• Food Science of Animal Resources
• /
• v.35 no.5
• /
• pp.674-682
• /
• 2015

The objective of this study was to evaluate the risk of illness from Campylobacter spp. on ham. To identify the hazards of Campylobacter spp. on ham, the general characteristics and microbial criteria for Campylobacter spp., and campylobacteriosis outbreaks were investigated. In the exposure assessment, the prevalence of Campylobacter spp. on ham was evaluated, and the probabilistic distributions for the temperature of ham surfaces in retail markets and home refrigerators were prepared. In addition, the raw data from the Korea National Health and Nutrition Examination Survey (KNHNES) 2012 were used to estimate the consumption amount and frequency of ham. In the hazard characterization, the Beta-Poisson model for Campylobacter spp. infection was used. For risk characterization, a simulation model was developed using the collected data, and the risk of Campylobacter spp. on ham was estimated with @RISK. The Campylobacter spp. cell counts on ham samples were below the detection limit (<0.70 Log CFU/g). The daily consumption of ham was 23.93 g per person, and the consumption frequency was 11.57%. The simulated mean value of the initial contamination level of Campylobacter spp. on ham was −3.95 Log CFU/g, and the mean value of ham for probable risk per person per day was 2.20×10⁻¹². It is considered that the risk of foodborne illness for Campylobacter spp. was low. Furthermore, these results indicate that the microbial risk assessment of Campylobacter spp. in this study should be useful in providing scientific evidence to set up the criteria of Campylobacter spp..

• Food Science of Animal Resources
• /
• v.32 no.1
• /
• pp.118-124
• /
• 2012

This study was conducted for quantitative microbial risk assessment (QMRA) of Clostridium perfringens with consumption on ham and sausage products in Korea, according to Codex guidelines. Frame-work model as product-retail-consumption pathway composed with initial contamination level, the time and temperature in distributions, and consumption data sets for ham and sausage products and also used the published predictive growth and dose-response models for Cl. perfringens. The simulation model and formulas with Microsoft@ Excel spreadsheet program using these data sets was developed and simulated with @RISK. The probability of foodborne disease by Cl. perfringens with consumption of the ham and sausage products per person per day was estimated as $3.97{\times}10^{-11}{\pm}1.80{\times}10^{-9}$. There were also noted that limitations in this study and suggestion for development of QMRA in the future in Korea.

• Restorative Dentistry and Endodontics
• /
• v.49 no.1
• /
• pp.4.1-4.9
• /
• 2024

Objectives: This study aims to correlate caries-causing microorganism load, lactic acid estimation, and blood groups to high caries risk in diabetic and non-diabetic individuals and low caries risk in healthy individuals. Materials and Methods: This study includes 30 participants divided into 3 groups: Group A, High-risk caries diabetic individuals; Group B, High-risk caries non-diabetic individuals; and Group C, Low-risk caries individuals. The medical condition, oral hygiene, and caries risk assessment (American Dental Association classification and International Caries Detection and Assessment System scoring) were documented. Each individual's 3 mL of saliva was analyzed for microbial load and lactic acid as follows: Part I: 2 mL for microbial quantity estimation using nutrient agar and blood agar medium, biochemical investigation, and carbohydrate fermentation tests; Part II: 0.5 mL for lactic acid estimation using spectrophotometric analysis. Among the selected individuals, blood group correlation was assessed. The χ² test, Kruskal-Wallis test, and post hoc analysis were done using Dunn's test (p < 0.05). Results: Group A had the highest microbial load and lactic acid concentration, followed by Groups B and C. The predominant bacteria were Lactobacilli (63.00 ± 15.49) and Streptococcus mutans (76.00 ± 13.90) in saliva. Blood Group B is prevalent in diabetic and non-diabetic high-risk caries patients but statistically insignificant. Conclusions: Diabetic individuals are more susceptible to dental caries due to high microbial loads and increased lactic acid production. These factors also lower the executing tendency of neutrophils, which accelerates microbial accumulation and increases the risk of caries in diabetic individuals.

• Food Science of Animal Resources
• /
• v.37 no.4
• /
• pp.579-592
• /
• 2017

This study assessed the quantitative microbial risk of non-enterohemorrhagic Escherichia coli (EHEC). For hazard identification, hazards of non-EHEC E. coli in natural and processed cheeses were identified by research papers. Regarding exposure assessment, non-EHEC E. coli cell counts in cheese were enumerated, and the developed predictive models were used to describe the fates of non-EHEC E. coli strains in cheese during distribution and storage. In addition, data on the amounts and frequency of cheese consumption were collected from the research report of the Ministry of Food and Drug Safety. For hazard characterization, a doseresponse model for non-EHEC E. coli was used. Using the collected data, simulation models were constructed, using software @RISK to calculate the risk of illness per person per day. Non-EHEC E. coli cells in natural- (n=90) and processed-cheese samples (n=308) from factories and markets were not detected. Thus, we estimated the initial levels of contamination by Uniform distribution ${\times}$ Beta distribution, and the levels were -2.35 and -2.73 Log CFU/g for natural and processed cheese, respectively. The proposed predictive models described properly the fates of non-EHEC E. coli during distribution and storage of cheese. For hazard characterization, we used the Beta-Poisson model (${\alpha}=2.21{\times}10^{-1}$, $N_{50}=6.85{\times}10^7$). The results of risk characterization for non-EHEC E. coli in natural and processed cheese were $1.36{\times}10^{-7}$ and $2.12{\times}10^{-10}$ (the mean probability of illness per person per day), respectively. These results indicate that the risk of non-EHEC E. coli foodborne illness can be considered low in present conditions.

