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Public health risk assessment from drinking water from vending machines in Seri Kembangan (Malaysia)
Accepted Manuscript Public health risk assessment from drinking water from vending machines in Seri Kembangan (Malaysia)
Sarva Mangala Praveena, Nurul Fatihah Kamal Huyok, Claire de Burbure PII:
S0956-7135(18)30025-2
DOI:
10.1016/j.foodcont.2018.01.019
Reference:
JFCO 5950
To appear in:
Food Control
Received Date:
11 September 2017
Revised Date:
07 December 2017
Accepted Date:
14 January 2018
Please cite this article as: Sarva Mangala Praveena, Nurul Fatihah Kamal Huyok, Claire de Burbure, Public health risk assessment from drinking water from vending machines in Seri Kembangan (Malaysia), Food Control (2018), doi: 10.1016/j.foodcont.2018.01.019
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ACCEPTED MANUSCRIPT TITLE PAGE
1 2 Title
Public health risk assessment from drinking water from vending machines in Seri Kembangan (Malaysia)
Authors
Sarva Mangala Praveena1, Nurul Fatihah Kamal Huyok1, Claire de Burbure2
Affiliations
1Department
of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia 2Faculty
3 4 5 6 7 8 9 10 11 12 13
of Medicine, Université Catholique de Louvain, Louvain, Belgium
Name : Sarva Mangala Praveena (*Corresponding author) Phone : +603-89472692 Fax : +603-89472395 Email : [email protected] Complete mailing address : Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
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Abstract
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This study investigated the public health risk linked with microbial quality of drinking water
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from vending machines in Seri Kembangan city (Malaysia) using epidemiological and
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Quantitative Microbial Risk Assessment (QMRA) approaches. This study was also conducted
32
to understand associations between reported health symptoms and daily water intake
33
information. Following WHO guidelines on water safety, QMRA were performed was to
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estimate burden of disease from E. coli from water vending machines. Triplicate drinking
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water samples from water vending machines were collected from six sampling areas around
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the city, analysed for E. coli, information of health symptoms and daily water intake was
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obtained from 121 respondents by questionnaires. The results indicated the highest
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numbers of E. coli levels were found in Seri Serdang (45 – 68 CFU/ 100 mL) and Taman
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Pinggiran Putra (45 – 62 CFU/ 100 mL). Escherichia coli levels in drinking water samples
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from water vending machines obtained from Seri Serdang, Taman Pinggiran Putra, Taman
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Equine, Balakong and Serdang Jaya exceeded both Malaysian Drinking Water Quality and
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WHO Drinking Water Quality guidelines. Reported health symptoms were only significantly
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linked to brand which likely to be associated with regular maintenance of water vending
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machine. All the drinking water samples from water vending machines except from Lestari
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Perdana have exceeded the health based target outcomes by QMRA. Combination of
46
epidemiology
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understanding of public health risks and gateway for a better management of water vending
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machines.
and
quantitative
microbial
risk
assessment
have
provided
a
clear
49 50
Keywords: Public health; risk assessment; vending machine; drinking water
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1. Introduction
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There has been an exponential increase in the public availability of drinking water vending
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machines in urban areas, driven by modern working and public infrastructures, lifestyles
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changes as well as drinking habits. Sales of water vending machines are also influenced by
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local conditions such as ease of access to clean drinking water, convenience of the location,
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human friendly services, low setup cost and labour (Schillinger & Du Vall Knorr 2015).
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However, microbiological quality of the drinking water made available to the public from
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vending machines has been severely put to the test lately. Several recent studies have
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shown, not only in Malaysia but across the world, that water vending machine samples are
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not necessarily pathogen-free, as there is a risk of contamination by fecal coliform bacteria
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(Ee Yau et al., 2016; Schillinger & Du Vall Knorr, 2015; Simforian, Nonga, & Ndabikunze,
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2015). Indeed, the quality of the drinking water obtained from vending machines depends
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not only on water source, machine design and maintenance, but as reported by Dufour et
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al.
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maintenance process and in particular when handling the machine nozzle (Barrell, Hunter, &
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Nichols, 2000; Dufour et al., 2003)
(2003) on the cleaning and hygiene standards practised during the machine's
70 71
Quantitative Microbial Risk Assessment (QMRA) is a technique used in burden of
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disease estimation for particular pathogenic bacteria, and it would be suitable for studying
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the quality of the drinking water obtained from vending machines. However, implementation
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individual QMRA for each bacterial pathogen in turn would be highly impractical in terms of
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time and money and would not necessarily yield the necessary information. Therefore, the
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World Health Organization (2008) recommends the use of certain enteric bacteria in QMRAs
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as indicators for the potential presence of pathogens. Escherichia coli is often used as a
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reference bacterium for enteric bacterial pathogens and therefore an indicator of possible
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faecal contamination (World Health Organization, 2016). The use of an indicator organism in
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QMRA introduces layers of uncertainty (e.g. model suitability, cohort representativeness),
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which can be overcome by performing a Monte Carlo simulation. However, the Monte Carlo
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simulation is a complicated mathematical technique, which limitedly especially in developing
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and under-developed countries due to data availability. Therefore, the QRMA approach can
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also be used by limiting the scope of an exposure scenario to overcome data limitations and
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resources to estimate burden of disease from pathogenic bacteria and to ensure the results
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will help to protect public health (Haas et al. 2014; U.S. Environmental Protection Agency
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2002).
88 89
Investigations by The Straits Times (2014) indicated that 29 drinking water samples
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taken from vending machines within cities of the Klang Valley of Malaysia were found to be
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contaminated with E. coli, coliforms and Clostridium perfringens. This raised concerns about
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Malaysia's drinking water quality and safety. There have been previous studies focused on
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the microbiological quality of water vending machines in Malaysia (Dufour et al. 2003; Ee
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Yau et al. 2016; Gurpreet et al. 2011). However, little information is available with regards
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to QMRA in drinking water systems. Despite the fact that waterborne outbreaks linked to
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drinking water supply have been well documented in Malaysia (Gurpreet et al. 2011) to
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date, it appears that quantitative associated risk assessments related to drinking water have
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not yet been reported. Therefore, the present study aimed to determine the frequency of E.
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coli in drinking water samples from water vending machines in the city of Seri Kembangan
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and to understand the associations between its presence and reported health symptoms and
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daily water intake information. Ultimately, by applying a simplified QMRA, the intent of this
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work was to estimate a preliminary burden of disease linked to water vending machines in
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Seri Kembangan (Malaysia). To the best of the authors' knowledge, this study is believed to
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be the first to perform a quantitative health risk assessment of the water obtained from
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vending machines, in the hope that it will help local authorities and other stakeholders to
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understand any potential risk to public health.
