Knowledge and Perception of Plastic Waste Disposal Practices in Opobo/Nkoro Local Government Area, Rivers State

Reference Reference 29–39 years 1.64 (0.76–3.57) 1.45 (0.94–2.25) — 40–50 years 1.61 (0.68–3.81) 1.55 (1.02–2.35) 0.092 51–61 years 2.14 (0.73–6.28) 1.70 (1.05–2.75) 0.040* Above 61 years 1.00 (0.35–2.84) 0.98 (0.56–1.73) 0.031* Gender Male Reference Reference — Female 0.57 (0.31–1.03) 0.72 (0.47–1.10) 0.130 Educational level No formal education Reference Reference — Primary education 1.50 (0.53–4.26) 1.45 (0.72–2.93) 0.296 Secondary education 3.00 (1.23–7.34) 2.35 (1.30–4.25) 0.005* Tertiary education 7.64 (2.88–20.22) 4.80 (2.65–8.69) <0.001* Occupation Civil servant Reference Reference — Trader/business 0.38 (0.15–0.93) 0.55 (0.30–1.01) 0.054 Farmer/Fisherman 0.30 (0.11–0.85) 0.39 (0.17–0.89) 0.026* Student 0.62 (0.21–1.87) 0.75 (0.42–1.35) 0.338 Unemployed 0.35 (0.12–1.09) 0.60 (0.30–1.21) 0.154 Others NE NE NE IIARD International Journal of Geography & Environmental Management Household size 1–3 persons Reference Reference — 4–6 persons 0.84 (0.40–1.78) 0.88 (0.55–1.42) 0.610 7–9 persons 0.59 (0.25–1.39) 0.72 (0.42–1.23) 0.229 10 persons and above 0.63 (0.22–1.78) 0.76 (0.38–1.51) 0.431 Community of residence Nkoro Reference Reference — Kalibiama 0.72 (0.33–1.59) 0.70 (0.49–1.01) 0.057 Opobo Town 0.91 (0.42–2.00) 0.82 (0.56–1.21) 0.322 Note: * Significant at p < 0.05, COR = Crude Odds Ratio; AOR = Adjusted Odds Ratio; CI = Confidence Interval; NE = Not estimable because of complete separation Perception of Plastic Waste Disposal Practices among respondents As shown in Table 5, respondents held strongly positive perceptions of plastic waste as an environmental health risk, with mean scores between 3.37 ± 0.78 to 3.64 ± 0.64, well above the 2.50 benchmark. The highest-rated item was that plastic waste pollution can cause environmental degradation (3.64 ± 0.64), with 93.8% agreeing or strongly agreeing. This was followed closely by the view that plastic waste disposal is a major environmental problem in the community (3.63 ± 0.65; 93.8%. agreement) and that improper disposal can block drainage and cause flooding (3.59 ± 0.66; 93.8%). Most respondents also agreed that plastic waste can contaminate water sources (3.52 ± 0.73; 91.3%) and that burning plastic waste can cause air pollution and respiratory diseases (3.44 ± 0.79; 88.7%). The lowest, though still high, mean score was for the statement that plastic waste can increase the spread of malaria and cholera (.37 ± 0.78; 88.7%). The overall mean perception score was 3.53. When the responses were categorised, as shown in Figure 1, about 92.5% of respondents had a positive perception of plastic waste disposal as an environmental health risk, while only about 7.5% had a negative perception. Plastic waste disposal practices varied across sociodemographic characteristics, as presented in Table 6. Only 64 respondents (16.5%) practised proper disposal, while 325 (83.5%) practised improper disposal. Proper disposal was more common among males (20.0%) than females (12.7%). By age, the proportion practising proper disposal was highest among respondents aged 51–61 years (27.3%) and those above 61 years (26.5%), but lowest among those aged 29–39 years (11.5%) and 18–28 years (11.8%). Proper disposal increased with educational attainment, from 6.7% among respondents with no formal education to 20.7% among those with tertiary education. By occupation, proper disposal was highest among respondents in other occupations (35.7%) and civil servants (25.0%), but lowest among farmers and fishermen (4.0%). The proportion practising proper disposal decreased as household size increased, from 23.8% among households with 1–3 persons to 10.3% among those with 10 or more persons. Across communities, proper disposal was highest in Nkoro (21.9%), followed by Opobo Town (16.1%) and Kalibiama (12.9%). Sociodemographic factors were associated with positive perception (Table 7). Age was significantly associated with perception. Compared with those aged 18–28 years, respondents aged 40–50 years (AOR = 1.52; 95% CI: 1.01–2.30; p = 0.045), 51–61 years (AOR = 1.62; 95% CI: 1.03–2.55; p = 0.037), and above 61 years (AOR = 1.86; 95% CI: 1.03–3.36; p = 0.040) had higher odds of a positive perception. The 29–39 