i ADVERSE HEALTH EXPERIENCES, RISK PERCEPTION AND PESTICIDE USE BEHAVIOR BY MUHAMMAD KHAN A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY IN ECONOMICS 2012 FUUAST School of Economics Sciences Federal Urdu University of Arts, Science & Technology (FUUAST) Islamabad.
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i
ADVERSE HEALTH EXPERIENCES, RISK PERCEPTION AND PESTICIDE USE BEHAVIOR
BY
MUHAMMAD KHAN
A Thesis Submitted in Partial Fulfillment of the Requirements for the
Degree of DOCTOR OF PHILOSOPHY IN ECONOMICS
2012
FUUAST School of Economics Sciences Federal Urdu University of Arts, Science & Technology (FUUAST)
Islamabad.
ii
TO
MY PARENTS
BROTHERS AND
SISTERS
iii
ACKNOWLEDGEMENTS
Several individuals deserve acknowledgement for their contributions in one way or another during this study. My sincere and deepest appreciation goes to my supervisor Professor Dr. Rehana Siddiqui for her close supervision and professional advice throughout the course of research work. I know I was the source of much headache for her but no option. I especially thank her for taking time to read my work in her extremely busy schedule. I am also grateful for all that I have learned from her.
Second among this list is Prof. Dr. Nawab Haider Naqvi, Distinguish Professor of Economics and Director General of this University. Without his vision, support and passion to develop research in this university, we could not have come so far. He is the only source of hope in our most difficult times in this university. In a very personal way providing us with support and solution, he has managed to keep track of our studies. His invaluable services for the department, particularly for students are very much appreciated.
My special thanks are given to Dr. Abdul Salam and Dr. Muhammad Iqbal for their review and valuable comments on earlier drafts of the thesis. My appreciation goes to my teachers Dr. Adiqa Kiani, Dr Aitzaz Ahmed, Dr.Abdul quyyam, Dr. Imtiaz Ahmed, Dr. Waseem Shahid Malik, Saeed ahmed sheikh and Dr Seeme Malik.
I am indebted to my friend Iftikhar ul Husnain for his contribution which extends to several fronts. My thanks also go to all my classmates, particularly Zafar ul Husnain, Naeem Akram, Ihtasham ul Haq Padda and Saima Akhter Qureshi for their co-operation during the course of my study. I would like to acknowledge the support provided by Dilshad Ahmad, Kashif Bhatti and field enumerators during the fieldwork. My brother Kashif Mehmood assisted me in entering part of the data into computer who also deserves special commendation.
To get this goal, many people have made sacrifices for me, but my family members have borne a great deal. I want to thank most sincerely to my father. Absolutely words can’t express my gratitude to him. Without h is keenness and encouragement I might have not done this work. Thanks for insisting and pushing me forward. I know he will be the happiest person once this thesis is over. I am very grateful to my mother who raised me and instilled values in me. I count myself blessed to have mother like her. Thanks for countless prayers.
My heart-felt thanks go to my sisters Saima and Shumaila who made my life easier. I acknowledge the concerns and encouragement of my brothers also. I extend my deepest sense of gratitude to my grandmother and my aunts for their prayers, best wishes and moral support.
Finally, I thankfully acknowledge that this work would not have been possible without the financial support of the Higher Education Commission (HEC) Pakistan. Muhammad Khan
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Contents
ACKNOWLEDGEMENTS III
ABSTRACT XII
CHAPTER 1: INTRODUCTION 1
1.1 BACKGROUND AND MOTIVATION 1
1.2 STATEMENT OF THE STUDY PROBLEM 4
1.3 OBJECTIVE OF THE STUDY 7
1.4 CONTRIBUTION AND SIGNIFICANCE OF THE RESEARCH 7
1.5 SCOPE AND ORGANIZATION OF THE STUDY 10
CHAPTER 2: REVIEW OF LITERATURE 12
2.1 PESTICIDE USE AND HEALTH IMPACTS 12
2.2 PESTICIDE USE AND THE ENVIRONMENT 18
2.3 ECONOMICS OF PESTICIDE USE 20
2.3.1 PESTICIDE USE AND HEALTH COST 20 2.3.2 PESTICIDE USE AND NATURAL BIOLOGICAL RESOURCE DEGRADATION 21 2.3.2.1 BIODIVERSITY (RENEWABLE BIOLOGICAL CAPITAL RESOURCES) 21 2.3.2.2 PEST SUSCEPTIBILITY (NON-RENEWABLE BIOLOGICAL CAPITAL RESOURCES) 22
2.4 PSYCHOLOGY AND ECONOMICS 23
2.4.1 THE LINK BETWEEN PSYCHOLOGY AND ECONOMICS 23 2.4.2 USE OF PSYCHOLOGY IN ECONOMICS 25 2.4.2.1 THEORY OF REASONED ACTION(TRA) AND THEORY OF PLANNED BEHAVIOR (TPB) 26 2.4.2.2SOCIAL-COGNITIVE THEORY 27 2.4.2.3 THE COMMON SENSE MODEL 28 2.4.2.4 HEALTH BELIEF MODEL 29
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2.5 ECONOMIC COST OF PESTICIDE USE 34
2.6 THE CONTINGENT VALUATION METHOD 36
2.6.1 ECONOMIC EVALUATION OF HEALTH COST USING WTP 37
2.7 PESTICIDE USE BEHAVIOR 40
2.8 INTEGRATED PEST MANAGEMENT 50
2.9 SUMMARY 53
CHAPTER 3: CROP SECTOR IN PAKISTAN: MAJOR CROPS AND PESTICIDE USE 55
3.1 SIGNIFICANCE OF AGRICULTURE SECTOR IN THE ECONOMY 55
3.2 SELECTED MAJOR CROPS AND CHARACTERISTICS OF AGRICULTURAL PRODUCTION 56
3.3 PESTICIDE USE AND PRODUCTION OF MAJOR CROPS 60
3.3.1 THE PATH DEPENDENCE (PESTICIDE TREADMILL) 62
3.4 MANAGEMENT OF PESTICIDE USE AND INTEGRATED PEST MANAGEMENT 64
3.4.1 IPM STATUS IN PAKISTAN 64
3.5 AGRICULTURAL EXTENSION 65
3.6 SUMMARY 68
CHAPTER 4: STUDY AREA, SURVEY DESIGN AND DATA COLLECTION 70
4.1 SELECTION OF STUDY AREA 70
4.2 DEVELOPMENT OF SURVEY QUESTIONNAIRE 72
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4.3 DATA METHODOLOGY 73
4.3.1 FIELD SURVEY 75 4.3.2 SAMPLE SIZE 76
4.4 VALIDITY AND RELIABILITY ANALYSIS 76
4.4.1 RELIABILITY ANALYSIS 78 4.4.2 VALIDITY TESTS OF CVM 80
4.5 SUMMARY 82
CHAPTER 5: SURVEY RESULTS 84
5.1 BACKGROUND INFORMATION 84
5.1.1 AGE AND EDUCATION OF THE FARMERS 84 5.1.2 HOUSEHOLD CHARACTERISTICS 85 5.1.3 LAND OWNERSHIP AND FARM CHARACTERISTICS 85
5.2 PESTICIDE SAFETY KNOWLEDGE, INFORMATION SOURCE AND AVERTING BEHAVIOR 86
5.2.1 SOURCES OF INFORMATION ABOUT SAFETY PRACTICES 86 5.2.2 PESTICIDE SAFETY KNOWLEDGE AND AVERTING PRACTICES 87 5.2.3 RISK PERCEPTION 89 5.2.4 PESTICIDE PRACTICES AND USE OF PROTECTIVE MEASURES 91
5.3 CROP PROTECTION METHODS AND PESTICIDE APPLICATION 93
5.3.1 CROP PROTECTION METHODS IN STUDY AREA 93 5.3.2 PESTICIDE SPRAY FREQUENCY 94 5.3.3 USE OF PESTICIDE BY TOXICITY CLASSIFICATION 95
5.4 HEALTH AND ENVIRONMENTAL IMPACTS OF PESTICIDE USE 97
5.4.1 HEALTH EFFECTS OF PESTICIDE USE 97 5.4.2 IMPACT OF PESTICIDE USE ON THE ENVIRONMENT 100
5.5 WILLINGNESS TO PAY FOR SAFER PESTICIDE 100
5.6 SUMMARY 103
CHAPTER 6: THE CONCEPTUAL FRAMEWORK 106
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6.1 HEALTH BELIEF MODEL AND PESTICIDE USE BEHAVIOR 106
6.2 HEALTH EXPERIENCE, RISK PERCEPTION AND SAFETY BEHAVIOR (MODEL 1) 108
6.2.1 EMPIRICAL MODEL 110
6.3 HEALTH EXPERIENCE, FARMERS’ ATTITUDES AND ENVIRONMENTALLY SOUND BEHAVIOR OF PESTICIDE USE (MODEL 2) 114
6.3.1 EMPIRICAL FRAMEWORK 116
6.4 FARMER’S WILLINGNESS TO PAY FOR INTEGRATED PEST MANAGEMENT (MODEL 3) 118
6.4.1 EMPIRICAL MODEL 120
6.5 SUMMARY 121
CHAPTER 7: ANALYSIS OF PESTICIDE USE BEHAVIOR 123
7.1 HEALTH EXPERIENCE AND FARMERS’ ATTITUDES 123
7.1.1 ORDERED PROBIT RESULTS FOR RISK PERCEPTION OF PESTICIDE USE 125
7.2 HEALTH EXPERIENCE, RISK PERCEPTION AND SAFETY BEHAVIOR 130
7.3 HEALTH EXPERIENCE, RISK PERCEPTION AND ENVIRONMENTALLY SOUND BEHAVIOR OF PESTICIDE USE 134
7.4 FARMER’S WILLINGNESS TO PAY FOR INTEGRATED PEST MANAGEMENT 138
7.4.1 RESULTS OF ORDERED PROBIT MODEL 139
7.5 SUMMARY 143
CHAPTER 8: CONCLUSION AND POLICY IMPLICATIONS 145
8.1 CONCLUSION 145
8.2 POLICY IMPLICATIONS 150
8.3 FUTURE RESEARCH PRIORITIES 154
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REFERENCES 156
APPENDIXES 169
APPENDIX 1: FIGURES 169
APPENDIX II: TABLES 173
APPENDIX III: PESTICIDE LEGISLATION IN PAKISTAN 185
APPENDIX IV: DISTRICTS PROFILES 189
APPENDIX V: DESCRIPTION OF VARIABLES IN EMPIRICAL MODELS 193
APPENDIX VI : SURVEY QUESTIONNAIRE 198
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List of tables
Table 3.1. Production of Selected Major Crops in Pakistan (000 tonnes) _____________________________ 56 Table 3.2. Yield of major crops in Pakistan _______________________________________________________ 61 Table 4. I. Province wise share of cotton production _______________________________________________ 70 Table 4.2.Distribution of sample population by district ____________________________________________ 76 Table 4.3. Reliability analysis Item-Total Statistics ________________________________________________ 79 Table 4.4.Validity test in the implementation of the CV ____________________________________________ 81 Table 5.1. Distribution of education attainment by age groups _____________________________________ 84 Table 5.2. Distribution of farm size by household size _____________________________________________ 85 Table 5.3.Distribution of farm size and farm ownership (%) ________________________________________ 86 Table 5.4. Farmer’s behavior about safety instruction _____________________________________________ 88 Table 5.5. Per acre use of pesticide (kg) with different level of Risk perception ________________________ 90 Table 5.6. Main reasons, for not taking protective measures (%)____________________________________ 93 Table 5.7.Total amount of pesticide applied by WHO classification__________________________________ 96 In table 5.7, the sum of the total amounts of active ingredient used under the WHO classification system is provided. Most of the pesticides (54.7%) in use are moderately hazardous (category II) . Moreover, cotton accounts more than 70% of total pesticide use in this study area (see table 5.8). _____________________ 96 Table 5.8. Use of pesticide on selected crops by WHO classification (%) ______________________________ 97 Table 5.9. Distribution of Willingness to pay responses (%)________________________________________ 101 Table 5.10. Distribution of Mean WTP by district ________________________________________________ 101 Table 5.11. Distribution of willingness to pay by farm size (%) _____________________________________ 102 Table 5.12. Distribution of WTP by risk perception (%) ____________________________________________ 102 Table 5.13. Distribution of WTP by income ______________________________________________________ 103 Table 7.1.Pearson correlation coefficients (District Lodhran) ______________________________________ 123 Table 7.2.Pearson correlation coefficients (District Vehari) _______________________________________ 124 Table 7.3. Ordered probit results for risk perception ______________________________________________ 126 Table 7.4. Predicted probabilities and marginal effects for risk perception categories ________________ 127 Table 7.5. Results of ordered probit regression for protective behavior _____________________________ 131 Table7.6. Predicted probabilities and marginal effects from the estimat ed model____________________ 132 Table7.7. Maximum likelihood estimates of Probit for the use of alternative pest management practices____________________________________________________________________________________________ 134 Table 7.8.Predicted probabilities and marginal effects from the estimated probit model ______________ 135 Table 7.9. Estimated coefficients of Ordered Probit Model for positive WTP _________________________ 139 Table 7.10. Predicted probabilities and marginal effects from the estimated model __________________ 141
List of figures
Figure 2.1. Health Belief Model _________________________________________________________________ 32 Figure 3.1. Pesticide consumption in Pakistan (mt) ________________________________________________ 60 Figure 4.1. Map of Punjab Province _____________________________________________________________ 71 Figure 5.1. Farmer’s sources of information (%) __________________________________________________ 87 Figure 5.2. Farmers perception of pesticide risk (%) _______________________________________________ 90 Figure 5.3. Use of protective equipments during spray (%) _________________________________________ 92 Figure 5.4. Mean pesticide application on different crops __________________________________________ 95 Figure 5.5. Distribution of farmers’ attitudes towards the affect of pesticide on their health ___________ 98 Figure 5.6. Distribution of health effects experienced by farmers (%) ________________________________ 99 Figure 6.1. Relationship between health experiences, risk perception and pesticide use behavior ______ 107
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List of appendix Figures
Figure 1A.Farm ownership status .............................................................................................................................169 Figure 2A. Pesticide spray frequency by district .....................................................................................................169 Figure 3A. Use of protective measures by district .................................................................................................170 Figure 4A.Farmer’s perception of pesticide risk by district (%) ............................................................................170 Figure 5A. Farmers’ attitudes towards health effects of pesticide use in Vehari .............................................171 Figure 6A. Farmers’ attitudes towards health effects of pesticide use in Lodhran ..........................................171 Figure 7A. Distribution of mean pesticide application on vegetables ...............................................................172
List of appendix Tables
Table 1A. Distribution of farm size by district ____________________________________________________ 173 Table 2A. Distribution of farm size by farm ownership in Lodhran __________________________________ 173 Table 3A. Distribution of farm size by farm ownership in Vehari ___________________________________ 173 Table 4A. Distribution of farmer’s age _________________________________________________________ 174 Table 5A.Distribution of education attainment by age in Vehari ___________________________________ 174 Table 6A.Distribution of education attainment by age in Lodhran __________________________________ 174 Table 7A.WHO Hazard Classification of pesticides _______________________________________________ 175 Table 8A. Pesticide use by WHO hazard classification by district ___________________________________ 175 Table 9A.Crop wise pesticide use by WHO hazard classification in Vehari (%) ________________________ 175 Table 10A. Crop wise pesticide use by WHO hazard classification in Lodhran (%) ____________________ 176 Table 11A.WHO Category wise pesticide use on cotton by farm size (%) ____________________________ 176 Table 12A. WHO Category wise pesticide use on wheat by farm size (%) ____________________________ 176 Table 13A.WHO Category wise Pesticide use on vegetables by farm size (%) ________________________ 177 Table 14A. WHO Category wise pesticide use on other crops by farm size (%) _______________________ 177 Table 15A.Amount of pesticide used (Kg/per acre) by farm size ____________________________________ 177 Table 16A. Distribution of income by age group _________________________________________________ 178 Table 17A.Main source of information for farmers in study area __________________________________ 178 Table 18A. Use of IPM by method ______________________________________________________________ 179 Table 19A.Percentage of farmers who follow instructions on pesticide labels by level of education ____ 179 Table 20A.Descriptive statistics of important variables (district Lodhran) ___________________________ 180 Table 21A.Descriptive statistics of important variables (district Vehari) _____________________________ 180 Table 22A: Na me of the districts and share of total area under cotton in Punjab province ____________ 181 Table 23A. List of sample villages used for survey ________________________________________________ 182 Table 24A. Area, production and per hectare yield of major cotton producing countries (2005 -2006)___ 183 Table 25A.Area, production and per hectare yield of major rice producing countries (2005 -2006)______ 183 Table 26A. Area, production and per hectare yield of major sugarcane producing countries (2005 -2006)184 Table 27A.Area, production and per hectare yield of major wheat producing countries (2005-2006) ___ 184
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List of abbreviation
APO Agricultural Pesticide Ordinance
BSCV Burewala Strain of Cotton Virus
CCRI Central Cotton Research Institute (Multan)
CSM Common Sense Model
CV Contingent Valuation
CVM Contingent Valuation Method
EU European Union
FAO Food and Agriculture Organization
FFS Farmers Field School
GDP Gross Domestic Product
GR Green Revolution
HBM Health Belief Model
IPM Integrated Pest Management
LCV Leaf Curl Virus
LD Lethal Dose 50%
LFS Labour Force Survey
NARC National Agriculture Research Center
NFDC National Fertilizer Development Center
NOAA National Oceanic and Atmospheric Administration
NPS Non Point Source
PARC Pakistan Agriculture Research Center
SCT Social Cognitive Theory
SLT Social Learning Theory
TOF Training of Facilitators
TPB Theory of Planned Behavior
TRA Theory of Reasoned Action
UN United Nations
WHO World Health Organization
WTP Willingness to Pay
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Abstract
For Pakistan’s economy, agriculture is the most important sector. It contributes about 22
percent of the gross domestic product (GDP) and employs 45 percent of the national
employed labour force. It supports directly or indirectly about 65 percent of the
population living in rural areas for their sustenance. It also contributes about 65 percent
to total export earnings derived from raw and processed agricultural commodities.
