Human activities irreparably pollute natural resources. Various studies show that human actions have become hazardous to nature, with rivers and streams polluted by inorganic and non-degradable wastes, significantly affecting water quality. Quality of life is largely influenced by health status. Health is a central factor that affects daily activities and participation in social and community life. It is not merely the absence of disease but encompasses physical, social and emotional well-being. Disease disrupts normal human life, rendering a person unable to work effectively and making them dependent on others to complete their tasks. Human health is more valuable than wealth, as a fulfilling life is not solely based on material possessions but also on good health. Good physical health includes lifestyle habits such as eating a nutritious diet, drinking clean water, sleeping well, minimizing exposure to toxic chemicals and avoiding alcohol consumption, among other factors.
Several studies examining the effects of water pollution on health have suggested that drinking polluted water is akin to consuming slow poison.
Birundha Dhulasi (2004) analyzed various types of water pollutants, noting that pollutants are harmful substances produced by natural sources or human activities, with adverse effects on the environment. Water pollutants can be categorized as physical, chemical, or biological. Physical pollutants include taste, odor, temperature, color, solids and radioactivity. Chemical pollutants consist of pH, alkalinity, acidity, organic matter, oil and grease, residual chlorine, fluoride, arsenic, cadmium, lead, mercury, nickel, selenium, zinc, ammonia, nitrogen, phosphates, sulfates, chlorides, nitrates and carbon. Biological pollutants are mainly microorganisms, including pathogenic bacteria. These pollutants pose serious health risks.
Nanda and Almas Ali (2006) highlighted that a population’s health status reflects the socio-economic development of a country and is influenced by various factors such as income levels, living standards, housing, sanitation, water supply, education, employment, health consciousness, personal hygiene and access to affordable healthcare. Poor health is often the result of inadequate nutrition, lack of access to clean water and insanitary living conditions, leading to air-borne and water-borne diseases. Deprivation of essential amenities like safe water and sanitation results in high rates of illness and higher mortality.
Ali et al., (2025) study revealed that the power plant area was significantly contaminated by water and soil due to industrial activity. Lead and cadmium concentrations in the water were higher above the WHO’s safety guidelines, ranging from 0.1-1 ppm and 0.01-0.1 ppm, respectively. After being released into the Tigris River, the concentrations slightly decreased but were still higher than natural levels.
Considering these factors, this study examines the impact of anthropogenic hazards, specifically water pollution, on human health. The analysis is divided into two key areas: (1) the types of diseases that humans contact from polluted water and (2) how toxic materials in water affect human health.
Fig 1 illustrate the respondents’ opinions on whether drinking polluted water affects their health. A significant majority (57 per cent) agreed with the statement, while nearly 3 per cent disagreed. Additionally, 34.5 per cent of the respondents strongly agreed to the statement, while a small portion (2.2 per cent) strongly disagreed. About 3.3 per cent of the respondents had no idea. Balamurugan
Palani et al., (2021) investigated the anthropogenic sources of mercury contamination in Kodaikanal Lake. Their study reveals high levels of contamination and ecological risk due to mercury, underscoring the need for urgent remediation efforts to protect the environment and public health. From these empirical findings, it is clear that nearly 92 per cent of the respondents agreed that drinking polluted water affects their health, while around 3 per cent were uncertain. This clearly indicates that awareness on drinking polluted water has a significant impact on the health of people in the study area.
Water-borne diseases
There are various diseases that affect human health and water-borne diseases result from consuming polluted water.
Gangadharan (2006), in his analysis of urban morbidity, noted that communicable diseases often occur in areas where resistance levels are low and environmental conditions are weak in preventing disease spread. Poor nutrition, especially in young individuals, exacerbates the problem and overpopulation can further worsen the situation. Environmental factors that contribute to the spread of communicable diseases include unsafe water supplies, poor sanitation, inadequate drainage of surface water, improper waste disposal, poor domestic hygiene and inadequate housing.
Common water-borne diseases such as diarrhoea, typhoid, amoebiasis, gastroenteritis and guinea worm are prevalent under these conditions. Taking these factors into account, a thorough study was conducted in the research area and the results are presented in the table.
The above analysis (Table 1 Diarrhoea is caused by Mercury, Cadmium and Cobalt Containing in drinking water) and Fig 2 envisage the opinion of the respondents on the statement that whether diarrhoea is caused by mercury, cadmium and cobalt in drinking water. A vast majority of the respondents (50.8 per cent) agreed the statement. Another 3 per cent of the respondents disagreed the statement. Of the total 36.8 per cent of the respondents strongly agreed it. Only1.0 per cent of the respondents strongly disagreed and 8.4 per cent of the respondents had no idea.
Hence it was apparent from the empirical findings that the nearly 88 per cent of the respondents agreed upon the statement and nearly 9 per cent of the respondents didn’t have any opinion on the statement which emphatically implies that the respondents agreed that diarrhoea is spread by drinking contaminated water.
The above analysis Fig 3 pictures the opinion of the respondents on the statement that which typhoid is caused by drinking contaminated water. A vast majority of the respondents (53.4 per cent) agreed the statement. Nearly 4.5 per cent of the respondents disagreed the proclamation. About 10.3 per cent of the respondents strongly agreed to the statement and 8.3 per cent of the respondents strongly disagreed to it. Another 23.5 per cent of the respondents had no idea upon the statement, hence it was apparent from the empirical findings that the nearly 64 per cent of the respondents agreed upon the statement and nearly 24 per cent of the respondents didn’t have any idea which emphatically implies that the respondents accept that typhoid is the result of drinking polluted water.
