UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON, D.C. 20460 

ocr o 7 2DJ4 

OFFICE OF CHEMICAL SAFETY 

AND POLLUTION PREVENTION 

MEMORANDUM 

SUBJECT: 

FROM: 

THRU: 

TO: 

Upper Bound Es~imate of the Likelihood of Insecticide Residues on Food 

Resulting from Treatment in Food Handling Establishments (DP 413125) 

Jonathan 

Biological 

Becker, 

Analysis 

Senior 

Branch 

Science Advisor f'r/ fhA_ ~~ 

Amet Jones, Chief, Biological Analysis Branch 

Yu-Ting Guilaran, Director 

Wynne Miller, Deputy Division Director 

Biological and Economic Analysis Division (7503P 

Dana Vogel, Acting Division Director 

Christina Swartz, Chief, Risk Assessment Branch II 

Health Effects Divison 

Office of Pesticide Programs (7509P) 

) 

Peer Review Panel Date: June 4, 2014 

1 
SUMMARY 

BEAD recommends that the value of 4.65% be used for the likelihood of a commodity having a 

residue resulting from non-fumigant pesticide treatment in food handling establishments. This 

value is an upper bound estimate of the likelihood that any given commodity would have a 

residue resulting from treatment in food handling establishments. BEAD is reasonably certain 

that this level will not be exceeded and is appropriately conservative for use in a dietary risk 

assessment. Federal Register language is provided in Appendix 1. 

INTRODUCTION 

This document describes the method developed by the Biological and Economic Analysis 

Division (BEAD) with the Health Effects Division to estimate the likelihood of a commodity 

having a residue resulting from non-fumigant pesticide treatment in food handling 

establishments (FHEs). This method should be used for all non-fumigant active ingredients 

(e.g., liquids and aerosols used as space sprays or as crack and crevice sprays). Fumigants used 

in FHEs (e.g., flour mills) may be assessed using a previously developed method (Cook, et al., 

2009). BEAD is reasonably certain that the recommended value is unlikely to be exceeded. This 

value is not chemical specific, and as such, may be used for any dietary assessment. 

For the purposes of this report, food handling establishments are divided into the following 

segments: 

• Food Processors- includes manufacturers of baked goods, canned goods, processed 

foods, meats, spices, and beverages. 

• Food Warehouses- includes food warehouses, distribution centers, and food ingredient 

warehouses. 

• Commercial Kitchens- includes institutional facilities (schools, prisons, government 

buildings and arenas), lodging and hospitality establishments (hotels and motels), and 

healthcare facilities (hospitals, nursing homes, and convalescent centers). 

• Restaurants- includes both full-service and fast-food types. 

• Grocery Stores - includes any retail grocery stores. Survey data on pest control practices 

in retail grocery stores are not available. BEAD estimated that the contribution of 

grocery stores to the recommended value is very small. This is discussed further in the 

characterization section below. 

A generalized schema showing the major relationships between these FHE segments is provided 

in Figure 1. This schema is simplified and only includes those channels of trade that involve the 

food handling establishments described above. 

Commodities move from the producer to either a food processor or to a warehouse facility of a 

packer/shipper/distributer. Once processing is completed, the food products are also transported 

2 
to warehouse facilities of distributors. From there, foods are distributed to commercial kitchens, 

restaurants and grocery stores, and from there to the consumers. 

METHODS AND DATA 

The proportion of food that reaches the consumer containing potential residues acquired during 

transit through food handling establishments is the sum of the food likely to be exposed in every 

upstream segment. For example, a food item purchased from a grocery store could have residues 

as a result of the food handling establishment being treated during while the food item was in the 

channel of trade (i.e., from the processor to the food warehouse to the grocery store). This 

means, for the purpose of estimation, the proportion of food passing through each segment and 

the proportion of commodity that might be exposed at each segment must be determined. Table 

1 provides the notation and definitions used in this estimation. 

Table 1. Notation and definitions. 

