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This is to certify that the

thesis entitled

PROTECTIVE CIUIHING ACI'IQ‘JS
OF MICHIGAN (DEN AND APPLE GRQVERS
IN REGARD TO PESTICIDES

presented by

Lois C. Shern

has been accepted towards fulfillment
of the requirements for

M S degree in .1than_Enyironment
and Design

 

gm 6 /fl~c«/m/

Major professor

 

Date££¢rn Z Z /7X£_

0-7639 MS U is an Afl‘innative Action/Equal Opportunity Institution

 

 

MSU

LIBRARIES

 

RETURNING MATERIALS:
Place in book drop to
remove this checkout from
your record. FINES will
be charged if book is
returned after the date
stamped below.

 

 

.é j_<}»
?' MAYO-719‘

1' 3.42 7 o- ,.
'JUN 1 6 2001
OG’MQZQUE

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PROTECTIVE CLOTHING ACTIONS
OF MICHIGAN CORN AND APPLE GROWERS
IN REGARD TO PESTICIDES

By

Lois C. Shern

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

Master of Science

Department of Human Environment and Design

1986

ABSTRACT
PROTECTIVE CLOTHING ACTIONS

OF MICHIGAN CORN AND APPLE GROWERS
IN REGARD TO PESTICIDES

by

Lois C. Shern

Two hundred twenty-two Michigan growers who
applied pesticides in the past two years completed
usable self—administered questionnaires.

The objectives of this study were to: 1) gather
baseline data about selection, storage, and wearing
practices for pesticide soiled clothing, 2) determine
if corn and apple growers differ with respect to
selected demographic, clothing, and experience
variables, and 3) explore a model which explains
protective actions with respect to clothing.

Data were analyzed using Pearson Product Moment
correlations, two—tailed independent t-tests, principal
components factor analysis, and various descriptive
statistics.

The following conclusions were made:

Regular clothing, not protective, is worn by
both corn and apple pesticide applicators. Storage
and laundry actions for pesticide soiled clothing
are similar but differences were found in regard to

experience and protective health actions.

Lois C. Shern

Significant correlations were found among the
variables which represent dimensions of the Model to
Predict Protective Health Actions. A profile of two
types of pesticide applicators, the risk taker and

the risk avoider, emerged from data analysis.

ACKNOWLEDGMENTS

The author wishes to acknowledge the support and
encouragement which has been provided by several special
individuals throughout this undertaking.

Special thanks to Dr. Ann C. Slocum, advisor and
friend, as well as chairperson of my committee, for her
encouragement, interest, and continual assistance.

To Dr. Brenda Sternquist, Dr. George Ayers, and
Irene Hathaway, committee members, for their interest
and suggestions.

To Judy Pfaff, computer and statistical consultant,
for her special efforts in finding lost data.

To Deborah Johnson, friend and proofreader, for
her willingness to read and critique this manuscript.

And especially to my family for their patience,

support, and love throughout this endeavor.

ii

TABLE OF CONTENTS

LIST OF TABLES I I I I I I I I I I I I I I I I I I

LIST OF FIGURES I I I I I I I I I I I I I I I I I

Chapter
I.

II.

III.

INTRODUCTION I I I I I I I I I I I I I I I

Statement of the Problem . . . .
Scope of the Study . . . . . . .
Objectives . . . . . . . . . . .
Research Questions and Hypotheses
Limitations of the Study . . . .

REVIEW OF LITERATURE . . . . . . . . . . .

The Use of Clothing for Pesticide
Protection . . . . . . . . . . . . . .
Pesticide Risk - Attitudes and Practices
Risk - A Definition . . . . .
Health Protective Behavior
The Health Belief Model . .
Theoretical Framework . . .

Theoretical Definitions . . . . . . . .
Operational Definitions . . . . . . . .

METHODOLOGY I I I I I I I I I I I I I I I I

Description of the Instrument
Data Collection . . . . . . .
Data Coding . . . . . . . . .
Description of th Variables
Data Analysis Procedures . .

Statistical Tests I I I I I I I I I I I

iii

Page
vi

ix

H
H\O CIDVK»)

9—3
\JJ

16
17
18
19
27

29
32

36

38
39
NO
43

43

Chapter
IV. ANALYSIS, FINDINGS AND DISCUSSION
Description of the Sample . . .
Age . . . . . . . . . . . . .
Education . . . . . . . . . .

Income I I I I I I I I I I I

Descriptive Data for Objective 1

Question 1. What kind of clothing do

pesticide applicators wear when applying

peStiCideS? I I I I I I I I I

Question 2. Where is pesticide soiled
clothing stored before laundering?
Question 3. What kind of actions do
corn and apple growers engage in when
clothing becomes soiled with pesticides?

Tests and Findings for Objective 2

Summary of Findings for Objective 2 .

Questions and Hypotheses for Objective 3.

Summary of Hypotheses and Findings

for Objective 3 . . . . . . .
Factor Analysis . . . . . . . .

V. SUMMARY, CONCLUSIONS, LIMITATIONS
IMPLICATIONS FOR RESEARCH . . .

summary I I I I I I I I I I I I

Purpose . .
Methodology
Findings .

Conclusions . . . . . . . . . .
Limitations . . . . . . . . . .
Discussion of Imp ications for
Further Research . . . . . . .

iv

Page

46
46
46
46
49

5O

50
55

61
69
7o

87
94

104
104
104
105
105

108
109

110

Chapter Page
APPENDICES

A. Applicator Portion of Questionnaire Used
in This Study I I I I I I I I I I I I I I 1114’

B. Letter to Participants from Project Director 126
C. Respondent's Return Postcard . . . . . . . 127
D. Protective Clothing Index . . . . . . . . . 128
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . 129

O \O CDV O\U\ rm

H

5—:
H
o

[—3
N

13.

14.

15.

16.

17.
18.

LIST OF TABLES

Survey Response Rate . . . . . . . . . .
Age Distribution of the Sample . . . . .
Education Distribution of the Sample . .
Family Income Distribution of the Sample
Shirts Worn for Pesticide Application .
Pants Worn by Pesticide Applicators . .
Shoes Worn for Pesticide Application . .
Gloves Worn for Pesticide Application .

Hats Worn for Pesticide Application . .

Other Clothing Worn for Pesticide Application

Storage of Pesticide Soiled Clothing
Before Laundry . . . . . . . . . . . .

Soiled Garments Worn Again
Before Laundering . . . . . . . . . .

Number of Days Soiled Clothing Worn
Before Laundering . . . . . . . . . .

Time Reported Before Changing Non-waterproof

Clothing After Spilling Full Strength
Liquid Concentrate . . . . . . . . . .

Time Reported Before Changing Non-waterproof

Clothing That Has Become Saturated with
Pesticide Spray . . . . . . . . . . .

Years Applying Pesticides . . . . . . .
Days per Year Applying Pesticides . . .
Insecticide Used Most in Past Two Years

vi

Page
39
47
48
49
5O
51
52
53
53
54

56

57

58

59

60
63
64
65

Table Page

19. Other Pesticides Used Most
in Past Two Years . . . . . . . . . . . . . 65

20. Soiled Garments Stored With Family Laundry . . 67
21. Toxicity of Pesticides Spilled on Clothing . . 68

22. Pearson Product Moment Correlations
Between General Health and
Protective Health Actions . . . . . . . . . 71

23. Pearson Product Moment Correlations
Between Susceptibility and
Protective Health Actions . . . . . . . . . 76

24. Pearson Product Moment Correlations
Between Seriousness and
Protective Health Action 1 . . . . . . . . . 80

25. Pearson Product Moment Correlations
Between Objective Experience and
Protective Health Actions . . . . . . . . . 81

26. Pearson Product Moment Correlations
Between Perceived Benefits and
Protective Health Actions . . . . . . . . . 84

27. Pearson Product Moment Correlations
Between Perceived Barriers and
Protective Health Actions . . . . . . . . . 85

28. Pearson Product Moment Correlations
Between Modifying and Enabling Factors
and Protective Health Actions . . . . . . . 86

29. Summary of Significant Correlations
for General Health and Protective Health
Actions for Corn and Apple Growers . . . . . 88

30. Summary of Significant Correlations
for Perception of Risk and Protective Health
Actions for Corn and Apple Growers . . . . . 89

31. Summary of Significant Correlations
for Perceived Benefits and Protective Health
Actions for Corn and Apple Growers . . . . . 91

32. Summary of Significant Correlations
for Perceived Barriers and Protective Health
Actions for Corn and Apple Growers . . . . . 92

vii

Table Page
33. Summary of Significant Correlations
for Modifying and Enabling Factors
and Protective Health Actions for

Corn and Apple Growers . . . . . . . . . . . 93

34. Factor Loadings for Apple Growers . . . . . . 97

35. Factor Loadings for Corn Growers . . . . . . . 98

36. List of Variables Loading at .50 or Greater
for Corn Grower Factors . . . . . . . . . . 100

37. List of Variables Loading at .50 or Greater
for Apple Grower Factors . . . . . . . . . . 101

viii

LIST OF FIGURES

Figures Page
1. Original Health Belief Model . . . . . . . . . 21
2. Summary hypothesized model for explaining

and predicting health—related behaviors . . . 25
3. A Model to Predict Protective Health Actions . 30

ix

CHAPTER I

INTRODUCTION

Families, as part of a societal ecosystem, are
inextricably linked to a variety of environmental
systems-social and physical, natural and institutional.
American farm families numbered approximately 3 million
in 1984 (Block, 1984). However, over 22 million people
work in some phase of agriculture. Agriculture is
essential to the well-being of our nation - both nutri-
tionally and economically. In 1983, 65,000 Michigan
farms produced crops that totaled over $3 billion
worth of production (Ferris, 1984). Weather and pests
are a constant threat to agricultural production.

Pests destroy approximately thirty percent of annual
production before farmers can bring their crops to
harvest or livestock to slaughter (Block, 1984). The
use of pesticides has become an integral part of
farming today.

Farmers are the biggest users of pesticides.

Total pesticide usage in the U.S. has nearly doubled
since the 1960's. Agricultural use has nearly tripled
since 1964 (EPA, 1984). However, 1982 was the first

year in recent times when pesticide use in American

agriculture declined.

The benefits of these chemicals have not been
without costs. Toxic chemicals have caused damage to
both the environment and to public health. Knowledge
about pesticides and pesticide safety practices is not
only of great importance to those who work directly with
these chemicals but also to other members of the family
and the community.

The wise use of pesticides and other toxic
chemicals is essential for modern agriculture production
and public health. Beginning with the discovery of DDT
and other chemicals during World War II, agricultural
productivity has been enhanced and the incidence of
yellow fever, malaria, and other illnesses has been
greatly reduced. However, mounting evidence of the
dangers of pesticides and growing public awareness and
concern about environmental pollution from toxic
chemicals make it imperative that more is learned about
pesticide contamination. The lack of selectivity of
pesticides and their widespread overuse are causing
immense problems for agriculture itself.

Over the past seven years many health related
cases have been acted upon by EPA scientists and
the Pesticide Science Advisory Panel. According to
the World Health Organization, parathion poisoning is

the major cause of the estimated 500,000 human illnesses

and 20,000 deaths that occur worldwide each year from
the use of pesticides (Metcalf, 1984). Many people
believe that pesticides are among the worst of the
environmental pollutants (Carson, 1962; Epstein, 1979;
Boraiko, 1980). The Council for Environmental Quality,
in a public survey in 1980, found that the level of
public concern about toxic chemical wastes surpasses

that for any other environmental problem (Metcalf, 1984)

Statement of the Problem

For the farmer, the acceptability of the risk
related to pesticide application is positively
associated with large-scale benefits and the potential
for sizable accidents (Vlek and Stallen, 1981).
Knowledge about pesticides and their long-term effect
is still fragmentary. Long-term health risks for the
pesticide applicator, his family and the general
community are unknown. Many of the symptoms of
pesticide poisoning are similar to other illnesses.
Nausea, diarrhea, rash, headaches, and eye irritations
can be symptoms of low—level pesticide poisoning but
may be attributed to other sources of illness.

While few Americans want to return to fleas,
bedbugs, or the wormy apples of the 18th century it is
essential that the risks of pesticides are explored
and controlled. The issue of risk/benefit has become

the focal point of the pesticide controversy.

Edwin Johnson, Director of EPA's Office of

Pesticide Programs, has stated
pesticides by their very nature are designed to
be biologically active and kill pests and weeds,
(so) we speak in terms of relative risks,
rather than 'safety'. Much of the debate
about pesticides centers on this issue. To
the extent that some people focus on the risks
only, and are not cognizant of the benefits' side
of the equation, the risks can be overexaggerated
(Johnson, 1984, p. 6).

Last year, an estimated 82 million peOple were
added to the world's population. It is predicted that
the world will have to produce more food and fiber in
the next fifty years than in all previous human history
(Barr, 1984).

The editor of the National Geographic magazine
contends that

with a steadily expanding population and a
decrease in arable land, the world must use
pesticides to maintain high crop yields and
affordable food. At the moment there is simply
no other way to farm on the scale required
(Boraiko, 1980, p.145).
For many peOple involved on a day to day basis with
pesticides, the acceptability of risk depends on the
amount of the benefit to be received for taking the
risk. The need to produce food for the hungry of the
world challenges agriculture to recognize the mutual
dependencies of the environment, economics, and human
health.

Davies (1976) found that occupational exposure to

pesticides (this includes workers who manufacture,

formulate, transport, mix and dispose of pesticides) is
greatest to those individuals who apply pesticides to
agricultural crOps utilizing a variety of spraying and
dusting equipment. While 1982 showed a slight decline
in agricultural pesticide use, the pesticide industry
remained relatively stable when compared to manufac-
furers of machinery and fertilizer. The fact that
pesticide use declined only modestly while pesticide
prices increased and Operating costs sky rocketed is
attributed to farmers' reluctance to risk increased crop
losses (Farmline, 1983). The individuals who are most
at risk, also perceive the benefits of using pesticides.

Pesticide exposure is related to the type of
activity, method of application, concentration and
formulation of the particular chemical, and
environmental conditions, primarily wind velocity.
The particular chemical used varies with the type of
crop to which it is being applied and the particular
pest for which it is most effective. Michigan apple
growers apply several different insecticides at various
times during the entire growing season, usually as
spray. Corn insecticides are usually applied in a
granular formulation prior to or at planting. Virtually
all corn acreage is treated with herbicides.

Federal regulations require that pesticides be

labeled according to their toxicity and health effects.

State extension services have developed programs to
keep the agricultural community informed about safety.
Applicators are required to be licensed in order to
use chemicals which are on the EPA restricted list.

A great deal of research has concentrated on
determining the major routes of exposure to humans.
These are: (1) inhalation, (2) ingestion, and (3) skin
absorption. Researchers have compared the dermal and
respiratory routes and have determined that 87% of the
total human exposure is accounted for by dermal exposure
(Durham, 1962; Maibach, Feldmann, Milby, & Sert, 1971).
Maibach and his co-workers at the University of
California School of Medicine were able to chart the
rates at which pesticide residue was absorbed through
the skin. Absorption rates ranged from 8.6% for
the forearm to 100% for the scrotum. Research at
Michigan State University (DeJonge, Ayers, & Branson,
unpublished) identified spray deposition patterns
on clothing of agricultural workers who were driving
tractors and using high and low volume spray equipment.
Utilizing the absorption data from Maiback, Michigan's
study showed that special care should be taken to
protect the scalp, ear canal and forehead, as well as
the abdominal and waistline area.

The use of protective clothing has emerged as a

viable method of safety protection. Protective clothing

was classified as safety equipment in the 1982 CrOp and
Livestock Pesticide Usage Survey by the U.S. Department
of Agriculture. Gloves, long-sleeved shirts, and masks
are examples of safety equipment listed in the survey.
More than sixty percent of the 6,520 respondents
reported using the more common safety equipment (gloves,
long-sleeved shirts, and caps). Fifteen percent used
specialized safety equipment (dust mask, face shield or
goggles), but five percent reported using no pesticide
safety equipment of any kind when mixing, loading, or
applying pesticides.

However, it is only in recent years that research
has begun to address the complicated issue of pesticide
contaminated clothing. New disposable fabrics and
garments are being deveIOped but the safety of laundered
garments is still undetermined. Little is known about
the storage and laundry procedures used for pesticide

soiled clothing.

Scope of the Study
This study is part of North Central Region Project
170, "Limiting Pesticide Exposure Through Textile
Cleaning Procedures and Selection of Clothing", for
which the author is a graduate research assistant.
The overall purpose of the larger (regional) study is
two-fold: 1) Survey agricultural growers to learn

what selection, use, and care practices are currently

used for pesticide contaminated clothing and

2) Perform laboratory studies which will determine

the best methods for removal of pesticide residue

from fabrics. Five states are participating in the

survey portion of the regional study. This present

study will utilize only the Michigan portion of the

survey data.

Objectives

 

The objectives of this study are to:

1.

Gather baseline information about applicators'
selection, storage, and wearing practices for
pesticide soiled clothing.

Determine if there are differences between corn
and apple growers with respect to demographic
variables, experience and use of pesticides,
clothing and laundry practices, and toxicity
and formulation of pesticides that are reported
to get on clothing which is worn while applying
pesticides.

