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Table of Contents   
ORIGINAL ARTICLE  
Year : 2017  |  Volume : 10  |  Issue : 1  |  Page : 44-55
A case crossover analysis of primary air pollutants association on acute respiratory infection (ARI) among children in urban region of Klang valley, Malaysia


1 Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
2 Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
3 Department of Environmental Science, Faculty of Environment Studies, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
4 School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi; Institute for Environment and Development (Lestari), Universiti Kebangsaan Malaysia, Bangi, Malaysia

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Date of Web Publication5-May-2017
 

   Abstract 

Introduction: Acute respiratory infection (ARI) among children is one of the health effects associated with poor air quality. Objective: This study explores the distribution of ARI cases by subtypes among children in an urban region in tropical country and its association with the air pollution level. Method: Secondary data of primary air pollutants and the ARI data recorded at the selected main public hospital in the same area from 2006 to 2010 were analyzed descriptively using statistical software and spatially through the geographical information system (GIS). Results: In total, 54,542 cases of ARI hospital admission among children were reported with 16 subtypes. Most of the ARI cases were recorded at the general hospital located in the city center (Kuala Lumpur Hospital, N = 27,719, 50.82%), and other cases were distributed at the hospitals located at suburbs (Serdang Hospital, N = 6868 (12.59%), Selayang Hospital, N = 6548, (12.01%), and Klang Hospital, N = 5434, (9.96%). Most of the patients were boys (N = 31,682, 58.09%) and aged below 5 years (N = 45,393, 83.22%). Thirteen ARI subtypes were influenced by the particulate matter with diameter size less than 10 µm (PM10), followed by NO2 (eight subtypes), CO (four sub-types), and O3 (two sub-types). PM10 contributes to high risk of acute bronchiolitis (odd ratio (OR): 1.115, 95% CI: 1.093-1.138), acute upper respiratory infection of multiple and unspecified sites (OR: 1.065, 95% CI: 1.034-1.096), and unspecified acute lower respiratory infection (OR: 1.055, 95% CI: 1.051–1.059). In conclusion, this study supported the theory that children were mainly exposed to air pollution in urban area and they were at risk to experience ARI.

Keywords: Acute respiratory infection, air pollution, children health, Klang valley, spatial
Key message: Acute respiratory infections (ARI) were commonly reported among children aged less than 5-year old. PM10 significantly increased the risk of 13 ARI subtypes.

How to cite this article:
Abdul Rahman S R, Ismail S, Sahani M, Ramli MF, Latif MT. A case crossover analysis of primary air pollutants association on acute respiratory infection (ARI) among children in urban region of Klang valley, Malaysia. Ann Trop Med Public Health 2017;10:44-55

How to cite this URL:
Abdul Rahman S R, Ismail S, Sahani M, Ramli MF, Latif MT. A case crossover analysis of primary air pollutants association on acute respiratory infection (ARI) among children in urban region of Klang valley, Malaysia. Ann Trop Med Public Health [serial online] 2017 [cited 2019 Sep 22];10:44-55. Available from: http://www.atmph.org/text.asp?2017/10/1/44/205540

   Introduction Top


Urbanization and development process are the major sources of air pollution in an urban region and highly developed area in Peninsular Malaysia such as Klang Valley.[1] This area has extensive physical development of infrastructure, industrialization, and urbanization, which play an important role in the economic growth of the country.[2] The population in Klang Valley is forecasted to grow from 6.9 million to 7.8 million by 2020, and the urbanization process in this region has contributed badly to the existing air quality problem.[1]

The source of air pollution in Klang Valley was mainly from vehicles' emission.[3] The major pollutants: CO, NO2, and SO2 were mainly due to the influence of heavy traffic in Klang valley, whereas PM10 and O3 were predominantly related to regional tropical factors, such as biomass burning and ultra-violet radiation.[4] Heavy traffic flow also induced high PM10, CO, NO2, and SO2 in Klang Valley regarding which Zakaria et al., (2010) reported that vehicles emission and industrial activities are the major contributor of deteriorating air quality in this area.[5] The availability of many personal vehicles on road either for commercial or non-commercial matters has increased the air pollution level especially in the urban area.[6] This region also recorded the high level of pollutant concentrations that sometimes violated the air pollution index of Malaysia in some of the days of the years. For example, 59 days in 2010 were reported as unhealthy in Klang valley by the Department of Environment. The unhealthy days are reported throughout the years though at a decreasing trend such as 48 days in 2011 and 37 days in 2012.[7] The trans-boundary haze episodes in 2007 and 2009 also had significantly contributed to the number of unhealthy days and deteriorating air quality in this area.[8],[9],[10]

The respiratory illnesses range from mild and self-limiting, such as acute respiratory infections (ARI), to life-threatening entities such as bacterial pneumonia, pulmonary embolism, and lung cancer. [11],[12] Respiratory illness was among the 10 principal causes of death and the three common causes of hospitalization in Malaysia.[13] The percentage of hospitalization in the Ministry of Health (MoH) hospital due to respiratory diseases was 11.26% in 2014 increased from 9.56% in 2009. It was also the second leading cause of deaths in MoH hospitals in 2014 (18.19%) a decreased trend from 18.46% in 2019.[13],[14] Children are the most affected because of their immature respiratory system compared to adults.[15] The UNICEF estimated that the neonatal deaths due to ARI in Malaysia for 2015 was 26 and the post-neonatal death was 159. The deaths of children under 5 year of age due to ARI were estimate to be 185.[16] Acute respiratory illnesses, such as pneumonia, are the largest single cause of death in children under 5 years of age. The World Health Organization (WHO) estimates that 2 million children under 5 years of age die of pneumonia each year.[17] Air pollution was proven to be one of the factors affecting human respiratory systems especially among children in an urban area.[18]

The aim of this study was to assess the distribution of ARI cases among children who live in urbanized area and its association with the air pollution level. Findings of this study would fill in the gap of the association between the ARI and its subtypes with the outdoor air pollutants within the tropical climate country condition.