It is evident that pesticides are used for the benefits. However, use of pesticide leads to
negative externalities for the farmers and the society. Negative externalities may include
such as effects on human health, loss of bio-diversity, degradation of natural ecosystems
and irreversible changes in the environment. Various kinds of pesticides have been used
on a large scale in Pakistan since the early 1950s to protect crops from damages inflicted
by insects and diseases. After liberalization of pesticides in 1980, pesticide use increased
dramatically in Pakistan reaching 117513 metric tonnes in 2005 which was only 12530
metric tonnes in 1985. The massive increase in pesticide consumption is not translated
into productivity improvements rather accompanied by a huge cost in terms of human
health and degradation of the environment.
It is well established that the use of pesticides on the farm is largely governed by
voluntary behavior. Therefore, it is important to understand what drives farmer’s
behavior of pesticide use. Such information is critical to identify the prospects and
constraints to the adoption of alternative crop protection policy. According to
microeconomic consumer theory, individuals make choices following their preferences.
However, economic theory does not focus to the processes of individual’s reasoning
behind choices. Cognitive models in Public Health and Social Psychology argue that
persons who have had adverse health experiences are likely to undertake greater
preventive behavior. This study combines an approach from social psychology with micro
economic consumer theory to understand individual’s reasoning behind their decisions.
Further, it also examines the health implications of pesticide use as caused by behavior of
the farmers which help to inform policy makers about productivity reducing effects of
pesticide use.
A survey of 318 farmers in Vehari and Lodhran districts of Southern Punjab was drawn.
Results indicate that farmers are frequently exposed to pesticides. Over 90 percent
farmers reported at least one health problem in district Lodhran, where as in district
Vehari, almost 80 percent farmers reported the same. However, they appeared to give low
priority to health considerations and grossly under-estimating pesticide’s health risk
where almost all the farmers did not visit hospital or doctor for proper medication. This
misperception is largely translated into practical behavior where farmers were found
heavily skewed towards pesticide use for pest management and the use of protective
measures to avoid direct exposure of pesticides is not sufficient. Low level of education
combined with cultural/local beliefs regarding health effects of pesticide use is the main
xiii
reason of this comportment. Moreover, about 80% pesticides used in the study area are
highly or moderately hazardous. In terms of crops, cotton alone received over 70% of total
quantity. Similar pattern appeared in terms of toxicity, where cotton consumed over 88%
of highly hazardous and moderately hazardous pesticides. Farmers were found to be
overusing pesticides. They were also found applying pesticides very frequently. During
survey 73 percent of them reported that they applied pesticide more than 10 times on
cotton in a season. The spray frequency is as high as 16 on cotton crop in one season.
There is a dearth of formal training and information on proper use and safe handling of
pesticides. Most of the farmers did not know about IPM, hardly few of them using it
which helps them reduce dependence on pesticides.
The analysis supports the hypothesis that farmers who have had negative health
experiences related to pesticide use are more likely to have heightened risk perceptions
than farmers who have not had such problems. Education and training are also important
determinant of risk perception. Association also existed between the experience of health
problems and the use of protective measures. The results, however, do not support the
hypothesis that the farmers who have had negative health effects from pesticide use are
more likely to adopt alternative pest management practices. This however does not mean
that farmers who have had such experiences do not care about the effects of pesticide use.
The lack of information or access to alternative pest management practices is the likely
reason. The Contingent Valuation (CV) analysis shows that farmers are willing to pay
premium for safe alternatives of pesticides which support our argument.
Finally, research findings have some important implications, for example, the empirical
relation that appears to exist between training of safe handling and alternative pest
management would suggest that trained farmers significantly and effectively substitute
IPM for pesticide use. Hence, to improve awareness, necessary for better choices of
pesticide use, specific and relevant information regarding the health effects and
environmental risks of using pesticide should be provided to farmers through training
programs. For this, government should restructure current pro-pesticide extension
system and design effective outreach programs, such as farmer field schools which deal
specifically with health risk of pesticide use, averting behavior and better management of
pests. One such program (e.g. National IPM program) is already in place but with
limited coverage which needs to be strengthened and broadened through increased efforts
by government and NGOs to educate farmers which may help reduce dependency on
pesticide while at the same time maintaining or improving production. Further, policy
interventions should also include the restructuring of incentives and punishment to
reduce availability of highly toxic insecticides.
1
Chapter 1
Introduction
1.1 Background and motivation
The synthetic pesticides are an integral part of present day farming. Indeed, they
have significant contribution in the improvement of crop yield by killing pest which may
otherwise inflict huge damage to crops and in some cases destroy whole crops. It is said
that without pesticide use1, the level of yields and safety of today's crops could not be
possible (Rola and Pingali, 1993). However, on the other hand, this role of pesticide is
accompanied by disutility in the form of health impairment and environmental damage.
The increasing use of pesticide is held responsible for millions of poisoning in the
world. World Health Organization‘s estimates show that pesticide use causes 30, 00,000
cases of poisoning and 20,000 deaths annually across the globe. The majority of these
cases are reported from developing countries (WHO, 1990). Studies have also
documented the health effects of pesticide use e.g. cancer, kidney, lung, liver damage,
neurological and developmental disorder in children that may be the direct result of
either acute or chronic effect of pesticide exposure (Pimentel et al, 1996). In addition,
renal toxicity, reproductive problems and dermatomes have been found associated with
chemical pesticides. It has also been identified that pesticides are associated with
1Any substance (usually chemical) or mixture of substances intended to destroy, control or prevent any
pest (including vectors of̀ human and animal diseases, unwanted species of animals and plants) causing
harm or interfering with the production, processing, transport or storage of food and agricultural
lymphoma’ ( People & the Planet, 2007; Thomas, 1989).
5 Chronic health problems may include birth defects, neurological disorders, cancers, infertility and other
reproductive disorders (WHO, 1990). 6 In addition, studies have found that pesticide exposures to mothers, fathers, or both leads to increased
risks of preterm birth and fetal growth retardation.
14
with synthetic pesticide may have increased risk of losing an unborn baby to birth
defects. They are also identified to be associated with infertility in agricultural farm
workers who had been exposed to the pesticide (Potashnik, 1987; Schafer, 1968).
Because of direct exposure of pesticide or pesticide residues in the environment, sterility
is found in humans, generally in males. A study found that the young males in the lower
Columbia River and males in Florida's Lake Apopka have lesser reproductive organs
than the males in regions of their respective habitats that are not contaminated with
pesticides (Colborn et al, 1996).
It has also been found that agricultural workers in developing countries are at the
top of pesticide poisonings risk resultant from the unsafe practices. Research highlights
that although develop countries use more than 2/3 of total pesticide produced in the
world but the number of fatalities occur in these countries are less than half of all
pesticide- induced deaths (Pimentel et al, 1996). But the scenario is very different in
developing countries, where the share of pesticide poisonings and resultant deaths are
very high. World Health Organization‘s estimates show that pesticide use causes 30,
00,000 cases of poisoning and 20,000 deaths annually7 across the globe. The majority of
these cases are reported from developing countries (WHO, 1990). The latest studies
report pesticide associated fatalities as high as fifteen times higher8 than WHO
estimates.
7 The United Nations (UN) has estimated that about 2 million poisonings and 10,000 deaths occur each
year from pesticide and most of these occurring in developing countries (Quijano R, 1993).
In the United States, an estimated 67,000 pesticide associated poisonings and twenty-seven accidental
fatalities are reported every year (Pimentel et al, 1996). 8 Latest studies showed that the actual deaths may be around 300 000 every year (Eddleston, 2000; Rao,
2005).
15
Research has concluded that most of the pesticide related health and
environmental problems are occurring due to lack of knowledge and awareness,
misperception of hazard, insecure attitudes and unsafe practices (Dasgupta, 2005a).
Incorrect believes about pesticide hazard; scarce occupational safety standards,
protective and caring facilities; unsatisfactory enforcement; poor labeling of pesticide;
low level of education or illiteracy; and inadequate knowledge of pesticide hazards
(Pimentel et al, 1996). Evidence in different geographical settings suggests that farmers
use more toxic pesticides because they kill insects quickly (Dasgupta, 2005a).
According to WHO (1990) the pesticides, banned in developed countries, are still
extensively produced in developed nations for export to developing countries. The
farmers of less developed countries are using these pesticides on large scale,
deteriorating the already serious health and environmental problems in these countries
where many products of the WHO category I and II are still used at large scale. The
studies also revealed that farmers in developing countries are not expert in dealing with
pesticide. The expertise at their disposal for pesticide handling is often unsuitable:
sprayers are usually defective, defensive equipments9 are either lacking or unsuitable to
use, and first-aid provisions are largely missing. The studies found that lack of
information, knowledge and awareness are the chief contributing factors of pesticide
intoxication and dangerous work practices in developing countries (Forget, 1991). The
lack of information, knowledge and awareness in turn leads to misperception about
pesticide and pesticide poisoning and ultimately unsafe behavior that largely reduces the
9 Despite the much potential for pesticide exposure, workers who apply pesticide in the field often do not
use proper safety equipment, even when safety equipments are available. Further, many applicators do
not receive training of safe pesticide handling (Natural Resources Defense Council, 1998; Buckley, 2004).
16
ability of farmers and pesticide applicators to protect themselves aga inst pesticide
hazards (Ibitayo, 2006).
In Brazil, Recena (2006) found that pesticide associated poisoning rate was very
high among male farmer between the age periods of 15 to 49 years and insecticides were
main cause factor. Similarly Wim Hoek (2005) studied acute effects of pesticide
exposure in Sri Lanka. He compared different socio-demographic characteristics such as
age and education and adverse life events in cases and control group. He found that most
of the cases (84%) were because of deliberate self-poisoning. He reported that they had
lower educational level and were more probably unemployed. Study found that
individual‘s past experience of pesticide poisoning, mental disorder and heavy
dependence on alcohol were the main risk factors. Similar to intentional poisoning in Sri
Lanka, Srinivas Rao (2005) investigated the pesticide poisoning in Warangal district in
Andhra Pradesh, Southern India. The result shows that overall case fatality ratio was
more in India than found in Sri Lanka. Men and women ratio was (57%, 43%)
respectively with all pesticide types. A study carried out by Nhachi, Loewenson (1993)
in Zimbabwe‘s commercial farming sector shows that about 50% of workers on the
farms were exposed to organophosphates during spraying which is categorized as
extremely hazardous and is banned in developed countries. Adding literature on
pesticide related illness; Calvert (2008) studied pesticide-related acute occupational
poisonings among youths in United States and found that insecticides were involved for
nearly all of these illnesses (68%). However, he reported that the majority of poisonings
were of minor severity (79%). Similarly, Meulenbeit (1997) described a prospective
study which aims to determine the extent and severity of acute pesticide poisoning and
17
identifying working conditions that lead to these poisonings in Netherland. He found a
direct relation between exposure to pesticide and acute health problems in 37 out of 54
pesticide poisoning events. He found that in 67% of the cases, pesticide exposures took
place during mixing and other preparatory activities; repair of application equipment
(14%) and during re-entry (14%). In most accidents (74%) technical defects were
identified as major risk factors for exposure. Interestingly most of the workers had good
knowledge regarding pesticide poisonings and were aware of the risk of using pesticide,
but they were still careless in taking adequate protective measures, especially during
preparatory and reparation activities. Continuing with the literature on pesticide related
injuries Garry (2002) identified pesticide poisoning‘s related birth defects. Data of the
536 pesticide applicators with children was collected. It was found that children of
pesticide applicators had confirmed three times higher birth defects than the national
average. Some other side effects are also identified in health literature.
Adding up literature on pesticide health effects Ngatia (1980) noted statistically
significant reduction of plasma cholinesterase enzyme in employees who handled a
variety of chemical pesticide. Crossley (1999) in a case study of a farmer/commercial
applicator identified the relationship between occupational pesticide exposure and
neuropsychological brain functions. This case study suggests that specified brain
functions may be depressed during occupational exposures to pesticide and high levels
of work-related stress and fatigue. Dasgupta (2005b) assessed the main factors of
pesticide associated poisoning in Vietnam. Data from 482 farmers participating in both
survey and clinical tests were collected and analysed. Reported results of blood
cholinesterase tests suggest that the incidence of poisoning from exposure to
18
organophosphates and carbonates pesticide is quite high in Vietnam. However, the
farmers who usually use protective measures showed lower incidence of pesticide
poisoning. Maramba (1988) reported similar results. The comparison of medical tests of
farmers who usually take protective clothing while handling pesticides and farmers who
undertake pesticide operations without safety measures shows that hemoglobin levels
are significantly higher for farmers who usually take protective clothing while handling
pesticides than those who miss safety measures.
