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at Point-of-Service: Affect
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=
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sc Bid
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Programs on Foodborne
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IIIness Outcomes
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ADVANCEMENT OF THE SCIENCE
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Disclosing Inspection Results
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of Characteristics of Food
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Establishment Inspection
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A b St ra ct The significant proportion of foodborne illnesses
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attributed to restaurants highlights the importance of food establishment
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inspections. The objectives of this cross-sectional study were to characterize
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local inspection programs and evaluate the effects of programmatic
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characteristics, such as active public disclosure of inspection results, on
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select operational and foodborne illness outcomes. Between January 7
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and April 6, 2020, an online 36-question survey was administered to 790
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government-run food establishment inspection programs at state and
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local levels. Of 149 survey respondents, 127 (85%) represented local food
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establishment inspection agencies. Agencies that disclosed at the point-of-
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service reported fewer mean numbers of re-inspections by 15%, foodborne
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illness complaints by 38%, outbreaks by 55% (p = .03), and Salmonella
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cases by 12% than agencies that disclosed online only. Agencies that used
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some type of grading method for inspection results reported fewer mean
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numbers of re-inspections by 37%, complaints by 22%, outbreaks by 61%,
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and Salmonella cases by 25% than agencies that did not grade inspections.
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Programmatic characteristics appear to be associated with foodborne illness
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outcomes. These results warrant future research to improve the effectiveness
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of food establishment inspection programs.
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Introduction
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Approximately 51% of each consumer dollar
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dedicated to food spending in 2019 was spent
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in the food service industry, specifically in
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restaurants, compared with just 25% in 1955
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(National Restaurant Association, 2020).
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Coincidentally, there is growing evidence that
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restaurants are an important source of spo-
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radic and outbreak-associated foodborne dis-
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8 Volume 83 ¢ Number 6
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ease in the U.S. Jones & Angulo, 2006). In
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2017, there were 841 foodborne illness out-
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breaks resulting in 14,481 illnesses, 827 hos-
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pitalizations, 20 deaths, and 14 food recalls
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in the U.S., including Puerto Rico and Wash-
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ington, DC (Centers for Disease Control and
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Prevention [CDC], 2019).
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Among the illnesses and outbreaks for
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which a single location was identified, 44%
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Thuy N. Kim, MPH, CFOI
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Melanie J. Firestone, MPH, PhD
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University of Minnesota
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School of Public Health
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Natasha DeJarnett, MPH, PhD
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Laura Wildey, CP-FS
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Jesse C. Bliss, MPH
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David T. Dyjack, DrPH, CIH
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National Environmental
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Health Association
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Jennifer Edwards, PhD
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National Network of
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Public Health Institutes
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Harlan Stueven, MD
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Dining Safety Alliance
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Craig W. Hedberg, PhD
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University of Minnesota
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School of Public Health
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and 64%, respectively, were attributed to
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foods prepared in a restaurant setting (CDC,
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2019). The rise in expenditure on foods
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eaten away from the home and the sig-
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nificant proportion of foodborne illnesses
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attributed to restaurants have highlighted
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the importance of food establishment
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inspections, as they could flag the existence
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of food safety hazards and mitigate their
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public health impact.
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Public disclosure of inspection results
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from food establishments enables consum-
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ers to make informed decisions about where
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they choose to eat (Fung et al., 2007). Con-
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sumer priority of hygienic food preparation
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practices, in turn, incentivizes food estab-
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lishments to improve hygiene practices—a
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proxy for better sanitary conditions—within
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their facility. Improved and maintained san-
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itary conditions, theoretically, lead to fewer
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foodborne illnesses. From a programmatic
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standpoint, however, disclosure of inspec-
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tion results can create more work for the
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environmental health workforce tasked
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with putting the information into a present-
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able format. In a survey of the environmen-
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tal health workforce, 76% of workers sur-
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veyed indicated working in food safety and
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protection programs; however, 17% of all
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respondents performed public health duties
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outside of environmental health, and of
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those, 37% spent >50% of their time work-
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ing in nonenvironmental health programs
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(Gerding et al., 2019).