   Materials and Method Top


Description of study area

The study was conducted in the most urbanized area of Klang Valley, in a peninsular state of Selangor, Malaysia, where the air quality is heavily deteriorate [Figure 1]. Geographically, Klang Valley is bordered by Titiwangsa Mountains in the north east and the Straits of Malacca in the west.[19] The birth of industrial activities and congested traffic was the main contributors of air pollution in Klang Valley, exposing the population specifically the children to ARI. Klang Valley consists of 14 sub-areas with a size of 29,115 km2.[2],[20] This region contributes 23.5% of the Malaysia Growth Domestic Product (GDP).[21] A significant environmental deterioration including, soil contamination, water deficits and water quality deterioration, and air pollution has become apparent in Klang Valley.[6],[22],[23],[24] Being in a tropical country, Klang Valley experiences less seasonal variation except for hot and rainy seasons for the whole year.[25]
Figure 1: The air quality stations and major government hospitals in Klang Valley

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Description of air quality and ARI data

The ARI cases among children below 14 years were based on the hospital admission data obtained from seven government hospitals in Klang Valley from 2006 to 2010. The five-year air-quality data from January 2006 to December 2010 were obtained from eight air-quality monitoring stations in Klang valley provided by the Department of Environment (DOE). The ARI data obtained from the nearest air-quality monitoring station represented the air quality in that particular area [Table 1]. Based on the nearest hospital location, there are some areas that are represented by more than one hospital. For example, the area of Cheras is represented by Ampang and Kuala Lumpur hospital, whereas Shah Alam area is represented by Sungai Buloh hospital. The location of the air quality stations and major hospitals is shown in [Figure 1].
Table 1: The air quality monitoring stations matched to the nearest hospital

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Data Analysis

The ARI cases

Descriptive statistics was used to explore the ARI data in terms of socio-demographic distribution. The hospitalization data were categorized by age, gender, sex, nationality, race, and diagnoses subtypes. The relationship between ARI cases and air pollution was determined through case-crossover analysis. This design was primarily developed by Maclure to investigate the short-term exposure of acute event toward myocardial infarction.[26] Considering the fact that air pollution influences adverse health effects, the different pattern of exposure duration has been discussed widely for a clear view of mechanism toward a manifested disease by the subject.[27] Conditional logistic regression analysis was performed to estimate the OR of having ARI.[28]

Spatial distribution

The spatial distribution of ARI cases and air pollutants was interpolated within geographical information system (GIS) environment. A deterministic method of spatial interpolation provides the estimated value that cannot be measured in real life. The inverse distance weight (IDW) was applied in this study as it provides the low root mean square error (RMSE) value compared to other technique such as krigging and spline.[29] Basically, the general concept of the IDW is to estimate the unknown value of Y(Xo) in location Xo, given the observed Y value at sampled locations Xi according to the following equation:



IDW application assumed that the estimated value of concentration at Y (Xo) will have more weight if located near to the sampled locations compared to farther points. The IDW is an intuitive and efficient method of interpolation for GIS users especially to those without much knowledge of spatial statistics.[30] It best describes the even spaced sample point sets that average out the trends of the data even it weighs more on one side rather than other side.[29]


   Results Top


The ARI patient's background

In total, 54,542 ARI cases of children below 14 year of age were reported in the Klang valley from 2006 to 2010 [Table 2]. Most of the cases were reported in 2010 (N = 14,235) and 2009 (N = 14,224). Most of the ARI patients were Malaysian (N = 53,230, 97.59%). Children aged less than 5 years were the most affected by this disease (N = 45,393, 83.22%). In total, 12,100 of the cases reported in 2010 and 11,595 of the cases reported in 2009 were children between 0 and 5 years of age. Only 12.8% of the cases (N = 6978) reported were of children between 6 and 10 years and 3.98% (N = 2171) of children between 11 and 14 years.
Table 2: ARI patient's background

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Boys were among the most diagnosed with ARI, there were 31,682 cases (58.09%) reported from 2006 to 2010. Only 22,860 cases were reported among girls (41.91%). The highest cases were reported in 2009 (N = 8169, 57.43%) and 2010 (N = 8338, 58.57%) among boys. In parallel with the demographic in the country, Malays were among the majority patients (N = 40,895, 74.98%).

Most of the ARI cases (N = 30,236, 55.43%) were recorded from the Kuala Lumpur and Ampang hospital, which represent Cheras and Petaling Jaya areas. Meanwhile, 10,095 (18.51%) of the ARI cases were reported in Serdang and Kajang Hospital, which represent the area of federal administrative center of Putrajaya and the agricultural hub area of Banting. There were 12.01% (N = 6548) cases reported in Selayang hospital, which represent the area of Kuala Lumpur. About 9.96% cases (N = 5434) were reported in Klang hospital, which represent Klang area. Only small cases (N = 2229, 4.09%) were reported in Sungai Buloh hospital, which represent Shah Alam and Kuala Selangor areas.

Most of the patients were treated for less than a week (1 to 7 days) (N = 48,903, 89.66%). Less than 5% of the cases were treated as outpatients (N = 2394, 4.39%) and for more than 14 days (N = 2506, 4.60%). Only 739 (1.35%) cases were treated for more than 15 days. Most of the ARI patients formally went home (N = 53,888, 98.80%). Only in a few cases, the patients were discharged at their own risk (N = 323, 0.59%) or transferred to another hospital (N = 135, 0.25%). Very few patients discharged without permission (N = 48, 0.09%) or died due to ARI (N = 148, 0.27%) [Table 2].