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2. Materials and Methods
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2.1 Water Sampling and Analysis
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A total of 90 drinking water samples were collected randomly in triplicates from 30 water
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vending machines located in six areas (Balakong, Serdang Jaya, Seri Serdang, Taman
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Pinggiran Putra, Taman Equine, Lestari Perdana) in Seri Kembangan, Selangor (Malaysia)
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located at 3.03’N 101.7’E. These represented the most densely populated areas around Seri
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Kembangan city. High density areas in Seri Kembangan also resulted in increased numbers
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of water vending machines which mainly serve as drinking water sources due to their
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convenience, easy accessibility and backup drinking water supply during watermains
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interruptions (Zulzaha, 2015). A checklist was created for the purpose of recording the
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observed working condition of each water vending machine at the time of sampling, with
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the intent of obtaining information about its current surroundings, its direct environment,
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and most recent maintenance date (Table 1). The drinking water samples from water
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vending machines were collected using pre-sterilized Schott Duran bottles and analysed for
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E. coli using membrane filtration technique (American Public Health Association, 1998). The
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drinking water samples were placed immediately in an ice box, maintained between 1-4oC
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and analyzed within 12 hours from time of collection. A total of 100 mL of drinking water
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was passed through 0.45 μm Whatman membrane filters, placed on M-Lauryl Sulfate Agar
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incubated for 4 hours at 30ºC and followed by 14 hours at 44ºC. Yellow colonies on the
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filter membranes were counted as E. coli and reported as colony-forming units per 100 mL
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(cfu/100 mL). All glassware was sterilized to avoid any contamination during sample
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analysis. Additionally, drinking water samples were analysed in triplicates to ensure precision
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and accuracy of the analysis process.
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2.2 Resident Questionnaires
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Questionnaires were prepared and distributed to respondents who purchased water from
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the designated vending machines. The questionnaire was used to obtain water intake
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information and data regarding the presence or absence of health symptoms following the
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consumption of water obtained from vending machines. The number of total respondents (n
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= 121) was calculated according to Kirkwood & Sterne (2003) taking into account an
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additional 20% for potential non-responses. The questionnaire survey was pretested on 60
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residents of Sri Serdang (Malaysia) and found to have a Cronbach alpha value of 0.76, an
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acceptable measure of internal consistency of the questionnaire. Sri Serdang area was
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selected for the pretest session as respondents from this area had similar drinking water
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characteristics with high numbers of vending machines. The respondents were contacted
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after a week to obtain the accurate description, if any, of any health symptoms they may
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have experienced.
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Statistical analysis was performed using IBM SPSS Version 21. Descriptive statistics
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were applied to determine variations in the levels of E. coli in drinking water samples, while
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the Chi Square test was used to ascertain associations between reported health symptoms
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and daily water intake information with a 5% level of significance.
150 151
2.3 Quantitative Microbial Risk Assessment
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In this study, a simplified QMRA was performed as described by Haas et al. (2014) for
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quantifying risk of infection. Disease burden was calculated based on the method described
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by the World Health Organization (World Health Organization, 2016) and Howard et al.
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(2006). A summary of the procedure can be found in Table 2.
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The indicator organism chosen for QMRA in this study was E. coli based its detection in
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drinking samples from water vending machines. Since there is lack of specific pathogen data
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from the water supplies, we had to use indicator organisms as surrogates in a similar
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approach as the one applied by George et al. (2015) in quantifying microbial risk to estimate
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burden of disease due to particular microbial pathogen exposure in drinking water systems.
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In this study, the ratio used for generic E. coli: pathogenic E. coli was 1:0.08 (Haas et al.
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2000). A log reduction value of 105 was applied for treatment effect based on published
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reports on conventional treatment systems (World Health Organization 2008). The estimated
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mean daily consumption of water from the vending machines obtained from the
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questionnaires was 1.659 L/day. In order to get an estimate of the dose-response for this
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study the Beta-Poisson model was chosen as it provides an effective microbial dose-
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response relationship and designates the observed infectivity as a function of dosage (Haas
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et al. 2000). Disease burden related to gastroenteritis was adapted from previous published
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studies in the literature (Havelaar & Melse 2003) due to lack of disease occurrences and
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infection data representing developing countries such as Malaysia. Since there are to date
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very limited data available concerning exposed and susceptible populations in Seri
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Kembangan, a susceptible fraction value of 10% was taken from Howard et al. (2006), and
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the target reference level for tolerable risk for pathogenic E. coli was based on the value of
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10-6 set by the WHO Health-Based Targets.
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3. Results And Discussion
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Data presented in Table 3 shows E. coli levels (CFU/100 mL) in sampling areas from around
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the city of Seri Kembangan (Malaysia). The highest numbers of E. coli were found in Seri
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Serdang (45 – 68 CFU/ 100 mL) and Taman Pinggiran Putra (45 – 62 CFU/ 100 mL). These
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areas are surrounded by densely populated residential zones as they are located near
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several higher institutions and industries. E. coli enumerations for water samples collected
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from vending machines in Taman Equine, Serdang Jaya and Balakong ranged from 1 to 31
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CFU/ 100 mL); however, water samples from Lestari Perdana showed no detectable E. coli.
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In general, drinking water samples from water vending machines of sampling areas (Seri
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Serdang, Taman Pinggiran Putra, Taman Equine, Balakong and Serdang Jaya) exceeded the
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Malaysian Drinking Water Quality and World Health Organization Drinking Water Quality
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guidelines. Detection of E. coli in water vending machines in these areas can be associated
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with regular maintenance and location (Table 1). Small number of samples were collected
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from Lestari Perdana has also impacted the probability of E. coli detection. Inappropriate
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maintenance/ cleaning can result in biofilm formation which may have contributed to the
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presence of E. coli in water samples from water vending machines. Moreover, if the
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machines are located near dirty drains or unsanitary environments this may also contribute
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to bacteria contaminating samples. Contamination of the drinking water from these areas
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may results from aerosols or carriage by insect vectors (flies and cockroaches) contacting
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water vending machine compartments (Chaidez et al. 1999).
197 198
Microbiological analyses of water samples obtained from vending machines around
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the world, have shown a large proportion to be contaminated with E.coli (Chaidez et al.
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2016; Ebrahim et al. 2015; Ee Yau et al. 2016; Schillinger and Du Vall Knorr 2015). The
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quality of drinking water obtained from such machines depends on water source, design and
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maintenance of machines (Barrell et al. 2000). According to Ee Yau et al. (2016), bacteria
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including E. coli, can grow on the filters of water vending machines reaching substantial
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levels. Ee Yau et al. (2016) also reported that contamination with faecal bacteria may occur
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due to unsanitary hygiene practices of people handling the machines. Furthermore, old
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machines or those generally in poor working condition (corrosion) may be contributing
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factors not only for bacterial contamination but may also results in toxic chemicals entering
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the drinking water (Chaidez et al. 2016; Ebrahim et al. 2015). 8
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3.1 Consumer questionnaire
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Results of the consumer water intake survey are presented in Table 4. Overall, 47.1% of
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respondents consumed 5-7 cups of water daily in response to the recommendations of the
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Malaysian Dietary Guidelines (2013), which propose that an adult should drink 6 to 8 glasses
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of plain water daily to stay well hydrated and healthy. Most respondents bought water from
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shops, 56% for accessibility reasons. In terms of quantities, 47.1% of respondents chose to
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use 1.5 L bottles. The respondents were also asked about what they took into consideration
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before buying water, and brand appeared to be the most important factor (38.0%), due to
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their perception that only certain brands guarantee good drinking water quality. The
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preferred brand was Dr Sukida (57.0%) while Sipsipwater (15.7%), Imtiyaaz Bio Energy
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(14.9%), Water Drops (11.6%) and others (0.8%) were not as popular. Figure 2 shows the
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respondents' perceived health symptoms following the consumption ofwater from water
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vending machines. According to the questionnaire survey, 71.1% of respondents
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experienced no deleterious health symptoms after consuming the water, while 3.3% of
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respondents experienced gastroenteritis, which included symptoms such as vomiting,
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diarrhoea, nausea, abdominal cramps or stomach aches. About 9.9% had experienced
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headaches or dizziness while 15.7% of respondents said they experienced respiratory
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symptoms such as coughs, sore throats or runny noses.
