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October 2018 | Volume 6 | Article 278

Kobayashi et al.

Forest Walking Affects Autonomic Functions

considered to be a marker of parasympathetic activity, whereas

the LF component or LF/HF ratio is considered to be a marker

of sympathetic activity (14, 15). Several studies have consistently

demonstrated increases in HF and/or decreases in LF/HF in

forest environments compared with the corresponding levels in

urban environments (16–18). These results suggest that being

present in a forest environment relaxes the autonomic nervous

system.

HRV measurements have the advantages of enabling

continuous ambulatory monitoring and robustness against

artifacts, such as body movement. These advantages might

be maximized in measurement performed during walking in

a ﬁeld environment rather than during resting in laboratory

condition. HRV measurements have also been applied in studies

on the eﬀects of walking in natural environments (19–21),

which also reported relaxation of autonomic nervous system in

forest environments similar to that in studies conducted on a

resting condition. The present study investigated the HRV of

485 young male participants during walking in forest and urban

environments.

In eﬀorts to promote human health, there are two types

of strategy: a high-risk (individual) approach and a population

approach. The high-risk approach targets individuals with a

certain disease or impairment, whereas the population approach

targets an entire population. Nature therapy, including “shinrin-

yoku,” is one of the population approaches to promote health.

Although its eﬀects on each individual are relatively small, at the

population level, it can achieve greater health improvement by

shifting the risk distribution curve of the entire population (22).

Thus, the beneﬁcial eﬀect of exposure to the natural environment

should be evaluated using a population-based analysis with

special reference to its distribution characteristics. However, most

previous studies on nature therapy have merely focused on the

change in the mean values of health-related variables [e.g., (6–

13)]. To adopt a population-level perspective, in this study, we

analyzed HRV indicators of 485 male participants with special

reference to their distribution characteristics. In addition, we

compared our results obtained during walking with those during

the viewing landscapes reported in a previous study (17).

MATERIALS AND METHODS

Study Sites and Participants

The study areas were 57 forests and 57 urban sites across Japan.

Urban areas were downtown or near a Japan railway station.

Although 684 young (aged 19–29 years) Japanese male university

students participated in the experiments, only 520 participants

whose complete data could be obtained at both forests and urban

sites were analyzed. Demographic parameters of the participants

are shown in Table 1. None of the participants reported a history

of physical or psychiatric disorders. During the study period,

alcohol and tobacco consumption was prohibited and caﬀeine

consumption was controlled.

Experimental Design

The experiment was performed at each experimental area over

2 consecutive days. Prior to the experiment, the aim of this

TABLE 1 | Demographics of the participants (n = 520).

Age (year)

Height (m)

Max

1.88

Min

1.55

Mean

21.7

1.72

1.6

0.06

SD, standard deviation.

Body mass (kg)

110

64.6

9.5

study and the experimental protocol was explained and general

instructions were provided to the participants. The participants

participating in an experiment at each site were randomly divided

into two groups, and the order of the experimental conditions

(urban or forest) was counterbalanced among them. One group

performed the experiment in the forest area prior to the urban

area, and the other group performed the same experiment

in the urban area prior to the forest area. All participants

stayed in a waiting room before moving to the ﬁeld site. All

participants were instructed to rest in a chair for ∼5 min, which

mitigated the physiological eﬀects of physical activity before

the measurement period. The HRV data were obtained during

walking in a forest or an urban environment for ∼15 min.

On the second day, the participants switched ﬁeld sites. The

experimental protocol for the second day was the same as the

ﬁrst day.

Among the experiments at 57 locations, those at 44 locations

were performed with the experimental design of “Stay-in

Forest Therapy,” in which all participants were instructed to

reside in a hotel with identical single rooms. Meanwhile,

the experiments at 13 locations were performed with the

experimental design of “One-Day Forest Therapy,” in which

the participants returned home after the ﬁrst day of the

experiment. To reduce the burden on participants and the

research expenses, eventually all experiments were switched

to the simpliﬁed experimental design of One-Day Forest

Therapy.

