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Journal of Food Protection, Vol. 80, No. 4, 2017, Pages 674–684
Copyright !, International Association for Food Protection
Research Paper
Twenty-Two Years of U.S. Meat and Poultry Product Recalls:
Implications for Food Safety and Food Waste
Informatics Institute and 2Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign,
Urbana, Illinois 61801, USA
MS 16-388: Received 8 September 2016/Accepted 17 December 2016/Published Online 15 March 2017
The U.S. Department of Agriculture, Food Safety and Inspection Service maintains a recall case archive of meat and poultry
product recalls from 1994 to the present. In this study, we collected all recall records from 1994 to 2015 and extracted the recall
date, meat or poultry species implicated, reason for recall, recall class, and pounds of product recalled and recovered. Of a total of
1,515 records analyzed, the top three reasons for recall were contamination with Listeria, undeclared allergens, and Shiga toxin–
producing Escherichia coli. Class I recalls (due to a hazard with a reasonable probability of causing adverse health consequences
or death) represented 71% (1,075 of 1,515) of the total recalls. The amounts of product recalled and recovered per event were
approximately lognormally distributed. The mean amount of product recalled and recovered was 6,800 and 1,000 lb (3,087 and
454 kg), respectively (standard deviation, 1.23 and 1.56 log lb, respectively). The total amount of product recalled in the 22-year
evaluation period was 690 million lb (313 million kg), and the largest single recall involved 140 million lb (64 million kg) (21%
of the total). In every data category subset, the largest recall represented .10% of the total product recalled in the set. The amount
of product recovered was known for only 944 recalls. In 12% of those recalls (110 of 944), no product was recovered. In the
remaining recalls, the median recovery was 29% of the product. The number of recalls per year was 24 to 150. Recall counts and
amounts of product recalled over the 22-year evaluation period did not regularly increase by year, in contrast to the regular
increase in U.S. meat and poultry production over the same time period. Overall, these data suggest that (i) meat and poultry
recalls were heavily skewed toward class I recalls, suggesting recalls were focused on improving food safety, (ii) numbers of
products and amounts of each product recalled were highly variable but did not increase over time, and (iii) the direct contribution
of recalls to the food waste stream was associated with the largest recalls.
Key words: Food product recall; Food safety; Food Safety and Inspection Service; Food waste
The U.S. Department of Agriculture (USDA), Food
Safety and Inspection Service (FSIS) is responsible for
coordinating with U.S. firms that voluntarily recall meat and
poultry products that they have reason to believe are
adulterated or misbranded under the Federal Meat Inspection
Act or the Poultry Products Inspection Act (25). These
recalls serve to (i) protect public health by removing
adulterated or otherwise hazardous foods from commerce
and (ii) ensure fair trade by removing misbranded foods.
Reflecting these dual concerns, recalls overseen by the FSIS
are classified into three categories of public health concern:
class I, indicating a hazard with a reasonable probability of
causing adverse health consequences or death, such as
Listeria monocytogenes in ready-to-eat meat products; class
II, indicating a remote possibility of adverse health
consequences, such as a small amount of a mild allergen;
and class III, indicating no health hazard, such as
misbranding due to excess water.
* Author for correspondence. Tel: 217-265-0963; Fax: 217-265-0925;
E-mail: [email protected]
As part of their regulatory activities, the FSIS maintains
an online case archive (27), which contains records for all
recalls from 1994 to the present. Records for most recalls
include recall dates, food product descriptions, meat or
poultry species implicated, the reason for recall, recall class,
and quantitative data on the amount of product recalled and
the amount recovered. These data represent a comprehensive
recent history record of U.S. meat and poultry recall activity.
