relationship between built environment and walking

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THE RELATIONSHIP BETWEEN BUILT ENVIRONMENT AND WALKING

ABSTRACT

The present study aimed to explore the possible relationship between the built environment

and walking behaviour among Malaysian residents. The objectives outlined are; i) to

determine the level of neighbourhood walkability in Johor Bahru as perceived by the

residents; ii) to gauge the residents¶ accumulated walking minutes per week for non-work

travel; and iii) to describe the relationship between the built environment attributes and

walking behaviour of the residents. Data were collected at a randomly chosen neighbourhood

area; Taman Pelangi, which is located at the heart of Johor Bahru City Centre; whereby 107

randomly selected samples (male = 64%, female = 36%) ranging from age 25 to 65 years old

responded on self-administered questionnaire surveys on built environment and walking.

From the findings, it is ascertained that only two out of five built environment attributes show

that the study area has high walkability characteristic including high mix of land-use diversity

and low traffic hazards. The remaining three attributes including the low access to services

and facilities; high safety fears; and high crime rate in the study area indicated quite the

opposite. Regarding the second objective, it is found that most samples (38%) walked 10 to

19 minutes per week for non-work travel. The measure of association (Gamma) was utilized

to achieve the third objective, and it is established that the three attributes which were

statistically proven to have influence on walking includes land-use mix diversity ( P = 0.010),

traffic hazard ( P = 0.016) and crime ( P = 0.066), while the remaining two attributes including

land-use mix access ( P = 0.137) and safety ( P = 0.351), are deemed as having no influence on

walking. Overall, although the study area was perceived as having low mix of land-use access

and triggered high safety fears among residents, most still reported to have walked 10 to 19

minutes per week for non-work travel. This is opposing the previous studies.

KEYWORDS: Built environment, walking behaviour, neighbourhood area and measure of

association.

1.0 INTRODUCTION

The Department of Statistics Malaysia and

Malaysia¶s Ministry of Works haverevealed that there is an astonishing

increase of private vehicle ownership from

9.6 persons per vehicle in 1974 to 1.7

persons per vehicle in 2005. The same

source also revealed that the total numbers

of registered vehicles increased from

1,090,279 in year 1974 to 15,026,660

vehicles in 2005. As depicted in Figure 1,

the numbers of motorcar increasesignificantly every year. The annual

growth of motorcars from year 1991 to

2002 is about 9.53%, while for

motorization level is 6.78%. Compared to

the population annual growth rate (2.57%),

the increase in motorcar ownership is

relatively higher (almost 10% per year).



Figure 1: Motorization rate in Malaysia f rom

1991 to 2002

Many factors contribute to the

growth in the number of vehicles in

Malaysia, including increased population

size, disposable incomes, fuel subsidies,

and decentralization (Izatun Shari, 2009).

Moreover, the author continues to state

that the Malaysian government which

targeted the motor vehicle industry as a

key economic growth sector has further

encouraged the motorization rate.

This is particularly true in

Malaysia, as increasing disposable income

has made private motor vehicles more

affordable, leading to increased demand(Pucher et al ., 2005) hence, creating a

system that is moving away from

achieving pedestrian-friendly environment.

Besides, the planning and provision of

transportation infrastructure for urban

travel in Malaysia has been largely

oriented towards the needs of private car

users, which consequently, shaping a breed

of generation which dislikes walking.

To counter this problem of lowwalking activity among Malaysians, the

present study intend to find out which

factors would or would not promote

walking among Malaysians, taking a

neighborhood in the area of Johor Bahru as

the study boundary. Hence, this study

serves as the first step to understanding the

perception of the residence and how does

this perception influence their walking

behavior as a whole.

2.0 THEORITICAL FRAMEWORK

According to several previous studies on

human behavior, it can be concluded that

the behavior of a person is largely

influenced by logic and external factors;

one of which is a person¶s immediate

environment. For example, Borst et al.

(2009) has presented a model describing

the influence of environmental street

characteristics on the walking route choice

of elderly people.

Other examples including the

Behavioural Model of Environment

(BME) proposed by Moudon et al. (2003);

the Behavioural Framework studied by

Cao et al. (2009); Travel-To-School Mode

Choice Modelling studied by Muller et al.

(2008) and Parks¶ et al. (2006) Land-use

Transportation and Air Quality

(LUTRAQ) survey. All these models have

been tested empirically and justified therelationship between behaviour and the

environment in which a person lives in.

Also, it signified that the external

stimulus has influence on one¶s decision

making. Hence, this theory; which

supports that external factor has its

influence on a person¶s behaviour, frames

the fundamental idea of the present study

and become the foundation of the research.

