UNITED ST A TES ENVIRONMENT AL PROTECTION AGENCY 

WASHINGTON, D.C. 20460 

OFFICE OF CHEMICAL SAFETY AND 

POLLUTION PREVENTION 

MEMORANDUM 

DATE: March 15, 2016 

SUBJECT: Amended: (Amended] Paraquat & Herbicide Alternatives: Incident Rate Analysis 

(Changes: This document is the second amended memo. This amendment makes corrections to 

the proprietary designations in Appendix C. Specifically, four tables have been moved out of 

Appendix C into the non-proprietary Appendix B because they did not contain proprietary 

information.) 

PC Code: 016061. 016063 

Decisio n No. 5 I 4946 

Petition No.: NA 

OP Barcode: 432238 

Registra tion No.: NA 

Regulatory Action: NA 

Ris k Assessme nt Ty pe: NA Case No.: NA 

TX R No.: NA CAS No.: 72%3-72-5 

MRID No.: NA 40 CFR: NA 

FROM: /~ames Nguyen, Mathematical Statisticiani)i,/J 

· Chemical Exposure Branch ( 

Health Effects Division (7509P) 

and 

Elizabeth Evans, Environmental Protection Specialist 

Toxicology and Epidemiology Branch 

Health Effects Division (7509P) 

THROUGH: David J. Miller, Acting Branch Chief 

Toxicology and Epidemiology Branch 

Health Effects Division (7509P) 

TO: Marianne Mannix, Chemical Review Manager 

Risk Management and Implementation Branch III 

Pesticide Re-evaluation Division (7508P) 

and 

Tracy Peny, Team Leader 

Risk Management and Implementation Branch III 

Pesticide Re-evaluation Division (7508P) 

and 

Kelly Sherman, Branch Chief 

Risk Management & Implementation Branch III 

Pesticide Re-evaluation Division (7508P) 

Ver.Apr.08 

Page 1 of 13 
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This memorandum is an amendment to the previous amended memorandum #D431236. This 

document is the second amended memo. This amendment makes corrections to the proprietary 

designations in Appendix C. 

I. Summary of Incident Rate Comparison of Paraquat to Potential Alternatives: 

Diquat, Glufosinate and Glyphosate

 The incident rate (on a usage-normalized basis) for high and moderate severity

poisonings associated with paraquat use was significantly and substantially higher 

than that of two potentially comparable herbicides, glufosinate and glyphosate. More 

specifically, the incident rate associated with paraquat when considering high and 

moderate severity poisoning outcomes (after normalizing by amount a.i. used) was 

estimated to be about 10 times that of glufosinate and 23 times that of glyphosate. 

Diquat data was not part of this analysis because there are no high or moderate 

severity incidents. (Table 3) 

 The incident rate of all paraquat poisoning cases including high, moderate, and low 

severity outcomes (normalizing by amount a.i. used) was estimated to be about 7 

times higher than glufosinate and 13 times higher than glyphosate. There is no 

evidence to indicate the incident rates for diquat and paraquat are different.

(Table B1, Appendix B)

 Among the cases reported to SENSOR-Pesticides, poisoning incidents associated 

with paraquat tended to be more severe than those associated glyphosate incidents. 

The observed tendency of more severe incidents associated with paraquat than 

glufosinate was not statistically significant. Diquat was considered as an alternative 

to paraquat but was excluded from this portion of the analysis because diquat had no 

high or moderate severity incidents. (Table 4)

II. Background

At the 2/19/15 monthly manager’s meeting, the OPP Paraquat Team was tasked with 

developing an estimate of the incident rate of poisonings normalized to a “per amount of 

a.i. used” basis, for paraquat (PC Codes 016061 and 016063) compared to other 

“comparable” chemicals. The team selected three other herbicides considered as

potential paraquat alternatives: diquat (PC Codes 032201 and 032202), glyphosate (PC 

Codes 41730, 103607, 103605, 103604, 103608, 103601, 103603, and 128501), and 

glufosinate (PC Code 128850). 