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The value of actively disclosing inspec-
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tion results to the public has been dem-
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Vr... 1
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Summary Statistics for Local Agency Respondents (n = 124)
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a aaa Sa
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Active disclosure 82 (66)
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Active disclosure methods
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Online 75 (91)
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Point-of-service 24 (29)
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Other 4 (5)
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No active disclosure 42 (27)
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Grading methods
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Numerical score 53 (43)
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Letter grade 20 (16)
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Other 34 (27)
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No grading 30 (24)
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Inspection violation schemes (n =75)
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P-PF-C 24 (32)
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C/NC 21 (28)
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RF-GRP* 23 (31)
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P-PF-C 10 (43)
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C/NC 4 (17)
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Major/minor 3 (13)
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Other 7 (9)
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P-PF-C = Priority-Priority Foundations-Core; C/NC = Critical/Noncritical; RF-GRP = Risk Factor-Good Retail Practices.
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*Of the 23 agencies that indicated using RF-GRP, 6 agencies used RF-GRP only. The other 17 agencies used RF-GRP in
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combination with the other schemes listed below.
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onstrated in several settings throughout
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the U.S. The debate about the best mode
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to convey inspection results to the public,
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however, is still ongoing. A study of people
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at the Minnesota State Fair found increased
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interest in public access to inspection
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results. Furthermore, fairgoers expressed
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interest in disclosure methods of posting
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online and at the point-of-service, that is, at
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a food establishment (Firestone & Hedberg,
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2020). For local inspection agencies that
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disclose inspection results, the most com-
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mon method is through online disclosure
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only, typically accessed via departmental
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websites. Drawbacks of this method include
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difficulty in navigating these websites and
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lengthy reports that are confusing to the
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general public. Moreover, this method might
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not be accessible to those who are most vul-
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nerable to foodborne illness, such as older
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adults (Fleetwood, 2019).
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Disclosure at the point-of-service elimi-
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nates a barrier to using inspection data
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in the decision-making process, as this
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approach does not require a person to have
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online access to check a website for inspec-
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tion results. With the introduction of pub-
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lic disclosure by means of a color-coded
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inspection sticker placed at or near restau-
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rant entrances, Columbus Public Health
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(Ohio), saw inspection scores improve by
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1.14 points out of a possible 100 points
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(Choi & Scharff, 2017). In New York City,
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New York, implementation of public disclo-
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sure at the point-of-service in the form of
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letter grades was associated with improve-
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ments in sanitary conditions (Wong et al.,
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2015) and a 5.3% decrease in Salmonella
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cases per year (Firestone & Hedberg, 2018).
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Furthermore, in Los Angeles County, Cali-
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fornia, public disclosure of letter grades at
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the establishment led to a 13% decline in
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hospitalizations due to foodborne illness
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(Simon et al., 2005).
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While the act of disclosure is important,
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what information is disclosed and how the
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public interprets it is also important. Famil-
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iarity with the symbols used to represent
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inspection results lends to easier interpreta-
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tion by the general public. Grading practices
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can include letter grading and/or numerical
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grading, similar to most grading methods in
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a school system (e.g., A, B, C grades or 100%,
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90%, 80%) or other ordinal methods (e.g.,
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stoplight colors, emoticons).
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During inspections, a labeling system is
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used to classify different types of violations
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and convey severity of the violations. These
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violation schemes often correlate with the
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version of the Food and Drug Administration
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(FDA) Food Code an agency has adopted and
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can be used in combination at the agency's
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discretion. For example, in Food Code ver-
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sions before 2009, violations that were more
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likely “to contribute to food contamination,
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illness, or environmental health hazard” were
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classified as critical. In 2009, FDA revised
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the Food Code to distinguish critical items
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as priority if the item includes a quantifiable
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measure to show control (e.g., cooking), or
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priority foundation if the item requires the
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purposeful incorporation of specific actions
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(e.g., training) (Food and Drug Administra-
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tion [FDA], 2015). The categorization of risk
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factor or good retail practices corresponds to
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the organization of the FDA Food Establish-
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ment Inspection Report.
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Current inspection practices and methods
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of disclosure vary widely across jurisdictions
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in the U.S. and present unique challenges to
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evaluating program effectiveness. The objec-
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tives of this cross-sectional study were to 1)
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characterize local inspection programs and
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2) evaluate the effects of programmatic char-
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acteristics, such as active public disclosure
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methods, on select operational and food-
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borne illness outcomes.