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There was no association between reported health symptoms and quantity of daily
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water intake or perception of water vending machines (Table 5). However, results showed
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an association between reported health symptoms and preferred brand (Chi Square =
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26.497, 12) (p value = 0.009). Preferred brand of water is likely to be associated with the
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condition of water vending machines. Therefore those machines receiving regular
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maintenance provide a better margin of safety since procedures generally include steps to
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ensure compartments are clean and overall are more aesthetically pleasing. The lack of clear
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association between the few reported health symptoms and the consumption of water from
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vending machines shown to be contaminated with E. coli may be linked to the increasing
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diversity E. coli strains expressing virulence factors. E. coli are common occupants of the
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intestinal tracts of healthy humans and animal and are known to play an important role in
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luminal microbial flora stability and maintenance of normal intestinal homeostasis. However,
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a small subset of pathogenic strains have been identified which cause a broad spectrum of
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diseases when infecting the gastrointestinal and urinary tracts, as well as various other
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organs in the body (Mainil 2013). In humans, pathogenic E.coli strains are generally
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categorized as enteroinvasive, enterotoxigenic, enteropathogenic, enterohaemorrhagic,
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enteroaggregative, or necrotoxigenic. Their pathogenicity is linked to several virulence
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factors such as adhesins, which help them attach to host cells, reproduce and multiply, and
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variety of toxins including shiga-toxins and haemolysins (Kaper, Nataro & Mobley, 2004;
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Mainil, 2013).
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According to Soller et al. (2016), a low frequency of health symptoms being
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reported, coupled with unclear relationships between such symptoms or illness and E.coli
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detected in drinking water does not guarantee that the water is microbiologically safe.
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QMRA offers an alternative approach in terms of a quantitative measure to offer a more
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robust estimation risk. Results for the QMRA conducted here for each sampling area of Seri
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Kembangan city are given in Table 6. In general, the disease burden values showed that all
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drinking water samples from water vending machines from the four sampling areas (Seri
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Serdang, Taman Pinggiran Putra, Taman Equine, Balakong and Serdang Jaya) exceeded the
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WHO guidelines for health based target outcomes. It is noted that there were number of
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water vending machines in these areas were lacking in terms of maintenance service
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information. The only area with QMRA results meeting the WHO guidelines for acceptable
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microbiological quality was Lestari Perdana. Acceptable QMRA outcomes for Lestari Perdana
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may be related to information gather regarding regular machine maintenance and
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cleanliness surrounding areas where the water vending machines were installed. It should
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also be noted that only three water samples were collected from this area which would
264
impact the probability of E. coli detection.
265 266
Nevertheless, the overall results of this study imply that consumers of products from
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current water vending machines may be at risk of gastrointestinal illness. These results are
268
in line with findings from other studies conducted in Mysore, India (George et al. 2015) and
269
Kampala, Uganda (Howard et al. 2006). Detection of E.coli in water vending machines is
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most likely associated with poor machine maintenance by the vendor (Table 1).
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Contamination is possibly due to biofilms on the tubes which in turn impacts drinking water
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quality (Tsvetanova and Hoekstra 2012). Although the Ministry of Health (Malaysia) has
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required all water vending machines to be licensed under Regulation 360C(4) of the Food
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Regulations 1985, further strict actions and inspections need to take place (Hashim and
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Yusop 2016). Further actions such as replacement of proper pipes and periodic inspection of
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the water distribution systems are necessary for effective management of microbiologic
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quality of water vending machines.
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4. Study limitations
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This study was the first to assess quantitative health based targets via QMRA involving
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water vending machines; however QMRA findings here were based on several assumptions
282
and uncertainties due to limited availability of data on pathogenic E. coli, its fate and
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transmission related to vending machine water. Therefore, detection of E. coli needs to be a
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focal point for future QMRA studies in order to produce reliable and comparable data to
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ensure this information is adequate for the risk mitigation. Correspondingly, Boone, Van der
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Stede, Aerts, Mintiens, & Daube (2010) also recommended the importance of identifying the
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knowledge gap and ways to facilitate model improvement which should lead to more
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realistic QMRA results and its implications. This research was conducted as a cross sectional
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study from data collected from a population at a specific point in time. Therefore, there are
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several potential factors which may influence E. coli levels in drinking water samples from
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water vending machines, including seasonal patterns, daily or weekly effects, and long-term
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trends. These factors must be controlled in order to understand the contamination of
293
drinking water from water vending machine associated with gastrointernal illness
294
(Blumenthal et al. 2001; Mann et al. 2007).
295 296
5. Conclusion
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Viable E. coli were found in water samples from vending machines situated in five areas
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surveyed (Seri Serdang, Taman Pinggiran Putra, Taman Equine, Balakong and Serdang
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Jaya). The current epidemiological study found that there was no obvious association
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between the presence of E. coli in drinking water and the reported health symptoms,
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quantity of daily water intake or perception on water vending machines. However, there
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appeared to be an association between reported health symptoms and preferred brand.
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With respect to the QMRA, the disease burden values showed that all drinking water
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samples from water vending machines from sampling areas (Seri Serdang, Taman Pinggiran
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Putra, Taman Equine, Balakong and Serdang Jaya) exceeded the WHO guidelines for health
306
based targets. No detectable E. coli was found for drinking water samples from Lestari
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Perdana may related with under-sampled (only 3 samples) and sampling was conducted
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right after the maintenance process was completed. Although there are few assumptions
309
and limitations involving QMRA output, these preliminary findings have shown that the
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general public should be aware of microbiological water quality from water vending
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machines. These results are also critical for manufacturers to ensure regular maintenance of
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water vending machines is conducted to maintain quality and safety of drinking water their
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vending machines.
314 315 316
Acknowledgments
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The authors would like to thank the laboratory staff of the Department of Medical
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Microbiology and Parasitology (Faculty of Medicine and Health Sciences, Universiti Putra
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Malaysia) for their autoclave service. We thank two anonymous reviewers for their
320
constructive comments, which helped us to improve this manuscript.
321 322
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Kaper, J. B., Nataro, J. P., & Mobley, H. L. T. (2004). Pathogenic Escherichia coli. Nature
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Schillinger, J., & Du Vall Knorr, S. (2015). Drinking-water quality and issues associated with water vending machines in the city of Los Angeles. Journal of Environmental Health,
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The Straits Times. (2014). Bacteria found in water samples from Malaysia ’ s vending
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World Health Organization. (2008). WHO guidelines for drinking-water quality. (Vol. 38). doi:10.1016/S1462-0758(00)00006-6 World Health Organization. (2016). Quantitative Microbial Risk Assessment: Application for
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balakong-residents-say-water-tankers-not-sent-to-all-areas/
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Highlights
Public health risk linked to microbial quality of drinking water from vending machines
Escherichia coli were found in drinking water from all five sampling areas
Significant association found between reported health symptoms and preferred brand
Only Lestari Perdana showed none for burden of disease estimation
SERDANG JAYA LESTARI PERDANA
Seri Kembangan
Sampling locations
Fig. 1 Drinking water sampling from water vending machines in Seri Kembangan area
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Percentange
120
80
Yes
84.3
71.1
28.9
20
3.3
0
497 498
90.1
60 40
496
No
96.7
100
None
9.9
Health Symptoms Headache, dizziness
Gastroenteritis
15.7
Respiratory symptoms
Fig. 2 Perceived health symptoms after respondents consumed drinking water from water vending machines (total respondents n = 121)
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Table 1. Water vending machines checklist 428 Water Vending Machine
Location
Environment
Condition
1. 2. 3. 4. 5. 6. 7. 8. 9.
