| Literature DB >> 35482740 |
Salem Endris1, Zemenu Tamir1, Abay Sisay1.
Abstract
BACKGROUND: Biomedical wastes (BMWs) generated from medical laboratories are hazardous and can endanger both humans and the environment. Highly infectious biomedical wastes are produced at an unacceptably high rate from health laboratories in developing countries with poor management systems, such as Ethiopia. The purpose of this study was to assess the rate of biomedical waste generation, management practices, and associated factors in public healthcare medical laboratories in Addis Ababa, Ethiopia.Entities:
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Year: 2022 PMID: 35482740 PMCID: PMC9049513 DOI: 10.1371/journal.pone.0266888
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
Socio-demographic characteristics of study participants in Addis Ababa, Ethiopia (n = 362).
| Socio-demographic character | Variable | Total Percent (n = 362) | ||||
|---|---|---|---|---|---|---|
| Laboratory professionals (n = 298) | Waste handlers (n = 64) | |||||
| Frequency | Percent | Frequency | Percent | |||
| Sex | Male | 168 | 56.4% | 46.4% | ||
| Female | 130 | 43.6% | 64 | 100% | 53.6% | |
| Age | <21 years | 8 | 2.7% | 18 | 28.1% | 7.1% |
| 21–30 years | 186 | 62.4% | 24 | 37.5% | 58% | |
| 31–40 years | 97 | 32.5% | 18 | 28.1% | 31.7% | |
| > 40 years | 12 | 3.9% | 4 | 6.3% | 4.4% | |
| Level of Education | 1-8th grade | 16 | 25% | 4.4% | ||
| 9-12th grade | 40 | 62.5% | 11% | |||
| Diploma | 82 | 27.5% | 2 | 3.1% | 23.2% | |
| BSC degree | 208 | 69.8% | 4 | 6.3% | 58.6% | |
| MSC | 8 | 2.7% | 2.2% | |||
| other | 2 | 3.1% | .5% | |||
| Work experience | <1 year | 20 | 6.7% | 10 | 15.6% | 8.3% |
| 1–5 years | 98 | 32.9% | 32 | 50% | 35.9% | |
| 5–10 years | 134 | 45% | 18 | 28.1% | 42% | |
| 10–15 years | 34 | 11.4% | 2 | 3.1% | 9.9% | |
| 15–20 years | 10 | 3.4% | 2 | 3.1% | 2.8% | |
| >20 years | 2 | 0.7% | 1.1% | |||
Frequency of laboratory professionals of response for knowledge item questions for a study of biomedical waste management, Addis Ababa, Ethiopia (n = 298).
| Variable | Frequency Yes | Percent |
|---|---|---|
| Knowledge about biomedical waste management policy and guidelines | 228 | 63% |
| Knowledge about the common types of biomedical waste | 92 | 30.9% |
| Knowledge about the basic components of biomedical waste management | 92 | 30.9% |
| Knowledge about the common infectious microorganisms transmitted during biomedical waste management | 162 | 54.4% |
| Knowledge about the common health hazards associated with poor biomedical waste management | 148 | 49.7% |
| Knowledge about the maximum time biomedical wastes storage | 198 | 66.4% |
| Knowledge about the color code of waste bins that suit a type of biomedical waste | 284 | 95.3% |
| Knowledge about the common modes of treatment of biomedical waste before final disposal | 40 | 13.4% |
| Knowledge about the appropriate method for final disposal of biomedical wastes | 40 | 13.4% |
| Knowledge about safety box disposal time | 284 | 95.3% |
| Received training about the biomedical waste management | 150 | 50.3% |
Daily laboratory solid waste generation rate in public health care facilities in Addis Ababa, Ethiopia, 2021 (n = 26).
