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Post-war solid waste management in Adigrat Ethiopia

public awareness and insufficient municipal oversight, 2.4. Type of data collected during field observation
has contributed to this growing environmental concern. Both primary and secondary data were collected.
In particular, uncollected waste often clogs stormwater The research instruments used to collect data in
channels during the rainy season, increasing the risk of this study included: (i) a field survey questionnaire,
flooding and waterborne disease outbreaks in low-lying (ii) an interview and focus group discussion, (iii) an
areas. observation checklist, and (iv) a document review.

2.2. Sampling design and method 2.5. Qualitative data analysis
This study employed a mixed-method approach, Qualitative data were transcribed and coded to
combining quantitative and qualitative methods to assess identify key themes and patterns. The analysis
post-war SWM in Adigrat. A total of 165 households involved thematic coding, organization into sub-
were selected using simple random sampling. The themes, and cross-validation through research team
sample size was calculated using Kothari’s formula, discussions. The Statistical Package for the Social
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assuming a 95% confidence level and a 5% margin of Sciences software (version 20) supported data coding
error (Equation I): and organization.

Nz PQ
2
s = (I) 2.6. Quantitative data analysis
E 2 (N 1− ) z PQ+ 2 A linear regression model was used to assess the
relationship between respondents’ age and their
Where N represents the estimated population size, z perceptions of the health impact of waste disposal
corresponds to the z-value associated with the desired in open spaces. The model evaluated the statistical
confidence level, P denotes the estimated proportion significance and direction of this relationship. Household
or prevalence of a characteristic in the population, Q solid waste generation rates were derived from both
is the complementary probability of P, andE signifies self-reported estimates and physical measurements.
the desired margin of error or maximum acceptable During the field survey, a representative subsample
sampling error. 40
of households was selected for direct waste collection

2.3. Participant description and field observation and weighing over 3 consecutive days using calibrated
Participants for focus group discussions and interviews scales. These measurements were used to validate and
included elders, women, youth, religious leaders, adjust the self-reported data obtained through structured
and local officials to ensure diverse perspectives. Six questionnaires. Linear regression was used for statistical
kebeles were randomly selected for field observations analysis in the study.
to represent different parts of the city. The participant This mixed approach, combining self-estimates with
age distribution is presented below in Table 1. actual weighing, enhances reliability and is commonly
used in contexts with limited infrastructure, such as
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Table 1. Demographic characteristics of the post-conflict or low-income urban settings. However,
participants it is acknowledged that self-reported data may still
Demographic characteristics n Percentage underestimate actual waste generation due to social
Age group desirability bias or recall inaccuracies.
18 – 30 years 20 12 3. Results
31 – 45 years 30 18
46 – 60 years 90 54.5 3.1. Family size and waste generation rates
61 years and above 25 15.15 Table 2 illustrates the relationship between household
Household size size and daily waste generation. Households
1 – 2 20 12.1 with 1 – 2 members generated the least waste at
3 – 4 50 30.3 0.32 kg/household (hh)/day, whereas those with more
than seven members generated the most at 1.4 kg/hh/day.
5 – 6 80 48.5 The average waste generation rate across all households
≥7 15 6 was 1.087 kg/hh/day.

Volume 22 Issue 4 (2025) 21 doi: 10.36922/AJWEP025090061