Research Article
Olabisi Adetutu Adebanjo
Olabisi Adetutu Adebanjo
Corresponding
Author
Department of
Agricultural Technology, School of Technology, Yaba College of Technology,
Yaba, Lagos State, Nigeria.
Email: olabisi508@gmail.com, Tel: +07064989905
Folasade Oluremi Aminu
Folasade Oluremi Aminu
Department of
Agricultural Technology, School of Technology, Yaba College of Technology,
Yaba, Lagos State, Nigeria.
Olarenwaju Biodun Samuel
Olarenwaju Biodun Samuel
Department of
Agricultural Technology, School of Technology, Yaba College of Technology,
Yaba, Lagos State, Nigeria.
Abstract
This study aimed to assess the
health effects of fish processing among artisanal fish processors (AFP) in Epe
Local Government Area, Lagos State, Nigeria. A total of 120 respondents were selected using multi-stage sampling procedures.
Stage one is purposive selection of Epe LGA, stage two is the selection of
eight (8) wards from 19 wards in the LGA, lastly, random selection of 15 AFP
from each of the ward selected. Descriptive
statistics and logistic regression analysis were used. Results revealed that
majority (97.5%) of the processors were female with mean age of 38 years and
mean household size of 7 persons. Furthermore, 59.2% of the fish processors
processed sea fish with average processing experience of 13 years and mean
monthly income of ₦55,784.00k. The major health effects of fish
processing in the study area were eye irritation, back pain and sprain, excess
heat/cold, respiratory ailment, malaria, skin cuts and burns. Treatment sought
during illness was traditional and orthodox (54.2 %) and higher proportion (58.3%) depends on
family and friends as a coping strategy during illness. Logistic regression
revealed that sex, age, marital status, years of fish processing (p˂0.01)
labour source, frequency of processing (p˂0.10)
and processing medium (p˂0.05)
were significantly associated with the health
issues experienced by AFP. It can be
concluded that AFP in the study area was affected by various occupational
health issues. Thus, it is recommended AFP should be sensitized on preventive
measures (such as regular use of masks, gloves, gumboots, check-ups etc.) to
minimize occupational health hazards associated with fish processing.
Abstract Keywords
Fish processors;
effects; health issues; artisanal; processing; hazard.
1. Introduction
Fishing like any other hunting activities has been a
major source of protein for human race and has put an end to the unsavory
outbreak of anemia, kwashiorkor and so on. Fish is one of the most diverse
groups of animals known to man with more than 20,500 species in existence,
there are more species of fish than any other vertebrates. According to [1]. Fishery sub-sector was reported to have
contributed an average of about 10% of agricultural GDP between 2008 and 2012,
fisheries are also known as an enviable sub sector which provides employment to
the large proportion of the nation's population (about 65-70%) especially those
in riverine and fishing communities. Fish farming also generates employment
directly and indirectly in terms of people employed in the production of
fishing output and other allied businesses. In Africa, marine and inland
fisheries contribute towards the food security of 200 million Africans and the
income of 10 million engaged in production, processing and trade [2]. Studies have shown that between 40% and 45 %
of rural workforce in Lagos state engage in small scale artisanal fisheries.
