Microbial Quality of Ice Machines and Relationship to Facility Inspections in the Toledo, Ohio, Area.
Foodborne illnesses are estimated as annually responsible for 3,000 deaths and 128,000 hospitalizations in the U.S., which constitutes a significant public health threat (Centers for Disease Control and Prevention [CDC], 2011.) The causative agents responsible for foodborne illnesses frequently are not identified, with the Centers for Disease Control and Prevention (CDC) reporting that overall only 44% of foodborne disease cases have a known etiology. Of the cases for which the causative agents have been identified, norovirus was associated with 58% of the illnesses, and four bacteria species (Salmonella nontyphoidal, Clostridium perfringens, Campylobacter species, and Staphylococcus aureus) collectively were responsible for 33% of the illnesses. CDC further reported that the major types of foods associated with these illnesses were produce (46%), meat and poultry (22%), dairy and eggs (20%), and fish and shellfish (6.1%).
Health risks from contaminated ice rarely are reported, although evidence documented in the literature is sufficient to establish its potential for causing illness. For example, contaminated commercial ice has been implicated as a cause of Norwalk-like-viruses-related gastroenteritis on a cruise ship in Hawaii (Herwaldt et al., 1994). Another outbreak aboard a cruise ship was associated with consumption of ice contaminated by enterotoxigenic E. coli (ETEC). In that outbreak, water bunkered from Mexico or Guatemala was inadequately chlorinated and introduced ETEC into the ice machines (Koo et al, 2010).
Norovirus outbreaks have also been reported in several venues associated with ice. Contaminated water and ice from improperly set up and sanitized community dispensers caused an outbreak of norovirus gastroenteritis illness in a community in Arizona in 2004 (Reimus, Stratman, & Ludwig, 2004). Consumption of ice made from well water contaminated with sewage containing norovirus was responsible for an outbreak among football players during a game between the University of Pennsylvania and Cornell University in 1987 (Becker, Moe, Southwick, & MacCormack, 2000). Ice made using water contaminated with fecal material was a cause of norovirus outbreak in a resort town in Italy in 2002 (Boccia et al., 2002). Commercial ice made using environmentally contaminated water and/or inadequately treated water was a cause of diarrheagenic E. coli outbreak in a community in Brazil in 2004 (Falcao, Falcao, & Gomes, 2004). Ice contaminated with norovirus in restaurants provided further evidence of the potential for ice to be an important source of disease transmission (CDC, 2011).
Other studies not directly related to disease outbreaks show additional potential for contamination of ice that could lead to illness. A study at Taman University in Malaysia revealed the presence of fecal coliforms in about 36% of samples of ice cubes from 30 food service outlets (Mahat, Meor Ahmad, & Abdul Wahab, 2015). Mako and coauthors (2014) reported that 37% of their samples of ice bagged at retail sites and in ice from vending machines in Georgia contained an unsatisfactory level of coliform bacteria, and were significantly contaminated more frequently than ice cubes manufactured by companies monitored by the International Packaged Ice Association. Ice collected from retail points in Greece had large numbers of coliform and pathogenic strains of bacteria (Gerokomou et al, 2001). Another study reported that poor hygiene resulted in norovirus contamination of ice in hospital ice machines (Gebo et al, 2002). The viral load in the ice was considered large enough to cause illnesses in immune-compromised patients, but not in patients suffering from illnesses not related to immune suppression. Comparable results were found in other hospitals outside of the U.S. (Burnett, Weeks, & Harris 1994; Wilson, Hogg, & Barr, 1997).
Food service facilities regularly are licensed to operate following requirements established by each state, typically based on the Food and Drug Administration (FDA) Food Code. This code contains provisions related to the production and handling of ice at food service facilities. In Ohio, where this study was located, all food service facilities serving potentially hazardous foods--including ice--are required to obtain licenses. This requirement includes facilities in which ice is the only potentially hazardous food. In general, ice machine evaluations are limited to visual inspections, although such inspections might be inadequate for identifying the presence of pathogenic organisms (Kassa, Harrington, Bisesi, & Khuder, 2001).
Past work has established that ice machines have the potential for posing a significant risk of disease transmission, although ice machines have not been tested sufficiently to establish the magnitude of that risk. Our study explores this potential for risk through investigation of the microbial contamination of ice machines in food service facilities in the Toledo, Ohio, area. We also designed this study to provide information potentially linking ice machine contamination with public health protection practices as documented by food service facility inspection records.
Materials and Methods
We sampled ice machines in licensed food service facilities in Toledo, Ohio, for a variety of bacteria and fungi during the summer and fall of 2013. Although not inclusive of all potential types of contaminants (e.g., viruses), this examination should provide potentially useful information revealing the scope of contaminated ice machines regulated by a typical food service licensing program.