Seri Serdang
Nearby dustbin Nearby dustbin Nearby drain Nearby dustbin Nearby drain Nearby dustbin and drain In laundry shop Nearby drain Nearby drain and dustbin
Good and well functioning Good and well functioning Good and well functioning Bit rusty and well functioning Good and well functioning Good and well functioning Rusty and not function well Good and well functioning Good and well functioning
Length since last service during sampling in February 2016 (days) 12 12 NA 79 486 12 NA NA 492
10.
Serdang Jaya
Nearby dustbin and workshop Nearby drain Nearby dustbin Nearby laundry shop Nearby drain Nearby dustbin
Good and well functioning
NA
Rusty and not well maintained Bit rusty and well functioning Rusty and well functioning Rusty and not function well Not function well and full with sticker
NA 15 5 NA NA
11. 12. 13. 14. 15. 16.
Lestari Perdana
Nearby drain
Good and well functioning
0
17. 18. 19. 20. 21. 22. 23.
Taman Pinggiran Putra
Nearby drain Nearby drain Nearby drain and dustbin Nearby drain Nearby clothing stores Nearby dustbin Nearby stores
Good and well functioning Rusty and not function well Good and well functioning Good and well functioning Good and well functioning Good and well functioning Good and well functioning
11 NA NA 6 6 6 1
24. 25.
Taman Equine
Nearby drain Nearby grocery stores
Good and well functioning Had bird droppings and well functioning Good and well functioning Good and well functioning Good and well functioning
0 30
26. 27. 28. 29. 30.
429 430 431 432
Nearby grocery stores Nearby drain Nearby dustbin and drain Balakong
Nearby drain and workshop Nearby drain and workshop
Rusty and not function well Full with sticker and not well maintained
NA NA 40 NA NA
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433
434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450
Table 2. Summary of equations applied for disease burden calculation Equation Drinking water quality (CD) Consumption of drinking water (V) Exposure by drinking water(E) Dose response (r) Risk of infection (P inf, d) Risk of infection (P inf, y)
Unit Organisms per liter Liters per day
Formula CR x (1 – PT) Estimated
Organisms per liter Probability of infection Per day Per year
Risk of diarrhoeal illness given infection (Pill/inf) Risk of diarrhoeal disease (Pill) Disease burden (db)
Probability of illness per infection
CD x V From literature Exr 1 – (1 - P inf, d) x 365 (Haas et al., 2014) From literature
Susceptible fraction (fs) Disease burden (db)/health outcome target (HT)
% of population DALY per year
Per year DALY per case
Pinf,y x Pill,inf Calculated from available data in literature From literature Pill x db x fs
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451
452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474
Table 3. E. coli colonies in sampling areas from Seri Kembangan city (Malaysia) Areas
Number of samples
Lestari Perdana Taman Pinggiran Putra Serdang Jaya Seri Serdang Balakong Taman Equine
3 21 18 27 6 15
E. coli level variation (CFU/ 100 mL) 0 45 - 62 10 - 21 45 - 68 15 - 31 1-6
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475 476
477
Table 4. Water intake information (n = 121) Water intake information Frequency of drinking water daily 1-2 cups 2-4 cups 5-7 cups 8-10 cups More than 10 cups
Number of respondents
Percentage (%)
2 19 57 28 15
1.7 15.7 47.1 23.1 12.4
Location of buying water Shops College Others
69 34 18
57.0 28.1 14.9
Quantity to buy water 500ml 1L 1.5L 3L 5L 10L
22 14 57 4 23 1
18.2 11.6 47.1 3.3 19.0 0.8
Consideration before buying water Price Brand Availability Don’t care
31 46 33 11
25.6 38.0 27.3 9.1
Prefer brand for buying water Desa Dr Sukida Imtiyaaz Bio Energy Sipsipwater RO water Water drops
1 69 18 19 14
0.8 57.0 14.9 15.7 11.6
Heard of news on water vending machines contamination No Yes
53 68
43.8 56.2
Perception on water vending machine Good Fair Very good Very bad Bad
65 41 4 3 8
53.7 33.9 3.3 2.5 6.6
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491 492
Table 5. Chi-square test of contingency between reported health symptoms and daily water intake. Variables None Daily water intake 1-2 cups 2-4 cups 5-7 cups 8-10 cups More than 10 cups
2 15 33 23 13
0 2 2 0 0
0 1 8 2 1
0 1 14 3 1
Preferred brand Desa Dr Sukida Imtiyaaz Bio Energy Sipsipwater Water drops
1 56 11 8 10
0 1 0 3 0
0 8 1 2 1
0 4 6 6 3
Perception on water vending machines Good Fair Best Bad Significant at p<0.05 493
Reported health symptoms Gastroentritis Headache, Respiratory dizziness symptoms
42 28 4 12
2 1 0 1
7 4 1 0
8 8 3 0
ᵡ2 (df)
p
14.951 (12)
0.244
26.497 (12)
0.009
9.068 (9)
0.431
494
Table 6. Quantitative Microbial Risk Assessment for E.coli in drinking water from water vending machines Taman Equine Raw water quality (Cr)
495
Serdang Jaya
Seri Serdang
Taman Pinggiran Putra
Balakong
Lestari Perdana
3
10
55
23
54
0
Treatment effect Drinking water quality (CD) Exposure by drinking water(E) Dose response (r)
0.999
0.999
0.999
0.999
0.999
0.999
3.0E-2 4.9E-3 1.0E-03
1.0E-2 1.66E-2 1.0E-03
5.5E-2 9.12E-2 1.0E-03
2.3E-2 3.8E-2 1.0E-03
5.4E-2 9.0E-2 1.0E-03
0 0 1.0E-03
Risk of infection (P
inf, d)
5.0E-06
1.7E-05
9.1E-05
3.8E-05
9.0E-05
0
Risk of infection (P
inf, y)
1.8E-3
6.0E-3
3.3E-2
1.4E-2
3.2E-2
0
2.5E-1
2.5E-1
2.5E-1
2.5E-1
2.5E-1
2.5E-1
4.5E-4 4.5E-01 1E-1
1.5E-3 4.5E-01 1E-1
8.2E-3 4.5E-01 1E-1
3.5E-3 4.5E-01 1E-1
8.0E-3 4.5E-01 1E-1
0 4.5E-01 1E-1
2.0E-05
6.8E-05
3.7E-04
1.6E-04
3.6E-04
0
Risk of diarrhoeal illness given infection (Pill/inf) Risk of diarrhoeal disease (Pill) Disease burden (db) Susceptible fraction (fs) Disease burden (db)/health outcome target (HT)
Sarva Mangala Praveena, Nurul Fatihah Kamal Huyok, Claire de Burbure PII:
S0956-7135(18)30025-2
DOI:
10.1016/j.foodcont.2018.01.019
Reference:
JFCO 5950
To appear in:
Food Control
Received Date:
11 September 2017
Revised Date:
07 December 2017
Accepted Date:
14 January 2018
Please cite this article as: Sarva Mangala Praveena, Nurul Fatihah Kamal Huyok, Claire de Burbure, Public health risk assessment from drinking water from vending machines in Seri Kembangan (Malaysia), Food Control (2018), doi: 10.1016/j.foodcont.2018.01.019
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT TITLE PAGE
1 2 Title
Public health risk assessment from drinking water from vending machines in Seri Kembangan (Malaysia)
Authors
Sarva Mangala Praveena1, Nurul Fatihah Kamal Huyok1, Claire de Burbure2
Affiliations
1Department
of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia 2Faculty
3 4 5 6 7 8 9 10 11 12 13
of Medicine, Université Catholique de Louvain, Louvain, Belgium