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Methods
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An online 36-question survey was adminis-
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tered via Qualtrics to 790 government-run
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food establishment inspection programs at
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state, county, city, district, and territorial lev-
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els. Recipients were chosen based on avail-
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ability of program inspection data online or
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participation in FDAs Voluntary National
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Retail Food Regulatory Program Standards
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January/February 2021 e Journal of Environmental Health 9
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ADVANCEMENT OF THE SCIENCE
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TABLE 2
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Mean, Standard Deviation, and Median Estimates for Outcomes by Disclosure Methods, Grading Methods,
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and Inspection Violation Schemes
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Average # of Re-
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Average # of
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Average # of
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Average # of Salmonella
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Inspections/Establishment/ Complaints/1,000 Outbreaks/1,000 Cases/100,000 Population
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Year Establishments/Year Establishments/Year Served/Year
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(m= 109) (nm = 100) (n= 101) (n= 48)
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Mean (SD) Median Mean (SD) Median Mean (SD) Median Mean (SD) Median
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Disclosure methods
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Online 0.40 (0.55) 0.24 44.2 (49.6) 27.3 1.7 (2.4) 0.84 14.4 (7.2) 14.0
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Point-of-service 0.35 (0.46) 0.17 30.3 (45.3) 22.2 0.9 (1.4) 0.25 12.9 (6.5) 14.0
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None 0.53 (0.46) 0.50 31.3 (36.0) 18.5 7.0 (24) 0.00 9.9 (9.9) 6.7
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Other* 0.36 (0.43) 0.17 74.5 (86.4) 42.7 3.7 (4.7) 2.39 - -
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Grading methods
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Numerical score 0.32 (0.37) 0.17 40.6 (54.6) 22.2 3.0 (10.7) 0.35 12.4 (6.8) 13.6
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Letter grade 0.31 (0.48) 0.13 34.9 (41.7) 24.6 1.3 (1.6) 0.71 13.0 (7.0) 14.2
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None 0.59 (0.64) 0.50 49.1 (49.2) 29.2 6.5 (25.0) 0.82 15.9 (12.2) 13.1
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Other 0.46 (0.57) 0.27 36.4 (35.0) 27.6 1.9 (2.7) 0.95 12.0 (6.2) 12.7
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Inspection violation schemes
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P-PF-C 0.39 (0.45) 0.18 47.2 (53.3) 29.0 1.5 (1.7) 0.95 15.7 (7.4) 16.4
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C/NC 0.38 (0.49) 0.25 48.7 (45.2) 42.7 1.1 (1.4) 0.85 12.7 (8.8) 13.1
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RF-GRP 0.32 (0.39) 0.17 38.1 (51.1) 22.8 2.4 (2.2) 1.97 16.8 (8.1) eal
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Other 0.29 (0.37) 0.19 57.9 (73.9)* 11.8% 0.77 (0.78)* 0.62* 10.9 (7.8)* 11.7*
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P-PF-C = Priority-Priority Foundations-Core; C/NC = Critical/Noncritical; RF-GRP = Risk Factor-Good Retail Practices.
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*Contains data from <5 respondents.
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(Retail Program Standards). The Retail Pro-
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gram Standards provide recommendations
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aimed at facilitating inspections that are more
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effective and implementing foodborne illness
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prevention strategies. Enrollees in this pro-
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gram intend to actively use these standards as
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a tool to assess and improve their regulatory
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programs (FDA, 2019).
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We administered the survey in two rounds.
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The first round consisted of 151 recipients
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whose inspection data were publicly available
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online, resulting in a 40% response rate (n =
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60 respondents). The second round included
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639 recipients who participated in the Retail
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Program Standards, resulting in a response
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rate of 19% (n = 122 respondents). Via the
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survey, we obtained information on general
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program characteristics such as size of popu-
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lation served; number of routine inspections
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conducted; number of licensed establish-
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ments within the inspection jurisdiction; and
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10
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Volume 83 ¢ Number 6
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operational characteristics such as public dis-
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closure method, grading method, and FDA
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Food Code version in use.
