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International Journal of Pest Management
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/ttpm20
Assessment of pesticide exposure risks among
cocoa farmers in Western region of Ghana
Michael K. Miyittah, Boatemaa Ansah, Moses Kwadzo, Salifu Seidu-Larry &
Richard K. Kosivi
To cite this article: Michael K. Miyittah, Boatemaa Ansah, Moses Kwadzo, Salifu Seidu-
Larry & Richard K. Kosivi (2022): Assessment of pesticide exposure risks among cocoa
farmers in Western region of Ghana, International Journal of Pest Management, DOI:
10.1080/09670874.2022.2084175
To link to this article: https://doi.org/10.1080/09670874.2022.2084175
© 2022 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
Published online: 08 Jun 2022.
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INTERNATIONAL JOURNAL OF PEST MANAGEMENT
Assessment of pesticide exposure risks among cocoa farmers in
Western region of Ghana
Michael K. Miyittaha , Boatemaa Ansaha, Moses Kwadzob, Salifu Seidu-Larryc and Richard K.
Kosivia
aDepartment of Environmental Sciences, University of Cape Coast, Cape Coast, Ghana; bDepartment of Agricultural Economics
and Extension, University of Cape Coast, Cape Coast, Ghana; cDepartment of Biochemistry, University of Cape Coast, Cape Coast,
Ghana
ABSTRACT
A survey was conducted to investigate farmers’ knowledge, attitudes towards pesticide use,
storage/disposal, exposure risks and health symptoms in one of the eight cocoa growing
regions in Ghana. A considerable proportion of the farmers (32%) used the bush as a storage
facility for pesticides, 17% of the farmers stored chemicals in their living rooms, 3% of the
farmers stored chemicals in their kitchen, 15% in their food storeroom, and 4% in the animal
house. Personal protective equipment (PPE) use was positively associated with advice obtained
from agrochemical shops (OR = 1.735, p < 0.01) and extension services (OR = 1.643, p < 0.01)
as sources of information for PPE use. Female farmers (OR = 0.481, p < 0.01) were less likely
to use PPE. With respect to location, farmers in Suaman district were less likely to use PPE
(OR = 0.56, p < 0.010) compared with farmers in Wassa Amenfi. It is recommended that these
factors should be considered for policy intervention. Reinforcement of appropriate pesticide
storage and PPE education are necessary for securing safety in pesticide use.
1. Introduction
Cocoa is an international crop supplied by Ghana
and Ivory Coast providing over 60% of the cocoa
beans to the global chocolate industry (Wessel and
Quist-Wessel 2015). The cocoa sector represents
more than half (from 70 up to 100%) of the income
for roughly 800,000 smallholder farmers families in
Ghana, providing food, employment, tax revenue
and foreign exchange earnings for Ghana
(Anim-Kwapong and Frimpong 2004; Dormon et al.
2004). Despite the economic importance of cocoa,
its production in Ghana is threatened by pests and
diseases, a situation that reduced cocoa production,
with adverse impact on the Ghanaian economy
(Dormon et al. 2004). The low productivity phenom-
enon is aggravated by the climate change impacts.
Läderach et al. (2013) predicted low productivity in
spatially differentiated cocoa growing areas of Ghana
and Ivory Coast. These predicted potential effects
are already observed in Ghana, where higher pro-
ductive region for cocoa shifted from Ashanti Region
to Western Region (Ghana COCOBOD 2019).
In order to boost cocoa productivity, farmers
adopted pesticide use to control pests and diseases,
thus increasing yield and maintaining quality.
However, the use of pesticides in agriculture, and
for that matter the cocoa industry in Ghana, has
raised serious concerns about the safety of pesticide
residues in cocoa beans, soils and water, as well as
factors causing potential exposure to humans
(Adeogun and Agbongiarhuoyi 2006; Adejumo et al.
2014). In most developing countries like Ghana,
these consequences have often been severe because
farmers do not use approved pesticides and do not
follow recommended application practices as stipu-
lated by governmental agencies. Indeed, farmers
often misuse, apply pesticides indiscriminately
(Konradsen 2007; Damalas 2009; Hashemi et al.
2012; Antwi-Agyakwa et al. 2016) with disregard to
safety measures and regulations on chemical use. A
major global public health hazard about pesticides
is causing death (Bertolote et al. 2006). In develop-
ing countries, many people die annually from pes-
ticide effects through pesticide mishandling
(Konradsen et al. 2003). An estimated number of
220,000 pesticide related deaths and 3 million poi-
soning cases were reported by WHO in 1990
(Jeyaratnam 1990; Khan and Damalas 2015). Based
on the period it takes for toxicity symptoms to
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
CONTACT Michael K. Miyittah m-miyittah@ucc.edu.gh Department of Environmental Sciences, North Campus, University Avenue, Science
Building, Cape Coast, Ghana.
https://doi.org/10.1080/09670874.2022.2084175
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/
licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not
altered, transformed, or built upon in any way.
ARTICLE HISTORY
Received 6 September
2020
Revised 15 May 2022
Accepted 25 May 2022
KEYWORDS
Smallholder; cocoa;
pesticides; risk;
exposure; PPE
2 M. K. MIYITTAH ETAL.
manifest, pesticide health effect may be classified
as being acute or chronic. A situation where symp-
toms are observed within a short period of pesticide
exposure is termed acute toxicity, while long-term
symptoms are reported as chronic toxicity (Damalas
and Koutroubas 2016). Whatever the case, occupa-
tional health is a topical issue in developing coun-
tries and remains unaddressed (Nuwayhid 2004;
Khan and Damalas 2015).
The Western Region (WR) produces about 450,000
metric tonnes (avg. of the last 10 years)of cocoa and
is currently the leading producing area in Ghana
(Ghana COCOBOD 2019). In general, farmers use
pesticides extensively to control pests and diseases
and maximize crop yields. Recently, Okoffo et al.
(2016), and Paintsil (2017) studied pesticide appli-
cation among cocoa farmers, but their studies were
limited to one cocoa district within a region. In this
study, we broadened the scope by focusing on three
different cocoa districts because information regard-
ing pesticide documentation and safety practices by
cocoa farmers in the WR is limited. Unsafe pesticide
practices can lead to predictable health impacts on
farmers during pesticide application. This informa-
tion is necessary for understanding the factors influ-
encing farmers’ behaviour, pesticides exposure levels
of farmers and eventually, the mobility of pesticides
in the environment. Information on pesticides appli-
cation is important, so that policy interventions to
reduce environmental risks and human health
impacts can be developed. Also, such information
is important for analytical and environmental sci-
entists to gain insights into the socio-environmental
factors driving pesticides in the environment. The
objectives of this work were: i) to assess farmers’
knowledge of pesticides use; ii) to evaluate farmers’
attitudes in storage of pesticides and disposal prac-
tice after pesticides usage; and iii) to identify health
risk from pesticide exposure.
2. Methods
2.1. Study area and sampling procedure
The study was conducted in the WR of Ghana with
an approximate land cover of 23,921 km2, constitut-
ing about 10% of Ghana’s total surface land mass
and 10% of its population. The WR is the leading
producing area of cocoa since 1984 (Ghana
COCOBOD 2019). The region receives the highest
amount of precipitation nationwide and almost 75%
of its vegetation interspersed with the high forest
zone of Ghana (Figure 1).
For the purposes of assessing pesticides use
among farmers, data were collected through a
questionnaire in February 2018. The questionnaire
covered demographic characteristics of the farmers,
pesticide use practices, attitudes towards pesticide
use, wearing of personal protective equipment (PPE)
by cocoa farmers, and self-reported pesticide health
symptoms of farmers during pesticide applications.
