Food Protection Trends - January/February 2014 - (Page 27)

(Pennsylvania), or 24th (Rhode Island) restaurant from the list, arranged by county name, was selected to be included in the sample. Only restaurants and delis not associated with a gas station, grocery store, or caterer were included in the sample. Some states reported violation summaries, while others included detailed health inspection reports. The most recent routine inspection report from each establishment was selected for analysis. Dates of inspections ranged from June 2009 to February 2012. Data collection and consolidation State health inspection forms included different violations (i.e., Oklahoma notes 51 different violations, Pennsylvania 208, and Rhode Island 54), with inconsistent wording. The original wording was maintained for categorizing and further analyses of the data. Before combining the Food Code violations into predetermined categories, each violation was recorded, based on each state's inspection form. The Microsoft Access database with a separate file for each state. Food Code violations were evaluated and assigned to predetermined violation categories (i.e., behavioral versus non-behavioral, critical versus non-critical). Oklahoma and Rhode Island inspection reports included instances in which the descriptions implied both behavioral and non-behavioral violations. For example, one violation related to handwashing stated, "Handwash facilities adequate/Accessible with soap and towels." Even though employees have no control over adequate/inadequate handwashing facilities (nonbehavioral), employees can ensure that soap and paper towels are properly stocked (behavioral). Another example, related to sinks' stated, "Proper number of sinks: mop sinks, dishwashing sinks, food preparation sinks, used for intended purposes." An establishment may be cited for this code, based on inadequate facilities (non-behavioral) or improper use of sinks (behavioral). Because these cases cannot be verified as behavioral or non-behavioral violations, they were categorized as both. Therefore, the sum of behavioral and non-behavioral code violations slightly exceeds the total inspection items for both Oklahoma and Rhode Island. Critical versus non-critical violations were determined on the basis of each state's inspection reports, because violations were not consistently reported from state to state. If the state's inspection report indicated certain violations as critical, we classified them as critical even though the other two states may not consider them critical. After each code violation was classified into one of 30 violation categories and as behavioral/non-behavioral, and critical/non-critical, the data from all schools and restaurants were recoded, using the following Microsoft Excel equation: Ncat#, beh = Ncode1 x Beh(0 or 1) + Ncode2 x Beh(0 or 1) + Ncode3 x Beh(0 or 1) + . . . where Ncat#, beh is the number of behavioral code violations in category #; Ncode# is the number of code violations within the category #; and Beh(0 or 1) is the behavioral violation factor when 0 is assigned for non-behavioral and 1 for behavioral code violations. A similar equation was used to calculate total critical violations: Ncat#, Crit = Ncode1 x Crit(0 or 1) + Ncode2 x Crit(0 or 1) + Ncode3 x Crit(0 or 1) + . . . where Ncat#, Crit is the number of critical code violations in category # and Crit (0 or 1) is the critical violation factor when 0 is assigned for non-critical 1 for critical code violations. The number of behavioral, non-behavioral, critical, and noncritical violations in each food code violation category for each establishment was calculated using Microsoft Excel formulas. After each state's data were recoded into consistent categories and the numbers of behavioral, non-behavioral, critical, and non-critical violations were calculated, the data from all three states were compiled into one Microsoft Excel file, which was then converted to an SPSS format for further analysis. The final dataset included both restaurant and school inspection reports, with the number of behavioral and non-behavioral violations identified within each food code violation category. Data analysis was performed with 2,624 restaurant inspection reports and 2,511 school inspection reports. Data analyses SPSS for Windows (version 19.0, 2011) was used for data analysis. Descriptive statistics, with frequencies, means, and standard deviations were calculated to summarize the data. Cross-tabulation with chi-square analysis was conducted to compare the distribution of the data between restaurants and schools. Differences in the numbers of code violations between restaurants and schools were compared by use of independent sample t-tests for each category within the behavioral and non-behavioral violation classifications. Finally, the likelihood of behavioral, non-behavioral, critical, and non-critical violations in restaurants compared with schools was calculated by use of odds ratios. Before odds ratio analysis, data were recoded as1 if there were any violations within each classification and as 0 if there were no violations. Statistical significance was determined at P < 0.01. RESULTS AND DISCUSSION verall, restaurants had more total violations (4.75 ± 4.51) than schools (1.99 ± 1.98)(P < 0.001). In fact, schools had fewer violations in every category (behavioral, non-behavioral, critical, and non-critical) than restaurants, albeit the most highly significant difference (t value) was observed for behavioral violations (Table 1). In general, the number of food code violations in this study revealed that food safety risks were fewer and might be less severe for school foodservice establishments than for commercial restaurants, possibly because food preparation in school foodservice is less complex, with fewer items prepared than in restaurants. Many school foodservice operations use a large amount of pre-prepared food products to help contain operational costs (1), which also reduces personnel requirements. These factors may lessen the number of violations in schools. O foodprotection.org Food Protection Trends 27 http://www.foodprotection.org

Table of Contents for the Digital Edition of Food Protection Trends - January/February 2014

Food Protection Trends - January/February 2014
Contents
Economically Motivated Adulteration of Honey: Quality Control Vulnerabilities in the International Honey Market
Efficacy of Quaternary Ammonium Compounds on Different Conveyor Chips Contaminated with Poultry Rinsate
What Implications Does a Baseline of Self-efficacy of Food Safety in Adolescent Populations Have for Future Food Safety Education Interventions?
Food Safety Risks in Restaurants and School Foodservice Establishments: Health Inspection Reports
INOFOOD 2013 Conference & Expo
The 3rd Asia Pacific International Conference on Food Safety
China International Food Safety & Quality Conference (CIFSQ) + Expo
Dubai International Food Safety Conference (DIFSC)
Beyond the Bio
FSMA: Article 7
PDG
Industry Products
Coming Events

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