Restaurant Practices for Cooling Food in Minnesota: An Intervention Study

Abstract

Improper cooling of hot foods is a leading contributing factor to foodborne disease. Although the U.S. Food and Drug Administration (FDA) Food Code outlines the cooling parameters and methods to facilitate proper cooling, restaurants continue to have issues. The purpose of this study was to further examine restaurant cooling practices and determine the effect of an educational intervention on 30 Minnesota restaurants, each with a history of cooling violations. Descriptive data on restaurant cooling practices and a cooling curve were collected from each restaurant to determine compliance with the Food Code and to assess which cooling methods work best. Additionally, cooling education was provided to a manager and assessments were conducted preintervention, postintervention, and at the next routine inspection to determine if cooling knowledge improved. Restaurants were evaluated at their next routine inspection to see if cooling practices had changed and if cooling violations were present. Most study restaurants were not using appropriate cooling methods as per the Minnesota Food Code, and 53% of food items observed did not cool within required cooling parameters. Foods cooled in containers <3 inches in depth were significantly more likely to cool properly. Managers scored significantly higher on the postassessment and on the next routine inspection assessment than on the preassessment, suggesting that education on cooling can increase operator knowledge. Postintervention, 20% more kitchen managers reported having written cooling procedures and had verified their cooling process than was reported preintervention. However, the increase in knowledge and reported policy changes did not translate to a reduction in cooling violations at the next inspection. Our findings documented significant food safety gaps in restaurant cooling practices. Translation of knowledge into sustained, improved food safety practices remains a major challenge for the environmental health profession; overcoming this challenge should be a focus for behavioral scientists and others interested in improving practices in restaurants for the long term.

Introduction

Improper cooling of hot foods is a leading contributing factor to foodborne disease (Gould et al., 2013; Lipcsei et al., 2019). During 2009–2015, ∼9% of foodborne outbreaks in the United States were due to bacterial intoxication from pathogens such as Clostridium perfringens (Dewey-Mattia et al., 2018); these bacteria can multiply to disease-causing levels if food is cooled improperly (Doyle, 2002). Similarly, ∼10% of foodborne outbreaks in Minnesota each year are due to bacterial intoxication (Minnesota Department of Health, unpublished data, 2018), which are preventable if time–temperature control measures are properly implemented, including cooling.

To reduce the risk of foodborne disease, the U.S. Food and Drug Administration (FDA) Food Code (2017) includes guidelines for retail food service establishments to keep time and temperature control for safety foods. These guidelines state that food must be cooled from 135°F to 70°F within 2 h and from 135°F to 41°F within a total of 6 h (U.S. FDA, “FDA Food Code,” 2017). At the time of data collection for this study, the 1998 Minnesota Food Code was in effect, which stated that potentially hazardous foods (PHFs) must be cooled from 140°F to 70°F within 2 h and from 70°F to 41°F within 4 h (MN Dept. of Health, 1998).

The FDA Food Code contains guidelines, consistent with the 1998 Minnesota Food Code, on methods that help facilitate proper cooling, including placing food in shallow pans, using containers that facilitate heat transfer, adding ice as an ingredient, or other effective methods. However, there is no information on what methods or types of containers work best or a definition of “shallow.” In addition, the FDA recommends that operators monitor times and temperatures for cooling of foods to verify proper cooling (U.S. FDA, “Annex 3,” 2017). Recording times and temperatures in a cooling log is one way to provide verification.

Although these guidelines are in place, restaurants continue to struggle with proper cooling. An FDA study found that cooling was out of compliance in 72% (196) of the full-service restaurants where cooling was observed (U.S. FDA, “Report on the occurrence,” 2018). Another study of 420 restaurants concluded that many restaurants are not meeting FDA recommendations for cooling, and about one-third of kitchen managers did not know cooling regulations for their jurisdiction (Brown et al., 2014). Modeling conducted in the same study showed that about a third of restaurant cooling step observations had an estimated cooling rate that was slower than the Food Code guidelines (Schaffner et al., 2015). Restaurants are dynamic and fast-paced, making it difficult to monitor cooling of foods. Additionally, inspectors are only in restaurants for a snapshot of time, so it is difficult to determine Food Code compliance. Training and other intervention efforts are needed to teach restaurant operators how to cool food properly (Brown et al., 2014; Schaffner et al., 2015).