Artisanal fisheries according to Pauly, [3] are
the sector that employs traditional methods in carrying out their operational
activities which includes capturing, preservation (processing) and distribution
of fish and fish product. Fish processing involves all the activities that are
associated with fish and its products from time of fish harvest to the time the
fish is on the consumer’s table [1] Several
methods such as smoking, frying, boiling, drying, fermentation and canning have
been used for processing. However, the most commonly used methods among the
Nigerian small scale fish processors have been smoking and drying [4]. Fish processing is the most hazardous aspect
of fish farming that poses several occupational health hazards. Fish processing
workers are often susceptible to many physical, chemical, ergonomic and
biological hazards in the course of their work. All fish processing activities
are hazardous due to their nature and working environments. Considering that
most of these AFP do not put in place necessary safety aids, absence of
improved fish processing technologies and the fact that trainings were
not acquired on the different processing activities [5]
Thus, AFP are often faced with various occupational hazards which ranges
from redness/swelling of the eye (which is the commonest) to mechanical and
electrical accidents, bacterial and parasitic infections, noise induced hearing
loss, allergic respiratory diseases (Smoke inhaled by processors smoking fish
and fryers is of serious health risks as it can cause asthma and other
respiratory ailments.), and stress related health problems. The occupational
hazards, safety concerns and risks to health in the fish processing industry
are based on the types of operation, scale of production and the specific
species of interest. Processing is often handled and processed in unhygienic
conditions causing spoilage, contamination with disease causing germs and
leading to loss of fish, the farmers’ income and indirectly affect the health
of the processors. The U.S Government accountability office [6] identifies poor health in the agricultural workforce
as one of the major causes of chronic malnutrition (food insecurity) in
sub-Sahara Africa. Poor health has a significant negative impact on the growth
of developing countries. Good health is central to fishing activities but the
fishers are prevented from putting their maximum efforts into fish processing
due to common illnesses such as cold, fever, typhoid, flu and many others that
affect their maximum production efficiency [7] thus,
whatever affect the work force will affect fish production (processing).
Therefore, it is in this line that the study tends to;
i.
Describe the socio-economic
characteristics of the artisanal fish processors in Epe LGA.
ii.
Identify the respondents fish processing
characteristics in the study area.
iii. identify
the prevalent and frequency of health issues associated with fish processing
among artisanal fish processors in Epe LGA, Lagos state, Nigeria.
iv. Investigate
the constrains of fish processing in the study area.
2. Materials and methods
The study was conducted in Epe Local
Government area of Lagos State Nigeria. Epe is a city located in the North-east
of Lagos State, bounded to the South by the Lagos Lagoon, to the north by a
boundary with Ogun state (Ijebu-O de). Epe has a total land area of 965 km2
(373 sq m) and Coordinates at 60 35’40.54N and 30
58’39.59E, with current population of over 184711,000 (Census,2006). Fishing,
crop farming and trading is their major occupation. Multi-stage sampling
procedure was adopted in this study. The first stage involved the purposive
selection of Epe local government area, (LGA), due to the prominence of fish
farming, rearing and processing in the local government. The second stage is
the purposive selection of 40% wards from 19 wards in the LGA which gave eight
(8) wards. Stage three involved the use of simple random sampling selection of
fifteen AFP from each of the communities. This gave a total of one hundred and
twenty (120) respondents which constitute the sample size of the study. Data
collected were analysed using descriptive statistics and Logit regression
model. Specifically, logit regression was employed to determine the effect of
fish processing and socio-economic factors on the health of the respondents.
"The logit model assumes that the probability of a fish processor falling
sick (Pi) as a result of fish processing is a function of an index (Zi), which
is the inverse of the standard logistic cumulative function of Pi. Zi is also
the inverse of the standard logistic cumulative function of Pi, i.e.,
The dependent variable (Yi) is a dummy. It takes the
value of 1 if the farmers fall sick and 0 if otherwise.
In regression analysis, a dummy variable is a
regressor that can take only two values: either 1 or 0 they are typically used
to encode categorical features.
Zi = bo + biXi+ b2X2+ b3x3 +……………………………………bn+Xn
Where:
Z = Probability of falling sick
x=
Coefficient of explanatory variable which increase or decrease
X1= Age (in years)
X2= Sex (male or female)
X3= Educational level (years spent in
school)
X4= Marital status
X5= Household size (No of people)
X6= years of processing
X7= labour source
X8=processing methods
X9= frequency of processing
X10= access to credit
X11= cooperative membership
X12 = monthly income (₦)
X13= Extension contacts
E = Error term
bo= constant
3. Results and
discussion
The findings in Table 1 reveal the socio-economic
characteristics of the respondents. It reveals majority (97.5%) of the
respondents were female while 2.5% were male. This implies that fish processing
activities are mostly dominated by women and they play vital role in fish
industry. This is in line with [8]. The
results on Table 1 also reveals that, 54.2% of the fish processors were in the
age range of 31-40 years, 40.8% were between 41 and 50 years old, while 9.1%
and 4.2.7% were in age ranges of 20 - 30 years and older than 50 years respectively.