2.2 Pesticide use and the environment
There are also growing concerns about the consequences of pesticide use on the
environment. In addition to negative human health implications, the pesticides are also
responsible for the damage of environment. The pesticide use has caused domestic
animal poisonings, the death of useful predators and parasites, residues in air, fishery
and aquatic bodies‘ losses, the damage of flora and fauna, unintentional crop exposures,
death of birds and honeybees and undesirable residue in food items have all credited to
pesticides (Pimentel et al, 1992). It has been recognized that the chemical pesticide
residues are the key contributor to the destruction threats fac ing many endangered
species. Smith reported that U.S Government listed 663 threatened and endangered
species in 1995, of which 165 were linked to herbicides and other pesticides (Smith). In
addition, populations of honeybees10 which are necessary for pollinating many crops
have shrunk sharply and pesticide use is the primary suspect behind this aberrations.
10
The research shows that number of honeybee colonies in U.S. farmlands dropped from 4.4 million in
1985 to < 1.9 million in 1997 due to direct and indirect effects of pesticides (Horrigan, 2002 ). Exposures
to pesticides weaken honeybees’ immune system which makes them more vulnerable to natural enemies.
Pesticides also disrupt their reproduction system and development (Horrigan, 2002).
19
Pollution sources are usually classified as Point11 and Non-point.12 The NPS has
contributed to create deed zones in rivers and oceans, endangering the world‘s most
valuable stores of freshwater13 and survival of aquatic life (Woodwell et al, 2001). Fiore
et al (1986) in a study of women who had constantly taken groundwater for drinking
purpose and digested low level pollution reported confirmation of considerably reduced
immune response. In Japan, Sudo (2002) studied pesticide associated water pollution in
Lake Biwa. He measured the amount pesticides in the water at entering level and when it
crossing the boundary of Lake. The result indicated that although amount of pesticides
generally decreased in the water but does not totally eliminated which calls for serious
attention by the authorities. Similarly, Ntow (2005) in his paper highlighted the study on
Volta Lake in Ghana. The study tested pesticide residues in surface water and sediments
and found that pesticide residues are present in the water without any significant
contamination. Result tends to be different by region. Novak (1998) examined pesticide
concentration in the shallow groundwater of an eastern coastal plain watershed in U.S.
The study found that the nearly all (91%) of the wells had no detections for 11
compounds commonly used in the watershed.
11
Pollution originating from a single source, such as a discharge pipe from a factory or sewage plant, is
known as Point Source Pollution. 12
Pollution which does not originate from a single source, or point, is known as Non-point Source
Pollution (NPS). NPS pollution arises from many everyday activities that take place in residential,
commercia, and rural areas. Non Point Source (NPS) pollution is caused by rainfall or snowmelt moving
over and through the ground. As the runoff moves, it picks up and carries away pollutants into lakes,
rivers, wetlands, coastal waters, and even underground sources of drinking water. 13
The U.S. Geological Survey Pesticide National Synthesis Project tests surface water, ground water, and
sediments for 76 pesticide and seven pesticide breakdown products all over the country. The survey
reported that 90% of streams and 50% of wells had positive tests for at least one pesticide.
20
2.3 Economics of pesticide use
2.3.1 Pesticide use and health cost
Pesticide is the most familiar way to control pests. It helps farmers to kill pests
that would otherwise reduce the yield obtained from fields. This role of pesticide, on the
other hand is accompanied by disutility in the form of health impairment. A farmer,
who wants to maximize utility, faces two opposite forces, a positive income effect (in
terms of increased production) which requires higher use of pesticide and a negative
health effect which requires the use of less pesticide. In the beginning, the use of
pesticide may improve welfare of farm household through better crop productivity and
more profits. The farmers may continue using more chemical inputs to enhance farm
production up to certain maximum level but since pesticide is by nature a poison, the
further increase in pesticide use leads to serious health effects to farmer. The negative
health effects of pesticide use have serious implication14 on farm production. It is due to
the reason that labour is the central input in crop production and in less developed
countries farms and farm workers are highly interdependent (Ajayi, 2000; Archibald,
1988). In addition to short term health effects, there is now growing evidence of chronic
effects of pesticide use which indeed impose potential negative effects on farm
production in future. Given that agriculture labor is the central input in crop production
particularly in less developed countries, the use of pesticide therefore lowers potential
output not only in short run but also in the long run (Campbell, 1976).
14
The negative implication may manifest in a lower level of farm production (e.g. through a reduction in
the number of farm labour that are available to work at farm). It may also lead to decrease farm income
for the agricultural household (e.g. through a reduction in the farm output). Another negative effect is that
it may lead to a reduction in the amount of leisure time available for the household (through a reduction
in the leisure time available for sick worker or more stress of work for the healthy members o f farm
household who have to work more and harder to fill in for sick members).
21
2.3.2 Pesticide use and natural biological resource degradation
In addition to direct cost of pesticide use e.g. monetary cost of controlling pest
and taking protective measures, pesticide use also accompanies two types of indirect
cost also. The first is the health cost which is discussed above and the second is the
natural resource cost. Natural resource cost refers to the depletion of the natural
biological resources which maintain a natural regulatory mechanism in the ecosystem.
The biological resources exist in two major forms — renewable and non-renewable
resources (Ajayi, 2000). In the following sections, information regarding both types of
resources is discussed.
2.3.2.1 Biodiversity (renewable biological capital resources)
―Nature is comprised of biological diversity. Soil is one of the most diverse
habitats on earth. It contains one of the most diverse assemblages of living organisms –
bacteria, protozoa, fungi and invertebrate animals‖15 which serve to maintain
productivity of agro ecosystems by keeping the population of pests and predators in a
reasonable balance (Anne-Marie Izac, et al.), and hence provides invaluable services to
keep pests in check in agro ecosystems (Ajayi, 2000). When agricultural inputs like
pesticide and fertilizer are used, they disturb the balance and as a result soil biodiversity
declines. The disturbance in the balance and resultant reductions in biological diversity
seriously damage natural function which ultimately leads to reduce the ability of agro-
ecosystems to resist any turmoil and/or unexpected strain e.g pest infestation (Waibel,
1996).
15
Giller, et al, (1997)
22
2.3.2.2 Pest susceptibility (non-renewable biological capital resources)
In Botany, ―susceptibility is the extent to which a plant, vegetation complex or
ecological community would suffer from a pathogen if exposed.‖16 The natural
susceptibility of pests acts as natural predator and hence, provides invaluable service for
easy control of pests. ―Increasing the use of pesticide leads to a cumulative buildup of
adaptation processes within an ecosystem, and pests increasingly adapt to the chemicals
and become more resistant to them. The increase in pest resistance gradually degrades
the biological capital of pest susceptibility. Pest susceptibility is a fixed quantity in an
ecosystem and it can be exhausted‖ (Ajayi, 2000). When non-renewable biological
capital is depleted due to continued pesticide usage, pest develops resistance and even
greater amounts of pesticides are needed to obtain the same level of crop production
(Ajayi, 2000). As a result, pest resistance increases the cost of pesticide use.
The above discussion indicates that pesticide use decision is a tradeoff between
high yield in current time period and potential production loss through negative health
effects and biodiversity loss in the future time period. Economic theory suggests that
decision-making on pesticide use depends on the net effects of these two opposing
attributes of pesticide. If the pesticide use decisions include only direct costs of
pesticide use and ignore future costs (e.g. pest resistance, biodiversity loss and chronic
health costs), the pesticide use decision may be sub optimal because excluding negative
externalities of production can overstate productivity gains from pesticide use as some
cost of production is not counted. ―Rola and Pingali (1993) demonstrate that explicit
16
Giller, et al, (1997).
23
accounting for (human) health costs substantially raises the cost of using pesticide‖
(Ajayi, 2000). ―It follows therefore that accounting for the costs of health hazard, pest
resistance and the destruction of the natural control potential of an ecosystem changes
the relative economic advantage of self-regulating measures‖17 of pest management such
as Integrated pest management (IPM) versus external inputs like pesticide (Waibel,
1996). It must be bear in mind that unlike other input costs, farmers generally unable to
identify and manage pesticide related health impairment, biodiversity loss and pesticide
resistance costs. As a result, health and environmental costs cannot be easily accounted
by individual farmers and ultimately leads to sub-optimal pesticide use decisions.
2.4 Psychology and Economics
2.4.1 The Link between Psychology and Economics
There is an intrinsic relationship between psychology and economics, since
much of the economics has focused on the interaction that takes place in the market.
Indeed the market is often a defining characteristic of economics. At the same time
economists have extended their domain to include among others, family relationship,
leader follower relationship or even criminality. Clearly economic behavior resides in
social environment which makes a connection between social psychology and
economics both appropriate and practical (Kirkpatrick, 2007).
When tracing history of economics, during classical period, one comes to know
that economics and psychology had close link. The best example is ―The Theory of
17
Ajayi (2000)
24
Moral Sentiment‖ written by Adam Smith, a text clearly describing psychological
underpinnings of individual behavior (Kirkpatrick, 2007). During the neo-classical
period, psychological principles had been used in the analysis by many important figures
such as Edgeworth, Pareto, Irving Fisher and Keynes. At the end of 1940s economists
started developing more formal and practical models. They shifted their focus from
economic decision that assumed perfect information and maximizing behavior to
decision making which may not be rational necessarily. Herbert Simon‘s theory of
―Bounded Rationality‖ clearly states that due to mental constraints and moral
consideration not all alternatives are examined (Luce, 2000). Such decisions and
behaviors clearly run against rational consideration.
During 1960s researcher started using cognitive psychology in economic
decision making. Brain was the main focus of this research that act as an information
processing unit. Over time number of psychological effects has been translated into
behavioral economics concerning human judgment and decision-making (Luce, 2000).
'Prospect theory: An Analysis of Decision Under Risk' written by Kahneman18 and
Tversky in 1979, 'Theory of Crime' written by Becker in 1967 used cognitive
psychological techniques to explain individual behavior that diverge from neo-classical
theory in many economic decision making (Kahneman, 2003). Another seminal work
that explained psychological concepts into economic theory is from Herbert Simon
through theory of Bounded Rationality in which he explained that occasionally people
18
Daniel Kahneman was awarded with the Nobel prize in 2002 "for having integrated insights from
psychological research into economic science, especially concerning human judg ment and decision-
making under uncertainty.
25
are satisfied with irrational behavior instead of maximization principle as economic
theory postulates (Hogarth, 1987).
In short, psychology has a strong impact on economics in many ways.
Psychological concepts helped to reach a better understanding of economic behavior. It
has made experimental research a widely used research method and extended the view
of human nature by showing pro-social aspects in people‘s preferences (Vigna, 2007). In
this way psychology adds meat to the bones of economics.
2.4.2 Use of Psychology in Economics
Psychological factors are very important for many economic decisions. For
example, the classical microeconomic models based on consumer‘s observed choices
have generally been employed by the researchers to study individual preferences. These
models are based on the assumption of perfect market and hence assume specifically
that individuals have perfect knowledge about the market and they make rational
decisions based on utility maximization. However, one obvious shortcoming of classical
models of consumer behavior is that they fail to explain reasons behind consumer
behavior and also do not consider sociological and psychological factors that guide
consumer behavior. In this regard, social psychology is more successful in interpreting
these phenomena than is a plain economic model.
Health communication research has recommended the application of cognitive
psychological or behavioral models to understand relationship between information and
individual responses (Severtson, 2006). Several psychological models are potentially
relevant to farmer‘s pesticide use behaviors and they can contribute in the formulation of
26
policy interventions necessary to promote safety behaviors and observance to pesticide
associated health impairments (Munro, 2007). The availability of these theories, at the
same time, making it difficult for a researcher to select the most relevant one for the
current research. Therefore, these models need to be thoroughly studied to assess their
appropriateness to the present research. The next section provides a short description of
health psychology theories, their strengths and weaknesses, specifically within the realm
of understanding farmer‘s behavior of pesticide use.
2.4.2.1 Theory of Reasoned Action(TRA) and Theory of Planned
Behavior (TPB)
Originally, the Theory of Reasoned Action was developed in the context of
social psychological studies of behavior and attitudes. Later it has been widely used in
applied research in fields like family planning behavior, nuclear risk, health behavior,
voting behavior and of consumer behavior (Ajzen, 1985). In 1985, Theory of Planned
Behavior (TPB) expanded the theory of reasoned action by including an additional
element of behavior, the so called perceived behavioral control. This element has been
added in the theory to consider certain situations and environment where individual‘s
behavior is largely determined by the factors beyond his/her control. The originators of
the theory argue that individual will only perform those behaviors where he is
confidence that he has a control over it (Marcoux and Shope, 1997).
Individual intention is the main determinant of the behavior in both ‗Theory of Planned
Behavior‘ and Theory of Reasoned Action. The TRA and TPB both explain that the
individual intention is the best way to understand behavior and therefore, one should
measure behavioral intention in order to understand behavior (Marcoux and Shope,
27
1997). The behavioral intention however, depends on attitude of the individual and
subjective norm. The attitude is an individual‘s positive or negative evaluation of the
behavior while subjective norm is the social pressure on an individual to perform certain
behavior (Armitage, 1999). According to these models, if attitude and the subjective
norm are both favorable, there is more chances that individual perform certain behavior
(Armitage, 1999; Munro et al, 2007; Bandura, 2004).
Further, it is argued that certain other variables that affect attitudes or subjective
norms can also influence the individual behaviors. However, research has shown limited
support for this theory (Munro et al, 2007). Sutton (1997) has suggested that additional
explanatory variables (such as social and economic variables) should be incorporated to
improve both of the theories. He also stressed for more conceptualization (Munro et al,
2007).
2.4.2.2Social-Cognitive Theory
This theory explains that human behavior is a dynamic and ongoing process. The
personal, environmental and human factors influence each other in this process to
regulate human motivation and action (Bandura, 1997; Redding, 2000). According to
Social-cognitive theory (SCT), three main determinants determine the probability that an
individual will change health behavior: I) Self-efficacy; II) Goals; III) Outcome
expectancies. It describes that if individual is sure about personal self-efficacy, he can
change behavior even if he faces constraints to act and if an individual is not sure about
personal self-efficacy, he will not be ready or convince to act. This theory also suggests
that health behavior may also be influenced by the goals and expected outcomes (Munro
28
et al, 2007). In sum, this theory proposes that behavior will be performed for a certain
action if an individual is sure and confident to execute the behavior.
The weaknesses of this theory are that non-voluntary factors can also affect individual
behavior which this theory largely ignored. Further, this theory is also limited in scope
and do not explain external influences on behavior. Another limitation is that it lacks an
individualized approach.
2.4.2.3 The Common Sense Model
Another model of social psychology which provides theoretical support for the
study of health and protective behavior is Common Sense Model. The Common Sense
Model (CSM) assumes that individuals make mental image of their sickness based on
two type of information accessible to them. First; concrete or factual information and
second; abstract or nonfigurative information. This information helps shaping strategy to
cope with an illness (Leventhal et al, 1983). There are three main sources of
information which direct an illness representation. First; the general information already
learned (memory). Second; information from individual‘s social environment like
parents, family members, friends or other people or information from any authoritative
persons like doctors. Finally, through personal experiences with the health effects.
