Listeria monocytogenes Prevalence and Level in Ready-to-eat Meat and Poultry deli meat

Get Complete Project Material File(s) Now! »

Chapter 2. Listeria monocytogenes Prevalence and Level in Ready-to-eat Meat and Poultry deli meat


The presence and level of L. monocytogenes in ready-to-eat (RTE) meat and poultry products was determined using data from a study conducted by the National Alliance for Food Safety and Security (NAFFS) (6). The data collected in this study were also used in calculating the comparative risk ratio for listeriosis in retail-sliced versus prepackaged ready-to-eat meat and poultry products.

Materials and Methods

Data Collection.

The sampling group comprised four designated sites in the Foodborne Disease Active Surveillance Network (FoodNet). These were Northern California (CA), Georgia (GA), Minnesota (MN), and Tennessee (TN). Sampling was weighted by the populations in counties so that exposure could be estimated. Approximately 75% of shopping is done at major supermarket chains and 25% is done at other grocers, such as independent retailers (14). The number of samples collected from supermarkets versus independent retailers was weighted accordingly. Also, approximately 50% of consumers purchase RTE meat products that are sliced at delicatessens with the remainder purchasing sliced prepackaged products (1). The relative number of samples between prepackaged and retail-sliced was therefore kept approximately equal as part of the sampling design. Sample data were encoded by the researchers to prevent identification of the store.
Approximately 2,000 samples (125 grams each) were analyzed from each of the four designated sites, with approximately equal numbers of retail-sliced and prepackaged samples, and a small number of intact chubs or logs. Chubs data not included in this analysis. The sampling protocol was designed to allow for statistically valid comparisons among sites, RTE products type, and retail-sliced versus prepackaged, assuming an α = 0.05 and a 90% power of detecting a difference of 2% in the comparison of binomial proportions.
The following product types were sampled: cured poultry, uncured poultry, pork, and beef. Approximately 1,000 samples of each product type were analyzed to support conclusions at the desired level of certainty. Use of any growth inhibitors was noted at the time of sample collection. Specific instructions were provided for sample collectors, including the product category, the number of samples of each type of product to be obtained, size of the sample to be purchased, and how to choose, collect, hold and transport the sample.
Sample collection was standardized to maintain consistency. Sampling and laboratory analyses followed standard laboratory practices. These included temperature monitoring during shipment, chain of custody documentation, aseptic transfer and handling within the laboratory, and initiating analyses within 24 hours of receipt of sample. The laboratories were instructed to discard any sample with package damage such that the microbiological integrity of the sample was not compromised. Samples not meeting quality control requirements were noted and discarded. The FSIS standard laboratory method for L. monocytogenes detection was implemented by the laboratories for use in this study. All samples were tested for the presence of L. monocytogenes by inoculation in UVM broth followed by Fraser broth then modified Oxford (MOX) agar. Original samples were saved in case the sample was positive so that the concentration of L. monocytogenes could be quantified in cfu’s per gram. Positive samples were quantified using a FSIS protocol 9-tube Most Probable Number (MPN) method with a reported detection limit of 0.3 MPN/gram.
Samples were assigned codes and the following product information recorded: sampling location (FoodNet site along with producer information, retailer’s name, and location of purchase), date of receipt at the laboratory, whether the sample appeared to be packaged in-store or prepackaged, and the use-by or sell-by date. Any store information or identifiers were removed prior to transfer to FSIS.