The questionnaire was designed in English and then
translated into the local language of the area in case
that some farmers were uncertain of some technical
terms. Farmers with prior knowledge in pesticide
use application in the cocoa-growing communities
were sampled within the districts.
Multi-stage sampling was used to select respondents
for the study (Daniel 2012; Okoffo et al. 2016). One
main advantage of multi-stage sampling is that it cre-
ates a more representative sample of the population
than a single sampling technique and can reduce costs
of large-scale survey research (Green et al. 2006). The
multi-stage sampling in this study entailed four stages.
In the first stage, the WR of Ghana was purposively
selected due to the high production of cocoa in the
region. In the second stage, Aowin, Suaman and Wassa
Amenfi West districts known to be some of the major
cocoa growing areas in the WR were randomly selected
out of other cocoa-producing districts in the region.
In the third stage, three major cocoa growing com-
munities were randomly selected. In the final stage,
25 cocoa farmers were randomly selected from each
of the three selected cocoa growing communities.
Totally, 225 cocoa farmers were randomly sampled for
the study. That is, three districts × three communities
× 25 farmers = 225 farmers. In this study, the partic-
ipants were informed that the data provided would
contribute to the overall knowledge about the effects
of pesticides on human health. In addition, participants
were neither coerced nor financially induced to take
part in the research.
2.2. Data analyses
Analysis was conducted using Statistical Package for
the Social Sciences (SPSS) Version 21 (IBM, Chicago,
IL, USA), STATA 13 (Stata Corp, College Station,
TX, USA), and Microsoft Office Excel 2010
(Microsoft Corporation, Redmond, WA, USA).
Descriptive statistics (frequencies and percentages),
inferential statistics, analysis of variance (ANOVA),
and Pearson correlation/chi-square tests were con-
ducted on the data from the respondents to examine
significant differences among the identified categor-
ical groups. An alpha (α) level of 0.05 was used as
the criterion for statistical significance. The relation-
ship between response variable and explanatory vari-
ables was modelled using logistic regression.
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 3
Logistic regression has three common link func-
tions, that is, the logit, the probit, and the comple-
mentary log-log. The logit and the probit are
symmetric link functions, while the complementary
log-log is applicable when the data come from mul-
tiple groups and are not symmetric in the 0–1 inter-
val and increase slowly at small to moderate values,
but increase sharply to 1. This response implies that
we must not have the response curve of the partic-
ipants showing 50% in the affirmative and the other
50% in the negative (Collett 2003; Armah et al.
2019). In this study, a complementary log-log regres-
sion model was fitted to binary outcomes data at
the multivariate level. The complementary log-log
transformation is expressed as:
loglog 1p= +X+ X+ + X =Z.
o112
2k
k
(1)
where, βo = the constant of the equation, β1,2,3 = the
coefficient of the explanatory variables 1, 2, 3 to be
estimated; X1……. Xk are sets of explanatory vari-
ables; p is the predicted probabilities; and log{-
log(1-p)} is the link function.
log1 pe+X+X++X.
0112
2k
k
(2)
As the probability increases, the transformation
approaches infinity more slowly than either the pro-
bit or the logit. By using equations (1) and (2), the
relationship between the response variable and the
explanatory or predictor variable was modelled.
The response variable is the use of PPE and the
explanatory or predictor variables are the agrochem-
ical shops, extension services availability, years of
farmer’s experience, age, education and the districts.
The role of respondents using PPE or not in deter-
mining factors that influence famers’ choice to use
PPE during pesticide application was estimated using
a complementary log-log model and reported as
exponentiated coefficients or odds ratios (OR). An
OR value of 1 means that the predictor does not
affect odds of influencing farmers to use PPE during
pesticide application, while OR > 1 means that the
predictor is associated with higher odds of influenc-
ing farmers to use PPE during pesticide application.
Finally, OR < 1 means that the predictor is associ-
ated with lower odds influencing farmers to use PPE
during pesticide application. The study accounted
for clustering of observations in units of communi-
ties and robust estimates of variance was used to
correct for any statistical outliers in the estimation
of standard errors. The study made use of 95% con-
fidence interval (CI) and the level of statistical sig-
nificance was set at 0.05. The main or key predictors
used were agrochemical shop services, extension
services and years of farmers’ experience. Some com-
positional factors [(biosocial variables (age),
socio-cultural variables (education)] and contextual
factor (the districts where the study was conducted),
which were known in the literature to influence
farmer’s choice to use PPE during pesticide appli-
cation were controlled for in the models. Four mod-
els: main predictors, agrochemical shops/extension
services availability (model 1), biosocial (model 2),
socio-cultural (model 3), and contextual factors
Figure 1. A map showing the study area.
4 M. K. MIYITTAH ETAL.
(model 4) were run. Selection of reference groups
for the independent variables in the models was
based on theory and literature. “I do not get infor-
mation about pesticide use from agrochemical shop”
(No) was chosen as the reference group for the
agrochemical shop services. The reference group for
extension services was “I do not get information
about pesticide application from extension services”
(No). For farmers’ years of experience, “I do not get
information about pesticide use from farming years
of experience” (No) was used as the reference group.
Similarly, no formal education group was chosen as
the reference group for education since this has
direct influence on farmers’ knowledge of dangers
associated with pesticide use. The rest of the refer-
ence groups were “Male” for gender, and “Wassa
Amenfi West” for district.
In addition, to validate the sample distribution,
estimate the accuracy of a given parameter, and
strengthen the stability of the statistical model, the
bootstrap technique was used to provide support.
The method takes a sample with replacement from
the original sample and calculates the statistic of
interest repeatedly (Islam and Begum 2018). In this
study, the proxy sample population was 225 and
large sample size of 2000 was estimated in
bootstrapping.
2.3. Ethical statement
The study was approved by the Institute Review
Board (IRB) of the University of Cape Coast.
Agricultural extension officers of COCOBOD offered
permissible access to cocoa farmers. Consent to col-
lect and publish data was obtained from the
participants. In addition, participants were not
coerced through financial means to take part in this
research. They were informed that the outcomes of
the research would enhance their welfare in terms
of pesticide usage.
3. Results
3.1. Farmers knowledge and understanding on
pesticides
3.1.1. Socio-demographic description of the
respondents
Table 1 presents the demographic background of the
respondents from the selected districts.
The demographic data of the respondents
include sex, age, educational level, family position,
and economic activity. Out of 225 farmers, 154
males and 71 females were contacted in the study
showing that the males dominated in cocoa farm-
ing. The majority of the study participants were
males (68%), while the remaining (32%) were
females. One third of the respondents (33%) had
no formal education, 35% had only primary edu-
cation and (32%) secondary education. The main
economic activity for the sampling group was
farming (95%). Most farmers surveyed were
between the ages of 31 and 40 years old; however,
farmers were within the economically active age
range (18–65) (Table 1). Only 9% of the farmers
were between 21 and 30 years old. It was observed
that the farmers used different types of pesticides.
In all, eleven types of pesticides were identified,
and the most commonly used were the insecticides
followed by the fungicides. About 46% of the
Table 1. Socio-demographic characteristics of the study population.
N (%) N(%)
Respondent characteristics Male Female
Sex 154 (68.44) 71 (31.56)
District
Wassa Amen West 57 (76) 18 (24)
Aowin 44 (58.67) 31 (41.33)
Suaman 53 (70.67) 22 (29.33)
Age
10 − 20 1 (50) 1 (50)
21 − 30 15 (75) 5 (25)
31 − 40 41 (62.12) 25 (37.88)
41 − 50 35 (68.63) 16 (31.37)
51 − 60 44 (74.50) 15 (25.42)
61 and above 18 (66.67) 9 (33.33)
Level of Education
No formal 47 (63.50) 27 (36.50)
Primary 54 (68.40) 25 (31.60)
Secondary 53 (73.60) 19 (26.40)
Economic Activities
Farming 147 (95.45) 7 (4.55)
Small business 67 (94.37) 4 (5.63)
Mean Std. Err.