3.0 LITERATURE REVIEW

There are a growing number of studies

establishing the relationship between built

environment and walking. Most were done

through collecting the perceptions of the



public on the walkability of their

neighbourhood area and the reports of

their walking behaviour, which is

considered as a subjective measure (Lin et

al., 2010). These studies include a fairly

large sample which was selected from avariety of neighbourhood with different

characteristics. This is to further increase

the reliability of evidence which shows the

relationship between environmental

features and walking.

Most of the time, a person will

make a decision whether to walk or not to

walk to a destination based on his or hers

external environment. Hence, their

perception towards the environment is

crucial in determining their walking

behaviour. There are a few validated

studies which successfully outlined the

influence of the residents¶ perceptions

towards their walking behaviour. Below is

a discussion on the perception of residents

towards the physical attributes which

encourages and discourages walking

among residents of a neighbourhood.

3.1 The Perception of Physical

Attributes that Encouraged

Walking

There were six previous studies which

verified that respondents report a higher

level of walking behaviour when they

perceive that the sidewalks are of high

quality and highly accessible (Addy et al.,

2004; Brownson et al., 2000; Chad et al.,

2005; De Bourdeaudhuij et al., 2003;

Duncan et al., 2005; and King et al.,2003).The findings are further supported by

Booth¶s et al. (2000) and Humpel¶s et al.

(2004) studies, whereby both established

that respondents are more likely to walk

when their neighbourhood area provides

good access to various desired

destinations.

The desired destinations include

shopping areas (Addy et al., 2004; De

Bourdeaudhuij et al., 2003; Duncan et al.,

2005; King et al., 2003; Van Lenthe et al.,

2005), recreation facilities (Chad et al.,

2005), parks and open spaces (Foster et al., 2004; King et al., 2003; Li et al.,

2005), as well as public transportation

stops (De Bourdeaudhuij et al., 2003).

Borst et al. (2009) justified that higher

diversity of landuse mix, results in higher

non-motorized movement, especially by

foot.

Another aspect which inspires

higher level of walking activity is the

aesthetics of a pathway. This is supported

by studies done by Brownson et al. (2004),

Humpel et al. (2004) and Troped et al.

(2003). Cerin et al. (2007) has presented

the results for the Hong Kong sample

which shows that the residents which has

reported higher walking activity would

also report higher residential density, land-

use mix diversity, access to services, street

connectivity, infrastructure and safety for

walking, and more parking difficulties, but

fewer hilly streets, cul-de-sacs, physical

barriers, and traffic hazards. Based on the

study done by Parks et al. (2006), it

supports that higher density results in

higher walking activity.

3.2 The Perception of Physical

Attributes that Discouraged

Walking

There are some studies which suggest a

few aspects resulted in refusal to walk.Booth et al. (2000) and Foster et al. (2004)

found out that safety fears emerged as the

ultimate barrier to walking. Loukaitou-

Sideris (2006) and Loukaitou-Sideris et al.

(2002) addressed the way the

environmental and social features trigger

the fear of crime among residents, which



and Indian (14%). Of the original sample

of 107 respondents, all questionnaires

were used.

4 .3 Procedures

The Universiti Teknologi Malaysia (UTM)Skudai approved this study. After securing

other approvals from the Taman Pelangi

Security Guards, the inhabitants were

approached and asked to participate in this

study. The randomly selected samples then

completed the Built Environment and

Walking Survey questionnaire, which took

approximately 20 minutes each. To ensure

quality control for data entry, data were

100% verified through double checking

the entered data against the raw data.

4 .4 Measures

The 48-item Built Environment and

Walking Questionnaire contained

information from three domains:

demographics, built environment attributes

and walking report. The five built

environment attributes including the land-

use mix diversity, land-use mix access,

safety, crime and traffic hazard was taken

from previously published research (the

NEWS Questionnaire Survey) which has

strong reliability and validity. Besides that,

the walking report was adapted from

previous research by Cerin et al., 2006.

Other items were developed for use in this

study. The description of items relevant to

this study is provided below.

4.4.1 DemographicAge, gender, and race were included as

demographic variables in the study and the

questions were stated straight forwardly.

The samples were asked to write down

their age and gender on the space

provided, while race was assessed through

the question of µWhat is your race?¶ and

the answering categories include µMalay¶,

µChinese¶, µIndian¶ and µOthers¶.

4.4.2 Built Environment

The NEWS Questionnaire Survey is a 68-

item instrument which measures the perceived attributes of local environment

and is hypothesized to be used for

assessing physical activity; especially

walking. The subscales were perceived to

be related to walking and other physical

activities that are discussed in urban

planning literatures (Frank et al., 2003).

The questionnaire assesses the

characteristics of residential density; land

use mix diversity; land use mix access;

street connectivity; walking facilities;

aesthetics; pedestrian traffic safety and

crime safety.