Data Sources

To obtain the number of incidents, single active ingredient case reports1of the four 

herbicides (paraquat + the 3 potential alternatives) during the period 1998-2011 were 

obtained from the SENSOR database. All cases of intentional exposures or multiple 

 

1 Conducting single active ingredient queries is the standard protocol when conducting Tier I scoping, Tier I 

updates, and Tier II incident analyses. This is primarily in place to help ensure that symptoms and circumstances 

surrounding the cases for a chemical are related to the chemical exposure and not related to another pesticide.
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active ingredient exposures were excluded from the analysis. Further, only SENSOR 

cases where the “application site” was recorded as being on a farm for an agricultural 

crop were analyzed to ensure valid rate comparisons could be made. (See Appendix A

for additional details regarding the SENSOR data query parameters.) The final number 

of SENSOR cases included in the analysis are presented on the left hand side of Table 1.

Table 1. SENSOR-Pesticides Case Counts / Agricultural Use Data from 1998-2011

a.i.

Number of Incidents

Of Given Severity

(numerator)

Usage Metric

(denominator)

High Moderate Low Total Pounds used Acres applied Respondents

Diquat 0 0 3 3 700,000 2,200,000 9,500

Glufosinate 0 1 4 5 13,600,000 30,300,000 140,000

Glyphosate 0 24 124 148 732,000,000 870,000,000 2,400,000

Paraquat 1 19 52 72 27,000,000 58,000,000 200,000

 Usage metric from OPP Biological And Economic Analysis Division (BEAD) has been rounded to protect

proprietary data

*Exact calculations using proprietary data are included in Appendix C.

The right hand side of Table 1 provides the pesticide usage metrics. In order to 

normalize the incident counts obtained from SENSOR-Pesticide database to the 

“amount” of product use, use/usage data was obtained from an agricultural marketing

firm which produces survey estimates regarding use/usage data. Three normalization (or 

standardization) parameters were chosen for each of the four herbicides during 1998-

2011 period: 

 the amount of AI used in pounds

 the area treated with the AI in acres)

 the (estimated) number of people handling the AI

These data reflect the same time period over which the incidents were accumulated and was 

restricted to the specific states participating in the SENSOR program.

2 The three normalization 

(or standardization) factors can be considered as very rough measures of the geographical extent 

of the use (acres treated), the intensity of use (pounds applied) and the number of users 

(projected sample).

III. Statistical Method

As is common practice when examining incident rates and incident rate ratios, a Poisson 

regression model was used to estimate and compare the incident rates between the 

herbicides. The number of incidents were normalized by setting the logs of the total 

amount of a.i. used (expressed per unit of 100,000 pounds), the total areas treated (in 

 

2 SENSOR states included: Arizona, California, Florida, Iowa, Louisiana, Nebraska, New Mexico, New York, North 

Carolina, Michigan, Oregon, Texas, and Washington.
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units of 100,000 acres), and the number of respondents (in thousands) as offset values in 

the models (i.e. using as denominators to calculate incident rates). 

Two different analyses were done to estimate two different incident rates: (i) incident 

rates of cases including only high and moderate severity outcomes; and (ii) incident rates 

of all cases including high, moderate and low severity outcomes. The differences in 

incident rates among the herbicides were estimated and presented in terms of incident 

rates ratios (IRRs).

In addition, a second analysis of the data was performed which explores the tendency of 

one pesticide to have a systematically more severe outcome given a case than another 

(second “comparison”) pesticide. This potential for a systematic “shift” towards more 

severe cases was evaluated by using a proportional odds (aka ordinal logistic regression) 

model. The tendency toward a case resulting in a more severe outcome with one 

herbicide compared to another is expressed in terms of an estimated odds ratios. For 

example, if an odds ratio > 1 results when herbicide “X” is compared to herbicide “Y”,

this indicates that incidents associated with exposure to herbicide “X” are more likely to 

be more severe than incidents associated with exposure to herbicide “Y”.

IV. Results of Analysis

The estimated incident rate of cases for high3and moderate severity4outcomes of the 

herbicides are presented in Table 2. 

Table 2. Incident Rate for High & Moderate Severity

SENSOR-Pesticides Cases

AI

Incident rate per 

100,000 pounds 

applied

Incident rate per 

100,000 acres treated

Incident rate per 

1,000 respondents

Diquat 0.0 (NA, NA) 0.0 (NA, NA) 0.0 (NA, NA)

Glufosinate 0.01 (<0.01, 0.05) 0.003 (<0.001, 0.023) 0.01 (<0.01, 0.05)

Glyphosate 0.003 (0.002, 0.005) 0.003 (0.002, 0.004) 0.01 (<0.01, 0.02)

Paraquat 0.07 (0.05, 0.12) 0.03 (0.02, 0.05) 0.1 (<0.1, 0.2)

*Exact calculations using proprietary data are included in Appendix C.