Farm size (ha) 9.025 0.512
N = number of respondents in each category add up to 225; numbers in parenthesis indicate percentages; (ha) = hectares. Std. Err. = Standard
error of the mean.
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 5
pesticides were moderately/slightly hazardous
according to WHO classification. In addition,
about 8% of pesticide application fell into the
non-toxic class (Table 2).
3.1.2. Farmers’ knowledge of pesticide toxicity
An analysis of farmers’ knowledge on the routes of
entry of pesticides into the human body, on fruits
such as cocoa and vegetables, and in the environ-
ment brought out the results shown in Table 3.
There was a statistically significant difference
between educational level of farmers and their
knowledge of pesticide entering their bodies through
inhalation (χ2 = 10.28, p < 0.05), through the skin
(χ2 = 7.59, p < 0.05), and knowing whether pesticide
residue is left on fruits and vegetables after the
application of pesticides (χ2 = 10.054, p < 0.05).
However, the Chi-square (χ2) of variables that were
not significant (i.e. whether pesticides can cause
negative effects, or pesticides residue can be left on
air, soil, etc.) were positively associated with greater
percentage of the farmers saying “yes” to the ques-
tions, indicating that knowledge is relevant and
influential. In general, most farmers had good
knowledge of the effects of pesticides on human
health by explaining how their bodies react after
the spraying of pesticides.
Table 2. Commonly used pesticides by the farmers.
Trade name Active ingredient WHO toxicity class
Insecticides
Akate master Bifenthrin (27 g/l) II
Acati Power SL Thiamethroxam (200 g/l) II
Akate Star 3.5 EC Bifenthrin (30 g/l) II
Aceta Star 46 EC Bifenthrin (30 g/l) II
Condor 200 OD Thiamethroxam (240 g/l) III
Miricon EC Pyrethrin (12 g/l) + Deltamethrum (6 g/l) II
Fungicides
Champion WP Copper Hydroxide (77%) III
Ridomil Gold Plus 66WP Cuprous oxide (60%) + Metaxyl − M (6%) III
Nordox Super 75 wg Cuprous oxide (86%) III
Herbicides
Aduodzi 757 SG Glyphosate (757 g/l) III
Tackle360 SL Glyphosate (360 g/l) IV
I = extremely hazardous; II = moderately hazardous; III = slightly hazardous IV = non-toxic; ( WHO 2005).
Table 3. Relationship between farmers’ level of education and knowledge on pesticide toxicology.
Question asked No formal education Primary education
Secondary
education Inferential statistics
Can pesticides cause negative eects?
No 17 (43.60) 13 (33.30) 9 (23.10) X2 = 2.8589, p = 0.239
Yes 57 (30.60) 66 (35.50) 63 (33.90)
Do all pesticides have the same
health eects?
No 53 (33.30) 55 (34.60) 51 (32.10) X2 = 0.0753, p = 0.963
Yes 21 (31.80) 24 (36.40) 21 (31.80)
Can pesticides be dangerous to use?
No 10 (45.45) 8 (36.40) 4 (18.10) X2 = 2.6365, p = 0.268
Yes 64 (31.50) 71 (35.00) 68 (33.50)
Can pesticides enter the body
through inhalation?
No 9 (75.00) 2 (16.70) 1 (8.30) X2 = 10.2818, p = 0.006*
Yes 65 (30.50) 77 (36.20) 71 (33.30)
Can pesticides enter the body
through skin?
No 9 (75.00) 2 (16.70) 1 (8.30) X2 = 7.5390, p = 0.023*
Yes 65 (30.50) 77 (36.20) 71 (33.30)
Can pesticide residue be left in the
air?
No 6 (46.20) 5 (38.50) 2 (15.30) X2 = 1.9726, p = 0.373
Yes 68 (32.10) 74 (34.90) 70 (33.00)
Can pesticide residue be left in the
soil?
No 8 (26.70) 14 (46.70) 8 (26.70) X2 = 2.0316, p = 0.362
Yes 66 (33.80) 65 (33.40) 64 (32.80)
Can pesticide residue be left in the
fruit and vegetables?
No 20(55.60) 9 (25.00) 7 (19.4) X2 = 10.0541, p = 0.007*
Yes 54 (28.60) 70 (37.00) 65 (34.40)
N = number of respondents for each category is 225; Numbers in parenthesis indicate percentages; X 2= Pearson chi square; p = probability value;
* = Signicant result (p < 0.05)
6 M. K. MIYITTAH ETAL.
3.1.3. Pesticide acquisition, reason for application,
and knowledge of application
Table 4 shows pesticide acquisition, reason for appli-
cation and knowledge of application using descrip-
tive statistics. Farmers indicated agrochemical shops
(27%), local governmental shops (41%), and exten-
sion officers (38%) as their main sources of pur-
chasing pesticides. Part of the data (not shown)
revealed the following brand names: Akate master,
Confidor, Ridomil, and Nodox as the commonly
used pesticides. All farmers consented to using
motorized sprayers for insecticide application, while
the knapsack sprayer was the preferred equipment
for fungicide application. When farmers were asked
why they use pesticides, 80% of the farmers iden-
tified the presence of pests as the driving factor for
their decision to apply chemicals. When the respon-
dents were asked where they buy the pesticides from,
there was a plethora of sources and some of the
sources were not regulated. Less than half of the
respondents (41%) were buying pesticides from local
governmental shops in villages, while the remaining
were distributed among agrochemical shops in towns
(27%), and other general shops (7%) while (38%)
of the farmers obtained them from extension offi-
cers. Regarding timing of pesticides application, 30%
followed the recommended calendar spraying sched-
ules, no matter the observations in the field.
Application strategies employed by the majority of
the farmers involved the application of different
chemicals individually (90%), but the remaining
group (10%) indulged in the improper farming
practice of mixing different chemicals to have rapid
knockdown effects of pests. A greater part (88%) of
the farmers did not read instruction on labels before
using pesticides.
The majority of the farmers indicated that they
obtained pesticide knowledge from extension officers
(69%). Other farmers used their own experience
(10%) or, they were taught by fellow farmers (18%).
3.2. Pesticides storage environment
3.2.1. Pesticides storage location and level of
education
Figure 2 illustrates the result of storage of pesticides
options explored by the farmers. Thirty-two percent
(32%) of the farmers used the bush as their main
storage facility for the pesticides they used.
Some respondents (17%) stored chemicals within
their living rooms, whiles 7%, 3% and 4% of respon-
dents stored them in agrochemical shop, kitchen
and animal house respectively. The result of linking
storage location to the levels of education is pre-
sented in Table 5.
There was a statistically significant association
between farmers’ pesticide storage location and their
educational levels (X2 = 24.05, p < 0.05). This means
that farmers’ knowledge of pesticide storage location
is influenced by their level of education. Further, the
usual and common way of disposing empty pesticide
containers and remnants from spraying equipment
was throwing them in the farm (Figure 3). Anecdotal
evidence shows that empty pesticide containers and
Table 4. Pesticide application information by cocoa farmers.
Response N (%) Response N (%)
Questions and predened answers Ye s No
Why do you use pesticides?
To protect crops against insects and diseases 180 (80) 45 (20)
To make crops grow better 53 (23.56) 172 (76.44)
Because others use pesticides 5 (2.22) 220 (97.78)
Because I was advice to use it 10 (4.44) 215 (95.56)
Where do you get/buy the pesticides?