The mean age was found to be 38 years. This is an indication that artisanal
fish processors in the study area were still within the active economic age
group and are still proactive and productive in their occupation. Majority
(50.8%) of the respondents attained secondary education, 27.5% had no formal
education 1.7% obtained adult/vocational education. Education appears to play a
vital role in every individual disposition knowledge on activities done and
adoption of technology. This agrees with
the study of [9]. The Majority (81.2%) of
the fish processors were married while 9.2 % were widows. Only about 5.8% and
3.3% were divorced respectively. The proportion of married fish processors
could be to ensure food security to the household at easy daily reach. This is
in line with the findings of [10] which
reported that marriage is a highly cherished institution with great
responsibility to for household needs. Also, the mean household size was
about 7 persons. Fish processing requires more manual labours, consequently,
households with a larger number of family labours are more likely to work
efficiently and productively. Table 1 also shows that 59.2% of the respondents
were Christian while 35.0% of them were Islam and 5.8% practice traditional
worshiping. This indicates that religion is not a barrier when it comes to
artisanal fish processing. Major activities of the respondents were fish
farming and processing (40.8%) while 37.5% and 21.7% were involved in fish
processing and fish capturing alone, their average years of processing
experience was 13years with the mean monthly income of #55,784.00 this implies
that artisanal fish processors are well groomed in fish processing activities
which however, commensurate with their income. Finally, Table 1 also reveals
that majority (74.2%) of the fish processors used family labour, while 72.5%
had no access to credit facilities with 62.5% not belonging to any cooperative
society and almost 94.2 % all of the fish processors once had contact with an
extension service agent.
Table 1.
Socio-economic characteristics of the respondents
Characteristics |
Frequency (n= 90) |
Percentage |
Mean |
Age |
|
|
|
20-30 |
5 |
4.2 |
|
31-40 |
65 |
54.2 |
|
41-50 |
39 |
32.5 |
|
≥50 |
11 |
9.1 |
38years |
Sex |
|
|
|
Female |
117 |
97.5 |
|
Male |
3 |
2.5 |
|
Educational status |
|||
No formal education |
33 |
27.5 |
|
Primary |
22 |
17.5 |
|
Secondary |
61 |
50.8 |
|
Adult / Vocational |
2 |
1.7 |
|
Marital status |
|
|
|
Single |
11 |
9.2 |
|
Married |
98 |
81.7 |
|
Divorced |
7 |
5.8 |
|
Widowed |
4 |
3.3 |
|
Household size |
|||
≤5 |
12 |
10 |
|
6-10 |
85 |
70.8 |
|
≥10 |
23 |
19.2 |
7 persons |
Religion |
|
|
|
Christian |
71 |
59.2 |
|
Islam |
42 |
35.0 |
|
Traditional |
7 |
5.8 |
|
Major activity |
|||
Fish rearing |
26 |
21.7 |
|
49 |
40.8 |
|
|
45 |
37.5 |
|
|
Processing experience(yrs.) |
|||
≤5 |
28 |
23.3 |
|
6-10 |
23 |
19.2 |
|
11-15 |
29 |
24.2 |
|
16 and above |
40 |
33.3 |
|
Monthly income (#) |
|||
≤30,000 |
44 |
36.7 |
|
31,000-60,000 |
56 |
46.7 |
|
61,000-90,000 |
15 |
12.5 |
|
≥90,000 |
5 |
4.2 |
#55,784.00 |
Hired |
15 |
12.5 |
|
Family |
89 |
74.2 |
|
Both |
16 |
13.3 |
|
Access to credit |
|||
Yes |
87 |
27.5 |
|
No |
33 |
72.5 |
|
Extension contacts |
|||
Yes |
7 |
5.8 |
|
No |
113 |
94.2 |
|
Cooperative membership |
|||
Yes |
45 |
37.5 |
|
No |
75 |
62.5 |
|
Source: Field Survey data, 2022 |
3.1 Processing
characteristics and methods
Table 2 reveals the fish processors’
characteristics. It shows that majority (72.5%) of the artisanal fish
processors processed frozen fish, results in Table 2 also reveal that smoking
(55.8 %) is the major method of processing fish in the study area which they
engaged on a daily basis (70.8%) This indicates that smoking is the major
method of fish processing in the study area. The results show that the brick
kiln (Agbado type) was commonly used by 55.8% of the fish processors as
compared with the Altona smoking kiln and drum type which were used by 26.7%
and 17.5% of the fish processors respectively. This result is supported by the
findings of [11] who positioned that primitive
means of smoking is still in operation in some rural areas. It also
corroborates with the findings of [12] who
characterized artisanal fishery by low technology application. Furthermore,
based on pre-processing activities, results show that close to two-thirds (65.8
%) of the respondents allowed the fish to deice before degutting. Also, almost
all (93.3%) of the
artisanal fish processors practiced degutting before smoking their fishes while
one-third of the respondents salts their fish before processing.