| Name of health facility | Biomedical waste, kg/day | ||||
|---|---|---|---|---|---|
| Patients/ day | Total/kg/day | Mean of Infectious waste | Mean of Sharp waste | Overall mean | |
| Goro HC | 200 | 11.5 | 3.5 | 0.3 | 1.91 |
| Ferency Woreda 01 HC | 80 | 3 | 0.76 | 0.23 | 0.49 |
| Entoto kuter 1 HC | 30 | 5.5 | 1.25 | 1 | 1.125 |
| Tirunesh Beijing hospital | 134 | 9.55 | 2.265 | 0.915 | 1.59 |
| Ras desta hospital | 285 | 31 | 10 | 0.33 | 5.17 |
| Mikiland HC | 100 | 12.5 | 3.13 | 0.83 | 1.98 |
| Nifas selk woreda 2 HC | 120 | 8.5 | 2.5 | 0.33 | 1.41 |
| Arada HC | 80 | 7.5 | 1.83 | 0.66 | 1.25 |
| Ghandi memorial hospital | 180 | 6 | 1.66 | 0.33 | 0.995 |
| Menelik II hospital | 206 | 13.65 | 3.91 | 0.63 | 2.27 |
| Bisrate Gebirale HC | 200 | 14.9 | 4.5 | 0.46 | 2.48 |
| Hiwot Amba HC | 60 | 6.2 | 1.7 | 0.33 | 1.015 |
| Zewditu memorial hospital | 200 | 36 | 10 | 2 | 6 |
| Janmeda HC | 63 | 17 | 4.76 | 0.92 | 2.84 |
| Teklehaymanot HC | 70 | 16.7 | 4.43 | 1.13 | 2.78 |
| Kolfe HC | 77 | 20.1 | 5.33 | 1.36 | 3.34 |
| Yekatit 12 hospital | 170 | 10.58 | 3.303 | 1.953 | 2.62 |
| Saris HC | 42 | 13.2 | 3.6 | 0.8 | 4.4 |
| Mychew HC | 80 | 28.4 | 6.13 | 3.33 | 4.73 |
| Kality HC | 75 | 9.5 | 1.66 | 1.5 | 1.58 |
| Addis ketema Woreda 4 HC | 80 | 19.6 | 5.3 | 1.8 | 3.55 |
| Addis ketema woreda 7 HC | 70 | 7 | 1.25 | 1.08 | 1.16 |
| Entoto No.2 HC | 120 | 29 | 6.9 | 2.76 | 4.83 |
| Addis Gebeya HC | 50 | 17.2 | 3.6 | 2.13 | 2.86 |
| Semit HC | 74 | 9.7 | 2.66 | 0.56 | 1.61 |
| Kasanchis HC | 60 | 7.8 | 2.06 | 0.53 | 1.29 |
| Overall mean of Hospitals | 195.8 | 17.7 | 5.189 | 1.026 | 3.107 |
| SD of Hospitals | 50.621 | 12.507 | 3.807 | 0.767 | 2.016 |
| Overall mean of Health centers | 86.55 | 13.24 | 3.342 | 1.102 | 2.331 |
| SD of Health centers | 44.571 | 7.176 | 1.762 | 0.843 | 1.297 |
| Overall mean | 112 | 14.8052 | 3.8653 | 1.1004 | 4.947 |
| SD | 67.5 | 8.75676 | 2.6676 | 0.85389 | 3.1348 |
Comparison of biomedical waste generation rate with number of patients per day getting a laboratory service in public health care facilities (n = 26).
| Variable | Number of patients | Name of the organization | Value | |
|---|---|---|---|---|
| Solid waste generation Total Kg/day | 60 | Highest | Kasanchis HC | 7.8 |
| Lowest | Hiwot Amba HC | 6.2 | ||
| 70 | Highest | Teklehymanot HC | 16.70 | |
| Lowest | Addis Ketema W7 HC | 7 | ||
| 80 | Highest | Mychew HC | 28.40 | |
| Addis Ketema W4 HC | 19.60 | |||
| Lowest | Ferency W1 HC | 3 | ||
| Arada HC | 7.5 | |||
| 120 | Highest | Entoto No.2 HC | 29 | |
| Lowest | Nifas selk W02 HC | 8.5 | ||
| 200 | Highest | Zewdiut Hospital | 36 | |
| Triunesh Beijing Hospital | 19.10 | |||
| Lowest | Goro HC | 11 | ||
| Bisrate Gebirel HC | 14.90 | |||
Multivariate logistic regression analysis of factors related to knowledge regarding biomedical waste management.