Individual‘s personal characteristics e.g. education, age, access to media and cultural
background are also important factors (Severtson, 2006). The main sources of concrete
information are personal experiences. The influence of concrete information in shaping
representations and behavior is much more than abstract information. The Common
Sense Model has following dimensions: Identity, Cause, Consequences, Timeline and
Control.
29
1 Identity represents how people recognize and label a threat.
2 The cause represents those factors that are believed to be responsible for causing
the illness.
3 The consequences dimension refers to beliefs regarding the impact of the illness
on overall quality of life.
4 Timeline represents an individual‘s perception about the course of disease.
5 The cure/control refers to individual‘s confidence regarding effectiveness of
coping behaviors (e.g. taking protective measures help to avoid direct exposure
of pesticide use).
The major flaw of CSM model is that it totally focuses on individual
characteristics and ignores socio-economic environment in development of
representation (Munro et al, 2007).
2.4.2.4 Health Belief Model
This model is developed in 1952 by Godfrey Hochbaum,19 when he started
research to identify the factors that lead individuals to decide to have their examination
for prior detection of TB (Hochbaum, 1956). Since then, this model has been widely
used as a research tool in an array of health and environmental settings (Lichtenberg et
al, 1999). Over time the domain of this model has been extended to explain general as
well as specific health motivation for health behavior (Green, 2010; Strecher, 1997).
19
The health belief model is developed by researchers at the United States Public Health Service in the
1950s and Godfrey Hochbaum in itiated the first research on the HBM in 1952.
30
This theory postulates that a person who had experienced health effect is more likely to
take safe behavior, if he/she; 1). Believes that the illness can be avoided; 2). Believes
that by adopting suggested safety measures, illness can be avoided and; 3). Sure that
he/she can effectively take suggested safety measures.
Basically ―Health Belief Model‖ encourages a person to adopt positive health
actions using the desire and will to avoid illness as the key inspiration. For example, in
the current settings, pesticide exposure has negative health effect and the desire to avoid
direct exposure from pesticide can be used to motivate farmers into practicing protective
and safe use of pesticide. Broadly ―Health Belief Model‖ is based on six key concepts.
1) Perceived threat: It is further classified into two parts; perceived susceptibility
and perceived severity.
Perceived susceptibility: One's own belief of the chances of receiving a health
condition that may seriously affect one's health.
Perceived severity: One's personal belief of severity of health condition, for
example, pain and discomfort, reduced productivity and less time available for
work, extra economic burden, problems with day to day jobs and difficulties with
family relationships.
2) Perceived benefits: The believed effectiveness of strategy proposed to decrease
the risk of sickness.
31
3) Perceived barriers: The possible negative consequences that may result from
adopting certain health actions, such as physical and psychological stress and
economic loss.20
4) Cues to action: The variables that force or stimulate an individual to take
necessary steps to avoid illness or health threat. These stimuli may be internal or
external.
5) Modifying variables: Demographic, social, psychological and economic factors
that influence an individual's perceptions and thus indirectly affect behavior.
6) Likelihood of action: These include all those factors that indicate the probability
of taking suggested health action to prevent disease (Green, 2010). These factors
jointly affect an individual to undertake the recommended preventive health
action.
In short, the Health Belief Model postulates that individuals‘ behavior change is
a function of individuals‘ mental appraisal of the barriers and benefits of taking certain
action (Munro et al, 2007). If perceived health effects are serious and net benefits 21 of
taking action are positive, there is a more probability that individual will take action.
20
Due to these barriers, action may not take place, even though an individual may believe that the
benefits to taking action are effective. This may be due to barriers. Barriers relate to the characteristics of
a treatment or preventive measure may be inconvenient, expensive, unpleasant , painful or upsetting. These
characteristics may lead a person away from taking the desired action. 21
According to this model, the perceived seriousness of, and susceptibility to a disease influence
individual's perceived threat of disease. Similarly, perceived benefits and perceived barriers influence
perceptions of the effectiveness of health behavior. In turn, demographic and socio -psychological
variables influence both perceived susceptibility and perceived seriousness, and the perceived benefits
and perceived barriers to action. It is concluded that High-perceived threat, low barriers and high
perceived benefits to action increase the likelihood of engaging in the recommended behavior (Becker et
32
Figure 2.1. Health Belief Model
Individual perception Modifying Factors Likelihood of Action
Source: Strecher and Rosenstock (1997).
This study selected the health belief model to gain better understanding of
relationships between health experience, risk perception and pesticide use behavior. The
health belief model has been chosen for the present study because of several reasons; (1)
the health belief model considers individual as active info rmation processor and
independent decision maker. Since pesticide use is largely governed by voluntary
behavior, hence health belief model best suits in present circumstances; (2) another
advantage of HBM is its simplicity that makes it attractive to understand health
al, 1979).
Demographic & socioeconomic
Variables:
(Age, Sex, Personality, Knowledge
about the disease, socioeconomic
variable, etc)
Perceived Benefits
of preventive action
minus Perceived
barriers to
preventive action
Perceived threat of Disease
Perceived
susceptibility to
disease
Perceived
seriousness
(severity) of disease
Likelihood of taking
recommended
Preventive health
action Cues to action
Mass media Campaigns
Advice from other
Illness of family member or friend
Newspaper or Magazine article
33
behavior. Health Belief Model does not follow strict guidelines22 like other models of
health psychology to predict health behavior. Instead it describes the framework in
which each individual variable contributes in the prediction of health behavior (Nejad et
al, 2005). Although this lake of proper guidelines is considered a shortcoming of this
model and often a reason of heavy criticism, but at the same time, the flexibility of the
construct makes this model very attractive23 among researchers and it is the most
frequently used model in health psychology; (3) though, HBM is a health-specific
model, it allows socio-economic variables to be included in the model which affect
health motivation. Because of the features, discussed above, the HBM has received
much wider support from practitioners, academia and researchers (Munro et al, 2007).
There are few studies in pesticide use behavior literature that sought help from
social psychology to explain behavior. A seminal work in this regard is done by
Lichtenberg and Zimmerman (1999). Referencing social psychology they examined
specific hypothesis that ―whether or not adverse health experiences play a part in
shaping attitudes.‖24 The research has shown a strong support for health belief model.
The result indicated that there is significant relation between health effects that farmers
have experienced from the use of chemical pesticides and their risk perception toward
the seriousness of health effects. Study also found a strong relation between health
experiences from pesticides and the use of environmentally sound pest management
practices. Similarly Napier and Brown (1993) highlighted very well-built results for
22
The model comprises a series of broadly defined constructs that might explain the variance in health
behavior but there are no clear operational guidelines regarding relationships between them 23
Most health belief model based research to date has incorporated only selected component of HBM
(Munro et al, 2007). 24
Lichtenberg and Zimmerman (1999).
34
farmers who use pesticides and fertilizer in Ohio State USA and related their health risk
perception with environmental attitudes. The authors found that ―respondents who
supposed their families to be threatened by fertilizers and pesticide in groundwater likely
to perceive groundwater contamination to be chief environmental problem and were
more willing to compel land operators to alter production practices to keep groundwater
resources safe.‖25 Tucker and Napier (1998) in a study found that perceived negative
health effects from pesticide associated contaminated groundwater was the strongest
predictor of farmer‘s attitude.
2.5 Economic cost of pesticide use
Keeping in view, the chronic and acute poisonings, and other environmental
problems, economic cost of the application of pesticide seems to be very high. David
Pimentel (2005) estimated the economic cost of pesticide associated health and
environmental damage in United States. He estimated that the cost was as high as $10
billion. The distribution of major losses due to pesticide use was as follows; the cost to
public health was $1.1 billion, the development of pest resistance against pesticide was
$1.5 billion, the losses to crops and vegetation was $1.4 billion, the birds, honeybees and
animal losses due to pesticide use was $2.2 billion and groundwater contamination was
$2.0 billion per year. Following Pimentel, Azeem et al. (2002) measured health and
environmental cost of chemical pesticide use in Pakistan. The estimated cost of pesticide
use is 11941 million rupees per year. Most of the cost is caused through production
losses, amounted 5667 million due to resistance development in the pests. The damage
to animal amounted 1304.5, while health cost of pesticide use is estimated as more than
25
Napier and Brown (1993)
35
1032 million, including treatment cost, workday loss, and fatalities. Pesticide residue in
food chain are estimated more than109 million. The economic evaluation of pesticide
use shows that negative externalities of pesticide are very high in Pakistan which needs
urgent attention of policy makers.
A notable work in the context of South Asia is done by Wilson (2000) which
provides detail on respective issues. He justified that regardless of producing record
yields, the current agricultural practices in South Asia are unsustainable. Farmers are
totally dependent on heavy doses of chemical inputs, like fertilizer and pesticide. Due to
this dependence a high cost has arisen in terms of human health and natural
environment. Human health cost includes treatment/medical cost and time costs (work
days lost of ill workers and care giver‘s time lost). Human health prob lems also reduce
efficiency/ ability to work on lands which has it cost. He further described that overall
productivity of farm is affected because of indiscriminate use of pesticide and fertilizers.
The larger quantity of chemical pesticide depletes natural capital by destroying natural
predators of pests, disrupting ecological balance and reduces soil productiveness. As a
result of declining land productivity due to rise of pests and other diseases, larger
quantities of chemical fertilizer and pesticide have to be used in the production process,
which increase the costs of input use. Another type of cost of chemicals is agricultural
toxic run off which pollute water and affects other production processes, such as
production of fisheries which provides farmers an additional source of income.
Moreover, the safety measures taken to keep away from exposure to pesticide, though
insufficient, also incur cost.
36
2.6 The Contingent Valuation Method
Valuation is difficult for the outcomes such as reducing the risk o f human illness
because they are nonmarket goods (the goods that are not sold and purchased in any
market). Due to absence of market, Special techniques are required to study consumer
choices and preferences for environmental goods. One such technique is Contingent
Valuation Method (CVM). In this method individuals are directly questioned about their
willingness-to-pay for a given good or service. This is a survey based technique where
―respondents are offered a hypothetical market and they are asked to express their WTP
for existing or potential environmental goods or services not reflected in any real
market‖. ―The monetary values obtained in this way are thought to be contingent upon
the nature of the constructed market, and the commodity described in the survey
scenario‖ [Garming et al (2006)]. The respondent‘s answers help researcher to drive
demand curve for an environmental good and service directly in the absence of market
data (Hanemann; 1994).
Although there has been long-standing awareness in Contingent Valuation
technique in environmental and resource economics, the approach got momentum in
recent years when researchers in environmental and resource economics have made
increasing use of this approach to estimate the value of many type of environmental
goods and services (Carson, 2000a). The Contingent Valuation technique is of great use
because of its flexibility to measure value. It allows the estimation of an array of non-
market goods.26 Although Contingent Valuation (CV) is the most commonly used non-
market valuation method, the debate over the reliability of CV however, continues to
26
This is the only technique to measure passive use value
37
exist. However, researchers and experts in CV method have suggested that many of the
so-called problems with this technique can be resolved by expert plane and proper
implementation of the survey (Carson 2000a).27 In addition, CVM is direct
(hypothetical) measure and focuses on ex-ante behavior before some changes take place
whereas the indirect methods (e.g. travel cost and hedonic pricing) concern with ex-post
behaviors. Thus, from policy perspective the estimates of changes in welfare are
theoretically better approached using CV method than using indirect methods (Doherty,
1993).
2.6.1 Economic evaluation of health cost using WTP
As noted above, like many other environmental goods, economic evaluation of
health cost of pesticide use is embarrassed by the practical obstacles because of different
value components of human health; market component such as the cost of illness,
productivity loss, work days loss (are those on which a person is unable to engage in
ordinary gainful employment)28 and non market component like cost of discomfort.
Since it is difficult to integrate market and non-market elements of health cost of
pesticide use in a health cost model, the most of the researchers measuring health cost of
pesticide use have focused on the market components of health cost.29 Different
researchers used different approaches, for example, Ajayi (2000) and Huang et al.
27
For detail see: Portney R.P (1994); “The contingent valuation debate”: why should economists care.
Journal of economic perspectives-volume 8, number 4-fall 1994-pages 3-17
Income -.0069491 -.0426779 .0116047 .0492798 .0089637 District dummy -.0490742 -.1065122 .0289621 .1229888 .022371
The table 7.4 has two panels, the upper panel shows predicted probabilities and the
lower indicates the marginal effect for all explanatory variables. Since model includes
both continuous and binary variables, the interpretation of continuous and binary
variables is not same. In the case of continuous variables we usually interpret results
following our OLS regression understanding, such as o ther thing being constant, a unit
change in exogenous94 factor results a change in predicted probability equal to the size
of marginal effect. However the interpretation is different for binary variable95 that is the
94
Marginal effects for continuous variables case are calculated as:
Where is the normal probability distribution function. 95 In case of binary variables, the marginal effects are discretely approximated using the difference in
predicted probabilities when the discrete variable is set equal to one and zero:
128
marginal effect represents change in predicted probability provided that respondent falls
into that category. Note also that the marginal effects across all risk perception
categories (which are five here) must sum to zero for a particular explanatory variable
by definition96 (Cranfield et al, 2003).
Starting with the age variable of the farmers, they are likely to perceive no risk or
low risk, and less likely to perceive high risk with the increase of age. This is against our
expectations since we are taking age as the proxy of farming/pesticide use experience.
There are two possible explanations for the result. First; with the passage of time,
farmers are used to of these problems and they do not take these effects very serious. It
seems true, because many farmers believe that these health effects are routine matter and
they are ready to accept a certain level of health effects. This comportment may well
explain the lack of pesticide related health awareness. Second; these farmers may using
more protective measures and resultantly have not experienced/witnessed any health or
environmental problem.
The same is the case of farm size. The variable has positive marginal effects for
the first category as well as for the second category of risk perception (e.g., no risk at all
and low risk) but negative marginal effects for other three categories. An interpretation
for this result is that the land holding represents farme r‘s wealth. The more is the land,
the more is the farmer‘s ability to purchase protective measures. The farmers who are
using more protective measures are less likely to be effected from pesticide, hence less
(Cranfield, 2003).
96 Since the predicted probabilities for all the categories of risk perception must sum to one, the change in
probabilities for these categories must sum to zero.
129
likely to perceive risk perception. Another interpretation for the result is that they may
not be applying pesticide regularly and usually get this job done by hired labour,
resultantly; their perception of pesticide risk is low. The health effect variable has
negative marginal effects for the first category as well as for the second category of risk
perception (i.e., no risk at all and low risk) but positive marginal effects for other three
categories and this influence is very large for third (medium risk) and fourth (high risk)
categories. These results are very much expected since it is hypothesized that farmers
who experienced negative health impairment are more likely to perceive higher pesticide
risk. In short, the result indicates that health experiences strongly influence farmer‘s
attitudes. This result is very much similar to number of previous studies 97 and
underlying theory. Similarly, the marginal effects of training on no risk at all, low
risk/some small risk and medium amount of risk categories are negative, however the
marginal effects of training on high risk category and extremely high risk category is
positive and very strong. The finding is paralle l to that found by Lichtenberg and
Zimmerman (1999).