The ARI cases differed significantly by nationality (t = 13.834, P < 0.001), age (t = 5.715, P < 0.001), and races (t = 10.887, P < 0.001). A number of cases also differed significantly by warded days (t = 3.795, P < 0.001) and the discharge method (t = 4.648, P < 0.001).

The hospital admission cases reported according to ARI subtypes

In total, 16 ARI subtypes were commonly reported among children in Klang valley area as shown in [Table 3]. Five subtypes were reported to be the most common, namely pneumonia (organism unspecified) (N = 19 406, 34.92%), upper respiratory infection of multiple and unspecified sites (N = 8601, 15.76%), acute pharyngitis (N = 6635, 12.16%), acute bronchiolitis (N = 5779, 10.60%), and asthma (N = 5582, 10.24%). Pneumonia has increased by 1.24% from 2855 (36.31%) cases in 2006 to 4989 cases (35.07%) in 2009. Upper respiratory infection of multiple and unspecified sites also has increased by 11.65% from 688 cases (8.71%) in 2006 to 2974 cases (20.36%) in 2009. Acute pharyngitis has also increased by 0.35% from 887 cases (11.23%) in 2006 to 1648 cases (11.58%) in 2009.
Table 3: Hospital admission cases reported according to ARI subtypes from 2006 until 2010

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The influence of primary air pollutants to ARI subtypes

[Table 4] shows the risk of hospital admission according to ARI subtypes influenced by primary air pollutants. PM10 significantly influenced the risk of 13 ARI subtypes in this study. Acute bronchiolitis (odd ratio (OR) = 1.115, 95% CI: 1.093–1.138), acute upper respiratory infection of multiple and unspecified sites (OR: 1.065, 95% CI: 1.034–1.096), and unspecified acute lower respiratory infection (OR: 1.055, 95% CI: 1.051–1.059) were highly influenced by PM10.
Table 4: Risk of hospital admission according to ARI subtypes influenced by air pollution

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CO significantly increased the risk of four ARI subtypes, namely acute sinusitis (OR: 1.749, 95% CI: 1.079–2.836), acute upper respiratory infection of multiple and unspecified sites (OR: 1.785, 95% CI: 1.671–1.838), pneumonia due to other infectious organisms (not elsewhere classified) (OR: 1.287, 95% CI: 1.131–1.465), and pneumonia (organism unspecified) (OR: 1.476, 95% CI: 1.187–1.836).

NO2 significantly increased the risk of eight ARI subtypes, namely acute sinusitis (OR: 1.026, 95% CI: 1.018–1.035), acute pharyngitis (OR: 1.015, 95% CI: 1.011–1.019), acute tonsillitis (OR: 1.019, 95% CI: 1.013–1.026), acute obstructive laryngitis and epiglottitis (OR: 1.016, 95% CI: 1.012–1.021), acute bronchitis (OR: 1.012, 95% CI: 1.008–1.017), pneumonia due to  Haemophilus influenzae Scientific Name Search R: 1.021, 95% CI: 1.016–1.026), pneumonia due to other infectious organisms (not elsewhere classified) (OR: 1.016, 95% CI: 1.013–1.018), and pneumonia (organism unspecified) (OR: 1.022, 95% CI: 1.018–1.027). O3 significantly increased the risk for two ARI subtypes that is acute nasopharyngitis (OR: 1.010, 95% CI: 1.002–1.019) and acute tonsillitis (OR: 1.007, 95% CI: 1.004–1.010).

Spatial distribution of ARI cases and air pollutants

[Figure 2] shows that the distribution of ARI cases overlaid the primary air pollutants in 2009 and 2010.
Figure 2: Spatial distribution of (a) PM10, (b) CO, (c) O3, and (d) NO2 with ARI cases in 2009 and 2010

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The ARI patients' home addresses were geocoded on a map to show the distribution by area. Most of the ARI patients were from the areas of Cheras, Batu Muda, Petaling Jaya, and Klang. Based on visual interpretation, these were the locations with higher PM10 compared to the rest of area. There was no obvious difference observed through visual interpretation for other pollutants such as CO, O3, and NO2 maps. Further assessment is needed to determine the correlation between the distributions of ARI cases and the primary air pollutants in this study.


   Discussion Top


This study explores the association of ARI cases among children with the primary air pollutants in the urban region of Klang valley using the secondary data sets from 2006 to 2010. This study takes into account only the secondary data analysis without self-monitoring from the site. ARI is an acute effect of respiratory tract infection that last less than 30 days and consists of upper respiratory tract infection (URTI) and Lower Respiratory Tract Infection (LRTI). The ARI cases hospital admission data were matched to the nearest air quality monitoring station that monitors the air quality in that particular area.

Findings of this study indicate most of the ARI cases (55.43%) were recorded from the Kuala Lumpur and Ampang hospital that represent the incidence of this disease in Cheras, the major cities within the metropolitan area of Kuala Lumpur and the residential and commercial area of Petaling Jaya. These areas are the focal point in Klang valley where many industries, residential and commercial, were located. This situation produces high traffic-related pollution.[4],[31] There were 4.6 million motor vehicles registered in Kuala Lumpur and 2.2 million motor vehicles in Selangor in 2010 that mainly concentrated at the big cities such as Petaling Jaya and Cheras.[10],[32]

Meanwhile, the second highest cases were reported in Serdang and Kajang hospital (18.51%) that mainly represented the areas of Putrajaya and Banting. Putrajaya is the federal administrative center with an area of only 49 km2 and 88,000 populations, whereas Banting is the sub-urban agricultural hub with an area of 885 km2 and 222,261 populations. Kuala Lumpur was reported with 12.01% of ARI cases. It is the most populous global city of Malaysia and also the national capital of the country. About 9.96% cases (N = 5434) were reported in the industrial urbanized area of Klang located 32 km to the west of Kuala Lumpur and 6 km east from Port Klang, among the busiest trans-shipment and container port in the world. This significantly contributed to high traffic-related pollution in the area. Shah Alam and Kuala Selangor were reported with 4.09% cases. Shah Alam is a residential and commercial area with a population of 646 890 and Kuala Selangor is mainly an agricultural hub area that produces considerably less pollution related to traffic or industries.