Name : Sarva Mangala Praveena (*Corresponding author) Phone : +603-89472692 Fax : +603-89472395 Email : [email protected] Complete mailing address : Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
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Abstract
29
This study investigated the public health risk linked with microbial quality of drinking water
30
from vending machines in Seri Kembangan city (Malaysia) using epidemiological and
31
Quantitative Microbial Risk Assessment (QMRA) approaches. This study was also conducted
32
to understand associations between reported health symptoms and daily water intake
33
information. Following WHO guidelines on water safety, QMRA were performed was to
34
estimate burden of disease from E. coli from water vending machines. Triplicate drinking
35
water samples from water vending machines were collected from six sampling areas around
36
the city, analysed for E. coli, information of health symptoms and daily water intake was
37
obtained from 121 respondents by questionnaires. The results indicated the highest
38
numbers of E. coli levels were found in Seri Serdang (45 – 68 CFU/ 100 mL) and Taman
39
Pinggiran Putra (45 – 62 CFU/ 100 mL). Escherichia coli levels in drinking water samples
40
from water vending machines obtained from Seri Serdang, Taman Pinggiran Putra, Taman
41
Equine, Balakong and Serdang Jaya exceeded both Malaysian Drinking Water Quality and
42
WHO Drinking Water Quality guidelines. Reported health symptoms were only significantly
43
linked to brand which likely to be associated with regular maintenance of water vending
44
machine. All the drinking water samples from water vending machines except from Lestari
45
Perdana have exceeded the health based target outcomes by QMRA. Combination of
46
epidemiology
47
understanding of public health risks and gateway for a better management of water vending
48
machines.
and
quantitative
microbial
risk
assessment
have
provided
a
clear
49 50
Keywords: Public health; risk assessment; vending machine; drinking water
51 52 53 2
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1. Introduction
55
There has been an exponential increase in the public availability of drinking water vending
56
machines in urban areas, driven by modern working and public infrastructures, lifestyles
57
changes as well as drinking habits. Sales of water vending machines are also influenced by
58
local conditions such as ease of access to clean drinking water, convenience of the location,
59
human friendly services, low setup cost and labour (Schillinger & Du Vall Knorr 2015).
60
However, microbiological quality of the drinking water made available to the public from
61
vending machines has been severely put to the test lately. Several recent studies have
62
shown, not only in Malaysia but across the world, that water vending machine samples are
63
not necessarily pathogen-free, as there is a risk of contamination by fecal coliform bacteria
64
(Ee Yau et al., 2016; Schillinger & Du Vall Knorr, 2015; Simforian, Nonga, & Ndabikunze,
65
2015). Indeed, the quality of the drinking water obtained from vending machines depends
66
not only on water source, machine design and maintenance, but as reported by Dufour et
67
al.
68
maintenance process and in particular when handling the machine nozzle (Barrell, Hunter, &
69
Nichols, 2000; Dufour et al., 2003)
(2003) on the cleaning and hygiene standards practised during the machine's
70 71
Quantitative Microbial Risk Assessment (QMRA) is a technique used in burden of
72
disease estimation for particular pathogenic bacteria, and it would be suitable for studying
73
the quality of the drinking water obtained from vending machines. However, implementation
74
individual QMRA for each bacterial pathogen in turn would be highly impractical in terms of
75
time and money and would not necessarily yield the necessary information. Therefore, the
76
World Health Organization (2008) recommends the use of certain enteric bacteria in QMRAs
77
as indicators for the potential presence of pathogens. Escherichia coli is often used as a
78
reference bacterium for enteric bacterial pathogens and therefore an indicator of possible
79
faecal contamination (World Health Organization, 2016). The use of an indicator organism in
3
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QMRA introduces layers of uncertainty (e.g. model suitability, cohort representativeness),
81
which can be overcome by performing a Monte Carlo simulation. However, the Monte Carlo
82
simulation is a complicated mathematical technique, which limitedly especially in developing
83
and under-developed countries due to data availability. Therefore, the QRMA approach can
84
also be used by limiting the scope of an exposure scenario to overcome data limitations and
85
resources to estimate burden of disease from pathogenic bacteria and to ensure the results
86
will help to protect public health (Haas et al. 2014; U.S. Environmental Protection Agency
87
2002).
88 89
Investigations by The Straits Times (2014) indicated that 29 drinking water samples
90
taken from vending machines within cities of the Klang Valley of Malaysia were found to be
91
contaminated with E. coli, coliforms and Clostridium perfringens. This raised concerns about
92
Malaysia's drinking water quality and safety. There have been previous studies focused on
93
the microbiological quality of water vending machines in Malaysia (Dufour et al. 2003; Ee
94
Yau et al. 2016; Gurpreet et al. 2011). However, little information is available with regards
95
to QMRA in drinking water systems. Despite the fact that waterborne outbreaks linked to
96
drinking water supply have been well documented in Malaysia (Gurpreet et al. 2011) to
97
date, it appears that quantitative associated risk assessments related to drinking water have
98
not yet been reported. Therefore, the present study aimed to determine the frequency of E.
99
coli in drinking water samples from water vending machines in the city of Seri Kembangan
100
and to understand the associations between its presence and reported health symptoms and
101
daily water intake information. Ultimately, by applying a simplified QMRA, the intent of this
102
work was to estimate a preliminary burden of disease linked to water vending machines in
103
Seri Kembangan (Malaysia). To the best of the authors' knowledge, this study is believed to
104
be the first to perform a quantitative health risk assessment of the water obtained from
4
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vending machines, in the hope that it will help local authorities and other stakeholders to
106
understand any potential risk to public health.