Table 2. Processing characteristics of the respondents in the study area
|
Variables |
Frequency (n= 120) |
Percentage |
|
Type of fish process |
|
|
|
Frozen |
87 |
72.5 |
|
Sea fish |
33 |
27.5 |
|
Processing method |
||
|
Frying |
44 |
36.7 |
|
Smoking |
67 |
55.8 |
|
Drying |
8 |
6.7 |
|
Solar drying |
1 |
0.8 |
|
Frequency of fish processing |
||
|
Daily |
85 |
|
|
Once in a week |
5 |
4.2 |
|
Twice a week |
26 |
21.7 |
|
≥ Thrice |
4 |
3.3 |
|
Types of smoking kiln used |
||
|
Brickkiln with mesh
tray (agbado) |
67 |
55.8 |
|
Drum type |
21 |
17.5 |
|
Altona kiln |
32 |
26.7 |
|
Pre- processing activities* |
||
|
Soaked to deice |
79 |
65.8 |
|
Degutting |
105 |
93.3 |
|
Clean with water |
92 |
76.6 |
|
Salting |
52 |
43.3 |
Source: Field survey data, 2022 |
|||
3.2 Common
health issues associated with fish processors in the study
Table 3 presents the common health issues associated
with artisanal fish processors, from the table it revealed that eyes
irritation, back strain and sprain, Excessive heat and cold, Respiratory
ailments, Malaria, Skin cuts and burns, Sting from fish spines and headaches
were the common health issues associated with fish processors in the study area
with (85.8, 79.1%, 68.3%, 65%, 56.7%, 55.8%, 50.8% and 50.8%)
respectively. This result conforms to
the finding of [13], who reported that every
aspect of fishery activities has a peculiar occupational hazard that is
associated with their operational mode [14] and
observed that fish processing workers have a higher incidence of chronic
respiratory symptoms compared to workers in other sectors due to their frequent
exposure to fish aerosols, which presents a significant risk for the
development of respiratory diseases. Also, the International Food Policy
Research Institutes [15], stated that the
higher incidences of skeletal muscular and postural health problems such as
joint pains and back pains are perhaps indicative of work-related health
hazards. This may be due to the long and consistent bending, sitting and
standing posture of the fish processors during production. The Bone dislocation
was the least common health issue, reported by only 6.7% of respondents. Some
respondents mentioned that they had fallen due to the slipperiness of their
working environments.