The marginal effect of education is negative for the first two categories of risk
perception, however it is positive for the higher classes. This suggests that farmers with
more education are less likely to perceive no risk of pesticide use on health and/or low
level of health risk and more likely to perceive high risk, medium amount of risk and
extremely high risk. Holding all other things equal, there is a higher probability of being
in lower perception categories when farmer‘s education is low compared to when
farmer‘s education is higher. Differently, more educated farmers are more likely to
97
(Lichtenberg et al, 1999;Dasgupta etal,2005a; Huang,1993)
130
perceive high risk perception relative to less educated ones. The income variable follows
similar pattern, though not significant. The marginal effect for the first and second
category of perception is negative but positive for higher classes of perception. One
possible interpretation for this result is that the high income farmers usually have more
access to information and more access to education, compared to low income/small land
holders since agriculture extension services are heavily skewed towards progressive
farmers. This is also evident from the farmer‘s responses in both the districts.
Farmers in district Vehari relative to the farmers of d istrict Lodhran are more
likely perceive greater risk to health from the use of pesticide. The marginal effects are
also stronger for Vehari than for Lodhran. Such differences are not surprising given the
diversity of the population between districts and relatively higher level of education
among sampled farmers in Vehari.
7.2 Health experience, risk perception and safety behavior
The seriousness with which farmers view health problems associated with
pesticide has been analyzed from two different angles (from personal safety perspective
and from environmental perspective). The behavioral factor studied in this section was
the extent, to which farmers used safety measures to avoid pesticide exposure when they
believe that they have experienced negative health effects from pesticides.
Result shows that farmers who experienced health symptoms during mixing or
spraying pesticide are more likely to adopt protective measures, ceteris paribus. The
findings support the hypothesis that there is a strong linkage between adverse health
effects and protective behavior. Seriousness of health risk is important factor in shaping
131
individual‘s behavior. In line with previous literature and theoretical background
individual‘s risk perception appeared as an important factor to convince farmers to take
more protection. Thus, this evidence suggests that pesticide associated negative health
problems act as a signal, changing farmer‘s future behavior toward pesticide safety. The
result is consistent with theory and priori expectations.
It is widely accepted that education enhances awareness regarding health which
can be seen from the table 7.5. The more educated farmers reported taking more
protective clothing than farmers with less education. The result implies that education
exerts a significant effect on the decision to adopt protective measures. The farmers who
got training of safe pesticide handling reported significantly higher concern about
protection. This could be interpreted as indicating that the more learned farmers in terms
of safety are more likely to select higher level of protection than non-trained farmers.
Similar findings were noted by Lichtenberg and Zimmerman (1999). District controls
reveal that protection level to avoid direct exposure from pesticide is not significantly
different in both districts.
Table 7.5. Results of ordered probit regression for protective behavior
Variable Dependent variable:
Protective behavior
Health Effect .6161179 (0.001)
Risk perception .1402597 (0.037)
Age .1077838 (0.103)
Education .1421597 (0.000)
Training .8896106 (0.000)
Income -.1684239 (0.047)
District Dummy -.028836 (0.823)
Farm size .0579337 (0.464) The values in parenthesis are P values. Log likelihood = -373.34005, Pseudo R2 = 0.0920,
LR chi2 (12) = 75.62 (0.000)
132
The negative relationship between income and protective measures is the
harshest which can‘t be explained properly. Results do not provide any evidence of
statistical association between the age of farmers and level of protection. Again same
arguments can be presented that with farming experience farmers are ready to accept
certain level of health effects and they consider them a routine matter. Therefore their
risk perception is low and they are less likely to take protective measures. Similarly no
significant relation was found between farm size and level of protection in the study
area. Overall, results indicate that farmers who have had health experiences do care
about the effects of pesticide application and do engage in safety practices. Table 7.6
shows the predicted probabilities and marginal effects for different categories of
protective measures evaluated at the means of the sample data.
Table7.6. Predicted probabilities and marginal effects from the estimated model
Income -.0668723 -.2397955 .3003572 .0063106 3.72e-09
District dummy
.0023701 .008499 -.0106455 -.0002237 -1.32e-10
Starting from top of the table, age of the farmers, nevertheless not significant
more likely to pay premium for safer pesticide since we also assume age as the proxy of
farming/pesticide use experience, suggests that farmers who have been using pesticide
since long are more likely to perceive higher risk and therefore willing to pay premium
for safer pesticide. This can also be explained in terms of income of the farmers. Old
farmers are more likely having higher income and more empowered. The ―risk
perception‖ variable is negative for the first and second categories of willingness-to-pay,
but for the other three willingness-to-pay categories, it has positive marginal effects.
Moreover, the marginal effect tends to be very strong for the category ―medium amount
of risk‖. Thus the farmers who perceive pesticide a health risk are more likely to be
willing to pay premium relative to those who do not perceive pesticide a health hazard.
The pesticide related health effect variable has negative marginal effects for first
two categories of WTP but positive marginal effects for other three categories of WTP.
These results are analogous to priory expectation. Logically negative health experiences
142
from the pesticide are more likely to influence farmer‘s attitudes to pay higher premium
for safe pesticide. The marginal effect of education is negative for the first two
categories of WTP but it is positive for the higher categories of WTP. This suggests that
holding other things same, there is more chance for a farmer to be in lower WTP
categories when his education is low compared to when farmer‘s education is higher.
Alternatively, more educated farmers are more likely to pay more for safe pesticide use
relative to less educated farmers.
The marginal effects of training and IPM variables for the first two categories are
positive, such that the farmers who got training of safe handling of pesticide use and
farmers who currently practicing IPM are more likely to pay either no more money or up
to five percent more and very less likely willing to pay higher premium for safe use of
pesticide. The income variable shows opposite pattern. The marginal effect for the first
and second categories of WTP is negative however these effects are positive for other
three categories. This is because higher income farmers can afford premium. The farm
size variable follows same reasoning. This variable is an indicator of individual‘s wealth
which ultimately expands farmer‘s budget constraints. Thus more the size of farm, the
more likely farmer willing to pay premium for safe use of pesticide. The result is
parallel to priory expectation and consistent with the theory.
143
7.5 Summary
This chapter presents the econometric analysis of pesticide use behavior. In this
chapter, three different hypotheses are tested. The results supported the hypothesis that
farmers who have had negative health experience related to pesticide use are more likely
to have heightened perception than the farmers who have not such experience.
The results also support the hypothesis that there is a strong linkage between adverse
health effects and protective behavior. Seriousness of health risk is important factor in
shaping individual‘s behavior. As expected individual‘s risk perception appeared as an
important factor to convince farmer to take more protection. However, results tend to be
different and do not support the hypothesis that farmers who have had negative health
effects from pesticide use are more likely to adopt environmentally better management
practices. This does not indicate that attitudes of farmers on pesticide related health
effects are nominal (since their knowledge is not replicated in the farming practices).
Actually, the farmers in study area either haven‘t information regarding alternative pest
management techniques or haven‘t access to these alternatives. So they are forced to
adopt pesticide despite their reservations.
This chapter also highlights the results of contingent valuation method to
measure health cost of pesticide use from farmer‘s point of view. Analysis shows that
farmers are ready to pay at least 8.1% more of their total current pesticide cost for
avoiding pesticide related health risks. All the relevant indicators of WTP such as risk
perception, previous experience of pesticide related poisoning, education and income are
significant predictors for the positive WTP which are important for the ―Theoretical
144
validity‖ of the study. Compared to the other studies in literature (Garming et al, 2006,
Cuyno, 1999) mean willingness to pay is relatively small. This is not surprising, since
most of the farmers are poor (small-scale farmers), and uneducated, hence cannot afford
premium. From the results it is evident that health effects provide motivation for farmers
to pay more for practices like IPM that reduce dependence on pesticide use which in
turn is a strong motivation for policy makers to expand the scope of this technique
through more research on IPM and its implementation on grass root level.
145
Chapter 8
Conclusion and policy implications
8.1 Conclusion
Rising pest problems as well as easy availability of pesticides to farmers that
results from liberalization of pesticide market led to increased use of pesticides in crop
protection practices. Consequently, consumption of pesticides in Pakistan has reached
up to 117513 metric tonnes in 2005 which was only 665 metric tonnes in 1980. The
indiscriminate use of pesticide leads to both direct and indirect costs in terms of health
and environment. Indirect costs include pest resistance, degradation of biological capital,
loss of bio-diversity, negative effects on human health and irreversible changes in the
natural ecosystems which ultimately effect sustainability of agriculture.
The evidences from cotton growing areas have indicated that health impairments
of farm workers and environmental damage are mounting because of growing
dependence on pesticide use. The experience with the major outbreaks in 1992-93
onwards has shown that overuse of pesticide has led to destruction of natural enemy
populations in cotton growing areas of the country. As a result of destruction of natural
enemy populations, insects have developed resistance to chemical pesticide which led to
tremendous increase in pesticide use without any improvement in effectiveness of crop
protection particularly cotton in Pakistan.
From the discussion it is obvious that rising use of pesticides is not an optimal
option to protect crops from pest damage. However, given the Pakistan‘s agriculture
146
settings and cash crops security situation, it is expected that current crop protection
practices will likely continue to be the main agriculture system101 in the country because
farmers believe that pesticide use is the sole crop protection technique. The trust on
pesticide as the only crop protection technique leads to further dependence on pesticides.
It is therefore obvious that the environmentally sound pest management system should
be developed on urgent basis which ensures high yield crops while maintaining good
health of farmers and agriculture sustainability in Pakistan. However, before
undertaking such developments, it is important to understand farmer‘s behavior of
pesticide use. The information regarding farmer‘s behavior is critical to identify the
prospects and constraints to the adoption of environmentally sound crop protection
policy. What becomes striking about the pesticide use in Pakistan is that, despite the
recognition of the severity of problem, no systematic study exists in Pakistan that
discusses farmer‘s behavior of pesticide use.
The present study analyzed the existing crop management system or actual
practices in the field and behaviors with the view to identifying the prospects and the
constraints in the adoption of more sustainable practices. The study used Health Belief
Model from health psychology and combined it with new classical Microeconomic
theory to demonstrate farmers reasoning behind their decisions of pesticide use. The use
of psychological model improves understanding of farmer‘s pesticide uses behavior and
contributes to the design of more effective policy interventions to promote safe pest
management. The study through series of observations highlights preventive behavior at
101
Non-existent or lack of information about alternative pest management practices and pro -pesticide
extension services provided by pesticide companies led to convince farmers that pesticide use is the only
pest management technique.
147
personal and environmental levels. The study reveals that pest management is pro-
pesticide in Pakistan. Government policies (pro-pesticide extension system, soft rules for
import of pesticide and other support measures)102 either directly or indirectly encourage
farmers to use pesticide to achieve higher crop yields. Over the years pesticide
encouragement policies have led to eliminate alternative cultural and traditional
practices among farmers in cotton growing areas. Farmers in the study area are not well
conversant to integrated pest management and they have no choice except to use
pesticide, even their health concern. Study results underscore the significance of
providing information relevant to pesticide safety and health issues.
The result shows that about one-third of the respondents is illiterate and cannot
read or write. It has been noted that farmer‘s low level of education is the main reason of
incorrect beliefs regarding pesticide toxicity which acts as a constraint in the adoption of
alternative practices. Farmers are frequently exposed to pesticide. The prevalence of this
exposure is more in district Lodhran, where over 90 percent farmers reported at least one
health problem than in district Vehari, where almost 80 percent farmers appeared to
report these problems. They also appeared to give low priority to health considerations
and grossly under-estimating pesticide risk. They tended to consider those health effects
as common problems. This misperception is largely translated in practical behavior
where almost all the sample farmers did not visit hospital or doctor for proper
medication. Low level of education combined with cultural/local beliefs regarding
health conditions is the main reason of this misperception.
102
Agricultural Pesticide Ordinance 1971 and Agriculture Pesticide Rules 1973 were amended in favor of
importers in the Form 16 and 17 in 1992 and 1997, respectively. According to Form 16 and 17, the
pesticide registered in other countries can be imported without going through pesticide trials at two
research stations to test its efficacy against the target pests for two seasons (anonymous).
148
The misperception of farmers on the potential hazards of pesticide to health appeared
to have much impact on field practices of pesticide use, where farmers are found heavily
skewed towards pesticides and taking few safety measures. More than 80% pesticide
used is highly or moderately hazardous. In terms of crop, cotton alone received over
85% of total quantity. Other crops include vegetables 9% and wheat 5%. Similar pattern
appeared in terms of toxicity, where cotton consumed over 90% of highly hazardous
pesticide and about 89% moderately hazardous pesticide. Farmers also found applying
pesticides very frequently. It is quite common for them (73 percent) to use pesticide
more than 10 times on cotton in a season. The spray frequency is as high as 16 on cotton
crop in one season.
Although farmer‘s knowledge of pesticide and safety practices is reasonably good
but practically non-existent. Most of the farmers partially covered their body with
protective clothing while mixing or spraying pesticide. The formal IPM training and
information are largely non-existent in the study area. Most of the farmers did not know
about IPM, hardly few of them are using these alternatives as supplementary to reduce
their dependence on pesticide. They are totally dependent on pesticide dealers and
pesticide salesmen for information. Agricultural extension services are very limited in
the area. However, the encouraging is that most of the farmers are ready to pay a
premium for safe alternative crop protection approaches.
The analysis supported the hypothesis that farmers who have had negative health
experience related to pesticide use are more likely to have heightened risk perception
than farmers who have not experienced such health problems. Education and training are
also important determinants of risk perception. The findings also support the hypothesis
149
that there is a strong linkage between adverse health effects and protective behavior.
Seriousness of health risk is important fac tor in shaping individual‘s behavior. In line
with previous literature and theoretical background individual‘s risk perception appeared
as an important factor to convince farmers to take more protection. Again education and
training appeared as an important determinant of protective behavior. The results
however, tend to be different and do not support the hypothesis that the farmers who
have had negative health effects from pesticide use are more likely to adopt IPM. The
lack of information or access to these methods is likely a contributing factor which did
not allow many farmers to have proper awareness about alterna tive pest management
practices. The non-existent alternative methods of pest control as well lack of
information regarding these methods and pro-pesticide extension made farmers biased in
favor of pesticide use. As a result, alternative methods are locked out and crop
protection technology became almost synonymous with pesticide use. Therefore,
farmers consider pesticide as the only crop protection method in this part of Pakistan.
The positive and significant effect of risk perception on adoption of alternative pest
management practices and willingness to pay a premium for IPM support this argument.
Hence, improving farmers‘ awareness and access to other methods will be necessary for
their adoption of alternative crop protection practices.
Finally, the study concludes that cultural believes (ignorance) regarding pesticide
related health effects, lack of information regarding and/or non-existent alternative pest
management and fear of economic losses remain the main barriers in adoption of more
sustainable pest management practices. In addition, direct or indirect loans and
incentives offered by pesticide companies combined with powerful advertisement
150
network perpetuating the vicious circle of pesticide use and serving as the chief barriers
to switching to alternative pest management strategies. Therefore, farmers must be
informed about negative externalities of pesticide use and they should be trained enough
to use pesticide correctly and safely and avoid its misuse and overuse, so that farmers
could internalize the negative health and environmental externalities of pesticide use and
find better pest management solution.103 There is also an urgent need to convince
farmers that pesticide use is not the only way of controlling pests. Hence, improvement
in farmer‘s knowledge and awareness regarding pesticide safety issues is critical. The
availability of alternative pest management techniques is also an issue which should be
resolved. Although some farmers are fully convinced to adopt Integrated Pest
Management and many others are willing to pay a higher price to adopt Integrated Pest
Management, but such techniques are largely absent in study area. The study stresses
that increasing use of farm pesticide cannot be effectively checked if there is no practical
alternative pest management technology available.