age group did not differ significantly (AOR = 1.38; p = 0.099). Educational level again showed a clear gradient. Respondents with secondary education (AOR = 2.18; 95% CI: 1.22–3.90; p = 0.009) and tertiary education (AOR = 3.76; 95% CI: IIARD International Journal of Geography & Environmental Management 2.08–6.79; p < 0.001) were more likely to have a positive perception than those with no formal education, while primary education was not significant (p = 0.385). Farmers/fishermen had 64% lower odds of a positive perception than civil servants (AOR = 0.36; 95% CI: 0.15–0.86; p = 0.021). Other occupational groups, gender (female vs male: AOR = 0.70; p = 0.151), household size, and community of residence were not significantly associated with perception. Table 5: Public Perception of Plastic Waste Disposal Practices (n = 389) Items SA (4) A (3) D (2) SD (1) Sum Mean SD Plastic waste pollution can cause environmental degradation. 280 85 18 6 1,417 3.64 0.64 Improper plastic waste disposal can block drainage and cause flooding. 260 105 17 7 1,396 3.59 0.66 Plastic waste can contaminate water sources. 245 110 24 10 1,368 3.52 0.73 Burning plastic waste can cause air pollution and respiratory diseases. 230 115 30 14 1,339 3.44 0.79 Plastic waste can increase the spread of malaria and cholera. 200 145 30 14 1,309 3.37 0.78 Plastic waste disposal is a major environmental problem in my community. 275 90 18 6 1,412 3.63 0.65 Note: SA = Strongly Agree; A = Agree; D = Disagree; SD = Strongly Disagree; SD (last column) = Standard Deviation. IIARD International Journal of Geography & Environmental Management Table 6: Distribution of Plastic Waste Disposal Practice Level with Socio demographic Characteristics (n= 389) Socio demographic Characteristic Improper Disposal n (%) Proper Disposal n (%) Gender Male 160 (80.0%) 40 (20.0%) Female 165 (87.3%) 24 (12.7%) Age 18–28 years 75 (88.2%) 10 (11.8%) 29–39 years 115 (88.5%) 15 (11.5%) 40–50 years 70 (82.4%) 15 (17.6%) 51–61 years 40 (72.7%) 15 (27.3%) Above 61 25 (73.5%) 9 (26.5%) Educational Level No formal education 28 (93.3%) 2 (6.7%) Primary education 35 (87.5%) 5 (12.5%) Secondary education 120 (85.7%) 20 (14.3%) Tertiary education 142 (79.3%) 37 (20.7%) Occupation Civil servant 75 (75.0%) 25 (25.0%) Trader/business 105 (87.5%) 15 (12.5%) Farmer/Fisherman 48 (96.0%) 2 (4.0%) Student 53 (81.5%) 12 (18.5%) Unemployed 35 (87.5%) 5 (12.5%) Others 9 (64.3%) 5 (35.7%) Household Size 1–3 persons 80 (76.2%) 25 (23.8%) 4–6 persons 125 (83.3%) 25 (16.7%) 7–9 persons 85 (89.5%) 10 (10.5%) 10 and above 35 (89.7%) 4 (10.3%) Community of Residence Nkoro 75 (78.1%) 21 (21.9%) Kalibiama 115 (87.1%) 17 (12.9%) Opobo Town 135 (83.9%) 26 (16.1%) IIARD International Journal of Geography & Environmental Management Table 7: Socio demographic Reasons Associated with Positive Public Perception of Plastic Waste Disposal Practices among Respondents (n=389) Socio demographic variable COR (95% CI) AOR (95% CI) p value Age group 18–28 years Reference Reference — 29–39 years 1.60 (0.68–3.75) 1.38 (0.94–2.04) 0.099 40–50 years 1.88 (0.63–5.58) 1.52 (1.01–2.30) 0.045* 51–61 years 2.00 (0.54–7.40) 1.62 (1.03–2.55) 0.037* Above 61 years 2.50 (0.32–19.41) 1.86 (1.03–3.36) 0.040* Gender Male Reference Reference — Female 0.53 (0.22–1.28) 0.70 (0.43–1.14) 0.151 Educational level No formal education Reference Reference — Primary education 1.42 (0.42–4.79) 1.36 (0.68–2.72) 0.385 Secondary education 3.25 (1.00–10.57) 2.18 (1.22–3.90) 0.009* Tertiary education 6.17 (1.90–20.00) 3.76 (2.08–6.79) <0.001* Occupation Civil servant Reference Reference — Trader/business 0.46 (0.18–1.17) 0.59 (0.32–1.10) 0.097 Farmer/Fisherman 0.25 (0.07–0.91) 0.36 (0.15–0.86) 0.021* Student 0.50 (0.14–1.75) 0.68 (0.35–1.32) 0.247 Unemployed 0.40 (0.09–1.75) 0.63 (0.28–1.42) 0.263 Others NE NE NE Household size 1–3 persons Reference Reference — 4–6 persons 0.58 (0.24–1.39) 0.91 (0.53–1.56) 0.730 7–9 persons 0.39 (0.14–1.10) 0.79 (0.43–1.46) 0.451 10 persons and above 0.44 (0.13–1.50) 0.83 (0.39–1.76) 0.624 Community of residence Nkoro Reference Reference — Kalibiama 0.67 (0.26–1.70) 0.66 (0.40–1.10) 0.111 Opobo Town 0.91 (0.36–2.29) 0.88 (0.53–1.46) 0.616 Note: * Significant at p < 0.05COR = Crude Odds Ratio; AOR = Adjusted Odds Ratio; CI = Confidence Interval; NE = Not estimable. Significant at p < 0.05. Discussion The high composite awareness observed places Opobo/Nkoro in the higher range reported in recent studies of Nigerian communities. Evidence at the national level shows high public awareness of plastic pollution (Ibrahim et al., 2025), and public education is reported to be raising awareness of environmental sanitation (Chilote & Dhakal, 2025). This contrasts with the low sanitation awareness found among urban households in Kano (Abdulmumin et al., 2024). However, high awareness has not translated into proper practice in several settings. In Imo State, residents knew the health risks of improper disposal but did not act accordingly (Emesowum & Onyekwuo, 2024), and open dumping persisted despite good knowledge in the informal settlements of Jos (Sambo et al., 2021) and in Birnin Kebbi (Mainasara & Dodo, 2024). The same gap between awareness and practice was seen in the present study. Education was the strongest independent predictor of awareness, consistent with other Nigerian studies (Adeniran et al., 2024; Akintola et al., 2025) and with a logistic regression IIARD International Journal of Geography & Environmental Management analysis from Bogotá (Henaó Rodríguez et al., 2024). However, formal education alone did not consistently improve littering behavior in a multi-city Indonesian study (Brotosusilo et al., 2022), which suggests that the education gradient seen here may reflect exposure to information rather than a guarantee of practice. The lower awareness among farmers and fishermen is consistent with findings among occupationally dispersed, lower-service populations (Pathak et al., 2023), and may reflect less frequent contact with formal outreach. The higher unadjusted awareness among men differs from a Malaysian youth survey (Zulkipli et al., 2022), but since gender was not significant after adjustment, this more likely reflects context and confounding than a true gender effect. Awareness also varies by waste type, as fewer than half of Lagos residents had fair knowledge of pharmaceutical waste disposal (Adedeji Adenola et al., 2022), so high awareness of plastic waste should not be assumed for other waste streams. Because awareness is already high, further general awareness campaigns are unlikely to be the most effective intervention. Efforts should instead target the subgroups with relatively low awareness, namely farmers and fishermen, people with no formal education, and the youngest and oldest adults, and could be delivered through occupational associations and existing educational structures such as adult literacy programs. Gender, household size and community of residence were not significant after adjustment, so programs need not be tailored by sex or settlement. The high awareness itself probably reflects residents’ direct experience of flooding and blocked waterways in a riverine environment, exposure to government and agency education, and the role of formal education in accessing health messages, although this study did not test these explanations. As the study was cross- sectional, we cannot conclude that investing in education would raise awareness over time. The very high proportion of respondents with a positive perception of plastic waste as an environmental health risk, with agreement strongest for environmental degradation and weakest for the spread of disease vectors, places this community at the higher end of what has been reported in Nigeria and internationally over the past five years. At the national level, Ibrahim et al. (2025) reported high public awareness of plastic pollution across Nigeria. That study assessed awareness and perceptions of responsibility rather than health-risk perception, and its national sample has more variable exposure to the hazard than our study area, where plastic accumulation in waterways is directly and frequently visible. Our findings also align with Donuma et al. (2024), who found in Maiduguri that indiscriminate disposal had led to plastic waste accumulating in open spaces, drainage systems, and water bodies, with microplastic contamination of water sources that poses a potential risk to human health. This resembles the causal chain captured by the water contamination and drainage blockage items in our study, and it