As can be seen, the results in Table 2 indicate that the incident rate for incidents 

classified as having high and moderate severity outcomes for paraquat are 0.07 incidents 

per 100,000 thousand lbs. used. Alternatively, these rates can also be expressed in terms 

of acres treated and rate per 1,000 respondents and – when expressed in this way – are 

0.03 incidents per 100,000 acres treated or 0.1 incidents per 1,000 respondents. These

rates are substantially higher than those for glyphosate, glufosinate, and diquat. 

 

3 SENSOR defines “high” severity cases as “The illness or injury is severe enough to be considered life threatening and typically 

requires treatment. This level of effect commonly involves hospitalization to prevent death.”

4 SENSOR defines “moderate” severity cases as cases of less severe illness or injury often involving systemic manifestations. 

Generally treatment was provided.
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These comparisons can also be usefully expressed as incident rate ratios (IRRs) along 

with the 95% confidence intervals which is standard practice in the descriptive 

epidemiology literature. For high and moderate severity outcomes, these IRRs are 

presented in Table 3.

Table 3. Comparisons of Incident Rate Ratio for High & Moderate Severity Outcomes

SENSOR-Pesticides Cases

by pounds applied by acres applied by respondents

Comparison

Incidence Rate Ratio 

(95% CI)

PvalueIncidence Rate Ratio 

(95% CI)

PvalueIncidence Rate Ratio 

(95% CI)

Pvalue

Glufosinate vs. Glyphosate 2.2 (<1, 17) 0.43 1.2 (0.2, 8.9) 0.86 0.7 (0.1, 5.2) 0.74

Paraquat vs. Glufosinate 10 (1, 76) 0.02 10 (1, 77) 0.02 13 (2, 97) 0.01

Paraquat vs. Glyphosate 23 (13, 41) <0.01 12 (7, 23) <0.01 9 (5, 17) <0.01

*Exact calculations using proprietary data are included in Appendix C..

The results in Table 3 show that the incident rate of high and moderate severity outcome

cases for paraquat was significantly higher than that of glufosinate or glyphosate using 

any of the three methods for normalizing exposure. For example, the incident rate for

high and moderate severity outcomes normalizing by amount a.i. used for paraquat is

about 10 times greater than the corresponding rate for glufosinate and 23 times that of 

glyphosate. 

The estimated incident rate for all cases (i.e., high, moderate, and low severity) outcomes 

are presented in Table B1 in Appendix B, while the comparisons of incident rates of all 

cases including high, moderate, and low severity outcomes among the herbicides are 

presented in Table B2. 

Finally, the analysis of the tendency for exposure of one pesticide to result in a 

systematically more severe outcome compared to another pesticide using the numbers of 

SENSOR-Pesticides incidents are presented in Table 4.

Table 4. Odds Ratios Associated With More Severe Outcomes

Comparison Odds Ratio (95% CI) P-value

Glufosinate vs. Glyphosate 1.29 (0.27, 6.22) 0.75

Paraquat vs. Glufosinate 1.56 (0.32, 7.63) 0.58

Paraquat vs. Glyphosate 2.02 (1.25, 3.25) <0.01

*Exact calculations using proprietary data are included in Appendix C..

The results in Table 4 show that reported cases associated with paraquat exposures 

tended to be more severe than cases associated with glyphosate (OR= 2.02 (95% CI: 

1.25, 3.25)). More specifically, the odds of a random case associated with paraquat to be 

more severe than one associated with glyphosate was a statistically significant 2.02, or 
Page 6 of 13

about double the odds. Comparing paraquat with glufosinate, on the other hand, produced 

a non-significant Odds Ratio of 1.56 (95% CI: 0.32, 7.63), reflecting about 1 1⁄2 times the 

odds. 