Variable Definition 

Percent of commodities transiting a given FHE segment. "x" is a placeholder for 

%Cx each FHE segment - Food Processor (%Cp ), Food Warehouse (%Cw ), 

Commercial Kitchens I Restaurants (%CcKJR), and Grocery Stores (%Co). 

Percent of commodity with potential residues. "x" is a placeholder for each FHE 

%Rx segment- Food Processor (%Rp), Food Warehouse (%Rw), Commercial Kitchens 

I Restaurants (%RcKJR), and Grocery Stores (%Ro). 

Likelihood of treatment in a FHE segment. "x" is a placeholder for each FHE 

Px(T) segment- Food Processor (Pp(T)), Food Warehouse (Pw(T)), Commercial 

Kitchens I Restaurants (PcKJR(T)), and Grocery Stores (Po(T)). 

%Form R~lative percent of pest control expenditures spent on forms of pesticide products 

(liquids and aerosols) that could result in residues on commodities. 

%Fac Percent of facilities in a FHE segment that use pest control. Kline (2008) reports 

that all facilities in every FHE segment use some pest control measure. 

Po(T) Single day probability for treatment in a FHE segment. 

This is equivalent to the 1 I (number of days between treatments). 

%Sx Percent of food obtained by the consumer from a grocery store (%So) or from a 

non-grocery store source (%ScKJR). 

Commodities Passing Through Each FHE Segment (%Cx) 

Division of Commodities between Food Processors and Shipper I Warehouses I Distributers 

As is shown in Figure 1, once produced, commodities, are divided into two streams - one stream 

going to food processors and the other stream to warehouses, shippers, and distribution centers. 

The determination of the relative amounts in each of these two paths is complicated by the 

definition of "processed" and the metric used to quantify it. 

3 
The definition of processed food range from washed and packaged fruits and vegetables (e.g., 

bagged spinach) to "ready-to-eat" foods that require minimal preparation (e.g., granola bars) 

(Denny 2014, Foodinsight 2010, Jacob 2014). For the purpose of this analysis processed foods 

are considered to be "packaged foods" such as processed frozen and canned food, ready-to-eat 

meals, snacks and candy, bakery goods, dairy products and condiments. Fresh foods include 

fruits, vegetables, eggs, nuts, beans, meat and seafood (Fairfield 2010). 

Estimates of the amount of processed food consumed have been based on two metrics -- total 

calories consumed per capita, and total pounds consumed per capita. Values for both metrics are 

based on studies conducted by USDA's Economic Research Service. The NY Coalition for 

Healthy School Food (2009) reports that approximately 69% of the calories consumed in the 

United States come from processed foods. Fairfield (2010) reports that in 2009 the annual per 

capita consumption in the United States is 787 pounds of packaged foods and 602 pounds of 

fresh foods. 

For this analysis BEAD has selected the per capita consumption measured in pounds as the most 

appropriate metric for this analysis. BEAD assumes that the percent of the commodities going to 

food processors (%Cp) is equal to the percentage of the US per capita consumption (in pounds) 

of packaged foods [787lb I (787 + 602) = 56.6%]. 

Division of Commodities between Commercial Kitchens/Restaurants and Grocery Stores 

As shown in Figure 1, from warehouses, commodities are distributed to consumers through 

eating establishments and through grocery stores. BEAD estimates the proportion of produce 

passing through these FHEs according to the origin of food items. 

The source and location of food items consumed among the General US Population were 

estimated using data from the last 3 cycles (2003104, 2005106, 2007108) of the National Health 

and Nutrition Examination Survey (NHANES), What We Eat in America (WWEIA) survey 

(CDC 2014). These data are used in the US EPA's DEEM FCID model (Ver 3.18). Further 

information on the NHANES WWEIA surveys, the DEEM Model, and the Food Commodity 

Intake Database (FDIC 2014) database can be found at the following web site 

(http:llwww.epa.govlpesticideslscienceldeem/). A total of27,638 respondents provided food 

consumption data over these 3 WWEIA cycles. The combined 2003-08 WWEIA database 

contains 55,277 food diaries. 

