Donald W. Schaffner

Quantification and variability analysis of bacterial cross-contamination rates in common food service tasks.

This study investigated bacterial transfer rates between hands and other common surfaces involved in food preparation in the kitchen. Nalidixic acid-resistant Enterobacter aerogenes B199A was used as a surrogate microorganism to follow the cross-contamination events. Samples from at least 30 different participants were collected to determine the statistical distribution of each cross-contamination rate and to quantify the natural variability associated with that rate. The transfer rates among hands, foods, and kitchen surfaces were highly variable, being as low as 0.0005% and as high as 100%. A normal distribution was used to describe the variability in the logarithm of the transfer rates. The mean +/- SD of the normal distributions were, in log percent transfer rate, chicken to hand (0.94 +/- 0.68), cutting board to lettuce (0.90 +/- 0.59), spigot to hand (0.36 +/- 0.90), hand to lettuce (-0.12 +/- 1.07), prewashed hand to postwashed hand (i.e., hand washing efficiency) (-0.20 +/- 1.42), and hand to spigot (-0.80 +/- 1.09). Quantifying the cross-contamination risk associated with various steps in the food preparation process can provide a scientific basis for risk management efforts in both home and food service kitchens.

Glove Barriers to Bacterial Cross-Contamination between Hands to Food

Human hands are an important source of microbial contamination of foods. However, published data on the effectiveness of handwashing and glove use in a foodservice setting are limited. Bacterial transfer through foodservice quality gloves was quantified using nalidixic acid-resistant Enterobacter aerogenes (a nonpathogenic surrogate with attachment characteristics similar to Salmonella). Five transfer rates were determined: chicken to bare hand, chicken to hand through gloves, bare hand to lettuce, hand to lettuce through gloves (with low inoculum on hands), and hand to lettuce through gloves (with high inoculum on hands). At least 30 observations were made for each percent transfer rate using 30 individual volunteers. The logarithm of percent transfer data were then fit to distributions: chicken to bare hand, normal (0.71, 0.42); chicken to hand through gloves, gamma (5.91, 0.40, -5.00); bare hand to lettuce, logistic (1.16, 0.30); hand to lettuce through gloves (low inoculum), normal (0.35, 0.88); hand to lettuce through gloves (high inoculum), normal (-2.52, 0.61). A 0.01% transfer was observed from food to hands and from hands to food when subjects wore gloves and a 10% transfer was observed without a glove barrier. These results indicate that gloves are permeable to bacteria although transfer from hands to food through a glove barrier was less than without a glove barrier. Our results indicate that gloves may reduce both bacterial transfer from food to the hands of foodservice workers and in subsequent transfer from hands back to food.

Food safety self-reported behaviors and cognitions of young adults : Results of a national study

With limited opportunities to learn safe food handling via observation, many young adults lack the knowledge needed to keep them safe from foodborne disease. It is important to reach young adults with food safety education because of their current and future roles as caregivers. With a nationwide online survey, the demographic characteristics, self-reported food handling and consumption behaviors, food safety beliefs, locus of control, self-efficacy, stage of change, and knowledge of young adults with education beyond high school (n = 4,343) were assessed. Young adults (mean age, 19.92 +/- 1.67 SD) who participated were mainly female, white, never married, and freshmen or sophomores. Participants correctly answered 60% of the knowledge questions and were most knowledgeable about groups at greatest risk for foodborne disease and least knowledgeable about common food sources of foodborne disease pathogens. They reported less than optimal levels of safe food handling practices. Young adults generally had a limited intake of foods that increase the risk of foodborne disease, positive food safety beliefs, an internal food safety locus of control, and confidence in their ability to handle food safely, and they were contemplating an improvement in, or preparing to improve, their food handling practices. Females significantly outperformed males on nearly all study measures. Future food safety educational efforts should focus on increasing knowledge and propelling young adults into the action stage of safe food handling, especially males. Efforts to improve knowledge and, ultimately, food safety behaviors are essential to safeguard the health of these young adults and enable them to fulfill the role of protecting the health of their future families.

The survival of foodborne pathogens during domestic washing-up and subsequent transfer onto washing-up sponges, kitchen surfaces and food.