suggests that riverine and flood-prone communities most easily arrive at risk perception through the direct, observable consequences of plastic waste. High perception should not, however, be taken for granted. Omoyajowo et al. (2021) found high awareness but poor perception of microplastic pollution among residents, students, and fishermen around Lagos Lagoon. The difference from our findings may reflect that microplastics are far less visible than the plastic waste and blocked drains addressed by our items. Education also appears to matter internationally. In a review of survey-based research across nine countries, Walker et al. (2023) found that awareness of the negative impacts of plastic pollution was extremely high regardless of location, and highest among groups including the better educated. This is consistent with our data, in which respondents with tertiary education had the most favorable perception and those with no formal education the least. Formal schooling may also have a ceiling effect, as Anokye et al. (2024) found total agreement on the negative environmental impacts of plastic waste among senior high school teachers in rural Ghana, although that sample was small in scope and predominantly male. IIARD International Journal of Geography & Environmental Management The weaker agreement on the link between plastic waste and malaria and cholera is more likely explained by the cognitive distance of that causal chain than by weaker environmental concern. Recognizing that discarded plastic containers create stagnant-water breeding sites for vectors requires knowledge of an intermediate biological mechanism that cannot be directly observed, whereas recognizing that a blocked drain causes flooding is a short, observable inference. A study of soot pollution from artisanal crude oil refining in Rivers State showed a similar pattern, with awareness of the pollutant exceeding the proportion who linked it to specific health effects (Whyte et al., [year]). This suggests that the gap between visible, mechanical harms and biologically mediated harms is a general feature of how communities process environmental risk and not unique to Opobo/Nkoro. Resources should therefore go to this specific gap, through risk communication explaining how stagnant water in discarded containers and blocked drains supports the organisms that transmit malaria and cholera, rather than to basic sensitization on whether plastic waste is harmful. The unequal distribution of perception across subgroups is a second and possibly more important finding. Farmers and fishermen, who have the most direct and prolonged exposure to the rivers and streams where plastic waste accumulates, had the lowest positive perception of any occupational group. Research on coastal communities in Delta State has shown that residents may perceive persistent hazards such as oil pollution and flooding as normal parts of life rather than as major risks (Olowoporoku, 2023), which may help explain this result. It implies that the residents most affected by plastic pollution may be the least likely to see it as a concern, so an undifferentiated campaign aimed at the community average would under- serve them, and occupationally tailored interventions are needed. The marked difference by educational level likewise suggests that written pamphlets and formal health messaging may not reach, or persuade, the residents whose perception is weakest. Formal education plausibly strengthens the ability to link a visible cause to a less visible effect and increases exposure to structured health information, which is consistent with Walker et al. (2023) and with Adeniran et al. (2024), who showed that education was a significant factor in understanding environmental health risks. Finally, the contrast between high perception and low proper disposal practice in this study suggests that perception alone is not a strong enough lever to change behavior, and that these findings are exploratory because the cross-sectional design cannot establish why the differences exist. Author’s Contribution: The authors contributed to the conceptualisation, study design, data collection, data analysis, interpretation of findings, and preparation and revision of the manuscript. All authors read and approved the final manuscript.