HRV Measurements

HRV was measured using a portable electrocardiograph

(Activtracer AC-301A; GMS, Japan). Spectral analyses of HRV

in 15-min recordings were conducted using HRV software

(MemCalc/Win; GMS, Tokyo, Japan) based on the maximum

entropy method. HF and LF components were obtained by

integrating the power spectra at their 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 because it has

been reported that the raw HRV components exhibit skewed

distributions (23).

In this study, HRV was measured during spontaneous

breathing, and paced breathing was not applied. The

participants were instructed to avoid irregular breathing

during the measurements. A previous study reported

that the eﬀect of paced breathing on inter-individual

variations in the spectral components of HRV was

negligible (24).

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Kobayashi et al.

Forest Walking Affects Autonomic Functions

Outlier Processing

Outlier processing was performed on the results because

higher-moment statistics (skewness and kurtosis) are particularly

sensitive to outliers (25). The outlier processing was based on a

box-whisker plot (26). Upper and lower cut-oﬀs (upperCO and

lowerCO, respectively) were deﬁned as follows:

UpperCO = Q3 + 1.5 (IQR), (1)

LowerCO = Q1 – 1.5 (IQR), (2)

where

Q1: quartile 1 (25th percentile)

Q3: quartile 3 (75th percentile)

IQR: interquartile range (Q3–Q1)

The outlier processing was performed on the HRV indices

[lnHF and ln(LF/HF)] obtained in each environment (urban and

forest). The lowerCOs and upperCOs are summarized in Table 2.

The participants associated with outliers in either

environment were eliminated. As a result, 35 participants

were eliminated, and the data of the remaining 485 participants

were used for further analysis.

Statistical Analysis

HRV indicators of the 485 participants were plotted as

histograms by dividing the range [from 1.0 to 7.5 for lnHF, from

0.0 to 4.0 for ln(LF/HF)] into 40 segments. Changes in HRV

indices between urban and forest environments (forest–urban)

were also plotted as a histogram by dividing the range [from

−4.5 to +5.5 for lnHF, from −3.0 to +2.0 for ln(LF/HF)] into

40 segments.

The mean, median, standard deviation (SD), coeﬃcient of

variation (CV), IQR, skewness, and kurtosis of the distribution

were calculated. Skewness is a measure of the symmetry of

distribution. Negative or positive skewness is indicated when

the left or right tail, respectively, of the research data in a

histogram is longer than the other tail. The skewness of a normal

distribution is zero. Meanwhile, kurtosis is a measure of whether

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

relative to the normal distribution. The kurtosis of normally

distributed data is deﬁned as zero.

Diﬀerences in these statistics between urban and forest

environments were tested by performing a permutation test,

which is a statistical test with a non-parametric basis. Resampling

was performed 5,000 times. The p-value was calculated according

to the suggestion by Phipson and Smyth (27). The uncertainty of

a p-value near 0.05 was estimated to be 0.3%.

TABLE 2 | Cut-off values of heart rate variability for the outlier processing.

lnHF

Urban

Forest

ln(LF/HF)

Urban

Forest

LowerCO

0.85

1.09

0.49

0.22

UpperCO

6.95

7.54

3.83

3.76

CO, Cut-off value for the outlier processing.

For further analysis, results of this study were compared

with those of our previous study (17). In the previous study,

autonomic responses to urban and forest environments were

studied in 625 young male participants. The participants viewed

the landscape (forest or urban environment) for 15 min while

sitting on a chair. When viewing the landscapes, HRV was

monitored continuously.

Number of participants who indicated positive or negative

responses were calculated for present (walking) and the

previous (viewing) results. Positive and negative responses

to forest environments were deﬁned as a decrease in lnHF

and an increase in ln(LF/HF), respectively. The diﬀerence

between the present and previous studies with respect to

the ratio of negative/positive responders was compared using

Chi-squared test. p-values < 0.05 were considered indicative

of statistical signiﬁcance for permutation and Chi-squared

tests.

ETHICAL CONSIDERATIONS

The study was conducted in accordance with the Declaration

of Helsinki, and the protocol was approved by the Ethics

Committee of the Forestry and Forest Products Research

Institute, Japan (project identiﬁcation code number: 16-

558), or the Center for Environment, Health and Field

Sciences, Chiba University, Japan (project identiﬁcation

code number: 5). Participants were informed about the

purposes and procedures of the study and provided written

informed consent prior to enrollment. They were free to

not attend or cease participation in the program at any

time.