Explore a model which explains actions taken

with respect to pesticide soiled clothing.

Research Questions and Hypotheses

The research questions and hypotheses in the null

 

What kind of clothing do pesticide applicators

How is pesticide soiled clothing stored before

What kind of actions do corn and apple growers
engage in when clothing becomes soiled with

 

 

Are there differences between corn and apple

There will be no significant difference
between the mean ages of corn and apple

There will be no significant difference
between the mean years of education of

There will be no significant difference
between the mean incomes of corn and apple

There will be no significant difference
between the mean family size of corn and

There will be no significant difference
between the mean ages of the youngest child
living at home under 18 years for corn and

form are:
Questions for Objective 1
1.
wear when applying pesticides?
2.
laundering?
3.
pesticides?
Questions and Hypotheses for
Objective 2
1.
growers?
H1:
growers.
H2:
corn and apple growers.
H3:
growers.
H4:
apple growers.
H5:
apple growers.
H6:

There will be no significant difference
between the mean number of years individual
corn and apple growers have been applying
pesticides.

10

There will be no significant difference
between the mean number of days per year
that individual corn and apple growers

There will be no significant difference
between the toxicity of pesticides used

There will be no significant difference
between corn and apple growers regarding
the kind of clothing that is worn to apply

There will be no significant difference
between the storage practices for pesticide
soiled clothing of corn and apple growers.

There will be no significant difference in
the toxicity of the pesticide that gets on
clothing worn by corn and apple growers.

There will be no significant difference in
the time reported by corn and apple growers
for changing non-waterproof clothing after
spilling full strength liquid concentrate on

There will be no significant difference in
the time reported by corn and apple growers
for changing non-waterproof clothing that has
been saturated with pesticide spray.

 

 

Do components of the Protective Health
Action Model help predict the likelihood
of protective clothing actions for pesticide

Among pesticide applicators the variables that
comprise general health behavior will not be
significantly related to protective health

H7:
apply pesticides.
H8:
by corn and apple growers.
H9:
pesticides.
H10:
H11:
H12:
themselves.
H13:
Questions and Hypotheses for
Objective 3
1.
applicators?
H1:
actions.
H2:

Ambng pesticide applicators the variables that
comprise perception of risk will not be
significantly related to protective health
actions.

11

H3: Among pesticide applicators the variables that
comprise perceived benefits will not be
significantly related to protective health
actions.

H4: Among pesticide applicators the variables that
comprise perceived barriers will not be
significantly related to protective health
actions.

H5: Among pesticide applicators modifying and

enabling factors will not be significantly
related to protective health actions.

Limitations of the Study

 

Michigan farmers, as a group, are continually being
surveyed. Agricultural experts at Michigan State
University advised that a response rate of 15% to 20% is
considered good in a Michigan agricultural mail survey.
The length of the questionnaire (18 pages) is also
considered a limitation. Farmers will often not take
the time to fill out many pages of questions.

Michigan farmers are also very sensitive concerning
the issue of pesticides and regulations. There is fear
that regulations concerning protective clothing may be
introduced. This fear may prompt the respondents to
leave questions unanswered or bias the answers. It is
hOped that, by assuring confidentially, respondents will
feel free to give their unrestrained responses. It is
also hOped that the importance of the subject will
overcome objections to completing the questionnaire.

The questionnaire is part of a regional study. The

primary objective of the questionnaire, used by each of

12

the five states, was to collect descriptive data about
pesticide soiled clothing. It was not designed to
specifically explore a behavioral model. Therefore, the
questionnaire does not directly address all aspects of
the model. This will result in a limited representation

of some aspects of the model.

CHAPTER II

REVIEW OF LITERATURE

The review of literature is organized in five
sections. The first section discusses the emergence of
clothing as a means of pesticide protection and reviews
research concerning protective apparel for pesticide
users. The second section reviews studies that have
looked at perceived risk of pesticide use as it relates
to attitudes and practices of pesticide users. The
third section reviews selected studies relating to risk,
the fourth section defines health protective behavior,
and the fifth section traces the historic deveIOpment

and modification of the Health Belief Model.

The Use of Clothing for Pesticide Protection
The use of protective clothing has emerged as a

major, realistic strategy to managing safety for workers
using pesticides. After much debate among regulatory
agencies, growers, manufacturers, researchers, and the
general public, worker protection standards were ad0pted
on May 10, 1974. These standards, which are still in
effect today, include "at least a hat or other suitable
head covering, a long sleeved shirt and long legged

trousers or a coverall type garment (all of closely

13

14

woven fabric covering the body, including arms and
legs), shoes and socks (Federal Register, May 10, 1974).
The North Dakota Extension Service (1983) recommends
that protective clothing include: coveralls or long-
sleeved shirt and pants, waterproof gloves, waterproof
boots, waterproof hat with wide brim and/or a light-
weight raincoat or waterproof apron. Occupational
Safety and Health Administration Standard 1910.267a
(1973) suggests that protective clothing include a
washable fabric. Information concerning the laundering
of pesticide soiled clothing has been complied by
Nebraska (1984) and Iowa (1983) Extension Services.
These recommendations include using hot water of at
least 60 C and a heavy duty liquid detergent. Drying
clothes on a line, rather than in a dryer is also
recommended.

There are four major routes of entry of pesticide
into the body: 1) oral, 2) respiratory, 3) dermal via
intact skin and 4) through cuts and abrasions in the
skin (Maibach et al., 1971: Davies, 1976: Dedek, 1982).
Dermal absorption can normally be expected to be
controlled by the use of protective clothing but there
is evidence that such clothing, as well as clothing worn
beneath the protective clothing (Finley, Graves,
Summers, and Morris, 1977), can be contaminated by

pesticides (Finley and Rogillio, 1969). Traditional

15

worker garments such as denim pants and cotton chambray
shirts offer limited protection (Orlando et al.,1981).
The focus of recent research has been directed
toward the ability of fabric to prevent penetration of
pesticides (Freed, Davies, Peters and Parveen, 1980:
Orlando et al., 1981: Serat et al., 1982) and the
removal of contamination from fabric through laundering
(Finley et al., 1969, 1974, 1977, 1979: Easley et al.,
1981, 1982: Easter, 1982). Other work has shown that,
once contaminated, clothing in a pesticide applicators'
wardrobe is difficult to decontaminate through the
usual, accepted laundry procedures (Finley et al., 1977:
Easley et al., 1981, 1982: Laughlin et al., 1981: Kim,
et al., 1982). These researchers found that laundering
greatly reduces the amount of pesticide residues present
but even ten launderings may not be effective in re-
moving all residue, especially if the original spill was
a concentrate. Laundering also spreads the remaining
pesticide throughout the entire garment. Bioassay has
shown that residue remaining after repeated launderings
was biologically active (Finley, et al., 1974, 1979:
Easley et al., 1982). Finley and associates (1974)
found that pesticide was transferred to other "clean"
fabrics during laundering with pesticide soiled fabrics.
Easley (1981) confirmed that insecticide contamination

of the washing apparatus also occurred.

16

Pesticide Risk - Attitudes and Practices

 

Very little information is available in the
literature about the relationship between perceived risk
of pesticide use and attitudes and practices. Henry
(1980) and DeJonge et al., (1983-84) explored attitudes,
perceptions and practices of farmers concerning
protective clothing. They found that protection was
the only attitude that related to action or behavior.
Carlson (1982) looked at fear appeal as a means of
persuasion to adopt protective clothing. Fear appeal
was significantly related to change in perception of
hazard, benefits of protective clothing, and intentions
for future use. Reported behavior was not significantly
related to the fear appeal. Rucker (1983, unpublished)
found that in response to questions about exposure, most
applicators perceived that pesticides were frequently
deposited on their clothing but were much less likely to
believe that these chemicals get through to their skin.
The respondents were knowledgeable about the actual
toxicity level of the pesticides that were being used
but were likely to express agreement with the statement
that "the risk of getting pesticides on clothes is
nothing compared to breathing air pollution". Wolfe
and his associates (1967) reported that considerably
lower exposure to pesticides was sustained by a careful

Operator than a careless one.

17

Risk - A Definition

 

In a recent survey commissioned by the Marsh &
McLennan Companies, insurance brokers, and conducted by
Louis Harris and Associates, most Americans believe they
are facing considerably more risk now than they did
20 years ago. The survey reported that people expect
the risk of living in a technological society will
increase but that the future benefits from science and
technological innovation still outweigh the risks
(Management Review, 1980).

Risk is usually thought of as the probability of an
undesired occurrence, eg. an automobile accident (Otway
and Pahner, 1976). Risk assessment deals with the
potential risks that a product, such as a pesticide, may
pose to humans or wildlife. Risk management takes all
factors into consideration: risk of harm, benefits to
society, and the alternatives for reducing risk
(Johnson, 1984).

Otway and Pahner (1976) described risk situations
as being characterized by several levels:

1. physical, biological risks to man and the
environment:

2. the perception of these risks by individuals:

3. the potential risk to the psychological well-
being of individuals based upon perceptions:

4. the risks to social structures and cultural
values as influenced by the collective
psychological states of individuals.

18

The awareness that pesticides pose a risk to
health and the knowledge that protective clothing
provides a barrier to pesticides should lead pesticide
applicators to display protective health behavior.
However, many applicators view the health related
issues of pesticide application as a future risk

(Calabresi, 1970).

Health Protective Behavior

 

The classic definition of health behavior was
formulated by Kasl and Cobb (1966). They defined health
behavior as "any activity undertaken by a person
believing himself to be healthy, for the purpose of
preventing disease or detecting it in an asymptomatic
stage." Health behavior is distinguished from illness
and sick-role behaviors. Harris and Guten (1979) have
expanded this definition to include behaviors which are
self-defined health-protective actions. These behaviors
may not necessarily be medically defined health
behavior. Health-Protective Behaviors are conceptually
defined as:

any behavior performed by a person, regardless
of his or her perceived or actual health status,
in order to protect, promote, or maintain his
or her health, whether or not such behavior is
objectively effective toward that end

(Harris and Guten, 1979, p. 18).

This definition implies that a behavior is performed

in relation to an individual's perceptions of that

19

behavior's health-protective potential. Consequently
wearing protective clothing while spraying pesticides or
taking special precautions while laundering pesticide
soiled clothing should reflect the belief that these
actions will provide protection. Suchman (1967) used
the degree of acceptance of a protective glove as an
indicator of worker willingness to adOpt preventive
practices for reducing accidents.

Knutson observes in his book The Individual,

 

Society, and Health Behavior that
health behavior seems so inseparably linked to
motivation that logic impels one to orient any
discussion of health practices to human needs
and human motives (Knutson, 1965, p. 32).
Atkinson (1966) has applied "value—expectancy
theory," which describes behavior or decision making
under uncertainty, to the area of achievement. He
specifies that (a) motivation is needed to achieve
success or to avoid failure, (b) there is an incentive
value connected to a specific goal, and (0) there is
the expectation of a successful outcome. This theory

of motivation, based upon an approach drawn mainly

from Lewin (1935), underlies the Health Belief Model.

The Health Belief Model
The Health Belief Model (HBM) is a theoretical
model used to account for health-related behaviors.

Initially formulated by Rosenstock and his associates

20

(1966), the model (Fig. 1) viewed protective health
action as likely to be performed by persons who (1) feel
threatened by a disease (perceive themselves susceptible
to it and perceive its consequences to be severe), (2)
perceive the benefits of preventive action to outweigh
it costs, and (3) are exposed to some behavioral cues to
action. This model was constructed to predict
"preventive" health behavior such as tuberculosis and
Papanicolaou screening tests, immunizations, and annual
checkups.

The original Health Belief Model dealt only with
the negative aspect of health - some threat of a disease
or pathological condition (Becker et al., 1972). It also
did not consider a person's experience in conjunction
with his beliefs in its predictions or socioeconomic
information about an individual (Gochman, 1972).
Rosenstock and his associates (1974) viewed demographic,
socio-psychological, and structural variables as serving
to condition both individual perceptions and the
perceived benefits of preventive actions.

Evidence suggests that there is an association
between health behavior and indicators of socioeconomic
status. Suchman (1965) found demographic factors (i.e.,
sex, age, and social class) and group social structure
to be significantly related to an individual's medical

orientation. Mechanic (1968) found that persons of

21

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22

higher socioeconomic status are more likely to engage in
preventive health behavior. Steele and McBroom (1972)
reported that the degree of preventive health behavior
is in part a function of one's socioeconomic status.
Availability of health services, distance from a health
provider, as well as recent illness, also influenced
health related actions. Coburn and P0pe (1974), in
analysis of nine demographic and socio-psychological
correlates of preventive health behavior, found
socioeconomic status (SES) to be the most important
predictor variable (followed by age). Socioeconomic
status included education, income, and occupational
status. Maiman et al., (1982) found that income and
education levels are related to the types of medicines
and medical appliances that mothers use to treat various
health problems of their children.

Becker and his associates (1972, 1974, 1975),
through a series of investigations formulated the model
to show that individual social, psychological, and
situational variables all enter into the choice or
likelihood of action. Kirscht (1974) prOposed that
judgments about variables in the HBM are presumably
made on continuous scales and are integrated according
to a multiplicative rule to produce health-related
action. A change in any variable should result in a

change in health decisions and behavior. Further

23

testing of the model was done to assess the construct
validity of the Health Belief Model.

Cummings, Jette, and Rosenstock (1978) found that
the HBM variables can be measured with a substantial
amount of convergent validity using Likert or multiple
choice questionnaire items. Evidence from this study
suggests that perceptions of barriers and benefits are
quite different from perceptions of susceptibility and
severity. Perceptions of susceptibility and severity
were found to be substantially, but not entirely,
independent. A strong negative relationship was found
to exist between perceived benefits and barriers. This
suggests the possibility that benefits and barriers may
represent Opposite ends of a single continuum and not
separate health beliefs.

Janz and Becker (1984), in their comprehensive
review of the past ten years of HEM-related research,
created a "significance ratio" which they used to order
the HBM dimensions which were examined in 29 studies.
The ratio was computed by dividing the number of
positive and statistically significant finds for a HBM
dimension by the total number of studies which reported
significance levels (either positive or negative) for
that dimension. The barriers dimension was rated at
91%, benefits at 81%, and susceptibility at 77%. These

three dimensions were consistently associated with

24

outcomes (behaviors). Severity (59%) was rated lowest
among the dimensions of the HBM. It produced
significant results in only about one-third of 29
studies. This ordering of the dimensions was true for
both prospective and retrospective study designs.

When 46 pre-and post-197M studies were combined
each HBM dimension was shown to be significantly
associated with the health-related behaviors studied;
these include actions taken to avoid illness or injury,
actions taken after diagnosis of a medical problem, and
clinic visits. The significance-ratio orderings were
barriers (89%), susceptibility (81%), benefits (78%) and
severity (65%)-

Janz and Becker suggest that the low power of the
perceived severity dimension may be a reflection of its
lack of importance in preventive health behavior. How—
ever, they suggest that this dimension may be of great
importance to an individual with diagnosed illness.

A refined HBM model (Fig. 2) which incorporates
three broad classes of variables has been utilized in
the research of Fisher, 1977; Katatsky, 1977: Langlie,
1977; Becker et al., 1977, 1978; Radius et al., 1978;
and Rundall and Wheeler 1979; Leavitt, 1979. These
variable classes include the extent of the individual's
readiness to undertake recommended behaviors, various

modifying or enabling factors, and the extent of

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26

compliance with recommended behavior. The operational
definitions of the variables have been different in
every study. However, within each broad class are
several dimensions which have been consistently used.

Readiness to Undertake Recommended Compliant
Behavior may include: 1) the individual's general
motivations with regard to health care; 2) the
individual's view of his/her own vulnerability to the
perceived illness threat and one's belief's about the
severity of the illness defined either in terms of
physical harm or interference with social functioning
and 3) perception of benefits associated with actions
to reduce the level of threat or vulnerability and
evaluation of potential barriers associated with the
prOposed action which can be physical, psychological
or financial (perceived benefits vs barriers).

Modifying or Enabling Factors can include
behavioral cues to action, ie. previous illness, and a
set of demographic, structural, and social psychological
factors.

Compliance with Recommended Behavior has been
expanded to account for many types of health-related
behaviors such as dental check-ups and adoption of
birth control methods. The original HBM included only
recommended preventive health actions (TB screening

tests, polio shots).

27

As currently formulated, the Health Belief Model
views health-related behaviors as likely to be
performed by persons who 1) are motivated to perform
them, 2) perceive a value in reducing the threat of
disease, and 3) believe that health action will reduce

this threat (Harris and Guten, 1979).

Theoretical Framework

 

The theoretical framework for this study is based
primarily on the Health Belief Model. The earliest
formulation of the Health Belief Model (Rosenstock,
1966) stated that in order for an individual to take
action to avoid a disease one would have to believe that
(1) one was personally susceptible to it, (2) that
occurrence of the disease would have at least moderate
severity on some component of one's life, and (3)
pursing a particular action would be beneficial in
reducing the threat and the barriers to this action
would not be insurmountable. An underlying assumption
of the HBM is that "good health" is highly valued and a
goal for most individuals.