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The time period for the survey was chosen to
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match the availability of inspection data from
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the agencies. Three geographically diverse
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local inspection agencies piloted the survey
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to ensure appropriateness and relevancy of
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questions and answer choices. The data col-
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lection period was January 7—April 6, 2020.
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We paused data collection in April due to the
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COVID-19 pandemic response taking prec-
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edent at state and local health departments.
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We categorized inspection agencies into
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two main types, state and local. A state
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agency was defined as an inspection program
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that oversees the inspection of food establish-
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ments at the state government level, includ-
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ing U.S. territories and Washington, DC. A
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local agency differs in that the oversight of
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the inspection programs is at the county, city,
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city-county, or district government level.
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One survey respondent represented a univer-
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sity and thus was excluded from this analy-
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sis, as there could be significant policy dif-
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ferences between government agencies and
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universities. Local agencies were the primary
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focus of this analysis, as most food establish-
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ment inspection programs are operated at the
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local government level.
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Four operational and foodborne illness out-
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comes were calculated as rates from a combi-
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nation of variables obtained from the survey
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and expressed as an average number of:
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1. Re-inspections/establishment/year (calcu-
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lated as the quotient of average number
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of re-inspections and number of licensed
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food establishments within the jurisdiction
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of the agency).
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2. Foodborne illness complaints/1,000 licensed
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food establishments/year (2016-2018; most
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recent years included in data set).
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TABLE 3
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Mean, Standard Deviation, and Median Estimates for Outcomes by Point-of-Service (POS) Disclosure
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Versus Online (no POS) Disclosure
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Average # of Re-Inspections/
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Establishment/Year
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(n= 71)
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Average # of
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Complaints/1,000
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Establishments/Year
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(n = 62)
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Average # of
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Outbreaks/1,000
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Establishments/Year
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(n= 63)
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Average # of Salmonella
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Cases/100,000 Population
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Served/Year
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(n= 31)
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p-value 65 .16 44
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POS disclosure
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Mean (SD) 0.35 (0.46) 30.3 (45.3) 0.92 (1.4) 11.7 (6.6)
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Median 0.17 22.17 0.25 12.5
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Online (no POS) disclosure
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Mean (SD) 0.41 (0.57) 48.6 (50.0) 2.04 (2.69) 13.3 (8.5)
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Median 0.24 29.0 0.95 12.7
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3. Foodborne outbreaks/1,000 licensed food
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establishments/year (2016-2018).
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4. Salmonella cases reported/100,000 popula-
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tion served/year (2016-2018).
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In addition to the survey data, we were
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able to obtain some Salmonella case counts
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using departmental websites for jurisdictions
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that reported these data online.
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For the purposes of this study, active dis-
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||
closure was defined as agencies that volun-
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tarily and preemptively publicize some or
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all inspection data to the public. Inspection
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violation scheme was not included in the
|
||
survey, but was determined by searching
|
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online for inspection data from the respond-
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ing agencies.
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|
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Predictors were classified into three
|
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categories:
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1. Disclosure method consisting of online,
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point-of-service, no disclosure, and other
|
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disclosure methods.
|
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|
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2. Grading method consisting of numerical
|
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score, letter grade, no grading, and other
|
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grading methods.
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|
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3. Inspection violation scheme used for rou-
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tine inspections consisting of subcatego-
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ries Priority-Priority Foundations-Core;
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Critical/Noncritical; Risk Factor-Good
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Retail Practices; and other schemes.
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||
|
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The Risk Factor-Good Retail Practices sub-
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category relates to the inspection report form
|
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and therefore can be used in combination
|
||
with other violation schemes. The mean and
|
||
median values of outcomes for each combi-
|
||
nation of schemes were assessed in addition
|
||
|
||
|
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to the nonmutually exclusive scheme catego-
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ries previously stated. One respondent used
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a combination of three schemes: Risk Factor-
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Good Retail Practices, Critical/Noncritical,
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and Red/Blue. Of note, Red/Blue is similar
|
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and is sometimes used in reference to Criti-
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cal/Noncritical; therefore, this respondent's
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jurisdiction was included in the Risk Factor-
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Good Retail Practices and Critical/Noncriti-
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cal scheme combination.