107 108
2. Materials and Methods
109
2.1 Water Sampling and Analysis
110
A total of 90 drinking water samples were collected randomly in triplicates from 30 water
111
vending machines located in six areas (Balakong, Serdang Jaya, Seri Serdang, Taman
112
Pinggiran Putra, Taman Equine, Lestari Perdana) in Seri Kembangan, Selangor (Malaysia)
113
located at 3.03’N 101.7’E. These represented the most densely populated areas around Seri
114
Kembangan city. High density areas in Seri Kembangan also resulted in increased numbers
115
of water vending machines which mainly serve as drinking water sources due to their
116
convenience, easy accessibility and backup drinking water supply during watermains
117
interruptions (Zulzaha, 2015). A checklist was created for the purpose of recording the
118
observed working condition of each water vending machine at the time of sampling, with
119
the intent of obtaining information about its current surroundings, its direct environment,
120
and most recent maintenance date (Table 1). The drinking water samples from water
121
vending machines were collected using pre-sterilized Schott Duran bottles and analysed for
122
E. coli using membrane filtration technique (American Public Health Association, 1998). The
123
drinking water samples were placed immediately in an ice box, maintained between 1-4oC
124
and analyzed within 12 hours from time of collection. A total of 100 mL of drinking water
125
was passed through 0.45 μm Whatman membrane filters, placed on M-Lauryl Sulfate Agar
126
incubated for 4 hours at 30ºC and followed by 14 hours at 44ºC. Yellow colonies on the
127
filter membranes were counted as E. coli and reported as colony-forming units per 100 mL
128
(cfu/100 mL). All glassware was sterilized to avoid any contamination during sample
129
analysis. Additionally, drinking water samples were analysed in triplicates to ensure precision
130
and accuracy of the analysis process.
5
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2.2 Resident Questionnaires
133
Questionnaires were prepared and distributed to respondents who purchased water from
134
the designated vending machines. The questionnaire was used to obtain water intake
135
information and data regarding the presence or absence of health symptoms following the
136
consumption of water obtained from vending machines. The number of total respondents (n
137
= 121) was calculated according to Kirkwood & Sterne (2003) taking into account an
138
additional 20% for potential non-responses. The questionnaire survey was pretested on 60
139
residents of Sri Serdang (Malaysia) and found to have a Cronbach alpha value of 0.76, an
140
acceptable measure of internal consistency of the questionnaire. Sri Serdang area was
141
selected for the pretest session as respondents from this area had similar drinking water
142
characteristics with high numbers of vending machines. The respondents were contacted
143
after a week to obtain the accurate description, if any, of any health symptoms they may
144
have experienced.
145 146
Statistical analysis was performed using IBM SPSS Version 21. Descriptive statistics
147
were applied to determine variations in the levels of E. coli in drinking water samples, while
148
the Chi Square test was used to ascertain associations between reported health symptoms
149
and daily water intake information with a 5% level of significance.
150 151
2.3 Quantitative Microbial Risk Assessment
152
In this study, a simplified QMRA was performed as described by Haas et al. (2014) for
153
quantifying risk of infection. Disease burden was calculated based on the method described
154
by the World Health Organization (World Health Organization, 2016) and Howard et al.
155
(2006). A summary of the procedure can be found in Table 2.
156 6
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The indicator organism chosen for QMRA in this study was E. coli based its detection in
158
drinking samples from water vending machines. Since there is lack of specific pathogen data
159
from the water supplies, we had to use indicator organisms as surrogates in a similar
160
approach as the one applied by George et al. (2015) in quantifying microbial risk to estimate
161
burden of disease due to particular microbial pathogen exposure in drinking water systems.
162
In this study, the ratio used for generic E. coli: pathogenic E. coli was 1:0.08 (Haas et al.
163
2000). A log reduction value of 105 was applied for treatment effect based on published
164
reports on conventional treatment systems (World Health Organization 2008). The estimated
165
mean daily consumption of water from the vending machines obtained from the
166
questionnaires was 1.659 L/day. In order to get an estimate of the dose-response for this
167
study the Beta-Poisson model was chosen as it provides an effective microbial dose-
168
response relationship and designates the observed infectivity as a function of dosage (Haas
169
et al. 2000). Disease burden related to gastroenteritis was adapted from previous published
170
studies in the literature (Havelaar & Melse 2003) due to lack of disease occurrences and
171
infection data representing developing countries such as Malaysia. Since there are to date
172
very limited data available concerning exposed and susceptible populations in Seri
173
Kembangan, a susceptible fraction value of 10% was taken from Howard et al. (2006), and
174
the target reference level for tolerable risk for pathogenic E. coli was based on the value of
175
10-6 set by the WHO Health-Based Targets.
176 177
3. Results And Discussion
178
Data presented in Table 3 shows E. coli levels (CFU/100 mL) in sampling areas from around
179
the city of Seri Kembangan (Malaysia). The highest numbers of E. coli were found in Seri
180
Serdang (45 – 68 CFU/ 100 mL) and Taman Pinggiran Putra (45 – 62 CFU/ 100 mL). These
181
areas are surrounded by densely populated residential zones as they are located near
182
several higher institutions and industries. E. coli enumerations for water samples collected
7
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from vending machines in Taman Equine, Serdang Jaya and Balakong ranged from 1 to 31
184
CFU/ 100 mL); however, water samples from Lestari Perdana showed no detectable E. coli.
185
In general, drinking water samples from water vending machines of sampling areas (Seri
186
Serdang, Taman Pinggiran Putra, Taman Equine, Balakong and Serdang Jaya) exceeded the
187
Malaysian Drinking Water Quality and World Health Organization Drinking Water Quality
188
guidelines. Detection of E. coli in water vending machines in these areas can be associated
189
with regular maintenance and location (Table 1). Small number of samples were collected
190
from Lestari Perdana has also impacted the probability of E. coli detection. Inappropriate
191
maintenance/ cleaning can result in biofilm formation which may have contributed to the
192
presence of E. coli in water samples from water vending machines. Moreover, if the
193
machines are located near dirty drains or unsanitary environments this may also contribute
194
to bacteria contaminating samples. Contamination of the drinking water from these areas
195
may results from aerosols or carriage by insect vectors (flies and cockroaches) contacting
196
water vending machine compartments (Chaidez et al. 1999).
197 198
Microbiological analyses of water samples obtained from vending machines around
199
the world, have shown a large proportion to be contaminated with E.coli (Chaidez et al.
200
2016; Ebrahim et al. 2015; Ee Yau et al. 2016; Schillinger and Du Vall Knorr 2015). The
201
quality of drinking water obtained from such machines depends on water source, design and
202
maintenance of machines (Barrell et al. 2000). According to Ee Yau et al. (2016), bacteria
203
including E. coli, can grow on the filters of water vending machines reaching substantial
204
levels. Ee Yau et al. (2016) also reported that contamination with faecal bacteria may occur
205
due to unsanitary hygiene practices of people handling the machines. Furthermore, old
206
machines or those generally in poor working condition (corrosion) may be contributing
207
factors not only for bacterial contamination but may also results in toxic chemicals entering
208
the drinking water (Chaidez et al. 2016; Ebrahim et al. 2015). 8
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3.1 Consumer questionnaire
210
Results of the consumer water intake survey are presented in Table 4. Overall, 47.1% of
211
respondents consumed 5-7 cups of water daily in response to the recommendations of the
212
Malaysian Dietary Guidelines (2013), which propose that an adult should drink 6 to 8 glasses
213
of plain water daily to stay well hydrated and healthy. Most respondents bought water from
214
shops, 56% for accessibility reasons. In terms of quantities, 47.1% of respondents chose to
215
use 1.5 L bottles. The respondents were also asked about what they took into consideration
216
before buying water, and brand appeared to be the most important factor (38.0%), due to
217
their perception that only certain brands guarantee good drinking water quality. The
218
preferred brand was Dr Sukida (57.0%) while Sipsipwater (15.7%), Imtiyaaz Bio Energy
219
(14.9%), Water Drops (11.6%) and others (0.8%) were not as popular. Figure 2 shows the
220
respondents' perceived health symptoms following the consumption ofwater from water
221
vending machines. According to the questionnaire survey, 71.1% of respondents
222
experienced no deleterious health symptoms after consuming the water, while 3.3% of
223
respondents experienced gastroenteritis, which included symptoms such as vomiting,
224
diarrhoea, nausea, abdominal cramps or stomach aches. About 9.9% had experienced
225
headaches or dizziness while 15.7% of respondents said they experienced respiratory
226
symptoms such as coughs, sore throats or runny noses.