To the best of our knowledge, no comprehensive
analysis has been conducted on the extent or implications of
the FSIS recall data, although partial analyses do exist. For
each year since 2005, the FSIS has posted a summary page
with the number of recalls and the amount of food recalled
tabulated by recall class, reason for recall, and animal
species. Other reports have included the number of and
reasons for FSIS meat recalls from 1982 to 1998 (8),
manually coded data from 2006 to 2010 reporting reasons
and total amount recalled by species (5), tabulated recalls for
Escherichia coli O157:H7 in ground beef from 1994 to 2011
(18), and the number and amount of product recalled in 2011
(19). An analysis of the impact of recalls on stock prices of
publicly traded companies revealed that 13% of recalls were
J. Food Prot., Vol. 80, No. 4
from public companies and these recalls affected 45% of the
638 million lb (290 million kg) of products recalled from
1994 to 2013 (12). A comprehensive description of meat and
poultry recalls in the United States is needed covering the
time period of 1994 to the present.
Recall data have various implications for meat and
poultry safety and the food waste stream. Concerning food
safety, foodborne pathogens are estimated to cause 48
million illnesses and 3,000 deaths in the United States each
year (16, 17). Using U.S. outbreak data from 1998 to 2008
for attribution, 22% of illnesses and 29% of deaths due to
domestically acquired foodborne infections were attributed
to meat and poultry sources (9). Because class I and class II
recalls are intended to remove hazardous foods from
commerce, these recalls can be used to improve food safety.
Concerning food waste, the USDA Economic Research
Service estimates that 10 to 40% of food produced in the
United States each year is lost at the retail and consumer
level, depending on the commodity category (1). Because
these recall records quantify the amount of product recalled
and recovered, they can shed light on the direct contribution
of these recalls to the food waste stream in the United States.
These data describe the amount of recalled product
recovered by manufacturers, which must then either be
disposed through destruction, reworking, or relabeling (25);
in our analysis, we consider this disposed food to be wasted.
However, recovered food does not completely account for
all food waste associated with a recall. For example, sales of
frankfurter brands declined on average 22% following a
recall for L. monocytogenes contamination (20). Consumer
response may extend beyond the recalled brand to reduced
demand for the entire commodity category, both for foods
regulated by the FSIS (8) and by the U.S. Food and Drug
Administration (FDA) (10). However, FSIS-regulated food
recall and recovery is a concrete source of food waste that
should be quantified comprehensively.
Lack of a rigorous analysis of FSIS recalls may
contribute to potentially misleading commentary in the
nonacademic press concerning food safety and food waste.
For example, a Swiss insurance company collected 10 years
of data on both FDA- and FSIS-regulated food recalls and,
after acknowledging that a first look showed high variability,
compared recall counts from 2002 through 2004 with those
from 2012 through 2014 to claim that the number of recalls
is increasing (7). In a report in a major U.S. newspaper on 10
notable product safety recalls, three food safety recalls were
highlighted: a pet food melamine recall in 2007, a peanut
product Salmonella recall in 2009, and a ‘‘largest-ever meat
recall’’ of 143 million lb (65 million kg) of beef in 2008 due
to improper inspection (2). The statistics in these reports are
not technically inaccurate, but they lack full context, such as
the overall trends in the number and size of recalls over time.
To address the gaps in the literature, the goals of this
study were to systematically describe the extent of meat and
poultry recalls in the United States over a 22-year period and
to analyze trends in numbers and sizes of recalls by year,
severity class, reason for recall, and meat species. We also
explored the possible implications of these data for the food
safety drivers of recalls (the vast majority of recalls were
class I) and the amount of food wasted. The largest recalls
disproportionally impacted the total amount of recalled and
recovered product, although amounts were small compared
with the total U.S. production.
The main data set for this study was the FSIS recall case
archive (27). This online archive includes press releases for recalls
from 1994 to the present (2016) categorized by year. Although
records differ in format across years, from coded tables to plain text
entries, the records for most recalls include recall dates, food
product descriptions, meat or poultry species implicated, the reason
for recall, recall class, and quantitative data on the amount of
product recalled and recovered. The process of organizing these
data involved (i) data collection, i.e., the processes of downloading
recall records for each year in whatever aggregated or individual
record format was available, (ii) data cleaning, i.e., extracting
uniform metadata for each record to facilitate comparison between
years, and (iii) statistical analysis of the cleaned data set. Here, we
present the conceptual details involved in the data collection and
analysis, with complete data processing detailed in a supplemental
technical appendix. Additional supplemental materials contain the
final data set and code used to clean and analyze the data.