Agrochemical shops in town 61 (27.11) 164 (72.89)
Local government shops in the village 93 (41.33) 132 (58.67)
Extension ocers 85 (37.78) 140 (62.22)
General shops 15 (6.67) 210 (93.33)
Cooperative societies 0 (0.00) 225 (100)
Timing of pesticides application
Presence of pests 144 (64) 81 (36)
Degree of pest infection 17 (7.56) 208 (92.44)
Date of planning 3 (1.33) 222 (98.67)
On the calendar spray schedules 67 (29.78) 158 (70.22)
Pesticide application strategy
Mix more than one type of chemical 23 (10.22) 202 (89.78)
Depending on the instruction on the label 26 (11.56) 199 (88.44)
Sources of farmers’ knowledge on
pesticide application
Agrochemical shops 11 (4.89) 214 (65.11)
Extension ocers 156 (69.33) 69 (30.67)
Pesticides labels on packages 23 (10.22) 202 (89.78)
Fellow farmers 40 (17.78) 185 (82.22)
Own experience 23 (10.22) 202 (89.78)
N = number of respondents; Numbers in parenthesis indicate percentages. N (225).
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 7
sachets were found disposed of indiscriminately on
farms. Five of the respondents (2%) revealed that
they put empty pesticide containers to other use once
they were emptied of its content. Some farmers (8%)
also mentioned digging holes on farm and burying
containers as their preferred disposal method.
3.2.2. Farmers’ response towards pesticide use
Farmers’ opinion on the effectiveness of spraying
was sought by expecting respondents to agree or
disagree with certain statements. As shown in
Table 6, 55% of the respondents strongly agreed to
the statement that pesticide use was important to
secure good crops. The majority of the respondents
(98.7%) also admitted that knowledge was needed
for the application of pesticides. The majority of the
respondents agreed that precaution is necessary in
the administration of chemicals (53% strongly
agreed, 47% agreed). One third of the respondents
(32%) disagreed that minimal health risks is asso-
ciated with pesticide use, while the majority (68%)
agreed. Further, 37.8% recognized and agreed that
it is necessary to limit pesticides use. This might
apparently be due to health symptoms that some of
the respondents experienced during pesticide
application.
3.3. Health and safety impacts due to pesticide
application
3.3.1. The use of personal protective equipment
(PPE)
Farmers were asked whether they use a single item,
or multiple items of PPE. Multiple PPEs most often
involve wearing two or more of the following: hats,
gloves, goggles, respirator, protective boots, and cov-
eralls. Farmers were asked whether they used full
working gear of multiple PPEs for protection during
spraying (Table 7). Fifty-five (55) farmers failed to use
any safety equipment (zero PPE), while 68 of the farm-
ers revealed they used the full working gear (six PPE
items). Most of the farmers with zero PPE usage in
the study were noted to be farmers who had no formal
education. In addition, 102 of the farmers partially
protected themselves before using chemicals on the
farms (Table 7). Farmers with either primary or sec-
ondary level of education used all six PPEs items or
some form of partial PPEs during spraying.
Figure 2. Pesticides storage location by cocoa farmers.
Table 5. Relationship between pesticides storage location and farmers level of education.
Education
Storage location No formal Primary Secondary Inferential statistics
Agrochemical store 4 (5.4) 5 (6.3) 6 (8.3) X2 = 24.05, p = 0.045*
Cramer’s V = 0.231
Animal houses 2 (2.7) 4 (5.1) 3 (4.2)
In the food storeroom 8 (10.8) 13 (16.7) 12 (16.5)
Living house 8 (10.8) 9 (11.4) 22 (30.6)
In the kitchen 2 (2.7) 3 (3.8) 22 (30.6)
In the bush 26 (32.9) 26 (32.9) 19 (26.4)
In the toilet 6 (8.5) 5 (6.3) 5 (6.9)
In the Bathroom 18 (24.3) 14 (17.7) 3 (4.2)
X2 = Pearson chi square; P = probability value; Cramer’s V value (0–1) indicates how strong the values are associated with closeness to 1 which
implies greater association. * = Signicant result (p < 0.05); Numbers in parenthesis indicate percentages.
8 M. K. MIYITTAH ETAL.
3.3.2. Common health symptoms associated with
frequent pesticides usage
Table 8 shows common health symptoms self-reported
and experienced by the farmers due to pesticide
application. Data revealed that more than half of
the respondents experienced symptoms of headache
and burning eyes at 66% and 52% respectively. The
remaining symptoms were skin rashes (32%), itching
(48%), and chest pain (42%).
3.3.3. Factors inuencing PPE use and logistic
regression modelling
To investigate factors influencing PPE use, Cramer’s
V correlation was determined and presented in
Table 9. The result showed a positive and negative
correlation, with all the factors showing weak cor-
relation <10%, with the exception of gender (30%).
The weak correlation might suggest confounding
factors influencing the variables, since the literature
predicted otherwise. In Table 9 only gender and
district of the farmers showed a statistically signif-
icant difference (p < 0.01), although the literature
indicated several factors influencing PPE usage.
The data was modelled with the complementary
log-log regression and was assessed with goodness
of fit tests using Deviance, Pearson and Akaike
Information Criterion (AIC). The goodness fit test
showed Deviance to be 1.132, Pearson = 1.028, and
AIC = 1.167. Since Deviance, Pearson and AIC val-
ues are almost similar to each other and with very
Figure 3. Disposal of empty pesticide containers.
Table 6. Attitudes towards Pesticide Use.
Farmers’ perception on the eectiveness of
spraying
Respondents
N %
Important to secure good crops
Agree 101 44.89
Strongly Agree 124 55.11
Proper knowledge is necessary
Strongly Disagree 10.44
Disagree 20.89
Agree 96 42.67
Strongly Agree 126 56.00
Precautions should be used
Agree 106 47.11
Strongly Agree 119 52.89
Minimal Health Risks attached to
pesticide use
Strongly Disagree 10.44
Disagree 71 31.56
Agree 81 36.00
Strongly Agree 72 32.00
Limit pesticide use
Strongly Disagree 16 7.11
Disagree 63 28.00
Agree 85 37.78
Strongly Agree 61 27.11
N = number of respondents; Numbers in parenthesis indicate percentages.
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 9
small values, it suggested that the model fit was
considered satisfactory. The actual result of the
complementary log-log regression modelling is pre-
sented in Table 10 showing the odds ratios, standard
errors, p-values, and confidence intervals (CI) asso-
ciated with the use of PPE, as well as compositional
and contextual factors. Model 1 shows that agro-
chemical shops and extension services were statis-
tically significant, indicating that farmers who
depended on agrochemical shops (OR = 1.735,
p < 0.005) as a source of information with regard to
pesticide application were more likely to use PPE
during pesticide application compared to their coun-
terparts. Similarly, the probability that farmers who
depended on the extension services (OR = 1.643,
p < 0.007) as a source of knowledge with respect to
pesticide application increased as compared to their
counterparts. This situation could arise as farmers
meet the extension officers and thus they receive
educational information regarding the use of PPE
in pesticide application. Surprisingly, farmers’ years
of experience in pesticide application was not sta-
tistically significant.
