RESEARCH ARTICLE

Environment and air pollution: health services bequeathto grotesque menace

Muhammad Imran Qureshi & Amran Md. Rasli &Usama Awan & Jian Ma & Ghulam Ali & Faridullah &

Arif Alam & Faiza Sajjad & Khalid Zaman

Received: 5 July 2014 /Accepted: 8 September 2014# Springer-Verlag Berlin Heidelberg 2014

Abstract The objective of the study is to establish the linkbetween air pollution, fossil fuel energy consumption, indus-trialization, alternative and nuclear energy, combustible re-newable and wastes, urbanization, and resulting impact onhealth services in Malaysia. The study employed two-stageleast square regression technique on the time series data from1975 to 2012 to possibly minimize the problem ofendogeniety in the health services model. The results in gen-eral show that air pollution and environmental indicators actas a strong contributor to influence Malaysian health services.Urbanization and nuclear energy consumption both signifi-cantly increases the life expectancy inMalaysia, while fertilityrate decreases along with the increasing urbanization in acountry. Fossil fuel energy consumption and industrializationboth have an indirect relationship with the infant mortalityrate, whereas, carbon dioxide emissions have a direct relation-ship with the sanitation facility in a country. The resultsconclude that balancing the air pollution, environment, and

health services needs strong policy vistas on the end of thegovernment officials.

Keywords Environment . Air pollution . Health services .

Two-stage least square . Malaysia

Introduction

The economic viewpoint regarding health benefit suggeststhat investment for the welfare of the people transform intothe overall economic growth. Environmental, genetic, andbehavioral practices are the most important aspects causativeto the raise in environmental and public health problems andchallenges. Contact with air pollution, inadequate water re-sources, soil, and physiological hazards create high morbidity,disability, and mortality. In spite of the complex health tech-nology and development technologies, the world still faces

Responsible editor: Philippe Garrigues

M. I. QureshiFaculty of Management, Universiti Teknologi Malaysia, UTMSkudai, 81310 Johor, Malaysia

A. M. RasliCommercialization and Technology Management Group Faculty ofManagement, Universiti Teknologi Malaysia, UTM Skudai,81310 Johor, Malaysiae-mail: m-amran@utm.my

U. AwanDepartment of Management Sciences, COMSATS Institute ofInformation Technology, Vehari, Pakistane-mail: usama.awan@Ciitvehari.edu.pk

J. MaDepartment of East Asian Studies, Faculty of Arts and SocialScience, University of Malaya, 50603 Kuala Lumpur, Malaysia

G. AliDepartment of Commerce, University of Sargodha, Sargodha,Pakistan

.FaridullahDepartment of Environmental Sciences, COMSATS Institute ofInformation Technology, Abbottabad, Pakistan

A. AlamDepartment of Development Studies, COMSATS Institute ofInformation Technology, Abbottabad, Pakistan

F. Sajjad :K. Zaman (*)Department of Management Sciences, COMSATS Institute ofInformation Technology, Abbottabad, Pakistane-mail: khalidzaman@ciit.net.pk

Faridullah

Environ Sci Pollut ResDOI 10.1007/s11356-014-3584-2

child malnutrition, injury, and mortality rates (Ministry ofHealth 2011).

For this important notion, Malaysia, like other Asian coun-tries allocates a sizeable amount of budget for the healthsector. Malaysia is opportune to have wide-ranging healthcareservices. The government of Malaysia is dedicated to accesshigh-quality healthcare, through a network of nationwideclinics and hospitals. However, there are still some tribulationsrelated with the environmental factors and climatic changethat needs to be solved (Allianz Worldwide 2013). TheMalaysian economy is improving the economic situationwhich was trapped as a middle income country over a longperiod, although issues and challenges faced during the TenthMalaysia Plan (10MP) is quite similar to those in the NinthMalaysia Plan (9MP), i.e., the issues on globalization and therising trend of private health care spending creates a greatchallenge and distress on maintaining the power of the currenthealthcare system (Ministry of Health 2011). According toBrunekreef and Holgate (2002, p.1233),

“The health effects of air pollution have been subject tointense study in recent years. Exposure to pollutantssuch as airborne participate matter and ozone has beenassociated with increases in mortality and hospital ad-missions due to respiratory and cardiovascular disease”.