The analysis of the Fig 4 presents the respondents opinion on the statement whether Jaundice occurs due to drinking of contaminated water. A vast majority of the respondents (41.7 per cent) agreed to the statement. Among them 4.5 per cent of the respondents disagreed to the proclamation. Nearly 12.0 per cent of the respondents strongly agreed to it. Only 8.3 per cent of the respondents strongly disagreed to it. Out of the total 33.5 per cent of the respondents had no opinion upon the statement.
It was clear from the above table that majority of the respondents (54 per cent) had agreed to the statement and nearly 34 per cent of the respondents didn’t have any idea about the statement. Hence the respondents had accepted that drinking polluted water becomes the cause of spreading the disease Jaundice.
The above analysis of the Fig 5 explained the opinion of the respondents on the statement that whether lever and kidney damage is the result of drinking the polluted water. A very high percentage (45.6 per cent) of the respondents agreed to the statement. About 7.3 per cent of the respondents disagreed to the statement. Nearly 6.3 per cent of the respondents strongly agreed to the reason that drinking polluted water affects lever and kidney of the respondents. Among them 3.0 per cent of the respondents strongly disagreed to it. Remaining 37.8 per cent of the respondents had no idea about the statement. Thashlin
Govender et al., (2011) also focused on diarrheal diseases in South Africa, which account for 3.1% of total deaths. They suggested that improving water disposal, sanitation infrastructure and water quality could significantly reduce the incidence of such diseases.
The above data analysis revealed that the nearly 52 per cent of the respondents agreed to the statement and nearly 38 percent of the respondents didn’t agree to the statement which emphatically implies that drinking polluted water is the cause for lever and kidney problems.
Correlation analysis of awareness and importance of rainwater harvesting
The correlation analysis presented in Table 2 indicates a positive relationship between awareness of rainwater harvesting and the level of awareness among respondents. The Pearson correlation coefficient of 0.705 suggests a strong positive correlation, which is statistically significant at the 0.01 level (p<0.001). This finding implies that as awareness of rainwater harvesting practice has increased significantly, there is a corresponding increase in overall awareness regarding the implications of water level, usage of water, causes of water borne diseases and proper hygiene. Snelling
Lamond et al., (2023) implicit attitudes are generally more positive than explicit, especially in respondents with RWH systems, implying that the positivity is deep-seated in their subconsciousness. We also reveal differences between subconscious (implicit) beliefs and practical difficulties (explicit opinions). Outdoor uses of rainwater are preferred; hence, more work in promoting indoor uses is needed to maximise the resource potential of UK rainfall and uptake of RWH systems. The significance of this relationship underscores the importance of educational initiatives aimed at enhancing public knowledge about awareness of rain harvesting, as greater awareness may lead to improve the water level and quality.
In Table 3, the correlation between environmental impact and potential improvements of watershed management shows a stronger positive relationship, with a Pearson correlation coefficient of 0.671, also significant at the 0.00 level (p<0.001). This indicates that perceptions of environmental impact are positively associated with views on potential improvements in addressing industrial wastage, household wastage and various natural externalities. A higher perceived environmental impact correlates with a greater belief in the necessity for improvements, suggesting that individuals who recognize the negative environmental effects of government initiatives are more likely to advocate for reforms and enhancements in strengthening watershed management and public education. This finding highlights the need for targeted interventions that not only address legal aspects but also consider the broader environmental implications to foster a more informed and engaged public. Effectiveness of Watershed Management is described in Table 4.
The path analysis summary presented indicates a significant relationship between various independent variables (IVs) and the dependent variable (DV), which is the “Effectiveness of Watershed Management in Dindigul District.” The overall model shows an F value of 274.65 with a p value of .000, indicating that the model is statistically significant and that the independent variables collectively explain a portion of the variance in potential improvements, as evidenced by the R² value of .929. This suggests that approximately 92.9% of the variance in potential improvements can be attributed to the factors analysed, which include positive environmental impacts (vegetation, wildlife), reduction in conflicts over water resources, community received government support, government efforts to promote watershed management. Vishal
Kumbhar et al., (2013) stated that, actual implementation of watershed management options such as farm pond, gully plugs, contour trenching there is found that 3060 cum. Means there is water available for irrigation to farmer form his own land after watershed management options. Also, after implementation of intercropping pattern, there is also found that change in total crop production from farmers land is 15 ton per annum before watershed management to 20.75 ton per annum after watershed management. Finally, it is found that after implementation of watershed management technique, per capita of farmers family, increases by Rs. 878 (4.64%). Among the independent variables, positive environmental impacts have the strongest influence on potential improvements, with a Beta coefficient of .557 and a t-value of 12.737, both statistically significant at the 0.00 level (p<0.001). This finding emphasizes that enhancing positive environmental impacts are crucial for fostering potential improvements in the effectiveness of watershed management in Dindigul District. From the analysis the next independent variable “reduction in conflicts over water resources” also plays a significant role with a Beta of .428, while “community received government support” shows a smaller but still meaningful effect with a Beta of .062 (p = 0.029). The collinearity statistics reveal acceptable tolerance levels and VIF values for all independent variables, indicating that multicollinearity is not a concern in this analysis.
Naresh et al., (2025) observed that the model was calibrated by using the data from first four years of the study period. In the calibration process, the assigned weights were modified to improve the correlation coefficient between model computed values and the observed values. The values of these improved weights for each parameter were used to calculate the regression equation for each block of the study area. These regression equations were then used to validate the model for the next four-years. Statistical analysis (Root Mean Square Error and Average Absolute Error) was carried out to compare the model output with the observed values at different grid cells and found good agreement between different statistical parameters. The modified weights can be used for future estimation of nitrate as well as any other pollutants of the groundwater in the areas of similar conditions. Overall, these results highlight the importance of focusing on potential improvements of watershed management and effectiveness of watershed management to drive improvements of water usage and water condition in Dindigul District.