Table 3. Common health issues associated with fish processing in the study area
Health
issues
|
Frequency (n= 120) |
Percentage |
Respiratory ailments |
78 |
65.0 |
Excessive heat and cold |
82 |
68.3 |
Back Strain and Sprain |
94 |
79.1 |
Bruise |
48 |
40.0 |
Eyes irritation |
103 |
85.8 |
Sting from fish spines |
61 |
50.8 |
Skin cuts and burns |
67 |
55.8 |
Whitlow |
58 |
48.3 |
Headache |
61 |
50.8 |
Malaria |
68 |
56.7 |
Typhoid |
43 |
35.8 |
Broken bone or dislocation |
8 |
6.7 |
*Multiple response: Source: field survey
data, 2022 |
Results in Table 4 reveal the episodes of health
issues in a year and treatment sought. It shows that majority (62.5%) of the
artisanal fish processors experienced health issues 1-3times a year, followed
by 31.7% and 5.8% of the processors who experienced health issues between 4-6
times in above 7 times in a year respectively the average episodes of ill
health experienced by the fish processors was 4 times a year. This indicates
that fish processing often poses treat to the health of the fish
processors. Also, the information in
table 3 shows that half (54.2%) of the artisanal fish processors implore the
use of traditional and orthodox treatment during ill health. This implies that
the respondents have access to modern health facilities in the study area, yet
still rely on the use of local herbs and some mention because it is freely
available. The major coping strategy
during health issues is to fall back on their savings (58.3%) or borrow (50.8%)
from friends while 41.7 % just stop fish processing during illness. This
finding contrasts with the findings of [16]), who reported that intra-household labour
substitution was the most common coping strategy among fisher households in
Lagos State.
Table 4. Episodes of health issues in a year and treatment sought (n= 120)
Variables |
Frequency (n= 90) |
Percentage |
Mean |
Episodes of health issues (yrs.) |
|
||
1-3 |
75 |
62.5 |
|
4-6 |
38 |
31.7 |
|
>6 |
7 |
5.8 |
3.87±0.954 |
Treatment sought |
|||
Traditional |
39 |
32.5 |
|
Orthodox |
10 |
8.3 |
|
Traditional and orthodox |
65 |
54.2 |
|
None |
6 |
5.0 |
|
Coping
strategies adopted |
|
||
Hired labour |
15 |
12.5 |
|
Family and friend |
12 |
10.0 |
|
Savings |
70 |
58.3 |
|
Borrowing |
61 |
50.8 |
|
Stop work |
50 |
41.7 |
|
Source: field survey data, 2022. |
3.3 Effects
of fish processing and socio-economics factors on the health of artisanal fish
processors in Epe LGA.
Results in Table 5 present the effect of
fish processing and socio-economic factors on the health of artisanal fish
processors in the study area. The Nagelkerke R2 was 0.875 which
indicates that about 87 % of the variation in effect of fish processing on the
health of the respondents was jointly explained by the independent variables
included in the model. The Chi-Square of 78.01 (p<0.01) was significant
attesting to the goodness of fit of the model. The results reveal that sex,
age, marital status, household size, labour type, years of fish processing,
processing method and frequency of processing were significant factors
influencing the health of the artisanal fish processors in the study area.
The coefficient of age of the
respondents was positive and significant at 1% level of probability. This
implies that the probability that the fish processors will fall sick increases
with age. The older processors were more likely to fall sick as a result of
fish processing than the younger ones. This agrees with [17] and [18] that the
body’s immune system becomes weak with age. The coefficient of sex had a
positive significant relationship with probability of falling sick at 1% alpha
levels. This implies that the likelihood of experiencing health issues
increases with the female processors in the study area. In the same vein,
labour type and frequency of fish processing were found to be positively
significant at one-tailed test. The positive significant relationship of labour
type implies that, fish processors reliance on family labour will increase the
probability of falling sick. This might be because members of the family were
engaging in off-farm employment thereby reducing their participation in fish
processing activities in the study area. Furthermore, the probability of the fish
processors falling sick or having health issues as a result of fish processing
increases with the frequency of fish processing by 10% in the study area. This
suggests that the more exposure of the processors are to smoke, cold fish, cuts
etc. the more they experience health issues. A day increases in the frequency
of processing will increase the probability of falling sick by 1.833% in the
study area. This result affirms the reports by [19]
that the probability that agro-food processors would fall sick increased
with the time spent working.