The Health Belief Model is a psychosocial model
that relates an individual's decisions about preventive
health behavior to psychological theories of decision
making which attempt to explain action in a choice
decision. The HBM theorizes that modification in

beliefs and attitudes is necessary for change to occur

28

in one's behavior. The HBM analyzes an individual's
motivation to act as a function of the expectancy of
goal attainment in the area of health behavior (Maiman
and Becker, 197A).

The Health Belief Model was chosen as a conceptual
framework because it is based firmly on social
psychological theory, relies heavily on motivational
and cognitive factors and has a growing body of research
that supports the Model's explanatory capability. While
few studies have operationalized the variables in the
same way, the dimensions have remained predictive
despite the different measures.

The original Health Belief Model (Fig. 1, p. 21)
was used by Murray (1982) to explore the perception of
health risk of Michigan apple growers. This study
proposed that the healthwpreventivemxiewpoint is one of
the strongest incentives to purchase and use protective
garments. Results of the data analysis reported a
positive relationship between perception of health risk
and their willingness to use spray garments.

The three broad classes of variables which
comprise the current (Fig. 2, p. 25) Health Belief Model
(readiness to undertake recommended compliant behavior,
modifying and enabling factors, and compliant behaviors)
have been adapted by the writer to reflect protective

health actions as related to clothing actions.

29

The four major dimensions of the HBM (susceptibility,
seriousness, barriers, and benefits) are addressed.
Various additions and modifications have been made to
tailor the model to pesticide application and actions
related to protective clothing. Figure 3 summarizes the

model prOposed to be tested in this study.

Theoretical Definitions

 

This section includes theoretical definitions of

concepts relevant to the model proposed for this study.

1. Readiness to Undertake Protective Health Action
An individual's subjective state of "readiness to

take action" relative to a particular health related

activity. It is composed of the following dimensions.
General Health Care Motivation - An
individual's overall general concern about
health matters. The interacting variables
identify basic perceptions about general
concern for one's health and in this instance,
safety when using pesticides. This concern
can be reflected in a willingness to engage in
positive health activities.
Perception of Risk - This term refers to
the interaction of three dimensions:
susceptibility, seriousness and objective

experience. The perception of risk is based

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31

upon an individual's perceived likelihood of
being susceptible to an illness or vulnerable
to disease in general, the perception of

the seriousness of the illness that may affect
one physically or socially, and objective
experience which may reinforce individual
perceptions of risk and danger. Seriousness
and susceptibility are terms originally used
by Rosenstock and are still applicable to
ideas presented in recent works. Objective
experience is broader than that cited in the
review of literature which limited experience
to symptoms. In the case of pesticide
application other knowledge and experience
seem equally relevant.

Benefits vs Barriers - An individual's belief
that a specific action, in this case actions
relative to clothing, will reduce the threat
of illness weighed against the perceptions of
physical, financial, and psychological

barriers to the action.

2. Modifying and Enabling Factors

These factors include demographic and enabling
variables that might, in any given instance, interact in
the decision-making process and influence the choice of

protective health actions.

32

3. Protective Health Actions

 

These are actions that reflect protective health

behavior.

Operational Definitions

 

The following Operational definitions were
established in order to define the variables used
in this study. The number appearing after each
item refers to the questionnaire in Appendix A.

Model to Predict Protective Health Actions

Related to Pesticides and Clothing. A model, based on

 

the Health Belief Model, which attempts to identify
variables which influence an individual's adOption of
protective actions related to clothing and pesticide
safety (Fig.3, p. 30).

Readiness to Take Action. The interaction of three

 

broad variable classes: General Health Motivations,
Perception of Risk, and Benefits vs Barriers. The
interaction of these variables will result in some
protective health action.

General Health Motivations is made up of the
following statements selected from the questionnaire to
represent perceptions of general concern for one's
health and safety when using pesticides.

1) People really can't avoid getting pesticide on

their clothes if they farm nowadays. (Q-30)

2) Insecticide should be used only when

monitorin the insects indicates it is
needed. Q-31)

3)
A)

5)
6)

33

PeOple should never go into the house wearing
clothes that have pesticide on them. (Q-32)
Pesticides are not harmful if they are handled
properly- (Q—33)

It is better to pay someone else to apply
pesticide and avoid the health risk. (Q-37)
Risks are just part of the job in pesticide
application. (Q-38)

Perception of Risk is comprised of three

 

dimensions: A) Susceptibility, B) Seriousness, and C)

Objective Experience.

A)

B)

Susceptibility to pesticide related illness is
indicated by responses to the following
indicators:

1) How often would you sa pesticide gets
on your clothes? (Q-9

2) When pesticide gets on your clothes,
how often does it get through the
clothing to the skin? (Q-lO)

3) How effective do you feel the clothes
you usually wear are in protecting you
from pesticide exposure? (Q-18)

u) How likely is it that getting
pesticides on your skin will cause
immediate health risk? (Q-19)

5) How likely is it that getting
pesticides on your skin will cause long-
term harm? (Q-21)

6) Olothes keep pesticide off the skin.

Q-27

7) Most people are tough enough to take

exposure to pesticides without harm.
Q-29

8) The risk involved in getting pesticide
on clothes is nothing compared to
breathing pollution in the air. (Q-36)

Seriousness is measured by the individual’s
responses to:
1) How serious do you think that immediate
health risk is apt to be? (Q-20)

2) How serious do you think that long-term
harm is apt to be? (Q-22)

34

C) Objective Experience includes:

1)
2)

3)
4)

5)

Years of pesticide use. (Q-2)

Number of days per year using

pesticides. (Q-3)

Toxicity of insecticides used most in the
past two years. (Q-S)

Toxicity of other pesticides used most

in the past two years. (Q-6)

The toxicity of the pesticide that most
often gets on the clothes. (Q-7)

Perceived Benefits vs Barriers are measured by the

 

attitudes and practices related to pesticide use in the

following statements.

Perceived Benefits:

1)

2)

Overall, for you personally, how would
you rate the cr0p yield benefit
associated with pesticide application?
(Q-26)

The benefits of pesticides far exceed
whatever risks may be involved. (Q-35)

Perceived Barriers:

1)

2)

Overall, for you personally, how would
you rate the health risk associated
with pesticide application? (Q-26)
There are lots of things on the farm
that are far more dangerous than
pesticides. (Q-Bu)

Modifying and Enabling Factors are mediating

variables.

In this study the following demographic and

health related variables have been chosen as likely to

influence Readiness to Take Action and Protective

Health Behavior.

Age at the beginning of the study. (Q-39)

%ev:l)of education reported in the study.
Q- 0

Income for the previous year. (Q-MZ)

Number of current household members.(Q-39)

35

Age of youngest child living at home.
Q-39

Symptoms of pesticide poisoning. (Q-23)
Health problems that have necessitated an
end to pesticide usage. (Q-24)

Protective Health Actions are indicated by the

following measures:

1)

3)

4)
5)

Wearing protective clothing. This includes
coveralls or long-sleeved shirt and pants,
shoes, socks, and head covering or any
clothing that offers a degree of protect-
ion from pesticides. (Q-11)

The length of time that pesticide soiled
clothing is worn before laundering. (Q-13)
How soon clothing is changed after
spilling li uid concentrate on the
clothing. (Q-ls)

How soon clothing is changed after
becoming saturated with pesticide spray.
Storage of soiled clothin separate from
the family laundry. (Q—16

Other Operational definitions important to the

study are:

Pesticides. Any of the various substances used to

kill harmful weeds (herbicides), fungi (fungicides),

insects (insecticides), and rodents (rodenticides).

Toxicity.

 

This refers to the level of toxicity

of a pesticide determined by using the signal words

(danger, warning, caution) that appear on the product

label.

CHAPTER III

METHODOLOGY

This study is part of North Central Region Project
170, "Limiting Pesticide Exposure Through Textile
Cleaning Procedures and Selection of Clothing." The
Michigan project is directed by Dr. Ann C. Slocum in the
Department of Human Environment and Design. It is
funded by the Michigan State University Agricultural
Experiment Station. Five states participated in the
survey part of the regional project. The survey was
designed to determine current selection, use, and care

practices for pesticide contaminated clothing.

Description of the Instrument

A self-administered questionnaire was developed for
use as the data collection instrument. Pilot studies
were done during 1982 in Iowa and California to pretest
the questionnaire which would be used by all five
states participating in the regional survey project. An
evaluation of the prototype questionnaire was carried
out in Michigan during the summer of 1983. Fifteen
MSU College Week participants completed the trial

questionnaire and the questionnaire evaluation forms.

36

37

Throughout the fall of 1983 research teams from the five
states worked together to produce a revised instrument
which was ready to be mailed in February 1984. A basic
set of questions and the same questionnaire format was
used in all five states.

The final questionnaire consisted of two sections.
The first section was directed to the adult in the
household who applies pesticides most often and the
second section was to be completed by the adult who
usually does the laundry. The pesticide applicator was
asked to respond to forty-two questions. The launderer
answered thirty-six questions. Respondents were asked to
describe the kind of pesticides most frequently used,
types of clothing worn when applying pesticides, storage
practices and cleaning procedures for pesticide soiled
clothing, attitudes about pesticides use and protection,
and demographic variables. For this study only the
pesticide applicator section of the survey is being
used (Appendix A).

A cover letter, which was written on the inside of
the front page of the questionnaire booklet, invited the
grower to participate in the study. The project was
briefly described and respondent confidentiality was
assured. A phone number was listed so that participants
could call to confirm the legitimacy of the survey.

Participants were asked to return the blank

38

questionnaire if no one in the family had used
pesticides in the last two years. Booklet return was

simplified by the use of the business reply mail system.

Data Collection

 

Six hundred and fifty Michigan farm families were
selected from Michigan agricultural producers who
reported at least $1000 in farm produce sales for the
fiscal year 1982. Using a systematic random sampling
design from two lists, 150 apple growers and 500 corn
growers were chosen to receive questionnaires. The
number of growers in each sample was proportional
to the total number of growers on each list.

The initial mailing of the survey questionnaire
was made in late February, 1984. Approximately three
weeks later a second request-reminder was mailed to
nonrespondents. Participants were encouraged to
call if they had any questions about the project.
Thirty-one phone calls were received. A third letter
containing a return postcard was mailed approximately
two weeks later to those who had not responded to the
second letter. Several completed booklets were received
in plastic bags due to rough handling at the post
office. Total response for the survey was 366, 57.4%
were corn growers and 52.7% were apple growers. However,

30% and h8%, respectively, were useable (Table 1).

39

Table 1.--Survey Response Rate.

 

 

Growers

Category of Corn Apple
Response n % n %
Eligible 150 30.0 72 48.0
Retired 43 8.6 4 2.7
Use Commercial

Applicator 33 6.6 1 .7
Don't use pesticides 61 12.2 2 1.3
No response 213 42.6 71 47.3
Total 500 100.0 150 100.0

 

The response rate of this survey is similar to that
reported by Henry (1980) for a sample of licensed
Michigan pesticide applicators. Five hundred
questionnaires (41.7%) were returned from the original

mailing of twelve hundred.

Data Coding

 

Graduate and undergraduate students from Michigan
State University coded the completed questionnaires
during the spring of 1984. The coding procedures were
developed for use by all five states who participated in
the survey. Every tenth questionnaire was check coded
for inconsistencies. Discrepancies were discussed and
coding rules established as necessary. Coded responses
were than keypunched to computer cards and placed on

computer tape.

40

Questions were coded to reflect natural order:
eg., the higher the number, the greater the feeling of

exposure, risk, or danger.

Description of the Variables

 

Some of the variables used in this study were
created from answers to questionnaire items.

Health Cues to Action was created by taking the
average of the weighted response to eighteen illness
symptoms listed in 0-23. The scale ranges from 1 to 5.
A 5 indicates that the respondent always experiences
all the symptoms after working with pesticides.

A toxicity rating was assigned to each pesticide
checked as being used in the past two years. Each
pesticide checked was coded into four categories. The
code assigned was derived from the signal words that
appear on the label of the particular pesticide.
Danger-Poison (category I) appears on the labels of the
most toxic pesticides (code 4), Warning (category II)
denotes less danger (code 3), and the signal word
Caution describes pesticides that are in categories III
and IV (code 2 & 1).

Demographic data was condensed into fewer
groups. Respondents were grouped into six categories
based on their age (Table 2, p. 47), six groups based on
highest level of education reported (Table 3, p. 48),

and ten income categories (Table 4,p. 49). For the

41

purposes of statistical analysis the respondents' actual
age, the real number of years of education completed,
and the mid-point of the income categories was used.

Action 1, wear pesticide soiled clothing again
before laundering, was created from the responses to
0-13. The index ranged from 0 days (do not wear again
before laundering) to 10 (actual number of days
indicated by respondent that clothing is worn before
laundering).

Action 2, storage of pesticide soiled clothing
separate from family laundry, was created from the
tally of the number of types of soiled garments stored
separate from the general family laundry as reported in
0-16. Table 11 (p.56) reports the types of garments
corn and apple growers store separately.

Action 3, the protective clothing index, was
created from responses to 0-11. The garments reported
worn for pesticide application were assigned a value to
reflect area and thickness (Appendix D). The values
were summed and indicate the protection offered by the
clothing. The higher the sum, the more protection
during pesticide application.

Action 4, time before changing after spilling full
strength liquid concentrate, is the actual time reported
by respondents in 0-14 and Q-14a. Four categories were
created that summarized the hours reported by the

respondents. The categories ranged from less than

42

1 hour to 7+ hours.

Action 5, time before changing after saturation
with pesticide spray, is the time reported by the
respondents in 0-15 and Q—15a. Four categories were
created that ranged from less than 1 hour to 7+ hours.

The dimensions of the Protective Health Actions
Model were initially develOped by grouping questionnaire
items together based on the definitions of the HBM
dimensions reviewed in the literature and an analysis of
question content. The groupings were general health
motivations: perception of risk, comprised of
susceptibility, seriousness, and objective experience:
perceived benefits vs barriers: modifying and enabling
factors: and protective health behavior. These items are
found in the operational definitions, p. 32 — 35.

After the initial grouping, statistical tests
for reliability were run on each group to determine
whether the items could be summed and used as scales.

In general, the concept of reliability refers to how
accurate, on the average, the estimate of the true
score is in a pOpulation of objects to be measured.

If all the variation in observed scores is due to
errors in measurement, the reliability coefficient
will be zero. If there is no error of measurement,
the reliability coefficient will be one (Nie and Hull,

1981). According to Nie "alpha is perhaps the most

43

widely used reliability coefficient." Cronbach's
alpha is a reliability coefficient computed by SPSS.
Reliability coefficients of a well-made
standardized test tend to be high, .9 or above.
However, coefficients of .50 or less are not
uncommon and may be useful (Ferguson, 1971). After
reviewing the results of the computer analysis the
decision was made not to use any of the groupings
as they had been proposed. In every case the alpha
levels were less than .50. The model constructs will
therefore be represented by the individual items rather

than the groupings of items.

Data Analysis Procedures
The Statistical Package for the Social Sciences

(Nie, Hull, Jenkins, Steinbrenner, and Bent 1975, 1981)
was used for all statistical programs. The level of
significance for rejecting the null hypothesis was set
at .05. The decision was made to look at corn and apple
growers as two separate groups based on the number of
hypotheses where significant differences were found to
exist between the two groups. The unit of analysis is

the individual corn or apple grower.

Statistical Tests
T-tests were used to test the hypotheses dealing
with the differences between corn and apple growers.

This analysis is the comparison of two groups, with the

44

group mean as the basis for comparison. The goal of
this analysis is to establish whether or not a
difference between two samples is significant. The
assumptions for this test are: normality, equality of
variance, and independence. If populations of unequal
variances are given, t cannot be computed. Instead, an
approximation to t may be computed. An F test of sample
variances is performed and a decision to base t on
pooled-variance or separate variance must be made (Nie
et al., 1981). SPSS allows these tests to be done
simultaneously.

Pearson product-moment correlation provides a
single number which summarizes the relationship between
two variables. Pearson's r serves a dual purpose. It
indicates the goodness of fit,of the linear regression
and the strength of the linear relationship between the
two variables. The coefficient r takes on a value from
+1.0 to -1.0. Correlations that approach +1 indicate a
strong positive relationship: correlations that
approach -1 indicate a strong negative relationship.
When the linear regression line is a poor fit, r will
be close to 0.

When Pearson's r is squared the resulting
statistic, r53, measures the prOportion of variance in
one variable explained by the other. It ranges from a

minimum of O to a maximum of 1.0. The objectiveof

45

correlation analysis is to determine the extent to which
variation in one variable is linked to variation in the
other (Nie et al., 1975).

A principal components factor analysis with

 

iteractions and varimax rotation was conducted to

locate and define dimensions among the variables. The
most distinctive characteristic of factor analysis is
its data reduction capability. A smaller number of
clusters of variables can be obtained from a larger

set of independent items. Eigenvalues, loadings and
communality are important in understanding factor
analysis. The eigenvalue is a measure of the relative
importance of the function. The sum of the eigenvalues
is a measure of the total variance existing in the
discriminating variables. Total variance accounted for
by the combination of all common factors is usually
referred to as the communality of the variable. The
loadings represent regression coefficients of factors to
describe a given variable. In the initial factor
analysis twelve factors were generated. A second run
produced eight factors and a third, six factors. The
choice of variables which were used in the second and
third factor analyses was based on the eigenvalues and
loading score. Variables loading at .40 were inputed
for the second and third analysis. The six factors that
are reported in this study are made up of variables that

load at .50 or higher in the third analysis.

