Socio-demographic characteristics
A total of 738 households have participated in this study with a response rate of 99.7%. Out of the total participants, 410 (55.6%) were male. The mean age of the respondents was 40.2 (SD = ± 12.24) years. Almost all of respondents 733 (99.3%) were orthodox Christian, and the majority of the respondents 664(90.0%) were married. Concerning the educational status majority, 648 (87.8%) of the participants were illiterate. Above half of the respondents, 438 (58.9%) had 4–6 family members in their house. The mean household member was 5.01 (SD ± 1.72). The economic status of the respondents was assessed using the wealth index which showed, 19.0%, 20.3%, 19.2%, 18.8%, and 22.6% of the respondents ranked as wealthiest, wealthy, medium, poor, and poorest respectively. (Table 1)
Table 1
SOCIO DEMOGRAPHIC CHARACTERISTICS OF RESPONDENTS FOR KNOWLEDGE AND PRACTICE TOWARDS MALARIA PREVENTION IN WEST BELESA, AMHARA REGION, ETHIOPIA, 2019.
Variable
|
N=766
|
Frequency
|
percent
|
Age
|
18-24
|
49
|
6.6
|
25-34
|
193
|
26.2
|
35-44
|
234
|
31.7
|
45-54
|
165
|
22.4
|
55-64
|
66
|
8.9
|
>64
|
31
|
4.2
|
Sex
|
Male
|
410
|
55.6
|
Female
|
328
|
44.4
|
Religion
|
Orthodox
|
733
|
99.3
|
Others
|
5
|
0.7
|
Educational status
|
Illiterate
|
648
|
87.8
|
Literate
|
48
|
6.5
|
Formal education
|
42
|
5.7
|
Marital status
|
Married
|
664
|
90.0
|
Divorced
|
26
|
3.5
|
Not married
|
35
|
4.7
|
Widowed
|
13
|
1.8
|
Number of family members
|
<4
|
157
|
21.3
|
4-6
|
435
|
58.9
|
>6
|
146
|
19.8
|
Wealth index
|
Poorest
|
167
|
22.6
|
Poor
|
139
|
18.8
|
Medium
|
142
|
19.2
|
Wealthy
|
150
|
20.3
|
Wealthiest
|
140
|
19.0
|
Respondents Practice on Malaria prevention and control methods.
Most of the households 582(78.9%) did not have LLINs. A total of 212 LLINs were identified in 156(21.1%) households; of which 100(64.1%) received one LLINs and the remaining 56(35.9%) households received two LLINs from the government. Regarding utilization out of the mosquito bed net owners, 107(68.6 %) of them used the mosquito bed net in the previous night of data collection. Of the total respondents, 22(3%) of them used LLINs for other purposes. (Table 2)
In this survey the most frequently used malaria prevention method was IRS (80.5%) of which 130(17.8%) were re-plastered within six months after spray operation has been carried out. and the least frequently used malaria prevention methods were Closing windows and doors early in the evening (3.8%). In this study, 77.0% of the respondents participated in environmental measures such as compact and drainage to control malaria and 40.2% of the respondents participated in clearing the vegetation. Above half 408(55.3%) of the respondents have been participated in epidemic control. (Table 2)
Overall total respondents 379 (50.9%) of respondents had good practices (with 95% CI, 47.2–54.5) and 362(49.1%) of the respondents had poor practice towards malaria prevention and control overall. The median practices score for all respondents was 4 out of a possible 11 points (IQR = 2–4)
Table 2
practice on malaria prevention in west Belesa, North West Region, Ethiopia, 2019.
Practices toward malaria prevention and Control methods
|
N = 738
|
Percent
|
At least one LLIN
|
156
|
21.1
|
Use of LLIN in the previous night
|
107
|
14.5
|
IRS
|
594
|
80.5
|
Use of mosquito proofing in windows and doors
|
156
|
21.1
|
Closing windows and doors early at night
|
28
|
3.8
|
Environmental management (compact and drainage) to prevent malaria
|
568
|
77.0
|
Clear the vegetation
|
297
|
40.2
|
Participated in Epidemic control
|
408
|
55.3
|
Re-plastering the wall in 6 months of IRS spray
|
131
|
17.8
|
Others preventions methods
|
38
|
4.96
|
• Others preventions methods = smoking in the house, take tablets and using Aerosol spray |
In the FGD discussion, the IRS operation has a long history in their locality about half of the respondents explained that their house was sprayed in the last 12 months. The majority of the discussants participated in the IRS by preparing their house and fetching water for spray preparation. A 50 years old female participant in Abaytera kebele explained "we prepare the house for spray by renewing the wall, take out of materials which we use in the house, we keep away home animals and children for some hours, and fetch the water for spray."
As the discussant expressed there were few refusals and plastering of the wall in six month of spray due to different reasons such as miss-understanding of IRS chemicals; miss-conception of the chemical as a multiplier of other insect nuisance; and the current IRS chemical is less efficacious and expires in a short time to kill mosquitoes than the previous brands (i.e. DDT). A 60 years old male in Menti kebele FGD explained "The current yellow color IRS chemical is less efficacious and expires in a short time."