The result for model 2, where biosocial factors
were controlled for, showed that farmers who relied
on agrochemical shops (OR = 1.773, p < 0.005) and
extension services (OR = 1.507, p < 0.032) as a
source of information about pesticide application
were more likely to use PPE than those who
responded negatively. Gender (p < 0.000) also influ-
enced PPE use during pesticide application. It was
also revealed that female farmers were 48.1% less
likely to use PPE during pesticide application com-
pared to male farmers. This response may be
because although female farmers may be owners
of the farm, they may consult their male counter-
parts to do the spraying and may utilize PPE
during pesticide application. When the socio-cultural
factors (e.g. education) was controlled for in model
3, agrochemical shops (OR = 1.777, p < 0.004) and
extension services (OR = 1.497, p < 0.036) contin-
ued to predict the use of PPE. However, the prob-
ability of PPE use during pesticide spraying was
higher for farmers who depended on agrochemical
shops for information about of pesticide application
compared to their counterparts. Farmers who
depended on extension services on the other hand
were 100% likely to use PPE than their counter-
parts. Interestingly, there was no significant rela-
tionship between educational levels and the use of
PPE during pesticide application.
In model 4, contextual factors influencing famers’
choice to use PPE were considered by controlling
districts from which the respondents were drawn.
Table 7. Use of PPEs and educational background of the farmers during the application of pesticides.
Number of PPEs No formal education (N) Primary education (N) Secondary education (N) Total (N)
022 21 12 55
1 9 6 12 27
2 8 4 4 16
3 4 7 10 21
4 3 7 5 15
5 7 9 7 23
621 25 22 68
Total (N) 74 79 72 225
N = number of respondents; PPE = personal protective equipment.
Table 8. Common health symptoms associated with frequent pesticide usage.
Symptoms
Response N (%)
YES
Have you experienced any of the following symptoms after chemical application?
Headache 118(52.44)
Burning eyes 148(65.80)
Skin rash 73 (32.44)
Itching 109 (48.44)
Chest pain 95 (42.22)
N = number of farmers; Numbers in parenthesis indicate percentages.
Table 9. Correlation analysis of PPE use and source of pesticide knowledge with demographic variables.
Variables Sign Signicance
Agrochemicals (+) ns
Extension services (+) ns
Farmers experiences (-) ns
Gender (-) s
Education (+) ns
Districts (+) s
Signicant for coecient: p < 0.05; s for signicant and ns for non-signicant; + and – signs indicate positive or negative correlation.
10 M. K. MIYITTAH ETAL.
Table 10. Multivariate complementary log-log regression model predicting PPEs usage during pesticide application.
Source of pesticide knowledge (Model 1) Bio-social factors (Model 2) Socio-cultural factors (Model 3) Contextual factors (Model 4)
Predictors OR SE p95% CI OR SE p95% CI OR SE p95%CI OR SE p95%CI
Agrochemicals
shops (Ref:
No)
Yes 1.735 0.343 0.005 1.178–2.554 1.773 0.358 0.005 1.192–2.636 1.777 0.357 0.004 1.200–2.633 1.646 0.334 0.014 1.106–2.452
Extension services
(Ref: No)
Yes 1.643 0.303 0.007 1.144–2.359 1.507 0.287 0.032 1.037–2.189 1.497 0.288 0.036 1.027–2.183 1.374 0.268 0.104 0.937–2.015
Farmers’
experiences
(Ref: No)
Yes 0.752 0.752 0.362 0.408–1.388 0.833 0.259 0.557 0.452–1.533 0.838 0.260 0.569 0.456–1.539 0.837 0.262 0.57 0.453–1.546
Gender (Ref:
Male)
Female 0.481 0.097 0.000 0.325–0.713 0.483 0.097 0.000 0.325–0.716 0.466 0.094 0.000 0.313–0.693
Education (Ref:
No formal
education)
Primary education 1.010 0.217 0.961 0.663–1.540 1.095 0.240 0.679 0.713–1.681
Secondary
education
1.065 0.229 0.770 0.699–1.624 1.090 0.238 0.692 0.711–1.672
Districts (Ref:
Wassa
Amen
West)
Aowin 0.882 0.187 0.553 0.581–1.337
Suaman 0.568 0.125 0.010 0.368–0.875
OR-odds ratio; SE-standard error; p-probability value; CI-condence intervals.
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 11
Observations under farmers’ experience were not
statistically significant for models 1 to 3, while the
extension services variable, which was statistically
significant in models 1 and 2 ceased to be significant
in model 4, when the contextual factor was added.
In addition, agrochemical shop was significant under
models 1 to 4. Farmers who depended on agrochem-
ical shop services (OR = 1.646, p < 0.014) for infor-
mation about pesticide application were still more
likely to use PPE compared to their counterparts.
The result also showed that female farmers (OR =
0.466, p < 0.000) were still less likely to use PPE
during pesticide application than the male farmers.
Concerning districts, only Suaman district showed
relationship with PPE use. Farmers in Suaman (OR
= 0.568, p < 0.010) were less likely to use PPE com-
pared to Wassa Amenfi West district. It is obvious
from the results that agrochemical shop services and
extension services influence farmers’ choice to use
PPE during pesticide application.
3.3.4. Bootstrapping model statistics
In order to validate the model statistics and avoid
doubts of sample distribution, bootstrapping was
used to measure the accuracy of the logistic regres-
sion model (multivariate complementary log-log)
parameter estimates. Table 11 shows the result of
the bootstrapping used. The bootstrap method
attempted to estimate the sampling distribution
empirically with the given sample size of 225 and
estimate the parameters on large scale of 2000 sam-
ple size. There were no differences between the OR,
SE, and CI for logistic complementary log-log regres-
sion model in Tables 10 and 11. In addition, the
p-values were identical as predicted by both the
logistic regression and the bootstrap method. The
implication of the result is that the sample size dis-
tribution and parameter estimates are accurate
and correctly predicted by the complementary
log-log model.
4. Discussion
4.1. Demographic characteristics of farmers
This study investigated smallholder cocoa farmers’
knowledge of pesticide use, their attitudes towards
storage of pesticides, and evaluated their exposure
to health symptoms. The study revealed that the
common reason for using pesticides was to protect
cocoa plants from insects, pests and diseases. This
finding is in line with Khan and Damalas (2015),
who reported that in order to control pests and
prevent loss of crop yields in their crops, farmers
use synthetic pesticides extensively. The present
study also showed that the dominant gender involved
in cocoa farming in the study area is the male. The
large male to female ratio in this study is in line
with the findings of Bosompem et al. (2012), Boateng
et al. (2014 ), Antwi-Agyakwa et al. (2016), Zhu
(2015), and Tijani (2006). The educational back-
ground of respondents showed that a good number
of farmers had received basic and secondary level
education while the majority of the farmers did not
have further studies beyond the secondary school
level. Nonetheless, the proportion of illiterates was
equally low. This case is similar to Paintsil (2017)
and Zhu (2015) findings, where farmers had the
view that a high level of education is not necessary
for carrying out farming. A study from Nigeria
(Oluwole and Cheke 2009) also confirmed this trend
with a similar finding where the majority of farmers
surveyed had no formal education. Hence, it can be
deduced that the inability of a farmer to undertake
a good agricultural practice is because of poor edu-
cational background in rural Africa. The results
further show that three-fourths of the respondents
had either no or just primary level of education.
Thus, farmer’s level of education may be a contrib-
uting factor to their inability to read the labels on
the chemical containers and in understanding the
hazardous nature of pesticides chemistry. In a related
study, about 94% of the farmers stated that pesticide
labels were difficult to read and understand which
was attributed to low educational levels, poor literacy
skills and difficulty in following the language used
in the wording of the label (Damalas et al. 2006).