De Sario et al. (2013) conclude that climatic factors affectson the patterns of air pollution in the urbanized areas of theworld, associated with the significant effect on respiratoryhealth both independently and synergistically with weatherconditions. Balbus et al. (2013) examined the impact of globalclimate change (GCC) on the human health through the path-way from a chemical source in the environment. The resultsshow that GCC enhanced the level of contact of many envi-ronmental pollutants due to direct and indirect effects on theusage patterns, transport, and fate of chemicals. Rao et al.(2013) presented the set of policy scenarios on air pollution,climate change, energy access, and health impacts for 2030.The results highlighted the urgency of enforcing currentworldwide air quality legislation in addressing the impactsof outdoor air pollution. Akhmat et al. (2014a) explored thelong-run relationship between climatic factors, air pollution,and energy sources in the European Union-15 (EU-15) coun-tries, new EU member states, G-7 countries, and other coun-tries, during the period of 1975–2012. The policy directivethat reduces the greenhouse gases emissions concurrentlyalters emissions of conventional pollutants which have injuri-ous effects on human health and the environment. In anotherstudy, Akhmat et al. (2014b) examined the carbon dioxideemissions, greenhouse gas emissions, and low birthweight inPakistan, during the period of 1975–2012. The results showthat both air pollution and greenhouse gas emissions consid-erably affect the low birthweight in Pakistan, as air pollution

exhibit strong relationship with low birthweight, while there isone-to-one corresponding relationship between greenhousegas emissions and low birthweight in a country. Yasser(2014) examined the possibility of home power generationtechnologies utilizing renewable energies in rural Australia.The results show that home-based power generation is feasibleand an applicable alternative technique by using renewabletechnologies in rural Australia. According to Steinle et al.(2013, p. 184),

“Quantifying human exposure to air pollutants is achallenging task. Ambient concentrations of air pollut-ants at potentially harmful levels are ubiquitous in urbanareas and subject to high spatial and temporalvariability”.

D’Amato et al. (2014) concluded that the recent changes inthe regional temperature affected the varied set of physical andbiological systems across the globe. Allergens patterns amongone of them are changing drastically in response to climatechange. Rafindadi et al. (2014) examined the long-run rela-tionship between carbon dioxide emissions, fossil fuel energyconsumption, and water resources in the panel of selectedAsia-Pacific countries, during the period of 1975–2012. Theresults show that there is a strong nexus between carbondioxide emissions, fossil fuel energy consumption, andwater resources in the region; however, among other factors,fossil fuel has a strong influence on the changes in the airpollution. Sajjad et al. (2014) examined the long-run relation-ship between climatic factors, air pollution, and tourism de-velopment indicators in the aggregate data of South Asia, theMiddle East and North Africa, Sub-Saharan Africa, and EastAsia and the Pacific regions, covering the period of 1975–2012. The results reveal that both the climatic factors and airpollution have a negative impact on tourism indicators in theform of deforestation and natural resource depletion. Shahbazet al. (2014) investigates the long-run relationship betweenenergy consumption, economic growth, carbon dioxide emis-sions, and urbanization in the United Arab Emirates (UAE),covering the quarter frequency data over the period ofQ11975–Q42011. The results confirmed the existence of aninverted U-shaped relationship between economic growth andcarbon dioxide emissions in a country. The causality analysisconfirmed the bidirectional causality between carbon dioxideemissions and electricity consumption. Shabbir et al. (2014)examined the relationship between energy consumption, eco-nomic growth, and carbon dioxide emissions by using thestructural vector autoregressive technique in Pakistan. Theresults show that energy consumption both in the form ofrenewable and non-renewable energy consumption increaseseconomic growth, while carbon dioxide emissions decreaseeconomic activity in a country. Shafiq and Zaman (2014)examined the relationship between economic freedom

Environ Sci Pollut Res

indicators and energy consumption in Pakistan, over the peri-od of 1995–2013. The results reveal that economic freedomindicators increases energy consumption in Pakistan; howev-er, Granger causality test in most of the cases supportedneutrality hypothesis i.e., both economic freedom and eco-nomic growth does not Granger cause each other, except coalconsumption which partially supported the unidirectionalcausal relationship with the economic freedom indicators butnot vice versa. According to Mokhtar and Murad (2010, p.24),

“Environmental health problems in Malaysia are mostlyattributed to atmospheric pollution, water pollution, cli-mate change, ozone depletion, and solid waste manage-ment, as well as toxic, chemical, and hazardous wastemanagement. The Ministry of Health, Malaysia, hasbeen vigorously pursuing the environmental healthagenda by collaborating with other agencies at district,state, national, and international levels”.