CHAPTER IV

ANALYSIS, FINDINGS AND DISCUSSION

This chapter presents general descriptive data
about the survey sample and reports the results for
the research questions and hypotheses associated with
objectives one, two, and three. Findings related to the
three research objectives are discussed at the end of

each objective.

Description of the Sample

The data for this investigation is based on
responses from seventy-two Michigan apple growers
and a hundred and fifty Michigan corn growers who
applied pesticides to their crops during 1982 and 1983.
Three of the pesticide applicators were female.
Age

The corn applicators ranged in age from twenty to
seventy-five years, with a mean of forty-seven years.
Apple growers ranged in age from twenty-five to eighty,
with a mean of fifty-one years (Table 2).

Education

 

As indicated in Table 3, the mean level of
educational attainment for both corn and apple growers

was twelve or more years of school.

46

47

Table 2.--Age Distribution of the Sample

 

 

Growers
Age in Years n Corn % nApple %
20-30 19 12.7 a 5.6
31-40 28 18.7 12 16.7
41-50 31 20.7 20 27.8
51-60 31 20.7 14 19.4
61-70 19 12.6 10 13.9
71-80 5 3.3 6 8-3
Missing Data 17 11.3 6 8.3
Total 150 100.0 72 100.0
‘Mgan Corn Apple

 

Ages 47 yrs. 51 yrs.

 

48

Table 3.--Education Distribution of the Sample

 

 

 

Growers
Education Attained Corn Apple

n % n %
Thru 8 grades 8 5.3 6 8.3
school
High School 70 46.8 15 20.9
graduate
H.S. + 3 yrs. 33 22.0 23 31.9
Completed College 17 11.3 11 15.3
Post Graduate 3 2.0 6 8.3
Missing Data 5 3.3 3 4.2
Total 150 100.0 72 100.0

Mean Corn Apple
Grades

Completed 12.6 13.2

 

49

Fifteen percent of the apple growers have completed
college as compared to eleven percent of the corn
growers. Eight percent of the apple growers have post
graduate education.
Income

Family income ranged from less than $7500 per year
to more than $85,000 per year for both corn and apple
growers (Table 4). The mean income for corn growers is

$32,738 and for apple growers is $31,336.

Table 4.--Family Income Distribution of the Sample

 

 

Growers

Categgiylgg3Dollars n Corn % nApple %
less $7500 20 13.3 8 11.1
7,501-17,500 37 24.7 9 12.5
17,501-25,000 26 17.3 20 27.8
25,001-35,000 18 12.0 8 11.1
35,001-45,000 8 5.3 4 5.6
45,001-55,000 6 4.0 2 2.8
55,001-65.000 5 3.4 2 2.8
65,001-75,000 1 .7 1 1.4

75,001—85,000 1 .7 0 0
85,001 plus 14 9.3 4 5.6
Missing data 14 9.3 14 19.3

Total 150 100.0 72 100.0

 

50

Descriptive Data for Objective 1

 

The first objective of this study was to gather
base line information about applicators' selection,
storage, and wearing practices for pesticide soiled
clothing.

Question 1. What kind of clothing do pesticide

applicators wear when applying pesticides?

Respondents were asked to check all garments that
they usually wear when applying pesticides. Six groups
of clothing were listed. I

The first type of garment was shirts. Pesticide
applicators were asked to indicate what kind of shirt
they usually wear when applying pesticides. Table 5

reports shirts worn for pesticide application.

Table 5.--Shirts Worn for Pesticide Application

 

 

Growers
Style of Shirt Corn Apple

n % n %
Long sleeved 93 62.0 58 80.6
Short sleeved 37 24.7 13 18.1
Sleeveless 5 3.3 3 6.9
No shirt 1 .7 1 1.4
Missing Data 14 9.3 O 0
Total 150 100.0 77 107.0*

*Some individuals checked more than one garment.

 

51

Long sleeved shirts were reported to be worn by sixty-
two percent of the corn growers and eighty-one percent
of the apple growers. Less than one and a half percent
of either corn or apple pesticide applicators work
without wearing a shirt.

Table 6 reports the type of pants that applicators
usually wear. Approximately sixty-five percent of the
corn growers and sixty-four percent of the apple growers
wear jeans or work pants. A small percentage, less than
three percent, wear shorts or cutoffs. No one checked

wearing sweatpants.

Table 6.--Pants Worn by Pesticide Applicators

 

 

Growers
Style of Pants Corn Apple
n % n %

Coveralls with

long sleeves 32 21.3 25 34.7
Bib overalls 19 12.7 6 8.3
Jeans or Work Pants 97 64.7 46 63.9
Shorts, cutoffs 2 1.3 2 2.8
Total 150 100.0 79 109.7*

*Some individuals checked more than one garment.

 

As Table 7 shows, the biggest majority of
applicators, both corn and apple, wear leather shoes
or boots. Several respondents checked wearing waterproof

vinyl or rubber boots with their leather shoes.

52

Table 7.--Shoes Worn for Pesticide Application

 

 

Grower
Style of shoes Corn Apple

n % n %
Waterproof vinyl or
leather 11 7.3 15 20.8
Leather 118 78.7 59 81.9
Canvas 3 2.0 1 1.4
Missing Data 18 12.0 0 0
Total 150 100.0 75 104.1*

*Some individuals checked more than one type of
shoe.

 

Waterproof vinyl or rubber gloves are worn by
thirty-nine percent of the corn growers and forty-nine
percent of the apple growers. Table 8 also shows that
twenty-nine percent of the corn growers and nineteen
percent of the apple growers do not usually wear gloves
when applying pesticides.

The styles of hats worn by pesticide applicators
are reported in Table 9. Sixty-six percent of the corn
growers and sixty-one percent of the apple growers wear
company or baseball hats. Eight percent of the corn
growers and seven percent of the apple growers indicated
they do not wear any kind of head covering when applying

pesticides.

53

Table 8.--Gloves Worn for Pesticide Application

 

 

Growers
Type of Glove Corn Apple

n % n %
Waterproof vinyl or 48 32.0 35 48.6
rubber
Leather 15 10.0 10 13.9
Canvas 22 14.7 10 13.9
Other 7 4.7 3 4.2
Usually don't wear 43 28.7 14 19.4
Missing data 15 10.0 0 0
Total - 150 100.0 72 100.0

 

Table 9.—-Hats Worn for Pesticide Application

 

 

Growers
Style of Hat Corn Apple
n % n %
Hard plastic 3 2.0 9 12.5
Felt 5 3.3 1 1.4
Straw 3 2.0 5 6.9
Company or baseball 99 66.0 44 61.2
Other 10 6.7 6 8.3
Usually don't wear 12 8.0 5 6.9
Missing Data 18 12.0 2 2.8

Total 150 100.0 72 100.0

 

54

Other Clothes, shown in Table 10, has nine
different types of clothing listed. Twenty-seven
percent of the apple growers reported wearing a
waterproof jacket but only eleven percent of them wear
waterproof pants. Only about six percent of the corn
growers indicated they wear waterproof jackets and
pants. Several respondents wrote that they ride in an

enclosed tractor cab which they feel offers protection.

Table 10.--Other Clothing Worn for Pesticide Application

 

 

Growers
Type of Clothing Corn Apple
n % n %
Jacket or coat 59 39.3 36 50.0
Sweatshirt 26 17.3 9 12.5
Sleeveless vest 10 6.7 4 5.6
Undershirt 63 42.0 31 43.1
Jockey/Boxer shorts 75 50.0 37 51.4
Socks 83 55.3 44 29.3
Belt 72 48.0 33 45.8
Waterproof jacket 9 6.0 20 27.8
Waterproof pants 10 6.7 8 11.1

 

The typical pesticide applicator, both corn and
apple, is likely to wear a long sleeved shirt, jeans or
work pants, leather shoes, waterproof vinyl or rubber

gloves, and a company or baseball style hat.

55

Approximately one-third of the corn growers wear a
jacket or coat as compared to fifty percent of the
apple growers. In both groups about forty percent
wear undershirts and fifty percent indicated they
wear jockey or boxer shorts. Only one respondent
wrote in the questionnaire that a respirator was worn.

Question 2. Where is pesticide soiled clothing

stored before laundering?

Pesticide applicators were asked to check whether
they stored clothing worn for pesticide application with
other family laundry or separate from other family
laundry. Seven categories of clothing were listed.
These were:

a. shirts, jeans, workpants
b. underwear

c. jackets, coveralls

d. boots, shoes

e. hats, caps

f. gloves

g. belts

In six out of the seven categories of clothing,
over fifty percent of both corn and apple growers
stored the types of laundry separate from the other
family laundry. Category b, underwear, was the only
type of clothing that was stored over fifty percent of
the time with other family laundry. Table 11 reports

the storage of pesticide soiled clothing together or

separate from the rest of the family laundry.

56

Table 11.--Storage of Pesticide Soiled Clothing
Before Laundry

 

 

Growers
Corn Apple
Type of With Separate With Separate
Clothing Family Family

 

n % n % n % n %’

 

Shirts, 42 28.0 100 66.7
jeans,
workpants

16 22.2 54 75.0

Underwear 78 52.0 57 38.0 39 54.2 22 30.6

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
\O

 

Jackets, 26 17.3 102 68.0 12.5 57 79.2
coveralls

Boots, 29 19.3 103 68.7 13 18.1 55 76.4
shoes

Hats, 30 20.0 96 64.0 10 13.9 57 79.2
caps

Gloves 20 13.3 101 67.3 6 8.3 57 79.2
Belts 38 25.3 78 52.0 20 27.8 40 55.6
Corn n = 150

Apple n 72

57

Question 3. What kind of actions do corn and apple
growers engage in when clothing becomes soiled with
pesticides?
Table 12 reports the number of applicators who
wear clothes soiled with pesticides again before they
are laundered. Seventy-one percent of corn applicators
and seventy-two percent of apple applicators do not wear
pesticide soiled clothing again before laundering.

However, twenty-five percent of the apple growers do

wear their soiled clothing again.

Table 12.--Wear Soiled Clothing Again Before Laundering

 

 

Growers
Soiled garments Corn Apple
worn again n % n %
No 106 70.7 52 72.2
Yes 22 14.6 18 25.0
Missing data 22 14.7 2 2.8
Total 150 100.0 72 100.0

 

When asked how many days the pesticide soiled
clothing was worn applicators reported wearing the
clothing from one to ten days before laundering.

Table 13 reports the number of days soiled clothing is
worn before laundering. Approximately five percent of
the corn growers and ten percent of the apple growers

wear pesticide soiled clothing for two days before

laundering.

58

Table 13.--Number of Days Soiled Clothing Worn Before

 

 

Laundering
Growers

Number of Days Corn Apple
n % n %
0 106 70.7 52 72.2
1 O 0 3 4.2
2 7 4.7 7 9.6
3 7 4.7 2 2.8
4 1 .7 1 1.4
5 2 1.2 3 4.2

7 1 1.4 0 0
10 O 0 1 1.4
Missing data 27 18.0 2 2.8
Total 150 100.0 72 100.0

 

Table 14 shows responses to the question of how
soon corn and apple growers reported changing clothing
if full strength concentrate was spilled on non-
waterproof clothing. Twenty-one percent of the corn
growers and thirteen percent of the apple growers
indicated they did not spill liquid concentrate on
themselves. Forty-one percent of the corn growers and
twenty-six percent of the apple growers reported
changing within an hour of the spill. Thirteen percent
of the corn growers wore clothing that had been soiled
with liquid concentrate for seven or more hours as

compared to only one percent of the apple growers.

59

Table 14.--Time Reported Before Changing Non—waterproof
Clothing After Spilling Full Strength
Liquid Concentrate

 

 

Growers

Time Reported Before Corn Apple
Changing Clothes n % n %
Don't spill 21 14.0 13 18.1
Less than 1 hour 41 27.3 26 36.1
1 - 3 hours 28 18.7 20 27.8
4 - 6 hours 12 8.0 5 6.9
7 or more hours 19 12.7 1 1.4
Missing data 29 19.3 7 9.7
Total 150 100.0 72 100.0

Y corn = 1.3 hours 7 apple = .9 hours

 

When asked how soon they changed after their
non-waterproof clothing became saturated with pesticide
spray, thirty percent of the corn applicators and
thirty-six percent of the apple growers reported
changing in less than an hour. Table 15 reports that
approximately six percent of both corn and apple growers
wear clothing that has become saturated with pesticide
spray for seven or more hours. Seventeen percent of the
corn growers and twenty—one percent of the apple growers
responded that they did not become saturated with spray.
As Tables 14 and 15 show, approximately twenty percent
of the corn growers did not respond to either question.

It is possible they use only a granular formulation.

60

Table 15.--Time Reported Before Changing Non-waterproof
Clothing That Has Become Saturated with
Pesticide Spray

 

 

Growers

Time Reported Before Corn Apple
Changing Clothes n % n %
Not Saturated 26 17.3 15 20.9
Less than 1 hour 45 30.0 26 36.1
1 - 3 hours 31 20.7 18 - 25.0
4 - 6 hours 9 6.0 3 4.2
7 or more hours 9 6.0 5 6.9
Missing data 30 20.0 5 6.9
Total 150 100.0 72 100.0
7 corn = 2.4 hours 7 apple = 2.4 hours

 

When reporting actions in regard to clothing that
becomes soiled with pesticides approximately seventy
percent of both corn and apple growers do not wear their
pesticide soiled garments again before laundering.
However, twenty-five percent of the apple growers
reported wearing their soiled clothing again. One
respondent reported wearing his soiled clothing for ten
days.

When asked how soon they changed after spilling
either full strength liquid concentrate on their clothes
or becoming saturated with spray both corn and apple
growers reported similar actions. Less than twenty

percent reported they don't spill.

61

Tests and Findings for Objective 2

 

Procedures and test statistics for hypotheses were
presented in Chapter III. The results of statistical
tests performed for each hypotheses are presented and
the hypotheses are stated in the null form.

Objective 2 is to determine if there are any
differences between corn and apple growers in the study.
It should be noted that the greater the number of
separate tests performed, the greater the likelihood
that some difference may be claimed as real when it is
actually due to chance (Type II error).

H1: There will be no significant difference
between the mean ages of corn and apple
growers.

The two-tailed independent t-test (129) = -1.87
compared to the table value of 1.98, p <:.05 indicates
the decision is to accept the null hypotheses. There is
no significant difference in the mean ages of corn and
apple growers. The mean age of corn growers is 47 years

and 51 years for apple growers (Table 2, p. 47).

H2 There will be no significant difference
between the mean years of education of

corn and apple growers.

The mean years of education for corn growers is
12.6 and 13.2 for apple growers (Table 3, p. 48). The
two-tailed independent t-test (109) = -1.60 compared to

the table value of 1.98, p <:.O5 indicates that the

62

decision is to accept the null hypotheses. There is no
significant difference in the mean years of education
for corn and apple growers.

H3: There will be no significant difference
between the mean incomes of corn and apple
growers.

The mean income for corn growers is $32,739 and
$31,336 for apple growers (Table 4, p. 49). Based on
results of the two-tailed t-test the decision is made to
accept the null hypotheses that there are no significant
differences between the mean incomes of corn and apple
growers.

H4: There will be no significant difference

between the mean family size of corn and
apple growers.

The mean family size for corn growers is 3.6
members and 3.3 members for apple growers. Based on
the two-tailed independent t-test (211) = 1.51 compared
to the table value of 1.97, p <:.05 the decision is to
accept the null hypothesis that there are no significant
differences between the mean family size of corn and
apple growers.

H5: There will be no significant difference
between the mean ages of the youngest child
living at home under 18 years for corn and
apple growers.

The average age of the youngest child living at

home for corn growers is 8.2 years and 9.5 years for

63

apple growers. Based on the two-tailed independent
t-test the decision is made to accept the hypothesis
that there is no significant difference between the
mean ages of the youngest child living at home for
corn and apple growers.

H6: There will be no significant difference
between the mean number of years individual
corn and apple growers have been applying
pesticides.

Table 16 reports the number of years that

corn and apple growers have been applying pesticides.

Table 16.-—Years Applying Pesticides

 

 

Growers
Number of Years Corn Apple
n % n %
2 - 10 56 37.3 15 20.8
11 - 20 59 39.3 19 26.4
21 - 30 20 13.3 15 20.8
31 - 40 7 4.7 12 16.7
41 — 50 1 .7 1 1.4
51 - 60 1 .7 1 1.4
61 - 65 0 0 1 1.4
Missing data 6 4.0 1 1.4
Total 150 100.0 72 100.0
7 corn = 16.1 ‘7 apple = 24.7

 

Corn growers have been applying pesticides for an

average of 16.1 years and apple growers for an average

64

of 24.7 years. The decision is made is reject the null
hypothesis based on the two-tailed independent t-test.
There is significant difference in the mean number of
years that corn and apple growers have been applying
pesticides. Apple growers have applied pesticides for
more years on the average.

H7: There will be no significant difference

between the mean number of days per year
that individual corn and apple growers
apply pesticides.