• Journal of Food Hygiene and Safety
• /
• v.18 no.3
• /
• pp.107-112
• /
• 2003

Probabilistic exposure assessment has been recognized as an important tool in microbial risk assessment, because of obtained the desired results to characterize of variability and uncertainty associated with the microbial hazards. In addition, it will be provided much more actuality information than the point-estimate approaches. In this study, we present methodology using mathematical probability distribution in exposure assessment and estimating of contamination level of Listeria monocytogenes in meat and meat products as a case study. The result of estimation contaminatin level was mean ($50^{th}$ percentile) -4.08 Log CFU/g minimum ($5^{th}$ percentile) -4.88 Log CFU/g, maximum ($95^{th}$ percentile) -3.56 Log CFU/g.

• The Korean Journal of Community Living Science
• /
• v.15 no.2
• /
• pp.167-177
• /
• 2004

The number of foodborne salmonellosis was estimated by using microbial risk assessment(MRA) methodology and the possibility of application was studied through comparison with previous results. The contamination levels of Salmonella sp. were estimated by using published domestic studies(1997∼2000) and monitoring data (1999∼2001) from food-safety related institutes. Data on food consumption came from the 2001 National Health and Nutrition Survey, and dose-response models from studies in other countries. Simulation results showed that there were 753,368 cases of salmonellosis in Korea in 1 year, which is about 115 times that reported in previous years and lower than the WHO's estimation increase. From these results, microbial risk assessment is likely to be available for estimation of the number of foodborne illnesses and determination of the order of priority in food-safety management. Butthe verification methods are not established and most of the data on contamination levels of foodborne bacteria, food consumption, and dose-response relationships have not been established. In addition, the actual conditions of circulation, storage and cooking must be studied further.

• Asian-Australasian Journal of Animal Sciences
• /
• v.29 no.8
• /
• pp.1188-1196
• /
• 2016

This study evaluated the risk of Clostridium perfringens (C. perfringens) foodborne illness from natural and processed cheeses. Microbial risk assessment in this study was conducted according to four steps: hazard identification, hazard characterization, exposure assessment, and risk characterization. The hazard identification of C. perfringens on cheese was identified through literature, and dose response models were utilized for hazard characterization of the pathogen. For exposure assessment, the prevalence of C. perfringens, storage temperatures, storage time, and annual amounts of cheese consumption were surveyed. Eventually, a simulation model was developed using the collected data and the simulation result was used to estimate the probability of C. perfringens foodborne illness by cheese consumption with @RISK. C. perfringens was determined to be low risk on cheese based on hazard identification, and the exponential model ($r=1.82{\times}10^{-11}$) was deemed appropriate for hazard characterization. Annual amounts of natural and processed cheese consumption were $12.40{\pm}19.43g$ and $19.46{\pm}14.39g$, respectively. Since the contamination levels of C. perfringens on natural (0.30 Log CFU/g) and processed cheeses (0.45 Log CFU/g) were below the detection limit, the initial contamination levels of natural and processed cheeses were estimated by beta distribution (${\alpha}1=1$, ${\alpha}2=91$; ${\alpha}1=1$, ${\alpha}2=309$)${\times}$uniform distribution (a = 0, b = 2; a = 0, b = 2.8) to be -2.35 and -2.73 Log CFU/g, respectively. Moreover, no growth of C. perfringens was observed for exposure assessment to simulated conditions of distribution and storage. These data were used for risk characterization by a simulation model, and the mean values of the probability of C. perfringens foodborne illness by cheese consumption per person per day for natural and processed cheeses were $9.57{\times}10^{-14}$ and $3.58{\times}10^{-14}$, respectively. These results indicate that probability of C. perfringens foodborne illness by consumption cheese is low, and it can be used to establish microbial criteria for C. perfringens on natural and processed cheeses.

• Proceedings of the Korean Society of Food Hygiene and Safety Conference
• /
• 2005.11a
• /
• pp.159-173
• /
• 2005

• Journal of Food Hygiene and Safety
• /
• v.19 no.1
• /
• pp.19-24
• /
• 2004

Dose-response models in microbial risk assessment can be divided into biologically plausible models and empirical models. Biologically plausible models are formed by the assumptions in dose distribution of microbes, host sensitivity to microbes, and minimal infectious dose of microbes : there are Exponential model and $\beta$-Poisson model, representatively. Empirical models are mainly used to express the toxicity of chemicals : there are Weibull-Gamma model etc. Deviance function (Y) is used to fit available data to dose-response models, and some dose-response models for food-borne pathogens are developed in humans and experimental animals.

• Fisheries and Aquatic Sciences
• /
• v.25 no.9
• /
• pp.463-472
• /
• 2022

In this study, a microbial risk assessment was performed for the bacteria Vibrio parahaemolyticus, which causes a foodborne illness following the consumption of Jeotgal, a fermented seafood in South Korea. The assessment comprised of six stages: product, market, home, consumption, dose-response, and risk. The initial contamination level (IC) was calculated based on the prevalence of V. parahaemolyticus in 90 Jeotgal samples. The kinetic behavior of V. parahaemolyticus was described using predictive models. The data on transportation conditions from manufacturer to market and home were collected through personal communication and from previous studies. Data for the Jeotgal consumption status were obtained, and an appropriate probability distribution was established. The simulation models responding to the scenario were analyzed using the @RISK program. The IC of V. parahaemolyticus was estimated using beta distribution [Beta (1, 91)]. The cell counts during transportation were estimated using Weibull and polynomial models [δ = 1 / (0.0718 - 0.0097 × T + 0.0005 × T²)], while the probability distributions for time and temperature were estimated using Pert, Weibull, Uniform, and LogLogistic distributions. Daily average consumption amounts were assessed using the Pareto distribution [0.60284,1.32,Risk Truncate(0,155)]. The results indicated that the risk of V. parahaemolyticus infection through Jeotgal consumption is low in South Korea.