All of these subscales, except for

the residential density item and the land

use mix-diversity item, were measured by

a 4-point Likert type scale which ranges

from 1 (strongly disagree) to 4 (strongly

agree). The residential density item

questions about the frequency of various

types of residences available within the

perceived neighbourhood.

The possible answer ranges from

single-family detached homes to 13-storey

or higher apartments and condominiums. It

is measured by a 5-point Likert type scale

(1 = none; to 5 = all). On the other hand,

the land use mix-diversity item was

assessed by the walking proximity from

home to various types of stores and

facilities, with responses ranged from 5 (1to 5 minutes walking distance) to 1 (> 30

minutes of walking distance).

In the present study, only five out

of eight of the attributes were adapted due

to time and manpower constraint. The five

attributes were land use mix diversity; land



use mix access; pedestrian traffic safety

and crime safety.

In order to assess the land-use mix

diversity of the study area, all of the

respondents were asked to select the

perceived minutes of walking from their houses to the given services and facilities.

There are a total of 23 types of services

and facilities including supermarket,

hardware store, vegetable market and

library. The minutes of walking was

categorized into five choices ranging from

1 (>31 minutes) to 5 (<5 minutes).

Land-use mix access was assessed

through asking the respondents to rate four

questions in this part, for example, µI can

do most of my shopping at local stores¶.

The rating ranged from 1 (Strongly

Disagree) to 4 (Agree). The residents¶

perceived safety level of their

neighborhood was assessed through

questions including µThe sidewalks in my

neighborhood are well maintained¶ and

µMy neighborhood is well lit at night¶.

Consequently, the ten questions regarding

safety level were ranked by the

respondents and the choices ranged from 1

(Strongly Disagree) to 4 (Agree).

On the other hand, six questions

were asked in order to determine the

residents¶ perceived traffic hazard level of

their immediate neighborhood areas. The

questions asked including µThe speed of

traffic on the street I live in is usually

slow¶ and µWhen walking in my

neighborhood there are a lot of exhaust

fumes¶ were ranked with four choices (1for µStrongly Disagree¶ to 4 for µAgree¶).

Lastly, all respondents answered this

section which consists of only four

questions and it aims to find out the

perceived crime level of the neighborhood

area. For example, they were asked to rank

hypothetical situations such as µThere is a

high crime rate in my neighborhood¶ and

µThe high crime rate in my neighborhood

makes it unsafe to go for a walk at night¶

through a scale ranging from 1 (Strongly

Disagree) to 4 (Agree).

4.4.3 Walking Behaviour

The walking behavior of the respondents

was gained through asking them to report

their accumulated minutes of walking for

non-work travel per week. The choices

ranged from 1 (less than 4 minutes) to 5

(more than 30 minutes).

4 .5 Data Analysis

Gamma test was used to measure the

strength of relationship between the five

built environment attributes and the

residents¶ walking behaviour.

5.0 RESULTS

The null hypothesis of the research is that

none of the built environment attributes

has influence towards the residents¶

walking behaviour. Hence, P -values that

are less than = 0.10 means that it rejects

the null hypothesis, and vice versa.

Table 3: T e results of t e measure of

association between t e built environment

attributes and t e respondents¶ walking

behaviour using the Gamma test

Built

Environment

Attributes

P -

value

Verdict

(10%

signif icance

level)

R eject /

Accept

Null

Hypothesis

Diversity 0.010 P <0.10 RejectAccess 0.137 P >0.10 Accept

Saf ety 0.351 P >0.10 Accept

Traff ic 0.016 P <0.10 Reject

Crime 0.066 P <0.10 Reject

The result shows that there are

three attributes which significantly



influences the residents¶ walking

behaviour and the other two does not have

influence towards the residents¶ walking

behaviour. According to Table 3, the

attributes which have P -values less than

= 0.10, including land-use mix diversity ( P = 0.010), traffic hazard ( P = 0.016) and

crime ( P = 0.066), are statically proven as

having influence on walking behaviour.

On the other hand, the attributes which

have P -values more than = 0.10,

including land-use mix access ( P = 0.137)

and also safety ( P = 0.351), are deemed as

having no significant relationship with

walking behaviour.

6.0 DISCUSSION

This study was prompted by the fact that

the Malaysian lifestyle is in a wrench;

including the ever increasing private

vehicle ownership per person, the

provision of low quality walking facilities

and the negligence of pedestrianism in the

policy making process. All of which has

resulted in disinterest of its population to

walk, and thus, bringing an abundance of

negative externalities, for example,

increase in pollution emission and the loss

of valuable time on road due to severe

traffic congestion, just to name a few.

To counter this problem of low

walking activity among Malaysians, the

present study intend to find out which

factors would or would not promote

walking among Malaysians, taking aneighborhood in the area of Johor Bahru as

the study boundary. Hence, this study

serves as the first step to understanding the

perception of the residence and how does

this perception influence their walking

behavior as a whole.