The cocoa sector has been the mainstay of the
Ghanaian economy since 1957 (Vigneri and Kolavalli
2018). Surprisingly, however, it is pathetic to note
that this cash crop for Ghana is not attracting those
with tertiary level education. It is no wonder, the
cocoa farming production is still in the hands of
smallholder farmers. Ghana Statistical Service (2013)
data indicated that Ghana’s agricultural sector is
dominated by 90% smallholder farmers with less
than 2 hectares of land. These farmers still use tra-
ditional production methods and farm inputs. The
current global state of agricultural practice is driven
mainly by science and technology, but without ade-
quate level of education, applying science and tech-
nology to transform agriculture to a knowledge-based
enterprise may become quite problematic. Recently,
Kwadzo (2015) examined smallholder cocoa farmers
in Mpohor-Wassa East district, Ghana and found
that 73% of the farmers had shifted from cocoa to
rubber cultivation. The result buttressed the fact that
investment outcomes of cocoa have a significant
effect on their enterprise-shift behaviour and
12 M. K. MIYITTAH ETAL.
Table 11. Bootstrap results generated after 2000 samples to validate parameters of multivariate complementary log-log regression model predicting PPEs usage during pesticide
application.
Source of pesticide knowledge (Model 1) Bio-social factors (Model 2) Socio-cultural factors (Model 3) Contextual factors (Model 4)
Predictors OR SE p95%CI OR SE p95%CI OR SE p95%CI OR SE p95%CI
Agrochemicals
shops (Ref:
No)
Yes 1.735 0.365 0.009 1.149–2.619 1.773 0.387 0.009 1.156–2.718 1.777 0.370 0.006 1.182–2.673 1.646 0.334 0.014 1.106–2.452
Extension
services (Ref:
No)
Yes 1.643 0.317 0.010 1.125–2.399 1.507 0.290 0.033 1.033–2.198 1.497 0.299 0.043 1.012–2.215 1.374 0.268 0.104 0.937–2.015
Farmers’
experiences
(Ref: No)
Yes 0.752 0.250 0.392 0.392–1.443 0.833 0.284 0.591 0.427–1.623 0.838 0.290 0.610 0.425–1.653 0.837 0.262 0.570 0.453–1.546
Gender (Ref:
Male)
Female 0.481 0.103 0.001 0.316–0.734 0.483 0.103 0.001 0.318–0.732 0.466 0.094 0.000 0.313–0.693
Education
(Ref: No
formal
education)
Primary
education
1.010 0.227 0.963 0.651–1.569 1.095 0.240 0.679 0.713–1.681
Secondary
education
1.065 0.246 0.785 0.677–1.676 1.090 0.238 0.692 0.711–1.672
Districts (Ref:
Wassa
Amen
West)
Aowin 0.882 0.187 0.553 0.581–1.337
Suaman 0.568 0.125 0.010 0.368–0.875
OR-odds ratio; SE-standard error; p-probability value; CI-condence intervals.
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 13
decisions. If this trend is drifted to other districts
and regions, it may not auger well for the sustain-
ability of the cocoa sector.
4.2. Relationship between farmers’ level of
education and knowledge of pesticide toxicity
In general, most farmers had good knowledge of
the effects of pesticides on human health as they
indicated how their bodies react after the spraying
of pesticides. It was also discovered that farmers’
knowledge in health effects of pesticides was influ-
enced by their educational background. According
to Bagheri et al. (2018), well-educated farmers had
more safe behaviours than less-educated farmers.
Similarly, well-educated farmers were more likely to
pay a high premium for safe pesticides (Khan and
Damalas 2015). Thus, training and education posi-
tively influence environmentally sound behaviour in
pest management (Damalas and Khan 2017).
Interventions such as education and training of
farmers which enhance safety behaviour should be
intensified to minimize pesticides exposure among
farmers, (Damalas and Koutroubas 2017). It is clear
that having a clear insight regarding farmers’ level
of knowledge and farmers’ practices on safe use of
pesticides is necessary to augment the current sce-
nario for a new policy change (education). The pol-
icy change should involve the farmers, the extension
agents, the agrochemical retailers, and regulatory
agencies. This new policy change is needed to pro-
tect the public health. Contrary to expectations,
although, the majority of the farmers in this study
were aware of the harmful effects of pesticides, this
did not significantly change their practices or atti-
tudes towards safe pesticides use. This finding is
consistent with that of Sharifzadeh et al. (2019) and
showing that even though good knowledge about
pesticide safety is imperative for farmers, this alone
is not enough to encourage them to indulge in safety
behaviours. Perhaps cultural and social driving forces
are strong determinants limiting behavioural change
necessary to evoke a collective safety responsibility
(Feola and Binder 2010).
4.3. Relationship between pesticides storage
location and farmers level of education
The present study also highlighted some unsafe prac-
tices regarding storage of pesticides, i.e. in the
kitchen, living room and in the food storerooms.
Thus, it was clearly shown that farmers were lacking
knowledge regarding appropriate places for storing
pesticides. Storing pesticides in the living rooms,
kitchen, and food storerooms increases the potential
for pesticide exposure risks. The majority of the
farmers kept chemicals in their farmlands. However,
a good number of them kept chemicals within the
living room, kitchen, in the food storeroom, and in
the animal house. An additional fascinating situation
in these rural communities setting was the storage
of chemicals in the toilet and bathroom. A very
small proportion of the farmers (7%) kept pesticides
in the agrochemical stores. This finding is similar
to that of Paintsil (2017) because the selected study
area is in the same region but in different districts.
Oluwole and Cheke (2009) also gave similar support
to this assertion with data from rice farmers, while
Zhu (2015) recognized a similar trend in vegetable
farmers within the cocoa growing belts. Additionally,
Bagheri et al. (2018) found out that about 60% of
the farmers in Iran stored their pesticides in stalls
and warehouses, while about 40% threw empty pes-
ticide containers at the orchard and in the canal.
On the other hand, Tijani (2006) uncovered a dif-
ferent pattern, that is, the majority of the farmers
were storing pesticides in designated stores and a
minority was keeping them in their bedrooms. The
attitudinal behaviour exhibited by the farmers in
understanding the hazardous nature of pesticides
storage location is linked to the educational levels
of the farmers. Based on these findings, farmers
need to be trained on proper and safe storage of
pesticides. Damalas and Koutroubas (2017) have
shown that training of farmers was associated with
increased levels of knowledge of pesticides and
beliefs of pesticides hazard control, which was
accompanied by high safety attitude in farmers
resulting in lower occupational pesticide exposure.
Undoubtedly, farmers who undertake educational
programs experience fewer poisoning symptoms by
pesticides (Bagheri et al. 2018). Apart from educa-
tion, farmers can also be motivated to store and
dispose of pesticides in a safe manner through the
constitution of credit bonuses at the purchase of
pesticides. For example, part of the money paid for
the pesticide by the farmers can be given back to
them when they return the pesticide containers to
the manufacturers, retailers or packaging companies
(Bagheri et al. 2018).
It was also found that the most prominent con-
tainers and sachet disposal strategies currently
employed were throwing in the field, village landfills,
burning on farm and burying in a hole (Figure 3).
This trend is coherent with data reported by Tijani
(2006), Oluwole and Cheke (2009) and Paintsil
(2017). Previous studies in Ethiopia and Greece
found dumping empty pesticide containers by fields,
near, or into irrigation streams and canals and
14 M. K. MIYITTAH ETAL.
burning them in open fire are well-known practices
of pesticide container disposal methods that farmers
are often involved in, coupled with using them for
storage of fuel, water and food (Damalas et al. 2008;
Haylamicheal and Dalvie 2009). It was also observed
that some farmers practice rinsing the empty con-
tainers by discharging the water into nearby uncul-
tivated lands, throw away empty containers into
rivers, lakes or irrigation canals or bury them in
the ground. However, it is interesting and alarming
to note that some farmers also put the empty con-
tainers to other use for storing household items such
as salts, palm oil, flour and other products meant
for consumption. In addition, the majority of the
respondents were found even washing their pesticide
containers in rivers, streams or irrigation canals.