8.2 Policy implications
The results of the study bear some implications for policy formulation. It must be
noted that negative health and environmental externalities caused by indiscriminate use
of pesticide are severe. These externalities are affecting a large share of the farming
community in study area and there exist solutions that can contribute significantly in the
103
In seeking for a better solution to pest management problems and negative externalities of pesticide
use, the priority issues are not just how to set up regulations and policies that would ban pesticide use in
crop production, but how to use pesticide correctly and safely.
151
improvement the health of farmers and the environment. Based on the research results,
these areas should receive priority attention.
The government must understand that the use of pesticides in Pakistan
particularly in cotton growing areas of the country is promoted by official
intervention. Through series of interventions, the government encouraged the
farmers to adopt pesticides as crop protection technique and over time, due to
this policy pesticides became part and parcel of crop protection which ultimately
led to the massive use of highly toxic pesticides by farmers. Further, due to
multiple factors, a common farmer does not take protective measures necessary
for the safety. Resultantly, the increasing use of pesticide is held responsible for
thousands of health poisoning and environmental damage every year. Therefore,
it is the government who must take responsibility to control the massive use of
pesticides. The present situation can be changed only when government shows
even stronger commitment to reduce pesticide use and as a result, the health and
environmental hazards than to the initial campaigns to encourage farmers to use
pesticides in the first place. Realizing the situation, over time government made
laws to control toxic substances and to ensure their safe use but enforcement of
these laws remains insufficient. An important policy measure is that government
may take appropriate steps to control the use of highly hazardous pesticides.
Policy interventions may include the restructuring of incentives/punishment104 to
reduce availability of highly toxic insecticides.
104
Subsidy for less toxic pesticides and tax for highly toxic pesticides
152
The government should make serious efforts to reverse the present situation. The
promotion of environmentally safe use of pesticides requires substantial
allocation of funds for research and training in integrated pest management. The
countries that have succeeded to get rid of pesticide trap, spent generous amount
of economic resources on research and training. The best example is the
Indonesia that invested about 1 million U.S dollars a year in integrated pest
management research and training in 1980s and by 1990s Indonesia was able to
raise crop yield by 12% with remarkably low pesticide use (Pimentel, 1997;
Wilson, 2001).
One of the corner stone of this research is that the public resources diverted to
provide information regarding health and safety related issues can be effective
even when public investment for more comprehensive and detailed intervention,
such as provision of alternative pest management or enforcement of pesticide
related laws are lacking. The government should strengthen information and
services105 provided by the agriculture extension for plant protection. The
government may also engage other stakeholders106 in this process.
The study recognizes that education is a powerful tool for improving farmer‘s
awareness regarding pesticide related health and environmental problem that
farmers need to address according to their specific exposure circumstances. The
finding that education is positively and significantly related to farmers‘ risk
105
There is a need to overhaul current extension services by improving their knowledge on the changing
trends of pest populations. 106
The interventions can take many forms, including media events, NGOs and community programs
undertaken to promote awareness and understanding of the risk issues. Intervention should also include
social institutions (e.g., community leaders) that can help making farmers become aware of the risk and
subsequently leads to some sort of change in knowledge, attitudes and behaviors.
153
perception and behavior toward adopting protective measures and alternative
pest management offers important policy implication. It implies that innovative
and practical educational programs on health and safety would address incorrect
beliefs, misperception and misinformation and to facilitate farmer‘s
understanding of pesticide borne health risks. The continuous stress on the basic
safety measures would be an immediate solution to dangerous spray practices
and wrong habits which put farmer‘s health at jeopardy. The study results
however, stress that these educational programs need to target small land holders
and less educated farmers that appear to have less knowledge regarding health
and safety issues. But it must be noted that education alone is not enough to
address this issue. To improve the degree of success, training of safe and better
pest management practices is also necessary.
The results which indicate that heightened risk perception and IPM training are
the main determinants of safe behavior of pesticide use offer opportunities to
integrate IPM technology into current crop protection methods. The feasibility of
the IPM technology has been highlighted by many studies (e.g Azeem et al, 2002
& 2004) which were conducted in the same cotton area of Punjab. In addition,
the common belief among farmers in the area that most of the pesticides have
lost effectiveness against pests and they are not as dangerous to many pests as
before makes this claim stronger that the farming community in study area will
warmly welcome IPM methods of crop protection. Further, the argument is also
supported by the analysis which shows that farmers are willing to pay a premium
for IPM.
154
There is a need to develop and provide protective equipments feasible to the hot
and humid climate of Pakistan. These should also be affordable and accessible
for the average farmer.
The basic health-care facilities are generally lacking in rural areas which needs to
be strengthened because they provide first aid facilities107 to the farmers. The
local dispensaries and health care practitioners may better serve this purpose.
Therefore, they should be trained and supplied proper anti dotes. The emergency
poison centers should also be established in the area.
There is a need to inform farmers regarding the banned pesticide, their health and
environmental impacts. It would be much better if they are provided the list of
these pesticides.
8.3 Future Research Priorities
The present research offers some future research possibilities which are given below.
The future research may explore better information tools and more suitable
education programs for farmers regarding health and safety issues. The research
needs to determine what appropriate information tools and practical education
programs should be offered to farmers, in what way they would be most effective
and useful, and how they should be conveyed.
―Economic concerns of the farmers override their health concern‖ is well
distinguished by this research and therefore, immediate economic benefits like
crop yield likely to serve as a driving force in the acceptance of integrated pest
management. It must be noted that farmers take pesticide as a ‗reference point‘
107
The research shows that primary health care approach is most suitable for such situations.
155
against which they would evaluate integrated pest management and they will
adopt alternative pest management techniques only when they believe that
returns from doing so are positive. Improving awareness of the farmers regarding
integrated pest management methods alone may not guarantee that they will
substitute integrated pest management with pesticide use. The results of other
studies (e.g Ajayi, 2000) also indicated that farmer‘s decision regarding adoption
of integrated pest management would be purely based on economic returns of
these methods in comparison to pesticide use. Future studies should focus on
IPM‘s impact on productivity and profitability. Productivity estimates are
important to convince farmers to shift production practices at la rge scale. This
information also helps policy makers to understand whether or not, direct future
resources towards IPM program.
There is a need for further exploration of farmer‘s behavior on the line of current
research approach. It may be done by increasing the coverage in terms of area
and crops. This type of research greatly benefit policy makers to understand
whether the problems are similar in other geographical areas as identified by this
research which ultimately increase pressure on policy makers to change
agricultural production to more sustainable path.
156
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Figure 4A.Farmer‘s perception of pesticide risk by district (%)
171
Figure 5A. Farmers‘ attitudes towards health effects of pesticide use in Vehari
Figure 6A. Farmers‘ attitudes towards health effects of pesticide use in Lodhran
172
Figure 7A. Distribution of mean pesticide application on vegetables
173
Appendix II: Tables
Table 1A. Distribution of farm size by district
Vehari Lodhran
No of farmers Farm size Average land
holding
No of
farmers Farm size
Average
land holding
18 Up to2.50 1.8 18 Up to2.50 1.7
25 2.6-5.0 3.36 20 2.6-5.0 3.25
36 5.0-10.0 6.7 44 5.0-10.0 6.85
62 10.1-25.0 14.3 53 10.1-25.0 14.45
6 25.1-50.0 25.9 22 25.1-50.0 27.4
0 50.1-100 0 7 50.1-100 59.3
2 100+ 375 5 100+ 130
Total 149 169
Table 2A. Distribution of farm size by farm ownership in Lodhran
Farm size
Farm ownership
Total On the Farm
Rental
Arrangement Sharecropper
Up to2.50 72.7 13.6 13.6 100.0
2.6-5.0 79.2 20.8 0.0 100.0
5.0-10.0 88.6 4.5 6.8 100.0
10.1-25.0 95.2 0.0 4.8 100.0
25.1-50.0 100.0 0.0 0.0 100.0
50.1-100 100.0 0.0 0.0 100.0
100+ 100.0 0.0 0 100.0
Table 3A. Distribution of farm size by farm ownership in Vehari
Farm size
Farm ownership
Total Owner the farm
Rental
arrangement Sharecropper
Up to2.50 63.2 21.1 15.8 100.0
2.6-5.0 73.5 17.6 8.8 100.0
5.0-10.0 71.4 20.0 8.6 100.0
10.1-25.0 89.7 10.3 0.0 100.0
25.1-50.0 100.0 0.0 0.0 100.0
50.1-100 100.0 0.0 0.0 100.0
100+ 100.0 0.0 0 100.0
174
Table 4A. Distribution of farmer‘s age
Age % No.
11-20 04 13 21-30 35 111
31-40 31 96 41-50 21 67
51-60 09 29 61-70 32 01
Total 100 318
Table 5A.Distribution of education attainment by age in Vehari
Education attainment
Age
categories Illiterate
Up to
Primary Middle Metric
Higher
secondary
Graduation
and above Total
≤ 20 0 12.5 50.0 25.0 12.5 0.0 100.0
21-30 12.2449 22.4 30.6 22.4 4.1 8.2 100.0
31-40 36.53846 21.2 21.2 17.3 0.0 3.8 100.0
41-50 38.70968 12.9 29.0 9.7 6.5 3.2 100.0
51-60 44.44444 22.2 33.3 0.0 0.0 0.0 100.0
61+ 0 12.5 50.0 25.0 12.5 0.0 100.0
Table 6A.Distribution of education attainment by age in Lodhran
Education attainment
Age
categories Illiterate
Up to
Primary Middle Metric
Higher
secondary
Graduation
and above Total
≤ 20 0.0 60.0 40.0 0.0 0.0 0.0 100.0
21-30 14.5 37.1 25.8 9.7 3.2 9.7 100.0
31-40 36.4 27.3 22.7 2.3 4.5 6.8 100.0
41-50 36.1 38.9 5.6 16.7 2.8 0.0 100.0
51-60 23.8 28.6 14.3 9.5 14.3 9.5 100.0
61+ 0.0 0.0 0.0 100.0 0.0 0.0 100.0
175
Table 7A.WHO Hazard Classification of pesticides
Pesticide Class
LD50 for the rat (mg/kg body weight)
Oral
Solids Liquids
Ia (extremely hazardous) 5 or less 20 or less
Ib (highly hazardous) 5-50 20-200
II (moderately hazardous) 50-500 200-2000
III (slightly hazardous) 500-2000 2000-3000
IV (unlikely if used safely) Over 2000 Over 3000
WHO recommended classification of pesticide by hazard and guidelines to classification 2004.
Source: Murphy .H (2002) & WHO (2006)
Table 8A. Pesticide use by WHO hazard classification by district
Category
Lodhran Vehari
Amount(kg
A.I) %
Amount(kg
A.I) %
Extremely hazardous (Ia)
0.0 0.0 0.0 0.0
Highly hazardous (Ib) 615.5 24.1 522.2502 22.5
Moderately hazardous
(II) 1394.3 54.5 1271.682 54.9
Slightly hazardous (III) 455.9 17.8 422.5585 18.2
Unlikely (U) 92.7 3.6 100.412 4.3
Total 2558.5 100.0 2316.9027 100
Table 9A.Crop wise pesticide use by WHO hazard classification in Vehari (%)
Crops Highly
hazardous
Moderately
hazardous
Slightly
hazardous Unlikely (U)
Cotton 23.1 69.0 6.0 1.9
Vegetables 29.0 37.4 17.6 16.0
Wheat 2.7 20.2 77 0.1
Others 57.0 28 5.9 9.1
176
Table 10A. Crop wise pesticide use by WHO hazard classification in
Lodhran (%)
Crops Highly
hazardous
Moderately
hazardous
Slightly
hazardous Unlikely (U)
Cotton 22 64.9 10.1 5
Vegetables 40.5 32.2 19.6 7.7
Wheat 2.1 6.7 90.3 0.9
Others 47.8 35.5 5.6 10.3
Table 11A.WHO Category wise pesticide use on cotton by farm size (%)
Farm size Extremely
hazardous
Moderately
Hazardous
Slightly
Hazardous Unlikely
0.1- 2.5 28 53 19 0
2.6- 5.0 32 56 10 2
5.1- 10 22 63 13 2
10.1-25 18 66 11 5
25.1-50 33 59 8 0
50.1-100 22 71 7 0
100+ 25 69 6 0
Table 12A. WHO Category wise pesticide use on wheat by farm size (%)
Farm size Extremely
hazardous
Moderately
Hazardous
Slightly
hazardous Unlikely
0.1- 2.5 29 40 31 0
2.6- 5.0 22 37 41 0
5.1- 10 19 43 38 0
10.1-25 19 33 35 13
25.1-50 41 26 33 0
50.1-100 19 42 24 15
100+ 0 33 43 24
177
Table 13A.WHO Category wise Pesticide use on vegetables by farm size (%)
Farm size Extremely
hazardous
Moderately
hazardous
Slightly
hazardous Unlikely
0.1- 2.5 50 50 0 0
2.6- 5.0 12 38 28 22
5.1- 10 21 23 28 28
10.1-25 12 53 32 3
25.1-50 24 46 21 9
50.1-100 10 40 48 2
100+ 11 57 32 0
Table 14A. WHO Category wise pesticide use on other crops by farm size (%)
Farm size Extremely
hazardous
Moderately
hazardous
Slightly
hazardous Unlikely
0.1- 2.5 0 10 90 0
2.6- 5.0 0 20 5 75
5.1- 10 30 15 25 30
10.1-25 61 25 11 3
25.1-50 0 76 24 0
50.1-100 0 100 0 0
100+ 0 0 0 0
Table 15A.Amount of pesticide used (Kg/per acre) by farm size
Farm size Cotton Wheat Vegetables Others
0.1- 2.5 11.76 1.5 6.9 2.7
2.6- 5.0 9.5 1.45 7.3 0.8
5.1- 10 10.5 1.2 8.1 3.1
10.1-25 9.75 1.8 8.4 3.6
25.1-50 10 1.65 6.5 2.6
50.1-100 11.5 1.3 7.1 0.6
100+ 12 1.6 6.3 0
178
Table 16A. Distribution of income by age group
Income
Age (years) Rs= up to 10000
Rs=10001-20000
Rs> 20000 Total group
≤ 20 2.8 1.3 0.0 4.1
21-30 18.2 12.6 4.4 35.2 31-40 18.9 7.2 4.1 30.2
41-50 10.1 8.8 2.2 21.1
51-60 3.5 4.4 1.3 9.1 61+ 0.0 0.3 0.0 0.3
Total 53.5 34.6 11.9 100.0
Table 17A.Main source of information for farmers in study area Read the labels on the bottle/package and follow the Instructions (if you cannot read, please get help from
others who can read).
Agric ministry
(11% )
Sales person/companies
(37% )
Others
(41% )
Never heard
(9% )
Do not mix pesticide with bare Hands. While mixing, wear hand gloves and glasses/eye shield.
7% 50% 23% 16%
Mix them with a stick.