In this study, the survival of Salmonella, Campylobacter and Escherichia coli O157: H7, when exposed to a range of constant temperatures (47-60 degrees C), in hard or soft water, in the presence/absence of detergent (0-0.3%) and organic matter, and during drying, was investigated. Further experiments used a washing-up process simulation, where soiled dishes contaminated with bacteria were washed in a bowl of warm water containing detergent. In addition, this study considered the risk of bacterial transfer onto (1) sterile dishes and sponges via contaminated water, (2) kitchen surfaces wiped with a contaminated sponge, (3) items placed in direct contact with a contaminated kitchen surface, (4) food placed on a contaminated dish or (5) dishes from contaminated food. A proportion of dishes remained contaminated with all pathogen types after a typical washing-up. Water hardness did not appear to affect survival. E. coli, and to a lesser extent Salmonella, survived towel- or air-drying on dishes and after towel-drying the cloth became contaminated on every occasion, regardless of the test organism. A proportion of sterile dishes washed after contaminated dishes became contaminated with pathogens but transfer from dishes onto food was rare. Washing-up sponges frequently became contaminated with pathogens. The results of this study highlight the potential for survival and cross contamination of food borne pathogens in the kitchen environment.

Modeling the effect of temperature on the growth rate and lag time of Listeria innocua and Listeria monocytogenes.

Several mathematical models which predict growth rate and lag time as a function of temperature were compared. The growth rate and lag time of Listeria innocua PFEI and Listeria monocytogenes Scott A PFEI were determined in brain heart infusion broth between 275 and 319 K. TableCurve 3.01 was used to fit model parameters to the L. monocytogenes data and to evaluate growth rate and lag time models. The growth rate models were validated using L. monocytogenes data from real dairy food systems. L. innocua grew faster than L. monocytogenes at temperatures below 315 K and grew slower than L. monocytogenes at temperatures higher than 315 K. At temperatures below 281 K, the lag time of L. monocytogenes was longer than that of L. innocua . The r2 and F values show that the 4-parameter growth rate models fit the data better than the 6-parameter models. The 4-parameter Zwietering Square Root Model gives the best fit of all the models used to predict growth rate. The 2-parameter models predict lag time better than the models containing more parameters. The 2-parameter Square Root Model gives the best fit of all the models evaluated when a traditional method of determining lag time is used. The 2-parameter New Model gives the best fit of all the models, when the Solberg method of determining lag time is used. Four growth rate models are not only suitable for modeling the growth rate of L. monocytogenes in brain heart infusion broth but are also suitable for modeling its growth rate in the selected real dairy food systems.

Comparison of Logistic Regression and Linear Regression in Modeling Percentage Data

ABSTRACT Percentage is widely used to describe different results in food microbiology, e.g., probability of microbial growth, percent inactivated, and percent of positive samples. Four sets of percentage data, percent-growth-positive, germination extent, probability for one cell to grow, and maximum fraction of positive tubes, were obtained from our own experiments and the literature. These data were modeled using linear and logistic regression. Five methods were used to compare the goodness of fit of the two models: percentage of predictions closer to observations, range of the differences (predicted value minus observed value), deviation of the model, linear regression between the observed and predicted values, and bias and accuracy factors. Logistic regression was a better predictor of at least 78% of the observations in all four data sets. In all cases, the deviation of logistic models was much smaller. The linear correlation between observations and logistic predictions was always stronger. Validation (accomplished using part of one data set) also demonstrated that the logistic model was more accurate in predicting new data points. Bias and accuracy factors were found to be less informative when evaluating models developed for percentage data, since neither of these indices can compare predictions at zero. Model simplification for the logistic model was demonstrated with one data set. The simplified model was as powerful in making predictions as the full linear model, and it also gave clearer insight in determining the key experimental factors.

Quantitative assessment of the microbial risk of leafy greens from farm to consumption: preliminary framework, data, and risk estimates.

This project was undertaken to relate what is known about the behavior of Escherichia coli O157:H7 under laboratory conditions and integrate this information to what is known regarding the 2006 E. coli O157:H7 spinach outbreak in the context of a quantitative microbial risk assessment. The risk model explicitly assumes that all contamination arises from exposure in the field. Extracted data, models, and user inputs were entered into an Excel spreadsheet, and the modeling software @RISK was used to perform Monte Carlo simulations. The model predicts that cut leafy greens that are temperature abused will support the growth of E. coli O157:H7, and populations of the organism may increase by as much a 1 log CFU/day under optimal temperature conditions. When the risk model used a starting level of -1 log CFU/g, with 0.1% of incoming servings contaminated, the predicted numbers of cells per serving were within the range of best available estimates of pathogen levels during the outbreak. The model predicts that levels in the field of -1 log CFU/g and 0.1% prevalence could have resulted in an outbreak approximately the size of the 2006 E. coli O157:H7 outbreak. This quantitative microbial risk assessment model represents a preliminary framework that identifies available data and provides initial risk estimates for pathogenic E. coli in leafy greens. Data gaps include retail storage times, correlations between storage time and temperature, determining the importance of E. coli O157:H7 in leafy greens lag time models, and validation of the importance of cross-contamination during the washing process.

