A comparative analysis of public awareness level about drinking water quality in Guangzhou (China) and Karachi (Pakistan)

Abstract

Safe drinking water is fundamental for the existence of life. The establishment of public awareness about drinking water quality is a most significant issue in the protection of health and the wellbeing of humans. The present study focuses on the assessment of community awareness level of, as well as public trust in, the government-provided information about drinking water quality in two highly populated underrepresented megacities of Asia, i.e., Guangzhou (China) and Karachi (Pakistan). The study was conducted to explore the respondents’ knowledge about the existing quality issues and the practices to remove the contaminants in drinking water in both cities, which was determined by numerical analysis using the scoring method system and multinomial regression model. The results show that the respective respondents’ percentage awareness level and positive attitude in Guangzhou were 46.2% and 30.0% compared with 23.1% and 7.4% in Karachi, respectively. The respective percentage of respondents’ trust in media stories/reports about water pollution accidents was 76.0% and 70.8%, while the trust in government-provided information was 79.3% and 39.7% in Guangzhou and Karachi, respectively. The p-values for drinking water quality according to public approval based on sociodemographic parameters (gender, age, family members, household income/month, education, etc.) of respondents in both cities were <0.05, which supports that the variations in acquired results were significant. The study advocates that increased awareness campaigns by government agencies and nongovernmental organizations (NGOs) in educational institutes and/or community centers can improve the public awareness level, which would subsequently help the governments to enhance the public trust, especially in Karachi. Moreover, the study’s findings have national significance and a worldwide scope, particularly in low- and middle-income regions.