The healthcare management system in the country has improved with more systematic cases of ARI being reported in 2010 (N = 14,235) and 2009 (N = 14 224) as compared to the previous years of 2006—2008. Children aged less than 5 years (83.22%) were among the most diagnosed with ARI in this study and 16 ARI subtypes were commonly reported. The five most common ARI subtypes were pneumonia (organism unspecified) (34.92%), upper respiratory infection of multiple and unspecified sites (15.76%), acute pharyngitis (12.16%), acute bronchiolitis (10.60%), and asthma (10.24%).

As shown in [Table 4], the particulate matter with a diameter less than 10 µm (PM10) significantly increased the risk of 13 ARI subtypes in this study. PM10 can travel into human respiratory tract and even deeper into the lungs.[33],[34],[35] These particles accumulate in the respiratory tract based on their size, shape, and density. An upper airway system is the first organs that will be impacted by the particles.[36] These particles alter the cells in nasal mucosa and transport and penetrate deeper into the lower organs and further in lower respiratory tracts. The deposition of these particles differs according to their size. Particles between 2.5 and 10 µm in aerodynamic diameter (PM2.5–PM10) are trapped at the upper respiratory tract due to their bigger size, whereas particles smaller than 2.5 microns (PM2.5) are deposited in the bronchi tree in the lungs.[37] The penetration and deposition of these particles show varied clinical symptoms as it increase airway resistance in the normal respiratory system.

The small respiratory airway of the children at this age allows the particles to penetrate deeper in the respiratory system. The proportion of children's tongue that is larger than their small mouth and shorter neck allow the penetration of air particles pollutants into the lung.[15] Children have a larger lung surface area per kilogram of body weight than adults and under normal breathing they breathe 50% more air per kilogram of body weight than adults.[38],[39],[40],[41] Their lung is not fully developed that leads to greater permeability of the epithelial layer. Children also spend more time outdoors than adults that exposes them to more pollutants outdoors. The particles have the capacity to penetrate into the alveolus which is the place for gas exchanges. These particles are eliminated via sneezing, coughing, swallowing, or through the mucocilliary system.[37]

The OR in this study also indicated a significant risk of ARI caused by CO (four subtypes), NO2 (eight subtypes), and O3 (two subtypes). CO significantly increased the risk of acute sinusitis, acute upper respiratory infection of multiple and unspecified sites, and pneumonia (due to infectious organisms and unspecified organisms) in this study. CO is produced from the incomplete combustion of gas or fossil fuels due to insufficient oxygen supply.[42] The major sources of CO are motor vehicles and industrial process. The Department of Environment Malaysia has reported that the main production of CO was found mostly on the industrial site (0.750 ppm), followed by the urban area (0.723 ppm), and the suburban area (0.577 ppm).[43] Major CO producers in United Kingdom were motor vehicles' emission (69%).[42] CO effects human health by targeting the process of circulatory system that transports oxygen supply to the body by penetrating deeper into the lungs and confusing the process of gas exchange between oxygen and carbon dioxide through pulmonary capillary.[15],[42],[44],[45],[46] CO competes with oxygen for binding sites on hemoglobin molecules and reduces the oxygen level in the body.[37],[42] CO also encountered as the precursor pollutant produces the ozone layer, which makes it one of the pollutants that contributes to the greenhouse effect.[44]

NO2 significantly increased the risk of eight ARI subtypes in this study that are acute sinusitis, acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, acute bronchitis and pneumonia (due to Haemophilus influenzae, due to other infectious organisms and due to unspecified organisms). Motor vehicles' emission, industrial processes, and off-road equipment are the main sources of NO2.[47] During fuel combustion process in vehicles, nitrogen dioxide is formed through the oxidation of nitrogen in the presence of high temperature and pressure. Combustion process in the air might produce this nitrogen oxidant, but the composition of nitrogen in the combustion plays as a sole role to produce NO2.[48] NO2 plays a major role in producing O3 through photochemical reaction in the environment. Besides, it also acts as the precursor pollutant for acid formation.[49] NO2 also had been documented widely as one of the gases that is associated with adverse health effect in human.

Findings of this study also indicate a significant OR for acute nasopharyngitis and acute tonsillitis related to the increase of O3. O3 is hazardous gas formed through a photochemical reactions involving sunlight and heat.[4],[31],[50] The formation of O3 requires a chemical reaction of its "precursor" pollutants such as oxidizing nitrogen (NOx) and volatile organic compounds in the presence of sunlight.[48],[51] These precursor pollutants are mostly from the emissions of industrial facilities and electric utilities, motor vehicle exhaust, gasoline vapors, and chemical solvents.[52] Although these precursors often originate in urban areas, winds direction can carry NOx away that can eventually lead to ozone formation even in less populated area nearby.[53] The maximum or peak level of O3 is observed in the noon time especially in an congested traffic area.[4] O3 concentration is lower in urban area with busy traffic due to high NOx formation from the motor vehicles' exhaustion.[51] The contrast relationship between NOx and O3 explained the reaction between these chemical compounds during photochemical reactions.[48]