The first objective of the research

is to determine the level of neighborhood

walkability in Johor Bahru as perceived by

the residents in the study area. This

objective aimed to discover the

neighbourhood walkability through the perception of the residents by answering

the questions posed during the

questionnaire survey. The answers

gathered would be compared against the

previous studies of related topics and the

determination of the neighbourhood

walkability would be presented

accordingly.

Studies have showed that high mix

of land-use diversity (Cerin et al., 2007;

Parks et al., 2006; Crane, 1996; Ewing,

1999); high accessibility to the services

and facilities (Crane, 1996; Ewing, 1999;

Cerin et al., 2007; Borst et al., 2009; Chad

et al., 2005; Parks et al., 2006; Addy et al.,


Duncan et al., 2005; King et al., 2003;

Van Lenthe et al., 2005; Foster et al.,

2004; Li et al., 2005); low crime level

(refer Loukaitou-Sideris, 2006; Loukaitou-

Sideris et al., 2002); low safety fears

(Crane, 1996; Ewing, 1999; Addy et al.,

2004; Brownson et al., 2000; Chad et al.,


Duncan et al., 2005; and King et al.,2003;

Booth et al., 2000; Humpel et al., 2004)

and low traffic hazards (Booth et al.,

2000; Foster et al., 2004; Parsons et al .,

1993; Sarkar, 1993; Pikora et al ., 2002;

Ewing, 1999) are the signs of a highly

walkable neighbourhood area.In order to gauge the data from the

residents, the NEWS questionnaire survey

was employed, whereby they would have

to answer five domains including land-use

mix diversity, land-use mix access, crime,

traffic hazards, and safety fears. The result

of the analysis is that, the study area has a



high mix of land-use diversity; low access

to services and facilities; high safety fears;

low traffic hazards and high crime rate in

the study area as perceived by the

residents. This means that only two out of

five attributes mentioned above is agreeingthat the study area is of high walkability.

The second objective was to gauge

the residents¶ walking minutes per week

for non-work purposes. This is also

achieved through the questionnaire survey

session held on field. The residents were

given five ranges of choices; 1 (less than 4

minutes) to 5 (more than 30 minutes). The

result shows that a total of 38% of

respondents managed to walk 10 to 19

minutes per week, while 19% and 17% of

the respondents have walked 20 to 29

minutes per week and 5 to 9 minutes per

week respectively. Another 17% of them

have walked less than 4 minutes per week.

Lastly, only 9% of the residents have been

able to walk more than 30 minutes per

week for non-work travel.

The third objective of the study

aimed to describe the relationship between

the built environment attributes and the

residents¶ walking behaviour. In order to

achieve this objective, the measure of

association, which is the Gamma test, is

employed. Each and every one of the built

environment attributes were tested against

the residents¶ walking behaviour.

Therefore, the results were used to reject

or accept the null hypothesis outlined

earlier.

The present study found out thatare three attributes which significantly

influences the residents¶ walking

behaviour and the remaining two attributes

does not have influence towards the

residents¶ walking behaviour. The

attributes which have rejected the null

hypothesis and has P -values less than =

0.10, including land-use mix diversity ( =

0.010), traffic hazard ( = 0.016) and

crime ( = 0.066), are statically proven as

having influence on walking behaviour.

On the other hand, the attributes which

have accepted the null hypothesis and have P -values more than = 0.10, including

land-use mix access ( = 0.137) and also

safety ( = 0.351), are deemed as having

no significant relationship with walking

behaviour.

From the results shown, it is clear

that two of the attributes, including the

land-use mix access and safety fear have

differed from that of the previous research.

For the former attribute, although the

majority of the respondents have agreed

that they cannot do most of their shopping

at local stores, the self-reported minutes of

walking for non-work travel shows quite

the opposite, whereby most of them still

walks between 10 to 19 minutes per week.

This result is opposing the previous

research done by Booth et al. (2000),

Humpel et al. (2004), Addy et al. (2004),

Brownson et al. (2000), Chad et al. (2005),

De Bourdeaudhuij et al. (2003), Duncan et

al. (2005) and King et al. (2003), whereby

they all agreed that if the residents cannot

do most of their shopping at the local

stores, it would discourage walking.

As for the latter attribute, although

half of the respondents perceived their

neighbourhood to be unsafe, yet the

minutes of walking per week for non-work

purpose is still considerably high. The

result is opposing to previous researchfindings by Booth et al. (2000) and Foster

et al. (2004), whereby they certified that

safety fears is the ultimate barrier to

walking. Based on the discussion made, it

can be concluded that the research

objectives and research questions has been

achieved as well as answered accordingly.



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