Intermediate data are available from the corresponding author upon
Data collection. Accessing the recall case archive requires
browsing the FSIS Web site for each specific year. Comparison of
these data is challenging because they are formatted differently
depending on the year. It was necessary to use a different method
for collecting and cleaning the data associated for each recall
record. We identified four data structures for date ranges 1994 to
1999, 2000 to 2004, 2005, and 2006 to 2015.
Our approach to gathering data included downloading Excel
(Microsoft, Redmond, WA) information, when available, and
using a series of scripts written in Python (version 2.7.11, Python
Software Foundation, to automate the
process of downloading each record, parsing each record source,
and placing the results into a database. Records were uniquely
identified by their recall case number and tagged with their origin.
Any footnotes for each year were placed into a separate text file for
In some cases, depending on the date category, basic
information about the recall was provided as a formatted table of
information, such as the date of recall, the amount of product
recovered, and a unique case number embedded into a hyperlink
pointing towards a press release that contained more detail. In other
cases, all of the relevant information for the recall was unified into
a single data record and presented as a list of information without
the press release available. When a recall extension is issued, two
separate records may be created. When a recall has not been
closed, it either may not appear in the list of recalls for the year or
may have values updated over time. When multiple records were
found for the same recall case number, the records were merged,
retaining the report of the largest amount of product recalled or
recovered. The final data download occurred on 7 July 2016, so
records open at that time may be subsequently updated when
Data cleaning. Once all data were downloaded, the data were
processed by year into a single matrix for statistical analysis. This
process involved splitting the data into groups by year, formatting
each group, parsing individual records into data fields, merging
duplicate records, and cleaning up nonstandard record values.
Provenance was established through hierarchical files and folders
to trace changes made during each step of the data cleaning
process. Each folder contains the working data, Python code used,
and a log file. OpenRefine (version 2.6-rc.2 [TRUNK], https:// was used to collapse plain-text fields into
standardized values for product species, reason for recall, amounts
of product recalled or recovered, and recall class.
Specific key words (pork, veal, beef, etc.) were used to
identify species. All records were classified as either beef, pork,
poultry, or mixed, consistent with the FSIS summary table
classifications. Records with an ambiguous product type, e.g.,
‘‘sausage,’’ were manually reviewed to identify additional key
words that may indicate species. Any product that was not
identifiable as only beef, pork, or poultry was classified as mixed.
A table of all key words used for species assignment is presented in
the supplemental technical appendix. A review of the manually
tagged records compared with the FSIS summary tables for 2005
through 2015 showed a tendency to overclassify species as mixed,
with 32% of records tagged as mixed compared with 23% of
records reported by the FSIS as mixed. Some differences in
classification is expected because we used only those key words
available in the recall records, whereas FSIS has access to
additional documentation that could be used to better classify
records with ambiguous reports.
Similar to product species data cleaning, key words were used
to identify reasons for recall according to the FSIS summary table
classifications of extraneous material, Listeria, processing defect,
Salmonella, Shiga toxin–producing E. coli (STEC), undeclared
allergen, undeclared substance, and other. A table of all key words
used for reason assignment is presented in the supplemental
technical appendix.
Amounts of product recalled and recovered were coded to
differentiate three classes of values: (i) numeric data, where a recall
size in pounds was available, (ii) missing data, where no
information was reported, and (iii) insufficient data, where text
fields such as ‘‘undetermined’’ made it impossible to assign a
numeric value to the field. Numeric data included 0 values. In five
recall records, the numeric value for pounds recalled was 0. For the
two records from 2014, the recall notice text indicated these were
recalls for an undetermined amount and were then recoded as such;
for the three records from 1995 there were no associated press
release. Because it is illogical to issue a recall for no food, these
records were recoded as undetermined.