Findings of this study are consistent with most of the findings in the previous literature. For instance, exposure to PM10 (OR = 1.039 (95% CI: 1.020–1.059), CO (OR = 1.128, 95% CI: 1.074–1.184), NO2, OR = 1.068 (95% CI: 1.014–1.126) and SO2 OR = 1.043 (95% CI: 1.021–1.065) was observed to have significant affect toward respiratory disorder hospitalization among children in Italy.[28] A correlation is observed between CO and NO2 emissions from congested traffic roads ,which contribute to a higher prevalence rate of asthma among children in urban (5.7%) and rural areas (4.6%) in Malaysia.[5] A school-based, cross-sectional study among 1109 children in San Francisco by Kim et al. (2004) had determined positive OR for childhood asthma related to the high level of NO2 and adjusted OR of 1.07 (95% CI = 1.00–1.14).[54] A cohort study among Australian children also found a significant positive effect of PM10 on doctor visits for asthma (OR = 1.11, 95% CI = 1.04–1.119).[55]

A study on 394 children aged –15 years by Kumar et al. (2007) also indicated positive association between NO2 and airway respiratory obstruction among children living in a proximity to an industrial area in Delhi.[56] A majority of the children had a history of respiratory problems, including cough (62.7%), sputum production (24.4%), shortness of breath (32.0%), wheezing (25.6%), common cold (44.4%), and throat congestion (43.1%).

There is a risk of hospitalization due to asthma for children under 15 years in Seoul with PM10 (RR = 1.07, 95% CI = 1.04–1.11, IQR = 40.4 µg/m3), SO2 (RR = 1.11, 95% CI = 1.06–1.17, IQR = 4.4 ppb), NO2 (RR = 1.15, 95% CI = 1.10–1.20, IQR = 14.6 ppb), O3 (RR = 1.12, 95% CI = 1.07–1.16, IQR = 21.7 ppb), and CO (RR = 1.16, 95% CI = 1.10–1.22, IQR = 1.0 ppm).[57] Similar results were documented among children in Isfahan, Iran, which statistically proved the association between PM 10 and SO2 with the respiration hospital admission (0.8% to 3.4% increment for PM10 and RR of 1.05 for SO2).[58] Hashim et al. (2004) also highlights that asthmatic children have poor lung function especially in the congested traffic area of Kuala Lumpur compared to those living in less congested area in Terengganu, Malaysia.[46] Brauer et al. (2002) also found the positive risk of hospitalization for doctor-diagnosed flu/colds (OR = 1.14, 95% CI = 1.04–1.24) caused by NO2 exposure among children through a birth cohort study from mother experiencing second trimester in The Netherlands.[59]

Nevertheless, exposure to PM 2.5 had significant effect on admission rates for a subset of respiratory diagnoses asthma, bronchitis, chronic obstructive pulmonary disease, pneumonia, URTI of all age in Southeast Toronto with a relative risk of 1.24 (95% confidence interval, 1.05–1.45).[60] A study investigating short-term effect of air pollution toward all natural causes mortality across all age ranges in Klang Valley found the highest association of each pollutant with mortality that was observed for O3 (RR = 1.1054; 95% CI = 1.0389–1.1762), CO (RR = 1.0589; 95% CI = 1.0043–1.1165), NO2 (RR = 1.0559; 95% CI = 1.0011–1.1137), and PM10 (RR = 1.0363; 95% CI = 1.0058–1.0678.[61]

Most of the ARI patients in this study recovered within 7 days (89.66%) and only 1.35% of the patients recovered within 15 days. Majority of them (98.8%) were formally discharged. In a small number of cases, patients were discharged at their own risk (0.59%) or were transferred to another hospital (0.25%) and very few of them discharged without permission (0.09%) or died due to ARI (0.27%). This is because the human body system has difference susceptibility characteristics toward the infection of disease that determines their biological tendency to recover to the normal state of health.[15] Disturbance caused by foreign particles in the respiratory tract instills inflammation in the airways' system , which creates defense mechanism in order to promote exacerbation.[62] URTI is the most common infection with mild severity compared to the LRTI that is sometimes caused by viruses and bacterial infection.[11] However, URTI may also lead to LRTI due to its severity.[39] Among immunosuppressive children, the recovery may not be as fast as healthy children. To get back to their healthy state, longer recovery period is needed.[63]

A spatial distribution of ARI cases indicates that most of the cases were concentrated at the city center in Cheras, Batu Muda, Petaling Jaya, and Klang. Findings of this study support the theory that more air pollution exposure occurred among children in urban area and they were at high risk to experience ARI. These findings are consistent with other studies such as.[5],[39],[58],[60],[64] The GIS spatial analysis had been used as a display tool to visualize the output of analysis via maps.[65] GIS was broadly used to explore public health due to its ability to show thousands of data stored in a tabulate method in a form of simple preview in a spatial distribution way.[66] A simple process of locating the sources of exposure in the neighborhood and geo-code of the patient address, obtained from the hospital visits, used in this study helped us understand the results. The integration of GIS as a tool in environmental assessment is useful to visualize the dispersion of air pollution and to evaluate the association between the high concentration level and potential pollution sources.

Future study is recommended to investigate the primary pollutants, their additive and cumulative effect, to better understand the exact source, dispersion, and emission in the city. A fieldwork can improve the analysis since primary data are helpful in explaining the exact pollution in a particular area. The importance of fieldwork is that it tells us about surrounding situation so that it can be easier to focus on confounding variables in the monitoring site that might affect the results.

The study of air pollution and hospital admission regarding ARI cases among children had proved that exposure to some air pollutants may distract the respiratory system of children. The effect of these air pollutants as chemical substance that interrupts the respiratory system in human being is proven; however, this study did not provide the expected direct value of cases that may be affected by exposure to the air pollutants. A case crossover analysis approach in this study only verifies the short-term effect of air pollution exposure on health, though the disease caused by pollutants can also have long-term effects. Future research can take into account patient's individual characters, such as sex, age, home environment, or behavioral factors, that may cause severe ARI in children.