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Mean and median values were calculated
|
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to identify trends in outcomes based on each
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subcategory. The means were compared
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using t-tests; p-values were reported assum-
|
||
ing unequal variance. The analysis was con-
|
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ducted using SAS 9.4m6 University Edition.
|
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Linear regression was used to determine
|
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associations between the outcome variables
|
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reported by the local responding agencies.
|
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The level of statistical significance was set at
|
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o = .05.
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|
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|
||
Results
|
||
|
||
Of the 149 survey respondents, 127 (85%)
|
||
represented a local food establishment
|
||
inspection agency. More than one half of
|
||
agencies (66%) actively disclosed inspection
|
||
scores to the public and most (91%) did so
|
||
by posting online; only some (30%) posted
|
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at the point-of-service. Approximately 43%
|
||
of the agencies used numerical scores as
|
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a grading method, 24% used no grading
|
||
method, and 16% used letter grades (Table
|
||
1). Frequently used inspection violation
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||
schemes included Priority-Priority Foun-
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|
||
dations-Core (32%) and Critical/Noncriti-
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||
cal (28%). The scheme Risk Factor-Good
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||
Retail Practices (31%) was used in combina-
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tion with other violation schemes. Of the 23
|
||
agencies that used Risk Factor-Good Retail
|
||
Practices with another scheme, 43% used
|
||
Priority-Priority Foundations-Core, 22%
|
||
used Critical/Noncritical, and 13% used
|
||
Major/Minor schemes. Violation schemes
|
||
for 53 respondents could not be determined
|
||
using online searching.
|
||
|
||
Agencies disclosing at the point-of-service
|
||
had lower mean values for all outcome mea-
|
||
sures than did agencies disclosing online
|
||
(Table 2). Of the 24 agencies disclosing
|
||
inspection results at the point-of-service,
|
||
however, 21 (88%) also disclosed inspection
|
||
results online (Table 1). Due to this overlap,
|
||
we made further comparisons of agencies dis-
|
||
closing at the point-of-service and agencies
|
||
disclosing online only (Table 3). Agencies
|
||
that disclosed inspection results at the point-
|
||
of-service reported fewer mean numbers of
|
||
re-inspections by 15%, complaints by 38%,
|
||
outbreaks by 55% (p = .03), and Salmonella
|
||
cases by 12% than did agencies that disclosed
|
||
online only.
|
||
|
||
Agencies that used some type of grading
|
||
method for inspection results reported fewer
|
||
mean numbers of re-inspections by 37%,
|
||
complaints by 22%, outbreaks by 61%, and
|
||
Salmonella cases by 25% than did agencies
|
||
that did not grade inspection results. Agen-
|
||
cies using letter grades had lower mean values
|
||
for complaints by 14% and outbreaks by 43%
|
||
|
||
|
||
January/February 2021 e Journal of Environmental Health 11
|
||
|
||
|
||
ADVANCEMENT OF THE SCIENCE
|
||
|
||
|
||
TABLE 4
|
||
|
||
|
||
Linear Regression Comparisons of Outcomes
|
||
|
||
|
||
Average # of Average # of
|
||
|
||
|
||
Complaints/1,000
|
||
|
||
|
||
Average # of
|
||
Outbreaks/1,000
|
||
|
||
|
||
Average # of Salmonella
|
||
Cases/100,000 Population
|
||
|
||
|
||
Re-Inspections/
|
||
|
||
|
||
Establishment/Year Establishments/Year Establishments/Year Served/Year
|
||
Parameter | p-Value | # Parameter | p-Value| # Parameter | p-Value| # Parameter | p-Value| #
|
||
Estimate Estimate Estimate Estimate
|
||
(SE) (SE) (SE) (SE)
|
||
Average # of re-inspections/ - 11.49 306 91 | 0.943 (3.44) 784 92 | -0.18 (3.21) .956 44
|
||
establishment/year (11.16)
|
||
Average # of 0.001 .306 91 - 0.058 .079 93 | 0.06 (0.031) .051 48
|
||
complaints/1,000 (0.000995) (0.033)
|
||
establishments/year
|
||
Average # of outbreaks/1,000 | 0.00089 78 92 0.579 .079 93 - 0.40 (0.50) A3 47
|
||
establishments/year (0.00323) (0.326)
|
||
Average # of Salmonella -0.00042 96 44 1.305 .051 48 0.035 43 47 -
|
||
cases/100,000 population (0.0074) (0.652) (0.044)
|
||
served/year
|
||
|
||
|
||
than agencies using numerical scores, but 5%
|
||
more Salmonella cases (Table 2). Almost one
|
||
third of agencies, however, using numerical
|
||
scores also used letter grades (Table 1).