V. Conclusion

The OPP Paraquat Team estimated the incident rate of paraquat poisonings compared to 

other herbicides with a normalized pesticide use metric. A Poisson regression model was 

used to estimate and compare two different incident rates between the herbicides and 

presented in terms of incident rates ratios (IRRs). The incident rate of moderate and high 

severity paraquat poisonings was estimated to be about 10 times that of glufosinate and 

23 times that of glyphosate.5 The incident rate of all paraquat poisoning cases was 

estimated to be about 7 times higher than glufosinate and 13 times higher than 

glyphosate. There is no evidence to indicate the incident rates for diquat and paraquat are 

different.

Another analysis of the data was performed to explore the tendency of one pesticide to 

have a systematically more severe outcome given a case than another pesticide. The 

incident rate associated with paraquat when considering high and moderate severity 

cases, those associated with paraquat tended to be more severe than those associated 

glyphosate incidents. The observed tendency of more severe incidents associated with 

paraquat than glufosinate was not statistically significant.6

 

5 Diquat had no high or moderate severity cases for this analysis.

6 Diquat had no high or moderate severity cases for this analysis.
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Appendix A.

Paraquat/Diquat/Glyphosate/Glufosinate Incident Query Methodology:

1. Query of SENSOR-Pesticides case reports from 1998-2011

2. PC Codes query

a. Pc_code1 = 417300 or 103607 or 103605 or 103604 or 103608 or 103601 or 

103603 or 128501 or 128850 or 032201 or 032202 or 016061 or 016063

b. Pc_code2 is null 

c. This yields the total cases with a single active ingredient from above only

3. Intentional Exposures Removed: “Intnexpo does not = 1”

4. Includes only Application site (Appsite) = 01

a. Appsite 01 = Farm, all farms, orchard crop production excluding nursery, 

livestock and forest

5. Results: 

a. N= 228 cases total

b. (see “Single AI HerbicideCaseCompareAPPSITE1_becker.xlsx)

6. In the Excel output from Access, “Chemical” column was added and populated with 

chemical name (diquat, glufosinate, glyphosate, paraquat) that corresponded to pc_code1

SENSOR-Pesticides Query Results

Chemical Severity Total

High Mod Low

diquat 3 3

glufosinate 1 4 5

glyphosate 24 124 148

paraquat 1 19 52 72

Total 1 44 183 228
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Appendix B.

Table B1. Incident Rate for All 

SENSOR-Pesticide Cases

AI

Incident rate per 

100,000 thousand

pounds used

Incident rate per 

100,000 thousand

acres applied

Incident rate per 

1,000 respondents

Diquat 0.4 (0.1, 1.3) 0.1 (<0.1, 0.4) 0.3 (0.1, 1.0)

Glufosinate 0.04 (0.02, 0.09) 0.012 (0.01, 0.04) 0.04 (0.02, 0.09)

Glyphosate 0.02 (<0.01, 0.03) 0.02 (0.01, 0.02) 0.06 (0.05, 0.07)

Paraquat 0.3 (0.24, 0.34) 0.1 (0.09, 0.16) 0.3 (0.25, 0.4)

Table B2. Comparisons of Incident Rate Ratio for All 

SENSOR-Pesticide Cases

by pounds applied by acres applied by respondents

Comparison

Incidence Rate Ratio 

(95% CI)

PvalueIncidence Rate 

Ratio (95% CI)

PvalueIncidence Rate 

Ratio (95% CI)

Pvalue

Paraquat vs. Diquat 0.6 (0.2, 2) 0.44 0.9 (0.3, 2.8) 0.84 1. (0.3, 3.3) 0.94

Paraquat vs. Glufosinate 7 (3, 183) <0.01 7 (3, 18) <0.01 9 (4, 23) <0.01

Paraquat vs. Glyphosate 13 (10, 18) <0.01 7 (5, 10) <0.01 5 (4, 7) <0.01

Diquat vs. Glufosinate 12 (3, 49) <0.01 8 (2, 35) <0.01 9 (2, 38) <0.01

Diquat vs. Glyphosate 21 (7, 66) <0.01 8 (3, 26) <0.01 5 (2, 16) <0.01

Glufosinate vs. Glyphosate 2 (<1, 4) 0.19 1 (0.1, 2.4) 0.95 0.6 (0.2, 1.4) 0.22

The results show that the incident rates of all cases including high, moderate, and low severity 

outcomes of paraquat and diquat were significantly higher than that of glufosinate or glyphosate

in all three ways of normalizing by amount a.i. used (pounds), by number of treated acres, and by 

the number of respondents. For example, the incident rate of all cases including high, moderate, 

and low outcomes normalizing by amount a.i. used of paraquat was estimating about 7 times of 

glufosinate and 13 times of glyphosate.
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Table B3. Incident Rate for High & Moderate Severity 

SENSOR-Pesticides Cases

a.i.