   Conclusion Top


Most of the ARI cases were reported among children aged less than 5-year. Boys were among the most diagnosed with this acute disease. The highest cases were reported in 2009 and 2010. Most of the ARI cases were concentrated at the major city center such as areas of Cheras and Petaling Jaya with mixed housing and commercial center and offices as well as high traffic volume. Most of the ARI patients were treated for less than a week, and very few patients died due to ARI (148 out of 54,542 cases, 0.27%). PM10 significantly increased the risk of 13 ARI subtypes. Acute bronchiolitis, acute upper respiratory infection of multiple and unspecified sites, and unspecified acute lower respiratory infection were among the highest influenced diseases by PM10. CO significantly increased the risk of four ARI subtypes, namely acute sinusitis, acute upper respiratory infection of multiple and unspecified sites, and pneumonia (due to infectious organisms, and organism unspecified). NO2 significantly increased the risk of eight ARI subtypes, namely acute sinusitis, acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, and pneumonia (due to Haemophilus influenza, other infectious organisms, and organism unspecified). O3 significantly increased the risk of acute nasopharyngitis and acute tonsillitis.

Acknowledgment

The authors would like to thank the Universiti Putra Malaysia, for the Research University Grant Scheme (RUGS) (04-02-12-1803RU) for financial support and the respective government agencies for providing the data and information.

Financial support and sponsorship

Nil.

Conflict of interest

There are no conflicts of interest.

 
   References Top

1.
Tey NP. Internal migration in the Klang Valley of Malaysia: Issues and implications. Malays J China Stud 2012;1:40-59.  Back to cited text no. 1
    
2.
Ling OH, Ting KH, Shaharuddin A, Kadaruddin A, Yaakob M J. Urban air environmental health indicators for Kuala Lumpur City. Sains Malays 2012;41:179-91.  Back to cited text no. 2
    
3.
Jamal HH, Pillay MS, Zailina H, Shamsul BS, Sinha K, Zaman Huri Z, Khew SL, Mazrura S, Ambu S, Rahimah A, Ruzita MS. A study of health impact and risk assessment of urban air pollution in Klang Valley, UKM Pakarunding Sdn Bhd, Malaysia, Kuala Lumpur. 2004.  Back to cited text no. 3
    
4.
Azmi SZ, Latif MT, Ismail AS, Juneng L. Trend and status of air quality at three different monitoring stations in the Klang Valley, Malaysia. Air Qual Atmosph Health 2010;3:53-64.  Back to cited text no. 4
    
5.
Zakaria J, Lye MS, Hashim JH, Hashim Z. Allergy to air pollution and frequency of asthmatic attacks among asthmatic primary school children. Am-Euras J Toxicol Sci 2010;2:83-92.  Back to cited text no. 5
    
6.
Ling OHL, Ting KH, Shaharuddin A, Kadaruddin A, Yaakob MJ. Urban growth and air quality in Kuala Lumpur city, Malaysia. Environ Asia 2010;3:123-8.  Back to cited text no. 6
    
7.
Department of Environment Malaysia. Malaysia Environmental Quality Report 2012. Kuala Lumpur: Ministry of Science, Technology and Environment; 2012.  Back to cited text no. 7
    
8.
Sahani M, Jalaludin B, Mohamaed A, Ambu S. Particulate air pollution (haze) due to the 1997 forest fires and effect on deaths in Malaysia. Int Med J 2001;5:75e85.  Back to cited text no. 8
    
9.
Afroz R, Hassan MN, Ibrahim NA. Review of air pollution and health impacts in Malaysia. Environ Res 2003;92:71-7.  Back to cited text no. 9
[PUBMED]    
10.
Abdullah AM, Samah MA, Jun TY. An overview of the air pollution trend in Klang Valley, Malaysia. Open Environ Sci 2012;6:13-9.  Back to cited text no. 10
    
11.
Simoes EA, Cherian T, Chow J, Shahid-Salles SA, Laxminarayan R, John TJ. Acute respiratory infections in children. In: Disease Control Priorities in Developing Countries. 2nd ed. New York: Oxford University Press; 2006. pp. 483-98.  Back to cited text no. 11
    
12.
Simoes EAF, Cherian T, Chow J, et al. Acute respiratory infections in children. In: Jamison DT, Breman JG, Measham AR, et al. editors. Disease Control Priorities in Developing Countries. 2nd ed. Washington DC: World Bank; 2006. Chapter 25. Available from: http://www.ncbi.nlm.nih.gov/books/NBK11786/  Back to cited text no. 12
    
13.
Ministry of Health (MOH). Health Facts 2015. Malaysia: Health Informatic Centre; 2015.  Back to cited text no. 13
    
14.
Ministry of Health. Indicators for Monitoring and Evaluation of Strategy Health for All. Malaysia: Health Informatic Centre; 2010.  Back to cited text no. 14
    
15.
Tortora GJ, Grabowski SR. Principles of Anatomy and Physiology. 10th ed. United States of America: John Wiley and Sons Inc.; 2003.  Back to cited text no. 15
    
16.
UNICEF. Committing to Child Survival: A Promise Renewed. Key Findings. New York: United Nations Children Fund; 2015. ISBN: 978-92-806-4815-7.  Back to cited text no. 16
    
17.
Bryce J, Boschi-Pinto C, Shibuya K, Black RE. The Lancet: WHO estimates of the causes of death in children. Lancet 2005;365:1147-52.  Back to cited text no. 17
    
18.
Escamilla-Nuñez MC, Barraza-Villarreal A, Hernandez-Cadena L, Moreno-Macias H, Ramirez-Aguilar M, Sienra-Monge JJ, Romieu I. Traffic-related air pollution and respiratory symptoms among asthmatic children, resident in Mexico City: The EVA cohort study. Respir Res 2008;9:74-85.  Back to cited text no. 18
    