Facilities were selected through development of a study database drawing from the Toledo-Lucas County Health Department's (TLCHD) listing of 2,439 Risk Class 2, 3, and 4 food service facilities, as facilities with these risk classes can legally handle unpackaged ice cubes for service to consumers. The classification of facilities into different licensing categories is based on the relative health risk they pose to public health, with the higher classification numbers signifying a higher level of risk (Ohio Administrative Code, n.d.).
The TLCHD database was exported into an Excel spreadsheet and subjected to a "research randomizer" to select a potential sampling pool of 150 license numbers. Facilities from this initial pool were excluded if they did not produce ice during our sample collection and/ or walk-through inspection periods, if they had sealed ice making/dispensing systems, if they were permanently closed or changing their business plan before the end of the licensing period, if facility inspection reports were unclear, or if management was unwilling to participate. Based on these criteria, we included 115 facilities in this study.
At each food service facility, we collected swab samples from an ice bin wall, the ice scoop, and from the ice machine door gasket. Two TLCHD registered sanitarians working in the Food Protection Unit and trained in the sampling protocol collected the samples used in this study. For each facility, a sample collection kit was provided consisting of three tubes, each containing two sterile swabs and a screw-capped tube containing 1 mL of sterile phosphate buffered saline (PBS). Swabs were held in a plastic cap for each swab tube and the registered sanitarians handled only that cap during sampling.
Immediately prior to sampling, the swabs were moistened (not made dripping wet) by being touched to the surface of the PBS. After each sample had been collected, the registered sanitarians returned the swabs to the tubes and labeled the tubes with the establishment's health department license number and the area sampled (ice bin wall, ice scoop, or gasket.)
For the ice bin wall sample, an area of approximately 3 x 6 in. was swabbed below the normal level of the ice cubes. For the ice scoop sample, an area of approximately 3 x 6 in. was swabbed on the concave ice scoop surface. Areas were determined by visualizing a 3 x 6 in. sample area based on previous training. For these samples, the swabs were rubbed over the surface in at least three directions 60 degrees from each other, with the swabs turned over at least once during the sampling to use as much of the swab surface as possible. For the ice machine gasket, swabs were rubbed along the entire length of the gasket in the groove, and especially in any areas that appeared suspicious for mold growth and/or debris buildup. During each sampling day, the registered sanitarians prepared a field blank as a sterility check. They took the swabs out of the tube, moistened the swab with PBS, and immediately returned the swab to the tube.
Immediately after sampling, they placed the tubes in a cooler with frozen packs, and returned to the microbiology laboratory by the end of the day. Swabs were inoculated into isolation media that same day.
Plate media (tryptic soy agar [TSA], blood agar, Sabouraud agar, and MacConkey agar) were inoculated by rolling the swabs over approximately 20% of the medium surface--the "initial inoculum area." Sterile, disposable plastic loops were used to streak in parallel lines from that initial inoculum area into three other quadrants of the medium surface. The "field blank" swabs were cultured in the same manner as the samples. As a further sterility check of the PBS, each sampling day three or four used tubes of PBS were randomly selected and cultured.
The TSA, blood agar, and MacConkey agar plates were incubated aerobically at 35[degrees]C, and the Sabouraud agar plates were incubated at 25[degrees]C. After 2 and 3 days incubation, the TSA blood and MacConkey agar plates were examined for growth, and held for 5 days before reported as "no growth." The Sabouraud agar plates were examined after 2, 3, and 5 days and held for 7 days before reporting "no growth." For each organism isolated, a semiquantitative reporting protocol was followed (Table 1) as a measure of microorganism abundance.
The isolated fungi were identified to genus or species by standard mycological criteria based on growth rate, colony morphology, and pigmentation, plus microscopy of hyphae and sporing structures. Filamentous fungi with aseptate mycelia were identified as "zygomycete," with no further characterization as to genus. "Unidentified fungus" were those in which sporulation was not observed on the initial Sabouraud agar isolation medium or after subculture to potato dextrose agar. Nonpigmented yeast-like organisms were subcultured to rice extract agar with 0.1% Tween 80 and observed for pseudohyphae production at room temperature. If pseudohyphae were produced, the isolate was identified as a Candida species; if no pseudohyphae were seen, it was categorized as "yeast/yeast-like."
The protocol for identifying bacteria is summarized in Table 2 (see Kassa et al., 2001, for additional detail.)