For each food consumption diary, WWEIA respondents are asked to list all food items that they 

consumed over the previous 24 hour period (24-hour recall), the time of day the item was 

consumed, the primary source of that food item and whether it was consumed at home or 

elsewhere. Ofthe 798,170 food items reportedly consumed among these respondents, 

approximately 71% (= 568,008 I 798,170) were obtained from a store, and the remaining 29% 

were obtained elsewhere (restaurants, schools, etc.). 

4 
Residues on Commodities in Each Segment (Px(T)) 

The proportion of commodities with residues as it leaves each segment is a function of the 

likelihood of a treatment that might leave residues occurring on a given day plus any upstream 

residues: 

%Rx = %UntreatedCx x Px(T) + %Rx-l. 

This assumes that the typical daily throughput would be present in the FHE (i.e., there would be 

no clearing of commodity prior to treatment). Further, this assumes only previously unexposed 

commodity will be exposed at every stage (%UntreatedCx = 1 - %Rx-I) and that residues 

accumulate as the commodities move through the FHEs. 

The probability of treatment potentially producing residues on a given day in a FHE segment is 

equal to the percent of the facilities in the FHE segment using pest control products multiplied by 

the daily probability of treatment and the percent of the pest control products in a form that can 

result in residues on commodities (i.e., liquids and aerosols). 

Px(T) = * Po(T) * % Formx 

Pesticide Usage in Food Handling Establishments 

The estimates developed in this document are based on a 2008 market survey of pest control in 

food handing establishments (Kline 2008). Table 2 provides background information about the 

number of establishments, the number of surveys conducted, and the approximate pest control 

purchases in each FHE segment. This survey also showed that all FHE facilities use some type 

of pest control product (% Facx = 1 00). 

Table 2. Segments, Surveys and Pest Control Purchases 

FHE Segment Number of Number of Surveys Pest Control Purchases 

Establishments Conducted* (approximate) 

Food Processors 45,368 100 $ 11,200,000 

Food Warehouses 2,010 79 $ 14,950,000 

Commercial 231,700 211 $ 29,900,000 

Kitchens 

Restaurants 237,600 companies at 300 $ 68,500,000 

391,000 locations .. *In additiOn to the segment surveys, another 60 pest management professiOnals servmg this 

industry were also surveyed. Grocery stores were not included in this survey. See 

characterization and uncertainty section. 

5 
Pesticide Formulations Used in Food Handling Establishments 

Kline (2008) reports the amount of pest control product expenditures by the form of the product. 

BEAD combined these data into two groups for each FHE segment and calculated the relative 

percentages. Forms that are unlikely to produce residues on food (e.g., rodent traps, bait stations, 

gel baits) were grouped into one category and forms that may produce residues (e.g., aerosols, 

surface sprays) were grouped into another category. Table 3 provides the relative percent of pest 

control expenditures by product form. 

Table 3. Percent of Pest Control Expenditures by Product Form 

Form Food Food Commercial Restaurants 

Processors Warehouses Kitchens 

Non-Liquid or Non-Aerosol* 64.2 61.8 53.3 53.9 

Liquids and Aerosols(% Form) 35.8 38.1 46.7 46.1 

*Non-hqmd or non-aerosol forms mclude baits, glue boards I traps, blocks I pellets, granules, 

dusts, powders, and other forms not specified. 

Probability o(Pesticide Treatment in Food Handling Establishments 

Kline (2008) reports the pest control treatment schedule and the percent of facilities in each 

category for each FHE segment. The single day probability for treatment is the inverse of time 

in days between treatments. For example, if a given facility is treated monthly the single day 

probability of a pest control treatment occurring is 3.3% (1/30 days =3.33% per day). 

Table 4 provides an example of this calculation for the restaurant segment. The single day 

treatment probability for this segment is equal to the percent of facilities in each treatment 

interval multiplied by the single day probability of that treatment interval, summed across all 

treatment intervals. 