Corn growers apply pesticides a mean of 17.8 days
per year while apple growers apply pesticides a mean of
36.8 days per year. Based on the two-tailed independent
t-test the decision is made to reject the null
hypothesis. There is a significant difference between
the number of days that corn and apple growers apply

pesticides each year. Table 17 shows that apple growers

use pesticides more days per year than do corn growers.

Table 17.--Days per Year Applying Pesticides

 

 

Growers
Days Per Year Corn Apple
n % n %
1 to 30 days 133 88.7 41 56.9
31 to 90 days 6 4.0 25 34.8
91 to 180 days 5 3.3 5 6.9
Missing data 6 4.0 1 1.4
Total 150 100.0 72 100.0

Y corn 17.8 ‘Y apple = 36.8

 

65

H8: There will be no significant difference
between the toxicity of pesticides used
by corn and apple growers.

Tables 18 and 19 report the toxicity of insect-

icides and other pesticides used in the past two years.

Table 18.--Insecticide Used Most in Past Two Years.

 

 

Growers
Toxicity of Insecticide Corn Apple
n % n %

1 = least toxic 0 O

2 = less toxic 31 20.7 5 6.9
3 = toxic 42 28.0 15 20.8
4 = most toxic 35 23.3 48 66.7
Missing data 42 28.0 4 5.6
Total 150 100.0 72 100.0

Y corn = 3.0 7 apple = 3.6

 

Table 19.--Other Pesticides Used Most in Past Two Years

 

 

Growers
Toxicity of Other Corn Apple
Pesticides n % n %
1 = least toxic 1 .7 O O
2 = less toxic 53 35.3 16 22.2
3 = more toxic 23 15.3 6 8.3
4 = most toxic 33 22.0 43 59.8
Missing data 40 26.7 7 9.7
Total 150 100.0 72 100.0

7 corn = 2.8 ‘Y apple = 3.4

66

The decision is to reject the null hypothesis based on
the two-tailed independent t-test for both groups of
chemicals. There is significant differences in the
toxicity of the pesticides used by corn and apple
growers. Apple growers use more toxic chemicals.

H9: There will be no significant difference
between corn and apple growers regarding
the kind of clothing that is worn to apply
pesticides.

Based upon the score that each applicator received
through the use of the protective clothing index
(Appendix D), the two-tailed independent t-test
indicated that the decision is to reject the null
hypothesis. There is a difference in the kind of
clothing that corn and apple growers wear to apply
pesticides. The clothing index score reflects the area
and thickness of the clothing that applicators indicated
they wear when applying pesticides. The higher the
score the more protection offered. The possible range
for scores is four to forty-four. The mean of the
clothing index scores for corn growers is 19.9 and 22.0
for apple growers. Apple growers reported wearing
clothing that affords more protection.

H10: There will be no significant difference
between the storage practices for pesticide
soiled clothing of corn and apple growers.

Table 20 shows the number of pesticide soiled

garments that are stored with the family laundry. Corn

growers store a mean of 2.8 soiled garments with other

67

family laundry and apple growers a mean of 2.6 garments.
The two-tailed independent t-test indicates that there
is no significant difference between the storage
practices of corn and apple growers, therefore the

null hypothesis is accepted.

Table 20.--Soiled Garments Stored With Family Laundry

 

 

Growers
Category of Storage Corn Apple

n % n %
All stored separate 58 38.7 25 34.7
1 with family 31 20.7 20 27.8
2 with family 18 12.0 11 15.3
3 with family 16 10.7 7 9.7
4 with family 8 5.3 2 2.8
5 with family 6 4.0 2 2.8
6 with family 5 3.3 3 4.1
All with family 8 5.3 2 2.8
Missing data 0 0 O 0
Total 150 100.0 72 100.0

‘7 corn = 2.8 ‘7 apple = 2.6

 

H11: There will be no significant difference in
the toxicity of the pesticide that is spilled
on clothing worn by corn and apple growers.

Table 21 shows the toxicity of the pesticides

applicators report most frequently gets on their

clothing. The mean of the toxicity of the chemicals

that get on corn growers clothing most often is 1.9 and

68

the mean for apple growers is 3.2. The decision based
on the two-tailed independent t-test is to reject the
null hypothesis. The toxicity of the spills that get
on applicators clothing is significantly different for
corn and apple growers. Apple growers reported getting
more toxic pesticides on their clothing than did corn

growers.

Table 21.--Toxicity of Pesticides Spilled on Clothing

 

 

Growers
Toxicity of Pesticide Corn Apple

n % n %
Never spill 42 28.0 7 9.7
1 = least toxic 0 O O O
2 = less toxic 29 19.4 9 12.5
3 = more toxic 23 ‘ 15.3 14 19.5
4 = most toxic 32 21.3 41 56.9
Missing data 32 21.3 1 1.4
Total 150 100.0 72 100.0

‘7 corn = 1.9 ‘7 apple = 3.2

 

H12: There will be no significant difference in
the time reported by corn and apple growers
to change non-waterproof clothing after
spilling full strength liquid concentrate
on themselves.

Table 14 (p. 59) reports the time that corn and
apple growers reported it took them to change after a
full strength liquid concentrate spill. The two-tailed

independent t-test (184) = 2.30 compared to the table

69

value of 1.97, p <:.O5 indicates the decision to reject
the null hypothesis. There is significant difference
in the time reported by corn and apple growers to
change their clothing after spilling full strength
liquid concentrate. Corn growers report wearing their
soiled clothing longer on the average than do apple
growers.

H13: There will be no significant difference in

the time reported by corn and apple growers to
change clothing that has been saturated with
pesticide spray.

Results of the two-tailed independent t—test
indicate the decision to accept the null hypothesis.
There is no significant difference in the time reported
by corn and apple growers to change clothing that has
been saturated with pesticide spray. Table 15 (p. 60)
reports the time estimated to change spray saturated
clothing. The mean time for both corn and apple growers

is 2.4 hours.

Summary of Findings for Objective 2
There are no significant differences between
corn and apple growers in regard to age, years of
education, income, family size, ages of children
under eighteen living at home, laundry storage of
pesticide soiled clothing, and the length of time
non-waterproof clothing saturated with spray is

reported worn.

70

There are significant differences in number of
years that the corn and apple growers have applied
pesticides, the days per year that corn and apple
growers apply pesticides, the toxicity of pesticides
used in the last two years by corn and apple growers,
the kind of clothing that is worn, the length of time
that non-waterproof clothing soiled with full strength
liquid concentrate is worn and the toxicity of the
pesticides that are reported to get on applicators'

clothing.

Questions and Hypotheses for Objective 3

Objective 3 is to explore a model which explains

actions taken with respect to pesticide soiled clothing.

Question 1. Do components of the Protective

Health Action Model (Fig. 3, p. 30) help predict

the likelihood of protective clothing actions for

pesticide applicators?

H1: Among pesticide applicators the variables that
comprise general health behavior will not be
significantly related to protective health
actions. ‘

Six questions were originally included in the

General Health Dimension (p. 32). Only variables
which correlated at p <:.05 are reported.

As indicated in Table 22 four of the five

Protective Health Actions (p. 33) showed significant

correlations with four statements from the General

Health Dimension.

71

Table 22.—~Pearson Product Moment Correlations Between
General Health and Protective Health Actions

 

 

 

General Action Action Action Action

Health 1 2 3 5
Grower Growers Growers Growers
Corn Corn Apple Corn Apple Corn Apple

Can't avoid .179 .173 .243

pesticides .027 .030 .025

on clothes

Risk just -.169 .238 -.290

part of job .033 .026 .010

Don't go in -.200 -.353 .196

house wearing .008 .001 .015

soiled clothes

Pesticides -.238

differ in .020

toxicity

Action 1 = Wear pesticide soiled clothing again before

laundering.
Action 2 = Storage of pesticide soiled clothing separate
from family laundry.
Action 3 = Protective clothing index.
Action 5 = Time before changing after saturation with

pesticide spray.

72

For corn growers there was a positive, weak
relationship between the statement that one can't
avoid getting pesticide on clothing (r = .179, p = .027)
and Action 1, wear soiled clothing again before
laundering. A significant, negative relationship was
found between the statement that risk is just part of
the job (r = -.169: p = .033) and Action 1. Corn
growers who believe that one can't avoid getting
pesticides on clothing and that risks are just part
of the job in applying pesticides reported wearing
soiled clothing longer than other corn growers.

For both corn (r = -.200: p = .008) and apple
(r = -.353: p = .001) growers there was a negative,
moderate relationship between the belief that one should
not go into the house wearing pesticide soiled clothing
and Action 2, store soiled clothing separate from family
laundry. Agreeing that one should not go into the
house wearing pesticide soiled clothing was associated
with a greater number of garment types stored separate
from the family laundry.

There were significant relationships between three
General Health Dimension statements and Action 3, the
clothing index. For corn growers a weak relationship
exists between the statement don't go into the house
wearing pesticide soiled clothing (r = .196: p = .015)

and the clothing index. Apple growers showed a positive

73

relationship between risk is just part of the job
(r = .238: p = .026) and Action 3 and a negative
relationship between the statement that pesticides
differ in toxicity (r = -.238: p = .020) and Action 3.
Corn growers who believed that one shouldn't go into the
house wearing pesticide soiled clothing were more likely
to score higher on the clothing index, eg, have more
body covering when applying pesticides. Agreement about
variation in toxicity and disagreement with risk as part
of the job was associated with wearing more clothing for
apple growers.

For corn (r = .173: p = .030) and apple (r = .243:
p = .025) growers there was a significant, positive
relationship between the statement that one can not
avoid pesticides on clothes and Action 5. Apple growers
had a moderate, negative relationship (r = -.290:
p = .010) with the belief that risks are just part of
the job and Action 5. The more likely both corn and
apple growers were to agree that people can't avoid
getting pesticide on their clothing, the longer they
reported taking to change their clothing after becoming
saturated with pesticide spray. Apple growers who
agree that risks are just part of the job in pesticide
application also reported taking longer to change after

becoming saturated with spray.

74

Two kinds of relationships are observed between
reported behaviors and actions in the General Health
Dimension. There seems to be an attitude about risk
which can be characterized in terms of a risk taker or
a risk avoider.

The attitudes associated with a risk taker are
reflected in findings of Action 1. Corn growers who
believe that one can't avoid getting pesticides on
clothing and that risks are just part of the job
reported wearing soiled clothing longer. They indicate
a feeling of "it isn't going to affect me anyway so why
bother with wearing clean clothing every day." They
also indicated they did not immediately change clothing
that was saturated with spray.

The risk avoider reports correlations of high
scores on the clothing index and storing garments
separate from the family laundry and the belief that one
should not go into the house wearing pesticide soiled
clothing. The applicators labeled as risk avoiders
also disagreed that risk is just part of the job.

H2: Among pesticide applicators the variables that
comprise perception of risk will not be
significantly related to protective health
actions.

Perception of risk is comprised of three

dimensions: A) Susceptibility, B) Seriousness, and

C) Objective Experience.

75

Susceptibility

 

The initial susceptibility scale was comprised of
seven questions (p. 31). The statements which showed
significant correlations at the .05 level with at least
one of the five protective health actions are reported
in Table 23.

Corn growers showed a significant, negative
relationship between the belief that getting pesticides
on the skin will cause long-term harm (r = -.270:

p = .002) and Action 1. Corn growers who disagreed
that pesticide on the skin will cause long term harm
indicated they wore their pesticide soiled clothing
again before laundering. Evidently they did not view
the pesticide soiled clothing as a health hazard.

Corn growers showed a positive, moderate
relationship between the belief that clothing is
effective in offering protection from pesticide exposure
(r = .269: p = .013) and Action 2. Apple growers
reported a positive relationship between the statement
that clothes keep pesticide off the skin (r = .180:

p = .016) and Action 2. Apple growers who agree

that the clothing they usually wear is effective in
protecting them and corn growers who agree that clothes
keep pesticide off the skin reported storing garments

separate from the family laundry.

'76

Table 23. --Pearson Product Moment Correlations Between Susceptibility
' and Protective Health Actions

 

 

IVAction Action Action Action Action
1 2 3 1+ 5
Grower Growers Growers Growers Growers

Corn Corn Apple Corn Apple Corn Apple Corn Apple
Clothes,offer .269
protection 3 .013
Clothes keep .180 -.302 .174 .198 ‘
pesticide off .016 .006 .030 .016
the skin
Likelihood of -.270 .167
long-term harm .002 .035
Frequency that .204 .229
pesticide gets .010 .031
on clothes
Frequency -.249 .268
pesticide gets .021 .016
through to skin
Likelihood .301 .296
immediate health .001 .008
risk
Peeple tough .323 -.227 -.264
enough to take .001 . .036 .017
pesticides

 

Action 1 - Wear pesticide soiled clothing again before laundering.

Action 2 8 Storage of pesticide soiled clothing separate from family

laundry.

Action 3 8 Protective clothing index.

Action 4 = Time before changing after spilling full strength liquid
concentrate.

Action 5 = Time before changing after saturation with pesticide spray.

77

As shown in Table 23, for corn growers there is a
significant and positive relationship between the
likelihood of long-term harm (r = .167: p = .035), the
frequency that pesticide gets on clothes (r = .204:

p = .010), the likelihood of immediate health risk

(r = .301: p = .001), the belief that most people are
not tough enough to take pesticide exposure (r = .323:
p = .001) and Action 3. Corn growers who agreed that
there is a likelihood of immediate health risk and
long-term harm, reported getting pesticides on their
clothing, and believed that most peOple are not tough
enough to take pesticide exposure scored high on the
clothing index, eg. covered the body more.

Apple growers reported two negative and one
positive relationship with Action 3. These are the
belief that clothes keep pesticides off the skin
(r = -.302: p = .006), the frequency with which
pesticides get through to the skin (r = -.249: p = .021)
and the likelihood of immediate health risk (r = .296:
p = .008). Apple growers who agreed that clothes keep
pesticides off the skin, that pesticides do not get
through clothing to the skin, and believe that it is
very likely there might be an immediate health risk
scored high on the clothing index.

For corn growers there is a slight, significant

relationship between the statement clothes keep

78

pesticide off the skin (r = .174: p = .030) and

Action 4. Apple growers show a negative relationship
between the statement that people are tough enough

to take pesticide exposure (r = -.227: p = .036) and
Action 4. Corn growers who disagreed that clothes keep
pesticide off the skin and apple growers who agreed that
most pe0ple are tough enough to take pesticide exposure
reported taking longer to change their clothing after
spilling full strength liquid concentrate on themselves.
The relationship for corn growers is difficult to
explain. Perhaps corn growers do not identify with

the use of liquid concentrate or they believe that the
skin is a barrier to absorption. Apple growers do not
reveal a high degree of susceptibility. They

express the belief that peOple are tough enough to

take pesticide exposure and report not changing
immediately after spilling full strength liquid
concentrate on their clothing.

For corn growers, the statement that clothes keep
pesticide off the skin (r = .198: p = .016) showed a
positive relationship with Action 5. For apple growers,
the frequency that pesticide gets on clothes (r = .229:
p = .031), frequency that pesticides gets through to the
skin (r = .268: p = .016), and the statement that people
are tough enough to take pesticide exposure (r = -.264:

p = .017) were significantly related to Action 5. The

79

more likely corn growers were to disagree that clothes
keep pesticides off the skin, the longer it takes them
to change their clothing after becoming saturated with
pesticide spray. This may again be a situation where
corn growers do not identify with the use of spray.

Or, they may believe that if the clothing is wet and
they are not changing quickly, pesticide is getting on
the skin anyway. Apple growers were likely to agree
that pesticide often gets on their clothes and through
the clothing to the skin. This is very reasonable if in
fact they are wearing clothing that has been saturated
with spray for long periods of time. Apple growers also
indicated that the insecticide and other pesticide that
most frequently gets on their clothes is toxic. Many

of the sprays used by apple growers are insecticides
which are highly toxic. This may reflect a statement of
knowledge about the chemicals they are using. However,
it also indicates lack of belief in susceptibility and a
risk taker's attitude. They know the chemical on their
clothing is toxic but are not bothering to change
quickly after being saturated with spray.

Seriousness

 

Table 24 shows that for corn growers there was
a statistically, significant relationship between the
belief that getting pesticides on the skin will cause
serious long-term harm (r = -.175: p = .046) and

Action 1. Corn growers who believed that long-term

8O

harm was not very serious were more likely to wear
their pesticide soiled clothing again before laundering.
There were no other actions related to the seriousness
dimension.

Table 24.--Pearson Product Moment Correlations Between
Seriousness and Protective Health Action 1

 

Action 1
Wear Pesticide'Soiled Clothing Again Before Laundering

 

Growers
orn
Seriousness of -.175
long-term harm .046

 

Objective Experience

 

Five objective measures were included in the
objective experience dimension of perception of risk.
The correlations for four of these measures are reported
on Table 25, page 81.

For corn growers the days per year they apply
pesticides (r = .169: p = .032) and the toxicity of
other pesticides that most frequently get on their
clothes (r = .197: p = .028) is significantly related
to Action 1. The longer corn growers apply pesticides
during the year the more likely that they will wear
their soiled clothing again before laundering.

