*5.2. Waterborne Diseases in the Study Area*

Water is a necessary component of life on earth, and contaminated water causes a variety of ailments. Throughout the investigation, 24.22 percent of the households, or 462 out of 1907, said they were suffering from waterborne infections, significantly impacting their lives. Although filtration of plant water does not guarantee absolute purity or disease-free safety, it has been demonstrated that people who drink plant water have a lower risk of contracting waterborne infections than those who drink tap water. In the study area, diarrhea was the most common waterborne disease after hepatitis, tuberculosis, skin infection, kidney infection, lung infection, typhoid, abdominal pain, vomiting, and stomach infection.

The mean differences in health in study areas with and without local government filtration plants were assessed using independent group t-tests. According to this survey, waterborne infections were prevalent in locations without filtration facilities. Plant water is a major source of drinking water in plant areas, and most people choose to drink it. Waterborne infections are less common in these locations because they demonstrate the disposition of acts due to class circumstances and bring treated water for drinking. In terms of waterborne infections in newborns, children, females, and males, Table 3 compares plant and control areas.


**Table 3.** Independent samples test for the occurrence of waterborne diseases.

According to the findings, there is a mean difference in waterborne infections in newborns, children, females, and males. In the plant area, the mean occurrence of waterborne infections in infants and children is 2.0533, while in the control area, it is 4.4533. As a result, the mean difference in both areas is −2.4. Furthermore, in the case of the occurrence of waterborne infections in infants and children, the t-value and significance value were −5.322 and 0.000, respectively. Because the t-value was −5.322 and the sig value was 0.000, which is less than 0.05, it is clear that the disposition of the act resulted in a significant difference in the mean occurrence of waterborne infections in infants and children in plant and control regions. Because they do not engage in such behaviors, waterborne infections among infants and children are higher in control areas than in plant areas. In the case of waterborne disease in females, the mean value of the plant area, the mean value of the control area, and the value of the mean difference in both areas were 16.533, 3.1267, and −1.473, respectively. Furthermore, the t-value was −2.823, with a significance value of less than 0.005 and less than 0.05. Therefore, the findings indicated a considerable difference in the mean occurrence of waterborne infections in females in plant and control areas. As a result, females are more likely to contract the waterborne disease than in the plant area in the control area.

Similarly, the mean value of the plant area, the mean value of the control area, and the value of the mean difference in both areas were 18.867, 3.4867, and −1.6000, respectively, in the event of the occurrence of waterborne disease in males. The t-value was also −7.927, and the significance value was less than 0.000 or less than 0.05. As a result, it demonstrates a considerable difference in the mean occurrence of waterborne infections in men in the plant and control areas. As a result, females are more likely to contract waterborne diseases than in the plant area in the control area. In short, the mean occurrence of waterborne infections differs significantly across infants, children, females, and males. In the control region, the incidence of waterborne diseases or bad life chances in newborns, children, females, and males was higher than in the plant area due to a lack of life options from drinking plant water.

#### *5.3. Econometric Model for Waterborne Illness*

Waterborne diseases are considered dependent variables measured by dummy values 0 or 1. If a person is suffering from waterborne diseases, then the value of dummy variables is 1; otherwise, value 0 was assigned. Furthermore, family size is a quantitative variable that ranges from 1 to 18. It is theorized that the household head's age and education reduce the occurrence or probability of waterborne sickness in that family. Waterborne infections are less likely to arise when households spend more on drinking water.

In the same way, increasing plant water use reduces the risk of waterborne sickness in that home. The results of the binary logistic model summary are revealed in Table 4. Logistic estimates of household head education (E.H.), use of plant water (U.P.W.), drinking water expenditures (E.D.W.), and respondent area (R.A.) were negatively correlated with the probability of waterborne diseases, whereas respondent family size (F.S.) was positively correlated with the probability of waterborne diseases. However, the current study's household head (A.H.) age was insignificant in reducing waterborne illness. Moreover, the robustness regression was also analyzed to verify the results of logistic estimates, as

shown in Table 4 [64]. Robust regression is a form of regression analysis designed to overcome some limitations of traditional parametric and non-parametric methods. The current findings of robust regression are almost similar to the output of the binary logistic, indicating that the current model outputs are valid.


**Table 4.** Regression model summary for waterborne diseases.

Dependent Variable: Waterborne Disease.

Moreover, in the current model, the value of Cox and Snell R square was 0.278, representing that a 28 percent change in the explained variable is due to the study's independent variables, while its value range was always between 0 and 0.75. On the other hand, the value of Nagelkerke R Square was 0.376, which indicates that 38 percent of the variation in the dependent variable is due to the independent variables, while its value always ranged between 0 and 1. The value of −2 Log-likelihood was detected at 306.831 at df = 8, significant at a 5 percent significance level. The Lemeshow test value for this model was 0.221, which is greater than 0.05, indicating that the model is statistically significant. The intercept term was 0.645, indicating the average prevalence of waterborne infections (life chances).

The current findings showed that education of the household head, expenditures on drinking water, use of plant water, and respondent's area all have a negative effect on the occurrence of water bone diseases, with odd ratios (Exp-) less than 1, and these results are statistically significant at the 5% level of significance. Meanwhile, family size has an odd ratio (Exp-β) greater than 1, indicating that an increase in family size will increase the probability of waterborne illness for that household, and this result is significant at the 1 percent significance level. However, age is ineffective in reducing the probability of waterborne diseases because this variable is statistically insignificant, as its *p*-value was 0.699, greater than the significance level. An increase in the education of household heads creates more awareness regarding waterborne illnesses and, as a result, households with a higher level of education will have a lower probability or chance of occurrence of waterborne diseases. Similarly, increased use of plant water refers to making life choices using plant water; the occurrence of waterborne illnesses leads to positive life chances. A rise in the cost of drinking water (as defined in our research model) indicates that more plant water is being used to bring water from plants. People must travel a certain distance and pay a certain amount of money. As a result, increasing plant water use lowers the risk of contracting waterborne infections. As a result, in the respondent's location, people in the plant area prefer to drink plant water, lowering the risk of waterborne sickness in those families. In the same regard, Shah et al. [36] demonstrated that demographic

and socioeconomic attributes such as age, education, income, past experiences, and social networks played an important role in perceiving vulnerability to such waterborne illnesses. Similarly, Khalid and Khaver [55] concluded that polluted water poses a greater threat to human life.

Furthermore, access to information, health facilities, and clean water influences households' health vulnerability. Waterborne sickness is reduced through increased education, household per capita expenditures on safe drinking water, and access to safe drinking water. They also demonstrated that families without access to a water supply spend significant time obtaining water, resulting in additional costs for the poor household. Because of the high cost of disinfection methods for treating drinking water, low-income families were extremely unlikely to use them, preventing poor households from reaping the benefits of clean water. The results revealed that the value of all coefficients except the age of the household head is significant in regression at 1 and 5 percent levels of significance.