|
||
|
||
Agencies that used a Critical/Noncritical
|
||
violation scheme reported 3% more mean
|
||
complaints but 3% fewer mean re-inspec-
|
||
tions, 27% fewer outbreaks, and 19% fewer
|
||
Salmonella cases than those using Priority-
|
||
Priority Foundations-Core schemes. Agencies
|
||
that used Risk Factor-Good Retail Practices
|
||
schemes tended to have fewer re-inspections
|
||
and complaints but more outbreaks and Sal-
|
||
monella cases than did agencies not using
|
||
these schemes (Table 2). Although most of
|
||
these findings are not statistically different
|
||
from each other, the overall pattern of results
|
||
is noteworthy.
|
||
|
||
Regarding associations between outcome
|
||
measures, we observed an almost statistically
|
||
significant relationship between reported
|
||
number of complaints/1,000 establishments/
|
||
year and number of Salmonella cases/100,000
|
||
population/year. Every unit of increase in
|
||
reported Salmonella cases/100,000 popula-
|
||
tion/year was associated with an increase in
|
||
1.03 complaints/1,000 establishments (p =
|
||
.051) (Table 4).
|
||
|
||
|
||
Discussion
|
||
|
||
The trends observed in this study comple-
|
||
ment the existing literature that supports
|
||
the value of transparency in the disclosure of
|
||
|
||
|
||
12 Volume 83 * Number 6
|
||
|
||
|
||
food establishment inspection data. Disclo-
|
||
sure at the point-of-service was associated
|
||
with fewer mean numbers of re-inspections,
|
||
complaints, outbreaks, and Salmonella cases
|
||
than disclosure online only, with a signifi-
|
||
cant difference (p = .03) in the number
|
||
of outbreaks between the two disclosure
|
||
methods. These findings are consistent with
|
||
previous studies in New York City and Los
|
||
Angeles that demonstrated benefits to dis-
|
||
closure at the point-of-service. In this study,
|
||
disclosure at the point-of-service included
|
||
posting of inspection results inside and
|
||
outside of the food establishment. It was
|
||
not the goal of this study to parse the out-
|
||
comes resulting from disclosures of inspec-
|
||
tion results posted inside or outside of food
|
||
establishments. Future studies might be
|
||
warranted to evaluate the effectiveness of
|
||
the nuance of disclosure location at food
|
||
establishments.
|
||
|
||
Letter grading methods were associated
|
||
with fewer complaints and outbreaks than
|
||
numerical scoring methods but both meth-
|
||
ods had better outcomes than for inspections
|
||
in the absence of a grading system. The Criti-
|
||
cal/Noncritical inspection violation scheme
|
||
was associated with fewer outbreaks and Sal-
|
||
monella cases than Priority-Priority Founda-
|
||
tions-Core or Risk Factor-Good Retail Prac-
|
||
tices schemes. These results suggest that how
|
||
local agencies conduct and score food estab-
|
||
lishment inspections and disclose results
|
||
|
||
|
||
to the public likely affect the success of the
|
||
programs to control and prevent foodborne
|
||
illnesses and food safety hazards.
|
||
|
||
A strength of this study is that use of the
|
||
Retail Program Standards listserv allowed
|
||
for direct contact and survey dissemination
|
||
to managers or primary contacts of food
|
||
establishment inspection programs. The use
|
||
of this listserv also enabled access to a wide
|
||
geographic range of potential respondents,
|
||
as this program includes agencies from
|
||
all 50 states and Washington, DC, as well
|
||
as five U.S. territories: American Samoa,
|
||
Guam, Northern Mariana Islands, Puerto
|
||
Rico, and the Virgin Islands. Additionally,
|
||
given the variations in inspection practices,
|
||
many survey questions included an open-
|
||
text option for “Other” answers that were
|
||
not listed as potential answer choices. This
|
||
feature allowed for the capture of unique or
|
||
less common practices.