7% 50% 23% 16%
While cleaning the sprayer’s nozzle do not place your mouth on it or blow on it.
6% 36% 28% 22%
Before s praying pesticide take all protective measures such as wearing hand gloves, head cover; face shield,
full sleeve shirt/kurta, full length trousers /shalwar, and shoes.
7% 56% 16% 17%
Do not spray pesticide against the wind. Determine wind direction first and then s pray.
7% 57% 36% 0%
Do not eat or drink while s praying pesticide.
7% 57% 29% 4%
Do not smoke while spraying pesticide. The reaction may be toxic or even fatal.
7% 57% 29% 4%
Do not wash pesticide bottle or pesticide sprayer in the Pond/canal.
7% 17% 30% 35%
Wash and clean the sprayer and your clothes at a far distance from the pond.
7% 11% 25% 46%
After applying the pesticide on your field, dis play a signboard or an empty pesticide bottle, so that
everybody sees and understands that you s prayed pesticide on that field.
3% 1% 4% 88%
Do not keep other things in the pesticide bottle or package.
179
7% 57% 29% 5%
Tear up the pesticide package into pieces and bury them under the ground.
5% 3% 11% 79%
Keep pesticide under lock so that they are out of the reach of children.
7% 56% 28% 4%
Do not keep pesticide where you keep other things.
7% 56% 28% 4%
In the event of an accident, provide first aid to the patient, Following the instructions on the label of that
particular pesticide bottle. Take the patient and the pesticide Bottle to the doctor as soon as possible.
7% 3% 10% 77%
Keep the children and domestic cattle and poultry birds out of the immediate area.
9% 33% 40% 18%
Note: The four columns under every informat ion row represent different sources of informat ion in
percentages. The first column indicate % informat ion received from agricu lture extension, second
showing % information received from sales person/pesticide company, third column represents %
informat ion received from other sources(i.e. NGOs, relatives, fellow farmers, neighbors, public media and
self), last column shows % of farmers who did not received any information regarding above stated
informat ion.
Table 18A. Use of IPM by method
IPM Methods No. of farmers
Decreased dosage 12
Change with less toxic pesticide 17
Decreased no. of applications 30
Manual clearing 30
Enemy plants 9
Crop rotation 21
Variation in sowing and harvesting time 2
Biological methods 30
Other measures of IPM. 29
Table 19A.Percentage of farmers who follow instructions on pesticide labels
by level of education
Education level Both districts Vehari Lodhran
Illiterate 5.0 5.0 5.0
Primary 16.0 18.0 14.0
Middle 10.0 11.0 8.0
Matric 14.0 19.0 9.0
Higher secondary 51.0 48.0 53.0
Graduate 60.0 65.0 54.0
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Table 20A.Descriptive statistics of important variables (district Lodhran)
Variables Minimum Maximum Mean Std. Deviation
Perception 1 5 2.6 1.1
Health effect 0 1 0.9 0.3
Training 0 1 0.1 0.4
Age 15 66 32.3 9.8
Income 6 70 16.2 9.4
Education 0 16 5.6 4.3
IPM 0 1 0.1 0.4
Farm size 1 175 14.5 25.2
Table 21A.Descriptive statistics of important variables (district Vehari)
Variable Minimum Maximum Mean Std. Deviation
Education 0.0 16.0 5.9 4.3
Age 18.0 60.0 34.2 10.4
Income 5.0 60.0 18.0 9.2
Perception 1 5 2.9 1.1
Health effect 0 1 0.8 0.4
Training 0 1 0.1 0.3
Farm size 1.0 110 13.5 16.4
IPM 0.0 1.0 0.1 0.3
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Table 22A: Name of the districts and share of total area under cotton in Punjab province
District’s Name Area under
cotton crop
(In acres)
% Of Total Area
under cotton in Punjab province108
Number of
associated H.Hs* with
farming in each district
Rahim Yar Khan 798518 13.3 191024
BahawalPur 623173 10.3 149636
Bahawalnagar 473048 7.0 139640
Vehari 561312 10.0 119752
Pakpatan 49895 1.0 79305
Toba Tek Sing 111670 2.0 84011
Sahiwal 214171 3.5 99780
Khaniwal 498457 8.0 119363
Lodhran 444177 7.5 77667
Multan 418568 7.0 103515
Muzaffargarh 632236 11.0 205964
Total 2319279 82 1369657
Source: Agriculture census 2000, procedure & data tables Punjab, Government of Pakistan statistics
division Agricultural census organization Lahore. * H.Hs stands for households
108
% o f total area under cotton in Punjab is calculated by the formula= area under cotton crop in each
District/ Total area under cotton crop in Punjab province
182
Table 23A. List of sample villages used for survey
S.No. Name of village
No. of
respondent
interviewed
Tehsil District
1 HARI CHAND 16 MAILSI WAHARI
2 ALAM PURA 13 MAILSI WAHARI
3 MAZA GHAUSE 16 MAILSI WAHARI
4 QAZI QALDA 10 MAILSI WAHARI
5 CHACK-204/E-B 20 BOREWALA WAHARI
6 CHAK 255-EB 23 BOREWALA WAHARI
7 CHAK 203-EB 9 BOREWALA WAHARI
8 CHACK 547 EB 17 WAHARI WAHARI
9 MOZA GHAFFOR
WAH 9
WAHARI WAHARI
10 CHACK 248/E-B 7 WAHARI WAHARI
11 CHACK 249/E-B 9 WAHARI WAHARI
12 MASTA CHOWKI 5 PAKA KRORE LODHARAN
13 CHANAN WALA 7 PAKA KRORE LODHARAN
14 CAIAN WALA 18 PAKA KRORE LODHARAN
15 CHORIAN WALA 8 PAKA KRORE LODHARAN
16 DABE WALA 4 PAKA KRORE LODHARAN
17 BAGHAR WALA 7 PAKA KRORE LODHARAN
18 MERAN PUR 8 DUNIA PUR LODHARAN
19 CHACK 360/W-B 9 DUNIA PUR LODHARAN
20 CHAK No 366/W-B 5 DUNIA PUR LODHARAN
21 KHOOH BUKSH WALID MOZA BASTI BOHARH
5 DUNIA PUR
LODHARAN
22 WAHID BUKSH
KOTLY BAJWAH 7
DUNIA PUR
LODHARAN
23 CHAK 361/W-b 13 DUNIA PUR LODHARAN
24 CHAK No 372/W-B 7 DUNIA PUR LODHARAN
25 CHAK No 365/W-B 12 DUNIA PUR LODHARAN
26 KALO WALA 10 LODHARAN LODHARAN
27 MOZA KOT HAGI 11 LODHARAN LODHARAN
28 MOZA WAHI
SALLAMAT RAY 9
LODHARAN LODHARAN
29 PIPLI WALA 16 LODHARAN LODHARAN
30 MOZA SALSADAR 8 LODHARAN LODHARAN
183
Table 24A. Area, production and per hectare yield of major cotton producing countries (2005-2006)
Countries Area (000 hectares) Prod. (000 tonnes) Yield (kgs/ hectare)
China 5060 17100 3379
U.S.A 5586 12876 2305
India 8826 7500 850
Pakistan 3193 7279 714
Brazil 1254 3727 2972
Uzbekistan 1390 3770 2712
Turkey 600 2290 3817
Turkmenistan 600 1000 1667
Australia 335 1397 4170
Greece 365 1232 3375
Syria 218 1024 4697
Egypt 315 820 2603 Source: Agricultural statistics of Pakistan, Ministry of Food & Agriculture (2008), Government of
Pakistan, Islamabad.
Table 25A.Area, production and per hectare yield of major rice producing countries (2005-2006)
Countries Area (000 hectares) Prod. (000 tonnes) Yield (kgs/ hectare)
China 29030 181900 6266
India 43400 130513 3007
Indonesia 11801 53985 4575
Bangladesh 11100 41104 3703
Viet Nam 7339 36341 4952
Thailand 10200 27000 2647
Myanmar 6270 24500 3907
Philippines 4000 14615 3654
Brazil 3936 13141 3339
Japan 1706 11342 6648
U.S.A 1361 10126 7440
Pakistan 2520 7538 2991
Republic of Korea 980 6435 6566
Egypt 650 6200 9538 Source: Agricultural statistics of Pakistan, Ministry of Food & Agriculture (2008), Government of
Pakistan, Islamabad
184
Table 26A. Area, production and per hectare yield of major sugarcane producing countries (2005-2006)
Countries Area (000 hectares) Prod. (000 tonnes) Yield (kgs/ hectare)
Egypt 135 232320 121000
Brazil 5767 420121 72849
China 1326 87600 66063
Pakistan 966 47244 48907
Mexico 645 45195 70070
Colombia 432 39849 92243
Australia 441 37485 85000
Philippines 380 31000 81579
U.S.A 374 24751 66179
Indonesia 360 29300 81389
Argentina 305 19300 63279
South Africa 312 21725 69631
Guatemala 190 18500 97368
India 3750 15000 61952 Source: Agricultural statistics of Pakistan, Ministry of Food & Agriculture (2008), Government of
Pakistan, Islamabad
Table 27A.Area, production and per hectare yield of major wheat producing
countries (2005-2006)
Countries Area (000 hectares) Prod. (000 tonnes) Yield (kgs/ hectare)
China 22950 97000 4227
India 26500 72000 2717
U.S.A 20283 57280 2824
Russia 23045 47608 2066
France 5281 36878 6983
Germany 3174 23693 7465
Pakistan 8358 21612 2586 Source: Agricultural statistics of Pakistan, Ministry of Food & Agriculture (2008), Government of
Pakistan, Islamabad
185
Appendix III: Pesticide Legislation in Pakistan
Agricultural Pesticide Ordinance 1971
Agricultural pesticide Ordinance (APO) 1971 was issued on 25th January, 1971.
The main objective of APO was to regulate and monitor import, manufacture, sale/
distribution and use of pesticide in the country. Over time, the ordinance was amended
by issuing Acts in different years up to 2005 in order to make this ordinance compatible
with the modern day requirements.
The ordinance provided provision for the constitution of the Agricultural
Pesticide Technical Advisory Committee (APTAC) to direct the Government on
technical matters arising out of administration of this ordinance and to execute any other
role assigned to it by or under this ordinance. The APTAC is authorized to appoint sub-
committee consisting of specialists/experts for the consideration of particular matters as
it may consider necessary.
The APO also provided a provision for establishment of pesticide laboratory at
Federal or Provincial level to carry out the functions e.g. analysis of pesticide to ensure
their originality and specification. Government experts are provided authority for
checking the pesticide samples in the laboratory. The provision of Inspectors is also
given under this ordinance. Any Inspector is authorized within the specified local limits
for which he is appointed, to enter upon any premises where pesticide are stored, no
matter whether these pesticide are in containers or in bulk and take samples from for
examination. The APO also announces penalties for the offences and other
misappropriations.
186
The Agricultural Pesticide Rules, 1973
The Agricultural Pesticide Rules (APR), 1973 provides powers to the
Government to make rules in consultation with Agricultural Pesticide Technical
Advisory Committee (APTAC) for carrying out the provisions of this ordinance.
Pesticide Ordinance 2005
Under Pesticide Ordinance 2005, import, export, manufacture, formulation, sale,
distribution and use of pesticide are as follow:
1. Registration of Pesticide: No person shall import, manufacture,
formulate, repackage, holds in stock for sale or advertise any pesticide which has
not been registered in the prescribed manner. Any person intending to import,
manufacture, formulate, repackage, hold in stock for sale or advertise any
pesticide, may apply to the department for registration of the pesticide under
identified trade mark. It must also satisfy the department that the pesticide is
effective for the purpose for which it is claimed to be effective and that the
pesticide is not generally detrimental/ injurious to environment, human or animal
health when applied according to directions. Further, the pesticide must not
belong to formulations banned in Pakistan.
2. Cancellation of registration: If at any time after the registration of a
pesticide, the Federal Government is of the opinion that the registered pesticide
is leading to violation of the provision of this Act, the Director General may,
after giving an opportunity of being heard, cancel the registration with intimation
to the Federal Government.
187
3. Export: A pesticide registered in Pakistan, can be exported subject to
intimation to the department in the prescribed form and in conformity with any
other law and any relevant international convention or protocol for the time
being in force.
4. Renewal of registration of a pesticide: If a person who holds a previous
registration certificate desires that the registration of a pesticide be renewed, the
Federal Government may under this Act renew the registration for a further
period of three years, provided that no change has taken place in the ingredients
of that pesticide.
5. Testing at port of entry and exit: Every consignment of any pesticide
imported into or exported from Pakistan shall be invariably tested by the
Government Analyst and if found to be adulterated or sub-standard, incorrectly
or misleadingly tagged, the Federal Government may disallow the import or
export of such pesticide and may also cancel the registration of such pesticide.
6. Labeling: No person shall import, sell or advertise unless package
containing the pesticide is marked in printed characters in such manner as may
be prescribed. Certification of distributor or dealer who fails to maintain
prescribed requirements shall be cancelled.
7. Regulation of use: No person shall use any pesticide in violation of the
rules made under this Act.
188
8. Regulation of manufacture, formulation and repackaging: No
person shall engage in the manufacture, formulation, repackaging of a pesticide
including that of intermediates, without obtaining prior certification from the
department.
9. Renewal of certification of manufacturing, formulation or repacking
plant: The Federal Government may, upon application of the expiry of the
certification of a plant, renew the certification for a further period of five years.
189
Appendix IV: Districts profiles
District Vehari
Geography: Vehari109 is a district in the Punjab province of Pakistan. It is known as
city of cotton, is located at 30°1'60N 72°20'60E at an altitude of 135m (446ft). The total
area of the district is 4,364 square kilometers. It is about 93 kilometers in length and
approximately 47 kilometers in breadth. It borders with Bahawalnagar and Bahawalpur
on the southern side, with Pakpatan on the eastern, with Khanewal and Lodhran on
western and with Sahiwal and Khanewal on northern side. It lies about 100 kilometers
from the regional metropolis of Multan and about 25 kilometers north of the river
Satluj110. The district of Vehari is administratively subdivided into three tehsils, Mailsi,
Burewala and Vehari.
Weather: Like other districts of Southern Punjab, the summer in Vehari is very hot.
The summer season starts from April and continues until October. May, June, and July
are the hottest months in the district. The mean maximum and minimum temperatures
for these months are about 47 and 28 degrees Celsius. During summer dry, hot and dusty
winds are common in the district. The winter season lasts from November to March.
December, January and February are the coldest months. The mean maximum and
minimum temperatures for this period are about 22 and 4 °C. Fog is very common
during winter. In most parts of the district rain falls during the monsoon season from
109
The name Vehari means low lying settlement by a flood water channel. The district lies along the right
bank of the river Sutlej which forms its southern boundary. Information regarding district Vehari obtained
from Wikipedia. For further information and detail
During winter, the temperature fluctuates between 21C0 and 5C0. The entire district is
smooth plain. The average rainfall in the district is 71 millimeters.
Population and Culture: According to Population Census (1998) the total
population of the district is 1171800 (Density 422/ km²). The main languages are Saraiki
and Urdu. The native populations of the district are the Rajput, Kanjo, Dogar, Baloch
and Arain. Joint family system is common and usually all the members of the family live
in the same house. In few cases where they do not, the mutual economic and
interdependent relationship remains the principal cohesive factor among them.