19.
Asian Development Bank. Country Synthesis Report on Air Quality Management: Malaysia. Philippines: Asian Development Bank; 2006.  Back to cited text no. 19
    
20.
Rostam K. Migration to Klang Valley Metropolitan Peripheral Areas. Akademika 2006;68:3-27.  Back to cited text no. 20
    
21.
Department of Statistics Malaysia. Economic Census 2012. Malaysia: Department of Statistics; 2012.  Back to cited text no. 21
    
22.
Bahaa-Eldin EAR, Yusoff I, Rahim SA, Wan Zuhairi WY, Abdul Ghani MR. Heavy metal contamination of soil beneath a waste disposal site at Dengkil, Selangor, Malaysia. Soil Sedim Contam 2008;17:449-66.  Back to cited text no. 22
    
23.
Mohamed AF, Yaacob WW, Taha MR, Samsudin AR. Groundwater and soil vulnerability in the Langat Basin Malaysia. Eur. Jour Sci Res 2009;27:628-35.  Back to cited text no. 23
    
24.
Heng LY, Chukong LN, Stuebing RB, Omar M. The water quality of several oxbow lakes in Sabah, Malaysia and its relation to fish fauna distribution. J Biol Sci 2006;6:365-9.  Back to cited text no. 24
    
25.
Malaysian Meteorological Department. Annual Report 2010. Available from: http: //www.met.gov.my/. [Last accessed on 2015 March 12].  Back to cited text no. 25
    
26.
Maclure M. The case-crossover design: A method for studying transient effects on the risk of acute events. Am J Epidemiol 1991;133:144-53.  Back to cited text no. 26
    
27.
Chauhan AJ, Johnston SL. Air pollution and infection in respiratory illness. Brit Med Bull 2008;68:95-112.  Back to cited text no. 27
    
28.
Tramuto F, Cusimano R, Cerame G, Vultaggio M, Calamusa G, Maida CM, Vitale F. Urban air pollution and emergency room admissions for respiratory symptoms: A case-crossover study in Palermo, Italy. Environ Health 2011;10:31.  Back to cited text no. 28
    
29.
Lu GY, Wong DW. An adaptive inverse-distance weighting spatial interpolation technique. Comput Geosci 2008;34:1044-55.  Back to cited text no. 29
    
30.
Azpurua MA, Ramos KD. A comparison of spatial interpolation methods for estimation of average electromagnetic field magnitude. Progr Electromagn Res M 2010;14:135-45.  Back to cited text no. 30
    
31.
Latif MT, Huey LS, Juneng L. Variations of surface ozone concentration across the Klang Valley, Malaysia. Atmosph Environ 2012;61:434-45.  Back to cited text no. 31
    
32.
Ministry of Transport Malaysia. Transport Statistics Malaysia 2010. Ministry of Transport Malaysia; 2010.  Back to cited text no. 32
    
33.
American Thoracic Society. Recommended respiratory disease questionnaire for use with adults in epidemiological research. Am Rev Respir 1978;11892:7-35.  Back to cited text no. 33
    
34.
Zieliński J, Tobiasz M, Hawryłkiewicz I, Sliwiński P, Pałasiewicz G. Effects of long-term oxygen therapy on pulmonary hemodynamics in COPD patients: A 6-year prospective study. Chest 1998;113:65-70.  Back to cited text no. 34
    
35.
World Health Organization. Ambient (outdoor) air quality and health; 2015. World Health Organization Available from: http: //www.who.int/mediacentre/factsheets/fs313/en/  Back to cited text no. 35
    
36.
Brunekreef B, Forsberg B. Epidemiological evidence of effects of coarse airborne particles on health. Eur Respir J 2005;26:309-18.  Back to cited text no. 36
    
37.
Jimoda LA. Effects of particulate matter on human health, the ecosystem, climate and materials: A review. Facta Universitatis-Series: Work Living Environ Prot 2012;9:27-44.  Back to cited text no. 37
    
38.
Norlen M, Rozlan I, Ramlee R. The relationship between PM10 and daily upper respiratory tract infection. Epidemiological surveillance data analysis. NCD Malays 2004;3:2-7.  Back to cited text no. 38
    
39.
Arbex MA, Santiago SL, Moyses EP, Pereira LA, Saldiva PH, Braga ALF. Impact of urban air pollution on acute upper respiratory tract infections. In: Moldoveanu A, editor. Advanced Topics in Environmental Health and Air Pollution Case Studies. InTech. ISBN: 978-953-307-525-9.  Back to cited text no. 39
    
40.
Mansourian M, Javanmard SH, Poursafa P, Kelishadi R. Air pollution and hospitalization for respiratory diseases among children in Isfahan, Iran. Ghana Med J 2010;44:138-43.  Back to cited text no. 40
    
41.
Kleinman MT. The health effects of air pollution on children. South coast air quality management district 2000;Available from: http://www.aqmd.gov/forstudents/health_effects_on_children.pdf. [Last accessed on 2013 Jan 15].  Back to cited text no. 41
    
42.
Bull S. Carbon monoxide: General information. CHAPD HQ, HPA 2009 Version 3; 2009.  Back to cited text no. 42
    
43.
Department of Environment (DOE). Malaysia Environmental Quality Report. 2009; Malaysia: Department of Environment.  Back to cited text no. 43
    
44.
Jasim M.R, Tan KC, Lim H.S, Mat Jafri M.Z. Investigation on the Carbon Monoxide Pollution over Peninsular Malaysia Caused by Indonesia Forest Fires from AIRS Daily Measurement in Advanced Air Pollution, edited by Rajab, J. M., Tan, K. C., Lim, H. S., MatJafri, M.Z.,pp. 115–137.  Back to cited text no. 44
    