RESULTS

Histograms of HRV indicators during walking in urban and

forest environments are shown in Figure 1, and statistics of

these indicators are summarized in Table 3. The means of lnHF

were 3.93 and 4.33 for the urban and forest environments,

respectively. The permutation test revealed that mean lnHF

during walking in a forest was signiﬁcantly larger than during

walking in an urban area (p < 0.01). The medians of lnHF

were 3.96 and 4.27 for the urban and forest environments,

respectively, which were also signiﬁcantly diﬀerent (p < 0.01).

Although the diﬀerence was not signiﬁcant (p = 0.06), SD

was slightly greater in the forest environment than in the

urban environment, resulting in CV being almost unchanged

(p = 0.83). Both Q1 and Q3 were larger in forest walking

(p < 0.01), and as a result, there was no diﬀerence in IQR

(p = 0.62).

In regards to In(LF/HF) the means were 2.16 in the

urban environment and 1.96 in the forest environment, and

signiﬁcantly larger ln(LF/HF) was observed in the urban

environment than in the forest environment (p < 0.01). As for the

median of Q1 and Q3, the diﬀerences between urban and forest

areas were statistically signiﬁcant, but the diﬀerences in SD and

IQR were not as signiﬁcant. These results were similar to those

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Kobayashi et al.

Forest Walking Affects Autonomic Functions

FIGURE 1 | Histograms of heart rate variability during walking in urban and forest environments. Upper panels show the distribution of lnHF in urban (A) and forest

(B) environments, and lower panels show the distribution of ln(LF/HF) in urban (C) and forest (D) environments. For both lnHF and ln(LF/HF), no signiﬁcant differences

in the shape of the distribution curve were observed between urban and forest environments.

of lnHF, although the direction of the change was the opposite.

Unlike the results of lnHF, nevertheless, CV of ln(LF/HF) was

signiﬁcantly larger in the forest environment (32.1) than in the

urban environment (28.5) (p < 0.01).

The mean and median values were very close in both

HRV indicators and in both environments. For example, the

values were 3.93 (mean) and 3.96 (median) for lnHF in

an urban area. This suggested that the distribution curves

of this variable were almost symmetric. This symmetrical

distribution was also conﬁrmed by higher moment statistics.

Skewness and kurtosis were close to zero for both HRV

indicators and both environments, suggesting nearly normal

distributions.

The diﬀerences between urban and forest environments for

lnHF and ln(LF/HF) were plotted in a histogram (Figure 2).

Positive and negative values in the abscissa represent increases

and decreases in the HRV indicator in a forest environment,

respectively. Due to an increase in lnHF or a decrease

in ln(LF/HF) is considered to represent relaxation, it was

deﬁned that these changes are positive responses. Conversely,

a decrease in lnHF and an increase in ln(LF/HF) were deﬁned

as negative responses. As for lnHF, 316 (65.2%) participants

showed positive responses in the forest environment rather

than in the urban environment, and the remaining 169 (34.8%)

participants exhibited negative responses. The ln(LF/HF), 325

(67.0%) showed decreases in the forest environment and the

remaining 160 (33.0%) exhibited negative responses.

The present results of HRV during walking were compared

with the previously reported results on HRV during the

viewing of landscapes (17). The numbers of participants who

indicated positive/negative responses in HRV indicators in a

forest are summarized in Table 4. In our previous results (17),

79.2% participants exhibited positive responses (increases in the

forest environment) in lnHF during the viewing of landscapes.

The proportion of positive responders during viewing was

considerably larger than the proportion during walking. A chi-

square test revealed signiﬁcant diﬀerence in the proportion

of positive responders in lnHF between walking and viewing

(p < 0.01).

On the other hand, the proportion of positive responders in

ln(LF/HF) during viewing was 64.0%, which was close to the

proportion during walking (67.0%) demonstrated in this study.

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Kobayashi et al.