All of the food service operations studied had microbial growth on at least one of the sampling sites. In general, the microorganisms were nonpathogenic types characteristically found in fecal flora, in water, on human skin, on mucus membranes, and in environmental air and dust. A listing of the prevalence of isolated organisms is provided in Table 3.
The amount of contamination present as a function of sampling site (ice bin wall, ice scoop, and gasket) was examined as a measure of relative risk. The presence and relative abundance (determined by measuring growth on a scale of 0 to 4 as described in Table 1) of fungi and of bacteria in general varied significantly as a function of the location (ice bin wall, ice scoop, or gasket), with the largest amount of fungi and bacteria found on the gaskets (Table 4.) The only exception to this pattern was in Class 2 food service establishments, for which no significant difference was evident.
To build foundational understanding of possible differences in microbial-based risk as a function of different types of food service establishments, we examined the number and type of food service violations recorded during the previous inspection by the health department (Table 5). Analysis of variance revealed a significant difference between the facilities in the three classifications (p < .001). Differences between classifications 2 and 3 were least pronounced, with a significant difference between critical violations (p = .008), but not between noncritical violations (p = .127). Class 4 facilities had the greatest incidence of critical and noncritical violations.
In contrast to the differences found between bacteria and fungi levels as a function of sampling site (ice bin wall, ice scoop, and gasket), no differences were found between relative abundance as a function of facility classification (Table 5.)
To explore possible relationships between compliance with overall food safety practices and presence of fungi and bacteria, we looked for possible relationships between citations issued at the previous inspection by the health department and the relative abundance of fungi and bacteria. The relative abundance of fungi and bacteria, respectively, found as a total from the three sampling points (ice bin wall, ice scoop, and gasket) and the total number of violations is shown in Figures 1 and 2. These figures clearly illustrate the lack of relationship between inspection results and the relative abundance of fungi or bacteria at any of the three individual sampling sites.
Discussion and Conclusions
Ice machine contact surfaces typically harbored bacteria and fungi--thus providing a potential source of contamination of ice used for human consumption. Microbial populations were not routinely of a pathogenic origin, suggesting that most ice from ice machines (assuming the origin of the water used to make the ice is from a municipal water supply) will not present a health threat. The presence of nonpathogenic organisms, however, provides evidence that the ice machine environment can support microbial pathogenic populations should they be introduced. Coupled with evidence from the literature that reports on sporadic disease outbreaks resulting from contamination of ice from ice machines, our data suggest that the health risk might not be inconsequential from ice machines associated with food service facilities.
Inspections of food service facilities typically vary as a function of associated risk. In Toledo-Lucas County, the Class 4 food service facilities averaged significantly more violations per inspection than in the other food service classes. Typically, the greater size and complexity in operations of Class 4 facilities require that inspectors spend more time there than in lower class facilities, perhaps increasing the likelihood of revealing code violations. Alternatively or additionally, a greater number of violations might be found at Class 4 facilities because of inspectors' underlying awareness of a higher risk potential at these facilities, which thus increases--either intentionally or inadvertently--the intensity of their inspections. The inspection results, however, did not appear related to ice machine microbial populations. Overall, facility compliance with food safety standards does not appear to predict the level of risk from contamination of the facility's ice machines.
The evidence in the literature associating ice machines with disease outbreaks coupled with the results of this study suggest that problems from food service facilities that lead to disease outbreaks will not be predictable (and thus not preventable) following standard inspection practices. Even though foodborne disease outbreaks are most likely to occur in food service operations with chronically high inspection violations (Kassa et al., 2001), results do not indicate this association with ice machines. Rather, no clear relationship was found between inspection results and microbial populations in ice machines.
Instead, preventing ice machines from becoming fomites might be less a matter of inspection than of maintenance and prevention. Standards for cleaning and disinfection are not part of standard food service facility \operations, although the FDA Food Code (2013) does specify that "ice makers, and ice bins must be cleaned on a routine basis to prevent the development of slime, mold, or soil residues that may contribute to an accumulation of microorganisms." Similarly, sanitation performance recommendations are provided in the National Sanitation Foundation [NSF] International Standards for Automatic Ice Making Equipment (NSF International, 2009). Ice machine gaskets appear to be at particular risk of contamination and therefore need special attention, perhaps reflecting their vulnerability to hand contact when ice is removed from the bin, their exposure to warmer temperatures and general air contact due to their location at the ice machine entrance, and their difficulty of cleaning compared to hard metal surfaces.
This study did not reveal a smoking gun of ice machines presenting a large threat to public health. It did, however, reveal that ice machines present some risk of foodborne outbreak, and that the risk is not being addressed by current inspection practices. Further research should be useful in determining how to better minimize microbial contamination of ice machine surfaces through practical and routine interventions.