As the old saying goes, "Familiarity breeds
contempt." As corn growers work with toxic

pesticides, it may be that as they handle them

81

Table 25.--Pearson Product Moment Correlations Between
Objective Experience and Protective Health

 

 

Actions.
Action Action Action Action
1 2 4 5
Grower Grower Grower Grower
Corn Apple Apple Apple
Days/year applying .169 .241
pesticides .032 .028
Toxicity of .245
insecticide used .027
most last 2 yrs.
Toxicity of .222
insecticide most .036
frequently gets
on clothing
Toxicity of other .197 .220 .337
pesticides most .028 . .043 .002

frequently gets
on clothing

 

Action 1

Action 2

from family laundry.

Action 4

Action 5

pesticide spray.

Wear pesticide soiled clothing again before
laundering.

Storge of pesticide soiled clothing separate
Time before changing after spilling full
strength liquid concentrate.

Time before changing after saturation with

82

for long periods of time they lose sight of the
need for protective health actions. This may
be part of a risk taker's attitude.

The relationship of the toxicity of other
pesticides most frequently getting on the clothing was
significantly related to Action 2 for apple growers
(r = .220: p = .043). The more toxic the chemical used
the less likely that pesticide soiled garments would be
stored separate from the family laundry. This relation-
ship does not seem reasonable but it is possible. If
the applicator does not perceive a risk despite the
toxicity of the pesticide which is on the clothing it
is likely that little effort would be made to store the
soiled clothing separate from the family's laundry.

The days per year applying pesticides (r = .241:

p = .028) and the toxicity of the insecticide used most
in the last two years (r = .245: p = .027) showed a
moderate, positive relationship with Action 4 for apple
growers. Applicators who used pesticides more days

per year than others and indicate that they have used
highly toxic insecticides in the past two years took
longer to change their clothing after spilling full
strength liquid concentrate. These actions may be
typical of a risk taker. Applicators who use pesticides

for long lengths of time may not view them as dangerous.

83

For apple growers a significant relationship was
shown to exist between the toxicity of the insecticide
that most frequently gets on clothes (r = .222:

p = .036) the toxicity of other pesticides that most
frequently get on clothes and Action 5. Apple growers
who take longer to change their clothing after becoming
saturated with pesticide spray also indicate that the
insecticide and other pesticides that most frequently
get on their clothing is toxic. Again this is a
situation where there seems to be little perception of
risk. Apple growers indicate that they are using toxic
sprays yet do not quickly change their clothing after
becoming saturated with spray. They do not feel
susceptible to the effects of pesticide spray.

H3: Among pesticide applicators the variables that
comprise perceived benefits will not be
significantly related to protective health
actions.

Perceived benefits of pesticide use are defined

as the responses to questions 26 and 35 (p. 32).

Table 26 shows that for corn growers there was a

slight significant relationship between the statement
that the benefits of pesticides exceed the risks

(r = .180: p = .026) and Action 5. Corn growers who
agreed that the benefits of pesticides far exceed
whatever risk there is, reported taking longer to change

their clothing after becoming saturated with pesticide

84

spray. A strong belief in the benefits of pesticide use
may actually be a barrier to protective action.
Table 26.--Pearson Product Moment Correlations Between

Perceived Benefits and Protective Health
Action.

 

Action 5
Time Reported to Change Clothing
That Has Become Saturated With
Pesticide Spray

 

Growers
Corn
Benefits far .180
exceed the risks .026

 

H4: Among pesticide applicators the variables that
comprise perceived barriers will not be
significantly related to protective health
actions.

Two attitudinal statements were asked to measure
the perception of perceived barriers to pesticide use
(p. 34). Table 27 reports the correlations for these
statements and the protective health actions.

For corn growers there is a negative relationship
between the belief that there are lots of things on the
farm far more dangerous than pesticides (r = -.249:

p = .003) and Action 1. Corn growers who agreed that
there are lots of things on the farm far more dangerous
than pesticides reported wearing soiled clothing again
before laundering. Risk is relative, the corn grower

may be more concerned about getting caught in the power

takeoff of his tractor than illness from pesticides.

85

This lack of perception of risk may be a barrier to any
protective health action in regard to clothing. The
grower may view other safety and health protective
actions as much more important.

Table 27.--Pearson Product Moment Correlations Between
Perceived Barriers and Protective Health

 

 

Actions
Action 1
Wear Pesticide Soiled Clothing
Again Before Laundering

Growers
Corn
Lots of things on farm far -.249
more dangerous than pesticides .003

 

H5: Among pesticide applicators modifying and
enabling factors will not be significantly
related to protective health actions.

Seven variables were chosen to represent possible
modifying or enabling factors (p. 34). Only two
variables, applicator's age and illness symptoms, were
significantly related to any protective health actions.

Table 28 shows that for corn growers a positive
relationship exists between illness symptoms
(r = .220: p = .048) and Action 1. Illness symptoms
after working with pesticides were reported by those
corn growers who wear soiled clothing again before
laundering. Also reported for corn growers is a

relationship between illness symptoms (r = -.176:

p = .025) and Action 3. Corn growers who reported

86

fewer illness symptoms scored high on the clothing
index.

For apple growers there is a negative relationship
between applicator's age (r = -.348: p = .002) and
Action 2. The older the apple grower the more likely
that pesticide soiled garments would be stored separate
from the family laundry.

There also is a significant, negative relationship
for apple growers between applicator's age (r = -.275:
p = .014) and Action 3. Older apple growers were more
likely to score higher on the Clothing Index.

Table 28.--Pearson Product Moment Correlations Between

Modifying and Enabling Factors and Protective
Health Actions

 

 

 

Action Action Action
1 2 3
Grower Grower Grower
Corn Apple Corn Apple
Applicator's Age -.348 -.275
.002 .014
Illness Symptoms .220 -.176
.008 .025
Action 1 = Wear pesticide soiled clothing again before
laundering.
Action 2 = Storage of pesticide soiled clothing separate
from family laundry.
Action 3 = Protective clothing index.

87
Summary of Hypotheses and Findings for Objective 3

1. Do components of the Protective Health Action
Model help predict the likelihood of protective
clothing actions for pesticide applicators?

H1: Among pesticide applicators the variables that
comprise general health behavior will not be
significantly related to protective health
actions.

Seven questions are included in the general
health dimension. Four variables showed significant
correlations at the .05 level with at least one of four
protective health actions and the null hypotheses is
rejected for these variables. Table 29 (p. 88)
indicates which variables for corn and apple growers are
significantly related to protective health actions.

H2: Among pesticide applicators the variables that
comprise perception of risk will not be
significantly related to protective health
actions.

Perception of risk is comprised of three
dimensions: A) Susceptibility, B) Seriousness, and
C) Objective Experience.

Table 30 (p. 89) reports the significant
correlations for the perception of risk variables
and protective health actions. The null hypothesis
is rejected for the variables showing significant
correlations at the .05 level. The susceptibility
dimension is represented by eight statements. Seven of

the eight variables showed significant correlations with

at least one of the five protective health actions.

88

Table 29.--Summary of Significant Correlations for
General Health and Protective Health Actions
for Corn and Apple Growers

 

Actions
Variables that Comprise 1 2 3 4 5
General Health Motivations

 

People really can't avoid C C&A
getting pesticide on their
clothes if they farm nowadays.

Insecticide should be used
only when monitoring the
insects indicates it is needed.

PeOple should never go into C&A
the house wearing clothes
that have pesticide on them.

Pesticides are not harmful
if they are handled pr0perly.

It is better to pay someone
else to apply pesticide and
avoid the health risk.

Risks are just part C* A* A
of the job in pesticide
application.

Pesticides differ in A*
toxicity-some are very

dangerous and others

are not.

 

C* = Significant at .05 level of probability for
corn growers.
Null hypothesis rejected.

A = Significant at .05 level of probability for
apple growers.
Null hypothesis rejected.

C&A* = Significant at .05 level of probability for
corn and apple growers.
Null hypothesis rejected.

89

One seriousness statement was significantly correlated
with one protective health action. Four of the five
variables which represent objective experience are
significantly correlated with at least one action.
Table 30.--Summary of Significant Correlations for

Perception of Risk and Protective Health
Actions for Corn and Apple Growers

 

 

 

Variables that Comprise Actions

Perception of Risk 1 2 3 4 5
Susceptibility *

How often would you say C A”

pesticide gets on your

clothes?

When pesticide gets on your A* A“

clothes, how often does it
get through the clothing
to the skin?

How effective do you feel A”
the clothes you usually

wear are in protecting

you from pesticide exposure?

How likely is it that C&A*
getting pesticides on your

skin will cause immediate

health risk?

How likely is it that 0* 0*
getting pesticides on your
skin will cause long-term

harm?

Clothes keep pesticide off 0* A* 0* 0*
the skin.

Most people are tough enough C* A” A“

to take exposure to pesticides
without harm.

The risk involved in getting
pesticide on clothes is nothing
compared to breathing air pollution.

90

Table 30 (cont.)

 

Variables that Comprise
Perception of Risk

Actions

1 2 3 4 5

 

Seriousness
How serious do you think
that immediate health risk
is apt to be?

 

How serious do you think
that long-term harm is apt
to be?

Objective Experience
Years of pesticide use.

 

Number of days per year
using pesticides.

Toxicity of insecticides
used most in the past
two years.

The toxicity of the
pesticides that most
often get on clothes.

Toxicity of other
pesticides most often
get on clothing.

C
0 * 11*
A91-
A31-
Cit: A3? A36

 

C* = Significant at .05 level of probability for

corn growers.

Null hypothesis rejected.

A“ = Significant at .05 level of probability for

apple growers.

Null hypothesis rejected.

C&A* = Significant at .05 level of probability for

corn and apple growers.

Null hypothesis rejected.

91

H3: Among pesticide applicators the variables that
comprise perceived benefits will not be
significantly related to protective health
actions.

Perceived benefits of pesticide use are represented
by two attitudinal statements. One statement was
significantly correlated with one protective health

action.

Table 31.—-Summary of Significant Correlations for
Perceived Benefits and Protective Health
Actions for Corn and Apple Growers

 

Actions
Variables that comprise 1 2 3 4 5
Perceived Benefits

 

Overall, for you personally
how would you rate the crop
yield benefit associated with
pesticide application?

The benefits of pesticides C”
far exceed whatever risks
may be involved.

 

C“ = Significant at .05 level of probability for
corn growers.
Null hypothesis rejected.

92

H4: Among pesticide applicators the variables that
comprise perceived barriers will not be
significantly related to protective health
actions.

Perceived barriers to pesticide use are measured by
two statements. One statement is significantly
correlated with one protective health action. Table 32
reports the variables and significant correlations.
Table 32.--Summary of Significant Correlations for

Perceived Barriers and Protective Health
Actions for Corn and Apple Growers

 

Actions
Variables that Comprise 1 2 3 4 5
Perceived Barriers

 

Overall, for you personally,
how would you rate the health
risk associated with pesticide
application?

There are lots of things on C”
the farm that are far more
dangerous than pesticides.

 

3(-

C = Significant at .05 level of probability for
corn growers.
Null hypothesis rejected.

93

H5: Among pesticide applicators modifying and
enabling factors will not be significantly
related to protective health actions.

Seven health related variables comprise this factor.
Two variables were significantly correlated with three
protective health actions. Table 33 reports these
variables and correlations.

Table 33.—-Summary of Significant Correlations for
Modifying and Enabling Factors and

Protective Health Actions for Corn
and Apple Growers

 

Actions
Modifying and Enabling 1 2 3 4 5
Variables

 

Applicator's age A* A
Level of education reported
Income for previous year

Number of current household
members

Age of youngest child living

at home

Symptoms of pesticide C“ C*
poisoning

Health problems that have
necessitated an end to
pesticide usage

 

A“ = Significant at .05 level of probability for
apple growers.
Null hypothesis rejected.

C* = Significant at .05 level of probability for
corn growers.
Null hypothesis rejected.

94

A profile seems to be emerging in the data which

points to two types of pesticide applicators. One type

could be

classified as a risk taker and the other as

a risk avoider.

Based on the Pearson product moment correlation

matrix the risk taker_is one who does not engage in

protective health actions with regard to pesticides and

clothing.
1.

2.

30

10.

11.

12.

13.

This is the person who is likely to
Agree that one can't avoid risks.
Agree risks are just part of the job.

Agree that lots of things on the farm are far
more dangerous than pesticides.

Agree one can't avoid pesticide on one's
clothing.

Agree that pesticide often gets on their
clothing.

Disagree that clothes keep pesticide off the
skin.

Agree that pesticide gets through the clothing
to the skin.

Agree that people are tough enough to take
exposure to pesticide without harm.

Disagreed that pesticide on the skin will cause
long-term harm.

Disagree that long-term harm will be serious.

Believe that the benefits of pesticides far
exceed the risk.

Apply pesticides more days per year.

Report illness symptoms after working with
pesticides.

95

The applicator who is described as a risk avoider

is one who did engage in protective clothing actions

with regard to pesticides. The correlation matrix

indicates that this person is likely to

9.

Be aware of the variations in pesticide
toxicity.

Report getting pesticides on clothing worn.

Believe the clothing that is worn is effective
in protecting from pesticides.

Agree that clothes keep pesticide off the skin.

Agree that pesticides don't get through the
clothing to the skin.

Disagree that pe0ple are tough enough to take
exposure to pesticides without harm.

Agree that one shouldn't go into the house
wearing pesticide soiled clothing.

Agree that there is a likelihood of immediate
health risk.

Agree that there is a likelihood of long-term
harm.

10. Be an older applicator.

11. Report fewer illness symptoms.

96

Factor analysis began with a thirty-four item
correlation matrix which was factored by means of
the principal components analysis method of factor
extraction (p. 45). Factor loadings of .500 or greater
were used to identify the items that were assigned to
each factor in the final six-factor rotated matrix
which is reported in this chapter. Eigenvalues are all
greater than one. Data from corn and apple growers was
analyzed separately. Tables 34 (apple growers) and 35
(corn growers) report the factor loadings, communality,
eigenvalues and percent variation for the six factors
extracted.

The factor analysis of questionnaire items suggests
that dimensions of the model are represented in the
six factors. Items which make up the six factors are
similar, but not identical, for corn and apple growers.
The model dimensions of perception of risk, benefits and
barriers, modifying factors, and protective health
actions are reflected in the six factors. Table 36 and
Table 37 list the variables which loaded at .5 or
greater for the six factors.

The five items comprising Factor I were included in
the perception of risk part of the model. The first
four variables were defined as reflecting susceptibility
and seriousness in the model. The fifth variable was

included in the objective part of perception of risk.

97’

Table 34.--Factor Loadings for Apple Growers

 

Variables

Factor Factor Factor

 

Factor Factor Factor COMMUN-
1 2 3 4 5 ALITY
Yrs. applied pest. -.36742 -.59454 -.17439 .20676 .16631 .04045 .59093
Toxicity of pest. -.00597 -.16112 .00454 .24316 .58912 -.23724 .48848
used last 2 yrs.
Toxicity of insect. -.176?3 .01200 .5609? .12368 .29720 .15926 .47505
gets on clothes. .
Toxicity of pest. -.02628 .17289 .66591 -.02395 .04595 .02193 .47718
gets on clothes.
Pest. gets thru -.03978 .53842 .08785 .15446 .10706 .26617 .40536
clothes to skin.
Change after liq. .17281 -.02318 -.00560 .96696 .18834 -.01396 1.00111
concentrate spill.
Change after spray -.06797 .08165 .27480 .67823 -.21702 .09651 .60320
saturation.
Clothing effective -.16878 .79053 -.00061 .05299 .18306 .13074 .70684
in protection.
Likelihood immediate .65094 -.11637 -.14197 .12019 -.O725O -.25195 .54061
health risk.
Likelihood long- .8795? .0698? -.11661 .02851 .14860 .05470 .81801
term harm.
Clothes keep pest. .02869 .26094 -.35882 -.O8577 -.18305 .59590 .59363
off skin.
Seriousness of .82259 .10168 -.04667 .06409 .1345? .0717? .71653
long-term harm.
Rate health risk. .61459 .2361? -.18317 .01221 .47349 .28930 .77509
Can't avoid pest. -.04633 -.09554 .74900 .06147 -.08722 -.06853 .58836
on clothes. .
Lots of things more .30181 .04994 -.05884 -.18979 .68930 .07972 .61455
dangerous on farm. -
Applicator's age. -.25895 -.68201 .03386 .09004 -.01340 .50583 .79750
Eigenvalue % Variation Cummulative %

Factor 1 3-43145 29-6 29-6

Factor 2 2.15931 18.3 47.9

Factor 3 1.99757 17.0 64.8

Factor 4 1.58174 13.4 78.3

Factor 5 1.34294 11.4 89.?