Conversely, the coefficients of marital
status (p<0.01), household size (p<0.10) and processing method
(p<0.05) had negative significant relationship with the probability of the
fish processors falling. This implies that probability of falling sick
decreases with these variables in the study area. Based on marital status, it
is expected that numbers of health issues episodes experienced by the fish
processors will reduce due to assistance/support from their spouse i.e they
will be less susceptible to health challenges than their single counterpart.
This is corroborated by [20] studies who
concluded that single people had substantially higher risk of driver injury
than the married people. Also, household size will reduce stress and fatigue
associated with fish processing due to the availability of more members to
work. This concurs with the findings of [21].
Table 5. Logit regression results on effects of fish
processing and socio-economics factors on the health of artisanal fish
processors in Epe LGA.
Characteristics |
β Coefficients |
Wald |
Significance |
|||||
Age
|
|
2.832 |
|
4.431*** |
0.000 |
|
|
|
Sex
|
0.442 |
|
2.623*** |
0.009 |
|
|
|
|
Educational
status |
0.013 |
|
0.151 |
|
0.880 |
|
|
|
Marital
status |
|
-0.257 |
|
-3.539*** |
0.001 |
|
|
|
Households
size |
0.273 |
|
1. 843* |
0.080 |
|
|
|
|
Labour
type |
|
-0.089 |
|
1.845* |
|
0.089 |
|
|
Years
of processing |
0.208 |
|
3.469*** |
0.001 |
|
|
|
|
Access
to credit |
0.382 |
|
1.658 |
|
0.044 |
|
|
|
Cooperative
membership |
2.863 |
|
1.658 |
|
0.884 |
|
|
|
Extension
contacts |
|
-0016 |
|
-2.453 |
|
0.832 |
|
|
Processing
methods |
|
-0.098 |
|
-2.407** |
0.053 |
|
|
|
Frequency
of processing |
1.354 |
|
1.833* |
|
0.070 |
|
|
|
Constant
|
|
|
1.064 |
|
0.369 |
|
0.785 |
|
Model
summary Loglikelihood ratio= 210.64 Nagelkerke R2 =0.875 Chi-square = 78.01 |
||||||||
Significant at * 10%, ** 0.5 *** 1%; Source: field survey data, 2022. |
3.4 Constraints
of fish processing in the study area
The result in Table 6 explain the constraints faced
by artisanal fish processors in the study area. A 5-point Likert-like scale
(ranging from strongly agree, agree, undecided, strongly disagree and disagree)
was used. Value of the discriminating index was calculated: (5+4+3+2+1)/5= 3.0.
Thus, the mean value greater than or equals to 3.0 indicates that the
respondents agreed (A) to the variable as a constraint and any mean less than
3.0 implies that respondents disagree (DA) with such variable as a constrains
to fish processing in the study area.
The constrains were ranked according to their means which indicate the
level of severity of these constrains as a limitation to the fisherfolks
production efficiency and profitability.
According to some of the respondents the increases in
prices of firewood and transportation has really reduced their market returns.
“If the price of all these inputs continue increasing, we may stop fish
processing business as stated by one of the fish processors”. Thus, it become expedients for the
government to intervene on the alarming constrains in the fish processing
industry. This is in consonance [22] who also identify the
major constraints faced by women fish processors to be insufficient capital,
lack of improved processing facilities, and storage facilities.
Table 6. Mean scores of constraints of fish to processing in the study area (n = 120)
Constrains |
χ |
Rank |
Remarks |
Cost of inputs (charcoal, salts etc.) |
4.89 |
1st |
A |
Transportation
cost |
4.72 |
2nd |
A |
Poor access to credit |
4.59 |
3rd |
A |
Market price
fluctuation |
4.46 |
4th |
A |
Poor pricing of fish |
3.78 |
5th |
A |
Heavy workload |
3.59 |
6th |
A |
Inadequate
water supply |
2.78 |
7th |
DA |
Spoilage
of fish |
2.69 |
8th |
DA |
Discrimination |
2.43 |
9th |
DA |
Poor market access |
2.38 |
10th |
DA |
Cost
of labour |
2.35 |
11th |
DA |
Source:
Field Survey, 2022. A= Agreement DA=
disagreement |
|||
|
4.