Table 1 shows the current studies on air pollution, environ-mental hazards, and resulting impact on Malaysian healthservices.

The above studies found evidence of long-run relationshipbetween air pollution and health services across the globe. Inthe subsequent section, the study examines the relationshipbetween air pollution, environmental factors, and resultingimpact on Malaysian health services. The study is dividedinto the following sections: after introduction, data source, andmethodological framework presented in “Data source andmethodological framework”. Results are discussed in“Results”, while the final section concludes the study.

Data source and methodological framework

The data set for the selected variables i.e., carbon dioxideemissions, fossil fuel energy consumption, industrialization,alternative and nuclear energy,1 combustible renewable andwastes, urbanization, total fertility rate, total life expectancy atbirth, infant mortality rate, improved sanitation facilities, andimproved water sources were taken fromWorld DevelopmentIndicators published by the World Bank (2013).

The study employed two-stage least square regressiontechnique to possibly encounter the problem of endogenietyin the model. For this purpose, the study brings first lag of theexplanatory variables as an instrumental list. At first, the studyused different simultaneous equations model for five health-related factors in the context of Malaysia and explained withthe number of environmental and air pollutant factors in a

country. Model I to model V explained the impact of airpollutant and environmental indicators on health services inMalaysia i.e.,

Model I: total fertility rate, air pollution, and environmentalindicators

FERT ¼ β0 þ β1CO2þ β2FOSSILþ β3IND

þ β4NUCLEARþ β5RENWASTE

þ β6URBANþ μ

Model II: total life expectancy, air pollution and environ-mental indicators

LEXPECT ¼ β0 þ β1CO2þ β2FOSSILþ β3IND

þ β4NUCLEARþ β5RENWASTE

þ β6URBANþ μ

Model III: infant mortality rate, air pollution and envi-ronmental indicators

MORT ¼ β0 þ β1CO2þ β2FOSSILþ β3IND

þ β4NUCLEARþ β5RENWASTE

þ β6URBANþ μ

Model IV: improved sanitation facility, air pollution andenvironmental indicators

SANIT ¼ β0 þ β1CO2þ β2FOSSILþ β3IND

þ β4NUCLEARþ β5RENWASTE

þ β6URBANþ μ

Model V: improved water resources, air pollution andenvironmental indicators

WATER ¼ β0 þ β1CO2þ β2FOSSILþ β3IND

þ β4NUCLEARþ β5RENWASTE

þ β6URBANþ μ

Where, FERT represents fertility rate, total (births perwoman); LEXPECT represents life expectancy at birth, total(years); MORT represents mortality rate, infant (per 1,000 livebirths); SANIT represents improved sanitation facilities (% ofpopulation with access); WATER represents improved watersource (% of population with access); CO2 represents carbondioxide (CO2) emissions from manufacturing industries and

1 Clean energy is noncarbohydrate energy that does not produce carbondioxide when generated. It includes hydropower and nuclear, geothermal,and solar power, among others.

Environ Sci Pollut Res

Tab

le1

Airpollu

tion,environm

entalchallenges,and

health

services

inMalaysia

Study

Datasetand

timeperiod

Country

Methodology

Results

Loganathanetal.(2014)

1974–2010

Malaysia

Cointegratio

nandcausality

approach

Bidirectio

nalcausalitybetweencarbon

taxandCO2,

whileunidirectio

nalcausalityrunningfrom

econom

icgrow

thto

CO2,and

carbon

taxto

econom

icgrow

th

Othman

etal.(2014,a)

Daily

inpatientdatafrom

2005,2006,2008,

and2009

for14

haze-related

illnesses

werecollected

from

four

hospitals.

KualaLum

purandadjacent

areasin

thestateof

Selangor,M

alaysia

Survey

Asm

okehaze

incidencewas

linkedwith

anincrease

ininpatient

casesby

2.4per10,000

populatio

nseach

year.