Modeling Yeast Spoilage in Cold-Filled Ready-To-Drink Beverages with Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Candida lipolytica

ABSTRACT Mathematical models were developed to predict the probability of yeast spoilage of cold-filled ready-to-drink beverages as a function of beverage formulation. A Box-Behnken experimental design included five variables, each at three levels: pH (2.8, 3.3, and 3.8), titratable acidity (0.20, 0.40, and 0.60%), sugar content (8.0, 12.0, and 16.0 °Brix), sodium benzoate concentration (100, 225, and 350 ppm), and potassium sorbate concentration (100, 225, and 350 ppm). Duplicate samples were inoculated with a yeast cocktail (100 μl/50 ml) consisting of equal proportions of Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Candida lipolytica (∼5.0 × 104 CFU/ml each). The inoculated samples were plated on malt extract agar after 0, 1, 2, 4, 6, and 8 weeks. Logistic regression was used to create the predictive models. The pH and sodium benzoate and potassium sorbate concentrations were found to be significant factors controlling the probability of yeast growth. Interaction terms for pH and each preservative were also significant in the predictive model. Neither the titratable acidity nor the sugar content of the model beverages was a significant predictor of yeast growth in the ranges tested.

Comparison of food safety cognitions and self-reported food-handling behaviors with observed food safety behaviors of young adults

Background/Objective:Developing tailored and effective food safety education for young adults is critical given their future roles as caregivers likely to be preparing food for populations who may be at greater risk for foodborne disease (FBD). The objective of this study was to examine the relationship between food safety self-reported food-handling behaviors and cognitions of young adults to observed food-handling behaviors.Subjects/Methods:Participants were 153 young adults (mean age 20.74±1.30 s.d.) attending a major American university. Each prepared a meal under observation in a controlled laboratory setting, permitted researchers to observe their home kitchen and completed an online survey assessing food safety knowledge, behavior and psychosocial measures. Descriptive statistics were generated for participants’ self-reported food-handling behaviors, psychosocial characteristics, knowledge, food preparation observations and home kitchen observations. Determinants of compliance with safe food-handling procedures while preparing a meal and home food storage/rotation practices were identified using backward regression models.Results:Participants engaged in less than half of the recommended safe food-handling practices evaluated and correctly answered only two-thirds of the food safety knowledge items. They reported positive food safety beliefs and high food safety self-efficacy. Self-reported compliance with cross-contamination prevention, disinfection procedures and knowledge of groups at greatest risk for FBD were the best measures for predicting compliance with established safe food-handling practices.Conclusion:Food safety education directed toward young adults should focus on increasing awareness of FBD and knowledge of proper cross-contamination prevention procedures to help promote better compliance with actual safe food handling.

Staphylococcus aureus Growth Boundaries: Moving towards Mechanistic Predictive Models Based on Solute-Specific Effects

ABSTRACT The formulation of shelf-stable intermediate-moisture products is a critical food safety issue. Therefore, knowing the precise boundary for the growth-no-growth interface of Staphylococcus aureus is necessary for food safety risk assessment. This study was designed to examine the effects of various humectants and to produce growth boundary models as tools for risk assessment. The molecular mobility and the effects of various physical properties of humectants, such as their glass transition temperatures, their membrane permeability, and their ionic and nonionic properties, on S. aureus growth were investigated. The effects of relative humidity (RH; 84 to 95%, adjusted by sucrose plus fructose, glycerol, or NaCl), initial pH (4.5 to 7.0, adjusted by HCl), and potassium sorbate concentration (0 or 1,000 ppm) on the growth of S. aureus were determined. Growth was monitored by turbidity over a 24-week period. Toxin production was determined by enterotoxin assay. The 1,792 data points generated were analyzed by LIFEREG procedures (SAS Institute, Inc., Cary, N.C.), which showed that all parameters studied significantly affected the growth responses of S. aureus. Differences were observed in the growth-no-growth boundary when different humectants were used to achieve the desired RH values in both the absence and the presence of potassium sorbate. Sucrose plus fructose was most inhibitory at neutral pH values, while NaCl was most inhibitory at low pH values. The addition of potassium sorbate greatly increased the no-growth regions, particularly when pH was <6.0. Published kinetic growth and survival models were compared with boundary models developed in this work. The effects of solutes and differences in modeling approaches are discussed.