Forest Walking Affects Autonomic Functions

TABLE 3 | Distribution characteristics of heart rate variability indices urban and forest environments.

Urban

lnHF

Forest

Difference

(p-value)

Urban

ln(LF/HF)

Forest

Difference

(p-value)

Mean

Median

CV (%)

IQR

Skewness

Kurtosis

3.93

3.96

1.06

27.0

3.17

4.65

1.49

−0.03

−0.30

4.33

4.27

1.16

26.74

3.56

5.11

1.55

0.13

−0.13

p < 0.01

p = 0.06

p = 0.83

p < 0.01

p = 0.62

p = 0.24

p = 0.43

2.16

2.18

0.62

28.5

1.74

2.54

0.80

0.10

−0.15

1.96

1.95

0.63

32.1

1.53

2.39

0.86

0.18

−0.24

p < 0.01

p = 0.55

p < 0.01

p = 0.34

p = 0.47

p = 0.64

SD, standard deviation; CV, coefﬁcient of variation; Q1, quartile 1 (25th percentile); Q3, quartile 3 (75th percentile); IQR, interquartile range; 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. Differences between urban and forest

environments were tested by a permutation test.

FIGURE 2 | Histograms of difference in heart rate variability indicators between urban and forest environments. Left and right panels demonstrate histograms for the

difference in lnHF and ln(LF/HF), respectively. As for the parasympathetic indicator (lnHF), the percentage of positive responders (presenting an increase in forest

environment) was ∼65%. Regarding the sympathetic indicator [ln(LF/HF)], the percentage of positive responders (presenting a decrease in forest environment) was

∼67%.

A chi-square test revealed that this diﬀerence in ln(LF/HF) was

not statistically signiﬁcant (p = 0.30).

DISCUSSION

Analysis of Distribution Characteristics

One of this study’s feature is the inclusion of an analysis with

special reference to the distribution characteristics of individual

variations in the HRV response. Skewness and kurtosis of HRV

indices did not change in either lnHF or ln(LF/HF), although

signiﬁcant changes in the mean values were observed between

urban and forest environments. In other words, walking in a

forest environment shifted the distribution curve higher (lnHF)

or lower [ln(LF/HF)] while maintaining its shape. This was

similar to the results in HRV during the viewing of urban and

forest landscapes in a previously reported study (17).

Not all physiological indicators, however, maintain the shape

of their distribution curve in response to natural environments.

Salivary cortisol concentration indicated a signiﬁcant decrease in

forest environments compared with that in urban environments,

accompanying a more skewed and kurtotic distribution (10). This

modiﬁcation of the distribution curve might be attributed to a

ﬂoor eﬀect (28, 29). Therefore, an unchanged distribution curve

is a speciﬁc response in log-transformed HRV indicators.

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Kobayashi et al.

Forest Walking Affects Autonomic Functions

TABLE 4 | Number of participants who indicated positive / negative response of

HRV indices in forest environment.

lnHF

ln(LF/HF)

Positive

response

Negative

response

Positive

response

Negative

response

Walking (n = 485)

Viewing* (n = 625)

316

(65.2%)

495

(79.2%)

169

(34.8%)

130

(20.8%)

325

(67.0%)

400

(64.0%)

160

(33.0%)

225

(36.0%)

Chi-squared

27.4 (p < 0.01)

1.0 (p = 0.30)

*Results on HRV during viewing urban or forest landscapes were presented in our previous

report (17).

Effects of Natural Environment on HRV

During walking in forest environments, larger lnHF and smaller

ln(LF/HF) were observed compared with those upon walking in

urban environments. As the lnHF and ln(LF/HF) are indicators

of parasympathetic and sympathetic nervous activity, the present

results implied that the autonomic relaxation occurred during

walking in forest environments. The results are consistent

to those in our previous study (17). Therefore, walking in

forest environments and viewing forest landscapes demonstrated

qualitatively similar eﬀects on autonomic functions.