Abidinetal.(2014)

Aschool-based

cross-sectionalstudy

of1,952schoolchild

renliv

ingin

urbanand

semi-ruralareas

Malaysia

Multip

lelogisticregression

Atotalo

f11.4,7.6,9.5,and

7.0%

schoolchild

renhad

asthma,currentw

heeze,drycoughatnight,and

wheezingdueto

rapidincreasesin

trafficvolumes.

Latifetal.(2014)

A15-yeardatasetfocusingon

tenmajor

air

pollu

tantsandfour

meteorological

variables

Jerantut-Pahang,Malaysia

Principalcom

ponent

regression

(PCR)andsensitivity

analysis

Sevenof

thepollu

tants(N

O,N

O2,NOx,O3,PM

10,

THC,and

CH4)

show

edapositiv

eupwardtrendover

the15-yearperiod.

Ma’poletal.(2014)

481studentsof

14year-old

Malaysian

school

child

ren

Terengganu,M

alaysia

Fractio

nalexhaled

nitrogen

oxide

(FeN

O)m

easurementonqualitativ

equestio

nnaire

The

incidenceof

doctor

diagnosedasthmawas

7%,

ofwhich

38%

ofstudentswith

know

nasthmawere

onmedication.

Othman

etal.(2014,b)

30yearsdataset.

Kajangmunicipality

inthe

stateof

Selangor,

Malaysia

Avertivecostmethod

The

presentv

alue

ofaggregatebenefitsatvarioussocial

discount

ratesranged

from

MYR301millionto

MYR

768million.

Lim

andLam

(2014)

To-datedatafrom

GreenTech

Malaysiaof

Clean

DevelopmentM

echanism

(CDM)projectsin

theenergy

sector

Malaysia

Review

The

numberof

registered

CDM

projectsin

theenergy

sector

isin

rising

trendandassistin

largeam

ount

ofem

ission

reductions

inMalaysiaparticularly

through

biom

assandbiogas

projects.

Ashnani

etal.(2014)

Malaysia’sstatus

quoin

energy

and

biodieselm

arket

Malaysia

Review

The

major

segm

entofrawmaterialfor

producingbiodiesel

ispalm

oilasthecountryisam

ongthemajor

producers

ofpalm

oilatinternatio

nallevel.

Environ Sci Pollut Res

construction (% of total fuel combustion); FOSSIL representsfossil fuel energy consumption (% of total); IND representsindustry, value added (current US$); NUCLEAR representsalternative and nuclear energy (% of total energy use);RENWASTE represents combustible renewables and waste(% of total energy); and URBAN represents urban population(% of total). These variables are selected because of their vitalimportance in the Malaysian region. Figure 1 shows the trendof the data at level.

Results

This section presents the descriptive statistics, correlationmatrix, and two-stage least square regression technique onthe three most contingent variables i.e., air pollution, environ-ment, and health services in Malaysia. The study brings anumber of variables for air pollution, environment, and healthservices in Malaysia at country level which includes carbondioxide emissions from manufacturing industries and con-struction, fossil fuel energy consumption as percentage of totalenergy consumption, combustible renewables and waste aspercentage of total energy, alternative and nuclear energy aspercentage of total energy use, urban population in percent-age, industry, value added in current US dollar, total fertilityrate—births per woman, total life expectancy at birth in years,infant mortality rate per 1,000 live births, improved sanitationfacilities as percentage of population with access, and im-proved water source (% of population with access). Table 2

shows the descriptive statistics of the variables for the readyreference.

Table 3 shows the correlation matrix between the healthservices, air pollution, and environmental indicators inMalaysian context. The results show that fertility rate has astrong and negative relationship with the fossil fuel energyconsumption, industry value added, and urbanization inMalaysia, while there is a positive association between fertil-ity rate, carbon dioxide emissions, nuclear energy consump-tion, and renewable wastes in a country. Secondly, life expec-tancy exhibit positive association with the fossil fuel energyconsumption, industry value added, and urbanization, whilethere is negative relationship with the carbon dioxide emis-sions, alternative and nuclear energy consumption and renew-able energy and waste. The third determinant of health ser-vices is the infant mortality rate which shows that there ispositive correlation between infant mortality, carbon dioxideemissions, and renewable energy and waste in Malaysia.However, there is some negative association between infantmortality rate, fossil fuel energy consumption, industry valueadded, and urbanization in a country. The fourth factor ofhealth services is the improved sanitation facility which tendsto exhibit the strong positive correlation with the fossil fuelenergy consumption, industry value added, and urbanization,while there is negative correlation with the carbon dioxideemissions, nuclear energy consumption, and renewable ener-gy and waste in Malaysia. Finally, improved water resourceshave positive correlation with the fossil fuel energy consump-tion, industrialization, and urbanization, whereas there is