Please Note: Illustration(s) are not available due to copyright restrictions.
Acknowledgements: This research was assisted by the Environmental Health Division of TLCHD. We thank the registered sanitarians and their leadership for conducting the sampling, providing access to inspection reports, and contributing insight and expertise.
Corresponding Author: Gary S. Silverman, Professor, Department of Public Health Sciences, College of Health and Human Services, University of North Carolina at Charlotte, 9702 University City Boulevard, Charlotte, NC 28223. E-mail: firstname.lastname@example.org.
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Hailu Kassa, MSOH, MPH, PhD
Bowling Green State University
Brian Harrington, MPH, PhD
University of Toledo
Karim Baroudi, MPH, RS, REHS
Hancock Public Health
Gary S. Silverman, D Env, RS
University of North Carolina at Charlotte
Caption: FIGURE 1 Relative Abundance of Fungi Found at the Three Sampling Sites (Ice Bin Wall, Ice Scoop, and Gasket) and Number of Violations Cited at That Facility During Previous Inspection
Caption: FIGURE 2 Relative Abundance of Bacteria Found at the Three Sampling Sites (Ice Bin Wall, Ice Scoop, and Gasket) and Number of Violations Cited at That Facility During Previous Inspection
TABLE 1 Reporting Protocol Assigned Growth # Organism Growth Characteristic (Relative Abundance) 0 Organism growth absent 1 Organism growth only in initial inoculum area 2 Organism growth in initial and second quadrants 3 Organism growth in first three quadrants 4 Organism growth in all quadrants TABLE 2 Identification Protocol for Bacteria Type Identification Staph/micro Gram-positive cocci; catalase positive; either singly, in clusters, or packets. Primarily would be staphylococci or micrococci. G+ R spores (Bacillus sp.) Gram-positive rods with endospores. Member of the genus Bacillus (and the newly created genera for aerobic endospore formers). G+ R diphth/no spores Gram-positive rods with diphtheroid morphology and no endospores. G+ R branching Gram-positive rods with branching. Member of the Nocardia/Streptomyces group. E. coli Identified by its characteristic growth on MacConkey agar, indole positive, cytochrome oxidase negative. Serratia marcescens Gram-negative enteric rod with characteristic red pigment (possibly one or two other Serratia spp. that have red pigmented colonies). EGNR oxid -ve F lact + Enteric gram-negative rod, oxidase negative, indole-negative fermenter of carbohydrates, lactose fermentation (on MacConkey agar) positive. Member of the Enterobacteriaceae family. Isolates encountered here have pink (slightly acidic) mucoid colonies on MacConkey agar and were most likely in the Klebsiella/Enterobacter group. These members of the Enterobacteriaceae, together with E. coli, are called coliforms. EGNR oxid -ve F lact -ve Enteric gram-negative rod, oxidase negative, no acid from lactose on MacConkey agar but fermenter of glucose in oxidation/fermentation (O/F) medium. Member of the Enterobacteriaceae family. EGNR oxid -ve non-F Enteric gram-negative rod, oxidase negative, no acid from lactose on MacConkey agar, no fermentation of glucose in O/F medium. Not a member of the Enterobacteriaceae family. EGNR oxid + non-F Enteric gram-negative rod, oxidase positive, no acid from lactose on MacConkey agar, no fermentation of glucose in O/F medium. Not a member of the Enterobacteriaceae family. Probably a pseudomonad or related genus. Pseudomonas aeruginosa Identified by its characteristic growth, pigment, colony appearance, and odor on TSA blood and MacConkey agars. TABLE 3 Number of Sites With Isolated Organisms by Facility Class and Location Class 2 