The purpose of this study was to further examine restaurant cooling practices and to determine the effect of an educational intervention on restaurant cooling practices. Specific study objectives were to (1) collect descriptive data on restaurant cooling practices; (2) capture a cooling curve on a PHF in each restaurant to determine compliance with the Food Code and assess which cooling methods work best; and (3) determine if providing cooling education to managers would increase knowledge and result in changes to restaurant cooling practices.

Materials and Methods

Two Minnesota Department of Health (MDH) environmental health specialists, both registered sanitarians, collected data from September 2016 to May 2017 from a convenience sample of 30 restaurants in 5 Minnesota counties. Inspectors in these counties were asked to provide a list of restaurants that had a cooling violation on their last routine inspection. In total, 37 restaurant names were provided to the specialists, of those, three restaurants were excluded because the restaurant manager did not speak English and four refused to participate. The five counties represented both rural and metropolitan areas of the state and are regulated by MDH. A restaurant was defined as an establishment that prepares and serves food or beverages to customers, but is not an institution, food cart, mobile food unit, temporary food stand, supermarket, or caterer.

Specialists recruited restaurants by telephone. Restaurants were told that data on cooling practices would be collected at three points in time: preintervention, postintervention, and at the next routine inspection. Participating restaurants received a DeltaTrak thermometer ($50 value) as an incentive to participate. Kitchen managers (defined as a manager with authority over the kitchen) (hereafter referred to as manager) were told that participation was voluntary and nonregulatory and that all data collected would not be identifiable. They were also told that their inspector might accompany the specialist during the visit and that improperly cooled food could not be served to customers.

Preintervention

The first appointment was scheduled at a time that would coincide with the beginning of the restaurants' cooling processes of at least one PHF (selected by the manager). Specialists placed a data logger in the center of the food item to collect a cooling curve of that product. Observations on the cooling methods were noted. Managers were told to cool the food as they normally would, to keep the probe in the center of the food, and to not turn the probe off or remove it from the food item.

Specialists also interviewed the manager about restaurant characteristics and cooling practices and administered a nine-question multiple-choice assessment (preassessment) (Supplementary Fig. S1). Scoring was out of nine, and there was only one correct answer for each question.

Educational intervention

The specialist returned for a second appointment (often later that same day) to complete cooling observations, collect the data logger, and provide the educational intervention to the manager. The educational intervention took 30–45 min and consisted of verbally explaining an infographic (Supplementary Fig. S2) about cooling, sharing a cooling fact sheet (Supplementary Fig. S3) and a cooling log, and downloading and discussing the cooling curve collected. Specialists had standardized guidelines on how to deliver the educational component. Then, the assessment was conducted again (postintervention assessment) to measure any changes in the manager's knowledge.

Next routine inspection

Cooling practices were assessed again at the restaurants' next routine inspection, which occurred on average 240 d (range: 19–427 d, median: 286 d) after the intervention. Inspectors interviewed managers on cooling practices and provided the same assessment. Due to turnover and scheduling, the manager from the first two appointments was not necessarily the one being assessed during the routine inspection. Specialists reviewed the routine inspection report and noted if cooling violations were written.

To assess the impact of study interventions on the 30 restaurants, specialists reviewed data from 6507 routine restaurant inspections conducted under MDH jurisdiction in 2016 and compiled a list of restaurants with at least one cooling violation (minus the 30 study restaurants). Inspection data on those restaurants' next routine inspection (conducted in 2017 or 2018) were reviewed to see if they had another cooling violation.

DeltaTrak model 20902 data loggers, precalibrated and set to collect time and temperature data in 5-min intervals, were used to capture cooling curves. Temperatures of the refrigerator units were taken with a calibrated thermometer from the area where the food item was cooling. Descriptive and quantitative data analyses were performed with Microsoft Excel 2017 and SAS 9.4. p-Values <0.05 were considered statistically significant; associations with p-values <0.10 were also noted.