15

20

25

30

35

40

5 10 15 20 25 30 35

CO2

Carbon dioixde emissions from

manufacturing industries and construction

(% of total fuel combustion)

75

80

85

90

95

5 10 15 20 25 30 35

FOSSIL

Fossil fuel energy consumption (% of total)

4

8

12

16

20

24

5 10 15 20 25 30 35

RENWASTE

Combustible renewables and waste

(% of total energy)

0.5

1.0

1.5

2.0

2.5

3.0

5 10 15 20 25 30 35

NUCLEAR

Alternative and nuclear energy (% of total energy use)

30

40

50

60

70

80

5 10 15 20 25 30 35

URBAN

Urban population (% of total)

0.0E+00

4.0E+10

8.0E+10

1.2E+11

1.6E+11

5 10 15 20 25 30 35

IND

Industry, value added (current US$)

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5 10 15 20 25 30 35

FERT

Fertility rate, total (births per woman)

66

68

70

72

74

76

5 10 15 20 25 30 35

LEXPECT

Life expectancy at birth, total (years)

5

10

15

20

25

30

35

5 10 15 20 25 30 35

MORT

Mortality rate, infant (per 1,000 live births)

76

80

84

88

92

96

5 10 15 20 25 30 35

SANIT

Improved sanitation facilities

(% of population with access)

80

85

90

95

100

5 10 15 20 25 30 35

WATER

Improved water source

(% of population with access)

Fig. 1 Data trend at level

Environ Sci Pollut Res

negative association with the carbon dioxide emissions, nu-clear energy consumption and renewable energy and waste inMalaysia. The overall results indicate the significance of thesevariables in the context of Malaysia.

Table 4 shows the results of two-stage least square regres-sion for the two most promising health factors, i.e., infantfertility rate and life expectancy in a country.

The results show that there is a significant and positiverelationship between alternative and nuclear energy and thetwo most promising health factors, i.e., fertility rate (births perwoman) and life expectancy at birth. The results are quitecontradictory with the previous schools of thoughts whichclaim that the consequences of nuclear energy affects thereproductive health cycle. The studies failed to substantiatethat the consequences of energy radiations decreases the birthrates or decreases the life expectancy at birth (Wurzbacheret al. 2009; Cuttler and Pollycove 2009). The present studyshows the dramatic increase in the fertility rate and life expec-tancy in Malaysia, where the fertility rate increases by 0.211percentage points when there is 1 % increase in the nuclearenergy consumption. Similarly, life expectancy increases by0.010 percentage point in terms of 1 % increase in the nuclearenergy consumption in Malaysia.

Urbanization is one of the major problems in the develop-ing countries with no exception for the Malaysian economy aswell. The results show that there is a significant and negativerelationship between urbanization and fertility rate in

Malaysia, as 1 % increase in the urbanization, fertility ratedecreases by 4.229 percentage points. The results supportedthe findings of theWhite et al. (2008, p. 803) which opine thatthe urbanization is associated with lower fertility in the devel-oping countries or at least, urban women exhibit fertility rateslower than the rural women. The results of the second modelassociated with the increasing life expectancy and urbaniza-tion in Malaysia, as life expectancy increases by 0.164 per-centage point when there is 1 % increase in the urbanization ina country. The results conclude that the urban populations, ingeneral, become healthier than their rural counterparts, asurban residents have a better access to health care and servicesthan do residents in many rural parts (Phillips 1993).

The statistical test for both the models suggests the good-ness of the fit of the model, as the R square is in the range of0.941 to 0.996. The F statistics shows the stability of themodel, as the probability value for both the models show the99 % significance interval. The remaining explanatory vari-ables, i.e., carbon dioxide emission, fossil fuel energy con-sumption, industry value added, and combustible renewablewaste, are insignificant to express the relationship with thefertility rate and life expectancy in the given models. Table 5shows the effect of air pollution and environmental factors oninfant mortality rate in Malaysia.