227 228
There was no association between reported health symptoms and quantity of daily
229
water intake or perception of water vending machines (Table 5). However, results showed
230
an association between reported health symptoms and preferred brand (Chi Square =
231
26.497, 12) (p value = 0.009). Preferred brand of water is likely to be associated with the
232
condition of water vending machines. Therefore those machines receiving regular
233
maintenance provide a better margin of safety since procedures generally include steps to
234
ensure compartments are clean and overall are more aesthetically pleasing. The lack of clear
9
ACCEPTED MANUSCRIPT 235
association between the few reported health symptoms and the consumption of water from
236
vending machines shown to be contaminated with E. coli may be linked to the increasing
237
diversity E. coli strains expressing virulence factors. E. coli are common occupants of the
238
intestinal tracts of healthy humans and animal and are known to play an important role in
239
luminal microbial flora stability and maintenance of normal intestinal homeostasis. However,
240
a small subset of pathogenic strains have been identified which cause a broad spectrum of
241
diseases when infecting the gastrointestinal and urinary tracts, as well as various other
242
organs in the body (Mainil 2013). In humans, pathogenic E.coli strains are generally
243
categorized as enteroinvasive, enterotoxigenic, enteropathogenic, enterohaemorrhagic,
244
enteroaggregative, or necrotoxigenic. Their pathogenicity is linked to several virulence
245
factors such as adhesins, which help them attach to host cells, reproduce and multiply, and
246
variety of toxins including shiga-toxins and haemolysins (Kaper, Nataro & Mobley, 2004;
247
Mainil, 2013).
248 249
According to Soller et al. (2016), a low frequency of health symptoms being
250
reported, coupled with unclear relationships between such symptoms or illness and E.coli
251
detected in drinking water does not guarantee that the water is microbiologically safe.
252
QMRA offers an alternative approach in terms of a quantitative measure to offer a more
253
robust estimation risk. Results for the QMRA conducted here for each sampling area of Seri
254
Kembangan city are given in Table 6. In general, the disease burden values showed that all
255
drinking water samples from water vending machines from the four sampling areas (Seri
256
Serdang, Taman Pinggiran Putra, Taman Equine, Balakong and Serdang Jaya) exceeded the
257
WHO guidelines for health based target outcomes. It is noted that there were number of
258
water vending machines in these areas were lacking in terms of maintenance service
259
information. The only area with QMRA results meeting the WHO guidelines for acceptable
260
microbiological quality was Lestari Perdana. Acceptable QMRA outcomes for Lestari Perdana
10
ACCEPTED MANUSCRIPT 261
may be related to information gather regarding regular machine maintenance and
262
cleanliness surrounding areas where the water vending machines were installed. It should
263
also be noted that only three water samples were collected from this area which would
264
impact the probability of E. coli detection.
265 266
Nevertheless, the overall results of this study imply that consumers of products from
267
current water vending machines may be at risk of gastrointestinal illness. These results are
268
in line with findings from other studies conducted in Mysore, India (George et al. 2015) and
269
Kampala, Uganda (Howard et al. 2006). Detection of E.coli in water vending machines is
270
most likely associated with poor machine maintenance by the vendor (Table 1).
271
Contamination is possibly due to biofilms on the tubes which in turn impacts drinking water
272
quality (Tsvetanova and Hoekstra 2012). Although the Ministry of Health (Malaysia) has
273
required all water vending machines to be licensed under Regulation 360C(4) of the Food
274
Regulations 1985, further strict actions and inspections need to take place (Hashim and
275
Yusop 2016). Further actions such as replacement of proper pipes and periodic inspection of
276
the water distribution systems are necessary for effective management of microbiologic
277
quality of water vending machines.
278 279
4. Study limitations
280
This study was the first to assess quantitative health based targets via QMRA involving
281
water vending machines; however QMRA findings here were based on several assumptions
282
and uncertainties due to limited availability of data on pathogenic E. coli, its fate and
283
transmission related to vending machine water. Therefore, detection of E. coli needs to be a
284
focal point for future QMRA studies in order to produce reliable and comparable data to
285
ensure this information is adequate for the risk mitigation. Correspondingly, Boone, Van der
286
Stede, Aerts, Mintiens, & Daube (2010) also recommended the importance of identifying the
11
ACCEPTED MANUSCRIPT 287
knowledge gap and ways to facilitate model improvement which should lead to more
288
realistic QMRA results and its implications. This research was conducted as a cross sectional
289
study from data collected from a population at a specific point in time. Therefore, there are
290
several potential factors which may influence E. coli levels in drinking water samples from
291
water vending machines, including seasonal patterns, daily or weekly effects, and long-term
292
trends. These factors must be controlled in order to understand the contamination of
293
drinking water from water vending machine associated with gastrointernal illness
294
(Blumenthal et al. 2001; Mann et al. 2007).
295 296
5. Conclusion
297
Viable E. coli were found in water samples from vending machines situated in five areas
298
surveyed (Seri Serdang, Taman Pinggiran Putra, Taman Equine, Balakong and Serdang
299
Jaya). The current epidemiological study found that there was no obvious association
300
between the presence of E. coli in drinking water and the reported health symptoms,
301
quantity of daily water intake or perception on water vending machines. However, there
302
appeared to be an association between reported health symptoms and preferred brand.
303
With respect to the QMRA, the disease burden values showed that all drinking water
304
samples from water vending machines from sampling areas (Seri Serdang, Taman Pinggiran
305
Putra, Taman Equine, Balakong and Serdang Jaya) exceeded the WHO guidelines for health
306
based targets. No detectable E. coli was found for drinking water samples from Lestari
307
Perdana may related with under-sampled (only 3 samples) and sampling was conducted
308
right after the maintenance process was completed. Although there are few assumptions
309
and limitations involving QMRA output, these preliminary findings have shown that the
310
general public should be aware of microbiological water quality from water vending
311
machines. These results are also critical for manufacturers to ensure regular maintenance of
12
ACCEPTED MANUSCRIPT 312
water vending machines is conducted to maintain quality and safety of drinking water their
313
vending machines.
314 315 316
Acknowledgments
317
The authors would like to thank the laboratory staff of the Department of Medical
318
Microbiology and Parasitology (Faculty of Medicine and Health Sciences, Universiti Putra
319
Malaysia) for their autoclave service. We thank two anonymous reviewers for their
320
constructive comments, which helped us to improve this manuscript.