When no recall class was reported for recalls with a reason
given as Listeria or STEC, those recalls were assigned to recall
class I, consistent with the facts that (i) every Listeria and STEC
recall with an assigned class is a class I recall and (ii) these
foodborne pathogens can cause lethal illness. Recalls for other
reasons without a known class were designated as recall class
‘‘none assigned’’ because these recalls could be from any recall
Calculated variables. To facilitate analysis, the pounds of
product recalled and recovered were log transformed, adding a
value of 1 to allow for log transformation of zero values, e.g.,
recovered log ¼ log(recovered þ 1). All undetermined values were
treated as missing data.
The proportion of product recovered was calculated as the
ratio of recovered product to recalled product, i.e., Prrecovered ¼
recovered/recalled. The log transformation of the proportion of
product recovered was the difference of the log-transformed
values, i.e., Prrecovered_log ¼ log(recovered þ 1) # log(recalled þ 1).
The log transformation calculation has the advantage of presenting
recalls where no product was recovered (recovery ¼ 0) as a
J. Food Prot., Vol. 80, No. 4
negative log(recalled þ 1) value, rather than every value being
equal to 0 as is calculated using the simple proportion. For the 13
records where the quantity of product recalled was unknown but
the quantity recovered was reported, it was impossible to calculate
a proportion recovered; these data were excluded from the analysis.
To test for seasonal differences, we created a seasonal variable
from the date the recall notice was issued. We assigned the season
based upon the recall date being closest to an equinox or solstice
for the North American continent: spring equinox, summer
solstice, autumnal equinox, and winter solstice. Because the
solstice and equinox occur independently of the Gregorian
calendar, we chose the Python library Ephem (version,
commonly used for calculating astronomical events, to assign
Statistical analysis. Descriptive statistics and all plotting
were performed in R (version 3.2.3, R Foundation, Vienna).
Statistical testing including distribution fitting, linear regression,
and analysis of variance (ANOVA) were calculated in JMP
(version 12.0.1, SAS Institute, Cary, NC). These data contain the
full population of FSIS recalls over the 22-year period, less any
missing data in the records, which is not a representative sampling
of recalls. In this situation where the true distributions are known,
estimates such as means do not require formal statistical analysis.
We use standard ANOVA approaches to analyze the within- and
between-group differences in relation to the observed variability.
We gathered from the FSIS recall case archive all
recalls from the first year data were available (1994) through
the end of 2015. From each recall notification report,
standardized information was extracted for recall date, recall
class, meat species, reason for recall, amount of product
recalled, and amount of product recovered. Here, we report
the results of the analyses of these standardized data
regarding (i) the distribution of recalls among the various
categories, (ii) the quantities of meat recalled and recovered,
and (iii) trends over time. We also comment on the direct
contribution of meat and poultry recalls to the U.S. food
waste stream.
Descriptive statistics of FSIS recalls. We analyzed
1,515 meat recalls issued from 1994 to 2015 (Table 1), an
average of 69 recalls per year. The mean recall size was 3.83
log lb (6,800 lb [309 kg]), the standard deviation was 1.23
log lb, and the total size of all recalls was 8.84 log lb (690
million lb [313 million kg]); 45 recalls were of undetermined
size. The single largest recall was a class II recall of 8.16 log
lb (140 million lb [64 million kg]) of beef in 2008, initiated
when a firm processed nonambulatory cattle without proper
compliance with FSIS inspection regulations (22). Although
the quantity of product recovered during each recall was
available for only 1994 to 1999 and 2006 to 2015, these data
were available for 944 recalls; the mean recovery was 3.02
log lb (1,000 lb [454 kg]), the standard deviation was 1.56
log lb, and the total size of all recoveries was 8.21 log lb
(160 million lb [73 million kg]). In comparison, mean
product amount recalled over that time period was 3.88 log
lb (7,600 lb [345 kg]), and the total product recalled was
8.76 log lb (570 million lb [259 million kg]).
J. Food Prot., Vol. 80, No. 4
TABLE 1. Descriptive statistics for the FSIS recall case archive records from 1994 through 2015
Summary statistics for product amt (log lb)a
Mean Median
Maximum Sum
Mean Median
Maximum Sum
Full data set
1,515 3.83
3 …
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