Results

Most of the 30 study restaurants were independent restaurants (83%, 25); the remaining 17% (5) were chains. The majority (53%, 16) of managers interviewed had been working as managers in the restaurants for 2–5 years.

Restaurant cooling practices

Preintervention, 87% (26) of managers self-reported that they had a formal procedure for cooling PHFs (Table 1). Of these, 19% (5) reported that the procedures were written and 62% (16) reported that they had tested and verified the process. Twenty-three percent (7) of managers reported recording times and temperatures in a log, and logs were verified visually by the specialist.

Table 1.

Restaurant Cooling Practices (Ascertained by Manager Interview)

	Pre (n = 30)^a		Routine (n = 29)^b
	n	%	n	%
How long have you been a kitchen manager at this restaurant?
<2 years	2	7	—	—
2–5 years	16	53	—	—
6–10 years	3	10	—	—
11–20 years	5	17	—	—
>20 years	3	10	—	—
Refused	1	3	—	—
Does this restaurant have a formal procedure or process for cooling potentially hazardous foods?
Yes	26	87	29	100
No	3	10	—	—
Unsure	1	3	—	—
Are the procedures or processes written? (Pre: n = 26)
Yes	5	19	12	41
No	21	81	16	55
Unsure	—	—	1	3
Are the cooling procedures tested and verified? (Pre: n = 26)
Yes	16	62	24	83
No	9	35	3	10
Unsure	1	3	2	7
Do you record times and temperatures in a cooling log?
Yes	7	23	9	31
No	22	73	20	69
Unsure	1	3	—	—

Cooling logs were also visually verified by specialists and inspectors.

Pre means preintervention.

At the next routine inspection (routine), one restaurant had closed, n = 29.

At the routine inspection, all 29 managers interviewed (one restaurant had closed) said that they had a formal procedure for cooling PHFs. Forty-one percent (12) reported that the procedures are written, 83% (24) had tested and verified the process, and 31% (9) said they record times and temperatures in a log (visual verification by inspector). Sixty-two percent (18) of managers reported that they had made changes to their cooling practices since participating in the study. Reported changes included using shallow containers and stainless steel containers, using ice wands, and taking temperatures throughout the cooling process.

Cooling methods were observed on 34 food items: in 4 restaurants, 2 food items were observed. Types of PHFs varied and included soups, pasta, rice, meat, and sauces. Fifty-three percent (18) of foods were cooled in a stainless steel container, 35% (12) in a container <3 inches in depth, 35% (12) were stirred at some point during the cooling process, 32% (11) in an ice bath, and 26% (9) with an ice wand. Almost all (94%, 32) food items were ventilated (uncovered or loosely covered) and none were stacked.

Sixty-five percent (22) of foods were cooled using a combination of two or more of the following methods: stainless steel container, depth <3 inches, stirring, ice bath, or ice wand. Eighty-two percent (28) of foods were cooled in a refrigerator, 9% (3) in a freezer, and one in both. Most (86%, 24) refrigerators used to cool food were at or below 41°F. Eleven percent (3) of refrigerators were above 41°F.

Cooling curves

Thirty-three cooling curves were collected (Supplementary Fig. S4). For one food item, the data logger was not working properly, so start and end times and temperatures were used to determine compliance. Some food items were not completely cooled to 41°F when the specialist returned to collect the data logger. As a result, analysis on the cooling curves was grouped into the two cooling requirements outlined in the Minnesota Food Code: (1) 140°F to 70°F within 2 h and (2) 70°F to 41°F within 4 h. Fifty-nine percent (20) of the 34 foods met the first requirement. Of the 25 foods that had completely cooled, 68% (17) met the second requirement. Overall, 53% (18) of the 34 foods did not meet at least one of the cooling parameters.

Exploratory data analysis of cooling methods

Due to the limited number of food items that had completely cooled by the time data loggers were obtained, only the first cooling requirement (140–70°F within 2 h) was used to assess the effectiveness of the cooling methods (Table 2). Food cooled in containers <3 inches in depth was significantly more likely to meet the first cooling requirement (p = 0.035). There was also evidence that food cooled in stainless steel containers (p = 0.091) and food cooled in restaurants that had a written cooling procedure (p = 0.066) were more likely to meet the first cooling requirement. There were no significant differences in food items that were cooled using an ice bath, an ice wand, or a combination of two or more cooling methods.