Similar behaviour and attitudes were observed by
Jallow et al. (2017) among farm workers in Kuwait,
showing that the practice cut-across various cultural
backgrounds. Thus, again this study demonstrated
poor knowledge of cocoa farmers about pesticides
and their transport in the environment. These poor
handling and disposal practices can have devastating
effects on soil, water contamination, and the overall
impacts on public health. This is because such
unsafe practices can release pesticide residues and
contaminate the environment (Damalas and
Eleftherohorinos 2011, Miyittah et al. 2020).
4.4. Pesticide application information by cocoa
farmers
The present study also indicated that most farmers
obtained pesticides from local governmental shops
as their main source. Anecdotal evidence supported
by this reality is that most of these agrochemical
retailers themselves need more education on pes-
ticide use and handling. Moreover, if pesticide
retailers are well informed they can help by pro-
viding accurate source of information regarding
environmental and human health impacts of pes-
ticides to farmers who cannot read instructions or
labels on the containers. There is, therefore, a need
to train and equip pesticides retailers regarding
dissemination of agricultural information, since
they can play a critical role as a primary infor-
mation and knowledge source for the farmer. Lekei
et al. (2014) reported the impact of retailers as
technical advisors on farmers and other end users
as a key contributing factor in occupational expo-
sure to pesticides. Additionally, 69% of the respon-
dents obtained information for pesticides from
agricultural extension officers. This observation is
in line with results obtained by Tijani (2006) and
Zhu (2015). However, others prefer to use their
own experience or get information from their fel-
low farmers. There is nothing wrong if the farmer
gets information from their peers. However, the
difficulty occurs when the said information is not
accurate and the source of information cannot be
verified by the farmers themselves. The unverified
information can be further distorted along the
communication channels and such distortion can
contribute to propagation of inaccurate information
regarding pesticides use among cocoa farmers.
Agricultural extension officers in general act as
conduits between the Ministry of Food and
Agriculture and farmers, or farm workers. Extension
aims primarily at improving the knowledge of
farmers for rural development. Thus, agricultural
extension plays a critical component of technology
transfer (Bonye et al. 2012). In general, extension
officer-to-farmer ratio in Ghana is about 1:3000.
However, the COCOBOD as an agency in charge
of cocoa have reduced the ratio gap by having
extension services specialized for cocoa affairs.
This gap reduction in extension officer-to-farm
ratio may be the reason why 69% of the respondents
reported that they obtained information about pes-
ticides through extension officers. A considerable
number of the respondents (90%) reported mixing
more than one pesticide type and applying to cocoa
farms as one of the pesticide application strategy.
This practice has further demonstrated that the
farmers lack knowledge application doses and the
impact it may have on the toxicity of insect pests
and on the development of resistance of the insects
with respect to the said pesticides, as reported else-
where (Damalas and Khan 2017). It has been
reported that over 600 species of pests have devel-
oped some level of resistance to pesticides (Gill and
Garg 2014). Therefore, new policy and updated
training is urgently required to educate the retailers,
extension agents, farm workers and farmers regard-
ing pesticides resistance and the implications it may
have on the cocoa sector. There should be a docu-
mentation of all pesticides sold and a link of the
respective serial numbers on containers with the
farmer through the retailer. The farmer should have
a pesticide book with a documentation where the
pesticides was bought and with the documented
location of the retailer. At the end of the pesticide
application, a mechanism should be put in place to
retrieve all the empty containers. By this approach,
the empty containers would no longer be used as
alternative storage containers with its concomitant
health implications. The present study further
showed that most farmers had good knowledge of
the effects of pesticides on human health and the
environment. Most farmers were positive that
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 15
pesticide could enter the body via mouth (92%),
inhalation (94%), and skin (93%). The majority was
also aware that residues of pesticides can be depos-
ited on fruits and vegetables and they can contam-
inate soils and groundwater.
4.5. Common health symptoms associated with
frequent pesticide usage
It was also observed that 66% of the farmers expe-
rienced health symptoms such as headaches, burning
eyes, skin rashes, itching and chest pain. This may
be attributed to the heavy use of pesticides for pest
management and the non-use of PPE or the use of
inappropriate PPE during the various stages of pes-
ticide usage. Similarly, Atreya (2007), on the other
hand found that pesticide operators reported greater
signs and symptoms of pesticides exposure such as
skin irritations, stomach poisoning, and eye irrita-
tions than other farm workers. Similar effect was
observed in another study conducted by Neghab
et al. (2014) with 268 male farmers in Iran. The
result showed that 68% of the participants reported
to their general health practitioners, suffering from
burning and skin irritations, burning eyes, head-
aches, vertigo, nausea and vomiting during spraying.
Damalas and Koutroubas (2016) found that accurate
usage of appropriate PPE in all stages of pesticide
handling coupled with less use of pesticides could
reduce farmers’ exposure to pesticides. Toxicity
symptoms of pesticide may be categorized as mild
(skin irritation) and severe (headache, nausea and
dizziness) (Damalas and Koutroubas 2016).
4.6. Personal protective equipment (PPE) use by
the farmers
About fifty-five farmers failed to wear any personal
safety equipment (zero PPE), while 68 of the farmers
revealed they used the full working gear (six PPE
items). Most of the farmers who used zero PPE in
the study were noted to be farmers who had no
formal education. In addition, 102 of the farmers
partially protected themselves before using chemicals
on the farms. Farmers with either primary or sec-
ondary level of education used all six PPE items or
some form of partial PPE items during spraying.
Knowledge, attitudes, and practices (KAP) surveys
by Ntow et al. (2006) showed that only 32% of the
farmers were wearing full PPE. In addition, mea-
suring the relative toxicity of pesticides used in con-
trolling pest in Akumadan, Ghana, showed that 58%
of the farmers did not use any PPE, while only 29%
used some form of PPE. Furthermore, high illiteracy
rates contribute to farmers’ difficulty in
understanding and following instructions and safety
advice on pesticide use.
In Brazil, knowledge was not found to influence
pesticide application practices because the majority
of the farmers admitted receiving information,
training and claimed reading labels, adhering to
instructions and warnings, but did not take ade-
quate protective measures (Waichman et al. 2007).
The level of knowledge and perception of risk were
not enough to influence farmers’ self-protective
behaviour (Remoundou et al. 2014). It was also
reported that farmers were exposed to agrochem-
icals because of non-use of PPE cover cloths during
spraying and leakages from knapsack sprayers. In
addition, spraying during windy conditions can
cause incidental drifting of the chemicals to unap-
proved routes. The study also revealed a positive
correlation between education, agrochemical ser-
vices, extension services, and location of farmers
with farmers’ PPE use. However, farmers’ years of
experience and gender showed a negative correla-
tion with farmers’ PPE use. In addition, the mod-
elling showed that factors such as agrochemical
shops, extension services availability as sources of
information with respect to pesticide application
had positive significant influence on PPE usage.