The results show that along with the increase in the fossilfuel energy consumption in Malaysia, the rate of infant mor-tality significantly decreases, as the coefficient value indicate

Table 3 Correlation matrix

FERT LEXPECT MORT SANIT WATER CO2 FOSSIL IND NUCLEAR RENWASTE URBAN

FERT 1

LEXPECT −0.940 1

MORT 0.855 −0.972 1

SANIT −0.967 0.984 −0.934 1

WATER −0.972 0.980 −0.925 0.997 1

CO2 0.925 −0.900 0.803 −0.901 −0.902 1

FOSSIL −0.893 0.973 −0.970 0.955 0.950 −0.826 1

IND −0.943 0.872 −0.747 0.890 0.894 −0.922 0.804 1

NUCLEAR 0.415 −0.230 0.080 −0.331 −0.355 0.339 −0.287 −0.442 1

RENWASTE 0.871 −0.973 0.985 −0.943 −0.935 0.815 −0.995 −0.780 0.192 1

URBAN −0.981 0.982 −0.916 0.993 0.994 −0.933 0.942 0.928 −0.355 −0.928 1

Table 2 Descriptive statistics

CO2 FERT FOSSIL IND LEXPECT MORT NUCLEAR RENWASTE SANIT URBAN WATER

Mean 29.05508 3.133605 88.82387 3.86E+10 71.21510 14.87105 1.242268 9.951908 87.77257 54.99671 91.57358

Maximum 37.17702 4.209000 94.70309 1.25E+11 74.84229 34.50000 2.659627 22.56580 95.67234 73.36200 99.81000

Minimum 16.72500 1.975000 76.25783 3.36E+09 66.40188 6.900000 0.703096 4.601000 78.00000 37.65200 82.00000

Std. dev. 5.333605 0.706965 5.296116 3.40E+10 2.489246 8.251058 0.516982 5.141777 6.032120 11.27853 6.190169

Observations 38 38 38 38 38 38 38 38 38 38 38

Environ Sci Pollut Res

the more elastic relationship between fossil fuel energy con-sumption and infant mortality rate in a country. The resultsargued that the fossil fuel energy consumption lead to betterknowledge among the public, especially pregnant womenregarding the harmful effects of air pollution and thus, reducetheir exposure to air pollution by engaging in averting behav-ior (Cesur et al 2013). Similarly, there is an indirect relation-ship between urbanization and infant mortality rate; it meansthat if there is 1 % increase in urbanization, the infant mortal-ity rate decreases by 6.219 percentage points. Bandyopadhyayand Green (2013) argued that the most observable way inwhich the mortality decline can add to urbanization is in thecourse of an increase in rural population and following pop-ulation growth above urban threshold levels. The results fur-ther substantiate that due to the rapid industrialization inMalaysia, the rate of infant mortality increases during thestudy time period. The results conclude that industrialization

improved wealth and higher living standards, but it alsoformed industrial towns and big cities which enclosed a sig-nificant underclass whose health was cooperated by the socialand biological pathologies that pulverized poverty andmuddy,overcrowded, and disease-infested urban slums in the country(Encyclopedia of Children and Childhood in History andSociety 2008). Table 6 shows the results of sanitation facilityassess with the percentage of population in accordance withthe air pollution and environmental pollution in Malaysia.

The results show that both the carbon dioxide emissionsand urbanization significantly affect the sanitation facilityavailable to the percentage of population in Malaysia.However, the magnitude of urbanization is largely affectedthan the magnitude of carbon dioxide emissions in a countryas if there is 1 % increase in carbon dioxide emissions andurbanization, sanitation facility is positively affected by0.037% and 0.327 percentage points, respectively. The resultssuggest that the performance of municipal governments andpublic utilities should be improved, as public-private partner-ships be supposed to provide water management and sanita-tion services in a country. The remaining variables insignifi-cantly explained the sanitation facility in Malaysia. Table 7shows the improved water source access with the percent ofpopulation in Malaysia.

The results show that both the industry value added andalternative nuclear energy consumption has a negative andsignificant relationship with the water sources in Malaysia asif there is 1 %increase in the industry value added and alter-native nuclear energy, water accessibility to the populationdecreases by 0.037 and 0.012%, respectively. However, due tothe rapid urbanization in a country, accessibility of waterresources has been improved which lead to a healthy

Table 5 Results of two-stage least square regression on infant mortalityrate

Dependent variable: LOG(MORT)

Method: two-stage least squares

Variable Coefficient Std. error t Statistic Prob.