Factor 6 1.21686 10.3 100.0

953

Table 35.--Factor Loadings for Corn Growers

 

 

Variables Factor Factor Factor Factor Factor Factor COMMUN-
1 2 3 4 5 ALITY
Yrs. applied pest. .15193 .02084 .0170? .88731 -.11885 -.12561 .84102
Days per yr. apply .53793 .17631 .06791 .20715 .01051 -.11120 .38046
pesticides.
Toxicity of other .04850 .6906? -.1?870 -.O6684 .02029 .00064 .51619
pest. gets on clothes.
Change after liq. -.01265 .19251 .08553 -.07592 -.03772 .65780 .48442
concentrate spill.
Change after spray .04549 .09901 .17730 .00355 -.O9327 .65516 .48125
saturation.
Likelihood immediate .56065 .48444 -.28?55 -.18263 .23783 -.O7961 .?2?95
health risk.
Likelihood long— .80590 .20355 -.11088 -.22345 .05429 .04785 .75836
term harm.
Seriousness of .68571 .04654 -.08076 -.16075 .15906 .00501 .53005
long-term harm.
Rate health risk. .65741 .10188 .16365 -.00010 .10572 .01601 .48078
Crop yield benefit. .23402 .01149 .75818 .06100 ~.14320 -.01196 .65411
(Don't go in house .11013 .04813 .07500 -.02878 .95062 .0312? .92555
wearing pest. soiled
clothing.
Benefits exceed -.15525 .13306 .72261 -.O7166 -.00909 .21130 .61384
risks.
Applicator's age. -.28939 .19941 -.02672 .58568 .12052 .09453 .49070
Eigenvalue % Variation Cummulative %

Factor 1 3.14748 30.6 30.6

Factor 2 1.84590 17.9 48.5

Factor 3 1.6690? 16.2 64.7

Factor 4 1.47303 14.3 79.0

Factor 5 1.11915 10.9 89.9

Factor 6 1.03762 10.1 100.0

99

Factor II reflects an objective perception of
risk. Toxicity of other pesticides used most frequently
in the last two years was the only variable to load
above .50 in this factor.

Factor III appears to be related to barriers to
action in the model. Strong belief in the necessity for
pesticides for a good cr0p yield and the benefits of
pesticides may provide a barrier to taking protective
actions with respect to clothing.

Factor IV is made up of modifying factors. It is
quite logical to see the years applying pesticides and
an applicator's age cluster together. The more years
one has applied pesticides the older one would be.

Factor V pertains to an attitude about a protective
health action and an action. The question was not asked
if one did in fact "not go into the house wearing
pesticide soiled clothing". The statements dealing with
going into the house and storing soiled laundry separate
showed a moderate, negative correlation (p. 71) for both
corn and apple growers.

Factor VI includes two protective health actions.
Both deal with the time that the applicator reported for
changing clothing after either a full strength liquid
concentrate spill or becoming saturated with spray.

Factor I for apple growers again is related to the

dimension of perception of risk. It is made up of the

100

Table 36.--List of Variables Loading at .50 or Greater
for Corn Grower Factors.

 

 

Item Loading
Factor I
Likelihood of pesticide causing long-term .806
harm.
Seriousness of long-term harm .686
Rate health risk associated with pesticide
application. .657
Likelihood of pesticide causing immediate
health risk. .561
Days per year apply pesticides. .538
Factor II
Toxicity of other pesticides used most .691

frequently in the last two years.

Factor III

Rate crop yield benefit associated with .758
pesticide application.

Benefits of pesticide far exceed whatever .723

risks there are.

Factor IV

Years Applied Pesticides. .887

Applicator's Age .586

Factor V

PeOple should never go into the house .951
wearing pesticide soiled clothing.

Store soiled garments separate from -.449

family laundry.

Factor VI

Time reported to change clothing after .658
spilling full strength liquid concentrate.

Time reported to change clothing after .655

clothing saturated with pesticide spray.

101

Table 37.--List of Variables Loading at .50 or Greater
for Apple Grower Factors

 

 

Item Loading

Factor I

Likelihood of pesticide on skin causing .880
long-term harm

Seriousness of long-term harm .823

Likelihood of pesticide causing immediate .651
health risk

Rate health risk associated with pesticide .615
application

Factor II

Evaluation of effectiveness of clothing .791
worn for protection

Applicator's age -.682

Years applying pesticides -.595

Pesticide gets through clothes to skin .538

Factor III

People can't avoid getting pesticide on .749
their clothing

Toxicity of other pesticide most frequently .666
gets on clothes

Toxicity of insecticide most frequently .561

gets on clothes
Factor IV

Time reported to change clothing after .967
spilling full strength liquid concentrate

Time reported to change clothing after .678
clothing saturated with pesticide spray

Factor V

Lots of things more dangerous on farm .689
than pesticides.

Toxicity of insecticide used most often .589
in last two years.

Factor VI

Clothes keep pesticide off the skin .596
Applicator's age .506

102

same four variables that deal with susceptibility and
seriousness as Factor I for corn growers. Days per
year did not load in Factor I for apple growers.

Factor II is comprised of four variables, two
of which are related to clothing as a barrier to
pesticides. Applicator's age and years applying
pesticides load together but both are negative this
time. Evaluation of the effectiveness of clothing worn
for protection and whether or not pesticide gets through
clothes to the skin are included in this factor.

Factor III includes two statements about the
toxicity of chemicals which get on clothing and the
belief that people can't avoid getting pesticide on
their clothing.

Factor V combines the attitudinal statement that
lots of things are more dangerous on the farm than
pesticides and the toxicity of the insecticide used most
often in the last two years.

Factor VI clusters an attitude about clothing,
clothes keep pesticide off the skin, with the
applicator's age.

The results of the factor analysis suggest that
the attitudes expressed by corn and apple pesticide
applicators are reflected in the dimensions identified
as part of the Protective Health Action model. Factor

I for both corn and apple growers is substantially the

103

same. While other factors are not identical it appears
that they are very similar. Further factor analysis,
using a larger sample, would strengthen the support for
the relationships between the dimensions of the model

and the questionnaire items.

CHAPTER V

SUMMARY, CONCLUSIONS, LIMITATIONS AND

IMPLICATIONS FOR RESEARCH

This chapter includes the summary of the study,

conclusions, limitations, and implications for further

research.

Purpose

Summary

The primary focus of this study was to explore

actions and attitudes of Michigan corn and apple growers

with regard to pesticides and clothing. Specific

research objectives were:

1.

Gather baseline information about applicators'
selection, storage, and wearing practices for
pesticide soiled clothing.

Determine if there are differences between
corn and apple growers with respect to
demographic variables, experience and use

of pesticides, clothing and laundry practices,
and toxicity and formulation of pesticides that
are reported to get on clothing which is worn
while applying pesticides.

Explore a model which explains actions taken

with respect to pesticide soiled clothing.

104

105

Methodology

 

This investigation was part of the larger North
Central Region Project 170. "Limiting Pesticide Exposure
Through Textile Cleaning Procedures and Selection of
Clothing". The sample for this investigation was
150 corn growers and 72 apple growers who applied
pesticides within the last two years of the survey and
completed the applicator section of the questionnaire.

Data was analyzed using the SPSS computer package
which provided descriptive statistics, two-tailed
independent t—tests, Pearson Product Moment correlations

and factor analysis.

Findings

No significant differences were found between
Michigan corn and apple growers in regard to age, years
of education, income, family size, ages of children
living at home under the age of eighteen, laundry
storage of pesticide soiled clothing, and the length of
time reported that non-waterproof clothing saturated

with spray was worn. There were significantjdifferencesu
in the number of years that corn and apple growers have
applied pesticides, the days per year that corn and
apple growers apply pesticides, the toxicity of the

pesticides used in the last two years, the kind of

clothing that is worn, the length of time reported

106

to change non-waterproof clothing soiled with full
strength liquid concentrate, and the toxicity of the
pesticide most often reported getting on applicator's
clothing.

The typical pesticide applicator, both corn and
apple, is likely to wear a long sleeved shirt, jeans
or work pants, leather shoes, waterproof vinyl or
rubber gloves, and a company or baseball style hat.

In six out of seven categories of clothing listed, over
fifty percent of both corn and apple growers stored
pesticide soiled types of laundry separate from the
other family laundry. Only underwear was stored over
fifty percent of the time with the family laundry.

Over seventy percent of corn and apple growers
reported that they do not wear pesticide soiled garments
again before they are laundered. However, a small
percentage of applicators do wear soiled clothing up
to ten days. Both groups reported similar actions
concerning the length of time it takes to change
clothing which has become saturated with pesticide spray
or soiled with full strength liquid concentrate. Less
than twenty percent reported they don't spill pesticides
on themselves. Approximately fifty percent of both
groups report changing in three hours or less.

Components of a Model to Predict Protective

Health Actions were explored. The model is composed

107

of General Health Motivations, Perception of Risk,
Benefits vs Barriers, Modifying and Enabling Factors,
and Protective Health Actions. Significant correlations
were found among variables making up each component

and at least one of the Protective Health Actions.

Factor analysis suggests that there are underlying )
patterns of relationships in the variables of the data
which reflect some of the dimensions of the model. ‘
The six factors identified are not identical for corn yea
and apple growers. However, many of the same variables
are found in both sets of factors. Further analysis may
lead to the construction of questions which will more
accurately tap the dimensions of the model.

Based on the correlation data a profile of two
types of pesticide applicators seem to have emerged.
They are tentatively identified as, the Risk Taker and
the Risk Avoider, with regard to protective clothing
actions.

The individual identified as a Risk Taker did not
report taking protective clothing actions. Significant
correlations were observed between this type of
pesticide user and the belief one can't avoid risks,
getting pesticides on clothing, perception of
susceptibility to harm from pesticides, belief in the
seriousness of harm from pesticides, days per year

applying pesticides, the belief that the benefits of

108

pesticides far exceed the risks, and reported illness
symptoms after working with pesticides.

The applicator who is labeled as a Risk Avoider
did comply with protective clothing actions.
Significant correlations were found between this profile
and the belief that one shouldn't go into the house
wearing pesticide soiled clothing, belief that one is
susceptible to health risk, belief that harm from
pesticides is serious, applicator's age, and fewer
illness symptoms. According to the model this is an
individual who is in the "readiness to act" state.
For both corn and apple growers, more applicators can

be classified as Risk Takers.

Conclusions

 

The following conclusions are based upon the
results of data analysis and hypothesis testing.

Based on the significant differences in
experiential variables found between corn and apple
growers the decision was made to look at the pesticide
applicators as two separate groups.

Both corn and apple growers wear similar kinds
of clothing while applying pesticides.

Clothing actions reported in regard to soiled
clothing were similar for corn and apple growers.

Generally, components of the Protective Health

109

Action model correlated moderately with at least one
clothing action.

Factor analysis suggests that there is a
patterning in the variables of the study that may
encompass the dimensions of the model. The six factors
that emerged from the data reduction indicate that a
more concise, smaller set of questions may be deveIOped
which will account for the interrelationships observed
in the data.

Data from the study suggests that there are two
types of pesticide applicators who responded to the

questions, the Risk Taker and the Risk Avoider.

Limitations

 

On the basis of this investigation, the following
limitations and research recommendations are offered:

Generalization of the findings are limited to
the population represented by the respondents, Michigan
corn and apple growers. However, it is reasonable to
expect some commonality among farmers across the
different types of crops grown.

Responses to a survey questionnaire may not
reflect the actual actions and attitudes of this group.
Michigan farmers are constantly being questioned about
all facets of their occupation and fear that more
government regulations may result from any data

collected.

110

Two general attitudes about pesticides and
protective health actions seem evident in the emergence
of the risk taker and risk avoider profiles from the
data. The relationships between the components of the
model and the clothing actions may have been clearer if
the data had been analyzed on the basis of attitudes
rather than crops.

The questionnaire was not specifically written
to test a model. The number of questions that
represented the components of the model was not

sufficient.

Discussion of Implications for Further Research

 

Obvious limitations exist when utilizing data from
a questionnaire that was not designed to specifically
represent the dimensions of the Protective Health Model.
It is recommended that further research be devoted to
develOping valid and reliable questions and scales which
can be used to solicit data from respondents which will
define and expand the model. Further development of the
model would be enhanced by considering the ecosystem
principles.

The Protective Health Action Model stresses
that actions result when attitudes and beliefs of an
individual create a state of "readiness to take action"

for that individual. Based on analysis thus far, a

111

profile of a risk taker and risk avoider seems to be
present in the variables which make up the "readiness
to take action" part of the model. Whether or not
an applicator engaged in protective health actions
correlated with the category to which one belonged.

The risk taker did not engage in protective
clothing actions. One wonders therefore about the
perceptions of the person identified as a risk taker.

Do Michigan corn and apple growers perceive an immediate
and serious risk to their health from pesticides? Do
growers have any first hand experience in dealing with
illness which can be directly attributed to pesticides?
Is clothing viewed as a means of protection from
pesticide poisoning? Judging from the responses in
this survey very few have experienced any serious
health problems. While laboratory studies have
established toxicity levels, agricultural producers

do not directly link illness and the use of most
pesticides.

Another explanation for this lack of perception
of risk may be cognitive dissonance. The knowledge that
pesticides are harmful to one's health and the belief in
the benefit of their use may be very hard to reconcile.
So the individual rationalizes by believing that "most
applicators are tough enough to take pesticide exposure"

(and I'm one of the tough ones).

112

Protective clothing has been identified as a method
of safety protection for workers using pesticides.
However, clothing actions are only one aspect of
protective health behavior. The care in handling a
pesticide when mixing and loading and the protection of
an enclosed cab may be viewed as more important to the
applicator than the clothing related actions listed in
the questionnaire. The individual may perceive little
risk because other precautions or protective actions not
covered in this study are taken.

Pesticides are only one type of risk that an
agricultural worker faces. Injury from animals,
machinery accidents, illness from weather, and the
stress of being a farmer in today's economy may have
greater impact on perception of risk and health related
problems than do pesticides. These were not included in
this study.

Development of better textile products, safer
chemicals, and other technological advances can all
decrease the risk to which an agricultural worker is
exposed. However, the utilization of the Protective
Health Action Model may serve as a vehicle for
educational programs to develop specific health and
safety specific strategies for individuals and groups.
With the development and testing of questions that are

reliable and valid in identifying an individual's risk

113

profile, programs could be planned that would address
the reasons for protective actions. A computer game
which leads the participant through a series of
questions based on the dimensions of the model may
help individual's identify their attitudes about

risk and health.

The complexity of human attitudes and beliefs
makes it difficult to explain an individual's health
related behavior. But it is vitally important in
today's complicated world to address the problems of
pesticides and health. Protective clothing has been
identified as a means of providing protection from
pesticides and other toxic chemicals. The Protective
Health Action Model could provide a tool for clarifying
and defining perceptions of risk and encouraging
adoption of protective clothing and other clothing

related actions.

APPENDICES

APPENDIX A

APPLICATOR PORTION OF QUESTIONNAIRE

USED IN THIS STUDY

Clothes and Pesticides:
What is the Relationship?

 

SURVEY OF
PESTICIDE APPLICATOR FAMILIES

114

1155

MICHIGAN STATE UNIVERSITY

COLLEGE OF HUMAN ECOLOGY EAST LANSING ° MICHIGAN ° 48824

DEPARTMENT OF HUMAN ENVIRONMENT AND DESIGN

Dear Friends,

Information on the relationship between clothing and pesticide
exposure is limited, especially with respect to the effects of
different laundry methods on removal of pesticides. You are being
invited to participate in a survey concerned with the use and care
of clothing worn when applying pesticides. Our purpose is to learn
about the kind of clothes worn when applying pesticides, where these
clothes are stored after wearing, and what laundry procedures are
used for cleaning them. The study is being conducted by Michigan
State University Clothing and Textile researchers in conjunction with
four other universities as part of a regional research project.

Results of this research will be used to direct laboratory
experiments to determine more effective cleaning methods for clothing
worn when applying pesticides. Your participation is totally
voluntary. Your answers will remain confidential and will be
summarized with responses of other persons similar to yourself for
purposes of reporting. You may refuse to answer any question or set
of questions. However, we hope you will complete the questionnaire

to insure that we have the best information on which to base our
laboratory studies.

The questionnaire has two parts. Each part should take no
were that IS minutes to complete. The first part should be completed
by the adult in the family who uses pesticides most frequently. The
second part should be completed by the adult who is usually responsible
for doing the laundry. For purposes of this study, herbicides,

fungicides, insecticides, and rodenticides are all considered to be
pesticides.

If you have any questions about this survey, please call
Ann Slocum or Lois Shern at (5l7) 355-3779. If no one in your

family has applied any pesticides in the past two years, please
return the blank questionnaire.

Thank you for your help in answering our questions.
Sincerely, ‘
W 6' Mu

AS/lcs

1163

PART I: TO BE FILLED OUT BY THE ADULT WHO APPLIES PESTICIDES

_———_—_——————-

HOST OFTEN

 

 

SECTION A: EXPERIENCE WITH PESTICIDES -

0-1. 00 you work with pesticides primarily as (check one)
7

1. AN INDEPENDENT FARH OPERATOR
2. A COMMERCIAL APPLICATOR
3. OTHER (please specify)

 

C

0-2. About how many years have you used or applied pesticides?
(8-9) '

 

number of years

0-3. About how many days each year do you work with pesticides?
(IO—12)

 

number of days

0-4. Have you used any of the following insecticides or other
types of pesticides (herbicides, fungicides, and
rodenticides) in the past two years?

(check all you have used)

 

 

 

(13-22) (13—221
INSECTICIDES 1 PESTICIDES 2
l. COUNTER l. CYPREX (DODINE)
2. ' DYFONATE 2 CAPTAN
3. FURADAN 3. POLYRAM
A. THIMET 4. DIKAR
5. OTHER (please specify) 5° IMIDIAN
6 PLICTRAN
7 GUTHION
omen PESTICIDES 8 “OTHER (Please Specify)
6- __ ATRAZINE
7'-————-5UTAN 1 Corn growers questionnaire.
8- __ DUAL 2
9. LASSO Apple growers questionnaire.
10. OTHER (please specify)

 

0-5.
(23)

0-6.