Table 2.

Contingency Table of Cooling Methods and Achieving the First Parameter of Cooling Criteria

Cooling method	First guideline		Sig.^a
	Cooling from 140°F to 70°F within 2 h
	Yes	No
<3 Inches
Yes	10	2	0.035
No	10	12
Written procedures
Yes	7	1	0.067
No	13	13
Stainless steel
Yes	13	5	0.091
No	7	9
>2 Methods
Yes	15	7	0.128
No	5	7
Ice bath
Yes	7	4	0.495
No	13	10
Ice wand
Yes	5	4	0.736
No	15	10

n = 34.

Fisher's exact test right-sided Pr ≥ F.

Manager assessment scores

There was a significant increase in managers' scores from pre- to postintervention (p < 0.0001) (Table 3). There also was a significant increase in managers' scores from preintervention to the routine inspection (p = 0.01). However, postintervention scores were significantly better than scores at the next routine inspection (p < 0.001).

Table 3.

Comparison of Cooling Knowledge Assessment Scores for Managers Pre- and Postintervention

Mean (SD)		Mean difference^a	95% CI	t-statistic (df)	p
Pre vs. post^b
5.2 (1.18)	7.8 (1.14)	2.6	2.1–3.1	11.4 (31)	<0.0001
Pre vs. routine^c
5.2 (1.18)	6.1 (1.74)	1.5	0.9–2.1	2.5 (58)	0.01
Post vs. routine^c
7.8 (1.14)	6.1 (1.74)	1.6	0.8–2.4	4.2 (45)	<0.001

Routine has an n = 28, 1 establishment had closed, and in one establishment, the assessment was not completed.

Mean difference calculated by taking postscore minus prescore, routine score minus prescore, and postscore minus routine score.

For same respondents, a paired t-test was performed.

Where respondents may have differed, an independent t-test was performed.

CI, confidence interval; SD, standard deviation.

Postintervention inspection data

Of the 6507 restaurants at which a routine inspection was conducted by MDH in 2016, 472 (7%) had one or more cooling violations. Of those, 18% (84) had one or more cooling violations on their next routine inspection. In the study population, of the 29 establishments still in operation, 31% (9) had one or more cooling violations on their next routine inspection. When using a chi-square goodness-of-fit test, the difference between the baseline group and study group was not statistically significant (p = 0.07).

Discussion

Many managers were not following Food Code guidelines to facilitate proper cooling. Most managers reported that they had a formal procedure for cooling, but many had not verified that their cooling process worked, and few had written procedures or recorded temperatures in a log. These findings were almost identical to the manager-reported practices reported by Brown et al. (2012).

After the intervention, 20% more managers reported that their procedures had been verified, and an additional two restaurants were recording times and temperatures in a log. Although these changes were small, they could result in better practices. Testing and verification of times and temperatures are recommended best practices in the Food Code. The likelihood of temperature abuse is reduced when employees are monitoring food temperatures (U.S. FDA, “Annex 3,” 2017). Similarly, by not having written procedures for cooling, food workers may deviate from the establishment's cooling process or use methods that hinder cooling. Additional research looking into the social and behavioral factors affecting policy and procedure compliance would be beneficial.

The majority of restaurants were not utilizing proper cooling methods; only half cooled food in stainless steel containers and only about a third used containers <3 inches in depth or stirred the food. This resulted in almost half of the food items not meeting the cooling parameters required in the Food Code. Just over half of the foods cooled from 140°F to 70°F within 2 h. The initial 2-h cool period is a critical element of this cooling process (U.S. FDA, “Annex 3,” 2017) and necessary to minimize the time that food is kept in the temperature danger zone (U.S. FDA, “Danger Zone,” 2017). Clostridium perfringens, the leading cause of bacterial foodborne intoxication outbreaks, can grow very rapidly between 109°F and 117°F. Therefore, it is important for food to cool rapidly during this first step to prevent bacterial amplification (CDC, 2018).