C 64.316 26.134 2.461 0.019

LOG(CO2) −0.357 0.207 −1.721 0.095

LOG(FOSSIL) −8.725 3.948 −2.209 0.034

LOG(IND) 0.307 0.147 2.089 0.045

LOG(NUCLEAR) −0.030 0.052 −0.576 0.568

LOG(RENWASTE) −1.834 1.141 −1.607 0.118

LOG(URBAN) −6.219 1.743 −3.567 0.001

R squared 0.988 Mean dependent var 2.534

Adjusted R squared 0.986 S.D. dependent var 0.506

S.E. of regression 0.058 Sum squared resid 0.102

F statistic 450.5 Durbin-Watson stat 1.725

Prob(F statistic) 0.000 Second-stage SSR 0.038

Table 4 Results of two-stage least square regression in case of infantfertility rate and life expectancy

Model 1

Dependent variable: LOG(FERT)

Method: two-stage least squares

Variable Coefficient Std. error t Statistic Prob.

C 47.437 28.981 1.636 0.112

LOG(CO2) 0.144 0.230 0.627 0.535

LOG(FOSSIL) −5.408 4.378 −1.235 0.226

LOG(IND) −0.045 0.163 −0.280 0.780

LOG(NUCLEAR) 0.211 0.058 3.628 0.001

LOG(RENWASTE) −2.124 1.265 −1.678 0.103

LOG(URBAN) −4.229 1.933 −2.187 0.036

R squared 0.941 Mean dependent var 1.105

Adjusted R squared 0.929 S.D. dependent var 0.243

S.E. of regression 0.064 Sum squared resid 0.125

F statistic 82.543 Durbin-Watson stat 1.376

Prob(F statistic) 0.000 Second-stage SSR 0.059

Model 2

Dependent variable: LOG(LEXPECT)

Variable Coefficient Std. error t Statistic Prob.

C 2.785 1.001 2.780 0.009

LOG(CO2) 0.003 0.007 0.475 0.637

LOG(FOSSIL) 0.124 0.151 0.821 0.417

LOG(IND) 0.008 0.005 1.440 0.160

LOG(NUCLEAR) 0.010 0.002 5.011 0.000

LOG(RENWASTE) 0.025 0.043 0.584 0.563

LOG(URBAN) 0.164 0.066 2.468 0.019

R squared 0.996 Mean dependent var 4.266

Adjusted R squared 0.995 S.D. dependent var 0.033

S.E. of regression 0.002 Sum squared resid 0.000

F statistic 1357.699 Durbin-Watson stat 1.169

Prob(F statistic) 0.000 Second-stage SSR 7.51E-05

Environ Sci Pollut Res

Malaysia in the region. The results infer that water re-sources due to the enormous growth of coal mining,thermal power generation, and associated industrial ac-tions are anticipated to amplify pollution load to the riversystem (Reza and Singh 2010). The United NationsDevelopment Programme (UNDP) (2006) concludes thatindustrial production required water for processing,cooling, and disposal of waste products. Populationgrowth, per capita income, urbanization, and industrialdevelopment will increase demand for a fixed supply ofwater. In order to meet the demand of water for industrial

use, there is a growing need to use fossil fuel energyconsumption which substantiates carbon free economy ina country.

Conclusion

The objective of the study is to examine the relationshipbetween air pollution, environmental indicators, and healthservices inMalaysia, over the period of 1975–2012. The studyused carbon dioxide emissions as a proxy for air pollution,while fossil fuel energy consumption, combustible renewablesand waste, alternative and nuclear energy, urban population,and industry value added are taken as a proxy for environ-mental factors. Health services include direct and indirecthealth infrastructure, i.e., infant fertility rate, infant mortalityrate, and life expectancy are taken as a proxy for direct healthservices, while improved sanitation facility and water re-sources are taken as indirect health services in Malaysia. Thestudy selected two-stage least square (2SLS) regression tech-nique for simultaneous equations model. The following re-sults are drawn from this exercise, i.e.,

& Alternative and nuclear energy has a positive impact onfertility rate in Malaysia, while there is a negative andmore elastic relationship between urbanization and fertil-ity rate in a country.

& Along with the increase in alternative and nuclear energyand urbanization, life expectancy increases by 0.010 %and 0.164 percentage points, respectively.