Class 3 Facilities Facilities (n = 20) (n = 53) IW SP GT IW SP GT Yeast Aureobasidium sp. 4 1 11 5 3 10 Aspergillus niger 0 0 2 2 2 7 Aspergillus sp. (not niger) 1 2 2 3 2 10 Penicillium sp. 1 0 2 3 1 4 Alternaria sp. 4 1 4 6 7 14 Rhodotorula sp. 3 5 10 16 12 19 Yeast/yeast-like 1 1 2 1 1 3 Candida sp. 1 0 0 3 3 4 Fusarium sp. 1 0 1 0 1 1 Zygomycetes 0 0 0 0 1 1 Cladosporium sp. 0 0 6 4 2 5 Unidentified fungus 0 0 0 2 1 3 Bacteria Staph/micro 1 3 5 22 14 16 Strep not D 0 0 0 0 0 0 G+ R spores (Bacillus sp.) 10 11 10 23 16 25 G+ R diphth/no spores 1 2 2 6 2 6 E. coli 0 0 0 0 1 0 Serratia marcescens 0 1 0 0 0 0 EGNR oxid -ve F lact + 2 2 2 2 1 4 EGNR oxid -ve F lact -ve 0 0 0 0 0 0 EGNR oxid -ve non-F 0 1 2 2 2 4 EGNR oxid +ve non-F 1 3 3 7 6 12 Pseudomonas aeruginosa 0 1 0 1 0 0 Class 4 All Facilities Facilities (n = 42) (N = 115) IW SP GT IW SP GT Yeast Aureobasidium sp. 6 1 11 15 5 32 Aspergillus niger 1 3 2 3 5 11 Aspergillus sp. (not niger) 0 1 1 4 5 13 Penicillium sp. 0 0 2 4 1 8 Alternaria sp. 7 2 12 17 10 30 Rhodotorula sp. 12 15 24 31 32 53 Yeast/yeast-like 1 2 2 3 4 7 Candida sp. 3 1 2 7 4 6 Fusarium sp. 0 0 0 1 1 2 Zygomycetes 0 0 1 0 1 2 Cladosporium sp. 2 0 3 6 2 14 Unidentified fungus 0 1 4 2 2 7 Bacteria Staph/micro 9 11 12 32 28 33 Strep not D 0 0 0 0 0 0 G+ R spores (Bacillus sp.) 20 15 22 53 42 57 G+ R diphth/no spores 2 2 1 9 6 9 E. coli 0 0 0 0 1 0 Serratia marcescens 0 0 0 0 1 0 EGNR oxid -ve F lact + 2 0 5 6 3 11 EGNR oxid -ve F lact -ve 0 0 0 0 0 0 EGNR oxid -ve non-F 0 1 2 2 4 8 EGNR oxid +ve non-F 3 3 5 11 12 20 Pseudomonas aeruginosa 0 0 1 1 1 1 IW = ice bin wall; SP = ice scoop; GT = gasket. TABLE 4 Mean Bacteria and Fungi Relative Abundance at Each Sampling Location Within Ice Machine Organism Food # p-Value * Service Class Total bacteria All 115 .001 Total fungi All 115 .001 Total bacteria 2 20 .122 Total fungi 2 20 .001 Total bacteria 3 53 .004 Total fungi 3 53 .001 Total bacteria 4 42 .026 Total fungi 4 42 .001 Organism Gasket Ice Bin Wall Ice Scoop Mean SD Mean SD Mean SD Total bacteria 2.13 2.067 1.58 1.487 1.16 1.335 Total fungi 3.07 3.054 1.19 1.648 0.71 0.856 Total bacteria 2.55 2.585 1.30 1.455 1.55 1.791 Total fungi 3.90 2.751 0.95 1.146 0.70 0.865 Total bacteria 2.30 2.198 1.91 1.735 1.13 1.415 Total fungi 2.72 3.301 1.11 1.565 0.75 0.83 Total bacteria 1.71 1.535 1.31 1.047 1.00 0.911 Total fungi 3.12 2.847 1.40 1.939 0.67 0.902 * Determined by analysis of variance (ANOVA). SD = standard deviation. TABLE 5 Mean Bacteria and Fungi Relative Abundance at Each Food Service Classification Organism Food p-Value * Class 2 Service Facilities Class (n = 20) Mean SD Total bacteria All .065 1.80 2.040 Total fungi All .593 1.85 2.291 Total bacteria Gasket .237 2.55 2.585 Total fungi Gasket .336 3.90 2.751 Total bacteria Ice scoop .314 1.55 1.791 Total fungi Ice scoop .883 0.70 0.865 Total bacteria Ice bin wall .970 1.30 1.455 Total fungi Ice bin wall .539 0.95 1.146 Organism Class 3 Class 4 Facilities Facilities (n = 53) (n = 42) Mean SD Mean SD Total bacteria 1.78 1.865 1.34 1.221 Total fungi 1.53 2.313 1.73 2.285 Total bacteria 2.30 2.198 1.71 1.535 Total fungi 2.72 3.301 3.12 2.847 Total bacteria 1.13 1.415 1.00 0.911 Total fungi 0.75 0.830 0.67 0.902 Total bacteria 1.91 1.735 1.31 1.047 Total fungi 1.11 1.565 1.40 1.939 * Determined by analysis of variance (ANOVA). SD = standard deviation.
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|Title Annotation:||ADVANCEMENT OF THE SCIENCE|
|Author:||Kassa, Hailu; Harrington, Brian; Baroudi, Karim; Silverman, Gary S.|
|Publication:||Journal of Environmental Health|
|Date:||Nov 1, 2017|
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