45.
George P, Anastasia M, Spyridon P, Efthimia Z. Effects of smoking on cardiovascular function: The role of nicotine and carbon monoxide. Health Sci J 2014;8:274-90.  Back to cited text no. 45
    
46.
Hashim Z, Jalaluddin J, Hashim JH. Comparison of lung functions among asthmatic children in Malaysia. Pertan J Sci Technol 2004;12:11-20.  Back to cited text no. 46
    
47.
USEPA. National Emissions Inventory (NEI) air pollutant emissions trends data. 2012;Prepared by U.S. Environmental Protection Agency, Research Triangle Park, NC. Available from: http://www.epa.gov/ttn/chief/trends/index.html. [Last accessed on 2015 April 12].  Back to cited text no. 47
    
48.
Han S, Bian H, Feng Y, Liu A, Li X, Zeng F, Zhang X. Analysis of the relationship between O3, NO and NO2 in Tianjin, China. Aerosol Air Qual Res 2011;11:128-39.  Back to cited text no. 48
    
49.
Al Katheeri E, Al Jallad F, Al Omar M. Assessment of gaseous and particulate pollutants in the ambient air in Al Mirfa City, United Arab Emirates. J Environ Prot 2012;3:640-7.  Back to cited text no. 49
    
50.
Wang T, Ding A, Gao J, Wu WS. Strong ozone production in urban plumes from Beijing, China. Geophys. Res. Lett. 2006;33, L21806. DOI: 10.1029/2006GL027689.  Back to cited text no. 50
    
51.
Martuzzi M, Mitis M, Iavarone I, Serinelli M. Health impact of PM10 and ozone in 13 Italian cities. WHO Europe 2006;Available from: http://www.euro.who.int/pubrequest.  Back to cited text no. 51
    
52.
Mansouri B, Hoshyari E, Mansouri A. Study on ambient concentrations of air quality parameters (O3, SO2, CO and PM10) in different months in Shiraz city. Iran Int J Environ Sci 2011;1:1440-7.  Back to cited text no. 52
    
53.
Hosseinibalam F, Hejazi A. Influence of meteorological parameters on air pollution in Isfahan. International Proceedings of Chemical, Biological and Environmental Engineering 2012;46.  Back to cited text no. 53
    
54.
Kim JJ, Smorodinsky S, Lipsett M, Singer BC, Hodgson AT, Ostro B. Traffic-related air pollution near busy roads: The East Bay Children's Respiratory Health Study. Am J Respir Crit Care Med 2004;170:520-26.  Back to cited text no. 54
    
55.
Jalaludin BB, O'Toole BI, Leeder SR. Acute effects of urban ambient air pollution on respiratory symptoms, asthma medication use, and doctor visits for asthma in a cohort of Australian children. Environ Res 2004;95:32-42.  Back to cited text no. 55
    
56.
Kumar R, Nagar JK, Kumar H, Kushwah AS, Meena M, Kumar P, Gaur SN. Association of indoor and outdoor air pollutant level with respiratory problems among children in an industrial area of Delhi, India. Arch Environ Occup Health 2007;62:75-80.  Back to cited text no. 56
    
57.
Lee JT, Kim H, Song H, Hong Y C, Cho YS, Shin S Y, Kim Y S. Air pollution and asthma among children in Seoul, Korea. Epidemiology 2002;13:481-4.  Back to cited text no. 57
    
58.
Mansourian M, Javanmard SH, Poursafa P, Kelishadi R. Air pollution and hospitalization for respiratory diseases among children in Isfahan, Iran. Ghana Med J 2010;44:138-43.  Back to cited text no. 58
    
59.
Brauer M, Hoek G, Van Vliet P, Meliefste K, Fischer PH, Wijga A, Brunekreef B. Air pollution from traffic and the development of respiratory infections and asthmatic and allergic symptoms in children. Am J Respir Crit Care Med 2002;166:1092-98.  Back to cited text no. 59
    
60.
Buckeridge DL, Glazier R, Harvey BJ, Escobar M, Amrhein C, Frank J. Effect of motor vehicle emissions on respiratory health in an urban area. Environ Health Perspect 2002;110:293.  Back to cited text no. 60
    
61.
Mahiyuddin WRW, Sahani M, Aripin R, Latif MT, Thach TQ, Wong CM. Short-term effects of daily air pollution on mortality. Atmosph Environ 2013;65:69-79.  Back to cited text no. 61
    
62.
MacNee W, Donaldson K. Mechanism of lung injury caused by PM10 and ultrafine particles with special reference to COPD. Eur Respir J 2003;21:40(Suppl 4):7s-51s.  Back to cited text no. 62
    
63.
World Health Organization. Ambient (outdoor) air quality and health. 2015;Retrieved from World Health Organization: Available from: http://www.who.int/mediacentre/factsheets/fs313/en/ [Last accessed on 2015 Nov 26].  Back to cited text no. 63
    
64.
Ling OH, Ting K H, Shaharuddin A, Kadaruddin A. Yaakob M J Urban air environmental health indicators for Kuala Lumpur City. Sains Malays 2012;41:179-91.  Back to cited text no. 64
    
65.
Westminster. Geographic Information Systems. 2011;Available from: http://www.westminster.edu/staff/athrock/GIS/GIS.pdf [Last accessed on 2011 Mar 16].  Back to cited text no. 65
    
66.
Chaput EK, Meek JI, James I, Heimer R. Spatial analysis of human granulocytic ehrlichiosis near Lyme, Connecticut. Emerg Infectious Dis J 2000;8:943-8.  Back to cited text no. 66
    

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Correspondence Address:
S. N. S Ismail
Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM), Serdang, Selangor
Malaysia
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DOI: 10.4103/ATMPH.ATMPH_75_17

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