& Both the fossil fuel energy consumption and urbanizationexhibit the strong and negative impact on infant mortalityrate in Malaysia, as the coefficient value indicate the moreelastic relationship between the variables.

& While, there is a positive and less elastic relationshipbetween industrialization and infant mortality rate in acountry.

& Carbon dioxide emissions and urbanization both have apositive association with the sanitation facility available tothe people in Malaysia; however, urbanization has a great-er impact on improved sanitation as compared to thecarbon emissions in a country.

& Industrialization and alternative nuclear energy bothplayed a central role to decrease water resources, whilerising urban population improved the water resources in acountry.

& Combustible renewable and waste insignificantly explainthe health infrastructure in two-stage least square regres-sion model; however, in the correlation matrix, this vari-able has a strong and negative correlation with the twomost promising health variables, i.e., fertility rate andinfant mortality rate in Malaysia.

Table 7 Results of two-stage least square regression on improved watersources

Dependent variable: LOG(WATER)

Method: two-stage least squares

Variable Coefficient Std. error t Statistic Prob.

C 3.003 2.505 1.199 0.239

LOG(CO2) 0.024 0.019 1.206 0.237

LOG(FOSSIL) 0.114 0.378 0.303 0.763

LOG(IND) −0.037 0.014 −2.646 0.012

LOG(NUCLEAR) −0.012 0.005 −2.463 0.019

LOG(RENWASTE) −0.009 0.109 −0.082 0.934

LOG(URBAN) 0.459 0.167 2.748 0.010

R squared 0.994 Mean dependent var 4.517

Adjusted R squared 0.992 S.D. dependent var 0.066

S.E. of regression 0.005 Sum squared resid 0.000

F statistic 835.183 Durbin-Watson stat 1.392

Prob(F statistic) 0.000 Second-stage SSR 0.000

Table 6 Results of two-stage least square regression on improved watersanitation facility

Dependent variable: LOG(SANIT)

Method: two-stage least squares

Variable Coefficient Std. error t Statistic Prob.

C 4.186 2.515 1.663 0.106

LOG(CO2) 0.037 0.020 1.897 0.067

LOG(FOSSIL) −0.131 0.380 −0.345 0.732

LOG(IND) −0.017 0.014 −1.231 0.227

LOG(NUCLEAR) −0.006 0.005 −1.309 0.200

LOG(RENWASTE) −0.063 0.109 −0.574 0.569

LOG(URBAN) 0.327 0.167 1.948 0.060

R squared 0.994 Mean dependent var 4.475

Adjusted R squared 0.992 S.D. dependent var 0.067

S.E. of regression 0.005 Sum squared resid 0.000

F statistic 852.122 Durbin-Watson stat 0.907

Prob(F statistic) 0.000 Second-stage SSR 0.000

Environ Sci Pollut Res

& While, there is strong and positive correlation between thecombustible renewable and waste, life expectancy, im-proved sanitation facility and water resources in a country.

The results indicate that the expansion of fossil fuel energyconsumption has caused a significant decrease in the rate ofinfant fertility in Malaysia. In particular, a one percentagepoint increase in the rate of subscription to fossil fuel energyconsumption would cause the infant mortality rate to declineby about 8.725 %.

The study stresses the cost of increasing economic growthand industrialization in the developing countries likeMalaysia, where the pace of economic growth and industrial-ization deteriorate the environmental conditions and air qual-ity in a country. The air pollution is one of the serious threatsto health services in most developing countries; therefore,there is a special need to focus on environmental regulationsin Malaysia. The study results put forward that mortalitydecline in Malaysia causes urbanization through the construc-tion of new cities rather than promoting urban growth inalready-extant cities.

Advancing in efforts that measured the rates of populationgrowth through growing access to voluntary family planningservices which may help to ensure that sufficient water isaccessible for global food production, ecosystem health, andpolitical and social stability, there is a need of flexible andadaptable solutions on the design and development of watersupply infrastructure to trim down the exposure of systems tothese changes.

Increasing urbanization and industrialization is levelingstrain on the environment infrastructure; thus, leading tostrong air pollution which is ultimately reducing the nationalfabric of Malaysia. Energy consumption and industrializationis a good indicator of economic growth, but stabilizing theenvironment along with the investment injection is like oper-ating between a hard place and a rock. Balancing both needsstrong policy vistas on the end of the government officials.

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