(27)

2117

Which insecticide have you used in the greatest quantity in the
past two years? (list one) .

 

A. What was the formulation of the insecticide listed in
question 5? (Check one)

 

l. GRANULAR 4. OTHER (please specify)
2. POWDERED
3. LIQUID 5. DON'T KNOW

B. How was this insecticide applied? (check one)
(ZS-26)

l. __FIXED WING AIRCRAFT 7. ____FOGGER

2. __BOOM SPRAYER 8. ___DUSTER

3. _HYDRAULIC SPRAYER 9. _____GRANULE SPREADER

4. __AIR BLAST SPRAYER lO. ____SOIL INJECTOR

5. ___LOW VOLUME AIR SPRAYER ll. ____HAND EQUIPMENT

6. ________ULTRA-'-OW VOLUME SPRAYER l2. ___OTHER (please list)

 

What other t e of esticide (herbicide, fungicide, or
rodenticideI EaVEIyOU used in the greatest quantity in the
past two years? (list one)

 

A. What was the formulation of the pesticide listed in
question 6? .(check one)

 

(28)l.‘_____oRANULAR 4. _____0THER (please specify)
2. ___POWDERED * '
3. ___110010 ' 5. ____DON'T KNOW

B. How was this pesticide applied? (check one)

(29-30) .
l. ___FIXED WING AIRCRAFT 7. ______FOGGER
2. ___BOOM SPRAYER 8. ____DUSTER
3. ____HYDRAULIC SPRAYER 9. _____CRANUL£ SPREADER
4. ____AIR BLAST SPRAYER lo. _____SOIL INJECTOR
5. _____LOW VOLUME AIR SPRAYER II._____HAND EQUIPMENT
6. __ULTRA-LOW VOLUME SPRAYER l2. ____OTHER (please list)

 

11E3

SECTION B: PESTICIDES AND CLOTHING

0-7.
(31)

325

Q-lO.

(34)

Which brand of insecticide most frequently gets on your

clothes? (PLEASE ANSWER QUESTIONS 9 THROUGH 15 IN TERMS
OF THIS INSECTICIDE)

 

O. INSECTICIDE NEVER GETS ON CLOTHES

What other type of pesticide (herbicide, fungicide, or
rodenticide) most frequently gets on your clothes?

(IF YOU NEVER GET INSECTICIDE ON YOUR CLOTHES, PLEASE
ANSWER QUESTIONS 9 THROUGH 15 IN TERMS OF THIS OTHER
TYPE OF PESTICIDE)

 

O. OTHER PESTICIDES NEVER GET ON CLOTHES

 

00 T0 QUESTION 9 IF INSECTICIDE GETS ON CLOTHES:

GO TO QUESTION 16 IF NEITHER INSECTICIDE NOR OTHER
PESTICIDES GET ON CLOTHES.

 

How often would you say pesticide gets on your clothes?
(check one)

1. SELDOM (about once per application season)
2. SOMETIMES (two or three times per application
season)

3. USUALLY (about once a week during application
season)

4. ALWAYS (nearly every day)
5. DON'T KNOW

When pesticide gets on your clothes, how often does it get
through the clothing to the skin? (check one)

I. NEVER .
2. SELDOM (about once per application season)
3. SOMETIMES (two or three times per application
season)
4. USUALLY (about once a week during application
season)
5. ALWAYS (nearly every day)

6. DON'T KNOW

11$?

Q-ll. What clothing do you usually wear when applying pesticide?
Check all that apply in each category of clothing (A—F)

listed below.

A. WORK OR SPORT SHIRTS
(35-38)

1. __ LONG SLEEVES

2. ______SHORT SLEEVES

3. ______SLEEVELESS

4. DO NOT USUALLY WEAR

C. WORK SHOES/BOOTS

 

 

(44-47)

1. WATERPROOF VINYL/
RUBBER?

2. LEATHER

3. CANVAS

4. OTHER (describe)

E. HATS

(53-58)

1. HARD PLASTIC

2. FELT

3. __ STRAW

4. COMPANY/BASEBALL

5. OTHER (describe)

6. DO NOT USUALLY WEAR

 

 

B.Pmns
(39-43)
1. COVERALLS WITH
- LONG SLEEVES
2. BIB OVERALLS
3. JEANS 0R WORK PANTS
a. SWEAT PANTS
5. SHORTS. CUTOPPS
D. GLOVES
(48-52)
1. WATERPROOF VINYL/
RUBBER
2. LEATHER
3. CANVAS
4. ______0THER (describe)
5. ‘ DO NOT USUALLY WEAR
P. OTHER CLOTHES
(59-68)
1. JACKET 0R COAT
2. SWEATSHIRT
3. SLEEVELESS VEST
4. 'UNUERSHIRT
5. JOCKEY/BOXER SHORTS
6. SOCKS
7. BELT
8. WATERPROOF JACKET
9. UATERPROOE PANTS

10. OTHER (describe)

 

12C)

Q—lZ. 'When pesticide comes in contact with your clothes, is it
usually (check one)

 

 

 

(69-70)
1. __ GRANULAR
2. __ POWDERED
3. _____ LIQUID 1} 12a. Is the concentration
4. ______OTHER (explain) usually (check one)
1. __ DILUTED To PIELO
5. __ DON'T KNOW CONCENTRATION
2. __ PULL STRENGTH
3. _____ OTHER (explain)
4. DON'T KNOW

 

Q-l3. Do you usually wear clothes soiled with pesticide again

before they are laundered? (check one)
(71-74)

1. YES (give average number of days of wearing)

days
2. NO

 

Q-l4. If you are not wearing waterproof clothing and you spill
the full strength liquid concentrate of pesticide on your

clothes, do you usually change them immediately (within an
hour)? (check one)

 

 

 

(75 76)1. __ NOT APPLICABL-J - >{GQ TO _QUESTIQN_'1_§_]
2. __ YES J
3. _____ NO >= 14a. How soon do you change
clothes? (check one)
1. ____1To 3 HOURS
2. _____ 4 TO 6 HOURS
3. _____ 7 OR MORE HOURS

Q-lS. If you are not wearing waterproof clothing and your clothes
become saturated with spray during application of pesticide

do you usually change them immediately (within an hour)?
(check one)

(77-78)

 

 

1. NOT APPLICABLE1 >{G0 To QUESTION 16]
2. ““ J

NO

 

> 15a. How soon do you change
clothes? (check one)

1. 1 TO 3 HOURS
2. 4 TO 6 HOURS
3. 7 OR MORE HOURS

121

(1'5. 6,2)
Q-l6. Where do you usually store clothing worn for pesticide

application before it is washed? (check one answer for
each type of clothing)

(7-9)
Separate from
With other other family
family laundry laundry
a. shirts, jean, workpants ... l. 2.
b. underwear ................. l. 2.
c. jackets, coveralls......... l. 2.

Q-l7. Where do you usually store other items worn for pesticide

application until next use? (check one answer for each
type of item).

(IO-l3) Separate from
With other other family
family clothing clothing

a. boots, shoes ........... 1. 2.
b. hats, caps ............. l. 2.
c. gloves ................. l. 2.
do belts ......OOOIOOOOOOOO l. 2.

Q-18. How effective do you feel the clothes you usually wear are
in protecting you from pesticide exposure? (circle one)

(14)
VERY VERY
EFFECTIVE INEFPECTIVE
l 2 3 4 5 6 7

SECTION C: PESTICIDES AND HEALTH

Q-19. How likely is it that getting pesticides on your skin will
cause an immediate health risk? (circle one)

(15)
VERY VERY
LIKELY UNLIKELY
l 2 3 4 S 6 7

 

Wu. -9 .1m

Q-ZO. How serious do you think that immediate health risk is apt
to be? (circle one)
(16)

VERY VERY
SERIOUS MILD

l 2 3 4 5 6 7

1223

Q-Zl. 'How likely is it that getting pesticides on your skin will
cause long-term harm? (circle one)

(17)
VERY VERY
LIKELY UNLIKELY
1 2 3 a 5 6 7

EM TG'JUL 1 E‘s_T"I.£1‘U'__Z3Z]

Q-ZZ. How serious do you think that long-term harm is apt to he?
(circle one)

(18)
VERY VERY
SERIOUS MILD
1 2 3 a 5 6 7

Q-23. With over-exposure to some pesticides there is danger of
poisoning. After working with pesticides how often would

you say you have experienced the following? (circle one
answer for each item)

ALWAYS USUALLY SOMETIMES _SELDOH NEVER
(19-36)

UNUSUAL TIREUNESS......
HEADACHE...............
DIZZINESS..............
EYE IRRITATION.........
BLURREB VISION.........
NOSE BLEEDS............
NAUSEA.................
V0HITING...............
STOMACH CRAMPS.........
DIARRHEA...............
WEAKNESS...............
CHEST DISCOMFORT.......
DIFFICULTY BREATHING...
MUSCLE TWITCHES........
SKIN IRRITATION........
FAST HEART RATE........
EXCESS SWEATING........
PEVER..................

H—I-OO-‘HHr-‘HO-‘D-‘Hl-‘HFF‘l-‘v-‘F‘
NNNNNNNNNNNNNNNNNN
wwuwuuwuuwuwwwwwuu
bébb§§b駧§bbbbbfib

MU‘MU‘U‘U‘U’U‘U‘UU‘U‘MU‘MMUW

Q-24.

(37-47)

Q-ZS.

(48)

Q-26.

(49)

1223

Have you stopped using any pesticide because of health
related problems? (check one)

1. YES -—524a. If yes, please list the pesticide
and the related problem.

Pesticide Health Problem

 

 

 

 

 

 

Overall, for you personally, how would you rate the health
risk associated with pesticide application? (circle one)

VERY HIGH VERY LOW
I 2 3 4 5 6 7

Overall, for you personally, how would you rate the crop
yield benefit associated with pesticide application?
(circle one)

VERY HIGH VERY LOW
l 2 3 4 5 6 7

SECTION B: OPINIONS ABOUT PESTICIDES. We would like to.ask you

0-27.

(50)

0-28.

(51)

0-29.

(52)

0-30.

(53)

0-31.

(54)

for your opinions concerning use of pesticides. Do
you STRONGLY AGREE (SA), AGREE (A), ARE NOT SURE (NS),
DISAGREE (D), or STRONGLY DISAGREE (SD) with.the
following statements. Circle one answer for each

statement. a A fl Q 52

Clothes keep pesticide off 1 2 3 4 5
the skin.

Pesticides differ in their l 2 3 4 5
level of toxicity-some are

very dangerous and others

are not.

Most people are tough l 2 3 4 5
enough to take exposure
to pesticides without harm.

Peeple really can't avoid l 2 3 4 5
getting pesticide on their
clothes if they farm nowadays.

Insecticide should be used l 2 3 4 5
only when monitoring of the
insects indicates it is needed.

124-

53 A B: 2 s_0.
0-32. People should never go into 1 2 3 4 S
(55) the house wearing clothes

that have pesticide on them.
0-33. Pesticides are not harmful l 2 3 4 S
(56) if they are handled properly.
0-34. There are lots of things 1 2 3 4 S

(57) on the farm that are far
more dangerous than pesticide.

Q-35. The benefits of pesticides l 2 3 4 5
(58) far exceed whatever risks
may be involved.

0—36. The risk involved in getting l 2 3 4 5
(59) pesticide on clothes 5

nothing compared to breathing

pollution in the air.

0-37. It is better to pay someone l 2 3 4 5

(60) else to apply pesticide and
avoid the health risk.

Q-38. Risks are just part of the l 2 3 4 5
(61) ~job in pesticide application.

SECTION E: This section contains some questions we need to ask
about you and others who live in your household.
This information will be kept confidential, but will

be helpful to us in interpreting the information you
have already provided.

0-39. Please list everyone living in your household, starting
with yourself, and indicate age and sex for each.

(62-89)
PERSONS IN HOUSEHOLD AGE Circle one:
(myself, spouse, son, daughter, etc.) M=male
F=female
M

 

 

 

 

 

 

 

3333332
‘ri-n-nnn-n-nfl-n

 

1255

0-40. How many years of schooling have you completed? (check one)
(7)
. LESS THAN 8 GRADES

l

2. ___~*S GRADES 0F ELEMENTARY SCHOOL

3. _____l-3 YRS. OF HIGH SCHOOL

4.______COMPLETED HIGH SCHOOL

5. _____COMPLETED JR. COLLEGE, TRADE OR VOCATIONAL SCHOOL
(2 yr. program)

6. ______l-3 YRS. COLLEGE

7.______COMPLETED COLLEGE (4 yr. degree)

8.______GRADUATE DEGREE 0R PROFESSIONAL DEGREE

9. _____OTHER (please explain)

 

Q-4l. About how many acres of land do you farm? (check one)

(8)

1. 10-200 4. _ 601-800 '
2. 201-400 5. 801-1000 .
3. 401-600 6. lOOl or more

Q-42. Which of the following categories best describes your total
family income before taxes during 1983? (check one)

(9 10) l.______less than $5000 7.______$40,000 to $49,999
2.______$5000 to $9.999 8. _____$S0,000 to $59,999
3.__;;__s10,000 to $14,999 9. _____$60,000 to $59,999
4.______s15,000 to $19,999 1o.._____$70,000 to $79,999
5. _____$20,000 to $29,999 11. _____$80,000 to $89,999
6. _____$30,000 to $39,999 12. _____§90,000 or more

Thank you very much for providing information on pesticide application
and clothing practices. If there is any additional information that
you feel would be helpful to us, please add it below.

APPENDIX B

LETTER TO PARTICIPANTS FROM PROJECT DIRECTOR

126
MICHIGAN STATE UNIVERSITY

 

COLLEGE OF HUMAN ECOLOGY EAST LANSING ° MICHIGAN ' 48824
DEPARTMENT OF HUMAN ENVIRONMENT AND DESIGN

March l2, l984

Dear Friends,

Several weeks ago I wrote to you seeking information on the
use and care of clothing worn when applying pesticides. As
of today We have not received your completed questionnaire.

At present, information about the relationship between clothing

and pesticide exposure is limited. Responses to our research

will be used to direct laboratory studies to determine more

effective cleaning methods for clothing worn-when applying pesticides.

I am writing to you again because of the significance each
questionnaire has to the usefulness of the study. -Your name was
drawn through a scientific samplying process that produces a small
but representative sample of Michigan applicators. In order for

the results of this study to be truly representative of the respOnses
of Michigan applicators, it is essential that each household in the
sample return their questionnaire. As mentioned in our first letter
the questionnaire has two parts. The first part should be completed
by the adult in the family who uses pesticides most frequently, the
second part should be completed by the adult who is usually responsible
for the laundry.

We are looking forward to receiving your completed questionnaire. In
the event your questionnaire has been misplaced, please check the
appropriate box on the enclosed postcard. If you are not eligible to
participate because you are retired or hire a commercial applicator

we would appreciate your indication of this on the postcard. No postage
is necessary for the postcard. Just drop it in the mail.

Your cooperation is greatly appreciated. Thank you.

Sincerely.

Ann C. Slocum
Project Director

ACS/lcs

MS U it an Affirmative Action/Equal Opportunity Institution

APPENDIX C

RESPONDENT'S RETURN POSTCARD

I.

127

 

 

We haVe misplaced our copy of the
questionnaire. Please send another copy.

We hire commercial applicators to apply
our pesticides.

DUE] 1:1

We do not use pesticides in our farmino
operations.

We are retired and no longer apply pesticides.

 

 

7l—6552 |||||l

 

 

BUSINESS REPLY MAIL

NO" cuts "an" no," I“! uusmcmu.

 

 

POSTAGE Will BE PAID BY AOONISSH

'Ann C. Slocum

214 Human Ecology
Michigan State University
East Lansing, MI 48824

 

N0 POSTAG!
NICISSAIY
IF MARIO

IN TH!

UNITED STATES

 

 

 

 

 

 

APPENDIX D

PROTECTIVE CLOTHING INDEX

Appendix D - Protective Clothing Index

128

 

Area Thickness Range
Undershirt
not worn O O
worn 1 1 0-2
Shirt
not worn O O
sleeveless/short
sleeve 1 1
long sleeve 2 1 0-3
Coveralls
not worn O O
worn 2 1 0-3
Jacket
not worn O O
worn-not waterproof 2 2
worn-waterproof 2 u 0-6
Vest
not worn O O
worn 1 2 0-3
Undershorts
not worn O O
worn 1 1 0—2
Pants
cutoffs 1 1
long-not waterproof 2 1 2—3
Waterproof pants
not worn O O
worn 2 4 0-6
Hats
not worn O O
worn-not waterproof 1 1
worn-waterproof 1 3 O-u
Shoes
canvas 1 1
leather 1 2
waterproof 1 3 2-4
Socks
not worn O O
worn 1 1 0—2
Gloves
not worn O O
worn—not waterproof 1 1
worn—waterproof 1 3 0-4
Special Protective Clothing
not worn O O
worn 1 1 0—2
Possible Range hJHM

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