|
||
|
||
There are several limitations to this
|
||
study. First, the presence of selection bias
|
||
cannot be understated given the use of a
|
||
convenience sample of survey recipients
|
||
and online recruitment, which limits the
|
||
representativeness of the results to those
|
||
who participated in the FDA Retail Food
|
||
Program. Second, Salmonella cases were
|
||
self-reported. Many inspection agencies do
|
||
not track the number of Salmonella cases,
|
||
as that is typically the duty of epidemiol-
|
||
ogy divisions. As such, the number of cases
|
||
|
||
|
||
reported by survey respondents might not
|
||
reflect true case counts. Third, missing data
|
||
and an abbreviated collection period weak-
|
||
ened the survey data analysis; the data col-
|
||
lection period was truncated by local and
|
||
state health departments needing to focus
|
||
on the COVID-19 pandemic response. This
|
||
necessity limited the ability to obtain miss-
|
||
ing data points and limited the ability of
|
||
agencies to respond. Fourth, the survey did
|
||
not collect information about the number
|
||
and types of triggers for re-inspection of
|
||
an establishment, which vary across agen-
|
||
cies. A potential confounder might be the
|
||
size of the inspection agency or the num-
|
||
ber of inspectors, as agencies with more
|
||
inspectors or more aggressive practices
|
||
could potentially be able to conduct more
|
||
re-inspections or to detect more violations,
|
||
illnesses, and outbreaks than smaller agen-
|
||
cies. Fifth, the survey did not allow for cap-
|
||
ture of programmatic changes that occurred
|
||
between 2016 and 2018 (e.g., if a jurisdic-
|
||
tion updated its food code during this time).
|
||
|
||
|
||
"SS
|
||
|
||
|
||
References
|
||
|
||
|
||
Although most findings were not statisti-
|
||
cally significant on an individual basis due to
|
||
limitations in sample size, the overall pattern
|
||
of results supports and enhances the existing
|
||
literature on the performance of food estab-
|
||
lishment inspection programs. For example,
|
||
for every unit increase in complaints, there
|
||
was a corresponding increase in the number
|
||
of re-inspections. There was a similar rela-
|
||
tionship with reported foodborne outbreaks.
|
||
Future research should include a larger num-
|
||
ber of agencies by a factor of 2 or 3 to clarify
|
||
several of these relationships.
|
||
|
||
|
||
Conclusion
|
||
|
||
Overall, characteristics of food establishment
|
||
inspection programs appear to be associated
|
||
with foodborne illness and outcomes. These
|
||
results warrant future research efforts to
|
||
improve the effectiveness of these programs.
|
||
This study suggests that agencies that disclose
|
||
at the point-of-service reported 55% fewer
|
||
average number of outbreaks compared with
|
||
those using online disclosure only. Similarly,
|
||
|
||
|
||
applying a grading scheme as a summary
|
||
measure of inspection results was associated
|
||
with improved foodborne illness outcomes.
|
||
Policy makers should consider these findings
|
||
when evaluating program effectiveness mea-
|
||
sures and when considering changes to exist-
|
||
ing food inspection programs. “39M
|
||
|
||
|
||
Acknowledgements: This study was funded
|
||
through cooperative agreement 6NU380T
|
||
000300 between the Centers for Disease Con-
|
||
trol and Prevention (CDC) and the National
|
||
Environmental Health Association (NEHA).
|
||
The findings and conclusions are solely the
|
||
responsibility of the authors and do not nec-
|
||
essarily represent the official views of CDC
|
||
and NEHA.
|
||
|
||
|
||
Corresponding Author: Thuy N. Kim, Divi-
|
||
sion of Environmental Health Sciences, Uni-
|
||
versity of Minnesota School of Public Health,
|
||
420 Delaware Street SE, MMC 807, Minne-
|
||
apolis, MN 55455.
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||
|
||
E-mail: kim00977@umn.edu.
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|
||
Copyright 2021, National Environmental Health Association (www.neha.org)
|
||
|
||
|
||
January/February 2021 e Journal of Environmental Health 13
|
||
|
||
|