Controversy, quantitative comparisons between the present

and previous results revealed a diﬀerent tendency in the

autonomic response to walking and viewing. During walking

in forest environments, 65.2% participants exhibited a positive

response in the parasympathetic indicator (lnHF), which was

signiﬁcantly lower than the percentage of positive responders

during viewing of forest landscape (79.2%). Contrary, for the

sympathetic indicator, the percentage of positive responders

during walking (67.0%) was almost identical to that during

viewing (64.0%). Therefore, the eﬀect of a forest environment

on parasympathetic nervous activity was more apparent during

viewing than walking, whereas sympathetic activity exhibited

almost the same responses to viewing and walking regarding the

percentage of positive responders.

Positive and Negative Effects of a Natural

Environment

In 1984, the distinguished biologist Edward O. Wilson proposed

the biophilia hypothesis (30). Biophilia is deﬁned as the “innate

tendency to focus on life and life-like processes” (31). For millions

of years, our 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.

Alternatively, it is known that certain people show a strong

dislike for natural settings. This tendency is called biophobia

(32). Biophobia includes certain speciﬁc phobias, such as

arachnophobia (irrational fear of spiders) or entomophobia

(fear of insects). There is also a term referring to the fear

of forests (hylophobia/xylophobia) (33). Biophobia is also an

adaptive psychological trait because of inherent dangers in the

natural environment (e.g., predators and poisonous organisms).

Therefore, the eﬀect of the natural environment on humans is

two-sided.

From the perspective of evolutionary psychology, a model

for the eﬀects of the natural environment on humans has been

proposed, which includes three factors: drive, contentment, and

threat (34, 35). Drive includes emotions such as joy, approach,

appetite, stimulation, and positiveness. As an endocrine response,

it is related to dopamine secretion. In contrast, contentment

is concerned with emotions such as calmness, relaxation, and

safety and is related to the oxytocin and opiate systems. In terms

of autonomic regulation, drive and contentment are associated

with sympathetic and parasympathetic activities, respectively

(35). A relaxation in autonomic nervous activity [increase in

lnHF and decrease in ln(LF/HF)] was observed in the forest

environment during both walking and viewing; therefore, it

can be considered that exposure to a forest environment

mainly confers contentment rather than drive. Furthermore, a

comparison between present and our previous results suggested

that viewing a forest landscape could provide more contentment

than walking in a forest environment.

A major limitation of this study is that it included

only Japanese young male subjects. The tendency for

biophilia/biophobia may be aﬀected by diﬀerence in age,

gender, and ethnicity of participants. Eﬀects of demographic

and geographic factors on physiological responses to

natural environments should be investigated in a future

study.

CONCLUSION

The autonomic relaxation (increases in parasympathetic

indicator and/or decreases in sympathetic indicator) in forest

environments has been demonstrated by HRV analysis in

previous studies. This result was also conﬁrmed in this study.

However, a comparison between the present and our previous

study (17) suggested that the response of HRV diﬀer between

viewing and walking.

The eﬀect of forest environments consists of several factors,

including negative emotions. It is reasonable that a certain

percentage of a population exhibits a negative response to forest

environments. Therefore, population-based analysis is required

in which the existence of negative responders is taken into

consideration.

AUTHOR CONTRIBUTIONS

HK contributed to statistical analysis, interpretation of the

results, and manuscript preparation. CS and HI were involved

with data acquisition and initial analysis of the results. B-JP, JL,

and TK participated in data acquisition and study design. YM had

an important role in the research, particularly in experimental

design, data acquisition, and manuscript preparation. All authors

contributed to the preparation of the manuscript and are

responsible for the ﬁnal editing and approval.

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October 2018 | Volume 6 | Article 278

Kobayashi et al.

Forest Walking Affects Autonomic Functions

FUNDING

ACKNOWLEDGMENTS

This study was partially supported by a JSPS KAKENHI grant,

number JP16107007 and a research project by the Vehicle Racing

Commemorative Foundation.

The authors thank Takeshi Morikawa of the Forestry and

Forest Products Research Institute and Yuko Tsunetsugu of the

University of Tokyo for their assistance in the experiments.

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Conﬂict of Interest Statement: The authors declare that the research was

conducted in the absence of any commercial or ﬁnancial relationships that could

be construed as a potential conﬂict of interest.

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Frontiers in Public Health | www.frontiersin.org

October 2018 | Volume 6 | Article 278