Table 4. Example- Single Day Probability of Treatment for the FHE restaurants segment. 

Treatment Schedule Restaurants 

Interval Days in Single Day Percent of Facilities in Category Probability 

Interval Probability the Treatment Interval (weighted by% 

(1 I# Days) Facilities in Interval) 

Monthly 30 3.33% 65.0% 2.17% 

Every 2 weeks 14 7.14% 20.0% 1.43% 

Weekly 7 14.29% 8.0% 1.14% 

Every 2 or 3 months 75 1.33% 3.0% 0.04% 

Other* 21.06 4.75% 4.0% 0.19% 

Totals 100% 4.97% 

* Number of days IS calculated as a weighted average number of days across all FHE segments. 

Kline (2008) reports that all FHE facilities in their survey receive some sort of pest control. 

This, along with the calculated values shown in Tables 3 and 4, allows for the calculation of 

6 
Equation 1 for each FHE segment. The percent of facilities in each segment that use pest control 

products multiplied by the segment single day probability of treatment multiplied by the percent 

of expenditures on products that may produce residues yields the single day probability of 

treatment with product forms that may result in potential residues. The values for Px(T) are 

shown in Table 5. 

Table 5. Single Day Probability of Treatment with Product Forms Resulting in Potential Residues 

FHE Segment Percent of Segment Percent of Expenditures Single Day Probability 

Facilities in Single Day on Products That Could of Treatment with 

Segment Using Probability Result in Potential Product Forms 

Pest Control of Treatment Residues Resulting in Potential 

Products [Po(T)] (%Form) Residues 

(% Fac)* [Px(T)] 

Food Processors 100% 9.68% 35.8% 3.47% 

Food Warehouses 100% 5.23% 38.1% 1.99% 

Comm. Kitchens 100% 6.46% 46.7% 3.02% 

Restaurants 100% 4.97% 46.1% 2.29% 

Unweighted Average 2.65% 

of Restaurants & 

Comm. Kitchens .. . . * Kline (2008) reports that all fac1hties in every FI-lE segment use some pest control measure . 

** Restaurants account for a much larger share by volume of commodities based on number of 

establishments (Table 2) while commercial kitchens have a higher single day probability of 

treatment. Data to calculate this is lacking, but using an unweighted average likely overstates the 

probability of treatment. 

Residues on Commodities Consumed 

The next step is to mathematically accumulate the treatment probabilities as the food travels 

through the FHE segments from the producer to the consumer. This requires estimates of the 

relative amount of food moving through each segment (%Cx) and determining the probability of 

a treated commodity entering a given FHE segment with potential residues, the probability of 

treatment while in that segment [Px(T)], and the resulting residues in the food leaving the 

segment (%Rx). This can be expressed using the formulae below for each FHE segment. The 

results from these calculations are given in Table 6. 

For processors 

%Rp = Pp(T) * %Cp 

For warehouses 

%Rw = {%Rp + [(1- %Rp) * Pw(T)]} x %Cw 

For commercial kitchens and restaurants 

%RcKJR = {%Rw + [(1- %Rw) * PcKJR(T)]} x %CcKJR 

7 
For grocery stores 

%Ra = {[%Rw + [(1- %Rw) * Pa(T)] x %Co 

Table 6. Calculated values for the potential of finding residues inion commodities/food for each HIE 

segment. All values are in decimal percents. 

Packer I Commercial Kitchens Grocery 

Calculated Values Processor Warehouse I & Restaurants Stores 

Distributer Combined 

Entering Segment with Residues 0.00 0.0196* 0.0391 0.0391 

Untreated Amount 1.00 0.9804 0.9609 0.9609 

Probability of Treatment in 0.0347 0.0199 0.0265 0.000 Segment 

Newly Treated Amount 0.0347 0.0195 0.0255 0.000 

Leaving Segment 0.0347 0.0391 0.0647 0.0391 .. *This value IS based on 43.4% of commodities entermg the segment from producers (with zero 

residues) and 56.6% of commodities entering the segment from food processors (with 0.0347 

residues - see Table 5). 