Incident rate per 

100,000 pounds 

applied

Incident rate per 

100,000 acres treated

Incident rate per 

1,000 respondents

Diquat 0.000 (NA, NA) 0.000 (NA, NA) 0.000 (NA, NA)

Glufosinate 0.007 (0.001, 0.052) 0.003 (<0.001, 0.023) 0.007 (0.001, 0.050)

Glyphosate 0.003 (0.002, 0.005) 0.003 (0.002, 0.004) 0.010 (0.007, 0.015)

Paraquat 0.075 (0.048, 0.116) 0.034 (0.022, 0.053) 0.092 (0.059, 0.143)

Table B4. Comparisons of Incident Rate Ratio for High & Moderate Severity Outcomes 

SENSOR-Pesticides Cases

by pounds applied by acres applied by respondents

Comparison Incident Rate Ratio 

(95% CI)

PvalueIncident Rate Ratio 

(95% CI)

PvalueIncidence Rate Ratio 

(95% CI)

Pvalue

Glufosinate vs. Glyphosate 2.24 (0.30, 16.54) 0.4301 1.20 (0.16, 8.88) 0.8576 0.71 (0.10, 5.24) 0.7359

Paraquat vs. Glufosinate 10.21 (1.37, 76.11) 0.0233 10.37 (1.39, 77.30) 0.0224 12.98 (1.74, 96.70) 0.0124

Paraquat vs. Glyphosate 22.85 (12.62, 41.36) <.0001 12.46 (6.88, 22.55) <.0001 9.20 (5.08, 16.65) <.0001

Table B5. Incident Rate for All 

SENSOR-Pesticide Cases

a.i.

Incident rate per 

100,000 pounds used

Incident rate per 

100,000 acres applied

Incident rate per 

1,000 respondents

Diquat 0.425 (0.137, 1.318) 0.139 (0.045, 0.430) 0.318 (0.103, 0.987)

Glufosinate 0.037 (0.015, 0.088) 0.017 (0.007, 0.040) 0.035 (0.015, 0.085)

Glyphosate 0.020 (0.017, 0.024) 0.017 (0.014, 0.020) 0.062 (0.053, 0.073)

Paraquat 0.270 (0.214, 0.340) 0.123 (0.098, 0.156) 0.332 (0.263, 0.418)

Table B6. Comparisons of Incident Rate Ratio for All 

SENSOR-Pesticide Cases

by pounds applied by acres applied by respondents

Comparison

Incidence Rate Ratio (95% 

CI) P-value

Incidence Rate Ratio 

(95% CI) P-value

Incidence Rate Ratio 

(95% CI) P-value

Paraquat vs. Diquat 0.634 (0.200, 2.013) 0.4400 0.891 (0.281, 2.828) 0.8450 1.042 (0.328, 3.306) 0.9447

Paraquat vs. Glufosinate 7.354 (2.971, 18.205) <.0001 7.469 (3.017, 18.490) <.0001 9.344 (3.775, 23.132) <.0001

Paraquat vs. Glyphosate 13.340 (10.066, 17.679) <.0001 7.273 (5.488, 9.639) <.0001 5.370 (4.052, 7.117) <.0001

Diquat vs. Glufosinate 11.592 (2.770, 48.506) 0.0008 8.381 (2.003, 35.071) 0.0036 8.970 (2.144, 37.535) 0.0027

Diquat vs. Glyphosate 21.027 (6.705, 65.945) <.0001 8.161 (2.602, 25.595) 0.0003 5.155 (1.644, 16.167) 0.0049

Glufosinate vs. Glyphosate 1.814 (0.744, 4.423) 0.1903 0.974 (0.399, 2.374) 0.9533 0.575 (0.236, 1.401) 0.2231
Page 10 of 13

Appendix C (pages 11-13) contains 

proprietary pesticide usage data and is to be 

removed prior to posting in the docket.