193
Appendix V: Description of variables in empirical models
The number and type of variables to be included in a pesticide use model vary
depends on the objectives and hypotheses being tested, and the limitations imposed by
the data availability (Ajayi, 2000).
Table. Description of variables included in the empirical models
Variables Description
Environmentally sound
behavior (IPM)
Dichotomous variable represents whether or not farmer
use any IPM. 1 = Yes, 0 = No
Farm size Acres of land cultivated
Risk perception Farmer‘s perceived risk associated with pesticide use.
5=extremely high , 1= No risk at all
Education Number of years of formal schooling, categorized as 1= illiterate, 7= graduates and above
Training Dummy variable represents whether farmer got
training of pesticide use or not. 1 = Yes, 0 = No
Age Age of pesticide applicator in years
Income Farmer‘s monthly income in rupees
Geographical area District dummy, 0=Lodhran, 1=Vehari
Health effects Whether farmer experienced health problem or not? 1 = Yes, 0 = No
Willingness to pay Farmer‘s Willingness to pay to avoid health risk, 1= Not willing to pay, 5= willing to pay over and above 20 percent premium.
Risk perception: This variable measures whether or not farmers perceive pesticide a
potential danger to their health, particularly when mixing and applying pesticide. It is
very important in the course of behavior change since it motivates individuals to adopt
measures to protect themselves from negative environmental conditions. Risk perception
is specified as no risk at all=1 to very high risk=5. In defining the variable, the study
follows a similar method used by Lichtenberg and Zimmerman (1999). For empirical
model, risk perception is specified as dependent variable. The health experience, age,
194
education, training, income and geographical area are specified as independent variables.
The model thus controls for farm operator and farm characteristics that may influence
health experience in order to isolate the effects of health experience on attitudes.
Health effects: As farmers mix and spray pesticide, they are naturally exposed to the
toxicity of the chemicals. Exposure to pesticide can lead to number of health effects,
depending on the pesticide‘s toxicity and the dose absorbed by the body (Dasgupta,
2005a). Health effects variable is very important in the course of behavior change. It
heightens risk perception which ultimately motivates individuals to take protective
measures to minimize health risk. Health effect is specified as whether or not farmers
experienced negative health effects during or short after mixing or spraying operations.
The health effects of pesticide exposure are manifested as specific symptoms or a
combination of multiple symptoms. Building on WHO information as well as earlier
studies, 10 types of symptoms were first identified. The question was also left open to
include others if reported (any). The study focuses on acute health effects, as a detailed
medical examination of sample farmers was beyond the scope of this study. Study relied
on self-reported health effects, where farmers were questioned if they experienced any
health impairment after mixing and spraying pesticide. Following Dasgupta (2005a), the
health effects variable is defined as whether a farmer experienced at least one symptom
(=1) or not (=0). Given the results of previous studies and theoretical background health
effects is expected to have a positive relationship with risk perception, protective
behavior and alternative pest management practices.
IPM: The IPM variable is very important in the present context since this study makes
an explicit link between illness experiences and coping strategies. It measures whether
195
or not farmers adopt alternative pest management technique such as integrated pest
management which is supposed to environmentally sound. It is worth knowing that IPM
focuses on the adoption of various pest management practices regarded as
environmentally sound/beneficial and either substituting for or supplementing pesticide
use while not necessarily eliminating pesticide use.
Education: Education is expected to have positive impact on coping behavior. The
more educated people are expected to rank higher risk perception and subsequently
adopting IPM practices owing to better awareness. For the purpose of analysis, the
respondents were grouped into seven groups based on the education level— from 1=
illiterate, 2= 1 year of schooling up to 4 years, 3=from 5 years up to the 7 year s, 4= 8
years up to 9 years of schooling, 5= 10 years up to 11 years, 6=12 years up to 13 years
and 7= 14 years and above.
Income: Income is the total monetary equivalence of all expenditures made by the
household in the farm of cash plus total value of household grown agriculture products
kept for household‘s consumption during a month. The household grown products also
includes livestock‘s produced dairy products. Household were also asked about
variations in income during different seasons. 113 The income is defined in rupees and is
expected to impact risk perception, protective behavior and IPM positively. It is based
on the reasoning that high income individuals are more likely better aware and better
informed and can afford protective measures.
113
Based on the understanding that livestock generates products like milk, eggs and the like items are not
always same throughout the year. Similar reasoning holds for agricultural products like fruits and
vegetables.
196
Age: This variable represents farmers‘ age and is used as a proxy for farmer‘s
experience and management capacity of pesticide operations. Compared to youth, adult
are also assumed to be more caring. Given that farming is the major vocation in the
study area and most of the individuals are introduced to farming as early as their youth,
it is assumed that their age will better reflect pesticide hazard (Ajayi, 2000). As prior
expectation age is positively related to risk perception, protective behavior and IPM.
Training: Training is also a variable of interest. An individual usually undertake
training with the ultimate goal to avoid pesticide exposure. A trained farmer being better
informed is expected to perceive more risk and engage in better management practices.
The training variable is defined as whether a farmer got training of safe handling of
pesticide (=1) or not (=0)?
Farm size: Farm size is also included in the model to see the possible differences in
attitudes regarding pesticide use among small and large land holders. Based on the prior
evidences (pesticide use survey, 2002; Jeyaratnam, 1990; Forget, 1991) which states that
agriculture extension services often limited to big landholders, farm size is assumed to
be positive to risk perception and alternative pest management practices. Additionally,
farm size is taken as the proxy of duration of pesticide exposure, since larger the farm
size, higher the likelihood that farmers spend additional hours in spraying/farming
activities. Therefore, carrying higher probability of being exposed to pesticide.
Willingness to pay: Farmers were also asked about their willingness to pay for safe
alternatives like IPM. The amount was classified into categories, 1= Not willing to pay,
2= willing to pay from 1 percent up to 5 percent premium, 3= willing to pay up to 6
percent to 10 percent premium, 4= willing to pay up to 11 percent to 20 percent
197
premium, 5= willing to pay over and above 20 percent premium. From policy
perspective this variable is very important. If farmers have positive willingness to pay
for avoiding pesticide related health risks. It provides strong motivation for policy
makers to continue research on IPM and its implementation which is very limited in the
area.
198
Appendix VI : Survey Questionnaire
My name is_________ and I am from federal Urdu university of
Arts, Science & technology Islamabad. The purpose of this questionnaire is to investigate the use of pesticide by farmers, and the health &Environmental effects of pesticide use. It is for research purposes only. Please answer the questions to be best of your knowledge. Answers will be kept completely confidential and will only be presented in a summary format.
Do you agree to participate in this survey? 1. Yes 2. No
If yes, continue the survey Time started: ________________
2. 1 to less than 2.5 acre 7. 25 to less than 50 acres
3. 2.5 to less than 5 acres 8. 50 to 100 acres
4. 5 to less than 7.5 acres 9. More than 100 acres
5. 7.5 to less than 10 acres
Part 2: Personal General Information
B.1 Gender of the respondent
1. Male 2. Female B.2 Age of the respondent Years __________
B.3 How many people, including yourself, lives in your immediate household? (A household is defined to comprise all usual residents, where they sleep and share
common facilities) # of persons__________). B.4 what is the total monthly (cash) expenditure of the household? ______________ B.4.a What is the approximate value of all household grown products used only for
household consumption (use additional sheet if required)?
Product name Quantity (kg)
Price Product name
Quantity (kg)
Price
B.6 what is the highest level of education you have completed (in case not decision maker, please, also complete second row)?
Household‘s Education
Illiterate Under-
primary
Primary Middle Secondary Higher
Secondary
Graduation
& above
1.
Respondent
2. Head or decision
maker
Note; 1. Illiterate (can‘t read or write); 2. Under- primary (1-4 years of schooling; 3. Primary (5 years of
schooling); 4. Middle (6-8 years of schooling); 5. Secondary (9-10 years of schooling); 6. Higher
Secondary (12 years of schooling); 7. Graduation and above (14 years and above schooling)
200
Part 3: Pesticide Application
C.1 How long have you been applying pesticide? _____ Months ____ years. C.2 Do you mix different brands of pesticide before application?
1. Yes 2. No (if no, please go to C.2.b) C.2.a If yes, please specify the brand and mixture you use for each crop (use additional
sheet it required).
Crop name
No. of application/
Spray
Brand Name
Amount You mix
Prescribed Quantity
Price
1
2
3
4
5
6
7
8
9
10
11
12
13
14
C.2.a.1 What is the main reason why you mix the pesticide this way?
Please specify)__________________________
C.2.b If you use single brand, please specify the brand and quantity for each crop.
Crop name
No. of application/
Spray
Brand Name
Amount You mix
Prescribed Quantity
Price
1 2
3 4
5 6
7 8
9
10
201
C.3. Has the use of pesticides increased over the years? 1. Yes 2. No
C.3.a if yes, please give reason?
1. everybody else increased
2. Pesticide supplier said so 3. Pesticides are not effective
4. to make sure that it worked 5. I do not know
6. Other_________________ (please specify)
C.4 on a scale of 1-5, how much risk do you think you are exposed to while using
pesticide on this farm?
No risk at all
some small risks
A medium amount of risk
A large and significant amount of risk
Very toxic risks
C.5 Do you also use alternative pest management methods to control pest?
1. Yes 2. No (if no, please go to D.7.b)
C.5.a If yes, which method you use to reduce dependence on pesticide
Methods Please explain
Decreased dosage
Decreased no. of applications Change with less toxic pesticide Manual clearing Light traps Crop Rotation Variation in sowing and harvesting time
Enemy plants Biological methods Other measures of IPM.
e.g_______________
C.5.b If no, why you did not adopt any measure. Please specify ________________
202
Part 4 Health
The next section is related to health. Please recall the best you can about any problems that you may have experienced.
D.1 Have you ever had any of the following symptoms after applying pesticide
during the last year?
1. Eye irritation 6. Fever
2. Headache 7. Convulsion
3. Dizziness 8. Shortness of breath
4. Vomiting 9. Skin irritation
5. Diarrhea 10. Other (specify) ______
D.2 How sure or confident you are that the symptoms you experienced were caused
by exposure to pesticide?
1. Not sure 2. Little
3. Rather 4. Very
5. Extremely 6. I don‘t know
D.3 Did you visit doctor?
1. Yes 2. No D.3.a. If yes what did he diagnose (code of disease*114)?
Convelsion; 8. Shortness of breath; 9. skin irritation; 10. Others
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4. ________ 9. ________ 5. ________ 10. ________
D.5 How many days you spent in bed because of illness? _________
D.6 Do you think that pesticide use and/or exposure, overall, has any negative short-
term and long-term impacts on health?
1 2 3 4 5 6
No effect
Little effect
Some effects Large effects
Fatal effects I don't know
Part 5: Protection and safety
E.1 Have you ever-received basic training on safe handling and applying pesticide?
1. Yes 2. No
E.1.a if yes from where you got this training?________________________ E.1.b If no basic training, do you have access to someone who provides such training?
1. Yes 2. No E.1.b.1 If YES, who? ____________________________
E.2 when purchasing pesticide, are you usually supplied with information on the
pesticide, such as pamphlets or instructions, describing safety issues.
1. Yes 2. No
E.2.a If YES, do you read and follow the instructions in the pamphlets?
1. Yes 2. No
E.3 what do you typically wear while applying pesticide?
Protective
measures
Use Reason if protective measures not used
Costly Not available Unnecessary uneasy Others
Boot 1. yes
2. no
Hat 1. yes
2. no
Shirt/qamis 1. yes
2. no
Gloves 1. yes
2. no
Eye glasses 1. yes
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/goggles 2. no
Shalwar/lungi 1. yes
2. no
Mask 1. yes
2. no
others 1. yes
2. no
E.4 Do you take a bath right after spraying?
1. Yes
2. No (If no, why ____________________________) E.5 Do you change clothes right after spraying?
1. Yes
2. No (If no, why ___________________________)
E.6 How long is it after application before you re-enter the field? __ Hours __Days E.7 when you mix/use pesticide, does the liquid come into contact with any part of
your body?
1. Yes 2. No
E.7.a If YES, which part?
1. Hands 2. Feet
3. other part (Please specify) ____________
E.8 Please indicate the main source of the following instructions that you may have
received, and also tell, do you follow these instructions.
Instructions Information Source
Do you follow
If no, please explain why?
Read the labels on the
bottle/package and follow the Instructions.
1
2
3
4
5
YES
NO
Do not mix pesticides with bare Hands.
1
2
3
4
5
YES
NO
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Mix pesticides with a stick. While mixing, wear hand gloves and eye shield.
1
2
3
4
5
YES
NO
While cleaning the sprayer‘s nozzle do not place your mouth on it or
blow on it.
1
2
3
4
5
YES
NO
Before spraying pesticide take all
protective measures such as wearing hand gloves, head cover;
face shield, full sleeve shirt/kurta, full length trousers/shalwar, and shoes.
1
2
3
4
5
YES
NO
Do not spray pesticide against the wind. Determine wind direction
first and then spray.
1
2
3
4
5
YES
NO
Do not eat or drink while spraying
pesticide. 1
2
3
4
5
YES
NO
Do not smoke while spraying pesticide. The reaction may be toxic or even fatal.
1
2
3
4
5
YES
NO
Do not wash pesticide bottle or pesticide sprayer in the pond or
canal.
1
2
3
4
5
YES
NO
Pesticide from the bottle or Sprayer
will contaminate the water of the 1
2
YES
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pond or canal and will be deadly for the fish, cattle, birds and people.
3
4
5
NO
Wash and clean the sprayer and your clothes at a far distance from
the pond.
1
2
3
4
5
YES
NO
After applying the pesticide on your
field, display a signboard or an empty pesticide bottle, so that everybody sees and understands
that you sprayed pesticide on that field.
1
2
3
4
5
YES
NO
Do not keep other things in the pesticide bottle or package.
1
2
3
4
5
YES
NO
Tear up the pesticide package into pieces and bury them under the ground.
1
2
3
4
5
YES
NO
Keep pesticide under lock so that
they are out of the reach of children. 1
2
3
4
5
YES
NO
Do not keep pesticide where you keep other things.
1
2
3
4
5
YES
NO
In the event of an accident, provide
first aid to the patient, following the instructions on the label of that particular pesticide bottle. Take the
patient and the pesticide
1
2
3
4
YES
NO
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Bottle to the doctor as soon as possible.
5
Keep the children and domestic
cattle and poultry birds out of the immediate area.
1
2
3
4
5
YES
NO
Agri. Ministry Official=1, Pesticide Suppliers=2, NGOs =3, others =4, Never heard this
before=5
Part 6: Environment F.1 Have you ever heard or witnessed any of the pesticide-related accidents below in your
local area?
1 Water contamination, please describe _______________________
2 Air contamination, please describe _________________________
3 Death of fish, frogs, birds, bees, please describe ___________________
Part 7: Willingness to pay Now we are going to ask you a question about alternative pest management. Suppose that you were able to have access to a pesticide that was just as effective as the one(s) you are using now, but it d id not have any short-term or long-term
negative health effects. Thinking about the health effects you have experienced or observed with your current use of pesticides, how much would you be willing
to pay for the use of safer pesticide? (Note also that it will reduce your income for other purposes) __________________%
THANK YOU FOR CO-OPERATION TIME FINISHED_________________