In the discussions, the majority of the participants did not own LLINs. All groups in the discussions indicated that LLINs’ inaccessibility to buy and lack of provision appeared to contribute to the low household insecticide bed net ownership. A 39 years old male in Abaytera kebele FGD explained "for the last time the bed net was distributed three years ago." Somewhat surprisingly, in the discussion, some of them mentioned that there was the use of LLINs for others beyond the intended purpose. In Kalay kebele FGD participants, "We use the bed net for other purposes due to old age of the LLINs and lack of awareness." Some of the discussants also mentioned that nowadays there is a decrement in the efficacy of LLINs brands.
The discussants participated in environmental management (compact, drain, and clearing the vegetation) in Abaytera FGD "we participate in malaria prevention in environmental management using 1 to 5 group male and female groups and the group leaders organize every activity."
Determinants of practice towards malaria prevention and control
From the multivariable model, it was found that those individuals who live in Menti kebele had about 4 times increased odds of having a good practice as compared with respondents who live in Aswagari kebele [AOR = 3.88, 95% CI: 2.43, 6.20]. The odds of having good practice is decreased by 35% among female respondents as compared to male respondents [AOR = 0.65, 95% CI: 0.47, 0.90,]. The odds of having a good practice is decreased by 66% among illiterate respondents as compared to respondents who had formal education [AOR = 0.34, 95% CI: 0.16, 0.72. Moreover, the odds of having a good practice is decreased by 55% among respondents in the poorest wealth quintile as compared to the wealthiest [AOR = 0.45, 95% CI: 0.27, 0.76]. Similarly the odds of having good practice was decreased by 49%, 76%, and 79% among respondents in poor, Medium and wealthy wealth quintiles respectively as compared with wealthiest wealth quintiles with [AOR = 0.51, 95% CI: 0.30, 0.88]; [AOR = 0.24; 95% CI: 0.14, 0.42]; and [AOR = 0.21 95%CI: 0.12, 0.36] respectively. The odds of having good practice was decreased by 48% among respondents who have poor knowledge about malaria prevention as compared to their counterparts [AOR = 0.52, 95% CI: 0.36, 0.75]. (Table 3)
Table 3
determinants of malaria prevention and control Practice in West Belessa, North West Ethiopia, 2019.
Variable
|
Response
|
Level of Practice
|
|
|
Good (%)
|
Poor (%)
|
COR(95%CI)
|
AOR(95%CI)
|
P-value
|
Resident’s Kebele
|
Kalay
|
39(5.3)
|
70(9.5)
|
0.68(0.42–1.11)
|
0.62(0.37–1.05)
|
0.08
|
Abaytera
|
56(7.6)
|
94(12.7)
|
0.73(0.47–1.14)
|
0.68(0.43–1.09)
|
0.11
|
Menti
|
160(21.7)
|
48(6.5)
|
4.10(2.66–6.32)
|
3.88(2.43–6.20)
|
< 0.001
|
Amstya
|
38(5.1)
|
48(6.5)
|
0.97(0.58–1.63)
|
0.99(0.57–1.72)
|
0.96
|
Aswagari
|
83(11.2)
|
102(13.8)
|
1
|
1
|
|
Sex
|
Female
|
139(18.8)
|
189(25.6)
|
0.54(0.4–0.72)
|
0.65(0.47–0.90)
|
0.01
|
Male
|
237(32.1)
|
173(23.3)
|
1
|
1
|
|
Educational status
|
Illiterate
|
317(43.0)
|
331(44.9)
|
0.38(0.19–0.76)
|
0.34(0.16–0.72)
|
0.005
|
Literate
|
29(3.9)
|
19(2.6)
|
0.27(0.61–1.486)
|
0.39(0.15–1.04)
|
0.06
|
Formal education
|
30(4.1)
|
12(1.6)
|
1
|
1
|
|
Wealth index
|
Poorest
|
82(11.1)
|
85(11.5)
|
0.37(0.23–0.60)
|
0.45(0.27–0.76)
|
0.003
|
Poor
|
77(10.4)
|
62(8.4)
|
0.48(0.29–0.79)
|
0.51(0.30–0.88)
|
0.02
|
Medium
|
86(11.7)
|
56(7.6)
|
0.25(0.15–0.41)
|
0.24(0.14–0.42)
|
< 0.001
|
Wealthy
|
90(12.2)
|
60(8.1)
|
0.26(0.16–0.42)
|
0.21(0.12–0.36)
|
< 0.001
|
Wealthiest
|
101(13.7)
|
39(5.3)
|
1
|
1
|
|
Knowledge level
|
Poor
|
61(8.3)
|
116(15.7)
|
0.41(0.29–0.58)
|
0.52(0.36–0.75
|
0.001
|
Good
|
315(42.7)
|
245(33.2)
|
1
|
1
|
|