This finding is in line with the observation of
Okoffo et al. (2016) that the probability of a farmer
wearing PPE increases with the availability of agro-
chemical shops. This behaviour may be attributed
to the fact that agrochemical shop retailers can
serve as a conduit in educating the farmers on the
dangers in application of pesticides without the use
of PPE. Even when the model was controlled for
biosocial, socio-cultural, and contextual factors,
these parameter estimates were still significant,
except for extension services in contextual factor
modelling. These services should be used as a
medium to educate farmers on the importance of
PPE use by providing training and capacity build-
ing for extension officers and agrochemical retail-
ers. Previous research has shown that farmers who
perceived usefulness of PPE, such as effectiveness,
safety, and ease of use were more willing to use
PPE in the future (Sharifzadeh et al. 2017). The
implication is that proximity of farmers to exten-
sion officers and location were crucial in PPE
usage. In addition, the sources of information about
pesticide application should be supported by gov-
ernmental interventions regarding pesticide educa-
tional activities to encourage the famers to use
PPE. Surprisingly, however, farmers’ years of expe-
rience in pesticide use was not translated into PPE
usage. The parameter estimate for farmers’ years
of experience was similar under biosocial,
16 M. K. MIYITTAH ETAL.
socio-cultural, and contextual factors. The prevail-
ing socio-cultural conditions can serve as con-
founding factors (Feola and Binder 2010) such that
the educational information received maybe masked
after massive education regarding pesticide appli-
cation. The implication is that sociological condi-
tions underpinning the socio-cultural factors
hampering the use of PPE must be investigated to
shed more light on the situation regarding accept-
ability of PPE use in the study area. However, other
studies have indicated that farmers’ experience with
adverse health effects of pesticides significantly
influence their safety behaviour and the use of PPE
(Feola and Binder 2010; Hashemi et al. 2012;
Damalas and Abdollahzadeh 2016; Sharifzadeh et al.
2018, 2019). Thus, the more farmers experience
threats and health risks by pesticides, the more
they are likely to show safety behaviours
(Abdollahzadeh et al. 2015; Damalas and
Abdollahzadeh 2016). The inability of the female
farmers to use PPE could also be linked to what
some of them said during the field survey about
the discomfort they go through any time they put
on PPE. This phenomenon is worrisome because
when female farmers are exposed to pesticides, they
can indirectly expose their breast-feeding babies
(Lorenz et al. 2012). A study on the analysis of
pesticide contamination of farmers in Ghana
revealed the presence of residues of organo-chlorine
pesticides, including dichlorodiphenyltrichlo-
roethane (DDT), in the breast milk and blood of
female farmers (Ntow et al. 2008). The sociological
condition might also be the reason why females
are less likely to use PPE compared with their male
counterparts. Our preliminary interpretation is that
women would be more exposed to health risk of
pesticide than men. This may be attributed to the
fact that female smallholder farmers have limited
access to training programs regarding pesticide
safety, and hence, they follow just few pesticide
safety behaviours when handling pesticides (Naidoo
et al. 2010; Damalas et al. 2019). In order to
enhance pesticide safety awareness among female
farmers, gender-sensitive safety programs should
be organized (Wang et al. 2017; Damalas et al.
2019). In this study, about 30% of women were
engaged in cocoa farming and therefore, further
research is needed in this direction, since pesticide
hazards have several debilitating and consequential
effects on women as child-life support givers.
Educational levels have been observed as having
no influence on the use of PPE under socio-cultural
and contextual factors. On the contrary, other
researchers proposed that educational programs
enhance sustainable PPE use among pesticide appli-
cators and smallholder farmers (Sharifzadeh et al.
2019). This means that there is a significant pos-
itive effect on PPE use and education, and thus,
the educational status of the farmers strongly deter-
mines their PPE usage (Al Zadjali et al. 2015;
Blanco-Munoz and Lacasana 2011; Sharifzadeh et al.
2019). Educational impacts on individuals occurred
in multiple layers with interacting context
(Rappaport and Smith 2010; Armah et al. 2019).
Moreover, each of these contexts is a domain of
social relations and each factor in each domain
interacts. Thus, there is a difference between edu-
cation as a context and education as a process
because these two elements have different types of
implication on environmental health and can affect
pesticide use. This understanding is in line with
Feola and Binder (2010) who indicated that
socio-cultural factors are usually masked by edu-
cational factors; hence, there is a need to disaggre-
gate the various elements and their interacting
effects. Under the contextual factor, the location of
the district towards the use of PPE is a case in
point. For example, farmers in Suaman district were
less likely to use PPE compared with those in
Wassa Amenfi West. Thus, the sociological mindset
occurring in a particular district bounded by lan-
guage and culture may contribute towards the use
of PPE. Elements within the culture and the lan-
guage that is leading to the influence of PPE use
must be studied. Perhaps, more access to extension
services within the district may be the contributing
factor in using PPE as noted by Danso-Abbeam
et al. (2018) who reported agricultural extension
plays a critical role in improving the knowledge
base of the farmer and in the transfer of technol-
ogy. The use of PPE is a type of skill that influ-
ences productivity and the farmer must have it and
understand why it is important. This is because
the health of smallholder farmers who has been
the backbone of Ghana’s economy for decades is
at a risk, and there is the need to protect the
human health and the environment in order to
sustain the cocoa industry in a sustainable manner.
One limitation of this study is that it was based
on self-reported data that depends heavily on the
sincerity of the participants, which is subject to
some extent of biases (Weinstein and Klein 1996;
Jallow et al. 2017). Self-reported studies may include
some inaccurate data such as respondents trying
to be politically correct or report socially desirable
behaviours. A second limitation could be the inabil-
ity to link directly health symptoms with pesticide
exposure. It could be that other factors may be
INTERNATIONAL JOURNAL OF PEST MANAGEMENT 17
responsible for the health symptoms (Jallow et al.
2017). Despite these limitations, the study provided
a window of insight into pesticide use, knowledge,
and safety practices among smallholder cocoa farm-
ers and it could assist in major policy change to
protect public health and the environment. Policy
changes are necessary to ensure the overall cocoa
beans health for global exports and for the choc-
olate industry sustainability.
5. Conclusions
The drive to earn foreign exchange through increase
cocoa productivity is huge, and so is pesticide usage.
In this study, we investigated potential exposure fac-
tors that are likely to cause harm to human health
and the environment among cocoa farmers. We found
that farmer’s method of storing, disposing, and wash-
ing of empty pesticides containers after use were
inappropriate and potentially detrimental to human
health and the environment. Farmers’ level of educa-
tion had a strong association with the toxicological
routes of entry of pesticides into the human body.
Common and frequent health symptoms experienced
by the farmers were, headache, burning eyes, skin
rashes, itching and chest pain. These health symptoms
were likely due to inappropriate and inadequate use
of PPE. It was also found that farmers’ level of knowl-
edge acquired on the dangers of pesticides was not
translated into actual use of PPE. Several factors likely
influenced the usage of PPE among farmers. Through
modellng, factors affecting the use of PPE were agro-
chemicals shops, extension services, and farmers’ dis-
trict location. The obvious implication is that these
factors must be brought into the equation for policy
interventions that could minimize farmers’ exposure
to pesticides as well as health impacts of pesticide
use in cocoa farming.
Author contributions
M.K.M conceptualization, study design, methodology,
draing and review. B.A: coordination of the pesticide
analysis, soware programming, draing.
M.K soware programing, method validation, interpreta-
tion of results, review and editing of this article. S.S.L
method validation, review and editing of the article and
R.K.K soware programming, review and editing of the
article. All authors M.K.M., M.K., B.A., S.S.L., and R.K.K.
revised the manuscript critically for important intellectual
content and approved of the version to be published.
Acknowledgments
We acknowledged the support of Mr Gabriel Addae of
Ministry of Food and Agriculture (MoFA), Extension
Services Division and the COCOBOD Extension Officers,
together with the farmers during the survey.
Disclaimer
The authors declare that the findings and conclusions
in this article are those of the authors and do not rep-
resent the views of the organisations of affiliation or
agencies.
Disclosure statement
No potential conict of interest was reported by the
authors.
Ethics consent and permissions
All participants agreed to participate in the research study,
and they were free to participate without duress and
coercion.
Funding
is study was not funded by any grant.
ORCID
Michael K. Miyittah http://orcid.org/0000-0002-2033-7108
Data availability statement
e authors conrm that the majority of the data sup-
porting the ndings of this study are available within this
article.
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