The final step is to use the calculated values, combined with the source ofthe food consumed to 

determine the potential for consuming food with residues from FHE treatments, using the 

following equation: 

%Consumer (%RcKJR * %ScKJR) + (%Ra * %Sa) 

The values used for these calculations, as well as the results, are provide in Table 7. 

Table 7. Percent of total food consumed with potential residues from treatment in food handling 

establishments. 

Source Percent Residue Probability 

Food items not from grocery store 29% 0.0647 0.0187 

Food items from grocery store 71% 0.0391 0.0278 

Total 100% 0.0465 

CHARACTERIZATION AND RECOMMENDATIONS 

BEAD recommends that the value of 4.65% be used for the likelihood of a commodity having a 

residue resulting from non-fumigant pesticide treatment in food handling establishments. This 

value is an upper-bound estimate of the likelihood that any given commodity would have a 

residue resulting from treatment in food handling establishments. BEAD is reasonably certain 

that this level will not be exceeded and is appropriately conservative for use in a dietary risk 

assessment. 

8 
The characterization of this value as an upper bound estimate of the actual probability of 

consuming a food with residues from FHE treatment is based on a consideration of the 

following: 

• The recommended value is based on the assumption that only a single active ingredient is 

used in all of the food handling establishments for all liquid and aerosol pest control 

applications. The Kline (2008) survey shows that approximately 50 liquid or aerosol 

products containing well over a dozen active ingredients are used in FHEs. The 

assumption of a single active ingredient being used in all applications results in a very 

large over-estimation of the likelihood of potential residues. 

• Assumes that the facilities take no precautions, such as clearing processing lines, when 

making a pesticide treatment. 

• Assumes that the likelihood of treatment accumulates as the commodities travel through 

FHEs, thus maximizing the estimate of the total proportion of food exposed. Note that 

the magnitude of residues included in the dietary assessment is estimated or observed in a 

separate process and may reflect accumulated residues. 

• Assumes that commodity is exposed to residues no matter what packaging is used. Many 

products in commercial kitchens, restaurants, and warehouses are packaged in containers 

that limit or prevent direct contact with an insecticide. 

• Assumes that the facility is always treated according to the treatment schedule. 

Refrigerated and frozen products may not be treated as often as non-refrigerated food (i.e. 

temperatures below 50° F reduce insect feeding and development). 

• Assumes that the site of treatment (e.g. directly on food handling surfaces versus cracks 

and crevices) has no effect of the probability of residues on commodities. 

There remain several areas of uncertainty in the analysis. BEAD is reasonably certain that the 

effect of the following uncertainties would have a very small effect on the estimates: 

• Some pest control treatments may account for a larger percentage of expenditures than 

others. Currently, BEAD does not have sufficient information to account for this. 

• Grocery stores are not included in this definition of food handling establishments. There are 

no available survey data for pesticide used in this category. The contribution to the estimate 

is expected to be very small based on the following observations: 1) residence time of food 

in most grocery store is relatively short (stores are restocked frequently because of limited 

storage space and because of the need for "fresh" foods such as bread), 2) most fresh fruits 

and vegetables are refrigerated which substan~ially reduces the probability of a pest problem 

occurring that would be treated with sprays or aerosols, and 3) most of the remaining food is 

packaged in containers that prevents contamination by residues (e.g., canned) or is in a form 

that would not need treatment (.e.g., frozen). 

9 
• A small amount of food does not pass through FHEs (e.g., farmer markets) and therefore 

would not have residues from FHE treatments. The recommended value assumes all food 

passes through food handling establishments. This assumption results in a very small over 

estimation. 

10 
Figure 1. Simplified Flow of Commodities through Food Handling Establishments. 

56.6% of 1-

Producers I 43.4% of 

production 

+ 

production 

l l 

[~~:~~::;~;~::~! ------.. ~-~-~-~-~·_;_;_'o_o;_:_;_e~h-o-u-se_s_/_D_i_st-ri_b_u-to_r_s __. 