| Variable | Knowledge status | AOR | 95% Confidence Interval | P- value | |||
|---|---|---|---|---|---|---|---|
| Yes | No | Lower Bound | Upper Bound | ||||
| Gender | Male | 98 | 70 | 2.771 | 1.164 | 6.596 | .021 |
| Female | 64 | 66 | 0.862 | 1 | |||
| Work experience | <1 year | 14 | 6 | 2.824 | 2.67 | 4.21 | .974 |
| 1–5 years | 68 | 30 | 344.758 | 19.778 | 512.6 | .001 | |
| 5–10 years | 112 | 22 | 113.050 | 7.590 | 345.6 | .001 | |
| 10–15 Years | 24 | 10 | 605 | 582 | 690 | .991 | |
| 15–20 years | 8 | 2 | 174.8 | 164 | 238 | .983 | |
| >20 years | 2 | 0 | 729.1 | 1 | |||
| Training | Yes | 180 | 2 | 7.290 | 1.574 | 33.767 | .011 |
| No | 102 | 12 | 0.094 | 1 | |||
Multivariate logistic regression analysis which shows the association of knowledge with the practice of biomedical waste management, Addis Ababa, Ethiopia, 2021.
| Variable | Knowledge status | AOR | 95% Confidence Interval | P- value | ||||
|---|---|---|---|---|---|---|---|---|
| Yes | No | Lower Bound | Upper Bound | |||||
| Having a standard operational procedure | Yes | 204 | 18 | 2.499 | 2.294 | 2.846 | .010 | |
| No | 44 | 14 | 0.862 | 1 | ||||
| Waste holding bags enough to resist leak and puncture | Yes | 202 | 18 | 2.587 | 2.341 | 3.010 | .048 | |
| No | 54 | 10 | 1 | |||||
| Method of transport | Use of bare hands | 144 | 30 | 0.998 | 0.743 | 1.341 | .998 | |
| Wheel barrows | 46 | 24 | 1.898 | 1.743 | 2.341 | .045 | ||
| Trolley | 42 | 12 | 0.598 | .338 | 1.060 | .078 | ||
| Waste container itself | 22 | 2 | 1 | |||||
| Infectious waste treated before disposal | Yes | 206 | 48 | 2.598 | 2.338 | 3.060 | .001 | |
| No | 14 | 20 | 1 | |||||
| Separate financial source | Yes | 64 | 2 | 1.064 | 1.001 | 1.470 | .001 | |
| No | 58 | 22 | 1 | |||||
| I don’t know | 106 | 46 | 0.670 | 0.412 | 1.090 | .107 | ||
| Following the current policy and guideline legitimately | Yes | 154 | 26 | 1.034 | 1.021 | 1.659 | .001 | |
| No | 48 | 18 | 0.611 | 0.368 | 1.015 | .057 | ||
| I don’t know | 26 | 26 | 1 | |||||
|
| ||||||||
| Having a standard operational procedure | Yes | 204 | 18 | 2.522 | 2.295 | 2.921 | .025 | |
| No | 28 | 2 | 1 | |||||
| Liquid waste management | Decontaminated before dumping | 216 | 12 | 2.386 | 1.169 | 2.883 | .024 | |
| Dump in to running water | 24 | 8 | 0.648 | 0.429 | 0.978 | .039 | ||
| I don’t Know | 2 | 10 | 1 | |||||
| Common modes of treatment | Incineration | 132 | 10 | 3.621 | 2.468 | 3.825 | .001 | |
| Autoclaving | 24 | 2 | 1.608 | 0.555 | 4.660 | .382 | ||
| Chemical disinfection | 6 | 0 | 1 | |||||
Linear regression analysis of the association of number of patients per day with total generation of solid biomedical waste in medical laboratories.
| Variables | t- value | 95% Confidence Interval for B | P- value | ||
|---|---|---|---|---|---|
| Lower Bound | Upper Bound | ||||
| Number of patients per day | Solid waste generation Sharp kg/day | -3.516 | -33.006 | -8.474 | .002 |
| Solid waste generation Total kg/day | 3.032 | 2.421 | 12.999 | .006 | |
Bivariate correlation analysis of waste of coronavirus pandemic with waste segregation practice and availability of color coding.
| Variables | Waste segregation practice | Color coding | |
|---|---|---|---|
| Waste of coronavirus pandemic | Pearson Correlation coefficient | .510 | .431 |
| P-value | .009 | .032 | |