Statistical Analyses

Statistical analyses were performed using Number Cruncher Statistical Systems (NCSS) 2001 (15) and R version 2.6.1 (25). For statistical tests, p values less then 0.05 were considered statistically significant, and p values between 0.05 and 0.10 were considered marginally significant.
Data were analyzed in a variety of ways. The prevalence of L. monocytogenes among retail-sliced and prepackaged samples were analyzed by sampling site, product type, store type, time of day (morning or afternoon), and quarter of the year using tests of proportions. The null hypothesis for this test was that all the prevalence for both product types were equal. The alternative hypothesis was that the prevalence differed. This statistical test assumed independence among the samples, although this assumption is not likely met for these data. Because multiple samples were collected at the same store, multiple positive L. monocytogenes findings were likely correlated because of cross-contamination and poor hygienic conditions at the store. Statistical tests with correlated positive samples claim to find statistically significant results more commonly than intended.
Tests of proportions were also conducted at the retail store level. A store was considered positive for retail-sliced or prepackaged product if any of the samples for that category were found positive for L. monocytogenes. Stores are more likely to be independent than the individual data, but there are problems with using this approach. Store identifiers (even arbitrary labels) were removed from data provided prior to submittal to FSIS as part of the data encoding and blinding process. Store visits had to be estimated based on date and time of sampling collection. Sample collection times were not provided for samples from Minnesota, therefore the number of stores available was much smaller than the number of samples. Also, statistical tests based on only a few hundred samples have limited statistical power and are unlikely to detect small differences in prevalence at reasonable levels of confidence. Finally, this approach does not directly incorporate the number of samples collected at each store.
Another approach used was a logistic regression to predict the store prevalence for retail-sliced and prepackaged product as a function of a number of indicator variables: where the product was sliced, the store type, and the time of day the sample was collected. This approach is not subject to the correlation problem because it is based on store prevalence. The regression was weighted by the number of samples taken at the store, and evaluated more than one explanatory variable simultaneously.

READ  Engineering methionyl-tRNA synthetase for ligand:substrate binding and catalytic power 


Prevalence and Number of Samples

Fifty-seven samples were found to be positive for L. monocytogenes resulting in an overall prevalence of 0.76%. Two of these positives were found in chub samples, six were found in prepackaged samples, and the remaining 49 positives were found in retail-sliced samples. The number of prepackaged and retail-sliced samples across the four FoodNet sites is shown in Table 8.
Slightly fewer product samples were taken in CA than other sites. More stores were sampled in GA than other sites. In addition to prepackaged and retail-sliced product samples, 105 and 300 additional chub samples were collected in MN and TN respectively. Assuming independence, a test of proportions indicated no statistically significant difference for the prevalence within product samples among the four sites (p = 0.75). Neither was there any statistical difference for the store prevalence across the sites (p = 0.31). This allowed for pooling of the data for purposes of discussing total prevalence. The number and prevalence for retail-sliced and prepackaged samples by quarter of the year is shown in Table 9. More product samples and more stores were visited in the 3rd quarter than in other quarters. Assuming independence, a test of proportions indicated a statistically significant difference for the prevalence within product samples (p = 0.01) but not store prevalence (p = 0.31).
The more interesting time of day analysis looked solely at retail-sliced product as shown in Table 11. Retail-sliced product samples collected in the afternoon were more than twice as likely to test positive for L. monocytogenes – 1.92% versus 0.92%. Assuming independence, this difference was statistically significant (p = 0.04). While store prevalence was also higher in the afternoon (7.83% versus 5.80%), this difference was not statistically significant (p = 0.64).

Chapter 1. Introduction .
In-Plant Dynamic Model
1.1 Introduction
1.2 Material and Methods
1.3 Results and Discussion
1.4 Conclusions
Chapter 2. Listeria monocytogenes Prevalence and Level in Ready-to-eat Meat and Poultry deli meat
2.1 Introduction
2.2 Materials and Methods
2.3 Results
2.4 Logistic Regression
2.5 Comparison of Findings of the National Alliance for Food Safety and Security with
those of the Food Processors Association
2.6 Conclusions
Chapter 3. Comparative Risk of Listeria monocytogenes in Ready-to-Eat Meat and Poultry Products
3.1 Introduction
3.2 Materials and Methods
3.3 Results.
3.4 Discussion and Conclusions
Chapter 4. Conclusions 
Risk Assessment for Listeria monocytogenes in Ready-to-eat Meat and Poultry Products

Related Posts