! 

Commercial Kitchens and Restaurants Stores 

PG(T) = 0.00 

%RG = 0.0391 PcK/R(T) = 0.0265 

%RcK/R =0.0647 

:'"""''"'""""' ''''''''"' '' '' '' ''"''' '"'' '"""""""""""""""' '"""""'''' ''' '' '' ''u~ 

29% of Food items 

not from grocery 

stores ! ................ ,_,, .......................... ----··---··········-·-······j 

Consumer 

4.65 %of total fool consumed 

~ith potential FHE residues 

r·······················-·-· .. ···-~- --·· ················ ·······--~ 

71 % of Food items 

from grocery stores 

! ..·-··-····-····························································' 

11 
REFERENCES 

CDC. 2014. NHANES WWEIA survey. This survey can be accessed through the following site: 

http://www.cdc.gov/nchs/nhanes/about nhanes.htm . 

Cook, C., J. Becker, and E. Rim. 2009. Revised Assessment of Percent Commodity Treated 

Values used in the Registrant's Dietary Exposure Assessment for Fluoride. (DP# 

361041 ). Biological and Economic Analysis Division memo to K. Davis, V. Eagle, 

Registration Division and M. Doherty, C. Swartz, Health Effects Division, Office of 

Pesticide Programs, US Environmental Protection Agency. 

Denny, S. 2014. Avoiding Processed Foods? Surprise! This is Processed Too! Academy of 

Nutrition and Dietetics. Retrieved 1 April 2014 from 

http://www .eatright.org/Public/content.aspx?id=64424 71055 

Fairfield, H. 2010. Factory Food. New York Times (based on work conducted by M. Gehlhar, 

USDA Economic Research Service). 

FCID, 2014. What We Eat in America- Food Commodity Intake Database, 2003-2008 

(WWEIA-FCID 2003-08). Available at http://fcid.foodrisk.org/. 

FDIC. 2014. Food Commodity Intake Database. The FCID database can be accessed at the 

following site: http://fcid.foodrisk.org/faq/. 

Foodinsight. 2010. What is a Processed Food? You Might Be Surprised! Handout 1 of'S. 

International Food Information Council Foundation. Available at: www.foodinsight.org 

Jacob, A. 2014. Processed Food Definition. Demand Media, Hearst Communications. 

Retrieved 1 April 2014 from http:/ /healthyeating.sfgate.com/processed-food-definition2074.html 

Kline Market Research. 2008. Pest Control in Food-Handling Establishments 2008: U.S. 

Market Analysis and Opportunities. Kline Market Research. 

New York Coalition for Healthy School Food, 2009. U.S. Food Consumption as a% of 

Calories. Based on USDA Economic Research Service Publication EIB33. 

USEPA. 2014. DEEM-FCID model. This model can be downloaded at the following site: 

http:/ /www.epa.gov/oppOOOO 1/science/deem/ 

12 
APPENDIX 1. F:gDERAL REGISTER LANGUAGE 

EPA estimates the percent of commodities treated in Food Handling Establishments (FHE) for 

new uses of active ingredients based on the best available information. This includes survey 

information on pesticide usage related to the number of facilities being treated, product forms 

used (e.g., liquids and aerosols), and treatment"schedule by FHE segments (e.g., warehouse, food 

processor, distributor, and restaurant). EPA also incorporated the best available information 

related to the transfer of commodities between various segments of food handing establishments 

and the percent of food consumed by location, either in the home or outside the home. 

All information currently available has been considered and EPA has concluded that for any 

active ingredient, including [Chemical], there is at most a 4.65% likelihood that a food 

commodity could contain potential residues resulting from one or more treatments while in the 

food handling establishment channel of trade. Similar to estimates of agricultural use, this 

estimate should be reconsidered in 5 years. 

13