Conclusions
In conclusion, this study has
highlighted the significant health risks and hazards associated with fish
processing among artisanal fish processors in Epe Local Government Area. The
study showed that majority of the artisanal fish processors in the study area
processed frozen fish on daily basis using the old traditional brick kiln known
as agbado. The study identified various health issues that ranged from
respiratory ailments, eyes irritation, back strain and sprain,
excessive heat and cold, malaria, skin cuts and burns, sting from fish spines
and headache. The study further indicated that sex, age, and years of fish
processing, households’ size,
labour type and frequency of fish processing and processing medium are
significantly associated and contributing to the frequency and forms of health
issues experienced by the fish processors in the study area. The therefore recommends some measures to help lessen the frequency at
which artisanal fish processors experienced health issues associated with fish
processing in the study area.
i. Government intervention through bank of agriculture (BOA) in the area of
loans and credit availability for fish processors to help acquire inputs that
will facilitates their production.
ii. Also, government provision of improved processing mediums such as solar
dryer, gas oven, and Altona smoking kiln will help to reduce their constant
exposure to smoke inhalation and all other job hazards.
iii.
Sensitization by extension contact agent on how to take
precautionary measures against the occupational hazards (such
as regular use of mask, gloves, gumboots etc.) and how to promptly deal
with the consequences lest their families lose their source of livelihood. As
well as awareness and introductions of improved processing technology to the
artisanal fish processors.
iv. Regular medical check-ups and health education should be provided to
artisanal fish processors to improve their health status and well-being.
v. Further research should be conducted to investigate the specific
occupational health hazards and risks associated with the different types of
fish processing methods and processing medium used in the study area.
Authors’ contributions
Contributed to the paper idea, title, questionnaire design, data analysis
and wrote the manuscript, O.A.A.; Analysed data and assisted in writing the
manuscript, F.O.A.; Collected and coded data, O.B.S.
Acknowledgements
The authors hereby acknowledge the efforts of Odubitan Semiat Oluwaseun of
Yaba college of technology who also assisted in collection of data
Funding
This research was self-funded by the authors and did not receive funding
from any source.
Availability of data and materials
All data will be made available on request according
to the journal policy.
Conflicts of interest
Authors have
declared that no competing interests exist.
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Abstract
This study aimed to assess the
health effects of fish processing among artisanal fish processors (AFP) in Epe
Local Government Area, Lagos State, Nigeria. A total of 120 respondents were selected using multi-stage sampling procedures.
Stage one is purposive selection of Epe LGA, stage two is the selection of
eight (8) wards from 19 wards in the LGA, lastly, random selection of 15 AFP
from each of the ward selected. Descriptive
statistics and logistic regression analysis were used. Results revealed that
majority (97.5%) of the processors were female with mean age of 38 years and
mean household size of 7 persons. Furthermore, 59.2% of the fish processors
processed sea fish with average processing experience of 13 years and mean
monthly income of ₦55,784.00k. The major health effects of fish
processing in the study area were eye irritation, back pain and sprain, excess
heat/cold, respiratory ailment, malaria, skin cuts and burns. Treatment sought
during illness was traditional and orthodox (54.2 %) and higher proportion (58.3%) depends on
family and friends as a coping strategy during illness. Logistic regression
revealed that sex, age, marital status, years of fish processing (p˂0.01)
labour source, frequency of processing (p˂0.10)
and processing medium (p˂0.05)
were significantly associated with the health
issues experienced by AFP. It can be
concluded that AFP in the study area was affected by various occupational
health issues. Thus, it is recommended AFP should be sensitized on preventive
measures (such as regular use of masks, gloves, gumboots, check-ups etc.) to
minimize occupational health hazards associated with fish processing.
Abstract Keywords
Fish processors;
effects; health issues; artisanal; processing; hazard.
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