It is critical that establishments use a combination of cooling methods to help achieve cooling success, but it does appear that some cooling methods, such as cooling in containers <3 inches in depth, may be more effective than others. By reducing the volume of food in an individual container, the rate of cooling is dramatically increased (Schaffner et al., 2015, U.S. FDA, “Annex 3,” 2017).

The use of stainless steel containers and having formal, written cooling procedures were also variables of interest. Stainless steel allows for better heat transfer than plastic containers, which slow cooling (U of M extension, 2018). Written procedures indicate that employees are more likely to have been trained on the cooling process and could be an indicator of good, active managerial control. Further research is needed to fully assess the success of these methods. Clear guidance on what is considered shallow and what containers best facilitate heat transfer would be beneficial to operators and regulators.

Providing cooling education improved manager knowledge scores. The large increase in postassessment compared with preassessment scores may partly be due to a carryover effect (Bjorndal, 2018) since most managers took the pre- and postassessments within a day. However, the routine inspection scores were also significantly higher than preassessment scores, suggesting that a long-term increase in knowledge may have occurred. Postassessment scores were significantly higher than scores at the routine inspection, which could indicate that knowledge gained decreases over time, highlighting the need for periodic refresher training. Additional research on manager training and how it relates to long-term changes in practice is necessary.

Increased manager knowledge did not decrease the number of cooling violations on future inspections. Study restaurants, compared with all MDH restaurants, had a higher percentage of cooling violations on their next routine inspection. Although this difference was not significant, it is still concerning.

It is likely that many cooling violations are being undocumented on routine inspections because inspectors are only in the restaurant for a small portion of operating hours; inspectors may have looked more closely at cooling practices onsite in the study restaurants, allowing them to find more violations. Additionally, most study restaurants were independent restaurants with managers working at the restaurant for 5 years or less. Research has shown that independent restaurants have more food safety issues than chain restaurants due to inadequate training of staff and no formal policies (Brown et al., 2014) and that inexperienced managers have less food safety knowledge and training to ensure good practices (Brown et al., 2014). High employee turnover and physical facility or equipment constraints are other factors that may affect the inability to maintain practice changes.

This study had several limitations, we used a convenience sample of restaurants with English-speaking managers; therefore, the restaurants included in this study may not represent all restaurants that cool food within Minnesota. Due to our small sample size, there was a lack of power, making it difficult to determine factors of significance. Additionally, self-reported data were collected through manager interviews and may be affected by social desirability bias. Percentages of restaurants with food safety errors should be viewed as minimum estimates. Last, our conclusions regarding manager knowledge at the routine inspection have limitations since managers who took the pre- and postassessments may have not been the same, and the length of time routine inspections were conducted after the intervention varied, potentially affecting knowledge retention.

Conclusions

This study identified significant food safety gaps in cooling. Restaurant managers were often unaware of the requirements pertaining to proper cooling and did not utilize cooling methods to cool food as outlined in the Food Code, resulting in improperly cooled food. Our results suggest that education on cooling can increase manager knowledge; however, this did not translate into fewer cooling violations in the next routine inspection.

The lack of translation of knowledge into sustained, improved food safety practices remains a major challenge for the environmental health profession; overcoming this challenge should be a focus for behavioral scientists and others interested in improving practices in restaurants in the long term. Restaurants are dynamic environments and it can be difficult for food workers to closely monitor cooling of food. Training food workers and regulatory staff on cooling methods that best facilitate rapid cooling, such as portioning food into shallow containers with a depth of <3 inches, can help address the issue of improper cooling.

Footnotes

Acknowledgments

The authors would like to extend special thanks to the sanitarians who allowed them to collect data within their inspecting jurisdictions and to Leeann Austin (MDH), Deanna Scher (MDH), Kim Carlton (MDH), Dr. Laura Brown (CDC), Dr. E. Rickamer Hoover (Laulima Government Solutions, LLC), and Greg Stevens (MDH).

Disclosure Statement

No competing financial interests exist.

Funding Information

This study was supported by CDC awards funded under the Environmental Health Specialists Network Cooperative Agreement (grant no. U01-EH001295-02).

Supplementary Material

Supplementary Figure S1

Supplementary Figure S2

Supplementary Figure S3

Supplementary Figure S4

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