321 322
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Highlights
Public health risk linked to microbial quality of drinking water from vending machines
Escherichia coli were found in drinking water from all five sampling areas
Significant association found between reported health symptoms and preferred brand
Only Lestari Perdana showed none for burden of disease estimation
SERDANG JAYA LESTARI PERDANA
Seri Kembangan
Sampling locations
Fig. 1 Drinking water sampling from water vending machines in Seri Kembangan area
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Percentange
120
80
Yes
84.3
71.1
28.9
20
3.3
0
497 498
90.1
60 40
496
No
96.7
100
None
9.9
Health Symptoms Headache, dizziness
Gastroenteritis
15.7
Respiratory symptoms
Fig. 2 Perceived health symptoms after respondents consumed drinking water from water vending machines (total respondents n = 121)
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Table 1. Water vending machines checklist 428 Water Vending Machine
Location
Environment
Condition
1. 2. 3. 4. 5. 6. 7. 8. 9.
Seri Serdang
Nearby dustbin Nearby dustbin Nearby drain Nearby dustbin Nearby drain Nearby dustbin and drain In laundry shop Nearby drain Nearby drain and dustbin
Good and well functioning Good and well functioning Good and well functioning Bit rusty and well functioning Good and well functioning Good and well functioning Rusty and not function well Good and well functioning Good and well functioning
Length since last service during sampling in February 2016 (days) 12 12 NA 79 486 12 NA NA 492
10.
Serdang Jaya
Nearby dustbin and workshop Nearby drain Nearby dustbin Nearby laundry shop Nearby drain Nearby dustbin
Good and well functioning
NA
Rusty and not well maintained Bit rusty and well functioning Rusty and well functioning Rusty and not function well Not function well and full with sticker
NA 15 5 NA NA
11. 12. 13. 14. 15. 16.
Lestari Perdana
Nearby drain
Good and well functioning
0
17. 18. 19. 20. 21. 22. 23.
Taman Pinggiran Putra
Nearby drain Nearby drain Nearby drain and dustbin Nearby drain Nearby clothing stores Nearby dustbin Nearby stores
Good and well functioning Rusty and not function well Good and well functioning Good and well functioning Good and well functioning Good and well functioning Good and well functioning
11 NA NA 6 6 6 1
24. 25.
Taman Equine
Nearby drain Nearby grocery stores
Good and well functioning Had bird droppings and well functioning Good and well functioning Good and well functioning Good and well functioning
0 30
26. 27. 28. 29. 30.
429 430 431 432
Nearby grocery stores Nearby drain Nearby dustbin and drain Balakong
Nearby drain and workshop Nearby drain and workshop
Rusty and not function well Full with sticker and not well maintained
NA NA 40 NA NA
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433
434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450
Table 2. Summary of equations applied for disease burden calculation Equation Drinking water quality (CD) Consumption of drinking water (V) Exposure by drinking water(E) Dose response (r) Risk of infection (P inf, d) Risk of infection (P inf, y)
Unit Organisms per liter Liters per day
Formula CR x (1 – PT) Estimated
Organisms per liter Probability of infection Per day Per year
Risk of diarrhoeal illness given infection (Pill/inf) Risk of diarrhoeal disease (Pill) Disease burden (db)
Probability of illness per infection
CD x V From literature Exr 1 – (1 - P inf, d) x 365 (Haas et al., 2014) From literature
Susceptible fraction (fs) Disease burden (db)/health outcome target (HT)
% of population DALY per year
Per year DALY per case
Pinf,y x Pill,inf Calculated from available data in literature From literature Pill x db x fs
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451
452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474
Table 3. E. coli colonies in sampling areas from Seri Kembangan city (Malaysia) Areas
Number of samples
Lestari Perdana Taman Pinggiran Putra Serdang Jaya Seri Serdang Balakong Taman Equine
3 21 18 27 6 15
E. coli level variation (CFU/ 100 mL) 0 45 - 62 10 - 21 45 - 68 15 - 31 1-6
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475 476
477
Table 4. Water intake information (n = 121) Water intake information Frequency of drinking water daily 1-2 cups 2-4 cups 5-7 cups 8-10 cups More than 10 cups
Number of respondents
Percentage (%)
2 19 57 28 15
1.7 15.7 47.1 23.1 12.4
Location of buying water Shops College Others
69 34 18
57.0 28.1 14.9
Quantity to buy water 500ml 1L 1.5L 3L 5L 10L
22 14 57 4 23 1
18.2 11.6 47.1 3.3 19.0 0.8
Consideration before buying water Price Brand Availability Don’t care
31 46 33 11
25.6 38.0 27.3 9.1
Prefer brand for buying water Desa Dr Sukida Imtiyaaz Bio Energy Sipsipwater RO water Water drops
1 69 18 19 14
0.8 57.0 14.9 15.7 11.6
Heard of news on water vending machines contamination No Yes
53 68
43.8 56.2
Perception on water vending machine Good Fair Very good Very bad Bad
65 41 4 3 8
53.7 33.9 3.3 2.5 6.6
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491 492
Table 5. Chi-square test of contingency between reported health symptoms and daily water intake. Variables None Daily water intake 1-2 cups 2-4 cups 5-7 cups 8-10 cups More than 10 cups
2 15 33 23 13
0 2 2 0 0
0 1 8 2 1
0 1 14 3 1
Preferred brand Desa Dr Sukida Imtiyaaz Bio Energy Sipsipwater Water drops
1 56 11 8 10
0 1 0 3 0
0 8 1 2 1
0 4 6 6 3
Perception on water vending machines Good Fair Best Bad Significant at p<0.05 493
Reported health symptoms Gastroentritis Headache, Respiratory dizziness symptoms
42 28 4 12
2 1 0 1
7 4 1 0
8 8 3 0
ᵡ2 (df)
p
14.951 (12)
0.244
26.497 (12)
0.009
9.068 (9)
0.431
494
Table 6. Quantitative Microbial Risk Assessment for E.coli in drinking water from water vending machines Taman Equine Raw water quality (Cr)
495
Serdang Jaya
Seri Serdang
Taman Pinggiran Putra
Balakong
Lestari Perdana
3
10
55
23
54
0
Treatment effect Drinking water quality (CD) Exposure by drinking water(E) Dose response (r)
0.999
0.999
0.999
0.999
0.999
0.999
3.0E-2 4.9E-3 1.0E-03
1.0E-2 1.66E-2 1.0E-03
5.5E-2 9.12E-2 1.0E-03
2.3E-2 3.8E-2 1.0E-03
5.4E-2 9.0E-2 1.0E-03
0 0 1.0E-03
Risk of infection (P
inf, d)
5.0E-06
1.7E-05
9.1E-05
3.8E-05
9.0E-05
0
Risk of infection (P
inf, y)
1.8E-3
6.0E-3
3.3E-2
1.4E-2
3.2E-2
0
2.5E-1
2.5E-1
2.5E-1
2.5E-1
2.5E-1
2.5E-1
4.5E-4 4.5E-01 1E-1
1.5E-3 4.5E-01 1E-1
8.2E-3 4.5E-01 1E-1
3.5E-3 4.5E-01 1E-1
8.0E-3 4.5E-01 1E-1
0 4.5E-01 1E-1
2.0E-05
6.8E-05
3.7E-04
1.6E-04
3.6E-04
0
Risk of diarrhoeal illness given infection (Pill/inf) Risk of diarrhoeal disease (Pill) Disease burden (db) Susceptible fraction (fs) Disease burden (db)/health outcome target (HT)