Methods and Confidence Levels

We used several different methods to develop the active ingredient lists and estimate the probabilities. Our choice of a method for each scenario was based on the types and quality of information available. Professional judgment played a large role in many scenarios. Our level of confidence varies by scenario, depending on the type of method used, the extent to which judgment played a role, the quality of the data in the source materials, and other factors.

The methods used for deriving the active ingredient lists and probabilities are summarized here. Additional detail is provided in Colt J, Cyr MJ, Zahm SH, Tobias GS, Hartge P. 2006. Inferring past pesticide-exposures: a matrix of individual active ingredients in home and garden pesticides used in past decades. Environmental Health Perspectives (epub).

The scenarios to which each method applies, and the confidence level in the probability estimates for each scenario, can be found in the “Pesticide-Exposure Matrix” PDF file.

Method 1: Number of Acres Treated

This method was used when the Kline reports provided the number of acres nationwide treated with specific pesticide products. We assumed that the probability that a product (and each active ingredient in it) was used is equal to the percent of acres treated with that product.

We have a medium confidence level in the estimates for outdoor plant/tree insects (1990, 2000) and a high confidence level for the others. This is because the Kline data for outdoor plants do not include mature trees, which are often sprayed with insecticides by professional applicators. This use might be significant but is likely smaller than the market for insecticides applied to gardens and landscaping areas, upon which the Kline estimates are based. We do not believe this to be an important limitation for outdoor plant/tree pests other than insects.

Method 2: Number of Acres Treated (Derived from Pounds of Active Ingredients and Application Rates)

This method was used for lawns and outdoor plants/trees when Kline reported the pounds of individual active ingredients sold. We divided the pounds of each active ingredient by an estimated application rate (pounds/acre) to derive the number of acres treated with each active ingredient, and then proceeded as in Method 1.

Judgment was used for all of these scenarios and we have a medium level of confidence in the probability estimates. For lawn weeds (1980, 1990, 2000), we modified the Kline-reported pounds of some active ingredients to reflect our judgment about actual product formulations. For lawn and outdoor plant/tree insects (1980, 1990, 2000), Kline provided the active ingredient pounds aggregated across three pest types (lawn insects, outdoor plant insects, and non-plant insects), requiring us to allocate the pounds to each individual pest type. A similar situation was encountered for outdoor plant/tree diseases (1980, 1990, 2000).

Method 3: Number of Acres Treated (Derived from Dollar Sales, Unit Prices, and Application Rates)

This approach was used when Kline reported both dollar sales and unit prices (dollars per pound or gallon) for individual products. We divided the dollar sales by the unit price to estimate the pounds or gallons of each product sold. We then divided the pounds or gallons sold by an estimated application rate (pounds or gallons per acre) to derive the number of outdoor plant/tree acres treated with each product, and proceeded as in Method 1. We have a medium level of confidence in the probability estimates.

Method 4: Product Sales

We used this method when Kline reported dollar sales for individual products or active ingredients, but not unit prices. We assumed that the probability that a product (and each active ingredient in it) was used is equal to the product’s proportion of total dollar sales.

Because of the uncertainty associated with using product sales as the basis for probability of use, we have a medium confidence level in the probabilities for most of these scenarios. We gave high confidence ratings to the 1990 and 2000 professional termite scenarios, the former because the market was well understood by Kline and the latter because of the large sample size used by Kline. The consumer rodent market was rated high because it has been dominated by d-Con during the entire period of interest, and the professional segment was high because it has used a small number of active ingredients in a well-documented market. Our confidence level is low for professional treatment of outdoor plant/tree insects in 1976 and 1980 because the Kline data excluded insecticide applications to mature trees, and because the 1976 data were aggregated across more than one pest type. We have low confidence in the probabilities for flying insects in 2000 because they were based only on bees.

Method 5: Product Sales(Calculated from Company Sales)

This method was used when Kline reported dollar sales by manufacturer (but not by product or active ingredient) and identified each manufacturer’s main products and (typically) each product’s main active ingredients, but did not provide unit prices. We identified the active ingredients in each product when necessary. We apportioned each manufacturer’s dollar sales to its individual products or active ingredients using judgment. We assumed that the probability that a product (and each active ingredient in it) was used is equal to the product’s percent of total dollar sales.

For indoor plants in 1990, Kline reported sales by manufacturer and we used the U.S. EPA PPIS to identify the active ingredients that each manufacturer might have used. Probabilities for indoor plants pertain to insects only.

Our confidence level is medium for all scenarios except lawn weeds (1976) and outdoor plant/tree weeds (1976), which are rated low because our allocation of sales to active ingredients required more judgment than the other scenarios.

Method 6: Active Ingredient Frequencies from Pesticide Product Information System (PPIS)

For consumer treatment of household insects, the Kline reports were not sufficiently detailed for our purposes. Therefore, for scenarios 25-40, we used data from the U.S. EPA PPIS and the U.S. EPA Survey to estimate the active ingredient probabilities. This approach is described in detail in Colt J, Cyr MJ, Zahm SH, Tobias GS, Hartge P. 2006. Inferring past pesticide-exposures: a matrix of individual active ingredients in home and garden pesticides used in past decades. Environmental Health Perspectives (epub). We have a medium level of confidence in the probability estimates.

Method 7: Professional Judgment Based on Descriptive Data

Here, probabilities were based mostly on judgment, sometimes with a small amount of quantitative and/or descriptive data in the Kline reports, the literature, and the U.S. EPA PPLS . For indoor plants, the estimates pertain to treatment of insects only. Our confidence level is low.

Method 8: Active Ingredients Listed, Probabilities Not Estimated

For some scenarios, Kline does not maintain data and there was not enough information from other sources to support a probability estimate. Therefore, we developed lists of likely active ingredients but did not estimate probabilities. The lists were based on information from the Kline reports, the U.S. EPA PPLS, selected information from the literature, and judgment.

Method 9: No Active Ingredients Listed or Probabilities Estimated

We were unable to list active ingredients or estimate probabilities for consumer treatment of termites and professional treatment of indoor plants. There is no evidence that a significant number of consumers purchased products to self-apply termiticides until the late 1990s, and the market remains extremely small. Indoor plants are rarely treated by professional applicators.

• Pesticide-Exposure Matrix

• PDF: (4062201 kb)

Pesticide Exposure Matrix including type of pesticide, description of who applied it, what year, method used and confidence level.

• Data Sources

Summary of data sources used for the Pesticide-Exposure Matrix.

• Methods and Confidence Levels

Pesticide-Exposure Matrix methods used to develop active ingredient lists and estimate probabilities.

• References

List of publications

NIH…Turning Discovery Into Health®