| Literature DB >> 33920996 |
Tanzila Akmal1, Faisal Jamil1.
Abstract
Improper management of municipal waste has become a growing concern globally due to its impact on the environment, health, and overall living conditions of households in cities. Waste production has increased because households do not adopt waste management practices that ensure sustainability. Previous studies on household waste management often considered socio-economic aspects and overlooked the environmental and behavioral factors influencing the disposal practices and health status. This study adopted four constructs, defensive attitude, environmental knowledge, environmental quality, and waste disposal, by employing a structural equation modeling approach to explore research objectives. Data from 849 households of the Islamabad-Rawalpindi metropolitan was collected by using a multi-stage sampling technique. The structural model results showed that the two constructs, environmental knowledge and defensive behavior, positively affect household health status. The most significant health-related considerations are waste disposal and environmental quality, both of which negatively impact health status and do not support our hypothesis. The results provide valuable perspectives to enable households to engage actively in waste management activities. The findings indicate that understanding the intentions of household health status drivers can assist policymakers and agencies in promoting an efficient and successful community programmes related to sustainable solid waste management by allowing them to foster how the desired behavior can be achieved.Entities:
Keywords: health status; structural equation modeling; sustainable solid waste management
Year: 2021 PMID: 33920996 PMCID: PMC8071428 DOI: 10.3390/ijerph18084193
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Structural model of the hypotheses
Statements and scales used for the four constructs.
| Code | Description |
|---|---|
| HS1 | Waste affect the mental well-being of the residents. |
| HS2 | I am aware of the possible link between disease symptoms and improper waste disposal. |
| HS3 | Has anyone of you suffer from the following waste-related diseases. |
| HS4 | How would you evaluate your overall health status. |
| WD1 | I always put garbage in a closed bin. |
| WD2 | I always place plastic bag in bin. |
| WD3 | I do segregate waste sometimes. |
| WD4 | I positively engage in waste separation. |
| WD5 | I adopted segregation behavior to minimize the waste management cost. |
| WD6 | I feel responsible for segregating waste. |
| EQ1 | I don’t notice any negative environmental changes in my vicinity. |
| EQ2 | I don’t notice dumpsites near by me as the breading site for disease carrying vector? |
| EQ3 | I don’t experience improper waste blocking. |
| EQ4 | Water is not contaminated in my vicinity. |
| EQ5 | I believe air is not polluted in my vicinity. |
| Ek1 | I know how to segregate household waste properly. |
| EK2 | Segregation of waste can help to enhance landfill life. |
| EK3 | Waste disposal sites are not acting as breeding sites for disease carrying victors. |
| EK4 | Household waste separation can help to decrease the morbidity rate. |
| EK5 | Household waste separation can minimize the environmental damages. |
| EK6 | I believe, control dumping can minimize greenhouse gas emissions. |
| DB1 | I believe preventive measures should be taken to control mosquitoes. |
| DB2 | I believe preventive measures should be used to control other insects. |
| DB3 | I believe we should keep my drain free from blockage. |
| DB4 | I believe we should adopt waste minimization practices at the first place. |
| DB5 | I believe waste segregation can bring economic benefits. |
| DB6 | I believe waste segregation practices can improve environmental quality in my vicinity. |
Social-economic information of respondents.
|
|
| ||||
| 15–20 | 21–30 | 31–40 | 41–50 | >51 | |
| Female | 153 | 221 | 119 | 47 | 11 |
| Male | 92 | 94 | 109 | 3 | 1 |
|
|
| ||||
| <30k | 31k–50k | 51k–70k | 51k–70k | 71k–100,000 | |
| Illiterate | 92 | 57 | 21 | 7 | 26 |
| Primary | 30 | 10 | 9 | 3 | 5 |
| Secondary | 70 | 41 | 38 | 13 | 46 |
| Higher | 29 | 38 | 46 | 19 | 56 |
| Professional | 27 | 32 | 28 | 24 | 73 |
Source: [14].
Figure 2Structural equations modeling and path coefficients between variables.
Reliability and validity test.
| Goodness of Fit Measures | Recommendation Value | Structural Model (Results) |
|---|---|---|
| χ2 | >3.00 | 3.713 |
| CFI | >0.90 | 0.948 |
| NFI | >0.90 | 0.931 |
| RMSEA | <0.08 | 0.057 |
χ2 test statistics/df; CFI (comparative fit index); NFI (normed fit index); RMSEA (root mean square error of approximation).
Correlations of the constructs.
| Health Status | Waste Disposal | Environmental Quality | Environmental Knowledge | Defensive Behavior | |
|---|---|---|---|---|---|
| Health status | 1 | ||||
| Waste disposal | −0.111 ** (0.001) | 1 | |||
| Environmental quality | −0.114 ** (0.001) | −0.15 (0.666) | 1 | ||
| Environmental knowledge | 0.294 ** (0.00) | −0.61 (0.76) | −0.71 * (0.038) | 1 | |
| Defensive behavior | 0.69 * (0.044) | 0.0179 ** (0.00) | −0.283 ** (0.00) | 0.010 (0.769) | 1 |
Note: *, **, significant at 1% and 5% and squared correlations in parentheses.
Results of the structural model (SM).
| Structural Relations | Standardized Path Coefficient | S.E. | Hypothesis | Result |
|---|---|---|---|---|
| DA→HS | 0.094 *** | 0.024 | H1 | Supported |
| WD→HS | −0.273 *** | 0.028 | H2 | Not supported |
| EK→HS | 0.202 *** | 0.024 | H3 | Supported |
| EQ→HS | −0.049 ** | 0.019 | H4 | Not Supported |
Note: ***, **, significant at, 1%, and 5%.